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生态学杂志 ›› 2021, Vol. 40 ›› Issue (3): 813-824.doi: 10.13292/j.1000-4890.202103.004

• 研究报告 • 上一篇    下一篇

2015—2019年中东部地区PM2.5时空演变及其驱动力

姚荣鹏,张勃*,王立兵,张耀文   

  1. (西北师范大学地理与环境科学学院, 兰州 730070)
  • 出版日期:2021-03-10 发布日期:2021-03-17

Spatiotemporal variations of PM2.5 and driving factors over central and eastern China between 2015 and 2019.

YAO Rong-peng, ZHANG Bo*, WANG Li-bing, ZHANG Yao-wen   

  1. (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China).
  • Online:2021-03-10 Published:2021-03-17

摘要: 我国中东部地区雾霾事件频发。作为雾霾的主因,科学识别PM2.5时空演变特征与驱动力对于区域联防联控意义重大。基于国控环境空气质量监测站2014年12月—2019年11月PM2.5数据,结合地统计、REOF、地理探测器等方法分析了我国中东部地区PM2.5污染的时空特征与演变规律,确定了3个同比变化区,并进一步探究了各区域PM2.5分异的驱动因素。结果表明,中东部整体PM2.5年均浓度呈稳定下降趋势,年均下降3.2 μg·m-3,高年均PM2.5浓度区域在空间上呈快速收缩趋势,但存在部分区域PM2.5污染天数增加的不显著趋势;PM2.5浓度以京津冀地区为中心向外辐射降低,总体上呈“北高南低”的特征;中东部地区有显著的强空间集聚性,四季全局Moran I均超过0.70以上(P<0.01),热点区域主要分布在华北平原及其周围,冷点区域主要分布在华南地区;基于REOF分析得到3个同比变化区,其边界与地形地貌重叠较好,时间系数呈“脉冲型”的下降趋势,表明PM2.5污染有显著的改善趋势;气象因素与人类活动是引起各区域PM2.5分异的重要驱动因素,并在各区域具有不同的关键驱动因素。

关键词: PM2.5, 时空特征, 旋转经验正交函数(REOF), 地理探测器

Abstract: Smog events are widespread in central and eastern China. Scientifically identifying the spatiotemporal variations and the drivers of PM2.5, the primary cause of smog, is of great significance for regional prevention and control. Using PM2.5 data from December 2014 to November 2019 of the national air quality monitoring stations, the spatiotemporal characteristics and variations of PM2.5 pollution were analyzed by using the methods of geostatistics, REOF and Geodetector. The region classifications were identified, and the driving factors for differentiation of PM2.5 were identified in each region. The results showed a steady downward trend in mean annual PM2.5 concentration in central and eastern China, with a mean annual decrease of 3.2 μg·m-3. The area with high annual PM2.5 concentration showed a rapid spatial contraction. There was an insignificant increasing tendency of PM2.5 pollution days in some areas. The concentration of PM2.5 decreased outwardly in the center of BeijingTianjinHebei, with a characteristic of “higher concentration in the north than in the south”. The strong spatial agglomeration of PM2.5 concentration was distributed in central and eastern China. The values of global Moran’s I in all four seasons exceeded 0.70 (P<0.01). Hot spots were mostly distributed in and around the North China Plain, while cold spots were distributed in south China. Based on the result of REOF, three regions were classified. Their boundaries roughly overlapped with the topography and geomorphology. The time coefficients showed a “pulse” downward trend, indicating a significant improvement trend of PM2.5 pollution. Meteorological factors and human activities are essential drivers for the differentiation of PM2.5 in different regions, with the key drivers being region-specific.

Key words: PM2.5, spatiotemporal characteristics, rotated empirical orthogonal function (REOF), Geodetector.