Spent coffee grounds (SCG) are extensively generated as a byproduct of coffee production and consumption. Improper disposal of SCG contributes to greenhouse gas emissions, environmental pollution, and the loss of valuable resources when landfilled or discharged into sewage systems. In response, this study investigates the biodegradation potential of SCG using selected wood-decay fungi known for their ability to secrete a wide spectrum of lignocellulose-degrading enzymes and degrade complex organic compounds. White rot fungi, such as Irpex lacteus, Pleurotus dryinus, and Trametes versicolor, were cultivated in SCG-containing media to evaluate the degradation efficiency, fermentable sugar dynamics, and fungal enzyme secretion patterns. All tested fungi were able to metabolize SCG and exhibited active enzyme secretion during cultivation. P. dryinus and T. versicolor efficiently secreted both cellulases and laccases, with T. versicolor demonstrating laccase activity of 721.193 ± 41.72 U/L, indicating high oxidative potential. Fungal cultivation and enzyme production resulted in a significant carbohydrate degradation in SCG. The most significant decrease was observed in P. dryinus, which achieved a 43.32% reduction in SCG carbohydrates, while T. versicolor and I. lacteus ensured reductions of 39.07% and 35.55%, respectively. The findings demonstrate that SCG can serve as a low-cost substrate for fungal enzyme production, particularly for laccase generation by T. versicolor, while simultaneously enabling SCG biomass degradation. Together, the study shows the potential of white rot fungi for the biological treatment of SCG, contributing to the development of more sustainable strategies for coffee waste valorization as an alternative to environmentally harmful disposal routes.

Background: Dietary patterns face substantial environmental pressures, but few studies compare the ecological impact of those derived from widely implemented or recently proposed dietary guidelines. Updates to the American dietary pyramid have raised concerns about these environmental implications. Objectives: To compare greenhouse gas emissions (GHGE), water use, land use, and energy use across three dietary patterns: Dietary Approaches to Stop Hypertension (DASH), Mediterranean diet (MD), and Dietary Guidelines for Americans (DGA) 2025–2030-style diet. Design: Comparative analysis of modeled seven-day diets based on each guideline. Methods: Representative diets were constructed following food-based recommendations for each pattern. Environmental indicators for all food items were obtained from the Agribalyse® 3.0.1 database. Daily GHGE, water use, land use, and energy use were calculated. Differences between patterns were assessed using one-way ANOVA with Bonferroni corrections, before and after adjustment for total dietary energy intake. Results: The DGA 2025–2030-style diet showed significantly higher GHGE and energy use compared with DASH and MD (p < 0.001), while no significant differences were observed between DASH and MD. No significant differences were found for water or land use across dietary patterns, which may be due to the heterogeneous contribution of individual food items to these indicators across dietary patterns. The DGA 2025–2030-style diet also had the highest total energy intake (p < 0.001). After adjustment for dietary energy intake, only GHGE differences remained significant (F = 6.187, p = 0.009), with the DGA 2025–2030-style diet showing the highest values and the MD the lowest. Conclusions: Dietary guidelines should integrate environmental sustainability criteria alongside nutritional recommendations. Reducing the environmental impact of diets may be achieved by promoting dietary patterns such as the MD and DASH diets, and by limiting high-impact foods characteristic of the DGA 2025–2030-style diet, particularly those contributing to higher GHGE. These strategies could support the transition toward diets that are both nutritionally adequate and environmentally sustainable.

The subtropical wetlands of the Doon Valley function as significant net sources of greenhouse gases (GHGs), with methane (CH₄) dominating the radiative forcing (∼62% of CO₂-equivalent emissions) despite lower molar fluxes than carbon dioxide (CO₂). High-resolution field measurements reveal that CH₄ emissions are primarily controlled by anaerobic conditions, sustained soil moisture, elevated temperatures, and low dissolved oxygen, whereas CO₂ fluxes exhibit greater temporal variability and respond strongly to thermal regimes and ionic strength. A key biogeoclimatic insight is the seasonal decoupling of soil moisture and atmospheric water vapor (H2O), where summer drying coincides with peak humidity driven by energy-limited evapotranspiration. Pronounced spatial heterogeneity in gas fluxes further suggests that land-use context and modified hydrological pathways may interact with climatic drivers to influence wetland carbon dynamics. The wetland complex (221.39ha) emits approximately 0.0195 Mt CO₂-eq annually, underscoring its disproportionate role in regional GHG budgets. These findings reveal strong coupling among hydrological saturation, thermal regimes, redox conditions, and atmospheric moisture in regulating GHG emissions. The study underscores the high climate sensitivity of monsoon-dependent wetlands and highlights the need for targeted hydrological restoration and continuous monitoring to mitigate future amplification of emissions under warming scenarios.

