China actively promotes the dua-carbon strategy and the green low-carbon transformation of industrial parks to address the global climate crisis caused by excessive greenhouse gas emissions. In this context, the STIRPAT model was employed to analyze the carbon emission characteristics of industrial parks, and effective emission reduction plans were formulated to establish a viable technical framework for their transformation. The study identified 16 driving factors across five dimensions: energy, economy, population, technology, and emission reduction as the research focus. Subsequently, Pearson correlation analysis and multicollinearity analysis were applied to screen and evaluate the driving factors. Finally, the STIRPAT equation was calibrated through ridge regression yielding a standardized regression model. The results demonstrate that during the 2018–2023 study period, eight driving factors contributed to rising carbon emissions in the park, with industrial output value (GT) exhibiting the strongest influence; an increase in production capacity per unit of carbon emissions was found to suppress carbon emission growth; finally, the relative impact ranking of all driving factors was established.