Cumulative risk assessment and environmental equity in air permitting: interpretation, methods, community participation and implementation of a unique statute

Citizen science in environmental health research: A comparison with conventional approaches and creation of a guidance tool issued from the LILAS initiative

CONTEXT

Public interest for citizen science (CS) in environmental health is growing. The goals of environmental health research projects are diverse, as are the methods used to reach these goals. Opportunities for greater implication of the civil society and related challenges differ at each step of such projects. These methodological aspects need to be widely shared and understood by all stakeholders. The LILAS initiative (acronym for "application of citizen science approaches such as LIving LAbS to research on environmental exposures and chronic risks") aimed to 1) favor a mutual understanding of the main issues and research methods in environmental health, of their stakes for different actors, but also of the requirements, strengths and limitations of these methods and to 2) identify expected benefits and points of attention related to stronger degrees of participation as part of environmental health research projects.

METHODS

The LILAS initiative gathered institutional researchers, academics and civil society representatives interested in environmental exposures. Five meetings allowed to collectively identify different types of environmental health research studies and reflect about the benefits, limitations, and methodological issues related to the introduction of growing citizen participation as part of such studies. An analytic table matrix summarizing these aspects was co-created and filled by participants, as a tool devoted to help stakeholders with the definition of future CS research projects in environmental health.

RESULTS

For different fields of research (e.g.: studies for assessment of environmental exposures, interventions on these exposures, quantitative risk assessment, epidemiological studies), the matrix lists expected benefits for various stakeholders, the fundamental principles of research methods and related practical constraints, but also advantages and limitations related to the use of CS or conventional research approaches.

CONCLUSION

The LILAS initiative allowed to develop a tool which provides consolidated grounds for the co-creation of research projects on environmental exposures involving CS.

Selecting Data Analytic and Modeling Methods to Support Air Pollution and Environmental Justice Investigations: A Critical Review and Guidance Framework

Given the serious adverse health effects associated with many pollutants, and the inequitable distribution of these effects between socioeconomic groups, air pollution is often a focus of environmental justice (EJ) research. However, EJ analyses that aim to illuminate whether and how air pollution hazards are inequitably distributed may present a unique set of requirements for estimating pollutant concentrations compared to other air quality applications. Here, we perform a scoping review of the range of data analytic and modeling methods applied in past studies of air pollution and environmental injustice and develop a guidance framework for selecting between them given the purpose of analysis, users, and resources available. We include proxy, monitor-based, statistical, and process-based methods. Upon critically synthesizing the literature, we identify four main dimensions to inform method selection: accuracy, interpretability, spatiotemporal features of the method, and usability of the method. We illustrate the guidance framework with case studies from the literature. Future research in this area includes an exploration of increasing data availability, advanced statistical methods, and the importance of science-based policy.

Framing Environmental Health Decision-Making: The Struggle over Cumulative Impacts Policy

Little progress has been made to advance U.S. federal policy responses to growing scientific findings about cumulative environmental health impacts and risks, which also show that many low income and racial and ethnic minority populations bear a disproportionate share of multiple environmental burdens. Recent scholarship points to a “standard narrative” by which policy makers rationalize their slow efforts on environmental justice because of perceived lack of data and analytical tools. Using a social constructivist approach, ethnographic research methods, and content analysis, we examined the social context of policy challenges related to cumulative risks and impacts in the state of Maryland between 2014 and 2016. We identified three frames about cumulative impacts as a health issue through which conflicts over such policy reforms materialize and are sustained: (a) perceptions of evidence, (b) interpretations of social justice, and (c) expectations of authoritative bodies. Our findings illustrate that policy impasse over cumulative impacts is highly dependent on how policy-relevant actors come to frame issues around legislating cumulative impacts, rather than the “standard narrative” of external constraints. Frame analysis may provide us with more robust understandings of policy processes to address cumulative risks and impacts and the social forces that create health policy change.

Mobilizing for Community Benefits to Assess Health and Promote Environmental Justice near the Gordie Howe International Bridge

Transportation infrastructure decisions contribute to social, economic, and health inequities in the U.S. Health Impact Assessments (HIAs) may improve understanding of potential strategies to mitigate adverse effects on quality of life from planned developments. We use the Gordie Howe International Bridge (GHIB), currently under construction in southwest Detroit, MI, as a case study to examine 15 years of community mobilization, which resulted in community benefits that included an HIA. We describe community engagement processes, household survey methods, and select findings of the baseline HIA, with a focus on their application to inform recommendations to promote quality of life. Baseline HIA results indicated significantly higher self-reported asthma rates among children living within 500 feet of trucking routes. Residents reported substantial economic (e.g., decreased home values), health (e.g., adverse outcomes, lack of health care access), and environmental (e.g., air pollution) concerns related to the GHIB. We discuss specific recommendations, based on HIA results, to reduce adverse impacts of the GHIB. These recommendations will inform ongoing community benefits negotiations. This case study provides lessons for community, academic, and government partners conducting HIAs, especially during building and operation of major infrastructure, and discusses their potential role in improving community engagement opportunities towards environmental justice.

