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Landfills emissions, ranking as the third‐largest anthropogenic source of methane in the atmosphere, pose environmental challenges and threaten public health. The pivotal role of clay as a mitigating agent for methane emission within landfill cover systems cannot be overstated; however, our understanding of methane escape from fractured clay remains limited. This study aims to address the existing gaps by proposing a robust analytical model of methane transport in both fractures and clay matrix. Our investigation also includes a dimensionless analysis to govern the relative significance of diffusion and advection in methane emission from fractured clay, systematically reviewing factors such as the degree of water saturation (Sr) and fracture width. The methane concentration profiles in cracked clay demonstrated escalating sensitivity to Péclet (Pe) numbers, especially when advection dominates transport. Our findings also highlight the prevalence of preferential methane flow with increasing Sr in the clay matrix. The flux of methane emission from fractures at Sr = 0.8 was 130 times greater than that from intact clay. However, the study necessitates considering methane emission from clay matrix, particularly in dry clay conditions (Sr = 0.2 and 0.4). The accumulated methane emission flux from intact clay, more than that emitted from fractures by about 2.5 times at Sr = 0.2, was 1.3 × 10−5 g/m/s. The findings significantly advance the understanding of gas transport in fractured geomaterials, revealing the effect of water saturation and crack width on methane emissions from fractures. Overall, the outcomes emphasize the inclusion importance of methane emission from cracked clay in the design of gas barriers. [ABSTRACT FROM AUTHOR]

Simple Summary: Enteric methane (CH4) production in cattle accounts for a significant portion of global greenhouse gas emissions. Measurement of enteric methane emission is complex, expensive, and large-scale measurement is impractical. Therefore, in the absence of measurements, modeling can be used to predict CH4 production and help investigate mitigation options. In this study, we used dietary nutrient composition (g/kg), nutrients (kg/day), energy (MJ/day), and energy and organic matter (OM) digestibility (g/kg) as predictors of CH4 production to develop linear and nonlinear statistical models for predicting enteric methane emission from beef and dairy cattle and to evaluate the few available models. The objective of this study was to develop linear and nonlinear statistical models for predicting enteric methane emissions from beef and dairy cattle (EME, MJ/day). Ration nutrient composition (g/kg), nutrient (kg/day), energy (MJ/day), and energy and organic matter (OM) digestibility (g/kg) were used as predictors of CH4 production. Three databases of beef cattle, dairy cattle, and their combinations were developed using 34 published experiments to model EME predictions. Linear and nonlinear regression models were developed using a mixed-model approach to predict CH4 production (MJ/day) of individual animals based on feed composition. For the beef cattle database, Equation methane (MJ/d) = 1.6063 (±0.757) + 0.4256 (±0.0745) × DMI + 1.2213 (±0.1715) × NDFI + −0.475 (±0.446) × ADFI had the smallest RMSPE (21.99%), with 83.51% of this coming from random error and a regression bias was 16.49%. For the dairy cattle database, the RMSPE was minimized (15.99%) for methane (MJ/d) = 0.3989 (±1.1073) + 0.8685 (±0.1585) × DMI + 0.6675 (±0.4264) × NDFI, of which 85.11% was from random error and the regression deviation was 14.89%. When the beef and dairy cattle databases were combined, the RMSPE was minimized (24.4%) for methane(MJ/d) = −0.3496 (±0.723) + 0.5941 (±0.0851) × DMI + 1.388 (±0.2203) × NDFI + −0.027 (±0.4223) × ADFI, of which 85.62% was from the random error and the regression bias was 14.38%. Among the nonlinear equations for the three databases, the DMI-based exponential model outperformed the other nonlinear models, but the predictability and goodness of fit of the equations did not improve compared to the linear model. The existing equations overestimate CH4 production with low accuracy and precision. Therefore, the equations developed in this study improve the preparation of methane inventories and thus improve the estimation of methane production in beef and dairy cattle. [ABSTRACT FROM AUTHOR]

Wastewater treatment (WWT) contributes 2–9% of global greenhouse gas (GHG) emissions. The noticeable uncertainty in emissions estimation is due in large part to the lack of measurement data. Several methods have recently been developed for monitoring fugitive GHG emissions from WWT. However, limited by the short duration of the monitoring, only "snapshot" data can be obtained, necessitating extrapolation of the limited data for estimating annual emissions. Extrapolation introduces substantial errors, as it fails to account for the spatial and temporal variations of fugitive emissions. This research evaluated the feasibility of studying the long-term CH4 emissions from WWT by analyzing high spatial resolution Sentinel-2 data. Satellite images of a WWT plant in Calgary, Canada, taken between 2019 and 2023, were processed to retrieve CH4 column concentration distributions. Digital image processing techniques were developed and used for extracting the time- and space-varying features of CH4 emissions, which revealed daily, monthly, seasonal, and annual variations. Emission hotspots were also identified and corroborated with ground-based measurements. Despite limitations due to atmospheric scattering, cloud cover, and sensor resolution, which affect precise ground-level concentration assessments, the findings reveal the dynamic nature of fugitive GHG emissions from WWT, indicating the need for continuous monitoring. The results also show the potential of utilizing satellite images for cost-effectively evaluating fugitive CH4 emissions. [ABSTRACT FROM AUTHOR]

The study of the effect of the mechanism of urea addition to sewage sludge and sawdust-composting substrates on methane production is still limited. In the present study, the systematic investigation of the effect of urea addition (0.18, 0.9 and 1.8 kg) on methane production is discussed through the dynamics of physical properties, enzymes, and the microbial community during composting. The results showed that high urea addition (1.8 kg) suppressed methane production, with a lower rate and a shorter duration of warming in the thermophilic phase, but significantly enhanced cellulase activity, urease, and peroxidase, and promoted the degradation of organic carbon, as well as the loss of nitrogen. A high addition of urea stimulated the growth and reproduction of Sinibacillus, Pseudogracilibacillus, Sporosarcina, and Oceanobacillus. The random forest model indicated that the top six independent determinants of CH4 emissions were Methanobacterium, temperature, organic matter (OM), Methanospirillum, and NH4+-N. Furthermore, structural equation modeling displayed that NH4+-N, O2, and pH were the main physicochemical properties affecting CH4 emissions. Methanobacterium, Methanosarcina, and Methanosphaera were the main archaea, and Bacillaceae were the main bacteria affecting CH4 emissions. This study provides new insights and a theoretical basis for optimizing urea addition strategies during composting. [ABSTRACT FROM AUTHOR]

