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陕西省PM2.5时空分异规律及影响因素
南国卫, 孙虎
1.陕西师范大学地理科学与旅游学院
摘要:
PM2.5是导致中国多省市发生雾霾的罪魁祸首,明确其时空分布规律,厘清其影响因素对雾霾的综合治理意义深远。本文基于陕西省2015年50个监测站点的PM2.5浓度数据,采用空间数据统计方法、克里金插值法以及Morlet小波分析法来研究陕西省PM2.5浓度的时空分异规律,并运用灰色关联模型来探讨PM2.5浓度的影响因素。结果显示,①陕西省PM2.5浓度整体呈“高冬低夏、中春秋”的季节变化规律,“U形”起伏的月变化规律,周期性脉冲波动型的日变化规律以及“W形”起伏的时变化规律;②陕西省PM2.5浓度呈“南北低,中部高”的空间分布特征,且空间集聚性显著。不同季节的高值区均集聚于海拔相对较低的关中盆地内部城市。这与盆地内部空气不易扩散,静稳天气出现频率较高,易出现逆温现象密切相关;③影响陕西省PM2.5浓度最大的子系统是PM2.5污染来源,其次是城市化与土地利用,气象与地形因子影响最小;不同城市各系统的综合关联度差异较大。④各指标因子与PM2.5浓度均为强度关联。降雨量、机动车保有量、二氧化硫排放量、烟粉(尘)排放量、建成区面积、人口密度和人均GDP是影响陕西省PM2.5浓度的主要因子。影响各城市PM2.5浓度的主要指标因子具有一定的空间差异性。
关键词:  PM2.5  时空分异规律  影响因素  陕西省
DOI:
分类号:X513
基金项目:
Spatial and temporal characteristics of PM2.5 in Shaanxi province and its driving factors.
NAN Guowei, SUN Hu
Abstract:
As we know, PM2.5 is a main cause of serious haze in many provinces and cities of China. Therefore, to comprehensively treat haze, we must clarify the spatial and temporal distribution and influence factors of PM2.5. Based on PM 2.5 concentration data at all monitoring sites in Shaanxi province in 2015, in this paper, the spatial data statistics method, Kriging interpolation method, and Morlet wavelet analysis method was adopted to study the spatial-temporal differentiation rule of PM2.5 in Shaanxi province and the grey correlation model was used to explore the influence factors of PM2.5. The results showed that (1) The PM2.5 concentration is high in winter, low in summer, and medium in spring and autumn, and varies monthly in a U-shaped curve, daily in a periodical pulse fluctuation type, and hourly in a W-shaped curve. (2)The PM2.5 concentration is low in the north and south, and high in the middle, and has the obvious spatial aggregation characteristic. High PM2.5 concentration values in different seasons all come from basin cities with relatively low altitudes. This is caused by difficult air diffusion, and high occurrence frequency of static weather and temperature inversion in the basin areas.(3)PM2.5 pollution sources have the greatest influence on the PM2.5 concentration in Shaanxi province, the second is urbanization and land usage, and the minimum is climate and terrain. The comprehensive correlation degrees in each system in different cities have great differences.(4)The main influence factors of the PM2.5 concentration in Shaanxi province are rainfall, vehicle volume, sulfur dioxide emissions, smoke (dust) emissions, urban built-in area, population density, and per capita GDP. They are strongly correlated with the PM2.5 concentration. The main influence factors in different cities have spatial differences.
Key words:  PM2.5  spatial and temporal characteristics of PM2.5  driving factors  Shaanxi province