边界层方案与垂直混合对京津冀地区O<sub>3</sub>模拟的影响研究

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Abstract Three boundary layer schemes, YSU, MYJ, and ACM2, in the WRF-Chem model were used to simulate O₃ during June 2019, a typical pollution month, over Beijing-Tianjin-Hebei and surrounding areas. The spatial-temporal distribution of simulated surface meteorological variables, NO₂ and O₃ concentrations, and the vertical profiles of temperature, humidity, wind components, and O₃ concentrations were compared. The simulations showed favorable performance in the spatial-temporal distributions and the vertical profiles of these meteorological variables in all three schemes, with the best performance of MYJ. All schemes could well simulate the diurnal cycle of planetary boundary layer height (PBLH), with correlation coefficients ranging from 0.58 to 0.69, but with overestimation and underestimation in daytime and nighttime, respectively. The YSU scheme performed best in PBLH simulation. The simulated NO₂ concentrations were generally overestimated by three boundary layer schemes, while the O₃ simulations were underestimated. The deviations were smaller for daytime simulations and more significant for nighttime. The best simulation was from ACM2, followed by YSU and MYJ. All three schemes gave vertical distributions of O₃ but underestimated their concentration. The simulating differences of profiles were more significant in the morning than in the afternoon. Additionally, three sensitivity experiments based on YSU were set up in this paper to compare and analyze the effect of the change of vertical mixing process on the simulation of O₃ concentration by adjusting the turbulent diffusion coefficients threshold values (TDCTs) used in the chemistry module, and the simulated changes only reflected the difference of pollution due to the change of vertical mixing process in the boundary layer rather than the change due to the adjustment of the thermodynamic field. The simulation results showed that all three experiments could improve the simulating performance of surface NO₂ and O₃ at the upper surface of the region. In particular, the most significant improvement was found in the North China Plain, where O₃ is significantly underestimated by the original three boundary layer schemes, and the mean bias is reduced by 23.7%. Vertically, the adjustments of TDCT increased the O₃ concentration near-surface in the morning and improved the simulation bias, but at the same time increased the negative bias of the underestimated O₃ concentration in the upper levels. The sensitivity experiments significantly improved the simulation performance at nighttime but not significantly during the daytime. This study showed the importance of turbulent diffusion coefficients on the vertical mixing of O₃. Therefore, improving the parameterization of turbulent diffusion coefficients is necessary for O₃ simulations.

Key words： boundary layer schemes vertical mixing O₃ WRF-Chem model

Received: 16 May 2022

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	LU Yan-ting
	ZHAO Xiu-juan
	TANG Gui-qian
	XU Jing
	CHEN Dan
	AN Xing-qin

Cite this article:

LU Yan-ting,ZHAO Xiu-juan,TANG Gui-qian等. The study on the impact of boundary layer schemes on O₃ simulations in the Beijing-Tianjin-Hebei region[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(12): 5459-5471.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I12/5459

