Anthropogenic Methane Emissions Research Articles

Assessing the methane mitigation potential of innovative management in US rice production

Abstract Rice is an important global crop while also contributing significant anthropogenic methane (CH4) emissions. To support the future of rice production, more information is needed on the impacts of sustainability-driven management used to grow rice with lower associated methane emissions. Recent support for the impacts of different growing practices in the US has prompted the application of a regional methodology (Tier 2) to estimate methane emissions in different rice growing regions. The methodology estimates rice methane emissions from the US Mid-South (MdS) and California (Cal) using region-specific scaling factors applied to a region-specific baseline flux. In our study, we leverage land cover data and soil clay content to estimate methane emissions using this approach, while also examining how changes in common production practices can affect overall emissions in the US. Our results indicated US rice cultivation produced between 0.32 and 0.45 Tg CH4 annually, which were approximately 7% and 42% lower on average compared to Food and Agriculture Organization of the UN (FAO) and US Environmental Protection Agency (EPA) inventories, respectively. Our estimates were 63% greater on average compared to similar methods that lack regional context. Introducing aeration events into irrigation resulted in the greatest methane reductions across both regions. When accounting for differences between baseline and reduction scenarios, the US MdS typically had higher mitigation potential compared to Cal. The differences in cumulative mitigation potential across the 2008–2020 period were likely driven by lower production area clay content for the US MdS compared to Cal. The added spatial representation in the Tier 2 approach is useful in surveying how impactful methane-reducing practices might be within and across regions.

A Gridded Inventory of Annual 2012-2018 U.S. Anthropogenic Methane Emissions.

Nationally reported greenhouse gas inventories are a core component of the Paris Agreement's transparency framework. Comparisons with emission estimates derived from atmospheric observations help identify improvements to reduce uncertainties and increase the confidence in reported values. To facilitate comparisons over the contiguous United States, we present a 0.1° × 0.1° gridded inventory of annual 2012-2018 anthropogenic methane emissions, allocated to 26 individual source categories, with scale-dependent error estimates. Our inventory is consistent with the U.S. Environmental Protection Agency (EPA) Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI), submitted to the United Nations in 2020. Total emissions and patterns (spatial/temporal) reflect the activity and emission factor data underlying the GHGI, including many updates relative to a previous gridded version of the GHGI that has been extensively compared with observations. These underlying data are not generally available in global gridded inventories, and comparison to EDGAR version 6 shows large spatial differences, particularly for the oil and gas sectors. We also find strong regional variability across all sources in annual 2012-2018 spatial trends, highlighting the importance of understanding regional- and facility-level activities. Our inventory represents the first time series of gridded GHGI methane emissions and enables robust comparisons of emissions and their trends with atmospheric observations.

Effect of ellagic and gallic acid on the mitigation of methane production and ammonia formation in an in vitro model of short-term rumen fermentation

Ruminant production is an important source of animal proteins for human nutrition. However, ruminants contribute to about 30% of anthropogenic methane (CH4) emissions worldwide. The reduction of CH4 emissions could represent an important strategy against climate warming. Tannins can play an important role in the mitigation of CH4 emissions from ruminants. However, their mode of action is not yet well known. Thus, the present study aimed to gain a better understanding of the effect of ellagic acid (EA) and gallic acid (GA) on rumen fermentation using a model of short-term in vitro rumen fermentation. The basal diet (hay) was supplemented with EA and GA in five treatments (mg/g dry matter): i) EA 75, ii) EA 150, iii) GA 75, iv) GA 150 and v) EA 75 + GA 75. After a 24 h incubation, pH, ammonia formation, gas production, short-chain fatty acids (SCFA), in vitro organic matter digestibility (IVOMD) and the microbial count were assessed. Total gas production and digestible organic matter (dOM) were decreased after all the treatments, except for GA 75. The treatments EA 150 and EA+GA significantly decreased CH4 production per unit of dietary DM, dOM, CO2 and SCFA. Ammonia production was significantly decreased by EA 150 and EA+GA. EA and GA differently affected the relative abundance of selected bacterial taxa in rumen microbiota. To conclude, EA 150 and EA+GA exerted a significant effect on the reduction of CH4 emissions and ammonia formation, but affecting also the rumen degradability of the diet and the total SCFA production, whereas EA 75 and GA 75 were not effective as EA 150 and EA+GA on CH4 and ammonia, but were less detrimental on feed degradability and SCFA. Further studies are needed to determine whether the beneficial and detrimental effects of tannins on rumen fermentation can be dissociated.

