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Conserving and restoring ecosystem services in urban areas is an efficient measure to deal with increasing ecological challenges for cities while enhancing urban ecological resilience. However, rising inequalities threaten to improve critical environmental justice, public health and urban ecological resilience. This study proposed a non-monetary framework for accounting for urban ecosystem services and explored the inequality of ecosystem services using the Gini coefficient. Further, a regression-based decomposition method was used to identify primary socioeconomic factors that contributed to inequality. The results showed that the total ecosystem service in the urban areas presented a trend of first growing rapidly and then fluctuating steadily from 6.78 × 1022 sej in 1985 to 1.14 × 1023 sej in 2020 the percentage of existing services in the total ecosystem services was over 50%. The Gini coefficient of 1985 was more extensive than that of other years, which is 0.461. The runoff regulation service and the temperature mitigation service were the primary contributors for the inequality. Meanwhile, such income per capita, nonfarm rate and industrial production provided over 70% contribution rate to the inequality. This study assessed the inequality of urban ecosystem services and analyzed the driving factors, emphasizing the importance of reducing inequality, and providing a specific reference basis and theoretical support for decision-makers in urban planning and development strategies. • Establishing a framework to calculate urban ecosystem services. • Analyzing the inequality of ecosystem service inequality. • Pointing out the contributions of the related ecosystem services to the inequality. • Identifying certain socioeconomic factors that are affecting the inequality and these contributions. [ABSTRACT FROM AUTHOR]

Due to frequent and serious waterlog and environmental pollution in cities in recent years, urban stormwater management (USM) has become an essential issue of urban sustainable development in China. Low Impact Development (LID) technologies are effective and popular measures of USM, and can be used to reduce urban waterlog and the associated environmental pollution. In this paper, in order to identify an optimal strategy of LID technologies based on economic efficiencies and environmental performances, the construction costs and environmental benefits of the four LID technologies (including grass swales, bioretention cells, green roofs, and permeable pavement) were analyzed. Then, due to the uncertain feature of rainfall, concentration of pollutants and many social-economic factors, an inexact fuzzy chance-constrained programming (IFCCP) model was developed. Multiple uncertainties that can be expressed as interval parameters, fuzzy sets, and stochastic distribution can be addressed effectively and incorporated directly into the modeling process. Based on the analysis of the precipitation probability distribution and land use data, the developed model was applied to a university campus with relatively high building density and plot ratio in Beijing. Then, optimal solutions of multiple precipitation probabilities ( p m ) under varying USM goals were obtained. The four LID technologies were chosen to meet multiple USM goals based on multiple p m values. When   p m = 0.1 , 0.05 , 0.02 and   0.015 , the total construction investments would be 1.46 to 4.66, 1.46 to 5.25, 2.31 to 8.54 and 3.95 to 12.7 million yuan, respectively. The relationship between construction costs and p m represented the relationship between economic benefit and system risk. The results indicated that USM was influenced by the rainfall capacity, construction costs would increase with the increase of precipitation, and the risks of constraint violation would decrease as the construction costs increase. When considering the four LID technologies during the planning stage of USM, the preferred selection order would be bioretention cells, permeable pavements, grass swales and green roofs. Therefore, the solutions under each p m level could provide the references for desired USM plans. [ABSTRACT FROM AUTHOR]

In this research, a hybrid nonlinear grey-prediction and quota allocation model (HNGP-QAM) was developed for supporting optimal planning of China's carbon intensity reduction at both departmental and provincial levels in 2020. At such dual levels, HNGP-QAM can not only help forecast carbon intensity and its fluctuations over the concerned period, but also facilitate the identification of China's carbon intensity reduction target in 2020 and the corresponding quotas for minimizing the total abatement cost. Two scenarios were developed based on multiple governmental policies and allocation schemes among provinces and departments. The results showed that the total abatement cost would be 92.07 and 98.93 × 10 9 , as well as 180.57 and 194.19 × 10 9 RMB (It is another shortname for China Yuan) for provincial and departmental allocation schemes under the reduction ratios of 40 and 45%, respectively. Furthermore, the west, the east, and the central China would be allocated the emission assignments that would be accounting for 48.53, 28.26, and 23.21% of the total national emission reduction, respectively. The obtained results were particularly useful for multi-level governments in providing information to identify the carbon intensity reduction target, conducting emission reduction assignments among provinces and departments, as well as supporting relevant policy-making. The results also suggested that the developed HNGP-QAM be applicable to similar engineering and planning problems. [ABSTRACT FROM AUTHOR]

