Assessing impacts and determinants of China's environmental protection tax on improving air quality at provincial level based on Bayesian statistics

Facing severe PM2.5 pollution, China has adopted a series of clean air policies since 2013, but PM2.5 concentrations in China remain serious. Weighing both sustainable development and environmental protection, the Environmental Protection Tax Law was implemented in 2018 in China. This research employed a Bayesian space-time model to identify the impacts of the environmental protection tax on PM2.5 pollution (IEPTPM2.5P) at the provincial level in 2018 in China, combining remotely sensed and in-situ monitoring data. Then the influence factors of the IEPTPM2.5P was investigated using a Bayesian LASSO regression model. Results indicate that the IEPTPM2.5P resulted in a decreasing trend of annual PM2.5 concentrations in 31 provinces. The spatial pattern of the IEPTPM2.5P presented a distinct geographical feature. The highest five IEPTPM2.5P occurred in Beijing, Tianjin, Shanghai, Shandong, and Hebei, and the corresponding values were -1.81, -1.79, -1.52, -1.51, and -1.47 mu g/m(3 )per year, respectively. Tourism output value associated negatively with the IEPTPM2.5P, and the other five variables associated positively with the IEPTPM2.5P. The urbanisation rate and relief amplitude were the top two influencing factors, with contributions of 36.3% and 19.3%, respectively. The IEPTPM2.5P increased 0.0141 mu g/m(3) per year (95% credibility interval (CI): 0.0013, 0.0259) if the urbanisation rate increased one percentage point. The influencing contributions and magnitudes of the tax rate for air pollutants and the environmental tax revenue are 9.6% and 12.1%, 0.0016 (95% CI:-0.0038, 0.0076) and 0.0108 (95% CI:-0.0188, 0.0412) mu g/m(3) per year, respectively.