研究报告
于瑞新,刘旻霞,李亮,宋佳颖,孙瑞弟,张国娟,徐璐,穆若兰.长三角地区近15年大气臭氧柱浓度时空变化及影响因素[J].环境科学学报,2021,41(3):770-784
长三角地区近15年大气臭氧柱浓度时空变化及影响因素
- Spatial and temporal variation of atmospheric ozone column concentration and influencing factors in the Yangtze River Delta region in recent 15 years
- 基金项目:国家自然科学基金(No.31760135)
- 于瑞新
- 西北师范大学地理与环境科学学院, 兰州 730070
- 刘旻霞
- 西北师范大学地理与环境科学学院, 兰州 730070
- 李亮
- 西北师范大学地理与环境科学学院, 兰州 730070
- 宋佳颖
- 西北师范大学地理与环境科学学院, 兰州 730070
- 孙瑞弟
- 西北师范大学地理与环境科学学院, 兰州 730070
- 张国娟
- 西北师范大学地理与环境科学学院, 兰州 730070
- 徐璐
- 西北师范大学地理与环境科学学院, 兰州 730070
- 穆若兰
- 西北师范大学地理与环境科学学院, 兰州 730070
- 摘要: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(NOx)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.
- Abstract: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; NOx 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.