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Mitigating climate change requires a diverse portfolio of technologies and approaches, including negative emissions or removal of greenhouse gases. Previous literature focuses primarily on carbon dioxide removal, but methane removal may be an important complement to future efforts. Methane removal has at least two key benefits: reducing temperature more rapidly than carbon dioxide removal and improving air quality by reducing surface ozone concentration. While some removal technologies are being developed, modelling of their impacts is limited. Here, we conduct the first simulations using a methane emissions-driven Earth System Model to quantify the climate and air quality co-benefits of methane removal, including different rates and timings of removal. We define a novel metric, the effective cumulative removal, and use it to show that each effective petagram of methane removed causes a mean global surface temperature reduction of 0.21 ± 0.04°C and a mean global surface ozone reduction of 1.0 ± 0.2 parts per billion. Our results demonstrate the effectiveness of methane removal in delaying warming thresholds and reducing peak temperatures, and also allow for direct comparisons between the impacts of methane and carbon dioxide removal that could guide future research and climate policy. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Methane mitigation is essential for addressing climate change, but the value of rapidly implementing available mitigation measures is not well understood. In this paper, we analyze the climate benefits of fast action to reduce methane emissions as compared to slower and delayed mitigation timelines. We find that the scale up and deployment of greatly underutilized but available mitigation measures will have significant near-term temperature benefits beyond that from slow or delayed action. Overall, strategies exist to cut global methane emissions from human activities in half within the next ten years and half of these strategies currently incur no net cost. Pursuing all mitigation measures now could slow the global-mean rate of near-term decadal warming by around 30%, avoid a quarter of a degree centigrade of additional global-mean warming by midcentury, and set ourselves on a path to avoid more than half a degree centigrade by end of century. On the other hand, slow implementation of these measures may result in an additional tenth of a degree of global-mean warming by midcentury and 5% faster warming rate (relative to fast action), and waiting to pursue these measures until midcentury may result in an additional two tenths of a degree centigrade by midcentury and 15% faster warming rate (relative to fast action). Slow or delayed methane action is viewed by many as reasonable given that current and on-the-horizon climate policies heavily emphasize actions that benefit the climate in the long-term, such as decarbonization and reaching net-zero emissions, whereas methane emitted over the next couple of decades will play a limited role in long-term warming. However, given that fast methane action can considerably limit climate damages in the near-term, it is urgent to scale up efforts and take advantage of this achievable and affordable opportunity as we simultaneously reduce carbon dioxide emissions.

While methane is the second largest contributor to global warming after carbon dioxide, it has a larger warming effect over a much shorter lifetime. Despite accelerated technological efforts to radically reduce global carbon dioxide emissions, rapid reductions in methane emissions are needed to limit near-term warming. Being primarily emitted as a byproduct from agricultural activities and energy extraction, methane is currently monitored via bottom–up (i.e. activity level) or top–down (via airborne or satellite retrievals) approaches. However, significant methane leaks remain undetected and emission rates are challenging to characterize with current monitoring frameworks. In this paper, we study the design of a layered monitoring approach that combines bottom–up and top–down approaches as an integrated sensing network. By recognizing that varying meteorological conditions and emission rates impact the efficacy of bottom–up monitoring, we develop a probabilistic approach to optimal sensor placement in its bottom–up network. Subsequently, we derive an inverse Bayesian framework to quantify the improvement that a design-optimized integrated framework has on emission-rate quantifications and their uncertainties. We find that under realistic meteorological conditions, the overall error in estimating the true emission rates is approximately 1.3 times higher, with their uncertainties being approximately 2.4 times higher, when using a randomized network over an optimized network, highlighting the importance of optimizing the design of integrated methane sensing networks. Further, we find that optimized networks can improve scenario coverage fractions by more than a factor of 2 over experimentally-studied networks, and identify a budget threshold beyond which the rate of optimized-network coverage improvement exhibits diminishing returns, suggesting that strategic sensor placement is also crucial for maximizing network efficiency.

