Search Results (7,126)

The rising environmental temperatures and growing global demand for animal protein pose major challenges to sustainable livestock production, highlighting the urgent need for climate change mitigation strategies. The livestock system in different parts of the world, especially in developing and underdeveloped nations, holds a significant role in supporting the livelihoods and nutritional security of millions, yet climate change is jeopardizing its efficiency and exacerbating its carbon footprint. This increase in carbon footprint is an alarming challenge for global sustainability, which needs to be addressed meticulously with fruitful outcomes. As the world’s largest livestock hub, the Indian livestock system can be adopted as a model for understanding the challenges and opportunities within the livestock system to develop sustainable approaches. In 2022, India accounted for approximately 7% of global greenhouse gas emissions (GHGEs), with a total of 3.9 billion metric tons of CO₂e. This review provides updated insights on the livestock-related carbon footprint, sustainability-enhancing technologies, GHG estimation models, and strategies for climate-neutral livestock production. Emission estimation models are categorized into source-based and whole-farm models for a comprehensive assessment of emissions. Mitigation strategies for cattle include rumen modification, nutritional approaches, efficient manure management, and precision livestock farming. India’s commitment to achieving net-zero emissions by 2070 is reflected in various initiatives aimed at promoting sustainable livestock systems. Future perspectives emphasize decision modeling and climate-resilient technologies to address environmental challenges in alignment with the UN’s sustainable development goals. Full article

Improvements in quality of life, new technologies and population growth have significantly increased energy consumption in Brazil and around the world. The Paris Agreement aims to limit global warming and promote sustainable development, making green hydrogen a fundamental option for industrial decarbonization. Green hydrogen, produced through the electrolysis of water using renewable energy, is gaining traction as a solution to reducing carbon emissions, with the global hydrogen market expected to grow substantially. This study applies the ${\rho }_{DCCA}$ method to evaluate the cross-correlation between the green hydrogen market and various financial assets, including the URTH ETF, Bitcoin, oil futures, and commodities, revealing some strong positive correlations. It highlights the interconnection of the green hydrogen market with developed financial markets and digital currencies. The cross-correlation between the green hydrogen market and the index representing global financial markets presented a value close to 0.7 for small and large time scales, indicating a strong cross-correlation. The green hydrogen market and Bitcoin also presented a cross-correlation value of 0.4. This study provides valuable information for investors and policymakers, especially those concerned with achieving sustainability goals and environmental-social governance compliance and seeking green assets to protect and diversify various traditional investments. Full article

Agricultural productivity is significantly influenced by climate-related factors. Understanding the impacts of climate change on agroclimatic conditions is critical for ensuring sustainable agricultural practices. This study investigates how key agroclimatic variables—temperature, moisture conditions, and length of the growing season (LGS)—influence wheat suitability in the Upper Blue Nile Basin (UBNB), Ethiopia. The Global Agroecological Zones (GAEZ) methodology was employed to assess agroclimatic suitability, integrating climate projections from Climate Models Intercomparison Project v6 (CMIP6) under shared socioeconomic pathway (ssp370 and ssp585) scenarios. The CMIP6 data provided downscaled projections for temperature and precipitation, while the GAEZ framework translated these climatic inputs into agroclimatic indicators, enabling spatially explicit analyses of land suitability. Projections indicate significant warming, with mean annual temperatures expected to rise between 1.13 °C and 4.85 °C by the end of the century. Precipitation levels are anticipated to increase overall, although spatial variability may challenge moisture availability in some regions. The LGS is projected to extend, particularly in the southern and southeastern UBNB, enhancing agricultural potential in these areas. However, wheat suitability faces considerable declines; under ssp585, the highly suitable area is expected to drop from 24.21% to 13.31% by the 2080s due to thermal and moisture stress. This study highlights the intricate relationship between agroclimatic variables and agricultural productivity. Integrating GAEZ and CMIP6 projections provides quantified insights into the impacts of climate change on wheat suitability. These findings offer a foundation for developing adaptive strategies to safeguard food security and optimize land use in vulnerable regions. Full article

