Accounting and Driving-Effect Analysis of Carbon Emissions from Industrial Energy Consumption in Liaoning Old Industrial Base

The industrial sector in Liaoning Old Industrial Base exhibits energy consumption per unit of added value substantially above the national average, with carbon emissions from industrial energy consumption characterized by a large baseline and stringent reduction constraints. To address these challenges, this study applies the IPCC emission-factor method to construct a long time-series accounting of provincial carbon emissions from industrial energy consumption and develops a multi-dimensional carbon intensity evaluation system. An extended Logarithmic-Mean Divisia Index (LMDI) decomposition framework is employed to integrate five driving factors—energy structure, energy intensity, economic structure, per-capita economic output, and population scale—alongside differentiated mechanisms across four fossil-fuel categories (raw coal, crude oil, coke, and diesel). The results identify per-capita economic output as the dominant positive driver, while energy intensity and economic structure serve as primary abatement factors, with their cumulative contributions exhibiting notable phase transitions over the study period. These findings provide a quantitative foundation for designing industry- and region-specific emission-reduction policies and offer practical insights for reconciling industrial revitalization with the “dual-carbon” strategy in old industrial bases.