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Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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.

Methane, the second most prevalent greenhouse gas globally, is characterized by its high global warming potential and short atmospheric lifetime. It is primarily emitted from sectors such as coal mining, oil and gas production, agriculture, livestock rearing, and waste management. Active, prudent, and orderly control of methane emissions offers a multifaceted benefit: it mitigates global warming, enhances the economic value through the resource utilization of energy, provides environmental advantages by control of pollutants, and improves safety by reducing production accidents. Methane is also the principal greenhouse gas emitted in coal mine operations. Currently, monitoring and researching the distribution of methane emissions and their concentration within the three-dimensional space of coal mines have become a key focus in China’s methane emission control efforts, which is of significant importance for coal mining enterprises to align with national strategies. A study conducted on a high-gas mine in Shanxi and a low-gas mine in Shaanxi for methane emission monitoring and accounting utilized fixed monitoring, manual monitoring, drone monitoring, and post-mining activity monitoring to investigate the distribution of methane in high and low gas mines in China and to analyze their methane emissions. The results indicate that: ① The methane emission volumes for a certain high-gas mine in Shanxi and a low-gas mine in Shaanxi published by the U.S.-based Climate TRACE website for the year 2022 show a significant discrepancy from the results calculated using the ground measurement method, with the published annual methane emission volume for a certain low-gas mine being 10.92 times that of the ground measurement calculation. The top-down monitoring and accounting methods have been found to be insufficiently accurate and unable to provide reliable data support for carbon trading. ② In the monitoring and accounting of post-mining activities, the use of default values recommended by the IPCC results in methane emissions that are 3 to 5 times higher than those calculated using the ground measurement method, and there is a significant variation in the emissions calculated based on coal samples of different sizes and exposure durations. There is an urgent need for a unified and precise testing standard to ensure fair and accurate data for future carbon market transactions.

Abstract 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.

Anthropogenic methane emissions are a leading cause of the increase in global average temperatures, often referred to as global warming. Flooded soils play a significant role in methane production, where the anaerobic conditions promote the production of methane by methanogenic microorganisms. Rice fields contribute a considerable portion of agricultural methane emissions, as rice plants provide both factors that enhance and limit methane production. Rice plants harbor both methane- producing and methane-oxidizing microorganisms. Exudates from rice roots provide source for methane production, while oxygen delivered from the root aerenchyma enhances methane oxidation. Studies have shown that the diversity of these microorganisms depends on rice cultivars with some genes characterized as harboring specific groups of microorganisms related to methane emissions. However, there is still a need for research to determine the balance between methane production and oxidation, as rice plants possess the ability to regulate net methane production. Various agronomical practices, such as fertilizer and water management, have been employed to mitigate methane emissions. Nevertheless, studies correlating agronomic and chemical management of methane with productivity are limited. Moreover, evidences for breeding low-methane-emitting rice varieties are scattered largely due to the absence of coordinated breeding programs. Research has indicated that phenotypic characteristics, such as root biomass, shoot architecture, and aerenchyma, are highly correlated with methane emissions. This review discusses available studies that involve the correlation between plant characteristics and methane emissions. It emphasizes the necessity and importance of breeding low-methane-emitting rice varieties in addition to existing agronomic, biological, and chemical practices. The review also delves into the ideal phenotypic and physiological characteristics of low-methane-emitting rice and potential breeding techniques, drawing from studies conducted with diverse varieties, mutants, and transgenic plants.

The ongoing yearly rise in worldwide methane (CH4) emissions is mostly due to human activities. Nevertheless, since over half of these emissions are scattered and have a concentration of less than 3% (v/v), traditional physical–chemical methods are not very effective in reducing them. In this context, biotechnologies like biofiltration using methane-consuming bacteria, also known as methanotrophs, offer a cost-efficient and practical approach to addressing diffuse CH4 emissions. The present review describes recent findings in biofiltration processes as one of the earliest biotechnologies for treating polluted air. Specifically, impacts of biotic (such as cooperation between methanotrophs and non-methanotrophic bacteria and fungi) and abiotic factors (such as temperature, salinity, and moisture) that influence CH4 biofiltration were compiled. Understanding the processes of methanogenesis and methanotrophy holds significant importance in the development of innovative agricultural practices and industrial procedures that contribute to a more favourable equilibrium of greenhouse gases. The integration of advanced genetic analyses can enable holistic approaches for unravelling the potential of biological systems for methane mitigation. This study pioneers a holistic approach to unravelling the biopotential of methanotrophs, offering unprecedented avenues for biotechnological applications.

Advanced and innovative breeding and management of meat-producing animals are needed to address the global food security and sustainability challenges. Beef production is an important industry for securing animal protein resources in the world and meat quality significantly contributes to the economic values and human needs. Improvement of cattle feed efficiency has become an urgent task as it can lower the environmental burden of methane gas emissions and the reduce the consumption of human edible cereal grains. Cattle depend on their symbiotic microbiome and its activity in the rumen and gut to maintain growth and health. Recent developments in high-throughput omics analysis (metagenome, metatranscriptome, metabolome, metaproteome and so on) have made it possible to comprehensively analyze microbiome, hosts and their interactions and to define their roles in affecting cattle biology. In this review, we focus on the relationships among gut microbiome and beef meat quality, feed efficiency, methane emission as well as host genetics in beef cattle, aiming to determine the current knowledge gaps for the development of the strategies to improve the sustainability of beef production.

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.

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.

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.

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.