This study explores the impact of different light colors on the population growth, photosynthesis, and biochemical composition of Scenedesmus obliquus. Literature shows various biotechnological solutions to mitigate the environmental problems caused by greenhouse gas emissions from environmentally unsustainable processes, and microalgae cultures have emerged as a promising technology with the potential to support diverse production chains. In this context, Scenedesmus has demonstrated considerable potential. The present study presents a straightforward approach to enhance protein production in S. obliquus through the strategic manipulation of light wavelengths, with the potential for practical implementation. The paper goes on to outline future research directions for integrating light control technologies, emphasizing the potential for maximizing biomolecules accumulation. Cell density and viability, growth rates, carbohydrates and proteins, total carotenoids and photosynthesis inferred by pulse amplitude modulated fluorescence (PhytoPAM) were evaluated. Blue light was identified as optimal for total proteins production (5.5µg/mL vs. 2.5-3.8µg/mL in other light colors), while white light showed promise for carotenoid accumulation (0.160µg/mL vs. 0.10-0.13 in other light colors). Notably, the observed variations in the light spectrum did not result in any significant changes in the maximum growth rates (1.08-1.13), underscoring the robustness of the organism under study. Photosynthetic parameters remained unaffected by light quality, indicating a robust photosynthetic machinery (qP 1.0, NPQ 0.2, and effective quantum yield 0.58). These findings contribute to our understanding of algal biology and provide practical insights for biotechnological applications, paving the way for sustainable solutions.

Nitrification is a key process governing nitrogen (N) loss and greenhouse gas emissions in agricultural soils, and its regulation is strongly influenced by both chemical inhibitors and soil properties. Copper (Cu), a metal cofactor that is crucial for the function of ammonia monooxygenase (AMO), plays an important role in ammonia oxidation, whereas dicyandiamide (DCD) suppresses nitrification and may interact with Cu to inhibit AMO activity. However, the extent to which Cu availability and soil organic matter (SOM) jointly regulate DCD efficiency remains poorly understood. In this study, an incubation experiment was conducted using tropical paddy soils with contrasting SOM contents to explore how varying Cu levels (10 and 200 mg Cu kg−1 soil) impact DCD efficiency in regulating the nitrification process and controlling nitrous oxide (N2O) and carbon dioxide (CO2) emissions. Our results showed that DCD generally suppressed nitrification, as indicated by reduced NO3− accumulation and lower NO3−/NH4+ ratios. However, the response to Cu was strongly SOM-dependent. Under low SOM, Cu addition was associated with a partial restoration of nitrification activity, suggesting a potential reduction in DCD efficiency, whereas under high SOM, this effect appeared to be attenuated, likely due to Cu complexation and reduced bioavailability. Increasing Cu levels further weakened DCD inhibition, particularly in low SOM soils. DCD significantly reduced N2O emissions, but this mitigation effect declined with Cu addition, suggesting a Cu-mediated influence on nitrification–denitrification pathways. On the other hand, CO2 emissions were reduced under DCD application and appeared to be further reduced under Cu treatments. Changes in enzyme activities and nitrifier gene abundances supported these patterns, suggesting distinct responses of AOA and AOB communities under varying SOM and Cu conditions. This study provided evidence that the interaction of Cu availability and SOM may play an important role in governing the efficacy of nitrification inhibitors. This highlights the importance of considering soil-specific chemical environments when optimizing N management strategies to reduce environmental N losses.

