1. Simulation of PM2.5 Trace Elements in Detroit using CMAQ
Adam H. Reff1, David C. Wong1,2, Shawn Roselle1,2, Prakash V. Bhave1,2
1U.S. EPA, National Exposure Research Laboratory, Research Triangle Park, NC 27711
2On assignment from NOAA, Atmospheric Sciences Modeling Division
Abstract
Deleterious health effects are known to be associated with exposure to a number of metals present in PM2.5. Air quality models have historically been designed to simulate only the ionic and carbonaceous fractions of PM2.5, with the remaining mass treated as an inert species. In this work, we created a new version of the Community Multi-scale Air Quality (CMAQ) Model capable of tracking 94 source-specific fractions of the POA, PEC, and PMFINE aerosol species. A recently developed emissions inventory of PM2.5 trace elements was then input to this new CMAQ model, which, when combined with post-processing of the source-specific portions of PMFINE, allowed us to simulate concentrations of a suite of 42 PM2.5 species and trace elements across the eastern U.S. for what we believe is the first time. In addition, this new version of CMAQ also provides source contributions to each of the simulated PM2.5 species, providing a new source apportionment tool to complement other approaches such as positive matrix factorization (PMF) and chemical mass balance (CMB).
In this work, we present some results from an 18 day run of the new CMAQ model for the time period from 5/29/2004 to 6/15/ Resulting predictions are evaluated against measurements made at the Allen Park Speciation Trends Network (STN) site, and suggest a range of model biases across PM2.5 species. A comparison of the source composition of emissions and ambient concentrations indicates that the relative contributions of emissions in the inventory are not able to serve as a surrogate for the impact on ambient concentrations. All of these results are preliminary, and further evaluation will be performed using results from a full 90 day run that will be performed upon completion of CMAQ source code debugging. The results of the full simulation will be used to enhance the analysis and interpretation of EPA’s Detroit Exposure and Aerosol Research Study (DEARS).
3. Evaluation of CMAQ Output
4. Source Apportionment of Detroit Concentrations
Left-most column of numbers in the table at right shows mean concentrations from the 18-day (5/29/04 – 6/15/04) simulation using the speciated source apportionment version of CMAQ.
The columns on the right show mean concentration measurements and method detection limits (MDL) from the same 18 day period for samples collected by the Speciation Trends Network.
All data are from the Allen Park STN sampling site in Detroit, MI
Good agreement can be seen for crustal species such as Al, Ca, Si and Ti, as well as EC
Elements with typically low concentrations such as Ba, Sn fell below MDL in both the model and measurements.
Modeled SO4, NO3, NH4, and OC exhibited large discrepancies with observations
The simulated time period was only 18 days, so results are preliminary to a more thorough spatial and temporal analysis
Plots at right compare the source breakdown of V emissions and ambient concentrations from CMAQ
Data comes from an 18 day run (5/29/04 – 6/15/04)
Concentrations are time-averaged from the gridcell containing the Allen Park (Detroit) STN Monitor
Emissions are totaled from the 43x43 grid-cell block containing the Detroit MSA
These graphs illustrate how the source breakdowns of emissions do not necessarily predict the source breakdowns of concentrations:
The contribution of the Agricultural Soil source category to emissions is greater than the contribution to ambient concentrations
The contributions of Residual Oil Combustion and Catalytic Cracking source categories to ambient concentrations are substantially larger than their contributions to emissions
1. Emissions Preparation
297 profiles were selected from the EPA SPECIATE database for speciating PM2.5 emissions and concentrations, assigned to source categories, and composited
Plot at right shows the distribution of profiles assigned to the Unpaved Road Dust category
Medians were used for speciation to minimize outlier influence
PM2.5 emissions in the 2001 NEI were obtained from the Sparse Matrix Operating Kernel Emissions (SMOKE) system at the source category code (SCC) level of specificity
SCCs were classified into the same source categories as SPECIATE profiles
Figure at left schematically illustrates the iterative compositing and mapping process
N = 20
2. Instrumenting CMAQ for PM2.5 Source Apportionment
5. Conclusions and Future Directions
Selenium
Silicon
CMAQ v4.6 simulates concentrations of 5 primary aerosol species: PSO4, PNO3, POA, PEC, PMFINE
Figure at right below demonstrates the process followed for this work:
SMOKE was used to allocate total PM2.5 into each of the 94 source categories using the SCC mapping from Step 1
Each of the 94 PM2.5 fractions was further split into the 5 primary aerosol species using COMBINE
CMAQ source code was expanded to process all 94 fractions of each of PEC, POA, and PMFINE
PSO4 and PNO3 were not tracked, so source-specific fractions were summed to give usual totals
COMBINE was used to speciate CMAQ output into organic species and trace elements
Maps at right display concentrations of PM2.5 metals from a 18 day simulation
Modeling Details: Chemical mechanism = SAPRC99, Domain = Eastern U.S., 12 km grids
A PM2.5 source & species specific version of CMAQ v4.6 has been developed and a preliminary 18 day run has been performed
A preliminary evaluation suggests that the performance of this new CMAQ model will vary considerably among species, and this is expected to yield new insights into performance issues of the base model
The source apportionment capabilities have shown that the impact of emissions on ambient concentrations and exposures do not necessarily follow from their relative importance in the inventory
Next Steps:
Finalize debugging to eliminate small differences in total PMFINE (~ 3 mg/m3) between Base and Source Apportionment CMAQ models
Perform a 90 day simulation upon completion of debugging
Calculate and evaluate Organic PM2.5 Species
Compare simulated concentrations against DEARS outdoor residential measurements
Predict DEARS exposures and indoor concentrations and evaluation against measurements
Base Case CMAQ Processing of PM2.5
Source Apportionment Case Processing of PM2.5
Disclaimer
The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.