Search Results (845)

Measuring and simulating territorial space conflicts (TSCs) for the achievement of carbon neutrality is of critical significance for formulating regional sustainable utilization of territorial resources that are inherently green and low-carbon. This study develops a TSC evaluation framework: “conflict identification–scenario simulation–carbon effect assessment”. Focusing on Jiangsu Province, we clarify the evolutionary mechanism of TSCs under carbon neutrality goals, providing a scientific basis for high-quality regional development and low-carbon spatial governance. Results show that Jiangsu’s average TSC level was categorized as “strong conflict” (0.66) during 2005–2020. For 2030, four scenarios (natural development, economic priority, ecological protection, low-carbon development) project TSCs shifting from scattered to point-like distribution, concentrating in key core areas. Corresponding projected average carbon neutrality indices are 1.10, 1.11, 1.33, and 1.11, respectively. Under the low-carbon scenario, grid units with serious TSCs decreased by 4.53% compared to 2020—higher than natural development and economic priority scenarios, but lower than the ecological protection scenario (12.45%). Consequently, the low-carbon development scenario can optimally mitigate land use conflicts while maintaining carbon balance. This research provides robust data support for Jiangsu’s sustainable coordinated development and informs efficient land use and regional ecological security. Full article

Compared with other forest vegetation, bamboo forests have a stronger carbon sequestration capacity, which plays a vital role in achieving the national goals of carbon peak and carbon neutrality. Global warming has profoundly impacted the adaptive distribution and landscape fragmentation of bamboo forests. This study utilized an optimized MaxEnt model to calculate the current habitat range of Neosinocalamus affinis (Rendle) Keng f. forests across China and project their potential distribution under three future climate scenarios (SSP126, SSP370, SSP585) for the 2050s and 2090s and analyzed the landscape fragmentation of their land use using landscape indices. The results reveal that Neosinocalamus affinis forests are currently primarily distributed in Chongqing Municipality, eastern and southeastern Sichuan Province, and northern Guizhou Province. The key environmental factors influencing their distribution are identified as: mean diurnal temperature range (Bio2), precipitation of warmest quarter (Bio18), and precipitation of wettest quarter (Bio16). Across the three future scenarios, the suitable habitat area for Neosinocalamus affinis forests demonstrates an overall expanding trend. Rising CO₂ concentrations correlate with a reduction in suitable habitat. The habitat centroid shifts southward in the 2050s and northeastward in the 2090s. In the future, the fragmentation degree of highly suitable areas for Neosinocalamus affinis forests will be higher than at present and show an increasing trend, with forest fragmentation significantly intensifying and overall landscape quality further declining. The predictive results of this study provide a scientific basis for the effective conservation and management of Neosinocalamus affinis forests, thereby contributing to the sustainable utilization of bamboo forest resources. Full article

Amid the dual-driven trends of Industry 5.0 and smart manufacturing integration, as well as the global imperative for manufacturing sustainability to address resource constraints, carbon neutrality goals, and circular economy demands, human–robot collaborative (HRC) manufacturing has emerged as a core direction for reshaping manufacturing production modes while aligning with sustainable development principles. This paper comprehensively reviews HRC manufacturing systems, summarizing their technical framework, practical applications, and development trends with a focus on the synergistic realization of operational efficiency and sustainability. Addressing the rigidity of traditional automated lines, inefficiency of manual production, and the unsustainable drawbacks of high energy consumption and resource waste in conventional manufacturing, HRC integrates humans’ flexible decision-making and environmental adaptability with robots’ high-precision and continuous operation, not only improving production efficiency, quality, and safety but also optimizing resource allocation, reducing energy consumption, and minimizing production waste to bolster manufacturing sustainability. Its core technologies include task allocation, multimodal perception, augmented interaction (AR/VR/MR), digital twin-driven integration, adaptive motion control, and real-time decision-making, all of which can be tailored to support sustainable production scenarios such as energy-efficient process scheduling and circular material utilization. These technologies have been applied in automotive, aeronautical, astronautical, and shipping industries, boosting high-end equipment manufacturing innovation while advancing the sector’s sustainability performance. Finally, challenges and future directions of HRC are discussed, emphasizing its pivotal role in driving manufacturing toward a balanced development of efficiency, intelligence, flexibility, and sustainability. Full article

