Xue Bai

Energy-efficiency labeling may yield lower savings than engineering estimates suggest because market uptake is constrained by consumers and enterprises. This study aims to quantify this gap for dishwasher energy-efficiency labeling in China, identify the binding constraint, and assess its recoverable share. A logistic stock-flow model estimates theoretical savings under GB 38383-2019, while surveys of 199 consumers and 191 enterprises parameterize a dual-sided indicator system. Assuming that consumer and enterprise capacities are non-substitutable, a weakest-link model and scenario simulations estimate realized and recoverable savings. Theoretical savings reach 20.26 TWh by 2030, but only 55.9% (11.33 TWh) is realizable, leaving an 8.94 TWh gap. Consumer-side capacity (0.559) is lower than enterprise-side capacity (0.657), mainly because of experience-related barriers. The highest-intensity bilateral scenario recovers 33.0% of the gap and raises the realization rate to 70.4%. Thus, stricter standards alone cannot ensure realized savings; policies should prioritize consumer experience and label accessibility alongside enterprise compliance.

Edible oil is a primary energy source in human diets. This study investigates the effects of heating temperature on the physicochemical properties of edible oils and their impact on dishwasher cleaning performance. First, the density and dynamic viscosity of peanut oil, rapeseed oil, and soybean oil were measured at room temperature and after heating to 50, 100, 150, 200, and 250 °C. Accordingly, two oils with the greatest viscosity difference—soybean oil at room temperature (SO_25) and peanut oil heated to 250 °C (PO_250)—were selected for dishwasher cleaning performance tests. Residue penalty score (RPS) and re-deposition penalty score (RDPS) were defined to characterize the cleaning ability and anti-redeposition performance of dishwashers. The results indicated that PO_250 generally exhibited lower cleaning scores. In the quick wash mode, the RPS and RDPS of PO_250 and SO_25 were relatively similar; however, in the standard wash mode, both RPS and RDPS of PO_250 were higher than those of SO_25. Statistical analysis further revealed that changes in washing mode have a greater impact on cleaning scores for high-viscosity oil than for low-viscosity oil. Moreover, low-viscosity oil exhibited greater inter-machine variability in dishwasher cleaning scores compared with high-viscosity oil. Scanning electron microscopy (SEM) imaging showed that PO_250 formed an oil film on the ceramic surface, whereas SO_25 appeared as discrete particles. This study provides a scientific basis for developing regionally applicable dishwasher testing standards, contributing to the optimization of cleaning technologies.

With the rapid adoption of dishwashers in China’s households, the consequent growth in energy and water consumption presents new challenges for energy conservation, emission reduction, and water resource management in China. To address this, this study adopts the concept of the energy–water nexus to analyze the factors influencing dishwasher usage behaviors and quantifies the co-benefits of energy and water conservation through questionnaire surveys, establishing a household dishwasher energy and water accounting model. The findings reveal that dishwasher usage behaviors are influenced by dietary habits—greater oil usage in cooking leads to higher frequency of use and a greater tendency to select intensive wash modes, thereby increasing energy and water consumption. It is projected that by 2030, promoting energy-efficient dishwashers could achieve annual savings of approximately 390 million kWh of electricity and 4 million m³ of water. Furthermore, shifts in dietary habits offer significant potential for achieving co-benefits in energy and water conservation. Encouraging households to adopt low-oil cooking practices could yield additional annual savings of 5.14 billion kWh of electricity and 9.57 million m³ of water. Based on these results, this paper puts forward policy recommendations to facilitate the coordinated management of household energy and water conservation.

This study collected operational data from 2021 to 2023 to analyze the specific energy consumption (SEC) distribution and evaluate the impacts of influencing factors on SEC, including geographical region, plant scale, loading rate, treatment technology, and effluent quality. Through Spearman's rank correlation analysis, it is determined that in China, characterizing the SEC by the energy consumption per unit treated wastewater volume is more reliable. The results of statistical analysis indicated that the overall median SEC is 0.38 kWh/m3, representing a remarkable upward trend compared with the level prior to the nationwide effluent quality standard upgrades. Box-plot analysis was employed to investigate the effects of single factors and their two-factor interactions on SEC, and the random forest regression (RFR) algorithm was used to quantify the feature importance of each factor. The results showed that the loading rate emerged as the most robust key determinant of SEC, maintaining a consistent impact power across different groups of factors. The findings illustrate the current energy consumption levels in China's wastewater treatment and may provide insights for optimizing process selection based on expected loading conditions in wastewater treatment plants.