Drought, exacerbated by global warming, poses a significant threat to crop growth and productivity. This study identified a strain of Trichoderma harzianum from the rhizosphere of healthy Nicotiana tabacum L. plants and evaluated its role in enhancing drought tolerance. The isolated strain effectively colonized plant roots and promoted the growth of N. tabacum L. To investigate its potential, T. harzianum was inoculated into plants under varying drought conditions, and its impact on growth, physiological responses, and drought resilience was assessed. Comprehensive analyses of agronomic traits, physiological parameters, enzyme activities, photosynthetic performance, osmoprotectant levels, and membrane lipid peroxidation revealed that T. harzianum inoculation (light drought with T. harzianum, moderate drought with T. harzianum, and severe drought with T. harzianum treatments) systematically improved plant development and drought resistance. These findings provide valuable insights and lay a foundation for developing innovative biofertilizers to enhance crop drought tolerance and sustainability. Full article

In recent years, global warming has become a major driver of biodiversity loss, significantly impacting various vertebrate species, including mammals. Consequently, numerous smaller species face extinction risks due to anthropogenic factors as well as inadequate assessments and conservation planning. Thus, this study focuses on two recently described endemic giant flying squirrel species under the Petaurista genus—Petaurista mishmiensis and Petaurista mechukaensis—found in Arunachal Pradesh, India. Using an ensemble species distribution model (SDM), this research delineates suitable habitats for these lesser-known species and evaluates the effects of climate change and habitat fragmentation on these areas. This analysis aims to inform a comprehensive management plan for their conservation. The ensemble model identified suitable habitat patches for the two species, extending beyond their current IUCN-designated ranges in Arunachal Pradesh. Under present conditions, P. mishmiensis has the largest predicted suitable area (9213 sq. km), followed by P. mechukaensis (6754 sq. km). However, future projections reveal alarming habitat losses ranging from 13.45% to 55.86% across the study area. This study also highlights severe habitat fragmentation throughout the state as viable patches for P. mishmiensis are drastically reduced in size, resulting in many being completely lost and the remaining areas being closer together. However, the P. mechukaensis experiences significant disintegration, resulting in numerous smaller, more dispersed patches within Arunachal Pradesh. Hence, to address these challenges, this study recommends several actions such as genetic assessments to confirm evolutionary relationships, evaluations of corridor connectivity, and comprehensive field studies. Furthermore, establishing joint forest conservation committees involving local communities, forest personnel, defense forces, naturalists, and scientists are also encouraged. Ultimately, this research provides critical insights for guiding future field studies across Arunachal Pradesh’s vast landscapes and supports the development of detailed species management plans to protect these endemic flying squirrels. Full article

Addressing the pressing issue of global warming, sustainable rice cultivation strategies are crucial. Milk vetch (MV), a common green manure in paddies, has been shown to increase CH₄ emissions, necessitating effective mitigation. This two-year field experiment assessed the impact of applying calcium peroxide (CaO₂), widely used in wastewater treatment and soil remediation due to its oxygen-releasing properties, on CH₄ emissions in conventional paddy fields (chemical fertilizer-only) and MV-incorporated fields. The results revealed that in conventional paddy fields, CaO₂ application significantly reduced the average CH₄ emissions by 19% without affecting rice yield. Compared with chemical fertilizer alone, MV incorporation increased the average rice yield by 12% but significantly elevated CH₄ emissions. However, in paddy fields with MV incorporation, CaO₂ application significantly reduced CH₄ emissions by 19% while preserving the yield benefits of MV. Soil analyses indicated that MV incorporation led to increased soil carbon content and increased mcrA and pmoA gene copy numbers, with elevated mcrA gene copy numbers being primarily responsible for the promoted CH₄ emissions. CaO₂ application improved the soil redox potential, reducing mcrA gene copies and consequently mitigating CH₄ emissions. Overall, CaO₂ application can contribute to global efforts to reduce CH₄ emissions while supporting rice productivity. Full article

