Considering the cumulative risk of mixtures of chemicals – A challenge for policy makers

<p>Abstract</p> <p>Background</p> <p>The current paradigm for the assessment of the health risk of chemical substances focuses primarily on the effects of individual substances for determining the doses of toxicological concern in order to inform appropriately the regulatory process. These policy instruments place varying requirements on health and safety data of chemicals in the environment. REACH focuses on safety of individual substances; yet all the other facets of public health policy that relate to chemical stressors put emphasis on the effects of combined exposure to mixtures of chemical and physical agents. This emphasis brings about methodological problems linked to the complexity of the respective exposure pathways; the effect (more complex than simple additivity) of mixtures (the so-called 'cocktail effect'); dose extrapolation, i.e. the extrapolation of the validity of dose-response data to dose ranges that extend beyond the levels used for the derivation of the original dose-response relationship; the integrated use of toxicity data across species (including human clinical, epidemiological and biomonitoring data); and variation in inter-individual susceptibility associated with both genetic and environmental factors.</p> <p>Methods</p> <p>In this paper we give an overview of the main methodologies available today to estimate the human health risk of environmental chemical mixtures, ranging from dose addition to independent action, and from ignoring interactions among the mixture constituents to modelling their biological fate taking into account the biochemical interactions affecting both internal exposure and the toxic potency of the mixture.</p> <p>Results</p> <p>We discuss their applicability, possible options available to policy makers and the difficulties and potential pitfalls in implementing these methodologies in the frame of the currently existing policy framework in the European Union. Finally, we suggest a pragmatic solution for policy/regulatory action that would facilitate the evaluation of the health effects of chemical mixtures in the environment and consumer products.</p> <p>Conclusions</p> <p>One universally applicable methodology does not yet exist. Therefore, a pragmatic, tiered approach to regulatory risk assessment of chemical mixtures is suggested, encompassing (a) the use of dose addition to calculate a hazard index that takes into account interactions among mixture components; and (b) the use of the connectivity approach in data-rich situations to integrate mechanistic knowledge at different scales of biological organization.</p

Weighted Sampling for Combined Model Selection and Hyperparameter Tuning

The combined algorithm selection and hyperparameter tuning (CASH) problem is characterized by large hierarchical hyperparameter spaces. Model-free hyperparameter tuning methods can explore such large spaces efficiently since they are highly parallelizable across multiple machines. When no prior knowledge or meta-data exists to boost their performance, these methods commonly sample random configurations following a uniform distribution. In this work, we propose a novel sampling distribution as an alternative to uniform sampling and prove theoretically that it has a better chance of finding the best configuration in a worst-case setting. In order to compare competing methods rigorously in an experimental setting, one must perform statistical hypothesis testing. We show that there is little-to-no agreement in the automated machine learning literature regarding which methods should be used. We contrast this disparity with the methods recommended by the broader statistics literature, and identify a suitable approach. We then select three popular model-free solutions to CASH and evaluate their performance, with uniform sampling as well as the proposed sampling scheme, across 67 datasets from the OpenML platform. We investigate the trade-off between exploration and exploitation across the three algorithms, and verify empirically that the proposed sampling distribution improves performance in all cases.Comment: Accepted for presentation at The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020

Spatially explicit multimedia fate models for pollutants in Europe: State of the art and perspectives

A review by Hollander et al. (in preparation), discusses the relative potentials, advantages and shortcomings of spatial and non spatial models of chemical fate, highlighting that spatially explicit models may be needed for specific purposes. The present paper reviews the state of the art in spatially explicit chemical fate and transport modeling in Europe. We summarize the three main approaches currently adopted in spatially explicit modeling, namely (1) multiple box models, (2) numerical solutions of simultaneous advection–dispersion equations (ADE) in air, soil and water, and (3) the development of meta-models. As all three approaches experience limitations, we describe in further detail geographic information system (GIS)-based modeling as an alternative approach allowing a simple, yet spatially explicit description of chemical fate. We review the input data needed, and the options available for their retrieval at the European scale. We also discuss the importance of, and limitations in model evaluation. We observe that the high uncertainty in chemical emissions and physico-chemical behavior in the environment make realistic simulations difficult to obtain. Therefore we envisage a shift in model use from process simulation to hypothesis testing, in which explaining the discrepancies between observed and computed chemical concentrations in the environment takes importance over prediction per se. This shift may take advantage of using simple models in GIS with residual uses of complex models for detailed studies. It also calls for tighter joint interpretation of models and spatially distributed monitoring datasets, and more refined spatial representation of environmental drivers such as landscape and climate variables, and better emission estimates. In summary, we conclude that the problem is not “how to compute” (i.e. emphasis on numerical methods, spatial/temporal discretization, quantitative uncertainty and sensitivity analysis…) but “what to compute” (i.e. emphasis on spatial distribution of emissions, and the depiction of appropriate spatial patterns of environmental drivers)

