The infant mortality rate in Ukraine has been progressively decreasing over the past decade, but remains very high compared with the countries of the European Union. The mortality rate of infants in the first year of life in Ukraine is 2.5–3 times higher than in the EU countries, while the mortality rate of newborns during the first month of life exceeds the average European level by 6.6 times. This indicates a significant backlog of our country in the implementation of modern standards of medical care for both pregnant women and newborns using modern diagnostic and treatment methodologies.One of the most effective way that allowed to reduce significantly infant mortality and disability rates in the developed countries of the world proved to be introduction of expanded newborn screening as a tool of early detection of wide spectrum of inherited metabolic disorders (IMD) – orphan diseases caused by genetic defects of particular enzymes leading to alterations in specific metabolic pathways. As a rule, IMDs occurrence cannot be established during medical examination of newborns due to the absence of clinical symptoms. Therefore, IMDs are diagnosed in two ways: (i) with clinical manifestation in the form of "neonatal catastrophes" and/or sudden infant death syndrome, (ii) according to the results of a biochemical examination of the blood of all (asymptomatic) newborns (i.e. screening). Delays or errors in the diagnosis of these diseases often lead to irreversible damage of many organs, first of all, the brain (neurological deficits, mental retardation, oligophrenia). Newborn screening – measurement in dried blood spots, sampled in asymptomatic newborns, concentrations of a specific set of substances which characterize key processes of protein, carbohydrate and lipid metabolism as a tool of early IMDs identification and prompt treatment initiation of affected children to prevent metabolic decompensation episodes and disability development was started in the 1960s in the United States with just one disease – phenylketonuria.By now, newborn screening programs have been implemented in more than 50 countries of the world and provide diagnostics of more than 45 IMDs. A significant (8–10 times) expanding the spectrum of IMDs that can be detected upon examination of dried blood spots on filter paper has been achieved by application of a high-throughput quantitative bioanalysis method – tandem mass spectrometry (TMS) in the late 1990s. Unlike routinely applied immunofluorimetric method allowing to measure just one biochemical agent in one blood sample, TMS allowed to analyze concentrations of several dozen substances in one dried blood spot.Currently, in Ukraine newborn screening is carried out for 4 diseases: phenylketonuria, congenital hypothyroidism, congenital adrenal hyperplasia, and cystic fibrosis using the low-throughput immunofluorimetric method. In some cases, expanded newborn screening using TMS method is performed on a commercial basis in foreign laboratories. At the same time, according to the Law of Ukraine No. 2461 "On ensuring the prevention and treatment of rare diseases" dated April 15, 2014, and the Orders of the Ministry of Health of Ukraine No. 778 dated 10.27.2014, No. 919 dated December 30, 2015, and No. 731 dated June 29, 2017, "The list of rare (orphan) diseases, that lead to a reduction of patient's lifespan or their disability, and for these diseases there are well-established methods of treatment" comprises more than 60 inherited metabolic disorders.This indicates a significant backlog of our country in the issue of not only ethical and medical significance, but great social and economic importance.The key issue of the expanded newborn screening implementation using high-throughput and accurate TMS method in Ukraine is the absence of modern analytical instruments and supplementary equipment in the state medico-genetic laboratories, as well as analysts with sufficient level of training. TMS is a technically complex method based on application of expensive vacuum and chromatographic equipment, special software, isotopic labeling reagents, high-purity gases, instruments maintenance with the aid of foreign experts, as well as qualified lab staff.Such private clinical diagnostic laboratory, where TMS-measurements are performed routinely at site and biomaterials are not transferred abroad exists in Ukraine. This laboratory is capable to perform the full range of measurements at the initial stage of newborn screening (TMS-analysis) and the secondary confirmatory testing using gas-chromatography/mass-spectrometry (GC/MS) and high performance liquid chromatography (HPLC) methods, as well as enzymes activity assessment and molecular-genetic studies. On the basis of reached agreement in September 2017 it was started the development of the Program of improving the diagnostics of inherited metabolic diseases in newborns and older children in Ukraine. This Program has been initiated by the National Academy of Medical Sciences of Ukraine with the participation of "Association of Pediatricians of Ukraine" and "Association of Neonatologists of Ukraine", as well as membership of the "Institute of Pediatrics, Obstetrics and Gynecology named after academician O.M. Lukyanova of NAMS of Ukraine", medical universities and regional health-care providers.The purpose of the Program is to expand up to 29 the list of inherited metabolic disorders to be diagnosed in newborns and older children that allows early start of treatment and follow-up of affected patients. Wide implementation of the Program allows reducing the levels of neonatal, infant and child mortality and disability.The Program is based on the following principles: (i) a clear distribution of the responsibilities between participants considering newborn screening procedures and processes; (ii) implementation of electronic document management system to register transferring of biomaterial from the moment of sampling to presentation of laboratory measurement results, it's expert evaluation and medical recommendations for further actions; (iii) documented customer feedback to report the results and it's expert evaluation; (iv) creation of the database for calculating the threshold concentrations of biochemical markers and its' ratios (cut-off) for the Ukrainian population in order to reduce the number of false-negative and false-positive results.Financing of the Program have relied on funding of regional budgets, extra-budgetary funds and own funds of parents.The implementation of the preparatory phase of the Program was launched in Spring, 2018. The launch of the pilot part of the Program in 5 regions: Kiev, Kiev Region, Lugansk and Donetsk Regions, and the city Chernivtsi is scheduled for April 2019. The program is planned to be expanded throughout Ukraine at the end of 2020. ; Уровень детской смертности в Украине прогрессивно снижается в течение последнего десятилетия, но остается очень высоким по сравнению со странами Европейского Союза. Показатель смертности младенцев первого года жизни в Украине в 2,5-3 раза выше, чем в странах ЕС, при этом уровень смертности новорожденных в течение первого месяца жизни превышает среднеевропейский в 6,6 раз. Это свидетельствует о существенном отставании нашей страны во внедрении современных стандартов оказания медицинской помощи, как беременным женщинам, так и новорожденным с использованием современных методологий диагностики и лечения.Одним из наиболее эффективных направлений деятельности, которая обеспечила существенное снижение уровня детской смертности и инвалидности в развитых странах мира, стало внедрение расширенного массового скрининга новорожденных с целью выявления наследственных болезней обмена веществ (НБО) – орфанных заболеваний, которые возникают вследствие генетических дефектов ферментов. Наличие НБО, как правило, не удается установить при врачебном осмотре новорожденных из-за отсутствия клинических симптомов. Диагностируют НБО двумя способами: (i) по клиническим проявлениям в форме «катастроф неонатального периода» и синдрома внезапной смерти младенцев, (ii) по результатам биохимического обследования крови новорожденных (скрининга). Задержка или ошибки в диагностике этих заболеваний часто приводят к необратимым повреждениям многих органов и, в первую очередь, головного мозга (неврологические нарушения, психическое регресс, слабоумие).Неонатальный скрининг – измерение в крови новорожденных концентраций определенного набора веществ, характеризующих ключевые процессы белкового, углеводного и липидного обмена с целью раннего выявления и начала лечения детей с НБО и предотвращения их инвалидизации было начато в 60-х годах прошлого века в США с одной болезни – фенилкетонурии. Сегодня программы неонатального скрининга внедрены более, чем в 50 странах мира и обеспечивают диагностику более 45 НБО. Значительное (в 8-10 раз) расширение количества НБО, которые могут быть обнаружены при исследовании высушенных на фильтровальной бумаге пятен крови, стало возможным благодаря внедрению высокопроизводительного метода тандемной масс-спектрометрии (ТМС) в конце 90-х годов прошлого века. В отличие от иммунофлуориметрического метода, который позволяет определять один показатель в одной пробе крови, ТМС позволяет измерять концентрации нескольких десятков веществ в одной пробе крови.В настоящее время в Украине скрининг новорожденных ведется по 4-м заболеваниям: фенилкетонурии, врожденному гипотиреозу, адреногенитальному синдрому и муковисцидозу с использованием низкопродуктивного иммунофлуориметрического метода. В отдельных случаях расширенный скрининг новорожденных с использованием метода ТМС выполняется на коммерческой основе в зарубежных лабораториях. При этом, согласно Закону Украины № 2461 «Об обеспечении профилактики и лечения редких заболеваний» от 15.04.2014, и Приказов МОЗ Украины № 778 от 27.10.2014, № 919 от 30.12.2015 и № 731 от 29.06.2017, «Перечень редких (орфанных) заболеваний, приводящих к сокращению продолжительности жизни больных или их инвалидизации и для которых существуют признанные методы лечения» включает более 60 наследственных болезней обмена веществ. Это свидетельствует о значительном отставании нашей страны в вопросе, который, кроме этического и медицинского, имеет важное социальное и экономическое значение.Ключевым вопросом внедрения расширенного скрининга новорожденных с использованием высокопроизводительного и точного метода ТМС в Украине является отсутствие в государственных медико-генетических лабораториях современного аналитического оборудования и вспомогательной инфраструктуры, а также специалистов-аналитиков с достаточным уровнем подготовки. ТМС – технически сложный метод, требующий использования дорогостоящего вакуумного и хроматографического оборудования, специального программного обеспечения, реагентов с изотопными метками, высокочистых газов, сервисного обслуживания с привлечением иностранных специалистов, а также квалифицированного персонала.Учитывая наличие частной клинико-диагностической лаборатории, выполняющей ТМС-анализы в Украине, а не транспортирующей биоматериал в зарубежные лаборатории, способной выполнять весь комплекс исследований первого (массового) этапа скрининга, а также уточняющую диагностику НБО с использованием методов газовой хроматографии/масс-спектрометрии, высокоэффективной жидкостной хроматографии, определение активности ферментов и молекулярно-генетические исследования, в сентябре 2017 была начата разработка Программы усовершенствования диагностики наследственных болезней обмена веществ у новорожденных и детей старшего возраста в Украине. Инициаторами этой Программы являются Национальная академия медицинских наук Украины, ВОО «Ассоциация педиатров Украины», ВОО «Ассоциация неонатологов Украины», ГУ «ИПАГ имени академика О.М. Лукьяновой НАМН Украины», медицинские университеты и региональные лечебно-профилактические учреждения.Цель Программы – расширение до 29 нозологий перечня наследственных болезней обмена веществ, диагностируемых у новорожденных и детей старшего возраста, обеспечение своевременного медицинского сопровождения и лечения выявленных больных, что позволит снизить уровень неонатальной, младенческой и детской смертности и инвалидности. Программа базируется на следующих принципах: (i) четкое распределение сфер ответственности исполнителей, регламентированных рабочими процессами и процедурами скрининга; (ii) электронный документооборот с фиксацией движения биоматериала от момента отбора до выдачи результатов лабораторных измерений, документирование результатов их экспертной оценки и принятого решения относительно дальнейших действий; (iii) документированная обратная связь с заказчиком исследований с целью сообщения результатов и их экспертной оценки; (iv) создание информационной базы данных для расчета предельных уровней концентраций маркерных соединений (cut-off) для украинской популяции с целью снижения количества ложноотрицательных и ложноположительных результатов.Финансирование Программы планируется осуществлять за счет средств региональных бюджетов, внебюджетных фондов, собственных средств родителей.Выполнение подготовительного этапа Программы было начато весной 2018 года. Запуск пилотной части Программы в 5 регионах: Киев, Киевская область, Луганская и Донецкая области и г. Черновцы, - запланирован в апреле 2019. Расширение Программы по всей территории Украины планируется завершить в конце 2020 года. ; Рівень дитячої смертності в Україні прогресивно знижується протягом останнього десятиріччя, але лишається дуже високим у порівнянні з країнами Європейського Союзу. Показник смертності немовлят першого року життя в Україні у 2,5-3 рази вищий, ніж у країнах ЄС, при цьому рівень смертності новонароджених протягом першого місяця життя перевищує середньоєвропейський у 6,6 разів. Це свідчить про суттєве відставання нашої країни у впровадженні сучасних стандартів надання медичної допомоги як вагітним жінкам, так і новонародженим з використанням сучасних методологій діагностики та лікування.Одним з найбільш ефективних напрямків діяльності, яка забезпечила суттєве зниження рівня дитячої смертності та інвалідності у розвинутих країнах світу стало впровадження розширеного масового скринінгу новонароджених з метою виявлення спадкових хвороб обміну речовин (СХОР) – орфанних захворювань, які виникають внаслідок генетичних дефектів ферментів. Наявність СХОР, зазвичай, не вдається встановити при лікарському огляді новонароджених через відсутність клінічних симптомів. Діагностують СХОР двома способами: (і) по клінічним проявам у формі «катастроф неонатального періоду» та синдрому раптової смерті немовлят, (іі) по результатам біохімічного обстеження крові новонароджених (скринінгу). Затримка або помилки в діагностиці цих захворювань часто призводять до незворотних пошкоджень багатьох органів і, в першу чергу, головного мозку (неврологічні порушення, психічний регрес, слабоумство).Неонатальний скринінг – вимірювання у крові новонароджених концентрацій певного набору речовин, які характеризують ключові процеси білкового, вуглеводного та ліпідного обміну з метою раннього виявлення і початку лікування дітей зі СХОР та запобігання їх інвалідизації було розпочато у 60-х роках минулого століття у США з однієї хвороби – фенілкетонурії. Сьогодні програми неонатального скринінгу впроваджені більш, ніж в 50 країнах світу та забезпечують діагностику понад 45 СХОР. Значне (у 8-10 разів) розширення кількості СХОР, що можуть бути виявлені при дослідженні висушених на фільтрувальному папері плям крові, стало можливим завдяки впровадженню високопродуктивного методу тандемної мас-спектрометрії (ТМС) наприкінці 90-х років минулого століття. На відміну від імунофлюорометричного методу, який дозволяє визначати один показник в одній пробі крові, ТМС дозволяє вимірювати концентрації декількох десятків речовин в одній пробі крові.На теперішній час в Україні скринінг новонароджених впроваджено лише для 4 захворювань: фенілкетонурії, вродженого гіпотиреозу, адреногенітального синдрому та муковісцидозу, який проводиться з використанням низькопродуктивного імунофлюорометричного методу. В окремих випадках розширений скринінг новонароджених з використанням методу ТМС виконується на комерційній основі в зарубіжних лабораторіях. При цьому, згідно з Законом України № 2461 «Про забезпечення профілактики та лікування рідкісних захворювань» від 15.04.2014 та Наказами МОЗУ № 778 від 27.10.2014, № 919 від 30.12.2015 та № 731 від 29.06.2017, «Перелік рідкісних (орфанних) захворювань, що призводять до скорочення тривалості життя хворих або їх інвалідизації та для яких існують визнані методи лікування» включає більше, ніж 60 спадкових хвороб обміну речовин. Це свідчить про значне відставання нашої країни в питанні, яке, крім етичного та медичного, має важливе соціальне та економічне значення.Ключовим питанням впровадження розширеного скринінгу новонароджених з використанням високопродуктивного і точного методу ТМС в Україні є відсутність у державних медико-генетичних лабораторіях сучасного аналітичного обладнання та допоміжної інфраструктури, а також фахівців-аналітиків з певним рівнем підготовки. ТМС – технічно складний метод, який вимагає використання коштовного вакуумного та хроматографічного обладнання, спеціального програмного забезпечення, реагентів з ізотопними мітками, високочистих газів, сервісного обслуговування з залученням закордонних фахівців, а також кваліфікованого персоналу.З огляду на наявність приватної клініко-діагностичної лабораторії, яка виконує ТМС-аналізи в Україні, а не транспортує біоматеріал в закордонні лабораторії та здатна виконувати весь комплекс досліджень першого (масового) етапу скринінгу, а також уточнюючу діагностику СХОР з використанням методів газової хроматографії/мас-спектрометрії, високоефективної рідинної хроматографії, визначення активності ферментів та молекулярно-генетичні дослідження, у вересні 2017 р. було розпочато розробку Програми удосконалення діагностики спадкових хвороб обміну речовин у новонароджених і дітей старшого віку в Україні. Ініціаторами цієї Програми є Національна академія медичних наук України, ВГО «Асоціація педіатрів України», ВГО «Асоціація неонатологів України», ДУ «ІПАГ імені академіка О.М. Лук'янової НАМН України», медичні університети та регіональні лікувально-профілактичні заклади.Мета Програми – розширення до 29 нозологій переліку спадкових хвороб обміну речовин, які виявляються у новонароджених та дітей старшого віку, забезпечення своєчасного медичного супроводу та лікування виявлених хворих, що дозволить знизити рівень неонатальної, малюкової й дитячої смертності та інвалідності. Програма базується на наступних принципах: (і) чіткий розподіл відповідальності виконавців, регламентований робочими процесами та процедурами скринінгу; (іі) електронний документообіг з фіксацією руху біоматеріалу від моменту відбору до видачі результатів лабораторних визначень, документування результатів їх експертної оцінки та прийнятого рішення стосовно подальших дій; (ііі) документований зворотній зв'язок з замовником досліджень з повідомленням результатів та їх експертної оцінки; (iv) створення інформаційної бази даних для розрахунку граничних рівнів концентрацій маркерних сполук (cut-off) для української популяції з метою зниження кількості хибно-негативних та хибно-позитивних визначень.Фінансування Програми планується здійснювати за рахунок коштів регіональних бюджетів, позабюджетних фондів, власних коштів батьків.Виконання підготовчого етапу Програми було розпочато на весні 2018 року. Запуск пілотної частини Програми у 5 регіонах: м. Київ, Київська область, Луганська та Донецька області та м. Чернівці, – запланований у квітні 2019 р. Розширення Програми по всій території України планується завершити наприкінці 2020 року.
The infant mortality rate in Ukraine has been progressively decreasing over the past decade, but remains very high compared with the countries of the European Union. The mortality rate of infants in the first year of life in Ukraine is 2.5–3 times higher than in the EU countries, while the mortality rate of newborns during the first month of life exceeds the average European level by 6.6 times. This indicates a significant backlog of our country in the implementation of modern standards of medical care for both pregnant women and newborns using modern diagnostic and treatment methodologies.One of the most effective way that allowed to reduce significantly infant mortality and disability rates in the developed countries of the world proved to be introduction of expanded newborn screening as a tool of early detection of wide spectrum of inherited metabolic disorders (IMD) – orphan diseases caused by genetic defects of particular enzymes leading to alterations in specific metabolic pathways. As a rule, IMDs occurrence cannot be established during medical examination of newborns due to the absence of clinical symptoms. Therefore, IMDs are diagnosed in two ways: (i) with clinical manifestation in the form of "neonatal catastrophes" and/or sudden infant death syndrome, (ii) according to the results of a biochemical examination of the blood of all (asymptomatic) newborns (i.e. screening). Delays or errors in the diagnosis of these diseases often lead to irreversible damage of many organs, first of all, the brain (neurological deficits, mental retardation, oligophrenia). Newborn screening – measurement in dried blood spots, sampled in asymptomatic newborns, concentrations of a specific set of substances which characterize key processes of protein, carbohydrate and lipid metabolism as a tool of early IMDs identification and prompt treatment initiation of affected children to prevent metabolic decompensation episodes and disability development was started in the 1960s in the United States with just one disease – phenylketonuria.By now, newborn screening programs have been implemented in more than 50 countries of the world and provide diagnostics of more than 45 IMDs. A significant (8–10 times) expanding the spectrum of IMDs that can be detected upon examination of dried blood spots on filter paper has been achieved by application of a high-throughput quantitative bioanalysis method – tandem mass spectrometry (TMS) in the late 1990s. Unlike routinely applied immunofluorimetric method allowing to measure just one biochemical agent in one blood sample, TMS allowed to analyze concentrations of several dozen substances in one dried blood spot.Currently, in Ukraine newborn screening is carried out for 4 diseases: phenylketonuria, congenital hypothyroidism, congenital adrenal hyperplasia, and cystic fibrosis using the low-throughput immunofluorimetric method. In some cases, expanded newborn screening using TMS method is performed on a commercial basis in foreign laboratories. At the same time, according to the Law of Ukraine No. 2461 "On ensuring the prevention and treatment of rare diseases" dated April 15, 2014, and the Orders of the Ministry of Health of Ukraine No. 778 dated 10.27.2014, No. 919 dated December 30, 2015, and No. 731 dated June 29, 2017, "The list of rare (orphan) diseases, that lead to a reduction of patient's lifespan or their disability, and for these diseases there are well-established methods of treatment" comprises more than 60 inherited metabolic disorders.This indicates a significant backlog of our country in the issue of not only ethical and medical significance, but great social and economic importance.The key issue of the expanded newborn screening implementation using high-throughput and accurate TMS method in Ukraine is the absence of modern analytical instruments and supplementary equipment in the state medico-genetic laboratories, as well as analysts with sufficient level of training. TMS is a technically complex method based on application of expensive vacuum and chromatographic equipment, special software, isotopic labeling reagents, high-purity gases, instruments maintenance with the aid of foreign experts, as well as qualified lab staff.Such private clinical diagnostic laboratory, where TMS-measurements are performed routinely at site and biomaterials are not transferred abroad exists in Ukraine. This laboratory is capable to perform the full range of measurements at the initial stage of newborn screening (TMS-analysis) and the secondary confirmatory testing using gas-chromatography/mass-spectrometry (GC/MS) and high performance liquid chromatography (HPLC) methods, as well as enzymes activity assessment and molecular-genetic studies. On the basis of reached agreement in September 2017 it was started the development of the Program of improving the diagnostics of inherited metabolic diseases in newborns and older children in Ukraine. This Program has been initiated by the National Academy of Medical Sciences of Ukraine with the participation of "Association of Pediatricians of Ukraine" and "Association of Neonatologists of Ukraine", as well as membership of the "Institute of Pediatrics, Obstetrics and Gynecology named after academician O.M. Lukyanova of NAMS of Ukraine", medical universities and regional health-care providers.The purpose of the Program is to expand up to 29 the list of inherited metabolic disorders to be diagnosed in newborns and older children that allows early start of treatment and follow-up of affected patients. Wide implementation of the Program allows reducing the levels of neonatal, infant and child mortality and disability.The Program is based on the following principles: (i) a clear distribution of the responsibilities between participants considering newborn screening procedures and processes; (ii) implementation of electronic document management system to register transferring of biomaterial from the moment of sampling to presentation of laboratory measurement results, it's expert evaluation and medical recommendations for further actions; (iii) documented customer feedback to report the results and it's expert evaluation; (iv) creation of the database for calculating the threshold concentrations of biochemical markers and its' ratios (cut-off) for the Ukrainian population in order to reduce the number of false-negative and false-positive results.Financing of the Program have relied on funding of regional budgets, extra-budgetary funds and own funds of parents.The implementation of the preparatory phase of the Program was launched in Spring, 2018. The launch of the pilot part of the Program in 5 regions: Kiev, Kiev Region, Lugansk and Donetsk Regions, and the city Chernivtsi is scheduled for April 2019. The program is planned to be expanded throughout Ukraine at the end of 2020. ; Уровень детской смертности в Украине прогрессивно снижается в течение последнего десятилетия, но остается очень высоким по сравнению со странами Европейского Союза. Показатель смертности младенцев первого года жизни в Украине в 2,5-3 раза выше, чем в странах ЕС, при этом уровень смертности новорожденных в течение первого месяца жизни превышает среднеевропейский в 6,6 раз. Это свидетельствует о существенном отставании нашей страны во внедрении современных стандартов оказания медицинской помощи, как беременным женщинам, так и новорожденным с использованием современных методологий диагностики и лечения.Одним из наиболее эффективных направлений деятельности, которая обеспечила существенное снижение уровня детской смертности и инвалидности в развитых странах мира, стало внедрение расширенного массового скрининга новорожденных с целью выявления наследственных болезней обмена веществ (НБО) – орфанных заболеваний, которые возникают вследствие генетических дефектов ферментов. Наличие НБО, как правило, не удается установить при врачебном осмотре новорожденных из-за отсутствия клинических симптомов. Диагностируют НБО двумя способами: (i) по клиническим проявлениям в форме «катастроф неонатального периода» и синдрома внезапной смерти младенцев, (ii) по результатам биохимического обследования крови новорожденных (скрининга). Задержка или ошибки в диагностике этих заболеваний часто приводят к необратимым повреждениям многих органов и, в первую очередь, головного мозга (неврологические нарушения, психическое регресс, слабоумие).Неонатальный скрининг – измерение в крови новорожденных концентраций определенного набора веществ, характеризующих ключевые процессы белкового, углеводного и липидного обмена с целью раннего выявления и начала лечения детей с НБО и предотвращения их инвалидизации было начато в 60-х годах прошлого века в США с одной болезни – фенилкетонурии. Сегодня программы неонатального скрининга внедрены более, чем в 50 странах мира и обеспечивают диагностику более 45 НБО. Значительное (в 8-10 раз) расширение количества НБО, которые могут быть обнаружены при исследовании высушенных на фильтровальной бумаге пятен крови, стало возможным благодаря внедрению высокопроизводительного метода тандемной масс-спектрометрии (ТМС) в конце 90-х годов прошлого века. В отличие от иммунофлуориметрического метода, который позволяет определять один показатель в одной пробе крови, ТМС позволяет измерять концентрации нескольких десятков веществ в одной пробе крови.В настоящее время в Украине скрининг новорожденных ведется по 4-м заболеваниям: фенилкетонурии, врожденному гипотиреозу, адреногенитальному синдрому и муковисцидозу с использованием низкопродуктивного иммунофлуориметрического метода. В отдельных случаях расширенный скрининг новорожденных с использованием метода ТМС выполняется на коммерческой основе в зарубежных лабораториях. При этом, согласно Закону Украины № 2461 «Об обеспечении профилактики и лечения редких заболеваний» от 15.04.2014, и Приказов МОЗ Украины № 778 от 27.10.2014, № 919 от 30.12.2015 и № 731 от 29.06.2017, «Перечень редких (орфанных) заболеваний, приводящих к сокращению продолжительности жизни больных или их инвалидизации и для которых существуют признанные методы лечения» включает более 60 наследственных болезней обмена веществ. Это свидетельствует о значительном отставании нашей страны в вопросе, который, кроме этического и медицинского, имеет важное социальное и экономическое значение.Ключевым вопросом внедрения расширенного скрининга новорожденных с использованием высокопроизводительного и точного метода ТМС в Украине является отсутствие в государственных медико-генетических лабораториях современного аналитического оборудования и вспомогательной инфраструктуры, а также специалистов-аналитиков с достаточным уровнем подготовки. ТМС – технически сложный метод, требующий использования дорогостоящего вакуумного и хроматографического оборудования, специального программного обеспечения, реагентов с изотопными метками, высокочистых газов, сервисного обслуживания с привлечением иностранных специалистов, а также квалифицированного персонала.Учитывая наличие частной клинико-диагностической лаборатории, выполняющей ТМС-анализы в Украине, а не транспортирующей биоматериал в зарубежные лаборатории, способной выполнять весь комплекс исследований первого (массового) этапа скрининга, а также уточняющую диагностику НБО с использованием методов газовой хроматографии/масс-спектрометрии, высокоэффективной жидкостной хроматографии, определение активности ферментов и молекулярно-генетические исследования, в сентябре 2017 была начата разработка Программы усовершенствования диагностики наследственных болезней обмена веществ у новорожденных и детей старшего возраста в Украине. Инициаторами этой Программы являются Национальная академия медицинских наук Украины, ВОО «Ассоциация педиатров Украины», ВОО «Ассоциация неонатологов Украины», ГУ «ИПАГ имени академика О.М. Лукьяновой НАМН Украины», медицинские университеты и региональные лечебно-профилактические учреждения.Цель Программы – расширение до 29 нозологий перечня наследственных болезней обмена веществ, диагностируемых у новорожденных и детей старшего возраста, обеспечение своевременного медицинского сопровождения и лечения выявленных больных, что позволит снизить уровень неонатальной, младенческой и детской смертности и инвалидности. Программа базируется на следующих принципах: (i) четкое распределение сфер ответственности исполнителей, регламентированных рабочими процессами и процедурами скрининга; (ii) электронный документооборот с фиксацией движения биоматериала от момента отбора до выдачи результатов лабораторных измерений, документирование результатов их экспертной оценки и принятого решения относительно дальнейших действий; (iii) документированная обратная связь с заказчиком исследований с целью сообщения результатов и их экспертной оценки; (iv) создание информационной базы данных для расчета предельных уровней концентраций маркерных соединений (cut-off) для украинской популяции с целью снижения количества ложноотрицательных и ложноположительных результатов.Финансирование Программы планируется осуществлять за счет средств региональных бюджетов, внебюджетных фондов, собственных средств родителей.Выполнение подготовительного этапа Программы было начато весной 2018 года. Запуск пилотной части Программы в 5 регионах: Киев, Киевская область, Луганская и Донецкая области и г. Черновцы, - запланирован в апреле 2019. Расширение Программы по всей территории Украины планируется завершить в конце 2020 года. ; Рівень дитячої смертності в Україні прогресивно знижується протягом останнього десятиріччя, але лишається дуже високим у порівнянні з країнами Європейського Союзу. Показник смертності немовлят першого року життя в Україні у 2,5-3 рази вищий, ніж у країнах ЄС, при цьому рівень смертності новонароджених протягом першого місяця життя перевищує середньоєвропейський у 6,6 разів. Це свідчить про суттєве відставання нашої країни у впровадженні сучасних стандартів надання медичної допомоги як вагітним жінкам, так і новонародженим з використанням сучасних методологій діагностики та лікування.Одним з найбільш ефективних напрямків діяльності, яка забезпечила суттєве зниження рівня дитячої смертності та інвалідності у розвинутих країнах світу стало впровадження розширеного масового скринінгу новонароджених з метою виявлення спадкових хвороб обміну речовин (СХОР) – орфанних захворювань, які виникають внаслідок генетичних дефектів ферментів. Наявність СХОР, зазвичай, не вдається встановити при лікарському огляді новонароджених через відсутність клінічних симптомів. Діагностують СХОР двома способами: (і) по клінічним проявам у формі «катастроф неонатального періоду» та синдрому раптової смерті немовлят, (іі) по результатам біохімічного обстеження крові новонароджених (скринінгу). Затримка або помилки в діагностиці цих захворювань часто призводять до незворотних пошкоджень багатьох органів і, в першу чергу, головного мозку (неврологічні порушення, психічний регрес, слабоумство).Неонатальний скринінг – вимірювання у крові новонароджених концентрацій певного набору речовин, які характеризують ключові процеси білкового, вуглеводного та ліпідного обміну з метою раннього виявлення і початку лікування дітей зі СХОР та запобігання їх інвалідизації було розпочато у 60-х роках минулого століття у США з однієї хвороби – фенілкетонурії. Сьогодні програми неонатального скринінгу впроваджені більш, ніж в 50 країнах світу та забезпечують діагностику понад 45 СХОР. Значне (у 8-10 разів) розширення кількості СХОР, що можуть бути виявлені при дослідженні висушених на фільтрувальному папері плям крові, стало можливим завдяки впровадженню високопродуктивного методу тандемної мас-спектрометрії (ТМС) наприкінці 90-х років минулого століття. На відміну від імунофлюорометричного методу, який дозволяє визначати один показник в одній пробі крові, ТМС дозволяє вимірювати концентрації декількох десятків речовин в одній пробі крові.На теперішній час в Україні скринінг новонароджених впроваджено лише для 4 захворювань: фенілкетонурії, вродженого гіпотиреозу, адреногенітального синдрому та муковісцидозу, який проводиться з використанням низькопродуктивного імунофлюорометричного методу. В окремих випадках розширений скринінг новонароджених з використанням методу ТМС виконується на комерційній основі в зарубіжних лабораторіях. При цьому, згідно з Законом України № 2461 «Про забезпечення профілактики та лікування рідкісних захворювань» від 15.04.2014 та Наказами МОЗУ № 778 від 27.10.2014, № 919 від 30.12.2015 та № 731 від 29.06.2017, «Перелік рідкісних (орфанних) захворювань, що призводять до скорочення тривалості життя хворих або їх інвалідизації та для яких існують визнані методи лікування» включає більше, ніж 60 спадкових хвороб обміну речовин. Це свідчить про значне відставання нашої країни в питанні, яке, крім етичного та медичного, має важливе соціальне та економічне значення.Ключовим питанням впровадження розширеного скринінгу новонароджених з використанням високопродуктивного і точного методу ТМС в Україні є відсутність у державних медико-генетичних лабораторіях сучасного аналітичного обладнання та допоміжної інфраструктури, а також фахівців-аналітиків з певним рівнем підготовки. ТМС – технічно складний метод, який вимагає використання коштовного вакуумного та хроматографічного обладнання, спеціального програмного забезпечення, реагентів з ізотопними мітками, високочистих газів, сервісного обслуговування з залученням закордонних фахівців, а також кваліфікованого персоналу.З огляду на наявність приватної клініко-діагностичної лабораторії, яка виконує ТМС-аналізи в Україні, а не транспортує біоматеріал в закордонні лабораторії та здатна виконувати весь комплекс досліджень першого (масового) етапу скринінгу, а також уточнюючу діагностику СХОР з використанням методів газової хроматографії/мас-спектрометрії, високоефективної рідинної хроматографії, визначення активності ферментів та молекулярно-генетичні дослідження, у вересні 2017 р. було розпочато розробку Програми удосконалення діагностики спадкових хвороб обміну речовин у новонароджених і дітей старшого віку в Україні. Ініціаторами цієї Програми є Національна академія медичних наук України, ВГО «Асоціація педіатрів України», ВГО «Асоціація неонатологів України», ДУ «ІПАГ імені академіка О.М. Лук'янової НАМН України», медичні університети та регіональні лікувально-профілактичні заклади.Мета Програми – розширення до 29 нозологій переліку спадкових хвороб обміну речовин, які виявляються у новонароджених та дітей старшого віку, забезпечення своєчасного медичного супроводу та лікування виявлених хворих, що дозволить знизити рівень неонатальної, малюкової й дитячої смертності та інвалідності. Програма базується на наступних принципах: (і) чіткий розподіл відповідальності виконавців, регламентований робочими процесами та процедурами скринінгу; (іі) електронний документообіг з фіксацією руху біоматеріалу від моменту відбору до видачі результатів лабораторних визначень, документування результатів їх експертної оцінки та прийнятого рішення стосовно подальших дій; (ііі) документований зворотній зв'язок з замовником досліджень з повідомленням результатів та їх експертної оцінки; (iv) створення інформаційної бази даних для розрахунку граничних рівнів концентрацій маркерних сполук (cut-off) для української популяції з метою зниження кількості хибно-негативних та хибно-позитивних визначень.Фінансування Програми планується здійснювати за рахунок коштів регіональних бюджетів, позабюджетних фондів, власних коштів батьків.Виконання підготовчого етапу Програми було розпочато на весні 2018 року. Запуск пілотної частини Програми у 5 регіонах: м. Київ, Київська область, Луганська та Донецька області та м. Чернівці, – запланований у квітні 2019 р. Розширення Програми по всій території України планується завершити наприкінці 2020 року.