Methane is a potent greenhouse gas that significantly contributes to global warming, making the accurate quantification of methane emissions essential for climate change mitigation. The traditional matched filter (MF) algorithm, commonly used to derive methane enhancement from hyperspectral satellite data, is limited by its tendency to underestimate methane plumes, especially at higher concentrations. To address this limitation, we proposed a novel approach—the multi-level matched filter (MLMF)—which incorporates unit absorption spectra matching using a radiance look-up table (LUT) and applies piecewise regressions for concentrations above specific thresholds. This methodology offers a more precise distinction between background and plume pixels, reducing noise interference and mitigating the underestimation of high-concentration emissions. The effectiveness of the MLMF was validated through a series of tests, including simulated data tests and controlled release experiments using satellite observations. These validations demonstrated significant improvements in accuracy: In radiance residual tests, relative errors at high concentrations were reduced from up to −30% to within ±5%, and regression slopes improved from 0.89 to 1.00. In simulated data, the MLMF reduced root mean square error (RMSE) from 1563.63 ppm·m to 337.09 ppm·m, and R² values improved from 0.91 to 0.98 for Gaussian plumes. In controlled release experiments, the MLMF significantly enhanced emission rate estimation, improving $R^2$ from 0.71 to 0.96 and reducing RMSE from 92.32 kg/h to 16.10 kg/h. By improving the accuracy of methane detection and emission quantification, the MLMF presents a significant advancement in methane monitoring technologies. The MLMF’s superior accuracy in detecting high-concentration methane plumes enables better identification and quantification of major emission sources. Its compatibility with other techniques and its potential for integration into real-time operational monitoring systems further extend its applicability in supporting evidence-based climate policy development and mitigation strategies. Full article

Understanding global patterns of tree canopy height and density is essential for effective forest management and conservation planning. This study examines how these attributes vary along latitudinal gradients and identifies key climatic drivers influencing them. We utilized high-resolution remote sensing datasets, including a 10 m resolution canopy height dataset aggregated to 1 km for computational efficiency, and a 1 km resolution tree density dataset derived from ground-based measurements. To quantify the relationships between forest structure and environmental factors, we applied nonlinear regression models and climate dependency analyses, incorporating bioclimatic variables from the WorldClim dataset. Our key finding is that latitude exerts a dominant but asymmetric control on tree height and density, with tropical regions exhibiting the strongest correlations. Tree height follows a quadratic latitudinal pattern, explaining 29.3% of global variation, but this relationship is most pronounced in the tropics (−10° to 10° latitude, R² = 91.3%), where warm and humid conditions promote taller forests. Importantly, this effect differs by hemisphere, with the Southern Hemisphere (R² = 67.1%) showing stronger latitudinal dependence than the Northern Hemisphere (R² = 35.3%), indicating climatic asymmetry in forest growth dynamics. Tree density exhibits a similar quadratic trend but with weaker global predictive power (R² = 7%); however, within the tropics, latitude explains 90.6% of tree density variation, underscoring strong environmental constraints in biodiverse ecosystems. Among climatic factors, isothermality (Bio 3) is identified as the strongest determinant of tree height (R² = 50.8%), suggesting that regions with stable temperature fluctuations foster taller forests. Tree density is most strongly influenced by the mean diurnal temperature range (Bio 2, R² = 36.3%), emphasizing the role of daily thermal variability in tree distribution. Precipitation-related factors (Bio 14 and Bio 19) moderately explain tree height (~33%) and tree density (~25%), reinforcing the role of moisture availability in structuring forests. This study advances forest ecology research by integrating high-resolution canopy structure data with robust climate-driven modeling, revealing previously undocumented hemispheric asymmetries and biome-specific climate dependencies. These findings improve global forest predictive models and offer new insights for conservation strategies, particularly in tropical regions vulnerable to climate change. Full article

