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Modelling at the basin scale offers crucial insights for policymakers as they make decisions regarding the optimal utilization of water resources. This study employed the MIKE HYDRO Basin model to analyse water demand and supply dynamics in the Parvati Basin of Rajasthan, India, for the period 2005–2020. The MIKE11 NAM model showcased strong alignment between simulated and observed runoff during both the calibration (NSE = 0.79, PBIAS = −2%, R2 = 0.79, RMSE = 4.95, RSR = 0.5, and KGE = 0.84) and validation (NSE = 0.67, PBIAS = −12.4%, R2 = 0.68, RMSE = 8.3, RSR = 0.62, and KGE = 0.67) phases. The MIKE HYDRO Basin model also exhibited excellent agreement between observed and simulated reservoir water levels, with R2, NSE, RMSE, PBIAS, RSR, and KGE values of 0.86, 0.81, 3.87, −2.30%, 0.43, and 0.88, respectively. The MIKE HYDRO Basin model was employed to create six distinct scenarios, considering conveyance efficiency, irrigation method, and conjunctive water use, to assess irrigation demands and deficits within the basin. In the initial simulation, featuring a conveyance efficiency of 45%, flood irrigation, and no groundwater utilization, the average water demand and deficit throughout the study period were estimated as 43.15 MCM and 3.45 MCM, respectively, resulting in a sustainability index of 0.506. Enhancing conveyance efficiency to 75% under flood irrigation and 5% conjunctive use could elevate the sustainability index to 0.92. Transitioning to sprinkler irrigation and a lift irrigation system could raise the system's sustainability index to 1. These developed models hold promise for real-time reservoir operation and irrigation planning across diverse climatic conditions and varying cropping patterns. [ABSTRACT FROM AUTHOR]

The recent energy crisis has renewed interest in forecasting crude oil prices. This paper focuses on identifying the main drivers determining the evolution of crude oil prices and proposes a statistical learning forecasting algorithm based on regression analysis that can be used to generate future oil price scenarios. A combination of a generalized additive model with a linear transfer function with ARIMA noise is used to capture the existence of combinations of non-linear and linear relationships between selected input variables and the crude oil price. The results demonstrate that the physical market balance or fundamental is the most important metric in explaining the evolution of oil prices. The effect of the trading activity and volatility variables are significant under abnormal market conditions. We show that forecast accuracy under the proposed model supersedes benchmark specifications, including the futures prices and analysts' forecasts. Four oil price scenarios are considered for expository purposes. [ABSTRACT FROM AUTHOR]

A prospective analysis of the Mexican power system has been carried out, and the possibilities for complying with the National Determined Contribution (NDC) commitments adopted in the Paris Agreement in the National Climate Change Strategy of the General Law for Climate Change are presented. A hybrid approach was used, inspired by Foresight Frameworks on one side, and using an accounting and scenario-based modeling platform called Low Emissions Analysis Platform (LEAP) with economic optimization on the other, to analyze four possible scenarios to 2050: Trend, also known as Business As Usual (BAU), which only looks at the growth rate of the gross domestic product (GDP) and population, along with the country's proven potential for renewable resources under the policy framework before 2015; Market, which considers the trend of installation of renewable technologies and the policies of the past administration; Sovereignty, which does the same as the previous scenario but for the policies of the current Mexican government; and Sustainable, which together with GDP and population growth takes into account the possible potential of national renewable resources and characteristics that the country should have to foster this. The research question was: Is there a long-term energy policy for the Mexican power sector to accomplish its NDCs? The study concluded that the best scenario is Sustainable, showing that the possible potential of the country's renewable resources has the capacity to meet the Mexican commitments adopted in the Paris Agreement if, on one side, techno-economic renewable technologies and electricity storage systems are used, and on the other, if the country's strategic areas evolve into a more holistically sustainable future. [ABSTRACT FROM AUTHOR]

BackgroundWith the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions.MethodsWe used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates.ResultsThe results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates.ConclusionThese results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries.

The recent energy crisis has renewed interest in forecasting crude oil prices. This paper focuses on identifying the main drivers determining the evolution of crude oil prices and proposes a statistical learning forecasting algorithm based on regression analysis that can be used to generate future oil price scenarios. A combination of a generalized additive model with a linear transfer function with ARIMA noise is used to capture the existence of combinations of non-linear and linear relationships between selected input variables and the crude oil price. The results demonstrate that the physical market balance or fundamental is the most important metric in explaining the evolution of oil prices. The effect of the trading activity and volatility variables are significant under abnormal market conditions. We show that forecast accuracy under the proposed model supersedes benchmark specifications, including the futures prices and analysts’ forecasts. Four oil price scenarios are considered for expository purposes.

Limited water resources and rapid socioeconomic development pose new challenges to watershed water resource management. By integrating the perspectives of stakeholders and decision-makers, this study aims to identify cases and approaches to achieve sustainable water resources management. It improves and expands the experience of previous project research. The comparative evaluation provides an analytical basis to verify the importance of stakeholder participation in water policy interactions. The results show that if an effective demand management policy is not implemented, the Guanzhong area will not meet water demand in the future. Through the combination of water-saving policies, water transfer projects and other measures, the available water resources will continue into the future. Optimizing management measures, improving the ecological environment, and encouraging stakeholder participation will help change this situation, although supply-side limitations and future uncertainties likely cause unsustainable water. Therefore, decision-makers should pay attention to the application potential of water-saving and other measures to reduce dependence on external water sources. In addition, the three sustainable development decision-making principles identified in this paper can promote the fairness and stability of water policy.

