Many investigations have found that the effects of chemical composition of PM2.5 plays an important role on human health. This study develops an air pollution source reduction strategy that apportions health risk among different emission sources by combining the receptor model and human health risk assessment technique. The goal is to identify emission source of PM2.5 that have the greatest impact on human health. We establish a PM2.5 sampling station in Sha-Lu, Taiwan. Five PM2.5 pollution sources were identified in this study. They are steel industry, residual oil combustion, road dust and traffic, coal-fired power plant, and glass production industry. The results of health risk assessment indicated that the metal contributes the most cancer risk is arsenic, followed by hexavalent chromium. The emissions of these two metals are closely related to coal-fired power plant. We suggested that the power plants should use coal with a low As and Cr content of coal in order to reduce the health risk associated with exposure to PM2.5. The limitation of this study is that only a small fraction of compounds was measured in the samples. However, this study demonstrates that an analysis of the degree to which emission sources contribute to health risks is a useful technique. Most importantly, it provides valuable information for making environmental management decision.
