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- Van den Brink, P. J., et al.
(author)
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Toward sustainable environmental quality: Priority research questions for Europe
- 2018
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In: Environmental Toxicology and Chemistry. - : Wiley. - 0730-7268 .- 1552-8618. ; 37:9, s. 2281-2295
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Journal article (peer-reviewed)abstract
- The United Nations' Sustainable Development Goals have been established to end poverty, protect the planet, and ensure prosperity for all. Delivery of the Sustainable Development Goals will require a healthy and productive environment. An understanding of the impacts of chemicals which can negatively impact environmental health is therefore essential to the delivery of the Sustainable Development Goals. However, current research on and regulation of chemicals in the environment tend to take a simplistic view and do not account for the complexity of the real world, which inhibits the way we manage chemicals. There is therefore an urgent need for a step change in the way we study and communicate the impacts and control of chemicals in the natural environment. To do this requires the major research questions to be identified so that resources are focused on questions that really matter. We present the findings of a horizon-scanning exercise to identify research priorities of the European environmental science community around chemicals in the environment. Using the key questions approach, we identified 22 questions of priority. These questions covered overarching questions about which chemicals we should be most concerned about and where, impacts of global megatrends, protection goals, and sustainability of chemicals; the development and parameterization of assessment and management frameworks; and mechanisms to maximize the impact of the research. The research questions identified provide a first-step in the path forward for the research, regulatory, and business communities to better assess and manage chemicals in the natural environment. Environ Toxicol Chem 2018;37:2281-2295. (c) 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
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- Bertram, Michael G., et al.
(author)
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Frontiers in quantifying wildlife behavioural responses to chemical pollution
- 2022
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In: Biological Reviews. - : John Wiley & Sons. - 1464-7931 .- 1469-185X. ; 97:4
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Journal article (peer-reviewed)abstract
- Animal behaviour is remarkably sensitive to disruption by chemical pollution, with widespread implications for ecological and evolutionary processes in contaminated wildlife populations. However, conventional approaches applied to study the impacts of chemical pollutants on wildlife behaviour seldom address the complexity of natural environments in which contamination occurs. The aim of this review is to guide the rapidly developing field of behavioural ecotoxicology towards increased environmental realism, ecological complexity, and mechanistic understanding. We identify research areas in ecology that to date have been largely overlooked within behavioural ecotoxicology but which promise to yield valuable insights, including within- and among-individual variation, social networks and collective behaviour, and multi-stressor interactions. Further, we feature methodological and technological innovations that enable the collection of data on pollutant-induced behavioural changes at an unprecedented resolution and scale in the laboratory and the field. In an era of rapid environmental change, there is an urgent need to advance our understanding of the real-world impacts of chemical pollution on wildlife behaviour. This review therefore provides a roadmap of the major outstanding questions in behavioural ecotoxicology and highlights the need for increased cross-talk with other disciplines in order to find the answers.
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- Ferizi, U., et al.
(author)
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Diffusion MRI microstructure models with in vivo human brain Connectome data: results from a multi-group comparison
- 2017
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In: NMR in Biomedicine. - : Wiley. - 0952-3480 .- 1099-1492. ; 30:9, s. Article no e3734 -
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Journal article (peer-reviewed)abstract
- A large number of mathematical models have been proposed to describe the measured signal in diffusion-weighted (DW) magnetic resonance imaging (MRI). However, model comparison to date focuses only on specific subclasses, e.g. compartment models or signal models, and little or no information is available in the literature on how performance varies among the different types of models. To address this deficiency, we organized the White Matter Modeling Challenge' during the International Symposium on Biomedical Imaging (ISBI) 2015 conference. This competition aimed to compare a range of different kinds of models in their ability to explain a large range of measurable in vivo DW human brain data. Specifically, we assessed the ability of models to predict the DW signal accurately for new diffusion gradients and b values. We did not evaluate the accuracy of estimated model parameters, as a ground truth is hard to obtain. We used the Connectome scanner at the Massachusetts General Hospital, using gradient strengths of up to 300mT/m and a broad set of diffusion times. We focused on assessing the DW signal prediction in two regions: the genu in the corpus callosum, where the fibres are relatively straight and parallel, and the fornix, where the configuration of fibres is more complex. The challenge participants had access to three-quarters of the dataset and their models were ranked on their ability to predict the remaining unseen quarter of the data. The challenge provided a unique opportunity for a quantitative comparison of diverse methods from multiple groups worldwide. The comparison of the challenge entries reveals interesting trends that could potentially influence the next generation of diffusion-based quantitative MRI techniques. The first is that signal models do not necessarily outperform tissue models; in fact, of those tested, tissue models rank highest on average. The second is that assuming a non-Gaussian (rather than purely Gaussian) noise model provides little improvement in prediction of unseen data, although it is possible that this may still have a beneficial effect on estimated parameter values. The third is that preprocessing the training data, here by omitting signal outliers, and using signal-predicting strategies, such as bootstrapping or cross-validation, could benefit the model fitting. The analysis in this study provides a benchmark for other models and the data remain available to build up a more complete comparison in the future.
