DOI QR코드

DOI QR Code

서해 조석현상에 따른 국지기상 변화가 수도권 오존농도에 미치는 영향

Impacts of Local Meteorology caused by Tidal Change in the West Sea on Ozone Distributions in the Seoul Metropolitan Area

  • 김성민 (부산대학교 지구환경시스템학부) ;
  • 김유근 (부산대학교 대기환경과학과) ;
  • 안혜연 (부산대학교 지구환경시스템학부) ;
  • 강윤희 (부산대학교 환경연구원) ;
  • 정주희 (부산대학교 환경연구원)
  • Kim, Sung Min (Division of Earth Environmental System, Pusan National University) ;
  • Kim, Yoo-Keun (Department of Atmospheric Sciences, Pusan National University) ;
  • An, Hye Yeon (Division of Earth Environmental System, Pusan National University) ;
  • Kang, Yoon-Hee (The Institute of Environmental Studies, Pusan National University) ;
  • Jeong, Ju-Hee (The Institute of Environmental Studies, Pusan National University)
  • 투고 : 2018.12.06
  • 심사 : 2019.01.03
  • 발행 : 2019.03.31

초록

In this study, the impacts of local meteorology caused by tidal changes in the West Sea on ozone distributions in the Seoul Metropolitan Area (SMA) were analyzed using a meteorological model (WRF) and an air quality (CMAQ) model. This study was carried out during the day (1200-1800 LST) between August 3 and 9, 2016. The total area of tidal flats along with the tidal changes was calculated to be approximately $912km^2$, based on data provided by the Environmental Geographic Information Service (EGIS) and the Ministry of Oceans and Fisheries (MOF). Modeling was carried out based on three experiments, and the land cover of the tidal flats for each experiment was designed using the coastal wetlands, water bodies (i.e., high tide), and the barren or sparsely vegetated areas (i.e., low tide). The land cover parameters of the coastal wetlands used in this study were improved in the herbaceous wetland of the WRF using updated albedo, roughness length, and soil heat capacity. The results showed that the land cover variation during high tide caused a decrease in temperature (maximum $4.5^{\circ}C$) and planetary boundary layer (PBL) height (maximum 1200 m), and an increase in humidity (maximum 25%) and wind speed (maximum $1.5ms^{-1}$). These meteorological changes increased the ozone concentration (about 5.0 ppb) in the coastal areas including the tidal flats. The increase in the ozone concentration during high tide may be caused by a weak diffusion to the upper layer due to a decrease in the PBL height. The changes in the meteorological variables and ozone concentration during low tide were lesser than those occurring during high tide. This study suggests that the meteorological variations caused by tidal changes have a meaningful effect on the ozone concentration in the SMA.

