Abstract

Energy, water, and environment are inextricably interwoven in the complex social and economic networks. This study proposes an optimization model for planning the energy–water–environment nexus system (EWENS) through incorporating the linear autoregressive integrated moving average model prediction model (ARIMA), Monte Carlo simulation, chance-constrained programming (CCP), and type-2 fuzzy programming (T2FP) into one general framework. This method effectively tackles type-2 fuzzy set and stochastic uncertainties. The proposed model can quantitatively explore the interconnections between water, energy, and environment systems and generate an optimized solution for EWENS. The proposed model was applied to a coal-dominated region of China, i.e., Inner Mongolia. Several findings and policy implications were obtained. First, the total water supply for energy-generating activities will range from 1368.10 × 106 m3 to 1370.62 × 106 m3, at the end of planning periods. Second, the electricity for water supply will range from 2164.07 × 106 kWh to 2167.65 × 106 kWh at the end of the planning periods, with a growth rate of 46.06–48.72%. Thirdly, lifecycle carbon dioxide emission (LCDE) is projected to range from 931.85 × 106 tons to 947.00 × 106 tons at the end of the planning periods. Wastewater and SO2, NOx, and particulate matter (PM) emissions are projected to be 42.72 × 103–43.45 × 103 tons, 183.07 × 103–186.23 × 103 tons, 712.38 × 103–724.73 × 103 tons, and 38.14 × 103–38.80 × 103 tons at the end of the planning periods. Fourthly, as the largest electricity-exporting city of China, Inner Mongolia’s electricity outflows will export 1435.78 × 106 m3 of virtual water to other regions, implying that Inner Mongolia is pumping its important water resource to support other regions’ electricity demands. Finally, high carbon mitigation levels can effectively optimize the electricity power mix, reduce consumption amounts of water and coal, and mitigate air pollutants, wastewater, and LCDE. The obtained results provide useful information for managers to develop a sustainability plan for the EWENS.

Highlights

  • Water, energy, and environment are inextricably interwoven in the complex social and economic networks

  • An AM-CT2FPM is developed through incorporating the autoregressive integrated moving average model prediction model (ARIMA) model, Monte Carlo simulation, chance-constrained programming (CCP), and type-2 fuzzy programming (T2FP) into one general framework, which is capable of effectively tackling the uncertainties shown as type-2 fuzzy sets and stochastic

  • The proposed model can overcome the shortage of traditional FMP and CCP methods; the ARIMA model is used to predict the electricity demands; and Monte Carlo is employed to simulate the probability distribution of electricity demands

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Summary

Introduction

Energy, and environment are inextricably interwoven in the complex social and economic networks. 90% of the energy activities in the world are water-intensive and used for processes such as cooling, steam generation, and desulfurization [1]. Energy is demanded for a series of water-related processes such as surface water extraction, groundwater pumping, water treatment, water distribution, and wastewater treatment [2]. Considerable carbon emissions and pollutants emitted from combustion of fossil fuels for providing water and energy supply, which cause severe environmental pollution and worsen global warming [4]. It is necessary to incorporate the environment into the analyses of the energy–water nexus, as well as exploring the interconnections between energy, water, and environment systems

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