Browse > Article
http://dx.doi.org/10.5572/KOSAE.2017.33.4.377

PM2.5 Simulations for the Seoul Metropolitan Area: (II) Estimation of Self-Contributions and Emission-to-PM2.5 Conversion Rates for Each Source Category  

Kim, Soontae (Department of Environmental & Safety Engineering, Ajou University)
Bae, Changhan (Department of Environmental & Safety Engineering, Ajou University)
Yoo, Chul (Air Quality Policy Division, Ministry of Environment)
Kim, Byeong-Uk (Georgia Environmental Protection Division)
Kim, Hyun Cheol (NOAA/Air Resources Laboratory)
Moon, Nankyoung (Environmental Assessment Group, Korea Environment Institute)
Publication Information
Journal of Korean Society for Atmospheric Environment / v.33, no.4, 2017 , pp. 377-392 More about this Journal
Abstract
A set of BFM (Brute Force Method) simulations with the CMAQ (Community Multiscale Air Quality) model were conducted in order to estimate self-contributions and conversion rates of PPM (Primary $PM_{2.5}$), $NO_x$, $SO_2$, $NH_3$, and VOC emissions to $PM_{2.5}$ concentrations over the SMA (Seoul Metropolitan Area). CAPSS (Clean Air Policy Support System) 2013 EI (emissions inventory) from the NIER (National Institute of Environmental Research) was used for the base and sensitivity simulations. SCCs (Source Classification Codes) in the EI were utilized to group the emissions into area, mobile, and point source categories. PPM and $PM_{2.5}$ precursor emissions from each source category were reduced by 50%. In turn, air quality was simulated with CMAQ during January, April, July, and October in 2014 for the BFM runs. In this study, seasonal variations of SMA $PM_{2.5}$ self-sensitivities to PPM, $SO_2$, and $NH_3$ emissions can be observed even when the seasonal emission rates are almost identical. For example, when the mobile PPM emissions from the SMA were 634 TPM (Tons Per Month) and 603 TPM in January and July, self-contributions of the emissions to monthly mean $PM_{2.5}$ were $2.7{\mu}g/m^3$ and $1.3{\mu}g/m^3$ for the months, respectively. Similarly, while $NH_3$ emissions from area sources were 4,169 TPM and 3,951 TPM in January and July, the self-contributions to monthly mean $PM_{2.5}$ for the months were $2.0{\mu}g/m^3$ and $4.4{\mu}g/m^3$, respectively. Meanwhile, emission-to-$PM_{2.5}$ conversion rates of precursors vary among source categories. For instance, the annual mean conversion rates of the SMA mobile, area, and point sources were 19.3, 10.8, and $6.6{\mu}g/m^3/10^6TPY$ for $SO_2$ emissions while those rates for PPM emissions were 268.6, 207.7, and 181.5 (${\mu}g/m^3/10^6TPY$), respectively, over the region. The results demonstrate that SMA $PM_{2.5}$ responses to the same amount of reduction in precursor emissions differ for source categories and in time (e.g. seasons), which is important when the cost-benefit analysis is conducted during air quality improvement planning. On the other hand, annual mean $PM_{2.5}$ sensitivities to the SMA $NO_x$ emissions remains still negative even after a 50% reduction in emission category which implies that more aggressive $NO_x$ reductions are required for the SMA to overcome '$NO_x$ disbenefit' under the base condition.
Keywords
$PM_{2.5}$; SMA; Emissions ($NO_x$, $SO_2$, $NH_3$, VOC, and PPM)-to-$PM_{2.5}$ conversion rates;
Citations & Related Records
Times Cited By KSCI : 6  (Citation Analysis)
연도 인용수 순위
1 Bae, C., C. Yu, B.-U. Kim, H.C. Kim, and S. Kim (2017) $PM_{2.5}$ Simulations for the Seoul Metropolitan Area: (III) Application of the Modeled and Observed $PM_{2.5}$ Ratio on the Contribution Estimation, Journal of Korean Society for Atmospheric Environment (Under review).
2 Byun, D.W. and J.K.S. Ching (1999) Science Algorithms of the EPA Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System, EPA Report, EPA/600/R-99/030, National Exposure Research Laboratory, Research Triangle Park, NC.
