Observed changes in China's methane emissions linked to policy drivers.

China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country's future progress. Here, using satellite and surface observations, we quantify China's methane emissions during 2010-2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China's methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China's energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China's methane emissions, providing input to formulating methane policy toward its climate goal.

The challenge of estimating global termite methane emissions.

Methane is a powerful greenhouse gas, more potent than carbon dioxide, and emitted from a variety of natural sources including wetlands, permafrost, mammalian guts and termites. As increases in global temperatures continue to break records, quantifying the magnitudes of key methane sources has never been more pertinent. Over the last 40 years, the contribution of termites to the global methane budget has been subject to much debate. The most recent estimates of termite emissions range between 9 and 15 Tg CH4 year-1, approximately 4% of emissions from natural sources (excluding wetlands). However, we argue that the current approach for estimating termite contributions to the global methane budget is flawed. Key parameters, namely termite methane emissions from soil, deadwood, living tree stems, epigeal mounds and arboreal nests, are largely ignored in global estimates. This omission occurs because data are lacking and research objectives, crucially, neglect variation in termite ecology. Furthermore, inconsistencies in data collection methods prohibit the pooling of data required to compute global estimates. Here, we summarise the advances made over the last 40 years and illustrate how different aspects of termite ecology can influence the termite contribution to global methane emissions. Additionally, we highlight technological advances that may help researchers investigate termite methane emissions on a larger scale. Finally, we consider dynamic feedback mechanisms of climate warming and land-use change on termite methane emissions. We conclude that ultimately the global contribution of termites to atmospheric methane remains unknown and thus present an alternative framework for estimating their emissions. To significantly improve estimates, we outline outstanding questions to guide future research efforts.

Persistent net release of carbon dioxide and methane from an Alaskan lowland boreal peatland complex.

Permafrost degradation in peatlands is altering vegetation and soil properties and impacting net carbon storage. We studied four adjacent sites in Alaska with varied permafrost regimes, including a black spruce forest on a peat plateau with permafrost, two collapse scar bogs of different ages formed following thermokarst, and a rich fen without permafrost. Measurements included year-round eddy covariance estimates of net carbon dioxide (CO2 ), mid-April to October methane (CH4 ) emissions, and environmental variables. From 2011 to 2022, annual rainfall was above the historical average, snow water equivalent increased, and snow-season duration shortened due to later snow return. Seasonally thawed active layer depths also increased. During this period, all ecosystems acted as slight annual sources of CO2 (13-59 g C m-2 year-1 ) and stronger sources of CH4 (11-14 g CH4 m-2 from ~April to October). The interannual variability of net ecosystem exchange was high, approximately ±100 g C m-2 year-1 , or twice what has been previously reported across other boreal sites. Net CO2 release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH4 emissions were related to increased soil moisture and inundation status. The dominant emitter of carbon was the rich fen, which, in addition to being a source of CO2 , was also the largest CH4 emitter. These results suggest that the future carbon-source strength of boreal lowlands in Interior Alaska may be determined by the area occupied by minerotrophic fens, which are expected to become more abundant as permafrost thaw increases hydrologic connectivity. Since our measurements occur within close proximity of each other (≤1 km2 ), this study also has implications for the spatial scale and data used in benchmarking carbon cycle models and emphasizes the necessity of long-term measurements to identify carbon cycle process changes in a warming climate.

A Comprehensive Integration and Synthesis of Methane Emissions from Canada's Oil and Gas Value Chain.

Methane emissions from the global oil and gas value chain are a major contributor to climate change, and their mitigation could avoid 0.1 °C of warming by 2050. Here, we synthesize nearly a decade of research encompassing thousands of multiscale methane measurements along the oil and gas value chain (production to end use) to better constrain estimates of methane emissions from Canada's energy sector and to identify research gaps contributing to uncertainty in current estimates. We find that total value chain methane emissions are 2,600 (2,100-3,700) kt, which broadly agrees with Canada's latest official inventory that now includes atmospheric measurement data in some of their oil and gas methane estimates. Accurate understanding of emission magnitudes is critical because Canada committed to a 75% reduction of oil and gas methane emissions by 2030. We also identify and discuss information gaps in both emissions and activity data, namely, from the midstream, downstream, and end-use sectors. While they make up a smaller portion of the total inventory, accurate quantification of these emissions is still important and could point to more cost-effective mitigation solutions. This work emphasizes the need for frequent, comprehensive measurements to better constrain the climate impacts of the oil and gas sector and to validate reductions and commitments pledged by industry and governments.

