Urban circular economy (UCE) plays a critical role in advancing circular economy (CE) implementation and facilitating urban sustainability transitions. However, existing evaluation frameworks for UCE performance still face challenges in the systematic selection of indicators and their classification across sustainability dimensions. To address this gap, this study develops a structural UCE evaluation framework integrating Social Network Analysis (SNA) and feature-based Semi-Supervised Learning (SSL). Based on 46 existing indicator systems, 198 indicators are analyzed to identify their structural significance and classified into economic, environmental, and social dimensions through a multi-label classification approach. Accordingly, a comprehensive UCE evaluation indicator system is constructed and empirically applied to 44 CE pilot cities in China. The results reveal a mismatch between theoretically emphasized indicators and empirically dominant indicators, particularly in emerging domains such as public awareness and education, indicating a gap between UCE theory and practice. Furthermore, significant spatial heterogeneity is observed, with eastern cities exhibiting higher UCE performance than other regions. The proposed framework extends evaluation beyond conventional indicator aggregation by introducing a structured logic for indicator system design, thereby enhancing methodological rigor. Based on these findings, differentiated urban development strategies are proposed, together with implications for refining indicator-based UCE evaluation frameworks to support sustainable urban transitions.

The confluence of circular economy and carbon emission mitigation strategies has catalyzed the emergence of a concept called the Circular Carbon Economy (CCE). This study introduces a novel CCE evaluation framework targeting urban areas and employs Explainable Artificial Intelligence (XAI) to bolster transparency and interpretability. Through the application of big data mining techniques, key indicators were extracted from literature and policy documents to construct a multi-dimensional CCE evaluation system. This system was integrated with the Explainable Boosting Machine (EBM) model-a key XAI technique-to resolve the precision-interpretability trade-off prevalent in traditional models. The EBM-based framework achieves black-box-level accuracy while providing transparent decision pathways through feature importance quantification. Empirical validation with China's Circular Economy pilot cities demonstrates its applicability, offering a transferable paradigm for global urban CCE assessments. Our findings show that industrial solid waste utilization and the promotion of green buildings are the most critical drivers for advancing CCE in urban areas. The city rankings generated by the EBM model bolster the scientific validity and reliability of our framework. Moreover, the study uncovers significant regional disparities, with cities located in eastern and central China generally exhibiting higher levels of CCE development compared to their western and northeastern counterparts. Based on these insights, we propose three key recommendations-targeted development strategies, differentiated evaluation frameworks, and balanced regional development-to lay the theoretical groundwork and offer practical guidance for urban-level CCE development.

Achieving industrial symbiosis and zero emissions requires integrated frameworks for optimizing industrial waste valorization. However, existing studies often overlook the synergy between operational paradigms and multidimensional efficiency. This study bridges this gap through a mixed-methods investigation of 48 Chinese industrial waste resource (IWR) utilization centers, combining qualitative analysis of 1.90 GB of textual case data with a Multi-Criteria Decision Making-Grey Relational Projection Method (MCDM-GRPM) quantitative analysis framework. Two key contributions emerge: (1) redefining industrial waste as IWRs and formulating a "technology-enterprise-policy" paradigm that integrates policy incentives, cross-sector collaboration, and technological innovation to facilitate closed-loop recycling; and (2) developing a multidimensional efficiency evaluation system incorporating technical, economic, and ecological criteria to assess IWR utilization performance. Findings demonstrate that the proposed paradigm operationalizes the 3R principles, transforming waste into high-value resources while fostering industrial symbiosis. Efficiency analysis reveals notable disparities among centers, with top performers (e.g., DMU25, DMU21) leveraging geographic advantages, waste-type characteristics, and industrial diversification. High efficiency in individual dimensions does not ensure overall performance, underscoring the need for balanced, multicriteria-driven strategies. By integrating qualitative and quantitative insights, this study provides a replicable framework for advancing circular economy transitions and promoting industrial symbiosis, aligning economic and environmental objectives.

