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基于地质探测器和地理空间模型的中国臭氧污染风险时空变化及其影响因素。

Spatio-temporal variation of ozone pollution risk and its influencing factors in China based on Geodetector and Geospatial models.

机构信息

School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China; School of Geosciences and Info Physics, Central South University, Changsha, 410000, China.

School of Civil and Surveying & Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China.

出版信息

Chemosphere. 2022 Sep;302:134843. doi: 10.1016/j.chemosphere.2022.134843. Epub 2022 May 6.

DOI:10.1016/j.chemosphere.2022.134843
PMID:35533939
Abstract

Ozone (O) has become the primary pollutant in many cities, and high concentrations of O cause significant harm to the ecological environment and human health. This study investigated the spatiotemporal distribution of surface concentrations of ozone over entire China and analyzed the influencing factors based on the geographical detector technique. Moreover, the Pearson correlation analysis was used to analyze the influence of various meteorological factors on ozone concentrations. The results showed that, on the national scale, the daily average O concentration in the cities of China in 2019 was 92.441 μg/m and the nonattainment rate of daily average ozone was 7.98%. However, the ozone nonattainment rate was 33.33% in heavily polluted regions. The highest O concentration was observed in summer, and the lowest was observed in spring. The O concentrations in cities across the country showed significant spatial distribution characteristics. Among the five pollutants, the highest correlation was observed between O and PM and the lowest was observed between O and SO. Among the metrological factors, wind speed and solar radiation are the most influencing factors, and showed positive correlation. Moreover, the annual precipitation is negatively correlated with O-8h concentrations. The methods and findings of this paper can be used as an aid for air pollution control programs in different regions for diminishing the risk of exposure to various air pollutants.

摘要

臭氧(O)已成为许多城市的主要污染物,高浓度的臭氧对生态环境和人类健康造成了重大危害。本研究利用地理探测器技术,调查了中国各地表臭氧浓度的时空分布,并分析了影响因素。此外,还采用 Pearson 相关分析方法分析了各种气象因素对臭氧浓度的影响。结果表明,在全国范围内,2019 年中国城市的日平均臭氧浓度为 92.441μg/m,臭氧日平均不达标率为 7.98%。然而,在重污染地区,臭氧不达标率为 33.33%。臭氧浓度在夏季最高,春季最低。全国各城市的臭氧浓度呈现出显著的空间分布特征。在五种污染物中,臭氧与 PM 的相关性最高,与 SO 的相关性最低。在气象因素中,风速和太阳辐射是最具影响力的因素,呈正相关。此外,年降水量与 O-8h 浓度呈负相关。本文的方法和结果可作为不同地区空气污染控制计划的辅助手段,以降低暴露于各种空气污染物的风险。

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