988 resultados para METHANE HYDRATE


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Methane is a potent greenhouse gas with a global warming potential ∼28 times that of carbon dioxide. Consequently, sources and sinks that influence the concentration of methane in the atmosphere are of great interest. In Australia, agriculture is the primary source of anthropogenic methane emissions (60.4% of national emissions, or 3260kt-1methaneyear-1, between 1990 and 2011), and cropping and grazing soils represent Australia's largest potential terrestrial methane sink. As of 2011, the expansion of agricultural soils, which are ∼70% less efficient at consuming methane than undisturbed soils, to 59% of Australia's land mass (456Mha) and increasing livestock densities in northern Australia suggest negative implications for national methane flux. Plant biomass burning does not appear to have long-term negative effects on methane flux unless soils are converted for agricultural purposes. Rice cultivation contributes marginally to national methane emissions and this fluctuates depending on water availability. Significant available research into biological, geochemical and agronomic factors has been pertinent for developing effective methane mitigation strategies. We discuss methane-flux feedback mechanisms in relation to climate change drivers such as temperature, atmospheric carbon dioxide and methane concentrations, precipitation and extreme weather events. Future research should focus on quantifying the role of Australian cropping and grazing soils as methane sinks in the national methane budget, linking biodiversity and activity of methane-cycling microbes to environmental factors, and quantifying how a combination of climate change drivers will affect total methane flux in these systems.

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Viruses of prokaryotes (phages) are obligate microbial pathogens that can, in the lytic phase of development, infect and lyse their respective bacterial or archaeal hosts. As such, these viruses can reduce the population density of their hosts rapidly, and have been viewed as possible agents of biological control (phage therapy). Phage therapy is becoming increasingly important as a means of eradicating or controlling microbial populations as the use of antibiotics and chemical treatments becomes both less effective and less publicly acceptable. Phage therapy has therefore been raised as a potential strategy to reduce methane (CH 4) emissions from ruminants, providing an innovative biological approach, harnessing the potent, yet targeted, biocidal attributes of these naturally occurring microbial predators.

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Viruses of prokaryotes (phages) are obligate microbial pathogens that can, in the lytic phase of development, infect and lyse their respective bacterial or archaeal hosts. As such, these viruses can reduce the population density of their hosts rapidly, and have been viewed as possible agents of biological control (phage therapy). Phage therapy is becoming increasingly important as a means of eradicating or controlling microbial populations as the use of antibiotics and chemical treatments becomes both less effective and less publicly acceptable. Phage therapy has therefore been raised as a potential strategy to reduce methane (CH4) emissions from ruminants, providing an innovative biological approach, harnessing the potent, yet targeted, biocidal attributes of these naturally occurring microbial predators.

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Spot measurements of methane emission rate (n = 18 700) by 24 Angus steers fed mixed rations from GrowSafe feeders were made over 3- to 6-min periods by a GreenFeed emission monitoring (GEM) unit. The data were analysed to estimate daily methane production (DMP; g/day) and derived methane yield (MY; g/kg dry matter intake (DMI)). A one-compartment dose model of spot emission rate v. time since the preceding meal was compared with the models of Wood (1967) and Dijkstra et al. (1997) and the average of spot measures. Fitted values for DMP were calculated from the area under the curves. Two methods of relating methane and feed intakes were then studied: the classical calculation of MY as DMP/DMI (kg/day); and a novel method of estimating DMP from time and size of preceding meals using either the data for only the two meals preceding a spot measurement, or all meals for 3 days prior. Two approaches were also used to estimate DMP from spot measurements: fitting of splines on a 'per-animal per-day' basis and an alternate approach of modelling DMP after each feed event by least squares (using Solver), summing (for each animal) the contributions from each feed event by best-fitting a one-compartment model. Time since the preceding meal was of limited value in estimating DMP. Even when the meal sizes and time intervals between a spot measurement and all feeding events in the previous 72 h were assessed, only 16.9% of the variance in spot emission rate measured by GEM was explained by this feeding information. While using the preceding meal alone gave a biased (underestimate) of DMP, allowing for a longer feed history removed this bias. A power analysis taking into account the sources of variation in DMP indicated that to obtain an estimate of DMP with a 95% confidence interval within 5% of the observed 64 days mean of spot measures would require 40 animals measured over 45 days (two spot measurements per day) or 30 animals measured over 55 days. These numbers suggest that spot measurements could be made in association with feed efficiency tests made over 70 days. Spot measurements of enteric emissions can be used to define DMP but the number of animals and samples are larger than are needed when day-long measures are made.

