Search Results (5,242)

Wheat (Triticum aestivum L.) is considered one of the most important cereals globally, contributing significantly to the human population’s caloric and protein requirements. Therefore, ensuring a sufficient yield of wheat for global consumption plays a significant role in maintaining food security in different parts of the world. With increasing demand and dwindling production capacity, due to increasingly uncertain growing conditions, projections indicate that there should be an upswing of 60–70% in wheat productivity by 2050 to fulfill the requirement. However, drought represents the most significant and widespread abiotic limitation to global wheat production, currently resulting in approximately 10% yield losses worldwide. Furthermore, each additional 1 °C increase in temperature is anticipated to decrease staple calorie production by 4.4%. The factors contributing to drought in wheat, as well as its impact on the plant’s biochemical, physiological, and morphological structures, include altered rainfall patterns, elevated atmospheric CO₂ levels, increased temperatures, hot and dry winds, and restricted soil water availability. These factors initiate a series of morphological, physiological, and biochemical disruptions that hinder wheat growth and productivity. Drought impact on wheat starts at biochemical levels through reactive oxygen species (ROS) generation and degradation of chlorophylls, and tolerance to stress is influenced by a polygenic system where numerous genes contribute minor effects and interact significantly with environmental factors transitioning to osmoprotectants. At the physiological level, drought alters the water content in the plant body, leading to reduced net photosynthetic rates, stomatal conductance, transpiration rates, and water utilization efficiency. At the morphological level, drought impacts all kinds of structures such as roots, shoots, leaves and reproductive parts. To counter these effects, wheat develops a set of tolerant mechanisms called drought escape, avoidance and tolerance. An increase in trichomes and leaf waxes, alteration of root–shoot ratios, the staying green phenomenon, production of stress proteins like proline, activity of enzymes including superoxide dismutase (SOD), ascorbate peroxidase, catalase, etc., osmotic adjustment, abscisic acid (ABA) accumulation, expression of dehydration proteins called dehydrin, etc., contribute towards drought tolerance. This comprehensive review investigates the intricate interactions between drought and various wheat genotypes, emphasizing their substantial impacts on plant physiology, biochemistry, growth dynamics, and grain yield. Additionally, this review assesses a variety of genetic and biotechnological strategies aimed at enhancing the resilience of wheat genotypes to drought stress. By integrating recent research findings with practical applications, this review provides a detailed framework for improving the adaptive capacity of wheat plants to withstand the escalating threats of drought stress, thereby supporting sustainable wheat production in a changing climate. Addressing drought stress through genetic and biotechnological management practices is crucial for maintaining wheat productivity. Full article

Green accounting is an extension of conventional accounting that incorporates environmental considerations into economic measurement and reporting. It examines the relationships between economic activity and the natural environment by identifying environmental costs, resource use, ecological impacts and related responsibilities. Green accounting may be applied within organisations to support management and reporting or at the national level to assess how economic development affects natural resources and environmental quality. Its main purpose is to provide a broader understanding of performance by showing that economic value cannot be evaluated independently of environmental sustainability. In this way, it supports more responsible decision-making, greater accountability and long-term planning. Full article

Based on microdata from A-share listed companies from 2016 to 2025, this study uses corporate digital governance capabilities as a threshold variable and combines an intermediary effects model with a threshold regression model to empirically examine the nonlinear impact of proprietary AI computing power investment on corporate green sustainable development performance, as well as its underlying transmission mechanisms and moderating boundaries. The study finds that there is a significant “N”-shaped nonlinear relationship between investment in proprietary AI computing power and corporate green sustainable development performance. This relationship primarily facilitates green empowerment by optimizing firms’ green pure technical efficiency, while having no significant effect on scale efficiency; green innovation plays a significant mediating role in this relationship, and investment in proprietary AI computing power can indirectly empower the improvement and upgrading of corporate green sustainable development by driving the iteration of green innovation. Digital governance capabilities exert a significant dual-threshold moderating effect on the green empowerment process of AI computing power; the green empowerment effects of computing power exhibit differentiated characteristics across different digital governance ranges, and a moderate level of digital governance can maximize the green development dividends of AI computing power. The study’s conclusions provide empirical support and decision-making references for enterprises to scientifically allocate AI computing power resources, establish appropriate digital governance systems, and advance the synergistic transformation of digitalization and green development. Full article

