• Energy Research
• 2016-2025close
• 6. Clean water close
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In recent years, the rapid development of the rare earth industry has had a serious impact on the environment. Some enterprises have taken measures to improve the production process. In order to explore the sustainability of this industry and these improvements’ environmental benefits, this paper combines emergy analysis and lifecycle assessment to evaluate and compare the production process of rare-earth oxides considering the three aspects of emergy flow, pollutant emissions, and emergy-based indicators. Changes in the emergy of pollutant emissions before and after improvement of the production process are discussed. The results show that the greatest inputs in the mining and beneficiation stage and smelting separation stage are labor force and service and non-renewable resources, respectively. These two production stages are highly dependent on external input and have weak competitiveness. Both stages place great pressure on the environment, so the bastnasite production process would be unsustainable in the long term. After the improvement, the environmental impact of the production process for bastnaesite changed significantly, indicating that the improvement effect of the wastewater treatment facilities and the change of fuel from coal to natural gas is remarkable.

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

Abstract A new formulation for the evaporation, flashing, condensation processes taking place in the effects of thermal desalination systems which simulates the operation of both forward and parallel/cross configurations is coupled with an exergo-economic model based on the SPECO method. The thermo-economic model uses accurate properties for the seawater, brine, pure water and vapour and is solved with an equation solver which does not require the development of a specific solution algorithm as in most previous studies. This flexible model is used to analyze the influence of the number of effects N and the temperature difference ΔT e between effects on the technical and economic performance of multi-effect desalination systems with ejector vapour compression. In particular, it is shown that the performance calculated by an earlier black-box approach is not attainable by technically and economically realistic systems. It is also shown that for each feed configuration and a given number of effects there exists an optimum value of ΔT e which minimizes the cost of the produced potable water. This last result forms the basis of a procedure that combines black-box results with the optimum value of ΔT e and can be used to select the appropriate system for any specific application.

Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

A natural holm oak forest was selectively thinned to test thinning as a tool to reduce tree mortality, increase productivity, and reverse the recent regression of the dominant species (Quercus ilex) induced by climate change. Thinning increased aboveground productivity and reduced stem mortality in this Mediterranean forest during four years just after thinning, contributing to the maintenance of forest functioning under changing climatic conditions. Q. ilex was the only species positively affected by the thinning: stem growth increased for all stem sizes, and mortality was significantly lower in thinned plots. On the contrary, mortality rates of Phillyrea latifolia and Arbutus unedo were not significantly lower. Stem growth increased for P. latifolia only in the smallest stem-size class. Our results highlight the suitability of selective thinning for improving the forest productivity and ensuring the conservation of Mediterranean coppices. Other benefits of selective thinning, such as a decrease in the risk of fire dispersion and an increase in the water supply for human populations, are also discussed.

Abstract The 2013/2017 Nankai Trough (Japan) and 2017 Shenhu Area (China) offshore methane hydrate production tests showed the world the possibility and feasibility of the oceanic methane hydrate production by depressurization. However, the relatively low gas production rate still remained as one of the critical bottlenecks for the economical utilization. This study chose the Nankai Trough as a target area, and aimed at the gas recovery enhancement from the methane hydrate reservoir using vertical wells. A traditional single-vertical-well system and a new dual-vertical-well system were proposed, and special production strategies of the aggressive depressurization and permeability improvement were applied to these two systems for the effectiveness verification. Based on the 15-year simulation results, it was found that the middle low-permeability silt-dominated layers in the reservoir held the key to the gas recovery enhancement, and for the single-vertical-well system, the permeability improvement in this sublayer seemed more reliable and feasible than the aggressive depressurization. On the other hand, the dual-vertical-well system significantly exceeded the single-vertical-well system due to the synergistic effect of the two wellbores, and could raise the average gas production rate (9.5 × 103 m3/day) by one order of magnitude (to 7.9 × 104 m3/day). Moreover, if this new system was combined with the aggressive depressurization, the average gas production rate could be further raised by one order of magnitude (to 3.4 × 105 m3/day).

Humidification dehumidification water desalination system using two cycles of air flow (open and closed-air cycles).