키워드

참고문헌

  1. An, H. Y., Kim, Y. K., Jeong, J. H., 2017, Impacts of land cover change of tidal flats on local meteorology in Gyeonggi Bay, West Sea of Korea, J. Korean Meteor. Soc., Atmos., 27(4), 399-409.
  2. Banta, R. M., Senff, C. J., Alvarez, R. J., Langford, A. O., Parrish, D. D., Trainer, M. K., Darby, L. S., Hardesty, R. M., Lambeth, B., Neuman, J. A., Angevine, W. M., Nielsen-Gammon, J., Sandberg, S. P., White, A. B., 2011, Dependence of daily peak $O_3$ concentrations near Houston, Texas on environmental factors: Wind speed, temperature, and boundary-layer depth, Atmospheric Environment, 45(1), 162-173. https://doi.org/10.1016/j.atmosenv.2010.09.030
  3. Choi, M. K., Cho, K. C., Kang, C. M., Yeo, H. G., Kim, H. K., 1998, A Study on the characteristics of particulate matter in the coastal regions, J. Environ. Health Sci., 24(3), 114-123.
  4. Community Modeling and Analysis System; CMAS, http://www.cmascenter.org/cmaq/
  5. Dawson, J. P., Adams, P. J., Pandis, S. N., 2007, Sensitivity of ozone to summertime climate in the eastern USA: A modeling case study, Atmospheric Environment, 41(7), 1494-1511. https://doi.org/10.1016/j.atmosenv.2006.10.033
  6. Environmental Geographic Information Service; EGIS, http://egis.me.go.kr/req/intro.do
  7. Han, Z., Peng, F., 2012, Soil moisture quantitative study of the Nanhui tidal flat in the Yangtze river estuary by using ENVISAT ASAR data, 2012 International Conference on Systems and Informatics (ICSAI2012), Yantai, 2188-2192.
  8. Hanna, S. R., 1994, Mesoscale meteorological model evaluation techniques with emphasis on needs of air quality models, Mesoscale Modeling of the Atmosphere, Amer. Meteor. Soc., 25, 47-58.
  9. Jeon, W. B., Lee, H. W., Lee, S. H., Choi, H. J., Kim, D. H., Park, S. Y., Numerical study on the impact of meteorological input data on air quality modeling on high ozone episode at coastal region, J. Environ. Sci. Int., 27(1), 30-40.
  10. Jeong, Y. M., Lee, S. H., Lee, H. W., Jeon, W. B., 2012, Numerical ttudy on the process analysis of ozone production due to emissions reduction over the Seoul metropolitan area, J. Environ. Sci. Int., 21(3), 339-349. https://doi.org/10.5322/JES.2012.21.3.339
  11. Jung, J. A., 2016, A Numerical study using coupled model on cold water region and fog occurrence over the southwest coast of the Korean peninsula, Master Dissertation, Pusan National University, 68(in Korean with English abstract).
  12. Kang, D. H., Kwon, B. H., Kim, P. G., 2010, $CO_2$ respiration characteristics with physicochemical properties of soils at the coastal ecosystem in Suncheon bay, J. Environ. Sci. Int., 19(2), 217-227. https://doi.org/10.5322/JES.2010.19.2.217
  13. Kang, D. H., Kwon, B. H., Yu, H. S., Kim, P. S., Kim, K. H., 2011, Seasonal and spatial variations of $CO_2$ fluxes between surface and atmosphere in foreshore, paddy field and woods sites, J. Environ. Sci. Int., 20(8), 963-975. https://doi.org/10.5322/JES.2011.20.8.963
  14. Kang, G. U., 2010, Chemical composition of respirable $PM_{2.5}$ and inhalable $PM_{10}$ in Iksan city during fall, 2004, 36(1), 61-71. https://doi.org/10.5668/JEHS.2010.36.1.061
  15. Kang, J. W., Moon, S. R., Park, S. J., 2004, Necessities of the simulation of tidal flats in hydrodynamic numerical models, Journal of the Korea Society of Civil Engineers B, 24(3B), 259-265.
  16. Kang, Y. H., Kim, Y. K., Oh, I. B., Hwang, M. K., Kang, J. E., 2008, Improvement of the air quality modeling using high-resolution land use in the greater Seoul area, J. Korean Soc. Atmos. Environ., 557-558. https://doi.org/10.5572/KOSAE.2007.23.5.557
  17. Kang, Y. H., Oh, I. B., Jeong, J. H., Bang, J. H., Kim, Y. K., Kim, S. T., Kim, E. H., Hong, J. H., Lee, D. G., 2016, Comparison of CMAQ ozone simulations with two chemical mechanisms (SAPRC99 and CB05) in the Seoul metropolitan region, J. Environ. Sci. Int., 25(1), 85-97. https://doi.org/10.5322/JESI.2016.25.1.85