The Role of Emission Size Distribution on the Efficacy of New Technologies to Reduce Methane Emissions from the Oil and Gas Sector.

Methane emissions from oil and gas operations exhibit skewed distributions. New technologies such as aerial-based leak detection surveys promise cost-effective detection of large emitters (greater than 10 kg/h). Recent policies such as the US Environmental Protection Agency (EPA) methane rule that allow the use of new technologies as part of leak detection and repair (LDAR) programs require a demonstration of equivalence with existing optical gas imaging (OGI) based LDAR programs. In this work, we illustrate the impact of emission size distribution on the equivalency condition between the OGI and site-wide survey technologies. Emission size distributions compiled from aerial measurements include significantly more emitters between 1 and 10 kg/h and lower average emission rates for large emitters compared to the emission distribution in the EPA rule. As a result, we find that equivalence may be achieved at lower site-wide survey frequencies when using technologies with detection thresholds below 10 kg/h, compared to the EPA rule. However, equivalence cannot be achieved with a detection threshold of 30 kg/h at any survey frequency, because most emitters across most US basins exhibit emission rates below 30 kg/h. We find that equivalence is a complex tradeoff among technology choice, design of LDAR programs, and survey frequency that can have more than one unique solution set.

Unaddressed Uncertainties When Scaling Regional Aircraft Emission Surveys to Basin Emission Estimates.

Wide-area aerial methods provide comprehensive screening of methane emissions from oil and gas (O & G) facilities in production basins. Emission detections ("plumes") from these studies are also frequently scaled to the basin level, but little is known regarding the uncertainties during scaling. This study analyzed an aircraft field study in the Denver-Julesburg basin to quantify how often plumes identified maintenance events, using a geospatial inventory of 12,629 O & G facilities. Study partners (7 midstream and production operators) provided the timing and location of 5910 maintenance events during the 6 week study period. Results indicated three substantial uncertainties with potential bias that were unaddressed in prior studies. First, plumes often detect maintenance events, which are large, short-duration, and poorly estimated by aircraft methods: 9.2 to 46% (38 to 52%) of plumes on production were likely known maintenance events. Second, plumes on midstream facilities were both infrequent and unpredictable, calling into question whether these estimates were representative of midstream emissions. Finally, 4 plumes attributed to O & G (19% of emissions detected by aircraft) were not aligned with any O & G location, indicating that the emissions had drifted downwind of some source. It is unclear how accurately aircraft methods estimate this type of plume; in this study, it had material impact on emission estimates. While aircraft surveys remain a powerful tool for identifying methane emissions on O & G facilities, this study indicates that additional data inputs, e.g., detailed GIS data, a more nuanced analysis of emission persistence and frequency, and improved sampling strategies are required to accurately scale plume estimates to basin emissions.

Organic Matter Accumulation and Hydrology as Drivers of Greenhouse Gas Dynamics in Newly Developed Artificial Channels.

Artificial channels, common features of inland waters, have been suggested as significant contributors to methane (CH4) and carbon dioxide (CO2) dynamics and emissions; however, the magnitude and drivers of their CH4 and CO2 emissions (diffusive and ebullitive) remain unclear. They are characterized by reduced flow compared to the donor river, which results in suspended organic matter (OM) accumulation. We propose that in such systems hydrological controls will be reduced and OM accumulation will control emissions by promoting methane production and outgassing. Here, we monitored summertime CH4 and CO2 concentrations and emissions on six newly constructed river-fed artificial channels, from bare riparian mineral soil to lotic channels, under two distinct flow regimes. Chamber-based fluxes were complemented with hydrology, total fluxes (diffusion + ebullition), and suspended OM accumulation assessments. During the first 6 weeks after the flooding, inflowing riverine water dominated the emissions over in-channel contributions. Afterwards, a substantial accumulation of riverine suspended OM (≥50% of the channel's volume) boosted in-channel methane production and led to widespread ebullition 10× higher than diffusive fluxes, regardless of the flow regime. Our finding suggests ebullition as a dominant pathway in these anthropogenic systems, and thus, their impact on regional methane emissions might have been largely underestimated.

Unraveling Spatially Diverse and Interactive Regulatory Mechanisms of Wetland Methane Fluxes to Improve Emission Estimation.