This study aimed to improve the nutritional value of Sargassum horneri (SH) and evaluate its effect on rumen fermentation characteristics and greenhouse gas emissions. The first trial estimated the effects of blanching temperatures (21, 60, 70, and 80 °C) and durations (1, 2, and 3 min) on the chemical and mineral content of SH. The second trial evaluated the effects of SH supplementation levels (0, 1, 3, and 5%) and blanching temperatures (21 and 70 °C) on in vitro rumen fermentation characteristics and greenhouse gas emissions. As the blanching temperature and time increased, the dry matter and crude ash content decreased (p < 0.05), and the ether extract, neutral detergent fiber, and acid detergent fiber content increased (p < 0.05). There were significant reductions in Na, K, and As (p < 0.01) when the blanching temperatures increased. As the SH supplementation levels increased, in vitro digestibility of both dry and organic matter decreased (p < 0.001) and the methane production reduced (p < 0.001). Therefore, this study shows that blanching SH at 70 °C for 3 min optimized its nutritional value and improved its potential as a feed source that has methane mitigation characteristics at 3 to 5% supplementation levels. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) and greenhouse gas (GHG) emissions are substantial contributors to C and N loss in composting. Lignite can increase N retention by absorbing ${\rm N}{\rm H}_4^ +$ N H 4 + and NH3. However, the effects of co-composting on NH3 and GHG emissions in view of closing nutrient cycle are still poorly investigated. In the study, poultry litter was composted without (CK) or with lignite (T1) or dewatered lignite (T2), and their respective composts ${\rm N}{\rm H}_4^ +$ N H 4 + Com_CK, Com_T1, and Com_T2) were tested in a soil incubation to assess NH3 and GHG emission during composting and following soil utilization. The cumulative NH3 flux in T1 and T2 were reduced by 39.3% and 50.2%, while N2O emissions were increased by 7.5 and 15.6 times, relative to CK. The total GHG emission in T2 was reduced by 16.8% compared to CK. Lignite addition significantly increased nitrification and denitrification as evidenced by the increased abundances of amoA, amoB, nirK, and nirS. The increased reduction on NH3 emission by dewatered lignite could be attributed to reduced pH and enhanced cation exchangeable capacity than lignite. The increased N2O was related to enhanced nitrification and denitrification. In the soil incubation experiment, compost addition reduced NH3 emission by 72%∼83% while increased emissions of CO2 and N2O by 306%∼740% and 208%∼454%, compared with urea. Com_T2 strongly reduced NH3 and GHG emissions after soil amendment compared to Com_CK. Overall, dewatered lignite, as an effective additive, exhibits great potential to simultaneously mitigate NH3 and GHG secondary pollution during composting and subsequent utilization of manure composts. [ABSTRACT FROM AUTHOR]

Simple Summary: Agricultural greenhouse gas emissions account for 14.5% of global anthropogenic emissions, with beef and dairy cattle contributing 35% and 30% of global livestock emissions, respectively. This study focuses on dairy cattle, exploring the relationships between rumen microbiota and methane emission. Using a laser methane detector (LMD), methane emissions from 968 lactating cows were measured, and 107 cows were selected for high and low emission groups. The results showed that the abundance of Bacteroidales and Prevotellaceae in the rumen of high methane-emitting cows was significantly higher than that in the low methane-emitting cows. Additionally, it was found that bacterial functions related to biosynthesis and carbohydrate metabolism were more active in the high methane-emitting cows. These findings provide new insights for developing strategies to reduce methane emissions, supporting the sustainable development of the dairy industry. Agricultural activities are a significant contributor to global greenhouse gas emissions, accounting for 14.5% of total anthropogenic emissions. Specifically, greenhouse gas emissions from beef cattle and dairy cattle constitute 35% and 30% of total global livestock emissions, respectively. This study focuses on dairy cattle, exploring the complex relationships between rumen microbiota and methane emission. The methane emissions of 968 lactating Holstein cows were measured using a laser methane detector (LMD, Shanghai Hesai Technology Co., Ltd., Shanghai, China). Among the measured cows, 107 individuals were further selected into high (HME) and low methane-emitting (LME) groups, including 50 cows in the HME group and 57 in the LME group. This study analyzed differences in rumen microbiota and microbial functions between cows with varying levels of methane emissions. The results showed significant differences in the Simpson and Pielou indices of rumen bacterial communities between the HME and LME groups. Beta diversity analysis revealed significant differences in microbial community structure between the two groups. It was found that the abundance of Bacteroidales and Prevotellaceae in the rumen of cows in the HME group cows was significantly higher than that of cows in the LME group (LDA > 3, p < 0.05). Additionally, bacterial functions related to biosynthesis and carbohydrate metabolism were more active in the HME group. This study revealed distinct differences in the rumen bacterial communities between HME and LME cow in Chinese Holstein cattle, and identified specific bacteria and their functional differences in the HME group. The microbial characteristics and metabolic pathways provide new insights for developing strategies to reduce methane emissions, supporting the sustainable development of the dairy industry. [ABSTRACT FROM AUTHOR]

Methane is the second most significant greenhouse gas after carbon dioxide. As global warming intensifies, the quantification of methane point sources is becoming increasingly crucial. However, retrieving high-quality methane signals from remote sensing data remains challenging due to various factors, including surface reflectance, atmospheric interference, sensor noise, wind speed, and sensor sensitivity. In real-world scenarios, methane remote sensing quantification often encounters unfavourable conditions that lead to low signal-to-noise ratio (SNR) signals, resulting in reduced quantification accuracy. To address these challenges, we introduce a novel multi-task learning-based approach. Specifically, we incorporate a denoising auxiliary task into the quantification network by introducing an additional denoising branch that recovers clean plume column concentration maps. The network is trained with supervision using both denoising and quantification losses, which enables it to acquire robust feature representations to noise and benefits the quantification of low SNR images. During the inference phase, the denoising branch is removed, resulting in an efficient and robust single quantification network with reduced inferring time, supporting onboard computation. We construct a low SNR database based on the AVIRIS-NG sensor and evaluate the generalization ability of our method. DQNet achieves the highest RMSE, MAPE, and R of 16.478 kg/h, 15.296%, and 95.167% respectively on the synthetic dataset. Across the entire range of SNR, DQNet exhibits a greater relative advantage as SNR decreases. However, our approach is not limited to AVIRIS-NG and can be easily extended to various multispectral and hyperspectral satellites. [ABSTRACT FROM AUTHOR]

Ventilation Air Methane (VAM) significantly contributes to global warming. Capturing and mitigating these emissions can help combat climate change. One effective method is the thermal decomposition of methane, but it requires careful control to prevent explosions from the high temperatures involved. This research investigates the influence of methane concentration and coal dust particle properties on the minimum ignition energy (MIE) required for fugitive methane thermal decomposition and flame propagation properties. This knowledge is crucial for the mining industry to effectively prevent and mitigate accidental fires and explosions in VAM abatement plants. Coal dust samples from three different sources were selected for this study. Experiments were conducted using a modified Hartmann glass tube and a Thermal Gravimetric Analyser (TGA). The chemical properties of coal dust were determined through ultimate and proximate analysis. The particle size distribution was determined using a Mastersizer 3000 apparatus (manufactured by Malvern Panalytical, Malvern, UK). The results showed that the MIE is significantly affected by coal dust particle size, with smaller particles (<74 µm) requiring less energy to ignite compared to coarser particles. Additionally, blending methane with coal dust further reduces the MIE. Introducing methane concentrations of 1% and 2.5% into the combustion space reduced the MIE by 25% and 74%, respectively, for the <74 µm coal dust size fraction. It was observed that coal dust concentration can either raise or lower the MIE. Larger coal dust concentrations, acting as a heat sink, reduce the likelihood of ignition and increase the MIE. This effect was noted at a methane concentration of 2.5% and coal dust levels above 3000 g/m3. In contrast, small amounts of coal dust had little impact on MIE variation. Moreover, the presence of methane during combustion increased the upward flame travel distance and propagation velocity. The flame's vertical travel distance increased from 124 mm to 300 mm for a coal dust concentration of 300 g·m−3 blended with 1% and 2.5% methane, respectively. [ABSTRACT FROM AUTHOR]

