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冀中南平原区气溶胶标高变化及估算模型研究
引用本文:张蒸腾,张凌云,沈坛,李夫星,张佳怡,李欣悦,郭云娟,冀文涛,李缘.冀中南平原区气溶胶标高变化及估算模型研究[J].地球与环境,2021,49(2):147-156.
作者姓名:张蒸腾  张凌云  沈坛  李夫星  张佳怡  李欣悦  郭云娟  冀文涛  李缘
作者单位:河北师范大学资源与环境科学学院,石家庄050024;河北师范大学资源与环境科学学院,石家庄050024;河北省环境演变与生态建设省级重点实验室,石家庄050024
基金项目:河北省自然科学基金(D2019205027);河北省教育厅科技项目(QN2018035);河北师范大学博士基金项目(L2018B20)。
摘    要:作为反映大气气溶胶垂直分布的重要参量,气溶胶标高被广泛应用于气溶胶反演及模型订正研究中。为研究气溶胶标高时空变化规律并构建其简易计算模型,基于2009~2016年气象站点观测资料及MODIS卫星反演数据,利用Peterson模型及多元回归分析对冀中南平原区气溶胶标高进行了估算分析。研究结果表明:区域气溶胶标高夏季最高,春秋季次之,冬季最低,其中2016年气溶胶标高年均值最低。此外,标高空间分布差异性较大,整体表现为东北高西南低分布模式。低值区主要分布于太行山山前平原区,而高值区则主要分布于冀中南平原北部地区。气溶胶标高与气温、气压、地面温度、相对湿度、水汽压、能见度等气象要素具有显著相关性关系。通过多元回归分析,构建了基于气象要素的气溶胶标高经验估算模型,模型分析结果表明气温等气象要素可以解释气溶胶标高61.8%的变化,且研究期内平均标高的相对误差大都在10%以内,这对于冀中南地区气溶胶浓度反演以及大气环境治理与优化有着重要的现实意义。

关 键 词:冀中南平原区  气溶胶标高  时空变化  Peterson模型  多元回归分析
收稿时间:2020/6/14 0:00:00
修稿时间:2020/7/30 0:00:00

Variation of Aerosol Scale Height in South Central Hebei Plain and Its Evaluation Model
ZHANG Zhengteng,ZHANG Lingyun,SHEN Tan,LI Fuxing,ZHANG Jiayi,LI Xinyue,GUO Yunjuan,JI Wentao,LI Yuan.Variation of Aerosol Scale Height in South Central Hebei Plain and Its Evaluation Model[J].Earth and Environment,2021,49(2):147-156.
Authors:ZHANG Zhengteng  ZHANG Lingyun  SHEN Tan  LI Fuxing  ZHANG Jiayi  LI Xinyue  GUO Yunjuan  JI Wentao  LI Yuan
Institution: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.
Keywords:South Central Hebei Plain  aerosol scale height  temporal-spatial variation  Peterson Model  Multiple Regression Analysis
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