Independent and Joint Contributions of Fine Particulate Matter Exposure and Population Vulnerability to Mortality in the Detroit Metropolitan Area

Fine particulate matter is associated with adverse health outcomes. Exposure to fine particulate matter may disproportionately affect urban communities with larger numbers of vulnerable residents. We used multilevel logistic regression models to estimate the joint effects of fine particulate matter (PM_2.5) and population vulnerabilities on cardiopulmonary mortality (CPM). We estimated the health benefits of reductions in PM_2.5 across census tracts in the Detroit metropolitan area with varying levels of population vulnerability, using cluster-specific odds ratios scaled to reflect PM_2.5-attributable cardiopulmonary risk. PM_2.5 and population vulnerability were independently associated with odds of CPM. Odds of CPM and the number of deaths attributable to PM_2.5 were greatest in census tracts with both high PM_2.5 exposures and population vulnerability. Reducing PM_2.5 in census tracts with high PM_2.5 would lead to an estimated 18% annual reduction in PM_2.5-attributable CPM. Between 78–79% of those reductions in CPM would occur within census tracts with high population vulnerabilities. These health benefits of reductions in PM_2.5 occurred at levels below current U.S. reference concentrations. Focusing efforts to reduce PM_2.5 in the Detroit metropolitan area in census tracts with currently high levels would also lead to greater benefits for residents of census tracts with high population vulnerabilities.

Advice and Frequently Asked Questions (FAQs) for Citizen-Science Environmental Health Assessments

Citizen science provides quantitative results to support environmental health assessments (EHAs), but standardized approaches do not currently exist to translate findings into actionable solutions. The emergence of low-cost portable sensor technologies and proliferation of publicly available datasets provides unparalleled access to supporting evidence; yet data collection, analysis, interpretation, visualization, and communication are subjective approaches that must be tailored to a decision-making audience capable of improving environmental health. A decade of collaborative efforts and two citizen science projects contributed to three lessons learned and a set of frequently asked questions (FAQs) that address the complexities of environmental health and interpersonal relations often encountered in citizen science EHAs. Each project followed a structured step-by-step process in order to compare and contrast methods and approaches. These lessons and FAQs provide advice to translate citizen science research into actionable solutions in the context of a diverse range of environmental health issues and local stakeholders.

Cumulative risk assessment toolbox: methods and approaches for the practitioner

The historical approach to assessing health risks of environmental chemicals has been to evaluate them one at a time. In fact, we are exposed every day to a wide variety of chemicals and are increasingly aware of potential health implications. Although considerable progress has been made in the science underlying risk assessments for real-world exposures, implementation has lagged because many practitioners are unaware of methods and tools available to support these analyses. To address this issue, the US Environmental Protection Agency developed a toolbox of cumulative risk resources for contaminated sites, as part of a resource document that was published in 2007. This paper highlights information for nearly 80 resources from the toolbox and provides selected updates, with practical notes for cumulative risk applications. Resources are organized according to the main elements of the assessment process: (1) planning, scoping, and problem formulation; (2) environmental fate and transport; (3) exposure analysis extending to human factors; (4) toxicity analysis; and (5) risk and uncertainty characterization, including presentation of results. In addition to providing online access, plans for the toolbox include addressing nonchemical stressors and applications beyond contaminated sites and further strengthening resource accessibility to support evolving analyses for cumulative risk and sustainable communities.

Cumulative risk assessment: an overview of methodological approaches for evaluating combined health effects from exposure to multiple environmental stressors

Systematic evaluation of cumulative health risks from the combined effects of multiple environmental stressors is becoming a vital component of risk-based decisions aimed at protecting human populations and communities. This article briefly examines the historical development of cumulative risk assessment as an analytical tool, and discusses current approaches for evaluating cumulative health effects from exposure to both chemical mixtures and combinations of chemical and nonchemical stressors. A comparison of stressor-based and effects-based assessment methods is presented, and the potential value of focusing on viable risk management options to limit the scope of cumulative evaluations is discussed. The ultimate goal of cumulative risk assessment is to provide answers to decision-relevant questions based on organized scientific analysis; even if the answers, at least for the time being, are inexact and uncertain.