The PGC was funded by National Institute of Mental Health (NIMH) Grant Nos. MH085520 (to PFS) and MH080403. Statistical analyses were carried out on the Genetic Cluster Computer (http://www. geneticcluster.org) hosted by SURFsara and financially supported by the Netherlands Scientific Organization Grant No. NWO 480-05-003 (to D. Posthuma) and the department of Psychology, Vrije Universiteit Amsterdam along with a supplement from the Dutch Brain Foundation. The Bonn/Mannheim GWAS was supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Genome Research Network Systematic Investigation of the Molecular Causes of Major Mood Disorders and Schizophrenia Grant Nos. 01GS08144 and 01GS08147, under the auspices of the National Genome Research Network plus, and through the Integrated Network Integrated Understanding of Causes and Mechanisms in Mental Disorders, under the auspices of the e:Med Programme Grant Nos. 01ZX1314A and 01ZX1314G. The Bonn/Mannheim GWAS was also supported by the German Research Foundation (DFG) Grant Nos. FOR2107, RI908/11-1, and NO246/10-1. The GenRED GWAS project was supported by NIMH R01 Grant Nos. MH061686 (to DFL), MH059542 (to W.H. Coryell), MH075131 (W.B. Lawson), MH059552 (JBP), MH059541 (W.A. Scheftner), and MH060912 (MMW). Max Planck Institute of Psychiatry MARS study was supported by the BMBF Program Molecular Diagnostics: Validation of Biomarkers for Diagnosis and Outcome in Major Depression by Grant No. 01ES0811. Genotyping was supported by the Bavarian Ministry of Commerce, and the BMBF in the framework of the National Genome Research Network by Grant Nos. NGFN2 and NGFN-Plus, FKZ 01GS0481 and 01GS08145. The Netherlands Study of Depression and Anxiety and the Netherlands Twin Register contributed to Genetic Association Information Network (GAIN)-MDD and to MDD2000. Funding for NTR/NESDA was from the following: the Netherlands Organization for Scientific Research (MagW/ZonMW Grant Nos. 904-61-090, 985-10-002, 904-61-193, 480-04004, 400-05-717, 912-100-20; Spinozapremie Grant No. 56-464-14192; Geestkracht program Grant No. 10-000-1002); the Center for Medical Systems Biology (NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure, Vrije Universiteit's Institutes for Health and Care Research and Neuroscience Campus Amsterdam, BIC/BioAssist/RK (Grant No. 2008.024); the European Science Foundation (Grant No. EU/QLRT-200101254); the European Community's Seventh Framework Program (Grant No. FP7/2007-2013); ENGAGE (Grant No. HEALTH-F4-2007-201413); and the European Science Council (Grant No. ERC 230374). Genotyping was funded in part by the GAIN of the Foundation for the US National Institutes of Health, and analysis was supported by grants from GAIN and the NIMH (Grant No. MH081802). Funding for the QIMR samples was provided by the Australian National Health and Medical Research Council (Grant Nos. 241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496675, 496739, 552485, 552498, 613602, 613608, 613674, 619667), the Australian Research Council (Grant Nos. FT0991360, FT0991022), the FP-5 GenomEUtwin Project (Grant No. QLG2-CT-2002-01254), and the US National Institutes of Health (Grant Nos. AA07535, AA10248, AA13320, AA13321, AA13326, AA14041, MH66206, DA12854, DA019951), and the Center for Inherited Disease Research (Baltimore, MD). RADIANT was funded by the following: a joint grant from the UK Medical Research Council and GlaxoSmithKline (Grant No. r G0701420); the National Institute for Health Research Specialist Biomedical Research Centre for Mental Health at the South London and Maudsley National Health Service Foundation Trust and the Institute of Psychiatry, King's College London; the UK Medical Research Council (Grant No. G0000647), and the Marie Curie Industry-Academia Partnership and Pathways (Grant No. 286213). The GENDEP study was funded by a European Commission Framework 6 grant (EC Contract Ref.: LSHB-CT2003- 503428). Genotyping of STAR* D was supported by NIMH Grant No. MH072802 (to SPH). STAR* D was funded by NIMH Grant No. N01MH90003 to the University of Texas Southwestern Medical Center at Dallas (to A.J. Rush). The CoLaus/PsyCoLaus study was supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (Grant Nos. 3200B0-105993, 3200B0-118308, 33CSCO-122661, 33CS30-139468, 33CS30-148401) and two grants from GlaxoSmithKline Clinical Genetics. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (Grant Nos. 01ZZ9603, 01ZZ0103, 01ZZ0403), the Ministry of Cultural Affairs, and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide data have been supported by the Federal Ministry of Education and Research (Grant No. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany, and the Federal State of Mecklenburg-West Pomerania. SHIP-LEGEND is funded by the DFG (Grant No. GR 1912/5-1). The TwinGene study was supported by the Swedish Ministry for Higher Education, the Swedish Research Council (Grant No. M-2005-1112), GenomEUtwin (Grant Nos. EU/QLRT2001-01254,QLG2-CT-2002-01254), the Swedish Foundation for Strategic Research and the US National Institutes of Health (Grant No. U01 DK066134). The collection of PRISME control subjects and genotyping of the 883 Danish control subjects was supported by grants from The Danish Strategic Research Council, The Stanley Research Foundation, and H. Lundbeck A/S. The Muenster Depression cohorts were supported by the European Union (Grant No. N Health-F2-2008-222963) and by grants from the DFG (Grant Nos. FOR 2107 and DA1151/5-1 [ to UD]), Innovative Medizinische Forschung of the Medical Faculty of Munster (Grant Nos. DA120903, DA111107, and DA211012 [ all to UD]). Generation Scotland is supported by a Wellcome Trust Strategic Award "Stratifying Resilience and Depression Longitudinally" (Reference No.: 104036/Z/14/Z) and core support from the Chief Scientist Office of the Scottish Government Health Directorates (Grant No. CZD/16/6) and the Scottish Funding Council (Grant No. HR03006).r The NIMH Cell Repository at Rutgers University and the NIMH Center for Collaborative Genetic Studies on Mental Disorders made essential contributions to this project. Genotyping was carried out by the Broad Institute Center for Genotyping and Analysis with support from Grant No. U54 RR020278 (which partially subsidized the genotyping of the GenRED cases). Collection and quality control analyses of the control dataset were supported by grants from NIMH and the National Alliance for Research on Schizophrenia and Depression.r We acknowledge the contributions of Dr. George S Zubenko and Dr. Wendy N Zubenko, Department of Psychiatry, University of Pittsburgh School of Medicine, to the GenRED I project. We are grateful to Knowledge Networks (Menlo Park, CA) for assistance in collecting the control dataset. We express our profound appreciation to the families who participated in this project, and to the many clinicians who facilitated the referral of participants to the study. We thank the twins and their families registered at the Australian Twin Registry for their participation in the many studies that have contributed to this research. We thank V. Mooser, G. Weaber, and P. Vollenweider who initiated the CoLaus project. We express our gratitude to the Lausanne inhabitants who volunteered to participate in the PsyCoLaus study. We would like to acknowledge the PRISME-study group, Denmark, for collection of the PRISME samples. We thank David M. Hougaard, Section of Neonatal Screening and Hormones, Statens Serum Institute, Copenhagen, Denmark; Preben Bo Mortensen, National Centre for Register-based Research, Aarhus University, Denmark; Merete Nordentoft, Mental Health Centre, Copenhagen, Denmark; and The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark. Funding from the BBSRC and MRC is gratefully acknowledged.r Data used in the preparation of this article were obtained from the Genetic and Environmental Risk for Alzheimer's disease (GERAD1) Consortium. As such, the investigators within the GERAD1 consortia contributed to the design and implementation of GERAD1 and/or provided data but did not participate in analysis or writing of this report.r SS, HS, KS, and TET are employees of deCODE Genetics/Amgen. VA received funds from the German Federal Ministry of Education and Research, from the European Union (FP 7), and from the Interdisciplinary Center for Clinical Research Munster, and he has served on the advisory boards of, or has given presentations on behalf of the following companies: Astra-Zeneca, Janssen-Organon, Lilly, Lundbeck, Servier, Pfizer, Otsuka, and Trommsdorff. BTB has received funding from the National Health and Medical Research Council Australia and honoraria from Lundbeck, BristolMeyers Squibb, Sanofi, Servier, Astra-Zeneca, Pfizer. IJD is supported by the MRC-BBSRC, Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (Grant No. MR/K026992/1). HJG has received funding from German Research Foundation and Federal Ministry of Education and Research Germany and speakers honoraria from Eli Lilly and Servier. CH acknowledges support from the Medical Research Council (MRC) and the Biotechnology and Biological Sciences Research Council (BBSRC). DJM is supported by an , funded by the Chief Scientist Office. AMM is supported by a Scottish Funding Council Senior Clinical Fellowship and by the Dame Theresa and Mortimer Sackler Foundation and has received research support from Pfizer, Janssen, and Lilly. CMM was supported by the Netherlands Organization for Scientific Research (Grant No. NOW VENI 916-76-125). BM- M has consulted for Affectis Pharmaceuticals. MP has served on the advisory boards of Lundbeck and Eli Lilly ; BACKGROUND: Major depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. METHODS: Discovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer's disease, and coronary artery disease. RESULTS: We identified one replicated genome-wide significant locus associated with adult-onset (.27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11–1.21, p 5 5.2 3 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. CONCLUSIONS: We demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder. ; United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Mental Health (NIMH) MH085520 MH080403 ; SURFsara ; Netherlands Scientific Organization NWO 480-05-003 ; Department of Psychology, Vrije Universiteit Amsterdam ; Dutch Brain Foundation ; Federal Ministry of Education & Research (BMBF) 01GS08144 01GS08147 ; National Genome Research Network plus, and through the Integrated Network Integrated Understanding of Causes and Mechanisms in Mental Disorders ; e:Med Programme 01ZX1314A 01ZX1314G ; German Research Foundation (DFG) FOR2107 RI908/11-1 NO246/10-1 ; United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Mental Health (NIMH) MH061686 MH059542 MH075131 MH059552 MH059541 MH060912 ; Federal Ministry of Education & Research (BMBF) 01ES0811 ; Bavarian Ministry of Commerce ; Federal Ministry of Education & Research (BMBF) NGFN2 NGFN-Plus FKZ 01GS0481 01GS08145 ; Netherlands Organization for Scientific Research (MagW/ZonMW) 904-61-090 985-10-002 904-61-193 480-04004 400-05-717 912-100-20 ; Spinozapremie 56-464-14192 ; Geestkracht program 10-000-1002 ; Center for Medical Systems Biology (NWO Genomics) ; Biobanking and Biomolecular Resources Research Infrastructure ; Vrije Universiteit's Institutes for Health and Care Research and Neuroscience Campus Amsterdam ; BIC/BioAssist/RK 2008.024 ; European Science Foundation (ESF) EU/QLRT-200101254 ; European Union (EU) FP7/2007-2013 ; ENGAGE HEALTH-F4-2007-201413 ; European Science Council ERC 230374 ; United States Department of Health & Human Services National Institutes of Health (NIH) - USA ; GAIN ; United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Mental Health (NIMH) MH081802 MH072802 N01MH90003 ; National Health and Medical Research Council of Australia 241944 339462 389927 389875 389891 389892 389938 442915 442981 496675 496739 552485 552498 613602 613608 613674 619667 ; Australian Research Council FT0991360 FT0991022 ; FP-5 GenomEUtwin Project QLG2-CT-2002-01254 ; United States Department of Health & Human Services National Institutes of Health (NIH) - USA AA07535 AA10248 AA13320 AA13321 AA13326 AA14041 MH66206 DA12854 DA019951 U01 DK066134 ; Center for Inherited Disease Research (Baltimore, MD) ; UK Medical Research Council and GlaxoSmithKline G0701420 ; National Institute for Health Research (NIHR) ; Maudsley National Health Service Foundation Trust ; Institute of Psychiatry, King's College London ; Medical Research Council UK (MRC) G0000647 ; European Union (EU) 286213 ; European Commission Framework 6 grant (EC) LSHB-CT2003- 503428 ; GlaxoSmithKline ; Faculty of Biology and Medicine of Lausanne ; Swiss National Science Foundation (SNSF) 3200B0-105993 3200B0-118308 33CSCO-122661 33CS30-139468 33CS30-148401 ; GlaxoSmithKline Clinical Genetics ; Federal Ministry of Education & Research (BMBF) 01ZZ9603 01ZZ0103 01ZZ0403 03ZIK012 ; Ministry of Cultural Affairs ; Social Ministry of the Federal State of Mecklenburg-West Pomerania ; Siemens Healthcare, Erlangen, Germany ; German Research Foundation (DFG) GR 1912/5-1 FOR 2107 DA1151/5-1 ; Swedish Ministry for Higher Education ; Swedish Research Council M-2005-1112 ; GenomEUtwin QLG2-CT-2002-01254 EU/QLRT2001-01254 ; Swedish Foundation for Strategic Research ; Danske Strategiske Forskningsrad (DSF) ; Stanley Research Foundation ; European Union (EU) N Health-F2-2008-222963 ; Innovative Medizinische Forschung of the Medical Faculty of Munster DA120903 DA111107 DA211012 ; Wellcome Trust Strategic Award "Stratifying Resilience and Depression Longitudinally" 104036/Z/14/Z ; Chief Scientist Office of the Scottish Government Health Directorates CZD/16/6 ; Scottish Funding Council HR03006 ; Broad Institute Center for Genotyping and Analysis U54 RR020278 ; NARSAD ; Biotechnology and Biological Sciences Research Council (BBSRC) ; Medical Research Council UK (MRC) ; Federal Ministry of Education & Research (BMBF) ; Interdisciplinary Center for Clinical Research Munster ; National Health and Medical Research Council of Australia ; MRC-BBSRC, Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative MR/K026992/1 ; German Research Foundation (DFG) ; Federal Ministry of Education ; Research Germany and speakers honoraria from Eli Lilly and Servier ; Medical Research Council UK (MRC) ; Biotechnology and Biological Sciences Research Council (BBSRC) ; NRS Career Fellowship - Chief Scientist Office ; Scottish Funding Council Senior Clinical Fellowship ; Dame Theresa and Mortimer Sackler Foundation ; Netherlands Organization for Scientific Research (NWO) NOW VENI 916-76-125 ; Lundbeckfonden R155-2014-1724 ; Medical Research Council UK (MRC) MR/K026992/1 MC_PC_U127561128 1292844 ; Chief Scientist Office CZD/16/6/4
ENIGMA-CNV working group. ; Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function. ; 1000BRAINS: The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (Caspers) and the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement 945539 (Human Brain Project SGA3; Amunts, Caspers, Cichon). Brainscale: The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret I. Boomsma), 51.02.060 (Hilleke E. Hulshoff Pol), 668.772 (Dorret I. Boomsma and Hilleke E. Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret I. Boomsma), the European Research Council (ERC-230374) (Dorret I. Boomsma), High Potential Grant Utrecht University (Hilleke E.Hulshoff Pol) and NWO Brain and Cognition 433-09-220 (Hilleke E.Hulshoff Pol). Betula: The Betula study was funded by the Knut and Alice Wallenberg (KAW) foundation (Nyberg). The Freesurfer segmentations on the Betula sample were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N (in Umeå, Sweden), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers from the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud University Medical Centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received support from the participating departments and centres and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant 'Language in Interaction', the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 602450 (IMAGEMEND), 278948 (TACTICS) and 602805 (Aggressotype), as well as from the European Community's Horizon 2020 programme under grant agreement no. 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. deCODE genetics: deCODE genetics acknowledges support from the Innovative Medicines Initiative Joint Undertaking under grant agreement nos. 115008 (NEWMEDS) and 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union's Seventh Framework Programme (EU-FP7/2007-2013), EU-FP7-funded grant agreement no. 602450 (IMAGEMEND) and EU-funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC). Dublin: This work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and grant SFI08/IN.1/B1916-Corvin to Aidan C. Corvin). ECHO-DEFINE: The ECHO study acknowledges funding from a Medical Research Council (MRC) Centre Grant to Michael J. Owen (G0801418), the Wellcome Trust (Institutional Strategic Support Fund (ISSF) to van den Bree and Clinical Research Training Fellowship to Joanne L. Doherty), the Waterloo Foundation (WF 918-1234 to van den Bree), the Baily Thomas Charitable Fund (2315/1 to van den Bree), National Institute of Mental Health (NIMH 5UO1MH101724 to van den Bree and Michael J. Owen), the IMAGINE-2 study (funded by the MRC (MR/T033045/1) to van den Bree, Jeremy Hall and Michael J. Owen), the IMAGINE-ID study (funded by MRC (MR/N022572/1) to Jeremy Hall, van den Bree and Owen). The DEFINE study was supported by a Wellcome Trust Strategic Award (100202/Z/12/Z) to Michael J. Owen. ENIGMA: ENIGMA is supported in part by NIH grants U54 EB20403, R01MH116147 and R56AG058854. NIA T32AG058507; NIH/NIMH 5T32MH073526. EPIGEN-Dublin: The EPIGEN-Dublin cohort was supported by a Science Foundation Ireland Research Frontiers Programme award (08/RFP/GEN1538). EPIGEN-UK (Sisodiya): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health's NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. GAP: This work was supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King's College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. GOBS: The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111 and R01 MH083824, with work conducted in part in facilities constructed under the support of NIH grant C06 RR020547. GSP: Data were in part provided by the Brain Genomics Superstruct Project (GSP) of Harvard University and Massachusetts General Hospital (MGH) (Principal Investigators: Randy Buckner, Jordan Smoller and Joshua Roffman), with support from the Center for Brain Science Neuroinformatics Research Group, Athinoula A. Martinos Center for Biomedical Imaging, Center for Genomic Medicine and Stanley Center for Psychiatric Research. Twenty individual investigators at Harvard and MGH generously contributed data to the overall project. We would like to thank Randy Buckner for insightful comments and feedback on this work. HUBIN: The HUBIN study was financed by the Swedish Research Council (K2010-62X-15078-07-2, K2012-61X-15078-09-3, 521-2014-3487 K2015-62X-15077-12-3, 2017-00949), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet. HUNT: The HUNT study is a collaboration between HUNT Research Centre (Faculty of Medicine and Movement Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant 'STRATIFY' (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907),the FP7 projects IMAGEMEND(602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300-2), the Medical Research Council Grant 'c-VEDA' (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152, 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants, SM 80/7-2, SFB 940/2), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l'Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. Lifespan: The study is funded by the Research Council of Norway (230345, 288083 and 223273). NCNG: NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the Research Council of Norway, to le Hellard, Steen and Espeseth. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to Arvid Lundervold, Grant 911397 and 911687 to Astri Johansen Lundervold). NTR: The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004,463-06-001, 451-04-034, 400-05-717, Addiction-31160008, 016-115-035, 481-08-011, 056-32-010, Middelgroot-911-09-032, OCW_NWO Gravity programme—024.001.003, NWO-Groot 480-15-001/674, Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) and University Research Fellow grant (URF) to Dorret I. Boomsma; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community's Seventh Framework Programme (FP7- HEALTH-F4-2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC Starting 284167, ERC Consolidator 771057, ERC Advanced 230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the National Institutes of Health (NIH, R01D0042157-01A1, R01MH58799-03, MH081802, DA018673, R01 DK092127-04, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by NWO through grant 2018/EW/00408559, BiG Grid, the Dutch e-Science Grid and SURFSARA. OATS: The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Programme (ID No. 401162) and NHMRC Project Grants (ID Nos. 1045325 and 1085606). This research was facilitated through Twins Research Australia, a national resource in part supported by an NHMRC Centre for Research Excellence Grant (ID No.: 1079102). We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organization Flagship Collaboration Fund Grant. Osaka: Osaka study was supported by the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS: Grant Number JP18dm0207006), Brain/MINDS& beyond studies (Grant Number JP20dm0307002) and Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities (Grant Number JP20dk0307081) from the Japan Agency for Medical Research and Development (AMED), Grants-in-Aid for Scientific Research (KAKENHI; Grant Numbers JP25293250 and JP16H05375). Some computations were performed at the Research Center for Computational Science, Okazaki, Japan. PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI2005-0308007 and the FundaciónMarqués de Valdecilla API07/011. Biological samples from our cohort were stored at the Valdecilla Biobank and genotyping services were conducted at the Spanish 'Centro Nacional de Genotipado' (CEGEN-ISCIII). MCIC/COBRE: The study is funded by the National Institutes of Health studies R01EB006841, P20GM103472 and P30GM122734 and Department of Energy DE-FG02-99ER62764. PING: Data collection and sharing for the Paediatric Imaging, Neurocognition and Genetics (PING) Study (National Institutes of Health Grant RC2DA029475) were funded by the National Institute on Drug Abuse and the Eunice Kennedy Shriver National Institute of Child Health & Human Development. A full list of PING investigators is at http://pingstudy.ucsd.edu/investigators.html. QTIM: The QTIM study was supported by the National Institute of Child Health and Human Development (R01 HD050735) and the National Health and Medical Research Council (NHMRC 486682, 1009064), Australia. Genotyping was supported by NHMRC (389875). Medland is supported in part by an NHMRC fellowship (APP1103623). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide single-nucleotide polymorphism typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. StrokeMRI: StrokeMRI was supported by the Norwegian ExtraFoundation for Health and Rehabilitation(2015/FO5146), the Research Council of Norway (249795, 262372), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Department of Psychology, University of Oslo. Sydney MAS: The Sydney Memory and Aging Study (Sydney MAS) is funded by National and HealthMedical Research Council (NHMRC) Programme and Project Grants (ID350833, ID568969 and ID109308). We also thank the Sydney MAS participants and the Research Team. SYS: The SYS Study is supported by Canadian Institutes of Health Research. TOP: Centre of Excellence: RCN #23273 and RCN #226971. Part of this work was performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT) (tsd-drift@usit.uio.no). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2013-COFUND) under grant agreement no. 609020—Scientia Fellows; the Research Council of Norway (RCN) #276082—A lifespan perspective on mental illness: toward precision medicine using multimodal brain imaging and genetics. Ida E. Sønderby and Rune Bøen are supported by South-Eastern Norway Regional Health Authority (#2020060). Ida E. Sønderby and Ole A. Andreassen have received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant agreement no. 847776 (CoMorMent project) and the KG Jebsen Foundation (SKGJ-MED-021). UCLA_UMCU: The UCLA_UMCU cohort comprises of six studies which were supported by National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) (20244 to Prof. Hillegers), The Netherlands Organisation for Health Research and Development (ZonMw) (908-02-123 to Prof. Hulshoff Pol), and Netherlands Organisation for Scientific Research (NWO 9120818 and NWO-VIDI 917-46-370 to Prof. Hulshoff Pol). The GROUP study was funded through the Geestkracht programme of the Dutch Health Research Council (ZonMw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly and Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ inGeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord-Holland-Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia Psycho-medical Center, The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh, voor Geestelijke Gezondheid, Mondriaan, Virenzeriagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-JozefKortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht, GGZ Centraal and Delta.). UK Biobank: This work made use of data sharing from UK Biobank (under project code 27412). Others: Work by Pierre Vanderhaeghen was funded by Grants of the European Research Council (ERC Adv Grant GENDEVOCORTEX), the EOS Programme, the Belgian FWO, the AXA Research Fund and the Belgian Queen Elizabeth Foundation. Ikuo K. Suzuki was supported by a postdoctoral fellowship of the FRS/FNRS. ; Peer reviewed
Der Eintrag von Phosphor in die Umwelt führt zur Eutrophierung von Gewässern, sodass ein Großteil dieser innerhalb der Europäischen Union (EU) in keinem guten chemischen Zustand ist. Phosphor gelangt überwiegend auf zwei Wegen in die Umwelt, diffus durch Auswaschung von auf landwirtschaftlichen Flächen ausgebrachten Düngemitteln oder punktuell über das gereinigte Abwasser. Der Eintragspfad über das Abwasser umfasst auch die zahlreichen dezentralen Kleinkläranlagen (KKA), die in letzter Zeit zunehmend in den Fokus rückten. So muss zum Beispiel durch die Verschärfung der gesetzlichen Vorgaben in sensiblen Gebieten in Bayern auch in KKA eine Phosphorentfernung realisiert werden. Ein weiterer Aspekt in diesem Zusammenhang ist, dass die EU-Staaten auf Importe von Phosphor sowie Phosphaterz angewiesen sind, sodass eine gezielte Rückgewinnung des entfernten Phosphors anzustreben ist. Ziel dieser Dissertation war die Entwicklung eines nachhaltigen Verfahrenskonzeptes zur wartungsarmen Phosphorentfernung in KKA unter Gewinnung eines marktfähigen Phosphorproduktes, wobei eine Adsorptionsstufe den Kern des Verfahrens bilden sollte. Die Phosphorentfernung aus der Wasserphase in einem Festbettadsorber ermöglicht neben dem wartungsarmen Betrieb, einen geringen Platzbedarf, eine hohe Effizienz und nach der wirtschaftlich notwendigen Adsorbensregenerierung die vergleichsweise einfache Phosphorrückgewinnung durch Fällung. Viele verschiedene Materialien, von synthetischen Mineralen und Ionenaustauschern über Hybridmaterialien bis hin zu industriellen Nebenprodukten, wurden anhand von Literaturangaben und Laborversuchen bezüglich ihrer Eignung zur Phosphatadsorption betrachtet. Für potenziell geeignete Materialien mit hoher Verfügbarkeit wurde mit Hilfe des Linear Driving Force (LDF-) Modells eine validierte Prognose für einen Festbettadsorber in einer KKA erstellt. Dabei wurde die geforderte Phosphorkonzentration von maximal 2 mg/L im Ablauf des Festbettadsorbers während des sechsmonatigen Wartungsintervalls insbesondere durch die granulierten Eisenoxidhydrate GEH® 104 und Bayoxide® E 33 HC eingehalten. Die weiteren Untersuchungen erfolgten überwiegend am Beispiel des Adsorbens GEH® 104. Die Phosphatadsorption an GEH® 104 in einem biologisch gereinigten Abwasser wird lediglich durch den pH-Wert und die Gesamthärte signifikant beeinflusst. Diese Abhängigkeit lässt sich gut mit Hilfe eines empirisch ermittelten Gleichungssystems beschreiben, welches die Berechnung der Freundlich-Parameter der Gleichgewichtsisotherme und des effektiven Stofftransportkoeffizienten der Korndiffusion aus diesen Wasserparametern ermöglicht. Die Anwendung dieses Gleichungssystems erlaubt den Verzicht auf mehrwöchige Laborversuche. Die Dimensionierung eines Festbettadsorbers in einer KKA mit dem LDF-Modell basierend auf dem pH-Wert (6.8), der Gesamthärte (0,5.4,5 M) und der Phosphatkonzentration (ca. 50 mg/L) ist so innerhalb einiger Minuten möglich. Die Wirtschaftlichkeit der adsorptiven Phosphorentfernung wird durch eine erfolgreiche Regenerierung mitbestimmt. Es konnte nachgewiesen werden, dass vor allem auf der Adsorbensoberfläche abgeschiedene Calciumphosphate zu Verlusten von bis zu 85 % der Adsorptionskapazität der eingesetzten Eisenoxidhydrate führen. Etwa 80 % des Calciums liegen auf der Adsorbensoberfläche physisorbiert vor, während die restlichen 20 % durch lokale Ausfällungen die Oberfläche blockieren. Die neu entwickelte pH-Swing-Regenerierung, die eine saure Konditionierung bei pH 2,5 vor der alkalischen Phosphatdesorption enthält, entfernt diese Ablagerungen. Dabei werden die Eisenoxidhydratadsorbentien vollständig regeneriert und währenddessen nur zu etwa 0,0001 % aufgelöst. Über 13 Regenerierungszyklen wurde keine Verringerung der Adsorptionskapazität weder in Modell- noch gereinigtem Abwasser beobachtet. Die saure Konditionierung bei pH 2,5 lässt sich mit den Mineralsäuren HCl und HNO3 realisieren, wobei sich eine Kreislaufführung als vorteilhaft hinsichtlich des Chemikalieneinsatzes erwies. Zur Desorption von 95 % des adsorbierten Phosphats waren 5 Bettvolumen (BV) der 1 M NaOH bei einer Leeraumkontaktzeit (EBCT) von mindestens 25 min ausreichend. Die abschließende Rekonditionierung im Kreislauf erfolgte mit 2 BV Wasser sowie 0,16 BV HCl (konz.) zur Einstellung von pH 6 auf der Adsorbensoberfläche. Aus der phosphatreichen Desorptionslösung wurde durch Verwendung technischer, feindisperser Kalkmilch ein amorphes Calciumphosphat (aCP) mit einem Phosphorgehalt von mindestens 10 % gefällt, während die Natronlauge zur erneuten Phosphatdesorption zur Verfügung stand. Das aCP enthielt Calciumcarbonat und -hydroxid als Nebenbestandteile, während der TOC unter 1 % lag. Im Gegensatz zu organischen Spurenstoffen adsorbierten Schwermetalle an GEH® 104 und wurden bei der sauren Konditionierung zu großen Teilen wieder entfernt. Das während eines Pilotversuchs an einer KKA gewonnene Fällungsprodukt (Pilot-aCP) hielt die gesetzlichen Anforderungen für Düngemittel in Deutschland und der EU bezüglich des Gehalts an Schwermetallen ein. Es wies zudem eine ausreichende Citrat-, Neutralammoniumcitrat und Wasserlöslichkeit auf und könnte als Düngemittel eingesetzt werden. Insgesamt ist das Verfahren der dezentralen adsorptiven Phosphorentfernung mit zentraler pH-Swing-Regenerierung deutlich wirtschaftlicher als die Einmalnutzung des Adsorbens ohne Regenerierung. Auch wenn das Pilot-aCP lediglich als Nebenprodukt der Adsorbensregenerierung anfällt, kann das Verfahren in mehreren Punkten (Phosphorrückgewinnungsgrad, Produktqualität, Markt und Kompatibilität mit der bestehenden Infrastruktur auf Kläranlagen) mit anderen Technologien zur Phosphorrückgewinnung konkurrieren. Es bietet eine zuverlässige Lösung für das Erreichen niedriger Ablaufwerte für Phosphor in (Klein-)Kläranlagen.:1. Einleitung 1.1. Bedeutung von Phosphor für den menschlichen Organismus 1.2. Phosphoreintrag in die Umwelt 1.3. Zielstellung und Struktur der Dissertation 2. Grundlagen 2.1. Ressourcenverteilung und -entwicklung 2.2. Strategien zum nachhaltigen Phosphormanagement in der Landwirtschaft 2.3. Phosphor in der zentralen Abwasserreinigung 2.3.1. Phosphorentfernung an punktuellen Emissionsquellen 2.3.2. Phosphorrückgewinnung 2.4. Kleinkläranlagen zur Abwasserbehandlung und Phosphorentfernung 2.4.1. Abwasserbehandlung in Kleinkläranlagen 2.4.2. Phosphorentfernung in Kleinkläranlagen 2.5. Technische Adsorption 2.5.1. Adsorptionsgleichgewicht 2.5.2. Adsorptionsmodellierung 3. Potenziell geeignete Materialien zur Phosphatadsorption in Kleinkläranlagen - Adsorbensauswahl 3.1. Stand der Forschung 3.1.1. Ionenaustauscher 3.1.1.1. Klassische Ionenaustauscher 3.1.1.2. Schichthydroxide 3.1.2. Hybridmaterialien 3.1.2.1. Polymere Ligandenaustauscher (PLE) 3.1.2.2. Hybride Anionenaustauscher (HAIX) 3.1.3. Adsorbentien 3.1.3.1. Verbindungen der Hauptelemente der Erdhülle 3.1.3.2. Verbindungen der Nebenelemente der Erdhülle 3.1.3.3. Kohlenstoffbasierte Materialien 3.1.3.4. Industrielle Nebenprodukte 3.1.4. Auswahl geeigneter Adsorbentien 3.1.5. Auslegung eines Festbettadsorbers in KKA 3.2. Material und Methoden 3.2.1. Chemikalien und angewandte Analysenverfahren 3.2.2. Untersuchte Adsorbentien 3.2.2.1. Klassische Adsorbentien 3.2.2.2. Hybride Anionenaustauscher (HAIX) 3.2.3. Modellabwasser 3.2.4. Methoden zur Untersuchung der Phosphatadsorption 3.2.5. Zur Modellierung eingesetzte Programme 3.3. Modellierung einer 4 EW-KKA 3.3.1. Erhobene experimentelle Daten 3.3.1.1. Wasserzusammensetzung einer KKA 3.3.1.2. Bestimmung der Freundlich-Isothermen der Adsorbentien - Adsorptionsgleichgewicht 3.3.1.3. Untersuchung der Kinetik der Korndiffusion 3.3.2. Modellierung der Durchbruchskurve 3.3.2.1. Basisdaten 3.3.2.2. Modellierung der Durchbruchskurven 3.3.3. Experimentelle Validierung der modellierten Durchbruchskurven im Labor 3.3.4. Erstellung der Prognose eines Festbettadsorbers zur Phosphatentfernung in einer 4-EW-KKA 4. Wasserchemische Einflussfaktoren auf die Phosphatadsorption an Eisenoxidhydraten 4.1. Stand der Forschung 4.1.1. Phosphatbindung an Eisenoxidhydraten 4.1.2. Phosphatadsorption in Anwesenheit anderer Anionen 4.1.3. Phosphatadsorption in Anwesenheit organischer Stoffe 4.1.4. Phosphatadsorption in Gegenwart von Kationen 4.2. Material und Methoden 4.2.1. Chemikalien und angewandte Analysenverfahren 4.2.2. Modellwässer 4.2.3. Methoden 4.3. Untersuchung der Einflussfaktoren auf die Phosphatadsorption an GEH® 104 4.3.1. Phosphatadsorption in Anwesenheit anionischer Verbindungen 4.3.2. Phosphatadsorption in Gegenwart von Kationen 4.3.2.1. Einfluss des pH-Wertes 4.3.2.2. Einfluss der Calciumkonzentration 4.3.2.3. Einfluss der Magnesiumkonzentration 4.3.2.4. Einfluss der Gesamthärte des Wassers 4.4. Matrixanpassbare Modellierung der Phosphatadsorption an GEH® 104 5. Regenerierung von Eisenoxidhydraten 5.1. Stand der Forschung 5.2. Material und Methoden 5.2.1. Chemikalien 5.2.2. Angewandte Analysenverfahren 5.2.3. Modellwässer 5.2.4. Methodik der Adsorbensregenerierung 5.2.4.1. Aufnahme von Durchbruchskurven 5.2.4.2. Beladen des Adsorbens zur Untersuchung der Regenerierung 5.2.4.3. Vergleich der Calciumdesorption mit verschiedenen Desorptionslösungen 5.2.4.4. Entfernung von Ablagerungen durch saure Konditionierung 5.2.4.5. Desorption von Phosphat 5.2.4.6. Rekonditionierung des Adsorbens 5.2.5. Zur Modellierung eingesetzte Programme 5.3. Untersuchung der Adsorbensoberfläche 5.4. Entfernung des Oberflächenbelags 5.4.1. Einführung einer sauren Konditionierungsstufe 5.4.1.1. Säurestabilität des Adsorbens und möglicher Oberflächenpräzipitate 5.4.1.2. Wechselwirkungen von Calcium mit der Adsorbensoberfläche 