Under the dual-carbon targets and the rapid construction of new-type power systems, large-scale photovoltaic (PV) integration has led to pronounced output volatility and severe curtailment in low-load periods, which significantly restricts further improvement of renewable accommodation capability. Focusing on PV accommodation in new-type power systems, this paper develops a coordinated source–grid–load–storage optimization framework that explicitly models PV output uncertainty, flexible demand response, and energy storage regulation. First, mathematical models are established for PV output and net load to capture the impact of high PV penetration on conventional generation scheduling. Then, an integrated model is constructed for energy storage, demand response, and system power balance, and curtailment and PV utilization indicators are defined to quantify accommodation performance. System flexibility margins and PV hosting capacity indices are further introduced to evaluate the ability of the grid to withstand short-term fluctuations. Finally, a multi-objective optimization model is formulated that jointly minimizes operating cost, increases PV utilization, and maintains sufficient flexibility margins, thereby deriving coordinated scheduling strategies for conventional units, energy storage, and responsive loads. The proposed framework provides a systematic modeling and decision-making approach for enhancing PV accommodation in new-type power systems.

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In pursuit of the strategic objectives of "carbon peaking and carbon neutrality," the proportion of installed renewable energy capacity has consistently increased on an annual basis. However, the inherent volatility of renewable energy output does not correspond with the temporal and spatial demands for electricity, thereby complicating the challenge of maintaining power balance. Consequently, Virtual Power Plants (VPPs) and the associated technologies have emerged as vital solutions for reconciling green, low-carbon development with the dual imperatives of energy security and economic electricity supply. In this context, this paper outlines a detailed design for a multi-resource aggregation scheme for Virtual Power Plants (VPPs) and proposes operational models for typical scenarios. A case study of a representative virtual power plant that features various adjustable resources is included. Additionally, the paper analyzes the revenue generated from participation in the electricity market, elucidating the economic aspects of VPP involvement.

PurposeThis study examines how local governments and enterprises can implement ecological restoration of abandoned mines based on ecology-oriented development (EOD), which will be more beneficial to local environmental protection and economic development under the central government’s policy of outcome incentives or process subsidies.Design/methodology/approachWe construct a dynamic differential game model to simulate the interactions between local governments and enterprises during the ecological restoration of abandoned mines from an EOD perspective.FindingsThe findings suggest that under the central government’s outcome incentive policy, cooperation between local governments and enterprises is an optimal strategy. Under the process subsidy policy, while neither cooperative nor non-cooperative models significantly affect the investment levels of local governments and enterprises, a cooperative approach ensures optimal investments from both without solely relying on the process subsidy. Additionally, incorporating altruistic preferences can lead to Pareto improvements in economic and environmental results under central government outcome incentives.Practical implicationsThis research offers a policy foundation for governments to encourage the EOD model in the ecological restoration of abandoned mines. It provides theoretical support for achieving environmental sustainability and high-quality economic development, and is particularly significant for resource-depleted cities seeking to transform their development strategies.Originality/valueThrough a dynamic differential game model involving government agencies and enterprises to simulate decision-making in the ecological restoration of abandoned mines, incorporating altruistic preferences into this restoration process, and identifying optimal strategies and policies for ecological restoration.

Climate change and sustainable development drive transformation in economic development models. Carbon emission reduction and the circular economy propel climate change and sustainable development, yet it's unclear if they synergize or counteract each other. This study examines the question from theoretical and practical perspectives. Using a theory-practice framework, bibliometric and big data analyses were conducted on the Web of Science and Chinese case data, totaling 2.29GB, to explore synergies between carbon emission reduction and the circular economy. The study finds predominantly synergistic interactions between the circular economy and carbon emission reduction, with minimal offsetting effects. That is, the circular economy markedly enhances carbon emissions reduction. At the theoretical level, the two fields are gradually evolving towards in-depth research, while at the practical level, collaboration is coalescing around four areas: hot fields, potential fields, auxiliary fields and common goals. A noteworthy contribution of this study is the development of a framework that synergizes theory and practice, providing a structured approach for future research in this domain. By quantifying the synergistic and offsetting relationship between the circular economy and carbon emissions reduction through systematic big data analysis, this research offers insights essential for achieving the UN's Sustainable Development Goals. We also stress the need for diverse case studies and multi-dimensional analyses in ongoing research.

