Journal of Environmental Management最新文献

The relentless surge in carbon emissions is exacting a devastating toll on human wellbeing, critical infrastructure, and natural ecosystems, leaving a stark and distressing legacy of destruction. Communities worldwide are reeling from the impacts of pervasive smog, record-breaking wildfires, and deadly heatwaves-manifestations of a climate crisis that grows more severe by the day. Once a vanguard of environmental policy, the Organisation for Economic Co-operation and Development (OECD) now struggles with exceeding emissions targets, eroding its credibility and influence. Fragmented implementation of key frameworks-such as Inclusive Green Growth, the Circular Economy, and Energy Transition-has undermined their impact. The urgency of the moment was underscored by the report of COP29, which issued an unequivocal call to action for OECD nations to step up and lead with ambitious, unified strategies. Embracing inclusive green growth (IGG)-a paradigm that harmonizes economic development with environmental sustainability and social equity-offers a clear path forward. By integrating these elements into a cohesive response, the OECD can reignite its leadership role and drive meaningful progress toward a sustainable future. This paper advocates for a unified strategy integrating IGG, CE, and ET to achieve carbon neutrality. It introduces a streamlined environmental model designed to assess the effectiveness of this integrated approach rigorously. Drawing on data from 24 countries between 2000 and 2020, and employing advanced time series and dynamic analysis, this study offers theoretical and empirical insights into the interactions among the key variables. The results show that integrated policies significantly enhance the effectiveness of green growth and energy transitions, ensuring equitable benefits across all societal segments, including marginalized communities. By addressing the complex, interrelated nature of sustainability challenges, these policies offer a robust framework consolidating diverse perspectives and expertise, driving transformative and profound change.

Amid rapid urbanization, land use shifts in cities globally have profound effects on ecosystems and biodiversity. Birds, as a crucial component of urban biodiversity, are highly sensitive to environmental changes and often serve as indicator species for biodiversity. This study, using Shenzhen as a case study, integrates machine learning techniques with spatial statistical methods. Firstly, a multi-layer perceptron (MLP) model was employed to globally simulate bird richness based on citizen science data. Subsequently, a geographic weighted random forest (GW-RF) model was used to construct the complex relationship between bird diversity and land use. Additionally, SHAP analysis evaluates the effects of urban factors and development patterns on bird diversity. The findings reveal that anthropogenic disturbances and habitat factors significantly influence bird diversity. Furthermore, the impact of land landscape patterns on bird diversity exhibits notable spatial heterogeneity, with landscape patterns within ecological spaces and developed land showing marked differences in their effects on bird diversity. The study's findings clarify the intricate effects of urbanization on bird diversity, pinpointing specific ecological conservation areas. It underscores the importance of ecological conservation in guiding urban development, advocating for strategic restoration to bolster urban sustainability and optimize land use for the protection of ecological diversity.

Cadmium (Cd) is a silvery-white and shiny heavy metal that is common in daily life and can adversely affect the development, lifespan, and reproduction of organisms. In this study, Drosophila melanogaster (F₀) were cultured from eggs to adults in medium containing different Cd concentrations (0, 2.25, and 4.5 mg/kg), and offspring (F₁-F₄ generations) were cultured in standard medium. The morphology of the ovaries of female flies under Cd stress changed, apoptosis occurred, fertility decreased, and the levels of 20-Hydroxyecdysone and vitellogenin decreased significantly. These changes were more significant under high-concentration treatment. In addition, the inhibitory effects of Cd on reproduction-related genes (spook, phantom, disembodies, shadow, shade, ECR, vg, and Kr-h1) in F₀ female flies could transmit to two or three generations. Cd exposure also induced increased expression of miR-927 and mediated its transgenerational inheritance. These results indicate that damage to the ovaries and the changes in related-genes expressions of female flies induced by Cd stress can be transmitted to offspring and may be related to changes in miRNA expression in Drosophila. The transgenerational inheritance effects of heavy metals on organisms and their potential risks to future ecosystems deserve attention and reassess.