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Few data exist on direct greenhouse gas emissions from pen manure at beef feedlots. However, emission inventories attempt to account for these emissions. This study used a large chamber to isolate N2O and CH4 emissions from pen manure at two Australian commercial beef feedlots (stocking densities, 13-27 m(2) head) and related these emissions to a range of potential emission control factors, including masses and concentrations of volatile solids, NO3-, total N, NH4+, and organic C (OC), and additional factors such as total manure mass, cattle numbers, manure pack depth and density, temperature, and moisture content. Mean measured pen N2O emissions were 0.428 kg ha(-1) d(-1) (95% confidence interval [CI], 0.252-0.691) and 0.00405 kg ha(-1) d(-1) (95% CI, 0.00114-0.0110) for the northern and southern feedlots, respectively. Mean measured CH4 emission was 0.236 kg ha(-1) d(-1) (95% CI, 0.163-0.332) for the northern feedlot and 3.93 kg ha(-1) d(-1) (95% CI, 2.58-5.81) for the southern feedlot. Nitrous oxide emission increased with density, pH, temperature, and manure mass, whereas negative relationships were evident with moisture and OC. Strong relationships were not evident between N2O emission and masses or concentrations of NO3- or total N in the manure. This is significant because many standard inventory calculation protocols predict N2O emissions using the mass of N excreted by the animal.

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The methods for estimating methane emissions from cattle as used in the Australian national inventory are based on older data that have now been superseded by a large amount of more recent data. Recent data suggested that the current inventory emissions estimates can be improved. To address this issue, a total of 1034 individual animal records of daily methane production (MP) was used to reassess the relationship between MP and each of dry matter intake (DMI) and gross energy intake (GEI). Data were restricted to trials conducted in the past 10 years using open-circuit respiration chambers, with cattle fed forage-based diets (forage >70%). Results from diets considered to inhibit methanogenesis were omitted from the dataset. Records were obtained from dairy cattle fed temperate forages (220 records), beef cattle fed temperate forages (680 records) and beef cattle fed tropical forages (133 records). Relationships were very similar for all three production categories and single relationships for MP on a DMI or GEI basis were proposed for national inventory purposes. These relationships were MP (g/day) = 20.7 (±0.28) × DMI (kg/day) (R2 = 0.92, P < 0.001) and MP (MJ/day) = 0.063 (±0.008) × GEI (MJ/day) (R2 = 0.93, P < 0.001). If the revised MP (g/day) approach is used to calculate Australia’s national inventory, it will reduce estimates of emissions of forage-fed cattle by 24%. Assuming a global warming potential of 25 for methane, this represents a 12.6 Mt CO2-e reduction in calculated annual emissions from Australian cattle.

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Metanogeenit ovat hapettomissa oloissa eläviä arkkien pääryhmään kuuluvia mikrobeja, joiden ainutlaatuisen aineenvaihdunnan seurauksena syntyy metaania. Ilmakehässä metaani on voimakas kasvihuonekaasu. Yksi suurimmista luonnon metaanilähteistä ovat kosteikot. Pohjoisten soiden metaanipäästöt vaihtelevat voimakkaasti eri soiden välillä ja yhden suon sisälläkin, riippuen muun muassa vuodenajasta, suotyypistä ja kasvillisuudesta. Väitöskirjatyössä tutkittiin metaanipäästöjen vaihtelun mikrobiologista taustaa. Tutkimuksessa selvitettiin suotyypin, vuodenajan, tuhkalannoituksen ja turvesyvyyden vaikutusta metanogeeniyhteisöihin sekä metaanintuottoon kolmella suomalaisella suolla. Lisäksi tutkittiin ei-metanogeenisia arkkeja ja bakteereita, koska ne muodostavat metaanin tuoton lähtöaineet osana hapetonta hajotusta. Mikrobiyhteisöt analysoitiin DNA- ja RNA-lähtöisillä, polymeraasiketjureaktioon (PCR) perustuvilla menetelmillä. Merkkigeeneinä käytettiin metaanin tuottoon liittyvää mcrA-geeniä sekä arkkien ja bakteerien ribosomaalista 16S RNA-geeniä. Metanogeeniyhteisöt ja metaanintuotto erosivat huomattavasti happaman ja vähäravinteisen rahkasuon sekä ravinteikkaampien sarasoiden välillä. Rahkasuolta löytyi lähes yksinomaan Methanomicrobiales-lahkon metanogeeneja, jotka tuottavat metaania vedystä ja hiilidioksidista. Sarasoiden metanogeeniyhteisöt olivat monimuotoisempia, ja niillä esiintyi myös asetaattia käyttäviä metanogeeneja. Vuodenaika vaikutti merkittävästi metaanintuottoon. Talvella havaittiin odottamattoman suuri metaanintuottopotentiaali sekä viitteitä aktiivisista metanogeeneista. Arkkiyhteisön koostumus sen sijaan vaihteli vain vähän. Tuhkalannoitus, jonka tarkoituksena on edistää puiden kasvua ojitetuilla soilla, ei merkittävästi vaikuttanut metaanintuottoon tai -tuottajiin. Ojitetun suon yhteisöt kuitenkin muuttuivat turvesyvyyden mukaan. Vertailtaessa erilaisia PCR-menetelmiä todettiin, että kolmella mcrA-geeniin kohdistuvalla alukeparilla havaittiin pääosin samat ojitetun suon metanogeenit, mutta lajien runsaussuhteet riippuvat käytetyistä alukkeista. Soilla havaitut bakteerit kuuluivat pääjaksoihin Deltaproteobacteria, Acidobacteria ja Verrucomicrobia. Lisäksi löydettiin Crenarchaeota-pääjakson ryhmiin 1.1c ja 1.3 kuuluvia ei-metanogeenisia arkkeja. Tulokset ryhmien esiintymisestä hapettomassa turpeessa antavat lähtökohdan selvittää niiden mahdollisia vuorovaikutuksia metanogeenien kanssa. Tutkimuksen tulokset osoittivat, että metanogeeniyhteisön koostumus heijastaa metaanintuottoon vaikuttavia kemiallisia tai kasvillisuuden vaihteluita kuten suotyyppiä. Soiden metanogeenien ja niiden fysiologian parempi tuntemus voi auttaa ennustamaan ympäristömuutosten vaikutusta soiden metaanipäästöihin.

