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Carbon-reduction policy affects socio-economy and Water-Energy-Food (WEF) nexus contained therein. Existing studies concentrated on policy performances on resource consumption, but cannot quantify the impacts on resource utilization efficiency. To fulfill such gap, this study developed an integrated evaluation method through integrating computable general equilibrium model with data envelopment analysis to explore the impact of carbon tax on WEF environmental efficiency of China. Results show that increasing carbon taxes would improve the energy structure and reduce carbon emissions. While the increased cost of fossil fuels would have negative but limited impacts on economic output of water supply and food sectors through economic activity connections. Synergistic effect of WEF resource conservation could be observed in most production sectors, expect for clean energy sectors. Carbon tax would improve the WEF environmental efficiency expressed as the trade-offs between economic and carbon emission outputs and WEF resource inputs. There are significant differences in WEF efficiency and its growth rate among production sectors, with food sectors experiencing the most significant improvement in WEF efficiency at a carbon tax of 70 yuan/ton. The evaluation results raised the awareness of the performance of carbon tax on WEF nexus and provide a new perspective for promoting WEF nexus efficiency. • An integrated evaluation approach is developed with the combination of CGE and DEA models. • This method can assess the impacts of carbon tax policy on WEF environmental efficiency. • Carbon tax improves energy structure, but negatively affects water and food sectors' economic output. • Synergistic effects of WEF resource conservation exist in most production sectors. • Carbon tax would improve both the national and the sectoral WEF environmental efficiency. [ABSTRACT FROM AUTHOR]

Water scarcity and water pollution are essential factors limiting coordinated regional development, especially in water-deprived regions. Industrial restructuring is an effective water management solution to alleviate water scarcity and mitigate water pollution. However, due to widely existing inexact parameter information in the water resource management system, it is challenging to allocate water resources among industrial sectors. To address these problems, an export coefficient coupled with a two-stage stochastic robust programming method (EC-TSRP) was developed through integrating an export coefficient model (ECM), two-stage stochastic programming (TSP) and robust optimization. The proposed EC-TSRP model could effectively deal with the multiple uncertainties expressed as stochastic and the intervals with fluctuation ranges, and enhance the robustness of optimal plans for supporting water resource allocation among industrial sectors under complex uncertainties. It was then applied to Bayan Nur City, in arid north-west China. The optimization alternatives indicate that wheat, sheep and services would be the most sensitive sectors among all industrial sectors, when non-point source (NPS) pollution exports are restricted. In addition, comparing the EC-TSRP results with the deterministic model, the reliability of the system could be improved significantly, while the value of the objective function would be decreased slightly. The simulation results were also compared with the historical data from 2012 to 2016. Although the total revenue of Bayan Nur City would decrease by 1.52%, the pollutant loads of total nitrogen, total phosphorus and chemical oxygen demand (TN, TP and COD) would decrease by 14.5%, 7.75% and 2.07%, respectively, and total water allocation also would decrease from 4.6 billion m3 to 4.23 billion m3. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID‐19) has spread around the world and requires effective control measures. Like the human‐to‐human transmission of the severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2), the distribution of COVID‐19 was driven by population flow and required emergency response measures to slow down its spread and degrade the epidemic risk. The local epidemic risk of COVID‐19 is a combination of emergency response measures and population flow. Because of the spatial heterogeneity, the different impacts of coupled emergency responses and population flow on the COVID‐19 epidemic during the outbreak period and a control period are unclear. We examined and compared the impact of emergency response measures and population flow on China's epidemic risk after the Wuhan lockdown during the outbreak period and a control period. We found that the population flow out of Wuhan had a long‐term impact on the epidemic's spread. In the outbreak period, a large population flow out of Wuhan led to nationwide migration mobility, which directly increased the epidemic in each province. Meanwhile, quick emergency responses mitigated the spread. Although low population flow to provinces far from Hubei delayed the outbreak in those provinces, relatively delayed emergency response increased the epidemic in the control period. Consequently, due to the strong transmission ability of the SARS‐CoV‐2 virus, no region correctly estimated the epidemic, and the relaxed emergency response raised the epidemic risks in the context of the outbreak. Key Points: Population outflow from Wuhan had a long‐term impact on the spread of COVID‐19Areas with low population inflow lacked awareness of prevention, started emergency response later, and failed to prevent the COVID‐19 caused by population mobilityThe degree to which population mobility and emergency measures affected the development of the epidemic exists spatial heterogeneity in China [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]