Giant foxtail is a common weed in foxtail millet fields, and continuous cropping of foxtail millet increases its occurrence. Rotating foxtail millet with sorghum is a major practice in the dry farming regions of northern China. Given this situation, this study combined Petri dish germination tests with pot experiments to clarify the allelopathic effects of water extracts from different sorghum parts on giant foxtail. Distilled water (SCK) was used as the control, and treatments included stock solution (S1), as well as 10× dilution (S2), 50× dilution (S3), and 100× dilution (S4) of water extracts prepared from sorghum roots, stems, leaves, and rhizosphere soil. The results showed that water extracts from all sorghum parts exhibited promotion of giant foxtail seed germination at higher dilutions and inhibition at lower dilutions. The S3 treatment of rhizosphere soil extract achieved a germination rate of 62.22%, which was significantly higher than that of the SCK by 40.00%. The germination energy of root extract S1 was only 4.00%, which was significantly lower than that of the SCK by 86.67%. The S3 treatment showed the strongest allelopathic promotion effect. All dilution treatments promoted the plant height, stem diameter, and above ground fresh and dry weight of giant Foxtail, and these effects increased initially and then stabilized over time. The root extract exhibited higher allelopathic activity than the other extracts. The activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) first increased and then decreased as the dilution factor increased, while the S1 treatment inhibited enzyme activities and caused an imbalance in the antioxidant system. Sorghum root water extract had a significant effect on CAT activity in giant foxtail, with an increase of 98.82% under the S3 treatment compared with the SCK at 40 d. Malondialdehyde (MDA) content increased with decreasing dilution factor, and the undiluted extract induced membrane lipid peroxidation damage. In conclusion, the allelopathic effects of sorghum extracts on giant foxtail were closely related to the dilution level. Higher dilutions activated the antioxidant defense system and promoted growth, while lower dilutions disrupted enzyme system balance and exacerbated membrane damage. These findings provide basic data and theoretical support for the development and utilization of sorghum allelochemicals and for the green control of giant foxtail. Full article

Green consumption is a crucial pathway for promoting ecological environmental improvement and fostering sustainable economic and social development. Although policies have been continuously implemented and residents’ environmental awareness is gradually increasing, there remains a significant gap in the transformation from cognition to behavior. Promoting green consumption is a systematic project that requires deep coordination among three key actors: the government, enterprises, and residents. However, existing studies have mostly focused on interactions between the government and enterprises, paying insufficient attention to the long-term strategic interactions among all three parties when residents are incorporated into the game system. To address this gap, this study develops a tripartite evolutionary game model that includes the government, enterprises, and residents to analyze the intrinsic driving forces behind the development of green consumption, thereby extending the research perspective to multi-agent dynamic strategic interaction. Through mathematical derivation of the replicator dynamic equations and the Jacobian matrix for each party, this study finds that the system has a unique evolutionarily stable equilibrium point, namely a tripartite synergistic state characterized by active government intervention, green production by enterprises, and green consumption by residents. Sensitivity analysis examines the impact of changes in key parameters on the evolutionary trajectory of the system, providing parameter-level evidence for differentiated policy design. Simulation results indicate that efforts should be directed toward building a collaborative governance system based on government guidance, enterprise responsibility, and resident participation, so as to promote the transformation of green consumption governance from single-dimensional management to pluralistic co-governance. Full article

As a linchpin of global energy conversion systems, the coking industry faces an imperative sustainable transition driven by tightening environmental regulations. The green development of coking enterprises is constrained by persistent heterogeneity across firms, exacerbated by the lack of a standardized enterprise-level evaluation framework—collectively impeding the industry’s green transition. This study established a comprehensive evaluation model for Green Coking Enterprises comprising 124 indicators, drawing on existing research, standards, and regulatory frameworks, and proposed the green coking concept. It covers seven core dimensions: infrastructure, management system, energy and resource inputs, environmental protection, products, by-products, and performance. Through a 2023 case analysis of the Ordos Etuoke Economic Development Zone—a strategic coking cluster positioned along China’s energy transition corridor—the applied framework revealed critical performance gaps. These gaps primarily manifested in three core dimensions: comparative disadvantages in resource consumption efficiency, deficiencies in environmental management systems, and lagging capabilities in deep processing of by-products. Accordingly, four improvement strategies closely aligned with these identified gaps are discussed. The development assessment model for coking enterprises constructed in this study provides a systematic methodology for evaluating the level of green transformation in such enterprises. It holds significant practical value for accurately identifying technical shortcomings, supporting management decision-making, and promoting the green upgrading of the coking industry. Full article

