Search Results (1,818)

Green innovation is a critical driver of sustainable development, yet it often faces efficiency challenges in rapidly industrializing economies. This study investigates the effect of China’s Circular Economy Demonstration Policy (CEDP) on urban green innovation efficiency (GIE) using city-level panel data from 2010 to 2021. Employing a difference-in-differences (DID) approach, we find that CEDP significantly enhances GIE, with the policy effect becoming statistically significant after a three-year lag and accumulating over time. Robustness tests, including placebo analyses, alternative dependent variables, and propensity score matching, confirm the validity of the results. Mechanism analysis reveals that the policy improves green innovation primarily by reducing capital distortion, promoting market integration, and enhancing resource allocation efficiency. Further heterogeneity analyses show that the positive effects are stronger in central cities, capital cities, and eastern regions, reflecting the role of local economic and institutional conditions. The study concludes with policy implications emphasizing regionally tailored implementation, capacity building, and long-term commitment to maximize green innovation outcomes. Full article

China’s economy is shifting from an era of rapid expansion to one focused on high-quality development, making it imperative to tackle environmental degradation linked to energy use. Understanding how New Quality Productive Forces (NQPF) interact with energy efficiency, along with the mechanisms driving this relationship, is essential for economic transformation and long-term sustainability. This study establishes an evaluation framework for NQPF, integrating technological, green, and digital dimensions. We apply fixed-effects models, the spatial Durbin model (SDM), a moderation model, and a threshold model to analyze the influence of NQPF on Green Total Factor Energy Efficiency (GTFEE) and its spatial implications. This underscores the necessity of distinguishing it from traditional productivity frameworks and adopting a new analytical perspective. Furthermore, by considering dimensions such as input, application, innovation capability, and market efficiency, we reveal the moderating role and heterogeneous effects of artificial intelligence (AI). The findings are as follows: The development of NQPF significantly enhances GTFEE, and the conclusion remains robust after tail reduction and endogeneity tests. NQPF has a positive spatial spillover effect on GTFEE; that is, while improving the local GTFEE, it also improves neighboring regions GTFEE. The advancement of AI significantly strengthens the positive impact of NQPF on GTFEE. AI exhibits a significant U-shaped threshold effect: as AI levels increase, its moderating effect transitions from suppression to facilitation, with marginal benefits gradually increasing over time. Full article

Green manufacturing has emerged as a critical objective in the evolution of advanced production systems. Although digital twin technology is widely recognized for enhancing efficiency and promoting sustainability, the majority of existing research focuses exclusively on physical systems. They neglect the impact of soft systems, including human behavior, decision-making, and operational strategies. To address this limitation, the present study introduces an innovative hybrid digital twin model that integrates both physical and soft systems to support green manufacturing initiatives comprehensively. The primary contributions of this work are threefold. First, a novel hybrid architecture is developed by coupling real-time physical data with virtual soft system components that simulate factory operations. Second, lean production principles are systematically incorporated into the soft system, thereby facilitating reduced energy consumption and minimizing environmental impact. Third, a parameter-driven programming model is formulated to correlate critical variables with green performance metrics, and a genetic algorithm is utilized to optimize these variables, ultimately enhancing sustainability outcomes. This integrated approach not only expands the applicability of digital twin technology but also offers a data-driven decision-support tool for the advancement of green manufacturing practices. Full article

Systems thinking (ST) is a foundational cognitive skillset to advance sustainability education but has not been well examined for learners prior to higher education. This case study research in rural middle schools in the Midwestern U.S. examines systems thinking outcomes of a place-based energy literacy unit focused on energy-efficient building design. The unit employs the science of energy-efficient, green buildings to illuminate the ways in which energy flows between natural and built environments. The unit emphasized electrical, light, and thermal energy systems and the ways these systems interact to create functional and energy-efficient buildings. This study focuses on three case study classrooms where students across schools (n = 89 students) created systems models as part of pre- and post-unit tests (n = 162 models). The unit tests consisted of student drawings, annotations, and writings, culminating into student-developed systems models. Growth from pre- to post-test was observed in both the identification of system elements and the linkages between elements. System elements included in the models were common classroom features, such as windows, lights, and temperature control, suggesting that rooting the unit in place-based teaching may support ST skills. Full article

