Forecast of CO 2 and Pollutant Emission Reductions from Electric Vehicles in Beijing–Tianjin–Hebei

Li Li, Honglin Liu and Bingchun Liu ()
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Li Li: College of Economics and Management, Tianjin University of Science and Technology, Tianjin 300222, China
Honglin Liu: School of Management, Tianjin University of Technology, Tianjin 300384, China
Bingchun Liu: School of Management, Tianjin University of Technology, Tianjin 300384, China

Sustainability, 2025, vol. 17, issue 14, 1-22

Abstract: The promotion of new energy vehicles (NEVs) represents a critical strategy for mitigating carbon emissions and air pollution. To evaluate the CO 2 and air pollutant reduction potential of NEVs in the Beijing–Tianjin–Hebei region, this study developed an integrated framework combining gray correlation analysis (GRA) and bidirectional long short-term memory (BiLSTM), referred to as the GRA-BiLSTM model, to forecast the adoption trend of NEVs and calculate the CO 2 and air pollutant emission reduction. The GRA-BiLSTM model developed in this study shows optimal predictive performance. The results indicate that new energy vehicles (NEVs) have great potential for environmental collaborative emission reduction in the transportation sector: it is predicted that by 2035, the total number of NEVs will be nearly 11.88 million, with a cumulative reduction of 2.76 billion tons of carbon emissions and significant reductions in various key air pollutants. This study provides an important quantitative basis for formulating pollution reduction and carbon reduction policies in the transportation sector.

Keywords: new energy vehicles; gray relation analysis; BiLSTM; carbon emission reduction; atmospheric pollutant (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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