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- Fork, Megan L., et al.
(author)
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Dosing the Coast: Leaking Sewage Infrastructure Delivers Large Annual Doses and Dynamic Mixtures of Pharmaceuticals to Urban Rivers
- 2021
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In: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 55:17, s. 11637-11645
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Journal article (peer-reviewed)abstract
- Pharmaceuticals are commonly detected at low concentrations in surface waters, where they disrupt biological and ecological processes. Despite their ubiquity, the annual mass of pharmaceuticals exported from watersheds is rarely quantified. We used liquid chromatography-mass spectroscopy to screen for 92 pharmaceuticals in weekly samples from an urban stream network in Baltimore, MD, USA, that lacks wastewater treatment effluents. Across the network, we detected 37 unique compounds, with higher concentrations and more compounds in streams with higher population densities. We also used concentrations and stream discharge to calculate annual pharmaceutical loads at the watershed outlet, which range from less than 1 kg to μ15 kg and are equivalent to tens of thousands of human doses. By calculating annual watershed mass balances for eight compounds, we show that μ0.05 to μ42% of the pharmaceuticals consumed by humans in this watershed are released to surface waters, with the importance of different pathways (leaking sewage vs treated wastewater effluent) differing among compounds. These results demonstrate the importance of developing, maintaining, and improving sewage infrastructure to protect water resources from pharmaceutical contamination.
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- Gardner, T. A., et al.
(author)
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Transparency and sustainability in global commodity supply chains
- 2019
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In: World Development. - : Elsevier BV. - 0305-750X .- 1873-5991. ; 121, s. 163-177
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Journal article (peer-reviewed)abstract
- Over the last few decades rapid advances in processes to collect, monitor, disclose, and disseminate information have contributed towards the development of entirely new modes of sustainability governance for global commodity supply chains. However, there has been very little critical appraisal of the contribution made by different transparency initiatives to sustainability and the ways in which they can (and cannot)influence new governance arrangements. Here we seek to strengthen the theoretical underpinning of research and action on supply chain transparency by addressing four questions: (1)What is meant by supply chain transparency? (2)What is the relevance of supply chain transparency to supply chain sustainability governance? (3)What is the current status of supply chain transparency, and what are the strengths and weaknesses of existing initiatives? and (4)What propositions can be advanced for how transparency can have a positive transformative effect on the governance interventions that seek to strengthen sustainability outcomes? We use examples from agricultural supply chains and the zero-deforestation agenda as a focus of our analysis but draw insights that are relevant to the transparency and sustainability of supply chains in general. We propose a typology to distinguish among types of supply chain information that are needed to support improvements in sustainability governance, and illustrate a number of major shortfalls and systematic biases in existing information systems. We also propose a set of ten propositions that, taken together, serve to expose some of the potential pitfalls and undesirable outcomes that may result from (inevitably)limited or poorly designed transparency systems, whilst offering guidance on some of the ways in which greater transparency can make a more effective, lasting and positive contribution to sustainability.
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