Modeling urban eco-environmental sustainability under uncertainty: Interval double-sided chance-constrained programming with spatial analysis

Abstract

In this study, an interval double-sided chance-constrained programming (abbreviated as IDCP) method is developed for dealing with uncertainties expressed as interval values and double-sided randomness in both left- and right-hand sides of constraints. The method is applied to planning urban eco-environmental management of Shenzhen (China), where various eco-environmental indicators are used for ensuring ecological security. Through solving the IDCP-based urban eco-environmental management (abbreviated as IDCP-UEM) model, solutions for land-use pattern, industrial structure, system benefit, and ecosystem service value under different probability levels (i.e. p level) have been generated. Then, the conversion of land use and its effect at small regional extent (abbreviated as CLUE-S) model is used for analyzing the spatial characteristic of land-use pattern, which can further optimize the results from the IDCP-UEM model through providing the spatial allocation of land resources. Results reveal that (i) uncertainties existed in the urban ecosystem have significant impacts on system benefit and land-use pattern; (ii) at the end of the planning horizon, the area of forest land would be raised and the expansion of construction land would slow down; (iii) industries of electronic information and machinery manufacturing should be developed because they contribute higher benefit and discharge relatively less pollutant than other industries; (iv) system benefit would be raised and pollutant emissions (e.g., chemical oxygen demand, ammonia nitrogen, and solid waste) would be mitigated over the planning horizon. The findings are helpful for decision makers to gain insights into tradeoffs between eco-environmental protection and urban-economic development.