This study investigates how consumer brand trust is shaped by the interplay of sustainability disclosure valence (positive/negative), domain (social/environmental), and information source credibility (internet influencer/scientific report). Using a mixed-methods approach, combining a series of focus groups and a 2 × 2 × 2 between-subjects scenario experiment with a sample of 354 university students, we analyzed both the main and interactive effects of these factors on brand trust via hierarchical regression. The findings confirm that positive disclosures in both social and environmental domains significantly enhance brand trust. We observed a significant synergistic interaction, where consistent positive disclosures across both sustainability domains yield the greatest increase in trust. The study uncovers a domain-specific boundary condition for source credibility. While the source of information significantly moderates the impact of social sustainability disclosures—with influencers failing to generate the same punitive impact as scientific reports regarding social transgressions—source credibility exerts no significant influence on environmental disclosure processing. These findings suggest that consumers process environmental data as technical information (source-neutral) but social data as moral signals (source-dependent). Practically, the results suggest that brands require a holistic sustainability communication strategy and rely on highly credible sources for sensitive social messaging, especially when managing reputational risk or responding to negative disclosures. Full article

This paper proposes a data-driven model-free robust predictive control strategy for parallel three-level NPC inverters based on finite control set model predictive control (FCS-MPC), focusing on the zero-sequence circulating current (ZSCC) problem under parameter mismatch conditions. A set of virtual voltage vectors with zero average common-mode voltage (CMV) is introduced to effectively suppress ZSCC without adding additional constraints to the cost function. Meanwhile, an Integral Sliding Mode Observer (ISMO) is integrated into the predictive control framework to enhance robustness and enable reliable control using only input–output data. Unlike existing studies that primarily consider ZSCC suppression under an ideal system, this work specifically addresses the practical scenario in which system parameters deviate from their nominal values. Even when ZSCC suppression strategies are employed, parameter mismatch can still lead to noticeable circulating currents, motivating the need for a more robust solution. Simulation and experimental results validate that the proposed approach achieves excellent current tracking, neutral-point voltage balance, and effective ZSCC suppression under parameter variations, demonstrating strong robustness and feasibility for practical applications. Full article

As low-carbon supply chains increasingly integrate green transition strategies with digital transformation, coordinating high-cost green technology investments with data-driven marketing (DDM) becomes a complex managerial task. While these dual investments are essential for market growth, the inherent tension between economic efficiency and fairness concerns often triggers strategic friction phenomenon whose impact under cap-and-trade regulations remains insufficiently explored. This paper investigates the strategic implications of fairness concerns in a low-carbon supply chain in which a manufacturer invests in carbon emission reduction and a retailer engages in data-driven marketing (DDM), under a cap-and-trade regulation. We formulate four Stackelberg game models—Neutral Benchmark (NF), Retailer Fairness (RF), Manufacturer Fairness (MF), and Bilateral Fairness (BF)—to analyze the interplay between behavioral equity and economic efficiency. The main analytical results indicate that (1) fairness concerns universally function as an “efficiency tax” on the supply chain system, where the rational benchmark consistently yields the highest system efficiency. In contrast, bilateral fairness concerns lead to the worst performance due to double friction effects. (2) Counter-intuitively, the retailer can “weaponize” fairness concerns to extract surplus from the leader. Specifically, in environments with high carbon emission reduction costs, a fairness-concerned retailer compels the manufacturer to grant significant wholesale price concessions, thereby achieving higher profits than in a purely rational setting. (3) The manufacturer’s fairness creates a “Benevolence Trap” for the follower; to balance equity, a fair manufacturer tends to underinvest in green technologies, which severely contracts market demand and, unlike the retailer fairness scenario, fails to yield economic benefits for the retailer. (4) A critical “regime-switching” dynamic exists regarding the carbon trading price. While the retailer benefits from fairness strategies in nascent carbon markets, a pivot to rationality becomes optimal as carbon prices surge and efficiency dividends dominate. These findings offer novel managerial insights for supply chain members to navigate behavioral complexities and for policymakers to align incentive mechanisms. Full article

