An innovative environmental regulation tool for regional air pollution based on DEA-RFR

Abstract

Environmental regulation tools are one of the conventional means for pollution control in various countries. For large-scale urbanization regions, reasonable pre-allocation of pollutant emission amount for each area is an effective regulation to improve air quality. Treating pollutant emission quota as a resource element, a comprehensive input-output model has been established based on Data Envelopment Analysis (DEA) method, to evaluate the rationality of pollutant emission allocation and provide adjustment scheme, thus developing an environmental regulation tool. The index system includes factors of economy, environment, energy consumption, demographic and land-use as input indicators, regional GDP and environmental air quality index as output indicators. The regulation tool is applied to the current air pollutant emission management in Henan Province, China. The results show that 7 cities need to further adjust the allocation scheme, among which, Anyang, Xinxiang, Nanyang and Shangqiu are suggested to reduce the emission allocation quotas; Puyang and Zhumadian are suggested to increase the emission allocation quotas; Pingdingshan shall seek optimization paths through collaborative improvement. Further, to verify the effectiveness of the tool, by joint using Random Forest Regression (RFR), a DEA efficiency reassessment is conducted on the obtained new allocation scheme of Nanyang City. The results show that the efficiency of the new allocation scheme has reached optimal. This study provides a practical and effective regulation tool for regional management of pollutant emission, to balance economic growth and environmental protection.

Keywords

• environmental regulation tool
• air pollutant emission allocation
• input-output model
• DEA efficiency method
• Random Forest Regression