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In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

Methane emissions are responsible for approximately $0.5$$°\mathrm{C}$, or about 30%, of total greenhouse-gas-induced warming. For many countries, methane represents an even larger share of their overall warming footprint. Assessing the warming contributions of individual methane-emitting countries to global warming is not straightforward due to methane’s short atmospheric lifetime and the non-linear (convex) relationship between radiative forcing and the atmospheric concentration of this gas. This study addresses this challenge using a simple climate model in combination with a warming allocation approach derived from cooperative game theory. Applying this method, the warming contributions of several high-methane-emitting countries and regional groupings are quantified relative to the early industrial period. The analysis reveals that the commonly used marginal attribution method underestimates methane-induced warming by approximately 20%. This discrepancy is due to the substantial rise in the atmospheric concentration of methane since early industrial times. Full article

The transition towards a low-carbon energy system remains a critical challenge for regions heavily dependent on fossil fuels, such as Andalusia. This study proposes an energy planning framework based on the Low Emissions Analysis Platform (LEAP) to model alternative scenarios and assess the feasibility of meeting the 2030 and 2050 decarbonisation targets. Three scenarios are evaluated, the Tendential Scenario (TS01), the Efficient Scenario (ES01), and the Efficient UJA (EEUJA) Scenario, with this last being specifically designed to ensure full compliance with regional energy goals. The results indicate that, while the Tendential Scenario falls short in reducing primary energy consumption and greenhouse gas (GHG) emissions, the Efficient Scenario achieves significant progress, though it is still insufficient to meet renewable energy integration targets. The proposed EEUJA Scenario introduces more ambitious measures, including large-scale electrification, smart grids, energy storage, and green hydrogen deployment, resulting in a 39.5% reduction in primary energy demand by 2030 and 97% renewable energy penetration by 2050. Furthermore, by implementing sector-specific decarbonisation strategies for the industry, transport, residential, and services sectors, Andalusia could position itself as a frontrunner in the energy transition while minimising economic and environmental risks. These findings underscore the importance of policy enforcement, technological innovation, and financial incentives in securing a sustainable energy future. The methodology developed in this study is replicable for other regions aiming for carbon neutrality and energy resilience through strategic planning and scenario analysis. Full article

This study investigates the impact of reducing waiting times for port berth on improving the Carbon Intensity Indicator (CII) ratings of Korean-flagged container ships. As the International Maritime Organization (IMO)’s CII regulation mandates corrective actions for poorly rated ships for Greenhouse Gas (GHG) reduction in international shipping, the analysis focuses on container ships with projected D or E ratings by 2035. Using Automatic Identification System (AIS) data from ships, this study identifies annual waiting times and simulates changes in CII ratings under scenarios of reduced waiting times (30%, 50%, 70%, and 100%). The relationship between ship speed and fuel consumption was established by analyzing the recent literature, and the CII improvement was evaluated based on IMO Data Collection System (DCS) 2022 data. The results show that a 30% reduction in waiting time can lower CO₂ emissions by 12.18% and improve the CII rating by one or two levels for approximately half of the sample ships. However, a 50% reduction or more is required to maintain improved ratings beyond 2030. The findings highlight the significance of just-in-time (JIT) practices in minimizing latency and enhancing regulatory compliance. The policy recommendations advocate for prioritizing port call optimization and recommend the adoption of JIT as a measure to achieve the IMO’s GHG reduction targets. Full article

The power generation sector is a major contributor to global greenhouse gas (GHG) emissions and a significant consumer of freshwater, due to the extensive water use in cooling processes of thermoelectric power plants. While net-zero strategies increasingly focus on eliminating emissions to mitigate climate change, the critical role of water as a key sustainability resource remains underexplored and often underrepresented in mitigation scenarios, strategies, and policy frameworks. This study examines the impact of power sector decarbonization on global and regional electricity-related water demand under two climate ambition scenarios: continuation of current climate policies (CP) and a net-zero emission (NZ) scenario where countries implement their net-zero pledges by 2050 or later. Using the PROMETHEUS energy system model, we quantify how different climate ambitions could affect global and regional water demand, considering different levels of cooling technology evolution. Results show that water demand is not only driven by how much energy is produced but by the technology mix used to generate electricity. The findings highlight the significant co-benefits of power sector decarbonization for reducing water needs and ensuring freshwater resource sustainability, underscoring the importance of integrating water management into climate policy frameworks. This integrated perspective is critical for policymakers, energy system planners, and water resource managers aiming to balance ambitious climate goals with sustainable water use amid growing climate and resource challenges. Full article