The energy potential of municipal solid waste landfills receded into the background compared to more traditional sources of energy. Such possibilities as landfill degassing, as well as extraction of thermal energy from the depths of landfills, were little-researched, due to being kind of risky phenomena for their wide application. Currently, the energy system of Ukraine is under the risk as due to the military actions - objects of critical energy infrastructure have become the easy targets for the enemy. About 53 mln m3 of household waste were generated in Ukraine in 2021. Over 10 mln tons were buried at 6000 of landfills, total area of which accounts for 9000 hectares. The energy potential of these waste was used ineffective. Only 28 landfills of total have the degassing system established. The case of using landfill gas as an energy source lies between such challenges: the increasing amount of MSW, proper waste management and the energy crisis in Ukraine caused by the shellings. Landfill spreading throughout the country makes it possible to operate safely and reduce the risk of bringing any significant damage to such infrastructure. The study was focused on the Sumy City landfill, the potential of which is estimated as 36397 m3/t of solid waste. The degassing system was designed based on the methodology of State building regulations of Ukraine. Analysis of the efficiency of the system was done, including the potential energy output as a result of operation of such a system which comes paramount in dealing with the imperative of soaring amount of MSW, reducing greenhouse gas emissions and producing green, cheap energy. The negative impact of MSW landfills on the environment is beyond all dispute so it is crucial that their potential be used at full capacity. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Flavonoids have been recognized as potential phytochemicals to reduce enteric methane (CH4) production and improve rumen nitrogen efficiency in ruminants. We evaluated whether naringin, hesperidin, their combination, or a mixed citrus flavonoid extract (CFE) as additives can inhibit methanogenesis and ammoniagenesis in dairy cows using an in vitro rumen batch refermentation system. The rumen inocula from dairy cows were incubated in batch cultures with five groups: no addition (CON), hesperidin (20 g/kg DM), naringin (20 g/kg DM), hesperidin + naringin (10 g/kg DM of hesperidin + 10 g/kg DM of naringin), and CFE (20 g/kg DM). The combination of naringin plus hesperidin and CFE achieved greater reductions in CH4 and ammonia production compared to either naringin or hesperidin alone. Microbiome analysis revealed that the decrease in CH4 emissions may have been caused by both the direct inhibitory impact of citrus flavonoids on Methanobrevibacter and a simultaneous decrease in protozoa Isotricha abundance. The relatively lower proportion of Entodinium in naringin plus hesperidin or CFE was responsible for the lower ammonia concentration. These results suggest that citrus flavonoids possess potential synergistic effects on mitigating ruminal CH4 emissions by cows and improving nitrogen utilization. [ABSTRACT FROM AUTHOR]

Simple Summary: Predicting emissions from livestock housing is crucial for helping farmers understand how various factors impact emissions at the pig house level. This knowledge empowers decision-makers and the farmers to make informed choices that encourage emission reduction and improve air quality in pig houses. To create innovative, low-emission pig housing systems, the development of a prediction model appears to be a straightforward solution. This paper introduces such a model for predicting methane and ammonia emissions from two commercial pig houses with two manure management systems: one with long storage in deep pits and the other with short storage, through daily flushing of a shallow pit with sloped walls (a reduced emitting surface) and partial manure dilution. This simulation model, which considers factors like animal weight, age, feed, and pen dimensions as input data, calculates manure quantity and quality, as well as methane and ammonia emissions over the growing period. In this model, the calculation of ammonia emission involves aggregating emissions from various sources identifiable within pig houses. These sources include manure channels, slatted floors, and solid floors, encompassing fouled areas, pigs, and pen partitions. This model successfully predicts the development of methane and ammonia emissions based on animal and farm characteristics. This paper describes a model for the prediction of methane and ammonia emissions from fattening pig houses. This model was validated with continuous and discrete measurements using a reference method from two manure management systems (MMS): long storage (LS) in deep pits and short storage (SS) by daily flushing of a shallow pit with sloped walls and partial manure dilution. The average calculated methane and ammonia emissions corresponded well with the measured values. Based on the calculated and measured results, the average calculated CH4 emission (18.5 and 4.3 kg yr−1 per pig place) was in between the means from the continuous data from sensors (15.9 and 5.6 kg yr−1 per pig place) and the means from the discrete measurements using the reference method (22.0 and 3.1 kg yr−1 per pig place) for the LS and SS systems, respectively. The average calculated NH3 emission (2.6 and 1.4 kg yr−1 per pig place) corresponded well with the continuous data (2.6 and 1.2 kg yr−1 per pig place) and the discrete measurements using the reference method (2.7 and 1.0 kg yr−1 per pig place) from LS and SS, respectively. This model was able to predict the reduction potential for methane and ammonia emissions by the application of mitigation options. Furthermore, this model can be utilized as a predictive tool, enabling timely actions to be taken based on the emission prediction. The upgraded model with robust calculation rules, extensive validations, and a simplified interface can be a useful tool to assess the current situation and the impact of mitigation measures at the farm level. [ABSTRACT FROM AUTHOR]

