Search

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]

• A systematic framework was proposed to assess urban flood resilience (UFR). • Each resilience phase (e.g., resistance, adaptation, & recovery) were considered. • The system framework incorporated hybrid flood model and system performance curve. Urban flooding can seriously threaten urban ecological security and human life, and therefore urban flood resilience (UFR) is important for urban safety and stability. To comprehensively evaluate urban system performance during the entire process of rainfall, runoff, flooding, and drainage, we developed a systematic framework for UFR assessment covering runoff simulation, flood estimation, and resilience assessment, which broadly corresponded to the phases of resistance, adaptation, and recovery. The UFR in the phases of resistance, adaptation, and recovery was simulated and assessed using a system performance curve (SPC) and technically combining with the hybrid flood model while mainly considering the total simulation time and inundated urban proportion in SPC. Because the extent of urban flooding can be influenced by climate change and the rate of urbanization, we chose the corresponding representative factors of precipitation and infiltration rate and considered 21 simulation scenarios (seven rainfall return periods and three infiltration rates) for which UFR was quantified according to urban system performance. The effectiveness of this framework was demonstrated in application to a typical highly urbanized area (i.e., Dongguan, China). The following results were derived: (1) The inundated area under the pessimistic scenario (i.e., S19) would be nearly four times greater than that under the optimistic scenario (i.e., S3); (2) The values of UFR in Dongguan were 0.9494–0.9863, locating at the high and very high level; (3) The lowest UFR value was 0.6552 in the Shuixiang New City district; and (4) The rainfall return period was the main factor influencing UFR under relatively short rainfall return periods (i.e., S1–S9), while infiltration rate was the principal influencing factor under relatively long rainfall return periods (i.e., S10–S21). The proposed systematic framework could be applied in other cities and large-scale regions like urban agglomerations and provinces. [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]

Highlights • A new evaluation framework of urban ecosystem health (UEH) is proposed. • UEH is evaluated from dimensions of structure, function, process and development. • The fuzzy matter-element model is established to evaluate the UEH states. • The health states of typical Chinese cities along the 'B & R' are assessed. • Suggestions are proposed to improve health states of different types of cities. Abstract As key social nodes and development engines, the status of various cities is important for the construction of "the Silk Road Economic Belt" and "21st Century Maritime Silk Road" (hereafter called the "B&R"). To comprehensively evaluate the status of cities along the B&R, the concept of urban ecosystem health was applied in this paper, and an innovative assessment framework of "structure-function-process-development" was proposed based on the understanding of the concept of urban ecosystem health. Then, four-layer assessment indicators were established to reflect the health status of urban ecosystems. Subsequently, a fuzzy matter-element model was constructed to measure the urban ecosystem health status, grade the health levels, and identify the limiting factors. A case study was conducted on 14 typical Chinese cities along the B&R. The temporal dynamics indicated that the health states of most of these cities gradually improved during the study period. With respect to spatial differences, city types could be ranked from high to low health in the order of coastal innovative and open cities, inland open cities, and open-window cities. Based on further analysis of limiting factors, suggestions to improve the ecosystem health levels of cities along the "B&R" were proposed for the different types of cities. [ABSTRACT FROM AUTHOR]

