Multiscale Spatial Modeling of Human Exposure from Local Sources to Global Intake

Accessible methods and tools to estimate chemical exposure in humans to support risk assessment: A systematic scoping review

Exposure assessment is a crucial component of environmental health research, providing essential information on the potential risks associated with various chemicals. A systematic scoping review was conducted to acquire an overview of accessible human exposure assessment methods and computational tools to support and ultimately improve risk assessment. The systematic scoping review was performed in Sysrev, a web platform that introduces machine learning techniques into the review process aiming for increased accuracy and efficiency. Included publications were restricted to a publication date after the year 2000, where exposure methods were properly described. Exposure assessments methods were found to be used for a broad range of environmental chemicals including pesticides, metals, persistent chemicals, volatile organic compounds, and other chemical classes. Our results show that after the year 2000, for all the types of exposure routes, probabilistic analysis, and computational methods to calculate human exposure have increased. Sixty-three mathematical models and toolboxes were identified that have been developed in Europe, North America, and globally. However, only twelve occur frequently and their usefulness were associated with exposure route, chemical classes and input parameters used to estimate exposure. The outcome of the combined associations can function as a basis and/or guide for decision making for the selection of most appropriate method and tool to be used for environmental chemical human exposure assessments in Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment (ONTOX) project and elsewhere. Finally, the choice of input parameters used in each mathematical model and toolbox shown by our analysis can contribute to the harmonization process of the exposure models and tools increasing the prospect for comparison between studies and consistency in the regulatory process in the future.

Space-specific flux estimation of atmospheric chemicals from point sources to soil

Predicting chemical flux to soil from industrial point sources accurately at a regional scale has been a significant challenge due to high uncertainty in spatial heterogeneity and quantification. To address this challenge, we developed an innovative approach by combining California Air Resources Board Puff (CALPUFF) and mass balance models, leveraging their complementary strengths in quantitative accuracy and spatial precision. Specifically, CALPUFF was used to predict the polycyclic aromatic hydrocarbons (PAHs) flux to soil due to industrial sources. Additionally, the spatial distribution coefficient of PAHs flux (e.g., si for spatial unit i) was calculated by neural network and combined with the mass balance model to obtain the results of total PAHs fluxes, which were then combined with the results predicted by CALPUFF to effectively estimate the contribution of industrial sources to soil PAHs flux. Taking a petrochemical industry region located in Zhejiang province, China as a case study, results showed the input Phenanthrene (Phe) and Benzo(a)pyrene (BaP) fluxes predicted by CALPUFF were generally lower than those by the mass balance model, with slightly different distribution patterns. CALPUFF results, based on 36 industrial sources, partially represent those of the mass balance model, which includes all sources and pathways. It was suggested that industrial sources contributed 49%-89% and 65%-100% of soil Phe and BaP, respectively across the study area. The average Phe flux from point sources by deposition averaged 2.68 mg m-2∙a-1 in 2021, accounting for approximately 60% of the total Phe flux to soil. The average BaP flux from point sources by deposition averaged 0.0755 mg m-2∙a-1, accounting for only 0.1%-3.65% of the total BaP flux to soil. Thereby, our approach fills up a gap between the relevance to point sources and the accuracy of deposition quantification in estimating chemical flux from specific point sources to soil at a regional scale.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

A PETAR method for risk assessment of human health and environment on the regional scale

Risk assessments are necessary to effectively reveal the state of the degradation of living environments on a regional scale. However, risk assessments are often limited by time, cost, and technology, which make conducting effective evaluations difficult. Thus, in this study, the procedure for ecological tiered assessment of risk (PETAR) method was used to analyze the human health and environmental risks in Daye, China. This method first used the United States Environmental Protection Agency's risk assessment approach to qualitatively determine the risk sources, pressures, receptors, and effect endpoints and constructed a conceptual model of threats to the human living environment. Each risk-prone subregion was then evaluated using the fuzzy logic method. Next, a quantitative assessment was conducted for the subregions with the most serious environmental degradation. Finally, quantitative analyses were performed to verify the original hypotheses. The results showed that the high-risk areas were distributed in the industrial regions of Daye, wherein mining and processing clusters and mining settlements are widespread and confirmed the locations of the particular subregions with the most serious human health and environmental risks. This study also validated the practicality of the PETAR method for human health risk assessments in mining areas with large-scale, multifactor, and multihazard paths. Integr Environ Assess Manag 2023;19:239-253. © 2022 SETAC.