Global emissions from the transportation sector were nearly 7.7 GtCO₂ in 2021. In Thailand, the transportation sector emitted 69 MtCO₂ and consumed 27,460 ktoe of final energy in the same year. Transitioning from internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) can help reduce greenhouse gas emissions and air pollution, particularly PM2.5, in major metropolitan areas. However, in the early stages, the adoption of EVs may affect consumer considerations. This study aimed to investigate motivators and environmental awareness regarding EV adoption in Thailand. It also analyzed CO₂ emissions from the transportation sector in Thailand, covering the period from 1987 to 2023, to understand long-term trends and recent changes. An online questionnaire was conducted, and a total of 459 respondents participated. The results revealed that the top three motivators for respondents to consider EVs were the potential tax refund for purchasing an EV, lower charging costs compared to fuel costs for ICEVs, and lower operating costs for EVs compared to ICEVs. In terms of environmental awareness, respondents expressed concerns about adapting to global warming, the potential for EVs to reduce air pollution, and the environment in general. Based on the findings, individuals aged between 26 and 35 years old could be the key target group for early EV adoption. Full article

The Antarctic sea ice concentration (SIC) plays a crucial role in global climate dynamics by influencing atmospheric and oceanic circulation. This study examines SIC variability and its relationship with major climate modes, including the El Niño-Southern Oscillation (ENSO), Pacific-South American (PSA) pattern, Southern Annular Mode (SAM), and Antarctic Dipole (ADP). Using NSIDC satellite-derived sea ice data and ERA5 reanalysis from 1980 to 2022, we analyzed SIC anomalies in the Weddell, Ross, and Bellingshausen and Amundsen (B&A) Seas, assessing their response to climatic forcings across different timescales. Our findings reveal strong linkages between SIC variability and large-scale atmospheric circulation. ENSO-related teleconnections drive a dipolar SIC response, with warming in the Pacific sector and cooling in the Atlantic during El Niño, and the opposite pattern during La Niña. PSA and ADP further modulate this response by altering Rossby wave propagation and heat fluxes, leading to significant SIC fluctuations. The ADP emerges as a dominant driver of interannual SIC anomalies, showing an out-of-phase relationship between the Atlantic and Pacific sectors of the Southern Ocean. Regional SIC trends exhibit contrasting patterns: the Ross Sea shows a significant positive SIC trend, while the B&A and Weddell Seas experience persistent negative anomalies due to enhanced meridional heat transport and stronger westerly winds. SAM strongly influences SIC, particularly in the Atlantic sector, with delayed responses of up to six months, likely due to ice-albedo feedbacks and ocean memory effects. These results enhance our understanding of Antarctic sea ice variability and its sensitivity to large-scale climate oscillations. Given the observed trends and ongoing climate change, further research is needed to assess how these processes will evolve under future warming scenarios. This study highlights the importance of continuous satellite observations and high-resolution climate modeling for improving projections of Antarctic sea ice behavior and its implications for the global climate system. Full article

The operational energy efficiency of new buildings in the EU should be at the level of ultra-low or near-zero energy buildings. It is therefore relatively difficult to achieve further energy savings. However, the pre-operational phase—raw material sourcing, manufacturing, transportation, and construction—offers significant energy savings and greenhouse gas reduction opportunities, referred to as embodied energy and equivalent CO₂ emissions. Unlike operational energy, no standard or legislative criteria have yet been established for embodied energy. Setting maximum embodied energy values converted to the unit of heated building area, accounting for building shape factor, and differentiating between high-mass and lightweight constructions are proposed. This study illustrates assessing environmental indicators based on building shape, highlighting the necessity of relative assessments over absolute values to favour energy efficiency. It also emphasizes that precise criteria should derive from authentic data collected during the energy certification and building permitting processes. Integrating assessments of embodied energy and operational energy demand facilitates a comprehensive evaluation of buildings’ environmental performance. Full article

Background: With global warming and climate change, the occurrence of abiotic stresses has become increasingly prevalent. Drought often occurs with high temperatures, especially in arid and semi-arid regions. However, the molecular mechanisms of plants responding to combined drought and high-temperature stress remains unclear. Results: Through integrative physiological, transcriptomic, and metabolomic analyses, we systematically investigated the adaptive mechanisms of Dendrobium huoshanense under combined drought and high-temperature stress. Our findings revealed that combined drought and high-temperature stress led to significant reductions in photosynthetic efficiency and increased oxidative damage in Dendrobium huoshanense, with high-temperature stress being the primary contributor to these adverse effects. The joint analysis shows that three core pathways—signal transduction, lipid metabolism, and secondary metabolite biosynthesis—were identified as critical for antioxidant defense and stress adaptation. Conclusions: These findings not only deepen our understanding of plant responses to combined drought and high-temperature stress but also provide new directions for future research on the cultivation and resistance improvement of Dendrobium huoshanense. Full article