Groundwater serves as one of the crucial natural resources in the safety and sustainable development of Beijing economy. Due to the fact that Beijing is one of the megacities with groundwater as the main water source, it abstracts two-thirds of the city's water supply from groundwater. Meanwhile, the groundwater aquifer storage depletion has been larger than 1.04 × 1010 m3 during the past decades, which has brought serious eco-environmental problems to Beijing. The purpose of this study is to evaluate various abstraction schemes using a 3-D transient numerical groundwater flow model, to understand the present situation and future trend of groundwater resources in Beijing plain. The sustainable utilization of groundwater under these scenarios was comprehensively analyzed. The most reasonable scenario, which meets the appraisal restraint conditions, is the one that the groundwater extraction volumes of the three subsidence centers are reduced by 50%, 20%, and 100%, respectively, with the groundwater abstraction rate of 1.769 × 109 m3/year. Countermeasures that could be considered to improve sustainable groundwater management include: reducing groundwater abstraction directly; importing surface water from outside river basins; improving agricultural water use efficiency; and controlling the groundwater abstractions in the subsidence centers. The results of the modeling study could be used to inform policymakers and the government of Beijing. [ABSTRACT FROM AUTHOR]

Africa stands at a critical crossroads, grappling with the complex interplay between global climate targets and urbanization dynamics. The rapid growth of urban populations coupled with unsustainable urban planning practices exacerbates inherent conflicts, impeding our collective efforts to mitigate carbon emissions. In this context, we systematically decompose the key demographic, economic, and technological drivers of emissions, evaluating their contributions and spatial variations within African city boundaries from 2000 to 2020. By integrating three shared socioeconomic pathways (i.e., SSP119, SSP245, SSP434) and two urbanization strategies (i.e., linear and urbanization-led), we aim to assess the disparities in carbon mitigation outcomes that correspond to varying urban development trajectories by the year 2060, all while adhering to the same climate targets. Our findings reveal that the pursuit of urbanization may result in a substantial reduction in carbon mitigation efforts, with potential reductions ranging from 34% to a staggering 95%. In the "Middle Road" scenario (SSP434), we posit that land productivity must witness an increase of 26%–46% to attain mitigation outcomes comparable to those achieved through a linear trajectory. This implies that the concurrent efforts to urbanize and mitigate carbon emissions may narrow disparities among cities, limiting diversity of existing mitigation measures. The proactive planning of sustainable urban clusters and the provision of localized subsidies for clean energy are imperative to fortify urban climate resilience. [Display omitted] • Gridded carbon emissions of African cities were decomposed. • Six scenarios were analyzed under three SSP and two urbanization strategies. • Convergence was found in achieving net-zero emission targets. • Urban growth may decrease the diversity of carbon mitigation. [ABSTRACT FROM AUTHOR]

Floods devastate communities and result in large economic losses in the lower reaches of the Chao Phraya River Basin, Thailand. The aim of this study was to determine whether nonstructural flood countermeasures would help prevent flash floods in the upstream area of the Upper Chao Phraya River Basin, and control the volume of floodwaters reaching the downstream area. Numerical models were used to quantify the effects of nonstructural measures, namely land use regulation, reforestation, and retention areas, and to examine how efficient these proposed nonstructural approaches would have been during the severe flood events that occurred in 1995, 2006 and 2011. Three scenarios, reforestation, retention areas, and the combination of reforestation and retention areas, were developed for these nonstructural flood countermeasures, as outlined in the Thai Master Plan for Water Resources Management. Their effectiveness in the Upper Chao Phraya River Basin was quantitatively assessed by comparing the model results for the actual conditions with the scenario results. Results showed that the proposed nonstructural measures had considerable potential to reduce peak discharges and flood volumes in the Upper Chao Phraya River Basin. Integration of these proposed nonstructural flood countermeasures with the existing countermeasures in the Chao Phraya River Basin may be the most practical way to cope with the challenges of future flood disasters.

Background: With the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions., Methods: We used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates., Results: The results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates., Conclusion: These results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries., 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 © 2024 Fu, Liu, Wang, Zhao, Cui, Hu, Zhang, and Wang.)

Abstract Colombia represents that group of developing countries that is facing new challenges in energy demand due to climatic phenomena, technological changes and the growing use of renewable energy. This article presents a joint research work between the Unidad de Planeación Minero Energética - UPME (In Spanish) and the University of Bogotá Jorge Tadeo Lozano to analyze the energy demand and greenhouse gas emissions produced in Colombia. The study was conducted using the Long-Range Energy Alternatives Planning System (LEAP) software, through the construction of a model based on the year 2015 and with two future scenarios (positive and negative). The LEAP model is extrapolated until the years 2030 and 2050 to obtain the future predictions of the country's economic sectors: tertiary sector, industrial sector, housing sector and transport sector. The negative scenario is characterized by low economic growth and few incentives for technological change, which translates into low growth in energy efficiency, as well as a low substitution of petroleum-based energy. In contrast, in the positive scenario the economic growth of the sectors is greater and the technological substitution is accelerated which allows higher efficiency levels in the final use of energy and a greater migration towards cleaner technologies. Highlights • It represents the most complete characterization of the Colombian economic sectors. • It includes the technological change using two scenarios. • Results are projected to 2030 and 2050 using the software LEAP™. • Transport sector would be the sector with the highest energy demand to 2050. • 150 Mton of CO2 will be produced in 2050 in the negative scenario. [ABSTRACT FROM AUTHOR]

