Search Results (1,410)

Improving carbon emission efficiency (CEE) is crucial for coordinating economic development and reducing carbon emissions. Drawing on panel data for 30 provinces in China from 2013 to 2022, this paper selects six key antecedent conditions guided by the Technology–Organization–Environment (TOE) framework. Then the dynamic qualitative comparative analysis (DQCA) is employed to explore CEE improvement pathways from a configurational perspective, and regression analysis is used to compare the driving effects of different pathways. The findings reveal that (1) single factors cannot independently achieve high CEE; instead, multiple factors must work synergistically to form various improvement pathways, including “technology–organization dual-driven”, “environment-dominated”, and “multi-equilibrium” pathways, with industrial structure upgrading as the core factor for improving CEE; (2) temporally, these improvement pathways demonstrate universality, while, spatially, they exhibit significant provincial heterogeneity; and (3) in terms of marginal effects, the “multi-equilibrium” pathway has the strongest driving effect on CEE. The findings provide valuable policy implications for developing targeted CEE enhancement strategies across provinces at different developmental stages. Full article

China has identified the high-quality development of its green manufacturing transition as the top priority for upgrading their industrial structure system which will lead to the sustainable development of an innovation ecosystem. To assess their progress in this area, this study selects the panel data of 31 provinces in China from 2011 to 2021 and constructs an evaluation index system for the green transformation of the manufacturing industry from four dimensions: environment, resources, economy, and industrial structure. This not only comprehensively and systematically reflects the dynamic changes in the green transformation of the manufacturing industry but also addresses the limitations of currently used indices. The entropy value method is used to calculate the comprehensive score of the green transformation of the manufacturing industry, while the key factors influencing the convergence of the green transformation of the manufacturing industry are further explored. The results show that first, the overall level of the green transformation of the manufacturing industry has significantly improved as evidenced by an approximate 32% increase. Second, regional differences are significant with the eastern region experiencing significantly higher levels of transformation compared to the central and western regions, along with a decreasing trend from the east to the central and western regions. From a policy perspective, the findings suggest that tailored production methods for each region should be adopted with a greater emphasis on knowledge exchanges to promote green transition in less developed regions. In addition, further regulations are required which, in part, focus on increasing the degree of openness to the outside world to promote the level of green manufacturing transition. Full article

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

The impacts of land use transition on ecological environment quality (EEQ) during China’s rapid urbanization have attracted growing concern. However, existing studies predominantly focus on single-scale analyses, neglecting scale effects and driving mechanisms of EEQ changes under the coupling of administrative units and grid scales. Therefore, this study selects Zhejiang Province—a representative rapidly transforming region in China—to establish a “type-process-ecological effect” analytical framework. Utilizing four-period (2005–2020) 30 m resolution land use data alongside natural and socio-economic factors, four spatial scales (city, county, township, and 5 km grid) were selected to systematically evaluate multi-scale impacts of land use transition on EEQ and their driving mechanisms. The research reveals that the spatial distribution, changing trends, and driving factors of EEQ all exhibit significant scale dependence. The county scale demonstrates the strongest spatial agglomeration and heterogeneity, making it the most appropriate core unit for EEQ management and planning. City and county scales generally show degradation trends, while township and grid scales reveal heterogeneous patterns of local improvement, reflecting micro-scale changes obscured at coarse resolutions. Expansive land transition including conversions of forest ecological land (FEL), water ecological land (WEL), and agricultural production land (APL) to industrial and mining land (IML) primarily drove EEQ degradation, whereas restorative ecological transition such as transformation of WEL and IML to grassland ecological land (GEL) significantly enhanced EEQ. Regarding driving mechanisms, natural factors (particularly NDVI and precipitation) dominate across all scales with significant interactive effects, while socio-economic factors primarily operate at macro scales. This study elucidates the scale complexity of land use transition impacts on ecological environments, providing theoretical and empirical support for developing scale-specific, typology-differentiated ecological governance and spatial planning policies. Full article