5.4.1.3. Auswahl des Konditionierungsmittels 5.4.1.4. Auswahl des pH-Wertes für die saure Konditionierung 5.4.1.5. Übertragbarkeit der sauren Konditionierung auf weitere eisenoxidhydrathaltige Adsorbentien 5.4.1.6. Auswirkung der sauren Konditionierung auf die Ablagerungen 5.4.1.7. Auswirkung der sauren Konditionierung auf die Adsorbensoberfläche 5.4.2. Validierung der sauren Konditionierung 5.5. Optimierung der pH-Swing-Regenerierung 5.5.1. Optimierung der Betriebsweise der sauren Konditionierung 5.5.1.1. Kreislaufführung 5.5.1.2. Wiederverwendung der Konditionierungslösung 5.5.2. Optimierung der Phosphatdesorption 5.5.2.1. Einfluss der Konzentration der Natronlauge auf die Phosphatdesorption 5.5.2.2. Einfluss der Kontaktzeit auf die Phosphatdesorption 5.5.2.3. Prozessführung zur Phosphatdesorption von GEH® 104 5.5.3. Optimierung der Rekonditionierung des Adsorbens 5.5.4. Zusammenfassung 6. Phosphorrückgewinnung 6.1. Stand der Forschung 6.1.1. Gewinnung von Phosphatrecyclaten 6.1.2. Schadstofftransfer vom Abwasser in Phosphatrecyclate 6.1.2.1. Organische Spurenstoffe 6.1.2.2. Schwermetalle 6.1.3. Pflanzenverfügbarkeit von Phosphatrecyclaten 6.2. Material und Methoden 6.2.1. Chemikalien 6.2.2. Angewandte Analysenverfahren 6.2.3. Verwendete Wässer 6.2.4. Methodik zur Untersuchung der Phosphorrückgewinnung 6.3. Phosphatfällung 6.3.1. Auswahl des Fällmittels 6.3.2. Zusammensetzung des Fällungsproduktes 6.4. Verhalten organischer Spurenstoffe bei der Phosphorrückgewinnung 6.5. Untersuchung der Düngemitteleignung anhand einer Pilotanlage zur Phosphorentfernung aus KKA 6.5.1. Adsorbensbeladung im Pilotmaßstab 6.5.2. Regenerierung von Pilotversuchsmaterial 6.5.2.1. Saure Konditionierung als Schwermetalldesorption 6.5.2.2. Verunreinigungen bei der Phosphatdesorption 6.5.2.3. Phosphorrückgewinnung aus dem Pilotversuch 6.5.3. Pflanzenverfügbarkeit 7. Diskussion 7.1. Verfahrenskonzept für die Phosphorentfernung in Kleinkläranlagen (KKA) 7.2. Verfahrensbewertung 7.2.1. Technologie 7.2.1.1. Rückgewinnungsgrad 7.2.1.2. Inputflexibilität 7.2.2. Produkt 7.2.3. Markt 7.2.4. Umwelt 7.2.4.1. Chemikalieneinsatz 7.2.4.2. Energiebedarf 7.2.4.3. Anfallende Abfälle 7.2.5. Wirtschaftlichkeit 7.2.5.1. Investitionsbedarf 7.2.5.2. Operative Kosten 7.2.5.3. Produktertrag 7.2.5.4. Zusatzerträge und -nutzen 7.2.6. Kompatibilität 7.2.6.1. Einfluss auf die heutige Entsorgungslandschaft 7.2.6.2. Kompatibilität mit dem Betrieb der Kläranlage 7.2.7. Rechtlicher Rahmen 7.2.8. Zusammenfassung der Verfahrensbewertung 7.3. Fazit 8. Publikationsliste Literaturverzeichnis Abkürzungsverzeichnis Symbolverzeichnis Abbildungsverzeichnis Tabellenverzeichnis A. Anhang A.1. Anhang Kapitel 3 A.1.1. Materialien zur Phosphatentfernung in der Literatur A.1.1.1. Ionenaustauscher A.1.1.2. Hybridmaterialien A.1.1.3. Adsorbentien A.1.2. Aufbau eines Differentialkreislaufreaktors A.1.3. Bestimmung des geschwindigkeitsbestimmenden Schrittes der Adsorption A.1.4. Validierung der Modellierung mit LDF-Modell A.2. Anhang Kapitel 4 A.2.1. Phosphatdurchbruchskurve mit variierender Sulfatkonzentration A.2.2. Phosphatisotherme bei variierendem pH-Wert A.2.3. Wasserhärte in Deutschland nach Wasserversorgern A.2.4. Phosphatadsorption in Abhängigkeit von den vorliegenden Kationen A.2.5. Zweifaktorielle Varianzanalyse A.3. Anhang Kapitel 5 A.3.1. Saure Konditionierung im Kreislauf A.3.2. Löslichkeitsmodellierung mit PHREEQC A.3.3. Desorbierbarkeit von Calcium und Magnesium mit Natriumnitratlösung A.3.4. Austrag von Calcium, Phosphat und Eisen bei der sauren Konditionierung von beladenem Bayoxide® E 33 HC A.3.5. Reproduzierbarkeit des Phosphatdurchbruchs bei pH-Swing-Regenerierung mit Salpetersäure A.3.6. Zusammensetzung verschiedener Calciumphosphate A.4. Anhang Kapitel 6 A.4.1. Grenzwerte für Schwermetalle in mineralischen und Recyclingphosphordüngemitteln in Europa A.4.2. Messbedingungen für die Analysen mittels LC-MS/MS A.4.3. Thermische Zersetzung von amorphem Calciumphosphat A.4.4. Phosphorentfernung in der Pilotanlage in Bramsche A.4.5. Regenerierung eines beladenen Adsorbens aus der Pilotanlage A.4.6. Untersuchte organische Spurenstoffe bei der Gewinnung von Pilot-aCP A.5. Anhang Kapitel 7 A.5.1. Kostenabschätzung für das Verfahrenskonzept zur Phosphorentfernung auf KKA A.5.2. Preisentwicklung für Phosphate von 1999 bis 2019 auf dem Weltmarkt A.5.3. Einordnung des entwickelten Verfahrenskonzeptes nach dem BAFU-Leitfaden Danksagung Erklärung ; Phosphorus pollution of the environment causes the eutrophication of surface water bodies, so many of them within the European Union (EU) are not in good status. Phosphorus enters the environment mainly via two pathways, diffusely by leaching of fertilizers applied to agricultural areas or as a point source via treated wastewater. The discharge via wastewater also includes the numerous decentralized small sewage treatment plants (SSTPs), that have increasingly come into focus. For example, a tightening of the legal requirements in sensitive areas in Bavaria requires the implementation of phosphorus removal also in SSTPs. Another aspect is the dependency of the EU on imports of phosphorus and phosphate ore, so the removed phosphorus should therefore be recovered. The aim of this dissertation was to develop a sustainable process concept for low-maintenance phosphorus removal in SSTPs while obtaining a marketable phosphorus product, based on an adsorption stage. Using a fixed-bed adsorber for phosphorus removal allows operation with low maintenance, low space requirements and high efficiency. Moreover, after the economically necessary adsorbent regeneration, a comparatively easy phosphorus recovery using precipitation is possible. Many different materials, beginning with synthetic minerals and ion exchange resins to hybrid materials and industrial by-products, were examined for their suitability for phosphate adsorption based on literature references and laboratory tests. For potentially suitable materials with high availability, a validated prognosis of the fixed-bed adsorber performance in a SSTP was carried out using the linear driving force (LDF) model. Only the granular ferric (hydr)oxides GEH® 104 and Bayoxide® E 33 HC met the required phosphorus concentration of a maximum of 2 mg/L in the effluent of the fixed-bed adsorber during the six-month maintenance interval. Further investigations were mainly carried out using the adsorbent GEH® 104 as an example. The phosphate adsorption onto GEH® 104 in biologically treated wastewater is significantly influenced only by pH and total hardness. This dependence can be described well by an empirical system of equations that allows the calculation of the Freundlich parameters of the equilibrium isotherm and the effective intraparticle mass transfer coefficient for the given conditions. The application of this system of equations allows the avoidance of time-consuming laboratory experiments. In contrast to the weeks of lab experiments, the scale-up of a fixed-bed adsorber in a SSTP with the LDF model based on pH value (6.8), total hardness (0.5.4.5 M) and phosphate concentration (approx. 50 mg/L) takes only a few minutes. The economic efficiency of adsorptive phosphorus removal depends on a successful regeneration. It was demonstrated that the calcium phosphates precipitated on the adsorbent surface caused losses of up to 85 % of the adsorption capacity of the ferric (hydr)oxide used. About 80 % of the calcium is bound via physisorption on the adsorbent surface, while the remaining 20 % blocks the surface by local precipitation. A newly developed pH-swing-regeneration, which includes an acidic conditioning at pH 2.5 prior to alkaline phosphate desorption, was found to remove these deposits. During this process the ferric (hydr)oxides are completely regenerated and the mass loss by dissolution is only about 0.0001 %. For 13 regeneration cycles no reduction in adsorption capacity was observed, neither for model nor for biologically treated wastewater. Acidic conditioning at pH 2.5 can be carried out using the mineral acids HCl and HNO3. A recirculation of these acids proved to be advantageous regarding the consumption of chemicals. For the desorption of 95 % of the adsorbed phosphate, 5 bed volumes (BV) of 1 M NaOH with an empty bed contact time (EBCT) of at least 25 min were sufficient. The final reconditioning requires 2 BV of water and 0.16 BV of HCl (conc.) to adjust the pH on the adsorbent surface to 6. The phosphate-rich desorption solution was used for the precipitation of an amorphous calcium phosphate (aCP) using technical grade, fine dispersed milk of lime. The phosphorus content of aCP was at least 10 % and the sodium hydroxide solution can be used for renewed phosphate desorption. The aCP contained calcium carbonate and hydroxide as minor constituents, while organic carbon content was below 1 %. In contrast to organic micropollutants, heavy metals adsorbed onto GEH® 104 and were largely removed during acidic conditioning. However, the precipitation product obtained during a pilot test at a SSTP (pilot-aCP) meets the legal requirements for fertilizers in Germany and the EU regarding heavy metal content. In addition, it was sufficiently soluble in citrate, neutral ammonium citrate and water and could therefore be used as a fertilizer. In summary the process of decentralized adsorptive phosphorus removal with centralized pH-swing-regeneration is more economical than the one-time use of the adsorbent without regeneration. Even though the pilot-aCP is only a by-product of adsorbent regeneration, the process can compete with other phosphorus recovery technologies in several aspects (phosphorus recovery efficiency, product quality, market and compatibility with existing infrastructure at sewage treatment plants). It offers a reliable solution for achieving low effluent values for phosphorus in (small) sewage treatment plants.:1. Einleitung 1.1. Bedeutung von Phosphor für den menschlichen Organismus 1.2. Phosphoreintrag in die Umwelt 1.3. Zielstellung und Struktur der Dissertation 2. Grundlagen 2.1. Ressourcenverteilung und -entwicklung 2.2. Strategien zum nachhaltigen Phosphormanagement in der Landwirtschaft 2.3. Phosphor in der zentralen Abwasserreinigung 2.3.1. Phosphorentfernung an punktuellen Emissionsquellen 2.3.2. Phosphorrückgewinnung 2.4. Kleinkläranlagen zur Abwasserbehandlung und Phosphorentfernung 2.4.1. Abwasserbehandlung in Kleinkläranlagen 2.4.2. Phosphorentfernung in Kleinkläranlagen 2.5. Technische Adsorption 2.5.1. Adsorptionsgleichgewicht 2.5.2. Adsorptionsmodellierung 3. Potenziell geeignete Materialien zur Phosphatadsorption in Kleinkläranlagen - Adsorbensauswahl 3.1. Stand der Forschung 3.1.1. Ionenaustauscher 3.1.1.1. Klassische Ionenaustauscher 3.1.1.2. Schichthydroxide 3.1.2. Hybridmaterialien 3.1.2.1. Polymere Ligandenaustauscher (PLE) 3.1.2.2. Hybride Anionenaustauscher (HAIX) 3.1.3. Adsorbentien 3.1.3.1. Verbindungen der Hauptelemente der Erdhülle 3.1.3.2. Verbindungen der Nebenelemente der Erdhülle 3.1.3.3. Kohlenstoffbasierte Materialien 3.1.3.4. Industrielle Nebenprodukte 3.1.4. Auswahl geeigneter Adsorbentien 3.1.5. Auslegung eines Festbettadsorbers in KKA 3.2. Material und Methoden 3.2.1. Chemikalien und angewandte Analysenverfahren 3.2.2. Untersuchte Adsorbentien 3.2.2.1. Klassische Adsorbentien 3.2.2.2. Hybride Anionenaustauscher (HAIX) 3.2.3. Modellabwasser 3.2.4. Methoden zur Untersuchung der Phosphatadsorption 3.2.5. Zur Modellierung eingesetzte Programme 3.3. Modellierung einer 4 EW-KKA 3.3.1. Erhobene experimentelle Daten 3.3.1.1. Wasserzusammensetzung einer KKA 3.3.1.2. Bestimmung der Freundlich-Isothermen der Adsorbentien - Adsorptionsgleichgewicht 3.3.1.3. Untersuchung der Kinetik der Korndiffusion 3.3.2. Modellierung der Durchbruchskurve 3.3.2.1. Basisdaten 3.3.2.2. Modellierung der Durchbruchskurven 3.3.3. Experimentelle Validierung der modellierten Durchbruchskurven im Labor 3.3.4. Erstellung der Prognose eines Festbettadsorbers zur Phosphatentfernung in einer 4-EW-KKA 4. Wasserchemische Einflussfaktoren auf die Phosphatadsorption an Eisenoxidhydraten 4.1. Stand der Forschung 4.1.1. Phosphatbindung an Eisenoxidhydraten 4.1.2. Phosphatadsorption in Anwesenheit anderer Anionen 4.1.3. Phosphatadsorption in Anwesenheit organischer Stoffe 4.1.4. Phosphatadsorption in Gegenwart von Kationen 4.2. Material und Methoden 4.2.1. Chemikalien und angewandte Analysenverfahren 4.2.2. Modellwässer 4.2.3. Methoden 4.3. Untersuchung der Einflussfaktoren auf die Phosphatadsorption an GEH® 104 4.3.1. Phosphatadsorption in Anwesenheit anionischer Verbindungen 4.3.2. Phosphatadsorption in Gegenwart von Kationen 4.3.2.1. Einfluss des pH-Wertes 4.3.2.2. Einfluss der Calciumkonzentration 4.3.2.3. Einfluss der Magnesiumkonzentration 4.3.2.4. Einfluss der Gesamthärte des Wassers 4.4. Matrixanpassbare Modellierung der Phosphatadsorption an GEH® 104 5. Regenerierung von Eisenoxidhydraten 5.1. Stand der Forschung 5.2. Material und Methoden 5.2.1. Chemikalien 5.2.2. Angewandte Analysenverfahren 5.2.3. Modellwässer 5.2.4. Methodik der Adsorbensregenerierung 5.2.4.1. Aufnahme von Durchbruchskurven 5.2.4.2. Beladen des Adsorbens zur Untersuchung der Regenerierung 5.2.4.3. Vergleich der Calciumdesorption mit verschiedenen Desorptionslösungen 5.2.4.4. Entfernung von Ablagerungen durch saure Konditionierung 5.2.4.5. Desorption von Phosphat 5.2.4.6. Rekonditionierung des Adsorbens 5.2.5. Zur Modellierung eingesetzte Programme 5.3. Untersuchung der Adsorbensoberfläche 5.4. Entfernung des Oberflächenbelags 5.4.1. Einführung einer sauren Konditionierungsstufe 5.4.1.1. Säurestabilität des Adsorbens und möglicher Oberflächenpräzipitate 5.4.1.2. Wechselwirkungen von Calcium mit der Adsorbensoberfläche 5.4.1.3. Auswahl des Konditionierungsmittels 5.4.1.4. Auswahl des pH-Wertes für die saure Konditionierung 5.4.1.5. Übertragbarkeit der sauren Konditionierung auf weitere eisenoxidhydrathaltige Adsorbentien 5.4.1.6. Auswirkung der sauren Konditionierung auf die Ablagerungen 5.4.1.7. Auswirkung der sauren Konditionierung auf die Adsorbensoberfläche 5.4.2. Validierung der sauren Konditionierung 5.5. Optimierung der pH-Swing-Regenerierung 5.5.1. Optimierung der Betriebsweise der sauren Konditionierung 5.5.1.1. Kreislaufführung 5.5.1.2. Wiederverwendung der Konditionierungslösung 5.5.2. Optimierung der Phosphatdesorption 5.5.2.1. Einfluss der Konzentration der Natronlauge auf die Phosphatdesorption 5.5.2.2. Einfluss der Kontaktzeit auf die Phosphatdesorption 5.5.2.3. Prozessführung zur Phosphatdesorption von GEH® 104 5.5.3. Optimierung der Rekonditionierung des Adsorbens 5.5.4. Zusammenfassung 6. Phosphorrückgewinnung 6.1. Stand der Forschung 6.1.1. Gewinnung von Phosphatrecyclaten 6.1.2. Schadstofftransfer vom Abwasser in Phosphatrecyclate 6.1.2.1. Organische Spurenstoffe 6.1.2.2. Schwermetalle 6.1.3. Pflanzenverfügbarkeit von Phosphatrecyclaten 6.2. Material und Methoden 6.2.1. Chemikalien 6.2.2. Angewandte Analysenverfahren 6.2.3. Verwendete Wässer 6.2.4. Methodik zur Untersuchung der Phosphorrückgewinnung 6.3. Phosphatfällung 6.3.1. Auswahl des Fällmittels 6.3.2. Zusammensetzung des Fällungsproduktes 6.4. Verhalten organischer Spurenstoffe bei der Phosphorrückgewinnung 6.5. Untersuchung der Düngemitteleignung anhand einer Pilotanlage zur Phosphorentfernung aus KKA 6.5.1. Adsorbensbeladung im Pilotmaßstab 6.5.2. Regenerierung von Pilotversuchsmaterial 6.5.2.1. Saure Konditionierung als Schwermetalldesorption 6.5.2.2. Verunreinigungen bei der Phosphatdesorption 6.5.2.3. Phosphorrückgewinnung aus dem Pilotversuch 6.5.3. Pflanzenverfügbarkeit 7. Diskussion 7.1. Verfahrenskonzept für die Phosphorentfernung in Kleinkläranlagen (KKA) 7.2. Verfahrensbewertung 7.2.1. Technologie 7.2.1.1. Rückgewinnungsgrad 7.2.1.2. Inputflexibilität 7.2.2. Produkt 7.2.3. Markt 7.2.4. Umwelt 7.2.4.1. Chemikalieneinsatz 7.2.4.2. Energiebedarf 7.2.4.3. Anfallende Abfälle 7.2.5. Wirtschaftlichkeit 7.2.5.1. Investitionsbedarf 7.2.5.2. Operative Kosten 7.2.5.3. Produktertrag 7.2.5.4. Zusatzerträge und -nutzen 7.2.6. Kompatibilität 7.2.6.1. Einfluss auf die heutige Entsorgungslandschaft 7.2.6.2. Kompatibilität mit dem Betrieb der Kläranlage 7.2.7. Rechtlicher Rahmen 7.2.8. Zusammenfassung der Verfahrensbewertung 7.3. Fazit 8. Publikationsliste Literaturverzeichnis Abkürzungsverzeichnis Symbolverzeichnis Abbildungsverzeichnis Tabellenverzeichnis A. Anhang A.1. Anhang Kapitel 3 A.1.1. Materialien zur Phosphatentfernung in der Literatur A.1.1.1. Ionenaustauscher A.1.1.2. Hybridmaterialien A.1.1.3. Adsorbentien A.1.2. Aufbau eines Differentialkreislaufreaktors A.1.3. Bestimmung des geschwindigkeitsbestimmenden Schrittes der Adsorption A.1.4. Validierung der Modellierung mit LDF-Modell A.2. Anhang Kapitel 4 A.2.1. Phosphatdurchbruchskurve mit variierender Sulfatkonzentration A.2.2. Phosphatisotherme bei variierendem pH-Wert A.2.3. Wasserhärte in Deutschland nach Wasserversorgern A.2.4. Phosphatadsorption in Abhängigkeit von den vorliegenden Kationen A.2.5. Zweifaktorielle Varianzanalyse A.3. Anhang Kapitel 5 A.3.1. Saure Konditionierung im Kreislauf A.3.2. Löslichkeitsmodellierung mit PHREEQC A.3.3. Desorbierbarkeit von Calcium und Magnesium mit Natriumnitratlösung A.3.4. Austrag von Calcium, Phosphat und Eisen bei der sauren Konditionierung von beladenem Bayoxide® E 33 HC A.3.5. Reproduzierbarkeit des Phosphatdurchbruchs bei pH-Swing-Regenerierung mit Salpetersäure A.3.6. Zusammensetzung verschiedener Calciumphosphate A.4. Anhang Kapitel 6 A.4.1. Grenzwerte für Schwermetalle in mineralischen und Recyclingphosphordüngemitteln in Europa A.4.2. Messbedingungen für die Analysen mittels LC-MS/MS A.4.3. Thermische Zersetzung von amorphem Calciumphosphat A.4.4. Phosphorentfernung in der Pilotanlage in Bramsche A.4.5. Regenerierung eines beladenen Adsorbens aus der Pilotanlage A.4.6. Untersuchte organische Spurenstoffe bei der Gewinnung von Pilot-aCP A.5. Anhang Kapitel 7 A.5.1. Kostenabschätzung für das Verfahrenskonzept zur Phosphorentfernung auf KKA A.5.2. Preisentwicklung für Phosphate von 1999 bis 2019 auf dem Weltmarkt A.5.3. Einordnung des entwickelten Verfahrenskonzeptes nach dem BAFU-Leitfaden Danksagung Erklärung
Brussels Ii Conference On 'supporting The Future Of Syria And The Region': Co-chairs Declaration ; Council of the EU PRESS EN PRESS RELEASE 219/18 25/04/2018 Brussels II Conference on 'Supporting the future of Syria and the region': co-chairs declaration 1. The Second Brussels Conference on "Supporting the Future of Syria and the Region" took place on 24-25 April 2018. It was hosted by the European Union and co-chaired by the United Nations. 2. One year after Brussels I, and following the previous three pledging conferences in Kuwait as well as the London Conference in 2016, the Conference renewed and strengthened the political, humanitarian and financial commitment of the international community to support the Syrian people, the neighbouring countries, and the communities most affected by the conflict. Brussels II brought together 86 delegations including 57 States, 10 representatives of regional organisations and International Financial Institutions (IFIs) as well as 19 UN agencies. More than 250 Non-Governmental Organisations (NGOs) were also associated throughout the preparations and the two days of the Conference. 3. The former co-chairs of Brussels I: Germany, Kuwait, Norway, Qatar and the United Kingdom (UK) brought substantial input to the preparations and the proceedings of the Conference. Jordan and Lebanon were closely associated, in a spirit of partnership and in full acknowledgement of their tremendous efforts since the beginning of the Syrian conflict. Turkey also provided important contributions, both as the country hosting the largest number of Syrian refugees and as a key regional actor. 4. Civil society and NGOs were very closely and substantially associated to Brussels II and its preparations, including through extensive consultations with NGOs implementing humanitarian and resilience programmes in the region. The first day of the Conference was devoted to a high-level dialogue with representatives from 164 NGOs, including 15 from Syria and 72 from the three main refugee-hosting countries. 5. In addition, Syrian Civil Society Organisations (CSOs) from across Syria and neighbouring countries discussed their role in the future of Syria in a closed-door side event undertaken by the EU and the Office for the Special Envoy for Syria. The CSOs' views were further presented during the ministerial plenary on 25 April. The international community, and the EU in particular, will continue to work with Syrian civil society as essential stakeholders towards reaching a peaceful solution to the conflict and in its legitimate aspirations to contribute to the country's future. 6. Syria's artistic community was also given prominence through a string of cultural events, including a Syrian art space, "Tourab", that ran for ten days in central Brussels around the dates of the Conference. These events were meant as a tribute to the remarkable individual efforts of the Syrians since the start of the conflict. 7. The Conference reaffirmed that only an inclusive, comprehensive and genuine political solution in accordance with UNSCR 2254 and the Geneva Communiqué, that meets the legitimate aspirations of the Syrian people for dignity and freedom will ensure a sustainable end to the Syrian conflict, prevent regional escalation and a return of ISIL/Da'esh, and guarantee a peaceful and prosperous future for Syria and the region. It reiterated the international community's commitment to Syria's sovereignty, independence, unity and territorial integrity, and safety and security for all citizens. Participants stressed the importance of women's engagement in the political process, including through their adequate representation within the delegations of parties to the conflict. 8. The humanitarian and resilience needs of people inside Syria and in the region remain enormous. Current UN appeals are severely underfunded. In 2018, the UN-coordinated appeal for Syria requests to cover assistance and protection needs inside Syria amounts to US$ 3.51 billion. In addition, through the Regional Refugee and Resilience Plan (3RP), an appeal of US$ 5.6 billion, inclusive of US$ 1.2 billion already committed, is required to support refugee and host community humanitarian and resilience related assistance in Turkey, Lebanon, Jordan, Iraq and Egypt. 9. The Conference acknowledged the continuing generosity of neighbouring host countries and their communities in providing refuge to millions of displaced people. Participants pledged, for both Syria and the region, $ 4.4 billion (€ 3.5 billion) for 2018, as well as multi-year pledges of $ 3.4 billion (€ 2.7 billion) for 2019-2020. In addition, some international financial institutions and donors announced around $ 21.2 billion (€17.2 billion) in loans, of which elements are on concessional terms. The Conference noted that pledges made at Brussels I in 2017 had been largely fulfilled, and in some cases exceeded. Co-chairs and main donors agreed to widen the resource base and ensure greater predictability, coherence and effectiveness of the aid. The attached fundraising annex sets out the pledges made at this Conference. Political 10. The Conference expressed its strong support for the work of the UN Special Envoy for Syria in his mandate to facilitate the political process, with a view to a lasting political settlement based on the Geneva Communiqué and the full implementation of relevant UNSC Resolutions, including UNSCR 2254 (2015). It welcomed the twelve "Living Intra-Syrian essential principles" developed as commonalities in the Geneva process, offering a perspective of a vision of a future Syria that can be shared by all. It also welcomed the parameters on the constitutional and electoral baskets and the importance of a safe, calm and neutral environment, as outlined by the UN Special Envoy for Syria in his Security Council Briefing on 19 December 2017. Participants gave their full support to the Special Envoy's efforts to facilitate, in consultation with all concerned, the implementation of the Sochi Final Statement (as circulated to the Security Council on 14 February 2018) for the establishment of a Constitutional Committee for Syria in Geneva, under UN auspices and in accordance with UNSCR 2254 (2015). 11. The Conference reiterated the importance of preventing and combating terrorism in Syria in accordance with relevant United Nations Security Council resolutions. They took note of considerable progress in military operations to combat ISIL/Da'esh since the last Brussels Conference, while underscoring the continuing need to combat terrorism in accordance with international law. Efforts to combat terrorism do not supersede other obligations under international law 12. The co-chairs expressed their strong condemnation of the use of chemical weapons by any party to the conflict and under any circumstances. Their use is abhorrent and a clear violation of international law. It is very important that any alleged use be followed by an impartial, independent and effective investigation. Ensuring accountability for the use of chemical weapons is our responsibility, not least to the victims of such attacks. Co-chairs called upon all participants to use their influence to prevent any further use of chemical weapons. Humanitarian 13. Violence and human suffering have increased in Syria, with military escalation by parties to the conflict further increasing to an alarming extent in 2018. The civilian population has continued to endure the bulk of the suffering caused by the conflict, including severe, constant and blatant violations of International Humanitarian Law (IHL) and human rights law, in particular: deliberate and indiscriminate attacks on civilians and civilian infrastructure, reported and ongoing use of chemical weapons, forced displacement, arbitrary detention, enforced disappearances, and torture, including sexual exploitation and abuse and gender-based violence. More than 12 million people have now been displaced, including more than 5.6 million refugees hosted in neighbouring countries and 6.6 million displaced inside Syria. Nearly 13.1 million people, almost half of whom are children, urgently need humanitarian assistance and protection inside the country. 14. The co-chairs, together with all participants, reiterated their appreciation for Kuwait's and Sweden's efforts in drafting UNSC Resolution 2401 (2018) and called for its immediate and full implementation, as well as all other relevant resolutions on Syria. They urged all parties to the conflict to strictly adhere to their obligations under IHL. Attacks against civilians, humanitarian workers as well as any civilian infrastructure, particularly health facilities and schools, violate the most basic human rights, may amount to war crimes under international law, and must stop without delay. They also requested that humanitarian mine action programming be accelerated as a matter of urgency. 15. The Conference reconfirmed the importance of delivering needs-based humanitarian assistance to all civilians, in line with humanitarian principles of humanity, neutrality, impartiality and independence. Participants stressed the critical link between protection and access. They called for unconditional, unimpeded and sustained humanitarian access through the most direct routes, including to the 2.3 million people still living in besieged and hard-to-reach areas across Syria through all aid modalities: cross-line, cross-border and regular programme, in line with UNSC Resolution 2393 (2017). 16. Particular concerns were noted over the escalation of fighting and dramatic humanitarian situation still faced by civilians in many parts of Syria. The Conference stressed the need to ensure that any evacuation of civilians must be safe, informed, temporary, voluntary in nature and a solution of last resort including the destination of their choice, the right to return and the choice to stay, as per IHL. All efforts should be made to ensure the unconditional medical evacuation of those in need of urgent medical treatment. Denials of medical supplies and of access to healthcare are violations of international law and should be stopped at once. The systematic removal of life-saving medical items from humanitarian convoys is unacceptable and needs to be addressed once and for all. 17. Participants agreed that present conditions are not conducive for voluntary repatriation in safety and dignity. Significant risks remain for civilians across the country as the situation remains characterised by continued fighting and displacement, with 2.6 million people displaced in 2017 alone. Conditions for returns, as defined by the UNHCR and according to international refugee law standards, are not yet fulfilled. Any organised return should be voluntary and in safety and dignity. Regional/development 18. The international community acknowledged and commended the huge efforts made by the neighbouring countries and their citizens, in particular Jordan, Lebanon and Turkey, as well as Iraq and Egypt, in hosting millions of refugees from Syria. Participants recognised the deepening vulnerability of Syrian refugees, Palestinian refugees from Syria and host communities, which should be addressed through sustained humanitarian and resilience support. 19. Participants committed to remaining fully engaged, in a spirit of partnership, in supporting neighbouring countries to address the challenges they face. Substantial progress has been made by governments, donors and the UN in implementing the commitments undertaken in London in 2016 and in Brussels in 2017, including through the EU Compacts with Jordan and Lebanon. However, more should be done to ensure the continued and effective protection of refugees against risks of forced evictions and returns and improvement of their legal residency status. 20. While the countries of the region continue to face enormous humanitarian challenges, the Conference agreed that increased focus is required to support reform and longer-term development in a sustainable manner. It remains critical to support health and education, economic development, job creation and integration into labour markets, for both host communities and refugees, especially vulnerable groups such as women and youth. The Conference underlined the essential need to reach all children and young people, who will one day have a key role in the recovery and rebuilding of the region, with quality education and skills training. It expressed support for targeted resilience programming and an increase in allocations to women and girls. Extremely vulnerable refugees and host communities will continue to require support through cash assistance and enhanced social protection mechanisms. Resettlement was recognised as an essential protection tool for refugees with heightened protection risks and its importance was highlighted, together with other legal pathways, in offering safe and dignified access to safety beyond the immediate region. 21. The Conference welcomed the Lebanese Government's Vision for Stabilisation, Growth and Employment including the Capital Investment Programme together with its commitment to establish a timetable for reforms that were presented in Paris on 6 April 2018, whose implementation and follow-up with the support of the international community is critical. The Conference also welcomed the Rome II ministerial meeting in support of Lebanon's armed and internal security forces that was held on 15 March 2018. 22. The Conference equally welcomed the fiscal and structural reforms that are being implemented by the Jordanian Government in a difficult economic environment, with a view to ensuring fiscal sustainability and improving the investment climate in line with the "Jordan 2025" vision document and with the Economic Growth Plan for 2018-22. The Conference also welcomed the UK's intention to host an international Conference with Jordan in London later this year to showcase Jordan's economic reform plans, its aspiration to build/enable a thriving private sector, and mobilise support from international investors and donors. 23. The Conference commended the Turkish Government for its generous and large-scale efforts in hosting millions of Syrian refugees and integrating them into national services, including health, education, employment and other municipal and social services. Joint frameworks have been established with the international community under programmes such as the EU Facility for Refugees in Turkey and the UN Regional Refugee and Resilience Plan 2017-2018. Addressing the protracted refugee situation will require continued co-operation along those lines. 24. Participants committed to supporting further investments to foster inclusive economic growth and social development in Lebanon and Jordan, including through concessional financing, blending of grants with loans and the use of the EU External Investment Plan in cooperation with the support of European Financial Institutions and the private sector. They commended the efforts made by host countries to open access to education, water and sanitation and health services and encouraged further progress. Investment in infrastructure and in human capital is necessary to improve the quality of services and will continue to be supported. Participants also noted the importance of vocational training for refugees and host communities, closely aligned with private sector labour needs. Protection measures, in particular the provision of legal residency, should be reinforced. 25. Inside Syria, support to inclusive and accountable service delivery and to livelihood opportunities for the affected populations, particularly women and youth, should continue while ensuring that it does not condone, or indirectly entrench, social and demographic engineering as a result of forced displacement and intentional creation of obstacles to return. Work will address needs related to safe and equal access to civil documentation, housing and property rights to ensure that the rights of Syrians are protected and that those displaced are provided the basic conditions to be able to return to their homes in a dignified, safe and voluntary way when conditions allow. It is also important to support Syrian civil society, social cohesion/dialogue and seek to promote accountability and transitional justice. Funding decisions shall be conflict-sensitive and shall in no way benefit or assist parties who have allegedly committed war crimes or crimes against humanity. The UN reiterated that its Parameters and Principles for UN assistance in Syria will guide UN assistance beyond emergency life-saving aid in Syria. Future steps 26. The EU and the UN committed to tracking the commitments made during the Conference and reporting regularly on their delivery, including through reviews at key international events during the year. 27. Donor countries present at the Conference reiterated that reconstruction and international support for its implementation will only be possible once a credible political solution, consistent with UNSCR 2254 and the Geneva Communiqué, is firmly underway. A successful reconstruction process also requires minimal conditions for stability and inclusiveness, a democratic and inclusive government, an agreed development strategy, reliable and legitimate interlocutors as well as guarantees in terms of funding accountability. None of these conditions are fulfilled in Syria. In the meantime, participants agreed to regularly review post-agreement plans, including those produced by the UN-led post-agreement planning process initiated by the 2016 London Conference on Syria. 28. Participants also called upon all parties to release all persons who are arbitrarily detained, in line with UNSC Resolutions 2254 (2015) and 2268 (2016). Access to all detention facilities should be granted to independent monitors and information provided on cases of forced disappearances. Ongoing work on the release of detainees and abductees by all parties is valuable and can help build confidence between them. Participants expressed support to the UN proposal for a Standing Secretariat under UN auspices, recently proposed to support the working group formed by the Astana guarantors. 29. Finally, participants recalled that transitional justice and accountability are required for sustainable peace and an inherent part in any meaningful process of reconciliation. War crimes and violations of international humanitarian law and human rights abuses need to be investigated. Any entities and individuals guilty of such violations, including the use of chemical weapons, must be held accountable. The co-chairs commended the role of the Commission of Inquiry and welcomed progress in the work of the International Independent and Impartial Mechanism (IIIM) and called for continuous efforts to ensure the necessary means for its functioning. They called for the situation in Syria to be referred to the ICC. Annex - Fundraising - Supporting the future of Syria and the region Annex - Situation inside Syria Annex - Jordan partnership paper Annex - Lebanon partnership paper Annex - Turkey partnership paper Press office - General Secretariat of the Council Rue de la Loi 175 - B-1048 BRUSSELS - Tel.: +32 (0)2 281 6319 press.office@consilium.europa.eu - www.consilium.europa.eu/press