The acceleration of urbanization has posed significant challenges for the urban organic-waste treatment in megacities and large cities of developing countries. Synergistic organic-waste treatment in eco-industrial parks is essential for achieving China's "zero-waste" and ambitious low-carbon targets. However, the environmental impact and benefit evaluation of synergistic organic-waste treatment in eco-industrial parks remain unclear. In this study, life cycle assessment methods were applied for the environmental management of a newly developed eco-industrial park for synergistic organic-waste treatment in Shenzhen city, China, with a population of 20 million. The synergistic eco-industrial park alleviated the direct and indirect environmental impacts of waste treatment and increased the profit, owing to the electricity recovery, fewer transportation activities, and cocomposting treatment. A 38.8-88.2% decrease was observed in the environmental impacts of unit capacity in the synergistic mode compared to the independent mode. Moreover, the profit in the synergistic mode was 2 times higher than in the case with independent plants. Overall, synergistic organic-waste treatment facilities can be incorporated in industrial parks to treat organic waste in an effective and environmentally friendly manner. These findings can provide novel insights for understanding synergistic organic-waste treatment in eco-industrial parks and enhancing the low-carbon performance of megacities and large cities.

The massive production and accumulation of industrial solid waste (ISW) have led to environmental pollution and natural resource underutilization. China's efforts to build trial industrial waste resource utilization centers provide strong support for sustainable development. However, these centers and the factors driving ISW utilization have yet to be evaluated. This paper utilizes context-dependent data envelopment analysis models without explicit inputs (DEA-WEI) to evaluate the overall utilization performance of 48 industrial waste resource utilization centers in China from 2018 to 2020. It also builds a Tobit model to assess which indicators and waste types affect overall ISW utilization. The results show overall ISW utilization performance of centers in the sample has improved, with the average value falling from 1.7193 in 2018 to 1.5624 in 2020. However, there are clear regional performance gaps, with East China having the highest utilization performance (1.3113) while the Southwest had the lowest (2.2958). Finally, this paper proposes measures to improve the overall utilization of industrial waste resources based on an analysis of the factors driving solid waste utilization.

Hydrothermal treatment (HTT) can efficiently valorize the digestate after anaerobic digestion. However, the disposal of the HTT liquid is challenging. This paper proposes a method to recover energy through the anaerobic co-digestion of food waste and HTT liquid fraction. The effect of HTT liquid recirculation on anaerobic co-digestion performance was investigated. This study focused on the self-generated hydrochars that remained in the HTT supernatant after centrifugation. The effect of the self-generated hydrochars on the methane (CH4) yield and microbial communities were discussed. After adding HTT liquids treated at 140 and 180 °C, the maximum CH4 production increased to 309.36 and 331.61 mL per g COD, respectively. The HTT liquid exhibited a pH buffering effect and kept a favorable pH for the anaerobic co-digestion. In addition, the self-generated hydrochars with higher carbon content and large oxygen-containing functional groups remained in HTT liquid. They increased the electron transferring rate of the anaerobic co-digestion. The increased relative abundance of Methanosarcina, Syntrophomonadaceae, and Synergistota was observed with adding HTT liquid. The results of the principal component analysis indicate that the electron transferring rate constant had positive correlationships with the relative abundance of Methanosarcina, Syntrophomonadaceae, and Synergistota. This study can provide a good reference for the disposal of the HTT liquid and a novel insight regarding the mechanism for the anaerobic co-digestion.

实现碳中和是应对气候问题的重要目标,现有研究缺乏对相关研究热点与演化的总结分析.本文基于文献计量分析方法,对中国知网数据库CNKI(3 674篇)和外文数据库WoS核心合集(9 733篇)中"碳中和"相关主题论文进行分析.研究发现:(1)CNKI高被引文献对技术方法类的研究少于WoS文献;(2)中外文献的作者在团队内部合作较多,团队间的合作略少;(3)地理位置较近的机构合作更多,中国的发文机构和发文量最多,但在影响力上不及美国等发达国家;(4)碳排放问题在两类文献中均为热点方向,CNKI文献侧重于碳排放因素分解与核算的研究,WoS文献更侧重于评估减排效果与研究技术方法.最后,对能源效率与能源转型、碳交易与碳税、隐含碳排放等方面的研究进行了展望.

