Exploring the Impact of Climate Change on Road Fatalities: A Macroscopic Panel Data Analysis.
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| Title: | Exploring the Impact of Climate Change on Road Fatalities: A Macroscopic Panel Data Analysis. |
|---|---|
| Authors: | Hu, Qirui1 (AUTHOR), Zou, Yajie1 (AUTHOR), Wu, Shubo1 (AUTHOR) shubowu@tongji.edu.cn, Zhang, Siyang1 (AUTHOR) siyangzhang@tongji.edu.cn, Zhang, Yue2 (AUTHOR), Wu, Lingtao3 (AUTHOR), Lee, Jaeyoung Jay (AUTHOR) |
| Source: | Journal of Advanced Transportation. 9/30/2025, Vol. 2025, p1-11. 11p. |
| Subjects: | Climate change, Traffic fatalities, El Niño, Traffic safety, Panel analysis, Environmental disasters, Data analysis, Socioeconomic factors |
| Geographic Terms: | United States |
| Abstract: | The present road traffic safety situation faces significant challenges. Examining the influences of diverse contributing factors on road traffic crashes is of crucial importance. However, different factors may have different influences as the change of location and time and the neglect of potential heterogeneity while modelling the frequency of traffic crashes may lead to biases in parameter estimation and incorrect inference. To address the unobserved spatiotemporal heterogeneity and accurately explore the correlations between contributing factors and fatal traffic crashes, a fixed effects panel model with structural breaks is applied to identify the influences of crucial factors on fatal traffic crashes from a macroscopic level. A multisource dataset, including fatal crash numbers, socioeconomic factors, laws and regulations and climate factors is collected from the United States spanning 45 years (from 1977 to 2021). The climate change events (i.e., El Niño–Southern Oscillation phenomena) are examined for their influences on fatal traffic crashes. The experimental results illustrate that high temperatures and frequent meteorological disasters have increasing impacts on fatal crash numbers. High precipitation shows a decreasing one from a macroscope level because of the lagged effect of precipitation on crashes across days. Particularly, the climate change events (including EP E1 Niño, CP E1 Niño and La Niña) represent an adverse impact on road traffic safety. Additionally, the states with similar meteorological characteristics are categorized as high temperature, high precipitation and frequent meteorological disaster subsets for separate analysis. Under these subsets, rural trip proportion becomes a more pronounced factor that affects fatal road traffic crashes, and helmet laws are more efficient in reducing fatal crash frequency. The research findings reveal an increasingly complex road traffic safety environment in the context of global warming, offering valuable perspectives for enhancing road traffic safety. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Advanced Transportation is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 188366256 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Exploring the Impact of Climate Change on Road Fatalities: A Macroscopic Panel Data Analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hu%2C+Qirui%22">Hu, Qirui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zou%2C+Yajie%22">Zou, Yajie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Shubo%22">Wu, Shubo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> shubowu@tongji.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Siyang%22">Zhang, Siyang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> siyangzhang@tongji.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Yue%22">Zhang, Yue</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Lingtao%22">Wu, Lingtao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lee%2C+Jaeyoung+Jay%22">Lee, Jaeyoung Jay</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Advanced+Transportation%22">Journal of Advanced Transportation</searchLink>. 9/30/2025, Vol. 2025, p1-11. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Climate+change%22">Climate change</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+fatalities%22">Traffic fatalities</searchLink><br /><searchLink fieldCode="DE" term="%22El+Niño%22">El Niño</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+safety%22">Traffic safety</searchLink><br /><searchLink fieldCode="DE" term="%22Panel+analysis%22">Panel analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Environmental+disasters%22">Environmental disasters</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomic+factors%22">Socioeconomic factors</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The present road traffic safety situation faces significant challenges. Examining the influences of diverse contributing factors on road traffic crashes is of crucial importance. However, different factors may have different influences as the change of location and time and the neglect of potential heterogeneity while modelling the frequency of traffic crashes may lead to biases in parameter estimation and incorrect inference. To address the unobserved spatiotemporal heterogeneity and accurately explore the correlations between contributing factors and fatal traffic crashes, a fixed effects panel model with structural breaks is applied to identify the influences of crucial factors on fatal traffic crashes from a macroscopic level. A multisource dataset, including fatal crash numbers, socioeconomic factors, laws and regulations and climate factors is collected from the United States spanning 45 years (from 1977 to 2021). The climate change events (i.e., El Niño–Southern Oscillation phenomena) are examined for their influences on fatal traffic crashes. The experimental results illustrate that high temperatures and frequent meteorological disasters have increasing impacts on fatal crash numbers. High precipitation shows a decreasing one from a macroscope level because of the lagged effect of precipitation on crashes across days. Particularly, the climate change events (including EP E1 Niño, CP E1 Niño and La Niña) represent an adverse impact on road traffic safety. Additionally, the states with similar meteorological characteristics are categorized as high temperature, high precipitation and frequent meteorological disaster subsets for separate analysis. Under these subsets, rural trip proportion becomes a more pronounced factor that affects fatal road traffic crashes, and helmet laws are more efficient in reducing fatal crash frequency. The research findings reveal an increasingly complex road traffic safety environment in the context of global warming, offering valuable perspectives for enhancing road traffic safety. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Advanced Transportation is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=188366256 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1155/atr/4693354 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1 Subjects: – SubjectFull: Climate change Type: general – SubjectFull: Traffic fatalities Type: general – SubjectFull: El Niño Type: general – SubjectFull: Traffic safety Type: general – SubjectFull: Panel analysis Type: general – SubjectFull: Environmental disasters Type: general – SubjectFull: Data analysis Type: general – SubjectFull: Socioeconomic factors Type: general – SubjectFull: United States Type: general Titles: – TitleFull: Exploring the Impact of Climate Change on Road Fatalities: A Macroscopic Panel Data Analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hu, Qirui – PersonEntity: Name: NameFull: Zou, Yajie – PersonEntity: Name: NameFull: Wu, Shubo – PersonEntity: Name: NameFull: Zhang, Siyang – PersonEntity: Name: NameFull: Zhang, Yue – PersonEntity: Name: NameFull: Wu, Lingtao – PersonEntity: Name: NameFull: Lee, Jaeyoung Jay IsPartOfRelationships: – BibEntity: Dates: – D: 30 M: 09 Text: 9/30/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 01976729 Numbering: – Type: volume Value: 2025 Titles: – TitleFull: Journal of Advanced Transportation Type: main |
| ResultId | 1 |