This report describes trends in the beef industry in the Monsoonal North. It aims to provide the region's natural resource management (NRM) groups with an understanding of how best to support the industry, undertake the changes required to improve its environmental sustainability and economic viability, and to provide it with resilience in the face of increasing development pressures and climate change. This report charts the industry's history and development; describes its current condition and the pressures and drivers it is experiencing; and explores how these are likely to change in the near future. The region: The Monsoonal North covers 20% of Australia's land surface across the tropical savannas. It shares a monsoonal climate, extensive intact ecological systems, generally poor soils and limited development. Its river systems carry nearly half of the runoff. The region has a large Indigenous population; most land is either under Indigenous ownership or subject to Native Title; and the highest proportion of Indigenous people live in the region's north and north-west. The region also faces a number of shared issues, particularly the challenges of intensifying climatic extremes and pressure to exploit Asia's growing demand for agricultural produce, which is placing pressure on land and water resources. The industry: Cattle production is northern Australia's most important agricultural industry. Two-thirds of the Monsoonal North is currently used for extensive cattle grazing. Through most of the region, cattle are grazed at low stocking rates on native pastures, with introduced pasture species being restricted in extent. Most enterprises breed animals for the low-value live export trade or for fattening and finishing on better pastures or in feedlots. Cattle numbers in Queensland, Northern Territory and Western Australia have doubled since 1965, and fluctuated with changes in demand and climatic conditions. In 2009, the Monsoonal North held around 5.7 million head of cattle. High export demand from Asia and drought destocking has seen the region's cattle numbers fall and prices rise through 2014-15. In the longer-term, continued growth in global demand, a reduced Australian dollar and high global prices, and improved incomes are forecast for Australian beef producers. Since 2009, each of the three northern governments have released policy documents that included targets to increase the herd size by between 1 and 5%, with the greatest planned increases on Aboriginal land in the Kimberley. Between 2009 and 2014, the Northern Territory herd grew by more than the projected 5% increase. Herd size in Queensland has recently diminished because of drought, and the current government's stance on herd-building is unclear. Nevertheless, long-term growth is expected to increase the northern Australian herd by a further 80% by 2050. Recent growth in the northern cattle herd has been achieved through intensification (spreading grazing pressure using water points and fencing) and development of underutilised properties, notably on Indigenous lands. Indigenous pastoralism is growing rapidly, with developments in all parts of the sector from cattle breeding to slaughter. Markets: Most beef grown in northern Australia is sent to Asia, with Indonesia being the largest buyer of live cattle. Despite a long-established framework for assuring animal health and welfare within Australia, widely-publicised animal mistreatment in Indonesia resulted in the temporary closure of the live-export market in 2011 until animal welfare could be assured throughout the supply chain. This closure demonstrated how dependence on a single market exposed the northern beef industry to market volatility. Bilateral and multilateral trade negotiations by the federal government are now progressively broadening market access, with agreements favouring Australian beef now in place or close to finalisation with most significant beef markets. Enterprises: Cattle enterprises in the Monsoonal North have been struggling because, in real terms, cattle prices have declined, while input costs have remained stable. In addition, escalating land prices through the 1990s and 2000s encouraged many land owners to increase their mortgages to levels that became unsustainable once land prices fell. This has implications for environmental management. In comparison to pastoralists in a good financial position, those in debt have less resilience to cope with drought; are less likely to adopt practice improvements needed for improving enterprise viability and environmental conditions; and are more likely to suffer adverse health effects. Many enterprises, especially those with small herds, derive more income from off-farm work than they earn from cattle operations. While large cattle enterprises allow economies of scale, increasing cattle herd size seems less important to profitability than does improving herd performance. Performance: Except on Mitchell Grass pastures and small areas of intensively managed pastures, cattle performance in the Monsoonal North is substandard when compared to the rest of the country, and is affected by poor quality pasture quality. Breeding performance is typically poor; with low pregnancy rates; high foetal and calf death rates; and many cows are lost. However, the achievements of the top 25% of the industry indicate there is great potential to improve performance on the remaining properties. Health and well-being: Pastoral production is a stressful occupation, involving financial insecurity and isolation; and pastoralists have high rates of injury, disease, accident and suicide. Recent years have brought additional challenges associated with falling land prices, market instability and drought. In the Burdekin Dry Tropics, proposed coal mining is increasing stress levels for many pastoralists. Supply and demand: Domestic demand for beef in Australia stagnated because per capita beef consumption has fallen, but global demand is escalating with population growth and economic development. Demand for beef is expected to keep increasing until at least 2050, with greatest growth occurring in China. Australia was the world's top beef exporter until 2003. Only Brazil and India currently export more beef than Australia does. Australia's disease-free status gives it access to markets that are closed to these exporters. Australia's dominance of the live-export trade to Indonesia also helps provide a disease free buffer to its north. Australian beef producers are disadvantaged by protectionist measures employed by both beef importing countries and exporting countries. The Australian Government has been engaging in international trade agreements that will overcome some of these barriers and increase market access. Market requirements and consumer preference: A high percentage of Brahman genes in the herd makes northern cattle attractive for slaughter and feedlots in tropical countries. However, slow growth rates and long transport distances mean most beef is sold in the low end of the market. Ethical, health and environmental concerns have contributed to the decline in domestic meat consumption, and are influencing consumer preferences in global markets. These concerns are driving practice improvement throughout the Australian beef supply chain. Challenges: Industry viability is constrained by lack of infrastructure, including feedlots, intensive fattening pastures, saleyards and meatworks, inactive ports and poor quality roads, all of which combine to make freight expensive, pushing up input costs. Considerable advances have been made in alleviating these constraints by building meatworks in Darwin, Arnhem Land and the Kimberley. However, lack of competition through the supply chain may be depressing returns at the farm gate. The ports of Darwin and Townsville are operating at record capacity, but some northern ports with export facilities (Port Hedland, Weipa, Mourilyan and Mackay) have not operated for several years. Water for cattle operations and irrigated crops may be at risk if extraction for these and other activities is not sustainably allocated. While broadscale irrigated cropping is likely to be restricted to a small proportion of the region, its requirements for water resources and fertile soil may deprive the pastoral industry of some of its most productive pasture land. Extraction for mining and irrigated agriculture is of particular concern. This has become a contentious issue with several coal projects in Queensland's Galilee Basin. Mining also has the potential to disrupt pastoral operations by removing land from production for both mineral extraction and infrastructure. Again, this is a significant issue in Queensland, where several landholders will be affected by the rail corridor servicing mines in the Galilee Basin. The disruption caused by mining poses a risk, not only to the financial viability of pastoral enterprises, but also to the health and welfare of pastoralists and their families. If well managed, however, mining and agricultural development can also have co-benefits, improving regional economies and providing employment and infrastructure. Weeds, fire, pest animals, disease and cattle theft all impose financial burdens on northern pastoral operations. Production losses caused by weeds have been estimated at costing the industry around $1,000 million/year; pest animals: ca $36 million/year; disease and parasites: ca $390 million; and cattle theft between $1.5 and $2 million a year in Queensland alone. No industry-wide estimates are available for impacts of fire, cyclones or other natural disasters. Conversely, pastoral managers perform important roles in control of weeds, fire, pest animals and diseases that would not be undertaken if no one was living on the lands they manage. Climatic and seasonal conditions are also serious constraints, particularly in inland Queensland, where periods of drought of two or more years are not uncommon. Conversely, extended periods of above average rainfall may encourage pastoralists to stock land beyond its long-term carrying capacity, and develop unrealistic impressions of what average conditions are. This could be an issue in the Kimberley if the elevated rainfall of the last few decades is not sustained. Climate change is already being felt in the region. Temperature have risen by up to 1.0°C since 1910, with further increases of up to 5°C expected by the end of the century. Droughts, cyclones, wildfires and flooding rains are likely to intensify over the next few decades, and continue to intensify until at least the end of the century. Carbon dioxide enrichment may increase forage production, but reduce its quality and stimulate woody thickening, as woody plants are favoured over tropical grasses. In most climate change scenarios, whether rainfall remains roughly the same or decreases, pasture growth and safe stocking rates in the Monsoonal North are expected to decrease, with the worst scenarios predicting decreases in pasture growth and safe stocking rates of between 50% and 60%. Climate change will also have adverse impacts on each stage of the supply chain, with effects ranging from increasingly uncomfortable work conditions to increased frequency of flood and cyclone damage to infrastructure. Policy environment: Many organisations have an influence on the direction of the pastoral industry. Individually, or as part of cross jurisdictional alliances, national, state and territory governments promote industry sustainability and herd-building. The preferred approach is to improve trade relations; simplify regulation; invest in roads; and provide a conducive business environment to attract infrastructure investment. The Developing Northern Australian White Paper and the Agricultural Competitiveness White Paper further these objectives. Under Australian national legislation, the Red Meat Advisory Council was established to represent the interests of beef and other meat producers, and is reported to by various state farming organisations that work closely with the industry as advocates and information and extension providers. Research and marketing is largely driven by Meat and Livestock Australia (informed on northern issues by the North Australia Beef Research Council) and extension is delivered by state agencies, state farming organisations and NRM groups. The emphasis of both research and extension is on practice improvement, rather than herd building. The Australian Government funded Indigenous Land Corporation is also playing a pivotal role in the northern grazing industry by assisting Indigenous people acquire, develop and manage pastoral properties. Finally, the policies and assessments made by financial institutions can both determine the level of debt that a pastoral enterprise can acquire and the cost of repayment, and influence whether developments seeking external funding are seen as viable. The Australian Government is committed to climate change action by virtue of signing international agreements. Its commitments to reduce emissions will help moderate the long-term impacts of climate change. Both the Western Australian and Northern Territory Governments have also made climate change commitments and the Queensland Government is currently revitalising its climate change agenda. Regulatory environment: Legislation and regulation govern much activity on pastoral properties, most of which are pastoral leases coexisting with Native Title. This type of land tenure allows pastoralists to undertake most activities that can be justified as core business to a pastoral operation, including pastoral-related activities that reduce carbon footprints. Diversification into other activities requires the consent of Native Title holders, which is usually negotiated through Indigenous Land Use and Access Agreements. Pastoralists have the right to water stock and clear vegetation for pastoral uses, but conditions vary between jurisdictions and water use for agricultural development requires a permit. There is a lack of clarity about whether permits can be granted for non-pastoral uses (including diversification into broadacre cropping) in Western Australia and Queensland. Pastoral leases also come with a range of legislated responsibilities. Leaseholders in each jurisdiction are to manage weeds, pest animals and diseases and to report notifiable cattle diseases to the relevant authority. They must use National Livestock Identification Scheme tags to ensure their cattle can be traced through the supply chain, and adhere to animal health and welfare standards. In addition, as employers, pastoral operators must follow conditions laid down by Fairwork Australia. Graziers in the Burdekin catchment are required to manage their properties to minimise reef pollution. The rights of miners to access land and water override those of pastoral leaseholders. While legislation facilitating exploitation of mineral and gas and fuel resources purports to safeguard other interests (notably environmental matters and water access), few mining proposals have been rejected because of environmental or pastoral concerns. Practice improvement: Much effort has been invested in identifying the best practices to improve the profitability and environmental sustainability of the northern beef industry. Key areas of knowledge advancement include: • Improving land condition • Improving diet through exotic pastures and supplementary feeding, especially at finishing • Improving reproductive performance by culling non-productive animals, vaccinating against reproductive diseases and improving diet quality • Increasing liveweight gain through early weaning and improving diet quality • Spreading grazing pressure by increasing fencing and water points. Improvements to herd management are largely compatible with practice change required for reducing adverse impacts on biodiversity, carbon footprints and Great Barrier Reef water quality. Improved animal performance increases animal growth rates (meaning fewer animals are required to produce the same volume of meat), and therefore also reduces the methane emissions generated. Good herd performance in rangelands is also dependent on moderate stocking rates to maximise forage quality, especially by improving the cover of productive perennial grasses. Improved ground cover also reduces soil loss (when cover is at least 50%) and gully formation (when at least 75%). Resilience to climate change will be built by undertaking the practice improvements identified to improve pastoral productivity and land condition. Of particular importance is the ability to adjust stocking rates in relation to seasonal conditions. At the industry level, decision support, including improved access to climatic information, is required to assist pastoralists make the best decisions for their circumstances. Diversification: Another approach to increasing enterprise resilience is diversification. Options being canvased include small-scale irrigation of pasture crops for finishing cattle on the property, grain and oil seed crops, biodiversity conservation and carbon abatement. Conservation efforts on some properties attracted subsidies in return for entering into conservation agreements. Biodiversity offsets may widen opportunities for on-property conservation, particularly in Queensland, where a formalised offset scheme is being developed. A small number of pastoral properties in the region are also receiving funding for fire management to reduce carbon emissions. A range of other emission reduction opportunities are at various stages of development, including reducing emissions from pastoral operations through improved herd management and adjusting cattle diets and storing carbon in soil or vegetation. Natural resource management implications: As practices to improve performance are adopted and/or diversification options are pursued, careful management will be required to avoid potential adverse environmental impacts. Best-bet options for improving environmental outcomes along with pastoral productivity include: • Avoiding the use of "transformer" grasses (with high biomass and fuel loads), or at least ensuring they do not escape from improved pasture plantings • Protecting areas of high biodiversity values when increasing extent and/or intensity of grazing, in particular protecting biodiversity values on riparian corridors when planning irrigated cropping projects • Ensuring wet season supplementary feeding does not weaken native perennial grasses • Ensuring early dry season burning does not lead to vegetation thickening and biodiversity decline. The NRM implications of the current trajectory of the pastoral industry are mixed. Herd building will put more pressure on the natural environment. However, performance improvement has many benefits by reducing the number of hooves and mouths required to produce a kilogram of meat. If well managed, mosaic agriculture can contribute to herd performance while taking pressure off pastures and the natural environment during the wet season, but managed poorly could result in further degradation of alluvial environments and over stocking of adjacent areas. The environmental footprint of diversification into agriculture would similarly need to be managed carefully. However, increasing income from various forms of ecosystem service delivery, particularly on lands that are marginal for grazing, would be a boon to both pastoral enterprises and the environment. Central to all this change are the pastoralists themselves. And with all that is required from them and all the stresses and strains they already have to bear, many will be in no position to take up improved practices, let alone participate in conservation activities. Pathways out of debt must be found before resilience in the face of change can be achieved, and pastoralists must be supported in the adoption of new practices, rather than have it mandated.
Implementación del proyecto SNAP por el PNUD UruguayDesde el período de Post-Guerra, a partir de la creación de la Organización de Naciones Unidas en 1945, ha ido creciendo la trascendencia de la cooperación internacional "en la solución de problemas internacionales de carácter económico, social, cultural o humanitario, y en el desarrollo y estímulo del respeto a los derechos humanos y a las libertades fundamentales de todos" (Carta de las Naciones Unidas; 1945; artículo 1). Así es que la responsabilidad de los organismos que se fueron creando con dicho propósito ha ido aumentando, debido a la gran cantidad de fondos que disponen y la influencia que tienen sobre la vida de muchas otras entidades y personas.Hoy en día, las organizaciones internacionales de cooperación presentan mecanismos de accountability, es decir, de transparencia y rendición de cuentas en sus políticas y prácticas, frente a distintos stakeholders. Éstos son los "individuos o grupos que pueden afectar o son afectados por las políticas o/y las acciones de una organización" (Blagescu y otros; 2005; 20), también denominados "contrapartes" o "actores" de la organización. Los stakeholders de un organismo tienen capacidades desiguales en cuanto a recursos financieros y know-hows, distintas posibilidades de acceso a información confiable, así como necesidades y expectativas dispares. Estas diferencias son la traducción de niveles desparejos de influencia, lo que conlleva a la existencia de procesos de rendición de cuentas variables en la práctica de la organización en cuestión.La comunidad internacional ha desarrollado la idea de que la existencia de mayoraccountability es positivo para las instituciones y la sociedad civil. Sin embargo, es recurrente la publicación de críticas realizadas a organismos de cooperación acerca de falta de transparencia durante la implementación de proyectos o en misiones de ayuda, particularmente en países subdesarrollados. A su vez, gran parte de los trabajos académicos existentes sobre accountability en las entidades internacionales se centran principalmente en el estudio de la cantidad o calidad de mecanismos de rendición de cuentas, así como de su efectividad, poniéndola muchas veces en tela de juicio. En cambio, el trabajo aquí presentado busca entender cómo se efectúan los procesos de accountability de una organización de cooperación dependiendo específicamente de quién sea el destinatario de ésta. Así es que se introdujo una nueva variable en la investigación sobre accountability de los organismos internacionales: sus stakeholders.Los hallazgos de la investigación se obtuvieron a partir del estudio de un caso único de agencia de cooperación, el Programa de Naciones Unidas para el Desarrollo (PNUD) en Uruguay (1). Esta metodología apuntó a captar las circunstancias y condiciones de una situación cotidiana, asumiéndose que los aprendizajes obtenidos del estudio de caso dan pautas acerca de la realidad y las situaciones existentes en las organizaciones internacionales para el desarrollo en general, que pueden presentar diferentes dinámicas y modalidades de funcionamiento entre ellas pero enfrentarse a problemáticas similares. El PNUD tiene una larga trayectoria de trabajo en el país y, por ende, presenta mecanismos de accountability bien definidos. Se distingue como órgano de cooperación para el desarrollo en que gran parte de sus programas son de interés y ejecución nacional, dándole así al Gobierno una participación sustancial en muchos aspectos.La investigación se acotó a uno de los proyectos llevados a cabo por el PNUD en el país en el área de Medio Ambiente desde el año 2005, el de "Fortalecimiento del Proceso de Implementación del Sistema Nacional de Áreas Protegidas (SNAP) de Uruguay", proyecto complejo que cuenta con una cantidad importante de contrapartes, a quienes se les debe rendir cuentas. Comprende varios donantes y lo ejecuta una Unidad especializada dentro del MVOTMA, en conjunto con el PNUD como Agencia de Implementación, por lo que la organización de cooperación y el Ministerio se encuentran en constante interacción.El marco teórico utilizado para el estudio fue el institucionalismo neoliberal de Robert O. Keohane, quién hace una distinción entre las contrapartes que tiene un organismo internacional. Califica de stakeholders "internos" a la organización, a los grupos que son parte de ella o a los donantes formalmente vinculados a ella. En este caso, las principales contrapartes internas de la Oficina del PNUD en Uruguay son la Sede central del PNUD, que se encuentra en Nueva York, y el GEF (Fondo Mundial para el Medio Ambiente), el mayor donante para el proyecto. Por otro lado, los stakeholders "externos" son los grupos o individuos que se ven afectados por las decisiones y actividades de la organización pero no son parte de la misma. En este proyecto, los más destacados son dos entes gubernamentales: la Oficina de Planeamiento y Presupuesto (OPP), contraparte principal en todo lo relevante a la cooperación internacional en nuestro país, y el Ministerio de Vivienda, Ordenamiento Territorial y Medio Ambiente (el MVOTMA), Organismo Nacional de Ejecución del proyecto. Cabe aclarar que la sociedad civil no fue considerada como actor externo al PNUD porque la forma de cooperar de la organización en este proyecto es apoyar al Gobierno a ejecutarlo. Entonces, canaliza los distintos fondos, participa en su administración y brinda mucho apoyo con su know-how, pero la ejecutora del proyecto es la Unidad creada por el Gobierno en el MVOTMA. Por ende, la sociedad civil sería más bien un stakeholder del Gobierno.En su desarrollo teórico, Keohane explica que los procesos de accountability están estrechamente vinculados a las relaciones de poder. El autor define el poder como"la habilidad que tiene un actor de lograr que otro haga algo que en otras circunstancias no haría" (Keohane; 1988;11) y, como una institución no brindaaccountability por sí misma ya que hacerlo restringiría su autonomía, asegura que algunos stakeholders reciben mayor accountability que otros según el poder que tengan dentro de la organización. Keohane sostiene que son las contrapartes internas quienes tienen mayor poder y, por lo tanto, siempre recibirán mayoraccountability por parte del organismo internacional que las externas.Las hipótesis que guiaron el estudio están derivadas de dicho marco teórico. Por lo tanto, la investigación buscó comprobar o refutar el supuesto de que losstakeholders internos a la Oficina del PNUD en Uruguay reciben mayoraccountability que las contrapartes externas debido a que tienen mayor poder sobre la agencia de cooperación. Se utilizaron determinados criterios para evaluar los mecanismos de accountability brindada a los stakeholders por el organismo, que incluyen la transparencia de la agencia, la participación de las contrapartes, las instancias de evaluación y los mecanismos de quejas y respuestas que presenta el PNUD hacia cada actor.La exploración de los procesos de accountability presentados por la Oficina del PNUD a sus principales contrapartes a lo largo del proyecto se centró en la revisión de documentos y la realización de entrevistas a funcionarios de la organización y a representantes de los stakeholders involucrados. La agencia destina diversos mecanismos de accountability a los distintos stakeholders en la implementación del proyecto, como por ejemplo informes, instancias de participación o consulta para las distintas contrapartes, acceso a la información.Para contrastar las expectativas teóricas planteadas con la realidad empírica del caso de estudio, fue indispensable realizar una comparación entre lo pautado formalmente y lo que ocurre en la práctica. Cada actor involucrado tiene un rol diferente en el proyecto, pero el foco de análisis del trabajo fue en qué forma y en qué medida éstos reciben accountability por parte del PNUD.El GEF y la Sede de la organización, contrapartes internas, son efectivamente las que reciben mayor accountability, agregando que las instancias de rendición de cuentas destinadas a ellas son más formales que las presentadas a los dos órganos gubernamentales. Tanto la Sede central como el GEF tienen manuales de monitoreo y seguimiento detallados para controlar las actividades de la Oficina en Uruguay, le exigen que presente informes con requisitos muy específicos y plazos que cumplir y cuentan con órganos o personal técnico para evaluar el cumplimiento de estas instancias. La Oficina del PNUD en Uruguay también ingresa y actualiza constantemente todos los datos relevantes de sus proyectos en un sistema informático, llamado "Atlas", al que tienen acceso todas las demás oficinas de la organización, incluyendo la Oficina Regional para América Latina (intermediario entre las Oficinas Nacionales de la región y la Sede) y la misma Sede central. Estas instancias de accountability que reciben las contrapartes externas, no solo se ven plasmadas en documentos normativos, sino que están institucionalizadas en el funcionamiento diario de la organización.En cambio, los stakeholders externos a la organización, la OPP y el MVOTMA, no tienen realmente institucionalizados mecanismos de carácter formal destinados a controlar la actuación del PNUD. Por ejemplo, no presentan manuales de procedimiento para el monitoreo ni personal técnico que se dedique exclusivamente a estudiar las evaluaciones que se le puedan realizar a la agencia de cooperación. Sí existen mecanismos que, a grandes rasgos, le otorgan a ambos entes gubernamentales las facultades para obtener accountabilty. Por ejemplo, elAcuerdo entre la República y el Programa de las Naciones Unidas para el Desarrollo es el marco legal que rige la relación entre la organización y el Gobierno, pero plasma ideas muy abstractas sin especificar de qué forma se llevarán a cabo. Por otra parte, las instancias de rendición de cuentas que se les brinda a las contrapartes internas no se basan en lo que éstas exijan sino que son iniciativa de la propia organización o fueron demandadas por otros actores.Al contrastar estas observaciones con las hipótesis iniciales, lo primero que pudo notarse fue que en este caso de estudio los stakeholders internos efectivamente reciben mayor accountability. Sin embargo, la investigación no permitió verificar que esto se explicase en base al poder de las contrapartes sobre la organización. Todos los actores, tanto la Sede y el principal donante para el proyecto (el GEF), como los dos órganos de Gobierno involucrados, tienen poder sobre la actividad del PNUD Uruguay en este proyecto y tienen la potestad de que ésta les rinda cuentas. Esta oficina representa a la Sede y depende de ella, por lo que debe seguir todos sus reglamentos e indicaciones; a la vez, el GEF es un fondo que financia muchos proyectos en los que coopera el PNUD en el mundo y es el mayor donante para el Proyecto SNAP. Por otra parte, como la agencia cobra por sus actividades de cooperación para sustentarse, es de su conveniencia participar en la mayor cantidad de proyectos posibles, para los que la debe elegir el Gobierno como Agencia de Implementación. El MVOTMA es el Órgano de Ejecución del proyecto, tomando las decisiones y siendo otro importante financiador de éste, y la OPP es la coordinadora de la cooperación internacional en el país. Entonces, si bien losstakeholders externos se ven evidentemente beneficiados por el apoyo de la agencia en la implementación del proyecto SNAP, éstos también tienen poder sobre la Oficina de País.A pesar de no encontrarse fundamentos que permitieran afirmar que las contrapartes que recibían mayor rendición de cuentas eran las más poderosas, la investigación permitió sugerir otra explicación para la diferencia de accountabilitydestinada a unos u otros stakeholders, más bien basada en la exigencia que tiene cada uno para con el organismo. Se pudo observar que la Sede y el GEF pautan y demandan mayores instancias de rendición de cuentas al PNUD en la implementación del proyecto de las que le piden la OPP y el MVOTMA. Un hallazgo a destacar es que el Gobierno, la OPP y el MOVTMA, no parecen tener tan interiorizado el demandar accountability como sí lo tienen los stakeholdersinternos a la organización. La agencia no cuenta con mecanismos deaccountability claros destinados hacia el Gobierno, pero éste tampoco los pide.Entonces, el estudio llevó a observar que la falta de exigencia de instancias de monitoreo y evaluación del PNUD por ambos stakeholders externos, se debe en parte a una carencia de capacidad institucional para hacerlo. Incluso, el actual Oficial del PNUD que fue entrevistado hizo referencia a esta falta de capacidad institucional de los entes gubernamentales, declarando que:"(…) preocupa como el Estado no genera las capacidades para exigir esa accountability. Ahí hay un problema también…porque un país como Uruguay debería tener niveles superiores de desarrollo institucional. Es decir, aplicar exigencias mayores a los organismos de los que tienen."Lo relevante de este hallazgo es que el Gobierno no demanda mayoraccountability. Esto no sucede porque no cuente con la potestad de hacerlo, sino debido a una falta de capacidad institucional. Luego, se desprende que la variable de poder no es la más relevante para entender la dinámica entre los stakeholders y el PNUD en este caso.A su vez, otro dato que aporta cierta explicación a la poca exigencia por parte del Gobierno es el alto grado de confianza que pudo observarse que todos losstakeholders tienen en el PNUD. Efectivamente, debido al estrecho vínculo que han generado durante todos los años de trabajo en conjunto, el Gobierno y el PNUD han forjado una confianza mutua. También, el GEF confía en que éste, como agencia de implementación de los proyectos, realizará los procedimientos estipulados de la forma correcta. Sin embargo, a pesar de la confianza que ambos grupos de contrapartes tienen en la forma de funcionar de la agencia, las agencias internas siguen controlando las actividades de la organización y esperando que les sea accountable, mientras que las externas – que están además presentes diariamente en todos los ámbitos del proyecto – no ven la utilidad de un mayor control.La investigación no permite definir todas las variables que influyen en la cantidad y en la forma en que se brinda accountability a ambos grupos de stakeholders, pero introduce un nuevo parámetro de análisis. Éste consiste en la cantidad deaccountability que cada una de las contrapartes exige a la agencia de cooperación. El Gobierno cuenta con ámbitos que le permitirían demandar accountability al PNUD, pero no los pone realmente en práctica. Entonces, la organización internacional, "acostumbrada" a que sean los actores internos los que exijan mayoraccountability, basa el sistema de rendición de cuentas y transparencia que genera en lo que éstos solicitan. Es decir que la carencia de exigencia por parte de losstakeholders externos lleva al PNUD a desarrollar sus procesos de accountabilityen un "lenguaje" destinado a ser comprendido casi solo por los internos.Finalmente, puede concluirse que la forma en que la agencia internacional brindaaccountability a sus stakeholders no depende únicamente del poder que éstos tengan sobre ella, sino de que ejerzan dicho poder para exigirle que les seaaccountable. El ejercicio efectivo de poder de un stakeholder está ligado a que éste presente las capacidades institucionales para llevarlo a cabo. En este aspecto es que se hacen notar las mencionadas deficiencias institucionales del gobierno uruguayo para generar mayores instancias de exigencia de accountability. Entonces, podemos suponer que los países con características similares a Uruguay, con estabilidad democrática y socio-económica, se encuentran con este tipo de desafíos en lo que refiere a los mecanismos de accountability que demandan a los organismos internacionales en su cooperación.No se pretende afirmar que la variable que podemos calificar como "exigencia deaccountability" es la de mayor trascendencia para el análisis de los procesos deaccountability, ya que la investigación realizada expuso la gran complejidad existente en las relaciones entre las contrapartes y el organismo internacional. Sí es válido destacar la importancia de que se amplíe el espectro de parámetros a considerar en el análisis de los procesos de accountability en la implementación de proyectos de cooperación internacional, para así ampliar en un futuro el alcance de la teoría de Keohane sobre los procesos de accountability y los stakeholders.(1)La página principal en español es http://www.beta.undp.org/undp/en/home.html. La página sobre Uruguay es http://www.undp.org.uy/. *Estudiantes de la Licenciatura en Estudios InternacionalesDepto de Estudios InternacionalesFACS – Universidad ORT UruguayREFERENCIAS BIBLIOGRÁFICASAcuerdo entre el Gobierno de la República Oriental del Uruguay y el Programa de las Naciones Unidas para el Desarrollo 1985 y ratificado por la Ley Nacional Nº 15.957. 1988.BLAGESCU, Mónica; DE LAS CASAS, Lucy; LLOYD, Robert. Pathways to Accountability. The GAP Framework. En: One World Trust [online]. 2005. Disponible en internet: KEOHANE, Robert O.; NYE, Joseph S. 1988. Poder e interdependencia. Serie: La política mundial en transición. Buenos Aires: Grupo Editor Latinoamericano (GEL).KEOHANE, Robert O.; RUTH, Grant. Accountability and Abuse of Power in World Politics. En: Princeton University. [online]. 2005. Disponible en Internet: MO, Macarena; PERRONE, Sofía; TECHERA, Maia. 2011 Monografía: Los procesos de accountability en los organismos internacionales de cooperación. Universidad ORT UruguayUNITED NATIONS. 1945. Carta de las Naciones Unidas. [online]. Disponible en Internet:
Bodenerosion durch Wasser ist ein ubiquitäres Problem, dass sowohl die landwirtschaftliche Produktivität vermindert, Bodenfunktionen einschränkt und auch in anderen Umweltkompartimenten schädliche Auswirkungen haben kann. Oberflächengewässer sind durch die mit Bodenerosion einhergehende Belastung durch Sediment, sedimentgebundenen und gelösten Nährstoffen sowie anderen Schadstoffen besonders betroffen. Das Wissen über Erosionsprozesse und Sedimentfrachten hat daher große Bedeutung für den Schutz der Güter Boden und Wasser und darüber hinaus eine ökonomische Bedeutung. Generell kann innerhalb eines Hanges oder Einzugsgebietes von einer Zone der Erosion, des Transports und der Sedimentation ausgegangen werden. Jedoch führen Abflussbildungsprozesse und rauhigkeits- bzw. topographiebeeinflusste Abflusskonzentration zu einer individuellen Differenzierung. Räumliche und zeitliche Prozessdiskontinuitäten oder Konnektivitäten und Schwellenwerte modifizieren die Erosions- und Sedimentaustragssituation in einem Einzugsgebiet darüber hinaus. Die Landschaftstrukturelemente Relief und Boden kontrollieren demnach über die Bodenfeuchtedifferenzierung im entscheidenden Maße die Abflussbildung und Sedimentfracht in einem Einzugsgebiet. Obwohl in den gemäßigten und kühlen Klimaregionen ein großer Teil der Abflussbildung im Winter stattfindet und von Bodenfrost sowie Schneeschmelzen geprägt sein kann, ist über die Prozesse und die Größe der Sediment- und Nährstoffausträge bei solchen winterlichen Randbedingungen nur wenig bekannt. Systematische Untersuchungen existieren vor allem für Norwegen und Russland. Dieses Defizit spiegelt sich auch in den vorhandenen Modellansätzen zur Abbildung der Bodenerosion und der Abschätzung von Sedimentausträgen aus Einzugsgebieten wider. Zum einen werden in der Regel weder Schneedeckenaufbau bzw. -schmelze noch die Veränderungen des Bodenwasserflusses bei Bodenfrost berücksichtigt. Zum anderen werden die Erosivität des Schneeschmelzabflusses und die Beeinflussungen der Bodenerodibilität, z.B. durch Frost-Tau Zyklen, nicht hinreichend wiedergegeben. Ziel der vorliegenden Arbeit ist es daher, auf der Analyse von Daten aus einem deutschen und einem russischen Untersuchungseinzugsgebiet aufbauend, die wichtigsten Prozesse und Größen der Abflussbildung und Stoffausträge bei winterlichen Rahmenbedingungen zu charakterisieren und in einem Modellsystem umzusetzen. Die weitergehende Anwendung dieses Modellsystems dient der Interpretation räumlicher Heterogenitäten und zeitlicher Variabilitäten sowie der Auswirkungen von klimatischen- und Landnutzungsänderungen auf den Sedimentaustrag der beiden Untersuchungseinzugsgebiete. Das 1.44 km² große Einzugsgebiet Schäfertal liegt im östlichen Unterharz. Über den Grauwacken und Tonschiefern haben sich aus einem periglazialen Decklagenkomplex Braun- und Parabraunerden entwickelt, die ackerbaulich mit einer Wintergetreide-Raps Fruchtfolge genutzt werden. In der Tiefenlinie dominieren hydromorph überprägte Böden mit Wiesennutzung. Das Klima weist bei einer Jahresmitteltemperatur von 6.8°C und 680 mm Jahresniederschlagssumme eine geringe kontinentale Überprägung auf. Neben langjährigen umfangreichen hydro-meteorologischen Messungen finden seit mehreren Jahren Untersuchungen zum Sediment- und Nährstoffautrag statt. Eine regelmäßige zweiwöchentliche Beprobung des Abflusses am Gebietsauslass wird durch eine automatisierte Hochwasserprobenahme vor allem bei Schneeschmelzen ergänzt. Neben der Sedimentkonzentration werden unter anderem Phosphor und gelöster organischer Kohlenstoff nach Standardmethoden bestimmt. Auch im russischen Zielgebiet Lubazhinkha liegt das Hauptaugenmerk auf der Charakterisierung der Abflussbildung und der Stoffausträge bei den jährlich auftretenden Schneeschmelzen. Das Einzugsgebiet liegt ungefähr 100 km südlich von Moskau im Übergangsbereich der südlichen Taiga zur Waldsteppe. Die insgesamt 18.8 km² werden zur Hälfte landwirtschaftlich und zu einem Drittel forstwirtschaftlich genutzt. Die aktuelle räumliche Differenzierung der Nutzung in diesem Gebiet wird durch die reliefbedingte Kappung und hydromorphe Überprägung der vorherrschenden grauen Waldböden bestimmt. Das Klima und die Hydrologie sind durch Schneedeckenaufbau und –schmelze, bei einer Jahresdurchschnittstemperatur von 4.4°C und einer Jahresniederschlagsmenge von 560 mm, geprägt. Zur Erfassung des Stoffaustrags werden Hochwasserprobenahmen am Gebietsauslass sowie an den beiden wichtigsten Zuflüssen genommen und neben Sediment- und Nährstoffkonzentrationen weitere physikalische und chemische Parameter bestimmt. Die Auswertung der Daten des Schäfertals zeigen für den Untersuchungszeitraum eine deutliche Dominanz der Hochwasserereignisse, die durch Schneeschmelzen hervorgerufen werden. Einzugsgebietsbedingungen mit gefrorenem Boden führen zu einer Modifizierung der Abflussentwicklung vor allem im ansteigenden Teil des gemessenen Hydrographen durch Auftreten von schnellen oberflächen- oder oberflächennahen Abflüssen. Der Spitzenabfluss bei den acht zur Interpretation herangezogenen Hochwasserereignissen variiert zwischen 30 und 270 l s-1, bei Abflussmengen von 1-50 mm. Die am Gebietsauslass ermittelten maximalen Sedimentkonzentrationen liegen für die beiden Ereignisse ohne gefrorenen Boden bei unter 650 mg l-1 und damit deutlich unter den bis zu 6000 mg l-1 bei teilweise oder ganz gefrorenen Böden im Schäfertal. Lediglich bei einem Ereignis mit Niederschlag und ungefrorenem Boden treten hohe Sedimentkonzentrationen auf, die auf Gerinnepflegemaßnahmen und dadurch leichte Mobilisierbarkeit von Material zurückzuführen sind. Dementsprechend schwanken die Sedimentfrachten der Einzelereignisse und erreichen bis zu 17 t. Die wichtigste Steuergröße ist dabei die Ausbildung erosiven Abflusses auf den Hängen durch eine Verminderung der hydraulischen Leitfähigkeit bei gefrorenen Böden. Der Vergleich der Sedimentkonzentrationen der Hochwasserereignisse mit der zweiwöchentlichen Grundbeprobung verdeutlicht, ebenso wie Hysteresekurven der Einzelereignisse, die unterschiedlichen Dynamiken der Austragssituationen. Während die durch Bodenfrost geprägten Ereignisse ein gegen den Uhrzeigersinn verlaufendes Abfluss-Sedimentkonzentrationsverhältnis aufweisen, das auf eine Sedimentquelle auf den Hängen hinweist, sind die Hysteresekurven bei nicht gefrorenen Böden im Uhrzeigersinn orientiert. Eine Sedimentherkunft in Gerinnenähe oder den Gerinneböschungen selbst ist daher wahrscheinlich. Diese Annahmen werden auch durch eine differenzierte Phosphoranreicherungsrate im ausgetragenen Sediment bestätigt. Darüber hinaus kann teilweise eine ereignisinterne Dynamik beobachtet werden, die auf zeitliche Variabilität in der Abflussbildung und damit zusammenhängend, eine räumliche Heterogenität der Sedimentquellen belegt. Während im Untersuchungsgebiet Schäfertal ein mehrmaliges Auftreten von Schneeschmelzen innerhalb eines Winters möglich ist, kommt es im russischen Einzugsgebiet zu einem regelmäßigen Schneedeckenaufbau über den Winter hinweg und einer Schneeschmelze in der Regel im März oder in der ersten Aprilhälfte. Die Auswertung mehrjähriger Datenreihen belegt die Bedeutung der Schneeschmelze für die Abflussbildung und den Sedimentaustrag aus dem Untersuchungsgebiet Lubazhinkha. Für die drei zur Interpretation herangezogenen Schneeschmelzen liegt die Sedimentfracht zwischen 50 und 630 t bei deutlichen Unterschieden in den hydrologischen Rahmenbedingungen. Die ereignisbezogene Sedimentfracht von mindestens 0.3 t ha-1 liegt zwar über der für das Schäfertal ermittelten, befindet sich aber im Bereich der Werte, die in anderen Studien bei vergleichbaren Böden und Nutzungsformen bestimmt wurden. Eine detaillierte Analyse der Messwerte der Schneeschmelze im Jahr 2003 belegt eine Dynamik innerhalb dieses Einzelereignisses. Bei Sedimentkonzentrationen im Abfluss am Gebietsauslass von 6 bis 540 mg l-1 kommt es zu einer Sedimentfracht von ungefähr 190 t. Während die maximalen Konzentrationen von Sediment und Phosphor mit der Spitze des Abflusses einhergehen, liegt für DOC eine Verzögerung vor, die durch eine langsamere Schneeschmelze und Mobilisierung von DOC aus dem humusreichen Oberboden der Waldflächen ausgelöst wird. Eine Differenzierung der Abflusskomponenten ermöglicht eine weitergehende Interpretation der ereignisinternen Dynamik der Stoffquellen und Eintragspfade. Bei geringen Abflussmengen (< 2,5 mm d-1) findet ein Stoffeintrag überwiegend in gelöster Form über die Bodenwasserpassage und langsame Abflusskomponenten in den Vorfluter statt. Bei höheren Abflussmengen dominieren schnelle Abflusskomponenten bzw. Oberflächenabfluss, der zeitlich dynamisch unterschiedliche Stoffquellen mobilisiert. Neben diesen ereignisinternen treten interanuelle Variabilitäten auf, die durch witterungsbedingte Faktoren bestimmt werden. Wie im Schäfertal spielt auch im Lubazhinkhaeinzugsgebiet die Ausbildung von Bodenfrost und damit verbundene Veränderung der Infiltrationseigenschaften der Böden eine große Rolle. Das Schneewasseräquivalent, die Schneeschmelzdynamik und Bodenfrosteigenschaften, z.B. Eindringtiefe, sind die wichtigsten Steuergrößen. Die Variabilität dieser Randbedingungen führt zu einer hohen interannuellen Differenzierung der Abflussbildung und der Sedimentausträge. Für die Schneeschmelze 2004 kann so bei überdurchschnittlich hohen Wintertemperaturen und nur teilweise gefrorenen Böden sowie geringem Schneewasseräquivalent eine geringe Sedimentfracht ermittelt werden. Darüber hinaus verdeutlichen die Hysteresekurven der Sedimentkonzentrationen Unterschiede in der Sedimentquelle für die Einzeljahre, die von den oben genannten Rahmenbedingungen abhängen. Auf der Basis des Monitoring lassen sich für beide Einzugsgebiete die wichtigen abflussbildenden Prozesse charakterisieren und Einflussgrößen erfassen. Dem Bodenfrost und der Schneeschmelzdynamik kommen dabei übergeordnete Bedeutung zu. In beiden Gebieten werden bei winterlichen Rahmenbedingungen erhebliche Mengen an Sediment und Nährstoffen ausgetragen. Die Interpretation physikalischer bzw. chemischer Parameter des Abflusses ermöglicht darüber hinaus auch Aussagen über die zeitliche Variabilität und räumliche Heterogenität der Sedimentherkunftsräume. Aus den Erkenntnissen der Einzugsgebietsbeobachtung ergeben sich für einen Modellansatz verschiedenen Anforderungen, die vor allem die räumlich differenzierte Darstellung des Einflusses von Bodenfrost auf den Bodenwasserhaushalt sowie die Bodenerosion durch oberflächlich abfließendes Schneeschmelzwasser betreffen. Die Grundlage für das Modellsystem "IWAN" (Integrated Winter erosion And Nutrient load model) stellt das hydrologische Modell WASIM ETH Ver. 2 und das Stoffhaushaltsmodell AGNPS 5.0 dar. Die Verknüpfung dieser beiden auf Rasterzellen aufbauenden Modelle ermöglicht die Nutzung von kontinuierlichen, räumlich differenzierten Informationen zum Oberflächenabfluss für die Abschätzung der Bodenerosion. Durch diese Schnittstelle wird die sehr hohe Parametersensitivität des SCS-CN Verfahrens in AGNPS durch geringere Einzelsensitivitäten verschiedener Parameter des Bodenwasserhaushaltes in WASIM ersetzt und gleichzeitig eine plausible, prozessbasierte räumliche Abflussbildung berechnet. Durch die Implementierung eines Moduls zur Abschätzung der Bodentemperatur in WASIM ist zusätzlich die Grundlage für eine weitergehende Verbesserung der Abflussbildung bei winterlichen Randbedingungen gelegt. Durch das Modul wird die Oberbodentemperatur aus Werten der Lufttemperatur unter Einbeziehung der Exposition und der Landnutzung auf der Basis einer Polynomanpassung abgeschätzt. Bei einer modellierten Schneedecke von mehr als 5 mm Schneewasseräquivalent wird die berechnete Bodentemperatur des Vortages übernommen. Bei Bodentemperaturen unter dem Gefrierpunkt wird darüber hinaus die gesättigte hydraulische Leitfähigkeit des Bodens auf Null herabgesetzt, so dass im Zuge der Schneeschmelze zunächst das noch freie Porenvolumen aufgefüllt wird und danach Oberflächenabflussbildung beginnt. Für das Schäfertal liegt die Güte der Anpassung der Bodentemperatur bei Korrelationskoeffizienten von 0.62 bis 0.81 und für das Lubazhinkhaeinzugsgebiet bei Werten von 0.82 bis 0.91. Die räumlich und zeitlich differenzierte Oberflächenabflussinformation dient als Grundlage einer neu entwickelten Berechnung der Rillenerosion bei Schneeschmelzen, die den dafür nicht geeigneten empirischen Ansatz in AGNPS ersetzt. Basierend auf der Grundannahme eines dreieckigen, nicht durch Frost in der Eintiefung beeinträchtigten Rillenprofils und, da wassergesättigt, nichtkohesiver Bodeneigenschaften wird für jede Rasterzelle eine Rille simuliert. Die Erodibilität des Bodens wird als Funktion von Wurzelparametern und des Durchmessers der wasserstabilen Aggregate erfasst. Die Scherkraft des Schneeschmelzeabflusses in der Rille wird in Abhängigkeit von der Oberflächenrauhigkeit und dem Aggregatdurchmesser betrachtet und darauf aufbauend in einem Impulsstromansatz die erodierte Bodenmenge berechnet. In Verbindung mit dem durch das modifizierte WASIM berechneten und gerouteten Oberflächenabfluss ergibt sich so ein räumlich differenziertes Bild der Bodenerosion. Das Modellsystem IWAN beinhaltet neben der Erosionsberechnung ein eingabefenstergesteuertes Menü zur Datenkonvertierung und zum Prä- sowie Postprozessing. Die Ergebnisse der Anwendung des Modellsystems für die beiden Einzugsgebiete belegen, dass sowohl die entscheidenden Prozesse der Abflussbildung als auch des Sedimentaustrags wiedergegeben werden. Für das Schäfertal wurde für die Kalibrierungsjahre 1994 bis 1995 eine Modellierungsgüte von R2 0.94 bzw. 0.91 erzielt. Mit Ausnahmen der Schneeschmelze im Jahr 1996 werden die Episoden hohen Abflusses in den Jahren 1996 bis 2003 mit dem kalibrierten Parametersatz gut wiedergegeben und das witterungsbedingte Trockenfallen im Sommer zufriedenstellend dargestellt. Auf dieser Basis wird für die experimentell erfassten und diskutierten Schneeschmelzereignisse das Gesamtabflussvolumen dieser Ereignisse mit hoher Güte abgebildet. Die räumlich differenziert berechnete Bodenfeuchte und Bodenfrostvorkommen bedingen einen variablen Anteil des Oberflächenabflusses am Gesamtabfluss. Für das Schneeschmelzerosionsmodul hat das Abflussvolumen ebenso wie die Hangneigung und Abflusslänge eine positive Sensitivität. Aufgrund von Parameterkombinationen und nichtlineare Algorithmen kann es jedoch vor allem für die Wurzelparameter und den Manning Koeffizienten zu differenzierten Sensitivitätsentwicklungen kommen. Für die Simulation der Erosion im Schäfertal wurde daher zunächst auf einen Parametersatz zurückgegriffen, der auf der Basis von Erosionsparzellenversuchen kalibriert wurde. Die Mittelwerte der berechneten Erosion liegen zwischen 0.0006 und 0.96 t ha-1 für die sechs gemessenen Einzelereignisse im Schäfertal. Die Medianwerte und hohen Standardabweichungen belegen jedoch, dass insgesamt Zellen mit geringen Erosionswerten überwiegen. Die Ereignisse mit gefrorenen Böden weisen eine signifikant höhere Erosion auf. Unterschiede in der Erosion treten bei gleichen Gesamtabflussvolumen wie z.B. bei den Ereignissen vom 20.01.2001 und 26.02.2002 durch differenzierte Abflusskonzentration auf dem nord- bzw. südexponierten Hang auf. Neben einer Überprüfung der Plausibilität der berechneten Werte, werden die räumlichen Verteilungsmuster durch Geländeaufnahmen bestätigt. Die Anpassung der berechneten Sedimentfracht an die gemessenen Werte erfolgte durch die Kalibrierung des Manning Koeffizienten für ein Ereignis. Die simulierte Sedimentfracht ist in einigen Hangfußbereichen aufgrund der Abflussakkumulation besonders hoch und erreicht für den Gebietsauslass Werte zwischen 0.0 und 13.84 t. Mit der Ausnahme des Ereignisses vom 26.02.2002 ist die Sedimentfracht leicht unterschätzt, so dass sich in der Summe für die drei Winterhalbjahre 2001 bis 2003 ein Gesamtfehler von 11 t ergibt. Die Differenz zwischen der simulierten und beobachteten Sedimentfracht ist für den 26.12.2002 am größten. Als mögliche Ursache für die Abweichungen der berechneten zu den gemessenen Werten, wird die zeitliche Variabilität und räumliche Heterogenität der Oberflächenrauhigkeit, vor allem in Hinblick auf Bodenbearbeitung und Bodenfrosteinflüssen, diskutiert. Die generelle Verteilung der Sedimentquellen, Transportwege und Übertrittstellen vom Hang ins Gewässer stimmt mit Geländebeobachtungen überein. Eine quantitative Überprüfung der räumlichen Ergebnisse auf der Einzelereignisebene ist für das Schäfertal jedoch nicht möglich. Für das Lubazhinkhaeinzugsgebiet können zwei Parametersätze für das Kalibrierungsjahr 2004 identifiziert werde, die eine zufriedenstellende Modellierungsgüte für das hydrologische Modell erreichen. Obwohl einer dieser Parametersätze die Schneeschmelzsituationen und Maximalabflüsse gut darstellt, sind die Areale mit Oberflächenabflussbildung innerhalb des Einzugsgebietes nicht plausibel verteilt. Im Gegensatz dazu werden die lateralen Wasserflüsse und damit die prozessbestimmende Bodenfeuchteverteilung durch den anderen Parametersatz besser abgebildet. Es kommt jedoch zu einer Überschätzung der Spitzenabflüsse der Schneeschmelzhochwasser für die Validierungsjahre 2003 und 2005. Die auf der Basis der Messwerte erkannten Unterschiede zwischen den Einzeljahren werden ebenso dargestellt wie die differenzierte Abflussbildung innerhalb einer Schneeschmelzsituation. Neben Oberflächenabflussbildung auf den flachen Kuppenbereichen und auf Sättigungsflächen in den Talböden, wird auch die beobachtete verzögerte Abflussbildung unter Wald durch das Modell berücksichtigt. Bei zehn Tagen mit Oberflächenabfluss innerhalb der drei Schneeschmelzen 2003 bis 2005 mit Oberflächenabflussvolumen von 0.3 bis 24.1 mm d-1 werden durch das Modellsystem IWAN Erosionssummen von 10 bis 280 t d-1 simuliert. Bei einem variablen Flächenanteil von ca. 5 bis 46 % des Gesamtgebietes, auf dem Erosion stattfindet, bewegen sich die Werte der effektiven Erosion bei 0.1 bis 0.32 t ha-1 für die Einzeltage und 0.44 bis 0.92 t ha-1 für die mehrtägigen Schneeschmelzen. Die am Gebietsauslass simulierte Sedimentfracht liegt zwischen 6.7 und 365.8 t pro Tag und summiert sich auf 246.2 t für die Schneeschmelze 2003. Im Jahr 2004 werden 99.9 t und im Jahr 2005 sogar 757.9 t Austrag simuliert. Für das Kalibrierungsjahr 2004 kommt es zu einer Überschätzung der Sedimentfracht im Vergleich zur gemessenen von lediglich 10 t bzw. 12%. Für die Schneeschmelze im Jahr 2003 liegt die Abweichung mit diesem Parametersatz bei -9 %. Für das Jahr 2005 fällt die Berechnung mit einem Fehler von 33 % nicht so gut aus. Insgesamt führen Schneeschmelztage mit geringer simulierter Erosionsmenge zu einer zusätzlichen Mobilisierung von Sediment aus dem Gerinne und umgekehrt, hohe Erosionsmengen zu einer Deposition von Material auf den Wald- und Grünlandflächen und im Gerinne selbst. Hohe Sedimentfrachten werden daher vor allem für die Talflanken und die kerbtalähnlichen Talanfänge berechnet. Durch die räumliche Differenzierung der Abfluss- und Erosionsprozesse kommt es zu signifikanten Unterschieden bei der berechneten Sedimentfracht für die beiden Teileinzugsgebiete. Bei Schneeschmelztagen mit Abflussbildung unter Wald wird aufgrund des höheren Waldanteils im Lubazhinkhateilgebiet eine höhere Sedimentmenge ausgetragen. Die Unterschiede im Gerinneverhalten und zwischen den Teileinzugsgebieten verdeutlichen die insgesamt hohe Prozessrepräsentanz der Modellergebnisse. Das Modellsystem IWAN bildet für beide Einzugsgebiete mit hoher Plausibilität die räumliche und zeitliche Dynamik der Oberflächenabflussbildung während der Schneeschmelze und die damit verbundenen Erosionsprozesse ab. Der Modellansatz stellt somit eine Möglichkeit zwischen Modellergebnisaggregierung für den Gebietsauslass und aufwendiger Geländebeobachtung bzw. –messungen dar. Die prozessbeschreibende Modellierung mit zufriedenstellender Güte sowohl für das Schäfertal als auch für das Lubazhinkhaeinzugsgebiet stellt die Grundlage für die Berechnung von Klima- oder Landnutzungsszenarien dar. Eine Auswertung der bestehenden langjährigen Datenreihe aus dem Schäfertal bestätigt zunächst den allgemeinen Trend zur Erwärmung vor allem im Winterhalbjahr. Demgegenüber lässt der instrumentenbedingte Fehler bei der Niederschlagmessung keine Ableitung eines Trends aus den vorhandenen Daten zu. Aus der meteorologischen Datenreihe des Schäfertals wurden insgesamt 13 Jahre mit definierter Abweichung von +2.5 bis -2.5 °C und fünfmal +0.5 °C von der durchschnittlichen Winterlufttemperatur (Jd 330-90) gegenüber dem langjährigen Wintermittel ausgewählt. Im Gegensatz zu Wettergeneratoren werden dadurch eine Kombinationen aus Lufttemperatur und Niederschlag erfasst, die typischen Witterungssituationen entsprechen. Die Niederschlagssummen für den Winterzeitraum dieser Szenariojahre liegen zwischen -45 % und + 75 % gegenüber den langjährigen Mittelwerten. Die Modellergebnisse belegen die große Bedeutung der Witterungssituationen für die Abflussbildung in der Art, dass eine erhöhte Niederschlagsumme nicht zwingend auch eine überdurchschnittliche Abflussmenge hervorruft. Schneedeckendynamik und Bodenfrost sind die prägenden Elemente. Die Anzahl der Schneetage und die Dauer einer Schneeperiode liegt bei negativen Temperaturabweichungen deutlich über den Szenarien mit positiver Abweichung. Insgesamt zeigen die Ergebnisse der hydrologischen Simulation für die Szenarien, dass sowohl eine starke Abweichung nach oben oder unten vom bisherigen Durchschnitt vermehrt zu Oberflächenabflussbildung führt. Die Erosionssummen der Szenariotage mit Oberflächenabfluss variieren zwischen 4 und 141 t d-1 und stehen aufgrund des nicht veränderten Parametersatzes in direkter Abhängigkeit zum Abflussvolumen. Die berechneten Erosionssummen für Situationen ohne Bodenfrost fallen generell geringer aus, befinden sich aber wie auch die Ereignisse mit Bodenfrost im Wertebereich der Referenzereignisse. Im Bereich der Referenzereignisse liegen auch die Sedimentfrachten mit 0.03 bis 13.15 t d-1. Eine erhöhte Variabilität ist zu erwarten, wenn die Veränderungen der Vegetationsperioden und der Fruchtfolgen in den Modellansatz aufgenommen würden. Eine Betrachtung der Erosionsummen und Sedimentfrachten nicht auf Basis von Tageswerten sondern von Schneeschmelzereignissen zeigt deutlich, dass die Klimaszenarien mit hohen Abweichungen von den Normwerten auch erhöhte Gesamtstoffausträge verursachen. Im russischen Lubazhinkhaeinzugsgebiet führen die Transformationsprozesse im Landwirtschaftssektor zu tiefgreifenden Änderungen der Landnutzung. Auf einer Analyse der Entwicklung in den letzten 15 Jahren aufbauend, kann für das Gebiet von einer deutlichen Modifikation im Verhältnis Grünland, Acker und Wald ausgegangen werden. Diese Dynamik spiegelt sich in den fünf Szenarien wider, die flächenspezifische Änderungen vorsehen. Die Variationen reichen von einem Szenario, in dem ein ausländischer Investor die landwirtschaftliche Nutzfläche auf alle geeigneten Böden ausdehnt, über eine Ausdehnung der Waldflächen in einem laufenden staatlichen Waldschutzprogramm bis hin zum Aufbau kleinbäuerlicher Strukturen und lokale Vermarktung der Produkte durch sich entwickelnden Tourismus. Die Gesamtabflussmenge der Szenarien liegt zwischen 276.4 und 293.3 mm für die Simulationsperiode 2003 bis 2005. In Abhängigkeit vom Waldflächenanteil und der damit verbundenen Evapotranspiration treten im Vergleich zum Ist-Zustands des Referenzszenarios nur geringe positive oder negative Abweichungen auf. Im Unterschied dazu treten bei der Betrachtung der Oberflächabflussentwicklung für die drei Schneeschmelzperioden relativ große Abweichungen bis zu über 20 mm auf. Diese Unterschiede sind am deutlichsten in den durch Bodenfrost und hohes Schneewasseräquivalent ausgezeichneten Jahre 2003 und 2005 für das Szenario mit dem größten Waldflächen- und Grünlandanteil. Mit wenigen Ausnahmen führen die Szenarien zu einer Erhöhung der simulierten Sedimentfracht am Gebietsauslass. Die Ergebnisse belegen darüber hinaus, dass eine Verminderung der Erosion auf den Hängen allein nicht zu einer Frachtreduzierung führen muss, da bei geringer Sedimentbelastung im Gerinne Material aufgenommen werden kann. Ein flächenspezifischer Vergleich zweier Szenarien belegt die Bedeutung der Verortung der Nutzungsänderungen innerhalb des Einzugsgebietes und der damit einhergehenden Konnektivität von abflussbildenden Arealen und Erosionsflächen zum Gerinne hin. Die Szenarioergebnisse weisen auf die steigende Bedeutung von Extremereignissen hin, die im Zuge des Klimawandels zu erwarten sind. Ebenso wird die Verknüpfung von Hang- und Gerinneprozessen als Attribut eines Einzugsgebietes unterstrichen, das bei Managementmaßnahmen beachtet werden muss. Insgesamt belegen die Ergebnisse für beide Untersuchungsgebiete, dass das Modellsystem IWAN nach einer Kabibrierung erfolgreich zur Abschätzung von möglichen zukünftigen Sedimentquellen und Sedimentausträgen eingesetzt werden kann. Weitergehender Forschungsbedarf besteht in der Frage der Übertragbarkeit des Monitoringansatzes in Naturräume mit anderen, zum Teil komplexeren hydrologischen Einzugsgebietsreaktionen und darauf aufbauenden Stoffausträgen und Austragspfaden. Darüber hinaus kann im Modellsystem IWAN eine Verbesserung durch eine Berechnung der Rillenausbildung auf dem Hang sowie eine Modifikation der Sedimenttransportberechnung erzielt werden. Bei einer Übertragung auf andere Einzugsgebiete sollte eine umfassende Sensitivitätsanalyse und Ergebnisunsicherheitsbetrachtung vor allem in Hinblick auf die Kopplung von Teilmodellen innerhalb des Modellsystems erfolgen.:Gliederung Gliederung V Liste der Abbildungen VII Liste der Tabellen XII 1 Einleitung und Fragestellung 3 1.1 Bodenerosion und Sedimentfracht in Einzugsgebieten 3 1.1.1 Abflussbildung, Bodenerosion und Sedimentaustrag 3 1.1.2 Winterliche Situationen 5 1.2 Modellierungsansätze 13 1.2.1 Modelle und Modellkopplungen 13 1.2.2 Probleme der Modellanwendung 17 1.3 Wissensdefizite und Zielstellung 23 2 Untersuchungsgebiete und Methoden 25 2.1 Schäfertal 25 2.1.1 Naturraum 25 2.1.2 Methoden 28 2.2 Lubazhinkha 31 2.2.1 Naturraum 31 2.2.2 Methoden 36 2.3 Datenverarbeitung 38 3 Ergebnisse und Diskussion des Monitorings in den Einzugsgebieten 41 3.1 Schäfertal 41 3.1.1 Abflussbildung 41 3.1.2 Stoffausträge bei Hochwasserereignissen 45 3.2 Lubazhinkha 54 3.2.1 Bedeutung der Schneeschmelze für den Stoffaustrag 54 3.2.2 Stoffdynamik während der Schneeschmelze 57 4 Modellentwicklung 69 4.1 Zielstellungen der Modellmodifikation und -entwicklung 69 4.2 WASIM-AGNPS 70 4.2.1 Wasserhaushaltsmodell WASIM 70 4.2.2 Stofftransportmodell AGNPS 72 4.2.3 Schnittstelle WASIM-AGNPS 74 4.3 Modifikation von WASIM für winterliche Abflussbildung 76 4.3.1 Grundlagen 76 4.3.2 Datenerhebung 77 4.3.3 Sensorauswahl 77 4.3.4 Ergebnisse 79 4.3.5 Empirisches Modell 82 4.3.6 Bodentemperaturteilmodul 83 4.3.7 Anpassung mit Daten aus dem Einzugsgebiet Lubazhinkha 85 4.4 Schneeschmelzerosionsmodell (SMEM) 87 4.4.1 Rillenprofil 87 4.4.2 Bodenerosion 90 4.4.3 Technische Umsetzung 96 4.5 Modellsystem IWAN 97 4.5.1 Schnittstelle SMEM-AGNPS 97 4.5.2 Graphische Benutzeroberfläche 99 5 Modellergebnisse und Diskussion 105 5.1 Schäfertal 105 5.1.1 Bodentemperatur 105 5.1.2 Hydrologie 108 5.1.3 Schneeschmelzerosion 113 5.1.4 Sedimentfracht 120 5.2 Lubazhinkha 126 5.2.1 Hydrologie 126 5.2.2 Schneeschmelzerosion 133 5.2.3 Sedimentfracht 137 6 Szenariorechnungen 143 6.1 Klimaszenarien Schäfertal 143 6.1.1 Szenarienauswahl 143 6.1.2 Modellergebnisse und Diskussion 148 6.2 Landnutzungsszenarien Lubazhinkha 158 6.2.1 Szenarienauswahl 158 6.2.2 Modellergebnisse und Diskussion 163 7 Schlussfolgerungen 169 7.1 Einzugsgebiete 169 7.2 Modellsystem IWAN 172 7.3 Szenarien 176 7.4 Forschungsbedarf 178 8 Zusammenfassung 179 9 Summary 189 10 Literatur 199 Appendix 207 Abkürzungen Modellübersicht Quellcode (VBA) ; Soil erosion by water is a ubiquitous problem that impairs the agricultural productivity, diminishes soil functionality and may harmfully affect neighbouring environmental compartments. Surface waters are especially affected by the sediment, sediment bounded and soluble nutrients as well as pollutants mobilised by soil erosion. The knowledge about erosion processes and sediment loads is of high relevance for the protection of the soil and water and has moreover an economic dimension. Generally, a slope or catchment can be divided into three zones: erosion, transport and sedimentation. However, runoff generating processes and roughness or topography triggered runoff concentration lead to an individual differentiation. Furthermore, spatial and temporal discontinuities of processes or connectivities and thresholds modify the erosion and sediment characteristics. Relief and soil as structural elements of a catchment control accordingly the soil moisture differentiation and in an essential way the runoff generation and sediment load. In temperate and cold climates an important portion of runoff is generated in winter and can be affected by soil frost and snowmelt. However, only little knowledge exists about the processes and dimension of sediment and nutrient emissions under these wintry conditions. Systematic research exists particularly in Russia and Norway. The related deficits are also reflected in existing model approaches to estimate soil erosion and sediment fields from catchments. On the one hand neither the snow development or snow melt nor the modification of the soil water flow in case of frozen soil is considered. On the other hand the erosivity of the snow melt runoff and the modification of the soil erodibility through, for example frost-thaw cycles, is adequately reflected. It is the main focus of the presented work to identify, by analysing data from a German and a Russian catchment, the dominant processes and triggers of runoff generation and diffuse pollution under winter conditions. The results are implemented into a model system which is utilised to analyse spatial heterogeneity and temporal variability of processes and to estimate the effects of climate and land use change on sediment loads in the two target areas. The 1.44 km² catchment Schaefertal is located in the eastern lower Harz Mountains approx. 