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中国广东地区颗粒物浓度对交通违规行为及事故严重程度的影响。

The effects of PM concentrations on traffic violations and accident severity in Guangdong China.

作者信息

Fan Ling, Chen Mingqin

机构信息

School of Environment, South China Normal University, Guangzhou, 510006, China.

Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, 510275, China.

出版信息

Sci Rep. 2025 Jul 2;15(1):22792. doi: 10.1038/s41598-025-05354-w.

Abstract

How does air pollution affect road safety? This study examines the impact of local PM concentrations on traffic violations and accident severity in Guangdong Province, China, from 2006 to 2014. Using instrumental variable methods to address endogeneity, we find a significant relationship between PM concentrations and the occurrence of high-penalty traffic violations and severe accidents. Robustness checks confirm these results hold when using alternative pollutants (PM, SO, and SO). To account for the bias caused by nonlinear relationships between air pollution and weather, we employ a random forest model to isolate the weather-independent component of PM concentrations. Further analysis reveals significant heterogeneity in these effects across driver characteristics and geographic areas. This paper also explores potential visual and psychological mechanisms through which PM influences traffic safety. Our findings offer valuable policy implications for environmental and traffic management strategies.

摘要

空气污染如何影响道路安全?本研究考察了2006年至2014年中国广东省当地细颗粒物(PM)浓度对交通违规行为和事故严重程度的影响。我们使用工具变量法来解决内生性问题,发现PM浓度与高处罚交通违规行为及严重事故的发生之间存在显著关系。稳健性检验证实,在使用替代污染物(PM、SO和SO)时这些结果依然成立。为了应对空气污染与天气之间非线性关系所导致的偏差,我们采用随机森林模型来分离出PM浓度中与天气无关的部分。进一步分析表明,这些影响在驾驶员特征和地理区域方面存在显著的异质性。本文还探讨了PM影响交通安全的潜在视觉和心理机制。我们的研究结果为环境和交通管理策略提供了有价值的政策启示。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1411/12216440/9fabf8bfaff1/41598_2025_5354_Fig1_HTML.jpg

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