The proposed research aims to analyse the effects of the relationship between Sustainability Governance (SG) and Climate Impact (CI), taking into consideration Green Finance (GF). Furthermore, it examines how Institutional Support (IS) enhances the governance systems governing these variables. The research provides a holistic approach for analysing the effects of financial dynamics on climate impacts. Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed in this research study. The data were collected from various industries using a standardised questionnaire. The structural model examined the direct and indirect relationships between variables such as GF, SG, and CI. IS emerged as the moderated variable. The outcomes of the study confirmed that “GF has an important and direct as well as indirect (through SG as the mediator) impact on CI. IS significantly increases SG and thus exerts an overall enhancing effect on the impact of GF on the climate.” The study has supported the research objectives and aims. The limitations of this study comprised constraints related to both time and cost. The researchers encountered limitations in accessing senior managers and directors of various organisations for the study. IS emerged as an important intermediate factor that can significantly link various actions and activities that impact the climate. This study supports both global and local research objectives. The study offers significant insights, underscoring the critical role of SG within Green Business (GB). Additionally, IS emerges as a vital enabling tool that strengthens the overall governance framework. The study contributes significantly to the development of integrated frameworks for institutions seeking to effectively address environmental challenges. The implications for action indicate that furthering entrenched institutional structures and instilling good governance practices can add tremendous value to the transformation potential of GF and usher in accelerated efforts to achieve national and international objectives on climate change.

Climate change is one of the most pressing global challenges of the 21st century, influencing ecosystems, biodiversity, and human societies. Microbial communities play a central yet often underappreciated role in regulating Earth’s climate through their involvement in biogeochemical cycles, including carbon sequestration, nitrogen fixation, and greenhouse gas emissions. Due to their rapid response to environmental changes, microbial ecosystems serve as early indicators of climatic perturbations. However, the intrinsic complexity, diversity, and high dimensionality of microbial datasets pose significant challenges for conventional analytical approaches. Recent advances in artificial intelligence (AI), particularly machine learning and deep learning techniques, have demonstrated exceptional potential in modelling non-linear, high-dimensional biological systems. This paper presents a comprehensive AI-based framework for analysing microbial community data to predict climate impacts. By integrating metagenomic sequencing data with environmental variables, the proposed approach leverages unsupervised learning for microbial pattern discovery, supervised deep learning models for climate-variable prediction, and explainable AI techniques to enhance interpretability. The study highlights how AI-driven microbial analysis can significantly improve prediction accuracy of climate-related parameters such as soil carbon flux, methane emissions, and ecosystem resilience under climate stress. Results indicate that AI models outperform traditional statistical techniques and provide meaningful ecological insights. This research establishes a robust interdisciplinary framework that bridges microbiology, climate science, and artificial intelligence, contributing to improved climate forecasting, environmental monitoring, and sustainable policy formulation.

Genomes record past climatic impact on species' range shifts, admixture, refugial isolation, and adaptative evolution. However, these processes are poorly understood in perennial herbaceous species forming a dominant group of temperate flora. We present a demographic history of the perennial herb woodland strawberry (Fragaria vesca L.) reconstructed from 200 genomes spanning most of its European range. Temporal population structure reveals a strong division into western and eastern genetic clusters along a longitudinal climatic gradient, with eastern core populations showing greater resilience during glaciations. Divergence patterns indicate that postglacial recolonization of western and eastern Europe occurred from distinct refugia in multiple waves. The current largest, admixed populations from the Mediterranean to northern Europe form a continuous chain maintained by east-west gene flow through Central Europe, with historical migration patterns indicating comparable connections during earlier interglacials. Our reconstruction of woodland strawberry's climatic history with high temporal resolution reveals how the late Pleistocene core-periphery dynamics shaped its survival and genome evolution under climate change. The data points to populations that are essential for maintaining the long term genetic diversity of the species and opens new avenues to understand climatic adaptation of temperate flora.