Under the dual pressures of global climate change and China’s “carbon peak and carbon neutrality” targets, traditional urban development models are insufficient to support sustainable transitions. Smart cities (SCs) have emerged as key platforms for achieving low-carbon urban transformation, yet the systemic causal mechanisms and dynamic transmission pathways of carbon emissions within these cities remain underexplored. This study develops an integrated DEMATEL–ISM–SD modeling framework to systematically identify key drivers, reveal causal structures, and simulate the dynamic evolution of carbon emissions in SCs. Eighteen influencing factors were identified through a comprehensive literature review. DEMATEL analysis evaluated the causal strength and centrality of factors, ISM constructed a five-level hierarchical structure, and a system dynamics model was established for scenario simulation, using Shenzhen as a case study. The results show that green technological innovation capacity exhibits the highest centrality, while energy structure demonstrates the strongest causal influence. SC policy intensity is positioned at the deepest level of the hierarchical structure, serving as a foundational driver that exerts influence on all other factors. Scenario simulations indicate that enhancing green innovation, optimizing industrial and energy structures, and developing smart transportation systems can significantly reduce carbon emissions over time. The research findings reveal the key drivers and transmission pathways of carbon emissions in SCs, providing a reference basis for policy formulation on urban low-carbon transformation and sustainable development. Full article

The European Union’s energy transition is based on three fundamental pillars, the realisation of which is intended to achieve climate neutrality by 2050. These pillars comprise the decarbonization of the economy, the development of renewable energy sources (RES), and the improvement of energy efficiency. The prevailing decarbonization trend involves a systematic reduction in the use of fossil fuels across the economy and their replacement with energy derived from low-emission and renewable sources. These objectives pose a significant challenge, particularly for countries such as Poland, where electricity generation remains predominantly reliant on hard coal and lignite. In recent years, a substantial reduction in CO₂ emissions has been observed in the energy sector, primarily due to the increasing share of renewables in the electricity generation mix. The main energy companies, most of which are majority-owned by the State Treasury, have developed specific strategies to meet these targets. This article analyses the strategic documents of domestic energy companies together with other publicly available sources. Based on these documents, projections have been developed regarding the decommissioning of individual generating units in public power plants and combined heat and power facilities fuelled by hard coal and lignite. Scenario-based analyses were then conducted, drawing on these projections and assumptions, to assess the potential scale of CO₂ emission reductions from the domestic energy sector through to 2050. Full article

The study presents a comprehensive assessment of greenhouse gas (GHG) emissions and the carbon footprint (CF) of high-percentage spirit production in a Polish distillery. The analysis followed the GHG Protocol and ISO 14067:2018 standards, covering direct and indirect emissions across three Scopes. Using life cycle assessment (LCA) with a gate-to-gate boundary, emissions were across key technological processes. Verified operational data for 2022–2024 included detailed records of energy and fuel consumption. Electricity use was identified as the dominant emission source, accounting for 70–93% of total GHG emissions, followed by natural gas and transport fuels. The integration of renewable energy sources, including biomass and photovoltaic installations, resulted in a significant decrease in GHG emissions. The average carbon footprint of spirit production declined from 1.02 kg CO_2eq/L in 2022 to 0.12–0.15 kg CO_2eq/L in 2023–2024, representing an over 85% reduction in emission intensity. Production increased, but the company implemented better practices, including the use of biomass and photovoltaics as energy sources, which translated into a reduction in its carbon footprint. Scenario analysis showed that implementing the replacement of conventional fuels with renewables could lower total GHG emissions by up to 35%. The results confirm that renewable energy implementation and energy-efficiency improvements are effective decarbonization strategies for the spirits industry, supporting compliance with European Green Deal objectives and the transition toward climate-neutral production. Full article

Many cities worldwide face decline due to mineral-resource exhaustion, with mining-induced subsidence and land degradation posing urgent land use challenges. At the same time, carbon neutrality has become a global agenda, promoting ecological restoration, emissions reduction, and green transformation in resource-exhausted cities. However, empirical evidence on how carbon neutrality strategies drive land use transition remains scarce. Taking Xuzhou, China, as a case study, we integrate the GeoSOS–FLUS land use simulation model with a Markov chain model to project land use patterns in 2030 under three scenarios: natural development (ND), land recovery (LR), and carbon neutrality (CN). Using emission factors and a land use carbon inventory, we quantify spatial distributions and temporal shifts in carbon emission and sequestration. Results show that LR’s rigid recovery policies restrict broader transitions, while the CN scenario effectively reshapes land use by enhancing the competitiveness of low-carbon types such as forests and new-energy land. Under CN, built-up land expansion is curbed, forests and new-energy land are maximized, and emissions fall by 4.95% from 2020. Carbon neutrality offers opportunities for industrial renewal and ecological restoration in resource-exhausted cities, steering transformations toward approaches that balance ecological function and carbon benefits. Long-term monitoring is required to evaluate policy sustainability and effectiveness. Full article