Silicon-induced optimization on phase structure and surface property of Pd/ZrO2 catalysts for enhanced methane combustion

Palladium-based catalysts are relatively active for eliminating anthropogenic methane emissions through catalytic combustion, while they tend to degrade under drastic conditions. Herein, the silicon promoter was rationally introduced into Pd/ZrO2 catalysts to tune the monoclinic (m-) and tetragonal (t-) phase ratio and boost the catalytic performance. The introduced Si–O–Zr structure in ZrO2 not only reduced the grain size, but also produced oxygen vacancies due to lattice distortion, which greatly improved the stability of t-ZrO2 in high-temperature (800 °C) calcined catalysts. However, the excessive Si-addition caused the blockage of oxygen vacancies by amorphous SiO2, facilitating the transformation from t-ZrO2 to m-ZrO2. In the Pd/0.05Si–ZrO2 catalyst with a relatively high t-ZrO2 ratio, the presence of abundant oxygen vacancies stimulated the formation of surface-active oxygen and Pd2+ species, improved the reducibility of PdO and the redox of Pd ↔ PdO, meanwhile depressed the accumulation of hydroxyls. These, coupled with the enhanced hydrophobicity by Si-modification, made Pd/0.05Si–ZrO2 exhibit superior catalytic activity, stability and water-resistance to catalysts with low t-ZrO2 ratio. The revealed Si-promotion effect could be generalized to design phase-regulated Pd-based catalysts with optimized surface property for catalytic oxidation reactions.

Automated detection and monitoring of methane super-emitters using satellite data

Abstract. A reduction in anthropogenic methane emissions is vital to limit near-term global warming. A small number of so-called super-emitters is responsible for a disproportionally large fraction of total methane emissions. Since late 2017, the TROPOspheric Monitoring Instrument (TROPOMI) has been in orbit, providing daily global coverage of methane mixing ratios at a resolution of up to 7×5.5 km2, enabling the detection of these super-emitters. However, TROPOMI produces millions of observations each day, which together with the complexity of the methane data, makes manual inspection infeasible. We have therefore designed a two-step machine learning approach using a convolutional neural network to detect plume-like structures in the methane data and subsequently apply a support vector classifier to distinguish the emission plumes from retrieval artifacts. The models are trained on pre-2021 data and subsequently applied to all 2021 observations. We detect 2974 plumes in 2021, with a mean estimated source rate of 44 t h−1 and 5–95th percentile range of 8–122 t h−1. These emissions originate from 94 persistent emission clusters and hundreds of transient sources. Based on bottom-up emission inventories, we find that most detected plumes are related to urban areas and/or landfills (35 %), followed by plumes from gas infrastructure (24 %), oil infrastructure (21 %), and coal mines (20 %). For 12 (clusters of) TROPOMI detections, we tip and cue the targeted observations and analysis of high-resolution satellite instruments to identify the exact sources responsible for these plumes. Using high-resolution observations from GHGSat, PRISMA, and Sentinel-2, we detect and analyze both persistent and transient facility-level emissions underlying the TROPOMI detections. We find emissions from landfills and fossil fuel exploitation facilities, and for the latter, we find up to 10 facilities contributing to one TROPOMI detection. Our automated TROPOMI-based monitoring system in combination with high-resolution satellite data allows for the detection, precise identification, and monitoring of these methane super-emitters, which is essential for mitigating their emissions.