Amid rising population pressure, heightened volatility in international markets, and increasingly binding domestic resource and environmental constraints, safeguarding food security while maintaining ecological security has become a salient policy and academic concern in China. Within this context, our study investigates whether and how green finance contributes to the dual security of food and ecology. Building on a theoretical analytical framework, we elaborate on the functional role of green finance and empirically assess its effects using provincial panel data from China. We construct a composite index to gauge the level of green finance development and then employ a two-way fixed-effects model with province and year fixed effects to identify the overall impact of green finance, followed by a mediation model to uncover the underlying transmission mechanisms and sub-sample regressions to examine heterogeneity. The empirical evidence indicates that, while green finance significantly improves the dual security of food and ecology, substantial heterogeneity is observed, with stronger effects in southern regions, major grain-producing functional areas, and plain regions. Mechanism analyses further show that green finance advances dual security through three primary channels of agricultural structure adjustment, planting specialization, and agricultural green technological innovation, among which shifts in agricultural production structure, greater centralization of planting, and enhanced agricultural green innovation capacity constitute the dominant transmission mechanisms. By integrating food security and ecological security within a unified framework, we clarify the multidimensional pathways through which green finance supports sustainable agricultural development and provide new empirical evidence on how financial instruments can reconcile production and environmental objectives. Full article

In the context of the global implementation of the United Nations 2030 Sustainable Development Goals (SDGs), urban green development serves as a core practical pathway to advance SDG8 (Decent Work and Economic Growth), SDG11 (Sustainable Cities and Communities), and SDG15 (Life on Land). This study constructed a three-dimensional evaluation framework encompassing the green economy, green ecology, and green society, and utilized panel data from 282 Chinese prefecture-level cities from 2009 to 2021. By integrating the CRITIC weighting method, spatial autocorrelation, the Standard Deviational Ellipse (SDE) approach, and the Dagum Gini decomposition, we systematically quantified multi-scale spatiotemporal evolution and disparity patterns at the national scale, as well as across four major economic zones and five core urban agglomerations. Nationwide, the composite green development index rose from 0.422 to 0.522 (+23.70%), while the overall Dagum Gini coefficient declined from 0.072 to 0.053 (−26.39%), with the spatial center of gravity gradually shifting toward the southwest. Eastern China persistently maintained the highest development level; Western China achieved the fastest cumulative growth (26.43%), and Northeastern China lagged behind with the lowest growth rate (20.10%). Among five major urban agglomerations, the Yangtze River Delta (YRD) and Pearl River Delta (PRD) shared an identical average score of 0.582, whereas the Chengdu–Chongqing (CC) agglomeration recorded the highest growth of 33.07%. This research contributes multi-scale empirical evidence for localized SDG implementation in China and provides differentiated policy insights for cross-regional green transition governance. Full article