This study explores the relationship between greenhouse gases (GHGs) and particulate emissions and quality of life. The aim is to understand how emissions affect quality of life globally—across countries, regions, and the global population. Statistical methods were used to examine the impact of various emissions' indicators on different aspects of quality of life. The study highlights the urgent need for climate change action and encourages policymakers to take strategic steps. Climate change adversely affects numerous aspects of daily life, leading to significant consequences that must be addressed through policy changes and global governance recommendations. Key findings include that higher CO2 and methane emissions and air pollution negatively impact quality of life. CO2 emissions are positively associated with electricity while air pollution is positively associated with GDP and negatively with unemployment. Air pollution has an adverse effect on all three aspects of the children's welfare dimension of quality of life. These results provide timely and convincing insights for policy- and decision-making aimed at mitigating the impact of emissions on quality of life. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effects of encapsulation and combining probiotics with different nitrate forms on methane emission and the in vitro fermentation process of ruminants. Sodium nitrate (NaNO3) and nitric acid (HNO3) were used as nitrate forms, while lactic acid bacteria Lactiplantibacillus plantarum TSD-10 was used as a probiotic source. Twelve different treatments with four replicates were allocated in the factorial block design (2 × 2 × 3). During each replicate, the test was conducted individually in a different week so that each block could be considered separately. Data analysis followed the analysis of variance (ANOVA) and then continued with the Duncan multiple range test. After encapsulation, significant increases (p < 0.05) in gas production, gas kinetics, total volatile fatty acids (TVFAs), and production of propionic acid were observed. In addition, encapsulation significantly decreased (p < 0.05) the pH, ammonia concentration (NH3), nutrient digestibility, and the ratio of acetic to propionic acid (p < 0.05). The addition of combined encapsulated probiotics and encapsulated nitrate significantly increased (p < 0.05) gas production, maximum gas production, TVFAs, and the molar portion of propionic acid, and significantly decreased (p < 0.05) enteric methane emission, acetic acid, ammonia concentration, pH, and nutrient digestibility. The addition of sodium nitrate significantly increased (p < 0.05) the concentration of TVFAs and acetic acid, while nitric acid significantly increased (p < 0.05) the gas production rate. However, there was no significant effect due to combining unencapsulated probiotics with unencapsulated nitrate forms on the rumen fermentation process. There was a significant interaction (p < 0.05) between encapsulation probiotics and nitrate on ammonia concentration. In conclusion, combining encapsulated probiotics with encapsulated nitrate is an alternative method for enhancing the fermentation process and mitigating enteric methane emission in ruminants.

ABSTRACT: Inhibition of methyl-coenzyme M reductase can suppress the activity of ruminal methanogens, thereby reducing enteric methane emissions of ruminants. However, developing specific and environmentally friendly inhibitors is a challenging endeavor. To identify a natural and effective methane inhibitor that specifically targets methyl-coenzyme M reductase, molecular docking technology was employed to screen a library of phytogenic compounds. A total of 52 candidate compounds were obtained through molecular docking technique. Rosmarinic acid (RA) was one of the compounds that could traverse a narrow channel and bind to the active sites of methyl-coenzyme M reductase, with a calculated binding free energy of −9.355 kcal/mol. Furthermore, the effects of RA supplementation on methane production, rumen fermentation, and the microorganism community in dairy cows were investigated through in vitro rumen fermentation simulations according to a random design. Supplementation of RA resulted in a 15% decrease in methane production compared with the control. In addition, RA increased the molar proportion of acetate and propionate, whereas the sum of acetate and butyrate divided by propionate was decreased. At the bacterial level, the relative abundance of Rikenellaceae RC9 gut group, Christensenellaceae R7 group, Candidatus Saccharimonas, Desulfovibrio, and Lachnospiraceae FE2018 group decreased with RA supplementation. Conversely, the addition of RA significantly increased the relative abundance of DNF00809 (a genus from Eggerthellaceae), Denitrobacterium, an unclassified genus from Eggerthellaceae, an unclassified genus from Bacteroidales, and an unclassified genus from Atopobiaceae. At the archaeal level, the relative abundance of Methanobrevibacter decreased, whereas that of Methanosphaera increased with RA supplementation. These findings suggested that RA has the potential to be used as a novel natural additive for inhibiting ruminal methane production.

Abstract The layout of methane sensors in the working face cannot meet the needs for monitoring methane concentrations within confined spaces, and it is challenging to determine the precise locations for manual inspections. Therefore, the working face is firstly divided into different areas and grids. Then combined with the characteristics of methane emissions and the measured data on site, the boundary conditions of simulation experiments are set up and the research is carried out on the diffusion law of methane in the confined space of the working face under different conditions. The experimental results show that methane emission intensity from coal walls affects its distribution. As emission intensity rises, methane nearer the coal wall decreases, while methane further away increases. Among coal mining points, point 2 shows the widest methane diffusion range. Rising wind speeds decrease methane diffusion from the coal wall, increasing vertical diffusion distance. Methane from the coal wall shifts to the air inlet, while methane from the mining point diffuses increasingly to the downwind side. The location of the maximum methane concentration generated from falling coal and its transportation process is only related to the location of the coal mining point. The key areas for methane monitoring in confined spaces of the working face should be the overlapping locations of the vertical‐3 and vertical‐4 areas and the horizontal‐1 and horizontal‐3 areas. The key areas for manual inspection should be the overlapping locations of the vertical‐2 and vertical‐3 areas and the horizontal‐1 area.

Dietary fat content can reduce the methane production of dairy cows; however, the relevance fatty acid (FA) composition has towards this inhibitory effect is debatable. Furthermore, in-depth studies elucidating the effects of unsaturated fatty acids (UFA) on rumen function and the mechanism of reducing methane (CH4) production are lacking. This study exposed 10 Holstein cows with the same parity, similar milk yield to two total mixed rations: low unsaturated FA (LUFA) and high unsaturated FA (HUFA) with similar fat content. The LUFA group mainly added fat powder (C16:0 > 90%), and the HUFA group mainly replaced fat powder with extruded flaxseed. The experiment lasted 26 d, the last 5 d of which, gas exchange in respiratory chambers was conducted to measure gas emissions. We found that an increase in the UFA in diet did not affect milk production (P > 0.05) and could align the profile of milk FAs more closely with modern human nutritional requirements. Furthermore, we found that increasing the UFA content in the diet lead to a decrease in the abundance of Methanobrevibacter in the rumen (|linear discriminant analysis [LDA] score| > 2 and P 2 and P

Methane production in ruminants is primarily due to the conversion of metabolic hydrogen (H2), produced during anaerobic microbial fermentation, into methane by ruminal methanogens. While this process plays a crucial role in efficiently disposes of H2, it also contributes to environmental pollution and eliminating methane production in the rumen has proven to be challenging. This study investigates the use of probiotics, specifically propionate-producing bacteria, to redirect accumulated H2 in a methane-mitigated environment. For this objective, we supplemented experimental groups with Lactiplantibacillus plantarum and Megasphaera elsdenii for the reinforced acrylate pathway (RA) and Selenomonas ruminantium and Acidipropionibacterium thoenii for the reinforced succinate pathway (RS), as well as a consortium of all four strains (CB), with the total microbial concentration at 1.0 × 1010 cells/mL. To create a methane-mitigated environment, 2-bromoethanesulfonate (BES) was added to all experimental groups at a dose of 15 mg/0.5 g of feed. BES reduced methane production by 85% in vitro, and the addition of propionate-producing bacteria with BES further decreased methane emission by up to 94% compared with the control (CON) group. Although BES did not affect the alpha diversity of the ruminal bacteriome, it reduced total volatile fatty acid production and altered beta diversity of ruminal bacteriota, indicating microbial metabolic adaptations to H2 accumulation. Despite using different bacterial strains targeting divergent metabolic pathways (RA and RS), a decrease in the dominance of the [Eubacterium] ruminantium group suggesting that both approaches may have a similar modulatory effect. An increase in the relative abundance of Succiniclasticum in the CB group suggests that propionate metabolism is enhanced by the addition of a propionate-producing bacterial consortium. These findings recommend using a consortium of propionate-producing bacteria to manage H2 accumulation by altering the rumen bacteriome, thus mitigating the negative effects of methane reduction strategies. [ABSTRACT FROM AUTHOR]