Cities consume most of the global energy and account for approximately 75% of global CO 2 emissions. Moreover, resource-based cities tend to consume higher amounts of fossil fuel and produce higher carbon emissions than other cities, whereas there are still insufficiencies about energy carbon reduction in resource-based cities in developed urban agglomerations. Therefore, it is necessary to explore the energy planning of such cities to achieve carbon peaking and carbon neutrality, and this is crucial for achieving carbon neutrality in urban agglomerations. This study aims to apply a scenario-based analysis approach to a resource-based heavy industrial city in China, Tangshan, based on the Long-range Energy Alternative Planning model, to explore Tangshan's future energy consumption, generation, and associated carbon emissions from 2010 to 2050. The impacts of different energy policies are analyzed for the Tangshan energy system by considering four scenarios. Under each scenario, energy consumption increased steadily by 2050, but the growth rate is different. The business as usual scenario is the fastest, and the low-carbon scenario is the slowest. In the comprehensive and integrated low-carbon transition scenarios, CO 2 is expected to peak at 298.34 million tons (Mt) in 2028. The main industrial sectors of Tangshan with high output value, high energy consumption, and high carbon emissions include smelting and pressing of ferrous metals, petroleum processing and coking, raw chemical materials and chemical products, etc. Combining Tangshan's coal resource endowment, the development of renewable energy, and introducing advanced technology can effectively reduce carbon emissions and increase the diversity of energy supply. We analyzed the cost-benefit of the energy system and found that the implementation of carbon capture and storage technology could effectively reduce carbon emissions by 219.62 Mt and increased costs by 563.12 billion yuan. The research could provide a scientific basis for the medium and long-term energy sustainable transformation of resource-based cities, especially for resource-based cities in urban agglomerations. [ABSTRACT FROM AUTHOR]

Modern agriculture calls for efficient and environmental-friendly agricultural water and land management practice. Agricultural water and land utilization mode has a great impact on the amount of carbon emissions, and thus the aim of this work is to propose an optimal modeling approach for generating efficient agricultural water and land management alternatives and reducing carbon emission in agricultural water-energy-food nexus system. This study presents a novel approach consisting of carbon footprint lifecycle assessment method and bi-level multi-objective stochastic programming model. The proposed approach has contributions in following aspects: (1) the environmental impact of different resource allocation strategies can be measured in optimization (2) the spatial variability of spatial data (e.g., ET 0 and precipitation); can be fully reflected via remote sensing information; (3) tradeoffs among two decision-making levels and their conflicting objectives under randomness of surface water availability can be addressed. The proposed approach was applied to the middle reaches of the Heihe River basin, northwest China. After solving the proposed model, the optimal water and land use alternatives under different hydrological years can be generated. Decision makers can plan agricultural production strategy according to optimization schemes, and reduce carbon emission through increasing vegetable cultivation and surface water utilization. Furthermore, the performance comparison of different models indicated that fierce conflicts exist between income fairness and economic benefits. The comprehensive evaluation value of bi-level multi-objective stochastic programming model is 0.7036, which is highest among single- and multi-objective models, showing that such model has obvious advantage in dealing with multiple decision-making levels and conflicting objectives. This approach can help decision makers of similar regions manage the agricultural production system in a more efficient and environment-friendly way. [Display omitted] • Lifecycle assessment of carbon footprint was used for measuring environmental impacts. • Spatial data (e.g. ET 0 and precipitation) were collected and processed with the help of remote sensing information. • Vegetable cultivation increasing and groundwater use decreasing can help reduce carbon emission in agricultural production. • BLMOSP model has obvious advantage among single- and multi-objective models for addressing such problems. [ABSTRACT FROM AUTHOR]