Operations management personnel emphasize the maintenance of workforce empowerment on the shop floor. This is made possible by implementing effective operations and human resource management practices. However, organizations are adept at controlling the workforce empowerment domain within operational scenarios. In the current industry revolution scenario, industry personnel often face failure due to a laggard mindset in the face of industry revolutions. There are higher possibilities of failure because of standardized operations controlling the shop floor. Organizations utilize well-established human resource concepts, including McClelland’s acquired needs theory, Herzberg’s two-factor theory, and Maslow’s hierarchy of needs, in order to enhance the workforce’s performance on the shop floor. Current SME individuals require fast-paced approaches for tracking the performance and idleness of a workforce in order to control them more efficiently in both flexible and transformational stages. The present study focuses on investigating the parameters and factors that contribute to workforce empowerment in an industrial revolution scenario. The present research is used to develop a framework utilizing operations and human resource management approaches in order to identify and address the issues responsible for deteriorating workforce contributions. The framework includes HRM and operations management practices, including Herzberg’s two-factor theory, Maslow’s theory, and lean and smart approaches. The developed framework contains four phases for achieving desired outcomes on the shop floor. The developed framework is validated by implementing it in a real-life electric vehicle manufacturing organization, where the human resources and operations team were exhausted and looking to resolve employee-related issues instantly and establish a sustainable work environment. The current industry is transforming from Industry 3.0 to Industry 4.0, and seeks future-ready innovations in operations, control, and monitoring of shop floor setups. The operations management and human resource management practices teams reviewed the results over the next three months after the implementation of the developed framework. The results revealed an improvement in workforce empowerment within the existing work environment, as evidenced by reductions in the number of absentees, resignations, transfer requests, and medical issues, by 30.35%, 94.44%, 95.65%, and 93.33%, respectively. A few studies have been conducted on workforce empowerment by controlling shop floor scenarios through modifications in operations and human resource management strategies. The results of this study can be used to fulfil manufacturers’ needs within confined constraints and provide guidelines for efficiently controlling workforce performance on the shop floor. Constraints refer to barriers that have been decided, including production time, working time, asset availability, resource availability, and organizational policy. The study proposes a decision-making plan for enhancing shop floor performance by providing suitable guidelines and an action plan, taking into account both workforce and operational performance. Full article

The ecological environment is crucial for human survival and development. As ecological issues become more pressing, studying the spatiotemporal evolution of ecological quality (EQ) and its driving mechanisms is vital for sustainable development. This study, based on MODIS data from 2000 to 2022 and the Google Earth Engine platform, constructs a remote sensing ecological index for the Beibu Gulf Urban Agglomeration and analyzes its spatiotemporal evolution using Theil–Sen trend analysis, Hurst index (HI), and geographic detector. The results show the following: (1) From 2000 to 2010, EQ improved, particularly from 2005 to 2010, with a significant increase in areas of excellent and good quality due to national policies and climate improvements. From 2010 to 2015, EQ degraded, with a sharp reduction in areas of excellent quality, likely due to urban expansion and industrial pressures. After 2015, EQ rebounded with successful governance measures. (2) The HI analysis indicates that future changes will continue the past trend, especially in areas like southeastern Chongzuo and northwestern Fangchenggang, where governance efforts were effective. (3) EQ shows a positive spatial correlation, with high-quality areas in central Nanning and Fangchenggang, and low-quality areas in Nanning and Beihai. After 2015, both high–high and low–low clusters showed changes, likely due to ecological governance measures. (4) NDBSI (dryness) is the main driver of EQ changes (q = 0.806), with significant impacts from NDVI (vegetation coverage), LST (heat), and WET (humidity). Urban expansion’s increase in impervious surfaces (NDBSI rise) and vegetation loss (NDVI decline) have a synergistic effect (q = 0.856), significantly affecting EQ. Based on these findings, it is recommended to control construction land expansion, optimize land use structure, protect ecologically sensitive areas, and enhance climate adaptation strategies to ensure continuous improvement in EQ. Full article

The rapid development of the logistics industry has underscored the urgent need for efficient and sustainable urban freight systems. As a core component of freight systems, heavy-duty trucks (HDT) have been researched regarding surface-level descriptive statistics of their heterogeneities, such as trip volume, frequency, etc., but there is a lack of in-depth analyses of the spatial interaction between freight travel and freight functional clustering, which restricts a systematic understanding of freight systems. Against this backdrop, this study develops a data-driven framework to analyze HDT behavioral heterogeneity and its spatial interactions with a freight functional zone in Shanghai. Leveraging the high-frequency trajectory data of nearly 160,000 HDTs across seven types, we construct a set of regional indicators and employ hierarchical clustering, dividing the city into six freight functional zones. Combined with the HDTs’ application scenarios, functional characteristics, and trip distributions, we further analyze the spatial interaction between the HDTs and clustered zones. The results show that HDT travel patterns are not merely responses to freight demand but complex reflections of urban industrial structures, infrastructure networks, and policy environments. By embedding vehicle behaviors within their spatial and functional contexts, this study reveals a layered freight system in which each HDT type plays a distinct role in supporting economic activities. This research provides a new perspective for deeply understanding the formation mechanisms of HDT trip distributions and offers critical evidence for promoting targeted freight management strategies. Full article