Rising global temperatures and urbanization have intensified the demand for sustainable cooling solutions, particularly in hot and arid climates such as Iraq, where conventional air conditioning exacerbates energy consumption and greenhouse gas emissions. Evaporative cooling provides an energy-efficient method to reduce ambient temperatures through water evaporation. However, their effectiveness is highly dependent on local climatic conditions. The study objectives were to provide practical insights into the application and limitations of direct evaporative cooling in real-world Iraqi circumstances, beyond technical modeling. A climate-responsive assessment framework for evaporative cooling systems by combining the Köppen climate classification with localized thermal comfort analysis was developed. The effectiveness of evaporative cooling for sustainable thermal comfort was assessed through case studies in major Iraqi cities (Baghdad, Basrah, and Mosul) from 1st May to 30th September under two scenarios: (i) air cooled via direct evaporative processes; and (ii) unconditioned outdoor air delivered through mechanical ventilation. Various modules of the simulation software were used to model hourly air conditions under these scenarios. The results demonstrated that Basrah had the lowest thermal comfort under mechanical ventilation circumstances, with only 6% of summer hours falling into the comfort zone which made it the most vulnerable city in Iraq. Evaporative cooling substantially enhanced the number of thermally comfortable hours during peak summer conditions in Baghdad, Basrah, and Mosul by 41.28%, 54.48%, and 30.55%, respectively, in comparison to scenarios utilizing mechanical ventilation. Integrating climate responsive design and thermal comfort indices through evaporative cooling enhanced energy efficiency and sustainable building performance.

Tunnel kilns are widely used in ceramic manufacturing due to their continuous operation, stable performance, and relatively high thermal efficiency. However, the firing stage remains highly energy-intensive and is a major source of environmental impact, necessitating advanced strategies for performance optimization and sustainability. This study presents a comprehensive and critical review of recent developments in tunnel kiln technology, focusing on heat transfer mechanisms, thermal modeling, process optimization, airflow management, energy recovery, computational fluid dynamics (CFD), and environmental sustainability. The literature shows that kiln performance is governed by strongly coupled interactions among fluid flow, heat transfer, combustion, and material transformations. Although significant progress has been achieved through analytical modeling, experimental studies, and numerical simulations, many approaches rely on simplified assumptions or isolated subsystem analyses, limiting their applicability to real industrial conditions. Key findings emphasize the importance of optimizing airflow distribution, kiln geometry, and product arrangement to enhance convective heat transfer and temperature uniformity. Energy optimization strategies—including waste heat recovery, combustion control, and reduction in kiln car thermal mass—demonstrate considerable potential, but their effectiveness depends on integrated, system-level implementation. Environmental analyses identify the firing stage as the primary source of greenhouse gas emissions, highlighting the need for coordinated energy and emission reduction strategies. In this context, Digital Twin and Industry 4.0 technologies offer promising capabilities for real-time monitoring, predictive control, and data-driven optimization. Generally, this review underscores the need to transition from isolated optimization approaches to integrated, multi-scale frameworks that combine advanced modeling, experimental validation, and intelligent digital systems to achieve sustainable and energy-efficient ceramic manufacturing.

Climate change is one of the most pressing global challenges and is closely related to the increase in greenhouse gas emissions resulting from human activities. The State of São Paulo stands out due to its economic relevance and pronounced socioeconomic heterogeneity among municipalities, making it an appropriate case for analyzing the relationship between development and environmental emissions. This study aims to examine the socioeconomic determinants of carbon dioxide equivalent emissions in the State of São Paulo, using the STIRPAT model estimated through fixed effects regressions. The results indicate that the expansion of the vehicle fleet has a positive and statistically significant impact on CO₂eq emissions. Conversely, industrial value added shows a negative coefficient, suggesting productivity gains and a potential decoupling between industrial growth and emissions in certain places. The findings reveal a strong spatial concentration of emissions among a small number of municipalities within the state.

Water-energy-carbon nexus and de-carbonation pathways in integrated urban water system for a megacity study.

