Suchergebnisse

Durch unterschiedlichste anthropogene Nutzungen ist eine Vielzahl von insbesondere persistenten Stoffen ubiquitär in allen Umweltmedien verteilt. Um festgelegte Umweltziele zu erreichen sind wirksame Maßnahmen umzusetzen. Hierfür ist stoffspezifisch die Kenntnis der wichtigsten Quellen und Eintragspfade zwingend notwendig. Modelle sind hier wichtige Werkzeuge, um regional spezifisch grundlegende Aussagen zu liefern. Deutschlandweit wird für den Wasserbereich vom Umweltbundesamt das Modell MoRE (Modelling of Regionalized Emissions) verwendet. Dabei sind Modellaussagen insbesondere für ubiquitäre Stoffe bisher mit erheblichen Unsicherheiten behaftet. Grund sind die nach wie vor bestehenden Datenlücken, sowohl bezogen auf die stoffspezifischen Eingangsdaten, als auch die Validierungsdaten. Um die daraus resultierenden Unsicherheiten zu reduzieren, wurde für die Eingangsdaten, basierend auf dem Umweltverhalten der Stoffe, ein systematischer Plausibilisierungsansatz erarbeitet und auf die bestehenden Datengrundlagen angewendet. Ein Gewässermonitoring mit Langzeitmischproben wurde durchgeführt, um die verfügbaren Validierungsdaten besser interpretieren zu können. Im Ergebnis wurden, mit Blick auf die Verbesserung der Aussagefähigkeit der Modellergebnisse, notwendige Arbeitsschritte für zukünftige Modellierungsarbeiten bzw. künftige Bestandsaufnahmen für ubiquitäre Stoffe formuliert. Als weiterer wichtiger Baustein für die Prüfung der Einhaltung von Umweltzielen in Fließgewässern, wurde ein Gewässergüteansatz hinsichtlich der Umsetzung in der deutschlandweiten Modellierung geprüft und Empfehlungen für die Umsetzung formuliert. Abschließend wurde MoRE erfolgreich erweitert um eine separate Modellierung für den PAK Vertreter Benzo[a]pyren. Hintergrund ist, dass in der Richtlinie über Umweltqualitätsnormen (2013/39/EU) Benzo[a]pyren als Leitparameter für weitere PAK-Vertreter beschrieben wird.

This book provides a comprehensive, up-to-date overview on the most pressing issues in the conservation and management of archaeological, architectural, and urban landscapes. Multidisciplinary research is presented on a wide range of built heritage sites, from archaeological ruins and historic centers through to twentieth century and industrial architectural heritage. The role of ICT and new technologies, including those used for digital archiving, surveying, modeling, and monitoring, is extensively discussed, in recognition of their importance for professionals working in the field. Detailed attention is also paid to materials and treatments employed in preventive conservation and management. With contributions from leading experts, including university researchers, professionals, and policy makers, the book will be invaluable for all who seek to understand, and solve, the challenges face d in the protection and enhancement of the built heritage. Lucia Toniolo is Full Professor of Material Science and Technology (SSD ING/IND22) in the Faculty of Civil Architecture, Politecnico di Milano, where she is in charge of the courses Materials in Architecture, Laboratory of Architectural Restoration, and Durability of Materials in Architecture. In 2011, she was appointed President of the Center for Conservation and Promotion of Cultural Heritage of the Politecnico di Milano, having previously been Vice-President. Since 2006 she has been the Scientific Advisor on Laboratory Materials and Methods for Cultural Heritage in the Department of Chemistry, Materials, and Material Engineering. Professor Toniolo has been scientific coordinator of various important activities and research projects. She is currently scientific advisor on the project 'Monitoring of the façade of Milan Cathedral'. She has held scientific responsibility for various projects of the Ministry of Education, Universities, and Research (MIUR-PRIN). Her main research areas are: (a) chemical and morphological characterization of materials of cultural heritage (particularly natural stones, mortars and plasters, mural paintings, ceramic materials, polychrome surfaces, and polymeric items); (b) characterization and evaluation of polymeric treatments applied to cultural heritage; and (c) micro- and non-invasive spectroscopic characterization of materials. Professor Toniolo is the author of more than 60 scientific publications in international journals (H index 16) and 150 publications in proceedings of international conferences, books etc. Gabriele Guidi received his M.S. Degree in Electronic Engineering in 1988 from the University of Florence, and Ph.D. in 1992 from the University of Bologna, Italy. He is Associate Professor at Politecnico di Milano. He worked for more than 10 years on researches about ultrasound equipment for biomedical imaging. Since 2000 he reoriented his activity by applying imaging technologies to the field of non contact 3D measurement. He has been working on applications of 3D imaging in various fields, with special emphasis to Industrial Design and Cultural Heritage documentation. Dr. Guidi is Senior Member of the IEEE. He works as reviewer of a few international journals such as 'The IEEE Transactions on System, Man and Cybernetics', 'The IEEE Transactions on Image Processing' and 'Machine Vision and Applications' (Springer).