Climate change poses significant challenges, making low-carbon development an essential global trend. In this context, building a green brand has become a critical strategy for companies to enhance consumer loyalty and maintain competitiveness. This study explores how the digital economy shapes sports brand loyalty, focusing on a dataset of Chinese A-share listed companies from Shanghai and Shenzhen, spanning 2011 to 2020. The findings suggest that the digital economy can significantly foster sports brand loyalty. In this process, the digital transformation of enterprises plays a mediating role. This effect is more pronounced in southern regions, non-resource cities and regions actively implementing the Broadband China strategy. This highlights the important role of regional and policy factors in amplifying the impact of digitalization. The study highlights that digital transformation not only improves operational efficiency, but also caters to consumers and their preference for innovative and sustainable practices, further cementing brand loyalty. By exploring the specific role of the digital economy for the business of sport, this study provides important insights into the use of digital tools to build green and loyal brands, offers practical insights for companies seeking to combine sustainability with digital strategies, and emphasizes the need to adapt approaches regionally. Embodying the transformative potential of the digital economy to address climate challenges, support low-carbon development and strengthen brand loyalty in the sports sector, this research contributes to the understanding of how businesses can thrive in an era of rapid environmental change.

Forestry activities, i.e., drainage system maintenance or regeneration fellings may alter the water quality in catchments as well as in runoff and induce risks of acidification. In Latvia, most of the anthropogenic pollution to ecosystems is air-borne and comes from transboundary sources, while in drained forested catchments, nutrients may be leached more due to management-induced disturbances. In this study, critical load approaches were used to evaluate acidification risks in five relatively small drained forested peatland catchments, including effects of drainage network maintenance and in three locally typical forest site types of various trophic states after different intensity regeneration fellings (stem-only harvesting, whole-tree harvesting). Studied drainage catchments presented high acidity, S and N critical loads reaching far above factual loads by precipitation, because of organic soils in combination with high basic cation concentrations. Drainage network maintenance significantly increased acidity and S critical loads, while N critical loads increased but not significantly in all catchments. At the felling sites also, no exceedances of critical loads were detected. Higher critical loads were observed with higher trophic levels. At the eutrophic site, higher critical loads were observed after stem-only harvesting while, at the oligotrophic site, higher critical loads were observed after whole-tree harvesting. The critical load modelling approaches demonstrated the potential to assess the impacts of various forestry management practices. With broadened base of knowledge, these methods can be utilised to support decision making and define acceptable levels of disturbance for sensitive sites and in regionally specific conditions.

An important question in restoration ecology is whether restored ecological regimes are more vulnerable to transitions back to a degraded state. In woody-invaded grasslands, high-intensity fire can collapse woody plant communities and induce a shift back to a grass-dominated regime. Yet, legacies from woody-dominated regimes often persist and it remains unclear whether restored regimes are at heightened vulnerability to reinvasion. In this study, we utilize a 17-year history of fire-based restoration in Nebraska's Loess Canyons Experimental Landscape to determine whether restored grassland regimes experience faster rates of Juniperus virginiana (eastern redcedar) reinvasion compared to the initial invasion process in adjacent grasslands. In addition, we examine whether reinvasion and invasion patterns are clearly differentiated based on former ecotonal boundaries between grassland and woodland regimes. Our results show that J. virginiana reinvasion of restored grassland regimes outpaced the initial invasion process in adjacent grasslands, providing evidence that restored grassland regimes are more vulnerable to transitions back to woody dominance. J. virginiana seedlings established sooner and increased faster in density and cover during reinvasion compared to the initial invasion process. Seedlings established 1-year post-fire in restored grassland regimes compared to 14-years post-fire in adjacent grasslands that were >40 m from the former grassland-woodland boundary. Reinvasion was initially easy to differentiate from invasion based on former ecotonal boundaries between grassland and woodland; however, reestablished juniper woodlands eventually began to expand into adjacent grasslands. Our findings demonstrate clear differences between reinvasion and invasion and highlight the need for management frameworks that explicitly account for reinvasion.

