乌鲁木齐市大气污染物浓度的变化特征

Variation characteristics of air pollutant concentrations in Urumqi

利用乌鲁木齐2014年3月1日至2015年2月28日PM2.5、PM10、SO2、CO、NO2、O3浓度的日平均数据,结合相应气象要素资料,分析了大气污染物浓度的逐日变化、季节变化特征.建立了基于气体污染物的PM2.5浓度预测模型,探讨了污染物浓度与气象要素的相关性.结果表明:(1)整个1年期间PM2.5、PM10、SO2、NO2、O3年平均浓度分别为67.9、159.3、24.9、56.1、31.5μg·m-3,CO为1.4 mg·m-3.(2)各污染物浓度频率分布不一.期间SO2的污染并未超标,NO2超标率为15.3%,说明"煤改气"能源结构的调整对SO2浓度的降低起到了积极作用,但是由于机动车保有量的增加,使得机动车排放的NO2浓度超过了燃煤.(3)PM2.5与PM10、SO2、CO、NO2、O3具有很强的相关性,尤其与SO2、CO、NO2更为明显,说明机动车尾气和化石燃料的燃烧是乌鲁木齐市PM2.5的重要来源,此外,建立了基于气体污染物的PM2.5浓度预测模型为:CPM2.5=0.21376CPM10+0.42422CSO2+41.66384CCO-0.24325CNO2+0.12466CO3-24.15316.(4)PM2.5、SO2和CO均与气温和水汽压存在较大的负线性相关关系,与O3呈显著的正相关关系.相对湿度与O3浓度的相关性最高为-0.62,与CO有一定的正相关关系,与其他污染物的相关性不大.风速对大气污染的影响较小.日照时数对污染物也有一定影响.

In this paper,the daily and seasonal variations of air pollutant concentrations were analyzed based on the average daily data of air pollutant concentrations in Urumqi during the period of March 1,2014 to February 28,2014. Also,based on the corresponding meteorological data,PM2.5concentration prediction models based on gaseous pollutants were built. Moreover,the main factors affecting the variations of air pollutant concentrations were discussed. The results obtained were as follow：（ 1） Annual average concentrations of PM2.5,PM10,SO2,NO2 and O3were 67. 9,159.3,24. 9,56. 1 and 31. 5 μg·m^-3,respectively,with the concentration of CO found to be1.4 mg·m^-3.（ 2） Frequency distribution of each pollutant concentration varied during theobservation. SO2 concentrations all fell below standard rate,indicating the significant role that the adjustment of energy structure ＂ coal to gas ＂ had played in reducing SO2 concentrations. NO2 exceeded standard with 15. 3% rate which can be attributed to the increase in vehicle ownership.Thus,automobile emissions of NO2 exceeded the coal-fired plants.（ 3） Strong correlation between PM2.5and PM10,SO2,CO,NO2,O3 was observed,with more significant correlation between PM2.5and SO2,CO,NO2. This shows that the vehicle exhaust and the burning of fossil fuels are important sources of PM2.5in Urumqi City. In addition,a PM2.5concentration prediction model based on gaseous pollutants was built,that is CPM 2.5= 0.21376CPM10＋0.42422CSO2＋41.66384CCO-0.24325CNO2＋0.12466CO3-24.15316.（ 4） PM2.5,SO2 and CO correlated negatively to temperature and water vapor pressure,but positive correlation occurred in the case of O3. The correlation coefficient of the relative humidity and the concentration of O3was-0.62. It was discovered that the wind speed had little effect on the air pollution whilst the solar radiation influenced the air pollution.