Methane fluxes (FCH4) vary significantly across wetland ecosystems due to complex mechanisms, challenging accurate estimations. The interactions among environmental drivers, while crucial in regulating FCH4, have not been well understood. Here, the interactive effects of six environmental drivers on FCH4 were first analyzed using 396,322 half-hourly measurements from 22 sites across various wetland types and climate zones. Results reveal that soil temperature, latent heat turbulent flux, and ecosystem respiration primarily exerted direct effects on FCH4, while air temperature and gross primary productivity mainly exerted indirect effects by interacting with other drivers. Significant spatial variability in FCH4 regulatory mechanisms was highlighted, with different drivers demonstrated varying direct, indirect, and total effects among sites. This spatial variability was then linked to site-specific annual-average air temperature (17.7%) and water table (9.0%) conditions, allowing the categorization of CH4 sources into four groups with identified critical drivers. An improved estimation approach using a random forest model with three critical drivers was consequently proposed, offering accurate FCH4 predictions with fewer input requirements. By explicitly accounting for environmental interactions and interpreting spatial variability, this study enhances our understanding of the mechanisms regulating CH4 emissions, contributing to more efficient modeling and estimation of wetland FCH4.

Long-term growth, feed efficiency, enteric methane emission, and blood metabolite responses to in utero hyperthermia in Holstein heifers.

Dairy producers are experiencing production and animal welfare pressures from the increasing frequency and severity of heat stress events due to global climate change. Offspring performance during the preweaning and lactating periods is compromised when exposed to heat stress during late gestation (in utero). However, knowledge of the lingering effects of in utero heat stress on yearling dairy heifers is limited. Herein, we investigated the long-term effects of in utero heat stress on heifer growth, feed efficiency, and enteric methane emissions in postpubertal heifers. During the last 56 d of gestation, 38 pregnant cows carrying heifer calves were exposed to either heat stress (IUHT; n = 17) or artificial cooling (IUCL; n = 21). At 18 ± 1 mo of age, the resulting IUCL and IUHT heifers were enrolled in the present 63-d study. Heifers were blocked by weight and randomly assigned to 3 pens with Calan gates. Body weights were recorded on 3 consecutive days at the start and end of the trial and used to calculate ADG. Body condition score, hip width, body length, and chest girth were measured at the start and end of the study. All heifers were fed a TMR comprised of 46.6% oatlage, 44.6% grass/alfalfa haylage, 7.7% male-sterile corn silage, 0.3% urea, and 0.8% mineral/vitamin supplement (on a DM basis). The TMR and refusal samples were obtained daily, composited weekly, and dried to calculate DMI. During the study, each pen had access to a GreenFeed unit for 8 ± 1d to measure CH4 and CO2 gas fluxes. During the last 3 d of measuring CH4 and CO2 fluxes, fecal samples were collected, composited by animal, dried, and analyzed to calculate NDF, OM, and DM digestibility. On the last day of fecal sampling, blood samples were also collected via coccygeal venipuncture, and GC time-of-flight MS analysis was performed. Residual feed intake (RFI; predicted DMI - observed DMI), and feed conversion efficiency (FCE; DMI/ADG) were calculated to estimate feed efficiency. No differences were found in initial or final BW, hip width, chest girth, or BCS; however, IUCL heifers were longer in body length compared with IUHT heifers. Dry matter intake, ADG, RFI, and FCE were similar between IUHT and IUCL heifers. In utero heat-stressed and IUCL heifers produced similar amounts of CH4 and CO2, and no differences were found in the number of GreenFeed visits or latency to approach the GreenFeed. The concentrations of 6 blood metabolites involved in lipogenic pathways were different between in utero treatments. In conclusion, in utero heat stress does not seem to have long-term effects on feed efficiency or methane emissions during the postpubertal growing phase; however, IUCL heifers maintained a body-length advantage over their IUHT counterparts and differed in concentrations of several candidate metabolites that encourage further exploration of their potential function in key organs, such as the liver and mammary gland.

Evaluating enteric methane emissions within a herd of genetically divergent grazing dairy cows.