3 Carter, W.P.L. (1999) Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment, Report to California Air Resources Board, Contracts 92-329 and 95-308.
4 Choi, J.K., J.B. Heo, S.J. Ban, S.M. Yi, and K.D. Zoh (2013) Source apportionment of $PM_{2.5}$ at the coastal area in Korea, Science of the Total Environment, 447, 370-380.   DOI
5 Cohan, D., J. Boylan, A. Marmur, and M. Khan (2007) An Integrated Framework for Multipollutant Air Quality Management and Its Application in Georgia, Environmental Management, 40, 545-554.   DOI
6 Dunker, A.M., G. Yarwood, J.P. Ortmann, and G.M. Wilson (2002) Comparison of source apportionment and source sensitivity of ozone in a three-dimensional air quality model, Environmental Science and Technology, 36(13), 2953-2964.   DOI
7 ENVIRON (2010) User's guide to the Comprehensive Air Quality Model with Extension (CAMx) version 5.30. http://www.camx.com.
8 Guenther, A., T. Karl, P. Harley, C. Wiedinmyer, P.I. Palmer, and C. Geron (2006) Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmospheric Chemistry and Physics Discussions, 6(1), 107-173.   DOI
9 Henneman, L.R.F., H.H. Chang, K.-J. Liao, D. Lavou, J.A. Mulholland, and A.G. Russell (2017) Accountability assessment of regulatory impacts on ozone and $PM_{2.5}$ concentrations using statistical and deterministic pollutant sensitivities, Air Quality, Atmosphere and Health, doi:10.1007/s11869-017-0463-2.   DOI
10 Karamchandani, P., Y. Long, G. Pirovano, A. Balzarini, and G. Yarwood (2017) Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data, Atmospheric Chemistry and Physics, 17(9), 5643-5664.   DOI
11 Kim, B.-U., C. Bae, H.C. Kim, E. Kim, and S. Kim (2017a) Spatially and chemically resolved source apportionment analysis: Case study of high particulate matter event, Atmospheric Environment, 162, 55-70. http://dx.doi.org/10.1016/j.atmosenv.2017.05.006.   DOI
12 Kim, E., C. Bae, H.C. Kim, J.H. Cho, B.U. Kim, and S. Kim (2017b) Regional Contributions to Particulate Matter Concentration in the Seoul Metropolitan Area, Korea: Seasonal Variation and Sensitivity to Meteorology and Emissions Inventory, Atmospheric Chemistry and Physics Discuss, doi:10.5194/acp-2016-1114.   DOI
13 Kim, S., C. Bae, B.-U. Kim, and H.C. Kim (2017c) $PM_{2.5}$ Simulations for the Seoul Metropolitan Area: (I) Contributions of Precursor Emissions in the 2013 CAPSS Emissions Inventory, Journal of Korean Society for Atmospheric Environment, 33(2), 139-158. (in Korean with English abstract)   DOI
14 Kwon, H., C. Jung, and Y. Kim (2016) The Impact of Local Government's Expenditure on Air Quality in Korea, Journal of Korean Society for Atmospheric Environment, 32(6), 583-592. (in Korean with English abstract)   DOI
15 Kim, S., O.G. Kim, B.-U. Kim, and H.C. Kim (2017d) Impact of Emissions from Major Point Sources in Chungcheongnam-do on Surface Fine Particulate Matter Concentration in the Surrounding Area, Journal of Korean Society for Atmospheric Environment, 33(2), 15-173. (in Korean with English abstract)
16 Kim, B.-U., O. Kim, H.C. Kim, and S. Kim (2016) Influence of fossil-fuel power plant emissions on the surface fine particulate matter in the Seoul Capital Area, South Korea. Journal of the Air and Waste Management Association, 66(9), 863-873.   DOI
17 Kim, D.K., T.J. Lee, S.C. Kim, and D.S. Kim (2012) Sources Apportionment Estimation of Ambient $PM_{2.5}$ and Identification of Combustion Sources by Using Concentration Ratios of PAHs, Journal of Korean Society for Atmospheric Environment, 28(5), 538-555.   DOI
18 Kim, J. (2014) National Institute of Environmental Research, Personal Communication.
19 Kim, S., N. Moon, and D.W. Byun (2008) Korea Emissions Inventory Processing Using the US EPA's SMOKE System, Asian Journal of Atmospheric Environment, 2(1), 34-46.   DOI
20 Lee, S., Y. Ghim, Y. Kim, and J. Kim (2006) Estimation of the seasonal variation of particulate nitrate and sensitivity to the emission changes in the greater Seoul area, Atmospheric Environment, 40(20), 3724-3736.   DOI
21 Seoul (2016) Development of Emissions Inventory and Intensive Monitoring for $PM_{2.5}$ Sources, http://opengov.seoul.go.kr/research/11895404 (accessed on Mary 30, 2017).
