DOI QR코드

DOI QR Code

동남지역 주요 배출지역의 PM2.5 기여도 분석

PM2.5 Source Apportionment Analysis to Investigate Contributions of the Major Source Areas in the Southeastern Region of South Korea

  • Ju, Hyeji (Department of Environmental and Safety Engineering, Ajou University) ;
  • Bae, Changhan (Department of Environmental and Safety Engineering, Ajou University) ;
  • Kim, Byeong-Uk (Georgia Environmental Protection Division) ;
  • Kim, Hyun Cheol (Air Resources Laboratory, National Oceanic and Atmospheric Administration) ;
  • Yoo, Chul (Air Quality Research Division, National Institute of Environmental Research) ;
  • Kim, Soontae (Department of Environmental and Safety Engineering, Ajou University)
  • 투고 : 2018.03.02
  • 심사 : 2018.07.16
  • 발행 : 2018.08.31

초록

We utilize the CAMx (Comprehensive Air Quality Model with eXtensions) system and the PSAT (Particulate Source Apportionment Technology) diagnostic tool to determine the $PM_{2.5}$ concentration and to perform its source apportionment in the southeastern region of South Korea. For a year-long simulation, eight local authorities in the region such as Pohang, Daegu, Gyeongju, Ulsan, Busan-Gimhae, Gosung-Changwon, Hadong, and all remaining areas in Gyeongsangnam-do, are selected as source areas based on the emission rates of $NO_x$, $SO_x$, VOC, and primary PM in CAPSS (Clean Air Policy Support System) 2013 emissions inventory. The CAMx-PSAT simulation shows that Pohang has the highest $PM_{2.5}$ self-contribution rate (25%), followed by Hadong (15%) and Busan-Gimhae (14%). With the exception of Pohang, which has intense fugitive dust emissions, other authorities are strongly affected by emissions from their neighboring areas. This may be measured as much as 1 to 2 times higher than that of the self-contribution rate. Based on these estimations, we conclude that the efficiency of emission reduction measures to mitigate $PM_{2.5}$ concentrations in the southeastern region of South Korea can be maximized when the efforts of local or regional emission controls are combined with those from neighboring regions. A comprehensive control policy planning based on the collaboration between neighboring jurisdictional boundaries is required.