Tartary buckwheat (Fagopyrum tataricum) not only provides a supplement to primary grain crops in China but also has high medicinal value, by virtue of its rich content of flavonoids possessing antioxidant, anti‐inflammatory, and anticancer properties. Light is an important environmental factor that can regulate the synthesis of plant secondary metabolites. In this study, we treated tartary buckwheat seedlings with different wavelengths of light and found that red and blue light could increase the content of flavonoids and the expression of genes involved in flavonoid synthesis pathways. Through coexpression analysis, we identified a new MYB transcription factor (FtMYB116) that can be induced by red and blue light. Yeast one‐hybrid assays and an electrophoretic mobility shift assay showed that FtMYB116 binds directly to the promoter region of flavonoid‐3′‐hydroxylase (F3'H), and a transient luciferase activity assay indicated that FtMYB116 can induce F3'H expression. After transforming FtMYB116 into the hairy roots of tartary buckwheat, we observed significant increases in the content of rutin and quercetin. Collectively, our results indicate that red and blue light promote an increase in flavonoid content in tartary buckwheat seedlings; we also identified a new MYB transcription factor, FtMYB116, that promotes the accumulation of rutin via direct activation of F3′H expression. We revealed that red and blue light promote flavonoid production and the expression of genes involved in flavonoid synthesis pathways in tartary buckwheat. We also identified a new MYB transcription factor, FtMYB116, that promotes rutin accumulation via direct activation of the expression of F3′H. [ABSTRACT FROM AUTHOR]

Water rights transfer is significantly required for alleviating the ever-intensive water crisis, particularly for arid watersheds with abundant farmland and fossil fuels. However, focusing solely on the re-allocation of water rights and disregarding agricultural water saving potential imperil the security of Water-Energy-Food (WEF) nexus. Furthermore, randomness in water availability leads to water shortage risks and subsequent impact on the whole system. In this study, a risk-based optimization model (RWEF) was proposed to promote inter-sectoral water rights transfer through encouraging energy sector to invest in agricultural water-saving works and get paid back in water rights. Chance-constrained programming is incorporated to analyze the trade-offs between system benefits and water-shortage risks. The developed model was applied to the Inner Mongolia section of the Yellow River Basin, China to verify its effectiveness, considering different development levels of food and energy industries. Results indicated that 488 million m3 of water could be transformed from agriculture to energy, without compromising agricultural production. The main recipients of transferred water rights would be traditional coal-based industries, while it would be difficult for thermal power and most modern coal chemical industries to participate. The construction of water-saving works would help safeguard agricultural production under risks. Compared against two alternative models without water rights transfer mechanism, the average benefit acquired from RWEF under varied water-shortage risks would be at least 68% higher. Particularly, when confronted with extreme water-shortage risk and increased production demands, RWEF would still be able to support agricultural and energy production, while the alternative models being incapable. • RWEF model is developed for investigating trans-sector water rights transfer under water-shortage risks. • Energy sector invests in agricultural water-saving works and get paid back in water rights. • Energy expansion plans with transferred water rights and cropping patterns with water-saving works are optimized. • RWEF synergistically promotes the benefits of agriculture and energy sectors. [ABSTRACT FROM AUTHOR]

