Transcriptomics- and FAME-GC-MS-assisted apomixis breeding generated Paspalum notatum hybrids with clonal reproduction and increased α-linolenic acid content, offering the potential to enhance livestock product's nutritional quality and reduce methane emissions A low omega-6:omega-3 fatty acid ratio is considered an indicator of the nutritional impact of milk fat on human health. In ruminants, major long-chain fatty acids, such as linoleic acid (18:2, omega-6) and α-linolenic acid (18:3, omega-3), originate from dietary sources and reach the milk via the bloodstream. Since forages are the primary source of long-chain fatty acids for such animals, they are potential targets for improving milk lipid composition. Moreover, a high 18:3 content in their diet is associated with reduced methane emissions during grazing. This work aimed to develop genotypes of the forage grass Paspalum notatum with high leaf 18:3 content and the ability for clonal reproduction via seeds (apomixis). We assembled diploid and polyploid Paspalum notatum leaf transcriptomes and recovered sequences of two metabolism genes associated with the establishment of lipid profiles, namely SUGAR-DEPENDENT 1 (SDP1) and PEROXISOMAL ABC TRANSPORTER 1 (PXA1). Primers were designed to amplify all expressed paralogs in leaves. qPCR was used to analyse SDP1 and PXA1 expression in seven divergent genotypes. Reduced levels of SDP1 and PXA1 were found in the polyploid sexual genotype Q4188. Fatty acid methyl esters/gas chromatography/mass spectrometry (FAME/GC/MS) assays confirmed an increased percentage of 18:3 in this genotype. Crosses between Q4188 and the obligate apomictic pollen donor Q4117 resulted in two apomictic F hybrids (JS9 and JS71) with reduced SDP1 and PXA1 levels, increased 18:3 content, and clonal maternal reproduction. These materials could enhance milk and meat quality while reducing greenhouse gas emissions during grazing.

The development of new measurement methods to assess fugitive methane (CH) emissions from industrial sources is needed to improve our understanding of these emissions and promote mitigation practices. Drone-based measurement methods have rapidly emerged in the last few years, however, there are still challenges in finding accurate drone-based measurement approaches and assessing their suitability. This study aims to validate and demonstrate a drone-based method that simultaneously measures atmospheric gas concentrations and wind vectors while flying downwind of the emission source. During the development phase, several tests were performed to ensure that the wind sensor was placed avoiding the majority of downwash and backwash interference. Comparing wind measurements taken at two wind masts and on a mast and a drone produced similar results, thus supporting the reliability of drone-based wind measurements. Moreover, the drone flux method (DFM) was validated by quantifying CH emissions from controlled release tests (2.18 or 3.59 kg h) and the release mimicked (1) a ground-based single source, (2) a ground-based double source and (3) an elevated single source. The DFM results had error rates ranging from +33 to -35%. The DFM was further used to assess emissions from a biogas plant, with simultaneous measurements using the tracer gas dispersion method (TDM). During the same time interval, the DFM quantified the biogas plant emitting CH at a rate of 25.3 ± 6.2 kg h, while the TDM averaged 25.7 ± 4.4 kg h. The method expanded uncertainty (95% confidence interval) assessment was 46% for the controlled release test for single flights quantification. By increasing the number of flights, the uncertainty theoretically decreased to 33% and to 27% for averages of 2 or 3 flights, respectively. Wind sensitivity analysis revealed the importance of assessing wind speed reliably, considering the measured plume height and atmospheric conditions; otherwise, significant errors in the emission determination can occur.

Methane emissions from livestock contribute to global warming. Seaweeds used as food additive offer a promising emission mitigation strategy because seaweeds are enriched in bromoform─a methanogenesis inhibitor. Therefore, understanding bromoform storage and production in seaweeds and particularly in a cell-like environment is crucial. As a first step toward this aim, we present an atomistic description of bromoform dynamics, diffusion, and aggregation in the presence of lipid membranes. Using all-atom molecular dynamics simulations with customized CHARMM-formatted bromoform force field files, we investigate the interactions of bromoform and lipid bilayer across various concentrations. Bromoform penetrates membranes and at high concentrations forms aggregates outside the membrane without affecting membrane thickness or lipid tail order. Aggregates outside the membrane influence the membrane curvature. Within the membrane, bromoform preferentially localizes in the membrane hydrophobic core and diffuses the slowest along the membrane normal. Employing general local-atomic descriptors and unsupervised machine learning, we demonstrate the similarity of bromoform local structures between the liquid and aggregated forms.

