Innovation driver and county air pollution: cost-benefit analysis perspective

Innovation is the first power to drive the county’s green and low-carbon. It is crucial to explore the impact of innovation on air pollution from the perspective of counties at the bottom of the administrative division hierarchy. The article is aimed at exploring the direct impact effects, spatial spillover effects, impact mechanism pathways, non-linear relationships, and cost-benefits of innovation drive on air pollution in counties. To this end, based on the collection of county-level data from 2007 to 2020 in mainland China, the article constructs a fixed-effects model, a dynamic panel model, and a spatial Durbin model for analysis. For every 1% increase in the quantity of innovation, the county SO 2 emission concentration decreases by 0.2% on average; for every 1% increase in the quality of innovation, the county SO 2 emission concentration decreases by 0.3% on average. When the county innovation quantity driver increases by one standard deviation, the county SO 2 concentration decreases by an average of 0.29%; when the county innovation quality driver each standard deviation increases, the county SO 2 concentration is reduced by 0.33% on average. The significant entry of high-end factors, the increased frequency of regulation by the environmental protection department, and the increasing efficiency of energy use are the important mechanism pathways for innovation-driven reduction of air pollution in counties. There is no significant “(inverted) U-shaped” relationship between innovation-driven air pollution in the county samples. There is a negative spatial spillover effect of the innovation quality drive on air pollution control in all Chinese county samples. Innovation to drive the declining size of the county’s sulfur dioxide can bring about one billion yuan (about 139.81 million U.S. dollars) in comprehensive economic benefits. In the coming period, county governments should build a new pattern of “blue sky and white clouds” with neighboring regions in terms of spatial agglomeration of high-end elements, green transformation and utilization of energy, and intelligent monitoring and supervision of pollution.