Spatially resolved environmental fate models: A review

Spatially resolved environmental models are important tools to introduce and highlight the spatial variability of the real world into modeling. Although various spatial models have been developed so far, yet the development and evaluation of these models remain a challenging task due to several difficulties related to model setup, computational cost, and obtaining high-resolution input data (e.g., monitoring and emission data). For example, atmospheric transport models can be used when high resolution predicted concentrations in atmospheric compartments are required, while spatial multimedia fate models may be preferred for regulatory risk assessment, life cycle impact assessment of chemicals, or when the partitioning of chemical substances in a multimedia environment is considered. The goal of this paper is to review and compare different spatially resolved environmental models, according to their spatial, temporal and chemical domains, with a closer insight into spatial multimedia fate models, to achieve a better understanding of their strengths and limitations. This review also points out several requirements for further improvement of existing models as well as for their integration.

Modeling pesticides in global surface soils: Evaluating spatiotemporal patterns for USEtox-based steady-state concentrations

To better manage pesticide pollution in surface soils, we introduced a first-order-kinetics-based screening model to evaluate the steady-state concentrations of pesticides in surface soils while considering degradation, volatilization, plant uptake, and precipitation processes. For each process, we developed a spatiotemporal-pattern-based model using spatiotemporal variables, including air temperature (T_A), relative humidity (RH_A), and rainfall intensity (I_R^A), to characterize the overall dissipation rates (k_T) of pesticides in the soil. These dissipation rates were converted to fate factors (FFs), which are commonly used in life cycle analyses. The results indicate that, in general, the k_T values increase with increasing T_A and I_R^A and decrease with increasing RH_A. This is because increased T_A boosts the degradation, volatilization, and plant uptake processes, whereas increased RH_A lowers the plant transpiration rate. Also, the simulation for over 700 pesticides indicated that the degradation process dominates the overall dissipation of most pesticides in the soil, and the volatilization process contributes the least. In addition, we simulated chlorpyrifos FFs for Brazil, China, the US, and the European Union (EU) using the annual average T_A, RH_A, and I_R^A values. The results indicate that, in general, Brazilian federal units have the smallest FFs and the narrowest simulated FF range because of their humid tropical climates. Meanwhile, the EU member states have the largest FFs and the widest FF range because of their range in locations. In addition, our simulated results show that the surface soils in the high-latitude regions could accumulate more chlorpyrifos than those in low-latitude regions because of the larger simulated FFs. Furthermore, we parameterized our model using 737 pesticides with the USEtox, thereby providing an alternative approach to simulate the steady-state concentration of pesticides in surface soils from the USEtox available data. The model developed herein is a useful screening tool for predicting pesticide concentrations in surface soil worldwide to improve soil and ecological health risk management.

Building a European exposure science strategy

Exposure information is a critical element in various regulatory and non-regulatory frameworks in Europe and elsewhere. Exposure science supports to ensure safe environments, reduce human health risks, and foster a sustainable future. However, increasing diversity in regulations and the lack of a professional identity as exposure scientists currently hamper developing the field and uptake into European policy. In response, we discuss trends, and identify three key needs for advancing and harmonizing exposure science and its application in Europe. We provide overarching building blocks and define six long-term activities to address the identified key needs, and to iteratively improve guidelines, tools, data, and education. More specifically, we propose creating European networks to maximize synergies with adjacent fields and identify funding opportunities, building common exposure assessment approaches across regulations, providing tiered education and training programmes, developing an aligned and integrated exposure assessment framework, offering best practices guidance, and launching an exposure information exchange platform. Dedicated working groups will further specify these activities in a consistent action plan. Together, these elements form the foundation for establishing goals and an action roadmap for successfully developing and implementing a 'European Exposure Science Strategy' 2020-2030, which is aligned with advances in science and technology.