The sustainable management of water resources is of high relevance with regard to overall socioeconomic development and environmental protection. Water quality monitoring plays a key role in this context as it provides the necessary information on the status of water resources and on the impact of human alterations of the hydrological cycle and hence forms an important basis for decision making. Current legislative approaches to water management like the European Water Framework Directive place a high importance to water quality monitoring. Monitoring systems have to provide relevant data in an efficient manner and are at the same time under budget constraints. This makes a case for optimization strategies for water quality monitoring networks, where the location of sampling stations and monitoring frequencies play a central role. Scientific methods to optimize water quality monitoring systems have been extensively described in literature. However, they are hardly ever applied since most of them depend on a-priory knowledge of the spatial and temporal variability of water quality parameters information which is seldom available. The objective of this dissertation is to develop a method which allows estimating long term variability of water quality parameters. The parameter nitrate is chosen as an example parameter and the Aconcagua watershed in Chile is selected as a case study. The variability of nitrate concentrations over space and time is modelled on the basis of available hydrological, land use and point source data for the time period 1986 2006. For estimating nitrate exports to surface water the export coefficient method was used. The results are validated with measured nitrate concentrations of the same period. Results show that the model represents nitrate concentrations well for the upper and lower part of the watershed while low agreement between modelled and observed values was found for the lower part of the watershed, probably due to an insufficient representation of the hydrology of that zone but it could also be related to shortcomings of the current sampling methods at that particular monitoring station.

The sustainable management of water resources is of high relevance with regard to overall socioeconomic development and environmental protection. Water quality monitoring plays a key role in this context as it provides the necessary information on the status of water resources and on the impact of human alterations of the hydrological cycle and hence forms an important basis for decision making. Current legislative approaches to water management like the European Water Framework Directive place a high importance to water quality monitoring. Monitoring systems have to provide relevant data in an efficient manner and are at the same time under budget constraints. This makes a case for optimization strategies for water quality monitoring networks, where the location of sampling stations and monitoring frequencies play a central role. Scientific methods to optimize water quality monitoring systems have been extensively described in literature. However, they are hardly ever applied since most of them depend on a-priory knowledge of the spatial and temporal variability of water quality parameters information which is seldom available. The objective of this dissertation is to develop a method which allows estimating long term variability of water quality parameters. The parameter nitrate is chosen as an example parameter and the Aconcagua watershed in Chile is selected as a case study. The variability of nitrate concentrations over space and time is modelled on the basis of available hydrological, land use and point source data for the time period 1986 2006. For estimating nitrate exports to surface water the export coefficient method was used. The results are validated with measured nitrate concentrations of the same period. Results show that the model represents nitrate concentrations well for the upper and lower part of the watershed while low agreement between modelled and observed values was found for the lower part of the watershed, probably due to an insufficient representation of the hydrology of that zone but it could also be related to shortcomings of the current sampling methods at that particular monitoring station.