Abstract A detailed comprehensive emission inventory of multiple air pollutants from civil aviation in China for the historical period of 1980–2015 is developed by using an approach of combining bottom-up with top-down for the first time. Annual emissions of various pollutants present a rapidly ascending trend along with the increase of economic volume and population, which are estimated at approximately 4.77 kt HC, 59.63 kt CO, 304.77 kt NO x , 59,961 kt CO 2 , 19.04 kt SO 2 , 3.32 kt PM 2.5 , 1.59 kt BC, 1.06 kt OC and 5.44 t heavy metals (HMs), respectively, by the year 2015. We estimate the local emissions in 208 domestic civil airports and allocate the total cruise emissions onto 299 main domestic flight segments with surrogate indexes, such as route distance, cargo and passenger turnover. The results demonstrate that emission intensities in central and eastern China are much higher than those in northeastern and western China, and these regions are characterized with high population density, huge economy volume, as well as transit convenience. Furthermore, we have explored emission characteristics of multiple pollutants under different operation modes in 2015. For PM 2.5 , SO 2 /CO 2 /HMs and NO x , the emissions from cruise process constitute the dominant contributor with a share of 89%, 92% and 81%, of the associated total emissions, respectively, comparing with 76% and 71% of the total CO and HC emissions release from Landing and Take-off (LTO) process. Consequently, there are notably different emission characteristics from different flight processes due to various combustion status of aviation fuel. In addition, we predict the future trends of multi-pollutants emissions from China's civil aviation industry through 2050 under three scenarios, and the results indicate that the reduction from the improvement of new technology or new national standards would be largely offset by the rise in multi-pollutants emissions from rapidly aviation fuel growth. Graphical abstract Unlabelled Image Highlights • A dedicated multi-pollutants emission inventory from China's civil aviation is established. • Temporal trend of multi-pollutants emission for historical period 1980–2015 is investigated. • Spatial distribution characteristics by varied airports and airlines are presented. • Multi-pollutants emissions features of LTO and cruise operation modes are analyzed. • Pollution from aviation can't be ignored due to rapid growth in aviation activities. [ABSTRACT FROM AUTHOR]

Electrified light commercial vehicles have gained increasing interest as an energy efficient means of transportation. At the same time, they are characterized by limited traveling range, necessitating careful design of batteries recharging planning and respective charging infrastructure deployment. Early available hydrogen fuel cell vehicles have the potential to overcome the range anxiety limitation, they require though an extended H 2 -refueling network. The scope of this work is to demonstrate a model-based evaluation of the H 2 -refueling strategy for a battery electric light commercial vehicle, equipped with a hydrogen fuel-cell based range extender. For this purpose, advanced vehicle modeling was combined with statistical analysis to thoroughly evaluate the studied vehicle's energy consumption, under a broad range of operating conditions and eventually define an optimal refueling strategy. The attempted analysis not only allowed for defining the refueling strategy, but also enabled to optimize the H 2 -tank size, which tends to highlight the interest of the followed approach. [ABSTRACT FROM AUTHOR]

Abstract A system dynamics model (SDM) is developed to assess the dynamic changes in water resources and the impacts of different policies and measures in the Weihe River Basin. The purpose of the model is to enhance understanding of the dynamic behavior of this interactive system and to provide decision support to promote the sustainable utilization of water resources and the coordinated development of socio-economic conditions and the ecological environment in the Weihe River Basin. Six scenarios are designed to simulate the variations in and the effects of key variables based on changing the values of parameters in the model. The simulation results show that the SDM developed in this study can provide deep insight into the actual system and accurately reflects the dynamic behaviour of the basin. The results of the scenario-based projections suggest that improving water efficiency is the most effective means of supporting rapid socio-economic development and improving the quality of the ecological environment. [ABSTRACT FROM AUTHOR]

Abstract China has the largest textile industry with the complete industrial chain and also the largest textile exporter in the world. The study analyses the energy substitution effect of technological progress of China's textile industry using a macroeconomics approach. In order to predict future energy saving potential, we examine the relationship between energy intensity and its five main factors (technological progress, enterprise scale, labor productivity, dependence on foreign trade and industrial electricity price) by co-integration technique. Empirical results indict that electricity shows alternative features to other energy sources in the context of technological progress in China's textile industry. Besides, there exists a long-run equilibrium among energy intensity and the five main factors. Monte Carlo method was applied for risk analysis to ensure the reliability of forecast. Further, future energy saving potential and CO 2 emission reduction of China's textile industry was predicted using scenario analysis. The result shows that energy conservation potential of China's textile industry is 16.16–27.53 million tons of standard coal equivalent in 2025. Additionally, it was revealed that the CO 2 emission reduction caused by the energy conservation will be 32.63–55.60 million tons in 2025. Finally, future policy priorities for energy conservation of Chinese textile industry are suggested. Highlights • We study the elasticity coefficients of influential variables of energy intensity. • Electricity shows alternative features to other energy sources. • Energy conservation potential of China's textile sector will be 27.53 Mtce by 2025. • CO 2 emission reduction potential is estimated to be 55.60 million tons by 2025. [ABSTRACT FROM AUTHOR]

A basic production scenario analysis (BPSA) using the TOUGH2 code (coupled with a fit-for-purpose modified EGS module) as a relevant simulator was conducted to study a potential geothermal site in I-lan Triangle, Taiwan. The outcome of numerical simulation shows that the capability of the code is compliant with heat production model analysis under a pair of recharging and production wells. In the BPSA application, the model was constituted with an assumed size of 2 km × 2 km × 2.5 km, taking into consideration a relevant boundary condition and using Case-A, B, and C to represent varied depths of recharging points. Heat production histories of target reservoirs containing a fault zone were simulated using a deterministic approach, and a collection of 30-year heat production P/T histories was obtained for all 3 cases. The effects of a fault zone near the production point are evaluated and found to be significant only when distance between the fault’s boundary and production point is minimum. The study also shows that relative locations of the recharging point from production point are important to reach an adequate design of production well layout in a geothermal plant. Significant temperature decline can be observed in Case-C of BPSA, where the distance between R-1 and P-1 is the least among the 3 cases studied. Results of this study would provide a useful numerical tool for evaluating future EGS development projects in Taiwan. By adopting a suitable conceptual model and a group of carefully selected relevant parameters, site-specific reservoir engineering problems associated with the recharging and production operation in a representative EGS geothermal field can be foreseen and predicted in a quantitative way. [ABSTRACT FROM AUTHOR]