The pursuit of the sustainable agriculture often ignores to consider the ecological benefits. To achieve this goal, it is necessary to evaluate the ecological impacts related to the sustainable development. Therefore, to assess the overall ecological impact of crop production in 31 provinces in China, this study proposes to set up a non-monetary framework and indicators based on Emergy theory. Further analysis focuses on sustainable ecosystem under three different planting scenarios to identify the driving factors. The results demonstrated that the ecosystem disservice of crop production processes is greater than the services. The total emergy inputs, fertilizers used and R%, all of these can affect the ecological benefits. Furthermore, simply changing the cultivation pattern cannot achieve a balance between ecology and economy, there is no doubt that other method needed are needed. These findings provide valuable insights for developing appropriate policies for decision makers. • Establishing a framework to calculate the agri-ecosystem services and dis-services. • Analyzing the ecological benefits of crop system in the three different scenarios. • Building three emergy-based ecosystem service indicators to assess the crop system. • Proposing some feasible advices from ecological benefits perspective. [ABSTRACT FROM AUTHOR]

Multiple correlated risks caused by uncertain information pose great challenges to the coordinated regulation of water-energy-food nexus (WEFN). In this study, a Copula-based radial interval chance-constrained programming (CRICP) was developed. CRICP can not only quantify composite risk induced by multiple risks with nonlinear correlations, but also tackle dual uncertainty expressed as redial intervals with adjustable protection levels. CRICP was applied to an irrigated agricultural management problem constrained by water, energy, and land resource in Bayan Nur City in northern China. Results indicate that system benefit would increase with the incline of composite risk or the decline of protection level. Monte Carlo simulation verified that the different definitions of composite risk could lead to significant differences in the combination of subsystem risks. The composite risk induced by the simultaneous shortage of multiple resources would have greater impacts on system benefits compared against composite risk caused by shortage of at least one resources, with an increase of [24.65%, 25.95%] in the minimum value of system benefits. Comparisons against two alternative models further verified that CRICP outweighs previous methods by modeling the correlation structure of multiple risks and tackling dual uncertainties without distribution information. • The complex interactions and inherent uncertainty affect the security of Water-Energy-Food Nexus. • A Copula-based radial interval chance-constrained programming method was developed. • It can tackle composite risk induced by random variables with unknown correlations. • It can also address dual uncertainties without detailed distributions. • The bias in decision making process triggered different composite risks were clarified. [ABSTRACT FROM AUTHOR]

Reservoir operation policies affect reservoir nitrogen (N) cycling and budgets through complex influences on physical and biogeochemical processes in water and sediment. However, the underlying influencing mechanisms, especially the impact of operations on sediment processes, remain unclear. This study combines a coupled hydrodynamic-eutrophication-sediment model and a reservoir operation model to clarify reservoir operation impact on N cycling processes in water and sediment as well as impact on stored and discharged water quality. Three typical reservoir operation policies (i.e., standard, hedging, and eco-friendly) were selected to create operation scenarios. The hydrodynamic-eutrophication-sediment model was used to simulate N cycling processes and N concentrations in stored and discharged water under each scenario. Using China's Danjiangkou Reservoir as a case study, results revealed that reservoir operation policies significantly affected spatiotemporal dynamics of N cycling processes and water quality. Specifically, reservoir sediment acted as a N source, contributing to annual net release of 9.5–16.1 Gg N. Higher water levels promoted sediment ammonium release through effects on reservoir submerged area and sediment temperature. Moreover, denitrification processes in water and sediment collectively contributed to annual N removal of 14.0–16.9 Gg N. Annual N removal was greater in the higher water level scenario despite its lower denitrification rate per unit area. Additionally, these processes and hydrodynamic conditions combine to affect N forms and concentrations. The N concentration in the lower water level scenario was generally higher, risking algal bloom outbreaks in the shallow-water zone. This study is intended to help guide reservoir operation policymaking to account for N management while also coordinating water quantity and quality targets. • Spatiotemporal dynamics in N cycling processes and water quality are assessed. • Higher storage levels can promote sediment ammonia release in deep reservoirs. • Denitrification in water and sediment significantly contributes to N removal. • Tradeoffs exist between the quantity and quality of water released to downstream. [ABSTRACT FROM AUTHOR]

