干旱区生态环境知识资源中心(Arid): 基于多源遥感数据的中国PM

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	基于多源遥感数据的中国PM_(2.5)变化趋势与影响因素分析
其他题名	Analysis on the Trend and Influencing Factors of PM_(2.5) in China Based on Multi-source Remote Sensing Data
	卢德彬 1; 毛婉柳 2; 杨东阳 3; 赵佳楠 4
来源期刊	长江流域资源与环境
ISSN	1004-8227
出版年	2019
卷号	28 期号:3 页码:651-660
中文摘要	基于长时间序列的遥感反演PM_(2.5)数据,采用Theil-Sen median趋势分析、Mann-Kendall、R/S和相关系数分析法,分析了1998~ 2014年我国PM_(2.5)时空格局、空间变化特征以及污染来源。结果表明:1998~ 2014年期间,最高只有24.67%的国土面积上,PM_(2.5)浓度达到世界卫生组织(WHO)的年平均准则值10mug/m~3的要求;PM_(2.5)浓度小于10mug/m~3地区主要是青藏高原、台湾、北疆,内蒙古北部和黑龙江西北部,年均PM_(2.5)浓度大于95mug/m~3的地区主要是南疆和华北平原。1998~ 2014年期间,全国61.84%的国土面积PM_(2.5)浓度呈上升趋势,平均上升了3.91mug/m~3,上升最大值为39.1mug/m~3。其中,呈显著上升的地区主要分布在中西部地区和华北平原,且未来部分地区仍呈增长的趋势。PM_(2.5)浓度上升的驱动因素包括自然因素与人类活动排放,其中,南疆的PM_(2.5)主要来自塔克拉玛干沙漠的沙尘气溶胶,而其他地区PM_(2.5)主要来自人类活动排放。
英文摘要	Based on the remote sensing retrieval of PM_(2.5) data in the long-time series,the temporal-spatial pattern of PM_(2.5) as well as its variation and sources of pollution in China from 1998 to 2014 were revealed by using the Theil-Sen median trend analysis,Mann-Kendall test and correlation analysis methods.The results showed that PM_(2.5) concentration reached the annual average criterion value of 10 mug/m~3 specified by the World Health Organization (WHO) in the land area of only 24.67% during the period from 1998 to 2014.PM_(2.5) concentrations were less than 10 mug/m~3 mainly in the Qinghai-Tibet Plateau,Taiwan,northern Xinjiang,north of Inner Mongolia and northwest of Heilongjiang,while the average annual PM_(2.5) concentrations were greater than 95 mug/m~3 mainly in southern Xinjiang and North China Plain.During the period from 1998 to 2014,the concentration of PM_(2.5) increased by an average of 3.91 mug/m~3 and the maximum value was 39.1 mug/m~3 in 61.84% of the national land area.Among them,the central and western regions and the North China Plain exhibited a significant rising trend and some regions still show an increasing trend in the future.The driving factors of increase in PM_(2.5) concentration included natural factors and emissions from human activities,wherein it mainly came from the sand dust aerosol in the Taklimakan Desert in the southern Xinjiang,while those in the other areas mainly came from emissions in the human activities.
中文关键词	空气污染 ; 变化趋势 ; 影响因素
英文关键词	PM_(2.5) PM_(2.5) air pollution long-term trend influence factors
语种	中文
国家	中国
收录类别	CSCD
WOS类目	ENVIRONMENTAL SCIENCES
WOS研究方向	Environmental Sciences & Ecology
CSCD记录号	CSCD:6463542
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/239693
作者单位	1.铜仁学院旅游与地理系;;华东师范大学地理科学学院, ;;, 铜仁;;, 贵州;;上海 554300;;200241, 中国; 2.浙江省地理信息中心, 杭州, 浙江 310012, 中国; 3.河南省大气污染综合防治与生态安全重点实验室, 河南省大气污染综合防治与生态安全重点实验室, 开封, 河南 475004, 中国; 4.华东师范大学地理科学学院, 上海 200241, 中国
推荐引用方式 GB/T 7714	卢德彬,毛婉柳,杨东阳,等. 基于多源遥感数据的中国PM_(2.5)变化趋势与影响因素分析[J],2019,28(3):651-660.
APA	卢德彬,毛婉柳,杨东阳,&赵佳楠.(2019).基于多源遥感数据的中国PM_(2.5)变化趋势与影响因素分析.长江流域资源与环境,28(3),651-660.
MLA	卢德彬,et al."基于多源遥感数据的中国PM_(2.5)变化趋势与影响因素分析".长江流域资源与环境 28.3(2019):651-660.