Energy is one of the cornerstones essential for human life, along with other services such as water and food. Understanding how the different services in the energy-water-food (EWF) nexus interact and are perceived by different actors is key to achieving sustainability. In this paper, we derive a model of the EWF nexus using fuzzy cognitive mapping (FCM). Data were collected in a two-step approach from workshops with researchers and stakeholders involved in the three focal sectors. Four FCMs were developed; one for each of the EWF sectors, and one for the interactions that create the nexus between EWF. The FCM represents the combined views of the groups who participated in the workshops, the importance and limitations of which is discussed. To demonstrate its effectiveness, the aggregated FCM was applied to predict the impacts on the EWF nexus of four scenarios under which the United Kingdom would depart from the European Union (i.e. Brexit). The FCM indicated that energy-related concepts had the largest influence on the EWF nexus and that EWF demand will decrease most under a ‘hard-Brexit’ scenario. The demand for energy was shown to decline relatively less than other services and was strongly associated with gross domestic product (GDP), whereas UK population size had a stronger effect on water and food demand. Overall, we found a threefold change across all concepts in scenarios without freedom of movement, contribution to the EU budget, and increased policy devolution to the UK. [ABSTRACT FROM AUTHOR]

Urban energy consumptions growth has become an urgent topic that requires solutions for significantly reduce carbon emission in the next decades. This paper aims in exploring the integration of building performance improvement and low carbon district heat technological choices by considering the upgrade of conversion technologies, efficiency and the exploitation of local resources. The paper is based on a GIS-based model that spatially characterize the space heating demand of urban buildings. Starting from clustering buildings with similar thermo-physical characteristics, the total energy use of buildings can be depicted and compared with the energy balance data of the city in order to scale the bottom-up results for matching the total load. Reasonable energy efficiency measures are further proposed by considering three different scenarios up to 2050. Long-term building scenarios are applied to a district heating simulation model for investigating how the reduction of building heat demand will impact the district heating production and operations. In particular, the combination of the building model and the district heating model aims at exploring the effects of district network expansion or new low carbon investments from an economic and environmental perspective. The model has been successfully applied to the city of Turin, Italy and the city of Stockholm, Sweden. The flexibility of the approach may allow it to be easily adjusted to different urban areas for providing indications on cost-effective strategies for efficient, low-carbon heat solutions in integrated energy systems. Results highlight that finding synergies between the demand and supply sector will lead to environmental and economic benefits, in particular for district-heated cities. [ABSTRACT FROM AUTHOR]

A reference scheme of a multiple energy complementation system is of great importance of Chongming's energy system development. In this paper, four feasible scenarios which are distinguished by energy supply forms have been discussed based on RETScreen software. Economic analysis as well as the renewable sources penetration was taken into account. The outcome of equipment size optimization of each subsystem was summarized and the comparison between different scenarios was afterwards conducted in order to provide some thoughtful comments for the future energy system construction. Results indicate that the introduction of natural gas based CHP system and biomass system is a necessity for covering the energy demand and minimizing the energy import. The CHP scenario achieves the most annual balance (0.3272 billion yuan) and net present value (2.556 billion yuan) and cuts down the GHG emission by 1.978 Mt per year. Moreover, the net present value of the proposed energy system is sensitive to the variation in energy policy. When the financial aids fluctuates by 50%, the net present value can change in the range from 60% to 70%. However, even when the policy is extremely unfavorable, the economical profit of CHP scenario is still obvious. [ABSTRACT FROM AUTHOR]

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Water and fertilizer are two important factors affecting crop growth and yield. Crop growth models are powerful tools for making irrigation and fertilization scheduling and predicting crop yield. The performance of crop models on potato under different irrigation amounts along with different N, P and K rates has been rarely evaluated, especially under drip fertigation. In this study, the accuracy of AquaCrop and DSSAT-SUBSTOR-Potato models in simulating potato growth, yield and water productivity under different drip fertigation regimes was compared. For model calibration and validation, a two-year field experiment with three irrigation levels (W 1 , 60% ET C ; W 2 , 80% ET C and W 3 , 100% ET C , where ET C was the crop evapotranspiration) and four fertigation (N-P 2 O 5 -K 2 O) rates (F 1 : 100–40–150 kg ha−1, F 2 : 150–60–225 kg ha−1, F 3 : 200–80–300 kg ha−1 and F 4 : 250–100–375 kg ha−1) was carried out in a sandy region of northwest China in 2018 and 2019. The statistical indicators showed that the AquaCrop model gave satisfactory predictions of canopy cover (R 2 ≥ 0.92, NRMSE ≤ 14.7%, d ≥ 0.96 and RMSE ≤ 10.8%), total dry matter (R 2 ≥ 0.92, NRMSE ≤ 25.0%, d ≥ 0.94 and RMSE ≤ 2.2 t ha−1), final dry tuber yield (R 2 ≥ 0.57, NRMSE ≤ 12.21%, d ≥ 0.82 and RMSE ≤ 0.83 t ha−1) and fresh tuber yield (R 2 ≥ 0.53, NRMSE ≤ 12.02%, d ≥ 0.81 and RMSE ≤ 4.91 t ha−1) in the four fertigation treatments (F 1 -F 4) under W 3 and W 2 during the two potato growing seasons. The final total dry matter and tuber yield under W 1 were over-estimated. The simulated water productivity and soil water content also agreed well with the observations (R 2 ≥ 0.91 , NRMSE ≤ 5.51%, d ≥ 0.94 and RMSE ≤ 0.48 kg m−3, and R 2 ≥ 0.40 , NRMSE ≤ 14.8%, d ≥ 0.77 and RMSE ≤ 11.5 mm). The simulation accuracy of DSSAT-SUBSTOR-Potato model was lower than that of AquaCrop model, which only showed a goodness of fit between simulated total dry matter, soil water content, tuber yield, water productivity and observations under high irrigation amount with high fertilization rate (W 3 F 4). Since the observed tuber yield increased with the increase of irrigation level (60–100% ET C) under the same fertigation rate, 120%ET C and 40%ET C were further simulated using the AquaCrop model to test the changes in tuber yield with further increased or decreased irrigation levels. The scenarios simulation showed that the tuber yield was only increased by 0.19%−1.52% under 120%ET C compared with that under 100% ET C , but 18.0% more irrigation water was consumed. Comprehensively considering water resources and tuber yield, the irrigation level of 100% ET C (W 3) along with fertigation (N-P 2 O 5 -K 2 O) rate of 200–80–300 kg ha−1 (F 3) was recommended for the sustainable potato production in the study region. The results of this study can provide guidance for the application of crop models in drip-fertigated potato. • AquaCrop and DSSAT-SUBSTOR-Potato were evaluated under various drip fertigation regimes. • AquaCrop adequately simulated the effects of irrigation and fertilization regimes on potato. • Simulation accuracy of DSSAT-SUBSTOR-potato was lower than that of AquaCrop. • 100% ET C along with N-P 2 O 5 -K 2 O rate of 200–80–300 kg ha−1 was recommenced for potato production. [ABSTRACT FROM AUTHOR]

