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北京城区可吸入颗粒物分布与呼吸系统疾病相关分析 被引量:70

Spatial Distribution of Inhalable Particulate and Association with Respiratory Disease in Beijing City
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摘要 可吸入颗粒物(PM10)已成为北京市首要空气污染物,严重影响城市环境质量及居民健康.本研究采集了北京市2008~2009年非采暖期与采暖期两个不同时期不同粒径(0.3、0.5、3.0和5.0μm)的大气颗粒物浓度,利用空间分析方法研究其分布规律;同时收集同期患呼吸系统疾病的病人数据,对其进行统计分析;再在回归分析的基础上,运用灰色关联模型探讨可吸入颗粒物与呼吸系统疾病的相关性.结果表明,细颗粒的空间分布情况相异,而粗颗粒物分布规律大致相同.呼吸系统疾病与可吸入颗粒物浓度有一定的关联,采暖期是呼吸系统疾病的高发期,可吸入颗粒物在采暖期对呼吸系统疾病的发病率影响相对较高.无论在采暖期还是非采暖期,细颗粒物的浓度均高于粗颗粒物,且细颗粒物对呼吸系统疾病的影响较大. Inhalable particulate has become the premier pollutant of Beijing,which has enormous influence on the environmental quality of the city and health of the residents.Inhalable particle pollutants(particulate matter of 0.3,0.5,3.0 and 5.0 μm) during the heating period and the non-heating period in 2008 and 2009 were collected,and spatial analysis was used to study the spatial distribution of each pollutant.Meanwhile,the hospital data about respiratory disease during the same time was gathered and counted.Then the relativity between inhalable particulate pollutants and respiratory disease was studied by grey correlation analysis on the base of regression analysis.The results showed that spatial distribution of fine particle was diverse but the pattern of coarse particle was similar.There was certain association between respiratory disease and inhalable particle pollutants.Heating period was the highest incidence period of respiratory disease.The prevalence of respiratory disease was higher in heating period than non-heating period.The concentration of fine particle was higher than that of coarse particle both in heating and non-heating periods,and fine particle had more effects on the respiratory system disease than coarse particle.
出处 《环境科学》 EI CAS CSCD 北大核心 2013年第1期237-243,共7页 Environmental Science
基金 北京市自然科学基金重点项目(KZ200910028006) 国际科技合作项目(2010DFA92400) 国家青年科学基金项目(41101404) 北京市教委科技计划面上项目(KM201110028013) 国家基础测绘项目(2011A2001)
关键词 可吸入颗粒物 呼吸系统疾病 空间分析 采暖期与非采暖期 KRIGING 灰色关联 inhalable particulate respiratory disease spatial analysis heating period and non-heating period Kriging grey correlation analysis
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