The agronomic benefits of pesticides combined with amino acid application to increase rice production have been recognized, but they are still not well-known for greenhouse gas (GHG) emissions and mitigation in irrigated paddy fields. Thus, this study was conducted to investigate the combined effects of pesticide and amino acid application on rice yield and methane (CH4) emissions in a Korean rice paddy. A field experiment was conducted with five levels: none (no pesticide application, T1), different conventional practices (combined application of insecticides and fungicide, T2 and T3), and GroMore® programs (combined application of insecticides, fungicides, and amino acids, T4 and T5). Rice grain yield and yield components were obtained using agronomic measurements. To determine the greenhouse gas intensity (GHGI) of each treatment, CH4 emissions were measured throughout the rice growing period. Results showed that the chemical applications in combination with amino acids in T4 obtained a higher grain yield and number of panicles per plant compared to T1, T2, and T3, while T4 and T5 showed no difference on filled spikelets except for T2. T3 and T5 showed lower respective cumulative CH4 emissions by 30% and 32% during the entire rice growing season, compared to no chemical application (T1). Meanwhile, N2O emissions were negligible in all treatments because the paddy field was flooded most of the growing season. The results of the impact of GroMore® programs on relatively higher grain yield and lower GHG emissions are presented. In conclusion, the application of pesticides combined with amino acids obtained lower GHGI values. [ABSTRACT FROM AUTHOR]

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Inhibition of methyl-coenzyme M reductase can suppress the activity of ruminal methanogens, thereby reducing enteric methane emissions of ruminants. However, developing specific and environmentally friendly inhibitors is a challenging endeavor. To identify a natural and effective methane inhibitor that specifically targets methyl-coenzyme M reductase, molecular docking technology was employed to screen a library of phytogenic compounds. A total of 52 candidate compounds were obtained through molecular docking technique. Rosmarinic acid (RA) was one of the compounds that could traverse a narrow channel and bind to the active sites of methyl-coenzyme M reductase, with a calculated binding free energy of −9.355 kcal/mol. Furthermore, the effects of RA supplementation on methane production, rumen fermentation, and the microorganism community in dairy cows were investigated through in vitro rumen fermentation simulations according to a random design. Supplementation of RA resulted in a 15% decrease in methane production compared with the control. In addition, RA increased the molar proportion of acetate and propionate, whereas the sum of acetate and butyrate divided by propionate was decreased. At the bacterial level, the relative abundance of Rikenellaceae RC9 gut group, Christensenellaceae R7 group, Candidatus Saccharimonas , Desulfovibrio , and Lachnospiraceae FE2018 group decreased with RA supplementation. Conversely, the addition of RA significantly increased the relative abundance of DNF00809 (a genus from Eggerthellaceae), Denitrobacterium , an unclassified genus from Eggerthellaceae , an unclassified genus from Bacteroidales , and an unclassified genus from Atopobiaceae. At the archaeal level, the relative abundance of Methanobrevibacter decreased, whereas that of Methanosphaera increased with RA supplementation. These findings suggested that RA has the potential to be used as a novel natural additive for inhibiting ruminal methane production. [ABSTRACT FROM AUTHOR]

The increase in global temperatures over the past few decades due to greenhouse gas emissions has raised concerns and necessitated further research in climate change mitigation and adaptation. Methane is a prominent greenhouse gas that significantly contributes to climate change, with a substantial amount generated through fermentation processes occurring in the rumen of ruminant animals. The potential of plant secondary metabolites, especially those derived from tannin-rich plants, warrants investigation to modify rumen fermentation and mitigate methane emissions in livestock diets. The objective of this study was to assess the impact of extracts obtained from green and black tea waste on rumen fermentation dynamics and gas (methane) production, utilizing in vitro methods. For this purpose, rumen fluid was collected from two fistulated sheep and subjected to three treatments: (1) a basal diet (control), (2) a basal diet + green tea waste extract (5% of dry matter), (3) a basal diet + black tea waste extract (5% of dry matter). The study assessed the effects of incorporating extracts from green and black tea waste on various parameters, including digestibility, protozoa population, ammonia nitrogen levels, volatile fatty acids, and methane gas production following a 24-h incubation period. Statistical analysis of the data was conducted using SAS software within a completely randomized design framework. The findings indicated that the addition of green and black tea waste extracts significantly decreased methane gas production (p < 0.05), protozoa count (p < 0.05), and ammonia nitrogen concentrations in rumen fluid (p < 0.05) when compared to the control group. The addition of green and black tea waste extracts has significantly altered the concentration of VFAs in rumen fluid (p < 0.05). Specifically, the addition of green tea waste extract has led to a highly significant reduction in acetic acid, (p < 0.01) and the addition of both extracts has resulted in a significant increase in propionic acid (p < 0.05). Consequently, the results suggest that the inclusion of green and black tea waste extracts in livestock diets may effectively mitigate methane emissions in the rumen, thereby reducing feed costs and reducing environmental pollution. [ABSTRACT FROM AUTHOR]

There is considerable uncertainty about the methane emission from Arctic shelf seas. Methane fluxes in this region can be underestimated and play a significant role due to the large volume of gas contained in bottom sediments in the permafrost and gas hydrates. We analyzed the model sensitivity to the parameterization of gas exchange processes on the sea surface based on the numerical modeling of the transport of dissolved methane in Arctic seas. A dissolved methane transport model is included into the basic model of the ocean and sea ice SibCIOM developed at Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences. Methane emissions into the atmosphere were estimated with various parameterization of the gas exchange process in the "water–atmosphere" and "water–ice–atmosphere" systems with NCEP/NCAR reanalysis data. The uncertainty of the estimate of annual methane emission amounted to 6–12% when considering different dependencies of gas exchange on wind. The scheme which considers the ice cover has a more pronounced influence on methane flux calculations: the uncertainty increased to 50–130%. Parameterization of the relation between ice cover and gas exchange can have a great effect on the calculated methane fluxes and lead to underestimation of its emission from Arctic shelf seas. [ABSTRACT FROM AUTHOR]

Purpose: the article focuses on the issue of sustainable use of methane in the European Union. In this area - and it should be particularly emphasized - the EU attaches great importance to the issue of reducing methane emissions, due to its significant role in climate change and the need to achieve greenhouse gas reduction goals. The importance and significance of these activities is emphasized by the fact that the strictest standards in the world regarding the release of greenhouse gases, including methane from the mining industry, are in force and planned in the EU. In the face of such environmental goals of the European Community countries, it is crucial, apart from the economic factors, to take into account the social aspects highlighted in the article, without which rational shaping of the new transformation policy cannot take place. Methodology: the theses presented in the article verified using the following methods: literature review, critical analysis of literature, dogmatic and legal analysis, analysis and comparison of documents. Results: it seems that implementing comprehensive strategies for the sustainable use of methane in the EU will require not only political will and investment, but also continuous monitoring, evaluation and adaptation of actions based on the latest scientific and technological achievements. Only through cooperation and joint efforts can the goals of reducing greenhouse gas emissions and protecting the environment be achieved. Originality: the sustainable use of methane can not only contribute to achieving the EU's climate and energy goals, but also have a positive impact on human health, environmental quality and the economic stability of regions affected by mining activities. Therefore, it is not only a challenge, but also an opportunity to create a more fair, innovative and future-oriented economy that takes into account the needs of both current and future generations. [ABSTRACT FROM AUTHOR]

