Search Results (1,494)

The integration of renewable energy and power-to-gas (P2G) technology into park-level integrated energy systems (PIES) offers a sustainable pathway for low-carbon development. This paper presents a low-carbon economic dispatch model for PIES that incorporates uncertainties in renewable energy generation and load demand. A novel two-stage P2G, replacing traditional devices with electrolysers (EL), methane reactors (MR), and hydrogen fuel cells (HFC), enhances energy efficiency and facilitates the utilisation of captured carbon. Furthermore, adjustable thermoelectric ratios in combined heat and power (CHP) and HFC improve both economic and environmental performance. A ladder-type carbon trading and green certificate trading mechanism is introduced to effectively manage carbon emissions. To address the uncertainties in supply and demand, the study applies information gap decision theory (IGDT) and develops a robust risk-averse model. The results from various operating scenarios reveal the following key findings: (1) the integration of CCT with the two-stage P2G system increases renewable energy consumption and reduces carbon emissions by 5.8%; (2) adjustable thermoelectric ratios in CHP and HFC allow for flexible adjustment of output power in response to load requirements, thereby reducing costs while simultaneously lowering carbon emissions; (3) the incorporation of ladder-type carbon trading and green certificate trading reduces the total cost by 7.8%; (4) in the IGDT-based robust model, there is a positive correlation between total cost, uncertainty degree, and the cost deviation coefficient. The appropriate selection of the cost deviation coefficient is crucial for balancing system economics with the associated risk of uncertainty. Full article

The development of the digital economy has become a significant driving force for the innovation of green technology in the manufacturing sectors. Green technology innovation in the manufacturing sectors is not only a key engine for realizing economic green transformation and achieving the goal of achieving peak carbon emissions by 2030 and carbon neutrality by 2060, but also an important path for cultivating new quality productivity. Based on Schumpeter’s endogenous growth theory, in this study, we constructed an analytical model with a unified framework of digital economic development and environmental regulation, systematically explored the mechanism of digital economic development with respect to green technological innovation in the manufacturing sectors and the moderating effect of environmental regulation, and carried out empirical research based on panel data at the provincial level and the level of the subdivided manufacturing sectors in China. We found that the development of the digital economy promotes green technology innovation in the manufacturing industry. However, according to the theory of increasing marginal information costs, it shows a significant nonlinear relationship. Absorptive capacity is the key means of support that manufacturing enterprises can leverage to improve their level of green technological innovation. Environmental regulation plays a crucial role in guiding green technological innovation in the manufacturing sectors. A further heterogeneity analysis showed that the development of the digital economy exerts a stronger positive impact on green technological innovation in cleaner-production-oriented manufacturing sectors and those located in regions with more advanced financial regions and in technology-intensive industries. This study provides theoretical support for understanding the driving mechanisms of green technological innovation in the manufacturing sector against the backdrop of the digital economy, offering practical implications for optimizing environmental regulation policies and enhancing the level of green development in manufacturing. Full article

In the context of the “dual-carbon” goal to promote the green and low-carbon transformation of the economy, the mechanism of environmental regulation as a core policy tool for carbon emission reduction remains theoretically controversial. Based on this, this paper uses panel data from 30 provinces in China from 2015 to 2022 and adopts a two-way fixed-effects analysis method to examine the direction and intensity of the impact of environmental regulations on carbon emissions, introducing industrial intelligence and green technological innovation as mediating variables. Research indicates that (1) for every 1-unit increase in the intensity of environmental regulation, carbon emissions are reduced by about 0.9866 units on average, and its carbon emission reduction effect is more significant in the eastern region, where the proportion of secondary industry is medium and high, as well as in non-technology-intensive regions. (2) Industrial intelligence and green technological innovation play a partial mediating role between environmental regulations and carbon reduction. (3) After categorizing green technology innovations, it is found that environmental regulations do not significantly incentivize substantive green technology innovations, but they can contribute to carbon emission reduction by promoting the development of strategic green technology innovations. (4) The analysis of spatial effects shows that carbon emissions in China’s provinces are characterized by significant spatial agglomeration. Enforcement of environmental regulations also exerts a suppressive effect on carbon emissions in adjacent provinces, and its carbon emission reduction effect is characterized by “total effect > indirect effect > direct effect”. Compared with existing studies, this paper elucidates the transmission mechanism whereby environmental regulation achieves carbon emission reductions through industrial intelligence and green technological innovation, thereby contributing a novel analytical framework for examining regulatory impacts on carbon emissions while furnishing actionable policy implications for facilitating socioeconomic greening and low-carbon transitions. Full article