Enteric methane (CH4) emissions of 3 genetic groups (GG) of dairy cows were recorded across the grazing season (early March to late October). The 3 GG were (1) high economic breeding index (EBI) Holstein-Friesian (HF) representative of the top 1% of dairy cows in Ireland at the time of the study (elite), (2) national average (NA) EBI, which were representative of the average HF dairy cow in Ireland, and (3) purebred Jersey (JE) cows. Enteric CH4 was recorded using GreenFeed technology. Seasonal variation in CH4 was observed, with the lowest daily CH4 emissions and CH4 expressed per unit of dry matter intake occurring in spring (253 g/d and 15.56 g/kg, respectively), intermediate in summer (303 g/d and 18.26 g/kg, respectively), and greatest in autumn (324 g/d and 19.80 g/kg, respectively). Seasonal variation was also observed in the proportion of gross energy intake converted to CH4 (Ym); in the spring the Ym was lowest at 0.046, increasing to 0.053 and 0.058 in the summer and autumn, respectively. There was no difference in daily CH4 between the elite and NA, whereas JE had lower CH4 emissions compared with the elite. When expressed per unit of milk solids (fat + protein yield; MS), the elite and JE produced 6.8% and 9.7% less CH4 per kilogram of MS, respectively, compared with NA. There was no difference between the GG for CH4 per unit of DMI or the Ym. This research emphasizes the variation in CH4 emissions across the grazing season and among cows of differing genetic merit for CH4 emission intensities but not for CH4 per unit of DMI or the Ym.

Ruminal microbiome changes across lactation in primiparous Holstein cows with varying methane intensity: Heritability assessment.

Methane is a potent greenhouse gas produced during the ruminal fermentation and is associated with a loss of feed energy. Therefore, efforts to reduce methane emissions have been ongoing in the last decades. Methane production is highly influenced by factors such as the ruminal microbiome and host genetics. Previous studies have proposed to use the ruminal microbiome to reduce long-term methane emissions, as ruminal microbiome composition is a moderately heritable trait and genetic improvement accumulates over time. Lactation stage is another important factor that might influence methane production, but potential associations with the ruminal microbiome have not been evaluated previously. This study sought to examine the changes in ruminal microbiome over the lactation period of primiparous Holstein cows differing in methane intensity (MI) and estimate the heritability of the abundance of relevant microorganisms. Ruminal content samples from 349 primiparous Holstein cows with 14 to 378 DIM were collected from May 2018 to June 2019. Methane intensity of each cow was calculated as methane concentration/milk yield. Up to 64 taxonomic features (TF) from 20 phyla had a significant differential abundance between cows with low and high MI early in lactation, 16 TF during mid lactation, and none late in lactation. Taxonomical features within the Firmicutes, Proteobacteria, Melainabacteria, Cyanobacteria, Bacteroidetes, and Actinobacteria phyla were associated with low MI, whereas eukaryotic TF and those within the Euryarchaeota, Verrucomicrobia, Kiritimatiellaeota, and Lentisphaerae phyla were associated with high MI. Out of the 60 TF that were found to be differentially abundant between early and late lactation in cows with low MI, 56 TF were also significant when cows with low and high MI were compared in the first third of the lactation. In general, microbes associated with low MI were more abundant early in lactation (e.g., Acidaminococcus, Aeromonas, and Weimeria genera) and showed low to moderate heritabilities (0.03 to 0.33). These results suggest some potential to modulate the rumen microbiome composition through selective breeding for lower MI. Differences in the ruminal microbiome of cows with extreme MI levels likely result from variations in the ruminal physiology of these cows and were more noticeable early in lactation, probably due to important interactions between the host phenotype and environmental factors associated with that period. Our results suggest that the ruminal microbiome evaluated early in lactation may be more precise for MI difference, and hence, this should be considered to optimize sampling periods to establish a reference population in genomic selection scenarios.

Understanding potential opportunities and risks associated with feeding supplemental rumen available fats to mitigate enteric methane emissions in lactating dairy cows.