Simple Summary: This review highlights the benefits of using valuable alternative feeds such as crop residues, silage, grasses, hay, browse, plant leaves, shrubs, and agro-industrial by-products in small ruminants' diets. Alternative feeds can significantly improve the productivity and reduce carbon footprints and GHG fluxes of small ruminant farms, making them both environmentally friendly and cost-effective. Additionally, these alternative feeds possess antioxidant, antimicrobial, and antiseptic properties that can enhance the quality of the meat and milk produced. Small ruminants, such as sheep (Ovisaries) and goats (Capra hircus), contribute to approximately 475 million metric tons of carbon dioxide equivalent (MtCO2e) greenhouse gas (GHG) emissions, accounting for approximately 6.5% of the global emissions in the agriculture sector. Crop residues, silage, grasses, hay, browse, plant leaves, shrubs, agro-industrial by-products, poultry litter, and other alternative feed sources are frequently utilized for small ruminant production. The use of these valuable alternative feeds can significantly improve animal productivity and reduce carbon footprints and GHG fluxes, making it both environmentally friendly and cost-effective. Additionally, these alternative feeds possess antioxidant, antimicrobial, and antiseptic properties that can enhance the quality of the meat and milk produced. By impacting the bacteria involved in ruminal biohydrogenation, alternative feeds can reduce methane emissions and contribute to a decrease in the carbon footprint. Overall, the use of alternative feed sources for small ruminants generally improves their apparent nutrient digestibility and productivity, and has an impact on the production of greenhouse gases, especially methane. Finally, this review recommends evaluating the economic analysis of reducing methane emissions in small ruminants by utilizing different feed sources and feeding techniques. [ABSTRACT FROM AUTHOR]

Currently, carbon-based substances are widely used in agriculture and industry, leading to obvious accumulation in ecosystems. Natural ecosystems, especially water-logged areas, are important sources of greenhouse gases. However, it is not clear whether the dimensions of carbon-based substances can affect their emission. Herein, the effects of three kinds of carbon-based substances (including carbon nanotubes, graphene, and graphite powder) with dimensions from one to three on the CO2 and CH4 production potential were tested from a saltmarsh wetland soil. Carbon nanotubes inhibited CH4 production, and graphene showed slight inhibition. In contrast, graphite powder could promote methanogenesis, and the maximum CH4 concentration was 53.02 mmol g−1 L−1. With a decrease, the maximum CH4 concentration with carbon nanotubes was only 38.09 mmol g−1 L−1. Interestingly, the effect of carbon-based substances on CO2 production was opposite to that on CH4. Carbon nanotubes showed the greatest promotion effect on CO2 production. In addition, by comparing the effects of carbon-based substances on global warming equivalent, graphite powder showed a promotion effect compared with the control, while carbon nanotubes decreased it. This study provides basic data for understanding the effects of carbon-based substances with diverse dimensions on greenhouse gas dynamics in saltmarsh wetland soil. [ABSTRACT FROM AUTHOR]

Simple Summary: Consumer perception related to health and environmental issues associated with ruminant products, such as greenhouse gas emissions, has led to a paradigm shift aimed at mitigating the potential harmful effects of ruminant production. This study consolidated the current body of research on dietary rumen manipulating strategies with an aim to quantify their impact on rumen fermentation, enteric methane (CH4) emission and productivity by creating a global database on in vivo evaluation studies. A meta-analytical approach was used to achieve the study's aim and the result showed that nitrate, saponin, oils, biochar and 3-nitroxypropanol (3-NOP) were effective dietary rumen modulating strategies to mitigate enteric CH4 emission. Of these effective strategies, oils and 3-NOP provided a co-benefit in terms of improving productivity in ruminant livestock. Concentrate feeding equally improved production without any significant effect on enteric methane emissions. A meta-analysis was conducted with an aim to quantify the beneficial effects of nine different dietary rumen modulating strategies which includes: the use of plant-based bioactive compounds (saponin, tannins, oils, and ether extract), feed additives (nitrate, biochar, seaweed, and 3-nitroxy propanol), and diet manipulation (concentrate feeding) on rumen fermentation, enteric methane (CH4) production (g/day), CH4 yield (g/kg dry matter intake) and CH4 emission intensity (g/kg meat or milk), and production performance parameters (the average daily gain, milk yield and milk quality) of ruminant livestock. The dataset was constructed by compiling global data from 110 refereed publications on in vivo studies conducted in ruminants from 2005 to 2023 and anlayzed using a meta-analytical approach.. Of these dietary rumen manipulation strategies, saponin and biochar reduced CH4 production on average by 21%. Equally, CH4 yield was reduced by 15% on average in response to nitrate, oils, and 3-nitroxy propanol (3-NOP). In dairy ruminants, nitrate, oils, and 3-NOP reduced the intensity of CH4 emission (CH4 in g/kg milk) on average by 28.7%. Tannins and 3-NOP increased on average ruminal propionate and butyrate while reducing the acetate:propionate (A:P) ratio by 12%, 13.5% and 13%, respectively. Oils increased propionate by 2% while reducing butyrate and the A:P ratio by 2.9% and 3.8%, respectively. Use of 3-NOP increased the production of milk fat (g/kg DMI) by 15% whereas oils improved the yield of milk fat and protein (kg/d) by 16% and 20%, respectively. On the other hand, concentrate feeding improved dry matter intake and milk yield (g/kg DMI) by 23.4% and 19%, respectively. However, feed efficiency was not affected by any of the dietary rumen modulating strategies. Generally, the use of nitrate, saponin, oils, biochar and 3-NOP were effective as CH4 mitigating strategies, and specifically oils and 3-NOP provided a co-benefit of improving production parameters in ruminant livestock. Equally concentrate feeding improved production parameters in ruminant livestock without any significant effect on enteric methane emission. Therefore, it is advisable to refine further these strategies through life cycle assessment or modelling approaches to accurately capture their influence on farm-scale production, profitability and net greenhouse gas emissions. The adoption of the most viable, region-specific strategies should be based on factors such as the availability and cost of the strategy in the region, the specific goals to be achieved, and the cost–benefit ratio associated with implementing these strategies in ruminant livestock production systems. [ABSTRACT FROM AUTHOR]