Recent studies have indicated that sleep is fundamental for adolescents' physical and mental health. Although it is known that context influences sleep, the impact of school climate on sleep duration remains understudied. Using a large, diverse, population-based sample of adolescents attending California high schools (N = 277,954; data collection: 2018-2019) and applying two statistical methods suggested for quantitative research using an intersectionality approach (linear regressions with interaction terms and Exhaustive Chi-square Automatic Interaction Detection [ECHAID]), this study examined associations between school climate and sleep duration among adolescents at the intersection of multiple social positions. Similar proportions of participants were assigned male and female at birth. The sample was racially and ethnically diverse (54.1% Latina/x/o). The large majority of participants were straight (85.4%) and cisgender (97.7%). On average, participants slept 6.75 h/night. Positive school climate was associated with longer and adequate sleep duration; however, this association varied across social positions, such that the effects of school climate on sleep duration were attenuated among adolescents who held some minoritized social positions. ECHAID results indicated that those reporting the lowest averages of sleep duration not only perceived school climate as negative but also held multiple minoritized identities. In contrast, those who perceive their school climate as positive are overrepresented among those who reported the highest averages of sleep duration. Findings underscore the impact that schools have on adolescents' sleep health. Our study indicates that adolescents with multiple minoritized social positions face additional challenges impacting their sleep. Future interventions should focus on strategies to improve school climates, given that they would benefit a large number of students.

Cross-regional characteristics, chemical composition, and source contributions of atmospheric particulate matter in Germany and India.

The relevance of this study is driven by the increasing requirements for the energy efficiency and indoor comfort of residential and public buildings, particularly in regions with extreme climatic conditions characterized by substantial daily and seasonal temperature fluctuations. Effective management of heat transfer through building envelopes has become a key factor in reducing energy consumption and improving indoor comfort. This paper presents the results of an experimental–numerical investigation of the thermal behavior of an adaptive exterior wall system with a controllable air cavity. Steady-state and transient simulations were performed for three envelope configurations: a baseline design, a design with vertical air channels, and an adaptive configuration equipped with adjustable openings. Quantitative analysis showed that during the winter period, the adaptive configuration increases the interior surface temperature by 1.5–2.3 °C compared to the baseline design, resulting in a 12–18% reduction in the specific heat flux through the wall. In the summer period, the temperature of the exterior cladding decreases by 3–5 °C relative to the baseline, which reduces heat gains by 8–14% and lowers the cooling load. Additional analysis of temperature fields demonstrated that the presence of vertical air channels has a limited effect during winter: temperature differences at the surfaces do not exceed 1 °C. A similar pattern is observed in warm periods; however, due to controlled air circulation, the adaptive configuration provides an improved thermal regime. The results confirm the effectiveness of the adaptive wall system under the climatic conditions of southern Kazakhstan, characterized by high solar radiation and large diurnal temperature variations. The practical significance of the study lies in the potential application of adaptive façades to enhance the energy efficiency of buildings during both winter and summer seasons.

ABSTRACT This study investigates how national cultural values moderate the relationship between innovation ecosystems and climate change performance across 28 countries from 2013 to 2022. While innovation infrastructure, comprising regulatory quality, education, ICT, investment, and knowledge diffusion, is widely regarded as a key driver of climate action, countries with similar innovation capacities often demonstrate stark differences in environmental outcomes. Drawing on Hofstede's six cultural dimensions and the technology–structure–behavior (TSB) framework, this paper theorizes that cultural norms act as informal institutions that shape how societies internalize and operationalize innovation for climate impact. Using a dual‐method approach, we employ panel regressions to test six interaction hypotheses and apply ensemble machine learning models (Bagging, Random Forest, and Boosting) with SHAP and Partial Dependence Plots to uncover nonlinearities and contextual effects. Results reveal that cultural traits such as masculinity, indulgence, and long‐term orientation significantly moderate the effectiveness of innovation drivers, whereas others like power distance and individualism show limited influence. These findings highlight that climate innovation strategies must be culturally contextualized to enhance their effectiveness. The study contributes theoretically by advancing a culture‐sensitive institutional model of innovation‐led sustainability and offers actionable insights for tailoring climate policy to national value systems.

