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The food industry faces two paradoxical demands: on the one hand, foods need to be microbiologically safe for consumption and on the other hand, consumers want fresh, minimally processed foods. To meet these demands, more insight into the mechanisms of microbial growth is needed, which includes, among others, the microbial lag phase. This is the time needed by bacterial cells to adapt to a new environment (for example, after food product contamination) before starting an exponential growth regime. Since food products are often contaminated with low amounts of pathogenic microorganisms, it is important to know the distribution of these individual cell lag times to make accurate predictions concerning food safety. More precisely, cells with the shortest lag times (i.e., appearing in the left tail of the distribution) are largely decisive for the outgrowth of the population. In this study, an integrated modeling approach is proposed and applied to an existing data set of individual cell lag time measurements of Listeria monocytogenes. In a first step, a logistic modeling approach is applied to predict the fraction of zero‐lag cells (which start growing immediately) as a function of temperature, pH, and water activity. For the nonzero‐lag cells, the mean and variance of the lag time distribution are modeled with a hyperbolic‐type model structure. This mean and variance allow identification of the parameters of a two‐parameter Weibull distribution, representing the nonzero‐lag cell lag time distribution. The integration of the developed models allows prediction of a global distribution of individual cell lag times for any combination of environmental conditions in the interpolation domain of the original temperature, pH, and water activity settings. The global fitting quality of the model is quantified using several measures indicating that the model gives accurate predictions, erring slightly on the fail‐safe side when predicting the shortest lag times.

We report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess lead (Pb) exposure to pre-school children resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate internal Pb exposure in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Model simulations at individual level are compared with biomonitoring data from a Belgian monitoring campaign (Flemish Government, 2008; Van Holderbeke et al., 2008) in order to verify the model performance of MERLIN-Expo when simulating complex scenarios that account for subject mobility, i.e., duration at the different considered locations (both indoors and outdoors) with varying exposure levels, and individual food consumption patterns. Adopting an assessment approach at individual level improves on more commonly performed generic exposure assessments at population level, by including intake of Pb from local and purchased food products, and taking into account the mobility of the participants, which results in a more comprehensive assessment of individual recent intake of lead. Also, the accuracy of the model predictions as compared to Pb biomonitoring data has been tested via different accuracy approaches and metrics. We calculated a Probability of detection (or true positive rate) of 0.93, reflecting that almost all blood levels above a chosen trigger value of 2.25 mg.L-1 are predicted as such by the model; a Bias of 1.87, i.e. reflecting a slight overestimation of the model, and F1 and F2 scores of 0.65 and 0.8, respectively, confirming that most of the measured positives are detected as such by the model (high F2 score) with a slight overestimation (lower F1 score). Although the model predictions for individual children slightly overpredict the biomonitoring data, they overlap with the prediction interval calculated by MERLIN-Expo based on population averages ...

We report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess lead (Pb) exposure to pre-school children resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate internal Pb exposure in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Model simulations at individual level are compared with biomonitoring data from a Belgian monitoring campaign (Flemish Government, 2008; Van Holderbeke et al., 2008) in order to verify the model performance of MERLIN-Expo when simulating complex scenarios that account for subject mobility, i.e., duration at the different considered locations (both indoors and outdoors) with varying exposure levels, and individual food consumption patterns. Adopting an assessment approach at individual level improves on more commonly performed generic exposure assessments at population level, by including intake of Pb from local and purchased food products, and taking into account the mobility of the participants, which results in a more comprehensive assessment of individual recent intake of lead. Also, the accuracy of the model predictions as compared to Pb biomonitoring data has been tested via different accuracy approaches and metrics. We calculated a Probability of detection (or true positive rate) of 0.93, reflecting that almost all blood levels above a chosen trigger value of 2.25 mg.L-1 are predicted as such by the model; a Bias of 1.87, i.e. reflecting a slight overestimation of the model, and F1 and F2 scores of 0.65 and 0.8, respectively, confirming that most of the measured positives are detected as such by the model (high F2 score) with a slight overestimation (lower F1 score). Although the model predictions for individual children slightly overpredict the biomonitoring data, they overlap with the prediction interval calculated by MERLIN-Expo based on population averages (Fierens et al., 2016). Modelling exposure at individual level allows risk assessors to attribute the relative contribution of different exposure routes at various locations, reconstructing the exposure history for each individual in a complex site-specific exposure scenario. The slight overprediction of the actual observed Pb blood levels with a factor 2 is compatible with conservative decision-making.