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A novel compound obtained by the oxidation of the title compound with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone has been assigned structure (5) on the basis of spectral data and X-ray crystal structure analysis.

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Lakes serve as sites for terrestrially fixed carbon to be remineralized and transferred back to the atmosphere. Their role in regional carbon cycling is especially important in the Boreal Zone, where lakes can cover up to 20% of the land area. Boreal lakes are often characterized by the presence of a brown water colour, which implies high levels of dissolved organic carbon from the surrounding terrestrial ecosystem, but the load of inorganic carbon from the catchment is largely unknown. Organic carbon is transformed to methane (CH4) and carbon dioxide (CO2) in biological processes that result in lake water gas concentrations that increase above atmospheric equilibrium, thus making boreal lakes as sources of these important greenhouse gases. However, flux estimates are often based on sporadic sampling and modelling and actual flux measurements are scarce. Thus, the detailed temporal flux dynamics of greenhouse gases are still largely unknown. ----- One aim here was to reveal the natural dynamics of CH4 and CO2 concentrations and fluxes in a small boreal lake. The other aim was to test the applicability of a measuring technique for CO2 flux, i.e. the eddy covariance (EC) technique, and a computational method for estimation of primary production and community respiration, both commonly used in terrestrial research, in this lake. Continuous surface water CO2 concentration measurements, also needed in free-water applications to estimate primary production and community respiration, were used over two open water periods in a study of CO2 concentration dynamics. Traditional methods were also used to measure gas concentration and fluxes. The study lake, Valkea-Kotinen, is a small, humic, headwater lake within an old-growth forest catchment with no local anthropogenic disturbance and thus possible changes in gas dynamics reflect the natural variability in lake ecosystems. CH4 accumulated under the ice and in the hypolimnion during summer stratification. The surface water CH4 concentration was always above atmospheric equilibrium and thus the lake was a continuous source of CH4 to the atmosphere. However, the annual CH4 fluxes were small, i.e. 0.11 mol m-2 yr-1, and the timing of fluxes differed from that of other published estimates. The highest fluxes are usually measured in spring after ice melt but in Lake Valkea-Kotinen CH4 was effectively oxidised in spring and highest effluxes occurred in autumn after summer stratification period. CO2 also accumulated under the ice and the hypolimnetic CO2 concentration increased steadily during stratification period. The surface water CO2 concentration was highest in spring and in autumn, whereas during the stable stratification it was sometimes under atmospheric equilibrium. It showed diel, daily and seasonal variation; the diel cycle was clearly driven by light and thus reflected the metabolism of the lacustrine ecosystem. However, the diel cycle was sometimes blurred by injection of hypolimnetic water rich in CO2 and the surface water CO2 concentration was thus controlled by stratification dynamics. The highest CO2 fluxes were measured in spring, autumn and during those hypolimnetic injections causing bursts of CO2 comparable with the spring and autumn fluxes. The annual fluxes averaged 77 (±11 SD) g C m-2 yr-1. In estimating the importance of the lake in recycling terrestrial carbon, the flux was normalized to the catchment area and this normalized flux was compared with net ecosystem production estimates of -50 to 200 g C m-2 yr-1 from unmanaged forests in corresponding temperature and precipitation regimes in the literature. Within this range the flux of Lake Valkea-Kotinen yielded from the increase in source of the surrounding forest by 20% to decrease in sink by 5%. The free water approach gave primary production and community respiration estimates of 5- and 16-fold, respectively, compared with traditional bottle incubations during a 5-day testing period in autumn. The results are in parallel with findings in the literature. Both methods adopted from the terrestrial community also proved useful in lake studies. A large percentage of the EC data was rejected, due to the unfulfilled prerequisites of the method. However, the amount of data accepted remained large compared with what would be feasible with traditional methods. Use of the EC method revealed underestimation of the widely used gas exchange model and suggests simultaneous measurements of actual turbulence at the water surface with comparison of the different gas flux methods to revise the parameterization of the gas transfer velocity used in the models.