This study presents the development of Cu-doped NiMo/TiO₂ photoelectrocatalysts for simultaneous green hydrogen production and pharmaceutical pollutant removal under simulated solar irradiation. The catalysts were synthesized via wet impregnation (15 wt.% total metal loading with 0.6 wt.% Cu) and thermally treated at 400 °C and 900 °C to investigate structural transformations and catalytic performance. Comprehensive characterization (XRD, BET, SEM, XPS) revealed phase transitions, enhanced crystallinity, and redistribution of redox states upon Cu incorporation, particularly the formation of NiTiO₃ and an increase in oxygen vacancies. Crystallite sizes for anatase, rutile, and brookite ranged from 21 to 47 nm at NiMoCu400, while NiMoCu900 exhibited only the rutile phase with 55 nm crystallites. BET analysis showed a surface area of 44.4 m²·g⁻¹ for NiMoCu400, and electrochemical measurements confirmed its higher electrochemically active surface area (ECSA, 2.4 cm²), indicating enhanced surface accessibility. In contrast, NiMoCu900 exhibited a much lower BET surface area (1.4 m²·g⁻¹) and ECSA (1.4 cm²), consistent with its inferior photoelectrocatalytic performance. Compared to previously reported binary NiMo/TiO₂ systems, the ternary NiMoCu/TiO₂ catalysts demonstrated significantly improved hydrogen production activity and more efficient photoelectrochemical degradation of paracetamol. Specifically, NiMoCu400 showed an anodic peak current of 0.24 mA·cm⁻² for paracetamol oxidation, representing a 60% increase over NiMo400 and a cathodic current of −0.46 mA·cm⁻² at −0.1 V vs. RHE under illumination, nearly six times higher than the undoped counterpart (–0.08 mA·cm⁻²). Mott–Schottky analysis further revealed that NiMoCu400 retained n-type behavior, while NiMoCu900 exhibited an unusual inversion to p-type, likely due to Cu migration and rutile-phase-induced realignment of donor states. Despite its higher photosensitivity, NiMoCu900 showed negligible photocurrent, confirming that structural preservation and surface redox activity are critical for photoelectrochemical performance. This work provides mechanistic insight into Cu-mediated photoelectrocatalysis and identifies NiMoCu/TiO₂ as a promising bifunctional platform for integrated solar-driven water treatment and sustainable hydrogen production. Full article

This study aims to develop an optimal underwriting strategy for affordable (H1 and M1) and premium (L1 and M2) electric vehicles (EVs), balancing financial risk and sustainability commitments. The research is motivated by regulatory pressures, risk management needs, and sustainability goals, necessitating an adaptation of traditional underwriting models. The study employs a modified Delphi method with industry experts to identify key risk factors, including accident risk, repair costs, battery safety, driver behavior, and PCAF carbon impact. A sensitivity analysis was conducted to examine premium adjustments under different risk scenarios, categorizing EVs into four risk segments: Low-Risk, Low-Carbon (L1); Medium-Risk, Low-Carbon (M1); Medium-Risk, High-Carbon (M2); and High-Risk, High-Carbon (H1). Findings indicate that premium EVs (L1 and M2) exhibit lower volatility in underwriting costs, benefiting from advanced safety features, lower accident rates, and reduced carbon attribution penalties. Conversely, budget EVs (H1 and M1) experience higher premium fluctuations due to greater accident risks, costly repairs, and higher carbon costs under PCAF implementation. The worst-case scenario showed a 14.5% premium increase, while the best-case scenario led to a 10.5% premium reduction. The study recommends prioritizing premium EVs for insurance coverage due to their lower underwriting risks and carbon efficiency. For budget EVs, insurers should implement selective underwriting based on safety features, driver risk profiling, and energy efficiency. Additionally, incentive-based pricing such as telematics discounts, green repair incentives, and low-carbon charging rewards can mitigate financial risks and align with net-zero insurance commitments. This research provides a structured framework for insurers to optimize EV underwriting while ensuring long-term profitability and regulatory compliance. Full article