Revealing the long-term development trajectory and peak scenarios of the urban residential building sector is crucial for formulating targeted emission reduction strategies and contributing to achieving the "Dual carbon" target. Given that, significant variables affecting carbon emissions from urban residential buildings (URBCE) at both macro and end-use building levels are identified in this study. Furthermore, an innovative dynamic simulation model is developed by integrating the Monte Carlo simulation model with the Kaya identity model, taking into account the uncertainties of the variables. Subsequently, the long-term evolution trajectories, potential emission peaks, and peak time of the URBCE close to 2060 in China's hot summer and cold winter (HSCW) zone are simulated. Results indicate that URBCE is expected to reach its peak of 272.43 Mt CO 2 in 2040 under the baseline scenario. Through the dynamic simulation, the probable peak time of energy consumption in the HSCW zone is 2044 (±1.85), with a peak of 145.42 (±6.91) Mtce, and the possible peak time of carbon emissions is probably 2039 (±1.60), with a peak of 271.93 (±13.40) Mt CO 2. According to dynamic sensitivity analysis, carbon emission factor, per capita residential space, and heating energy intensity can promote the peak size and timing. These findings lay a robust foundation for the formulation of regionally specific carbon reduction targets and initiatives. Dynamic simulation results of peaking time and peak value of URBEC and URBCE. [Display omitted] [ABSTRACT FROM AUTHOR]

Production, consumption, and disposal of plastics are associated with the generation of a large amount of greenhouse gas (GHG). Polyethylene terephthalate (PET) is one of the most widely used plastics, which is mainly produced and consumed by China and causing increasing concerns. The previous studies mainly focused on flows and stocks of PET. Detailed information on GHG emissions for the entire life cycle of PET in China is limited. Particularly, the key paths of emission reduction for life-cycle PET considering carbon neutrality are unknown. In this research, a network analysis system and model of GHG emissions were developed for PET in China and helping explore characteristics of GHG emissions over the three development periods of the PET industry. The results showed that the most potential stage of carbon neutrality for PET was the stage of PET production, accounting for approximately 74.9% over 2000 to 2018. The manufacturing process of PET fibers and bottles would have a major contribution to GHG emissions. At the same time, GHG emissions from the mechanical recovery process should not be ignored. The plastic restriction order for PET and the waste treatment ways of low-carbon would have a significant contribution to emission reduction. According to the results, this study identified the most potential key process of carbon neutrality in the PET life cycle and proposed policies to reduce GHG emissions, which would provide scientific support for the PET industry to achieve the goal of carbon neutrality in China. • A comprehensive model for quantifying GHG emissions in PET life-cycle is developed. • The P stage of PET (74.9%) is the main source of GHG emissions in 2000–2018. • The M process of PET fibers has a major contribution to GHG emissions in M stage. • The plastic limit order in China has a significant effect on reducing GHG emissions. [ABSTRACT FROM AUTHOR]