Rewetting peatlands is required to limit carbon dioxide (CO) emissions, however, raising the groundwater level (GWL) will strongly increase the chance of methane (CH) emissions which has a higher radiative forcing than CO. Data sets of CH from different rewetting strategies and natural systems are scarce, and quantification and an understanding of the main drivers of CH emissions are needed to make effective peatland rewetting decisions. We present a large data set of CH fluxes (FCH) measured across 16 sites with eddy covariance on Dutch peatlands. Sites were classified into six land uses, which also determined their vegetation and GWL range. We investigated the principal drivers of emissions and gapfilled the data using machine learning (ML) to derive annual totals. In addition, Shapley values were used to understand the importance of drivers to ML model predictions. The data showed the typical controls of FCH where temperature and the GWL were the dominant factors, however, some relationships were dependent on land use and the vegetation present. There was a clear average increase in FCH with increasing GWLs, with the highest emissions occurring at GWLs near the surface. Soil temperature was the single most important predictor for ML gapfilling but the Shapley values revealed the multi-driver dependency of FCH. Mean annual FCH totals across all land uses ranged from 90 11 to 632 65 kg CH ha year and were on average highest for semi-natural land uses, followed by paludiculture, lake, wet grassland and pasture with water infiltration system. The mean annual flux was strongly correlated with the mean annual GWL (R = 0.80). The greenhouse gas balance of our sites still needs to be estimated to determine the net climate impact, however, our results indicate that considerable rates of CO uptake and long-term storage are required to fully offset the emissions of CH from land uses with high GWLs.

The increase in atmospheric methane (CH) level directly contributes to approximately one-fifth of global mean temperature rise since preindustrial era, only next to CO. Global anthropogenic CH emissions has augmented by nearly three-fifths during the past five decades; due to climate change, natural CH emissions are plausibly projected to increase in the foreseeable future. Thereby, examining and projecting long-term natural and anthropogenic CH emissions and sinks are imperative. According to peer-reviewed literatures as information sources for this compendium, we recapitulate natural and anthropogenic CH emissions, summarize available abatement approaches and their mitigation potentials, and investigate and encapsulate economic costs and social benefits of reductions. We list current challenges in realizing CH emissions reductions and suggest possible technical pathways for future mitigation.

In recent years, marine macroalgae have been recognized as potential alternative and sustainable feeding resources for livestock. Differences in nutritional values and biomass yield across macroalgal species are critical factors while aiming to utilize them as animal feed components. A brown macroalga, , also known as sugar kelp, has a promising biomass yield and high nutritional and bioactive compounds that can benefit both ruminant and monogastric animals. For example, the dietary inclusion of in dairy and beef cattle can enhance milk yield, meat quality, and iodine content in milk and meat while reducing enteric methane emissions in vitro. However, high iodine content and the presence of some potentially toxic elements (arsenic, cadmium, etc.) lead to critical challenges, demanding careful consideration while determining the inclusion level of in the livestock feed. To address these challenges, effective post-harvest biomass processing techniques, particularly hydrothermal treatments, have shown promise in reducing heavy metals and minerals of concern (e.g., iodine) and enhancing their safety as animal feed. It is thus essential to evaluate the sustainability of post-harvest processing techniques as they are usually energy-demanding and can negatively influence nutrient utilization in animals as certain digestible fractions can disappear during processing. Furthermore, variations in the nutritional and bioactive composition of due to seasonal and spatial factors can create challenges for commercial exploitation. In this context, multiple harvesting of biomass and choosing the appropriate harvesting seasons can maximize the nutritional potential of . In conclusion, can be a novel feed ingredient for livestock, but year-round biomass availability and identifying cost-effective and energy-efficient post-harvest biomass processing methods that optimize both nutritional values and digestibility of are critical for improving animal production, performance, and health.

We estimate methane emissions rates for urban waste treatment facilities from mobile in situ atmospheric concentration measurements using an inverse Gaussian plume methodology at facilities in Southern Ontario, Canada. We use these estimated emissions rates to investigate, update, and improve the existing high resolution methane inventories at the facility level for waste sources throughout the Greater Toronto Area and Southwestern Ontario. Our measurements encompass tens of thousands of kilometers worth of mobile survey data collected over 7 years, encompassing more than 650 downwind transects where we surveyed 14 active landfills, 11 closed landfills, 2 organic waste processing facilities, 3 open air windrow compost facilities, and 11 water resource recovery facilities across our study region. These sources account for 77% of the active landfills within Southern Ontario, which is estimated in inventories to be the largest source of methane emissions in the region. Within the Greater Toronto Area (GTA) megacity, the measured facilities represent about 52% of the total inventoried non-wetland methane emissions. We find that emissions from closed landfills are lower than inventory estimates, with significant implications for the methane budget in the GTA. We update the Facility Level and Area Methane Emissions for the GTA inventory with our measured emissions rates, which results in a 54% decline in the solid waste emissions, effecting a 35% lower estimate for the total anthropogenic methane emissions in the region. We attribute the bulk of this difference to a single facility: the Keele Valley landfill. Our atmospheric measurements also serve as a novel metric for evaluating the discrepancies between four facility level, and two high resolution gridded methane emissions inventories. Based on linear regressions of our measured emissions versus inventoried values, we find that the facility level first order decay model maintained by Environment and Climate Change Canada (ECCC) to be the most consistent with our measured emissions rates at landfills and the self-reported emissions to the Greenhouse Gas Reporting Program of ECCC to be the least consistent with our measurements.