The growing demand for sustainable animal production is compelling researchers to explore the potential approaches to reduce emissions of greenhouse gases from livestock that are mainly produced by enteric fermentation. Some potential solutions, for instance, the use of chemical inhibitors to reduce methanogenesis, are not feasible in routine use due to their toxicity to ruminants, inhibition of efficient rumen function or other transitory effects. Strategies, such as use of plant secondary metabolites and dietary manipulations have emerged to reduce the methane emission, but these still require extensive research before these can be recommended and deployed in the livestock industry sector. Furthermore, immunization vaccines for methanogens and phages are also under investigation for mitigation of enteric methanogenesis. The increasing knowledge of methanogenic diversity in rumen, DNA sequencing technologies and bioinformatics have paved the way for chemogenomic strategies by targeting methane producers. Chemogenomics will help in finding target enzymes and proteins, which will further assist in the screening of natural as well chemical inhibitors. The construction of a methanogenic gene catalogue through these approaches is an attainable objective. This will lead to understand the microbiome function, its relation with the host and feeds, and therefore, will form the basis of practically viable and eco-friendly methane mitigation approaches, while improving the ruminant productivity.

Anthropomorphic greenhouse gases are raising the temperature of the earth and threatening ecosystems. Since 1950 atmospheric carbon dioxide has increased 28%, while methane has increased 70%. Methane, over the first 20 years after release, has 80-times more warming potential as a greenhouse gas than carbon dioxide. Enteric methane from microbial fermentation of plant material by ruminants contributes 30% of methane released into the atmosphere, which is more than any other single source. Numerous strategies were reviewed to quantify their methane mitigation potential, their impact on animal productivity and their likelihood of adoption. The supplements, 3-nitrooxypropanol and the seaweed, Asparagopsis, reduced methane emissions by 40+% and 90%, respectively, with increases in animal productivity and small effects on animal health or product quality. Manipulation of the rumen microbial population can potentially provide intergenerational reduction in methane emissions, if treated animals remain isolated. Genetic selection, vaccination, grape marc, nitrate or biochar reduced methane emissions by 10% or less. Best management practices and cattle browsing legumes, Desmanthus or Leucaena species, result in small levels of methane mitigation and improved animal productivity. Feeding large amounts daily of ground wheat reduced methane emissions by around 35% in dairy cows but was not sustained over time.

The photocatalytic decomposition of atmospheric methane (CH 4 ) and nitrous oxide (N 2 O) could be valuable tools for mitigating climate change; however, to date, few photocatalyst deployment strategies have had their costs modeled. Here, we construct basic cost models of three photocatalytic CH 4 and N 2 O decomposition systems: (1) a ground-based solar system with natural airflow over photocatalyst-painted rooftops, (2) a ground-based LED-lit system with fan-driven airflow, and (3) an aerosol-based solar system on solid particles dispersed in the atmosphere. Each model takes as inputs the photocatalyst’s apparent quantum yield (AQY; a measure of how efficiently photons drive a desired chemical reaction) and the local CH 4 or N 2 O concentration. Each model calculates an overall rate of greenhouse gas (GHG) drawdown and returns a levelized cost of GHG removal per equivalent ton of carbon dioxide (tCO 2 e). Based on prior studies of atmospheric carbon dioxide removal, we adopt$100/tCO 2 e as a target cost. We estimate that painting rooftops with photocatalysts might meet the target cost for decomposition of >10 ppm CH 4 with catalyst AQYs >4%. If painting and cleaning costs were reduced by a factor of ∼3 from our scenario, removal of ambient CH 4 could meet the cost target with AQYs >1% and removal of ambient N 2 O could do so with AQYs >0.1%. Fan-driven systems with LED illumination appear to be very challenging, achieving removal costs <$ 100/tCO 2 e only for AQYs of >10% for CH 4 and >1% for N 2 O. Dispersing photocatalytic aerosols in the troposphere could be cost-effective with AQYs of >0.4% for ambient CH 4 or >0.04% for ambient N 2 O. However, the mass of aerosols required is large and their side effects and social acceptability are uncertain. We note that, for any system, AQYs on the order of 1% will likely be extremely challenging to achieve with such dilute reagents.

