Grantee Research Project Results
2010 Progress Report: Coarse PM Emissions Model Development and Inventory Validation
EPA Grant Number: R834552Title: Coarse PM Emissions Model Development and Inventory Validation
Investigators: Hannigan, Michael P. , Wiedinmyer, Christine , Fierer, Noah
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 Period Covered by this Report: June 1, 2010 through May 31,2011
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
Objective:
This research is designed to ultimately provide new emissions models for PM10-2.5 and PM10. An extensive measurement dataset of PM10-2.5 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 PM10-2.5 emissions. Further, a new emissions model that will simulate the emissions of primary biological particles will be developed.
Progress Summary:
During the first year, we were focused on staffing the project, improving the quantitative nature of our biological particle analyses, completing the collection of the PM filter samples, initiating carbon analysis of those filters, obtaining PM10-2.5 measurement time-series for 2005 from all the US regulatory sampling efforts, using those measurement time series to hunt for environmental parameters that impact PM10-2.5 levels and finally using those time series to evaluate the performance of the current generation of PM10-2.5 emissions inventories by comparing 2005 CMAQ model output to measurements. Full details are in the annual report but below we highlight the biological particle analysis as well as the exploration of environmental parameters and PM10-2.5 concentrations from the AQS. In addition to those highlights, we have also learned that (1) carbonaceous species commonly account for ¼ of the PM10-2.5 mass regardless of time of year in both Denver and Greeley, and (2) that with current PM10-2.5 emissions, CMAQ drastically under-predicts PM10-2.5 mass concentration and gets the spatial and temporal patterns wrong.
Biological Particle Analysis
To complement the PM10-2.5 and PM2.5 measurements of total mass, chemical composition and source modeling, we have developed a variety of high-throughput techniques to assess the abundance, diversity, and composition of airborne microbial communities found in the PM samples. These techniques will not only be useful for this project (as they will allow us to analyze hundreds of filter samples in a quantitative manner), they will likely prove useful to other researchers working on related research questions.
We developed a semi-automated method to determine the abundances of airborne microbes based on the selective staining of PM containing DNA (cells) followed by automatic counting using a flow cytometer (Cyan Flow cytometer, Beckman Coulter). To determine the diversity and community composition of the microbial cells contained within the PM size fractions, we developed a high-throughput DNA sequencing approach. This approach gives us the ability to characterize all types of bio-aerosols found in a given sample, including bacteria, fungi and pollen. To obtain DNA sequence data, DNA is extracted straight from the filters and amplified using a DNA primer set specific to the small subunit rRNA gene of bacteria, fungi and plants (e.g., pollen). The amplicons are then sequenced on a 454 Life Sciences Genome Sequence FLX (Roche) machine, and the sequence data is then analyzed using the phylogenetic procedures described in detail in Fierer, et al., 2008 and Hamady, et al., 2008. This tagged-pyrosequencing approach allows us to quantify the relative abundances of bacteria, fungi, and pollen in each sample and provides a taxonomic description of the specific types of bacteria, fungi, and pollen found in each sample. With the high-throughput sequencing, we can compare airborne microbial communities across samples and to the bacterial communities of likely source environments.
PM10-2.5 Concentration and Environmental Parameters
Since we collected all the existing PM10-2.5 mass concentration measurement data with the goal of comparing CMAQ output for PM10-2.5 to measurements, we decided to use that data to help us understand sources. We did this by exploring the temporal variations in the concentrations as well as the correlation with other environmental parameters. Some sources preferentially operate during different days of the week or times of the day or seasonally, so we explored each of those temporal patterns. Some sources are dependent on temperature, wind speed, wind direction, and/or soil moisture, so we explored correlations. These analyses give us ideas about the importance of different sources and the processes that impact emissions from different sources. For example, all urban sites (even small cities) exhibit a day-of week preference; Figure 1a shows this pattern for Albuquerque. This would indicate that there are influences from anthropogenic sources that vary by day of week, like heavy-duty vehicle traffic or construction. We found two interesting relationships with environmental parameters. Most sites show a decrease in PM10-2.5 at elevated soil moisture, but typically nonlinear with impacts in only 10 to 50% of the measurements as wet soil reduces dust resuspension. Figure 1b shows this pattern for Spokane; indicating the soil/road dust impact ambient levels of PM10-2.5. Several sites, but not all, exhibit a classic wind speed relationship with decreasing concentrations as wind speed increases (dilution) and an increase in concentration at the highest wind speed (resuspension). Figure 1c show this for Spokane.
Future Activities:
In the coming year, 2011-2012, we will focus on five tasks: completion of the analysis (biological, trace metals, and carbonaceous components) of the collected PM10-2.5 and PM2.5 filters, initiation of the source apportionment of those PM samples using the analysis results, completion of a manuscript that compares the PM10-2.5 measurements to CMAQ model output with the focus on informing on improvements needed in the emissions inventory framework, completion a manuscript that uses a comprehensive PM10-2.5 and PM2.5 measurement data set to explore sources and processes impacting PM10-2.5 concentrations, and initiate modifications to the existing PM10 and PM2.5 emissions inventories based on the results of the preceding tasks.
Journal Articles:
No journal articles submitted with this report: View all 7 publications for this projectSupplemental Keywords:
PM10-2.5, chemical speciation, dust, agriculture, geogenic, bioaerosolProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.