[1]	Wang T, Xue L, Brimblecombe P, et al. Ozone pollution in China:A review of concentrations, meteorological influences, chemical precursors, and effects[J]. Science of The Total Environment, 2017, 575:1582-1596.
[2]	Yin Z, Ma X. Meteorological conditions contributed to changes in dominant patterns of summer ozone pollution in Eastern China[J]. Environmental Research Letters, 2020,15(12):124062.
[3]	Wang Y, Gao W, Wang S, et al. Contrasting trends of PM2.5 and surface-ozone concentrations in China from 2013 to 2017[J]. National Science Review, 2020,7(8):1331-1339.
[4]	Cheng L, Wang S, Gong Z, et al. Regionalization based on spatial and seasonal variation in ground-level ozone concentrations across China[J]. Journal of Environmental Sciences, 2018,67:179-190.
[5]	Yu R, Lin Y, Zou J, et al. Review on atmospheric ozone pollution in China:formation, spatiotemporal distribution, precursors and affecting factors[J]. Atmosphere, 2021,12(12):1675.
[6]	Zeng Y, Cao Y, Qiao X, et al. Air pollution reduction in China:Recent success but great challenge for the future[J]. Science of The Total Environment, 2019,663:329-337.
[7]	中华人民共和国生态环境部.2019中国生态环境状况公报[R]. 北京:中华人民共和国生态环境部, 2020. Ministry of Ecology and Environment of the People's Republic of China. 2019 China ecological environment status bulletin[R]. Beijing:Ministry of Ecology and Environment of the People's Republic of China, 2020.
[8]	He J, Gong S, Yu Y, et al. Air pollution characteristics and their relation to meteorological conditions during 2014~2015 in major Chinese cities[J]. Environmental Pollution, 2017,223:484-496.
[9]	Dufour G, Eremenko M, Beekmann M, et al. Lower tropospheric ozone over the North China Plain:variability and trends revealed by IASI satellite observations for 2008~2016[J]. Atmospheric Chemistry and Physics, 2018,18(22):16439-16459.
[10]	Li J, Nagashima T, Kong L, et al. Model evaluation and intercomparison of surface-level ozone and relevant species in East Asia in the context of MICS-Asia Phase III-Part 1:Overview[J]. Atmospheric Chemistry and Physics, 2019,19(20):12993-13015.
[11]	Banks R F, Tiana-Alsina J, Rocadenbosch F, et al. Performance evaluation of the boundary-layer height from lidar and the weather research and forecasting model at an urban coastal site in the North-East Iberian Peninsula[J]. Boundary-Layer Meteorology, 2015, 157(2):265-292.
[12]	Jia W, Zhang X. The role of the planetary boundary layer parameterization schemes on the meteorological and aerosol pollution simulations:A review[J]. Atmospheric Research, 2020,239:104890.
[13]	徐敬,马志强,赵秀娟,等.边界层方案对华北低层O3垂直分布模拟的影响[J]. 应用气象学报, 2015,26(5):567-577. Xu Jing, Ma Zhiqiang, Zhao Xiujuan, et al. The effect of different planetary boundary layer schemes on the simulation of near surface O3 vertical distribution[J]. J. Appl. Meteor. Sci., 2015,26(5):567-577.
[14]	Zhao Y, Zhang L, Zhou M, et al. Influences of planetary boundary layer mixing parameterization on summertime surface ozone concentration and dry deposition over North China[J]. Atmospheric Environment, 2019,218:116950.
[15]	Banks R F, Baldasano J M. Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain[J]. Science of The Total Environment, 2016,572:98-113.
[16]	Cuchiara G C, Li X, Carvalho J, et al. Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in Houston/Texas[J]. Atmospheric Environment, 2014,96:175-185.
[17]	Sukoriansky S, Galperin B, Perov V. A quasi-normal scale elimination model of turbulence and its application to stably stratified flows[J]. Nonlinear Processes in Geophysics, 2006,13(1):9-22.
[18]	Hu X-M, Klein P M, Xue M. Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments[J]. Journal of Geophysical Research:Atmospheres, 2013,118(18):10,490-10,505.
[19]	Du Q, Zhao C, Zhang M, et al. Modeling diurnal variation of surface PM2.5 concentrations over East China with WRF-Chem:impacts from boundary-layer mixing and anthropogenic emission[J]. Atmospheric Chemistry and Physics, 2020,20(5):2839-2863.
[20]	王安庭,李煜斌,赵纯,等.边界层方案对南京地区PM2.5浓度模拟的影响[J]. 中国环境科学, 2021,41(7):2977-2992. Wang A T, Li Y B, Zhao C, et al. Influence of different boundary layer schemes on PM2.5 concentration simulation in Nanjing[J]. China Environmental Science, 2021,41(7):2977-2992.
[21]	Jia W, Zhang X, Zhang H, et al. Application of turbulent diffusion term of aerosols in mesoscale model[J]. Geophysical Research Letters, 2021,48(11).