In a rapidly changing water resources system, dynamic models based on the notion of systems thinking can serve as useful analytical tools for scientists and policy-makers to study changes in key system variables over time. In this paper, an integrated system dynamics simulation model was developed using a system dynamics modelling approach to examine the feedback processes and interaction between the population, the water resource, and the agricultural production sub-sectors of the Volta River Basin in West Africa. The objective of the model is to provide a learning tool for policy-makers to improve their understanding of the long-term dynamic behaviour of the basin, and as a decision support tool for exploring plausible policy scenarios necessary for sustainable water resource management and agricultural development. Structural and behavioural pattern tests, and statistical test were used to evaluate and validate the performance of the model. The results showed that the simulated outputs agreed well with the observed reality of the system. A sensitivity analysis also indicated that the model is reliable and robust to uncertainties in the major parameters. Results of the business as usual scenario showed that total population, agricultural, domestic, and industrial water demands will continue to increase over the simulated period. Besides business as usual, three additional policy scenarios were simulated to assess their impact on water demands, crop yield, and net-farm income. These were the development of the water infrastructure (scenario 1), cropland expansion (scenario 2) and dry conditions (scenario 3). The results showed that scenario 1 would provide the maximum benefit to people living in the basin. Overall, the model results could help inform planning and investment decisions within the basin to enhance food security, livelihoods development, socio-economic growth, and sustainable management of natural resources. [ABSTRACT FROM AUTHOR]

A model based on economic structure adjustment and pollutants mitigation was proposed and applied in Urumqi. Best-worst case analysis and scenarios analysis were performed in the model to guarantee the parameters accuracy, and to analyze the effect of changes of emission reduction styles. Results indicated that pollutant-mitigations of electric power industry, iron and steel industry, and traffic relied mainly on technological transformation measures, engineering transformation measures and structure emission reduction measures, respectively; Pollutant-mitigations of cement industry relied mainly on structure emission reduction measures and technological transformation measures; Pollutant-mitigations of thermal industry relied mainly on the four mitigation measures. They also indicated that structure emission reduction was a better measure for pollutants mitigation of Urumqi. Iron and steel industry contributed greatly in SO 2 , NO x and PM (particulate matters) emission reduction and should be given special attention in pollutants emission reduction. In addition, the scales of iron and steel industry should be reduced with the decrease of SO 2 mitigation amounts. The scales of traffic and electric power industry should be reduced with the decrease of NO x mitigation amounts, and the scales of cement industry and iron and steel industry should be reduced with the decrease of PM mitigation amounts. The study can provide references of pollutants mitigation schemes to decision-makers for regional economic and environmental development in the 12th Five-Year Plan on National Economic and Social Development of Urumqi. [ABSTRACT FROM AUTHOR]

Nowadays about 50% of global population lives in cities, responsible for about 70% of GHG emissions and by 2030 the urbanization rate will increase to over 75%. The paper analyses the new emerging concept of “Post-Carbon City” (PCC) and its main influencing factors regarding the building sector. It provides inspiration to re-think urban re-development patterns leading the way for new comprehensive approaches. In this new vision, energy and cost-effective retrofit of existing buildings cover a key role both in terms of saving potential and emission reduction towards nearly-zero energy building (nZEB) target. Moreover, in the building operational phase occupant behaviour has a strong impact on the real energy performance and its effect should be minimized. Therefore, these two issues should be mainly taken into account when energy city planning. Several mid/long-term scenarios analyses performed through quantitative energy demand forecasting tools − concerning not only the building sector, but the whole energy system − are the only opportunity to produce indications for an energy-oriented city planning. Finally, it highlights the necessity of new Advanced Input Modelling procedures to improve the effectiveness of measure recommendations derived through scenarios analysis. [ABSTRACT FROM AUTHOR]

Studying the driving factors and contributions of carbon emissions peak volume and time is essential for reducing the cumulative carbon emissions in developing countries with rapid economic development and increasing carbon emissions. Taking Jilin Province as a case study, four scenarios were set in this paper respectively: Business as Usual Scenario (BAU), Energy-Saving Scenario (ESS), Energy-Saving and Low-Carbon Scenario (ELS), and Low-Carbon Scenario (LCS). Furthermore, the carbon emissions were predicted according to the energy consumption based on the application of LEAP system. The research result showed that the peak time of carbon emissions would appear in 2045, 2040, 2035 and 2025 under the four different scenarios, respectively. The peak volumes would be 489.8 Mt, 395.2 Mt, 305.3 Mt and 233.6 Mt, respectively. The cumulative emissions by 2050 are respectively 15.632 Bt, 13.321 Bt, 10.971 Bt and 8.379 Bt. According to the forecasting, we analyzed the driving factors of and contributions to carbon emissions peak volume and time. On the premise of moderate economic growth, the "structural emission reduction", namely the adjustment of industrial structure and energy structure, and "technology emission reduction", namely the reduction of energy intensity and carbon emission coefficient could make the peak volume reduced by 20%-52% and cumulative carbon emissions (2050) reduced by 15%-46% on the basis of BAU. Meanwhile, controlling the industrial structure, energy structure and energy intensity could make carbon emissions reach the peak 5-20 years ahead of the time on the basis of BAU. Controlling GDP, industrial structure, energy structure, energy intensity and coefficient of carbon emissions is the feasible method to adjust the carbon emissions peak volume and time in order to reduce the cumulative emissions. [ABSTRACT FROM AUTHOR]