Growing demands for water, energy, and food put many systems at a composite risk of resource shortages. There was a lack of approaches capable of effectively assessing tridimensional composite risk and describing non-linear correlations among subsystem risks within a Water-Energy-Food (WEF) nexus system. In this study, an integrated approach was developed to assess the composite risk of WEF nexus systems and generate risk-based plans. Specifically, a composite risk assessment model that could capture the interdependence among the risk for water, energy, and food shortage was proposed. Furthermore, a generalized Copula-based chance-constrained programming model and its solving algorithm were developed. The proposed approach has been applied to an agricultural WEF nexus system in northern China, where the shortage of water, energy and / or land affected agricultural outputs. Results show that the composite risk of the entire system would be higher than the maximum value among subsystem risks, but less than their sum. Higher composite risks could bring higher benefits. Under a certain composite risk, the overall system benefit would vary with different combinations of subsystem risks; and it could be promoted through coordinating resources supplied by different subsystems. A risk - benefit frontier consisting of optimal solutions corresponding to different combinations of composite and subsystem risks was identified through Monte Carlo simulation. The scheme that could generate 12.76 billion Yuan under a moderate composite risk level of 0.22 was recommended for the study problem. Accordingly, net irrigation water, energy for agriculture, and effective irrigation area should be no less than 1.66 × 109 m3, 81.08 × 103 tce, and 509.12 × 103 hm2, respectively. • A novel risk management approach was proposed under Water-Energy-Food nexus. • It can assess composite risk induced by random input resources. • Composite risk-based planning schemes are provided. • System benefits are promoted through coordinating the supply of multiple resources. [ABSTRACT FROM AUTHOR]

Energy and water resources are closely linked in electric power systems, and the application of low-carbon technologies further affects electricity generation and water consumption in those systems. The holistic optimization of electric power systems, including generation and decarbonization processes, is necessary. Few studies have considered the uncertainty associated with the application of low-carbon technologies in electric power systems optimization from an energy-water nexus perspective. To fill such a gap, this study developed a simulation-based low-carbon energy structure optimization model to address the uncertainty in power systems with low-carbon technologies and generate electricity generation plans. Specifically, LMDI, STIRPAT and grey model were integrated to simulate the carbon emissions from the electric power systems under different socio-economic development levels. Furthermore, a copula-based chance-constrained interval mixed-integer programming model was proposed to quantify the energy-water nexus as the joint violation risk and generate risk-based low-carbon generation schemes. The model was applied to support the management of electric power systems in the Pearl River Delta of China. Results indicate that, the optimized plans could mitigate CO 2 emission by up to 37.93% over 15 years. Under all scenarios, more low-carbon power conversion facilities would be established. The application of carbon capture and storage would increase energy and water consumption by up to [0.24, 7.35] × 106 tce and [0.16, 1.12] × 108 m3, respectively. The optimization of the energy structure based on energy-water joint violation risk could reduce the water utilization rate and the carbon emission rate by up to 0.38 m3/104 kWh and 0.04 ton-CO 2 /104 kWh, respectively. • A simulation-based inexact optimization model for power systems planning. • A low-carbon electric power system was optimized under uncertainty. • CO 2 emissions under different socio-economic development levels were simulated. • The scale of generation facilities was optimized under different risk combinations. [ABSTRACT FROM AUTHOR]

• A Copula-based interval two-stage stochastic mixed-integer programming was built. • It may provide optimal resource allocation plan for agricultural irrigation system. • It can quantify water-energy joint risks in food production. • The application of water-saving irrigation for irrigation system are considered. The interactive water-energy relationship is a major restriction on food production in agricultural irrigation systems. Applying water-saving irrigation systems can further intensify the interrelationship between water and electricity and trigger a water-energy joint risk. Currently, there are no approaches capable of effectively assessing the various uncertainties and water-energy joint risks in irrigation districts. In this study, a novel mathematical programming method termed copula-based interval two-stage stochastic mixed-integer programming (CITSMIP) is proposed. CITSMIP quantifies water-energy joint risks in food production and provides an optimal resource allocation plan and water-saving irrigation application schemes under different joint risk levels. CITSMIP was applied to solve an irrigation resource management problem in northwest China. The results show that under a certain water-energy joint risk, planting sunflowers would be the first choice for water-saving irrigation applications. As water-saving applications have become increasingly common over time, the water-saving volume is expected to increase to [74.65, 84.46] × 107 m3 by 2035. Moreover, under a certain joint risk, compared with the water risk, fluctuations in energy risk would have a greater impact on the total benefit of the system and the total consumption of resources. Compared with single water risk or energy risk management, the joint risk management results would have a lower degree of uncertainty and higher lower-bound benefits. Establishing CITSMIP can provide valuable insights into informing stakeholders to allocate resources and maximize benefits under water-energy joint risk. [ABSTRACT FROM AUTHOR]