Green product certification is an important link between sustainable production and consumption, which are widely used by governments to promote sustainable development. However, the risks in the green product certification are not sufficiently addressed. The purpose of this study is to identify and evaluate the risk of green product certification, for a risk index system and the intelligent risk assessment model were constructed, which could provide support for risk management of green product certification. Green furniture products were taken as an example, as they are closely related to daily life and health. Based on the implementation specification of green product certification on furniture in China, six basic links and 19 certification risk indicators were pro-posed. Then an intelligent risk assessment model was constructed using the interpretation structure model, analytical network process and probabilistic neural networks methods. Based on the history data of green furniture product certification in China, the results show that on-site inspection stage has the highest risk weight of 0.3457 among the six links. The comprehensiveness of the information input has the highest risk weight of 0.1290 among the 19 indicators. The intelligent risk assessment model could accurately evaluate the risk, the results showed that there is always a certain risk in the green product certification. Therefore, some suggestions were recommended, certification traceability system, professional staff training and intelligent information filling would be helpful to risk management of green product certification. The results of this study could be extended to other fields of green products and be used for other countries to improve the risk management of green product certification.

生态足迹是衡量可持续发展的有效方法.为更全面了解国内外生态足迹研究进展,基于文献计量与知识图谱方法,以909篇中国知网数据库(CSSCI)和1951篇Web of science核心合集收录期刊数据为研究对象,从国内外生态足迹研究时空分布特征、研究热点及演进趋势方面展开对比分析.研究发现:国内外发文量趋势不同.中文发文量呈倒"U"形曲线,外文发文量呈指数级增长趋势,全球范围内美国发文量最多,中国位居第二;国内外均未形成核心作者群.学科交叉性较强.发文量最大的外文期刊为Ecological Indicators,其他植物、环境、生态学、毒理学、经济学等跨领域的期刊突出了国际生态足迹研究的综合性与交叉性.国内外研究侧重点不同.国内外在可持续发展评估、足迹家族、经济环境关系等方面研究具有相似性,国内研究表明了中国的生态文明政策导向和经济发展阶段特点.最后,认为未来生态足迹研究可能侧重于生态足迹与气候变化耦合、行业或地区的生态承载力/压力、可再生能源的生态效应等方面.

Constructing an eco-civilization is crucial in achieving green, low-carbon development, and thus bridging the gap between theory and practice is imperative to better promote urban ecological transformation. At present, there are inconsistencies and imbalances between theoretical research and practical efforts to achieve an eco-civilization. This paper uses bibliometric analysis and Latent Dirichlet Allocation to analyze China's progress towards an eco-civilization at the theoretical and practical levels. The 'theory' is analyzed using 632 articles, while the 'practice' is analyzed using 100 eco-civilization pilot zone reports. The two are compared, with results showing: First: from 2015 onwards, the theory is moving in an interdisciplinary direction, with seven themes focusing on macro topics. Second: eco-civilization construction projects have multiple overlapping themes, and the growing connection between energy consumption, economic growth and environmental impacts driven by significant projects is the key to improving the level of regional ecological development. Third: the theory and practice are similar in that both are concerned with environmental protection, ecological education, and ecotourism. However, eco-civilization construction projects lack forward-looking and dynamic development tracking of low-carbon research. Finally: the paper proposes that dynamic evaluation and project tracking methods should be applied to monitor critical indicators to achieve a solid link between the theory and practice during eco-construction projects. This paper also proposes academia should do more research on townships and other micro level phenomena to promote climate change and energy revolution in the construction of a Chinese eco-civilization.

