Exploring the Environmental Effect of Traffic-Related PM2.5 Emissions: A Multidisciplinary Approach
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 225
Special Issue Editor
Special Issue Information
Dear Colleagues,
The adverse environmental and health impacts of traffic-related PM2.5 emissions have been a growing concern worldwide. This special issue aims to shed light on the environmental impact of traffic-related PM2.5 emissions using a multidisciplinary approach. The issue welcomes original research or review articles that employ machine learning, spatio-temporal data mining, public health risk assessment, and scenario simulation to investigate the environmental impacts of traffic-related PM2.5 emissions. Topics of interest include, but are not limited to:
- Data mining methods to model the spatio-temporal patterns of traffic-related PM2.5 emissions.
- Machine learning techniques to explore the dynamic response relationship between traffic-related PM2.5 emissions and air quality.
- Public health risk assessment of traffic-related PM2.5 emissions exposure.
- Scenario simulation and policy analysis for mitigating traffic-related PM2.5 emissions and improving environmental sustainability.
Overall, this special issue will contribute to a better understanding of the environmental effects of traffic-related PM2.5 emissions and inform policymakers, researchers, and the public about the importance of reducing these emissions for a healthier and sustainable future.
Dr. Shifen Cheng
Guest Editor
Manuscript Submission Information
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Keywords
- traffic-related PM2.5 emissions
- machine learning
- spatio-temporal data mining
- public health risk
- scenario simulation
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