Predicting the impacts of water management policies under uncertainty can support policy-makers in making sound decisions. Most previous methods for policy-impact simulation lacked a calibration process that would allow model results to match observed values, and did not address the inherent uncertainties. To fill this methodological knowledge gap, an interval credibility-constrained positive mathematical programming (ICPMP) approach was first developed in this study for simulating the impacts of water management policies. This method improved over traditional positive mathematical programming in terms of uncertainty treatment. It also improved upon inexact programming methods through activating a calibration process. ICPMP was then coupled with a multi-attribute decision-making approach, leading to a simulation-evaluation method that could support the analysis and screening of policy alternatives. This method has been applied to an agricultural water management problem in northwestern China. Various policy alternatives corresponding to different water prices and varied fuzzy credibility levels of water availability were investigated. The impacts of these alternatives over farmers' income, irrigation water consumption, benefit per cubic meter of water, planting area, and fertilizer use were simulated through ICPMP. Forty policy alternatives with better indicator performances were selected to be comprehensively evaluated using the multi-attribute decision-making approach. The results indicated that when the decision-makers have a positive preference for water availability, the water price at the turning point of water use efficiency (i.e. benefit per cubic of water) was recommended. When decision-makers have conservative attitude towards water availability, it was recommended to keep the water price unchanged. Comparisons of ICPMP against traditional methods indicated that, ICPMP could generate more reliable results through incorporating uncertain information as inputs and reproducing actual situation. As well, solutions of ICPMP could provide in-depth analysis of the trade-offs between violation risk and system benefits. ICPMP and the associated simulation-evaluation method are also applicable to analyze other types of policies. • A novel ICPMP method was proposed to simulate the impacts of water management policies under uncertainty. • ICPMP could enhance accuracy of simulated results through calibrating to actual planting area and addressing input uncertainty. • ICPMP was coupled with an evaluation model to determine agricultural water pricing policies. • The full name of ICPMP is interval credibility-constrained positive mathematical programming. [ABSTRACT FROM AUTHOR]

In arid and semi-arid regions, improper irrigation activities not only exacerbate water shortages, but also lead to environmental pollution such as soil salinization that hinders crop growth and agricultural sustainability. There has been a lack of agricultural water management tools that could support agricultural water management with salinization-related grey water footprints being considered and associated uncertainties being addressed. In this study, salinization-related grey water footprints were measured through accounting for relationships among irrigation, soil salinity, evapotranspiration and crop yield, and then incorporated into an agricultural water management model for supporting environmentally sound irrigation decisions. Such an agricultural water management model was also characterized by a newly proposed generalized fuzzy interval fractional programming (GFIFP) method that could address ratio problems of two objectives and dual uncertainties. The developed methodology coupling the GFIFP method and grey water footprints was applied to an irrigation region in northwestern China where water scarcity and soil salinization hindered local development. Five credibility levels corresponding to decision makers' varied satisfactory degrees over water availability, and nine weight coefficients of possibility and necessity measures were considered. Results showed that, in order to reduce negative environmental impacts while increasing economic benefits, more irrigation water should be allocated to wheat and sunflower rather than corn. When the credibility level is 0.5 and weight coefficient is 0.9, the system efficiency would be the highest. Compared to the benchmark year of 2018, this scenario would generate [0.330, 6.647] billion yuan more benefits and [16.0, 133.9] million m3 less grey water footprints. Compared to three conventional approaches, GFIFP could provide decisions with more flexibility and less environmental impacts. The developed approach could also be applied to agricultural water management problems in other areas aiming at reducing grey water footprints and enhancing environmental benefits under uncertainty. • Grey water footprint was used to quantify negative environmental impacts related to soil salinization. • Grey water footprint related to soil salinization was integrated into a GFIFP method. • GFIFP was applied to agricultural water management in an arid and salinized area. • Economic benefits from unit grey water footprint were increased under different credibility levels and weight coefficients. [ABSTRACT FROM AUTHOR]

