Grantee Research Project Results
2012 Progress Report: Improvements in Emissions Inventories using Semi-Continuous Monitoring Data and Concentrations Field Analysis
EPA Grant Number: R834557Title: Improvements in Emissions Inventories using Semi-Continuous Monitoring Data and Concentrations Field Analysis
Investigators: Schauer, James J. , Turner, Jay R. , deFoy, Benjamin
Institution: University of Wisconsin - Madison , Washington University , Saint Louis University - Main Campus
Current Institution: University of Wisconsin - Madison , Saint Louis University - Main Campus , Washington University
EPA Project Officer: Chung, Serena
Project Period: June 1, 2010 through May 30, 2013 (Extended to May 30, 2014)
Project Period Covered by this Report: June 1, 2012 through May 31,2013
Project Amount: $499,777
RFA: Novel Approaches to Improving Air Pollution Emissions Information (2009) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Air
Objective:
This project focuses on using year-long datasets from St. Louis, Milwaukee, and Los Angeles to map sources of air pollutants that do not have well developed emissions inventories. The modeling efforts are directed at improving emissions inventory data for black carbon, ultrafine particle number concentrations and fine particle organic carbon using data from the EPA-funded St. Louis Supersite; speciated mercury compounds in the Milwaukee region using data from an EPA STAR Project; and fine particle carbonaceous particulate matter and associated precursor gases in Los Angeles. Concentration Field Analysis (CFA) and related mapping tools are being used to map emissions sources and identify unknown or poorly identified source regions using stochastic backward and forward particle trajectories with a temporal resolution finer than one hour and spatial resolution finer than 5 km during the year-long study periods. The integration of high quality monitoring data with multiple 3D modeling approaches is being used to assess existing emissions inventories and improve the understanding and representation of the temporal distribution of emissions, spatial distributions of emissions, missing sources, and inaccurate emissions estimates for point sources, mobile sources and area sources.
The goal of this project is to couple high-resolution meteorological modeling with existing high time resolution atmospheric pollutant data sets to assess and improve emissions inventories.
CFA is being used to identify probabilistic source regions from the measurements independent of the emissions inventory data. Forward Lagrangian modeling then will be used to evaluate individual transport events. Cluster analysis will link year-long trends with the hour-long episodes to assess the statistical relevance of the conclusions. Uncertainties due to the simulation of vertical dispersion will be constrained by comparing measurements and particle transport with forward Eulerian models.
Progress Summary:
Inverse Modeling of Elemental and Organic Carbon at the St. Louis Supersite
The goal of this analysis is to better understand the emissions of elemental and organic carbon aerosols using measurements made at the East St. Louis Supersite. We apply an inverse model using a combination of backward particle trajectories and forward Eulerian simulations. Hourly measurements were obtained from April 2001 to July 2003.
Preliminary analysis used windroses to identify dominant wind patterns at the surface associated with high EC and OC concentrations. This showed that high concentrations of carbonaceous particles were clearly associated with calm winds and with winds from the south-southeast. The diurnal profile showed lower concentrations during the day with maxima at night.
A time series analysis also was performed using a Least-Squares Linear Model. This was applied to all the data available at the supersite as well as monitoring data available from EPA's Air Quality System (AQS) network. The analysis was used to look at the association between the EC and OC measurements and to compare them with the optical measurements for Black Carbon. The results of the analysis suggest that black carbon measurements and elemental carbon measurements were closely associated, but that the black carbon measurements also were influenced by other pollutants. Organic carbon shares some features with elemental carbon but appeared to be more influenced by mobile sources (CO and NO2) as well as more regional impacts (ozone).
During year 2 of the project we performed nested grid simulations using the Weather Research and Forecast model (WRF). These were run for 18 months on grids starting with a resolution of 27 km down to 3 km for the finer domain around the measurement site. The wind simulations were input into WRF-FLEXPART in order to calculate particle back-trajectories. One-thousand particles were released for every hour of the 18 months being analyzed, and they were tracked for a duration of 6 days.
The particle back-trajectories were converted to grids (known as Residence Time Analysis, RTA) to identify dominant wind transport directions. Whereas the prevailing winds aloft are westerlies, the simulations suggested that at the surface the site was impacted by transport form the south and from the north along the river valley. Using these grids, we performed a Concentration Field Analysis (CFA) to identify potential source regions of the pollutants. As expected, there was a signal from the St. Louis metropolitan region. However, there also was a signal from the southeast. Ongoing work is trying to establish the impact of local sources as well as those of stagnation events on these results.
