Multi-objective programming for economy–energy–environment system and policy mix with dual constraints of carbon emission and water consumption based on multi-scenario analysis. (November 2022) - Fu, Zhenghui; Zhang, Yang; He, Shanshan; Wang, Han; Jiang, Xia; Wang, Shuhang
Abstract: Balancing the tradeoff between economy, energy, environment, water resources and carbon emissions has become the major challenge for sustainable development. In this study, a fuzzy multi-objective method is developed by integrating multi-objective programming, fuzzy linear programming and multiple scenarios. The developed approach can tackle multiple uncertainties and complexities existing in economy–energy–environment system, random carbon dioxide emission and water consumption control policies mix. Results disclose that (1) policy orientation and carbon emission control policy can achieve both carbon and water resource control goals, and water resource control policies are relatively unnecessary; (2) the tertiary sector will become the leading industry, accounting for more than three quarters of the total output value, the construction industry will also overgrow, and the proportion of the manufacturing industry will drop significantly; (3) coal still dominates in the energy production and total quantity consumed, and petroleum consumption will fall, coal accounts for about 75 percent of total energy consumption and electricity for about 15 percent; (4) according to different sources, carbon dioxide emissions are mainly from coal and electricity utilization. Coal's contribution gradually rose to 65 percent, while electricity dropped from 35 percent to 30 percent. For each industry, the mining industry, the electricity industry and the tertiary sector are the primary sources. (5) the sulfur dioxide control policy and carbon dioxide control policy has a strong correlation, and nitrogen oxide control policies have a specific correlation with them. The water resource control policy and particulate matter control policy are relatively independent.