Oil palm plantation has expanded rapidly in Indonesia, driven by the enormous increase in the global demand for oil palm products. While the production and exporting of oil palm products have stimulated economic growth and improved living standards of local people, the expansion has imposed significant costs on the environment. Indonesia faces tough challenges to balance oil palm production with the growing commitment to protect tropical forest and peatland. This research offered a comprehensive assessment of the local responses in land-use changes and the associated environmental impacts in Indonesia to the dynamics on the global market of oil palm products. We employed generalized geo-economic gravity models to project export demand for oil palm products from Indonesia by 2050 under three different international trade scenarios. With the help of parametric survival analysis, we allocated the projected demands to 1km × 1km grids across Indonesia and quantified the possible trade-offs between oil palm expansion and environmental conservation. Results show that about 313–679 million tons of oil palm products (oil palm fruit equivalent) from Indonesia would be needed by 2050, which means about 18.58–45.59 million hectares of new plantation. We estimated that 8%–22% of secondary forest and 21%–54% of peatland would lose to oil palm expansion by 2050 if the expansion follows the historical pathways. Shifting the expansion from natural forest and peatland to degraded land with low environmental values would reduce the CO 2 emission by about 87–142 Mton/year, at the expense of increased transportation and infrastructure accessibility costs. This shift towards sustainable palm oil production can be facilitated by extending current policies and regulations to secondary forest, enforcing stricter restrictions on peatland, supporting infrastructure development, and providing economic incentives. [ABSTRACT FROM AUTHOR]

Nowadays about 50% of global population lives in cities, responsible for about 70% of GHG emissions and by 2030 the urbanization rate will increase to over 75%. The paper discusses new emerging concept of “Post-Carbon” City, in which the “vision” consists in the opportunity of breaking the carbon-dependent system of urban areas. It provides inspiration to re-think urban re-development patterns. In this new vision buildings and occupant behaviour role and need for new comprehensive planning tools are investigated. The paper deals with a project that is undergoing study and represents a picture of the current situation related to “Post-Carbon” City topic. [ABSTRACT FROM AUTHOR]

In this paper a Multiple Criteria Mathematical Programming model has been developed integrating vulnerability maps; its purpose is to optimize and facilitate the decision making process relating to the problems of water management, land use and environmental protection. The model is used to support irrigation water use and eco-friendly decision processes in agricultural production planning. It has been developed in the context of the research project entitled EU Water (transnational integrated management of water resources in agriculture for European water emergency control). For accessing the vulnerability of agricultural land to water and nitrogen losses, a set of indices were utilised. It was implemented in the Sarigkiol basin in the north-eastern part of the Kozani prefecture in Northern Greece, combining different criteria to a utility function under a set of constraints concerning different categories of labour, land, available capital, etc. On the same time the model is taking into account the vulnerability maps which have been developed for the area. The aim of the study was to achieve optimum crop plans in the aforementioned area and it was further used to simulate different scenarios and policies, due to changes on different social, economic and environmental parameters (e.g. different levels of chemicals or water consumption per crop). The decision maker can get alternative production plans and agricultural land uses as well as the social, economic and environmental impact of different policies. Results show that the model can be considered as an important planning tool enabling the regional authorities to design optimal spatial development policies and protect groundwater from the excessive fertilizer and other pollution agents use. [ABSTRACT FROM AUTHOR]

In this article, the future trend of energy demand in Iran is analyzed using a long-range energy alternatives planning system (LEAP) model. First, the structure of Iran's energy consumption and its historical trend are evaluated. Then the key assumptions of a LEAP model are defined, which comprise different economic growth, population growth, and urban settlement perspectives in combination with several assumptions on energy-saving policy rules. These assumptions are categorized into three different scenarios: reference, high, and low. Results imply an ever-growing demand in all three scenarios, and the ratio of final energy demand in the year 2041 to that of 2010 in High, Reference, and Low growth scenarios are projected to be 2.24, 1.8, and 1.6, respectively. According to the reference scenario, if current trends of energy conservation continue, by the year 2041 the shares of natural gas, petroleum products, electricity, and renewable energy from Iran's energy demand basket are predicted to be, respectively, 53%, 34%, 10%, and 3%. Results show that Iran has a large potential for energy conservation, and, according to the reference scenario, the implementation of currently adopted rules may reduce its final energy demand by 21%. Additionally, renewable solar energy will play a more prominent role in the implementation of energy conservation policy acts in Iran. [ABSTRACT FROM AUTHOR]

The Referee Assignment Problem (RAP) is a novel arising problem in sports management, in which a limited number of referees with different qualifications and availabilities should be assigned to a set of games already scheduled, in order to respect a list of constraints. Number and nature of these constraints may significantly vary for sports, nation and type of league. Almost each tournament has its own particular set of constraints to be satisfied, therefore it is very difficult to generalize this problem. The goal of the problem is to find a feasible assignment, i.e., a configuration which allows to respect all the constraints given. An extension of the RAP is the Fair Referee Assignment Problem (FRAP), in which the objective is to minimize the violation of a set of soft (optional) constraints, while satisfying all the hard (mandatory) ones. In this work, the Italian Major Soccer League, the so-called SERIE A, is addressed, and an integer programming model for the related FRAP is proposed. Soft and hard constraints have been formulated according to the rules suggested by the AIA (Italian Referee Association) which is in charge of referee assignment for the SerieA. The model has been tested on a real instance taken from the season 2011/2012. Results obtained show the efficacy and the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Flooding is the most frequent disaster in China. It affects people's lives and properties, causing considerable economic loss. Flood forecast and operation of reservoirs are important in flood emergency management. Although great progress has been achieved in flood forecast and reservoir operation through using computer, network technology, and geographic information system technology in China, the prediction accuracy of models are not satisfactory due to the unavailability of real-time monitoring data. Also, real-time flood control scenario analysis is not effective in many regions and can seldom provide online decision support function. In this research, a decision support system for real-time flood forecasting in Yujiang River Basin, South China (DSS-YRB) is introduced in this paper. This system is based on hydrological and hydraulic mathematical models. The conceptual framework and detailed components of the proposed DSS-YRB is illustrated, which employs real-time rainfall data conversion, model-driven hydrologic forecasting, model calibration, data assimilation methods, and reservoir operational scenario analysis. Multi-tiered architecture offers great flexibility, portability, reusability, and reliability. The applied case study results show the development and application of a decision support system for real-time flood forecasting and operation is beneficial for flood control. [ABSTRACT FROM AUTHOR]

