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A simulation-based interval stochastic bi-level multi-objective programming (SISBLMOP) model was proposed in this research, through integrating the global nutrient export from watersheds model, interval parameter programming and stochastic chance-constrained programming into a general bi-level multi-objective programming framework. The SISBLMOP model can handle multiple uncertainties expressed as discrete intervals and probability density functions in both the simulation and optimization processes. System complexities, including the hierarchy structure of upper- and lower-level decision makers, can also be addressed in the model. The proposed model is applied to a real-world case study of the Xinfengjiang Reservoir Watershed in South China to identify the satisfactory implementation levels of multiple best management practices (BMPs). The model results show that multiple BMP schemes for water quality management can be obtained under different upper- and lower-level decision-making and risk-violation scenarios, reflecting the cooperation and gaming results of the two-level decision makers. Consequently, the corresponding BMP implementation costs are acceptable to both the upper- and lower-level decision makers. The model is widely applicable and can be effectively used for water quality management under multiple uncertainties and complexities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Graphical abstract Highlights • Structures of industrial sectors have significant impacts on energy intensity. • The energy intensity may be affected by uncertainties in industrial activities. • The randomness of energy intensity may lead to unexpected violation events. • Copula-based violation risk analysis can support decision-making in energy-intensity mitigation. Abstract An integrated approach was developed through incorporating a copula-based violation risk analysis into a programming model for optimizing industrial structures of urban clusters in uncertain conditions. Also, this approach can be used to support decision making about promoting advanced manufacturing sectors (AMSs) and mitigating industrial energy intensity. The advantages and the improvements of this approach lie in (a) reflecting the relationships between energy consumption and economic benefits in industrial sectors, and (b) incorporating the violation risk of the targets in energy-intensity mitigation into an optimizing model. A case study was conducted to illustrate the application of this approach in the Pearl River Delta of China, a highly urbanized area that includes the cities of Guangzhou, Shenzhen, Zhuhai, Dongguan, Huizhou, Zhaoqing, Foshan, and Jiangmen. The results indicated that under the desired industrial structures, violation risk of energy-intensity mitigation in the urban cluster of the Pearl River Delta would be indistinctive in the single-city perspective. Also, except Dongguan, Jiangmen and Zhaoqing, the cities of the urban cluster would achieve the goal for developing AMSs, based on the Industrial Plans for the 13th Five Year. [ABSTRACT FROM AUTHOR]

In this study, a hybrid approach was established to identify future heterogeneity of urban ecosystem health (UEH) transferred by variations of land-use, socio-economic development, and ecological function in lower scales of cities (i.e., districts), incorporating uncertainty analysis into a multi-criteria decision assessment framework. In consideration of multiple driving factors of UEH scores, the contribution of the main indicators to UEH scores was identified by geographical detector model. To verify effectiveness of the approach, a case study was applied in Dongguan City of China. The results indicated that UEH scores of Dongguan didn't greatly change during 2010–2020. Conversely, the scores would increase from 2023 to 2030, influenced by socio-economic development and ecological function under the district scale. Concurrently, the heterogeneity of urban ecosystem health ranks (UEHRs) in 32 districts occurred during 2010–2020, further influencing UEH scores of Dongguan. Owing to inconsistent of land-use, ecological function, and socio-economic development of districts, the heterogeneity of UEHRs was intensified in 2025–2030. From 2010 to 2020, the spatial variations of UEH scores in Dongguan City depended on the synergy of land-use intensity and economic growth. The joint influence from economic development, energy consumption and land-use patterns would contribute greatly to the variations of UEH scores in Dongguan City from 2023 to 2030. Thus, heterogeneity of UEHRs under district scale as well as promotion for sustainable economic development should be paid attention to by decision-makers, to identify internal characteristics in urban ecosystems. [ABSTRACT FROM AUTHOR]