Meeting the International Maritime Organization’s (IMO) 2050 targets for reducing greenhouse gas (GHG) emissions requires cost-effective solutions that minimize wind resistance without compromising safety, particularly for medium-sized multipurpose vessels (MPVs), which have been underrepresented in prior research. This study numerically evaluates 20 bow-mounted NaviScreen configurations using a coupled high-fidelity computational fluid dynamics (CFD) and finite element analysis (FEA) approach. Key design variables—including contact angle (35–50°), lower-edge height (1.2–2.0 m), and horn position (3.2–5.3 m)—were systematically varied. The sloped Type-15 shield reduced aerodynamic resistance by 17.1% in headwinds and 24.5% at a 30° yaw, lowering total hull resistance by up to 8.9%. Nonlinear FEA under combined dead weight, wind loads, and Korean Register (KR) green-water pressure revealed local buckling risks, which were mitigated by adding carling stiffeners and increasing plate thickness from 6 mm to 8 mm. The reinforced design satisfied KR yield limits, ABS buckling factors (>1.0), and NORSOK displacement criteria (L/100), confirming structural robustness. This dual-framework approach demonstrates the viability of NaviScreens as passive aerodynamic devices that enhance fuel efficiency and reduce GHG emissions, aligning with global efforts to address climate change by targeting not only CO2 but also other harmful emissions (e.g., NOx, SOx) regulated under MARPOL. The study delivers a validated CFD-FEA workflow to optimize performance and safety, offering shipbuilders a scalable solution for MPVs and related vessel classes to meet IMO’s GHG reduction goals. Full article

Methane (CH₄) is the second largest greenhouse gas (GHG) after carbon dioxide (CO₂), and ruminant production is an important source of CH₄ emissions. Among the six types of livestock animal species that produce GHGs, cattle (including beef cattle and dairy cows) are responsible for 62% of livestock-produced GHGs. Compared to beef cattle, continuous lactation in dairy cows requires sustained energy intake to drive rumen fermentation and CH₄ production, making it a key mitigation target for balancing dairy production and environmental sustainability. Determining how to safely and efficiently reduce CH₄ emissions from dairy cows is essential to promote the sustainable development of animal husbandry and environmental friendliness and plays an important role in improving feed conversion, reducing environmental pollution, and improving the performance of dairy cows. Combined with the factors influencing CH₄ emissions from dairy cows and previous research reports, this paper reviews the research progress on reducing the enteric CH₄ emissions (EMEs) of dairy cows from the perspectives of the CH₄ generation mechanism and emission reduction strategies, and it summarizes various measures for CH₄ emission reduction in dairy cows, mainly including accelerating genetic breeding, improving diet composition, optimizing feeding management, and improving fecal treatment. Future research should focus on optimizing the combination of strategies, explore more innovative methods, reduce EME without affecting the growth performance of dairy cows and milk safety, and scientifically and effectively promote the sustainable development of animal husbandry. Full article

Forest soil greenhouse gas emissions play a critical role in global climate change. This review synthesizes the mechanisms of temperature change impacts on forest soil greenhouse gas (CO₂, CH₄, N₂O) emissions, the complex response patterns of ecosystems, and existing knowledge gaps in current research. We highlight several critical mechanisms, such as the high temperature sensitivity (Q₁₀) of methane (CH₄) and CO₂ emissions from high-latitude peatlands, and the dual effect of chronic nitrogen deposition, which can cause short-term stimulation but long-term suppression of soil CO₂ emissions. It emphasizes how climatic factors, soil characteristics, vegetation types, and anthropogenic disturbances (such as forest management and fire) regulate emission processes through multi-scale interactions. This review further summarizes the advancements and limitations of current research methodologies and points out future research directions. These include strengthening long-term multi-factor experiments, developing high-precision models that integrate microbial functional genomics and isotope tracing techniques, and exploring innovative emission reduction strategies. Ultimately, this synthesis aims to provide a scientific basis and key ecological threshold references for developing climate-resilient sustainable forest management practices and effective climate change mitigation policies. Full article