Anthropogenic methane emissions are a leading cause of the increase in global average temperatures, often referred to as global warming. Flooded soils play a significant role in methane production, where the anaerobic conditions promote the production of methane by methanogenic microorganisms. Rice fields contribute a considerable portion of agricultural methane emissions, as rice plants provide both factors that enhance and limit methane production. Rice plants harbor both methane- producing and methane-oxidizing microorganisms. Exudates from rice roots provide source for methane production, while oxygen delivered from the root aerenchyma enhances methane oxidation. Studies have shown that the diversity of these microorganisms depends on rice cultivars with some genes characterized as harboring specific groups of microorganisms related to methane emissions. However, there is still a need for research to determine the balance between methane production and oxidation, as rice plants possess the ability to regulate net methane production. Various agronomical practices, such as fertilizer and water management, have been employed to mitigate methane emissions. Nevertheless, studies correlating agronomic and chemical management of methane with productivity are limited. Moreover, evidences for breeding low-methane-emitting rice varieties are scattered largely due to the absence of coordinated breeding programs. Research has indicated that phenotypic characteristics, such as root biomass, shoot architecture, and aerenchyma, are highly correlated with methane emissions. This review discusses available studies that involve the correlation between plant characteristics and methane emissions. It emphasizes the necessity and importance of breeding low-methane-emitting rice varieties in addition to existing agronomic, biological, and chemical practices. The review also delves into the ideal phenotypic and physiological characteristics of low-methane-emitting rice and potential breeding techniques, drawing from studies conducted with diverse varieties, mutants, and transgenic plants. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar (SAR) imagery, notably Sentinel-1A's C-band, VV, and VH polarized SAR, has emerged as a crucial tool for mapping rice fields, especially in regions where cloud cover hinders optical imagery. Employing multi-temporal characteristics, SAR data were regularly collected and parameterized using MAPscape-Rice software, which integrates a fully automated processing chain to convert the data into terrain-geocoded σ° values. This facilitated the generation of rice area maps through a rule-based classifier approach, with classification accuracies ranging from 88.5 to 91.5 and 87.5 percent in 2017, 2018, and 2022, respectively. To estimate methane emissions, IPCC (37.13 kg/ha/season, 42.10 kg/ha/season, 43.19 kg/ha/season) and LST (36.05 kg/ha/season, 41.44 kg/ha/season, 38.07 kg/ha/season) factors were utilized in 2017, 2018 and 2022. Total methane emissions were recorded as 19.813 Gg, 20.661 Gg, and 25.72 Gg using IPCC and 19.155 Gg, 20.373 Gg, and 22.76 Gg using LST factors in 2017, 2018 and 2022. Overall accuracy in methane emission estimation, assessed against field observations, ranged from (IPCC) 85.71, 91.32, and 80.25 percent to (LST) 83.69, 91.43, and 84.69 percent for the years 2017, 2018 and 2022, respectively, confirming the efficacy of remote sensing in greenhouse gas monitoring and its potential for evaluating the impact of large-scale water management strategies on methane emissions and carbon credit-based ecosystem services at regional or national levels. [ABSTRACT FROM AUTHOR]

The ongoing yearly rise in worldwide methane (CH4) emissions is mostly due to human activities. Nevertheless, since over half of these emissions are scattered and have a concentration of less than 3% (v/v), traditional physical–chemical methods are not very effective in reducing them. In this context, biotechnologies like biofiltration using methane-consuming bacteria, also known as methanotrophs, offer a cost-efficient and practical approach to addressing diffuse CH4 emissions. The present review describes recent findings in biofiltration processes as one of the earliest biotechnologies for treating polluted air. Specifically, impacts of biotic (such as cooperation between methanotrophs and non-methanotrophic bacteria and fungi) and abiotic factors (such as temperature, salinity, and moisture) that influence CH4 biofiltration were compiled. Understanding the processes of methanogenesis and methanotrophy holds significant importance in the development of innovative agricultural practices and industrial procedures that contribute to a more favourable equilibrium of greenhouse gases. The integration of advanced genetic analyses can enable holistic approaches for unravelling the potential of biological systems for methane mitigation. This study pioneers a holistic approach to unravelling the biopotential of methanotrophs, offering unprecedented avenues for biotechnological applications. [ABSTRACT FROM AUTHOR]

