长江流域资源与环境 >> 2022, Vol. 31 >> Issue (11): 2489-2499.doi: 10.11870/cjlyzyyhj202211014

• 生态环境 • 上一篇    下一篇

长江经济带地表臭氧时空格局与驱动因素分析

龚旭昇1,柯碧钦2,何超3*
  

  1. (1.湖北科技学院核技术与化学生物学院,湖北 咸宁 437100;2. 武汉大学资源与环境科学学院,地理信息系统教育部重点实验室,湖北 武汉 430079;3. 长江大学资源与环境学院,湖北 武汉 430100)
  • 出版日期:2022-11-20 发布日期:2022-12-26

Spatiotemporal Patterns and Drivers of Surface #br# Ozone in the Yangtze River Economy Belt

GONG Xu-sheng1, KE Bi-qin2, HE Chao3   

  1. (1.School of Nuclear Technology and Chemistry and Biology, Hubei University of Science and Technology, Xianning 437100, China; 
    2. School of Resources and Environmental Sciences, Wuhan University, Key Laboratory of Geographic Information System, 
    Ministry of Education, Wuhan 430079, China; 3. College of Resources and Environment, Yangtze University, Wuhan 430100, China)
  • Online:2022-11-20 Published:2022-12-26

摘要: 长江经济带地区的地表臭氧(O3)污染日趋严重,不利于区域O3的联合防控。利用趋势分析、热点分析、空间聚类和时空地理加权回归模型(GTWR),研究了2013~2020年长江经济带地区O3浓度的时空分布、演变格局和变化驱动因素间的复杂非线性关系。结果表明:(1)长江经济带地区年均O3浓度大于100 μg/m3,整体呈显著增长趋势,平均增长速率为2.88 μg(m3·a)(p < 0.05);空间上O3平均浓度呈东北高,西部低的分布格局;(2)O3浓度变化速率的热点区域分布在湖北、安徽、江苏、上海、浙江、江西和湖南等区域;冷点区域分布在四川东部、重庆东部、湖北和湖南西部以及贵州东部;(3)第二产业占GDP比重是长江经济带O3浓度变化的主要社会经济驱动因素,回归系数为0.328;降水是长江经济带O3浓度的主要气象驱动因子,其次是气温、相对湿度、风速、平均能见度和气压;O3浓度与气温呈显著正相关,与降水、相对湿度、风速、平均能见度和气压呈显著负相关。该研究可为长江经济带大气污染防治提供参考依据。

Abstract: Surface ozone (O3) pollution in the Yangtze River Economic Belt (YREB) region is becoming increasingly severe, which is not beneficial to the integrated regional O3 prevention and prevention. Based on the trend analysis, hotspot analysis, spatial clustering and spatio-temporal geographically weighted regression model (GTWR), we investigated the complex nonlinear relationships between the spatiotemporal distribution, evolution patterns and drivers of O3 concentrations in the YREB region from 2013 to 2020.The results show that: (1) The annual average O3 concentration in the YREB is over 100 μg/m3, with a significant increase trend and an average increase rate of 2.88 μg/m3/year (p<0.05); Spatially, the average O3 concentration shows a distribution pattern of high in the northeast and poor in the west. (2) The hot spot regions of O3 concentration variations rate were distributed in Hubei, Anhui, Jiangsu, Shanghai, Zhejiang, Jiangxi and Hunan regions; the cold spot regions were distributed in eastern Sichuan, eastern Chongqing, western Hubei and Hunan and eastern Guizhou. (3) The proportion of secondary industry in GDP was the dominant socioeconomic driver of O3 concentration in the YREB, with a regression coefficient of 0.328. Precipitation was the primary meteorological driver of O3 concentration, followed by temperature, relative humidity, wind speed, mean visibility and pressure; O3 concentration was significantly positively associated with temperature and negatively correlated with precipitation, relative humidity, wind speed, mean visibility and barometric pressure. This investigation could provide a benchmark for the prevention and control of air pollution in the YREB.


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