150 km SW of Berlin, Germany. Cambisols and Luvisolos have developed from periglacial slope deposits on greywacke and argillaceous shale. These slopes are utilised agriculturally with a crop rotation of mainly winter grain and canola. The thalweg is dominated by hydromorphic soils and pasture. The climate is slightly continental with an annual average temperature of 6.8°C and 680 mm total annual precipitation. In addition to long-time hydro-meteorological measurements, since several years research into sediment and nutrient emissions is conducted. A routine biweekly sampling of the runoff at the catchment outlet is supplemented by automatic high flow sampling especially during snow melt flows. Besides suspended sediment concentration, phosphorus species and dissolved organic carbon are sampled and analysed following standard methods. Also in the Russian catchment Lubazhinkha the main focus is the characterisation of runoff generation and sediment/nutrient transport during snowmelt events. The catchment is located about 100 km south of Moscow, Russia in the transition zone from southern Taiga to forest steppe. The area of 18.8 km² is utilised half by agriculture and one third by forestry. The recent spatial differentiation of this land use is triggered by the relief determined erosive shortening and hydromorphic characteristics of the dominant grey forest soils. Climate and hydrology are dominated by snow cover accumulation and snow melt; annual average temperature is 4.4°C and the annual precipitation sum is 560 mm. High flow samples are taken at the catchment outlet behind a small dam and at the two most important tributaries to characterise mobilisation processes and the sediment and nutrient concentrations. The interpretation of data from the Schaefertal demonstrate for the period of investigation the importance of high flow situations that are caused by snow melt. Catchment conditions characterised by frozen soils lead to a modification of the measured hydrograph, especially through the occurrence of fast surface or near-surface components. The peak flow of the eight high flow events which are employed for interpretation vary between 30 and 270 l s-1, with total runoff volumes in a range from 1 to 50 mm. The sediment concentrations that are observed at the catchment outlet are below 650 mg l-1 for the two events without frozen soil and therewith distinct below the maximum of around 6000 mg l-1 for events with frozen or partly frozen soil conditions. Solely, one event with rainfall on unfrozen soil is characterised by high sediment concentration which is caused by channel maintenances and easy mobilisation of material from the channel banks. According to this, the sediment yields vary for the single events and achieve up to 17 t. The most important trigger is the generation of erosive surface runoff on the slopes by reduction of the hydraulic conductivity of the frozen soils. The comparison of the sediment concentrations of high flow events and the biweekly sampling as well as hysteresis curves of the single events clarify the differing dynamics of sediment export situations. The soil frost affected events show an anti-clockwise direction of the discharge-sediment relationship which points to a sediment source on the slope, whereas the hysteresis curves of unfrozen soil conditions are oriented clockwise. For these events a sediment source near the channel or the channel bank is probable. These assumptions are also supported by a differentiated phosphorus enrichment ratio in the exported sediment. Furthermore, a dynamic in the progress of the single events can be observed which is caused by the temporal variability of the runoff generation and confirms the related spatial heterogeneity of sediment sources. Contrary to the Schaefertal with several snow melt events per year, in the Russian catchment the snow cover is accumulated over the entire winter and one snow melt flood occurs in March or during the first half of April. The interpretation of multiannual data document the importance of the spring snow melts for the runoff generation and sediment export from the catchment Lubazhinkha. The sediment yield of three observed snow melt events varies between 50 and 630 t in dependency on the hydrological conditions. The event related sediment load of at least 0.3 t ha-1 is above the values that were measured in the Schaefertal but in the range of other studies with comparable soils and land use. Detailed analyses of the measurements of the snow melt in spring 2003 document the dynamic within one event. A sediment concentration at the catchment outlet from 6 to 540 mg l-1 led to a total event sediment yield of 190 t. The maximum concentrations of sediment and phosphorus peak with the discharge. In contrast, the concentration of dissolved organic carbon (DOC) is delayed compared to the runoff peak due to the slow snow melt development under forest stands and mobilisation of DOC from the organic rich topsoil of these forest areas. A differentiation of runoff components allows a further interpretation of event specific dynamic of sediment sources and transport pathways. In case of low discharge (< 2.5 mm d-1) the material transfer is dominated by dissolved forms and enters the channel passing the soil as slow runoff. Fast runoff components or surface runoff dominate situations with higher amounts of discharge in which sediment and nutrient sources are mobilised with temporal dynamic. Besides this event internal dynamic inter-annual variability exists that is a result of weather conditions in the specific winter. Similar to the Schaefertal, the development of frozen soils and the related modification of infiltration characteristics of the soils play an important role in the Lubazhinkha catchment. Other important triggers are snow water equivalent, snow melt dynamic and specific soil frost characteristics, i.e. depth of penetration. The variability of these boundary conditions led to a high inter-annual differentiation of runoff generation and sediment loads. Thus, for the snowmelt 2004 with above average winter air temperatures and only partly frozen soils, as well as low snow water equivalent, a comparable low sediment load was observed. In addition, the hysteresis curves of the discharge-sediment concentration relationship indicate differences in the sediment sources for the single snow melt events which are in dependency of the abovementioned factors. For both catchments the established monitoring system and selected parameters provide an insight into runoff generating processes and relevant triggers. Occurrences of soil frost and snow melt dynamics are most important factors. Wintry conditions led to high sediment and nutrient yields in both catchments. The interpretation of physical and chemical parameters of discharge allows the identification of spatial heterogeneity and temporal variability of sediment source areas. Several demands for a model approach arise from these findings of catchment monitoring which are especially related to the spatial differentiated estimation of surface runoff generating areas and soil erosion through snow melt water. The basis for the model system "IWAN" (Integrated Winter erosion And Nutrient load model) is the hydrological model WASIM ETH Ver.2 and the nutrient load model AGNPS 5.0. The linking of these two raster-based models facilitates the utilisation of continuous, spatial differentiated information for surface runoff to estimate soil erosion. By this, the high parameter sensitivity of the SCS-CN approach in AGNPS is replaced with sensitivities distributed among different parameters of the soil water calculation in WASIM and the concurrent calculation of a plausible process based spatial differentiated runoff generation. The implementation of a module to estimate the soil temperature forms the basis for an improved calculation of soil water flows and runoff generation under winter conditions. This module calculates the topsoil temperature based on values of air temperature and considers exposition and land use. The calculated soil temperature of the previous day is assumed in case of a snow cover of more than 5 mm water equivalent. The saturated hydraulic conductivity of the soil is set to zero if the calculated soil temperature drops below freezing and surface runoff begins after the water free soil pore volume is filled up. The goodness of fit for the Schaefertal shows a correlation coefficient of 0.62 to 0.81 and for the Lubazhinkha catchment values in a range between 0.82 and 0.91. The spatial and temporal differentiated information of surface runoff is fundamental to a new developed calculation of rill erosion during snow melt situations which replaces the empirical erosion estimation of AGNPS. One rill for each raster cell is simulated on the assumption of a non-cohesive soil through water saturation and that soil frost does not hinder the deepening of the triangular rill profile. The soil erodibilty is a function of root parameters and diameter of water stable aggregates. The erosivity of the snow melt runoff in the rill is calculated in dependency of surface roughness and soil aggregate diameter. A spatial differentiated estimation of soil erosion is possible in combination with the routed surface runoff from the modified WASIM. In addition to the erosion estimation, the model system IWAN comprises a user interface for data conversion as well as pre- and post-processing options. The results of the model system application for both catchments demonstrate that the dominant processes of runoff generation as well as sediment loss are matched. For the Schaefertal a modelling agreement of r² equalling 0.94 and 0.91 is realised for the year of calibration 1994 and the year of validation 1995, respectively. With the exception of 1996 all periods of high flow and the falling dry of the channel in summer from 1996 until 2003 are represented satisfactorily with the calibrated set of parameters. On this basis, the total runoff volume of the observed and above discussed snow melt events has been modelled with a high degree of accuracy. The spatially differentiated calculation of soil moisture and soil frost occurrence results in a variable fraction of surface runoff on the total runoff for these events. Runoff volume, slope and flow length show positive sensitivities in the new snow melt erosion module. However, parameter combinations and non-linear algorithms, especially for root parameters and the Manning coefficient, may lead to more complex sensitivity properties. Thus, the simulation of soil erosion in the Schaefertal was first conducted with a set of parameters that was calibrated with results of erosion plot experiments. The average values of calculated erosion vary between 0.0006 and 0.96 t ha-1 for the six events from the Schaefertal. However, the median values and high standard deviations prove that most of the cells have low erosion values. The results for events with frozen soils are characterised by significant higher values of erosion. Despite similar total runoff volume i.e. of the events from 20.01.2001 and 26.02.2002 differences occur because of distinctions in runoff concentration on the north and south exposed slope. The spatial results are positively compared to field mapping in addition to a plausibility control of the calculated values. The adjustment of the calculated values for sediment load against the observations is done with calibration of the Manning coefficient for one randomly selected event. The sediment load in some footslope areas caused by runoff concentration is especially high and in the range of 0.0 to 13.84 t for single events. The event sediment yield is generally underestimated with the exception of the event on 26.02.2002. The total absolute error for the three winter seasons is 11 t. The difference between simulated and observed sediment load is highest for the 26.12.2002. This distinction may originate in the temporal variability and spatial heterogeneity of surface roughness against the background of soil frost influences and tillage operations. The general distribution of modelled sediment sources, transport pathways and connecting points to the channel are confirmed by field observations. However, a quantification of the spatial model results on the basis of the observed single events is not possible. For the Lubazhinkha catchment two sets of hydrological parameters are identified for the year of calibration 2004 which achieve satisfying results in comparison to the observed discharge. Although one of these set of parameters performed better in reproducing the peak flows of the snow melt situations, the spatial distribution of surface runoff generating areas was not plausible. Contrary, the second set of parameters characterises the lateral water flows and thus the important spatial soil moisture distribution in a more realistic way. However, the snow melt peak flows for the years of validation 2003 and 2005 are overestimated. The difference between the years, which was identified on the basis of the interpretation of the observations, is matched as well as the dynamic of runoff generation. Surface runoff generation on the flat interfluves areas and saturated areas in valley bottoms are modelled satisfactorily as well as the delayed runoff generation under forest stands. The model system simulates erosion sums of 10 to 280 t d-1 for a total of ten days with surface runoff in a range of 0.3 to 24.1 mm d-1 in the entire modelling period of three years. Considering the variable area of 5 to 46 % on which erosion takes place, the values of effective erosion vary between 0.1 and 0.32 t ha-1 for single days and between 0.44 to 0.92 t ha-1 for multi-day snow melts. The simulated sediment load at the catchment outlet range from 6.7 to 365.8 t per day and sums up to 246.2 t for the snow melt 2003. For the year 2004 99.9 t and for 2005 757.9 t are calculated. In comparison to the observations for the calibration year 2004, the sediment load is overestimated by 10 t or 12 %. The deviation for 2003 is -9 %, with the same set of parameters. The result for 2005 is with an error of 33 % not as good as in the two other years. Overall, the days of snow melt with a low amount of erosion cause additional mobilisation of sediment from the channel banks and contrary, high amount of erosion on the slopes result in deposition processes on the forest and pasture areas near in the valley bottom and in the channel itself. Thus, high sediment loads are estimated for the bottom slopes and the small V-shaped first order valleys. The sediment loads for the two sub-catchments differ significantly because of the spatially differentiated processes of runoff generation and soil erosion. For the days with runoff generation in forest areas higher sediment yields are calculated for the Lubazhinkha-subcatchment which is characterised by a higher degree of forested areas. Differences in slope-channel interaction and variations between the two subcatchments illustrated the overall high process relevance of the model results. The model system IWAN estimates for the Schaefertal and the Lubazhinkha catchment the spatial and temporal dynamics of surface runoff generation and the related erosion processes during snow melt episodes with high plausibility. The model approach demonstrates an option between model result aggregation at the catchment outlet and intensive spatial field observation and measurement within a catchment. The satisfactory modelling of processes for the Schaefertal, as well as for the Lubazhinkha catchment, forms the basis for the calculation of climate and land use scenarios. An analysis of the existing long-term dataset from the Schaefertal approves the general trend of warming, especially in the winter half year. Contrary, the instrument error for rainfall measurements disallows an identification of a trend in the present data. A total of 13 years with defined deviation of +2.5 to -2.5 °C and five years with a deviation of +0.5 °C from the average air temperature in winter (Jd 330-90) were selected from the data set. In contrast to the utilisation of weather generators, this selection provides a dataset with a combination of air temperature and rainfall/snow that is in accordance with typical atmospheric situations. The amount of rainfall for the winter period of the scenario years deviates -45 % to +75 % from the long term average of winter. The model results substantiate the role of weather situations such that an increased amount of rainfall does not automatically result in above-average runoff. Snow cover dynamics and soil frost occurrence are the controlling factors. The number of days with snow and the duration of each snow period are significant higher for scenarios with negative temperature deviation compared to the scenarios with positive deviation. Overall the results of the hydrological calculation of the scenarios show that extreme positive and negative deviations lead to increased surface runoff probability. The sums of erosion for single days with surface runoff varies between 4 to 141 t d-1 and are in direct relation to runoff volume due to the unchanged set of parameters. Generally the calculated sums of erosion for situations without soil frost are lower than with soil frost, but both types are in the range of values of the measured and modelled reference events. Also the calculated sediment yields from 0.03 to 13.15 t d-1 for the scenario days are in the range of the measurements. A higher variability could be expected when considering modifications to vegetation period or crop rotations. An interpretation of erosion and sediment yield on the basis of snow melt periods clarifies those scenarios with extreme deviations also tend to higher sediment export from the catchment. Transformation processes in the agricultural sector of Russia trigger fundamental changes in land use. Based on an analysis of the development of the past 15 years for the Lubazhinkha catchment a significant modification of the pasture, arable land and forest areas is probable in the future. This dynamic is reflected in five scenarios with area-specific changes in land use distribution. The variations range from scenarios with a foreign investor who extends the arable land to all suitable soils in the catchment, an expansion of forest areas in the frame of a governmental forest protection program to the development of small family farms with local market structures because of tourism. The calculated total runoff for the scenarios varies between 276.4 and 293.3 mm for the entire simulation period 2003 to 2005. Small positive or negative deviations occur compared to the as-is state in relation to the variable forest area and combined evapotranspiration. Contrary, the surface runoff shows large deviations of more than 20 mm for the three snow melt periods. These differences are pronounced for the scenario with highest portion of forest and pasture area in the years 2003 and 2005 that are characterised by soil frost and high water equivalent in snow. With only few exceptions the scenarios lead to an increase in simulated sediment yield at the catchment outlet. Moreover, the results document that a decrease of erosion on the slopes does not consequently result in a yield reduction. In the case of low sediment input from the slopes additional material from the channel bed and banks may attribute significantly to the sediment loading. An area specific comparison of two scenarios clarifies the importance of localisation of land use changes and the according connectivity of surface runoff areas and erosion areas to the channel. The scenarios document the increasing importance of extreme events that can be expected due to climate change. Additionally, the link of slope and channel processes, as attribute of a catchment, has to be considered in planning of management measures. The results prove for both catchments that the model system IWAN can be applied for estimating future potential sediment sources and sediment yield after successful calibration. Further research is needed in the question of transferability of the monitoring approach to other environments with a different, more complex hydrological catchment reaction and linked sediment sources and transport mechanisms. The model system IWAN can be improved by a dynamic calculation of rill network generation on the slope and a modification of the sediment transport algorithms. The transfer of the model system to other catchments has to be accompanied by a comprehensive sensitivity and uncertainty analysis especially respecting the model chain within IWAN.:Gliederung Gliederung V Liste der Abbildungen VII Liste der Tabellen XII 1 Einleitung und Fragestellung 3 1.1 Bodenerosion und Sedimentfracht in Einzugsgebieten 3 1.1.1 Abflussbildung, Bodenerosion und Sedimentaustrag 3 1.1.2 Winterliche Situationen 5 1.2 Modellierungsansätze 13 1.2.1 Modelle und Modellkopplungen 13 1.2.2 Probleme der Modellanwendung 17 1.3 Wissensdefizite und Zielstellung 23 2 Untersuchungsgebiete und Methoden 25 2.1 Schäfertal 25 2.1.1 Naturraum 25 2.1.2 Methoden 28 2.2 Lubazhinkha 31 2.2.1 Naturraum 31 2.2.2 Methoden 36 2.3 Datenverarbeitung 38 3 Ergebnisse und Diskussion des Monitorings in den Einzugsgebieten 41 3.1 Schäfertal 41 3.1.1 Abflussbildung 41 3.1.2 Stoffausträge bei Hochwasserereignissen 45 3.2 Lubazhinkha 54 3.2.1 Bedeutung der Schneeschmelze für den Stoffaustrag 54 3.2.2 Stoffdynamik während der Schneeschmelze 57 4 Modellentwicklung 69 4.1 Zielstellungen der Modellmodifikation und -entwicklung 69 4.2 WASIM-AGNPS 70 4.2.1 Wasserhaushaltsmodell WASIM 70 4.2.2 Stofftransportmodell AGNPS 72 4.2.3 Schnittstelle WASIM-AGNPS 74 4.3 Modifikation von WASIM für winterliche Abflussbildung 76 4.3.1 Grundlagen 76 4.3.2 Datenerhebung 77 4.3.3 Sensorauswahl 77 4.3.4 Ergebnisse 79 4.3.5 Empirisches Modell 82 4.3.6 Bodentemperaturteilmodul 83 4.3.7 Anpassung mit Daten aus dem Einzugsgebiet Lubazhinkha 85 4.4 Schneeschmelzerosionsmodell (SMEM) 87 4.4.1 Rillenprofil 87 4.4.2 Bodenerosion 90 4.4.3 Technische Umsetzung 96 4.5 Modellsystem IWAN 97 4.5.1 Schnittstelle SMEM-AGNPS 97 4.5.2 Graphische Benutzeroberfläche 99 5 Modellergebnisse und Diskussion 105 5.1 Schäfertal 105 5.1.1 Bodentemperatur 105 5.1.2 Hydrologie 108 5.1.3 Schneeschmelzerosion 113 5.1.4 Sedimentfracht 120 5.2 Lubazhinkha 126 5.2.1 Hydrologie 126 5.2.2 Schneeschmelzerosion 133 5.2.3 Sedimentfracht 137 6 Szenariorechnungen 143 6.1 Klimaszenarien Schäfertal 143 6.1.1 Szenarienauswahl 143 6.1.2 Modellergebnisse und Diskussion 148 6.2 Landnutzungsszenarien Lubazhinkha 158 6.2.1 Szenarienauswahl 158 6.2.2 Modellergebnisse und Diskussion 163 7 Schlussfolgerungen 169 7.1 Einzugsgebiete 169 7.2 Modellsystem IWAN 172 7.3 Szenarien 176 7.4 Forschungsbedarf 178 8 Zusammenfassung 179 9 Summary 189 10 Literatur 199 Appendix 207 Abkürzungen Modellübersicht Quellcode (VBA)
Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease ; The i-Select chips was funded by the French National Foundation on Alzheimer's disease and related disorders. The French National Fondation on Alzheimer's disease and related disorders supported several I-GAP meetings and communications. Data management involved the Centre National de Génotypage,and was supported by the Institut Pasteur de Lille, Inserm, FRC (fondation pour la recherche sur le cerveau) and Rotary. This work has been developed and supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant (Development of Innovative Strategies for a Transdisciplinary approach to ALZheimer's disease) and by the LABEX GENMED grant (Medical Genomics). The French National Foundation on Alzheimer's disease and related disorders and the Alzheimer's Association (Chicago, Illinois) grant supported IGAP in-person meetings, communication and the Alzheimer's Association (Chicago, Illinois) grant provided some funds to each consortium for analyses. EADI The authors thank Dr. Anne Boland (CNG) for her technical help in preparing the DNA samples for analyses. This work was supported by the National Foundation for Alzheimer's disease and related disorders, the Institut Pasteur de Lille and the Centre National de Génotypage. The Three-City Study was performed as part of a collaboration between the Institut National de la Santé et de la Recherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne Regional Councils, Agence Nationale de la Recherche, ANR supported the COGINUT and COVADIS projects. Fondation de France and the joint French Ministry of Research/INSERM «Cohortes et collections de données biologiques» programme. Lille Génopôle received an unconditional grant from Eisai. The Three-city biological bank was developed and maintained by the laboratory for genomic analysis LAG-BRC - Institut Pasteur de Lille. Belgium sample collection: The patients were clinically and pathological characterized by the neurologists Sebastiaan Engelborghs, Rik Vandenberghe and Peter P. De Deyn, and in part genetically by Caroline Van Cauwenberghe, Karolien Bettens and Kristel Sleegers. Research at the Antwerp site is funded in part by the Belgian Science Policy Office Interuniversity Attraction Poles program, the Foundation Alzheimer Research (SAO-FRA), the Flemish Government initiated Methusalem Excellence Program, the Research Foundation Flanders (FWO) and the University of Antwerp Research Fund, Belgium. Karolien Bettens is a postdoctoral fellow of the FWO. The Antwerp site authors thank the personnel of the VIB Genetic Service Facility, the Biobank of the Institute Born-Bunge and the Departments of Neurology and Memory Clinics at the Hospital Network Antwerp and the University Hospitals Leuven. Finish sample collection: Financial support for this project was provided by the Health Research Council of the Academy of Finland, EVO grant 5772708 of Kuopio University Hospital, and the Nordic Centre of Excellence in Neurodegeneration. Italian sample collections: the Bologna site (FL) obtained funds from the Italian Ministry of research and University as well as Carimonte Foundation. The Florence site was supported by grant RF-2010-2319722, grant from the the Cassa di Risparmio di Pistoia e Pescia (Grant 2012) and the Cassa di Risparmio di Firenze (Grant 2012). The Milan site was supported by a grant from the «fondazione Monzino». The authors thank the expert contribution of Mr. Carmelo Romano. The Roma site received financial support from Italian Ministry of Health, Grant RF07-08 and RC08-09-10-11-12. The Pisa site is grateful to Dr. Annalisa LoGerfo for her technical assistance in the DNA purification studies. Spanish sample collection: the Madrid site (MB) was supported by grants of the Ministerio de Educación y Ciencia and the Ministerio de Sanidad y Consumo (Instituto de Salud Carlos III), and an institutional grant of the Fundación Ramón Areces to the CBMSO. The authors thank I. Sastre and Dr. A. Martínez-García for the preparation and control of the DNA collection, and Drs. P. Gil and P. Coria for their cooperation in the cases/controls recruitment. The authors are grateful to the Asociación de Familiares de Alzheimer de Madrid (AFAL) for continuous encouragement and help. Swedish sample collection: Financially supported in part by the Swedish Brain Power network, the Marianne and Marcus Wallenberg Foundation, the Swedish Research Council (521-2010-3134), the King Gustaf V and Queen Victoria's Foundation of Freemasons, the Regional Agreement on Medical Training and Clinical Research (ALF) between Stockholm County Council and the Karolinska Institutet, the Swedish Brain Foundation and the Swedish Alzheimer Foundation. CHARGE AGES: The AGES-Reykjavik Study is funded by National Institutes of Health (NIH) contract N01-AG-12100 (National Institute on Aging (NIA) with contributions from the National Eye Institute, National Institute on Deafness and Other Communication Disorders and National Heart, Lung, and Blood Institute (NHLBI)), the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). ASPS/PRODEM: The Austrian Stroke Prevention Study and The Prospective Dementia Register of the Austrian Alzheimer Society was supported by The Austrian Science Fond (FWF) grant number P20545-P05 (H. Schmidt) and P13180; The Austrian Alzheimer Society; The Medical University of Graz. Cardiovascular Health Study (CHS): This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and HHSN268200960009C; and NHLBI grants HL080295, HL087652, HL105756 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629, AG15928, AG20098, AG027058 and AG033193 (Seshadri) from the NIA. A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Research Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Framingham Heart Study (FHS): This work was supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with A_ymetrix, Inc for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study as also supported by grants from the National Institute on Aging: AG08122 and AG033193 (Seshadri). Drs. Seshadri and DeStefano were also supported by additional grants from the National Institute on Aging: (R01 AG16495; AG031287, AG033040), the National Institute of Neurological Disorders and Stroke (R01 NS17950), and the National Heart, Lung and Blood Institute (U01 HL096917, HL093029 and K24HL038444, RC2-HL102419 and UC2 HL103010. Fundació ACE would like to thank patients and controls who participated in this project. This work has been funded by the Fundación Alzheimur (Murcia), the Ministerio de Educación y Ciencia (PCT-010000-2007-18), (DEX-580000-2008-4), (Gobierno de España), Corporación Tecnológica de Andalucía (08/211) and Agencia IDEA (841318) (Consejería de Innovación, Junta de Andalucía). The authors thank to Ms. Trinitat Port-Carbó and her family for their generous support of Fundació ACE research programs. The Rotterdam Study: The Rotterdam Study was funded by Erasmus Medical Center and Erasmus University, Rotterdam; the Netherlands Organization for Health Research and Development; the Research Institute for Diseases in the Elderly; the Ministry of Education, Culture and Science; the Ministry for Health, Welfare and Sports; the European Commission;and the Municipality of Rotterdam; by grants from the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), Internationale Stichting Alzheimer Onderzoek, Hersenstichting Nederland, the Netherlands Genomics Initiative–Netherlands Organization for Scientific Research (Center for Medical Systems Biology and the Netherlands Consortium for Healthy Aging), the Seventh Framework Program (FP7/2007-2013), the ENGAGE project (grant agreement HEALTH-F4-2007-201413), MRACE-grant from the Erasmus Medical Center, the Netherlands Organization for Health Research and Development (ZonMW Veni-grant no. 916.13.054). ARIC: The Atherosclerosis Risk in Communities Study (ARIC) is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01- HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022 and grants R01-HL087641, RC2-HL102419 (Boerwinkle, CHARGE-S), UC2 HL103010, U01-HL096917 (Mosley) and R01-HL093029; NHGRI contract U01- HG004402; and NIH contract HHSN268200625226C and NIA: R01 AG033193 (Seshadri). Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. GERAD Cardiff University was supported by the Wellcome Trust, Medical Research Council (MRC), Alzheimer's Research United Kingdom (ARUK) and the Welsh Government. ARUK supported sample collections at the Kings College London, the South West Dementia Bank, Universities of Cambridge, Nottingham, Manchester and Belfast. The Belfast group acknowledges support from the Alzheimer's Society, Ulster Garden Villages, N. Ireland R & D Office and the Royal College of Physicians/Dunhill Medical Trust. The MRC and Mercer's Institute for Research on Ageing supported the Trinity College group. DCR is a Wellcome Trust Principal Research fellow. The South West Dementia Brain Bank acknowledges support from Bristol Research into Alzheimer's and Care of the Elderly. The Charles Wolfson Charitable Trust supported the OPTIMA group. Washington University was funded by NIH grants, Barnes Jewish Foundation and the Charles and Joanne Knight Alzheimer's Research Initiative. Patient recruitment for the MRC Prion Unit/UCL Department of Neurodegenerative Disease collection was supported by the UCLH/UCL Biomedical Centre and their work was supported by the NIHR Queen Square Dementia BRU. LASER-AD was funded by Lundbeck SA. The Bonn group would like to thank Dr. Heike Koelsch for her scientific support. The Bonn group was funded by the German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant number 01GI0102, 01GI0711, 01GI0420. The AgeCoDe study group was supported by the German Federal Ministry for Education and Research grants 01 GI 0710, 01 GI 0712, 01 GI 0713, 01 GI 0714, 01 GI 0715, 01 GI 0716, 01 GI 0717. The Homburg group was funded by the German Federal Ministry of Education and Research (BMBF): German National Genome Research Network (NGFN); Alzheimer's disease Integrated Genome Research Network; AD-IG: 01GS0465. Genotyping of the Bonn case-control sample was funded by the German centre for Neurodegenerative Diseases (DZNE), Germany. The GERAD Consortium also used samples ascertained by the NIMH AD Genetics Initiative. Harald Hampel was supported by a grant of the Katharina-Hardt-Foundation, Bad Homburg vor der Höhe, Germany. The KORA F4 studies were financed by Helmholtz Zentrum München; German Research Center for Environmental Health; BMBF; German National Genome Research Network and the Munich Center of Health Sciences. The Heinz Nixdorf Recall cohort was funded by the Heinz Nixdorf Foundation (Dr. Jur. G.Schmidt, Chairman) and BMBF. Coriell Cell Repositories is supported by NINDS and the Intramural Research Program of the National Institute on Aging. The authors acknowledge use of genotype data from the 1958 Birth Cohort collection, funded by the MRC and the Wellcome Trust which was genotyped by the Wellcome Trust Case Control Consortium and the Type-1 Diabetes Genetics Consortium, sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Allergy and Infectious Diseases, National Human Genome Research Institute, National Institute of Child Health and Human Development and Juvenile Diabetes Research Foundation International. The Nottingham Group (KM) are supported by the Big Lottery. MRC CFAS is part of the consortium and data will be included in future analyses. ADGC The National Institutes of Health, National Institute on Aging (NIH-NIA) supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, R01 AG041797; MIRAGE R01 AG025259; Banner Sun Health Research Institute P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, and UL1 RR029893; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653, AG041718; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duke University Medical Center is funded by NINDS grant # NS39764, NIMH MH60451 and by Glaxo Smith Kline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG034504 to AJM, The Banner Alzheimer's Foundation, The Johnnie B. Byrd Sr. Alzheimer's Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resource (funding via the Medical Research Council, local NHS trusts and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England (HEFCE), Alzheimer's Research Trust (ART), BRACE as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, Universitat de Barcelona. Marcelle Morrison-Bogorad, PhD., Tony Phelps, PhD and Walter Kukull PhD are thanked for helping to co-ordinate this collection. ADNI Funding for ADNI is through the Northern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, Glaxo-SmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer's Association, Alzheimer's Drug Discovery Foundation, the Dana Foundation, and by the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, K01 AG030514. Data collection and sharing for this project was funded by the ADNI (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514. The authors thank Drs. D. Stephen Snyder and Marilyn Miller from NIA who are ex-o_cio ADGC members. Support was also from the Alzheimer's Association (LAF, IIRG-08-89720; MP-V, IIRG-05-14147) and the United States Department of Veterans Affairs Administration, Office of Research and Development, Biomedical Laboratory Research Program. Peter St George-Hyslop is supported by Wellcome Trust, Howard Hughes Medical Institute, and the Canadian Institute of Health