The escalating climate crisis and unsustainable waste management practices necessitate integrated approaches that simultaneously address energy security and environmental degradation. Hydrogen, with its high energy density and zero-carbon combustion, is a key vector for decarbonization; however, conventional production methods are fossil-dependent and carbon-intensive. This systematic review explores biowaste-to-hydrogen (WtH) technologies as dual-purpose solutions, converting organic waste to clean hydrogen while reducing greenhouse gas emissions and landfill reliance. A comprehensive analysis of different conversion pathways, including thermochemical (gasification, pyrolysis, hydrothermal, and partial oxidation (POX)), biochemical (dark fermentation, photofermentation, and sequential fermentation), and electrochemical methods (MECs), is presented, assessing their hydrogen yields, feedstock compatibilities, environmental impacts, and technological readiness. Systematic literature review methods were employed using databases, such as Scopus and Web of Science, with strict inclusion criteria focused on recent peer-reviewed studies. This review highlights hydrothermal gasification and dark fermentation as particularly promising for wet biowaste streams, like food waste. Comparative environmental analyses reveal that bio-based hydrogen pathways offer significantly lower greenhouse gas emissions, energy use, and pollutant outputs than conventional methods. Future research directions emphasize process integration, catalyst development, and lifecycle assessment. The findings aim to inform technology selection, policymaking, and strategic investment in circular, low-carbon hydrogen production. Full article

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’s construction sector. The suggested methodology utilizes BIM for dynamic energy simulations and design visualization, PMBOK for integrating sustainability into project-management processes, and ML for predictive modeling and real-time energy optimization. Implementing an integrated model that incorporates building-management strategies and machine learning for both commercial and residential structures can offer stakeholders a thorough solution for forecasting energy performance and environmental impact. This is particularly essential in arid climates owing to specific conditions and environmental limitations. Using a simulation-based methodology, the framework was evaluated based on two representative case studies: (i) a commercial complex and (ii) a residential building. The neural network (NN), reinforcement learning (RL), and decision tree (DT) were implemented to assess performance in energy prediction and optimization. Results demonstrated notable seasonal energy savings, particularly in spring (15% reduction for commercial buildings) and fall (13% reduction for residential buildings), driven by optimized heating, ventilation, and air conditioning (HVAC) systems, insulation strategies, and window configurations. ML models successfully predicted energy consumption and greenhouse gas (GHG) emissions, enabling targeted mitigation strategies. GHG emissions were reduced by up to 25% in commercial and 20% in residential settings. Among the models, NN achieved the highest predictive accuracy (R² = 0.95), while RL proved effective in adaptive operational control. This study highlights the synergistic potential of BIM, PMBOK, and ML in advancing green project management and sustainable construction. Full article

Autonomous public transport (APT) is revolutionizing urban mobility by integrating advanced technologies, including electric autonomous buses and shared autonomous vehicles (SAVs). This paper examines the historical evolution of APT, from early automation efforts in the 1920s to the deployment of autonomous shuttles in contemporary cities. It highlights technological milestones, legislative developments, and shifts in public perception that have influenced the adoption of APT. The research identifies key benefits of APT, including enhanced road safety, reduced greenhouse gas emissions, and improved cost-efficiency in public transport operations. Additionally, the environmental potential of SAVs to reduce traffic congestion and emissions is explored, particularly when integrated with renewable energy sources and sustainable urban planning. However, the study also addresses significant challenges, such as handling emergencies without human intervention, rising cybersecurity threats, and employment displacement in the transportation sector. Social equity concerns are also discussed, especially regarding access and the risk of increasing urban inequality. This paper contributes to the broader discourse on sustainable mobility, transportation innovation, and the future of smart cities by providing a comprehensive analysis of both opportunities and obstacles. Effective policy frameworks and inclusive planning are essential for the successful implementation of APT systems worldwide. Full article

Soils act as sources or sinks for three major greenhouse gases (CO₂, CH₄, and N₂O). Approximately 20% of global CO₂ emissions are released from soils through the soil respiration process. Soil respiration (soil CO₂ emission) can account for over 85% of ecosystem respiration. The aim of this study was to compare managed and unmanaged stands of pedunculate oak (Quercus robur L.) in order to investigate the impact of forest management on soil CO₂ emissions. We selected one managed and two unmanaged stands. The first stand (S1) represents a managed middle-aged stand, which is the optimal stage of development. The second stand (S2) belongs to the over-mature stage of development in an old-growth oak forest, while the third stand (S3) belongs to the decay stage of development in an old-growth oak forest. The closed chambers method was used for air sampling and the air samples were analyzed using gas chromatography (GC). Multiple regression models that include soil temperature (ST), soil moisture (SM), and their interaction provide a better explanation for variation in soil CO₂ emission (SCDE) (higher R² values) compared to regression models that only involve two variables (ST and SM). The study showed that SCDE in the decay stage of old-growth forest (S3) was significantly lower (p < 0.001) compared to the other two stands (S1 and S2). S3 is characterized by very low canopy cover and intensive natural regeneration, unlike S1 and S2. However, there were no significant differences in SCDE between the managed middle-aged stand (S1) and the over-mature (old-growth) stand (S2). Over a long-term rotation period in pedunculate oak forests, forest management practices that involve the periodic implementation of moderate silvicultural interventions can be deemed acceptable in terms of maintaining the carbon balance in the soil. Full article

