Coarse PM Emissions Model Development and Inventory ValidationEPA Grant Number: R834552
Title: Coarse PM Emissions Model Development and Inventory Validation
Investigators: Hannigan, Michael P. , Fierer, Noah , Wiedinmyer, Christine
Institution: University of Colorado at Boulder , National Center for Atmospheric Research
EPA Project Officer: Chung, Serena
Project Period: June 1, 2010 through May 31, 2013
Project Amount: $500,000
RFA: Novel Approaches to Improving Air Pollution Emissions Information (2009) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
The proposed research is designed to ultimately provide new emissions models for coarse PM and PM10. An extensive measurement dataset of coarse PM and PM2.5. mass as well as chemical and biological composition will be collected. This dataset will then be used to evaluate existing PM10. emissions inventories. Existing emissions modules will be updated to more accurately simulate coarse PM emissions. Further, a new emissions model that will simulate the emissions of primary biological particles will be developed.
To accomplish these objectives, we will collect an extensive dataset of PM2.5 and coarse PM at both urban and rural sites in the Front Range of Colorado, as well as detailed meteorology for each sampling site. The collected filters will be subjected to a robust analysis of chemical and biological characterization, including inorganic and organic speciation, and detailed DNA analysis of the biological component to elucidate the contribution of bacteria, fungal spores, and pollen. Source apportionment and bioinformatics tools will be applied to the data collected to identify source contributions and relationships with controlling factors such as wind speed or soil moisture. These results will provide information that will be used to evaluate existing PM10 emission inventories, including an assessment of the temporal variations in the estimates. Existing models for the estimation of PM10 will be updated to include better temporal resolution and dependency on controlling factors as determined from the results of the measurement analysis. A new primary biological emissions model will be developed to simulate the emissions of bacteria, fungal spores, and pollen to the atmosphere. The final models will be packaged into a modeling framework that is readily implemented with EPA regional modeling tools.
The proposed research will contribute to our understanding of the sources and controlling variables of coarse PM. This greater understanding, along with an increase in our ability to predict these emissions, will enable more efficient pollution control strategy development. Additionally, the information developed here will provide important information for use in public health studies of PM impacts and possibly PM estimates that can better constrain climate models.