An EG-Tree Model Incorporating Spatial Heterogeneity for Analyzing Multifactorial Coupling Effects on Carbon Emissions Across Industries and Regions in China

With the proposal of the dual carbon goals, it is of great significance to identify the causes of carbon emissions and reduce carbon emissions directly. There is a lack of analysis on the causes of carbon emissions considering the coupling effect of multiple factors and regional heterogeneity. The causes of carbon emissions are examined from multiple perspectives utilizing the panel data spanning from 1997 to 2022, encompassing 30 provinces in China. To further analyze the causes of carbon emissions, an enhanced feature and regularized gradient boosting tree (EG-Tree) model is constructed, and a scoring method for the tree structure is proposed. The coupling effect of multiple factors are analyzed such as coal, coke, crude oil, gasoline, kerosene, diesel oil, fuel oil, liquefied petroleum gas, natural gas, etc., on the carbon emission intensity of various industries and their regional heterogeneity. The results show that: (1) The EG-Tree model constructed in this study could accurately analyze the causes of carbon emissions under the coupling of multiple factors based on the cumulative iterative feature branching contribution values (impact factors), with an average model fitting precision of 0.30. This means the carbon emission intensity values were predicted by various industries in different regions based on different energy consumption levels and industry-specific carbon emissions, compared with the carbon emission intensity values calculated using the carbon emission measurement dataset. (2) The consumption of coal and coke has a significant impact on the average carbon emission factors of various industries, with values of 7139.95 and 7217.05, respectively. The consumption of natural gas and liquefied petroleum gas has a smaller impact on the average carbon emission intensity of various industries under the EG-Tree model with corresponding carbon emission intensity impact factors of 5057.90 and 2789.57, respectively. (3) The Northeast region is a low-carbon area, while the East region is a high-carbon area, with total carbon emissions of 2,238,646.60 million tons and 5,566,314.00 million tons of CO2, respectively. The Northeast region has the lowest pollution intensity for heating and cooling, with carbon emissions of 155,661.73 million tons of CO2; the industrial carbon emissions in the East region are relatively high at 1,623,835.62 million tons of CO2. The research findings of this study are beneficial for relevant departments to focus on the main impact factors of carbon emissions in different regions and industries, and to develop targeted emission reduction policies.