College of Geographical Sciences, Harbin Normal University, Harbin, China.
Key Laboratory of Remote Sensing Monitoring of Geographic Environment of Heilongjiang Province, Harbin Normal University, Harbin, China.
PLoS One. 2024 May 31;19(5):e0300185. doi: 10.1371/journal.pone.0300185. eCollection 2024.
Based on the background of urbanization in China, we used the dynamic spatial panel Durbin model to study the driving mechanism of ozone pollution empirically. We also analyzed the spatial distribution of ozone driving factors using the GTWR. The results show that: i) The average annual increase of ozone concentration in ambient air in China from 2015 to 2019 was 1.68μg/m3, and 8.39μg/m3 elevated the year 2019 compared with 2015. ii) The Moran's I value of ozone in ambient air was 0.027 in 2015 and 0.209 in 2019, showing the spatial distribution characteristics of "east heavy and west light" and "south low and north high". iii) Per capita GDP industrial structure, population density, land expansion, and urbanization rate have significant spillover effects on ozone concentration, and the regional spillover effect is greater than the local effect. R&D intensity and education level have a significant negative impact on ozone concentration. iv) There is a decreasing trend in the inhibitory effect of educational attainment and R&D intensity on ozone concentration, and an increasing trend in the promotional effect of population urbanization rate, land expansion, and economic development on ozone concentration. Empirical results suggest a twofold policy meaning: i) to explore the causes behind the distribution of ozone from the new perspective of urbanization, and to further the atmospheric environmental protection system and ii) to eliminate the adverse impacts of ozone pollution on nature and harmonious social development.
基于中国城市化的背景,我们使用动态空间面板 Durbin 模型实证研究了臭氧污染的驱动机制。我们还使用 GTWR 分析了臭氧驱动因素的空间分布。结果表明:i)2015 年至 2019 年,中国环境空气中臭氧浓度的年平均增长率为 1.68μg/m3,2019 年比 2015 年升高了 8.39μg/m3。ii)2015 年和 2019 年环境空气中臭氧的 Moran's I 值分别为 0.027 和 0.209,呈现出“东重西轻”和“南高北低”的空间分布特征。iii)人均 GDP、产业结构、人口密度、土地扩张和城市化率对臭氧浓度具有显著的溢出效应,区域溢出效应大于局部效应。研发强度和教育水平对臭氧浓度有显著的负向影响。iv)教育程度和研发强度对臭氧浓度的抑制作用呈下降趋势,人口城市化率、土地扩张和经济发展对臭氧浓度的促进作用呈上升趋势。实证结果具有双重政策意义:i)从城市化的新视角探索臭氧分布的原因,进一步完善大气环境保护体系;ii)消除臭氧污染对自然和和谐社会发展的不利影响。