In arid and semi-arid regions, there exist great potential for supplementing irrigation water with brackish water desalinated by clean energies. Determining technology portfolio is essential for the establishment of clean energy-driven desalination-irrigation (CEDI) systems, requiring multi-criteria group decision-making. Unfortunately, few existing methods were capable of assessing such a complex problem that involves multiple technologies and uncertainties. During multi-criteria group decision-making, uncertainty arising from linguistic information and varying confidence in estimation is usually available as interval-valued intuitionistic fuzzy sets (IVIFSs). Previous studies relied on the direct provision of IVIFSs by experts, which made them inapplicable in real-world problems because experts' understanding over IVIFSs might be limited and inconsistent. Therefore, an easy-to-operate method for collection and conversion of IVIFSs was proposed in this study to avoid misunderstanding and facilitate realistic reflection of expert judgements. Duplex rating sets (DRSs) were proposed to express uncertain estimates and the associated confidence levels, and transformation equations were established to convert DRSs into IVIFSs. Based on the introduction of DRSs and transformation equations, an entropy-weighted TOPSIS approach with IVIFSs information was then developed. The developed method was then applied to northwest China for supporting the assessment of CEDI technology portfolios. The most desirable portfolio was screened out under the criteria of agriculture, ecology, economy, and system performance. Moreover, results of sensitivity analysis showed that the selected portfolio would perform the best in twelve of the total twenty scenarios. Without loss of generality, the developed method is also applicable for other decision-making problems involving multiple criteria, stakeholders and uncertainties. • Duplex rating sets were proposed to collect experts' estimates and corresponding confidence levels. • An entropy-weighted TOPSIS method with interval-valued intuitionistic fuzzy information was established. • A clean energy-driven desalination-irrigation system was constructed under food-energy-water nexus. • The best technology portfolio was selected. [ABSTRACT FROM AUTHOR]

China has pledged to strictly maintain wetland ecosystem services at the COP 14 of the Ramsar Convention on Wetlands that was recently held in Wuhan, highlighting the necessity of measuring wetland ecosystem service value (ESV) in China. Yet existing studies mainly focus on ecosystem service valuation of wetlands from the consumer side, while a donor-side evaluation of the temporal-spatial characteristics of the wetland ESV of China is lacking. This study introduces the thermodynamic concept of cosmic exergy into the evaluation of wetland ESV, which provides an objective evaluation index for the unified measurement and analysis of the ecological value and degradation of resources in the process of material, energy, and information transformation of the ecosystem. By constructing a cosmic-exergy-based accounting framework for wetland ecosystem valuation, this study comprehensively investigated the temporal-spatial variations of China's wetland ESV during 1990–2020 from the donor side. Results showed that from 1990 to 2020, the total wetland ESV in China first decreased and then increased notably, with an overall growth rate of 22%. Meanwhile, the ecological quality of wetlands, as indicated by cosmic exergy intensity, showed an upward trend in the middle and lower reaches of the Yangtze River Basin, but a downward trend in western China. Regions in the Yangtze River Basin, the Qinghai-Tibet Plateau, and Northeast China were demonstrated as the major contributors to the total wetland ESV. In addition, this study identified the vital role of marsh wetlands in ecosystem service supply, contributing nearly 30% to the total ESV, and microclimate regulation was the most prominent service type, accounting for up to 74%. The outcome of this study can offer a new biophysical perspective for the donor-side valuation of wetland ecosystem services and may provide a benchmark reference for policymakers to formulate supporting measures for wetland production and restoration. [Display omitted] • A donor-side evaluation of China's wetland ESV during 1990–2020 is conducted. • China's wetland ecosystem service value has increased by 22% during 1990–2020. • Wetlands' quality trends upward in the Yangtze River but downward in West China. • Marshes as the top contributor account for about 30% of China's wetland ESV. • Microclimate regulation is the most prominent service, contributing 74% of total ESV. [ABSTRACT FROM AUTHOR]

