Particles reduce visibility, change climate, and affect human health. In 1997, the National Ambient Air Quality Standard (NAAQS) for PM2.5 (particles less than 2.5 mm) was promulgated. The annual mean PM2.5 mass concentrations in Atlanta, Georgia exceed the standard, and control is needed. The first goal of this study is to develop the control strategies of PM2.5 in Atlanta, Georgia. Based on the statistical analysis of measured data, from 22% to 40% of emission reductions are required to meet the NAAQS at 95% CI. The estimated control levels can be tested using the Community Multiscale Air Quality (CMAQ) model to better assess if the proposed levels will achieve sufficient reduction in PM2.5. The second goal of this study is to analyze various uncertainties residing in CMAQ. For the model to be used in such applications with confidence, it needs to be evaluated. The model performance is calculated by the relative agreement between volume-averaged predictions and point measurements. Up to 14% of the model error for PM2.5 mass is due to the different spatial scales of the two values. CMAQ predicts PM2.5 mass concentrations reasonably well, but CMAQ significantly underestimates PM2.5 number concentrations. Causes of the underestimation include that assumed inaccurate particle density and particle size of the primary emissions in CMAQ, in addition to the expression of the particle size with three lognormal distributions. Also, the strength and limitations of CMAQ in performing PM2.5 source apportionment are compared with those of the Chemical Mass Balance with Molecular Markers. Finally, the accuracy of emissions, one of the important inputs of CMAQ, is evaluated by the inverse modeling. Results show that base level emissions for CO and SO2 sources are relatively accurate, whereas NH3, NOx, PEC and PMFINE emissions are overestimated. The emission adjustment for POA and VOC emissions is significantly different among regions.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/7541 |
| Date | 23 November 2005 |
| Creators | Park, Sun-kyoung |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 6830787 bytes, application/pdf |
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