Based on LEAP and WEAP, this paper establishes the coupled model of energy and water in cities. With Beijing as a case, 26 scenarios are designed to explore the energy saving/water saving of different policies in Beijing in the future and its nexus effect, including the sensitivity analysis of the results. The results show that the total energy consumption in Beijing will grow slowly by year. Carbon emissions will peak in 2020, and fluctuate after 2035 it will slowly increase until 2050. Total water demand is stable between 3.6 and 4.1 billion cubic meters. According to the forecasted water supply capacity, there is no shortage of water supply and demand. The proportion of groundwater from the source of water supply fell to 27%, and the proportion of water in the South-to-North Water Transfer increased to 40%. The total energy saving of the “13th Five-Year Plan” water saving policy is 1.003 million tons of standard coal, which is equivalent to 8.165 billion kWh of electricity. The energy saving policy has reached 276 million cubic meters of water, equivalent to 140 Kunming Lakes. The energy demand of residents' lives, service industry, construction industry and traditional manufacturing industry has a good correlation with water demand value, which proved they are important water-coupled sectors. In terms of energy-saving/water-saving effects in different scenarios and recent/long range periods, the industrial structure optimization policy showed good energy-saving potential in the short-term, but the long-term energy-saving effect was not obvious, while it was accompanied by an increase in water consumption. The irrigation technology innovation and planting structure optimization scenarios in the agricultural sector have better energy saving and water saving effects in the short term. However, with the occurrence and further expansion of water shortage, the medium and long term the water saving effect is sill, while the energy saving effect is not significant. The sensitivity analysis shows that the parameters of the scenario such as economic slowdown, industrial structure optimization, development of public transportation, and planting structure optimization are more sensitive. For the synergistic effect of water and energy conservation, the synergy effect is more obvious in the energy saving scenarios of the service industry and the industrial sector. For the policies of the same department, the synergistic saving effect of the situation of improving energy intensity is obvious. From the perspective of the difficulty in policy implementation process and overview effects, the water saving and energy saving policies of the industrial sector face more difficulties while implementation. The external power regulation policy and the capital rising residents’ wareness of water saving policy has good performance both in the difficulty of implementation and overview effects.

Economic growth largely requires the support of growth in energy consumption and has also caused many carbon emissions. China is one of the few energy producers and consumers dominated by coal in the world. The rebound in coal energy efficiency will affect the country’s energy security and carbon neutrality by 2060. Therefore, this article initially defines the energy efficiency rebound effect of the coal industry and compares the rebound effect coefficient (REC) at the coal industry level and the enterprise (YK Group) level. The study found that energy intensity at the macro and micro levels has been downward, but with a rebound effect; at the industry level, the REC in the last 20 years was 30.27%, while at the enterprise level is 3.03%. The main reason for the huge gap is the difference in energy consumption statistics at different levels. Finally, this article proposes that coal consumption as raw material should not be defined as ”energy consumption” at the enterprise level. It gives suggestions for energy efficiency improvement at the enterprise level according to the practice.

Ecological civilization construction is an essential means of achieve sustainable development in China. It promotes not only the decoupling of environmental degradation from economic development, but additionally the coupling of positive ecological development with economic development. Presently, most of the research on ecological civilization focuses on its indices and evaluation methods. However, there exist some gaps such as the use of incomplete scientific indicators, and insufficient practice caused by inadequate sample size. In this study, we first take the evaluation framework for ecological civilization pilot areas combined with academic research to construct a comprehensive framework and indicator system. Second, we calculate the Coupling Coordination Degree (CCD) for each of the pilot areas based on the entropy weight and identify typical industries that promote the coupling of ecology and economy. Third, we use the Relative Development Coefficient (RDC) to measure the development of ecology and economy between 2014 and 2019, and study the different kinds of development models for cities. Results of the study found that the regional economy is highly positive correlated with CCD, indicating a mutually reinforcing relationship between economic development and ecological development. Further, the RDC reveals that the level of urban ecological development is relatively higher at the stage of decoupling and coordination with economic system. Finally, strategic emerging industries are a common element in pilot areas with a high level of ecological development, as they offer higher economic output without the ecological degradation associated with traditional industries.

Based on the data of 285 prefecture-level cities, hierarchical cluster analysis and a decomposition approach using the Gini coefficient were used to explore multi-sectoral determinants of the carbon emission inequality in Chinese clustering cities. The results indicate that the emission disparity of the industrial consumption sector is the main source of emission inequalities in clustering city groups. Compared with the base period, the emission inequality of each clustering city group decreased in the reporting period, which was mainly attributed to changes in emissions per capita, whereas an impact of population mobility on emission inequality was not detected. Our results have important implications for Chinese city governments that are to adopt differentiated emission reduction policies.