A critical step in water management policy development is the analysis of its socio-economic and environmental implications. However, few methods could proactively and reliably predict and assess the impacts of policies while handling the inherent uncertainty. To fill such a gap, an inexact simulation-evaluation method was developed for analyzing the impacts of multiple water management policies under uncertainty. The interval positive mathematical programming (IPMP) method was proposed as the simulation tool by coupling interval programming with positive mathematical programming (PMP). The evaluation tool was developed by combining the interval TOPSIS method and the interval maximum deviation method. This simulation-evaluation method can directly communicate a policy's simulation outcomes into the evaluation process while addressing the uncertainties in both simulation and evaluation. The proposed method can also reproduce the actual situation with a calibration process, which enables accurate and smooth responses to policy changes. This approach was used for agricultural water management in arid north-west China. Seventy-five policy alternatives generated from three groundwater allocation limits and twenty-five differential water pricing levels were investigated. The impacts of these alternatives on farmer income, farmer employment, water consumption, planting areas, and fertilizer use were simulated using IPMP. Twenty-four non-inferior alternatives were selected and further evaluated with multi-dimensional criteria. The final results showed that, the water price for grain crops with traditional irrigation methods should rise by 60%, those for cash crops with drip irrigation should decrease by 60%, and the groundwater quota should be reduced by 20%. Compared with traditional models, IPMP can increase simulation accuracy by reproducing observed situations, enhance robustness by reflecting input uncertainty, and improve flexibility in decision-making by providing interval solutions. The inexact simulation-evaluation model can also be widely used to analyze other policies. • An inexact simulation-evaluation method was developed to analyze water policies under uncertainty. • Simulation accuracy could be improved by calibration and uncertainty treatment. • Uncertain policy impacts could be communicated to the evaluation model. • Optimal water pricing and groundwater allocation policies were generated. [ABSTRACT FROM AUTHOR]

[Display omitted] • A simulation-based inexact fractional programming model was proposed to control pollution. • This model can tackle ratio optimization problems with mixed-integer variables and uncertain parameters. • Placement plans for best management practices were optimized for both pollution abatement and cost saving. • The dual-objective model outperformed the single-objective one in cost efficiency. The implementation of best management practices (BMPs) is crucial for protecting and restoring watersheds from nonpoint source (NPS) pollution. BMP placement plans with a high pollution reduction to cost ratio are highly desired by decision makers. Nevertheless, few studies tackled such a ratio optimization problem in their efforts to identify BMP placement plans. BMP planning also faces challenges in handling inherent uncertainties and estimating NPS pollution loads. To address these gaps, a simulation-based inexact credibility-constrained mixed-integer fractional programming (SICMFP) model was proposed for supporting the placement of BMPs. This model was developed by integrating the export coefficient model (ECM), compound topographic index (CTI), inexact programming, and mixed-integer programming within a fractional programming framework. SICMFP extends the capability of previous BMP placement models by optimizing the ratio of conflicting objectives and handling uncertain parameters based on interval theory and credibility measure. It can also conveniently simulate the spatiotemporal distribution of pollution loads through the ECM, and efficiently identify potential wetland sites using CTI. SICMFP was applied to plan BMP placement in the Luan River Basin, located in northern China. The results showed that SICMFP could provide BMP placement plans with the optimal system efficiency between pollution reductions and cost savings under different credibility levels. These plans could help decision makers gain in-depth insights into the tradeoffs between expected system efficiency and the risk of constraint violation. As the credibility level rises from 0.6 to 0.9, the optimal ratio between pollution reduction and cost declined from [0.88, 1.66] kg/103 yuan to [0.70, 1.15] kg/103yuan, whereas the costs and pollution reductions increased. Compared with the least-cost single-objective model, SICMFP could lead to more pollution reductions and higher system efficiency. The developed SICMFP approach can also be extended to address the ratio optimization problems of water pollution management in other watersheds. [ABSTRACT FROM AUTHOR]