Adaptive irrigation management by Balinese farmers reduces greenhouse gas emissions and increases rice yields.

The potential for changes in water management regimes to reduce greenhouse gases (GHG) in rice paddies has recently become a major topic of research in Asia, with implications for top-down versus bottom-up management strategies. Flooded rice paddies are a major source of anthropogenic GHG emissions and are responsible for approximately 11% of global anthropogenic methane (CH4) emissions. However, rice is also the most important food crop for people in low- and lower-middle-income countries. While CH4 emissions can be reduced by lessening the time the plants are submerged, this can trigger increased emissions of nitrous oxide (N2O), a more potent GHG. Mitigation options for CH4 and N2O are different, and minimizing one gas may increase the emission of the other. Accurate measurement of these gas emissions in rice paddies is difficult, and the results are controversial. We analysed these trade-offs using continuous high-precision measurements in a closed chamber in 2018-2020. Based on the results, we tested a bottom-up adaptive irrigation regime that improves nitrogen uptake by rice plants while reducing combined GHG emissions and nitrogen runoff from paddies to reefs in agricultural drainages. In 2023, we undertook a follow-up study in which farmers obtained higher rice yields with adaptive intermittent irrigation compared to uniformly flooded fields. These results use the polycentric, self-governing capacity of Balinese subaks for continuous adaptation. This article is part of the theme issue 'Climate change adaptation needs a science of culture'.

Trends in atmospheric methane concentrations since 1990 were driven and modified by anthropogenic emissions

The atmospheric methane trend is not fully understood. Here we investigate the role of the main sink, the main natural source, and anthropogenic emissions on the methane growth rate over the last three decades using numerical models and emission inventories. We find that the long-term trend is driven by increased anthropogenic methane emissions, while wetland emissions show large variability and can modify the trend. The anthropogenic influence on hydroxyl radical, through nitrogen oxides and carbon monoxide emissions, has modified the trend over the last decades and contributed to the atmospheric methane stabilization from 2000 to 2007. The hydroxyl radical increase prior to this stabilization period might have contributed to the decline in the isotopic ratio after 2007 due to the time dependent isotopic response of hydroxyl radical. Emission reductions due to COVID-19 restrictions via the influence on hydroxyl radical, possibly contributed to approximately two thirds of the increase in methane growth from 2019 to 2020.

Cadmium reduced methane emissions by stimulating methane oxidation in paddy soils

Flooded rice paddy fields are a significant source of anthropogenic methane (CH4) emissions. Cadmium (Cd) is one of the most common and toxic contaminants in paddy soils. However, little is known about how the soil microbial communities associated with CH4 emissions respond to the increasing Cd-stress in paddies. In this study, we employed isotopically 13C-labelled CH4, high-throughput sequencing analysis, and gene quantification analysis to reveal the effect and mechanism of Cd on CH4 emissions in paddy soils. Results showed that 4.0 mg kg−1 Cd addition reduced CH4 emissions by 16–99% in the four tested paddy soils, and significantly promoted the transformation of 13CH4 to 13CO2. Quantitative polymerase chain reaction (qPCR) demonstrated that Cd addition increased the abundances of pmoA gene, the ratios of methanogens to methanotrophs (mcrA/pmoA) showed a positive correlation with CH4 emissions (R2 = 0.798, p < 0.01). Furthermore, the composition of the microbial community containing the pmoA gene was barely affected by Cd addition (p > 0.05). This observation was consistent with the findings of a pure incubation experiment where methanotrophs exhibited high tolerance to Cd. We argue that microbial feedback to Cd stress amplifies the contribution of methanotrophs to CH4 oxidation in rice fields through the complex interactions occurring among soil microbes. Our study highlights the overlooked association between Cd and CH4 dynamics, offering a better understanding of the role of rice paddies in global CH4 cycling.

