生态与农村环境学报 ›› 2015, Vol. 31 ›› Issue (4): 460-465.doi: 10.11934/j.issn.1673-4831.2015.04.003

• 区域环境与发展 • 上一篇    下一篇

我国城市冬季PM2.5空间特征及其人为影响因子

林巧莺,陈永山   

  1. 泉州师范学院资源与环境科学学院
  • 收稿日期:2014-12-30 修回日期:2015-06-13 出版日期:2015-07-25 发布日期:2015-07-25
  • 通讯作者: 林巧莺 E-mail:qiaoyinglin@163.com
  • 作者简介:林巧莺(1980-),女,福建福州人,讲师,博士生,主要研究方向为环境科学与GIS应用。E-mail.qylin@iue.ac.cn
  • 基金资助:

    中国科学院城市环境与健康重点实验室(城市环境研究所)开放基金(KLUEH201301)

Spatial Variation of PM2.5 in Cities in Winter and Anthropogenic Influencing Factors in China

LIN Qiao-ying, CHEN Yong-shan   

  1. College of Resources and Environmental Sciences, Quanzhou Normal University
  • Received:2014-12-30 Revised:2015-06-13 Online:2015-07-25 Published:2015-07-25

摘要:

我国114个城市冬季(2013年12月—2014年2月)公布的PM2.5数据为基础,结合其他相关数据,运用空间自相关分析、克里格插值法和逐步回归分析法,研究我国冬季PM2.5浓度空间分布差异及其影响因素。结果显示,研究期间PM2.5在空间分布上具有高值集聚、低值集聚和高值邻域的低值集聚的变化特征,全局自相关系数Moran's I为0.27。PM2.5浓度分布由北到南、从内陆到沿海具有先升高后逐渐降低的变化趋势,高浓度区域主要集中在华北平原、长江中下游平原和陕西关中平原等地区,这些区域的冬季PM2.5平均质量浓度都达到150μg·m-3以上,最高达250μg·m-3。多因子逐步回归分析结果表明,人为活动对我国高浓度PM2.5(〉150μg·m-3)分布影响显著,对低浓度PM2.5(≤75μg·m-3)分布影响不显著。市辖区人口密度和第二产业GDP是显著影响我国高浓度PM2.5分布的主要人为影响因子。市辖区建成区面积、全市年末总人口和市辖区道路面积等是影响我国城市间PM2.5浓度分布差异的主要人为影响因子。

关键词: PM2.5, 空间结构, 人为影响因子, GIS

Abstract:

Based on the PM2. 5 data published by 114 cities of China in winter( from December 2013 to February 2014),differences in spatial distribution of PM2. 5 concentration in winter between the cities and their affecting factors were studied by means of spatial auto-correlation analysis,Kriging interpolation and stepwise regression analysis. Results show that during this period of time,the spatial distribution of PM2.5 concentration was characterized by clustering of high values,clustering of low values and clustering of low values in high-value domains; the overall Moran's I was 0. 27; PM2.5 concentration displayed a rising first and then declining trend from North to South and from the inland to the coast; and high PM2.5 concentration was mainly distributed in North China Plain,the middle-lower reaches of the Yangtze River and Guanzhong Plain of Shaanxi,where the mean concentrations were all beyond 150 μg·m^- 3and reached as high as 250 μg·m- 3. Multiple factors stepwise regression analysis shows that the impact of anthropogenic activities was significant on distribution of high PM2.5 concentrations( 〉150 μg·m- 3),but not on that of low concentrations( ≤75 μg·m- 3). The dense population and GDP of the secondary industry in the cities were the two main factors affecting distribution of high PM2. 5concentrations,while the area of built districts in the city area,the total population at end of the year of the whole city and the area of paved roads in the city area,were the major factors causing differences between cities in distribution of PM2.5 concentration.

Key words: PM2.5, spatial structure, anthropogenic influencing factor, GIS