Abstract: To evaluate the potential for energy conservation and CO2 emissions mitigation in China's iron and steel industry during 2010 and 2020, a detailed model was developed and applied based on Asian-Pacific Integrated Model (AIM). Three scenarios including the business as usual (BAU) scenario, the integrated policy (INT) scenario and the strengthen policy (STR) scenario have been set to describe future policy measures in relation to the development of the iron and steel industry. Results show that STR scenario in 2020 would realize an additional energy saving potential of 58.2 million tce accounting for 14.18% of the total energy consumption, while the potential for CO2 mitigation of 218.0 million ton CO2 takes up 14.53% of the predicted emission. And results indicate that technology promotion is the main driver for energy saving and emissions reduction, more than structure adjustment. In order to meet the targets set by the 12th Five-Year Plan in China's iron and steel industry, it is essentially to promote technologically advanced approaches with a high-demand policing rate. Specific energy conservation technologies could aid significantly to the cause. In the long term, energy saving and emissions reduction of China's iron and steel industry will rely mostly on technology promotion. [Copyright &y& Elsevier]

Biochar application has been proposed as a promising practice for sustainability due to its potential to ensure food security while alleviating the water shortage and fertilizer overuse. Scheduling the proper integrated management of deficit irrigation, nitrogen fertilization, and biochar addition are necessary to facilitate the effective use of biochar in agriculture. The objectives of this study were to test the AquaCrop model for winter wheat under different irrigation, nitrogen, and biochar regimes and to optimize the integrated strategies. For the model calibration and validation, a field experiment of winter wheat with two irrigation levels (full and deficit irrigation) and three fertility levels (200 kg/ha N, 100 kg N + 15 t/ha biochar, 0 kg/ha N) was conducted in the North China Plain during 2017/2018 and 2018/2019 growing seasons. The results showed that AquaCrop performed well in simulating soil water content (0.82 ≤ R2, 0.92 ≤ d, RMSE ≤ 2.82%, NRMSE ≤ 17.34%), canopy cover (0.89 ≤ R2, 0.95 ≤ d, RMSE ≤ 7.58%, NRMSE ≤ 13.33%), biomass (0.96 ≤ R2, 0.96 ≤ d, RMSE ≤ 1.04 t/ha, NRMSE ≤ 16.75%), and grain yield (0.94 ≤ R2, 0.97 ≤ d, RMSE ≤ 0.34 t/ha, NRMSE ≤ 5.32%). The effects of biochar on soil moisture, fertility, and wheat production could be adequately simulated by AquaCrop using the hydraulic properties of the biochar-mixed soil layer and its semi-quantitative method for soil fertility stress. The optimal integrated strategies were deficit irrigation with three irrigations of 60 mm at the jointing, anthesis, and grain-filling stage for dry years, two irrigations of 60 mm at the jointing and anthesis stage for normal years, and one irrigation of 60 mm at the anthesis stage for wet years, combined with 100 kg/ha N and 15 t/ha biochar, which could achieve over 80% of the potential yield while substantially increasing irrigation water productivity. Nonetheless, the model tended to under-estimate soil moisture, leaf growth and senescence, and grain yield in the biochar amended treatments, particularly under drought. Further improvements in the modules of soil properties, soil water balance, and canopy cover can be performed to increase the estimation accuracy. Additionally, AquaCrop was only calibrated and validated based on a two-year experiment under the weather conditions of no drought and moderate drought. Therefore, future validation studies using the long-term field data with the larger climate variability are necessary to better identify the impacts of integrated strategies and climate change. Finally, considering its good balance in simplicity, robustness, and accuracy, AquaCrop could be a reliable tool to guide the field management of irrigation, fertilization, and biochar addition. • AquaCrop was tested under various irrigation, nitrogen, biochar regimes. • AquaCrop adequately simulated the effects of biochar on winter wheat. • Integrated strategies of irrigation, nitrogen, biochar were optimized. • Optimal integrated strategies could achieve over 80% of the potential yield. [ABSTRACT FROM AUTHOR]

Abstract: Policy variables, such as security levels at seaports, affect port efficiency in a non-linear way while other factors affecting efficiency at ports such as a number of berths, the area of port yard, and the number of port labors have linear structural relation. Ensuring a certain level of regulations can increase port efficiency, while an excess of the level may result in the reverse of these gains. Addressing seaport-related issues is not a simple undertaking because a seaport is regarded as a system-of-system, which is both difficult to understand and to model. Therefore, studies that adequately analyze the overall dynamic of a port complex in terms of security concerns have been seen insufficient, leaving a significant research gap to fill in. To analyze the relationship between seaport security levels and container volumes, this study adopts the method of System Dynamics (SD). Use of the SD can demonstrate the benefits of simulations, such as suggesting the visual causal loops among evaluation factors, representing the several sub-models, and enabling various forms of analysis, such as the base model, optimistic scenario model, and pessimistic scenario model. As a result of simulation, the impacts on handling container cargo volumes in Korea due to the increasing level of security is estimated at 2,770,000TEUs by the year 2015 and 3,050,000TEUs by 2020. Appropriate tailor of the proposed SD based methodology can stimulate security–economic quantitative analysis in a wider range of port context, thus promoting effective implementation of security measures. [Copyright &y& Elsevier]

