The Homology of Atmospheric Pollutants and Carbon Emissions in Industrial Parks: A Case Study in North China

Industrial parks are well-known as a critical intervention point for global carbon emission reductions due to the high carbon emissions emitted. Conducting carbon accounting research in these parks can provide more precise foundational data for carbon reduction initiatives, promoting low-carbon industrial park development. However, industrial parks, positioned as non-independent accounting units between provincial and industry levels, face severe challenges due to ambiguous boundaries, complex accounting entities, and data selection difficulties that significantly impact the carbon accounting accuracy. This study employed the IPCC emission factor method for industrial parks, taking its management structure as the accounting boundary. Additionally, we constructed a carbon accounting method and representation system by considering the carbon emission flow path and integrating the correlation between pollutant and carbon emissions. By categorizing carbon emissions into five groups, this study obtained emissions from fuel combustion (E1), industrial processes (E2), purchased/sold electricity (E3), purchased/sold heat (E4), and carbon-sequestering products (E5). Between 2016 and 2021, the industrial park’s carbon emissions fell from 15.0783 to 6.7152 million tons, while the intensity dropped from 4.86 to 1.91 tons of carbon dioxide (CO2) per CNY 10,000. The park achieved dual control targets for the total carbon emissions and intensity, with E2 being the main reduction source (70% of total). Meanwhile, total atmospheric pollutants decreased from 9466.19 to 1736.70 tons, with C25 and C26 industries contributing over 99%. In particular, C26 achieved significant reductions in nitrogen oxides (NOx) and sulfur dioxide (SO2), aiding pollution mitigation. A strong positive correlation was found between pollutants and carbon emissions, especially in C26, SO2 (0.77), and NOx (0.89), suggesting NOx as a more suitable carbon emission indicator during chemical production. These findings offer a theoretical framework for using pollutant monitoring to characterize carbon emissions and support decision-making for sustainable industrial development.