Research on Pathways to Achieve the "Dual Carbon" Goals Driven by New Energy Vehicle Popularization Based on a Multi-Source Data Fusion Model

Abstract

Amid growing global concerns over greenhouse gas emissions, the adoption of new energy vehicles (for short: NEVs) is a key pathway for China to achieve its "Dual Carbon" goals. Existing research examines NEVs from four main dimensions: life cycle emissions, policy mechanisms, regional impacts, and multi-source data integration. While NEVs have lower life cycle emissions than fuel vehicles, their benefits depend heavily on the power mix. Policy studies highlight the importance of subsidies and infrastructure, while regional analyses reveal spatial spillover effects and scenario-dependent emission reductions. This study employs multi-source data fusion, integrating atmospheric and power system data, to build high-precision carbon monitoring models. Using the Bass diffusion model, grey relational analysis, and consumer survey data, we analyze market trends and decision factors. A multi-objective optimization model, enhanced by particle swarm and genetic algorithms, evaluates policy scenarios under constraints of emissions, cost, and efficiency. Results show NEVs significantly reduce urban emissions, with policy-market synergy crucial for long-term growth. Findings emphasize the need to coordinate innovation, incentives, and public engagement to promote green mobility and inform adaptive, efficient policymaking for China’s low-carbon transition.