BackgroundAlthough existing research has fully demonstrated that employe safety citizenship behavior is crucial for workplace safety, there is relatively little research on how psychosocial safety climate affects safety citizenship behavior.ObjectiveThis study aims to verify the impact of psychosocial safety climate on safety citizenship behavior among construction workers and examine the mediating role of job resources and harmonious safety passion.MethodsA hierarchical linear model analysis was used with data from 879 frontline workers from 50 construction companies in China.ResultsThe results showed that psychosocial safety climate significantly and positively predicted safety citizenship behavior. Job resources and harmonious safety passion play a multilevel mediating role between psychosocial safety climate and safety citizenship behavior. Moreover, the psychosocial safety climate influences safety citizenship behavior through the multilevel chain mediating effect of job resources and harmonious safety passion.ConclusionLeaders at all levels of construction companies should actively participate in safety management practices and conduct safety communication to create a robust psychosocial safety climate. In this way, employes feel that the organization provides them with sufficient work resources and stimulates their work enthusiasm and subjective initiative, thus improving safety citizenship behavior.

Volatile anesthetics representa relevant yet largely avoidable source of greenhouse gas emissions in the healthcare system. In Germany, their use accounts for approximately69 kt of CO2 equivalents annually. While desflurane is used in only about3% of inhalation anesthesia procedures, it is responsible for more than50% of the associated emissions due to its extremely high global warming potential. Modelling studies indicate that complete substitution of desflurane with sevoflurane would reduce total emissions by approximately53%; replacing isoflurane as well would increase the reduction to65%. From a clinical perspective, desflurane offers no proven advantage over sevoflurane with respect to patient safety or postoperative outcomes. Isoflurane likewise shows no clinical superiority. This creates substantial scope for substitution without compromising quality of care. Under minimum alveolar concentration (MAC)-adjusted conditions, desflurane causes an approximately34-fold higher global warming per anesthesia hour than sevoflurane. The contrast is even greater when compared to total intravenous anesthesia (TIVA). Of particular relevance is the short-term climate impact. Due to its high radiative efficiency, desflurane exerts most of its warming effect within a few decades, precisely the critical period up to2050. In addition, volatile anesthetics contribute to environmental contamination with persistent perfluoroalkyl and polyfluoroalkyl substances (PFAS), posing potential long-term risks to ecosystems and human health. Eliminating desflurane requires no new infrastructure, is economically rational and can be implemented immediately. It hence represents a rare opportunity in the healthcare system to achieve rapid and substantial emission reductions through a simple clinical decision, while maintaining patient safety and quality of care.

Volatile anesthetics representa relevant yet largely avoidable source of greenhouse gas emissions in the healthcare system. In Germany, their use accounts for approximately69 kt of CO2 equivalents annually. While desflurane is used in only about3% of inhalation anesthesia procedures, it is responsible for more than50% of the associated emissions due to its extremely high global warming potential. Modelling studies indicate that complete substitution of desflurane with sevoflurane would reduce total emissions by approximately53%; replacing isoflurane as well would increase the reduction to65%. From a clinical perspective, desflurane offers no proven advantage over sevoflurane with respect to patient safety or postoperative outcomes. Isoflurane likewise shows no clinical superiority. This creates substantial scope for substitution without compromising quality of care. Under minimum alveolar concentration (MAC)-adjusted conditions, desflurane causes an approximately34-fold higher global warming per anesthesia hour than sevoflurane. The contrast is even greater when compared to total intravenous anesthesia (TIVA). Of particular relevance is the short-term climate impact. Due to its high radiative efficiency, desflurane exerts most of its warming effect within a few decades, precisely the critical period up to2050. In addition, volatile anesthetics contribute to environmental contamination with persistent perfluoroalkyl and polyfluoroalkyl substances (PFAS), posing potential long-term risks to ecosystems and human health. Eliminating desflurane requires no new infrastructure, is economically rational and can be implemented immediately. It hence represents a rare opportunity in the healthcare system to achieve rapid and substantial emission reductions through a simple clinical decision, while maintaining patient safety and quality of care.