[22]	Jia W, Zhang X. Impact of modified turbulent diffusion of PM2.5 aerosol in WRF-Chem simulations in eastern China[J]. Atmospheric Chemistry and Physics, 2021,21(22):16827-16841.
[23]	Grell G A, Peckham S E, Schmitz R, et al. Fully coupled "online" chemistry within the WRF model[J]. Atmospheric Environment, 2005,39(37):6957-6975.
[24]	Fast J D, Gustafson W I, Easter R C, et al. Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model[J]. Journal of Geophysical Research-Atmospheres, 2006,111(D21):D21305.
[25]	Wang X, Fu T-M, Zhang L, et al. Sensitivities of ozone air pollution in the Beijing-Tianjin-Hebei Area to local and upwind precursor emissions using adjoint modeling[J]. Environmental Science & Technology, 2021,55(9):5752-5762.
[26]	Tang G Q, Liu Y T, Huang X, et al. Aggravated ozone pollution in the strong free convection boundary layer[J]. Science of the Total Environment, 2021,788.
[27]	Tang G, Zhu X, Hu B, et al. Impact of emission controls on air quality in Beijing during APEC 2014:lidar ceilometer observations[J]. Atmospheric Chemistry and Physics, 2015,15(21):12667-12680.
[28]	Zaveri R A, Peters L K. A new lumped structure photochemical mechanism for large-scale applications[J]. Journal of Geophysical Research:Atmospheres, 1999,104(D23):30387-30415.
[29]	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.
[30]	Zaveri R A, Easter R C, Fast J D, et al. Model for simulating aerosol interactions and chemistry (MOSAIC)[J]. Journal of Geophysical Research:Atmospheres, 2008,113(D13).
[31]	Thompson G, Field P R, Rasmussen R M, et al. Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II:Implementation of a new snow parameterization[J]. Monthly Weather Review, 2008,136(12):5095-5115.
[32]	Iacono M J, Delamere J S, Mlawer E J, et al. Radiative forcing by long-lived greenhouse gases:Calculations with the AER radiative transfer models[J]. Journal of Geophysical Research-Atmospheres, 2008,113(D13):D13103.
[33]	Grell G A. Prognostic evaluation of assumptions used by cumulus parameterizations[J]. Monthly Weather Review, 1993,121(3):764-787.
[34]	Grell G A, Devenyi D. A generalized approach to parameterizing convection combining ensemble and data assimilation techniques[J]. Geophysical Research Letters, 2002,29(14):1693.
[35]	Chen F, Dudhia J. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I:Model implementation and sensitivity[J]. Monthly Weather Review, 2001,129(4):569-585.
[36]	Li M, Liu H, Geng G, et al. Anthropogenic emission inventories in China:a review[J]. National Science Review, 2017,4(6):834-866.
[37]	Zheng B, Tong D, Li M, et al. Trends in China's anthropogenic emissions since 2010as the consequence of clean air actions[J]. Atmospheric Chemistry and Physics, 2018,18(19):14095-14111.
[38]	Guenther A, Karl T, Harley P, et al. Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)[J]. Atmospheric Chemistry and Physics, 2006,6(11):3181-3210.
[39]	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.
[40]	Janjić Z I. The step-mountain eta coordinate model:Further developments of the convection, viscous sublayer, and turbulence closure schemes[J]. Monthly Weather Review, 1994,122(5):927-945.
[41]	Pleim J E. A Combined Local and Nonlocal Closure Model for the Atmospheric Boundary Layer. Part I:Model Description and Testing[J]. Journal of Applied Meteorology and Climatology, 2007,46(9):1383-1395.
[42]	Hu X M, Nielsen Gammon J W, Zhang F. Evaluation of three planetary boundary layer schemes in the WRF Model[J]. Journal of Applied Meteorology and Climatology, 2010,49(9):1831-1844.
[43]	陈炯,王建捷.北京地区夏季边界层结构日变化的高分辨模拟对比[J]. 应用气象学报, 2006,(4):403-411. Chen Jiong, Wang Jianjie. Diurnal cycles of the boundary layer structure simulated by WRF in Beijing[J]. Journal of Applied Meteorological Science, 2006,17(4):403-411.
[44]	王颖,张镭,胡菊,等.WRF模式对山谷城市边界层模拟能力的检验及地面气象特征分析[J]. 高原气象, 2010,29(6):1397-1407. Wang Ying, Zhang Lei, Hu Ju, et al. Examination of the WRF model's ability to simulate the valley city boundary layer and analysis of ground meteorological characteristics[J]. Plateau Meteorology, 2010, 29(6):1397-1407.
[45]	Kim S W, McKeen S A, Frost G J, et al. Evaluations of NOx and highly reactive VOC emission inventories in Texas and their implications for ozone plume simulations during the Texas Air Quality Study 2006[J]. Atmospheric Chemistry and Physics, 2011,11(22):11361-11386.
[46]	DeMore W B, Patapoff M. Comparison of ozone determinations by ultraviolet photometry and gas-phase titration[J]. Environmental Science & Technology, 1976,10(9):897-899.