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The largest national difference discovered between preceding and posterior CH 4 emissions is from China, mainly due to the energy sector. Our global network's emissions estimates are in good agreement with those from previous regional surveys and point source-specific studies. According to our findings, global anthropogenic CH 4 emissions in the first six months of 2020 were, on average, 470 Gg per month higher than in 2019, mainly due to the energy and agricultural industries. During the onset of the global recession, emission levels in CH 4 emissions from China increased above expected levels for the first year on year, according to the study; however, during later months, emissions fell below target levels. The cumulative effect of the COVID-19 downturn on CH 4 emissions from March–June 2020 may be small relative to the long-term positive trend in emissions, according to the first 6 months of 2019/20's findings.
Source link: https://doi.org/10.5194/acp-22-5961-2022
The Upper Silesian Coal Basin in southern Poland is one of Europe's biggest sources of anthropogenic methane emissions due to its abundant coal mining resources. We provide update on CH 4 emission estimates for coal mine ventilation plants in the United StatesCB here. Our estimates were influenced by pairwise upwind-downwind reports of CH 4's column-average dry-air mole fractions by a network of four portable, ground-based, sun-viewing Fourier transform spectrometers of the type EM27/SUN's CoMet campaign from May to June 2018. Wind fields estimated by WRF under assimilation of vertical wind profile measurements of three co-deployed wind lidars was triggered by the latter. We find that our ad hoc network can support individual or groups of ventilation plants, according to the catchment area of the downwind measurements, but that testing the emissions averaging kernels is necessary to find correlated estimates.
Source link: https://doi.org/10.5194/acp-22-5859-2022
Methane is a potent greenhouse gas with a short atmospheric lifetime, and therefore, effective methane mitigation strategies could play a major role in achieving UN Sustainable Development Goal #13 of taking rapid action against climate change. A significant percentage of agricultural greenhouse gas emissions comes from enteric fermentation Methane emissions. Only a handful of other seaweeds have been tested for their anti-methanogenic properties, with Red Seaweed from the genus Asparagopsis proving near to complete absence of enteric methane from ruminants. Bonnemaisonia hamifera, Euptilota cirrhosum, Vidalia colensoi, and identified aquaculture target species Ecklonia radiata and Ulva sp. All seaweeds except Ulva sp. were excluded except for Ulva sp. The production of methane by up to 50. 5 and 39. 5%, respectively at an inclusion level of 10%, with no effect on measured fermentation parameters.
Source link: https://doi.org/10.1080/26388081.2022.2059700
To update the available estimates of CH4 emission levels in the atmosphere and to obtain a multi-year series of observations, monitoring methane leaks from lakes ofnorthern territories is needed. During summer 2016, field measurements of diffuse methane fluxes were carried out on lakes at various stages of the thermokarst process located in Yamalo-Nenets Autonomous District, using the static chamber technique.
Source link: https://doi.org/10.24057/2071-9388-2018-11-1-58-73
The Arctic average atmospheric methane concentration in the Arctic is generally higher than in other regions of the globe. During the cruise in the autumn 2016, we present the findings of measurements of the atmospheric methane concentration and its isotope composition in the East Siberian Arctic Seas. The measurements showed that there could be peaks of high methane in atmospheric surface air above the East Siberian Arctic Shelf, where methane release from the bottom sediments has been suspected.
Source link: https://doi.org/10.24057/2071-9388-2018-11-1-85-92
A technically ready method is used in 2015 using two area-limited transport models at three horizontal resolutions with multiple data sets of emission and boundary conditions as inputs, as inputs. Total CH4 emissions measurement error is 22% and emission errors are heterogeneous at both sector and country scales, with the largest errors occurring in the waste industry due to uncertainty in operation and emission factors, and in Finland due to uncertainties regarding natural wetland emissions.
Source link: https://doi.org/10.1080/16000889.2021.1914989
From late November 2012 to mid-February 2013, we used a new still developing measurement device to investigate the partial pressure of methane in surface seawater and overlying air in the Southern Ocean from late November 2012 to mid-February 2013. The number, which was determined as CH4 saturation ratios obtained by atmospheric CH4 content divided by CH4 content equilibrated with atmospheric CH4, varied between 85 and 185 percent, except for those from south of the Southern limit of Upper Circumpolar Deep Water in the southern reaches. We observed a strong linear correlation between SR and apparent oxygen use south of the Polar Front. We estimated the climatic sea-air flux of CH4 from December to February for the entire Southern Ocean south of 50°S, with 0. 5 Tg yr1 in January, 0. 04 Tg yr1 in January, and 0. 019 Tg yr1 in February.
Source link: https://doi.org/10.1080/16000889.2018.1478594
Climate change has impacted Taiga-tundra boundary ecosystems. Methane emissions in taiga-tundra boundary ecosystems have scarcely been assessed from local to regional scales. Using high-resolution satellite photographs in an ecosystem on permafrost, we estimated CH4 emissions at a local scale and estimated CH4 fluxes with vegetation cover in situ and scaled these results to estimate CH4 emissions at a local scale. Lakes and rivers were CH4 sources, with forest floors remaining mostly neutral in terms of CH4 emissions. Our findings show that: sedge and emergent wetland ecosystems are the hot spots for CH4 emissions, and sparse tree coverage does not regulate local CH4 emissions and balance, as shown by our survey results.
Source link: https://doi.org/10.1080/16000889.2019.1581004
The residual methane emission analysis of ruminant livestock has been proposed as the most accurate phenotype for determining the methanogenic potential of ruminant livestock due to the animal's independence from animal production but in heavy adherence to daily methane emissions. Methane emissions were estimated from individual animals using the GreenFeed Emissions Monitoring system for 21 days during a mean feed intake measurement period of 91 days. For 282 crossbred finishing beef cattle, there were a 30 percent difference in all expressions of methane emissions between high and low RME ranked animals, which meant a 30% difference in all expressions of methane emissions was measured. Using a trans-oesophageal sampling kit, Rumen fluid samples were successfully obtained from 268 animals during the last week of the methane measurement period. In low RME animals, an increased abundance of the genus Methanosphaera and Methanobrevibacter RO clade was discovered within the rumen methanogen community.
Source link: https://doi.org/10.3389/fmicb.2022.855565
To determine methane emissions from natural gas infrastructure, researchers have used Other Test Method 33A. We discuss two methods of uncertainty estimation. paraphrasedoutput measurements' uncertainty was assessed by the second layer of uncertainty estimation, which was a modified Hollinger and Richardson technique that was intended for quantifying the uncertainty of eddy covariance measurements. The resultant minimum uncertainty of 17. 4% was combined measurement uncertainty with that of stochasticity. Methane emissions transport and indirect measurements obtained from the natural gas industry are vital in understanding the transport of methane emissions and indirect measurements.
Source link: https://doi.org/10.3390/environments9040047
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