DOI QR코드

DOI QR Code

Simulation of Air Quality Over South Korea Using the WRF-Chem Model: Impacts of Chemical Initial and Lateral Boundary Conditions

WRF-Chem 모형을 이용한 한반도 대기질 모의: 화학 초기 및 측면 경계 조건의 영향

  • Lee, Jae-Hyeong (Department of Atmospheric Science, Kongju National University) ;
  • Chang, Lim-Seok (National Institute of Environmental Research, Global Environment Research Division) ;
  • Lee, Sang-Hyun (Department of Atmospheric Science, Kongju National University)
  • 이재형 (공주대학교 대기과학과) ;
  • 장임석 (국립환경과학원 지구환경연구과) ;
  • 이상현 (공주대학교 대기과학과)
  • Received : 2015.07.30
  • Accepted : 2015.12.10
  • Published : 2015.12.31

Abstract

There is an increasing need to improve the air quality over South Korea to protect public health from local and remote anthropogenic pollutant emissions that are in an increasing trend. Here, we evaluate the performance of the WRF-Chem (Weather Research and Forecasting-Chemistry) model in simulating near-surface air quality of major Korean cities, and investigate the impacts of time-varying chemical initial and lateral boundary conditions (IC/BCs) on the air quality simulation using a chemical downscaling technique. The model domain was configured over the East Asian region and anthropogenic MICS-Asia 2010 emissions and biogenic MEGAN-2 emissions were applied with RACM gaseous chemistry and MADE/SORGAM aerosol mechanism. Two simulations were conducted for a 30-days period on April 2010 with chemical IC/BCs from the WRF-Chem default chemical species profiles ('WRF experiment') and the MOZART-4 (Model for OZone And Related chemical Tracers version 4) ('WRF_MOZART experiment'), respectively. The WRF_MOZART experiment has showed a better performance to predict near-surface CO, $NO_2$, $SO_2$, and $O_3$ mixing ratios at 7 major Korean cities than the WRF experiment, showing lower mean bias error (MBE) and higher index of agreement (IOA). The quantitative impacts of the chemical IC/BCs have depended on atmospheric residence time of the pollutants as well as the relative difference of chemical mixing ratios between the WRF and WRF_MOZART experiments at the lateral boundaries. Specifically, the WRF_MOZART experiment has reduced MBE in CO and O3 mixing ratios by 60~80 ppb and 5~10 ppb over South Korea than those in the WRF-Chem default simulation, while it has a marginal impact on $NO_2$ and $SO_2$ mixing ratios. Without using MOZART-4 chemical IC, the WRF simulation has required approximately 6-days chemical spin-up time for the East Asian model domain. Overall, the results indicate that realistic chemical IC/BCs are prerequisite in the WRF-Chem simulation to improve a forecast skill of local air quality over South Korea, even in case the model domain is sufficiently large to represent anthropogenic emissions from China, Japan, and South Korea.