Abstract: The olive oil industry is a significant productive sector in the European Union; indeed, three quarters of world production is concentrated in Europe. After Spain, Italy is the second largest olive oil producing country (27% and 20% of European and world production respectively) and Sicily is the third most important olive oil producing region in Italy (8% of Italian production) after Puglia and Calabria which account for almost 70% of national production. In Sicily, the province of Messina occupies sixth place in regional production and production is characterized by eight predominant cultivars (with different nutritional, organoleptic and productivity characteristics) and a variety of different practices and techniques for the agricultural production of olives and for their processing into olive oil. Depending on these differences, the production of olive oil is associated with several adverse effects on the environment, both in the agricultural and olive oil production phases. The aim of this paper is to provide useful information for taking strategic decisions aimed at the improvement and optimization of the local olive oil production chain in the province of Messina. To this purpose the LCA methodology has been used to determine the potential environmental impacts of activities connected to olive oil production in the province, in order to identify the processes which give rise to the most significant environmental problems and to design a more efficient and environmentally friendly local olive oil chain. Data on the various agricultural and industrial methods used in the province were obtained through the development of a questionnaire, then distributed to a sample of companies of the local association of oil producers (APOM). The study is part of the Eco-Management for Food - EMAF - Project (PRIN 2008 No. 2008TXFBYT - http://ww2.unime.it/emaf) co-funded by the Italian Ministry of Education, University and Research (MIUR). [Copyright &y& Elsevier]

Based on the precipitation and temperature data of the 12 meteorological stations in the 'Three-River Headwaters' region and the observed runoff data of Zhimenda in the headwater sub-region of the Yangtze River, Tangnaihai in the headwater sub-region of the Yellow River and Changdu in the headwater sub-region of the Lancang River during the period 1965-2004, this paper analyses the trends of precipitation, temperature, runoff depth and carries out significance tests by means of Mann-Kendall-Sneyers sequential trend test. Makkink model is applied to calculate the potential evaporation. The runoff model driven by precipitation and potential evaporation is developed and the influence on runoff by climate change is simulated under different scenarios. Results show that during the period 1965-2004 the temperature of the 'Three-River Headwaters' region is increasing, the runoff of the three hydrological stations is decreasing and both of them had abrupt changes in 1994, while no significant trend changes happen to the precipitation. The runoff model suggests that the precipitation has a positive effect on the runoff depth, while the potential evaporation plays a negative role. The influence of the potential evaporation on the runoff depth of the Lancang River is found to be the significant in the three rivers; and that of the Yellow River is the least. The result of the scenarios analysis indicates that although the precipitation and the potential evaporation have positive and negative effects on runoff relatively, fluctuated characteristics of individual effect on the runoff depth in specific situations are represented. [ABSTRACT FROM AUTHOR]

Abstract: Fertilizers that are spread on agricultural fields can leach into aquifers and contaminate groundwater sources for drinking water particularly with nitrate. Modeling this phenomenon can help in evaluating the impact of current or future agricultural practices on nitrate content within an aquifer. The three-dimensional Water flow and Nitrate transport Global Model (WNGM), that was previously developed and applied to a well-capture zone, is actually used to simulate future land management scenarios over the same zone. The studied area is located in a region with intensive agricultural practice in Southern Québec (Canada). The sandy unconfined aquifer underlying the agricultural fields is highly vulnerable to nitrate contamination from ground surface and nitrate concentrations around critical threshold of 45mg/L were observed in the municipal well. Using the calibrated WNGM, a number of land management scenarios were simulated in order to predict future trends of nitrate concentrations in the pumping well from 2008 through 2040 that could be induced by changes in land management practices over this well-capture zone. More specifically, these scenarios simulate implementation of improved or ideal agricultural practices within the agricultural portion of the well-capture zone, and modification of the pumping rate at the municipal well. The results show how a decrease and stabilization of nitrate concentration should occur at the municipal well after a period varying from 5 to 30years depending on the implemented agricultural modifications. It is also shown that, in this particular case, an increase of the pumping rate at the municipal well from 700 to 2800m3/d would lead to an increase of the well-capture zone from 0.8 to 2.5km2 and to a decrease of nitrate concentrations at the municipal well from 43 to 34mg/L. Furthermore, it is predicted that application of improved agricultural practices in the vicinity of this municipal well could lead to a reduction of nitrate concentrations at the well of about 8mg/L. [Copyright &y& Elsevier]

Abstract: A research associated with urban transportation was carried out in Rawalpindi and Islamabad to analyze the status of emission of air pollutants and energy demands. The study included a discussion of past trends and future scenarios in order to reduce the future emissions. A simple model of passenger transport has been developed using computer based software called Long-Range Energy Alternatives Planning System (LEAP). The LEAP model was used to estimate total energy demand and the vehicular emissions for the base year 2000 and extrapolated till 2030 for the future predictions. Transport database in Rawalpindi and Islamabad, together with fuel consumption values for the vehicle types and emission factors of NO x , SO2 and PM10 corresponding to the actual vehicle types, formed the basis of the transport demand, energy consumption and total emission calculations. Apart from base scenario, the model was run under three alternative scenarios to study the impact of different urban transport policy initiatives that would reduce energy demand and emissions in transport sector of Rawalpindi and Islamabad. The prime objective was to arrive at an optimal transport policy, which limits the future growth of fuel consumption as well as air pollution. [Copyright &y& Elsevier]

The Ecological Footprint (EF) is a powerful tool to advance the science of sustainability. However, the static snapshot of EF accounting is not designed to make projections of future sustainability consequences, which fails to elicit policy implications from a dynamic, temporally explicit perspective. This work attempts to incorporate system dynamics (SD) into EF to develop a dynamic EF forecasting framework, and provide a platform to support policy making for urban sustainability improvement. SD is firstly adopted to model the dynamics and interactions of EF driving forces, and then incorporated into the EF framework by correlating system drivers to EF-related consumption categories, embodied EF is finally calculated using the compound-based method. Based on different policy feasibility and sustainability targets, four policy scenarios are designed to explore future sustainability prospects and formulate integrated policies which would attain that sustainability scenario. The modeling procedure is applied to a case study area to illustrate how it works, and policy making for urban sustainability can hopefully be supported using this developed framework in the near future. [Copyright &y& Elsevier]