키워드

참고문헌

  1. Bae, C., Kim, E., Kim, B.U., Kim, H.C., Woo, J.H., Moon, K.J., Shin, H.J., Song, I.H., Kim, S. (2017a) Impact of Emission Inventory Choices on $PM_{10}$Forecast Accuracy and Contributions in the Seoul Metropolitan Area. Journal of Korean Society for Atmospheric Environment, 33(5), 497-514. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.5.497
  2. Bae, M., Kim, H.C., Kim, B.-U., Kim, S. (2017b) Development and Application of the Backward-tracking Model Analyzer to Track Physical and Chemical Processes of Air Parcels during the Transport, Journal of Korean Society for Atmospheric Environment, 33(3), 217-232. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.3.217
  3. Bae, C., Yoo, C., Kim, B.-U., Kim, H.C., Kim, S. (2017c) $PM_{2.5}$ 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, 33(5), 445-457. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.5.445
  4. Benjey, W., Houyoux, M., Susick, J. (2001) Implementation of the SMOKE emission data processor and SMOKE tool input data processor in models-3, US EPA.
  5. Carter, W.P.L. (2016) SAPRC-99 Mechanism Files and Associated Programs and Examples, http://www.engr.ucr.edu/-carter/SAPRC99/index (accessed on Nov. 13, 2016).
  6. Chaloulakou, A., Kassomenos, K., Spyrellis, N., Demokritou, P., Koutrakis, P. (2003) Measurements of $PM_{10}$and $PM_{2.5}$ particle concentrations in Athens, Greece, Atmospheric Environment, 37, 649-660. https://doi.org/10.1016/S1352-2310(02)00898-1
  7. Chang, J.S., Brost, R.A., Isaksen, I.S.A., Madronich, S., Middleton, P., Stockwell, W.R., Walcek, C.J. (1987) A threedimensional Eulerian acid deposition model: physical concepts and formulation, Journal of Geophysical Research: Atmospheres, 14681-14700.
  8. Chen, F., Dudhia, J. (2001) Coupling an advanced land surface-hydrology model with the penn state-NCAR MM5 modeling system. Part I: model implementation and sensitivity, Monthly Weather Review, 129(4), 569-585. https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
  9. Chou, M.D., Suarez, M.J. (1994) An efficient thermal infrared radiation parameterization for use in general circulation models, NASA Technical Memorandum, 104606 (3), 85.
  10. Colella, P., Woodward, P.R. (1984) The piecewise parabolic method (PPM) for gas-dynamical simulations, Journal of Computational Physics, 54, 174-201. https://doi.org/10.1016/0021-9991(84)90143-8
  11. Dunker, A.M., Yarwood, G., Ortmann, J.PW, Wilson, G.M. (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. https://doi.org/10.1021/es011418f
  12. Emery, C., Tai, E., Yarwood, G. (2001) Enhanced Meteorological Modeling and Performance Evaluation for Two Texas Ozone Episodes, Prepared for the Texas Natural Resource Conservation Commission. ENVIRON International Corporation, Novato, CA.
  13. Emery, C., Liu, Z., Russell, A.G., Odman, M.T., Yarwood, G., Kumar, N. (2017) Recommendations on statistics and benchmarks to assess photochemical model performance, Journal of the Air & Waste Management Association, 67(5), 582-598. https://doi.org/10.1080/10962247.2016.1265027
  14. ENVIRON International Corporation (2014) User's Guide: COMPREHENSIVE AIR QUALITY MODEL with EXTENSIONS Version 6.1, http://www.camx.com.
  15. Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P.I., Geron, C. (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. https://doi.org/10.5194/acpd-6-107-2006
  16. Han, Y.-J., Kim, T.-S., Kim, H. (2008) Ionic constituents and source analysis of $PM_{2.5}$ in three Korean cities, Atmospheric Environment, 42, 4735-4746. https://doi.org/10.1016/j.atmosenv.2008.01.047
  17. Hong, S.Y., Dudhia, J., Chen, S.H. (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation, Monthly Weather Review, 132(1), 103-120. https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2
  18. Hong, S.-Y., Noh, Y., Dudhia, J. (2006) A new vertical diffusion package with an explicit treatment of entrainment processes, Monthly Weather Review, 134, 2318-2341. http://dx.doi.org/10.1175/MWR3199.1.
  19. Jeon, B.-I., Hwang, Y.-S. (2014) Characteristic of Metallic and Ionic Concentrations in $PM_{10}$and $PM_{2.5}$, Journal of Environmental Science International, 23(5), 819-827. (in Korean with English abstract) https://doi.org/10.5322/JESI.2014.5.819
  20. Ju, H., Kim, H.C., Kim, B.-U., Kim, Y.S., Shin, H.J., Kim, S. (2017) Long-term Trend Analysis of Key Criteria Air Pollutants over Air Quality Control Regions in South Korea using Observation Data and Air Quality Simulation, Journal of Korean Society for Atmospheric Environment, 34(1), 101-119. (in Korean with English abstract)
  21. Jung, J.H., Lee, H.D., Jeon, S.B., Yoo, J.K., Shon, B.H. (2012) Chemical Characteristics and Particle Size Distribution of $PM_{10}$in Iron and Steel Industrial Complex, Journal of the Korea Academia-Industrial Cooperation Society, 13(11), 5601-5609. https://doi.org/10.5762/KAIS.2012.13.11.5601
  22. Kain, J.S. (2014) The kain-fritsch convective parameterization: an update, Journal of Applied Meteorology, 43, 170-181.
