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北京大气污染区域分布及变化趋势研究
引用本文:王英,金军,李令军,赵越,李云婷.北京大气污染区域分布及变化趋势研究[J].中央民族大学学报(自然科学版),2008,17(1):59-65.
作者姓名:王英  金军  李令军  赵越  李云婷
作者单位:1. 中央民族大学生命与环境科学学院,北京,100081
2. 北京市环境保护监测中心,北京,100044
摘    要:本文利用2000-2005年北京市8个国控点PM10、SO2、CO、NO2和NOX等污染物浓度数据,分析了北京各区域大气污染分布与季节变化特征,以及近几年大气污染变化趋势.方法以主成分分析为主,辅以时间序列分析.分析结果显示:北京大气污染存在明显的时空差异,第一、二主分量可以很好地表征城市大气污染属性,所有污染物对第一主分量贡献都为正值,能够清楚区分大气污染程度,以及城市与区域背景的异同,第二主分量可以区分城市污染的源排放特征.基于此标准,全市范围内大气污染划分为燃煤型、机动车排放型、过渡型以及环境背景等四种污染类型.

关 键 词:北京  大气污染  主成分分析  时间序列分析
文章编号:1005-8036(2008)01-0059-07
修稿时间:2007年5月23日

Study on Distribution and Changes Regularity of the Air Pollution in Beijing
WANG Ying,JIN Jun,LI Ling-jun,ZHAO Yue,LI Yun-ting.Study on Distribution and Changes Regularity of the Air Pollution in Beijing[J].Journal of The Central University for Nationalities(Natural Sciences Edition),2008,17(1):59-65.
Authors:WANG Ying  JIN Jun  LI Ling-jun  ZHAO Yue  LI Yun-ting
Institution:WANG Ying, JIN Jun, LI Ling-jun, ZHAO Yue, LI Yun-ting ( 1. College of Life and Environmental Sciences, Central University for Nationalities, Beijing 100081, China ; 2. Beijlng Municipal Environmental Monitoring Center, Beijing 100044, China)
Abstract:Temporal and spatial characteristics of atmospheric pollution from 2000 to 2005 in Beijing is revealed and analyzed through applying principal component analysis and time series analysis methods with data of PM10, SO2, CO, NO2 and NOx in this paper. The results show that air pollution in Beijing includes four types: coal burning pattern, traffic exhaust pattern, transfer pattern, and background pattern. Seasonal variation of ambient air quality is obvious, with the worst in autumn but not in dust storm season (spring), for the concentration of PM10 is very high in dust storm season, but strong wind blows gas pollutants away. With the development of the city construction, traffic exhaust pollution appears more obvious and the difference of pollution pattern between different districts of Beijing becomes more and more little.
Keywords:Beijing  air pollution  principal components analysis  time series analysis
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