摘要
京津冀地区是典型的PM_(2.5)高污染区,研究该地区PM_(2.5)污染现况及其影响因素,对科学有效地治理大气污染意义重大。利用2016年京津冀地区空气质量监测站点的PM_(2.5)数据,结合风速、日照时长、相对湿度等气象资料,综合运用空间插值、聚类分析和相关分析等方法,探讨了PM_(2.5)的时空分布特征及其与气象因素的关系。结果表明,(1)2016年京津冀地区PM_(2.5)年均质量浓度为71.8μg?m^(-3),较2015年下降7.8%,PM_(2.5)达标天数比例为67.7%。(2)京津冀地区PM_(2.5)质量浓度呈北低南高的空间格局,南北差异显著,北部属于PM_(2.5)长期优良区,中部和南部PM_(2.5)污染较重,呈集中连片分布态势。(3)京津冀地区PM_(2.5)污染具有明显的时间变化规律,从季节上看,夏季PM_(2.5)污染相对较轻,春秋次之,冬季污染最重;从月份上看,PM_(2.5)质量浓度呈现出"U"形起伏的变化规律,1月、3月和10—12月PM_(2.5)日均值超标率高于40%,2月及4—9月超标率均低于30%;从日变化上看,春夏季PM_(2.5)日变化呈单峰单谷型分布,秋冬季呈双峰双谷型分布,最大值出现在10:00左右,而最小值出现在16:00左右。(4)京津冀地区PM_(2.5)与气压、相对湿度呈正相关,与气温、日照时长、风速呈负相关,其中风速、相对湿度和日照时长与PM_(2.5)具有较强的相关性,各季节中,冬季的气象因素对PM_(2.5)质量浓度的影响比其他季节更为显著。
Beijing-Tianjin-Hebei （BTH） area is a typical PM2.5 high-polluted area. The research of this region’s pollution status and influencing factors of PM2.5 is significant for air pollution controlling. Based on the PM2.5 data and meteorological data in BTH of 2016, this paper explored the spatiotemporal characteristics of PM2.5 and its relationship with meteorological factors using spatial interpolation combined the methods of cluster analysis and correlation analysis. The results showed that： （1） The average concentration of PM2.5 in BTH was 71.8 μg？m-3 in 2016, which decreased 7.8% comparing with 2015, and about 67.7% days meet Grade Ⅱ standard of ambient air quality standards （GB 3095-2012）. （2） The PM2.5 in the north was obviously worse than that of the south, and it had concentrated contiguous distribution trend in BTH with the northern part was in good condition all the year around while the central and southern part were heavily polluted areas. （3） It was very obvious that PM2.5 changes with time. The seasonal comparison indicated that PM2.5 pollution was lowest in summer and heavy in winter. Monthly data showed a U-shaped variation in 2016, about 26.6% days failed to meet Grade Ⅱ air quality standards. In January, March and October to December, daily average of PM2.5 exceeded the standard rate was more than 40%, while it was less than 30% in February and April to September. Diurnal data showed a unimodal variation （spring and summer ） and an bimodal variation （autumn and winter） in BTH,the highest value appeared around 10：00, and the lowest value appeared around 16：00. （4） The concentration of PM2.5 in BTH was positively correlated with air pressure and relative humidity, negatively correlated with air temperature, sunshine duration and wind speed. The wind speed, relative humidity and sunshine duration were significant factors for PM2.5, the influence of meteorological factors on PM2.5 in winter was more significant than that in other seasons.
出处
《生态环境学报》
CSCD
北大核心
2017年第10期1747-1754,共8页
Ecology and Environmental Sciences
基金
国家青年科学基金项目(41201488)
国家基础测绘基金项目(2011A2011)
关键词
PM2.5
京津冀
时空分布
气象因素
相关性
PM2.5
Beijing-Tianjin-Hebei （BTH）
Spatio-temporal Distribution
meteorological factors
Correlation