Physical activity and ventilation rates have an effect on an individual's dose and may be important to consider in exposure−response relationships; however, these factors are often ignored in environmental epidemiology studies. The aim of this study was to evaluate methods of estimating the inhaled dose of air pollution and understand variability in the absence of a true gold standard metric. Five types of methods were identified: (1) methods using (physical) activity types, (2) methods based on energy expenditure, METs (metabolic equivalents of task), and oxygen consumption, (3) methods based on heart rate or (4) breathing rate, and (5) methods that combine heart and breathing rate. Methods were compared using a real-life data set of 122 adults who wore devices to track movement, black carbon air pollution, and physiological health markers for 3 weeks in three European cities. Different methods for estimating minute ventilation performed well in relative terms with high correlations among different methods, but in absolute terms, ignoring increased ventilation during day-to-day activities could lead to an underestimation of the daily dose by a factor of 0.08−1.78. There is no single best method, and a multitude of methods are currently being used to approximate the dose. The choice of a suitable method for determining the dose in future studies will depend on both the size and the objectives of the study. ; This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) is a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission Grant Agreement 602624. E.D. is supported by a postdoctoral scholarship from FWO-Research Foundation Flanders. M.L. holds a joint PASTA/VITO Ph.D. scholarship.

While the annual number of trips of the average urban inhabitant has grown steadily in recent years, people are becoming less active while doing so. This lack of physical activity causes major health problems for individuals and great economic costs for society as a whole. Replacing short motorized trips by walking and cycling has been shown to increase physical activity in everyday life. The PASTA "Physical Activity through Sustainable Transport Approaches" project collected data in a longitudinal web-based survey with a cohort design to study the effects of active mobility on overall physical activity and health. An opportunistic sampling approach focusing on cyclists was applied to recruit more than 10000 participants in seven European cities, with half of them completing valid 1-day travel diaries at various time points. For this study, we compared 'cyclists' and 'non-cyclists' in terms of their overall travel behavior, physical activity and health. More than 2400 participants were identified as regular cyclists, 90% of which reached at least 30 min of active travel per day (the WHO´s recommended level) only by routine trips. When compared to non-cyclists, the share of women cycling regularly was lower; however, the share of people who had a driver's license and had at least sometimes access to a car was higher for regular cyclists. There were significant differences between cities in terms of cycling mode share, trip rates, trip duration and length, trip purpose and total physical activity, reflecting different geographical, economic, climatic and socio-cultural contexts. Our results indicate that cycling as a means of transport can help reach the WHO's physical activity recommendations. ; This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) is a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission - Grant Agreement No. 602624. Evi Dons is supported by a postdoctoral scholarship from FWO - Research Foundation Flanders.