With the rising importance of nuclear energy in the global energy landscape, the sustainable development of uranium resources has garnered increasing attention. Salt lake brine, as an unconventional uranium source, holds significant potential due to its relatively high uranium concentration and the co-occurrence of valuable elements such as lithium, boron, and potassium. However, the high salinity and complex ionic composition of brine environments pose considerable challenges for the efficient and selective extraction of uranium. In recent years, the rapid advancement of novel adsorbent materials has provided promising technological pathways for uranium extraction from salt lake brine. This review systematically summarizes recent progress in the application of inorganic and carbon-based materials, organic polymers with functional group modifications, and biomass-derived and green adsorbents in this field. The construction strategies, performance characteristics, and adsorption mechanisms of these materials are discussed in detail, with particular emphasis on their selectivity and stability under complex saline conditions. Furthermore, the application status and future prospects of emerging materials and techniques—such as photocatalysis and electrochemistry—are also explored. This review aims to offer theoretical insights and technical references to support the sustainable exploitation of uranium resources from salt lake brines. Full article

This study examines whether China’s high-tech enterprise identification policy promotes corporate sustainable innovation. Using panel data from Chinese listed firms on the Shanghai and Shenzhen stock exchanges between 2008 and 2022, we adopt a time-varying difference-in-differences (DID) model to evaluate the policy’s effectiveness and explore its underlying mechanisms. The results reveal that this certification policy significantly facilitates green innovation, and the findings remain robust across various checks, including alternative measurements, placebo tests, propensity score matching DID (PSM-DID), and the exclusion of digital transformation trend and confounding macro-level policies. Mechanism analysis shows that the policy influences green innovation by alleviating financing constraints, increasing access to government subsidies, facilitating the agglomeration of scientific and technological talent, and encouraging greater R&D investment. Heterogeneity analysis further indicates that the policy effect is more pronounced among non-state-owned enterprises, small-scale firms, capital-intensive businesses, those located in high-institutional-quality regions, and firms in China’s eastern provinces. Moreover, the positive impact is strongest for growth-stage firms. The policy has also been found to improve green innovation efficiency. These findings offer empirical insights for optimizing selective industrial policies to enhance sustainable innovation and support China’s dual-carbon goals. Full article

Environmental protection tax (EPT), as a major tool to improve air quality and reduce carbon emissions, is of great significance for promoting urban low-carbon transformation. In this context, this paper has compiled a dataset from 282 Chinese cities during 2006–2022 and empirically identify the implication of EPT for carbon emissions at the city level by using the intensity difference-in-differences (I-DID) model. The result discloses that EPT greatly lowers carbon emissions by an average of 10.9% compared to non-pilot cities. Even after conducting some robustness checks, the result remains unchanged. Mechanism testing reveals that EPT curbs carbon emissions through enhancing energy utilization efficiency, fostering green technological advancements, and modernizing urban industries. Meanwhile, we show that EPT exerts a more substantial effect on carbon emissions in innovative cities, central and western cities, non-industrial-based cities, and non-resource-dependent cities. More importantly, EPT greatly promotes imitation and learning in neighboring regions, forming a radiation impact upon carbon reduction in surrounding areas. Hence, these results offer an important decision-making guide for optimizing the EPT system, strengthening the coordinated governance of carbon emission across regions, and ultimately promoting urban low-carbon development. Full article