Biochar has gained significant attention as a possible anti-methanogenic supplement for ruminants due to its potential to reduce methane (CH₄) emissions from enteric fermentation. However, its effects on rumen methanogenesis have been inconsistent and, in some cases, contradictory. These variations are likely influenced by factors such as the type of biochar used, its source material, and how it is administered, including the form in which it is provided and the dosage needed to achieve desired outcomes. This study aimed to examine the effects of two fit-for-purpose biochars on rumen fermentation, CH emissions, and the rumen microbiome of cattle-fed roughage-based diets. Two experiments were conducted to assess the potential of biochar in mitigating CH emissions.

Microbial methane oxidation plays a significant role in regulating methane emissions from lakes and reservoirs. However, the differences in methane oxidation activity and methanotrophic community between lakes and reservoirs remain inadequately characterized. In this study, sediment and water samples were collected from the large shallow lake (Dianchi) and deep reservoirs (Dongfeng and Hongjiadu) located in karst area, Southwest China. The results indicated that the rates of aerobic oxidation of methane (AeOM) in lake sediment ranged from 7.1 to 27.7 μg g d, which was higher than that in reservoirs sediment (1.92 to 11.56 μg g d). Similarly, the average AeOM in the water column of lake (104.7 μg L d) was much higher than that of reservoirs (46 μg L d). The content of sediment organic carbon and dissolved inorganic carbon were important factors that influenced the rates of AeOM in sediment and water column, respectively. 16S rRNA genes sequencing revealed a higher relative abundance of methanotrophs in lake sediments compared to reservoir sediments. The dominant methanotrophic taxa in lake was Methylococcaceae (type Ib), while Methylomonadaceae (type Ia) was predominant in reservoirs. Meanwhile, anaerobic methane-oxidizing microorganisms Candidatus Methylomirabilis and Candidatus Methanoperedens were also abundant in sediments of reservoirs. However, metatranscriptomic analysis revealed that the type I methanotrophs, especially Methylobacter, was most active in the sediment of both lake and reservoir. Water depth and conductivity could be the key controlling factors of the structures of methanotrophic communities in sediment and water column, respectively. Metagenome-assembled genomes suggested that type I methanotrophs exhibited greater motility, as evidenced by a higher number of flagellar assembly genes, while type II methanotrophs demonstrated advantages in metabolic processes such as carbon, phosphorus, and methane metabolism.

Reducing water input and promoting water productivity in rice field under alternate wetting and drying irrigation (AWD), instead of continuous flooding (CF), are vital due to increasing irrigation water scarcity. However, it is also important to understand how methane (CH) and nitrous oxide (NO) emissions and global warming potential ( of CH and NO) respond to AWD under the influence of various factors. Here, we conducted a meta-analysis to investigate the impact of AWD on CH and NO emissions and , and its modification by climate conditions, soil properties, and management practices. Overall, compared to CF, AWD significantly reduced CH emissions by 51.6% and by 46.9%, while increased NO emissions by 44.0%. The effect of AWD on CH emissions was significantly modified by soil drying level, the number of drying events, mean annual precipitation (MAP), soil organic carbon content (SOC), growth cycle, and nitrogen fertilizer (N) application. Regarding NO emissions, mean annual temperature (MAT), elevation, soil texture, and soil pH had significant impacts on the AWD effect. Consequently, the under AWD was altered by soil drying level, soil pH, and growth cycle. Additionally, we found that MAP or MAT can be used to accurately assess the changes of global or national CH and NO emissions under mild AWD. Moreover, increasing SOC, but not N application, is a potential strategy to further reduce CH emissions under (mild) AWD, since no difference was found between application of 60-120 and > 120 kg N ha. Furthermore, the soil pH can serve as an indicator to assess the reduction of under (mild) AWD as indicated by a significant linear correlation between them. These findings can provide valuable data support for accurate evaluation of non-CO greenhouse gas emissions reduction in rice fields under large-scale promotion of AWD in the future.