Supplemental dietary rumen available fats show promise as enteric methane (eCH4) mitigators for lactating dairy cows. However, concerns include variability in eCH4 response and possible negative effects on dairy cow performance. Successful implementation of this mitigation option requires better prediction of responses specifically to rumen available FA as well as understanding the modulating effects of other dietary and animal characteristics. Using meta-analytic and meta-regression techniques, 35 published studies with diet definition were used to assess changes in eCH4 emissions and lactation performance associated with supplemental fat, specific supplemental rumen available FA types, and other dietary characteristics. Enteric CH4 (g/d) was reduced by 3.77% per percentage unit of supplemental rumen available EE (RAEE). Supplemental rumen available PUFA (C18:2 and C18:3) and UFA (C18:1, C18:2, C18:3) mitigated eCH4 (g/d) emissions in dairy cows by 6.88 and 4.65% per percentage unit increase, respectively. The anti-methanogenic effects of PUFA, MUFA and MCFA increased with correspondingly greater basal dietary levels of each FA type. Higher rumen-degradable starch (RDS; > 18% DM) in the basal diet promoted greater reductions in eCH4 yield (eCH4/DMI, g/kg) with supplemental rumen available PUFA and UFA. Both milk fat percentage and yield (kg/d) were reduced with rumen available fat supplementation with a reduction of 7.8% and 6.0%, respectively, relative to control diets. Our results highlight the importance of determining basal levels of the rumen available FA before providing supplemental rumen available FA as an option for enteric eCH4 mitigation. Dairy nutritionists can use estimates generated from this analysis to predict changes in eCH4 emissions and dairy cow performance associated with dietary supplementation of rumen available EE and specific rumen available FA types for the purpose of eCH4 mitigation.

In-Silico and in vitro Studies Revealed that Rosmarinic Acid Inhibited Methanogenesis via Regulating Composition and Function of Rumen Microbiota.

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

Curbing methane emissions from Italian cattle farms. An agroeconomic modelling simulation of alternative policy tools.

Methane (CH4) emissions from cattle farms have been prioritised on the EU agenda, as shown by recent legislative initiatives. This study employs a supply-side agroeconomic model that mimics the behaviour of heterogeneous individual farms to simulate the application of alternative economic policy instruments to curb CH4 emissions from Italian cattle farms, as identified by the 2020 Farm Accountancy Data Network survey. Simulations consider increasing levels of a tax on each tonne of CH4 emitted or of a subsidy paid for each tonne of CH4 curbed with respect to the baseline. Individual marginal abatement costs are also derived. Besides, to consider possible technological options to curb emissions, a mitigation strategy is simulated, with different levels of costs and benefits to appraise the potential impacts on the sector. Relevant reductions in operating income are foreseen, the most substantial in farm types and size classes characterised by lower levels of carbon productivity. The introduction of the mitigation strategy shows that the outcome in terms of mitigation potential, without undermining production level, highly depends on the implementation costs, but can also vary widely due to heterogeneous farms' economic performances. Policy implications are also derived.

Effects of Saccharomyces cerevisiae and Bacillus subtilis on in vitro fermentation in the rumen of Hu sheep.

BACKGROUND: The demand for animal products is increasing in developing countries due to population growth. However, livestock production contributes significantly to global warming, accounting for 25%. Probiotics can help improve livestock efficiency by enhancing gut microbes and fat metabolism. They can modify rumen populations, enhance fermentation, reduce methane emissions and improve feed digestion. In this study, the goal was to determine the most effective method of reducing methane emissions in the rumen of sheep in vitro by adding different concentrations of Saccharomyces cerevisiae and Bacillus subtilis. RESULTS: Adding 8 × 106 CFU g-1 S. cerevisiae during fermentation reduced pH levels after 48 h. This also increased the concentrations of NH3-N, microbial protein and total gas production. At the same time, it decreased methane emissions. Furthermore, adding 20 × 106 CFU g-1 B. subtilis to the mixture increased total gas production (TGP) and methane production, with the highest production observed after 48 h. However, it did not affect pH levels after 48 h. CONCLUSION: It can be concluded that S. cerevisiae had significantly increased microbial protein and NH3-N concentrations after fermentation without altering pH. Additionally, the addition of S. cerevisiae enhanced TGP and reduced methane emissions. It is worth noting that TGP increased because B. subtilis was added at a concentration of 20 × 106 CFU g-1, with no significant differences between concentrations. Therefore, we recommend adding S. cerevisiae and B. subtilis to the diet at doses of 8 and 20 × 106 CFU g-1, as it resulted in higher TGP and reduced methane emissions. © 2024 Society of Chemical Industry.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables.

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

Mitigation of ammonia and methane emissions with manure amendments during storage of cattle slurry.