Η χρήση ενός CPS (Cyber-Physical System) με σκοπό την παρακολούθηση και άμεση ενημέρωση για την διαχείριση κρίσεων -Περιοχή Μελέτης : Μάνδρα Αττικής

Σκοπός της παρούσας διατριβής είναι η μελέτη του φαινομένου των στιγμιαίων πλημμυρών και συγκεκριμένα έχοντας για πεδίο μελέτης την περιοχή της Μάνδρας στην δυτική Αττική η οποία πλήχθηκε ακόμα μία φορά από μία στιγμιαία πλημμύρα που κόστισε την ζωή 23 ανθρώπων καθώς και η μελέτη χωροθέτησης ενός συστήματος έγκαιρης προειδοποίησης με δυνατότητες και καινοτομίες που μέχρι τώρα είχαν περιορισμένη εφαρμογή στον τομέα της διαχείρισης καταστροφών. Το ιστορικό της συγκεκριμένης περιοχής και η συχνότητα εμφάνισης τέτοιου είδους καιρικών φαινόμενων στην ευρύτερη περιοχή καθιστά την μελέτη απαραίτητη για την αποφυγή παρομοίων γεγονότων οποιασδήποτε κλίμακας. Για την υλοποίηση την εργασίας χρησιμοποιήθηκαν μετρήσεις(ύψος στάθμης νερού) οι οποίες πραγματοποιήθηκαν από την ερευνητική ομάδα του μεταπτυχιακού προγράμματος σπουδών στην περιοχή της καταστροφής καθώς και ψηφιακά μοντέλα εδάφους και επιφάνειας(DEM,DSM) τα οποία μου παρείχε η ερευνητική ομάδα. Η ανάλυση, επεξεργασία και εξαγωγή αποτελεσμάτων πραγματοποιήθηκε με την χρήση Συστήματος Γεωργαφικών Πληροφοριών(GIS) και συγκεκριμένα με τη χρήση του λογισμικού ArcGIS Desktop – Arc Map (ESRI) και του εργαλείου(SANET) που δημιουργήθηκε από τον Καθηγητή Atsu Okabe και την ομάδα του από το πανεπιστήμιο Aoyama Gakuin στο Τόκιο της Ιαπωνίας, μέσω του οποίου είχα την δυνατότητα να εξάγω σε μορφή χαρτών τον πλημμυρικό κίνδυνο της περιοχής. Εν συνεχεία συσχετίζοντας τα δεδομένα πεδίου, τους χάρτες και το θεωρητικό υπόβαθρο από τη βιβλιογραφία, δημιουργήθηκε ο τελικός χάρτης, όπου απεικονίζεται η χωροθέτηση ενός συστήματος έγκαιρης προειδοποίησης και παρακολούθησης(CPS) το οποίο αλληλοεπιδρά μεταξύ του φυσικού και του ψηφιακού κόσμου.The purpose of the present thesis is to study the phenomenon of flash floods and specifically to study the area of Mandra in western Attica, which was once more affected by an instantaneous flood that cost the lives of 23 people, as well as the study of the location of an early warning system with capabilities and innovations that until now have been limited in the field of disaster management. The history of this area and the frequency of such weather events in the wider area make the study necessary to avoid similar events of any scale. For the realization of the work measurements (height of water level) were carried out by the research team of the postgraduate program in the area where the destruction occurred as well as digital ground and surface models (DEM, DSM) provided by the research team. The analysis, processing and extraction of results was carried out using the GIS and in particular the ArcGIS Desktop - Arc Map (ESRI) and the SANET tool created by Professor Atsu Okabe and his team from the Aoyama Gakuin University in Tokyo, Japan, through which I was able to map out the flood risk of the area. Then, taking into account the field data, maps and theoretical background from the bibliography, the final map was created, depicting the scheduling of an early warning and tracking system (CPS) that interacts between the physical and the digital world. Λέξεις κλειδιά: Δυτική Αττική, Μάνδρα, στιγμιαίες πλημμύρες, Πλημμυρικός κίνδυνος, γεωγραφικά συστήματα πληροφοριών, ψηφιακό μοντέλο εδάφους, σύστημα έγκαιρης προειδοποίησης, διαχείριση καταστροφώ