Fungal lytic polysaccharide monooxygenases (LPMOs) have revolutionized the field of biomass degradation by introducing an oxidative mechanism that complements traditional hydrolytic enzymes. These copper-dependent enzymes catalyze the cleavage of glycosidic bonds in recalcitrant polysaccharides such as cellulose, hemicellulose, and chitin, through the activation of molecular oxygen (O₂) or hydrogen peroxide (H₂O₂). Their catalytic versatility is intricately modulated by structural features, including the histidine brace active site, surface-binding loops, and, in some cases, appended carbohydrate-binding modules (CBMs). The oxidation pattern, whether at the C1, C4, or both positions, is dictated by subtle variations in loop architecture, amino acid microenvironments, and substrate interactions. LPMOs are embedded in a highly synergistic fungal enzymatic system, working alongside cellulases, hemicellulases, lignin-modifying enzymes, and oxidoreductases to enable efficient lignocellulose decomposition. Industrial applications of fungal LPMOs are rapidly expanding, with key roles in second-generation biofuels, biorefineries, textile processing, food and feed industries, and the development of sustainable biomaterials. Recent advances in genome mining, protein engineering, and heterologous expression are accelerating the discovery of novel LPMOs with improved functionalities. Understanding the balance between O₂- and H₂O₂-driven mechanisms remains critical for optimizing their catalytic efficiency while mitigating oxidative inactivation. As the demand for sustainable biotechnological solutions grows, this narrative review highlights how fungal LPMOs function as indispensable biocatalysts for the future of the Circular Bioeconomy and green industrial processes. Full article

An ultrasonic-enhanced hydrogen peroxide water-washing process was developed to recover lead from raw flue dust (RFD) under neutral conditions. At optimal parameters (40 °C, 30 min, 4 mL H₂O₂, liquid-to-solid ratio 2:1, 240 W ultrasound), the Pb mass fraction in the solid residue increased from 41.68% in the RFD to 68.11%, accompanied by a Pb recovery rate of 97.1%. These values are significantly higher than those obtained under identical conditions without ultrasound (64.07% and 95.93%, respectively). Ultrasound promotes de-agglomeration and generates •OH radicals that accelerate the oxidation of PbSO₃ to insoluble PbSO₄ while concurrently removing impurity cadmium. This research offers a green and efficient alternative to traditional lead recovery methods, fostering sustainable development in the metallurgical industry. Full article

As Chinese open-pit mines progressively transition to deeper operations, challenges such as rising stripping ratios, declining slope stability, and environmental degradation have become increasingly pronounced. The sustainability of traditional open-pit mining models faces substantial challenges. Underground mining, offering higher resource recovery rates and minimal environmental disruption, is emerging as a pivotal technological pathway for the green transformation of mining. Consequently, the transition from open-pit to underground mining has emerged as a central research focus within mining engineering. This paper provides a comprehensive review of key technological advancements in this transition, emphasizing core issues such as mine development system selection, mining method choices, slope stability control, and crown pillar design. A typical case study of the Anhui Xinqiao Iron Mine is presented to analyze its engineering approaches and practical experiences in joint development, backfilling mining, and ecological restoration. The findings indicate that the mine has achieved multi-objective optimization of resource utilization, environmental coordination, and operational capacity while ensuring safety and recovery efficiency. This offers a replicable and scalable technological demonstration for the green transformation of similar mines around the world. Full article

Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable outputs. We decompose AGTFP into technical change and efficiency change, conduct redundancy analysis to identify sources of inefficiency and explore its spatiotemporal dynamics through kernel density estimation and convergence analysis. Results show that (1) AGTFP in Tibet grew at an average annual rate of 0.78%, slower than the national average of 1.6%; (2) labor input, livestock scale, and agricultural carbon emissions are major sources of redundancy, especially in pastoral regions; (3) technological progress is the main driver of AGTFP growth, while efficiency gains have a limited impact, reflecting a technology-led growth pattern; (4) AGTFP follows a “convergence-divergence-reconvergence” trend, with signs of conditional β convergence after controlling for regional heterogeneity. These findings highlight the need for region-specific green agricultural policies. Priority should be given to improving green technology diffusion and input allocation in high-altitude pastoral areas, alongside strengthening ecological compensation and interregional coordination to enhance green efficiency and promote high-quality development across Tibet. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

: This study reports the development of a sustainable biocatalyst system for free fatty acid (FFA) production from cocoa bean shell (CBS) oil using Burkholderia cepacia lipase (BCL). CBS was explored as both a support material and a reaction substrate. Six immobilized systems were prepared using organic (CBS), inorganic (silica), and hybrid (CBS–silica) supports via physical adsorption or covalent binding. Among them, the covalently immobilized enzyme on CBS (ORG-CB) showed the most balanced performance, achieving a catalytic efficiency (Ke) of 0.063 mM⁻¹·min⁻¹ (18.6% of the free enzyme), broad pH–temperature tolerance, and over 50% activity retention after eight reuse cycles. Thermodynamic analysis confirmed enhanced thermal resistance for ORG-CB (Ed = 32.3 kJ mol⁻¹; ΔH‡ = 29.7 kJ mol⁻¹), while kinetic evaluation revealed that its thermal deactivation occurred faster than for the free enzyme under prolonged heating. In application trials, ORG-CB reached 60.1% FFA conversion from CBS oil, outperforming the free enzyme (49.9%). These findings validate CBS as a dual-function material for enzyme immobilization and valorization of agro-industrial waste. The results also reinforce the impact of immobilization chemistry and support composition on the operational and thermal performance of biocatalysts, contributing to the advancement of green chemistry strategies in enzyme-based processing. Full article