A bio-augmented system with Methylosarcina sp. LC-4 immobilized on bio-carriers: Towards an integrated approach to mitigate and valorize methane emissions from landfills to biodiesel

Bio-augmented systems based on methanotrophs are indispensable in curbing anthropogenic methane emissions from engineered landfills or dumpsites to curtail rising levels of greenhouse gases. Using a defined methanotroph culture immobilized on an inert material-based bio-carrier makes it possible to harness these methane emissions for creating value-added products, thus contributing to the circular bio-economy. The methane oxidation capacity of the model methanotroph Methylosarcina sp. LC-4, a prospective organism for biodiesel production using methane present in landfill gas, immobilized on several inert bio-carriers, was evaluated to identify a bio-carrier that provided optimum conditions for the process.Among the several bio-carriers evaluated, perlite and vermiculite were selected due to their high specific surface area and superior water-holding capacity, which result in the retention of nutrients and biomass and higher methane elimination capacity. While perlite showed high biomass holding capacity and methane transport, vermiculite supported a high growth of methanotrophs. LC-4 immobilized on perlite and vermiculite as the bio-carrier showed maximum methane elimination capacity (MEC) of 291.3 g m−2 day−1 and 155.5 g m−2 day−1, respectively. The low bed height of only 0.13 m and a short start-up period of 2–4 days are promising for use as alternate daily cover in a landfill. The recovered biomass had 12% (w/w) fatty acid methyl ester (FAME), with a high fraction of (∼85%) of C14–C18 saturated and monounsaturated fatty acids, suitable for biodiesel production. The combination of perlite and vermiculite increased MEC and FAME content levels. The current study demonstrated a new bio-augmented system designed with a pure methanotroph for methane elimination with a short start-up time and the valorization of the assimilated methane.

Assessing the relationship between energy-related methane emissions and the burden of cardiovascular diseases: a cross-sectional study of 73 countries

The energy industry significantly contributes to anthropogenic methane emissions, which add to global warming and have been linked to an increased risk of cardiovascular diseases (CVD). This study aims to evaluate the relationship between energy-related methane emissions and the burden of CVD, measured in disability-adjusted life years (DALYs), in 2019. We conducted a cross-sectional analysis of datasets from 73 countries across all continents. The analyzed datasets included information from 2019 on environmental energy-related methane emissions, burden of DALYs due to CVD. The age-standardized prevalence of obesity in adults and life expectancy at birth were retrieved. The relationship between the variables of interest was evaluated using multiple linear regression models. In the multiple model, we observed a positive linear association between methane emissions and the log-transformed count of DALYs related to CVD. Specifically, for each unit increase in energy-related methane emissions, the burden of CVD increased by 0.06% (95% CI 0.03–0.09%, p < 0.001). The study suggests that reducing methane emissions from the energy industry could improve public health for those at risk of CVD. Policymakers can use these findings to develop strategies to reduce methane emissions and protect public health.

Impacts of production structure changes on global CH4 emissions: Evidences from income-based accounting and decomposition analysis

Globalization drives anthropogenic methane (CH4) emissions from upstream to downstream agents through global supply chains. However, previous studies have overlooked the indirect CH4 emissions enabled by primary suppliers. In this study, we use the Ghosh Multi-Regional Input-Output (MRIO) model and Structural Decomposition Analysis (SDA) to explore the temporal changes in global income-based CH4 emissions and decompose the socioeconomic drivers. Our results show that global income-based CH4 emissions increased by 17.21% from 2001 to 2014, with per capita primary inputs and technology being the two key drivers. Specifically, in China and India, income-based CH4 emissions were mainly from agriculture, and input structure was responsible for restraining the growth in CH4 emissions from their agricultural activities. On the other hand, service activities dominated the United States and the European Union, and production output structure was accountable for their emission growth related to service activities. To achieve global CH4 emission mitigation, key sectors of major economies with high income-based CH4 emissions should optimize their primary input structures, production output structure, and production technologies from the supply-side. It is crucial to reduce enabled CH4 emissions in emerging economies, particularly in Asia, through the adjustment of primary input activities.