  23. Kim, S. (2011) Ozone Simulations over the Seoul Metropolitan Area for a 2007 June Episode, Part V: Application of CMAQ-HDDM to Predict Ozone Response to Emission Change, Journal of Korean Society for Atmospheric Environment, 27(6), 772-790. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2011.27.6.772
  24. Kim, B.-U., Bae, C., Kim, H.C., Kim, E., Kim, S. (2017a) Spatially and chemically resolved source apportionment analysis: Case study of high particulate matter event, Atmospheric Environment, 162, 55-70. https://doi.org/10.1016/j.atmosenv.2017.05.006
  25. Kim, S., Bae, C., Yu, C., Kim, B.-U., Kim, H.C., Moon, N. (2017b) $PM_{2.5}$ simulations for the Seoul Metropolitan Area: (II) estimation of self-contributions and emission to $PM_{2.5}$ conversion rates for each source category, Journal of Korean Society for Atmospheric Environment, 33(4), 377-392. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.4.377
  26. Kim, S., Bae, C., Kim, B.-U., Kim, H.C. (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) https://doi.org/10.5572/KOSAE.2017.33.2.139
  27. Kim, S., Bae, C., Kim, E., You, Y.H., Bae, M., Lee, J.B., Seo, I.S., Lim, Y.J., Kim, B.U., Kim, H.C., Woo, J.H. (2017d) Domestic Ozone Sensitivity to Chinese Emissions Inventories: A Comparison between MICS-Asia 2010 and INTEXB 2006, Journal of Korean Society for Atmospheric Environment, 33(5), 480-496. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.5.480
  28. Kim, S., Kim, O., Kim, B.-U., Kim, H.C. (2017e) 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), 159-173. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2017.33.2.159
  29. Kim, H.C., Kim, S., Kim, B.-U., Jin, C.S., Hong, S.H., Park, R.J., Son, S.W., Bae, C., Bae, M., Song, C.K., Stein, A. (2017f ) Recent increase of surface particulate matter concentrations in the Seoul Metropolitan Area, Korea. Scientific reports, 7, 4710, doi:10.1038/s41598-017-05092-8.
  30. Lee, T.J., Jeon, W.-B., Lee, H.W. (2017) Analysis of meteorological patterns causing high concentration of $PM_{10}$in the Korean peninsula during the last 10 years, Proceedings of the Korea Environmental Sciences Society Conference, 26
  31. Leem, J.H., Lee, J.T., Kim, D.G., Shin, D.C., Roh, J.H. (1998) Shortterm-Effects of Air Pollution on Hospital Visits for Respiratory Diseases in Seoul, Korean Journal of Occupational and Environmental Medicine, 10(3), 333-342.
  32. Ministry of Environment (MOE) (2016) Fine Dust Countermeasure Plan, http://www.me.go.kr/issue/finedust (accessed on Feb. 23, 2017).
  33. Mlawer, E.J., Taubman, S.J., Brown, P.D., Iacono, M.J., Clough, S.A. (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research : Atmospheres, 102(D14), 16663-16682. https://doi.org/10.1029/97JD00237
  34. Nenes, A., Pandis, S.N., Pilinis, C. (1998) ISORROPIA: A new thermodynamic equilibrium model for multiphase multicomponent inorganic aerosols, Aquatic Geochemistry, 4(1), 123-152. https://doi.org/10.1023/A:1009604003981
  35. Oh, I., Bang, J.H., Kim, S., Kim, E., Hwang, M.K., Kim, Y. (2016) Spatial Distribution of Air Pollution in the Ulsan Metropolitan Region, Journal of Korean Society for Atmospheric Environment, 32(3), 394-407. (in Korean with English abstract) https://doi.org/10.5572/KOSAE.2016.32.4.394
  36. Ramboll-Environ (2016) Comprehensive Air Quality Model with Extensions, http://www.camx.com/ (accessed on Sep. 20, 2016).
  37. Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M., Duda, M.G., Huang, X., Wang, W., Powers, J.G. (2008) A description of the advanced research WRF version 3 (Note NCAR/TN-475+STR), National Center For Atmospheric Research Boulder Co Mesoscale and Microscale Meteorology Div.
  38. SMA (2017) http://cleanair.seoul.go.kr/ (accessed on Feb. 23, 2017).
  39. Strader, R., Lurmann, F., Pandis, S.N. (1999) Evaluation of secondary organic aerosol formation in winter, Atmospheric Environment, 33(29), 4849-4863. https://doi.org/10.1016/S1352-2310(99)00310-6
  40. United States Environmental Protection Agency (US EPA) (2011) Air Quality Modeling Technical Support Document: Source Sector Assessments, https://www3.epa.gov/scram001/reports/EPA454_R11_006.pdf (accessed on Aug. 2011).
  41. Wagstrom, K.M., Pandis, S.N., Yarwood, G., Wilson, G.M., Morris, R.E. (2008) Development and application of a computationally efficient particulate matter apportionment algorithm in a three-dimensional chemical transport model. Atmospheric Environment, 42(22), 5650-5659. https://doi.org/10.1016/j.atmosenv.2008.03.012
  42. Yarwood, G., Morris, R.E., Wilson, G.M. (2007) Particulate matter source apportionment technology (PSAT) in the CAMx photochemical grid model, Air Pollution Modeling and its Application XVII, 478-492.
  43. Zhang, W., Capps, S.L., Hu, Y., Nenes, A., Napelenok, S.L., Russell, A.G. (2012) Development of the high-order decoupled direct method in three dimensions for particulate matter: enabling advanced sensitivity analysis in air quality models. Geoscientific Model Development, 5(2), 355-368. https://doi.org/10.5194/gmd-5-355-2012