As urbanization progresses rapidly, cities face growing challenges of land resource scarcity and the pressure on green ecological spaces. This not only affects the sustainable development of cities but also presents a major challenge to the resilience of urban ecosystems (UER). As an emerging land use model, land financialization (LF), which involves the circulation and financing of land as a financial asset, has become an important means to promote UER. Therefore, this paper examines 221 prefecture-level cities across mainland China to explore the impact of land financialization on urban ecological resilience and aims to reveal the specific pathways through which land financialization improves urban ecological resilience through mechanisms like resource reallocation, industrial structure rationalization, green innovation, green signals, and environmental regulation. This paper employs a two-way fixed effects model, robustness tests, and endogeneity tests, supplemented by mechanism and heterogeneity analysis, to explore the impact of LF on UER. The findings show that LF plays a significant role in improving UER. Mechanism analysis reveals that LF significantly boosts UER by optimizing the distribution of land and financial resources, as well as enhancing the rationalization of the industrial structure. Additionally, enterprise green technology innovation, green value, and the intensity of environmental regulation play a positive moderating role in this process. In addition, the heterogeneity analysis reveals the inclusive characteristics of LF on urban ecological transformation. In cities with higher levels of land price distortion, as well as in old industrial cities, small cities, and peripheral cities with poorer resource characteristics and administrative resources, LF has a more significant impact on promoting the improvement of UER. Based on the findings, this paper proposes policy recommendations to promote the improvement of urban green ecology and support the innovation of land financialization. These insights contribute to the theoretical discourse on greenization and provide essential, practical guidance for optimizing the allocation of land and financial resources, as well as establishing a framework for green and high-quality development. Full article

This study develops a comprehensive analytical framework to examine how nations secure core positions in global supply chains (GSCs) for key industries. It combines a comparative analysis of advanced economies—Los Angeles (aerospace), Munich (high-end manufacturing), London (biopharmaceuticals), and Tokyo (automotive)—with a survey-based empirical assessment of Chinese industry practitioners. Using the Analytic Hierarchy Process (AHP), factor analysis and the Delphi method, an evaluation framework is constructed across five dimensions: technology, value, governance, resilience, and sustainability. The findings show that developed economies sustain their leadership through upstream innovation and standard-setting, coordination of high-value activities, integrated industrial ecosystems, and risk-buffering mechanisms. Empirical results reveal that while China demonstrates relative strengths in governance and value creation, it continues to lag in frontier technologies, resilience, and sustainability. Building on both comparative and empirical evidence, the study proposes strategic pathways for China’s key industries, including technological breakthroughs, innovation-driven clusters, governance reforms, digital resilience, and green cooperation. These insights provide actionable guidance for policymakers and highlight how latecomer economies can transform structural disadvantages into innovation momentum, evolving from participants to rule-setters in global supply chains. Full article

As a new type of production factor, releasing data dividends is of great significance in improving corporate energy efficiency. Based on the data of listed enterprises in China from 2011 to 2022, the establishment of government open data platforms in each prefecture-level city is taken as a policy shock event, and the impact of government open data on corporate energy efficiency is empirically examined through a multi-period DID model. The results show that government open data improves enterprise energy efficiency by approximately 2.5% (relative to the mean), and capacity utilization and biased technological progress are the main pathways of action. In addition, the application of big data technology can better fulfill the role of data factors in improving enterprise energy efficiency. Heterogeneity analysis finds that government open data has a stronger effect on enterprise energy efficiency improvement in areas with high manufacturing concentration, environmental tax rate leveling, and high Internet penetration. The study suggests that enterprises should apply big data technology and build a mechanism for integrating data assets and energy management so as to fulfill the important role of data elements in the green development of enterprises. Full article