The layout of methane sensors in the working face cannot meet the needs for monitoring methane concentrations within confined spaces, and it is challenging to determine the precise locations for manual inspections. Therefore, the working face is firstly divided into different areas and grids. Then combined with the characteristics of methane emissions and the measured data on site, the boundary conditions of simulation experiments are set up and the research is carried out on the diffusion law of methane in the confined space of the working face under different conditions. The experimental results show that methane emission intensity from coal walls affects its distribution. As emission intensity rises, methane nearer the coal wall decreases, while methane further away increases. Among coal mining points, point 2 shows the widest methane diffusion range. Rising wind speeds decrease methane diffusion from the coal wall, increasing vertical diffusion distance. Methane from the coal wall shifts to the air inlet, while methane from the mining point diffuses increasingly to the downwind side. The location of the maximum methane concentration generated from falling coal and its transportation process is only related to the location of the coal mining point. The key areas for methane monitoring in confined spaces of the working face should be the overlapping locations of the vertical‐3 and vertical‐4 areas and the horizontal‐1 and horizontal‐3 areas. The key areas for manual inspection should be the overlapping locations of the vertical‐2 and vertical‐3 areas and the horizontal‐1 area. [ABSTRACT FROM AUTHOR]

• A high cooling capacity Stirling cryocooler is developed to liquefy boil-off gas. • The relative Carnot efficiency of the cryocooler reaches 33.28% at 77 K. • The cryocooler is installed in the skid-mounted BOG liquefaction system. • The system produces 27.3 L/h LNG and shows a great application potential. Natural gas is a cost-effective energy supply for the development of low-carbon economy and environmental protection worldwide. Despite the environmentally friendly properties of natural gas, methane is a potent greenhouse gas. Therefore, efficiently recovering the boil-off methane gas (BOG) generated from liquefied natural gas (LNG) devices is becoming a pressing problem involving both the economy and the environment. The Stirling cryocooler is a promising technology in dealing with BOG. This technology has superior characteristics, including large cooling capacity, high efficiency, compact configuration, and flexible operating characteristics. In the study, a high cooling capacity Stirling cryocooler was developed. The influences of the regenerator on the cryocooler were studied. The refrigeration performance and the operating characteristics were systematically analyzed. A cooling power of 1050 W at 77 K with a relative Carnot efficiency of 33.28 % was achieved. Accordingly, the cryocooler outperforms the reported Stirling-type cryocoolers in terms of overall performance. A BOG liquefaction system based on the cryocooler was installed in an LNG refueling station. On-site test results demonstrated that the system can produce 27.3 L/h LNG with a power consumption of 14.5 kW. The present research lays a good foundation for future optimizations and applications of the cryocooler in liquefying BOG. [ABSTRACT FROM AUTHOR]

This study investigates methane emissions in the mangrove forests of Xuan Thuy National Park in Vietnam, examining seasonal variations and the influence of environmental factors. Data from the field measurements present methane flux rates ranging from 0.01 to 10.42 mg m-2 day-1, are substantially lower than the default estimations recommended by IPCC guidelines. The study highlights discrepancies between actual field measurements and suggested default values, emphasizing the necessity for site-specific monitoring to avoid overestimating greenhouse gas emissions, particularly in mangrove areas. The analysis reveals strong correlations between methane flux and environmental parameters. Factors such as water pH, turbidity, temperature, and nitrogen content significantly influence methane emissions. The study emphasizes the interconnectedness of various greenhouse gas emissions within mangrove ecosystems and underlines the importance of accurate, location-specific data in environmental assessments and policy-making. [ABSTRACT FROM AUTHOR]

Methane, with a global warming potential roughly 86 times greater than carbon dioxide over a 20‐year timeframe, plays a crucial role in global warming. Remote sensing retrieval is a pivotal methodology for identifying methane emission sources, with accuracy influenced largely by surface and atmospheric properties, including aerosols. In this study, we propose an Aerosol‐Calibrated Matched Filter (ACMF) algorithm to improve the traditional Matched Filter (MF) method. Our new approach incorporates an aerosol scattering correction factor to reduce the aerosol‐induced bias on methane retrievals. Validating our algorithm through simulated spectra, we demonstrate that considering the aerosol scattering effect significantly reduces retrieval errors compared to MF methods by an average of approximately 90%. We apply our newly developed algorithm to hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer—Next Generation in the Los Angeles Basin and focus on 11 plumes identified through case studies. Our results reveal that ACMF estimates of emission rates and inversion uncertainties exhibit an average reduction of approximately 4% compared to corresponding MF results, with deviation increasing with aerosol optical depth (AOD). Plain Language Summary: Emissions from facilities like oil and gas plants, coal mines, and waste management sites are a major contributor to atmospheric methane, which is a greenhouse gas that significantly impacts global warming. We can remotely measure these emissions using hyperspectral instruments. However, atmospheric particulates (aerosols) can skew these measurements by affecting how sunlight travels through the atmosphere. In our study, we have developed a new, computationally efficient approach to adjust for aerosol effects when analyzing data from these instruments. Tests with simulated data show that our method reduces errors caused by aerosols by about 90% compared with existing schemes. Investigations over 11 different methane emission plumes in the Los Angeles area indicate that traditional methods overestimate methane releases, especially when aerosols are present. Key Points: The Aerosol‐Calibrated Matched Filter (ACMF) is proposed for correction of aerosol‐induced bias in methane point source emission retrievalsThe ACMF method decreased the bias in methane concentration retrieval, demonstrating a clear improvement over the Matched Filter (MF) methodThe ACMF method, implemented in 11 cases over the LA Basin, yielded lower flux rate estimates and uncertainties compared to the MF method [ABSTRACT FROM AUTHOR]

Methane (CH4) emissions from large controlled dump sites play a significant role in global warming. However, when captured efficiently, CH4 is a valuable energy resource. This study optimizes electrical resistivity tomography (ERT) for improved CH4 detection in controlled dump sites, focusing on refining electrode array configurations. We assessed three configurations: dipole-dipole, Wenner-Schlumberger (WS), and Wenner arrays. The results were compared with synthetic data simulated using the forward modeling technique, and the model's accuracy was evaluated using the Nash-Sutcliffe model efficiency coefficient (NSE), model sensitivity, and root mean square error (RMSE). Additionally, we analyzed the model's correlation with CH4 flux measurements. The WS array demonstrated the best performance, achieving a lower RMSE (23.4 %), a higher NES (0.90), and model sensitivity (0.90), along with a moderate negative correlation (-0.50) with CH4 flux measurements. This configuration effectively identified subsurface features, such as organic waste layers and leachate zones, which are crucial for CH₄ capture and landfill gas collection. Forward modeling confirmed the WS array's ability to provide high-resolution subsurface imaging, enhancing CH₄ hotspot detection. By improving the spatial and temporal accuracy of CH₄ detection, this approach addresses limitations in traditional methods and supports the design of more efficient gas capture systems. Applied in Thailand, these findings highlight the potential of optimized ERT techniques for enhancing CH₄ recovery in waste-to-energy systems, contributing to more sustainable waste management practices and reducing greenhouse gas emissions.

The world's population is proliferating, and the growing population needs more food resources. Meat is one of the essential dietary components for humans, but the available meat resources are insufficient to fulfill consumers' demands. In this scenario, the meat alternative could be a sustainable resource for fulfilling the meat demand. Cultured meat is one of the best meat alternatives and also has the potential to fulfill the meat demand of the growing population. Cultured meat is produced by cultivating animal stem cells and allowing them to undergo a growth and division process that closely mimics the natural cellular development inside living organisms. The primary reasons behind cultured meat production are to minimize the environmental effect by reducing methane emissions, to minimize the meat cost so it will be economical for the consumer, and to provide antibiotic-free meat. This review explains cultured meat production and new technologies being introduced to create opportunities to improve the overall production of cultured meat. It also explores the cultured meat sector's market opportunities and challenges to the cultured meat industry.

