It is still necessary to regularly investigate the breakdown of socio-economic elements as a starting point for analyzing the effects of diverse human production activities on PM_2.5 intensity from industrial and regional viewpoints. In this paper, the emission factor model was adopted to measure PM_2.5 emissions in the Beijing–Tianjin–Hebei (BTH) region at the regional and industrial levels. The logarithmic mean Divisia index (LMDI) decomposition model was employed to analyze the factors affecting PM_2.5 emissions related to energy consumption in the BTH region at the regional and sectoral levels. Building on this foundation, a system dynamics (SD) model was established to make a prediction regarding PM_2.5 pollution in the BTH region in 2025. This study found that secondary industry was a major source of PM_2.5 emissions in the BTH region. Coal remained the main form of energy consumption in the BTH region. Secondly, the effect size of the factors affecting PM_2.5 intensity ranked in the order of energy intensity, energy structure, and industrial structure. Thirdly, in 2025, PM_2.5 emissions in the BTH region will decline appreciably, but there is still a certain gap in terms of meeting the targets of “the 14th Five-Year Plan” between the three provinces and cities. These results indicate that the BTH region should achieve the effective management of PM_2.5 pollution at the source through the following initiatives: it is necessary to carry out the continuous adjustment of energy structures to gradually increase the proportion of clean energy; we must steadily promote the decline in energy intensity reduction, and gradually strengthen scientific and technological innovation; and we must continue to promote the optimization of the industrial structure and increase the proportion of tertiary industry every year.

The continuous augmentation of greenhouse gas and pollution emissions has exerted a conspicuous and negative influence on social production, economic development, and human health. As the digital economy continues to penetrate into various fields of social development, whether the advancement of the digital economy can promote urban pollution and carbon dioxide emission reduction has emerged as a pivotal topic of interest across all sectors of society. This study adopts empirical research methods to delve into the direct static, dynamic effects, spatial effects, and spatial spillover effects of the digital economy on pollution and carbon dioxide emission reduction in the Yangtze River Delta Urban Agglomeration (YRDUA). As evidently suggested by the research findings, the digital economy has an inverted U-shaped impact on carbon dioxide and pollution emissions. As heterogeneity analysis reveals, this inverted U-shaped influence relationship exhibits heterogeneous effects in the high-level group and low-level group of digital economy development. The robustness of this conclusion was demonstrated through robustness testing. Mechanism analysis reveals that, in the early stage of digital development, infrastructure expansion serves as the primary channel driving emissions, whereas in the later stage, green technological progress becomes the key mechanism enabling emission reductions. Finally, the results confirms that digital economy has a significant negative spatial correlation effect on carbon dioxide and pollution emissions, and has an inverted U-shaped spatial spillover effect on neighboring regions.