To understand the importance of methane on the levels of carbon emission reductions required to achieve temperature goals, a processed-based approach is necessary rather than reliance on the transient climate response to emissions. We show that plausible levels of methane (CH4) mitigation can make a substantial difference to the feasibility of achieving the Paris climate targets through increasing the allowable carbon emissions. This benefit is enhanced by the indirect effects of CH4 on ozone (O3). Here the differing effects of CH4 and CO2 on land carbon storage, including the effects of surface O3, lead to an additional increase in the allowable carbon emissions with CH4 mitigation. We find a simple robust relationship between the change in the 2100 CH4 concentration and the extra allowable cumulative carbon emissions between now and 2100 (0.27 ± 0.05 GtC per ppb CH4). This relationship is independent of modelled climate sensitivity and precise temperature target, although later mitigation of CH4 reduces its value and thus methane reduction effectiveness. Up to 12% of this increase in allowable emissions is due to the effect of surface ozone. We conclude early mitigation of CH4 emissions would significantly increase the feasibility of stabilising global warming below 1.5 °C, alongside having co-benefits for human and ecosystem health.

Background Enteric methane emissions from dairy cows are an environmental problem as well as a gross feed energy loss to the animal. Methane is generated in the rumen by methanogenic archaea from hydrogen (H 2 ) + carbon dioxide and from H 2 + methanol or methylamines. The methanogenic substrates are provided by non-methanogens during feed fermentation. Methane mitigation approaches have yielded variable results, partially due to an incomplete understanding of the contribution of hydrogenotrophic and methylotrophic archaea to methanogenesis. Research indicates that 3-nitrooxypropanol (3-NOP) reduces enteric methane formation in dairy cows by inhibiting methyl-coenzyme M reductase (MCR), the enzyme responsible for methane formation. The purpose of this study was to utilize metagenomic and metatranscriptomic approaches to investigate the effect of 3-NOP on the rumen microbiome and to determine the fate of H 2 that accumulates less than expected under inhibited methanogenesis. Results The inhibitor 3-NOP was more inhibitory on Methanobrevibacter species than methanol-utilizing Methanosphaera and tended to reduce the gene expression of MCR. Under inhibited methanogenesis by 3-NOP, fluctuations in H 2 concentrations were accompanied by changes in the expression of [FeFe] hydrogenases in H 2 -producing bacteria to regulate the amount of H 2 production. No previously reported alternative H 2 sinks increased under inhibited methanogenesis except for a significant increase in gene expression of enzymes involved in the butyrate pathway. Conclusion By taking a metatranscriptomic approach, this study provides novel insights on the contribution of methylotrophic methanogens to total methanogenesis and regulation of H 2 metabolism under normal and inhibited methanogenesis by 3-NOP in the rumen. -iX6YPbp4qKjzQQ25nvbCQ Video Abstract

Ruminant enteric methane, the largest agricultural source of CH₄, is a key target in global climate policies. We developed a biowaste-derived live fed microbial (LFM) from fruit- and vegetable residues and evaluated its potential as a scalable intervention to reduce enteric methane while improving animal performance. In controlled in vitro assays and a 98 days in vivo feeding trial in bovine calves ( n  = 15), LFM at 2% dietary inclusion (dry-matter basis) improved feed efficiency by 30.9%, reduced modelled methane emissions by 25.2%, increased total volatile fatty acids by 45.5%, and lowered NH₃–N by 28.4%. At 3% inclusion, feed efficiency improved by 25.5%, methane emissions decreased by 30.4%, total VFA increased by 43.0%, and NH₃–N declined by 11.7%. Methane abatement was estimated by integrating in vitro and in vivo measurements using an empirically fitted conversion factor and Tier-2–compatible intake models. The IPCC (2006) Tier-2 equivalents indicated ~19% reduction. Scaling to India’s livestock herd suggested abatement of 15.4 Mt CH₄ yr⁻¹ (432.3 Mt CO₂-eq yr⁻¹; GWP₁₀₀ = 28) under full adoption, corresponding to ~US$494.1 million annually under the carbon-price assumption used. These findings position biowaste-derived LFM as a circular-economy feed technology capable of simultaneously improving productivity and reducing enteric methane emissions at scale.