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

Electric vehicles (EVs) emit substantially fewer air pollutants than conventional internal combustion engine vehicles. However, the continuous increase in electricity demand from the power grid for EV charging, resulting from the growing adoption and total vehicle miles traveled, leads to higher greenhouse gas emissions from the power sector. This study presents a predictive analysis of energy sector greenhouse gas emissions from EV charging at the regional level across the United States under various projection scenarios of technology costs, fuel prices, demand growth, and electricity sector policies. The predictive modeling of greenhouse gas emissions from EV charging is performed using a machine learning model developed on the Meta Prophet platform designed to capture temporal patterns and seasonality with a high level of precision. Trained on simulation data from the Cambium model, developed by the National Renewable Energy Laboratory (NREL), our model provides accurate and continuous predictions of CO2, N2O, and CH4 emission rates from EV charging through 2050 under eight power generation planning scenarios, each outlining different projections for costs, prices, demand, and policy outcomes. Our analysis suggests that, by 2030, total grid emissions of CO2, N2O, and CH4 from EV battery charging in the United States are projected to decline by 52.67%, 65.71%, and 53.65%, respectively, compared to 2025 under the mid-case scenario, despite an overall increase of 152.57% in EV electricity demand. By 2050, emissions are expected to decline further by 80.13%, 94.15%, and 75.62%, respectively, with total EV electricity demand rising by 802.02%. Our scenario analysis results underscore the pivotal role of regional energy mixes and the pace of renewable energy deployment in decarbonizing transportation through electrification, highlighting the urgent need for proactive policy measures to accelerate the adoption of clean and renewable energy technologies in order to meet long-term climate targets.

Abstract Metal Additive Manufacturing (MAM) enables resource efficient production however poses sustainability challenges due to high energy demand and inert gas usage. This study experimentally quantifies subsystem-level energy consumption and greenhouse gas emissions during Directed Energy Deposition with laser and powder feed (DED-LB/p) using Inconel 718. Real-time power measurements were conducted on a 3-axis gantry DED system to characterize the operational profiles of the fiber laser, motion control system, powder-gas feeder, and the cooling unit under idle and active states. Argon consumption was also quantified, and all data were integrated into a cradle-to-gate Life Cycle Inventory (LCI) framework. Findings show that the fiber laser operation is the dominant contributor to process energy, while argon emissions contribute only marginally to the environmental footprint when powered by renewable electricity mix. Additionally, build strategy particularly layer count and interpass idle duration strongly influences overall efficiency. The sustainability impact is primarily driven by the embodied energy of powder production, with recycled powder yielding significant reductions in both energy demand and CO2-equivalent emissions. This study provides new experimental insight into subsystem-level contributions within DED-LB/p and identifies process optimization and recycled powder utilisation as strategies for advancing energy and resource efficient metal additive manufacturing.

This study presents a cradle-to-grave lifecycle analysis of energy use and greenhouse gas (GHG) emissions for U.S. medium- and heavy-duty vehicles across current (2021) and future (2035) technologies using the Greenhouse gas, Regulated Emissions, and Energy use in Technologies (GREET) model with industry-vetted assumptions. Results vary across vehicle classes but point to common trends: today, battery electric vehicles (BEVs) offer significant (10-60%) GHG emissions reduction compared to diesel internal combustion engine vehicles and are the lowest emissions option per ton-mile of cargo movement, followed by hydrogen fuel cell electric vehicles (FCEVs) (5-50% emissions reduction). Emissions savings depend largely on the duty cycle and fuel economy of the vehicle type. Future vehicle technology advancements result in comparable emission reductions associated with BEVs and hydrogen FCEVs. Weight-limited BEV trucks see less per-ton-mile emissions reduction due to the impact of battery weight on increased vehicle weight and reduced payload capacity. By 2035, improvements in vehicle efficiency can reduce emissions across all powertrains. However, very low levels of emissions require switching vehicles' use-phase fuel/energy to low-carbon fuels and electricity. Renewable diesel, e-fuels, hydrogen produced from natural gas with carbon capture and storage or renewables, and use of low-carbon electricity can all achieve over 70% reduction in GHG emissions from the current day diesel-based internal combustion engine vehicle.

