Assessing personal exposure using Agent Based Modelling informed by sensors technology.

Technology innovations create possibilities to capture exposure-related data at a great depth and breadth. Considering, though, the substantial hurdles involved in collecting individual data for whole populations, this study introduces a first approach of simulating human movement and interaction behaviour, using Agent Based Modelling (ABM). A city scale ABM was developed for urban Thessaloniki, Greece that feeds into population-based exposure assessment without imposing prior bias, basing its estimations onto emerging properties of the behaviour of the computerised autonomous decision makers (agents) that compose the city-system. Population statistics, road and buildings networks data were transformed into human, road and building agents, respectively. Survey outputs with time-use patterns were associated with human agent rules, aiming to model representative to real-world behaviours. Moreover, time-geography of exposure data, derived from a local sensors campaign, was used to inform and enhance the model. As a prevalence of an agent-specific decision-making, virtual individuals of different sociodemographic backgrounds express different spatiotemporal behaviours and their trajectories are coupled with spatially resolved pollution levels. Personal exposure was evaluated by assigning PM concentrations to human agents based on coordinates, type of location and intensity of encountered activities. Study results indicated that PM2.5 inhalation adjusted exposure between housemates can differ by 56.5% whereas exposure between two neighbours can vary by as much as 87%, due to the prevalence of different behaviours. This study provides details of a new methodology that permits the cost-effective construction of refined time-activity diaries and daily exposure profiles, taking into account different microenvironments and sociodemographic characteristics. The proposed method leads to a refined exposure assessment model, addressing effectively vulnerable subgroups of population. It can be used for evaluating the probable impacts of different public health policies prior to implementation reducing, therefore, the time and expense required to identify efficient measures.

Development of a generic lifelong physiologically based biokinetic model for exposome studies.

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of µg/L.

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.

Biomarkers of exposure in environment-wide association studies - Opportunities to decode the exposome using human biomonitoring data.

BACKGROUND: The European Union's 7th Framework Programme (EU's FP7) project HEALS - Health and Environment-wide Associations based on Large Population Surveys - aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited. OBJECTIVES: The objective was to summarize the availability of BoEs for a broad range of environmental stressors and exposure determinants and corresponding reference and exposure limit values and biomonitoring equivalents useful for unraveling the exposome using the framework of environment-wide association studies (EWAS). METHODS: In a face-to-face group discussion, scope, content, and structure of the HEALS deliverable "Guidelines for appropriate BoE selection for EWAS studies" were determined. An expert-driven, distributed, narrative review process involving around 30 individuals of the HEALS consortium made it possible to include extensive information targeted towards the specific characteristics of various environmental stressors and exposure determinants. From the resulting 265 page report, targeted information about BoE, corresponding reference values (e.g., 95th percentile or measures of central tendency), exposure limit values (e.g., the German HBM I and II values) and biomonitoring equivalents (BEs) were summarized and updated. RESULTS: 64 individual biological, chemical, physical, psychological and social environmental stressors or exposure determinants were included to fulfil the requirements of EWAS. The list of available BoEs is extensive with a number of 135; however, 12 of the stressors and exposure determinants considered do not leave any measurable specific substance in accessible body specimens. Opportunities to estimate the internal exposure stressors not (yet) detectable in human specimens were discussed. CONCLUSIONS: Data about internal exposures are useful to decode the exposome. The paper provides extensive information for EWAS. Information included serves as a guideline - snapshot in time without any claim to comprehensiveness - to interpret HBM data and offers opportunities to collect information about the internal exposure of stressors if no specific BoE is available.

Human biomonitoring data analysis for metals in an Italian adolescents cohort: An exposome approach.

The first Italian human biomonitoring survey (PROBE - PROgramme for Biomonitoring general population Exposure) considered a reference population of adolescents, aged 13-15 years, living in urban and rural areas and investigated their exposure to metals. The study was expanded up to 453 adolescents living in the same areas of Latium Region (Italy) and blood samples were analyzed for 19 metals (As, Be, Cd, Co, Cr, Hg, Ir, Mn, Mo, Ni, Pb, Pd, Pt, Rh, Sb, Sn, Tl, V, and W) by sector field inductively coupled plasma mass spectrometry. The exposure assessment was contextualized following an exposome approach that considered several determinants related to the subjects, available environmental parameters and geo-coding of residence address. To assess the influence of exposure determinants and modifiers on children biomarkers levels we used two independent methodologies. The first makes use of the so-called Environment-Wide Association Study (EWAS) methodology while the second was based on the application of a Generalized Liner Model (GLM) capturing co-exposures to pairs of key determinants. Based on our analysis, Hg and As were positively associated with dietary pathways (primarily linked to fish and to a lesser extent to milk consumption) while Cr showed a more complex interaction between co-exposure to different dietary pathways (milk and fish) coupled to proximity of residence to industrial activities. In addition to diet, socio-economic status of the mother revealed robust statistical associations with Cd, Ni and W biomonitoring levels in the respective children.

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign.

Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.

User-Centred Design of a Final Results Report for Participants in Multi-Sensor Personal Air Pollution Exposure Monitoring Campaigns.

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies, enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of the results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user-centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n = 82), and feedback on the draft report was obtained from a focus group (n = 5). User requirements were assessed and validated using a post-campaign survey (n = 31). The UCD research was conducted amongst participants in Ljubljana, Slovenia, and the results report was distributed among the participating cities across Europe. The feedback made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution.

