自然科学版
陕西师范大学学报(自然科学版)
资源与环境科学
基于LUR和GIS的西安市PM2.5的空间分布模拟及影响因素
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江笑薇1, 任志远1,2*, 孙艺杰1
(1 陕西师范大学 旅游与环境学院, 西北国土资源研究中心;2 西北历史环境与经济社会发展研究院, 陕西 西安 710119)
任志远,男,教授,博士生导师。E-mail:renzhy@snnu.edu.cn
摘要:
从地学角度出发,基于土地利用、人口状况、道路交通和地形等自然人文因素构建土地利用回归模型(LUR),模拟西安市主城区2014年和2015年冬季采暖季PM2.5平均浓度的空间分布,并分析其空间分布成因和年际变化原因。结果显示:LUR模型构建中,2014年采暖季选择的变量主要有500 m缓冲区内植被面积、1 000 m缓冲区内植被和居民地面积以及人口密度,2015年采暖季选择的变量主要有1 500 m、2 000 m、2 500 m和3 000 m缓冲区内道路总长度。2014年和2015年采暖季LUR模型的R2分别为0.933和0.832,拟合效果很好。2014年采暖季各城区PM2.5平均浓度均较高,碑林区绝大部分区域空气质量为严重污染,新城区次之,其他区空气质量基本为重度污染。2015年各城区PM2.5平均浓度均有所下降,大部分区域为轻度污染。土地利用、污染源、道路交通、人口密度、国家环保相关政策、风向和DEM是西安市2014年和2015年采暖季PM2.5浓度空间分布规律、成因、污染来源和年际变化的影响因素。
关键词:
土地利用回归模型(LUR); GIS; PM2.5; 空间分布; 西安市
收稿日期:
2016-12-16
中图分类号:
X513;P208.2
文献标识码:
A
文章编号:
1672-4291(2017)03-0080-08doi:10.15983/j.cnki.jsnu.2017.03.431
基金项目:
教育部人文社会科学重点研究基地项目(14JJD84004);国家自然科学基金(41371523)
Doi:
Spatial distribution simulation and influencing factors of PM2.5 in Xi′an city based on LUR and GIS
JIANG Xiaowei1 , REN Zhiyuan1,2*, SUN Yijie1
(1 School of Tourism and Environment Sciences, Center for Land Resources Research in Northwest China;2 Northwest Institute of Historical Environment and Socio-Economic Development, Shaanxi Normal University, Xi′an 710119, Shaanxi, China)
Abstract:
From the perspective of Geonomy, based on land use, population, traffic, terrain factors, the average concentration of PM2.5 in 2014 and 2015 heating season in the main urban area of Xi′an city was simulated.Then the causes of the spatial distribution and the reason of annual variation of PM2.5 average concentration were analyzed.The results showed the main variables selected in LUR model in 2014 are 500 m buffer area of vegetation, 1 000 m buffer area of vegetation, population and population density. The main variables selected in LUR model in 2015 are the total length of the road in 1 500 m, 2 000 m, 2 500 m and 3 000 m buffer.The regression coefficients of R2 in LUR model were 0.933 and 0.832, respectively in 2014 and 2015, and the fitting effect is very good. The average concentration of PM2.5 was higher in 2014 heating season. The air quality in most Beilin district was very serious and Xincheng district was the second. The other area′s air quality is heavily polluted. In 2015, the average concentration of PM2.5 in all urban areas decreased, and most of them were slightly polluted.The land use types, pollution sources, traffic, population density, national policy on environmental protection, wind direction, and DEM are the main influencing factors.
KeyWords:
land use regression model(LUR); GIS; PM2.5; spatial distribution; Xi′an city