Residual feed intake (RFI) is a metric to identify high feed efficient (negative RFI; -RFI) and low feed efficient (positive RFI; +RFI) animals within and across cohorts. The objective of this study was to quantify and determine potential differences between the most RFI divergent cows in (1) metabolites, hormones, and fatty acids in tail vessel and mammary vein blood; (2) hepatic gene expression; (3) CH4, CO2, O2, and related metrics; and (4) hepatic mitochondrial function. Mid-lactation Holstein dairy cows (n = 64/trial) were enrolled in two 8-wk trials to quantify intake, BW, and milk production. The top and bottom 25% (n = 64; analyzed for all variables) and the most divergent 15% (n = 19; additional analysis of gene expression, mitochondrial function, and gas emissions and consumption) RFI subgroups were analyzed across the trials. Milk yield and milk energy output were similar, but milk lactose percentage was greater and MUN and SCS was lower in -RFI cows than +RFI cows. Tail vessel concentrations of C16:0, C16:1 cis, C17:0, C18:0, and C22:0 were (or tended to be) greater, and mammary vein C16:1 cis and C18:1 cis were greater in -RFI cows than +RFI cows. Mammary vein BUN was lower and tail vessel insulin concentration tended to be greater in -RFI cows than +RFI cows. Expression of uncoupling, mitochondrial, or tricarboxylic acid cycle genes were similar across RFI status. Mitochondrial complex IV, when quantified with complex I substrate, had lower oxygen consumption rates in -RFI cows than +RFI cows. Emissions of CH4 and overall CO2 were lower in -RFI cows than +RFI cows. Overall, mitochondrial function and nutrient partitioning differed in dairy cows of divergent RFI status, although differences did not appear to be due to changes in hepatic gene expression.

Combustion and emission characteristics of premixed coke oven gas-ammonia swirling flames

Abstract Mortar foam work is one of the contributors to global climate change that affects various aspects of life, including infrastructure development. Bridge construction contributes significant carbon emissions due to the use of heavy materials and high energy consumption during production and construction processes. The city of Yogyakarta, as an area with ever-increasing development activities, also faces challenges in effectively managing carbon emissions. The Life Cycle Assessment (LCA) method is an important approach to comprehensively measure and analyse the environmental impact throughout the life cycle of materials and construction processes. This study shows that large-scale mortar form, namely Unconfined Compression Strength (UCS) 800 KPa with volume 58,606 m 3 and UCS 2000 KPa with volume 15,662 m 3 , produces a total carbon emission impact from global warning amounting to 2.87E8 Kg CO 2 eq. The LCA analysis was conducted comprehensively, from raw material production and transportation to the construction process, using SimaPro 2016 Midpoint (H) software. The study results show that the process unit with the highest carbon emissions is the delivery of mortar foam material to the spreading location, with carbon emissions of 59,408.73 Kg CO 2 eq. Both conventional and non-conventional production processes also contribute significantly to environmental impacts. The five highest impacts identified are global warning, fossil resource scarcity, human non-carcinogenic toxicity, terrestrial ecotoxicity, and ozone formation, terrestrial ecosystem. This study recommends placing modular batching closer to the mortar foam material spreading site, which can also support a carbon footprint reduction of up to 1.52E8 Kg CO 2 eq or equivalent to a potential impact reduction of 54.29% at the mortar foam unit work scale, and encourage more sustainable infrastructure development.

Methane emissions from underground coal mines are a significant source of greenhouse gases (GHGs) and a major safety concern. In highly methane-prone operations, a large proportion of emissions comes from low-content abandoned mine methane (LCAMM) accumulated in post-mining goafs, where concentrations usually stay below 30% CH4. Building on the Research Fund for Coal and Steel (RFCS) REM project, this paper presents a cost–benefit analysis of a comprehensive scheme for capturing, transporting, and utilising LCAMM from post-mining goafs for electricity generation. The concept involves long-reach directional boreholes drilled behind isolation dams, a dedicated methane-reduced drainage system connected to a surface methane drainage station, and four 2 MWe gas engines designed to run on a 20–40% CH4 mixture. Greenhouse gas performance is evaluated by comparing a “business-as-usual” scenario in which post-mining methane is combusted in gas engines to produce electricity without further GHG cost–benefit consideration. The results indicate that the project can achieve a positive net present value, highlighting the role of LCAMM utilisation for methane-intensive coal mines. The paper also explores the monetisation of non-emitted methane using the European Union Emissions Trading System (EU ETS), as well as social cost benchmarks and penalty levels consistent with the emerging EU Methane Emissions Regulation (EU MER).

