The effects of different planetary boundary layer schemes on PM2.5 concentration simulations in winter stable weather of Shanxi
DONG Chun-qing1,2, ZHENG You-fei1, WU Yong-li2, GUO Yuan-yuan2, WANG Yang2
1. School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;
2. Shanxi Meteorological Observatory, Taiyuan 030006, China
Adequate air quality modeling is reliant on accurate meteorological simulation especially in the planetary boundary layer (PBL). To further understand how the boundary layer processes affect the mixing and transmission of air pollutants, the sensitivity tests of WRF-Chem model with different PBL schemes were utilized. Surface temperature, wind field, PM2.5 concentration, dynamic and thermal PBL stratification were simulated in the typical winter stable weather condition of Shanxi province, and the results were compared with the observational data. The simulation ability of different schemes were analyzed, and the effects of PBL thermal stratification and turbulent transportation differences on PM2.5 concentration simulation were discussed. The results indicated that both of the two schemes could simulate the spatial distribution and diurnal variation characteristics of surface temperature, wind speed, and PM2.5 concentration in the winter stable weather. The relatively larger error of temperature simulated normally occurred at night, while the simulation error of surface wind speed and PM2.5 concentration mainly appeared in the afternoon. Surface temperature, wind field and PM2.5 concentration simulated by MYJ scheme showed less error, and more close to the observations. The differences of PBL thermal stratification and turbulent transportation simulated by different PBL schemes led to the differences of surface PM2.5 concentration simulation. The thicker inversion layer of MYJ scheme caused the lower surface PM2.5 concentration at night, while the lower mixing layer and weaker surface wind speed simulated by MYJ scheme resulted in a higher surface PM2.5 concentration in the afternoon.
Tran H N Q, Molders N. Investigations on meteorological conditions for elevated PM2.5 in Fairbanks, Alaska [J]. Atmospheric Research, 2011,99(1):39-49.
Zhang D L, Zheng W Z. Diurnal cycle of surface winds and temperature as simulated by five boundary layer parameterizations [J]. Appl. Meteorol., 2004,43(1):157-169.
[7]
Pleim J E. A combined local and nonlocal closure model for the atmospheric boundary layer. Part II: Application and evaluation in a mesoscale meteorological model [J]. Appl. Meteor. Climat., 2007,46:1396-1409.
[8]
Zhang Y, M K Dubey, S C Olsen, et al. Comparisons of WRF-Chem Simulations in Mexico City with ground -based RAMA measurements during the 2006-MILAGRO [J]. Atmospheric Chemistry & Physics Discussions, 2009,9(11):3777-3798.
[9]
Cheng F Y, Chin S C, Liu T H. The role of boundary layer schemes in meteorological and air quality simulations of the Taiwan area [J]. Atmospheric Environment, 2012,54(4):714-727.
Zaveri R A, Peters L K. A new lumped structure photochemical mechanism for long-scale applications [J]. Journal of Geophysical Research Atmospheres, 1999,104(D23):30387-30415.
[20]
Wild O, Zhu X, Prather M J. Fast-J: Accurate Simulation of In-and below-cloud photolysis in tropospheric chemical models [J]. Journal of Atmospheric Chemistry, 2000,37(3):245-282.
[21]
Zaveri R A, Easter R C, Peters L K. A computationally efficient multicomponent equilibrium solver for aerosols (MESA) [J]. Journal of Geophysical Research Atmospheres, 2005,110(D24): 1064-1067.
[22]
Chen F, Duhia J. Coupling an advanced land-surface/ hydrology model with the Penn State/NCAR MM5 modeling system [J]. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 2001,129(4):569-585.
[23]
Kusaka H, Kondo H, Kikegawa Y, et al. A simple single layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models [J]. Boundary-Layer Meteorology, 2001,101(3):329-358.
[24]
Kusaka H, and Kimura F. Thermal effects of urban canyon structure on the nocturnal heat island: numerical experiment using a mesoscale model coupled with an urban canopy model [J]. Journal of Applied Meteorology, 2004,43(12):1899-1910.
[25]
Kusaka H, Kimura F, Hirakuchi H, et al. The effects of land-use alteration on the sea breeze and daytime heat island in the Tokyo metropolitan area [J]. Journal of the Meteorological Society of Japan, 2000,78(4):405-420.
Ma Xinye, Zhang Yaocun. Numerical study of the impacts of urban expansion on meiyu Precipitation over Eastern China [J]. J.meteor. Res., 29(2):237-256.
He K B. Multi-resolution emission inventory for China (MEIC): model framework and 1990-2010 anthropogenic emissions[C]// AGU Fall Meeting Abstracts. AGU Fall Meeting Abstracts, 2012.
[31]
Lei Y, Zhang Q, He K B, et al. Primary anthropogenic aerosol emission trends for China, 1990~2005 [J]. Atmospheric Chemistry & Physics, 2011,11(3):931-954.
[32]
Hong S Y, Noh Y, Dudhia J. A new vertical diffusion package with an explicit treatment of entrainment processes [J]. Monthly Weather Review, 2006,134(9):2318-2341.
[33]
Mellor G L, Yamada T. Development of a turbulence closure model for geophysical fluid problems [J]. Reviews of Geophysics, 1982,20(4):851-875.