The standard testing of washing machine performance faces reliability challenges, which stem from the uncontrollable degradation of base load. This study provided a quantified standard for base load age to enhance the reliability and stability of the washing machine performance testing process. First, the impact of base load aging on the cleaning performance and water extraction performance was investigated. Simultaneously, the changes in reflectance of the base load were recorded. Then, MLR and ANN models were developed using the remaining moisture content and reflectance of the base load to predict base load age. It was found that the water extraction performance is more easily affected by the aging of the base load than the cleaning performance. In addition, ANN has better performance in predicting base load age, resulting in an R_c² of 0.978, RMSEC of 9.295 h, and R_cv² of 0.972 h, RMSECV of 10.639 h for the front-loading washing machine, and R_c² of 0.958, RMSEC of 12.948 h, and R_cv² of 0.940, RMSECV of 15.572 h for the top-loading washing machine. This study establishes a theoretical foundation for optimizing base load age regulation. Further study could expand the sample size to enhance the robustness and generalizability of the proposed method.

Mechanical draft cooling towers are among the most critical water-consuming equipment in industries such as thermal power and petrochemicals. Strengthening their water usage performance is therefore crucial for alleviating China’s water resource pressure. To this end, this study employs the makeup water rate indicator to analyze the core factors influencing water-use efficiency in mechanical draft cooling towers, utilizing Spearman’s rank correlation coefficient analysis and partial least squares regression (PLSR) methods. The results reveal that ambient temperature and inlet pressure exhibit significant negative correlations with the makeup water rate, while blowdown pressure and concentration multiple show significant positive correlations. Gray correlation analysis indicates that blowdown pressure (correlation degree: 0.923) and concentration multiple (correlation degree: 0.897) are the key driving factors. The PLSR-based prediction model for the makeup water rate demonstrates a strong goodness of fit, with explanatory power exceeding 80%. This research provides a modeling foundation for optimizing the operational control of mechanical draft cooling towers, thereby promoting sustainable management of industrial water use.

Under the multiple pressures of intensifying global climate change disruption and rapid economic growth, China has become one of the countries facing the most serious water scarcity problems. Based on the ISO 14046 standard and the framework of water scarcity footprint theory, this study will break through the static limitations and lack of dimensions of traditional characteristic factors (i.e., water stress) and construct a water stress evaluation index system that combines nature, economy, and society. The results indicate that in recent years, regional water stress in China has exhibited significant spatiotemporal variations and spatial clustering, primarily driven by composite factors, with an overall decreasing trend. Among them, Shanghai is the highest-pressure area and Shaanxi is the lowest-pressure area, which is mainly due to the spatial projection of the coupling effect of multi-dimensional factors. In addition, the obstacle degree analysis method shows that indicators such as the utilization rate of water resource development constitute cross-regional constraints. To this end, all regions should make efforts to regulate and control the water use structure, introduce water-saving technologies, and strengthen water-saving publicity according to their needs. Therefore, this study not only provides a scientific basis for in-depth understanding of the distribution law and influencing mechanism of water stress but also provides an important reference for the rational allocation and sustainable use of water resources by upgrading the characteristic factors to system control signals.

In the context of increasing water scarcity, improving industrial water efficiency and resource management has become an urgent need, particularly in water-intensive sectors such as the cement industry. Based on the Water Life Cycle Assessment (WLCA) framework, in this study, a comprehensive assessment of water use, consumption, reuse, and wastewater discharge during cement production was conducted, and paths were proposed for improving water efficiency. Unlike traditional water footprint assessments, which primarily focus on measuring water consumption, the WLCA integrates a holistic analysis of the operational status of water systems. The research results show that for cement production in the Yellow River Basin, the waste heat power generation system accounts for the highest proportion of water consumption (65%), with its circulating cooling unit functioning as the core water-related subsystem. A large quantity of daily circulating cooling wastewater can be reused in production after treatment. Significant differences exist in unit product water consumption among enterprise types: clinker and cement production enterprises (0.18–0.30 m³/t) have higher water consumption than cement grinding stations (0.02–0.05 m³/t), and some enterprises hold considerable water-saving potential. Wastewater recovery and treatment technologies can markedly reduce water wastage. Meanwhile, waste heat recovery technologies improve energy utilization efficiency and indirectly lower water cooling demand. Additionally, waste co-processing technologies reduce virtual water consumption by replacing part of the coal used in cement production. This research provides practical technical solutions for water conservation and resource optimization in the cement industry, facilitating improvements in water efficiency management.

Against the backdrop of implementing the national carbon peaking and carbon neutrality strategy, this study proposes a standardized evaluation system for building low (zero) carbon industrial parks, which encompasses principles of construction, evaluation methods, indicators system, data collection, indicators calculation, evaluation results, and implementation steps. This proposal follows a deep understanding on the challenges facing industrial parks, such as trade barriers and discrepancies in technical standards, as well as opportunities under the context of high-quality development. Through quantitative analysis on the layout and distribution characteristics of government-approved industrial parks, it figures out the status quo of industrial parks in the development zone. Moreover, a case study of an economic development zone in the southeastern coastal area is made to validate the evaluation. Finally, this paper gives suggestions on the dynamic adjustment of indicators of the evaluation system and the collection of full-sample data.