Research based on machine-based pathways for pollution and carbon reduction from road mobile sources

PENG Lin; DONG Jiaqi; YANG Shijie; YAN Yulong; LYU Xin; YU Xuewei; YUE Ke; LI Junjie; WANG Bing

doi:10.11860/j.issn.1673-0291.20250038

Abstract：To address the challenges of precise governance arising from the spatiotemporal heterogene-ity and diverse patterns of pollutant and carbon emissions from road mobile sources in China,this study develops a machine learning-based analytical framework for emission characteristics,driving fac-tors,and mitigation pathways.First,a transport-carbon-environment dataset is constructed by inte-grating multi-source data to analyze the spatiotemporal distribution characteristics of emissions.Sec-ond,a knowledge-constrained non-negative matrix factorization model is developed to identify distinct emission patterns and their underlying drivers.Finally,a multi-pattern integrated multiple linear re-gression model is applied to evaluate effective pathways for pollution and carbon reduction.The results indicate that in recent years,particulate matter emissions from road mobile sources have shown a de-creasing trend,while carbon dioxide emissions continue to increase,with emissions of NOx,CO,and VOCs remaining substantial.Three primary emission patterns are identified across China:a"CO2-PM Reduction Pattern,"distributed across border and coastal regions and driven mainly by road passenger and freight transport activities and vehicle mileage(37.2%);a"Pollutant Reduction Pattern,"found in municipalities like Beijing and Tianjin and provinces such as Guangdong,mainly influenced by the Gross Transport Product(30.1%);and a"CO2-NOx Pollution Pattern,"located in the central and western regions,affected by multiple factors including railway development and its electrification,as well as the use of light-duty transport vehicles(23.6%).Pathway analysis indicates that accelerating economic development in the transport sector has the most significant impact on reduction,potentially reducing CO2 and NOx by up to 6.7%and 4.5%,respectively.Other significant measures include re-structuring the transport energy system,reducing road freight and vehicle mileage,and promoting the shift from road to rail alongside railway electrification.The proposed framework provides a quantita-tive basis and strategic guidance for coordinated pollution and carbon reduction from road mobile sources in the context of China's dual-carbon goals of carbon peaking and carbon neutrality.