Background: Sufficient sample size and minimal sample bias are core requirements in empirical data analyses. Combining opportunistic recruitment with an online survey and data collection platform yields new benefits compared to traditional recruitment approaches. Objective: The objective of this paper is to report on the success of different recruitment methods to obtain participants' characteristics, participation behavior, recruitment rates, and representativeness of the sample. Methods: A longitudinal online survey was implemented as part of the European PASTA project, which was online between November 2014 and December 2016. During this period participants in seven European cities were recruited on a rolling basis. For all cities to reach a sufficient number of adult participants a standardized guide on recruitment strategy was developed. In order to make use of the strengths and to minimize weakness a combination of different opportunistic recruitment methods was applied. In addition, the city of Oerebro applied random sampling approach. In order to reduce attrition rate and improve real-time monitoring the online platform featured a participant and a researchers` user interface and dashboard. Results: A total of 10,691 participants were recruited. Most people found out about the survey through their workplace or employer (21.5 %), outreach promotion (20.8 %), and social media (17.4 %). The average number of questionnaires filled-in per participant varied between the cities, with the highest number in Zurich (11.0 ± 0.33) and the lowest in Oerebro (4.8 ± 0.17). Collaboration with local organizations, the use of Facebook and mailing lists, and direct street recruitment were the most effective approaches in reaching a high share of participants (p = <.001). Under consideration of invested working hours Facebook (p = <.001) was one of the most time-efficient methods. Compared to the cities census data, the composition of study participants was broadly representative in terms of gender distribution, however included younger and better educated participants. Conclusions: We observed that offering a mixed recruitment approach was very effective in achieving a high participation rate. The highest attrition rate and the lowest average number of questionnaires filled-in per participant were observed in Oerebro, who also recruited participants through random sampling. The findings suggest that people that are more interested in the topic are more willing to participate and to stay in a survey than those who are selected randomly and may not have a strong connection to the research topic. Whereas direct face-to-face contacts were very effective with respect to the number of recruited participants; recruiting people through social media was not only effective, but also very time-efficient. The collected data is based on one of the largest recruited longitudinal samples with a common recruitment strategy in different European cities. ; This work was supported by the European PASTA project. PASTA is a 4-year project funded by the European Union's Seventh Framework Program under European Commission (Grant Agreement #602624). ED is supported by a postdoctoral scholarship from FWO (Research Foundation Flanders). We would like to thank all recruiters in the seven European cities and Astrid Guhnemann for proofreading the manuscript.

While the annual number of trips of the average urban inhabitant has grown steadily in recent years, people are becoming less active while doing so. This lack of physical activity causes major health problems for individuals and great economic costs for society as a whole. Replacing short motorized trips by walking and cycling has been shown to increase physical activity in everyday life. The PASTA "Physical Activity through Sustainable Transport Approaches" project collected data in a longitudinal web-based survey with a cohort design to study the effects of active mobility on overall physical activity and health. An opportunistic sampling approach focusing on cyclists was applied to recruit more than 10000 participants in seven European cities, with half of them completing valid 1-day travel diaries at various time points. For this study, we compared 'cyclists' and 'non-cyclists' in terms of their overall travel behavior, physical activity and health. More than 2400 participants were identified as regular cyclists, 90% of which reached at least 30 min of active travel per day (the WHO´s recommended level) only by routine trips. When compared to non-cyclists, the share of women cycling regularly was lower; however, the share of people who had a driver's license and had at least sometimes access to a car was higher for regular cyclists. There were significant differences between cities in terms of cycling mode share, trip rates, trip duration and length, trip purpose and total physical activity, reflecting different geographical, economic, climatic and socio-cultural contexts. Our results indicate that cycling as a means of transport can help reach the WHO's physical activity recommendations. ; This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) is a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission ‐ Grant Agreement No. 602624. Evi Dons is supported by a postdoctoral scholarship from FWO – Research Foundation Flanders.

Active travel (walking or cycling for transport) is considered the most sustainable form of personal transport. Yet its net effects on mobility-related CO2 emissions are complex and underresearched. Here we collected travel activity data in seven European cities and derived life cycle CO2 emissions across modes and purposes. Daily mobility-related life cycle CO2 emissions were 3.2 kgCO(2) per person, with car travel contributing 70% and cycling 1%. Cyclists had 84% lower life cycle CO2 emissions than non-cyclists. Life cycle CO2 emissions decreased by 14% per additional cycling trip and decreased by 62% for each avoided car trip. An average person who `shifted travel modes' from car to bike decreased life cycle CO2 emissions by 3.2 kgCO(2)/day. Promoting active travel should be a cornerstone of strategies to meet net zero carbon targets, particularly in urban areas, while also improving public health and quality of urban life. ; This work was supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA). PASTA (http://www.pastaproject.eu/) was a four-year project funded by the European Union's Seventh Framework Program (EU FP7) under European Commission - Grant Agreement No. 602624. CB is also supported by UK Research and Innovation (UKRI) under the Centre for Research on Energy Demand Solutions (CREDS, Grant agreement number EP/R035288/1). ED is also supported by a postdoctoral scholarship from FWO - Research Foundation Flanders. ML held a joint PASTA/VITO PhD scholarship. SS is supported by the Martin Filko Scholarship from the Ministry of Education in Slovakia. ; Brand, C (corresponding author), Univ Oxford, Transport Studies Unit, South Parks Rd, Oxford OX, christian.brand@ouce.ox.ac.uk