Optimizing aeration, fertilization, and irrigation is vital for improving greenhouse tomato production while mitigating soil greenhouse gas (GHG) emissions. This study investigated the combined effects of three aeration levels (A1: single Venturi, A2: double Venturi, CK: no aeration), two fertilization rates (F1: 180 kg/ha, F2: 240 kg/ha), and two irrigation levels (I1: 0.8 E_pan, I2: 1.0 E_pan) on tomato yield, CO₂, N₂O, and CH₄ emissions, net GHG emissions, net global warming potential (NGWP), and GHG intensity (GHGI) across Spring–Summer and Autumn–Winter seasons. Results showed that aeration and fertilization significantly increased CO₂ and N₂O emissions but reduced CH₄ emissions. Warmer conditions in Spring–Summer elevated all GHG emissions and yield compared to Autumn–Winter seasons. Tomato yield, net GHG emissions, NGWP, and GHGI were 12.05%, 24.3%, 14.46%, and 2.37% higher, respectively, in Spring–Summer. Combining the Maximal Information Coefficient and TOPSIS models, the optimal practice was A1-F1-I1 in Spring–Summer and A2-F1-I1 in Autumn–Winter seasons. These results provide a theoretical basis for selecting climate-smart management strategies that enhance yield and environmental sustainability in greenhouse tomato systems. Full article

For sustainable livestock manure management, composting is a common practice for supplying nutrients to crops. Therefore, optimizing plant locations for composting from livestock manure is essential in Bangladesh. This study performed a land suitability analysis using Geographic Information System (GIS) spatial modeling to identify suitable sites for composting plants, which was optimized through network analysis. After spatial analysis, 15, 42, and 147 locations were identified for large-scale, medium-scale, and small-scale manure-based compost production, respectively, across different scenarios. As a result, approximately 1537.74 kilotons/year of compost can be generated from 2703.86 kilotons of livestock manure, replacing about 44.31% of synthetic fertilizer use in Bangladesh in 2024. The potential reduction in greenhouse gas (GHG) emissions was assessed at 1986.76 gigagrams CO_2eq/year, with nutrient leaching reduction potentials of 15.11 and 10.98 kilotons/year for nitrogen and phosphorus, respectively. Additionally, around 4.51 million tons of livestock manure can be disposed of annually by establishing composting plants. However, assessing the potential environmental benefits by optimizing composting plant locations can support the development of strategies to produce organic fertilizer by utilizing natural resources in Bangladesh. Full article

With increasing wastewater treatment demands and decarbonization goals, synergistic reduction in pollutants and green house gas (GHG) emissions is crucial. High process emissions like N₂O pose significant challenges, yet optimized carbon reduction strategies for conventional plants are lacking. This study developed three mathematical models to quantify the impact of dissolved oxygen (DO), influent salinity, and C/N ratio on direct emissions (CH₄, N₂O) and indirect emissions. Response Surface Methodology (RSM) optimized these factors to minimize GHG emissions under three accounting scenarios: (1) plants with CH₄ reuse systems: salinity = 0.5 g L⁻¹, DO = 3.67 mg L⁻¹, C/N = 12.75; (2) plants focusing solely on direct emissions: salinity = 0.5 g L⁻¹, DO = 3.35 mg L⁻¹, C/N = 3; and (3) plants assessing total emissions: salinity = 0.5 g L⁻¹, DO = 2.5 mg L⁻¹, C/N = 7.18. Key findings indicated that increasing salinity exacerbated greenhouse gas emissions. Elevated DO levels in the aerobic stage reduced N₂O emissions but increased indirect emissions in the A²/O process. Higher C/N ratios promoted anaerobic CH₄ production, but sufficient carbon reduced N₂O by enabling complete heterotrophic denitrification. A 60−day continuous GHG emissions monitoring campaign was conducted at a WWTP to validate the actual emission reductions achievable under the identified optimal control conditions. An analysis and comparison of operational and economic costs were also performed. The findings provide practical insights into sustainable GHG emission management and offer potential solutions to advance the synergistic reduction in GHG emissions and pollutants. Full article