Planning energy economy and eco-environment nexus system under uncertainty: A copula-based stochastic multi-level programming method

Energy consumption, economic growth, and eco-environment protection of urban agglomeration is full of contradictions and continues to be challenges faced by decision makers. It is desired to develop effective methods to realize coordinated management of energy economy and eco-environment nexus (EEEN) system. In this study, a copula-based stochastic multi-level programming (CSMP) approach is first developed, where the conflicting objectives with multiple hierarchical levels and the uncertainty presented as random variables with different probability distributions can be tackled. CSMP can also reflect the complex interactions among random variables and examine the risk of violating joint-probabilistic constraints. The CSMP is then applied to planning EEEN system of Pearl River Delta (PRD) urban agglomeration (China) during the period of 2021–2035. Six scenarios based on joint and individual risk levels for violating energy consumption and GDP constraints are analyzed. Results reveal that the share of tertiary industry and high-tech industry would attain to 62.4% and 14.9% by 2035, the energy and CO2 intensity would decrease by 45.1% and 56.9%, and ecological land would expand to absorb more CO2, indicating that EEEN system would develop towards energy saving, economy and eco-environment friendly pattern. Results also disclose that decisions at high risk level would lead to high GDP, energy consumption and CO2 emissions, occupy ecological land and reduce CO2 absorption, and reduce the reliability of fulfilling system requirements.