Keywords

References

  1. Ackermann, I. J., H. Hass, M. Memmesheimer, A. Ebel, F. S. Binkowski, and U. Shankar, 1998: Modal aerosol dynamics model for Europe: Development and first applications. Atmos. Environ., 32, 2981-2999. https://doi.org/10.1016/S1352-2310(98)00006-5
  2. Benjey, W., M. Houyoux, and J. Susick, 2001: Implementation of the SMOKE emission data processor and SMOKE tool input data processor in models-3, U.S. EPA.
  3. Borge, R., J. Lopez, J. Lumbreras, A. Narros, and E. Rodriguez, 2010: Influence of boundary conditions on CMAQ simulations over the Iberian Peninsula. Atmos. Environ., 44, 2681-2695. https://doi.org/10.1016/j.atmosenv.2010.04.044
  4. Carmichael, G. R., G. Calori, H. Hayami, I. Uno, S.-Y. Cho, M. Engardt, S.-B. Kim, Y. Ichikawa, Y. Ikeda, J.-H. Woo, H. Ueda, and M. Amann, 2002: The MICSAsia study: Model intercomparison of long-range transport and sulfur deposition in East Asia. Atmos. Environ., 36, 175-199. https://doi.org/10.1016/S1352-2310(01)00448-4
  5. Cater, 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.
  6. Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Monthly Wea. Rev., 129, 569-585. https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2
  7. Cho, K.-T., J.-C. Kim, and J.-H. Hong, 2006: A study on the comparison of biogenic VOC (BVOC) emissions estimates by BEIS and CORINAIR methodologies. J. Korean Soc. Atmos. Environ., 22, 167-177.
  8. Coats, C. J. Jr., 1996: High performance algorithms in the sparse matrix operator kernel emissions (SMOKE) modeling system, Ninth Joint Conf. on Applications of Air Pollution Meteorology with the A & WMA, Atlanta, GA, Amer. Meteor. Soc., 584-588.
  9. Damian, V., A. Sandu, M. Damian, F. Potra, and G. R. Carmichael, 2002: The kinetic preprocessor KPP-a software environment for solving chemical kinetics. Comput. Chem. Eng., 26, 1567-1579. https://doi.org/10.1016/S0098-1354(02)00128-X
  10. Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077-3107. https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2
  11. Elbern, H., H. Schmidt, and A. Ebel, 1997, Variational data assimilation for tropospheric chemistry modeling. J. Geophys. Res., 102, 15967-15985. https://doi.org/10.1029/97JD01213
  12. Elbern, H., and H. Schmidt, 1999: A four-dimensional variational chemistry data assimilation scheme for Eulerian chemistry transport modeling. J. Geophys. Res., 104, 18583-18598. https://doi.org/10.1029/1999JD900280
  13. Elbern, H., and H. Schmidt, 2001: Ozone episode analysis by four-dimensional variational chemistry data assimilation. J. Geophys. Res., 106, 3569-3590. https://doi.org/10.1029/2000JD900448
  14. Elbern, H., A. Strunk, H. Schmidt, and O. Talagrand, 2007, Emission rate and chemical state estimation by 4-dimensional variational inversion. Atmos. Chem. Phys., 7, 3749-3769. https://doi.org/10.5194/acp-7-3749-2007
  15. Emmons, L. K., and Coauthors, 2010: Description and evaluation of the model for ozone and related chemical tracers, version 4 (MOZART-4). Geosci. Model Develop., 3, 43-67. https://doi.org/10.5194/gmd-3-43-2010
  16. Fast, J., and Coauthors, 2009: Evaluating simulated primary anthropogenic and biomass burning organic aerosols during MILAGRO: Implications for assessing treatments of secondary organic aerosols. Atmos. Chem. Phys., 9, 6191-6215. https://doi.org/10.5194/acp-9-6191-2009
  17. 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). Atmos. Chem. Phys., 6, 107-173. https://doi.org/10.5194/acpd-6-107-2006
  18. Ginoux, P., M. Chin, I. Tegen, J. M. Prospero, B. Holben, O. Dubovik, and S. J. Lin, 2001: Sources and distributions of dust aerosols simulated with the GOCART model. J. Geophys. Res., 106, 20225-20273. https://doi.org/10.1029/2000JD000025