PUBLISHED ; BACKGROUND: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p?=?1.4?10-6) and 14 (IGHV1-67 p?=?7.9?10-8) which indexed novel susceptibility loci. SIGNIFICANCE: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease. ; The i-Select chips was funded by the French National Foundation on Alzheimer?s disease and related disorders. The French National Fondation on Alzheimer?s disease and related disorders supported several I-GAP meetings and communications. Data management involved the Centre National de Ge ? notypage,and was supported by the Institut Pasteur de Lille, Inserm, FRC (fondation pour la recherche sur le cerveau) and Rotary. This work has been developed and supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant (Development of Innovative Strateg ies for a Transdisciplinary approach to ALZheimer?s disease) and by the LABEX GENMED grant (Medical Genomics). The French National Foundation on Alzheimer? s disease and related disorders and the Alzheimer?s Association (Chicago, Illinois) grant supported IGAP in-person meetings, communication and the Alzheim er?s Association (Chicago, Illinois) grant provided some funds to each consortium for analyses. EADI The authors thank Dr. Anne Boland (CNG) for her techn ical help in preparing the DNA samples for analyses. This work was supported by the National Foundation for Alzheimer?s disease and related disorders, the Instit ut Pasteur de Lille and the Centre National de Ge ? notypage. The Three-City Study was performed as part of a collaboration between the Institut National de la Sante ? et de la Recherche Me ? dicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthe ? labo. The Fondation pour la Recherche Me ? dicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salarie ? s, Direction Ge ? ne ? rale de la Sante ? , MGEN, Institut de la Longe ? vite ? , Agence Franc ?aise de Se ? curite ? Sanitaire des Produits de Sante ? , the Aquitaine and Bourgogne Regional Councils, Agence Nationale de la Recherche, ANR supported the COGINUT and COVADIS projects. Fondation de France and the joint French Ministry of Research/INSERM ?Cohortes et collec tions de donne ? es biologiques? programme. Lille Ge ? nopo ? le received an unconditional grant from Eisai. The Three-city biological bank was developed and maintained by the laboratory for genomic analysis LAG-BRC - Institut Pasteur de Lille. Belgium sample collection: The patients were clinically and pathologica l characterized by the neurologists Sebastiaan Engelborghs, Rik Vandenberghe and Peter P. De Deyn, and in part genetically by Caroline Van Cauwenberghe, Karolien Be ttens and Kristel Sleegers. Research at the Antwerp site is funded in part by the Belgian Science Policy Office Interuniversity Attraction Poles program, t he Foundation Alzheimer Research (SAO-FRA), the Flemish Government initiated Methusalem Excellence Program, the Research Foundation Flanders (FWO) and the Uni versity of Antwerp Research Fund, Belgium. Karolien Bettens is a postdoctoral fellow of the FWO. The Antwerp site authors thank the personnel of the VIB Genetic S ervice Facility, the Biobank of the Institute Born-Bunge and the Departments of Neurology and Memory Clinics at the Hospital Network Antwerp and the Univers ity Hospitals Leuven. Finish sample collection: Financial support for this project was provided by the Health Research Council of the Academy of Finland , EVO grant 5772708 of Kuopio University Hospital, and the Nordic Centre of Excellence in Neurodegeneration. Italian sample collections: the Bologna site (FL) obtained funds from the Italian Ministry of research and University as well as Carimonte Foundation. The Florence site was supported by grant RF-2010-2319722, gran t from the the Cassa di Risparmio di Pistoia e Pescia (Grant 2012) and the Cassa di Risparmio di Firenze (Grant 2010 ?fondazione Monzino?. The authors thank the expert contribution of Mr. Carmelo Romano. The Roma site received financial support from Italian Minist ry of Health, Grant RF07-08 and RC08-09-10-11-12. The Pisa site is grateful to Dr. Annalisa LoGerfo for her technical assistance in the DNA purification st udies. Spanish sample collection: the Madrid site (MB) was supported by grants of the Ministerio de Educacio ? n y Ciencia and the Ministerio de Sanidad y Consumo (Instituto de Salud Carlos III), and an institutional grant of the Fundacio ? n Ramo ? n Areces to the CBMSO. The authors thank I. Sastre and Dr. A. Mart? ? nez-Garc? ? afor the preparation and control of the DNA collection, and Drs. P. Gil and P. Coria for their cooperation in the cases/controls recruitment. The authors ar e grateful to the Asociacio ? n de Familiares de Alzheimer de Madrid (AFAL) for continuous encouragement and help. Swedish sample collection: Financially supported in part by the Swedish Brain Power network, the Marianne and Marcus Wallenberg Foundation, the Swedish Research Council (521-2010-3134), the King Gust af V and Queen Victoria?s Foundation of Freemasons, the Regional Agreement on Medical Training and Clinical Research (ALF) between Stockholm County Cou ncil and the Karolinska Institutet, the Swedish Brain Foundation and the Swedish Alzheimer Foundation. CHARGE AGES: The AGES-Reykjavik Study is funded b y National Institutes of Health (NIH) contract N01-AG-12100 (National Institute on Aging (NIA) with contributions from the National Eye Institute, N ational Institute on Deafness and Other Communication Disorders and National Heart, Lung, and Blood Institute (NHLBI)), the NIA Intramural Research Progra m, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). ASPS/PRODEM: The Austrian Stroke Prevention Study an d The Prospective Dementia Register of the Austrian Alzheimer Society was supported by The Austrian Science Fond (FWF) grant number P20545-P05 (H. Schmid t) and P13180; The Austrian Alzheimer Society; The Medical University of Graz. Cardiovascular Health Study (CHS): This CHS research was supported by NH LBI contracts HHSN268201200036C, HHSN268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, and HHSN268200960009C; and NHLBI grants HL080295, HL087652, HL105756 with additional contribution from the National Institute of Neurological Disor ders and Stroke (NINDS). Additional support was provided through AG023629, AG15928, AG20098, AG027058 and AG033193 (Seshadri) from the NIA. A full list of CH S investigators and institutions can be found at http://www.chs-nhlbi.org/pi. The provision of genotyping data was supported in part by the National Center for Advancing Translational Sciences, CTSI grant UL1TR000124, and the National Institute of Diabetes and Digestive and Kidney Disease Diabetes Resear ch Center (DRC) grant DK063491 to the Southern California Diabetes Endocrinology Research Center. Framingham Heart Study (FHS): This work was supported by th e National Heart, Lung and Blood Institute?s Framingham Heart Study (Contract No. N01-HC-25195) and its contract with A_ymetrix, Inc for genotyping s ervices (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evan s Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. This study as also supported by grants from the National Institute on Aging: AG08122 and AG033193 (Seshadri). Drs. Seshadri and DeStefano were also supported by additional grants from the Nati onal Institute on Aging: (R01 AG16495; AG031287, AG033040), the National Institute of Neurological Disorders and Stroke (R01 NS17950), and the National Heart, Lung and Blood Institute (U01 HL096917, HL093029 and K24HL038444, RC2-HL102419 and UC2 HL103010. Fundacio ? ACE would like to thank patients and controls who participated in this project. This work has been funded by the Fundacio ? n Alzheimur (Murcia), the Ministerio de Educacio ? n y Ciencia (PCT-010000- 2007-18), (DEX-580000-2008-4), (Gobierno de Espan ? a), Corporacio ? n Tecnolo ? gica de Andaluc? ? a (08/211) and Agencia IDEA (841318) (Consejer? ? a de Innovacio ? n, Junta de Andaluc? ? a). The authors thank to Ms. Trinitat Port-Carbo ? and her family for their generous support of Fundacio ? ACE research programs. The Rotterdam Study: The Rotterdam Study was funded by Erasmus Medical Center and Erasmus University, Rotterdam; the Netherlands Organization for Health Researc h and Development; the Research Institute for Diseases in the Elderly; the Ministry of Education, Culture and Science; the Ministry for Health, Welfare an d Sports; the European Commission;and the Municipality of Rotterdam; by grants from the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), Inte rnationale Stichting Alzheimer Onderzoek, Hersenstichting Nederland, the Netherlands Genomics Initiative?Netherlands Organization for Scientific Resea rch (Center for Medical Systems Biology and the Netherlands Consortium for Healthy Aging), the Seventh Framework Program (FP7/2007-2013), the ENGAGE project (gra nt agreement HEALTH-F4-2007-201413), MRACE-grant from the Erasmus Medical Center, the Netherlands Organization for Health Research and Developmen t (ZonMW Veni-grant no. 916.13.054). ARIC: The Atherosclerosis Risk in Communities Study (ARIC) is carried out as a collaborative study supported by N ational Heart, Lung, and Blood Institute contracts N01-HC-55015, N01-HC-55016, N01-HC-55018, N01- HC-55019, N01-HC-55020, N01-HC-55021, N01-HC-55022 and grants R01-HL087641, RC2-HL102419 (Boerwinkle, CHARGE-S), UC2 HL103010, U01-HL096917 (Mosley) and R01-HL093029; NHGRI contract U01- HG004402; and NIH contract HHSN268200625226C and NIA: R01 AG033193 (Seshadri). Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. GERAD Cardiff University was supported by the Wellcome Trust, Medical Resear ch Council (MRC), Alzheimer?s Research United Kingdom (ARUK) and the Welsh Government. ARUK supported sample collections at the Kings College London, the South West Dementia Bank, Universities of Cambridge, Nottingham, Manchester and Belfast. The Belfast group acknowledges support from the Alzheime r?s Society, Ulster Garden Villages, N. Ireland R & D Office and the Royal College of Physicians/Dunhill Medical Trust. The MRC and Mercer?s Institute for Research on Ageing supported the Trinity College group. DCR is a Wellcome Trust Principal Research fellow. The South West Dementia Brain Bank acknowledges suppo rt from Bristol Research into Alzheimer?s and Care of the Elderly. The Charles Wolfson Charitable Trust supported the OPTIMA group. Washington Univers ity was funded by NIH grants, Barnes Jewish Foundation and the Charles and Joanne Knight Alzheimer?s Research Initiative. Patient recruitment for the MRC Pr ion Unit/ UCL Department of Neurodegenerative Disease collection was supported by the UCLH/UCL Biomedical Centre and their work was supported by the NIHR Queen Square Dementia BRU. LASER-AD was funded by Lundbeck SA. The Bonn group would like to thank Dr. Heike Koelsch for her scientific support. The Bonn group was funded by the German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant number 01GI0102, 01GI0711, 01GI0420. The AgeCoDe study group was supported by the German Federal Ministry for Education and Research grants 01 GI 0710, 01 GI 0712, 01 GI 0713, 01 GI 0714, 01 GI 0715, 01 GI 0716, 01 GI 0717. The Homburg group was funded by the German Federal Ministry of Education and Research (BMBF): German National Genome Research Network (NGFN); Alzheimer?s disease Integrated Genome Research Network; AD-IG: 01GS0465. Genotyping of the Bonn case-control sample was funded by the German centre for Neurodegenerative Diseases (DZNE), Germany. The GERAD Consortium also used samples ascertained by the NIMH AD Genetics Initiative. Harald Hampel was supported by a grant of the Katharina-Hardt-Foundation, Bad Homburg vor der Ho ? he, Germany. The KORA F4 studies were financed by Helmholtz Zentrum Mu ? nchen; German Research Center for Environmental Health; BMBF; German National Genome Research Network and the Munich Center of Health Sciences. The Heinz Nixdorf Recall cohort was funded by the Heinz Nixdorf Foundation (Dr. Jur. G.Schmidt, Chairman) and BMBF. Coriell Cell Repositories is supported by NINDS and the Intramural Research Program of the National Institute on Agin g. The authors acknowledge use of genotype data from the 1958 Birth Cohort collection, funded by the MRC and the Wellcome Trust which was genotyped by the Wellcome Trust Case Control Consortium and the Type-1 Diabetes Genetics Consortium, sponsored by the National Institute of Diabetes and Digestive a nd Kidney Diseases, National Institute of Allergy and Infectious Diseases, National Human Genome Research Institute, National Institute of Child Hea lth and Human Development and Juvenile Diabetes Research Foundation International. The Nottingham Group (KM) are supported by the Big Lottery. MRC CFAS is part of the consortium and data will be included in future analyses. ADGC The National Institutes of Health, National Institute on Aging (NIH-NIA) supported thi s work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, R01 AG041797; MIRAGE R01 AG025259; Banner Sun Health Research Institute P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, UO1 AG06781, UO1 HG004610; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688 ; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, and UL1 RR029893; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R 01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of Californ ia, Irvine, P50 AG016573, P50, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Die go, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383; University of Michigan, P50 A G008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653, AG041718; University of Southern California, P50 AG0 05142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washing ton, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991. The Kathleen Price Bryan Brain Bank at Duk e University Medical Center is funded by NINDS grant # NS39764, NIMH MH60451 and by Glaxo Smith Kline. Genotyping of the TGEN2 cohort was supported by Kronos Science. The TGen series was also funded by NIA grant AG034504 to AJM, The Banner Alzheimer?s Foundation, The Johnnie B. Byrd Sr. Alzheimer?s Institute, the Medical Research Council, and the state of Arizona and also includes samples from the following sites: Newcastle Brain Tissue Resourc e (funding via the Medical Research Council, local NHS trusts and Newcastle University), MRC London Brain Bank for Neurodegenerative Diseases (funding via the Medical Research Council), South West Dementia Brain Bank (funding via numerous sources including the Higher Education Funding Council for England (HEFCE) , Alzheimer?s Research Trust (ART), BRACE as well as North Bristol NHS Trust Research and Innovation Department and DeNDRoN), The Netherlands Brain Bank (funding via numerous sources including Stichting MS Research, Brain Net Europe, Hersenstichting Nederland Breinbrekend Werk, International Par kinson Fonds, Internationale Stiching Alzheimer Onderzoek), Institut de Neuropatologia, Servei Anatomia Patologica, Universitat de Barcelona. Marcel le Morrison- Bogorad, PhD., Tony Phelps, PhD and Walter Kukull PhD are thanked for helping to co-ordinate this collection. ADNI Funding for ADNI is through the Nort hern California Institute for Research and Education by grants from Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Globa l Clinical Development, Elan Corporation, Genentech, GE Healthcare, Glaxo-SmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc, F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., Alzheimer?s Association, Alzheimer?s Drug Discovery Foun dation, the Dana Foundation, and by the National Institute of Biomedical Imaging and Bioengineering and NIA grants U01 AG024904, RC2 AG036535, K01 AG030514. Data collection and sharing for this project was funded by the ADNI (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Insti tute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer?s Assoc iation; Alzheimer?s Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc. ; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V.; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Sc ale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharm aceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are fa cilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research an d Education, and the study is coordinated by the Alzheimer?s Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by th e Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG03051 4. The authors thank Drs. D. Stephen Snyder and Marilyn Miller from NIA who are ex-o_cio ADGC members. Support was also from the Alzheimer?s Association (LAF, IIRG-08-89720; MP-V, IIRG-05-14147) and the United States Department of Veterans Affairs Administration, Office of Research and Developmen t, Biomedical Laboratory Research Program. Peter St George-Hyslop is supported by Wellcome Trust, Howard Hughes Medical Institute, and the Canadian Institute of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
This guide accompanies the following article: Doreen Anderson‐Facile and Shyanne Ledford, 'Basic Challenges to Prisoner Reentry', Sociology Compass 3/2 (2009): 183–195, 10.1111/j.1751‐9020.2009.00198.xAuthor's IntroductionCrime, incarceration and prisoner reintegration are pressing issues facing the United States today. As the prison population grows at record rates so, in turn, does the reentry of prisoners into society. The transition from prison to the outside world is often difficult for post‐release prisoners, their families, their communities and the larger society. Many formally incarcerated individuals do not have the skills or support to succeed outside prison walls. Unfortunately, when post‐release prisoners are not successfully reintegrated, they are often returned to prison and begin the cycle of incarceration.The following is a course designed around the basic challenges prisoners face upon reentry. The literature suggests that success depends in part on support and overcoming several barriers, such as homelessness and under/unemployment. This course begins with an examination of reentry barriers facing post‐release prisoners followed by an exploration of the relationship between prisoner reentry, race, gender, family, and employment and concludes with an assessment of ongoing research and public policy.Author RecommendsAnderson‐Facile, Doreen. (2009). 'Basic Challenges to Prisoner Reentry'. Sociology Compass, 3(2): 183–95.Anderson‐Facile's review of current research on prisoner reentry yields interesting results. Her article examines prisoner reentry as it relates to the barriers preventing successful reintegration. Anderson‐Facile begins with a look at incarceration and recidivism statistics leading readers through the barriers preventing reentry success. Barriers such as housing, family and community support, employment, and the stigma of a prison record make successful reentry difficult. Anderson‐Facile concludes with a look at current reentry programs. Anderson‐Facile highlights literature suggesting post‐release success begins with rehabilitation and ends with community support. The author notes that many successful programs are faith or character‐based. These programs focus on the individual and assist in substance abuse issues, vocational training, and transitional living arrangements. Finally, Anderson‐Facile notes that programs that work in one community may not show success in other communities, therefore concluding that matching programs with communities is a critical component for assuring post‐release success.Dhami, Mandeep K., David R. Mandel, George Loewesnstein, and Peter Ayton. (2006). 'Prisoners' Positive Illusions of Their Post‐Release Success'. Law and Human Behavior30: 631–47.Dhami et al. examine prisoners' forecasts of reentry success as this may have implications for how prisoners respond to imprisonment, release, and parole decisions. The authors examine sentenced US and UK prisoners' predictions for personal recidivism. The authors also asked UK prisoners how successful they will be compared to the average prisoner. Overall, both samples yielded overly optimistic, unrealistic beliefs about personal reentry success when compared to official data. The UK participants demonstrated a self‐enhancement bias by expressing that they would fair far better than the average prisoner. The authors conclude their article by discussing the implications of their findings and suggest future research possibilities.Holzer, Harry J., Steven Raphael, and Michael A. Stoll. (2002). 'Can Employers Play a More Positive Role in Prisoner Reentry? Urban Institute's Reentry Roundtable'.The authors report that in the early 21st century over 600 000 prisoners were released each year from prison and three million or more ex‐prisoners were in the general population. Holzer et al. indicate that one of the greatest hurdles for a newly released prisoner is finding employment because, as applicants, they are faced with an aversion on the employers part to hiring ex‐offenders. Holzer et al. explore the extent and nature of this aversion. Holzer et al. maintain that interventions by other agencies can help mediate employer aversions to hiring post‐release prisoners.La Vigne, Nancy G., Diana Brazzell, and Kevonne M. Small. (2007). 'Evaluation of Florida's Faith‐ and Character‐Based Institutions'. The Urban Institute.La Vigne et al. produced a summary of the findings from a 'process and impact' evaluation of two of Florida's faith and character‐based programs, also known as FCBIs. The authors' note that FCBIs are founded on principles of self‐betterment and faith development and are often ran by volunteers. The authors gathered data in the following ways: one on one interviews, semi structured interviews with staff members at all levels, focus groups with inmates, administrative data/official documents, and telephone and email communications with state corrections personnel. The authors noted that at six months, male FCBI housed participants were more successful than post‐released prisoners housed in Federal Department of Corrections (FDOC) facilities.La Vigne, Nancy G., Rebecca L. Naser, Lisa E. Brooks, and Jennifer L. Castro. (2005). 'Examining the Effect of Incarceration and In‐Prison Family Contact on Prisoners' Family Relationships'. Journal of Contemporary Criminal Justice21(4): 314–35.In this article, La Vigne, Naser, Brooks and Castro look at the role of the family in recidivism rates. Specifically, they examine the role of in‐prison contact with family members on released prisoner success. This article first defines family and then looks at the quality of familial bonds at imprisonment and during incarceration. Next, they examine the inter‐personal bonds in relationships, i.e., parent–child vs. husband‐wife of these post‐released prisoners. The authors' findings were inconsistent. For example, in some situations in‐prison contact was detrimental on family relationships and ties, wherein other cases the same contact served to strengthen the family and create a tighter network of family support for the newly released prisoner. These findings suggest further research is necessary.Pager, D. (2003). 'The Mark of a Criminal Record'. The American Journal of Sociology108(5): 937–75.Pager examined the relationship between prior incarceration and race on employment on two teams of subjects. One team consisted of two 23‐year‐old, white men and the other team was two 23‐year‐old, African‐American men. The two teams were nearly identical in personality, appearance, skills and employment history. The variables were race and criminal record. The findings suggest that race and employment history are important factors on post‐released employment. Thirty‐four percent of white applicants without criminal backgrounds received a call back while only 14 percent of black applicants without criminal backgrounds got called back. Seventeen percent of white applicants with criminal records received call backs while only 5 percent of black applicants with criminal records received call backs. These findings indicate that race and not prison record is a greater determinant of employment.Parsons, Mickey L. and Carmen Warner‐Robbins. (2002). 'Factors That Support Women's Successful Transition to the Community Following Jail/ Prison'. Health Care for Women International23: 6–18.Parson and Warner‐Robbins simply state the purpose of their article is to describe the factors that support the successful reentry of post‐release women into the community. The authors look at a specific program called Welcome Home Ministries (WHM), a community‐based program. The authors examine the demographics of the population, the rising incarceration rates, issues that lead to incarceration, and support for post‐release mothers. Through qualitative interviews with women who were participating in WHM programs upon release many themes emerged. The authors argue that these themes lead to implications about what future programs need to support women who are transitioning from prisoner to general public.Seiter, Richard P. and Karen R. Kadela. (2003) 'Prisoner Reentry: What Works, What Does Not, and What is Promising'. Crime and Delinquency49(3): 360–88.Seiter and Kadela examine the nature of the reentry issue and explore which reentry programs show success in reducing recidivism. The authors note a swing from modified sentencing to determinate sentencing which increases length of incarceration as an additional factor in successful reentry. Seiter and Kadela define reentry, categorize programs for prisoner reentry, and use the Maryland Scale of Scientific Method to determine program effectiveness. The authors find that programs that emphasized vocational training and employment development yield the most success.Travis, Jeremy and Joan Petersilia. (2001). 'Reentry Reconsidered: A New Look at an Old Question'. Crime and Delinquency47(3): 291–313.Travis and Petersilia drive prison reform by providing research‐based implications for revamping the current system of prisoner management. While prisoners have always been arrested and released, the authors point out that the numbers of both are increasing. They believe this is a call to action. Travis and Petersilia look at changing sentencing policies, changes in parole supervision, and how the removal and return of prisoners influence communities. The authors highlight the astronomical increase of prisoners at a time when sentencing policies are changing and are often inconsistent. They examine parole, the demographics of transitioning inmates, and the links between reentry and five social policies. The findings provide guidance for development of reentry policies.Wacquant, Loic. (2002). 'Deadly Symbiosis: Rethinking Race and Imprisonment in Twenty‐ First‐Century America'. Boston Review27(2): 22–31.Waquant begins his article with three abrupt facts about racial inequality and imprisonment in the United States all of which point to a 'blackening' of the nations prisons. The author points out that the high percentage of black people incarcerated in the United States is a direct result of four institutions; slavery, the Jim Crow System, the organizational structure of urban ghettos and the growing prison system. One of the main findings, according to Waquant, is that when laws and social reform restricted segregation (technically ended), the prisons picked up where society left off. Essentially he argues that, as evidenced by the ghettos and increasing numbers of African‐Americans behind bars, the prison serves to reaffirm racial inequality.Online MaterialsDepartment of Justice http://www.usdoj.gov/Urban Institute http://www.urban.org/California Departmen of Corrections and Rehabilitation http://www.cdcr.ca.gov/Bureau of Justice Statistics http://www.ojp.usdoj.gov/bjsLloyd Sealy Library at John Jay College http://www.lib.jjay.cuny.edu/Pew Center http://www.pewresearch.org/Sample Syllabus Week 1: Introduction to Prisoner Reentry Anderson‐Facile, Doreen. (2009). 'Basic Challenges to Prisoner Reentry'. Sociology Compass 3/2: 183–95.Visher, Christy A. and Jeremy Travis. (2003). 'Transitions from Prison to Community: Understanding Individual Pathways'. Annual Review of Sociology29: 89–113. Week 2: Introduction to Prisoner Reentry Continued Travis, Jeremy and Joan Petersilia. (2001). 'Reentry Reconsidered: A New Look at an Old Question.'Crime and Delinquency 47/3: 291–313.The Urban Institute. 'Beyond the Prison Gates: The State of Parole in America. A First Tuesday Forum.'http://www.urban.org/url.cfm?ID=900567, November 5, 2002. Week 3: Incarceration, Reentry, and Race Pettit, Becky, and Bruce Western. (2004). 'Mass Imprisonment and the Life Course: Race and Class Inequality in US Incarceration.'American Sociological Review69: 151–169.Wacquant, Loic. (2002). 'Deadly Symbiosis: Rethinking race and Imprisonment in twenty‐first‐century America'. Boston Review 27/2 (April/May): 22–31.Marbley, Aretha Faye and Ralph Ferguson. (2005). 'Responding to Prisoner Reentry, Recidivism, and Incarceration of Inmates of Color: A Call to the Communities'. Journal of Black Studies 35/5(May): 633–49. Week 4: Incarceration, Reentry, and Gender O'Brien, Patricia. (2007). 'Maximizing Success for Drug‐Affected Women after Release from Prison: Examining Access to and Use of Social Services During Reentry'. Women & Criminal Justice 17/2&3: 95–113.Severance, Theresa A. (2004). 'Concerns and Coping Strategies of Women Inmates Concerning Release: 'It's Going to Take Somebody in My Corner"'. Journal of Offender Rehabilitation 38/4: 73–97.Parsons, Mickey L. and Carmen Warner‐Robbins. (2002). 'Factors that Support Women's Successful Transition to the Community Following Jail/ Prison.'Health Care for Women International23: 6–18. Week 5: Incarceration, Reentry, and Family/ Home La Vigne, Nancy G., Rebecca L. Naser, Lisa E. Brooks, and Jennifer L. Castro. (2005). 'Examining the Effect of Incarceration and In‐Prison Family Contact on Prisoners' Family Relationships'. Journal of Contemporary Criminal Justice 21/4 (November): 314–35.Pearson, Jessica and Lanae Davis. (2003). 'Serving Fathers Who Leave Prison'. Family Court Review 41/3(July): 307–20.Roman, Caterina Gouvis and Jeremy Travis. (2004). 'Taking Stock: Housing, Homelessness, and Prisoner Reentry,'The Urban Institute.http://www.urban.org/url.cfm?ID=411096, March 8, 2004. Week 6: Incarceration, Reentry, and Employment Pager, Devah. (2003). 'The Mark of a Criminal Record,'American Journal of Sociology 108/5 (March): 937–75.Solomon, Amy L., Kelly Dedel Johnson, Jeremy Travis, and Elizabeth C. McBride. (2004). 'From Prison to Work: The Employment Dimensions of Prisoner Reentry'. Urban Institute Justice Policy Center. October 2004, pp. 1–32. Week 7: Incarceration, Reentry, and Employment Continued Holzer, Harry J., Steven Raphael, and Michael A. Stoll. (2002). 'Can Employers Play a More Positive Role in Prisoner Reentry? A Roundtable Paper'. The Urban Institute, March 20–21, 2002, pp. 1–16.Harrison, Byron, and Robert Carl Schehr. (2004). 'Offenders and Post‐Release Jobs: Variables Influencing Success and Failure'. Journal of Offender Rehabilitation 39/3: 35–68. Week 8: Prisoner Reentry: What Works? MacKenzie, Doris Layton. (2000). 'Evidence‐Based Corrections: Identifying What Works'. Crime and Delinquency46: 457–71.Petersilia, Joan. (2004). 'What Works in Prisoner Reentry? Reviewing and Questioning Evidence'. Federal Probation 68/2 (September): 4–8.Seiter, Richard P. and Karen R. Kadela. (2003). 'Prisoner Reentry: What Works, What Does Not, and What is Promising,'Crime and Delinquency 49/3 (July): 360–88. Week 9: Incarceration, Reentry, Research and Public Policy Lynch, James P. (2006). 'Prisoner Reentry: Beyond Program Evaluations.'Criminology and Public Policy 5/2: 401–12.Pager, Devah. (2006). 'Evidence‐Based Policy for Successful Prisoner Reentry'. Criminology and Public Policy 5/3: 505–14.La Vigne, Nancy G. Diana Brazzell, and Kevonne M. Small. (2007). 'Evaluation of Florida's Faith‐ and Character‐Based Institutions'. The Urban Institute http://www.urban.org/url.cfm?ID=411561, October 1, 2007.Jacobson, Michael. (2006). 'Reversing the Punitive Turn: The Limits and Promise of Current Research'. Criminology and Public Policy 5/2: 277–84. Week 10: Incarceration, Reentry, and Outcomes Dhami, Mandeep K., David R. Mandel, George Loewenstein, and Peter Ayton. (2006). 'Prisoners Positive Illusions of Their Post‐Release Success'. Law and Human Behavior30: 631–47.Richards, Stephen C., James Austin, and Richard S. Jones. (2004). 'Kentucky's Perpetual Prisoner Machine: It's About Money'. The Review of Policy Research 21/1: 93–106.Suggested ReadingsEvans, Donald G. (2005). 'The Case for Inmate Reentry'. Corrections Today pp. 28–9.Lynch, James P. and William J. Sabol. (2001). 'Prisoner Reentry in Perspective'. Crime Policy Report3: 1–25.'One in 100: Behind Bars in America 2008'. The Pew: Center on the States 2008, pp. 1–35.Petersilia, Joan. (1999). Parole and Prisoner Reentry in the United States, The University of Chicago.Petersilia, Joan (2003). When Prisoners Come Home: Parole and Prisoner Reentry. New York: Oxford University Press. ISBN 0‐19‐516086‐x.Travis, Jeremy, Amy L. Solomon, and Michelle Waul. (2001). 'From Prison to Home: The Dimensions and Consequences of Prisoner Reentry'. The Urban Institute.Young, D. Vernetta and Rebecca Reviere (2006). Women Behind Bars. London: Lynn Rienner Publishers. ISBN 1‐58826‐371‐1.Focus Questions
Think about the kind of crimes for which people are imprisoned. What types of crimes do you think the majority of the prisoners commit? What precursors would lead to someone being arrested and eventually imprisoned for these types of crimes? What is the likelihood that these factors remain upon release? Do you think prison should be rehabilitative or punitive? Do you think prison is always the best option for criminal behavior (in other words, is the old adage 'if you do the crime you need to do the time' valid?). Why are incarceration and recidivism rates different across race and class? How do you explain the disparities in incarceration rates for people of color? What kind of programs, if any, do you feel should be incorporated into a prison sentence (i.e. job training, counseling, AA, NA, religious opportunities, etc.). Suggested Culminating Activity: Students are to design a pilot program to assist prisoners successfully reenter into the community. Students must have the following parts in their report/ presentation: Prison/Community Summary (what population and community do you want to serve), Program Summary and Justification (what is the program – how does it work and why do you think it is a valuable program), Requirements for Participation in Program, Barriers to Success, Assessment/ Measurement of Success/ Failure, and Conclusion. Students must briefly site articles from this course to support their methodologies and indicate the problems they suspect they will face as they try to determine the success or failure of their program. Budgets and money are a non‐issue. In the 'real' world budgets are always an issue but for the purpose of this assignment they are not. However, when designing your program you should consider whether your design is financially feasible.. The goal of such an assignment is for students to recognize the barriers prisoners face to successful reentry, the evidence and research that goes into creating prisoner policies, and that a program must be multi‐faceted and comprehensive in order to provide a platform for former inmate success.
This sample syllabus above is modeled after a 10 week term. It is recommended for longer terms, that the following book be utilized:Irwin, John. (2005). The Warehouse Prison. California: Roxbury Publishing Company.ISBN: 1‐931719‐35‐7.John Irwin derived his data from a prison in Solano County, California. Irwin watched as incarceration rates doubled between 1980 and 2000 despite crime levels staying relatively stable. Irwin notes that most of the prisoners in his study were incarcerated for 'unserious' crimes and were often treated in unethical ways. Irwin begins by examining incarceration rates, the demographics of the prison population, problems prisoners faced while incarcerated, post‐release difficulties and hurdles, and the societal costs of the prison super‐structure. Irwin offers a thorough examination of why prisoners are incarcerated, what they face while inside prison walls, what challenges they face once released, and the financial implications of imprisoning people.