Photocatalytic Conversion of Methane: Current State of the Art, Challenges, and Future Perspectives.

With 28-34 times the greenhouse effect of CO2 over a 100-year period, methane is regarded as the second largest contributor to global warming. Reducing methane emissions is a necessary measure to limit global warming to below 1.5 °C. Photocatalytic conversion of methane is a promising approach to alleviate the atmospheric methane concentrations due to its low energy consumption and environmentally friendly characteristics. Meanwhile, this conversion process can produce valuable chemicals and liquid fuels such as CH3OH, CH3CH2OH, C2H6, and C2H4, cutting down the dependence of chemical production on crude oil. However, the development of photocatalysts with a high methane conversion efficiency and product selectivity remains challenging. In this review, we overview recent advances in semiconductor-based photocatalysts for methane conversion and present catalyst design strategies, including morphology control, heteroatom doping, facet engineering, and cocatalysts modification. To gain a comprehensive understanding of photocatalytic methane conversion, the conversion pathways and mechanisms in these systems are analyzed in detail. Moreover, the role of electron scavengers in methane conversion performance is briefly discussed. Subsequently, we summarize the anthropogenic methane emission scenarios on earth and discuss the application potential of photocatalytic methane conversion. Finally, challenges and future directions for photocatalytic methane conversion are presented.

Risk Management of Methane Reduction Clean Development Mechanism Projects in Rice Paddy Fields

Agriculture accounts for the largest share of anthropogenic methane emissions. Rice paddy fields emit a significant amount of methane gas worldwide. Changing paddy water management practices has an enormous potential to reduce greenhouse gases. The clean development mechanism (CDM) project uses a market mechanism to reduce methane through private participation. There are various risks associated with private investment in CDM projects, although carbon credits as an economic incentive assist in mitigating some of these risks. Farmer participation plays a key role in the success of paddy water management projects in rural areas; however, despite the significant potential to reduce global methane emissions, very few projects have been implemented. When designing a Sustainable Development Mechanism (SDM) system, it is crucial to understand why the market mechanism in the existing CDM projects has failed. This study identifies and categorizes the risks and barriers to paddy water management in CDM projects and analyzes risk management options in CDM projects in India, Indonesia, and Mozambique. The results of this study showed that aside from economic risks, barriers to the application of technology in the field pose critical risks. The lack of knowledge and implementation experiences in rural areas increases barriers to practice. This in turn causes risk of difficulties in technology transfer which can be alleviated by improving awareness and introducing new knowledge through education and training in rural project implementation. Additionally, we highlight the importance of international efforts to build governance between the private and public sectors and promote technology transfers through multi-stakeholder engagement. This study provides specific information to encourage methane reduction worldwide and vitalize rice paddy water management in carbon reduction projects.

Quantification of oil and gas methane emissions in the Delaware and Marcellus basins using a network of continuous tower-based measurements

Abstract. According to the United States Environmental Protection Agency (US EPA), emissions from oil and gas infrastructure contribute 30 % of all anthropogenic methane (CH4) emissions in the US. Studies in the last decade have shown emissions from this sector to be substantially larger than bottom-up assessments, including the EPA inventory, highlighting both the increased importance of methane emissions from the oil and gas sector in terms of their overall climatological impact and the need for independent monitoring of these emissions. In this study we present continuous monitoring of regional methane emissions from two oil and gas basins using tower-based observing networks. Continuous methane measurements were taken at four tower sites in the northeastern Marcellus basin from May 2015 through December 2016 and five tower sites in the Delaware basin in the western Permian from March 2020 through April 2022. These measurements, an atmospheric transport model, and prior emission fields are combined using an atmospheric inversion to estimate monthly methane emissions in the two regions. This study finds the mean overall emission rate from the Delaware basin during the measurement period to be 146–210 Mg CH4 h−1 (energy-normalized loss rate of 1.1 %–1.5 %, gas-normalized rate of 2.5 %–3.5 %). Strong temporal variability in the emissions was present, with the lowest emission rates occurring during the onset of the COVID-19 pandemic. Additionally, a synthetic model–data experiment performed using the Delaware tower network shows that the presence of intermittent sources is not a significant source of uncertainty in monthly quantification of the mean emission rate. In the Marcellus, this study finds the overall mean emission rate to be 19–28 Mg CH4 h−1 (gas-normalized loss rate of 0.30 %–0.45 %), with relative consistency in the emission rate over time. These totals align with aircraft top-down estimates from the same time periods. In both basins, the tower network was able to constrain monthly flux estimates within ±20 % uncertainty in the Delaware and ±24 % uncertainty in the Marcellus. The results from this study demonstrate the ability to monitor emissions continuously and detect changes in the emissions field, even in a basin with relatively low emissions and complex background conditions.

Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action

Abstract. We use 2019 TROPOMI satellite observations of atmospheric methane in an analytical inversion to quantify methane emissions from the Middle East and North Africa at up to ∼25 km × 25 km resolution, using spatially allocated national United Nations Framework Convention on Climate Change (UNFCCC) reports as prior estimates for the fuel sector. Our resulting best estimate of anthropogenic emissions for the region is 35 % higher than the prior bottom-up inventories (+103 % for gas, +53 % for waste, +49 % for livestock, −14 % for oil) with large variability across countries. Oil and gas account for 38 % of total anthropogenic emissions in the region. TROPOMI observations can effectively optimize and separate national emissions by sector for most of the 23 countries in the region, with 6 countries accounting for most of total anthropogenic emissions including Iran (5.3 (5.0–5.5) Tg a−1; best estimate and uncertainty range), Turkmenistan (4.4 (2.8–5.1) Tg a−1), Saudi Arabia (4.3 (2.4–6.0) Tg a−1), Algeria (3.5 (2.4–4.4) Tg a−1), Egypt (3.4 (2.5–4.0) Tg a−1), and Turkey (3.0 (2.0–4.1) Tg a−1). Most oil–gas emissions are from the production (upstream) subsector, but Iran, Turkmenistan, and Saudi Arabia have large gas emissions from transmission and distribution subsectors. We identify a high number of annual oil–gas emission hotspots in Turkmenistan, Algeria, and Oman and offshore in the Persian Gulf. We show that oil–gas methane emissions for individual countries are not related to production, invalidating a basic premise in the construction of activity-based bottom-up inventories. Instead, local infrastructure and management practices appear to be key drivers of oil–gas emissions, emphasizing the need for including top-down information from atmospheric observations in the construction of oil–gas emission inventories. We examined the methane intensity, defined as the upstream oil–gas emission per unit of methane gas produced, as a measure of the potential for decreasing emissions from the oil–gas sector and using as reference the 0.2 % target set by the industry. We find that the methane intensity in most countries is considerably higher than this target, reflecting leaky infrastructure combined with deliberate venting or incomplete flaring of gas. However, we also find that Kuwait, Saudi Arabia, and Qatar meet the industry target and thus show that the target is achievable through the capture of associated gas, modern infrastructure, and the concentration of operations. Decreasing methane intensities across the Middle East and North Africa to 0.2 % would achieve a 90 % decrease in oil–gas upstream emissions and a 26 % decrease in total anthropogenic methane emissions in the region, making a significant contribution toward the Global Methane Pledge.

Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images

Abstract. Anthropogenic emissions of methane (CH4) have made a considerable contribution towards the Earth's changing radiative budget since pre-industrial times. This is because large amounts of methane are emitted from human activities, and the global warming potential of methane is high. The majority of anthropogenic fossil methane emissions to the atmosphere originate from a large number of small (point) sources. Thus, detection and accurate, rapid quantification of such emissions are vital to enable the reduction of emissions to help mitigate future climate change. There exist a number of instruments on satellites that measure radiation at methane-absorbing wavelengths, which have sufficiently high spatial resolution that can be used for detecting plumes of highly spatially localised methane “point sources” (areas on the order of m2 to km2). Searching for methane plumes in methane-sensitive satellite images using classical methods, such as thresholding and clustering, can be useful but is time-consuming and often involves empirical decisions. Here, we develop a deep neural network to identify and quantify methane point source emissions from hyperspectral imagery from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite with 30 m spatial resolution. The moderately high spectral and spatial resolution, as well as considerable global coverage and free access to data, makes PRISMA a good candidate for methane plume detection. The neural network was trained with simulated synthetic methane plumes generated with the large eddy simulation extension of the Weather Research and Forecasting model (WRF-LES), which we embedded into PRISMA images. The deep neural network was successful at locating plumes with a F1 score, precision, and recall of 0.95, 0.96, and 0.92, respectively, and was able to quantify emission rates with a mean error of 24 %. The neural network was furthermore able to locate several plumes in real-world images. We have thus demonstrated that our method can be effective in locating and quantifying methane point source emissions in near-real time from 30 m resolution satellite data, which can aid us in mitigating future climate change.

Mobile Measurements of Atmospheric Methane at Eight Large Landfills: An Assessment of Temporal and Spatial Variability

Municipal solid waste landfills are major contributors to anthropogenic emissions of methane (CH4), which is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. The development of sensitive, selective, and fast-response instrumentation allows the deployment of mobile measurement platforms for CH4 measurements at landfills. The objectives of this study are to use mobile monitoring to measure ambient levels of CH4 at eight large operating landfills in southeast Michigan, USA; to characterize diurnal, daily and spatial variation in CH4 levels; and to demonstrate the influence of meteorological factors. Elevated CH4 levels were typically found along the downwind side or corner of the landfill. Levels peaked in the morning, reaching 38 ppm, and dropped to near-baseline levels during midday. Repeat visits showed that concentrations were highly variable. Some variation was attributable to the landfill size, but both mechanistically-based dilution-type models and multivariate models identified that wind speed, boundary layer height, barometric pressure changes, and landfill temperature were key determinants of CH4 levels. Collectively, these four factors explained most (r2 = 0.89) of the variation in the maximum CH4 levels at the landfill visited most frequently. The study demonstrates the ability to assess spatial and temporal variation in CH4 levels at landfills using mobile monitoring along perimeter roads. Such monitoring can identify the location of leaks and the best locations for long-term emission monitoring using fixed site monitors.