Water production, utilization and recycle in urban system associated with a large amount of energy consumption and carbon emission that has increasingly international attention under sustainable development goals. In this study, a comprehensive urban water resources system management model is proposed under water-energy-carbon nexus and multiple uncertainties. The water-energy-carbon nexus was reflected in the processes of water extraction, water production and sewage treatment, and two objectives of maximizing the system benefit and minimizing carbon emission is transformed into two linear programming problem through the dual-objective interval fractional programming. Considering the interaction among water supply/demand, pollutants discharge control, energy consumption and self-energy utilization, indirect carbon emission as the main constraints, the developed model is applied to a typical water and energy sources shortage area of Qingdao city in north China. Multiple scenarios related to energy consumption and carbon emission control are designed to search the relationship among energy consumption, carbon emission and water resources allocation schemes. The results indicated that water demand as the main driving factor of energy consumption and carbon emission in urban water system cannot be directly limited through water supply structure adjustment. Through introducing self-energy supply (sludge utilization) and energy consumption control, water resources allocation schemes and water supply structure would be changed to improve energy saving potential with an obvious decrease trend of carbon emission intensity from 0.7921 tCO 2 /MWh to 0.5544 tCO 2 /MWh. The model could effectively provide reasonable urban water system management strategies under different water allocation demands and carbon emission challenges scenarios and deal with multiple uncertainties in decision-making process. [Display omitted] • Urban water resources system brings ecological environment issues. • A comprehensive urban water resources system management model is proposed. • Maximizing the economic benefits of per carbon emission to obtain the scheme. • Sludge utilization and energy consumption control can reduce carbon emission. • The model provides experiences for water-scarce regions around the world. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems face serious degeneration risks from anthropogenic activities, among which land use heterogeneity transformation is one of the main threats on aquatic biodiversity. However, the mechanisms by which land use heterogeneity affects fish community structure in aquatic ecosystems are still difficult to determine. The results of this study showed that we detected a total of 164 fish species during two seasons, with 97 fish species belonging to 15 orders, 31 families and 74 genera in dry season and 138 fish species belonging to 14 orders, 40 families and 98 genera in wet season. The intergroup differences between the upstream, midstream and downstream of the basin in dry season were smaller than those in wet season, and the species richness in wet season were higher than this in dry season. The values of β-diversity between the upstream and midstream regions was greater than downstream in dry season. The value of β-diversity between upstream and downstream regions was larger than in the midstream in wet season. It concluded that the β-diversity values were generally smaller in wet season than in dry season. Land use types on both sides of the Han River basin are mostly cropland, forest land and man-made surfaces. The results of calculating LUI and fish life history characteristics showed a greater correlation between K and M values in the dry water period and a greater correlation between PD50 and longevity in the rich water period. Moreover, we calculated the correlation between the land use index (LUI) and β-diversity NMDS values, respectively, showed a significant positive correlationship (0.712 in dry season; 0.742 in wet season). This research (a) obtained the spatial and temporal distribution of α-diversity and β-diversity data of fish in the whole basin using eDNA technology; (b) analyzed the relationship of land use heterogeneity on fish life history characteristics; and (c) revealed the correlation between land use index and β-diversity communities. Overall, this study can provide data support and theoretical basis for integrated watershed ecosystem management, and provide suggestions for environmental protection and management around the watershed. • obtained the spatial and temporal distribution of fish diversity data based on eDNA technology for the whole basin. • analyzed the relationship of land use heterogeneity on fish life history characteristics. • revealed the correlation between land use index and diversity communities. [ABSTRACT FROM AUTHOR]

High flow events (including both the high flow pulses and floods) exert many critical ecological functions in riverine ecosystems and their elimination will lead to severe ecological degradation. However, common hydropower operations are only required to legally maintain the minimum environmental flows (e-flows). The extra release of high flow events will result in revenue loss of hydropower producers. In this research, we propose an approach to assessing the eco-compensation standard which is necessary to compensate the loss of hydropower producers and promote the release of high flows to downstream rivers. The scenario tree approach is adopted for the generation of possible scenarios of flows and electricity prices to deal with the uncertainties of the two factors in deregulated electricity markets. A stochastic linear programming method is proposed to determine the maximum mean annual revenues under two e-flow provision scenarios, i.e., only sustaining the minimum e-flows (scenario 1) and sustaining both the minimum e-flows and a specified number of high flow events (scenario 2). The revenue difference under the two e-flow scenarios is set as the eco-compensation standard. A case study in the Wangkuai reservoir, China, demonstrates that the eco-compensation standard is obviously influenced by the installed hydropower generation capacity (IHGC) and the number of high flow events planned to be released. Moreover, the greatest standards may be not corresponding to a very large IHGC. [ABSTRACT FROM AUTHOR]

