Analysis on the investment efficiency of industrial pollution control based on Markov and DEA model

Abstract

Taking the investment amount of industrial "three wastes" pollution control in 2000-2016 as an input indicator, the investment amount predicted by the grey residual GM (1, 1) Markov model is compared with the actual value in 2014-2016 to verify the feasibility and accuracy of the model. Sulphur dioxide removal, smoke (powder) dust removal, industrial wastewater discharge standards and solid waste comprehensive utilization are used as output indicators. The DEA-BCC model is used to calculate the input efficiency of industrial pollution control from 2000 to 2016, and the main factors restricting the effect of pollution control are analyzed, and the forecast model is used to provide basis for improving the input efficiency. The results show that the average comprehensive efficiency of industrial pollution control input from 2000 to 2016 was 0.887. Overall, the comprehensive efficiency is relatively low. The fluctuation of input efficiency fluctuated greatly and is not stable enough. There are only 6 years in DEA effective state. The unstable investment scale, the lack of rational allocation of resources, the shortage of talents and governance technologies and the low level of supervision are the key factors affecting the efficiency of industrial pollution treatment.