22 MOE (2016) Ministry of Environment, Fine Dust Countermeasure Plan. http://www.me.go.kr/issue/finedust (accessed on Feb. 23, 2017). (in Korean)
23 NACAA (2011) $PM_{2.5}$ Modeling Implementation for Projects Subject to National Ambient Air Quality Demonstration Requirements Pursuant to New Source Review, https://www3.epa.gov/scram001/10thmodconf/review_material/01072011-NACAA$PM_{2.5}$ModelingWorkgroupReport-FINAL.pdf (accessed on May 31, 2017).
24 NIER (2013) National institute of environmental research, Trans-boundary Transport of Air Pollutants over Northeast Asia(I). (in Korean)
25 Nopmongcol, U., J. Grant, E. Knipping, M. Alexander, R. Schurhoff, D. Young, J. Jung, T. Shah, and G. Yarwood (2017) Air Quality Impacts of Electrifying Vehicles and Equipment Across the United States, Environmental Science and Technology, 51(5), 2830-2837, DOI: 10.1021/acs.est.6b04868.   DOI
26 Pun, B. and C. Seigneur (2001) Sensitivity of Particulate Matter Nitrate Formation to Precursor Emissions in the California San Joaquin Valley, Environ, Environmental Science and Technology, 35(14), 2979-2987, DOI: 10.1021/es0018973.   DOI
27 Skamarock, W.C., J.B. Klemp, J. Dudhia, D.O. Gill, D.M. Barker, M.G. Duda, X. Huang, W. Wang, and J.G. Powers (2008) A description of the advanced research WRF version 3, NCAR Tech. Note NCAR/TN-475+STR, National Center for Atmospheric Research, Boulder, CO, 125.
28 SMA (2017) http://cleanair.seoul.go.kr/ (accessed on Feb. 23, 2017).
29 U.S. EPA (2007) Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, $PM_{2.5}$, and Regional Haze, https://www.epa.gov/scram001/guidance/guide/final-03-pm-rh-guidance.pdf (accessed on May 1, 2017).
30 SOS (2017) Southern Oxidants Study, https://www.ncsu.edu/sos/x.html (accessed on Feb. 23, 2017).
31 U.S. EPA (2014) Guidance for $PM_{2.5}$ Permit Modeling, https://www3.epa.gov/scram001/guidance/guide/Guidance_for_PM25_Permit_Modeling.pdf (accessed on May 31, 2017).
32 U.S. EPA (2016) $PM_{2.5}$ Precursor Demonstration Guidance, https://www.epa.gov/pm-pollution/draft-pm25-precursor-demonstration-guidance (accessed on May 31, 2017).
33 Zhang, W., S.L. Capps, Y. Hu, A. Nenes, S.L. Napelenok, and A.G. Russell (2012) Development of the high-order decoupled direct method in three dimensions for particulate matter: enabling advanced sensitivity analysis in air quality models, Geosci. Geoscientific Model Development, 5(2), 355-368.   DOI
34 U.S. EPA (2017) Modeling Procedures for Demonstrating Compliance with $PM_{2.5}$ NAAQS, https://www.epa.gov/nsr/modeling-procedures-demonstratingcompliance-pm-25-naaqs (accessed on March 30, 2017).
35 Wang, J., J. Xu, Y. He, Y. Chen, and F. Meng (2016) Long range transport of nitrate in the low atmosphere over Northeast Asia, Atmospheric Environment, 144, 315-324.   DOI
36 Woo, J.H., S. Quan, K.C. Choi, H.K. Kim, H. Jin, C.-K. Song, J. Han, and S. Lee (2014) Development of the CREATE Inventory in Support of Integrated Modeling of Climate and Air Quality for East Asia, In Global Emission InitiAtive Conference.