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Variation of Aerosol Scale Height in South Central Hebei Plain and Its Evaluation Model (Vol. 49, No.2, Tot No.340 2021) TEXT SIZE: A A A

ZHANG Zhengteng1, ZHANG Lingyun1,SHEN Tan1, LI Fuxing1,2, ZHANG Jiayi1, LI Xinyue1, GUO Yunjuan1, JI Wentao1, LI Yuan1
(1. Hebei Normal University, College of Resources and Environmental Science, Shijiazhuang 050024, China;
2. Laboratory of Environmental Evolution and Ecological Construction,Shijiazhuang 050024, China)

Abstract: As an important parameter to reflect the vertical distribution of atmospheric aerosol, aerosol scale height (ASH) has been widely applied to aerosol inversion and model revision. The Peterson Model and Multiple Regression Analysis are employed to evaluate the temporal-spatial variation of aerosol scale height in South Central Hebei Plain (SCHP) and to build its evaluation model based on the meteorological observation data and MODIS satellite inversion data from 2009 to 2016. The results show that the ASH is highest in summer, then in spring and autumn, and lowest in winter. The annual mean ASH is lowest in 2016 during the study period. In addition, the ASH indicated the spatial distribution patterns with high in northeast and low in southwest. And the low ASH mainly located in the piedmont of Taihang Mountain, while the high ASH in the north areas of SCHP. The ASH is significantly correlated to the air temperature, air pressure, ground temperature, relative humidity, vapor pressure and visibility. Using the Multiple Regression Analysis, the empirical estimation model of ASH is built according to the meteorological factors. The analyzing results of empirical model indicate that the meteorological factors could account for the 61.8% variations of ASH. The relative error between MODIS-ASH and simulated ASH is almost less than 10%. Understanding the variation of ASH and estimating the ASH values has important implications for the inversion of aerosol concentration and for the management of atmospheric environment in SCHP.

Key words: South Central Hebei Plain; aerosol scale height; temporal-spatial variation; Peterson Model; Multiple Regression Analysis

EARTH AND ENVIRONMENT Vol.49, No.2, Tot No.340, 2021, Page 147-156 


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