The energy sector in Pakistan continuously relying on imported fossil fuels, which remain costly, contribute to air pollution, and increase greenhouse gas (GHG) emissions. In this study, the Low Emission Analysis Platform (LEAP) model is used to compare three electricity supply scenarios between 2021 and 2050, including a Business-as-Usual (BAU) scenario, the Alternative and Renewable Energy Policy (AREP 2019) scenario, and a higher target Sustainable Pathway (SP) scenario. The scenarios are compared to evaluate the capabilities of renewable energy policies and interventions in ensuring that energy supply is secured, and climate change is mitigated in the context of Sustainable Development Goals (especially SDG 7 on clean energy and SDG 13 on climate action). The modelling outcomes estimate that by 2050, the electricity demand in Pakistan will be around 1489 TWh, whereas the GHG emissions will increase from 100 MtCO2-e(2025) to 564.7 MtCO2-e annually under BAU. Conversely, the SP scenario, by contrast, where a faster switch to renewables is assumed, would limit 2050 emissions to approximately 34 MtCO2-e, with more than 90% reduction over BAU. Moreover, SP scenario is consistent with cost benchmarks of Pakistan’s IGCEP plan. However, achieving this level assumes significant grid infrastructure upgrades, including advanced transmission and smart distribution systems, which are under ongoing development in Pakistan. These findings highlight Pakistan’s urgent need to speed up the move toward renewable energy. Using the country’s large, unused renewable resources through better policies and investments is essential for improving energy security and protecting the environment from climate change.

Biogenic carbon dioxide storage and mineral carbonation uptake in EU buildings.

Apply machine learning to predict greenhouse gas emissions in aerobic composting and achieve emission reduction by nanomembrane covering mode.

Greenhouse gas emissions and water-carbon cost-adjusted yield of drought-tolerant rice under varying irrigation amounts in the Jianghan Plain of China

Climate change poses the greatest threat to human health in the 21st century. The healthcare sector contributes approximately 5% of global greenhouse gas emissions and has a significant environmental impact. Although clinical trials are crucial for identifying effective and safe treatments and preventing disease, their environmental impact is poorly documented. Our study aimed to assess the environmental impact of a publicly funded, academic clinical trial by adapting life cycle assessment (LCA) methodology to clinical research. We performed a retrospective, simplified, full LCA using the EF 3.0 methodology on a prospective, double-blind, randomised controlled neurosurgery trial. The trial included 202 patients at 18 university hospitals throughout France. To identify hotspots of interest, 16 impact indicators and their combination into a single score were evaluated. The results showed that climate change (or greenhouse gas emissions) was the most important indicator, accounting for almost 30% of the single score. Greenhouse gas emissions were estimated at 31.6 t of carbon dioxide equivalent. The next most important were resource use of fossils (24%), resource use of minerals and metals (12%), and particulate matter emissions (8%). The main hotspots identified were patient transport and travel by clinical research assistants for source data verification. In conclusion, by using a full LCA approach, our study confirms that conducting a clinical trial has a substantial environmental impact, particularly with regard to greenhouse gas emissions. The main hotspots identified were related to patient transport and clinical research assistants' travel. Trial Registration: The SUCRE study (Treatment of Chronic Subdural Hematoma by Corticosteroids: A Prospective Randomised Study)-clinicaltrials.gov identifier: NCT02650609.