Various grass species with high biomass yield and low moisture demand have been introduced in the rangelands of Kenya to realize increased ruminant productivity that could not be achieved with the low quality of the indigenous grasses. However, this intervention ignores the different methane emission of the indigenous and introduced grasses, a necessary consideration for realizing increased productivity while minimizing greenhouse gas emissions. This study determined in-vitro digestibility and methane emission of three indigenous grasses: Eragrostis superba (E. superba), Cenchrus ciliaris (C. ciliaris), Enteropogon macrostachyus (E. macrostachyus) and two introduced grasses (two varieties of Chloris gayana; Boma rhodes and Extozi rhodes. Samples of these five grasses (whole plant above ground) were collected from established pasture plots in South Eastern rangelands of Kenya. The grass samples were collected at bloom stage using one-meter square quadrats for proximate analysis and determination of neutral detergent fiber (NDF), acid detergent lignin (ADL) and acid detergent fiber (ADF) using AOAC (1990) methods. On average, relative to the indigenous grasses, the introduced grasses were higher in crude protein (74.05 g Kg-1 dry matter (DM) vs. 52.11 g Kg-1 DM), organic matter digestibility 62.7% vs 53.6%) and in NDF (712.7 g Kg-1 DM vs. 708.0 g Kg-1 DM), metabolizable energy (16.35 vs 12.90 MJ/kg DM), methane emission (25.61 ml vs 15.93 ml) but with lower in-vitro-dry matter digestibility 54.24% vs 58.12%. Methane production positively correlated with crude protein, NDF, metabolizable energy, ADF and in-vitro organic matter digestibility. Hence, utilizing the introduced grasses to boost cattle production would achieve increased productivity but a point of concern are the higher methane emissions, not to mention the ecosystem change caused by the introduction of new species, which should affect the sustainability of the rangeland ecosystem. [ABSTRACT FROM AUTHOR]

This study was carried out to determine the effects of adding CuO and ZnO nanoparticles (at levels of 0, 10, and 20 mg of CuO and ZnO nanoparticles in mL rumen fluid) on in vitro gas and methane production of alfalfa (Medicago sativa) hay. Green-synthesized CuO and ZnO nanoparticles were characterized using scanning electron microscope (SEM), Fourier transform infrared (FTIR), energy dispersive X-Ray spectroscopy (EDX), and atomic force microscopy (AFM) microscopes. The use of CuO and ZnO nanoparticles had significant effects on ruminal protozoa colonization, in vitro gas production, and mitigation of methane emission (P < 0.05). The use of CuO nanoparticles led to a decrease in the protozoa population, thus indirectly decreasing the ruminal fermentation. The CuO nanoparticle is not recommended biologically, but ZnO increased protozoa population and gas production; therefore, this nanoparticle could only exert beneficial effects on rumen fermentation and is recommended. [ABSTRACT FROM AUTHOR]

This study explores the carbon stability in the Arctic permafrost following the sea‐level transgression since the Last Glacial Maximum (LGM). The Arctic permafrost stores a significant amount of organic carbon sequestered as frozen particulate organic carbon, solid methane hydrate and free methane gas. Post‐LGM sea‐level transgression resulted in ocean water, which is up to 20°C warmer compared to the average annual air mass, inundating, and thawing the permafrost. This study develops a one‐dimensional multiphase flow, multicomponent transport numerical model and apply it to investigate the coupled thermal, hydraulic, microbial, and chemical processes occurring in the thawing subsea permafrost. Results show that microbial methane is produced and vented to the seawater immediately upon the flooding of the Arctic continental shelves. This microbial methane is generated by the biodegradation of the previously frozen organic carbon. The maximum seabed methane flux is predicted in the shallow water where the sediment has been warmed up, but the remaining amount of organic carbon is still high. It is less likely to cause seabed methane emission by methane hydrate dissociation. Such a situation only happens when there is a very shallow (∼200 m depth) intra‐permafrost methane hydrate, the occurrence of which is limited. This study provides insights into the limits of methane release from the ongoing flooding of the Arctic permafrost, which is critical to understand the role of the Arctic permafrost in the carbon cycle, ocean chemistry and climate change. Plain Language Summary: Arctic permafrost stores ∼1,700 billion tons of organic carbon. If just a fraction of that melts, the escaping methane would become one of the world's largest sources of greenhouse gas and would severely impact the environment and the climate. Over the last ∼18,000 years, a quarter of the stored organic carbon in the Arctic permafrost has been flooded by the rising, warm seas. This has melted the ice and degraded the permafrost. But what happens to the carbon pools? This study investigates the stability of the carbon in the Arctic permafrost following the flooding using a newly developed numerical model. Results show that microbial methane is generated and emitted to the seawater immediately following the flooding. This methane is produced by the biodegradation of the previously frozen organic carbon near the seafloor. The maximum methane emission is predicted in the shallow water near the coast where the sediment has been warmed up, but the remaining amount of organic carbon is still high. This study provides insights into the limits of methane release from the ongoing flooding of the Arctic permafrost, which is critical to understand the role of the Arctic permafrost in the carbon cycle, ocean chemistry and climate change. Key Points: A numerical model is developed to simulate the coupled thermal, hydraulic, microbial and chemical processes in the thawing subsea permafrostThe biodegradation of the ancient organic carbon in the thawing subsea permafrost results in seabed microbial methane emissionSeabed methane emission is less likely to be caused by methane hydrate dissociation at the Arctic continental shelves [ABSTRACT FROM AUTHOR]

Abstract 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.

Abstract 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.

Methane metabolism, driven by methanogenic and methanotrophic microorganisms, plays a pivotal role in the carbon cycle. As seawater intrusion and soil salinization rise due to global environmental shifts, understanding how salinity affects methane emissions, especially in deep strata, becomes imperative. Yet, insights into stratigraphic methane release under varying salinity conditions remain sparse. Here we investigate the effects of salinity on methane metabolism across terrestrial and coastal strata (15–40 m depth) through in situ and microcosm simulation studies. Coastal strata, exhibiting a salinity level five times greater than terrestrial strata, manifested a 12.05% decrease in total methane production, but a staggering 687.34% surge in methane oxidation, culminating in 146.31% diminished methane emissions. Salinity emerged as a significant factor shaping the methane-metabolizing microbial community's dynamics, impacting the methanogenic archaeal, methanotrophic archaeal, and methanotrophic bacterial communities by 16.53%, 27.25%, and 22.94%, respectively. Furthermore, microbial interactions influenced strata system methane metabolism. Metabolic pathway analyses suggested Atribacteria JS1's potential role in organic matter decomposition, facilitating methane production via Methanofastidiosales. This study thus offers a comprehensive lens to comprehend stratigraphic methane emission dynamics and the overarching factors modulating them.