Unreasonable utilization of water resources cause serious water shortage and associated pollution problems. Improving water use efficiency (WUE) is helpful for alleviating water scarcity and mitigating water pollution. However, due to the conflict between water saving and economic development as well as uncertain parameter information, it is challenging to improve WUE. To address these problems, a water-footprint-based interval fuzzy robust fractional programming (WF-IFRFP) model was developed through integrating water footprint (WF), interval parameter programming (IPP) and fuzzy robust optimization (FRP) into a fractional programming (FP) framework. The developed WF-IFRFP model improved upon traditional methods by being able to tackle interval numbers and fuzzy sets under different system-violation risks. The developed model was applied to a water management case in the northwest of Inner Mongolia, China. The results of WF assessment showed that the water consumption of crop growth increased, water, whereas that used for reducing total nitrogen concentration decreased from 2012 to 2016. Then, specific benefit- and risk-explicit plans for cropping pattern adjustments were generated. The results showed that the water supply-demand ratio from WF-IFRFP would be [5.1, 10.7] % higher than that in the benchmark year of 2016. To assess its performance and merits, the optimal results from the WF-IFRFP model were compared to four alternative models. These comparisons reveal that the WF-IFRFP model is beneficial for improving irrigation WUE. • A novel framework was developed for improving irrigation water use efficiency. • Ecological water shortage risks and parameter uncertainties could be effectively handled. • The water footprint method was introduced to assess the water demand of economy and environment in semi-arid regions. • The developed model is beneficial for sustainable economic development and high-efficient water use. [ABSTRACT FROM AUTHOR]