Decarbonizing heavy-duty freight transport is essential for achieving climate neutrality targets. Although internal combustion engine (ICE) trucks currently dominate logistics, they contribute substantially to greenhouse gas emissions. Zero-emission alternatives, such as battery electric vehicles (BEVs) and hydrogen fuel cell vehicles (H2), provide different decarbonization pathways; however, their relative roles remain contested, particularly in small economies. While BEVs benefit from technological maturity and declining costs, hydrogen offers advantages for high-payload, long-haul operations, especially within energy-intensive cold supply chains. The aim of this paper is to examine the gradual transition from ICE trucks to hydrogen-powered vehicles with a specific focus on cold-chain logistics, where reliability and energy intensity are critical. The hypothesis is that applying a system dynamics forecasting approach, incorporating investment costs, infrastructure coverage, government support, and technological progress, can more effectively guide transition planning than traditional linear methods. To address this, the study develops a system dynamics economic model tailored to the structural characteristics of a small economy, using a European case context. Small markets face distinct constraints: limited fleet sizes reduce economies of scale, infrastructure deployment is disproportionately costly, and fiscal capacity to support subsidies is restricted. These conditions increase the risk of technology lock-in and emphasize the need for coordinated, adaptive policy design. The model integrates acquisition and maintenance costs, fuel consumption, infrastructure rollout, subsidy schemes, industrial hydrogen demand, and technology learning rates. It incorporates subsystems for fleet renewal, hydrogen refueling network expansion, operating costs, industrial demand linkages, and attractiveness functions weighted by operator decision preferences. Reinforcing and balancing feedback loops capture the dynamic interactions between fleet adoption and infrastructure availability. Inputs combine fixed baseline parameters with variable policy levers such as subsidies, elasticity values, and hydrogen cost reduction rates. Results indicate that BEVs are structurally more favorable in small economies due to lower entry costs and simpler infrastructure requirements. Hydrogen adoption becomes viable only under scenarios with strong, sustained subsidies, accelerated station deployment, and sufficient cross-sectoral demand. Under favorable conditions, hydrogen can approach cost and attractiveness parity with BEVs. Overall, market forces alone are insufficient to ensure a balanced zero-emission transition in small markets; proactive and continuous government intervention is required for hydrogen to complement rather than remain secondary to BEV uptake. The novelty of this study lies in the development of a system dynamics model specifically designed for small-economy conditions, integrating industrial hydrogen demand, policy elasticity, and infrastructure coverage limitations, factors largely absent from the existing literature. Unlike models focused on large markets or single-sector applications, this approach captures cross-sector synergies, small-scale cost dynamics, and subsidy-driven points, offering a more realistic framework for hydrogen truck deployment in small-country environments. The model highlights key leverage points for policymakers and provides a transferable tool for guiding freight decarbonization strategies in comparable small-market contexts. Full article

The global energy transition faces a chasm between current policy commitments (IEA’s STEPS) and the deep, rapid transformation required to realize all national net zero pledges (IEA’s APC). This perspective addresses the critical innovation and policy gap blocking the APC pathway, where many high-impact, clean technologies remain at low-to-medium Technology Readiness Levels (TRLs 3–6) and lack formal policy support. The insufficient nature of current climate policy nomenclature is highlighted, which often limits Nature-based Solutions (NbS) to incremental projects rather than driving systemic technological change (Bio-inspiration). Then, we propose that a deliberate shift from simple biomimetics (mimicking form) to biomimicry (emulating life cycle sustainability) is the essential proxy for acceleration. Biomimicry inherently targets the grand challenges of resilience, resource efficiency, and multi-functionality that carbon-centric metrics fail to capture. To institutionalize this change, we advocate for the mandatory integration of bio-inspired design into National Determined Contributions (NDCs) by reframing NbS as Nature-based Innovation (NbI) and introducing novel quantitative metrics. Finally, a three-step roadmap to guide this systemic shift is presented, from deployment of prototypes (2025–2028), to scaling evidence and standardization (2029–2035), to consolidation and regenerative integration (2036–2050). Formalizing these principles through policy will de-risk investment, mandate greater R&D rigor, and ensure that the next generation of energy infrastructure is not just carbon-neutral, but truly regenerative, aligning technology deployment with the necessary speed and depth of the APC scenario. Full article