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We report on the formation of tetrahydrofuran clathrate hydrate studied by x-ray Raman scattering measurements at the oxygen K edge. A comparison of x-ray Raman spectra measured from water-tetrahydrofuran mixtures and tetrahydrofuran hydrate at different temperatures supports stochastic hydrate formation models rather than models assuming hydrate precursors. This is confirmed by molecular dynamics simulations and density functional theory calculations of x-ray Raman spectra. In addition, changes in the spectra of tetrahydrofuran hydrate with temperatures close to the hydrate's dissociation temperature were observed and may be connected to changes in hydrate's local structure due to the formation of hydrogen bonds between guest and water molecules.

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Transition metal ammonium double sulphates (NH4)2M(SO4)2· 6H2O, where M = Fe, Co and Ni react with hydrazine hydrate in air giving crystalline compounds of the general formula (N2H5) [M(N2H3COO)3] H2O. The reaction proceeds through (N2H5)2 M(SO4)2, · 3N2H4, (N2H5)2 [M(OH)4 · (N2H4)2], M(N2H3COO)2 · (N2H4)2 and N2H5 [M(N2 H3 COO)3] intermediates. The reaction sequence is followed by chemical analysis and infrared spectra. A possible reaction mechanism has been suggested.

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Molecular dynamics calculations on methane sorbed in NaY (Si/Al = 3.0) employing realistic methane-methane and methane-zeolite intermolecular potential functions at different temperatures (50, 150, 220, and 300 K) and concentrations (2, 4, 6, and 8 molecules/cage) are reported. The thermodynamic results are in agreement with the available experimental data. Guest-guest and guest-host radial distribution functions (rdfs), energy distribution functions, distribution of cage occupancy, center-of-cage-center-of-mass (coc-com) rdfs, velocity autocorrelation functions for com and angular motion and the Fourier transformed power spectra, and diffusion coefficients are presented as a function of temperature and concentration. At 50 K, methane is localized near the adsorption site. Site-site migration and essentially free rotational motion are observed at 150 K. Molecules preferentially occupy the region near the inner surface of the alpha-cage. The vibrational frequencies for the com of methane shift toward higher values with decreasing temperature and increasing adsorbate concentration. The observed frequencies for com motion are 36, 53, and 85 cm-1 and for rotational motion at 50 K, 95 and 150 cm-1 in agreement with neutron scattering data. The diffusion coefficients show a type I behavior as a function of loading in agreement with NMR measurements. Cage-to-cage diffusion is found to be always mediated by the surface.

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Eddy covariance (EC)-flux measurement technique is based on measurement of turbulent motions of air with accurate and fast measurement devices. For instance, in order to measure methane flux a fast methane gas analyser is needed which measures methane concentration at least ten times in a second in addition to a sonic anemometer, which measures the three wind components with the same sampling interval. Previously measurement of methane flux was almost impossible to carry out with EC-technique due to lack of fast enough gas analysers. However during the last decade new instruments have been developed and thus methane EC-flux measurements have become more common. Performance of four methane gas analysers suitable for eddy covariance measurements are assessed in this thesis. The assessment and comparison was performed by analysing EC-data obtained during summer 2010 (1.4.-26.10.) at Siikaneva fen. The four participating methane gas analysers are TGA-100A (Campbell Scientific Inc., USA), RMT-200 (Los Gatos Research, USA), G1301-f (Picarro Inc., USA) and Prototype-7700 (LI-COR Biosciences, USA). RMT-200 functioned most reliably throughout the measurement campaign and the corresponding methane flux data had the smallest random error. In addition, methane fluxes calculated from data obtained from G1301-f and RMT-200 agree remarkably well throughout the measurement campaign. The calculated cospectra and power spectra agree well with corresponding temperature spectra. Prototype-7700 functioned only slightly over one month in the beginning of the measurement campaign and thus its accuracy and long-term performance is difficult to assess.

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Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).