Urban expansion has a profound impact on both society and the environment. In this study, VOSviewer 1.6.16 and CiteSpace 6.3.R1 were used to conduct a bibliometric analysis of 2987 articles published during the period of 1992–2022 from the Web of Science database in order to identify the research hotspots and trends of urban expansion and its driving factors. The number of articles significantly increased during the period of 1992–2022. The spatiotemporal characteristics and driving forces of urban expansion, urban growth models and simulations, and the impacts of urban expansion were the main research topics. The rate of urban expansion showed regional differences. Socioeconomic factors, political and institutional factors, natural factors, path effects, and proximity effects were the main driving factors. Urban expansion promoted economic growth, occupied cultivated land, and affected ecological environments. Big data and deep learning techniques were recently applied due to advancements in information techniques. With the increasing awareness of environmental protection, the number of studies on environmental impacts and spatial planning regulations has increased. Some political and institutional factors, such as subsidies, taxation, spatial planning, new development strategies, regulation policies, and economic industries, had controversial or unknown impacts. Further research on these factors and their mechanisms is needed. A limitation of this study is that articles which were not indexed, were not included in bibliometric analysis. Further studies can review these articles and conduct comparative research to capture the diversity. Full article

The present study was motivated by the need to enhance indoor air quality and reduce airborne disease transmission in dense urban environments where high-rise residential buildings face challenges in achieving effective natural ventilation. The problem lies in the lack of scalable and convenient tools to optimize natural ventilation rate, particularly in urban settings with varying building heights. To address this, the scientific technique developed with an innovative metric, the urbanized natural ventilation effectiveness factor (uNVeF), integrates regression analysis of wind direction, velocity, air change rate per hour (ACH), window configurations, and building height to quantify ventilation efficiency. By employing a field measurement methodology, the measurements were conducted across 25 window-opening scenarios in a 13.9 m² residential unit on the 35/F of a Hong Kong public housing building, supplemented by the Hellman Exponential Law with a site-specific friction coefficient (0.2907, R² = 0.9232) to estimate the lower floor natural ventilation rate. The results confirm compliance with Hong Kong’s statutory 1.5 ACH requirement (Practice Note for Authorized Persons, Registered Structural Engineers, and Registered Geotechnical Engineers) and achieving a peak ACH at a uNVeF of 0.953 with 75% window opening. The results also revealed that lower floors can maintain 1.5 ACH with adjusted window configurations. Using the Wells–Riley model, the estimation results indicated significant airborne disease infection risk reductions of 96.1% at 35/F and 93.4% at 1/F compared to the 1.5 ACH baseline which demonstrates a strong correlation between ACH, uNVeF and infection risks. The uNVeF framework offers a practical approach to optimize natural ventilation and provides actionable guidelines, together with future research on the scope of validity to refine this technique for residents and developers. The implications in the building industry include setting up sustainable design standards, enhancing public health resilience, supporting policy frameworks for energy-efficient urban planning, and potentially driving innovation in high-rise residential construction and retrofitting globally. Full article

The intensifying global competition for cobalt resources and the increasing likelihood of trade decoupling and disruption are profoundly impacting the global energy transition. In a globalized trade environment, a decline in cobalt supply from exporting countries can spread through the trade network, negatively affecting demand countries. Quantitative analysis of the negative impacts of export supply declines in various countries can help identify early risks in the global supply chain, providing a scientific basis for energy security, industrial development, and policy responses. This study constructs a trade network using trade data on metal cobalt, cobalt powder, cobalt concentrate, and ore sand from the upstream (mining, selection, and smelting) stages of the cobalt industry chain across 155 countries and regions from 2000 to 2023. Based on this, an impact diffusion model is established, incorporating the trade volumes and production levels of cobalt resources in each country to measure their resilience to shocks and determine their direct or indirect dependencies. The study then simulates the impact on countries (regions) when each country’s supply is completely interrupted or reduced by 50%. The results show that: (1) The global cobalt trade network exhibits a ‘one superpower, multiple strong players’ characteristic. Congo (DRC) has a far greater destructive power than other countries, while South Africa, Zambia, Australia, Russia, and other countries have higher destructive power due to their strong storage and production capabilities, strong smelting capabilities, or as important trade transit countries. (2) The global cobalt trade network primarily consists of three major risk areas. The African continent, the Philippines and Indonesia in Southeast Asia, Australia in Oceania, and Russia, the United States, China, and the United Kingdom in Eurasia and North America form the primary risk zones for global cobalt trade. (3) When there is a complete disruption or a 50% reduction in export supply, China will suffer the greatest average demand loss, far exceeding the second-tier countries such as the United States, South Africa, and Zambia. In contrast, European countries and other regions worldwide will experience the smallest average demand loss. Full article