  19. Gong, S. L., X. Y. Zhang, T. L. Zhao, I. G. Mckendry, D. A. Jaffe, and N. M. Lu, 2003: Characterization of soil dust aerosol in China and its transport and distribution during 2001 ACE-Asia: 2. model simulation and validation. J. Geophys. Res., 108, 4262, doi:10.1029/2002JD002633.
  20. Grell, G. A., S. E. Peckham, R. Schmitz, S. A. McKeen, G. Frost, W. C. Skamarock, and B. Eder, 2005: Fully coupled "online" chemistry within the WRF model. Atmos. Environ., 39, 6957-6975. https://doi.org/10.1016/j.atmosenv.2005.04.027
  21. Grell, G. A., and S. R. Freitas, 2013: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling. Atmos. Chem. Phys., 13, 23845-23893. https://doi.org/10.5194/acpd-13-23845-2013
  22. Hogrefe, C., P. S. Porter, E. Gego, A. Gilliland, R. Gilliam, J. Swall, J. Irwin, and S. T. Rao, 2006: Temporal features in observed and simulated meteorology and air quality over the Eastern United States. Atmos. Environ., 40, 5041-5055. https://doi.org/10.1016/j.atmosenv.2005.12.056
  23. Hong, S.-C., J.-B. Lee, J.-Y. Choi, K.-J. Moon, H.-J. Lee, Y.-D. Hong, S.-J. Lee, and C.-K. Song, 2012: The effect of the chemical lateral boundary conditions on CMAQ simulations of tropospheric ozone for East Asia. J. Korean Soc. Atmos. Environ., 28, 581-594. https://doi.org/10.5572/KOSAE.2012.28.5.581
  24. Hong, S.-Y., J. Dudhia, and S. H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Monthly Wea. Rev., 132, 103-120. https://doi.org/10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2
  25. Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Monthly Wea. Rev., 134, 2318-2341. https://doi.org/10.1175/MWR3199.1
  26. Horowitz, L. W., S. Walters, D. L. Mauzerall, L. K. Emmons, P. J. Rasch, C. Granier, X. Tie, J. F. Lamarque, M. G. Schultz, G. S. Tyndall, J. J. Orlando, and G. P. Brasseur, 2003: A global simulation of tropospheric ozone and related tracers: Description and evaluation of MOZART, version 2. J. Geophys. Res., 108, D24, 4784, doi:10.1029/2002JD002853.
  27. Horowitz, L. W., and S.-U. Park, 2002: A simulation of long-range transport of Yellow Sand observed in April 1998 in Korea. Atmos. Environ., 36, 4173-4187. https://doi.org/10.1016/S1352-2310(02)00361-8
  28. Horowitz, L. W., D. W. Byun, R. J. Park, N.-K. Moon, S. T. Kim, and S. Zhong, 2007: Impact of transboundary transport of carbonaceous aerosols on the regional air quality in the United States: A case study of the South American wildland fire of May 1998. J. Geophys. Res., 112, D07201, doi:10.1029/2006JD007544.
  29. Iacono, M. J., J. S. Delamere, E. J. Mlawer, M. W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, doi:10.1029/2008JD009944.
  30. Jeon, W.-B., H.-W. Lee, S.-H. Lee, J.-H. Park, and H.-G. Kim, 2014: Numerical study on the characteristics of high $PM_{2.5}$ episodes in Anmyeondo area in 2009. J. Environ. Sci. International, 23, 249-259. https://doi.org/10.5322/JESI.2014.23.2.249
  31. Jonson, J. E., J. K. Sundet, and L. Tarrason, 2001: Model calculations of present and future levels of ozone and ozone precursors with a global and a regional model. Atmos. Environ., 35, 525-537. https://doi.org/10.1016/S1352-2310(00)00314-9
  32. Kang, J.-Y., S.-W. Kim, and S.-C. Yoon, 2012: Estimation of dust emission schemes and input parameters in wintertime Asian dust simulation: A case study of winter dust event on December 29, 2007. J. Korean Soc. Atmos. Environ., 1, 1-11.
  33. Kim, J.-Y., J.-S. Kim, J.-H. Hong, D.-I. Jung, S.-J. Ban, and Y.-M. Lee, 2008a: Assessment of changed input modules with SMOKE model. J. Korean Soc. Atmos. Environ., 24, 284-299. https://doi.org/10.5572/KOSAE.2008.24.3.284
  34. Kim, S.-T., N.-K. Moon, and D.-W. Byun, 2008b: Korea emissions inventory processing using the US EPA's SMOKE system. Asian J. Atmos. Environ., 2, 34-46. https://doi.org/10.5572/ajae.2008.2.1.034