Agriculture is fundamental to food security and environmental sustainability. Advancing its holistic ecological transformation can stimulate socioeconomic progress while fostering human–nature harmony. Utilizing provincial data from mainland China (2013–2022), this research establishes a multidimensional evaluation framework across four pillars: agricultural ecology, low-carbon practices, modernization, and productivity enhancement. Through comprehensive assessment, we quantify China’s low-carbon green agriculture (LGA) development trajectory and conduct comparative regional analysis across eastern, central, and western zones. As for methods, this study employs multiple econometric approaches: LGA was quantified using the TOPSIS entropy weight method at the first step. Moreover, multidimensional spatial–temporal patterns were characterized through ArcGIS spatial analysis, Dagum Gini coefficient decomposition, Kernel density estimation, and Markov chain techniques, revealing regional disparities, evolutionary trajectories, and state transition dynamics. Last but not least, Tobit regression modeling identified driving mechanisms, informing improvement strategies derived from empirical evidence. The key findings reveal the following: 1. From 2013 to 2022, LGA in China fluctuated significantly. However, the current growth rate is basically maintained between 0% and 10%. Meanwhile, LGA in the vast majority of provinces exceeds 0.3705, indicating that LGA in China is currently in a stable growth period. 2. After 2016, the growth momentum in the central and western regions continued. The growth rate peaked in 2020, with some provinces having a growth rate exceeding 20%. Then the growth rate slowed down, and the intra-regional differences in all regions remained stable at around 0.11. 3. Inter-regional differences are the main factor causing the differences in national LGA, with contribution rates ranging from 67.14% to 74.86%. 4. LGA has the characteristic of polarization. Some regions have developed rapidly, while others have lagged behind. At the end of our ten-year study period, LGA in Yunnan, Guizhou and Shanxi was still below 0.2430, remaining in the low-level range. 5. In the long term, the possibility of improvement in LGA in various regions of China is relatively high, but there is a possibility of maintaining the status quo or “deteriorating”. Even provinces with a high level of LGA may be downgraded, with possibilities ranging from 1.69% to 4.55%. 6. The analysis of driving factors indicates that the level of economic development has a significant positive impact on the level of urban development, while the influences of urbanization, agricultural scale operation, technological input, and industrialization level on the level of urban development show significant regional heterogeneity. In summary, during the period from 2013 to 2022, although China’s LGA showed polarization and experienced ups and downs, it generally entered a period of stable growth. Among them, the inter-regional differences were the main cause of the unbalanced development across the country, but there was also a risk of stagnation and decline. Economic development was the general driving force, while other driving factors showed significant regional heterogeneity. Finally, suggestions such as differentiated development strategies, regional cooperation and resource sharing, and coordinated policy allocation were put forward for the development of LGA. This research is conducive to providing references for future LGA, offering policy inspirations for LGA in other countries and regions, and also providing new empirical results for the academic community. Full article

In this study, a green and efficient extraction methodology was developed by leveraging the unique properties of chitosan—namely its non-toxicity, biocompatibility, and adhesive nature—to enhance the recovery of bioactive ingredients from Forsythia suspensa leaves. The core mechanism involves the formation of complexes between chitosan and the target bioactive ingredients, which significantly boosts their extraction efficiency. To substantiate this mechanism, comprehensive characterization was performed using Powder X-ray Diffraction (PXRD), Fourier Transform Infrared Spectroscopy (FT-IR), Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), and molecular docking analyses. The results provided robust evidence of a strong interaction between chitosan and the bioactive ingredients, leading to a marked enhancement in both the stability and aqueous solubility of the target compounds. For process optimization, a multi-objective approach was implemented using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to simultaneously maximize the extraction yields of phillyrin and forsythoside A. The algorithm identified the optimal parameters as a leaf-to-chitosan mass ratio of 10:11.75, a solid-to-liquid ratio of 1:52 g/mL, a temperature of 80 °C, and a duration of 120 min. Under these optimized conditions, the corresponding extraction yields for phillyrin and forsythoside A were 1.68 ± 0.16% and 3.23 ± 0.27%, respectively. These findings collectively indicate that chitosan-assisted extraction represents a highly promising and advanced technology for the sustainable and effective extraction of bioactive ingredients from botanical sources. Full article