EC and OC share some of the same sources as NOx, and so we have extended the inverse analysis to include NOx. We used the CAMx model to carry out forward simulations of NOx based on the National Emission Inventory. In particular, we carried out individual simulations for different times of the day for weekdays and and for weekends. The inverse model then was used to identify scaling factors for those individual time series, and hence establish a diurnal profile of emissions based on the data itself. We found that the emissions factors for the weekdays were as follows: 0.46 for 1-6 am, 1.59 for 7-9 am, 1.20 for 10 am-4 pm, 1.14 for 5-7 pm and 1.24 for 8 pm-12 am. On weekends, we obtained: 0.39 for 1-6 am, 0.95 for 7-9 am, 0.57 for 10 am-4 pm, 0.46 for 5-7 pm and 1.00 for 8 pm-12 am. These results are still being analyzed. Uncertainty estimates (not shown here) suggest that the method can be used to yield insights on these scaling factors based on measurements. They also can identify potential model issues. In this case, the scaling factors are larger than expected for the evening (8 pm-12 am). Some of this may be due to larger mobile source emissions than previously thought at those times, but it also could be impacted by the parameterization of vertical diffusion, especially in the stable boundary layer at night.
The inverse model estimates gridded emissions on a polar grid based on the particle back-trajectories simulations. We can see a dominant signature from the south impacting the site. This is in contrast to EC (not shown), which has both a southern signature and a northern one that matches with the Chicago area. The results suggest that EC is more influenced by primary emissions, whereas OC is more influenced from south which experiences enhanced secondary formation. We are preparing a manuscript for submission to Atmospheric Environment tentatively titled “Sources of elemental and organic carbon measured in East-St. Louis using an inverse model.”
We also have been analyzing particle number measurements from the East-St. Louis Supersite in combination with local meteorology and other time series. This showed a very clear signal from a local source of SO2. The dominant nucleation events observed at the East-St. Louis site can be clearly matched with the SO2 plumes, and we are working on refining the analysis to identify some of the main factors influencing particle numbers during these events as well as in the remaining portion of the time series. We are considering expanding this work into a publication tentatively titled: “Nucleation events in an SO2 plume in an urban environment.”
Identification of Potential Source Areas for Fine Particle Organic Carbon Sources in LA, California
Daily PM2.5 samples collected from May 2009 through April 2010 in downtown LA were analyzed for OC, EC, WSOC and organic molecular markers. The results were used in a molecular marker PMF receptor model to obtain source contributions to PM2.5 OC. Five source categories were identified having stable profiles; anthropogenic secondary organic carbon (SOC), biogenic SOC, primary biogenic, mobile and wood smoke. A Potential Source Contribution Function (PSCF) was applied to estimate potential source areas related to high contributions of anthropogenic and biogenic SOC as well as mobile sources to PM2.5 OC in downtown LA. The backward trajectories of air parcels were calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT 4.9 version) using NAM 12 km gridded meteorological data from the National Weather Service’s National Centers for Environmental Prediction (NCEP). Five-day back trajectories arriving at heights of 500 m above ground levels at the monitoring site with an hourly interval were simulated using a vertical velocity model for each of 24-hour integrated ambient PM2.5 samples. The PMF resolved source contributions were assigned to the geophysical grid cells of 0.1º × 0.1º (latitude and longitude) along the corresponding back trajectories. The upper 25% of source contributions were used as the threshold criterion in order to calculate the high PSCF values that represent the potential source locations.
The high potential source areas leading to the high contributions of anthropogenic SOC to PM2.5 OC in downtown LA appear to be located along the Central Valley and South Coast Air Basin in California. These identified source regions through the PSCF analysis are well matched with the emission inventory map of anthropogenic VOCs in EPA Region 9. In contrast, the origins and paths of air masses that highly contribute to the high biogenic SOC in LA are the northeast which has rural and forested areas. County-total estimates of 2008 biogenic VOCs emissions based on the Biogenic Emissions Inventory System (BEIS) 3.14 version by EPA show that there are high biogenic VOCs emissions in San Bernardino, Riverside, Inyo, and Kern counties in California as well as Nye County in Nevada. The PSCF plot for the PMF biogenic SOC is comparable to the biogenic emission map.
Overall, the SOC aerosols in downtown LA are substantially influenced by air masses trajectories originating from their potential source areas. For the primary organic carbon sources, especially mobile sources, although the mountain chimney effects could explain the identified source areas, the trajectory analysis is not enough to trace back the local emission areas and more detailed meteorological analyses are needed to explore the local emission effects on PM2.5 OC.
Journal Articles on this Report : 2 Displayed | Download in RIS Format
Other project views: | All 17 publications | 15 publications in selected types | All 15 journal articles |
---|
Type | Citation | ||
---|---|---|---|
|
de Foy B, Wiedinmyer C, Schauer JJ. Estimation of mercury emissions from forest fires, lakes, regional and local sources using measurements in Milwaukee and an inverse method. Atmospheric Chemistry and Physics 2012;12(19):8993-9011. |
R834557 (2011) R834557 (2012) R834557 (Final) |
Exit Exit Exit |
|
de Foy B, Heo J, Schauer JJ. Estimation of direct emissions and atmospheric processing of reactive mercury using inverse modeling. Atmospheric Environment 2014;85:73-82. |
R834557 (2012) R834557 (Final) R829798 (2005) |
Exit Exit Exit |
Supplemental Keywords:
National Emissions Inventory, Toxics Release InventoryProgress 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.