The impact of restaurant menu eco labels on consumer meal selections: a randomized controlled trial.

ABSTRACT Climate change impacts are already evident and projected to worsen throughout the 21st century, even with mitigation efforts. Systematic mapping is key to organizing scientific evidence and identifying gaps, but current methods lack geographical context in relation to climate impact risk. In this study, we leverage machine learning to scale up systematic mapping and use automatic geolocation to track place-based research. We then enhance conventional systematic mapping by integrating location-based climate risk components—hazard, exposure, and vulnerability—to create an evidence gap index. This identifies high-risk regions that lack sufficient scientific study. We demonstrate this method using fluvial floods, combining research distribution with a flood-risk indicator (hazard), population density (exposure), and the Human Development Index (vulnerability). Our novel approach refines evidence mapping, supporting data-driven policymaking and directing research resources to the most urgent areas.

The purpose of the article was to examine how ESG (Environmental, Social, and Governance) criteria are applied to oil companies and highlight the need for industry-specific evaluation methods that better reflect their contribution to sustainable development. Authors used methods as comparative analysis of existing ESG rating methodologies, focusing on their limitations in assessing the oil industry. The study identifies key factors such as climate impact, resource use, and social responsibility that require greater integration into evaluation frameworks. Although ESG ratings are central to assessing investment attractiveness, current models often overlook the specific environmental and operational features of oil companies. This research addresses that methodological gap. Existing ESG systems can distort the sustainability profile of oil companies. Developing more tailored and transparent methods would improve rating accuracy and strengthen trust among investors and society. The paper outlines a conceptual basis for adapting ESG assessment models to industry characteristics, promoting fairer and more reliable sustainability evaluations.

A comfortable and livable living environment can be created through the design of patios in traditional southern rural Chinese dwellings. By connecting indoor and outdoor spaces, patios enable the comprehensive functions of ventilation and shading. To investigate the effects of patios on the building environment and energy conservation, the field parameters of the Wu Family Mansion in Cuijiao Village, Fujian Province, southern China, were measured in August 2016. The results indicate that patios located at the center of dwellings can effectively mitigate the impact of outdoor climate on the indoor environment. Furthermore, a reasonable depth-to-width ratio of the patio is conducive to natural ventilation and energy utilization. Through discussions and simulations using CFD and EcoTECT, it is determined that the reasonable depth-to-width ratio should not be less than 0.06, and a depth of 1.6 m is the most appropriate for patio design to achieve adequate ventilation and illumination. With the Adaptive Predicted Mean Vote (APMV) value ranging from 0 to 1.41, the indoor environment of this rural building falls within the adaptive comfort zone. Compared with air-conditioned rooms, the energy-saving rate achieved by natural ventilation is approximately 26.2%.

To study 1) the differences in dietary climate impact between sociodemographic groups, 2) the differences in food consumption and macronutrient intake as absolute amounts and in relation to energy intake by dietary climate impact level and 3) food groups as contributors of dietary climate impact. Food consumption and energy and macronutrient intakes were calculated based on two non-consecutive 24-hour dietary recalls. Dietary climate impact was calculated using national coefficients produced with life cycle assessment. Regression analysis was used to test the mean differences between sociodemographic groups and sex-specific dietary climate impact tertiles. Finnish national food consumption survey FinDiet 2017. 565 men and 682 women (age 18-74) after exclusion of energy under-reporters. The mean daily dietary climate impact was higher in men than in women (5.6 vs. 4.0 kg CO2eq) and in younger age group (18-44 years) than in older age group (65-74 years). The association of food consumption and dietary climate impact was mainly different for food consumption as absolute amounts (g/day) and in relation to energy (g/MJ). In relation to energy, the consumption of animal-based foods was higher and plant-based foods lower in the highest dietary climate impact tertile compared with the lowest tertile. Red and processed meat was a major contributor of dietary climate impact. Our study emphasizes the importance of considering food consumption and nutrient intake both as absolute amounts and in relation to energy intake. Our findings support the advantages of plant-based diets in being both healthier and more climate-friendly.