This paper examines how circular economy (CE) policies relate to sustainable economic growth and environmental sustainability across eight major emerging economies between 2005 and 2023, with particular attention to how that relationship shifts across time horizons. Much of the existing literature has a temporal aggregation problem: short- and long-run dynamics are averaged together into a single coefficient, which can obscure the underlying relationship or, worse, produce a misleading sign. We address this by decomposing two central CE variables—renewable energy share and energy intensity—into short-, medium-, and long-term frequency components using a Level-2 discrete wavelet transform. Each component is then estimated via two-way fixed-effects panel regressions; given the constraints of a relatively small panel, we validate inference using a Wild Cluster Bootstrap procedure. Three findings stand out. First, although the growth elasticity of renewable energy rises across horizons—a descriptive pattern consistent with short-run adjustment costs giving way to longer-run sustainable gains—Wild Cluster Bootstrap (WCB) inference indicates that these structural coefficients are not statistically significant in this sample. Second, the energy intensity coefficient reverses the sign, moving from a weakly significant negative short-run effect (p < 0.10) to positive estimates in the longer run; these longer-run effects, however, fail to reach statistical significance, and so offer only suggestive theoretical alignment with the macroeconomic Jevons Rebound Effect rather than firm empirical confirmation of it. Third, Industry Value Added stands out as the one robust macroeconomic factor in the model, remaining a significant and positive driver of sustainable development at every frequency horizon. Taken together, these results suggest that while CE transitions display suggestive multi-horizon dynamics, industrial expansion remains the more statistically dependable engine of sustainable growth across these emerging markets. Although statistical significance is dependent on the sample size, the identified trajectories provide a useful structural diagnosis for policymakers who need to plan different investment horizons for the sustainable green transition. Full article

As climate change increasingly threatens sustainable development goals, climate risk has emerged as a critical factor shaping corporate strategic decisions and capital allocation behavior. Using a sample of Chinese A-share listed firms over the period 2008 to 2024, this study constructs a firm-level climate risk index through textual analysis of annual report disclosures and examines its effect on corporate green investment. We find that climate risk is positively associated with corporate green investment. Mechanism analysis reveals that climate risk operates through dual pathways: it enhances firms’ green strategic orientation as the internal governance mechanism, and heightens public green attention as the external governance mechanism, both of which are positively related to increasing firms’ green investment. Heterogeneity analysis shows that the promoting effect is more pronounced for state-owned enterprises, heavy-polluting firms, firms with negative media coverage, and firms located in northern regions of China. Further analysis reveals that climate risk is more strongly associated with green transformation investment over end-of-pipe treatment investment, and firms that increase green transformation investment in response to climate risk achieve stronger firm growth. These findings provide new evidence on how climate risk shapes corporate environmental behavior, offering practical insights for promoting sustainable investment and advancing corporate contributions to sustainable development. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

Noise mitigation on urban rail transit lines in service is often constrained by the need to maintain uninterrupted operation and avoid large-scale demolition or reconstruction. Using Kunming Metro Line 4 as an engineering case study, this study combined onboard field measurements with data-driven analysis to characterize passenger-compartment noise and identify its principal determinants. A green noise-mitigation framework integrating source control, transmission-path control, and green operational management was developed, and its benefits were quantified across four dimensions: acoustic-environment improvement, human-health protection, low-carbon energy savings, and enhanced operation and maintenance efficiency. Passenger-compartment noise levels predominantly ranged from 78 to 82 dB(A). SHapley Additive exPlanations (SHAP) analysis identified train operating speed and track gradient as the two dominant factors, with relative importance values of 35.03% and 27.56%, respectively. Engineering implementation of the framework reduced peak noise levels in curved sections by 3–8 dB(A). The results further showed that noise-pollution mitigation and carbon-emission reduction share common sources and intervention pathways. The scenario-based assessment indicated that, under the specified parameter assumptions, the relevant measures could collectively achieve an estimated annual carbon emission reduction of approximately 3353.20 tCO₂. These findings provide a practical and scientific basis for green noise mitigation and coordinated pollution and carbon reduction on urban rail transit lines in service. Full article

High shrinkage-related defect rates in aluminum die casting reduce effective production capacity. They also create energy-intensive re-melting loops, which weaken production planning reliability and environmental performance. This study examines how Green Lean Six Sigma can stabilize a resource-constrained Small and Medium-Sized Enterprise (SME) die-casting process and translate quality improvement into measurable capacity recovery and Scope 2 electricity-related carbon savings. Based on a 10-month case study, the Define–Measure–Analyze–Improve–Control (DMAIC) framework was integrated with factorial ANOVA, the Response Surface Methodology (RSM), one-way analysis of variance (ANOVA) and statistical process control (SPC). These methods supported process parameter identification, operating-window development and shop-floor process stabilization. The analysis identified the filling speed and mold temperature as significant shrinkage drivers, developed a mold temperature control map, and determined the standardized filling speed at 800 mm/s. The intervention reduced the shrinkage defect rate from 7.19% to 1.46%, reduced the overall scrap rate from 7.60% to 2.71%, and improved the overall sigma level from 2.93 to 3.42. This yield improvement generated a 4.89 percentage-point yield-equivalent capacity gain, avoided 4401 kWh of re-melting electricity, reduced Scope 2 emissions by 2.36 t CO₂e, and generated gross annualized savings of RMB 249,214 (USD 35,783). Considering a one-time implementation cost of RMB 31,445 (USD 4515), the first-year net saving was RMB 217,769 (USD 31,268). The findings show that accessible statistical process control methods can provide SMEs with a resource-efficient pathway to improve process stability, capacity utilization and electricity-related environmental performance before investing in advanced digital technologies. Full article