Climate change is expected to reduce coffee yields and intensify infestations by Hypothenemus hampei, the most destructive coffee pest worldwide. Strengthening host plant resistance offers a sustainable approach to mitigate these impacts. This study aimed to characterize F₃ progenies derived from crosses between Castillo^®—a variety with high agronomic performance and resistance to Hemileia vastatrix—and Ethiopian Coffea arabica introductions exhibiting antibiosis to H. hampei for agronomic traits and, for the first time, modeled reductions in H. hampei infestation under projected climate change scenarios. Thirteen F₃ progenies with medium plant stature, rust resistance, and high productivity were selected using a 6 × 7 lattice design. Antibiosis was quantified under controlled conditions by infesting individual coffee beans with a single female borer and validated under field conditions by artificially infesting productive branches with 100 females. Relative to the susceptible control, oviposition decreased by 18.0–25.8% under controlled conditions and by 24.1–69.8% in the field. To anticipate progeny performance under warmer conditions, simulation modeling integrating laboratory and field data under Neutral and El Niño scenarios for the Naranjal and Paraguaicito experimental stations, indicated that progenies exhibiting 34–55% reductions in oviposition would maintain infestation below the economic damage threshold (5%) throughout the eight-month fruit development period. Progenies with the highest antibiosis (55%) would reach the action threshold (2%) only in the seventh month. These findings demonstrate the potential of antibiosis-based resistance to reduce insecticide use and strengthen integrated pest management under projected climate change scenarios. Full article

This study examines the behavior and control of zero-sequence parameters in IT-type electrical networks under conditions of capacitive insulation asymmetry and complex asymmetric faults on the power receiver side. Existing methods of zero-sequence analysis typically address either symmetrical network conditions or single-phase earth faults in isolation, and they often neglect the combined effects of conductor breakage, transient fault resistance, and capacitive unbalance. To overcome these limitations, this work develops an analytical model based on the general theory of electrical engineering and symmetrical components, enabling a unified description of zero-sequence voltages and currents that incorporates both insulation asymmetry and compound fault scenarios. The model establishes closed-form relationships linking zero-sequence quantities to network parameters, power receiver characteristics, and transient resistances at the fault point. The results demonstrate several previously unreported effects, including a 180° vector shift and nearly 50% reduction in zero-sequence voltage and current magnitudes during simultaneous conductor breakage and earth faults compared with conventional single-phase faults—phenomena that critically influence the correct setting of protection devices. The study further shows that capacitive insulation asymmetry alone may generate zero-sequence voltages sufficient to trigger earth-fault protection regardless of the neutral grounding mode. These findings reveal increased risks of fault escalation, misoperation of existing protection systems, and prolonged unsafe touch voltages. Overall, the derived dependencies provide a new analytical basis for improving the design and coordination of protection systems in IT-type networks. Full article

Accurate prediction of land use and land cover (LULC) change is essential for sustainable development and climate change adaptation planning. This study projects LULC changes across 17 administrative regions of South Korea from 2020 to 2050 using the Future Land Use Simulation (FLUS) model under four integrated SSP-RCP scenarios: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The model was calibrated with land cover data for 2000–2010 and validated against observations for 2010–2020 using socioeconomic variables together with CMIP6 climate projections. In practical terms, FLUS produces scenario-based maps of future land patterns that inform land regulation, infrastructure planning, and climate adaptation. Across all scenarios, urban areas expanded by 488,000–585,000 ha, mainly through the conversion of agricultural land, which accounted for 10–24% of transitions in high-growth regions. Agricultural land decreased by 124,000–174,000 ha, and forests declined by 473,000–572,000 ha. Transformation intensity peaked around 2030 and then slowed in later decades. Urban expansion was greatest under SSP5-8.5, followed by SSP3-7.0, SSP1-2.6, and SSP2-4.5. Gyeonggi Province exhibited the most pronounced spatial change, whereas Seoul showed limited additional growth consistent with its already saturated urban structure. Validation results indicated an overall accuracy range of 57–83% with metropolitan areas generally outperforming provincial regions. These findings reveal spatial and temporal hotspots of land cover change and provide region-specific information that can guide urban development, land and ecosystem management, climate adaptation policy, and progress toward carbon neutrality. Full article