The aim of the article is to highlight the increasing environmental burden on aquatic ecosystems in Slovakia due to continuous pollution from municipal, industrial and agricultural sources. Laboratory analyses have shown alarming exceedance of the limit values of contaminants, with nitrate nitrogen (NO₃⁻) reaching 5.8 mg/L compared to the set limit of 2.5 mg/L and phosphorus concentrations exceeding the permissible values by a factor of five, thereby escalating the risk of eutrophication and loss of ecological stability of the aquatic ecosystem. The accumulation of heavy metals is also a problem—lead (Pb) concentrations reach up to 9.7 μg/L, which exceeds the safe limit by a factor of ten. Despite the measures implemented, such as scum barriers, there is continuous contamination of the aquatic environment, with illegal waste dumps and uncontrolled runoff of agrochemicals playing a significant role. The research results underline the critical need for a more effective environmental policy and more rigorous monitoring of toxic substances in real time. These findings highlight not only the urgency of more effective environmental policy and stricter real-time monitoring of toxic substances, but also the necessity of integrating environmental logistics into the design of sustainable solutions. Logistical approaches including the optimization of waste collection, coordination of stakeholders and creation of infrastructural conditions can significantly contribute to reducing environmental burdens and ensure the continuity of environmental management in ecologically sensitive areas. Full article

The relationship between economic progress and environmental quality remains a central focus in global sustainability discourse. This study examines the link between per capita economic growth and CO₂ emissions across 128 countries from 1996 to 2022, controlling for energy consumption, trade volume, and foreign direct investment (FDI) inflows. It also evaluates the role of governance quality—measured by regulatory quality and its volatility—while considering the globalization index as a confounding factor influencing CO₂ emissions. We test the Environmental Kuznets Curve (EKC) hypothesis, which suggests that emissions initially rise with income but decline after reaching a certain economic threshold. Our findings confirm the global presence of the EKC. The analysis further shows that trade openness, governance, and globalization significantly influence FDI inflows, with FDI, in turn, reinforcing institutional quality through improved governance and globalization indicators. However, in countries with weaker governance and regulatory frameworks, FDI tends to promote pollution-intensive industrial growth, lending support to aspects of the Pollution Haven Hypothesis (PHH). We find a significant departure in EKC explained by post-COVID governance and globalization compromises, which induced the environment towards the PHH phenomenon. These results highlight the need for context-specific policy measures that align economic development with environmental constraints. Full article

Enhancing innovation capability can effectively promote the development of traditional industries. Based on Lewin’s behavioral model theory, this study investigated the relationship between industrial support policies and innovation behavior within traditional industries. Utilizing survey data collected from 152 traditional industrial enterprises in 2024 and employing structural equation modeling, the main findings are as follows: Industrial support policies can effectively alleviate the “innovation inertia” of traditional industries, with all policies being significant at the 1% confidence level. Among them, policies related to industry–university–research cooperation platforms have the most significant impact, with a standardized coefficient of 0.941, followed by fiscal and taxation policies (standardized coefficient: 0.846) and financial policies (standardized coefficient: 0.729). Innovation motivation acts as a mediating mechanism between industrial policies and innovation behavior. Industrial support policies accelerate the conversion of reserve-oriented patent portfolios into practical applications, helping to break through patent barriers and effectively alleviate innovation inertia. Consequently, the government should prioritize improving public services, and policy formulation needs to be oriented towards enhancing innovation efficiency. While ensuring industrial security, it is advisable to moderately increase competition to guide traditional industry market players towards thriving in competitive environments. Full article

The cement industry, a foundation of global infrastructure development, significantly contributes to environmental pollution. Key sources of pollution include dust emissions; greenhouse gases, particularly carbon dioxide; and the release of toxic substances such as heavy metals and particulate matter. These pollutants contribute to air, water, and soil degradation and are linked to severe health conditions in nearby populations, including respiratory disorders, cardiovascular diseases, and increased mortality rates. Noise pollution is also a significant issue, inducing auditory diseases that affect most workers in cement plants, and disturbing the population living in the neighborhoods and fauna behavior. This review explores the pollution paths and the multifaceted impacts of cement production on the environment. It also highlights the social challenges faced by communities, underscoring the urgent need for stricter environmental policies and the adoption of greener technologies to mitigate the adverse effects of cement production on both the environment and human health. Full article

The Three Gorges Reservoir Area in China presents a critical conflict between industrial development and ecological conservation. It functions as a key hub for water management, energy production, and shipping, while also serving as a vital zone for ecological and environmental protection. Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. The findings indicate the following: (1) The RAGA-PP model outperforms conventional AHP-CV methods in assessing Zigui County’s eco-geological environment, showing superior accuracy (higher Moran’s I) and spatial consistency. (2) Hotspot analysis confirms these results, revealing distinct spatial patterns. (3) From 2000 to 2020, “bad” quality areas decreased from 17.31% to 12.33%, while “moderate” or “better” zones expanded. (4) This improvement reflects favorable natural conditions and reduced human impacts. These trends underscore the effectiveness of China’s ecological civilization policies, which have prioritized sustainable development through targeted environmental governance, afforestation initiatives, and stringent regulations on industrial activities. Full article