ABSTRACT: Reduction of methane emission may become necessary for sustainable milk production. Several studies indicate a relationship between rumination time and the level of methane emission. The objectives of the current study were to estimate environmental factors affecting daily rumination time in high-yielding dairy cattle, genetic parameters for rumination time across parities, and environmental and genetic correlations between rumination time and economic traits, and to predict the consequence of inclusion of this trait in the Israeli breeding index. The data included more than 30 million daily records from 77,697 Israeli Holstein cows for rumination time and milk production. A lactation measure of daily rumination time per cow was computed as the mean of the residuals from a linear model analysis with rumination time as the dependent variable. The independent variables were parity and the square root, linear, quadradic and inverse of DIM by parity. Because of the shape of the lactation curve for rumination time, separate linear model analyses were performed for records up to 40 DIM and records with >40 DIM. The phenotypic correlation between first- and second-parity lactations for rumination time was almost 0.8, and close to 0.7 for milk. The heritability of lactation rumination time was close to 0.44 for parities 1 to 3. Heritability for milk production decreased from 0.5 in first parity to 0.3 in third parity. For both traits, genetic correlations among parities were all >0.9. Thus, for routine genetic analysis of rumination time, records in the different parities can be considered the same trait. The genetic correlation between rumination time and milk on first parity was 0.25 and increased slightly with increase in parity. Genetic correlations between rumination time, based on the first 40 DIM, were economically unfavorable with retained placenta but economically favorable with metritis, ketosis, and displaced abomasum. Genetic correlations between rumination time and the 9 traits included in the Israeli breeding index (milk, fat, and protein production; SCS; female fertility; herd-life; milk production persistency; calving ease; and calf mortality) were all economically favorable, except for the correlation of 0.17 with SCS. With the current index, daily rumination time with a current mean of 536 min and SD of 90 min is expected to increase by 11 min/d after 10 yr of selection. Inclusion of this trait with a positive index weight equivalent to 10% of the index should increase rumination time by 19 min. All changes in expected gains due to inclusion of rumination time in the index were economically positive, except for fat and SCS. Inclusion of rumination time in the index should result in 1 kg less gain in fat, a miniscule gain of 0.03 for SCS; and gains of 1.5 kg protein, 0.3% female fertility, and 5 d herd-life. Even though the case for a genetic correlation between rumination time and methane emission is still weak, inclusion of this trait in the commercial index may be justified, considering that equipment is now commercially available for routine recording at reasonable cost.

Reduction of methane emission may become necessary for sustainable milk production. Several studies indicate a relationship between rumination time and the level of methane emission. The objectives of the current study were to estimate environmental factors affecting daily rumination time in high-yielding dairy cattle, genetic parameters for rumination time across parities, and environmental and genetic correlations between rumination time and economic traits, and to predict the consequence of inclusion of this trait in the Israeli breeding index. The data included more than 30 million daily records from 77,697 Israeli Holstein cows for rumination time and milk production. A lactation measure of daily rumination time per cow was computed as the mean of the residuals from a linear model analysis with rumination time as the dependent variable. The independent variables were parity and the square root, linear, quadradic and inverse of DIM by parity. Because of the shape of the lactation curve for rumination time, separate linear model analyses were performed for records up to 40 DIM and records with >40 DIM. The phenotypic correlation between first- and second-parity lactations for rumination time was almost 0.8, and close to 0.7 for milk. The heritability of lactation rumination time was close to 0.44 for parities 1 to 3. Heritability for milk production decreased from 0.5 in first parity to 0.3 in third parity. For both traits, genetic correlations among parities were all >0.9. Thus, for routine genetic analysis of rumination time, records in the different parities can be considered the same trait. The genetic correlation between rumination time and milk on first parity was 0.25 and increased slightly with increase in parity. Genetic correlations between rumination time, based on the first 40 DIM, were economically unfavorable with retained placenta but economically favorable with metritis, ketosis, and displaced abomasum. Genetic correlations between rumination time and the 9 traits included in the Israeli breeding index (milk, fat, and protein production; SCS; female fertility; herd-life; milk production persistency; calving ease; and calf mortality) were all economically favorable, except for the correlation of 0.17 with SCS. With the current index, daily rumination time with a current mean of 536 min and SD of 90 min is expected to increase by 11 min/d after 10 yr of selection. Inclusion of this trait with a positive index weight equivalent to 10% of the index should increase rumination time by 19 min. All changes in expected gains due to inclusion of rumination time in the index were economically positive, except for fat and SCS. Inclusion of rumination time in the index should result in 1 kg less gain in fat, a miniscule gain of 0.03 for SCS; and gains of 1.5 kg protein, 0.3% female fertility, and 5 d herd-life. Even though the case for a genetic correlation between rumination time and methane emission is still weak, inclusion of this trait in the commercial index may be justified, considering that equipment is now commercially available for routine recording at reasonable cost. [ABSTRACT FROM AUTHOR]

Methane (CH4) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH4 fluxes is examined at 14 FLUXNET‐ CH4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance‐based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET‐CH4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques. Plain Language Summary: Methane is a critical greenhouse gas, and wetlands are the largest natural source of it. Accurately predicting methane emissions from wetlands is key to tackling climate change. But these predictions, made through computer models, are seldom spot‐on. Why? Because there are many factors in the models that lead to uncertain predictions. A major source of this uncertainty arises from the empirical model parameters. Just as tuning a radio dial ensures clear reception, models need properly adjusted parameters for accurate predictions. A sensitivity analysis was performed to determine which parameters are most crucial for accurate predictions. Instead of running the complex numerical model every time, machine learning was employed to create a faster and simpler version. Using this approach, five parameters were pinpointed as particularly sensitive, significantly impacting the predictions. The comparison of model‐predicted methane emissions with real‐world measurements showed that the model performed well in some cases but needed tweaking in others. Refining these sensitive parameters with more real‐world observations could make better predictions in the future. Key Points: Identified five key sensitive parameters for methane emissions using the Sobol sensitivity analysis methodParameters linked to production and diffusion present the highest sensitivities despite apparent seasonal variationFourteen out of nineteen model parameters exert negligible influence on methane emissions [ABSTRACT FROM AUTHOR]

To determine the pharmacokinetics in dairy heifers after oral and IV administration of bromoform, a potential antimethanogenic agent found in red seaweed, Asparagopsis spp. Twenty-four dairy heifers with a mean weight of 319 (SD 36.9) kg were used. The study was conducted in two phases, and each cohort of 12 heifers received an escalating dose of bromoform. In the first phase, 12 heifers successively received doses of 200, 400, 800, and 1600 mg of bromoform orally, separated by a 72-hour washout period. In the second phase, a different cohort of 12 dairy heifers was used. Each heifer received a total of four doses of bromoform separated by a wash-out period of 72 hours. Sequentially the treatments were (for each of the 12 heifers) an oral dose of 50 mg, followed by an IV dose of 50 mg, followed by an oral dose of 100 mg and finally an IV dose of 100 mg. Blood samples were assayed by gas chromatography-mass spectrophotometry for bromoform and dibromomethane to estimate the pharmacokinetic parameters using a non-compartmental analysis. Bromoform was rapidly absorbed as indicated by a short time to the maximum observed concentration of 15 minutes. For the routes of administration and dose ranges investigated, the mean terminal half-life ranged from 0.32 (SE 0.03) hours to 5.73 (SE 1.64) hours when administered orally or IV. With values for the mean area under the curve (AUC) to dose ratio ranging from 0.25 (SE 0.04) to 0.82 (SE 0.19) for oral and 1.39 (SE 0.39) to 4.02 (SE 0.37) for IV administration, bromoform appeared to exhibit non-proportional pharmacokinetic behaviour. The mean absolute bioavailability was 39.13 (SE 10.4)% and 3.36 (SE 0.83)% for 50-mg and 100-mg doses, respectively. Bromoform is rapidly absorbed and exhibits dose dependent elimination kinetics. [ABSTRACT FROM AUTHOR]

