Fugitive Chemicals and Environmental Justice: A Model for Environmental Monitoring Following Climate-Related Disasters.

The combination of population growth in areas of mixed (residential, commercial, and industrial) land use along U.S. waterfronts and the increasing frequency of devastating hurricanes and storm surges has led to community fears of widespread toxic chemical contamination resulting from accidental industrial or small business releases, particularly in the aftermath of an extreme weather event, such as a hurricane. Industrial waterfront communities, which are frequently environmental justice communities, contain numerous toxic chemical sources located in close proximity to residential housing, schools, daycare centers, playgrounds, and healthcare centers. Despite the longstanding concerns of community activists and researchers about the potential for "fugitive" chemicals to be released into floodwaters, there has been little coordinated research or action to develop environmental monitoring programs for disaster-affected communities. In the aftermath of Superstorm Sandy, a community-academic partnership was formed between the New York City Environmental Justice Alliance, UPROSE, The LifeLine Group, and the RAND Corporation. The collaboration, known as Grassroots Research to Action in Sunset Park (GRASP) has focused on identifying possible sources of chemical contamination, modeling the potential for chemical release into community areas and resulting exposure risks, and proactively developing actions for mitigating or preventing adverse community impacts. Through our ongoing work, we have identified barriers and drivers for community-based environmental monitoring, and in doing so, we have developed a framework to overcome challenges. In this article, we describe this framework, which can be used by waterfront communities bracing to deal with the effects of future devastating weather disasters.

Using publicly available information to create exposure and risk-based ranking of chemicals used in the workplace and consumer products.

Mandates that require the estimation of exposure and human health risk posed by large numbers of chemicals present regulatory managers with a significant challenge. Although these issues have been around for some time, the estimation of human exposure to chemicals from use of products in the workplace and by the consumer has been generally hindered by the lack of good tools. Logically and in the interest of cost-effective resource allocation and regulation one would typically and naturally first attempt to rank-order or prioritize the chemicals according to the human exposure potential that each might pose. We have developed an approach and systematic modeling construct that accomplishes this critical task by providing a quantitative estimate of human exposure for as many as several hundred chemicals initially; however, it could ultimately do this for any number of regulated chemicals starting only with the identity (Chemical Abstract Service number) for each chemical under consideration. These exposure estimates can then be readily linked to toxicological benchmarks for each item to estimate and rank the human health risk for the chemicals under consideration in a "worst things first" listing. This modeling construct, entitled Complex Exposure Tool (ComET) was developed by The LifeLine Group as a proof of concept under the sponsorship of Health Canada. ComET considers multiple routes of exposure, multiple subpopulations and different possible durations of exposure. A beta-version of ComET was issued and demonstrated in which users can change the assumptions in the model and see the impacts of these changes and the quality of information as they relate to the predicted exposure potential. We have advanced the operational elements of ComET into a tool entitled the Chemical Exposure Priority Setting Tool (CEPST) designed to provide quantitative estimation of the exposure potential of large groups of chemicals with little data and possibly multiple exposure scenarios. A basic feature of this tool is the utilization of an internally consistent approach and assumptions that are completely transparent. It uses publicly available information as critical input and is specifically designed to be continually reviewed, refined, expanded and updated using scientific peer review and stakeholder input.

Modeling framework for human exposure assessment.

We are at the dawn of a new era of quantitative consumer exposure and risk assessment of chemicals driven by regulatory mandates. This remarkable development also signals the beginning of a dramatic resurgence in the need for and development of human exposure models. This paper presents some of the philosophical background underlying exposure modeling in the context of human health risk assessment. The basic types of and structure of inhalation exposure models are discussed, as well as the research needed to move us forward into this exciting new period of development.

A conceptual framework for modeling aggregate and cumulative exposures to chemicals.

Computer simulation programs have been identified as useful tools for characterizing uncertainty and variability in longitudinal exposures to multiple sources by multiple routes of exposures. This paper provides a conceptual framework for such programs that separates and appropriately models the processes that determine uncertainty, inter- and intraindividual variability, as well as the processes that determine the relationships between the individuals and sources of exposure. The framework is based on a series of four nested loops. These are: the exposure event loop that models the route-specific doses to a person from one or more sources at one point in time; the time step loop that moves a person through time updating the sources and the person's characteristics, the interindividual variation loop that determines the initial characteristics of each person modeled, and finally the uncertainty loop that characterizes the uncertainty from model and parameter uncertainties. This framework provides a flexible and internally consistent approach for the design of simulation software.

Modeling interindividual variation in physiological factors used in PBPK models of humans.

Modeling interindividual variation in internal doses in humans using PBPK models requires data on the variation in physiological parameters across the population of interest. These data should also reflect the correlations between the values of the various parameters in a person. In this project, we develop a source of data for human physiological parameters where (1) the parameter values for an individual are correlated with one another, and (2) values of parameters capture interindividual variation in populations of a specific gender, race, and age range. The parameters investigated in this project include: (1) volumes of selected organs and tissues; (2) blood flows for the organs and tissues; and (3) the total cardiac output under resting conditions and average daily inhalation rate. These parameters are expressed as records of correlated values for the approximately 30,000 individuals evaluated in the NHANES III survey. A computer program, Physiological Parameters for PBPK Modeling (P3M), is developed that allows records to be retrieved randomly from the database with specification of constraints on age, sex, and ethnicity. P3M is publicly available. The database and accompanying software provide a convenient tool for parameterizating models of interindividual variation in human pharmacokinetics.