干旱区生态环境知识资源中心(Arid): 2015年中国PM_(2.5)浓度遥感估算与时空分布特征

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	2015年中国PM_(2.5)浓度遥感估算与时空分布特征
其他题名	Estimation and Spatial-temporal Distribution Characteristics of PM_(2.5) Concentration by Remote Sensing in China in 2015
	魏石梅; 潘竟虎; 妥文亮
来源期刊	遥感技术与应用
ISSN	1004-0323
出版年	2020
卷号	35 期号:4
中文摘要	以PM_(2.5)污染物为主的大气污染对社会的可持续发展及人类健康带来了严峻的挑战,厘清我国PM_(2.5)污染物的空间分布特征及演变规律,对于 PM_(2.5)污染物的区域联防联控具有重要的意义。基于Aqua/MODIS气溶胶产品、气象基础数据以及PM_(2.5)污染物实测站点监测数据, 构建地理加权回归模型,对2015年中国PM_(2.5)污染物浓度进行了模拟估算,对PM_(2.5)污染物浓度的空间分异格局及季节演化特征进行分析。结果表明:①2015年全国PM_(2.5)浓度整体表现出明显的空间地带性分异特征。北方PM_(2.5)污染物浓度明显高于南方,中部明显高于东部与西部;②4个季度PM_(2.5)浓度表现出明显的季节适应性演化特征。第四季度PM_(2.5)污染最重,第三季度和第一季度次之,第二季度最低,最大值出现在第四季度(165 mug/m~3),最小值出现在第二季度(4.3 mug/m~3)。③通过多因子构建的地理加权回归模型估算的PM_(2.5)浓度具有较高的模拟精度,第一至第四季度的相对误差分别为10.2%、7. 0%、9.3%和8.6%。
英文摘要	Air pollution characterized by PM_(2.5) pollutants poses severe challenges to the sustainable development of society and human health. Therefore,it is of great significance to clarify the spatial-temporal distribution and evolution of PM_(2.5) pollutants in China for regional joint prevention and control of PM_(2.5) pollutants. Based on the MODIS satellite aerosol products,meteorological basic data and PM_(2.5) pollutant monitoring site monitoring data, a geographically weighted regression model was established to simulate and estimate PM_(2.5) pollutant concentration in China in 2015 on the basis of aerosol and meteorological data pre-processing. In addition,the spatial distribution pattern,the seasonal evolution characteristics of PM_(2.5) pollutant concentration were analyzed. The results showed that:(1)the PM_(2.5) concentration values in China in 2015 as a whole showed obvious spatial zonal differentiation characteristics. The concentration of pollutants in the north is significantly higher than that in the south,and the areas with high PM_(2.5) concentrations are mainly concentrated in the Beijing-Tianjin-Hebei region, the Jianghuai plain,the Sichuan basin,and the Takaramalkan desert. The area has a wide spatial distribution and significant continuity;(2)The PM_(2.5) concentration in the fourth quarter showed obvious seasonal adaptive evolution characteristics. The PM_(2.5) concentration changed significantly in the season. PM_(2.5) pollution was the heaviest in the fourth quarter,followed by the first quarter of the third quarter and the lowest in the second quarter. The maximum occurred in the fourth quarter(165 mug/m~3). The minimum appeared in the second quarter(4.3 mug/m~3). Seasonal changes in PM_(2.5) concentrations were influenced by meteorological factors and human social activities;and(3)The accuracy of the inversion of PM_(2.5) concentration by a multi-factorial,geographically weighted regression model was higher,with relative errors in the four quarters being 10.2%,7.0%,9.3%, and 8.6%,respectively.
中文关键词	遥感估算 ; 时空分布 ; 中国
英文关键词	PM_(2.5) MODIS PM_(2.5) MODIS Remote sensing estimation Spatio-temporal distribution China
类型	Article
语种	中文
收录类别	CSCD
WOS类目	Environmental Sciences & Ecology
CSCD记录号	CSCD:6816409
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/353956
作者单位	魏石梅, 西北师范大学地理与环境科学学院, 兰州, 甘肃 730070, 中国. 潘竟虎, 西北师范大学地理与环境科学学院, 兰州, 甘肃 730070, 中国. 妥文亮, 西北师范大学地理与环境科学学院, 兰州, 甘肃 730070, 中国.
推荐引用方式 GB/T 7714	魏石梅,潘竟虎,妥文亮. 2015年中国PM_(2.5)浓度遥感估算与时空分布特征[J],2020,35(4).
APA	魏石梅,潘竟虎,&妥文亮.(2020).2015年中国PM_(2.5)浓度遥感估算与时空分布特征.遥感技术与应用,35(4).
MLA	魏石梅,et al."2015年中国PM_(2.5)浓度遥感估算与时空分布特征".遥感技术与应用 35.4(2020).