Estimating population exposure to power plant emissions using CALPUFF: a case study in Beijing, China

Abstract Epidemiological studies have shown a significant association between ambient particulate matter (PM) exposures and increased mortality and morbidity risk. Power plants are significant emitters of precursor gases of fine particulate matter. To evaluate the public health risk posed by power plants, it is necessary to evaluate population exposure to different pollutants. The concept of intake fraction (the fraction of a pollutant emitted that is eventually inhaled or ingested by a population) has been proposed to provide a simple summary measure of the relationship between emissions and exposure. Currently available intake fraction estimates from developing countries used models that look only at the near field impacts, which may not capture the full impact of a pollution source. This case study demonstrated how the intake fraction of power plant emissions in China can be calculated using a detailed long-range atmospheric dispersion model—CALPUFF. We found that the intake fraction of primary fine particles is roughly on the order of 10−5, while the intake fractions of sulfur dioxide, sulfate and nitrate are on the order of 10−6. These estimates are an order of magnitude higher than the US estimates. We also tested how sensitive the results were to key assumptions within the model. The size distribution of primary particles has a large impact on the intake fraction for primary particles while the background ammonia concentration is an important factor influencing the intake fraction of nitrate. The background ozone concentration has a moderate impact on the intake fraction of sulfate and nitrate. Our analysis shows that this approach is applicable to a developing country and it provides reasonable population exposure estimates.