Environmental, Economic, Greenhouse Gas Emission and Energy Balance Analysis of Open-Field Strawberry Production under Highland Conditions in Türkiye

Life-cycle greenhouse gas emissions analysis of battery-grade lithium production in Finland

This study addresses a critical gap in climate governance literature by investigating the empirical relationship between public climate finance and environmental outcomes in Nepal, a country highly vulnerable to climate change despite its minimal historical emissions. Using a correlational research design with a one-year lag, we analyze ten years of national data (2014-2023) to determine whether Nepal’s total climate-relevant budget (TCB) and its environment-sector share (ESB) are associated with changes in per-capita greenhouse gas emissions. Our analysis reveals a paradox: a very strong positive correlation between the rapidly expanding TCB and rising emissions, whereas a greater ESB shows a negative, though statistically weaker, association. The findings indicate that the scale of spending alone is an inadequate strategy for mitigation; instead, effectiveness is contingent upon strategic budget composition, prioritizing interventions with verifiable abatement potential, and overcoming systemic implementation bottlenecks. The primary implication for policy and practice is the necessity of a decisive pivot from quantitative expansion to qualitative targeting, establishing a mitigation-sensitive budgeting framework that directly links allocations to measurable emissions reductions through enhanced delivery systems and verification.

At present, urban greenhouse gas (GHG) emissions from different wastewater treatment stages are attracting increasing attention. Based on the Guidelines of the China Greenhouse Gas List Compilation (Trial) and the IPCC National Greenhouse Gas List Guidelines in 2006, this paper evaluated urban GHG emissions from wastewater treatment in China from 2011 to 2020. The contribution rates of GHG emissions to the total GHG emissions were calculated for the different wastewater treatment stages. The variations in annual GHG emissions and differences in GHG emissions among different regions and provinces were also analyzed. The total amount of equivalent CO2 emissions reaches 1478.51 million tons, and the annual average amount of equivalent CO2 emissions from 2011 to 2020 is 147.9 million tons, which shows a trend of decreasing first and then increasing. The distribution of GHG emissions from wastewater treatment is uneven among provinces and regions; Guangdong Province has the highest emission, while the Xizang autonomous Region has the lowest. The correlation and contribution rate analysis revealed that paper production and chemical and side food production could discharge a large amount of wastewater with a high COD content, which may have an important impact on GHG emissions during the wastewater treatment stages. According to the study results, CH4 accounts for the largest proportion (63.08%) of the total GHG emissions. The most important source of CH4 comes from the industrial wastewater treatment stage. The annual average CO2 emissions account for 22.24% of the total GHG emissions, which are mainly from the power and chemical consumption stage. The annual average N2O emissions account for 14.68% of the total GHG emissions and are mainly from the wastewater collection and discharge stage. Therefore, in the future, GHG emission reduction strategies should focus on CH4 emissions in the industrial wastewater treatment stage and develop CH4 recycling and utilization technologies.

The aim of this study was to assess the energy potential of woody grapevine (Vitis vinifera L.) shoots depending on the cultivation system, cultivar, and fruit colour. Field studies were conducted in 2024 at the Mendel University Vineyard in Lednice (Czech Republic) on Chardonnay, Merlot, Riesling, and Zweigelt cultivars, cultivated using the Guyot and Cordon systems. The cultivar analysis covered both the amount of biomass produced during pruning and its energy and emission properties. Laboratory tests of the energy potential of the biomass obtained were carried out at the University of Life Sciences in Lublin. The results showed that the varietal factor significantly influenced the biomass parameters—Chardonnay was characterised by the highest total plant weight (773.57 g), while Zweigelt (8.60 pcs.) had the highest number of shoots with the lowest unit weight (74.82 g). The Cordon system generated significantly higher biomass yields and more favourable combustion properties compared to Guyot. Differences in fruit colour indicate that, among the studied cultivars, white-berried varieties produce heavier shoots, whereas red varieties produce a greater number of shoots. The analysis of gas emissions showed a significant influence of the cultivar and training system, with the highest CO, CO2, and NOx emissions recorded for the Zweigelt cultivar. The results emphasise that an integrated approach, taking into account both genotypic factors, training systems and phenotypic characteristics of the vines, is crucial for optimising the use of wine biomass as an energy source in the context of a circular economy.

Comparative analysis of greenhouse gas emissions and energy consumption of composite cold-mixed asphalt mixture based on life cycle assessment

This study provides a comprehensive analysis of greenhouse gas (GHG) emissions in free surface constructed wetlands (FSCWs) by combining qualitative insights from literature with machine learning-based quantitative analysis. Key factors influencing CO₂, CH₄, and N₂O emissions were identified, with a focus on the effects of seasonal variation, vegetation, substrate, and influent characteristics. The qualitative review highlights vegetation and substrate as critical drivers, noting that specific plant traits, such as root oxygenation, significantly impact methane dynamics. Influents with high nutrient loads, such as agricultural runoff and municipal wastewater, were found to increase GHG emissions, underscoring the importance of influent composition in emissions management. The machine learning analysis, using tree-based models (Random Forest, Gradient Boosting, CatBoost, and XGBoost), further quantified variable importance, revealing that presence of vegetation and All Sky Surface Shortwave Downward Irradiance (SW DNI) are primary drivers for CO₂ and CH₄ emissions, while the age of the Wetland is an important determining factor for N₂O emissions due to its impact on nitrogen cycling. Earth skin temperature, the thermal metric used in this study, showed low importance. This may reflect the fact that SW DNI better captures surface energy inputs that influence microbial activity, or that different thermal variables, such as air temperature, are more relevant in other contexts. These findings emphasize the need for targeted management strategies to optimize GHG mitigation in FSCWs, supporting sustainable wetland design that balances wastewater treatment with climate mitigation goals.