  18. Kim, D. S., 2007, Greenhouse gas ($CH_4,\;CO_2,\;N_2O$) emissions from estuarine tidal and wetland and their characteristics, J. KOSAE, 2007.4, 225-241. https://doi.org/10.5572/KOSAE.2007.23.2.225
  19. Kim, S. T., Lee, C. B., 2010, Estimating influence of local and neighborthood emissions on ozone concentrations over the Kwang-Yang bay based on air quality simulations for a 2010 June Episode, J. KOSAE, 27(5), 504-522.
  20. Kim, T. H., Kim, Y. K., Shon, Z. H., Jeong, J. H., 2016, Sensitivity analysis of ozone simulation according to the impact of meteorological nudging, J. KOSAE, 32(4), 372-383. https://doi.org/10.5572/KOSAE.2016.32.4.372
  21. Kim, T. W., Cho, Y. K., Dever, E. P., 2007, An Evaluation of the thermal properties and albedo of a macrotidal flat. J. Geophys. Res., 112, C12009. https://doi.org/10.1029/2006JC004015
  22. Lam, J. S., Lau, A. K. H., Fung, J. C. H., 2006, Application of refined land-use categories for high resolution mesoscale atmospheric modeling, Bound.-Layer Meteor., 119, 263-288. https://doi.org/10.1007/s10546-005-9027-3
  23. Lee, H. W., Won, H. Y., Choi, H. J., Kim, H. G., 2005, Numerical simulation of effects of atmospheric flow fields using surface observational data on dispersion fields of air pollutants in Gwangyang bay, J. Korean Soc. Atmos. Environ., 21(2), 169-178. (in Korean with English abstract)
  24. Lee, J. B., Kim, Y. H., 2004, Sensitivity analysis of ozone concentration calculated by CMAQ model according to emission change, J. KOSAE, 247-249.
  25. Lee, Y. H., Ahn, K. D., Lee, Y. H., 2016, Parametrization of the tidal effect for use in the Noah land-surface model: Development and validation, Bound.-Layer Meteor., 161, 561-574. https://doi.org/10.1007/s10546-016-0178-1
  26. Mao, Q., Gautney, L. L., Cook, T. M., Jacobs, M. E., Smith, S. M., Kelsoe, J. J., 2006, Numerical experiment on MM5-CMAQ sensitivity to various PBL schemes, Atmospheric Environment, 40(17), 3092-3110. https://doi.org/10.1016/j.atmosenv.2005.12.055
  27. Ministry of Oceans and Fisheries, 2014. (https://www.mof.go.kr/ statPortal/bbs/report/view.do?ntt_id=155)
  28. National Institute of Environmental Research, 2014, Studies on the optimization method for improving the accuracy of air quality modeling, NIER-SP2013-210, 280pp.
  29. Oh, Y. J., Lee, H. O., Lee, H. J., Shin, M. K., Choi, S. I., Lee, C. D., Kim, J. W., Kim, Y. H., 2012, A Study on environmental characteristics and health evaluation of tidal flat sediments in Incheon, Incheon Institute of Health & Environment, (http://ecopia.incheon.go.kr/board/784/1815677).
  30. Park, S. E., Moon, W. M., Kim, D. J., 2009, Estimation of surface roughness parameter in intertidal mudflat using airborne polarimetric SAR data, IEEE Trans. Geosci. Remote Sens., 47(4), 1022-1031. https://doi.org/10.1109/TGRS.2008.2008908
  31. Pielke, R. A., Uliasz, M., 1998, Use of meteorological models as input to regional and mesoscale air quality models-limitations and strengths, Atmospheric Environment, 32, 1455-1466. https://doi.org/10.1016/S1352-2310(97)00140-4
  32. Pirovano, G., Coll, I., Bedogni, M., Alessandrini, S., Costa, M. P., Gabusi, V., Lasry, F., Menut, L., Vautard, R., 2007, On the influence of meteorological input on photochemical modelling of a severe episode over a coastal area, Atmos. Environ., 41, 6445-6464. https://doi.org/10.1016/j.atmosenv.2007.04.011
  33. Seaman, N. L., 2000, Meteorological modeling for air-quality assessments, Atmospheric Environment, 34(12-14), 2231-2259. https://doi.org/10.1016/S1352-2310(99)00466-5
  34. Stockwell, W. R., Middleton, P., Chang, J. S., Tang, X., 1990, The second generation regional acid deposition model chemical mechanism for regional air quality modeling, J. Geophys. Res., 95, 16343-16347. https://doi.org/10.1029/JD095iD10p16343