• Chengdu led global CO 2 emissions followed by Luoyang, Chongqing, and Los Angeles. • Katowice had highest CH 4 emissions, trailed by São Paulo, Lahore, and Delhi. • CO 2 levels rose from 394.470–394.477 ppm in 2003 to 394.501–394.510 ppm in 2020. • CH 4 levels increased from 1831.3–1833.3 ppb to 1832–1834.5 ppb over 17 years. • Minimum land surface air temperature rose by 2 °C, from −54.49 °C to −52.20 °C. This study examined global atmospheric variations in carbon dioxide (CO 2 ) and methane (CH 4 ), which are two major greenhouse gases (GHGs). The main objectives were as follows: (1) identify the top 50 cities with the highest CO 2 and CH 4 emissions, (2) analyze 17-year trends in emissions in cities worldwide, (3) conduct a spatiotemporal analysis of CO 2 and CH 4 emissions from 2003 to 2020, (4) quantify changes in GHG emissions during this period, and (5) assess the impact of GHG emissions on land surface air temperature (LSAT). These objectives were achieved using the global ERA5 reanalysis data from the Copernicus Climate Change Service. The findings indicated that Chengdu (China) had the highest cumulative CO 2 emissions between 2003 and 2020, followed by Luoyang (China), Chongqing (China), Myitkyina (Myanmar), Louangphrabang (Laos), Lampang (Thailand), Louang Namtha (Laos), Aizawl (India), Nola (Central African Republic), and Los Angeles (USA). Katowice (Poland) exhibited the highest CH 4 emissions, followed by São Paulo (Brazil), Lahore (Pakistan), Delhi (India), New Delhi (India), Moscow (Russia), Chengdu (China), Anshan (China), Andijan (Uzbekistan), and Fergana (Uzbekistan). Between 2003 and 2020, the mean annual atmospheric CO 2 concentration increased from 394.470–394.477 ppm to 394.501–394.510 ppm, whereas the CH 4 concentration increased from 1831.3–1833.3 ppb to 1832–1834.5 ppb. The analysis revealed significant increasing trends in CO 2 and CH 4 emissions globally, with certain cities exhibiting sharper increases. The LSAT also increased during the study period, with the minimum LSAT increasing by 2 °C (from − 54.49 °C to − 52.20 °C). This comprehensive analysis highlights the urgent need to address GHG emissions to mitigate their environmental and climatic effects.

Local policy makers increasingly have implemented nutrition standards for municipal programs to advance population health and climate change goals. Yet little is known about the impact of these policies. In 2008, New York City established nutrition standards for food purchased and served by city agencies, and in 2022, it revised the standards to limit meat and increase plant-based options. Using menu data from four agencies serving 77percent of all city meals, we examined changes in their entrée offerings, as well as greenhouse gas and nutrition content associated with their total menu offerings, from fiscal year 2019 through fiscal year 2024. All agencies reduced the frequency of beef entrées offered on menus and increased the frequency of vegetarian entrées. Changes in total menu offerings were associated with an estimated reduction of 0.64 kilograms of carbon dioxide equivalent in greenhouse gas emissions per portion across all agencies and programs, while the nutrition content generally remained consistent. These findings suggest that municipal food standards can support greenhouse gas reductions without compromising nutrition, and they offer a model for other jurisdictions seeking to advance both population and environmental health goals.

As the biggest greenhouse gas (GHG) emitter globally, China has pledged to achieve carbon neutrality by 2060. However, the environmental sustainability of this goal has not been assessed comprehensively on a life cycle basis. Focusing on the electricity sector, which contributes >40% to China's GHG emissions, this study evaluates the role and the potential of renewables for achieving net-zero by estimating their life cycle impacts across 31 provinces in China. A future (2050) renewable electricity grid is designed considering daily demand and generation curves, as well as resource potential and future technological advancements. Most of the electricity is generated by solar and wind (70%), followed by hydro (9%), biomass with and without carbon capture and storage (6%), and energy storage (14%). This mix achieves a net-negative climate change impact of −12 kg CO 2 eq./MWh electricity generated (compared to the current 877 kg CO 2 eq./MWh). The net negative impact is found in 18 provinces (−2.1 to −166.1 kg CO 2 eq. per MWh) owing to the biomass energy with carbon capture and storage (BECCS). The rest of the provinces have a net-positive but still relatively low impact (0–42 kg CO 2 eq./MWh) because of the high share of renewables. The majority of the remaining 17 impacts are also significantly lower (5.5–96%) than the impacts of the current grid, except for metal depletion, water consumption and freshwater and marine ecotoxicity. The minimum requirements for achieving the net-zero target for the electricity sector are either the utilisation of 55% of the total estimated biomass energy potential of 22 EJ, or BECCS share of 46% in the total capacity of biomass plants, equivalent to 2.25% of electricity generation. These results help to identify the environmental trade-offs in meeting the decarbonisation targets and to guide a future deployment of net-zero electricity in China.

Experimental evaluation of a R290 vapour compression refrigeration system hybridised with a thermoelectric subcooler

Recent advances in metabolic engineering of purple non‑sulfur photosynthetic bacteria for enhanced biohydrogen production.

Structural and techno-functional modifications of pea protein fractions by non-thermal technologies.