Low-carbon transition pathways for heavy-industry parks: A case study from Fujian, China

Industrial parks are pivotal to China's Dual Carbon goals, yet mitigation is often constrained by incomplete accounting and unstable driver estimates under multicollinearity. This study constructs a high-resolution emission inventory for a representative heavy-industry park in Fujian Province from 2019 to 2023 and estimates an expanded STIRPAT model using ridge regression to obtain stable, interpretable coefficients. The results indicate that total emissions followed a V-shaped trajectory, declining from 4.48 Mt CO₂e in 2019 to 4.29 Mt CO₂e in 2021 and rebounding to 4.48 Mt CO₂e in 2023. Structurally, direct fossil-fuel combustion contributed about 92% of total emissions, with coke and raw coal accounting for more than 98% of combustion emissions. In terms of drivers, ridge estimates identify total industrial energy use and coal consumption as the dominant positive drivers, followed by gross industrial output, while environmental governance investment is significantly negative (β = -1.545). As a single-case study, these findings are most transferable to coal-dependent heavy-industry parks and motivate future comparative analyses across diverse park types.