The amount of China's sulfur dioxide emission remains significantly large in recent years. To further reduce sulfur dioxide emission, the key is to find out the leading factors affecting sulfur dioxide emission and then take measures to control it accordingly. In order to investigate the influential factors of sulfur dioxide emission of various provinces, the data of sulfur dioxide emission of 30 provinces in China from 2001 to 2020 were collected. We established the symbolic regression model to explore the relationship between the GDP (x1), total population (x2), total energy consumption (x3), thermal power installed capacity (x4), and sulfur dioxide emission (dependent variable) for each province. The results show that the amount of China's total sulfur dioxide emission and sulfur dioxide emission in most provinces meet the environmental Kuznets curve (EKC). The influential degree of the factors affecting China's sulfur dioxide emission are GDP, total energy consumption, thermal power installed capacity, and total population. The provinces with the primary factor of GDP have the lowest average total energy consumption and average thermal power installed capacity, and their average sulfur dioxide emissions are also relatively low. The provinces with the primary factor of GDP do not show obvious geographical characteristics, but the provinces with the primary factor of total energy consumption are all distributed in southern China. Based on the research results, some control measures are also put forward.
Keywords: GDP; Installed capacity; Sulfur dioxide emission; Symbolic regression; Total energy consumption; Total population.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.