Holistic and integrated systemic policies and practices for decarbonization

AbstractA bold, visionary, transforming, systemic, holistic, integrated, caring, inclusive, equitable, sustainable, and resilient paradigm for fast transitions toward a clean energy and decarbonized future is imperative and urgently needed. Business as usual and silo approaches are not viable with the changes that are occurring. These changes are linked and interacting systems of physical, natural, health, social, economic, finance, governance, and institution.The effects and impacts are dire, existential, and pervasive.The 2021 IPCC Report Physical Science Basis: Summary for Policymakers, in clear language stated “it is unequivocal that human influence has warmed the atmosphere, oceans and land”.The scientific communities in the US, Europe, Asia and other regions all subscribe to this situation.Well documented global empirical evidence is also confirming the profound systems and systemic transformations that are occurring.Business, industry, and the general public, in particular youths, worldwide are all increasingly demanding actions – that transcend words of what needs to be done to deeds of how and now.In the US, the 2022 Inflation Reduction Act, would allocate US 370 billion for combating climate change and clean energy production. The IRA is the largest climate spending package ever.President Biden has called for 100% clean electricity by 2035 and pledged to cut carbon emissions by 50%–52% below 2005 levels by the end of this decade, doubling the previous target.A decarbonized future was endorsed by Leaders at the 2021 G‐7 Carbis, UK Summit. There is growing realization that the global climate change crisis requires strengthened and expanded global cooperation with new, innovative and non‐bureaucratic mechanisms for collaboration.The 2021 IPCC Report summarized that global surface temperature will continue to increase until at least the mid‐ century under all emissions' scenarios considered. “Global warming of 1.5 and 2°C will be exceeded during the 21st century unless deep reductions in CO2 and other greenhouse gas emissions occur in the coming decades.” The UNEP and IEA contends reducing anthropogenic methane emissions will help mitigate climate change and is a cost‐effective proposition.The release of methane and micro‐organisms from melting of permafrost needs to be better studied and understood., The confluence of increased heat, humidity, fine particulates air pollution, water contaminants and the COVID pandemic, will exacerbate health burdens. This will have serious consequences for human wellbeing, and cascading into national and global security. With climate change, therapeutics and vaccines will not work.The article provides a brief overview of the unprecedented climate related hurricanes, storms, floods and wildfires disasters occurring in all regions of the world. It highlights of some of the key effects, impacts and consequences with current policies and practices with regard to the energy‐climate conundrum. There is an imperative to change course toward a decarbonized future.A number of systemic expeditious interventions are delineated. These include actions by all on:The* fundamental need to change behavior; *afforestation, reforestation, rehabilitation of wetlands, mangroves, wastelands and coral reefs to restore ecosystem functions which would also create significant number of employment and livelihoods' opportunities; *retrofitting existing structures to be more energy efficient, incorporate increasing renewable energy, sustainability and resiliency criteria, – to “build back better” and provide jobs; *the life cycle of food and agriculture practices need to be systemically examined to reduce adverse impacts on climate, Energy, environment and health.There are difficulties and challenges. The commensurate opportunities and benefits of a decarbonized paradigm include clean and safe jobs; healthy quality of life; and a sustained and resilient future for current and future generations.

Spectrometric imaging of sub-hourly methane emission dynamics from coal mine ventilation

Anthropogenic methane (CH4) emissions contribute significantly to the current radiative forcing driving climate change. Localized CH4 sources such as occurring in the fossil fuel industry contribute a substantial share to the anthropogenic emission total. The temporal dynamics of such emissions is largely unresolved and unaccounted for when using atmospheric measurements by satellites, aircraft, and ground-based instruments to monitor emission rates and verify reported numbers. Here, we demonstrate the usage of a ground-based imaging spectrometer for quantifying the CH4 emission dynamics of a ventilation facility of a coal mine in the Upper Silesian Coal Basin, Poland. To this end, we deployed the imaging spectrometer at roughly 1 km distance from the facility and collected plume images of CH4 column enhancements during the sunlit hours of four consecutive days in June 2022. Together with wind information from a co-deployed wind-lidar, we inferred CH4 emission rates with roughly 1 min resolution. Daily average emission rates ranged between 1.39 ± 0.19 and 4.44 ± 0.76 tCH4 h−1, 10 min averages ranged between (min) 0.82 and (max) 5.83 tCH4 h−1, and puff-like events caused large variability on time scales below 15 min. Thus, to monitor CH4 emissions from such sources, it requires measurement techniques such as the imaging spectrometer evaluated here that can capture emission dynamics on short time scales.

National contributions to climate change due to historical emissions of carbon dioxide, methane, and nitrous oxide since 1850

Anthropogenic emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) have made significant contributions to global warming since the pre-industrial period and are therefore targeted in international climate policy. There is substantial interest in tracking and apportioning national contributions to climate change and informing equitable commitments to decarbonisation. Here, we introduce a new dataset of national contributions to global warming caused by historical emissions of carbon dioxide, methane, and nitrous oxide during the years 1851–2021, which are consistent with the latest findings of the IPCC. We calculate the global mean surface temperature response to historical emissions of the three gases, including recent refinements which account for the short atmospheric lifetime of CH4. We report national contributions to global warming resulting from emissions of each gas, including a disaggregation to fossil and land use sectors. This dataset will be updated annually as national emissions datasets are updated.