The contamination of water bodies by industrial dyes poses a significant environmental challenge on a global scale. Conventional wastewater treatment methods often suffer from limitations related to high cost, limited efficiency, and potential secondary environmental impacts. Recent advances in photocatalytic technologies have highlighted the potential of metal sulfide-based photocatalysts, particularly those synthesized through environmentally friendly, plant-mediated approaches, as promising alternatives for efficient and sustainable dye degradation. However, despite their promising potential, metal sulfide photocatalysts often suffer from limitations such as photocorrosion, low stability under irradiation, and rapid recombination of charge carriers, which restrict their long-term applicability. In light of these challenges, this review provides a comprehensive examination of the physicochemical characteristics, synthetic strategies, and photocatalytic applications of metal sulfides. Particular emphasis is placed on green synthesis routes employing plant-derived extracts, which offer environmentally benign and sustainable alternatives to conventional methods. Moreover, the review elucidates various modification approaches, most notably, the formation of heterostructures, as viable strategies to enhance photocatalytic efficiency and mitigate the aforementioned drawbacks. The green synthesis of metal sulfides, aligned with the principles of green chemistry, offers a promising route toward the development of sustainable and environmentally friendly water treatment technologies. Full article

This study examines the safety and cost-effectiveness of implementing shoulder rumble strips (SRS) and road lighting on Saudi Arabian freeways, providing insights into their roles in fostering sustainable transport systems. By leveraging the Highway Safety Manual (HSM) framework, this research develops localized Crash Modification Factors (CMFs) for these interventions, ensuring evidence-based and context-specific evaluations. Data were collected for two periods—pre-pandemic (2017–2019) and post-pandemic (2021–2022). For each period, we obtained traffic crash records from the Saudi Highway Patrol database, traffic volume data from the Ministry of Transport and Logistic Services’ automated count stations, and roadway characteristics and pavement-condition metrics from the National Road Safety Center. The findings reveal that SRS reduces fatal and injury run-off-road crashes by 52.7% (CMF = 0.473) with a benefit–cost ratio of 14.12, highlighting their high cost-effectiveness. Road lighting, focused on nighttime crash reduction, decreases such crashes by 24% (CMF = 0.760), with a benefit–cost ratio of 1.25, although the adoption of solar-powered lighting systems offers potential for greater sustainability gains and a higher benefit–cost ratio. These interventions align with global sustainability goals by enhancing road safety, reducing the socio-economic burden of crashes, and promoting the integration of green technologies. This study not only provides actionable insights for achieving KSA Vision 2030’s target of improved road safety but also demonstrates how engineering solutions can be harmonized with sustainability objectives to advance equitable, efficient, and environmentally responsible transportation systems. Full article

Although product environmental information serves as an effective tool for promoting green consumption which is a critical lever for advancing broader sustainability goals, its varied impacts across product categories (durable goods vs. fast-moving consumer goods) and the underlying mechanisms remain unexplored. Grounded in the theory of consumption values (TCV), this study investigated the heterogeneous effects and mediating pathways of such information through a comparative analysis of representative products: organic milk (fast-moving consumer goods, FMCGs) and energy-efficient air conditioners (durable goods). The results show the following: (1) epistemic value, which exhibits the strongest association with product environmental information, demonstrates significantly different influence patterns between purchases of green durable goods and green FMCGs across both online and offline channels; (2) in the e-commerce context, green FMCG consumption is mainly driven by product environmental information through the mediating effect of conditional value. For green durable goods, product environmental information influences green consumption through multiple pathways including functional value, conditional value, and epistemic value. This study extends the classic theory of consumption values, and the results suggest that differentiated information strategies of emphasizing conditional value for FMCGs and integrating multi-dimensional values for durables can optimize green consumption promotion. Such strategies hold substantial potential to strengthen the green development of the omnichannel retailing sector, reinforcing its contribution to reaching sustainability objectives. Full article