  35. Kim, S.-T., N.-K. Moon, K.-T. Cho, D.-W. Byun, and E.-Y. Song, 2008c: Estimation of biogenic emissions over South Korea and its evaluation using air quality simulations. J. Korean Soc. Atmos. Environ., 24, 423-438. https://doi.org/10.5572/KOSAE.2008.24.4.423
  36. Kim, S.-T., and C.-B. Lee, 2011: Estimating influence of local and neighborhood emissions on ozone concentrations over the Kwang-Yang Bay based on air quality simulations for a 2010 June episode. J. Korean Soc. Atmos. Environ., 27, 504-522. https://doi.org/10.5572/KOSAE.2011.27.5.504
  37. Kim, S.-T., 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, J. Korean Soc. Atmos. Environ., 27, 772-790. https://doi.org/10.5572/KOSAE.2011.27.6.772
  38. Klimont, Z., J. Cofala, W. Schopp, M. Amann, D. G. Streets, Y. Ichikawa, and S. Fujita, 2001: Projections of $SO_2$, $NO_x$, $NH_3$ and VOC emissions in East Asia up to 2030. Water, Air Soil Pollut., 130, 193-198. https://doi.org/10.1023/A:1013886429786
  39. Kurokawa, J., T. Ohara, T. Morikawa, S. Hanayama, G. Janssens-Maenhout, T. Fukui, K. Kawashima, and H. Akimoto, 2013, Emissions of air pollutants and greenhouse gases over Asian regions during 2000-2008: Regional emission inventory in Asia (REAS) version 2. Atmos. Chem. Phys., 13, 11019-11058. https://doi.org/10.5194/acp-13-11019-2013
  40. Lee, H.-J., S.-W. Kim, J. Brioude, O. R. Cooper, G. J. Frost, C.-H. Kim, R.-J. Park, M. Trainer, and J.-H. Woo, 2014: Transport of $NO_x$ in East Asia identified by satellite and in situ measurements and lagrangian particle dispersion model simulations. J. Geophys. Res., 119, doi:10.1002/2013JD021185.
  41. Lee, S.-H., S.-W. Kim, M. Trainer, G. J. Frost, S. A. McKeen, O. R. Cooper, F. Flocke, J. S. Holloway, J. A. Neuman, T. Ryerson, C. J. Senff, A. L. Swanson, and A. M. Thompson, 2011: Modeling ozone plumes observed downwind of New York City over the North Atlantic Ocean during the ICARTT field campaign. Atmos. Chem. Phys., 11, 7375-7397.
  42. Liu, S. C., and Coauthors, 1996: Model study of tropospheric trace species distributions during PEM-West A, J. Geophys. Res., 101, 2073-2085. https://doi.org/10.1029/95JD02277
  43. Liu, X., L. Duan, J. Mo, E. Du, J. Shen, X. Lu, Y. Zhang, X. Zhou, C. He, and F. Zhang, 2011: Nitrogen deposition and its ecological impact in China: An overview. Environ. Pollut., 159, 2251-2264. https://doi.org/10.1016/j.envpol.2010.08.002
  44. Madronich, S., 1987: Photodissociation in the atmosphere 1. Actinic flux and the effects of ground reflections and clouds. J. Geophys. Res., 92, 9740-9752. https://doi.org/10.1029/JD092iD08p09740
  45. McKeen, S. A., G. Wotawa, D. D. Parrish, J. S. Holloway, M. P. Buhr, G. Hubler, F. C. Fehsenfeld, and J. F. Meagher, 2002: Ozone production from Canadian wildfires during June and July of 1995, J. Geophys. Res., 107, 4192, doi:10.1029/2001JD000697.
  46. McKeen, S. A., S. H. Chung, J. Wilczak, G. Grell, I. Djalalova, S. Peckham, W. Gong, V. Bouchet, R. Moffet, Y. Tang, G. R. Carmichael, R. Mathur, and S. Yu, 2007: Evaluation of several $PM_{2.5}$ forecast models using data collected during the ICARTT/NEAQS 2004 field study. J. Geophys. Res., 112, doi:10.1029/2006JD007608.
  47. Meij, A. D., E. Bossioli, C. Penard, J. F. Vinuesa, and I. Price, 2015: The effect of SRTM and Corine Land Cover data on calculated gas and $PM_{10}$ concentrations in WRF-Chem. Atmos. Environ., 101, 177-193. https://doi.org/10.1016/j.atmosenv.2014.11.033
  48. Moon, Y.-S., and Y.-S. Koo, 2006: A study on examples applicable to numerical land cover map data for atmospheric environment fields in the metropolitan area of Seoul-Real time calculation of biogenic $CO_2$ flux and VOC emission due to a geographical distribution of vegetable and analysis on sensitivity of air temperature and wind field within MM5. J. Korean Soc. Atmos. Environ., 22, 661-678.