AOP-helpFinder webserver: a tool for comprehensive analysis of the literature to support adverse outcome pathways development

Motivation: Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome. Results: Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment

Entrepreneurship, local development and the Green Region

The current financial crisis coupled with the pressure on the environment create the increasing need to deliver creative disruptions in the global economy if sustainable development is to be achieved. For this to happen, a regional environmental management system needs to be put together through the coordination of strategic local plans that may result in branding whole regions as “green”. This would have significant benefits to the local entreprises, especially if put in place through an entrepreneurial development action plan that would create an “entrpreneurial ecology”. This system would capture the sustainability potential offered by the dynamic interactions and innovation initiatives of market actors while reducing the exogenous energy and material flows of the economic system, and addressing efficiently the issue of sustainable consumption

Health impact assessment by the implementation of Madrid City air-quality plan in 2020

OBJECTIVES: Air pollutant concentrations in many urban areas are still above the legal and recommended limits that are set to protect the citizens' health. Madrid is one of the cities where traffic causes high NO2 levels. In this context, Madrid City Council launched the Air Quality and Climate Change Plan for the city of Madrid (Plan A), a local strategy approved by the previous government in 2017. The aim of this study was to conduct a quantitative health impact assessment to evaluate the number of premature deaths that could potentially be prevented by the implementation of Plan A in Madrid in 2020, at both citywide and within-city level. The main purpose was to support decision-making processes in order to maximize the positive health impacts from the implementation of Plan A measures. METHODS: The Regional Statistical Office provided information on population and daily mortality in Madrid. For exposure assessment, we estimated PM2.5, NO2 and O3 concentration levels for Madrid city in 2012 (baseline air-quality scenario) and 2020 (projected air-quality scenario based on the implementation of Plan A), by means of an Eulerian chemical-transport model with a spatial resolution of 1 km × 1 km and 30 vertical levels. We used the concentration-response functions proposed by two relevant WHO projects to calculate the number of attributable annual deaths corresponding to all non-accidental causes (ICD-10: A00-R99) among all-ages and the adult population (>30 years old) for each district and for Madrid city overall. This health impact assessment was conducted dependant on health-data availability. RESULTS: In 2020, the implementation of Plan A would imply a reduction in the Madrid citywide annual mean PM2.5 concentration of 0.6 μg/m3 and 4.0 μg/m3 for NO2. In contrast, an increase of 1 μg/m3 for O3 would be expected. The annual number of all-cause deaths from long-term exposure (95% CI) that could be postponed in the adult population by the expected air-pollutant concentration reduction was 88 (57-117) for PM2.5 and 519 (295-750) for NO2; short-term exposure accounted for 20 (7-32) for PM2.5 and 79 (47-111) for NO2 in the total population. According to the spatial distribution of air pollutants, the highest mortality change estimations were for the city centre - including Madrid Central and mainly within the M-30 ring road -, as compared to peripheral districts. The positive health impacts from the reductions in PM2.5 and NO2 far exceeded the adverse mortality effects expected from the increase in O3. CONCLUSIONS: Effective implementation of Plan A measures in Madrid city would bring about an appreciable decline in traffic-related air-pollutant concentrations and, in turn, would lead to significant health-related benefits.This HIA study was funded by the European Project ICARUS (Integrated Climate forcing and Air pollution Reduction in Urban Systems; Horizon 2020, GA N° 690105) and by SaludAire-España (Contaminación atmosférica y salud en España: morbilidad en atención primaria y mortalidad; Carlos III Health Institute, AESI grant PI18CIII/00022). Air-quality modelling was funded by the Madrid City Council (Environment and Mobility Division of the General Directorate of Sustainability and Environmental Control) within the framework for the development and assessment of Plan A.S