A two-chamber slurry microbial fuel cell (SMFC) was constructed using black-odorous river sediments as substrate for the anode. We tested addition of potassium ferricyanide (K3[Fe(CN)6]) or sodium chloride (NaCl) to the cathode chamber (0, 50, 100, 150, and 200 mM) and aeration of the cathode chamber (0, 2, 4, 6, and 8 h per day) to assess their response on electrical generation, internal resistance, and methane emission over a 600-h period. When the aeration time in the cathode chamber was 6 h and K3[Fe(CN)6] or NaCl concentrations were 200 mM, the highest power densities were 6.00, 6.45, and 6.64 mW·m-2, respectively. With increasing K3[Fe(CN)6] or NaCl concentration in the cathode chamber, methane emission progressively decreased (mean ± SD: 181.6 ± 10.9 → 75.5 ± 9.8 mg/m3·h and 428.0 ± 28.5 → 157.0 ± 35.7 mg/m3·h), respectively, but was higher than the reference having no cathode/anode electrodes (~ 30 mg/m3·h). Cathode aeration (0 → 8 h/day) demonstrated a reduction in methane emission from the anode chamber for only the 6-h treatment (mean: 349.6 ± 37.4 versus 299.4 ± 34.7 mg/m3·h for 6 h/day treatment); methane emission from the reference was much lower (85.3 ± 26.1 mg/m3·h). Our results demonstrate that adding an electron acceptor (K3[Fe(CN)6]), electrolyte solution (NaCl), and aeration to the cathode chamber can appreciably improve electrical generation efficiency from the MFC. Notably, electrical generation stimulates methane emission, but methane emission decreases at higher power densities.

Objective: This research aimed to evaluate potential tropical seaweed from Indonesia as an ingredient or supplement feed for ruminants based on chemical composition and in vitro rumen fermentation parameters. Materials and methods: The seven natural tropical seaweeds (three green and four red species) were collected from Ndrini and Sepanjang Beach, Gunungkidul, Yogyakarta, Indonesia. The experimental design on secondary metabolite profiles used a completely randomized design, and the in vitro gas production test used a randomized complete block design with seven seaweed species variances and four replications (blocks) based on rumen fluid collection time. The data obtained was analyzed using analysis of variance (ANOVA), and Duncan‘s Multiple Range Test was used to test the variation in the analysis. Results: The seven tropical seaweed species have potential as mineral sources for ruminants, except for macromineral (P and S) and micromineral (Cu). The red tropical seaweed has potential as a protein source (Gelidium spinosum (S.G.Gmelin) P.C. Silva, Hypnea pannosa, and Acanthopora muscoides (L.) Bory), and the green seaweed (Chaetomorpha linum (O.F. Mull.) Kutz and Cladopora sp.) has potential as a crude fiber (CF) source for ruminants. As indicated by secondary metabolites and gas production in vitro, the green species (C. linum (O.F. Mull.) Kutz and Enteromorpha compressa) and red species (A. muscoides (L.) Bory and Gelidium amansii (J.V. Lamouroux) J.V. Lamouroux) could be degraded in the rumen and had quite high phenolic compounds. Conclusion: The seven tropical seaweed species have the potential to be an ingredient or supplement feed for ruminants, and there were four species that have the potential to reduce methane emissions. [J Adv Vet Anim Res 2023; 10(4.000): 751-762]

Tea waste (TW) has a protein content of approximately 30% and the potential to replace other protein sources. However, the effect of dietary TW supplement is still ambiguous. The objective of this study was to investigate the effect of three levels of a dietary TW supplement on the performances and physiological changes in goats. Nine multiparous crossbred Saanen lactating goats were arranged in three replicates of a 3 × 3 Latin square. The three groups of goats were fed with 0, 5, or 10 by weight [wt%] dry matter [DM] basis TW, respectively, for a 21-day period. All diets were a total mixed ration (TMR) containing a 40:60 (DM basis) ratio of concentrate: roughage. The goats were weighed at 15 and 21 days. Faeces and urine were collected during the last 7 days of each period. The TW addition had no effect on the DM intake (DMI), DMI% and body weight. The milk protein content in goats on a 10 wt% TW diet was significantly higher (p