  49. Moon, Y.-S., Y.-S. Koo, and O.-J. Jung, 2014: Analysis of sensitivity to prediction of particulate matters and related meteorological fields using the WRF-Chem model during Asian dust episode days. J. Korean Earth Sci. Soc., 35, 1-18. https://doi.org/10.5467/JKESS.2014.35.1.1
  50. Samaali, M., M. D. Moran, V. S. Bouchet, R. Pavlovic, S. Cousineau, and M. Sassi, 2009: On the influence of chemical initial and boundary conditions on annual regional air quality model simulations for North America. Atmos. Environ., 43, 4873-4885. https://doi.org/10.1016/j.atmosenv.2009.07.019
  51. Sandu, A., D. N. Daescu, and G. R. Carmichael, 2003: Direct and adjoint sensitivity analysis of chemical kinetic systems with KPP: Part I-theory and software tools. Atmos. Environ., 37, 5083-5096. https://doi.org/10.1016/j.atmosenv.2003.08.019
  52. Schell, B., I. J. Ackermann, H. Hass, F. S. Binkowski, and A. Ebel, 2001: Modeling the formation of secondary organic aerosol within a comprehensive air quality model system. J. Geophys. Res., 106, 28275-28293. https://doi.org/10.1029/2001JD000384
  53. Seinfeld, J. H., and S. N. Pandis, 1997: Atmospheric chemistry and physics: From air pollution to climate change. Wiley Intersci., 1326 pp.
  54. Song, C.-K., D.-W. Byun, R. B. Pierce, J. A. Alsaadi, T. K. Schaack, and F. Vukovich, 2008: Downscale linkage of global model output for regional chemical transport modeling: Method and general performance. J. Geophys. Res., 113, D08308, doi:10.1029/2007JD008951.
  55. Stockwell, W. R., F. Kirchner, M. Kuhn, and S. Seefeld, 1997: A new mechanism for regional atmospheric chemistry modeling. J. Geophys. Res., 102, 25847-25879. https://doi.org/10.1029/97JD00849
  56. Skamarock, W. C., and J. B. Klemp, 2008: A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J. Comput. Phys., 227, 3465-3485. https://doi.org/10.1016/j.jcp.2007.01.037
  57. Tang, Y., and Coauthors, 2007: Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models. J. Geophys. Res., 112, D10S18, doi:10.1029/2006JD007515.
  58. Tang, Y., and Coauthors, 2009: The impact of chemical lateral boundary conditions on CMAQ predictions of tropospheric ozone over the continental United States. Environ. Fluid Mech., 9, 43-58, doi 10.1007/s10652-008-9092-5.
  59. Tuccella, P., G. Curci, G. Visconti, B. Bessagnet, L. Menut, and R. J. Park, 2012: Modeling of gas and aerosol with WRF/Chem over Europe: Evaluation and sensitivity study. J. Geophys. Res., 117, D03303, doi:10.1029/2011JD016302.
  60. Wu, J.-B., J. Xu, M. Pagowski, F. Geng, S. Gu, G. Zhou, Y. Xie, and Z. Yu, 2015: Modeling study of a severe aerosol pollution event in December 2013 over Shanghai China: An application of chemical data assimilation. Particuology, 20, 41-51. https://doi.org/10.1016/j.partic.2014.10.008
  61. Zannetti, P., 2003: Air quality modeling: Theories, methodologies, computational techniques, and available databases and software. EnviroComp Institute Air Waste Manage. Assoc., 42-43.
  62. Zhang, Q., D. G. Streets, K. He, Y. Wang, A. Richter, J. P. Burrows, I. Uno, C. J. Jang, D. Chen, Z. Yao, and Y. Lei, 2007: $NO_x$ emission trends for China, 1995-2004: The view from the ground and the view from space. J. Geophys. Res., 112, D22306, doi:10.1029/2007JD008684.
  63. Zhang, Q., D. G. Streets, G. R. Carmichael, K. B. He, H. Huo, A. Kannari, Z. Klimont, I. S. Park, S. Reddy, J. S. Fu, D. Chen, L. Duan, Y. Lei, L. T. Wang, and Z. L. Yao, 2009: Asian emissions in 2006 for the NASA INTEXB mission. Atmos. Chem. Phys., 9, 5131-5153. https://doi.org/10.5194/acp-9-5131-2009

Cited by

  1. Detection of Strong NOX Emissions from Fine-scale Reconstruction of the OMI Tropospheric NO2 Product vol.11, pp.16, 2019, https://doi.org/10.3390/rs11161861
  2. Comparison of PM2.5 Chemical Components over East Asia Simulated by the WRF-Chem and WRF/CMAQ Models: On the Models’ Prediction Inconsistency vol.10, pp.10, 2019, https://doi.org/10.3390/atmos10100618