The problem of fresh water scarcity is one of the major constraints for regional development. Rapid urbanization and rising economic prosperity has further exacerbated problems with not only water quantity, but also water quality. Hence, sustainable utilization of water resources should be a priority, especially in water stressed areas. However, most current studies on optimal water allocation models are based on physical water, which cannot fully reveal the water flows embedded in imported and exported raw materials and products throughout all production processes. Thus, they fail to achieve sustainability goals. Therefore, the objective of this study was to set up an optimal water allocation model for industrial sectors based on water footprint accounting. In this paper, first the internal and external blue and gray water footprints were evaluated. The results indicated that the external water footprint was the major contributor to Dalian's water footprint, which shared around 72.58% of the total. Among all the industrial sectors, the chemical industry and chemical production sector had the highest total WF. Second, analyses of water productivity intensity of the WF and physical water for the industrial sectors were conducted. The comparison of the results revealed that physical water productivity intensity failed to explain the embedded water inflows in the production processes among the regions and sectors. Third, an optimization model based on the water footprint accounting results was thus set up. The optimal consequences indicated that a water allocation plan could meet both the water requirements for the blue and gray water footprints of the industrial sectors, and their target output goals as well. Therefore, this optimal allocation model is both rational and applicable for sustainable water utilization in future water management strategy formulations. [ABSTRACT FROM AUTHOR]

Approximately half of the global population resides in cities and accounts for over 80% of global carbon emissions. To improve efficiency in carbon emission reduction, and enhance adaptability of cities to climate change, it is essential to undertake accounting of urban carbon cycle. This plays a prominent role in global carbon cycle. An integrated accounting framework for urban carbon cycle was established herein to support uniform accounting and place-specific comparisons, covering natural and artificial carbon cycles, vertical and horizontal carbon flows, carbon storage and fluxes, and carbon inputs and outputs. Guangyuan, a mountainous city in China that was seriously stricken by Wenchuan earthquake in 2008, was chosen as the case to demonstrate the framework and investigate the effects of post-earthquake reconstruction on carbon cycle. The results show: 1) the proposed framework could effectively assess dynamics of carbon cycle under external disturbances, 2) there were abundant vegetation and correspondingly a large natural carbon tank and vertical carbon input, and low industrialization degree and correspondingly small horizontal and vertical carbon outputs in Guangyuan, 3) the post-earthquake reconstruction led to a series of impacts on carbon cycle, from both aspects of amount and structure, and 4) such impacts of post-earthquake construction on artificial carbon cycle were distinct with a tendency toward low-carbon development in Guangyuan. The results were helpful for investigating the effects of natural disturbance and human interference on urban carbon cycle, which in turn could improve the adaptation to climate change. [ABSTRACT FROM AUTHOR]

