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西安市春夏气象因素对大气污染的影响
引用本文:范天藤,贾予平,潘小川.西安市春夏气象因素对大气污染的影响[J].环境与健康杂志,2007,24(2):98-100.
作者姓名:范天藤  贾予平  潘小川
作者单位:1. 北京大学公共卫生学院预防医学专业,北京,100083
2. 北京大学公共卫生学院劳动卫生与环境卫生学系,北京,100083
摘    要:目的 探讨气象因素对大气污染的影响.方法 收集2005年4月1日-6月30日西安市气象因素(日最高、最低气温、日平均气压、日平均相对湿度)和大气污染物浓度(SO2、NO2及PM10)资料,绘制资料中各要素的时间趋势图,研究气象因素以及大气污染物随时间变化的趋势;对大气污染物浓度与气象因素进行多重线性回归分析和相关分析.结果 该时间段气温呈上升趋势,日均相对湿度也呈一定上升趋势,日均气压逐渐下降;空气污染物浓度呈一定下降趋势但并不明显.各气象因素和大气污染物之间呈现一定统计学相关(P<0.05),各气象因素对大气污染物浓度影响的回归方程为lnSO2=-3.352 0.019×最高气温-0.026×最低气温,lnNO2=-3.448-0.003×日均湿度 0.012×最高气温-0.015×最低气温,lnPM10=-2.197 0.011×最高气温-0.021×最低气温.结论 气象因素的变化对大气污染状况具有一定的影响.

关 键 词:空气污染  气象因素  回归分析
文章编号:1001-5914(2007)02-0098-03
修稿时间:2006-10-06

Relationship between Air Pollution and Meteorological Factors in Summer in Xian City, China
FAN Tian-teng,JIA Yu-ping,PAN Xiao-chuan.Relationship between Air Pollution and Meteorological Factors in Summer in Xian City, China[J].Journal of Environment and Health,2007,24(2):98-100.
Authors:FAN Tian-teng  JIA Yu-ping  PAN Xiao-chuan
Institution:School of Public Health, Peking University, Beijing, 100083, China
Abstract:Objective To explore the effect of the meteorologic factors on air pollution in the summer in Xian, China. Methods The data of SO2?NO2 and PM10 concentrations in the air and the related meteorologic factors maximum temperature(tmax), minimum temperature(tmin), average air pressure(P) and relative humidity(H)) from April 1st to June 30th in 2005 were collected. The correlation between the air pollutant level and related meteorologic factors was analyzed by the elements time diagram and multiple regression models with SPSS 11.0 software. Results A significant correlations between the meteorological elements and air pollutants was seen, the regression models for air pollutants were as follows, lnSO2=-3.352 0.019 tmax-0.026 tmin, lnNO2=-3.448-0.003H 0.012 tmax-0.015 tmin and lnPM10=-2.197 0.011 tmax-0.021 tmin. Conclusion The meteorologic factors have some effects on the air pollution levels and then impact human health in some degree.
Keywords:Air pollution  Meteorological factor  Regression analysis
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