The warming impact of methane (CH4) emissions calculated using the metrics proposed by the Intergovernmental Panel on Climate Change (IPCC), which measure its global warming potential in 100 years (GWP100) expressed as carbon dioxide equivalents (CO2e), accounts for the greatest impact in animal production chains. This work uses the new metrics, proposed to consider the difference between short living climate pollutants (SLCP), such as CH4, and long living climate pollutants (LLCP), such as carbon dioxide (CO2), which measure the warming equivalent (we) effect relative to that of CO2 in a given time frame (GWP*) and expressed as CO2we. The GWP* was applied to CH4 emissions from all Italian livestock supply chains and compared with GWP100 for annual and cumulative assessment from 2010 to 2020 of the impact of this gas on climate change. Using official data published by Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA) from 1990 to 2020, almost all species, except for buffalo (+272.6% of emissions calculated with the new metrics), revealed lower CH4 emissions with the greatest re-dimensioning for non-dairy cattle (-53786 kt of CO2we of calculated with GWP* compared to +66437 kt of CO2e estimated with the GWP100 method). The total cumulative contribution of Italian livestock production to global warming over the past 10 years, including the nitrous oxide (N2O) emissions, has been greatly negative (-48759 kt of CO2we) compared to the data calculated using the GWP100 method (+206091 kt of CO2e). In conclusion, the application of GWP* metric to CH4 emissions of all Italian livestock supply chains allowed to better identify the role of Italian livestock on climate change. Over the 2010–2020 time frame, the Italian animal supply chains reduced the warming impact related to its CH4 emission, with the ruminants (expect buffaloes) being the major contributor to this positive effect.HIGHLIGHTS The application of GWP* metric reduced the warming impact of CH4 emissions of Italian dairy cattle, non-dairy cattle, sheep, goats, poultry and rabbits. The reduction of CH4 emission from the major ruminant species is the major contributor to the positive effect on climate change detected over 2010–2020 time frame. The application of GWP* metric to CH4 emissions of all Italian livestock supply chains allowed to better identify the role of Italian livestock on climate change.

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 (3. 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.

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.

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: This study aimed to evaluate trade-offs between enteric and manure CH4 emissions, and the size of synergistic effects for CH4 and nitrogenous emissions (NH3 and N2O). Sixty-four Holstein-Friesian cows were blocked in groups of 4 based on parity, lactation stage, and milk yield. Cows within a block were randomly allocated to a dietary sequence in a crossover design with a grass silage-based diet (GS) and a corn silage-based diet (CS). The GS diet consisted of 50% grass silage and 50% concentrate, and CS consisted of 10% grass silage, 40% corn silage, and 50% concentrate (dry matter basis). The composition of the concentrate was identical for both diets. Cows were housed in groups of 16 animals, in 4 mechanically ventilated barn units for independent emission measurement. Treatment periods were composed of a 2-wk adaptation period followed by a 5-wk measurement period, 1 wk of which was without cows to allow separation of enteric and manure emissions. In each barn unit, ventilation rates and concentrations of CH4, CO2, NH3, and N2O in incoming and outgoing air were measured. Cow excretion of organic matter was higher for CS compared with GS. Enteric CH4 and cow-associated NH3 and N2O emissions (i.e., manure emissions excluded) were lower for CS compared with GS (−11, −40, and −45%, respectively). The CH4 and N2O emissions from stored manure (i.e., in absence of cows) were not affected by diet, whereas that of NH3 emission tended to be lower for CS compared with GS. In conclusion, there was no trade-off between enteric and manure CH4 emissions, and there were synergistic effects for CH4 and nitrogenous emissions when grass silage was exchanged for corn silage, without balancing the diets for crude protein content, in this short-term study.

The addition of antibiotics as growth promoters to ruminant feed can result in bacterial resistance and antibiotic residues in ruminant products. Correspondingly, there is serious public concern regarding the presence of antibiotic residue in ruminant products and the consequent threat to human health. As a result, the addition of plants and their products to ruminant feeds, as an alternative to antibiotics, has received much attention recently. Garlic and its products are rich in organosulphur compounds, which have a variety of biological activities and have been widely used as natural additives in animal production. This review presents recent knowledge on the addition of garlic products (powder, skin, oil, leaf and extracts) to the diets of ruminants. In this paper, garlic products are evaluated with respect to their chemical composition, bioactive compounds, and their impacts on the rumen ecosystem, antioxidant status, immune response, parasitic infection, growth performance and product quality of ruminants. This review provides valuable guidance and a theoretical basis for the development of garlic products as green, highly efficient and safe additives, with the aims of promoting ruminant growth and health, reducing methane emissions and improving ruminant product quality. Garlic extracts have the potential to control parasite infections by decreasing the faecal egg count. Garlic powder, oil and allicin are able to reduce the methane emissions of ruminants. Organosulphur compounds such as allicin, which is present in garlic products, have the potential to inhibit membrane lipid synthesis of the archaeal community, thus influencing the population of methanogenic archaea and resulting in a reduction in methane emissions. Some garlic products are also able to increase the average daily gain (garlic skin, water extract, and leaf) and the feed conversion ratio (garlic skin and leaf) of ruminants. Garlic stalk silage fed to sheep has the potential to improve the nutritional value of mutton by increasing the concentrations of linoleic and linolenic acids and essential amino acids. Sheep fed a diet containing garlic powder or oil are able to produce milk with higher concentrations of the conjugated linoleic acids and n-3 fatty acids, which has health benefits for consumers, due to the widely recognized positive impact of n-3 polyunsaturated fatty acids and conjugated linoleic acids on human heart health, improving platelet aggregation, vasodilation and thrombotic tendency. Overall, garlic products have the potential to enhance growth performance and product quality and reduce parasite infections, as well as methane emissions of ruminants.