• A novel uncertainty analysis method of agricultural grey water footprint was proposed. • Impacts of production conditions on agricultural grey water footprint were reflected. • Interval characteristics of agricultural grey water footprint can be obtained. • The proposed method can help identify water pollution risk more accurately. Agricultural grey water footprint (GWF) is an important index for quantitatively describing the impact of agricultural production on water environment, which can help evaluate regional water pollution risk (WPR). However, changes in agricultural production conditions lead to strong uncertainties in agricultural GWF. Therefore, advanced methods to deal with these uncertainties for improving the accuracy of regional WPR assessment are required. By combining min–max/max-max programming models with a GWF assessment framework, an integrated uncertainty analysis method for agricultural GWF affected by production conditions was proposed in this study. Based on the method, extreme scenarios of GWF evaluation were established to obtain lower and upper bounds of agricultural GWF. The proposed method was applied in the Guangdong Province in South China, and the following results were obtained. Agricultural GWFs in the Guangdong Province were [124.67, 237.37], [110.63, 204.90], and [104.04, 178.01] Gm3 in 2005, 2010, and 2015, respectively. Different contributing factors of agricultural GWF were shown in the minimum and maximum GWF scenarios. For crop planting, the contribution of dryland and paddy fields to GWF was larger than that of garden land in the minimum GWF scenario, whereas the contribution of garden land was greatest in the maximum GWF scenario. For livestock and poultry breeding, the contribution of livestock raised under dry cleaning condition to the GWF was larger than that under flushing condition in the minimum GWF scenario, whereas the opposite situation was observed in the maximum GWF scenario. Based on the interval values of agricultural GWF, the WPR of the cities of Zhanjiang, Maoming, Yunfu, Chaozhou, Foshan, and Dongguan were identified as unacceptable. By identifying the uncertainties within agricultural GWF evaluation induced by the variability of production conditions, the proposed method can provide helpful information for agricultural planning in the context of sustainable agricultural development. [ABSTRACT FROM AUTHOR]

[Display omitted] • Patch complexity and urban compactness indexes were developed to assess urban form. • The impact of urban form on PM 2.5 was explored in GBA by spatial panel models. • The complexity of urban patches had a negative effect on PM 2.5 concentrations. • The impact of urban compactness on PM 2.5 concentrations was positive. • A more complex and less compact urban form was adoptable in terms of reducing PM 2.5. Given the serious threat of PM 2.5 pollution to the environment and public health in China, reducing PM 2.5 concentrations through urban planning practices has become a common interest of urban planners and policymakers. In this regard, identifying the relationship between urban form and PM 2.5 concentrations has been a matter of much concern. This paper seeks to investigate how urban form influences PM 2.5 concentrations by taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study. First, the urban form was assessed by two indicators, i.e., the patch complexity index (PCI) and urban compactness index (UCI), which were developed based on multiple landscape metrics and the principal component analysis. Then, the relationship between PM 2.5 concentrations and the two urban form indicators was revealed by spatial panel models. Our results mainly showed that PCI and UCI were negatively and positively associated with PM 2.5 concentrations, respectively, indicating that less compact urban forms with high patch complexity had advantages in reducing the PM 2.5 concentrations. According to these empirical results, the mixed-use urban development with high green coverage, which is conducive to constructing a more complex and less compact urban form, would be adoptable in terms of mitigating PM 2.5 concentrations in the GBA urban agglomeration. [ABSTRACT FROM AUTHOR]

• An integrated modeling approach is developed. • Multiple modeling methods were combined. • The approach is applied in a City Cluster of China. • Coordination for WEF and economy is analyzed under multiple scenarios. In this research, an integrated approach is developed through the incorporation of systems dynamics (SD), catastrophe progression (CP), and coupled coordination degree (CCD) analysis within a general modelling framework. The developed SD-CP-CCD is then employed to simulate and evaluate relationships among the water-energy-food (WEF) and the economic systems. It will improve traditional methods for WEF nexus analysis through a) incorporating urban WEF connections and changes into the cross-system coupling analysis framework, b) evaluating its coordination with economic growth and a multi-scale and regional disparity, and c) promoting policy recommendations to ensure the guarantee of urban WEF under economic growth. The approach is then verified through WEF nexus system of Urban Agglomerations of Pearl River Delta City Cluster (PRDCC) in China. Temporal and spatial characteristics of CCD in the region were analyzed. The results revealed their performance in cities with multiple economic backgrounds. Also, the fragile factors of each city were reflected by multi-scale exploration. Regional inequality and spatial agglomeration effects were considered. The results showed that CCD has noticeable temporal and spatial differences. Geographically, CCD varied from uncoordinated to high-level coordination. The eastern cities were much better coordinated than the western cities. Due to the increasing pressure of population and economic growth in the future, the upward trend of CCD would occur in most cities. The vulnerability factors of each city were explored. Simultaneously, apparent spatial inequality and agglomeration patterns were observed, with a downward trend over time. The temporal and spatial patterns of CCD revealed in this study indicated that PRDCC policymakers should formulate policies that suit the characteristics of cities and reduce the targeted regional imbalances. [ABSTRACT FROM AUTHOR]