This study examines urban green infrastructure (UGI) branding as a governance practice shaped by institutional homogenization and strategic responses within China’s multi-level policy framework. Against the backdrop of global sustainability agendas, UGI branding is conceptualized as a policy-oriented, symbolically embedded instrument for communicating cities’ commitments to green development and climate resilience. Using an institutional “identity–label–image” framework, integrated with policy diffusion theory and multi-center regional development models, we systematically analyze historical brand-label data from 27 core cities in the Yangtze River Delta. Our findings reveal three key patterns: (1) brand diffusion follows dual pathways of mandatory and imitative homogenization, with evolutionary rhythms tied to five-year planning cycles, generating discernible “policy waves”; (2) within polycentric regional structures, core cities act as institutional “interpreters” and benchmarks, while peripheral cities pursue imitation-driven differentiation, reflecting complex dynamics of collaboration and competition; and (3) urban identities expressed through brand labels progressively align with substantive sustainability transitions, aiming to enhance regional competitiveness and upward recognition. We conclude that UGI branding constitutes a deep-seated mechanism of sustainable urban governance, offering a novel theoretical lens on China’s institutional logic of city branding and providing actionable insights for optimizing collaborative brand governance and integrated green infrastructure planning in urban agglomerations. Full article

Green hydrogen strategies proliferate across developing economies, yet most assume the planning authority possesses the state capacity, regulatory autonomy, and investment conditions that conflict-affected and fragile economies lack. Whether a strategy logic derived in one such context transfers to others with different institutional capacity remains untested. This study develops a Conflict-Affected Energy Transitions (CAET) framework and empirically examines its barrier gradient and conditional transferability propositions, analyzing at the country level a regional expert survey—data that prior single-case work, including the authors’ own, used only for binary external validation. A total of 137 energy experts across seventeen Arab states are grouped into three institutional clusters—conflict-affected/fragile, stable developing, and Gulf/high-capacity—and examined through cluster barrier and readiness profiles, a perceived-versus-predictive importance comparison, hierarchical clustering, and a Mode-A partial-least-squares path model with measurement invariance (MICOM) testing and permutation-based multi-group analysis. Energy justice and sovereignty are used as analytical and interpretive lenses, not as measured latent constructs in the structural model. Results show that barrier burdens follow a monotonic institutional fragility gradient: regulatory/institutional barriers rise from 3.02 (Gulf) through 3.52 (stable) to 4.06 (fragile), where they are the most severe constraint. Moreover, the perceived–predictive divergence—social barriers are rated least severe yet associate most strongly with sustainability—recurs across the region. In addition, the model satisfies compositional invariance across fragile and stable clusters while equality of regulatory means and variances fails as expected, and no structural path differs detectably between them at the current sample size. The adoption–governance–sustainability mechanism is therefore provisionally comparable rather than definitively invariant. We propose conditional transferability: the mechanism travels, provisionally, while priorities must be re-weighted by institutional context. Policy implications are differentiated—institutions-first, community-scale pathways for fragile states; finance and market formation for stable developing states; export-scale deployment for high-capacity states—and the CAET framework offers a generalizable alternative to techno-economic determinism for hydrogen strategy under constrained sovereignty. In practical terms, energy ministries in fragile states should sequence rule-making, permitting authority, and community-scale pilots before committing deployment capital; stable developing states should concentrate on de-risking finance and forming early offtake markets; and high-capacity states can proceed directly to export-scale projects and regional standard setting. Full article