The intensification of heat stress in a changing climate poses great threats to both human health and labor productivity. It is of great practical importance to assess the impacts of climate-induced heat stress on labor productivity and to develop effective adaptation strategies. In this paper, an integrated optimization-based productivity restoration modeling framework is proposed for the first time to develop the optimal policies for adaptation to climate change. To address underlying uncertainties associated with climate and labor management systems, we take into account ensemble projections from five global climate models (GCMs) under two Representative Concentration Pathways (RCP2.6 and RCP8.5) and inexact system costs. The system costs, including direct and indirect costs such as management costs, energy costs, and labor costs, are presented as interval numbers due to inherent uncertainty caused by population growth, technology development, and other social-economic factors. Uncertain information can be effectively communicated into the optimization processes in this study to generate optimal and reliable decision alternatives. We find that the increased Wet-Bulb Globe Temperature (WBGT) will lead to a large reduction in labor capacities over China except for the Tibetan Plateau under both RCPs by the end of the 21st century. The less developed regions tend to achieve the minimum system cost by having labor productivity recovered through working overtime due to the relatively low cost of overtime. This could result in more heat-related work injuries in the less developed regions. Since the less developed regions are not heat-prone areas in China, the changing climate would be a more dangerous threat and cause more damages to these regions where the residents are less acclimatized to heat stress. Moreover, we obtain a range of minimum system costs from 1.86 to 8.97 billion dollars under RCP2.6 and from 9.42 to 32.31 billion dollars under RCP8.5 (about 0.2% of China's GDP in 2019, 0.01% of China's GDP projected in 2100 under a sustainable socio-economic development scenario) for the restoration of labor productivity in a warming climate. We argue that urgent actions are needed to mitigate global warming impacts on labor productivity. • An integrated optimization modeling framework is developed to achieve optimal labor productivity restoration in a warming climate. • Various uncertainties are addressed through ensemble climate projections and interval programming models. • Intensification of heat stress leads to a large decrease in labor capacity over China except for the Tibetan Plateau. • More losses in working hours are projected for moderate labor activities compared to light and heavy labor activities. • Less developed regions tend to have more working hours recovered by working overtime than air conditioning. [ABSTRACT FROM AUTHOR]

As the basis of urban social-economic development, water and energy resources are indivisible and interrelated in the production and consumption activities of cities. The frequent intercity trade of energy-related goods aggravates water withdrawal in neighboring cities and causes the spatial transfer of resources. The spatial correlation of water withdrawal and energy consumption is rarely considered in the city-level water-energy nexus. As one of China's most serious water shortage regions, Hebei Province is the third-largest energy consumer in China and is a major supplier of mineral resources, industrial raw materials, water resources, electricity, and agricultural products to Beijing and Tianjin. The spatial Durbin model with the two-way fixed effects is applied to explore spatial effects of water-energy nexus in cities of Heibei province. Seven influencing factors, including energy consumption, energy structure, population, GDP, water withdrawal intensity, urbanization, and agriculture structure were considered. Results showed that all factors had positive impacts on water withdrawal except energy structure. Water withdrawal intensity made the most considerable contribution to water withdrawal, followed by urbanization, energy consumption, GDP, industrial structure, and population. The urbanization level of neighboring cities exerted the most significant positive spatial spillover impact on local water withdrawal, whereas the energy consumption showed a negative impact. The exploration of city-level spatial correlation regarding water withdrawal and energy consumption provides a reference for regional cooperation to improve resource utilization efficiency, establishing sustainable energy and water systems, and promoting sustainable development. [ABSTRACT FROM AUTHOR]

This paper develops an interval multi-stage robust programming model for regional low-carbon electric power system planning with energy-water nexus. The model integrates interval programming and multi-stage stochastic programming to handle uncertainties with different probability distribution information. In addition, under the framework of robust programming, the optimal solutions could provide tradeoff information between system cost and decision maker's risk preference. The hybrid programming method is tailored for a case study of Shandong Province, China to validate its applicability and provide useful managerial insights, where energy-water interactions are gain great concerns. The model helps to make robust strategies associated with risk control for capacity expansion, carbon capture and storage (CCS) technology retrofitting, power generation, imported electricity, and water allocation for electricity generation, with the goal of minimizing total cost. Besides, considering the variation of water resource conditions and environmental policies under climate change, the impacts of water resource availability and carbon emission caps on regional electric power system planning are explored and discussed. It is found that stricter carbon emission cap policy would facilitate the investment on CCS devices but have little impact on the installed capacity structure, meanwhile it would increase water consumption per power generation. However, scarcer water resource situation would promote the development of renewable energy generation, and limit the investment on CCS technology. • Low-carbon power system management optimization with energy-water nexus under uncertainties. • Impact analysis of various water resource availability and carbon emission cap on optimal strategies. • Useful managerial insights on energy system planning from energy-water nexus perspective. • Robust solutions with risk-cost tradeoff information to reflect different risk preferences. [ABSTRACT FROM AUTHOR]