The objective of this project is to conduct a laboratory study providing a comprehensive, contemporary evaluation of selected respiratory and cardiac health hazards of repeated inhalation exposure to “simulated downwind” emissions of coal combustion. The work will be conducted in two phases:  (1) development of the exposure atmosphere and (2) conduct of the toxicology study and analysis of results.  This project will provide for the first time an integrated toxicological evaluation of the existence and dose-response relationships of cardio respiratory effects of repeatedly inhaling a mixture of particulate matter (PM) and gases simulating the principal components of  “downwind (i.e., not “top-of-stack”) air pollutants originating from coal-fired power plant emissions.  The goal is not to attempt simulation of the full range of coal-derived emissions and possible atmospheric reaction products, but rather to simulate key pollutant species to which coal emissions contribute most strongly. 

A second objective is to provide a direct comparison of the health hazards of the coal emission exposure to those of exposures to other key source emissions—diesel and gasoline engine emissions, hardwood smoke, and street dust—using an identical protocol.  The work will be conducted within the protocol framework of the source emissions studies of the National Environmental Respiratory Center.

Rats and mice of different strains, genders and ages will be exposed by inhalation for various durations to one of four dilutions of a synthesized coal emissions atmosphere or to clean air as controls.  Following exposure, a range of cardio respiratory health outcomes spanning several public health concerns will be measured using animal/exposure pattern models specific to each category of outcome.

The project team also includes SKS Consultants, which will perform biostatistical analysis of data; the University of North Carolina (Chapel Hill), which will assist in the evaluation of DNA oxidative injury; and Eigenvector, which will perform multivariate data analysis.