Bamboos, as imperative vegetations in Chinese traditional gardens, also significantly influenced the recently originated Neo-Chinese-style landscape in China, and their habitat ranges have been profoundly impacted by global climate warming. Current studies on the distribution dynamics of bamboo reveal existent gaps in assessing the suitable distribution area of Neo-Chinese-style landscapes. In this study, we calculated the habitat ranges of two widely distributed bamboo genera (Phyllostachys and Bambusa) based on the optimal MaxEnt model, predicted their future (2050s, 2070s and 2090s) distributions under different climate scenarios (SSP1-2.6 and SSP5-8.5), and assessed the suitable distribution area of the Neo-Chinese-style landscape according to the distribution union of two bamboo genera. The results showed that the optimal MaxEnt model exhibited high evaluation indices (AUC > 0.90) for the two bamboo genera. The habitat ranges of bamboo genera were significantly influenced by the minimum temperature of the coldest month and would expand northwardly in the future. The suitable distribution area of Neo-Chinese-style landscapes covered about 71.3% cities of China, which would expand 5.9%–8.7% of cities and 10%–18.7% of cities under the SSP1-2.6 climate scenario and the SSP5-8.5 climate scenario, respectively. The suitable distributions are mainly located in the southeast part of China. This study advanced our understanding of the restriction of bamboo to the distribution of the Neo-Chinese-style landscape and provided valuable insights and a scientific basis for landscape construction in different areas of China. Full article

The historical City of Venice, with its lagoon, has been severely exposed to repeated marine flooding since historical times due to the combined effects of sea level rise (SLR) and land subsidence (LS) by natural and anthropogenic causes. Although the sea level change in this area has been studied for several years, no detailed flooding scenarios have yet been realized to predict the effects of the expected SLR in the coming decades on the coasts and islands of the lagoon due to global warming. From the analysis of geodetic data and climatic projections for the Shared Socioeconomic Pathways (SSP1-2.6; SSP3-7.0 and SSP5-8.5) released in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC), we estimated the rates of LS, the projected local relative sea level rise (RSLR), and the expected extent of flooded surfaces for 11 selected areas of the Venice Lagoon for the years 2050, 2100, and 2150 AD. Vertical Land Movements (VLM) were obtained from the integrated analysis of Global Navigation Satellite System (GNSS) and Interferometry Synthetic Aperture Radar (InSAR) data in the time spans of 1996–2023 and 2017–2023, respectively. The spatial distribution of VLM at 1–3 mm/yr, with maximum values up to 7 mm/yr, is driving the observed variable trend in the RSLR across the lagoon, as also shown by the analysis of the tide gauge data. This is leading to different expected flooding scenarios in the emerging sectors of the investigated area. Scenarios were projected on accurate high-resolution Digital Surface Models (DSMs) derived from LiDAR data. By 2150, over 112 km² is at risk of flooding for the SSP1-2.6 low-emission scenario, with critical values of 139 km² for the SSP5-8.5 high-emission scenario. In the case of extreme events of high water levels caused by the joint effects of astronomical tides, seiches, and atmospheric forcing, the RSLR in 2150 may temporarily increase up to 3.47 m above the reference level of the Punta della Salute tide gauge station. This results in up to 65% of land flooding. This extreme scenario poses the question of the future durability and effectiveness of the MoSE (Modulo Sperimentale Elettromeccanico), an artificial barrier that protects the lagoon from high tides, SLR, flooding, and storm surges up to 3 m, which could be submerged by the sea around 2100 AD as a consequence of global warming. Finally, the expected scenarios highlight the need for the local communities to improve the flood resiliency plans to mitigate the consequences of the expected RSLR by 2150 in the UNESCO site of Venice and the unique environmental area of its lagoon. Full article