Spatial variability of ecosystem exposure to home and personal care chemicals in Asia

It is well recognized that there are currently limitations in the spatial and temporal resolution of environmental exposure models due to significant variabilities and uncertainties in model inputs and parameters. Here we present the updated Pangea multi-scale multimedia model based on the more spatially resolved, catchment-based hydrological HydroBASINS dataset covering the entire globe. We apply it to predict spatially-explicit exposure concentrations of linear alkylbenzene sulphonate (LAS) and triclosan (TCS) as two chemicals found in homecare (HC) and personal care (PC) products in river catchments across Asia, and test its potential for identifying/prioritizing catchments with higher exposure concentrations. In addition, we also identify the key parameters in the model framework driving higher concentrations and perform uncertainty analyses by applying Monte Carlo simulations on emissions and other non-spatial model inputs. The updated combination of Pangea with the HydroBASINS hydrological data represents a substantial improvement from the previous model with the gridded hydrological dataset (WWDRII) for modelling substance fate, with higher resolution and improved coverage in regions with lower flows, with the results demonstrating good agreement with monitored concentrations for TCS in both the freshwater (R² = 0.55) and sediment (R² = 0.81) compartments. The ranking of water basins by Predicted Environmental Concentrations (PECs) was similar for both TCS and LAS, with highest concentrations (Indus, Huang He, Cauvery, Huai He and Ganges) being one to two orders of magnitude greater than the water basins with lowest predicted PECs (Mekong and Brahmaputra). Emissions per unit volume of each catchment, chemical persistence, and river discharge were deemed to be the most influential factors on the variation of predicted PECs. Focusing on the Huang He (Yellow River) water basin, uncertainty confidence intervals (factor 31 for LAS and 6 for TCS) are much lower than the variability of predicted PECs across the Huang He catchments (factors 90,700 for LAS and 13,500 for TCS).

Overview and recommendations for regionalized life cycle impact assessment

PURPOSE

Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still faces multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicated cross-cutting working group on regionalized LCIA aims to provides an overview of the status of regionalization in LCIA methods. We give guidance and recommendations to harmonize and support regionalization in LCIA for developers of LCIA methods, LCI databases, and LCA software.

METHOD

A survey of current practice among regionalized LCIA method developers was conducted. The survey included questions on chosen method spatial resolution and scale, the spatial resolution of input parameters, choice of native spatial resolution and limitations, operationalization and alignment with life cycle inventory data, methods for spatial aggregation, the assessment of uncertainty from input parameters and model structure, and variability due to spatial aggregation. Recommendations are formulated based on the survey results and extensive discussion by the authors.

RESULTS AND DISCUSSION

Survey results indicate that majority of regionalized LCIA models have global coverage. Native spatial resolutions are generally chosen based on the availability of global input data. Annual modelled or measured elementary flow quantities are mostly used for aggregating characterization factors (CFs) to larger spatial scales, although some use proxies, such as population counts. Aggregated CFs are mostly available at the country level. Although uncertainty due to input parameter, model structure, and spatial aggregation are available for some LCIA methods, they are rarely implemented for LCA studies. So far, there is no agreement if a finer native spatial resolution is the best way to reduce overall uncertainty. When spatially differentiated models CFs are not easily available, archetype models are sometimes developed.

CONCLUSIONS

Regionalized LCIA methods should be provided as a transparent and consistent set of data and metadata using standardized data formats. Regionalized CFs should include both uncertainty and variability. In addition to the native-scale CFs, aggregated CFs should always be provided, and should be calculated as the weighted averages of constituent CFs using annual flow quantities as weights whenever available. This paper is an important step forward for increasing transparency, consistency and robustness in the development and application of regionalized LCIA methods.

Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways

Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study, chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources-consumer (near-field), dietary, far-field industrial, and far-field pesticide-to the general population. The balanced accuracies of these source-based exposure pathway models range from 73 to 81%, with the error rate for identifying positive chemicals ranging from 17 to 36%. We then used exposure pathways to organize predictions from 13 different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R² of ∼0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479 926 chemicals, mostly with minimal exposure information. This approach identifies 1880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 μg/kg BW/day for 474572 compounds.

Advancements in Life Cycle Human Exposure and Toxicity Characterization

BACKGROUND

The Life Cycle Initiative, hosted at the United Nations Environment Programme, selected human toxicity impacts from exposure to chemical substances as an impact category that requires global guidance to overcome current assessment challenges. The initiative leadership established the Human Toxicity Task Force to develop guidance on assessing human exposure and toxicity impacts. Based on input gathered at three workshops addressing the main current scientific challenges and questions, the task force built a roadmap for advancing human toxicity characterization, primarily for use in life cycle impact assessment (LCIA).

OBJECTIVES

The present paper aims at reporting on the outcomes of the task force workshops along with interpretation of how these outcomes will impact the practice and reliability of toxicity characterization. The task force thereby focuses on two major issues that emerged from the workshops, namely considering near-field exposures and improving dose–response modeling.

DISCUSSION

The task force recommended approaches to improve the assessment of human exposure, including capturing missing exposure settings and human receptor pathways by coupling additional fate and exposure processes in consumer and occupational environments (near field) with existing processes in outdoor environments (far field). To quantify overall aggregate exposure, the task force suggested that environments be coupled using a consistent set of quantified chemical mass fractions transferred among environmental compartments. With respect to dose–response, the task force was concerned about the way LCIA currently characterizes human toxicity effects, and discussed several potential solutions. A specific concern is the use of a (linear) dose–response extrapolation to zero. Another concern addresses the challenge of identifying a metric for human toxicity impacts that is aligned with the spatiotemporal resolution of present LCIA methodology, yet is adequate to indicate health impact potential.

CONCLUSIONS

Further research efforts are required based on our proposed set of recommendations for improving the characterization of human exposure and toxicity impacts in LCIA and other comparative assessment frameworks. https://doi.org/10.1289/EHP3871.

Source-to-exposure assessment with the Pangea multi-scale framework - case study in Australia

Effective planning of airshed pollution mitigation is often constrained by a lack of integrative analysis able to relate the relevant emitters to the receptor populations at risk. Both emitter and receptor perspectives are therefore needed to consistently inform emission and exposure reduction measures. This paper aims to extend the Pangea spatial multi-scale multimedia framework to evaluate source-to-receptor relationships of industrial sources of organic pollutants in Australia. Pangea solves a large compartmental system in parallel by block to determine arrays of masses at steady-state for 100 000+ compartments and 4000+ emission scenarios, and further computes population exposure by inhalation and ingestion. From an emitter perspective, radial spatial distributions of population intakes show high spatial variation in intake fractions from 0.68 to 33 ppm for benzene, and from 0.006 to 9.5 ppm for formaldehyde, contrasting urban, rural, desert, and sea source locations. Extending analyses to the receptor perspective, population exposures from the combined emissions of 4101 Australian point sources are more extended for benzene that travels over longer distances, versus formaldehyde that has a more local impact. Decomposing exposure per industrial sector shows petroleum and steel industry as the highest contributing industrial sectors for benzene, whereas the electricity sector and petroleum refining contribute most to formaldehyde exposures. The source apportionment identifies the main sources contributing to exposure at five locations. Overall, this paper demonstrates high interest in addressing exposures from both an emitter perspective well-suited to inform product oriented approaches such as LCA, and from a receptor perspective for health risk mitigation.