Introduction: Only one-third of the European population meets the minimum recommended levels of physical activity (PA). Physical inactivity is a major risk factor for non-communicable diseases. Walking and cycling for transport (active mobility, AM) are well suited to provide regular PA. The European research project Physical Activity through Sustainable Transport Approaches (PASTA) pursues the following aims: (1) to investigate correlates and interrelations of AM, PA, air pollution and crash risk; (2) to evaluate the effectiveness of selected interventions to promote AM; (3) to improve health impact assessment (HIA) of AM; (4) to foster the exchange between the disciplines of public health and transport planning, and between research and practice. Methods and analysis: PASTA pursues a mixedmethod and multilevel approach that is consistently applied in seven case study cities. Determinants of AM and the evaluation of measures to increase AM are investigated through a large scale longitudinal survey, with overall 14 000 respondents participating in Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zurich. Contextual factors are systematically gathered in each city. PASTA generates empirical findings to improve HIA for AM, for example, with estimates of crash risks, factors on AM-PA substitution and carbon emissions savings from mode shifts. Findings from PASTA will inform WHO's online Health Economic Assessment Tool on the health benefits from cycling and/or walking. The study's wide scope, the combination of qualitative and quantitative methods and health and transport methods, the innovative survey design, the general and city-specific analyses, and the transdisciplinary composition of the consortium and the wider network of partners promise highly relevant insights for research and practice. Ethics and dissemination: Ethics approval has been obtained by the local ethics committees in the countries where the work is being conducted, and sent to the European Commission before the start of the survey. The PASTA website (http://www.pastaproject.eu) is at the core of all communication and dissemination activities. ; This work is supported by the European project Physical Activity through Sustainable Transportation Approaches (PASTA), which has partners in London, Rome, Antwerp, Örebro, Vienna, Zurich, and Barcelona. PASTA (http://www.pastaproject.eu/) is a 4-year project funded by the European Union's Seventh Framework Program under EC-GA No. 602624-2 (FP7-HEALTH-2013-INNOVATION-1).

Human biomonitoring has become a pivotal tool for supporting chemicals' policies. It provides information on real-life human exposures and is increasingly used to prioritize chemicals of health concern and to evaluate the success of chemical policies. Europe has launched the ambitious REACH program in 2007 to improve the protection of human health and the environment. In October 2020 the EU commission published its new chemicals strategy for sustainability towards a toxic-free environment. The European Parliament called upon the commission to collect human biomonitoring data to support chemical's risk assessment and risk management. This manuscript describes the organization of the first HBM4EU-aligned studies that obtain comparable human biomonitoring (HBM) data of European citizens to monitor their internal exposure to environmental chemicals. The HBM4EU-aligned studies build on existing HBM capacity in Europe by aligning national or regional HBM studies. The HBM4EU-aligned studies focus on three age groups: children, teenagers, and adults. The participants are recruited between 2014 and 2021 in 11 to 12 primary sampling units that are geographically distributed across Europe. Urine samples are collected in all age groups, and blood samples are collected in children and teenagers. Auxiliary information on socio-demographics, lifestyle, health status, environment, and diet is collected using questionnaires. In total, biological samples from 3137 children aged 6–12 years are collected for the analysis of biomarkers for phthalates, HEXAMOLL(®) DINCH, and flame retardants. Samples from 2950 teenagers aged 12–18 years are collected for the analysis of biomarkers for phthalates, Hexamoll(®) DINCH, and per- and polyfluoroalkyl substances (PFASs), and samples from 3522 adults aged 20–39 years are collected for the analysis of cadmium, bisphenols, and metabolites of polyaromatic hydrocarbons (PAHs). The children's group consists of 50.4% boys and 49.5% girls, of which 44.1% live in cities, 29.0% live in towns/suburbs, ...