China’s sustained economic growth and industrialisation have led to increasingly serious problems of resource consumption and environmental pressure, making green development an inevitable choice for the country’s transformation and development. Green finance policies are becoming an increasingly important tool for increasing the use of green energy in cities. Using a dual machine learning (DML) model, this paper assesses the specific impact of green finance policies on green energy efficiency in Chinese cities, the mechanism of action, and regional disparities. The analysis is based on objective and scientific measurement of the level of green finance policies and green energy efficiency in 282 Chinese cities at prefecture level and above from 2006 to 2022. Benchmark regression results show that green finance policies significantly promote green energy efficiency in Chinese cities, passing a rigorous robustness test. Green bond policies are found to have the greatest promotional effect, whereas green support policies are found to have no significant effect. The results of the heterogeneity analysis suggest that green finance policies are more effective in promoting green energy efficiency in resource-based cities, cities with established industrial bases, and more developed cities. The results of the impact mechanism suggest that green finance policies can promote green energy efficiency by allocating the three internal urban factors of labour, capital and technology. The results of the analysis of regional disparities demonstrate that green finance policies effectively reduce disparities in urban green energy efficiency at the national level, between the north and south, and between coastal and inland regions. However, they also widen the disparities between central and peripheral cities within each province, hindering balanced regional development. This paper makes relevant policy recommendations based on this. Full article

In Central Asian countries (CACs) atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

Apolygus lucorum is one of the main pests affecting tea quality. Chemical control is the primary method for managing this pest, but issues such as pesticide residues and the development of resistance are inevitable. The pest’s extensive host range holds significant practical implications for developing novel food baits. This study first investigated the preference of adult A. lucorum for tea branches under different conditions and various host plants by using the Y-tube olfactometer. Subsequently, the trapping efficacy of active tea volatile components and food baits was tested. The results revealed that adult A. lucorum exhibited a stronger preference for healthy and mechanically damaged tea branches, while they avoided branches infested with high densities of conspecifics. Adult A. lucorum showed significantly higher selection rates for Gossypium hirsutum, Vigna radiata leaf, Glycine max leaf, Phaseolus vulgaris, Lablab purpureus, and Brassica pekinensis compared with healthy tea branches. In field trials, three tea volatile baits showed effective trapping performance, (E,E)-α-farnesene, nonanal, and (Z)-3-hexenol. Three mixture baits of foods and tea plant volatiles, B. pekinensis + (Z)-3-hexenol, P. vulgaris + (E,E)-α-farnesene, and S. melongena + (Z)-3-hexenol, not only demonstrated high attractiveness but also maintained a residual effect period as long as 20 days. This study provides new insights and approaches for the integrated management of A. lucorum and offers technical support for the development of novel green pest control technologies in tea plantations. Full article

Despite extensive research on green consumption, consumer purchase intentions for bamboo products under China’s “replacing plastic with bamboo” policy remain underexplored, given growing plastic pollution concerns. Research remains focused on established green products (e.g., green agriculture, energy-efficient appliances, new energy vehicles), overlooking consumer behavior and cognition toward emerging bamboo alternatives. This study employs eye-tracking technology to examine purchase intentions and visual attention allocation mechanisms for bamboo versus plastic products, analyzing the role of green consumption values (GCVs). Using a 2 (material: bamboo/plastic) × 2 (GCVs: high/low) mixed design, we recorded fixation duration, fixation count, and heatmaps from 70 participants. Behavioral results revealed significantly higher purchase intention for bamboo products, particularly among high-GCV consumers. Eye-tracking data showed greater visual attention (fixation duration/count) to bamboo products, with high-GCV participants exhibiting significantly stronger attentional bias toward bamboo. Findings demonstrate that bamboo’s eco-friendly attributes enhance both purchase intention and visual attention allocation, validating material salience in green decision-making. High GCVs strengthen automatic attentional bias toward sustainable materials, reinforcing purchase inclinations. This research provides empirical support for VBN theory at the cognitive level and offers policy-relevant insights for promoting “Bamboo Instead of Plastic” initiatives. Full article