Route-based time-dependent life cycle greenhouse gas and NOₓ emissions analysis of heavy-duty trucks

Deploying small vertical axis wind turbines on urban rooftops — A parametric, dynamic, and hybrid life cycle energy and greenhouse gas emissions analysis

Concrete blocks are widely used for wall construction in Thailand, and reliable Carbon Footprint of Product (CFP) data for these blocks is essential for accurately estimating the embodied carbon of buildings—a crucial consideration in sustainable building design. This research evaluates the CFP of concrete blocks produced by a Thai factory, using a functional unit of one ton. The assessment applies a "Cradle to Gate" approach, covering both raw material acquisition and product manufacturing stages. The study period spans one year, from January 1, 2023, to December 31, 2023. Results show that the CFP for the case study block is 88.508 kgCO₂eq/t, with the raw material acquisition stage responsible for 84.778 kgCO₂eq/t (95.79% of the CFP), and production stage emissions at 3.730 kgCO₂eq/t (4.21% of the CFP). A detailed analysis of greenhouse gas (GHG) emissions reveals several key findings: (1) Portland cement is the primary source, accounting for 80.69% of the CFP; (2) emissions from the transportation of crushed stone and coarse sand are notably high; (3) electricity usage contributes 2.558 kgCO₂eq/t; and (4) broken concrete blocks constitute 12.93% of the mixture volume. This study not only addresses a critical gap in the availability of CFP data for concrete blocks in sustainable building analysis in Thailand, but also identifies key areas where GHG emissions associated with concrete block manufacturing can be reduced. The insights provided here are valuable for concrete block manufacturers across Thailand, especially those with similar production processes, as they work toward lowering the CFP of their products.

Livestock constitutes an integral component of Indian agriculture sector and also a major source of Greenhouse Gas Emissions(GHG) emissions. The study uses both secondary and primary data for estimating GHG emissions from livestock in India and also Telangana. The study presents spatial and temporal variations in GHG emissions from different age-groups, different Breeds, different censuses starting from 2003 to 2019 based on IPCC guidelines. The study mainly focus on estimating the carbon footprints of milk by applying Cool Farm Tool(CFT) in dairy setup especially in Telangana. The total GHGs emission from Indian livestock in 2019 is estimated at 281.23 Mt in terms of CO2 equivalent emissions. Although the Indian livestock contributes substantially to the methane budget, the per capita emission is only 24.89 kgCH4/animal/year. Top 10 states account for 75.47 % of missions from India. Telangana accounted for 3.46% of missions from India with a total of 9.73 Mt in 2019. Village level study indicated that per farm emissions were 173.56 kg CO2 equiv. per year and it is 3.91 kg CO2 per kg FPCM of buffalo milk produced. Co2 per kg FPCM is more in cow milk compared to buffalo milk due to inefficiency management practices resulting in low milk yield. Though the livestock is cause and sufferer of methane and GHG emissions, reducing animal numbers as a part of mitigation strategy will affect the food and nutritional security of people. Instead of reducing livestock numbers, mitigation strategies should aim at management practices like feeding, manure management, using methane reducing chemicals and also inventing new methods to converting methane to useful products which will help in achieving SDG goals relevant to livestock. Reducing greenhouse gas emissions will not only address. The findings can inform policymakers and researchers in developing sustainable practices and strategies for emission reduction in the livestock sector to achieve SDG goals.

This paper investigated the life cycle energy and Greenhouse gas (GHG) emission analysis of a direct air carbon capture (DACC) system. The cradle-to-grave life cycle approach has been adopted in the inventory stages. The life cycle stages namely extraction of the raw materials (Fe, Si, etc.), manufacturing of the component materials (stainless steel, mild steel, etc.), construction of the system, operation, disassembly, and disposal are considered for the analysis. The data were collected from the local industry through field surveys and available literature. Local and international transportation were considered. The result showed that the total life cycle energy consumption and CO2 emission found are 4,368 MJ and 428 kg respectively. The extraction causes the major energy consumption and GHG emissions throughout the life cycle. The SOx and NOx emissions are the dominant other GHG gases in the life cycle stages. Energy consumption and GHG emissions can be reduced by adopting recycling and reusing materials rather than importing from international sources.