摘要
为研究城市主干道边的空气污染状况,通过采用自动监测系统,在2007年1月至2月期间,对广州市新港西路两侧以及附近大学校园内的空气质量进行监测,获得了其空气污染物浓度的特征:(1)空气污染水平高,NO2与PM10日均值超标率较高;(2)污染物时空分布不均匀,NO浓度白天通常比夜间高,路边监测点NO小时浓度为校园对照点浓度的3倍左右。同时,分析了污染物浓度与气象条件及主干道交通流量的关系。结果表明:污染物浓度与气象因素之间有较高的多元线性相关性,但与单个因素的相关性不强;路边监测点的NO小时浓度和校园对照点的NO2小时浓度均与车流量有较高的相关系数,而PM10与车流量无显著相关性。综合考虑气象因素与交通流时,多元线性回归方程的复相关系数更高。
In order to investigate the air quality near city arteries, an experiment was conducted to monitor the air quality near Xingangxi Road of Guangzhou and in the university campus nearby with the automatic monitoring systems, during January and Febmary, 2007. Thus, the concentration characteristics of atmospheric pollution there was figured out that, （ 1 ） air pollution there was serious for the high exceeding rates of the daily concentrations of NO~ and PM10 ; （2） temporal - spatial distribution of the pollutants was uneven that NO concentrations in daytime were usually higher than that in nighttime, and the hourly concentrations of NO on roadside were about 3 times as that measured on campus. The relationship of pollutant concentrations and meteorological conditions and traffic volumes of the artery were also analyzed, which indicates that, the multiple linear correlation coefficient of meteorological factors and NO hourly concentrations was relatively high, while the correlation of a single factor the pollution and NO was signifi- cant. Both of the hourly concentrations of NO on roadside and NO2 in the campus had high correlation coefficients with the traffic volumes, while linear correlation of PM10 and traffic volumes was not significant. The multiple correlation coefficient of the multiple linear regression function would be greater when considering both the meteorological factors and traffic volumes.
出处
《环境科学与管理》
CAS
2008年第3期63-66,149,共5页
Environmental Science and Management
关键词
大气污染
空气质量监测
机动车排放
多元回归分析
广州市
atmospheric pollution
air quality monitoring
vehicular emission
multiple regression analysis
Guangzhou
