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Receptor modeling is the application of data analysis methods to elicit information on the sources of air pollutants. Typically, it employs methods of solving the mixture resolution problem using chemical composition data for airborne particulate matter (PM) samples. In such cases, the outcome is the identification of the pollution source types and estimates of the contribution of each source type to the observed concentrations. Receptor modeling also involves efforts to identify the locations of the sources through the use of local meteorology or ensembles of air parcel back trajectories. Compositional data were collected in a number of monitoring programs. The U.S. Environmental Protection Agency deployed a network of urban airborne PM samplers to provide PM2.5 composition data for urban centers across the United States. In addition, advanced monitoring methods were deployed at “supersites.” These data show the differences in composition in different part of the country and were also used to identify and apportion the particle sources. These results were used to (1)develop effective and efficient air quality management plans and (2) refine emission inventories for input into deterministic models to predict changes in air quality as the result of the implementation of various management plans. The apportionments also serve as exposure estimates for health effects models to identify those components of the PM that are most closely related to observed adverse health effects. Although current regulations target total airborne mass concentrations, such health effects results might result in targeting those sources that are most likely linked to adverse health effects and thus produce the maximum health benefit. [ABSTRACT FROM AUTHOR]

Mode of action (MOA) information is increasingly being applied in human health risk assessment. The MOA can inform issues such as the relevance of observed effects in laboratory animals to humans, and the variability of response within the human population. Several collaborative groups have developed frameworks for analyzing and utilizing MOA information in human health risk assessment of environmental carcinogens and toxins, including the International Programme on Chemical Safety, International Life Sciences Institute, and U.S. Environmental Protection Agency. With the goal of identifying gaps and opportunities for progress, we critically evaluate several of these MOA frameworks. Despite continued improvement in incorporating biological data in human health risk assessment, several notable challenges remain. These include articulation of the significant role of scientific judgment in establishing an MOA and its relevance to humans. In addition, binary (yes/no) decisions can inappropriately exclude consideration of data that may nonetheless be informative to the overall assessment of risk. Indeed, the frameworks lack a broad consideration of known causes of human disease and the potential for chemical effects to act additively with these as well as endogenous background processes. No integrated analysis of the impact of multiple MOAs over the same dose range, or of varying MOAs at different life stages, is included. Separate consideration of each MOA and outcome limits understanding of how multiple metabolites, modes, and toxicity pathways contribute to the toxicological profile of the chemical. An extension of the analyses across outcomes with common modes is also needed. [ABSTRACT FROM AUTHOR]

This article discusses the science of environmental risk assessment at the U. S. Environmental Protection Agency. They review new methods for risk assessment (e. G. , physiologically based pharmacokinetic models, biologically based dose-response models) uncertainty factors, and extrapolation (e. G. , from animals to humans, from high to low dose). The authors trace the history of environmental risk assessment. They discuss issues raised at the workshop and how EPA is responding to them. Examples are presented of how the EPA is changing their chemical health risk assessment reference values for certain common toxic organic chemicals.

Genomics information has great potential to enhance assessment of risks to human health and the environment. Although understanding genomic responses with respect to adverse ecological and human health outcomes is not, as yet, established, it is important to consider the likely future impacts of genomics technologies on risk assessment and decision-making. Four areas are identified as those likely to be influenced by the generation of genomics information within, and the submission of such information to, the U.S. Environmental Protection Agency (USEPA): risk assessment, prioritization of contaminants and contaminated sites, monitoring, and reporting provisions. For each of these risk assessment and regulatory applications, representative activities are presented to illustrate the application. Three major challenges for the USEPA associated with genomics are also identified in the areas of research, technical development, and capacity. The USEPA's initial activities to address these challenges are discussed. The Agency recognizes it must be prepared to use genomics information, and that many scientific, policy, ethical, and legal concerns will need to be addressed. The USEPA also recognizes it is essential to continue to collaborate with other federal agencies, academia, the regulated community, and other stakeholders in order to benefit from ongoing advances in genomics in the wider scientific and regulatory communities. [ABSTRACT FROM AUTHOR]