Suspect and non-targeted screening of chemicals of emerging concern for human biomonitoring, environmental health studies and support to risk assessment: From promises to challenges and harmonisation issues.

Large-scale suspect and non-targeted screening approaches based on high-resolution mass spectrometry (HRMS) are today available for chemical profiling and holistic characterisation of biological samples. These advanced techniques allow the simultaneous detection of a large number of chemical features, including markers of human chemical exposure. Such markers are of interest for biomonitoring, environmental health studies and support to risk assessment. Furthermore, these screening approaches have the promising capability to detect chemicals of emerging concern (CECs), document the extent of human chemical exposure, generate new research hypotheses and provide early warning support to policy. Whilst of growing importance in the environment and food safety areas, respectively, CECs remain poorly addressed in the field of human biomonitoring. This shortfall is due to several scientific and methodological reasons, including a global lack of harmonisation. In this context, the main aim of this paper is to present an overview of the basic principles, promises and challenges of suspect and non-targeted screening approaches applied to human samples as this specific field introduce major specificities compared to other fields. Focused on liquid chromatography coupled to HRMS-based data acquisition methods, this overview addresses all steps of these new analytical workflows. Beyond this general picture, the main activities carried out on this topic within the particular framework of the European Human Biomonitoring initiative (project HBM4EU, 2017-2021) are described, with an emphasis on harmonisation measures.

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.

The exposome - a new approach for risk assessment.

Complementing the human genome with an exposome reflects the increasingly obvious impact of environmental exposure, which far exceeds the role of genetics, on human health. Considering the complexity of exposures and, in addition, the reactions of the body to exposures - i.e., the exposome - reverses classical exposure science where the precise measurement of single or few exposures is associated with specific health or environmental effects. The complete description of an individual's exposome is impossible; even less so is that of a population. We can, however, cast a wider net by foregoing some rigor in assessment and compensating with the statistical power of rich datasets. The advent of omics technologies enables a relatively cheap, high-content description of the biological effects of substances, especially in tissues and biofluids. They can be combined with many other rich data-streams, creating big data of exposure and effect. Computational methods increasingly allow data integration, discerning the signal from the noise and formulating hypotheses of exposure-effect relationships. These can be followed up in a targeted way. With a better exposure element in the risk equation, exposomics - new kid on the block of risk assessment - promises to identify novel exposure (interactions) and health/environment effect associations. This may also create opportunities to prioritize the more relevant chemicals for risk assessment, thereby lowering the burden on hazard assessment in an expo-sure-driven approach. Technological developments and synergies between approaches, quality assurance (ultimately as Good Exposome Practices), and the integration of mechanistic thinking will advance this approach.

Development of Policy Relevant Human Biomonitoring Indicators for Chemical Exposure in the European Population.

The European Union's 7th Environmental Action Programme (EAP) aims to assess and minimize environmental health risks from the use of hazardous chemicals by 2020. From this angle, policy questions like whether an implemented policy to reduce chemical exposure has had an effect over time, whether the health of people in specific regions or subpopulations is at risk, or whether the body burden of chemical substances (the internal exposure) varies with, for example, time, country, sex, age, or socio-economic status, need to be answered. Indicators can help to synthesize complex scientific information into a few key descriptors with the purpose of providing an answer to a non-expert audience. Human biomonitoring (HBM) indicators at the European Union (EU) level are unfortunately lacking. Within the Horizon2020 European Human Biomonitoring project HBM4EU, an approach to develop European HBM indicators was worked out. To learn from and ensure interoperability with other European indicators, 15 experts from the HBM4EU project (German Umweltbundesamt (UBA), Flemish research institute VITO, University of Antwerp, European Environment Agency (EEA)), and the World Health Organization (WHO), European Core Health Indicator initiative (ECHI), Eurostat, Swiss ETH Zurich and the Czech environmental institute CENIA, and contributed to a workshop, held in June 2017 at the EEA in Copenhagen. First, selection criteria were defined to evaluate when and if results of internal chemical exposure measured by HBM, need to be translated into a European HBM-based indicator. Two main aspects are the HBM indicator's relevance for policy, society, health, and the quality of the biomarker data (availability, comparability, ease of interpretation). Secondly, an approach for the calculation of the indicators was designed. Two types of indicators were proposed: 'sum indicators of internal exposure' derived directly from HBM biomarker concentrations and 'indicators for health risk', comparing HBM concentrations to HBM health-based guidance values (HBM HBGVs). In the latter case, both the percentage of the studied population exceeding the HBM HBGVs (PE) and the extent of exceedance (EE), calculated as the population's exposure level divided by the HBM HBGV, can be calculated. These indicators were applied to two examples of hazardous chemicals: bisphenol A (BPA) and per- and polyfluoroalkyl substances (PFASs), which both have high policy and societal relevance and for which high quality published data were available (DEMOCOPHES, Swedish monitoring campaign). European HBM indicators help to summarize internal exposure to chemical substances among the European population and communicate to what degree environmental policies are successful in keeping internal exposures sufficiently low. The main aim of HBM indicators is to allow follow-up of chemical safety in Europe.

Public health impacts of city policies to reduce climate change: findings from the URGENCHE EU-China project.

BACKGROUND: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments. METHODS: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys. RESULTS: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied. CONCLUSIONS: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries.

Health impact assessment of transport policies in Rotterdam: Decrease of total traffic and increase of electric car use.

BACKGROUND: Green house gas (GHG) mitigation policies can be evaluated by showing their co-benefits to health. METHOD: Health Impact Assessment (HIA) was used to quantify co-benefits of GHG mitigation policies in Rotterdam. The effects of two separate interventions (10% reduction of private vehicle kilometers and a share of 50% electric-powered private vehicle kilometers) on particulate matter (PM2.5), elemental carbon (EC) and noise (engine noise and tyre noise) were assessed using Years of Life Lost (YLL) and Years Lived with Disability (YLD). The baseline was 2010 and the end of the assessment 2020. RESULTS: The intervention aimed at reducing traffic is associated with a decreased exposure to noise resulting in a reduction of 21 (confidence interval (CI): 11-129) YLDs due to annoyance and 35 (CI: 20-51) YLDs due to sleep disturbance for the population per year. The effects of 50% electric-powered car use are slightly higher with a reduction of 26 (CI: 13-116) and 41 (CI: 24-60) YLDs, respectively. The two interventions have marginal effects on air pollution, because already implemented traffic policies will reduce PM2.5 and EC by around 40% and 60% respectively, from 2010 to 2020. DISCUSSION: The evaluation of planned interventions, related to climate change policies, targeting only the transport sector can result in small co-benefits for health, if the analysis is limited to air pollution and noise. This urges to expand the analysis by including other impacts, e.g. physical activity and well-being, as a necessary step to better understanding consequences of interventions and carefully orienting resources useful to build knowledge to improve public health.