In recent decades, the threats of ticks and tick-borne diseases (TBDs) increased extensively with environmental change, urbanization, and rapidly changing interactions between human and animals. However, large-scale distribution of tick and TBD risks as well as their relationship with environmental change remain inadequately unclear. Here, we first proposed a "tick-pathogen-habitat-human" model to project the global potential distribution of main pathogenic ticks using a total of 70,714 occurrence records. Meanwhile, the effects of ecological factors and socio-economic factors driving the distribution pattern were evaluated. Based on this, the risk distribution of TBDs was projected by large-scale "tick-pathogen-disease" analysis. Furthermore, the distribution shifts of tick suitability were projected under different shared socio-economic pathways in the future. Our findings demonstrate that warm temperate countries (e.g., the United States, China and European countries) in the Northern Hemisphere represent significant high risk regions for ticks and TBDs. Specifically, solar radiation of January emerges as the main decisive factor determining the risk distribution pattern. Future shifts of tick suitability showed decrease trend under low greenhouse gas emission scenarios but increase trend under high scenarios. These suitability shifts were significantly correlated with future temperature- (9 species) and precipitation- (19 species) related factors. Collectively, in this study we first shaped the global risk distribution of main ticks and TBDs as well as tick suitability shifts correlated with future global climate change, which will provide helpful references for disease prevention and administration. The methods proposed here will also shed light on other emerging and recurrent zoonotic diseases (e.g., COVID-19, monkeypox) in the future.

Environmental degradation is a problem, and the consequences, in terms of emission of pollutants into different ecosystems, human health, and sustainable development are disastrous. This study explains the complex interactions that exist among sustainable finance, green technology innovation, green energy adoption, the climate change financial policy, green growth index, government spending, and financial globalization across the globe. This research applies to an extensive dataset that ranges to 23 years in 50 countries by enforcing robust dynamic econometric methods such as unit root tests, cointegration analysis, and generalized method of moments (GMM) estimations for the analysis of these complicated issues. The results show that Sustainable finance (SF) has a negative coefficient of -0.033, suggesting that increased sustainable financial practices contribute to reducing environmental degradation. Similarly, technology innovation (TI) and green energy (GE) both show significant negative impacts on environmental degradation, with coefficients of -0.132 and -0.075, respectively. The green growth index (GGI) has the most substantial negative effect, with a coefficient of -0.686, highlighting its critical role in mitigating environmental degradation. Lastly, the climate-related financial policy index (CRFPI) exhibits a positive coefficient of 0.029, indicating that advancements in financial policies targeting climate issues slightly offset environmental degradation. These results collectively emphasize the importance of financial, technological, and policy interventions in reducing environmental degradation. It also becomes clear that government spending and financial globalization both influence the efficacy of the government actions in reducing environmental pollution, while government efforts are affected by the second factor negatively. Those perceptions reveal why green finance that is advanced technologically along with renewable energy initiatives and governmental policy backing are the need of the hour in view of these very environmental challenges.

Fish migration patterns are driven by hydrodynamic factors, which are essential in aquatic ecology. This study investigated the hydrodynamic drivers of Gymnocypris przewalskii fish migration in two distinct river reaches-a straight reach (SR) and a confluence reach (CR)- in the area of Qinghai Lake, China, using a 3D numerical model, fish density field data, and four predictive models. Thirteen hydrodynamic factors, with a focus on water depth and velocity, were analyzed to identify their influence on fish migration. It was found that in the SR, linear factors of flow velocity and turbulent kinetic energy were most influential, while in the CR, nonlinear factors of water temperature and vortex intensity dominated. For CR, fish migration patterns are also important nonlinear factors. Methods that accurately reveal fish migration patterns, such as Random Forest, offer higher precision for habitat assessment. Our research also shows that fish swimming ability can, to some extent, reflect migration direction. Combining fish swimming ability with traditional linear habitat assessment methods can improve the adaptability of these methods in complex fluvial system. Based on our research findings, we propose a new workflow for fish habitat assessment that integrates both linear and nonlinear predictive methods. This framework provides valuable insights for enhancing fish conservation strategies in various fluvial systems.