With a high availability of lignocellulosic biomass and various types of cellulosic by-products, as well as a large number of industries, Sweden is a country of great interest for future large scale production of sustainable, next generation biofuels. This is most likely also a necessity as Sweden has the ambition to be independent of fossil fuels in the transport sector by the year 2030 and completely fossil free by 2050. In order to reach competitive biofuel production costs, plants with large production capacities are likely to be required. Feedstock intake capacities in the range of about 1-2 million tonnes per year, corresponding to a biomass feed of 300-600 MW, can be expected, which may lead to major logistical challenges. To enable expansion of biofuel production in such large plants, as well as provide for associated distribution requirements, it is clear that substantial infrastructure planning will be needed. The geographical location of the production plant facilities is therefore of crucial importance and must be strategic to minimise the transports of raw material as well as of final product. Competition for the available feedstock, from for example forest industries and CHP plants (combined heat and power) further complicates the localisation problem. Since the potential for an increased biomass utilisation is limited, high overall resource efficiency is of great importance. Integration of biofuel production processes in existing industries or in district heating systems may be beneficial from several aspects, such as opportunities for efficient heat integration, feedstock and equipment integration, as well as access to existing experience and know-how. This report describes the development of BeWhere Sweden, a geographically explicit optimisation model for localisation of next generation biofuel production plants in Sweden. The main objective of developing such a model is to be able to assess production plant locations that are robust to varying boundary conditions, in particular regarding energy market prices, policy instruments, investment costs, feedstock competition and integration possibilities with existing energy systems. This report also presents current and future Swedish biomass resources as well as a compilation of three consistent future energy scenarios. BeWhere is based on Mixed Integer Linear Programming (MILP) and is written in the commercial software GAMS, using CPLEX as a solver. The model minimises the cost of the entire studied system, including costs and revenues for biomass harvest and transportation, production plants, transportation and delivery of biofuels, sales of co-products, and economic policy instruments. The system cost is minimised subject to constraints regarding, for example, biomass supply, biomass demand, import/export of biomass, production plant operation and biofuel demand. The model will thus choose the least costly pathways from one set of feedstock supply points to a specific biofuel production plant and further to a set of biofuel demand points, while meeting the demand for biomass in other sectors. BeWhere has previously been developed by the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria and Luleå University of Technology and has been used in several studies on regional and national levels, as well as on the European level. However, none of the previous model versions has included site-specific conditions in existing industries as potential locations for industrially integrated next generation biofuel production. Furthermore, they also usually only consider relatively few different production routes. In this project, bottom-up studies of integrated biofuel production have been introduced into a top-down model and taken to a higher system level, and detailed, site-specific input data of potential locations for integrated biofuel production has been included in the model. This report covers the first stages of model development of BeWhere Sweden. The integration possibilities have been limited to the forest industry and a few district heating networks, and the feedstocks to biomass originating from the forest. The number of biofuel production technologies has also been limited to three gasification-based concepts producing DME, and two hydrolysis- and fermentation-based concepts producing ethanol. None of the concepts considered is yet commercial on the scale envisioned here. Preliminary model runs have been performed, with the main purpose to identify factors with large influence on the results, and to detect areas in need of further development and refinement. Those runs have been made using a future technology perspective but with current energy market conditions and biomass supply and demand. In the next stage of model development different roadmap scenarios will be modelled and analysed. Three different roadmap scenarios that describe consistent assessments of the future development concerning population, transport and motor fuel demands, biomass resources, biomass demand in other industry sectors, energy and biomass market prices etc. have been constructed within this project and are presented in this report. As basis for the scenarios the report "Roadmap 2050" by the Swedish Environmental Protection Agency (EPA) has been used, using 2030 as a target year for the scenarios. Roadmap scenario 1 is composed to resemble "Roadmap 2050" Scenario 1. Roadmap scenario 2 represents an alternative development with more protected forest and less available biomass resources, but a larger amount of biofuels in the transport system, partly due to a higher transport demand compared to Roadmap scenario 1. Finally Roadmap scenario 3 represents a more "business as usual" scenario with more restrictive assumptions compared to the other two scenarios. In total 55 potential biofuel plant sites have been included at this stage of model development. Of this 32 sites are pulp/paper mills, of which 24 have chemical pulp production (kraft process) while eight produce only mechanical pulp and/or paper. Seven of the pulp mills are integrated with a sawmill, and 18 additional stand-alone sawmills are also included, as are five district heating systems. The pulp and paper mills and sawmills are included both as potential biofuel plant sites, as biomass demand sites regarding wood and bioenergy, and as biomass supply sites regarding surplus by-products. District heating systems are considered both regarding bioenergy demand and as potential plant sites. In the preliminary model runs, biofuel production integrated in chemical pulp mills via black liquor gasification (BLG) was heavily favoured. The resulting total number of required production plants and the total biomass feedstock volumes to reach a certain biofuel share target are considerably lower when BLG is considered. District heating systems did not constitute optimal plant locations with the plant positions and heat revenue levels assumed in this study. With higher heat revenues, solid biomass gasification (BMG) with DME production was shown to be potentially interesting. With BLG considered as a production alternative, however, extremely high heat revenues would be needed to make BMG in district heating systems competitive. The model allows for definition of biofuel share targets for Sweden overall, or to be fulfilled in each county. With targets set for Sweden overall, plant locations in the northern parts of Sweden were typically favoured, which resulted in saturation of local biofuel markets and no biofuel use in the southern parts. When biofuels needed to be distributed to all parts of Sweden, the model selected a more even distribution of production plants, with plants also in the southern parts. Due to longer total transport distances and non-optimal integration possibilities, the total resulting system cost was higher when all counties must fulfil the biofuel share target. The total annual cost to fulfil a certain biofuel target would also be considerably higher without BLG in the system, as would the total capital requirement. This however presumes that alternative investments would otherwise be undertaken, such as investments in new recovery boilers. Without alternative investments the difference between a system with BLG and a system without BLG would be less pronounced. In several cases the model located two production plants very close to each other, which would create a high biomass demand on a limited geographic area. The reason is that no restrictions on transport volumes have yet been implemented in the model. Further, existing onsite co-operations between for example sawmills and pulp mills have not always been captured by the input data used for this report, which can cause the consideration of certain locations as two separate plant sites, when in reality they are already integrated. It is also important to point out that some of the mill specific data (obtained from the Swedish Forest Industries Federation's environmental database) was identified to contain significant errors, which could affect the results related to the plant allocations suggested in this report. Due to the early model development stage and the exclusion of for example many potential production routes and feedstock types, the model results presented in this report must be considered as highly preliminary. A number of areas in need of supplementing have been identified during the work with this report. Examples are addition of more industries and plant sites (e.g. oil refineries), increasing the number of other production technologies and biofuels (e.g. SNG, biogas, methanol and synthetic diesel), inclusion of gas distribution infrastructures, and explicit consideration of import and export of biomass and biofuel. Agricultural residues and energy crops for biogas production are also considered to be a very important and interesting completion to the model. Furthermore, inclusion of intermediate products such as torrefied biomass, pyrolysis oil and lignin extracted from chemical pulp mills would make it possible to include new production chains that are currently of significant interest for technology developers. As indicated above, the quality of some input data also needs to be improved before any definite conclusions regarding next generation biofuel plant localisations can be drawn.Due to the early model development stage and the exclusion of for example many potential production routes and feedstock types, the model results presented in this report must be considered as highly preliminary. A number of areas in need of supplementing have been identified during the work with this report. Examples are addition of more industries and plant sites (e.g. oil refineries), increasing the number of other production technologies and biofuels (e.g. SNG, biogas, methanol and synthetic diesel), inclusion of gas distribution infrastructures, and explicit consideration of import and export of biomass and biofuel. Agricultural residues and energy crops for biogas production are also considered to be a very important and interesting completion to the model. Furthermore, inclusion of intermediate products such as torrefied biomass, pyrolysis oil and lignin extracted from chemical pulp mills would make it possible to include new production chains that are currently of significant interest for technology developers. As indicated above, the quality of some input data also needs to be improved before any definite conclusions regarding next generation biofuel plant localisations can be drawn. A further developed BeWhere Sweden model has the potential for being a valuable tool for simulation and analysis of the Swedish energy system, including the industry and transport sectors. The model can for example be used to analyse different biofuel scenarios and estimate cost effective biofuel production plant locations, required investments and costs to meet a certain biofuel demand. Today, concerned ministries and agencies base their analyses primary on results from the models MARKAL and EMEC, but none of these consider the spatial distribution of feedstock, facilities and energy demands. Sweden is a widespread country with long transport distances, and where logistics and localisation of production plants are crucial for the overall efficiency. BeWhere Sweden considers this and may contribute with valuable input that can be used to complement and validate results from MARKAL and EMEC; thus testing the feasibility of these model results. This can be of value for different biofuel production stakeholders as well as for government and policy makers. Further, Sweden is also of considerable interest for future next generation biofuel production from a European perspective. By introducing a link to existing models that operate on a European level, such as BeWhere Europe and the related IIASA model GLOBIOM, BeWhere Sweden could also be used to provide results of value for EU policies and strategies. ; Sverige besitter goda tillgångar på skogsbiomassa och olika typer av cellulosabaserat avfall som potentiellt kan användas till framtida storskalig produktion av nästa generations biodrivmedel. Eftersom Sverige har satt som mål att vara oberoende av fossila bränslen inom transportsektorn år 2030 och helt fossilfritt 2050, är detta förmodligen också en nödvändighet. Att nå konkurrenskraftiga produktionskostnader kommer sannolikt kräva stora biodrivmedelsanläggningar. Ett råvaruintag i spannet 1-2 miljoner ton per år (motsvarande en anläggningskapacitet på 300-600 MW), kan förväntas, vilket innebär stora logistiska utmaningar. För att möjliggöra biodrivmedelsproduktion i så stora anläggningar kommer betydande infrastrukturplanering att vara nödvändigt. Den geografiska placeringen av produktionsanläggningar är därför av avgörande betydelse och måste vara strategisk för att minimera transporterna av såväl råvaror som slutprodukter. Konkurrensen om den tillgängliga råvaran från exempelvis skogsindustrin och kraftvärmesektorn, komplicerar lokaliseringsproblemet ytterligare. Eftersom potentialen för ett ökat biomassautnyttjande är begränsad, är resurseffektiviteten av stor betydelse. Integration av drivmedelsproduktion i befintliga industrier eller fjärrvärmesystem kan vara fördelaktigt ur flera perspektiv. Exempel är möjligheter till effektiv värmeintegrering, integrering av råmaterial och utrustning, samt utnyttjande av befintliga kunskaper och erfarenheter. Denna rapport beskriver utvecklingen av BeWhere Sweden – en geografiskt explicit optimeringsmodell för lokalisering av nästa generations biodrivmedelsproduktion i Sverige. Det främsta syftet med modellen är att kunna identifiera och värdera lokaliseringar som är så robusta som möjligt i förhållande till olika randvillkor, i synnerhet gällande energimarknadsaspekter, styrmedel, investeringskostnader och råvarukonkurrens. I rapporten presenteras också en översikt av nuvarande och framtida biobränsleresurser i Sverige, samt en sammanställning av tre konsekventa framtidsscenarier. BeWhere bygger på blandad heltalsprogrammering (Mixed Integer Linear Programming, MILP) och är skriven i den kommersiella programvaran GAMS, med CPLEX som lösare. Modellen minimerar kostnaden för hela det studerade systemet, inklusive kostnader och intäkter för produktion och transport av biomassa, produktionsanläggningar, transport och leverans av biodrivmedel, försäljning av biprodukter och ekonomiska styrmedel. System-kostnaden minimeras under ett antal olika bivillkor som beskriver till exempel tillgång och efterfrågan på biomassa, import/export av biomassa och biodrivmedel, anläggningsdrift och efterfrågan på biodrivmedel. Modellen kommer således välja de minst kostsamma kombinationerna av råvaror, produktionsanläggningar och leveranser av biodrivmedel, samtidigt som efterfrågan på biomassa i andra sektorer tillgodoses. BeWhere-modellen har tidigare utvecklats vid International Institute for Applied Systems Analysis (IIASA) i Laxenburg, Österrike och vid Luleå Tekniska Universitet, och har använts i ett stort antal studier på regional och nationell nivå, liksom på EU-nivå. Ingen av de tidigare modellerna har dock tagit hänsyn till platsspecifika förhållanden för potentiell integration av biodrivmedelsproduktion i exempelvis industrier. Dessutom har tidigare modeller generellt inkluderat relativt få olika produktionsalternativ. I det här projektet har bottom-up-studier av integrerad biodrivmedelsproduktion introducerats i en top-down-modell och tagits till en högre systemnivå, med beaktande av detaljerade platsspecifika data för de potentiella lägena för integrerad biodrivmedelsproduktion. Denna rapport omfattar de första faserna i modellutvecklingen av BeWhere Sweden. Integrationsmöjligheterna har här begränsats till skogsindustri och ett fåtal fjärrvärmenät, och råvarorna till biomassa som härrör från skogen. Produktionsteknikerna har begränsats till tre förgasningsbaserade koncept för produktion av DME, samt två hydrolys-och jäsningsbaserade koncept för produktion av etanol. Ingen av dessa tekniker är ännu kommersiell i den skala som beaktats i detta projekt. Preliminära modellkörningar har genomförts med det huvudsakliga syftet att identifiera faktorer med stor inverkan på resultaten, samt behov av ytterligare modellutveckling och förbättring. Dessa körningar har gjorts utifrån dagens system, med nuvarande energimarknadsvillkor och tillgång och efterfrågan på biomassa, men med ett framtidsperspektiv gällande tekniker. I nästa steg av modellutvecklingen kommer olika framtidscenarier att modelleras och analyseras. Tre olika scenarier med bedömningar av framtida befolkningsutveckling, transport- och drivmedelsbehov, tillgång och efterfrågan på biomassa i olika samhällssektorer, samt marknadspriser på energi och biomassa, har skapats och presenteras i denna rapport. Naturvårdsverkets rapport "Färdplan 2050" har använts som underlag för scenarierna, men med 2030 som tidsram. Färdplansscenario 1 är sammansatt för att efterlikna Scenario 1 i "Färdplan 2050". Färdplansscenario 2 representerar en alternativ utveckling med mer skyddad skog och färre tillgängliga biomassaresurser, men ed en större mängd biodrivmedel i transportsystemet, delvis beroende på en högre efterfrågan på transporter jämfört med i Färdplansscenario 1. Färdplansscenario 3 är slutligen mer av ett "business as usual"-scenario, med generellt mer restriktiva antaganden jämfört med de andra två scenarierna. Sammanlagt 55 potentiella platser för integrerad biodrivmedelsproduktion har inkluderats i detta skede av modellutvecklingen. Av dessa är 32 massa- och pappersindustrier, varav 24 producerar kemisk massa (sulfatmassa) och åtta tillverkar mekanisk massa och/eller papper. Sju av massabruken är även integrerade med ett sågverk. Ytterligare 18 fristående sågverk är också beaktade, liksom fem fjärrvärmesystem. Massa-och pappersbruken och sågverken ingår i modellen dels som möjliga lokaliseringar för biodrivmedelsproduktion, dels med avseende på biobränslebehov (stamved och/eller energi) som måste tillfredsställas, och dels som producenter av biobränsle (överskott av industriella biprodukter). Fjärrvärmesystemen beaktas både i form av möjliga lägen för integrerad drivmedelsproduktion, och med avseende på behov av bioenergi. I de preliminära modellkörningarna visade sig drivmedelsproduktion integrerat i kemiska massabruk baserat på svartlutsförgasning (BLG) vara särskilt gynnsamt. När BLG beaktades var både det resulterande erforderliga antalet produktionsanläggningar och det totala biobränslebehovet för att uppnå ett visst andelsmål för biodrivmedel i transportsektorn, betydligt lägre än om BLG inte beaktades. Fjärrvärmesystem visade sig generellt inte utgöra optimala lokaliseringar med de system som innefattats och de värmepriser som antagits i denna rapport. Med högre värmeintäkter visade sig att förgasning av fasta biobränslen med DME-produktion kan vara potentiellt intressant. Med BLG-baserad produktion inkluderad som produktionsalternativ skulle dock extremt höga värmepriser behövas för att göra fastbränsleförgasning i fjärrvärmesystem konkurrenskraftigt. I modellen kan mål för andelen biodrivmedel i transportsektorn anges för Sverige som helhet, eller som mål som måste uppfyllas i varje län. När målet angavs övergripande för Sverige gynnades anläggningslokaliseringar i norra Sverige, vilket ledde till mättnad av de lokala biodrivmedelsmarknaderna och ingen biodrivmedelsanvändning i de mer tätt-befolkade södra delarna. Om ett biodrivmedelsmål istället angavs länsvis valde modellen en jämnare geografisk fördelning av produktionsanläggningarna, med anläggningar även i södra Sverige. På grund av längre totala transportavstånd och icke-optimala integrations-möjligheter resulterade detta i en högre total systemkostnad jämfört med när målet angavs för Sverige som helhet. Den totala kostnaden för att uppfylla ett visst biodrivmedelsmål, liksom det totala kapitalbehovet, skulle också vara betydligt högre utan BLG i systemet. Detta förutsätter dock att alternativa investeringar annars skulle ha genomförts, såsom investeringar i nya sodapannor. Utan beaktande av alternativa investeringar skulle skillnaden mellan ett system med BLG och ett system utan BLG, vara mindre. I flera körningar valde modellen två produktionsanläggningar mycket nära varandra, vilket skulle innebära en stor efterfrågan på biomassa på ett begränsat geografiskt område. Anledningen är dels att restriktioner för transportvolymer ännu inte införts i modellen, dels att befintliga samarbeten mellan exempelvis sågverk och massabruk inte alltid fångats av de indata som använts. Detta kan medföra att vissa platser betraktats som två separata anläggningar, när de i verkligheten redan har en hög grad av integrering och därmed borde betraktas som ett läge. Under arbetets gång har en del bruksspecifika data som använts (vilka erhållits från Skogsindustriernas miljödatabas) visat sig innehålla väsentliga felaktigheter. Det är därför viktigt att poängtera att detta kan påverka resultaten gällande de anläggningslokaliseringar som framstår som mest gynnsamma. På grund av modellens tidiga utvecklingsstadium och att ett flertal potentiella produktionsalternativ och råvaror ännu inte inkluderats i modellen, måste de resultat som presenterats i denna rapport betraktas som mycket preliminära. Under arbetet har ett antal områden i behov av komplettering och vidareutveckling identifierats. Exempel är tillägg av både fler industrityper (t.ex. oljeraffinaderier) och fler potentiella anläggningsplatser, utökning av antalet produktionstekniker och drivmedel (t.ex. SNG, biogas, metanol och syntetisk diesel), inkludering av infrastrukturer för gasdistribution, samt explicit hänsyn till import och export av biomassa och biodrivmedel. Restprodukter från jordbruket och energigrödor för biogasproduktion anses också vara ett viktig och intressant tillägg till modellen. Dessutom skulle införandet av intermediärprodukter som torrefierad biomassa, pyrolysolja och lignin från kemiska massabruk göra det möjligt att inkludera ytterligare nya produktionskedjor som för närvarande är av betydande intresse för teknikutvecklare. Som diskuterats ovan behöver kvaliteten på vissa indata också förbättras innan några definitiva slutsatser kan dras om var nästa generations biodrivmedelsproduktion bör vara lokaliserad. En vidareutvecklad BeWhere Sweden-modell har potential att utgöra ett värdefullt verktyg för simulering och analys av det svenska energisystemet, industrin och transportsektorn inkluderade. Modellen kan exempelvis användas för att analysera olika biodrivmedels-scenarier och för att identifiera och utvärdera kostnadseffektiva lokaliseringar för drivmedelsproduktion, nödvändiga investeringar, samt kostnader och biomassabehov för att möta en viss efterfrågan på biodrivmedel. Idag baserar berörda myndigheter primärt sina analyser på resultat från modellerna MARKAL och EMEC. Ingen av dessa modeller tar dock hänsyn till den geografiska fördelningen av råvaror, anläggningar och energi- och råvarubehov. Sverige är ett vidsträckt land med långa transportavstånd där logistik och lokalisering av produktionsanläggningar är avgörande för den totala effektiviteten. BeWhere Sweden beaktar dessa aspekter och kan bidra med värdefulla resultat som kan användas för att i tur komplettera och validera resultat från MARKAL och EMEC, och på så sätt testa implementerbarheten av dessa modellresultat. Detta kan vara av värde för såväl intressenter i biodrivmedelstillverkning, som för myndigheter och politiska beslutsfattare. Vidare är Sverige av stort intresse för framtida tillverkning av nästa generations biodrivmedel även ur ett europeiskt perspektiv. Genom att införa en länk till befintliga modeller som verkar på europeisk nivå, såsom BeWhere Europe och den relaterade IIASA-modellen GLOBIOM, kan BeWhere Sweden också användas för att generera resultat av värde för EU:s politik och strategier.
HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples. ; 3C. Three-City Study. The work was made possible by the participation of the control subjects, the patients, and their families. We thank Dr. Anne Boland (CNG) for her technical help in preparing the DNA samples for analyses. This work was supported by the National Foundation for Alzheimer's disease and related disorders, the Institut Pasteur de Lille and the Centre National de Génotypage. The 3C Study was performed as part of a collaboration between the Institut National de la Santé et de la Recherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne Regional Councils, Fondation de France and the joint French Ministry of Research/INSERM "Cohortes et collections de données biologiques" programme. Lille Génopôle received an unconditional grant from Eisai. AGES. Age, Gene/Environment Susceptibility-Reykjavik Study. This study has been funded by NIH contract N01-AG-1-2100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association), and the Althingi (the Icelandic Parliament). The study is approved by the Icelandic National Bioethics Committee, VSN: 00-063. The researchers are indebted to the participants for their willingness to participate in the study. ARIC. Atherosclerosis Risk in Communities study. The ARIC study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C), R01HL087641, R01HL59367 and R01HL086694; National Human Genome Research Institute contract U01HG004402; and National Institutes of Health contract HHSN268200625226C. The authors thank the staff and participants of the ARIC study for their important contributions. Infrastructure was partly supported by Grant Number UL1RR025005, a component of the National Institutes of Health and NIH Roadmap for Medical Research. This work as well as YL and AK were supported by the German Research Foundation (KO 3598/2-1, KO 3598/3-1 and CRC1140 A05 to AK). ASPS. Austrian Stroke Prevention Study. The research reported in this article was funded by the Austrian Science Fond (FWF) grant number P20545-P05 and P13180. The Medical University of Graz supports the databank of the ASPS. The authors thank the staff and the participants of the ASPS for their valuable contributions. We thank Birgit Reinhart for her long-term administrative commitment and Ing Johann Semmler for the technical assistance at creating the DNA-bank. BMES. Blue Mountains Eye Study. The BMES has been supported by the Australian RADGAC grant (1992- 94) and Australian National Health & Medical Research Council, Canberra Australia (Grant Nos: 974159, 211069, 991407, 457349). The GWAS studies of Blue Mountains Eye Study population are supported by the Australian National Health & Medical Research Council (Grant Nos: 512423, 475604, 529912) and the Wellcome Trust, UK (2008). EGH and JJW are funded by the Australian National Health & Medical Research Council Fellowship Schemes. CILENTO. Italian Network on Genetic Isolates – Cilento. We thank the populations of Cilento for their participation in the study. The study was supported by the Italian Ministry of Universities and CNR 36 (PON03PE_00060_7, Interomics Flagship Project), the Assessorato Ricerca Regione Campania, the Fondazione con il SUD (2011-PDR-13), and the Istituto Banco di Napoli - Fondazione to MC. COLAUS. The CoLaus authors thank Yolande Barreau, Mathieu Firmann, Vladimir Mayor, Anne-Lise Bastian, Binasa Ramic, Martine Moranville, Martine Baumer, Marcy Sagette, Jeanne Ecoffey and Sylvie Mermoud for data collection. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, the Swiss National Science Foundation (33CSCO- 122661, 3200BO-111361/2, 3100AO-116323/1, 310000-112552). The computations for CoLaus imputation were performed in part at the Vital-IT center for high performance computing of the Swiss Institute of Bioinformatics. We thank Vincent Mooser for his contribution to the CoLaus study. EGCUT. Estonian Genome Center University of Tartu. EGCUT received financing from FP7 grants (278913, 306031, 313010) and targeted financing from Estonian Government (SF0180142s08). EGCUT studies were covered from Infra-structure grant no. 3.2.0304.11-0312 funded mostly by the European Regional Development Fund, Center of Excellence in Genomics (EXCEGEN) and University of Tartu (SP1GVARENG). We acknowledge EGCUT technical personnel, especially Mr V. Soo and S. Smit. Data analyses were carried out in part in the High Performance Computing Center of the University of Tartu. FamHS. Family Heart Study. The FHS work was supported in part by NIH grants 5R01HL08770003, 5R01HL08821502 (Michael A. Province) from the NHLBI and 5R01DK07568102, 5R01DK06833603 from the NIDDK (I.B.B.). The authors thank the staff and participants of the FamHS for their important contributions. FHS. Framingham Heart Study. This research was conducted in part using data and resources from the Framingham Heart Study of the National Heart Lung and Blood Institute of the National Institutes of Health and Boston University School of Medicine. The analyses reflect intellectual input and resource development from the Framingham Heart Study investigators participating in the SNP Health Association Resource (SHARe) project. This work was partially supported by the National Heart, Lung and Blood Institute's Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix, Inc. for genotyping services (Contract No. N02-HL-6-4278). A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center. GENDIAN. GENetics of DIAbetic Nephropathy study. The support of the physicians, the patients, and the staff of the Diabetes Zentrum Mergentheim (Head: Prof. Dr. Thomas Haak), the diabetes outpatient clinic Dr Nusser - Dr Kreisel, the dialysis centers KfH Amberg, KfH Bayreuth, KfH Deggendorf, KfH Donauwörth, KfH Freising, KfH Freyung, KfH Fürth, KfH Hof, KfH Ingolstadt, KfH Kelheim, KfH München Elsenheimerstraße, KfH München-Schwabing, KfH Neumarkt, KfH Neusäß, KfH Oberschleißheim, KfH Passau, KfH Plauen, KfH Regensburg Günzstraße, KfH Regensburg Caritas-Krankenhaus, KfH Straubing, KfH Sulzbach-Rosenberg, KfH Weiden, Dialysezentrum Augsburg Dr. Kirschner, Dialysezentrum Bad Alexandersbad, KfH Bamberg, Dialysezentrum Emmering, Dialysezentrum Klinikum Landshut, Dialysezentrum Landshut, Dialysezentrum Pfarrkirchen, Dialysezentrum Schwandorf, Dr. Angela Götz, the medical doctoral student Johanna Christ and the Study Nurse Ingrid Lugauer. The expert technical assistance of Claudia Strohmeier is acknowledged. Phenotyping was funded by the Dr. Robert PflegerStiftung (Dr Carsten A. Böger), the MSD Stipend Diabetes (Dr Carsten A. Böger) and the University Hospital of Regensburg (intramural grant ReForM A to Dr. A. Götz, ReForM C to Dr. Carsten Böger). Genome-wide genotyping was funded by the KfH Stiftung Präventivmedizin e.V. (Dr. Carsten A. Böger, Dr. Jens Brüning), the Else Kröner-Fresenius-Stiftung (2012_A147 to Dr Carsten A. Böger and Dr Iris M. Heid) and the University Hospital Regensburg (Dr Carsten A. Böger). Data analysis was funded by the Else 37 Kröner-Fresenius Stiftung (Dr. Iris M. Heid and Dr. Carsten A. Böger: 2012_A147; Dr. Carsten A. Böger and Dr. Bernhard K. Krämer: P48/08//A11/08). GENDIAN Study Group: Mathias Gorski, Iris M. Heid, Bernhard K. Krämer, Myriam Rheinberger, Michael Broll, Alexander Lammert, Jens Brüning, Matthias Olden, Klaus Stark, Claudia Strohmeier, Simone Neumeier, Sarah Hufnagel, Petra Jackermeier, Emilia Ruff, Johanna Christ, Peter Nürnberg, Thomas Haak, Carsten A. Böger. HABC. Health Aging and Body Composition Study. The HABC study was funded by the National Institutes of Aging. This research was supported by NIA contracts N01AG62101, N01AG62103, and N01AG62106. The genome-wide association study was funded by NIA grant 1R01AG032098-01A1 to Wake Forest University Health Sciences and genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to The Johns Hopkins University, contract number HHSN268200782096C. This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging. HCS. Hunter Community Study. The University of Newcastle provided $300,000 from its Strategic Initiatives Fund, and $600,000 from the Gladys M Brawn Senior Research Fellowship scheme; Vincent Fairfax Family Foundation, a private philanthropic trust, provided $195,000; The Hunter Medical Research Institute provided media support during the initial recruitment of participants; and Dr Anne Crotty, Prof. Rodney Scott and Associate Prof. Levi provided financial support towards freezing costs for the long-term storage of participant blood samples. The authors would like to thank the men and women participating in the HCS as well as all the staff, investigators and collaborators who have supported or been involved in the project to date. A special thank you should go to Alison Koschel and Debbie Quain who were instrumental in setting up the pilot study and initial phase of the project. HPFS. Health Professionals Follow-Up Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. INGI-CARLANTINO. Italian Network on Genetic Isolates – Carlantino. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. INGI-FVG. Italian Network on Genetic Isolates – Friuli Venezia-Giulia. We thank Anna Morgan and Angela D'Eustacchio for technical support. We are grateful to the municipal administrators for their collaboration on the project and for logistic support. We thank all participants to this study. 38 INGI-VAL BORBERA. Italian Network on Genetic Isolates – Val Borbera. We thank the inhabitants of the Val Borbera who made this study possible, the local administrations and the ASL-Novi Ligure (Al) for support. We also thank Clara Camaschella for data collection supervision and organization of the clinical data collection, Fiammetta Vigano` for technical help and Corrado Masciullo for building the analysis platform. The research was supported by funds from Compagnia di San Paolo, Torino, Italy; Fondazione Cariplo, Italy and Ministry of Health, Ricerca Finalizzata 2008 and 2011/2012, CCM 2010, PRIN 2009 and Telethon, Italy to DT. IPM. Mount Sinai BioMe Biobank Program. The Mount Sinai BioMe Biobank Program is supported by The Andrea and Charles Bronfman Philanthropies. KORA-F3 and F4. The genetic epidemiological work was funded by the NIH subcontract from the Children's Hospital, Boston, US, (H.E.W., I.M.H, prime grant 1 R01 DK075787-01A1), the German National Genome Research Net NGFN2 and NGFNplus (H.E.W. 01GS0823; WK project A3, number 01GS0834), the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ, and by the Else KrönerFresenius-Stiftung (P48/08//A11/08; C.A.B., B.K.K; 2012_A147 to CAB and IMH.). The Genetic Epidemiology at the University of Regensburg received financial contributions from the BMBF (01ER1206 and 01ER1507). The kidney parameter measurements in F3 were funded by the Else Kröner-FreseniusStiftung (C.A.B., B.K.K.) and the Regensburg University Medical Center, Germany; in F4 by the University of Ulm, Germany (W.K.). Genome wide genotyping costs in F3 and F4 were in part funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). De novo genotyping in F3 and F4 were funded by the Else Kröner-Fresenius-Stiftung (C.A.B., B.K.K.). The KORA research platform and the MONICA Augsburg studies were initiated and financed by the Helmholtz Zentrum München, German Research Center for Environmental Health, by the German Federal Ministry of Education and Research and by the State of Bavaria. Genotyping was performed in the Genome Analysis Center (GAC) of the Helmholtz Zentrum München. The LINUX platform for computation were funded by the University of Regensburg for the Department of Epidemiology and Preventive Medicine at the Regensburg University Medical Center. LIFELINES. The authors wish to acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all the study participants. Lifelines group authors: Behrooz Z Alizadeh1 , H Marike Boezen1 , Lude Franke2 , Pim van der Harst3 , Gerjan Navis4 , Marianne Rots5 , Harold Snieder1 , Morris Swertz2 , Bruce HR Wolffenbuttel6 and Cisca Wijmenga2 1. Department of Epidemiology, University of Groningen, University Medical Center Groningen, The Netherlands 2. Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands 3. Department of Cardiology, University of Groningen, University Medical Center Groningen, The Netherlands 4. Department of Internal Medicine, Division of Nephrology, University of Groningen, University Medical Center Groningen, The Netherlands 5. Department of Medical Biology, University of Groningen, University Medical Center Groningen, The Netherlands 6. Department of Endocrinology, University of Groningen, University Medical Center Groningen, The Netherlands MESA. Multi-Ethnic Study of Atherosclerosis. University of Washington (N01-HC-95159),Regents of the University of California (N01-HC-95160), Columbia University (N01-HC-95161), Johns Hopkins University 39 (N01-HC-95162, N01-HC-95168), University of Minnesota (N01-HC-95163), Northwestern University (N01-HC-95164), Wake Forest University (N01-HC-95165), University of Vermont (N01-HC-95166), New England Medical Center (N01-HC-95167), Harbor-UCLA Research and Education Institute (N01-HC- 95169), Cedars-Sinai Medical Center (R01-HL-071205), University of Virginia (subcontract to R01-HL- 071205) MICROS. Microisolates in South Tyrol study. We owe a debt of gratitude to all participants. We thank the primary care practitioners R. Stocker, S. Waldner, T. Pizzecco, J. Plangger, U. Marcadent and the personnel of the Hospital of Silandro (Department of Laboratory Medicine) for their participation and collaboration in the research project. In South Tyrol, the study was supported by the Ministry of Health and Department of Educational Assistance, University and Research of the Autonomous Province of Bolzano, the South Tyrolean Sparkasse Foundation, and the European Union framework program 6 EUROSPAN project (contract no. LSHG-CT-2006-018947). NESDA. The Netherlands Study of Depression and Anxiety. The infrastructure for the NESDA study is funded through the Geestkracht programme of the Dutch Scientific Organization (ZON-MW, grant number 10-000-1002) and matching funds from participating universities and mental health care organizations. Genotyping in NESDA was funded by the Genetic Association Information Network (GAIN) of the Foundation for the US National Institutes of Health. NHS. Nurses' Health Study. The NHS/HPFS type 2 diabetes GWAS (U01HG004399) is a component of a collaborative project that includes 13 other GWAS (U01HG004738, U01HG004422, U01HG004402, U01HG004729, U01HG004726, U01HG004735, U01HG004415, U01HG004436, U01HG004423, U01HG004728, RFAHG006033; National Institute of Dental & Craniofacial Research: U01DE018993, U01DE018903) funded as part of the Gene Environment-Association Studies (GENEVA) under the NIH Genes, Environment and Health Initiative (GEI). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GENEVA Coordinating Center (U01HG004446). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Genotyping was performed at the Broad Institute of MIT and Harvard, with funding support from the NIH GEI (U01HG04424), and Johns Hopkins University Center for Inherited Disease Research, with support from the NIH GEI (U01HG004438) and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). The NHS renal function and albuminuria work was supported by DK66574. Additional funding for the current research was provided by the National Cancer Institute (P01CA087969, P01CA055075), and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK058845). We thank the staff and participants of the NHS and HPFS for their dedication and commitment. NSPHS. The Northern Swedish Population Health Study. The NSPHS was supported by grants from the Swedish Natural Sciences Research Council, the European Union through the EUROSPAN project (contract no. LSHG-CT-2006-018947), the Foundation for Strategic Research (SSF) and the Linneaus Centre for Bioinformatics (LCB). We are also grateful for the contribution of samples from the Medical Biobank in Umeå and for the contribution of the district nurse Svea Hennix in the Karesuando study. RS-I. The Rotterdam Study. The GWA study was funded by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012), the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) project nr. 050-060-810. We thank Pascal Arp, Mila Jhamai, Dr Michael 40 Moorhouse, Marijn Verkerk, and Sander Bervoets for their help in creating the GWAS database. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are very grateful to the participants and staff from the Rotterdam Study, the participating general practitioners and the pharmacists. We would like to thank Dr. Tobias A. Knoch, Luc V. de Zeeuw, Anis Abuseiris, and Rob de Graaf as well as their institutions the Erasmus Computing Grid, Rotterdam, The Netherlands, and especially the national German MediGRID and Services@MediGRID part of the German D-Grid, both funded by the German Bundesministerium fuer Forschung und Technology under grants #01 AK 803 A-H and # 01 IG 07015 G, for access to their grid resources. Abbas Dehghan is supported by NWO grant (vici, 918-76-619). SAPALDIA. Swiss Study on Air Pollution and Lung Diseases in Adults. The SAPALDIA Team: Study directorate: T Rochat (p), NM Probst Hensch (e/g), N Künzli (e/exp), C Schindler (s), JM Gaspoz (c) Scientific team: JC Barthélémy (c), W Berger (g), R Bettschart (p), A Bircher (a), O Brändli (p), C Brombach (n), M Brutsche (p), L Burdet (p), M Frey (p), U Frey (pd), MW Gerbase (p), D Gold (e/c/p), E de Groot (c), W Karrer (p), R Keller (p), B Martin (pa), D Miedinger (o), U Neu (exp), L Nicod (p), M Pons (p), F Roche (c), T Rothe (p), E Russi (p), P Schmid-Grendelmeyer (a), A Schmidt-Trucksäss (pa), A Turk (p), J Schwartz (e), D. Stolz (p), P Straehl (exp), JM Tschopp (p), A von Eckardstein (cc), E Zemp Stutz (e). Scientific team at coordinating centers: M Adam (e/g), C Autenrieth (pa), PO Bridevaux (p), D Carballo (c), E Corradi (exp), I Curjuric (e), J Dratva (e), A Di Pasquale (s), E Dupuis Lozeron (s), E Fischer (e), M Germond (s), L Grize (s), D Keidel (s), S Kriemler (pa), A Kumar (g), M Imboden (g), N Maire (s), A Mehta (e), H Phuleria (exp), E Schaffner (s), GA Thun (g) A Ineichen (exp), M Ragettli (e), M Ritter (exp), T Schikowski (e), M Tarantino (s), M Tsai (exp) (a) allergology, (c) cardiology, (cc) clinical chemistry, (e) epidemiology, (exp) exposure, (g) genetic and molecular biology, (m) meteorology, (n) nutrition, (o) occupational health, (p) pneumology, (pa) physical activity, (pd) pediatrics, (s) statistics. Funding: The Swiss National Science Foundation (grants no 33CSCO-134276/1, 33CSCO-108796, 3247BO-104283, 3247BO-104288, 3247BO- 104284, 3247-065896, 3100-059302, 3200-052720, 3200-042532, 4026-028099), the Federal Office for Forest, Environment and Landscape, the Federal Office of Public Health, the Federal Office of Roads and Transport, the canton's government of Aargau, Basel-Stadt, Basel-Land, Geneva, Luzern, Ticino, Valais, and Zürich, the Swiss Lung League, the canton's Lung League of Basel Stadt/ Basel Landschaft, Geneva, Ticino, Valais and Zurich, SUVA, Freiwillige Akademische Gesellschaft, UBS Wealth Foundation, Talecris Biotherapeutics GmbH, Abbott Diagnostics, European Commission 018996 (GABRIEL), Wellcome Trust WT 084703MA. The study could not have been done without the help of the study participants, technical and administrative support and the medical teams and field workers at the local study sites. Local fieldworkers : Aarau: S Brun, G Giger, M Sperisen, M Stahel, Basel: C Bürli, C Dahler, N Oertli, I Harreh, F Karrer, G Novicic, N Wyttenbacher, Davos: A Saner, P Senn, R Winzeler, Geneva: F Bonfils, B Blicharz, C Landolt, J Rochat, Lugano: S Boccia, E Gehrig, MT Mandia, G Solari, B Viscardi, Montana: AP Bieri, C Darioly, M Maire, Payerne: F Ding, P Danieli A Vonnez, Wald: D Bodmer, E Hochstrasser, R Kunz, C Meier, J Rakic, U Schafroth, A Walder. Administrative staff: C Gabriel, R Gutknecht. SHIP and SHIP-TREND. The Study of Health in Pomerania. SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network 41 'Greifswald Approach to Individualized Medicine (GANI_MED)' funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. The University of Greifswald is a member of the 'Center of Knowledge Interchange' program of the Siemens AG and the Caché Campus program of the InterSystems GmbH. The SHIP authors are grateful to Mario Stanke for the opportunity to use his Server Cluster for the SNP imputation as well as to Holger Prokisch and Thomas Meitinger (Helmholtz Zentrum München) for the genotyping of the SHIP-TREND cohort. TRAILS. TRacking Adolescents' Individual Lives. Trails is a collaborative project involving various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in the Netherlands. TRAILS has been financially supported by grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grants 60- 60600-98-018 and 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 457-03-018, GB-MaGW 452-04-314, and GB-MaGW 452-06- 004; NWO large-sized investment grant 175.010.2003.005; NWO Longitudinal Survey and Panel Funding 481-08-013); the Sophia Foundation for Medical Research (projects 301 and 393), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006), and the participating universities. We are grateful to all adolescents, their parents and teachers who participated in this research and to everyone who worked on this project and made it possible. Statistical analyses were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation. WGHS. Women's Genome Health Study. The WGHS is supported by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with collaborative scientific support and funding for genotyping provided by Amgen. YFS. Young Finns Study. The YFS has been financially supported by the Academy of Finland: grants 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), and 41071 (Skidi), the Social Insurance Institution of Finland, Kuopio, Tampere and Turku University Hospital Medical Funds (grant 9M048 and 9N035 for TeLeht), Juho Vainio Foundation, Paavo Nurmi Foundation, Finnish Foundation of Cardiovascular Research and Finnish Cultural Foundation, Tampere Tuberculosis Foundation and Emil Aaltonen Foundation (T.L). The technical assistance in the statistical analyses by Ville Aalto and Irina Lisinen is acknowledged. ; Peer Reviewed
