“Cumulative impact assessment requires a systematic approach to characterize the combined effects from exposures to both chemical and non-chemical stressors over time across the affected population group or community” (EPA, 2023).^[1] Currently, using screening tools is the most common way to address exposure to these combined stressors in the context of cumulative impact assessment (CIA). While screening tools can generally identify communities that have the potential for disproportionately higher exposure to chemical and non-chemical stressors, screening tools are not sufficiently local to be used alone as a cumulative impact assessment. The data behind the screening tools can represent large geographic rural areas, may only be available across counties or zip codes rather than neighborhoods, and can use proxies and estimates rather than actual measures of exposure. With the exception of inhalation exposures, the screening tools do not quantify exposures to chemicals in a community. Chemicals like dioxin/furans, lead, and PFAS compounds have become ubiquitous in the environment at levels of toxicological interest, and in many cases, people’s general exposure is related to food consumption or other general conditions rather than a localized source. To consider chemical exposures in the context of CIA, the magnitude of these background population level and community exposures should be considered to put the source-specific exposures in context. Historically, these exposures have been addressed by default assumptions (e.g., maximum contaminant levels [MCLs]), setting benchmarks at increments above background (e.g., lead), or adjusting target levels to account for background (e.g., dioxins). The advent of population level data on body burdens for various indicators of chemical exposure provide an opportunity to refine these approaches across a wide variety of chemicals.

In this presentation, we review the historical approaches used to address cumulative chemical exposures when evaluating chemical risk and the opportunity that population level data on body burdens provides for refining that approach. For example, blood lead level data collected by the Centers for Disease Control (CDC) indicates that the 95% upper confidence limit for 1 to 5 year olds has decreased significantly from 1999 to 2018 (7.00 to 2.91 µg/dL)^[2]. Rather than using the historical benchmarks of 10 or 5 µg/dL blood lead, CDC has lowered their benchmark to 3.5 µg/dL.^[3] California’s Office of Environmental Health Hazard Assessment (OEHHA) is now using a benchmark of a site-specific contribution to blood lead greater than 1 µg/dL above background.

^[1] USEPA. (2023). Guidelines for Cumulative Risk Assessment: Planning and Problem Formulation (Public Comment Draft). https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=358060

^[2] CDC. National Report on Human Exposures to Environmental Chemicals. https://www.cdc.gov/exposurereport/report/pdf/Metals%20and%20Metalloids%20NHANES-p.pdf

^[3] https://www.cdc.gov/lead-prevention/php/guidelines/index.html