Environmental Management Of Industrial Ecosystems From The Perspective Of Whole-Process Pollution Control

Since the reform and opening-up,China's economy has achieved rapid growth.However,as a result of rough production,economic development has always been accompanied by serious environmental pollution problems.In particular,China's industrial system,while making a huge contribution to GDP,has also caused serious water environment pollution and air pollution.China is still in the process of industrialization,and industrial development has real problems such as high energy consumption,high pollution,and low energy utilization.Environmental management and sustainable economic development are imminent.To this end,our government has put forward the concept of green development and the long-term goal of carbon peaking and carbon neutrality.The thinking of pollution prevention and control has also changed from endof-pipe treatment to whole process control.Practice shows that to achieve sustainable development,scientific and reasonable management decision analysis of the environment is needed first.In order to promote the industrial green revolution and achieve the ambitious goal of carbon neutrality.Based on the data envelopment analysis method,this paper takes Chinese industrial sectors as the main research object and studies three stages of the Chinese industrial ecosystem:energy production stage,pollution treatment stage,and total adjustment stage from the perspective of whole process pollution control.Considering the characteristics of environmental indicators at each stage,we analyze and study the current energy efficiency level,pollution control capacity,and total adjustment plan of the industrial sector.The main research includes the following three areas.First,the impact of the heterogeneity of energy inputs and pollutant outputs on the evaluation of environmental performance in industrial production processes is investigated in Chapter 3.This chapter extends the DEA method with bilateral nonhomogeneity.By splitting and reorganizing the indicators,we transform the efficiency values of the non-homogeneous problem into the sum of the efficiency values of a set of homogeneous subsets.The model further relaxes the assumption condition of DEA theory on the homogeneity of indicators.The model is also applied to study the energy efficiency level of the industrial sector in China.And the changes in industrial energy efficiency over five years are dynamically analyzed and relevant policy recommendations are given.Secondly,in Chapter 4,focusing on the industrial pollution treatment process,the impact of the ratio-based indicators reflecting environmental control capacity on the evaluation of environmental control efficiency is investigated.In this chapter,a singlestage DEA model including proportional data is first constructed.We use the desirable ratio output as a replacement for the relevant undesirable output and to evaluate the pollution treatment capacity of the industrial sector.Later,considering the link continuity and index correlation between the treatment and production stages,we extended the single-stage model to a serial two-stage system and decomposed the overall environmental efficiency of the industry into production efficiency and treatment efficiency for separate studies.In the application of the model in this chapter,the validity of the ratio DEA environmental treatment model was first verified by Monte Carlo simulation.The two-stage model is then applied to evaluate the efficiency of environmental governance in China's industrial sectors,and the two-stage efficiency scores of the industrial sector and the trend of efficiency levels over five years are calculated and analyzed.Finally,policy recommendations for efficiency improvement are given.Finally,in Chapter 5,the allocation of emission reduction tasks in the total adjustment stage of the industrial system is studied.On the one hand,we consider the influence of the heterogeneity of energy indicators on the carbon emission rights allocation scheme,and on the other hand,we consider the government-issued energy conservation and emission reduction requirements the ratio binding indicator,the energy consumption per unit of industrial value-added,on the redistribution scheme.This chapter extends the carbon emission allocation model based on input heterogeneity.We divide the decision units into several sub-processes according to different energy inputs and transform the original non-homogeneous allocation problem into an allocation problem in a parallel network system with non-homogeneous subunits.Finally,combining the multi-objective planning approach and the constraints of ratio-type emission reduction targets,we investigate the impact of energy consumption structure differences in industrial sectors on the emission rights allocation scheme.We applied the model to allocate emission reduction tasks to 38 industrial sectors in China according to the CO2 reduction requirements proposed by the government.The task allocation is implemented into each energy consumption sub-process of each sector.Finally,we give recommendations for energy restructuring based on the allocation results,which provide directions for the next stage of production governance in each industrial sector.The contributions of this paper are mainly:(1)Taking the heterogeneity and ratio characteristics of environmental indicators as the entry point,this paper investigates the influence of environmental indicator characteristics on performance evaluation methods,broadens the evaluation indicator system for environmental performance analysis,and provides new ideas for environmental performance research.(2)In terms of research methods,this paper expands the research methods of non-homogeneous DEA,ratio DEA and network DEA,respectively,according to the influence of environmental indicator characteristics,and their applications in the field of environmental performance evaluation.This paper makes useful additions and improvements to the existing DEA methods.(3)This paper selects the industrial sector as the research object and completely investigates the level of environmental performance and improvement options of industrial ecosystems in the whole process of "production-governance-comprehensive adjustment" from the perspective of whole process control.This study provides new perspectives and policy recommendations for industrial systems to achieve green development and help to peak carbon dioxide emissions and achieve carbon neutrality.