长三角地区近15年大气臭氧柱浓度时空变化及影响因素

基于OMI遥感数据，分析了2005-2019年长三角地区O₃柱浓度的时空分布特征及影响因素，同时采用后向轨迹（HYSPLIT）模型进行对流层O₃来源的解析.结果表明：1从时间分布来看，15年间O₃柱浓度年际变化呈先上升后下降的变化趋势，其中，2005-2010年呈上升趋势，2010-2019年呈下降趋势，2010年和2016年分别达到最大值和最小值，分别为327.79 DU和276.43 DU；季节方面，每年季均浓度值均为春季最大，冬季最小.2在空间分布上，O₃柱浓度高值区在长三角中部及以北地区，且由北向南逐渐降低；四季分布有明显变化，15年的平均季均浓度为春季>夏季>秋季>冬季，高值主要出现在春季，低值出现在冬季.3气象因子上，O₃柱浓度与气温、降水、风速、日照时间呈正相关（p<0.05），与气压呈负相关（p<0.05）.人为因素上，O₃柱浓度与人口、第二产业及煤炭消费总量呈正相关.4通过不同高度模拟受点气流输送轨迹发现，上海市不同高度的气流轨迹与输送路径相差不大，均能反映O₃的来源与扩散方向.来自华北、黄海地区与西南方向及东海上空的气流汇聚是造成春季O₃柱浓度升高的主要原因，冬季O₃柱浓度低主要是因为来自华北地区高压气流对O₃的扩散作用.5O₃柱浓度与其他物质的空间对比分析显示，NO₂柱浓度、AOD指数、HCHO柱浓度均是影响O₃柱浓度空间分布的重要原因；该地区O₃前体物氮氧化物（NO_x）是引起O₃柱浓度增长的主要原因，两者之间呈显著正相关（p<0.01）；机动车尾气排放对O₃柱浓度水平的贡献不可忽视.长三角地区挥发性有机物（VOCs）是造成O₃柱浓度升高的又一重要原因，其中，人为源是主控原因，占总贡献量的96.9%，植物源占3.1%；人为源中，工业源和生活源贡献较大.

Spatial and temporal variation of atmospheric ozone column concentration and influencing factors in the Yangtze River Delta region in recent 15 years

Based on OMI remote sensing data, the spatial and temporal distribution characteristics and influencing factors of O₃ concentration were analyzed in the Yangtze River Delta from 2005 to 2019, and sources of tropospheric O₃ was analyzed by using HYSPLIT model. The results showed that:1 In terms of time,the annual variation of O₃ column concentration showed a trend of first increasing and then decreasing in the past 15 years, with an upward trend from 2005 to 2010 and a downward trend from 2010 to 2019. The maximum and minimum values were 327.79 DU and 276.43 DU in 2010 and 2016 respectively. In terms of seasons, the seasonal average concentration values were the largest in spring and the smallest in winter. 2 In terms of space, the high value area of O₃ column concentration was in the middle and north of Yangtze River Delta, and gradually decreased from north to South; the distribution of four seasons had obvious changes, the average seasonal concentration of 15 years was spring > summer > autumn > winter, the high value appeared in spring, and the low value appeared in winter. 3 In terms of meteorology, O₃ column concentration was significantly positively correlated with temperature, precipitation, wind speed and illumination time (p<0.05), which was significantly positively correlated with illumination time(p<0.01), and negatively correlated with air pressure (p<0.05). In terms of human factors, O₃ concentration was positively correlated with population, secondary industries and total coal consumption. 4 Through the simulation of air flow trajectory, it is found that there was little difference between the air flow trajectory and the transportation path at different heights in Shanghai, which could reflect the source and diffusion direction of O₃. The main reason for the increase of O₃ concentration in spring was the convergence of air flow from North China, Yellow Sea and southwest direction and over the East China Sea. The low concentration of O₃ in winter was mainly due to the diffusion of high pressure air from North China. 5 Spatial Comparison of O₃ concentration with other substances, NO₂ concentration, AOD index and HCHO concentration were the important factors affecting the spatial distribution of O₃ concentration; NO_x was the main reason for the increase of O₃ column concentration in this area, and there was a significant positive correlation between them (p<0.01); the contribution of vehicle exhaust to O₃ concentration level could not be ignored. VOCs were another important reason for the increase of O₃ column concentration in the Yangtze River Delta region. Anthropogenic sources were the main control factors, accounting for 96.9% of the total contribution, and plant sources account for 3.1%. Among the anthropogenic sources, industrial sources and domestic sources contribute more.