Bayesian algorithm implementation in a real time exposure assessment model on benzene with calculation of associated cancer risks.

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations.

How Sensors Might Help Define the External Exposome.

The advent of the exposome concept, the advancement of mobile technology, sensors, and the "internet of things" bring exciting opportunities to exposure science. Smartphone apps, wireless devices, the downsizing of monitoring technologies, along with lower costs for such equipment makes it possible for various aspects of exposure to be measured more easily and frequently. We discuss possibilities and lay out several criteria for using smart technologies for external exposome studies. Smart technologies are evolving quickly, and while they provide great promise for advancing exposure science, many are still in developmental stages and their use in epidemiology and risk studies must be carefully considered. The most useable technologies for exposure studies at this time relate to gathering exposure-factor data, such as location and activities. Development of some environmental sensors (e.g., for some air pollutants, noise, UV) is moving towards making the use of these more reliable and accessible to research studies. The possibility of accessing such an unprecedented amount of personal data also comes with various limitations and challenges, which are discussed. The advantage of improving the collection of long term exposure factor data is that this can be combined with more "traditional" measurement data to model exposures to numerous environmental factors.

Integrated exposure and risk characterization of bisphenol-A in Europe.

The current study aims at a comprehensive risk characterization of bisphenol A (BPA) supported by an integrated exposure modelling framework that comprises far field and near field exposure modelling coupled to a dynamic lifetime PBTK model. Exposure analysis was done on European data of BPA food residues and human biomonitoring (HBM). The latter were further assimilated through an advanced exposure reconstruction modelling framework to estimate the corresponding external and internal systemic dose of BPA and its metabolites. Special attention was paid on the assessment of exposure to BPA during critical developmental stages such as gestation by modelling the mother-fetus toxicokinetic interaction. Our findings showed that current exposure levels in Europe are below the temporary Tolerable Daily Intake (t-TDI) of 4 µg/kg_bw/d proposed by the European Food Safety Authority. Taking into account age-dependent bioavailability differences, internal exposure of premature neonates hosted in intensive care units was reckoned close to the biologically effective dose (BED) resulting from translating the EFSA temporary total daily intake (t-TDI) into equivalent internal dose. Use of the ToxCast21 Biological Pathway Altering Dose (BPAD) as an alternative internal exposure reference value, resulted in increased margins of safety compared to the conventional exposure/risk characterization scheme.

A methodological frame for assessing benzene induced leukemia risk mitigation due to policy measures.

The study relies on the development of a methodology for assessing the determinants that comprise the overall leukemia risk due to benzene exposure and how these are affected by outdoor and indoor air quality regulation. An integrated modeling environment was constructed comprising traffic emissions, dispersion models, human exposure models and a coupled internal dose/biology-based dose-response risk assessment model, in order to assess the benzene imposed leukemia risk, as much as the impact of traffic fleet renewal and smoking banning to these levels. Regarding traffic fleet renewal, several "what if" scenarios were tested. The detailed full-chain methodology was applied in a South-Eastern European urban setting in Greece and a limited version of the methodology in Helsinki. Non-smoking population runs an average risk equal to 4.1·10(-5) compared to 23.4·10(-5) for smokers. The estimated lifetime risk for the examined occupational groups was higher than the one estimated for the general public by 10-20%. Active smoking constitutes a dominant parameter for benzene-attributable leukemia risk, much stronger than any related activity, occupational or not. From the assessment of mitigation policies it was found that the associated leukemia risk in the optimum traffic fleet scenario could be reduced by up to 85% for non-smokers and up to 8% for smokers. On the contrary, smoking banning provided smaller gains for (7% for non-smokers, 1% for smokers), while for Helsinki, smoking policies were found to be more efficient than traffic fleet renewal. The methodology proposed above provides a general framework for assessing aggregated exposure and the consequent leukemia risk from benzene (incorporating mechanistic data), capturing exposure and internal dosimetry dynamics, translating changes in exposure determinants to actual changes in population risk, providing a valuable tool for risk management evaluation and consequently to policy support.

Exposure to major volatile organic compounds and carbonyls in European indoor environments and associated health risk.

This paper summarizes recent data on the occurrence of major organic compounds (benzene, toluene, xylenes, styrene, acetaldehyde, formaldehyde, naphthalene, limonene, α-pinene and ammonia, classified by the European Commission's INDEX strategy report as the priority pollutants to be regulated) and evaluates accordingly cancer and non-cancer risks posed by indoor exposure in dwellings and public buildings in European Union (EU) countries. The review process indicated that significant differences in indoor air quality exist within and among the countries where data were available, indicating corresponding differences in sources and emission strength of airborne chemicals, identified or not. Conservative exposure limits were not exceeded for non-carcinogenic effects, except for formaldehyde; for carcinogenic agents the estimated risks were up to three orders of magnitude higher than the one (10(-6)) proposed as acceptable by risk management bodies. However, the risk assessment evaluation process faces crucial difficulties, either due to the relative paucity of indoor air quality measurements in many EU countries, or by the lack of sampling consistency in the already existing studies, indicating the need for additional measurements of indoor air quality following a harmonized sampling and analytical protocol. Additionally, uncertainties embodied in the cancer potency factors and exposure limit values impose further difficulties in substance prioritization and risk management.