The steel industry is beset by issues, including excessive resource use and severe environmental pollution. Iron making is one of the intermediate processes of the steel industry. To assess the environmental implications of this process, a detailed cradle-to-gate life cycle assessment of a blast furnace and its associated units is conducted. The primary data is collected from an iron and steel plant located in the eastern part of India. For the secondary data source, the GaBi Indian extension database is applied. One ton of pig iron production has major impact categories, including abiotic depletion potential (fossil) of 2.64E + 4MJ, acidification potential of 10.3kg of SO2 equiv., global warming potential of 858kg of CO2 equiv., and human toxicity potential of 253kg of DCB equiv. The life cycle phases associated with coke oven and sinter operations are found to be the most influential. The detailed analysis showed that the transportation of raw materials via railways dominates the environmental footprint in both coke and sinter units. A detailed scenario analysis considering railway fuel (electricity, diesel, and a combination of diesel and electricity) was conducted to evaluate the climate impact of transporting raw materials over 1000km. The transportation via electricity and diesel locomotives indicated similar impacts on the environment.

Impacts of climate and human drivers on ecosystem services in the first batch of national parks in China: Spatiotemporal dynamics and implications for management

Impacts of climate and tectonics on orbital-scale sedimentary cycles in the Bohai Bay Basin since the late Pliocene

Guidelines for assessments of the global information and communication technology sector's direct energy use and climate impact: Key aspects and future scenarios

ABSTRACT Aim Terrestrial biodiversity is impacted by both climate and land use change. Yet, future biodiversity projections have rarely considered these two drivers in combination. In this study, we aim to assess the individual and combined impact of future climate and land use change on global terrestrial vertebrate diversity under a ‘sustainability’ (SSP1‐RCP2.6) and an ‘inequality’ (SSP4‐RCP6.0) scenario. Location Global land, excluding Antarctica. Time Period 1995, 2080. Major Taxa Studied Amphibians, birds, and mammals. Methods We combined global climate‐driven species distribution model (SDM) projections of 13,903 vertebrates (amphibians, birds, and mammals) with future and present land use projections from the Land Use Harmonisation 2 (LUH2) project. We refined the SDM outputs by the habitat requirements of each species using a land use filtering approach. We then analyzed future species richness changes globally, per region, and per land use category, and looked at taxon‐specific effects. Results Under both scenarios, decreases in future species richness dominate at low and mid‐latitudes, with climate and land use change playing an equally important role. Land use change can be either an alleviating (SSP1‐RCP2.6) or an exacerbating (SSP4‐RCP6.0) factor of climate‐induced biodiversity loss. Sub‐Saharan Africa is projected to become a high‐risk area for future land use‐driven biodiversity loss under the SSP4‐RCP6.0. Under SSP1‐RCP2.6, forested and non‐forested land areas increase, while SSP4‐RCP6.0 leads to higher rates of deforestation and pasture expansion. Mammals experience the largest climate‐driven losses, affecting 56.4% of land area under SSP4‐RCP6.0, while amphibians are particularly vulnerable to land use‐driven losses, especially under SSP4‐RCP6.0. Main Conclusions Our results suggest that both climate and land use pressures on biodiversity will be highest in lower latitudes, which harbor the highest levels of biodiversity.