This study aimed at assessing the efficacy of manure amendments in abating ammonia (NH3) and methane (CH4) emissions during storage. Two experiments were carried out. Experiment 1 was conducted using 20 L of slurry for 98 days. Treatments were: aluminium sulphate (alum), lactogypsum, zeolite, actiglene, ammonium thiosulphate, biochar, dairy processing waste, Digest-IT and control (without amendment). Experiment 2 was conducted using 660 L of slurry in underground storage tanks for 77 days. Treatments were: sulphuric acid, gypsum, biochar and control (without amendment). NH3 measurements for experiment 1 and experiment 2 were conducted using the photoacoustic gas monitor and dynamic chamber techniques, respectively. CH4 was measured using the static chamber technique in both experiments. The effect of amendments on slurry composition was determined at the end of the experiments. Experiment 1 showed a significant reduction in NH3 emissions in the alum (82%), lactogypsum (46%) and zeolite (32%) treatments relative to the control (100.3% total ammoniacal nitrogen (TAN)). CH4 was reduced significantly in the alum (87%), ammonium thiosulphate (64%) and lactogypsum (67%) relative to the control (291.9 g m-2). Experiment 2 showed a significant reduction (32%) in NH3 emissions in the sulphuric acid relative to the control (4.4% TAN). CH4 was reduced significantly in the sulphuric acid (46%), gypsum (39%) and biochar (15%) treatments relative to the control (291.9 g m-2). In general, amendments altered slurry composition such as dry matter, volatile solids, carbon and nitrogen contents at the end of storage. Lactogypsum, alum and sulphuric acid were effective in abating both NH3 and CH4 emissions and can contribute to improving air quality.

Unlocking the significant worldwide potential of better waste and resource management for climate mitigation: with particular focus on the Global South.

Numbers do matter; the Intergovernmental Panel on Climate Change (IPCC)'s 2010 data that the waste sector is responsible for just 3% of global greenhouse gas (GHG) emissions has led to the misperception that solid waste management (SWM) has little to contribute to climate mitigation. Global efforts to control methane emissions and divert organic waste from landfills had already reduced direct emissions. But end-of-pipe SWM has also been evolving into more circular waste and resource management, with indirect GHG savings from the 3Rs (reduce, reuse, recycle) which IPCC accounts for elsewhere in the economy. The evidence compiled here on both direct emissions and indirect savings demonstrates with high confidence that better waste and resource management can make a significant contribution to climate mitigation, and must form a core part of every country's nationally determined contribution. Even the most advanced countries can still achieve much from the 3Rs. In the Global South, the challenge of extending waste collection to all and stopping open dumping and burning (sustainable development goal 11.6.1), essential to improve public health, can be turned into a huge opportunity. Moving early to divert waste from landfill by separation at source and collecting clean organic and dry recycling fractions, will mitigate global GHG emissions, slash ocean plastics and create decent livelihoods. But this can only happen with targeted climate, plastics and extended producer responsibility finance; and help to local communities to help themselves.

The unexpected long period of elevated CH4 emissions from an inundated fen meadow ended only with the occurrence of cattail (Typha latifolia).

Drainage and agricultural use transform natural peatlands from a net carbon (C) sink to a net C source. Rewetting of peatlands, despite of high methane (CH4 ) emissions, holds the potential to mitigate climate change by greatly reducing CO2 emissions. However, the time span for this transition is unknown because most studies are limited to a few years. Especially, nonpermanent open water areas often created after rewetting, are highly productive. Here, we present 14 consecutive years of CH4 flux measurements following rewetting of a formerly long-term drained peatland in the Peene valley. Measurements were made at two rewetted sites (non-inundated vs. inundated) using manual chambers. During the study period, significant differences in measured CH4 emissions occurred. In general, these differences overlapped with stages of ecosystem transition from a cultivated grassland to a polytrophic lake dominated by emergent helophytes, but could also be additionally explained by other variables. This transition started with a rapid vegetation shift from dying cultivated grasses to open water floating and submerged hydrophytes and significantly increased CH4 emissions. Since 2008, helophytes have gradually spread from the shoreline into the open water area, especially in drier years. This process was periodically delayed by exceptional inundation and eventually resulted in the inundated site being covered by emergent helophytes. While the period between 2009 and 2015 showed exceptionally high CH4 emissions, these decreased significantly after cattail and other emergent helophytes became dominant at the inundated site. Therefore, CH4 emissions declined only after 10 years of transition following rewetting, potentially reaching a new steady state. Overall, this study highlights the importance of an integrative approach to understand the shallow lakes CH4 biogeochemistry, encompassing the entire area with its mosaic of different vegetation forms. This should be ideally done through a study design including proper measurement site allocation as well as long-term measurements.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.