Optimization of crop structure is an efficient way to reduce greenhouse gas (GHGs) from agriculture production. However, carbon footprint have rarely been incorporated into previous planting structure optimization models due to the challenges of assessing the spatial and temporal distribution of agricultural carbon footprint for multiple crops in irrigated districts. In addition, previous planting structure models suffered from strong subjectivity in objective function determination, and the obtained non-dominated solution set offered difficulties to decision-makers in selecting specific implementation options. To fill such gaps, an integrated accounting-assessment-optimization-decision making (AAODM) approach was proposed, which remedies the shortcomings of previous crop planting structure optimization models in carbon footprint mitigation, and overcomes the subjectivity of objective function determination and the difficulty in selecting specific implementation options. Firstly, life cycle assessment (LCA) method was used to account for the multi-year agricultural carbon footprints of multiple crops in the irrigation district. The optimization objective functions of planting structure optimization models can then be determined based on the assessment method of carbon footprint influencing factors. Next, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used to generate a non-dominated solution set of the optimization model. The optimal planting structure can be finally obtained based on decision making methods by determining the maximum harmonic mean (HM) and knee points (KPs) of the non-dominated solution set. The developed AAODM approach was then applied to a case study of agricultural crop management in Bayan Nur City, China. The results showed that the level of economic development was a key factor influencing the increase in carbon footprint in Bayan Nur City over the past 20 years. The regulation of the level of economic development would significantly influence the agricultural carbon footprint in Bayan Nur City. Moreover, two optimal crop cultivation patterns were provided for decision-makers by selecting solutions from the Pareto front with decision making methods. The comparison results with other methods showed that the solutions obtained by NSGA-II were superior to MOPSO in terms of carbon reduction. The developed AAODM approach for agricultural GHG mitigation could help agricultural production systems in achieving low carbon emissions and high efficiency., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: The management of latent tuberculosis infection (LTBI) is a key action for the realization of the "End tuberculosis (TB) Strategy" worldwide, and it is important to identify priority populations. In this prospective cohort study, we evaluated the prevalence of LTBI and incidence of active TB among close contacts and explored the suitable TB control strategy in schools., Methods: We designed a cohort with 2 years of follow-up, recruiting freshman/sophomore TB patients' close contacts from three administrative districts in Shanghai. These were chosen based on different levels of TB incidence reported in 2019. Questionnaires were included and all participants received both tuberculin skin test (TST) and QuantiFERON-TB Gold (QFT) at baseline, then tracked the outcomes of them during the follow-up period., Results: The prevalence of LTBI was 4.8% by QFT. Univariate analysis showed that the risk of LTBI was higher in those contacting bacteriologically confirmed patients or did not have BCG scars, including smokers. The risk increased with poor lighting and ventilation conditions at contact sites. Multivariate analysis showed that those contacting with bacteriologically confirmed patients (OR=4.180; 95%CI, 1.164-15.011) or who did not have BCG scars (OR=5.054; 95%CI, 2.278-11.214) had a higher risk of being LTBI, as did the current smokers (OR=3.916; 95%CI, 1.508-10.168) and those who had stopped smoking (OR=7.491; 95%CI, 2.222-25.249). During the 2-year follow-up period, three clinically diagnosed cases of TB were recorded, the 2-year cumulative incidence was 0.4% (95%CI 0.1-1.2), the median duration for TB occurrence was 1 year, the incidence rate of active TB was 2.0 per 1000 person-years with a total of 1497.3 observation person-years. For those LTBI, no one initiated preventive treatment, in the QFT (+) cohort, 1 TB case was observed, 71 person-years with an incidence rate of 14.1 14.1 (95%CI 2.5-75.6) per 1000 person-years, in the TST (+++) cohort, 2 TB cases were observed 91.5 person-years with an incidence rate of 21.9 (95%CI 6.0-76.3) per 1000 person-years., Conclusions: The results suggest that school close contacts are one of the key populations for LTBI management. Measures should be taken to further reduce the prevalence of LTBI and the incidence of active TB among them., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Xiao, Chen, Jiang, Li, Li, Lu, Zhao, Tang, Zhang, Wu, Rao, Yuan, Pan and Shen.)

Due to insufficient understanding of human-water interaction, many water-related problems arise in watersheds, posing severe threats to the sustainability of watershed development. Although water environmental carrying capacity (WECC) is a powerful tool to support sustainable development of watersheds, few studies considered aquatic ecological factors and uncertainty in indicator values, leading to losses of sample information in the evaluation of WECC. This paper developed a systematic framework for comprehensive WECC assessment that included the indicator system and a novel variable fuzzy pattern recognition (VFPR) approach. The WECC index system incorporated aquatic ecological factors, and addressed uncertainties associated with the indicator values. The proposed VFPR-based assessment model could realize successive evaluation to retain more original information of the sample and distinguish similar result values by treating the sample as having a continuous degree of membership instead of the traditional point form. In addition, it could be more adaptable to various circumstances including extreme cases, and closely reflect the impacts of indicator changes on the results. The established evaluation framework has been applied to Dongjiang River Basin in Guangdong Province. The spatial differences and main influencing factors of WECC in the study area were analyzed. Results show that 50% and 16.7% of the sub-regions in the study area would be subject to a poor level of WECC under pessimistic and optimistic circumstances, respectively. WECCs in the upper and lower reaches are the best and worst, respectively, which is in line with the levels of economic development in the Dongjiang River Basin. The proposed method can also be applicable to many other problems involving numerous indicators., (Copyright © 2021. Published by Elsevier Ltd.)