• 关键词：臭氧(O₃)  时空分异  气象要素  前体物  地理探测器  安徽省

• 基金项目：国家自然科学基金项目（No.41971378）；安徽省高校自然科学研究重点项目（No.KJ2020A0758）

• 王雷
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000

• 赵冰雪
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000;2. 南京大学地理与海洋科学学院, 南京 210023

• 郭雪漫
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000

• 方宇媛
• 3. 池州学院材料与环境工程学院, 池州 247000

• 王诺
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000

• 王娜
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000

• 杨燕
• 1. 池州学院地理与规划学院自然资源遥感应用研究中心, 池州 247000

• 摘要：基于2017—2018年安徽省132个空气质量监测站点的O₃浓度观测数据及各月份的气象与前体物排放数据, 采用空间自相关分析、地理探测器等方法分析安徽O₃浓度的时空分异及其驱动因素. 结果表明:安徽O₃浓度的峰值出现在5月和6月, 超标率分别为31.4%和42.8%. O₃浓度整体呈空间集聚特征, 高值区主要出现在安徽东北部的蚌埠、宿州、淮南和滁州4市, 低值主要分布在皖南山区. 气象要素是安徽省O₃浓度格局形成的主控因素, 其中6月的边界层高度(q=0.644)、近地面太阳辐射(q=0.597)和风速(q=0.571)的影响最大, 且呈正向影响, 风速的增大和边界层高度的增加可能使得输入性污染增加. 降雨量(q=-0.532)和相对湿度(q=-0.559)呈负向影响, 且降雨带的移动是影响安徽夏季O₃分布格局的一项关键因素. 本地前体物排放对安徽O₃浓度的影响受到气象要素的驱动, 在夏季呈正向, 而冬季呈反向, 其中CO的影响相对较大. 6月气象要素与本地前体物排放的双因子交互驱动对O₃浓度的空间分异具有增强作用. 边界层高度和近地面太阳辐射与本地前体物的组合解释力均大于0.7, 在不利的气象条件下, 应进一步加强对本地前体物排放的管控.

• Abstract：Based on the daily ozone concentration data from 132 environmental monitoring sites, monthly meteorological and precursor emission data, we studied the spatio-temporal differentiation of ozone concentration and its driving factors in Anhui Province from 2017 to 2018 via spatial auto-correlation analysis and geographical detector. The results are as follows: The peak values of ozone concentration appeared in May and June of Anhui Province, and the exceed ratios (MDA8>160 μg·m^-3) were 31.4% and 42.8% respectively. Ozone concentration presented a spatially aggregation characteristics (Moran's I was greater than 0). The high value concentrated in Bengbu, Suzhou, Huainan and Chuzhou city in the northeast of Anhui Province, while the low value concentrated in the southern mountainous areas of Anhui Province. Spatial pattern of ozone concentration was mainly affected by meteorological factors, among which boundary layer height (driving value, q = 0.644), solar radiation (q=0.597) and wind speed (q=0.571) in June provided a stronger positive driving force. Areas with higher average wind speeds and higher boundary layer heights may result in more external transport. Precipitation (q=- 0.532) and relative humidity (q=- 0.559) had negative effects, and the movement of rainfall belt was a key factor which affecting the distribution pattern of ozone concentration in summer. The driving force of local precursor emission on ozone concentration in Anhui Province was affected by meteorological factors, which had positive effects in summer, but negative ones in winter, and the driving force of CO was relatively greater among them. The interaction between meteorological factors and local precursors had a strong effect on the spatial differentiation of ozone concentration in June. The combined driving force between boundary layer height, solar radiation and local precursors was greater than 0.7. The control of local precursor emissions should be strengthened under adverse weather conditions.

• Key words：ozone  spatio-temporal differentiation  meteorological factors  precursors  geographical detector  Anhui

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