The purpose of this research was to investigate the impact of dietary supplementation of Caragana korshinskii tannin (CKT) on rumen fermentation, methane emission, methanogen community and metabolome in rumen of sheep. A total of 15 crossbred sheep of the Dumont breed with similar body conditions, were divided into three groups (n=5), which were fed with CKT addition at 0, 2 and 4%/kg DM. The study spanned a total of 74 days, with a 14-day period dedicated to adaptation and a subsequent 60-day period for conducting treatments. The results indicated that the levels of ammonia nitrogen (NH3-N) and acetate were reduced (p < 0.05) in rumen sheep fed with 2 and 4% CKT; The crude protein (CP) digestibility of sheep in 2 and 4% CKT groups was decreased(p < 0.05); while the neutral detergent fiber (NDF) digestibility was increased (p < 0.05) in 4% CKT group. Furthermore, the supplementation of CKT resulted in a decrease (p < 0.05) in daily CH4 emissions from sheep by reducing the richness and diversity of ruminal methanogens community, meanwhile decreasing (p < 0.05) concentrations of tyramine that contribute to methane synthesis and increasing (p < 0.05) concentrations of N-methy-L-glutamic acid that do not contribute to CH4 synthesis. However, CH4 production of DMI, OMI, NDFI and metabolic weight did not differ significantly across the various treatments. To sum up, the addition of 4% CKT appeared to be a viable approach for reducing CH4 emissions from sheep without no negative effects. These findings suggest that CKT hold promise in mitigating methane emissions of ruminant. Further investigation is required to evaluate it effectiveness in practical feeding strategies for livestock. [ABSTRACT FROM AUTHOR]

The global efforts on reducing methane (CH4) emissions was emphasized in COP 28 and the potential for improved estimation became feasible through bottom-up data acquisition with advanced remote sensing technology. The objectives of this study were to extract summer rice and winter crop cultivation areas based on satellite images and to incorporate into estimating CH4 emissions in South Korea for the year 2020. Satellite images of Sentinel-1 and Sentinel-2 were acquired from European Space Agency. Rice paddy was classified with backscattering coefficient from Sentinel-1 images, while the normalized difference vegetation index from Sentinel-2 images was used to identify winter cropping field. The equation of IPCC guidelines was used to estimate CH4 emissions by incorporating the areas of rice paddy and winter crop extracted with the respective satellite image. National farming statistics were used to determine the scaling factors for paddy organic matter and water management practices. The estimated areas for rice paddy and winter crop cultivation were 712,237 ha and 117,840 ha, respectively. The rice paddy areas were primarily concentrated in the western regions of the Korean peninsula, whereas winter crop cultivation was predominantly found in southern part of the country. The total amount of CH4 emissions was 6272 Gg CO2 eq./yr when considering rice straw and winter cropping practices into estimation (modified Tier 2 method). This represents a 7% increase compared to the method that considered solely the rice straw incorporation (current Tier 2 method). The CH4 emissions per unit area were also 8.82 tons CO2 eq./ha/yr with the modified Tier 2 method, indicating a 10% greater compared to the current Tier 2 method. Substantial CH4 emissions were primarily concentrated in western regions where extensive rice paddy cultivation occurs, while greater CH4 emissions per unit area were predominantly found in southern regions with substantial winter crop cultivation. The study findings hold importance for improving the accuracy of CH4 emissions estimation by employing bottom-up approach that utilizes satellite imagery to assess rice paddy and winter cropping areas. Further study would be needed to incorporate field-based data on rice crop management practices, such as rice straw and water management, to further refine CH4 emission estimation method. [ABSTRACT FROM AUTHOR]

Purpose: It is unclear whether a higher biochar (BC) application rate enhances rice (Oryza sativa L.) yield and reduces CH4 emissions. This study investigated changes in rice yield and CH4 emissions with varying BC application rates. Methods: Data on rice yield and CH4 emission from paddies amended with or without BC were collected from the literature, and the biochar effects were analyzed using the data set. Results: Across the biochar application rate from 2 to 48 t ha-1, the rice yield increased (by 10.8%) while the area-scaled (by 14.4%) and yield-scaled CH4 emission (by 22.2%) decreased. However, the correlation of BC application rates with rice yield and CH4 mitigation was not significant, implying that a higher BC application rate did not enhance rice yield and CH4 reduction. Interestingly, for a data set showing increased rice yield and decreased CH4 emission by BC, the magnitude of change in the rice yield and CH4 mitigation per unit weight of BC (1 t ha-1) decreased with an increase in the BC application rate. These results suggest that BC effects on rice yield and CH4 mitigation are not additive, probably because of the decreases in the inherent capacity of unit weight of BC to enhance rice yield and reduce CH4 emission, which might be caused by the adverse effects of toxic compounds contained in BC, losses of BC, and a higher degree of nutrient immobilization by BC. Conclusions: Annual BC application at a low rate (e.g., 2 t ha-1) rather than a luxury application may be an effective and economical strategy for long-term rice yield enhancement and CH4 mitigation using BC. [ABSTRACT FROM AUTHOR]

• Accounting methods of agricultural methane are summarized. • Influencing factors of emission sources from agricultural sources were analyzed. • Mitigation strategies based on accounting and actual situation are proposed. Methane is one of the major greenhouse gases (GHGs) and agriculture is recognized as its primary emitter. Methane accounting is a prerequisite for developing effective agriculture mitigation strategies. In this review, methane accounting methods and research status for various agricultural emission source including rice fields, animal enteric fermentation and livestock and poultry manure management were overview, and the influencing factors of each emission source were analyzed and discussed. At the same time, it analyzes the different research efforts involving agricultural methane accounting and makes recommendations based on the actual situation. Finally, mitigation strategies based on accounting results and actual situation are proposed. This review aims to provide basic data and reference for agriculture-oriented countries and regions to actively participate in climate action and carry out effective methane emission mitigation. [Display omitted] [ABSTRACT FROM AUTHOR]

In the framework of the eutrophic Ob fen study, methane fluxes were measured by the chamber method, and water was sampled for the analysis of general chemical composition, content of biophilic elements (C, N, and P) and δ13C of the dissolved inorganic carbon (δ13C-DIC). Samples were taken from open and forested areas within the fen, with the latter having long received discharged domestic wastewaters. The methane emissions positively correlate with the concentrations of nitrogen compounds and dissolved organic carbon (DOC). In both areas, higher methane emissions were observed from waterlogged microdepressions than from dry elevated microlandscape features. The largest emission was observed from the microdepressions in the forested area near the wastewater discharge point, where the extreme values of CH4 fluxes were almost 30 times higher than the background ones. However, the methane fluxes decrease to the background level at 160 m from the wastewater discharge point, together with the concentrations of almost all nitrogen and carbon compounds dissolved in the fen water. This led us to conclude that wastewater pollution significantly affects the intensity of methane fluxes by increasing ebullitive methane emission near the pollution source. The isotopic composition of the dissolved inorganic carbon (DIC) was heavier in the forested area (δ13C-DIC = –9.64 to –9.21‰) than in the open one (–12.83 to –11.24‰). In the open area of the fen, DIC isotopic composition became heavier away from the dry upland, correlating with the increase in the methane fluxes. The obtained data indicate that methane-generating processes are more active in the forested area of the fen than in the open one and become more active in the open area with increasing distance from the dry upland. This highlights the potentialities of using δ13C-DIC as a fingerprint of wastewater pollution, at least in the Ob fen area. [ABSTRACT FROM AUTHOR]

