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Evaluation of Contribution Rate of PM Concentrations for Regional Emission Inventories in Korean Peninsula Using Brute-force Sensitivity Analysis
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 Title & Authors
Evaluation of Contribution Rate of PM Concentrations for Regional Emission Inventories in Korean Peninsula Using Brute-force Sensitivity Analysis
Lee, Soon-Hwan; Lee, Kang-Yeol;
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 Abstract
In order to clarify the contribution rate of PM concentration due to regional emission distribution, Brute force analysis were carried out using numerical estimated PM data from WRF-CMAQ. The emission from Kyeongki region including Seoul metropolitan is the largest contribution of PM concentration than that from other regions except for emission of trans-country and source itself. Contribution rate of self emission is also the largest at Kyeongki region and its rate reach on over 95 %. And the rate at Gangwon region also higher than any region due to synoptic wind pattern. Due to synoptic wind direction at high PM episode, pollutants at downwind area along from west to east and from north to south tends to mix intensively and its composition is also complicated. Although the uncertainty of initial concentration of PM, the contribution of regional PM concentration tend to depend on the meteorological condition including intensity of synoptic and mesoscale wind and PM emission pattern over upwind region.
 Keywords
PM10;PM2.5;Air pollutant;Brute-force;AQM Sensitivity;
 Language
Korean
 Cited by
 References
1.
Byun, D. W., Schere, K. L., 2006, Review of the Governing Equations, Computational Algorithms, and Other Components of the Models‐3 Community Multiscale Air Quality (CMAQ) Modeling System, Applied Mechanics Reviews, 59(2), 51-77. crossref(new window)

2.
Carter, W. P. L., 2000, Documentation of the SAPRC 99 Chemical Mechanism for VOC Reactivity Assessment, Final Report to the California Air Resources Board, Contracts No. 92-329 and No. 95-308.

3.
Hanna, S. R., Lu, Z., Frey, H. C., Wheeler, N., Vukovich, J., Arunachalam, S., Fernau, M., Hansen, D. A., 2001, Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain, Atmospheric Environment, 35, 891-903. crossref(new window)

4.
Kim, D. Y., 2013, Causes and measures of fine dust that threaten the health, Gyeonggi Research Institute Issue & Analysis, 121.

5.
Kim, J. S., Jung, D. I., Hong, J. H., Kim, J. Y., Ban, S. J., Park, S. N., Lee, Y. M., Choi, E. G., 2006, Development of modeling input system for air quality assessment in Seoul metropolitan areas, NIER.

6.
Martien, P. T., Harley, R. A., Gauci, D. G., 2006, Adjoint sensitivity analysis for a three-dimensional photoche -mical model: Implementation and method comparison, Environmental Science & Technology, 40(8), 2663- 2670. crossref(new window)

7.
Napelenok, S. L., Cohan, D. S., Hu, Y., Russell, A. G., 2006, Decoupled direct 3D sensitivity analysis for particulate matter (DDM-3D/PM), Atmospheric Environment, 40, 6112-6121. crossref(new window)

8.
Umeda, T., Martien, P. T., 2002, Evaluation of a data assmilation technique for a mesoscale meteorological model used for air quality modeling, Journal of Applied Meteorology, 41, 12-29. crossref(new window)

9.
Yamaji, K., Uno, I., Irie, H., 2012, Investigating the response of East Asian ozone to Chinese emission changes using a linear approach, Atmospheric Environment, 55, 475-482. crossref(new window)

10.
U.S. EPA, 1996, Air Quality Criteria for Particulate Matter, Office of Research and Development, EPA/ 600/P-95/001bF.

11.
Zhang, Q., Streets, D. G., Carmicheal, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., Chen, D., Duan, L., Lei, Y., Wang, L. T., Yao, Z. L., 2009, Asian emissions in 2006 for the NASA INTEX-B mission, Atmospheric Chemistry and Physics, 9, 5131-5153. crossref(new window)