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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.

Environment-friendly treatment of sewage sludge has become tremendously important. Conversion of sewage sludge into energy products by environment-friendly conversion process, with its energy recovery and environmental benefits, is being paid significant attention. Direct liquefaction of sewage sludge into bio-oils with supercritical water (SCW) was therefore put forward in this study, as de-water usually requiring intensive energy input is not necessary in this direct liquefaction. Supercritical water may act as a strong solvent and also a reactant, as well as catalyst promoting reaction process. Experiments were carried out in a self designed high-pressure reaction system with varying operating conditions. Through orthogonal experiments, it was found that temperature and residence time dominated on bio-oil yield compared with other operating parameters. Temperature from 350 to 500°C and reaction residence time of 0, 30, 60min were accordingly investigated in details, respectively. Under supercritical conversion, the maximum bio-oil yield could achieve 39.73%, which was performed at 375°C and 0min reaction residence time. Meanwhile, function of supercritical water was concluded. Fuel property analysis showed the potential of bio-oil application as crude fuel.

Abstract A great deal of heat is wasted in intensive public shower facilities, such as those in schools, barracks and natatoriums, which open up at specified time. It will contribute a lot to energy saving and environmental protection with significant economic benefits to recycle the exhaust heat. In this paper, we propose two different kinds of heat pumps (an electric heat pump and an absorption heat pump) in the heat recovery systems. In both system, the used shower water is drained through a pipe and collected in a gray water pool. When the wastewater reaches certain volume, the heat pump system will begin working and recycling heat. The wastewater is filtered and piped to the heat exchanger to exchange heat with the tap water whose temperature will increase from 12 °C to 25 °C with the wastewater temperature dropping from 30 °C to 17 °C. Then the wastewater is piped to the heat pump evaporator and the tap water is piped to the condenser for farther heating. According to the different characteristics of the electric heat pump and absorption heat pump, we also introduce the processes and control methods of different heat recovery systems in details in this paper. Based on a practical example, this paper analyzes and compares the economic and environmental benefits of three retrofitting schemes, including “exhaust heat recovery using electric heat pump”, “exhaust heat recovery using electric heat pump + gas boiler” and “exhaust heat recovery using direct-fired heat pump”. Then we find out that the heat recovery system using direct-fired absorption heat pump has lower energy consumption, less pollution, lower operating cost, and shorter payback period. And it has a promising practical application.

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: The dynamics of reformation and replacement of gas hydrates were studied under nonequilibrium conditions. It was found that the reformation of gas hydrates is largely affected by the state of the gas‐water system and the restarting temperature. This suggests that the effects are caused by changes in the structure of the aqueous solution at a molecular level. Pure samples of CH4 gas hydrate were synthesized from ice crystals and the dissociated solution using the reformation method. Replacement of CO2 gas hydrate is achieved within a short duration in the solid‐phase sample of CH4 gas hydrate, if the pressure and temperature is precisely controlled in a pressure vessel.

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.

To find an appropriate method for sulfate-rich wastewater containing ethanol and acetate with COD/sulfate ratio of 1, a UASB reactor was operated for more than 180 days. The influences of HRT (hydraulic retention time) and OLR (organic loading rate) on organics and sulfate removal, gas production, and electrons utilization were investigated. The sludge activity and microorganism composition were also determined. The results indicated that this system removed more than 80% of COD and 30% of sulfate with HRT above 6h and OLR below 12.3 gCOD/L d. Further HRT decrease caused volatile fatty acids accumulation and performance deterioration. Except at HRT of 2h, COD and electron flow were mostly utilized by methane-producing archaea (MPA), and methane yield remained in the range of 0.18-0.24 LCH4/gCOD. Methane was mainly generated by Methanosaeta concilii GP6 with acetate as substrate, whereas sulfate was mainly reduced by incomplete-oxidizing Desulfovibrio species with ethanol as substrate.