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The U.S. Environmental Protection Agency’s (EPA) Superfund—the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) database—has collected and built an open-source database based on nearly 2000 US soil remediation cases since 1980, providing detailed information and references for researchers worldwide to carry out remediation work. However, the cases were relatively independent to each other, so the whole database lacks systematicness and instructiveness to some extent. In this study, the basic features of all 144 soil remediation projects in four major oil-producing states (California, Texas, Oklahoma and Alaska) were extracted from the CERCLA database and the correlations among the pollutant species, pollutant site characteristics and selection of remediation methods were analyzed using traditional and machine learning techniques. The Decision Tree Classifier was selected as the machine learning model. The results showed that the growth of new contaminated sites has slowed down in recent years; physical remediation was the most commonly used method, and the probability of its application is more than 80%. The presence of benzene, toluene, ethylbenzene and xylene (BTEX) substances and the geographical location of the site were the two most influential factors in the choice of remediation method for a specific site; the maximum weights of these two features reaches 0.304 and 0.288.

The importance and urgency of energy efficiency in sustainable development are increasing. Accurate assessment of energy efficiency is of considerable significance and necessity. The data envelopment analysis (DEA) method has been widely used to study energy efficiency as a total factor efficiency assessment method. In order to summarize the latest research on DEA in the field of energy efficiency, this article first analyzes the overall situation of related literature published in 2011–2019. Subsequently, the definition, measurement and evaluation variables of energy efficiency are introduced. After that, this article reviews the current DEA model and its extension models and applications based on different scenarios. Finally, considering the shortcomings of the existing DEA model, possible future research topics are proposed.

The electromagnetic vibration caused by electromagnetic force on the stator has threatened large hydro generators operating safely and stably. At the Zhexi hydropower station, the hydro generator was beset by electromagnetic vibration for a long time. Therefore, the paper provided a new method to help to find the vibration source and detect the hydro generator fault, through the combination of simulation and experiments. In this paper, the 3D stator pack structure model and the 2D hydro generator electromagnetic models under rotor eccentricity and rotor ellipse deformation conditions were built. Then, electromagnetism simulations were conducted to study the characteristics of the electromagnetic flux and electromagnetic force under different conditions by using the finite element method (FEM). Lastly, the vibration testing experiments and harmonic response simulations of stator frame were performed to present the characteristics of vibration distribution in frequency conditions. The simulation results were compared with the generator measured data to try to find out the main vibration source and guide the overhaul.

In order to evaluate the displacement effect of four kinds of injection media in tight oil sandstone, water, active water, CO2, N2 flooding experiments were carried out in laboratory. Online Nuclear Magnetic Resonance (NMR) spectrometers combine the advantages of NMR technology and core displacement experiments. In the displacement experiment, NMR data of different injection volumes were obtained and magnetic resonance imaging (MRI) was carried out. The results showed that micro and sub-micropores provided 62–97% of the produced crude oil. The enhanced oil recovery ratio of active water flooding was higher than that of conventional water flooding up to 10%. The recovery ratio of gas flooding in micro and sub-micropores was 60–70% higher than that of water flooding. The recovery ratio of CO2 flooding was 10% higher than that of N2 flooding. The remaining oil was mainly distributed in pores larger than 0.1 μm. Under the same permeability level, the remaining oil saturation of cores after gas flooding was 10–25% lower than water flooding. From MRI images, the displacement effects from good to bad were as follows: CO2 flooding, N2 flooding, active water flooding, and conventional water flooding.

Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.

This article describes the results of a study of Ecuador’s energy status, using the system dynamics methodology to model supply, demand and CO2 emissions scenarios for the year 2030. Primary energy production increased in the different projected scenarios, with oil as the most important source of energy. The increase observed in final energy consumption was mainly associated with the transport and industry sectors. A reduction in energy intensity was projected for the different scenarios, which could be associated with the projected economic growth. The results obtained were used to build a proposal for energy policies aimed at mitigating emissions. The proposed changes to the national energy matrix could be the factors that will contribute most to the achievement of carbon emission reductions projected by the different scenarios; changes in the energy matrix are mainly associated with the development of projects to replace fossil fuels with renewable energies, mainly hydropower.

Perovskite CsPbBr3 quantum dot (CsPbBr3-QD) recovery was performed using lead scrap from lead storage batteries. The perovskite CsPbBr3-QD characteristics were analyzed using different PbO/recycled PbO2 ratios. Scanning electron microscopy (SEM) was used to observe the film surface morphology and cross-section. High-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) were used to observe the perovskite CsPbBr3-QDs’ structural characteristics. A photoluminescence (PL) measurement system was used to analyze the optical properties. The results show that lead scrap from lead–acid batteries as a material for perovskite CsPbBr3-QD production can be successfully synthesized. This saves material and also proves that recycling is valuable. The proposed approach is helpful for future material shortages and materials not easily accessible. Although the efficiency is not very high, this process will be purified using recycled lead in the future to achieve higher quantum yield.