长江中游城市群PM2.5时空特征及影响因素研究

近年来，伴随着工业化和城市化进程的加快，长江中游城市群灰霾天气持续增多，空气污染问题日益突出。基于2015年1月至2016年2月长江中游城市群189个空气质量监测站点的PM2.5逐时监测数据，采用普通克里金插值、探索性空间数据分析法和相关系数法，从年、季、月尺度上分析了PM2.5的空间分布格局及其影响因素。结果表明：（1）在年尺度上，长江中游城市群PM2.5浓度空间分布总体呈现出明显的北部高南部低，局部地区略有突出的特征，该区PM2.5浓度年均值为55.28 μg/m3，其中湖北省PM2.5的年均值为三省市最高，为68.17 μg/m3；其次为湖南省，年均值为53.66 μg/m3；江西省PM2.5的年均值较小，为44.01 μg/m3。（2）在季节尺度上，长江中游城市群PM2.5浓度表现出冬春季高，夏秋季低的现势性，这与区域内夏季高温多雨、冬季低温少雨的气候条件密切相关。（3）长江中游城市群PM2.5月浓度变化大致呈U形分布，1月份PM2.5浓度最高， 1~6月份，PM2.5浓度呈逐步下降趋势， 6~8月份，区域PM2.5浓度处于“U”字的谷底。（4）NO2、CO是影响PM2.5浓度的两项主控大气污染物，而降水量和相对湿度则是影响PM2.5浓度的两个重要气象因素。 关键词： PM2.5浓度；时空特征；气象因素；长江中游城市群

Spatio-Temporal Characteristics of PM2.5 and Its Influencing Factors of the Urban Agglomeration in the Middle Reaches of the Yangtze River

China has been witnessing the rapid development of industrialization and urbanization in recently years. As a consequence, it suffers from air pollution, notably haze. Based on the data for PM2.5 from 189 automatic air quality monitoring stations of the urban agglomeration in the Middle Reaches of the Yangtze River from January 2015 to February 2016, this paper applied ordinary Kriging interpolation method, exploratory spatial data analysis and relevant correlation coefficient method to investigate the spatio-temporal characteristics and influencing factors of PM2.5of municipalities of the Middle Reaches of the Yangtze River from year, season and month time scales. The findings are the following. (1) On the year time-scale, the distribution of PM2.5 concentration within the Middle Reaches of the Yangtze River exhibits high values in the north and low values in the south, local projecting. The average value of PM2.5concentration was 55.28 μg/m3 in the whole study area.Specifically, Hubei province has the highest average value of PM2.5 concentration with 68.17μg /m3, followed by Hunan province with an average value of 53.66 μg/m3. Jiangxi province has the lowest average value of PM2.5 concentration with 44.01 μg/ m3. (2) On the season time-scale, PM2.5 concentration of the Middle Reaches of the Yangtze River presented significant seasonal variations, specifically, high values in both spring and winter, and low values in both summer and autumn. The seasonal variations are closely correlated with the regional climate conditions, specifically, high temperature and precipitation in summer, low temperature and precipitation in winter. (3) On month time-scale, PM2.5 concentration showed a U-shaped curve. Specifically, it reached the summit in January, continued to decline and then went down to the bottom in June, finally increased gradually from July. (4) NO2、CO were two main air pollutants factors affecting PM2.5 concentration. Moreover, precipitation and relative humidity were two main important meteorological factors affecting PM2.5 concentration.