Shale gas is an important alternative natural gas source that can meet China's growing energy demand. However, methane emissions during shale gas production could largely determine whether it could be considered as a bridging clean energy source. In this study, we performed methane emission measurements using three methods (on-site optical gas imaging, on-site methane patrolling, and downwind measurement) at shale gas production sites in Sichuan province, China, covering 18 well sites with 81 wells. The results showed that flowback water tanks were the major methane sources, with valves, separators, chemical injection pumps, and pneumatic controllers as other sources. The methane concentrations inside the 18 sites ranged from 1.42 to 459 μmol mol−1, with over 59% of the sites having the highest concentration less than 50 μmol mol−1. The optical gas imaging method, with its low detection limit over 5000 μmol mol−1, could not capture the emission effectively. The three successful downwind measurements resulted in site level emission rates between 0.02 and 0.17 kg h−1. When divided by the number of wells at each site, the emission intensity was 4%–28% of the wellhead emission factor for natural gas production in China. More measurements are required to better quantify methane emissions from shale gas sites in China. For sites in mountainous regions or long-term low-wind regions, detection methods other than downwind measurements should be suitable for quantifying site-level emissions.

A global effort towards improved quantitative understanding of greenhouse gas emissions is taking pace. This includes developing source identification, quantification, and apportionment in an attempt to understand global budget and trends, but also developing monitoring systems making emission reduction commitment verifiable. In this context, we demonstrate a novel approach to continuous methane emission monitoring at the spatial scale of an industrial facility. By combining multi-directional measurements of path-integrated methane concentrations with Bayesian state estimation, we show a realistic tomographic gas plume reconstruction, its evolution in time, and the associated estimation of the source map. The method is validated using measurements from controlled methane releases over a domain of area 120×40 m2. For the first demonstration, a two dimensional geometry has been used in the gas flow model; nevertheless, sources are located within 3–12 meters, and mass emission rates are estimated within

Relevance. The lack of elemental speciation data in the bottom sediments of the Laptev Sea, as well as the absence of its quantitative changes in occurrence forms in response to methane emissions. Aim. To assess changes in the elemental speciation in areas where methane-containing fluids are discharged. Objects. Nine samples of bottom sediments taken from three horizons of one “cold seep” and two background stations of the outer shelf-continental slope of the Laptev Sea during the AMK-82 expedition aboard R/V “Academician M.V. Keldysh” in autumn 2020. Methods. Sequential extraction BCR (the European Community Bureau of Reference) was performed to determine the elemental speciation in surface sediments; the residual fraction was determined by dissolving in nitric acid. The obtained fraction solutions were analyzed by ICP-MS (NexIon 300D, Perkin Elmer, Waltham, MA, USA), Pyrolysis (Rock-Eval 6 Turbo, Vinci Technologies). Results. The trend towards an increase in element mobility has been identified as a result of a shift in geochemical conditions that is presumably caused by the authigenic carbonate and sulfide formation. Moreover, the increase in the recoverable fraction (associated only with Fe oxides/hydroxides) is highlighted. We assume that the process of unloading methane-containing fluids plays a significant role in enrichment of authigenic carbonates U, Ni, Zn Co, oxides Fe – Sn and V, authigenic sulfides – Co, Mn and W. We also assume the potential formation of chalcopyrite as an authigenic sulfide in methane discharge areas.

This study proposed a method for measuring the methane (CH4)/carbon dioxide (CO2) ratio from individual beef cattle under on‐farm conditions and estimated the variance components of the CH4/CO2 ratio. Gas measurements were conducted using 166 Japanese Black cattle group‐housed in pens equipped with individual feed bins. The gas containing the animal's breath was measured individually after concentrate feeding by covering the feed bin with a sheet with sampling inlets. Measurements were performed six times (three consecutive days, twice daily) per individual. Most of the sampled gas contained more than 1000 ppm of the mean background‐corrected CO2, suggesting that the method proposed in this study successfully collected sufficient breath concentration to accurately measure the CH4/CO2 ratio. The between‐animal variance accounted for 31.7% of the total variance in the CH4/CO2 ratio. The results showed that the gas collection method proposed in this study could be a useful tool for measuring the CH4/CO2 ratio under on‐farm conditions. The variance component obtained from this study will help to establish protocols for generating data for genetic evaluation and performing dietary experiments with sufficient statistical power. [ABSTRACT FROM AUTHOR]

Submarine fluid flow system can transport methane into ocean. However, its evolution is not fully understood, particularly methane migration through the gas hydrate stability zone (GHSZ) in deep-water settings. Here, we used 3D seismic and well-logging data to show the currently active fluid flow system in the northern South China Sea. It was interpreted to have two parts and they together feed intermittent methane emission. Three gas clouds have been seismically imaged beneath the base of gas hydrate stability zone (BGHSZ) and a set of new faults can be identified within them. Twenty-eight seismic pipes were found to penetrate three vertically stacked mass transport deposits (MTDs) above the gas clouds. Log-seismic correlation shows that the seismic reflections in the pipe represent MTD sediment, bulk carbonate and gas hydrate- or free gas-bearing sediments. We interpreted faults and pipes as the main migration conduits below and above the BGHSZ respectively. The MTD within the GHSZ could seal the underlying free gas transported by faults and thus overpressure built up at the base prior to the occurrences of the pipes and the fracturing through the overlying sedimentary succession. Subsequently, focused fluid flow entered the GHSZ, with the methane probably bypassing the GHSZ before pore clogging of gas hydrates occurred. Additionally, mapping of high-amplitude reflections surrounding the upper portion of gas clouds reveals the relict free gas associated with three paleo-GHSZ bases. Episodic emplacements of new MTDs repeatedly caused the upward shifts of the BGHSZ and the resultant gas hydrate dissociation, contributing to methane emission. We proposed that the occurrences of MTDs may facilitate methane emission by intermittently trapping methane and inducing gas hydrate dissociation in deep-water settings. [ABSTRACT FROM AUTHOR]