Due to natural and anthropogenic disturbances, natural gas hydrates with morphologies of nodules and chunks dissociate and release massive free gas, creating large cavities within fine-grained marine sediments. However, it is still a challenge to quantify the impact of gas cavities on mechanical properties of cavitied fine-grained marine sediments as there is a lack of efforts focusing on the inner structure visualization. In this study, an oedometer test and X-ray computed tomography scans are jointly conducted on marine clayey silt with gas cavities, and the confined compressibility as well as the inner structure change under an undrained condition are explored, followed by development of a theoretical model depicting the void ratio change. The results show that vertical loading induces a void ratio reduction, and the reduced void ratio can fully recover after being unloaded. Although being fully recovered, unrecovered changes of the inner structure still remain after being unloaded. Examples include closed cracks in the lower matrix, new occurring cracks in the upper matrix, and the fragmented gas cavity. In addition, the void ratio linearly increases with the increasing inverse of normalized pore gas pressure, while the coefficient of the effective stress linearly decreases with the increasing inverse of normalized vertical loading stress. The proposed theoretical model captures the essential physics behind undrained confined deformation of fine-grained marine sediments with gas cavities when subjected to loading and unloading. [ABSTRACT FROM AUTHOR]

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity. To infer emissions from TROPOMI data, we used the prior emission estimates from global and national inventories and the GEOS-Chem chemical transport model to simulate atmospheric methane along with actual observations of TROPOMI. In this study, methane emissions from Toronto, Montreal, New York, Los Angeles, Houston, and Mexico City have been estimated using the analytical solution of Bayesian inversion using the cloud-based Integrated Methane Inversion (IMI) framework. Using the result from ensemble inversions, and city boundaries, the average total emissions were as follows: Toronto 230.52 Gg a−1, Montreal 111.54 Gg a−1, New York 144.38 Gg a−1, Los Angeles 207.03 Gg a−1, Houston 650.16 Gg a−1, and Mexico City 280.81 Gg a−1. The resulting gridded scale factors ranged from 0.22 to 6.2, implying methane prior emission underestimations in most of these cities. As such, this study underscores the key role of remote sensing in accurately assessing urban methane emissions, informing essential climate mitigation efforts. [ABSTRACT FROM AUTHOR]

Reducing methane emissions in the oil and gas industry is a top priority for the current international community in addressing climate change. Methane emissions from the energy sector exhibit strong temporal variability and ground monitoring networks can provide time-continuous measurements of methane concentrations, enabling the rapid detection of sudden methane leaks in the oil and gas industry. Therefore, identifying specific locations within oil fields to establish a cost-effective and reliable methane monitoring ground network is an urgent and significant task. In response to this challenge, this study proposes a technical workflow that, utilizing emission inventories, atmospheric transport models, and intelligent computing techniques, automatically determines the optimal locations for monitoring stations based on the input quantity of monitoring sites. This methodology can automatically and quantitatively assess the observational effectiveness of the monitoring network. The effectiveness of the proposed technical workflow is demonstrated using the Shengli Oilfield, the second-largest oil and gas extraction base in China, as a case study. We found that the Genetic Algorithm can help find the optimum locations effectively. Besides, the overall observation effectiveness grew from 1.7 to 5.6 when the number of site increased from 1 to 9. However, the growth decreased with the increasing site number. Such a technology can assist the oil and gas industry in better monitoring methane emissions resulting from oil and gas extraction. [ABSTRACT FROM AUTHOR]

China is likely the world's largest anthropogenic source of methane emissions, with coal mine methane (CMM) being the predominant contributor. Here, we deploy 2 years of satellite observations to survey facility‐level CMM emitters in Shanxi, the most prolific coal mining province in China. A total of 138 detected episodic events at 82 facilities are estimated to emit 1.20 (+0.24/−0.20, 95% CI) million tons of methane per year (Mt CH4/yr) during 2021–2023, roughly equivalent to 4.2 times the integrated flux from the Permian plumes and four times of the integrated flux from the Four Corners plumes, two of the world's largest hotspots for oil and gas methane emissions. This work reveals the heavy‐tailed distribution characteristic of CMM emission sources for the first time, with 20% of emitters contributing approximately 50% of total emissions. Comparison with the Global Energy Monitor (GEM) inventory reveals that the GEM estimate is about 4.1 times our estimate. Plain Language Summary: This study examines methane emissions from coal mines in Shanxi, China, identified as a significant source of global methane, a potent greenhouse gas. Using satellite data over 2 years, we found 138 detected episodic events at 82 facilities in Shanxi emitting an estimated 1.2 million tons of methane annually, far exceeding emissions from known global hotspots in the oil and gas sectors. Our analysis shows that a small percentage of these facilities contribute to the majority of emissions. The results, which challenge previous estimates from environmental monitoring organizations, underscore the need for direct, observational methods to accurately assess and address methane emissions. This work aims to guide efforts in mitigating climate change by identifying key areas for reducing methane release. Key Points: Satellite data identify 82 major methane emitters in Shanxi, China, with high annual emissions of up to 1.2 MtTop 20% of coal mines contribute to half of the region's total methane emissionsFindings highlight the importance of direct measurements for accurate emission estimates [ABSTRACT FROM AUTHOR]

Abstract Methane, with a global warming potential roughly 86 times greater than carbon dioxide over a 20‐year timeframe, plays a crucial role in global warming. Remote sensing retrieval is a pivotal methodology for identifying methane emission sources, with accuracy influenced largely by surface and atmospheric properties, including aerosols. In this study, we propose an Aerosol‐Calibrated Matched Filter (ACMF) algorithm to improve the traditional Matched Filter (MF) method. Our new approach incorporates an aerosol scattering correction factor to reduce the aerosol‐induced bias on methane retrievals. Validating our algorithm through simulated spectra, we demonstrate that considering the aerosol scattering effect significantly reduces retrieval errors compared to MF methods by an average of approximately 90%. We apply our newly developed algorithm to hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer—Next Generation in the Los Angeles Basin and focus on 11 plumes identified through case studies. Our results reveal that ACMF estimates of emission rates and inversion uncertainties exhibit an average reduction of approximately 4% compared to corresponding MF results, with deviation increasing with aerosol optical depth (AOD).

Rice-shrimp rotation systems are one of the widespread farming practices in the Vietnamese Mekong Delta coastal areas. However, greenhouse gas (GHG) emissions in the system have remained unclear. This study aimed to examine methane (CH4) and nitrous oxide (N2O) emissions from the system, including (i) land-based versus high-density polyethylene-lined (HDPE) nursery ponds and (ii) conventional versus improved grow-out ponds inoculated with effective microorganisms (EM) bioproducts. The results showed that CH4 flux in land-based and HDPE-lined nursery ponds were 1.04 and 0.25 mgCH4 m−2 h−1, respectively, while the N2O flux was 8.37 and 6.62 μgN2O m−2 h−1, respectively. Global warming potential (GWP) from land-based nursery ponds (18.3 g CO2eq m−2) was approximately 3 folds higher than that of the HDPE-lined nursery pond (6.1 g CO2eq m−2). Similarly, the mean CH4 and N2O fluxes were 15.84 mg CH4 m−2 h−1 and 7.17 μg N2O m−2 h−1 for the conventional ponds, and 10.51 mg CH4 m−2 h−1 and 7.72 μg N2O m−2 h−1 for the improved grow-out ponds. Conventional practices (2388 g CO2eq m−2) had a higher 1.5-fold GWP compared to the improved grow-out pond (1635 g CO2eq m−2). The continuation of the land-based nursery pond and conventional aquacultural farming practices increase CH4 emission and GWP, while applying HDPE-lined nursery ponds combined with improved grow-out ponds could be a promising approach for reducing GHG emissions in rice-shrimp rotation systems. This study recommends further works in the rice-shrimp rotation systems, including (i) an examination of the effects of remaining rice stubbles in the platform on the availability of TOC levels and GHG emissions and (ii) ameliorating dissolved oxygen (DO) concentration on the effectiveness of GHG emission reduction.