Control of rumen methanogenesis

During the last decades, considerable research on methane production in the rumen and its inhibition has been carried out. Initially, as methane production represents a significant loss of gross energy in the feed (2–15%), the ultimate goal of such intervention in rumen fermentation was an increase in feed efficiency. A second reason favouring research on methane inhibition is its role in the global warming phenomenon and in the destruction of the ozone layer. In this review, the authors describe briefly several interventions for reducing methane emission by ruminants. The objective can be reached by intervention at the dietary level by ration manipulation (composition, feeding level) or by the use of additives or supplements. Examples of additives are polyhalogenated compounds, ionophores and other antibiotics. Supplementation of the ration with lipids also lowered methanogenesis. More biotechnological interventions, e.g., defaunation, probiotics and introduction of reductive acetogenesis in the rumen, are also mentioned. It can be concluded that drastic inhibition of methane production is not unequivocally successful as a result of several factors, such as: instantaneous inhibition often followed by restoration of methanogenesis due to adaptation of the microbes or degradation of the additive, toxicity for the host animal, negative effects on overall digestion and productive performance. Therefore, methanogenesis and its inhibition cannot be considered as a separate part of rumen fermentation and its consequences on the animal should be taken into account.     

Diurnal variation of methane emissions from an alpine wetland on the eastern edge of Qinghai-Tibetan Plateau

Alpine wetland is a source for CH₄, but little is known about methane emission from such wetland, especially about its diurnal pattern. In this study we tried to probe the diurnal variation in methane emission from alpine wetland vegetation. The average methane emission rate was 9.6 ± 3.4 mg CH₄ m^???2 h^???1. There was an apparent diurnal variation pattern in methane emission with one minor peak at 06:00 and a major one at 15:00. The sunrise peak was consistent with a two-way transport mechanism for plants (convective at daytime and diffusive at night-time). CH₄ emission was found significantly correlated with redox potentials. The afternoon peak could not be explained by diurnal variation in soil temperature, but could be attributable to changes in CH₄ oxidation and production driven by plant gas transport mechanism. The results have important implications for sampling and scaling strategies for estimating methane emission from alpine wetlands.     

The rumen and hindgut as source of ruminant methanogenesis

The advantage of ruminants is their ability to convert fibrous biomass to high quality protein for human nutrition purposes. Rumen fermentation, however, is always associated with the formation of methane — a very effective greenhouse gas. Hindgut fermentation differs from rumen fermentation by a substantially lower methane production and the presence of reductive acetogenesis or dissimilatory sulfate reduction. Sulfate reduction and methanogenesis seem to be mutually exclusive, while methanogenesis and reductive acetogenesis may occur simultaneously in the hindgut. Although acetogenic bacteria have been isolated from the bovine rumen, methanogenesis prevails in the forestomachs. The substitution of acetate for methane as a hydrogen sink in the rumen should increase energy yield for the animal and decrease methane emissions into the environment. Differences in the major hydrogen sinks in both microbial ecosystems are discussed and mainly related to differences in substrate availability and to the absence of protozoa in the hindgut.     

A simplified sampling procedure for the estimation of methane emission in rice fields

Manual closed chamber methods are widely used for CH₄ measurement from rice paddies. Despite diurnal and seasonal variations in CH₄ emissions, fixed sampling times, usually during the day, are used. Here, we monitored CH₄ emission from rice paddies for one complete rice-growing season. Daytime CH₄ emission increased from 0800 h, and maximal emission was observed at 1200 h. Daily averaged CH₄ flux increased during plant growth or fertilizer application and decreased upon drainage of plants. CH₄ measurement results were linearly interpolated and matched with the daily averaged CH₄ emission calculated from the measured results. The time when daily averaged emission and the interpolated CH₄ curve coincided during the daytime was largely invariant within each of the five distinctive periods. One-hourly sampling during each of these five periods was utilized to estimate the emission during each period, and we found that five one-hourly samples during the season accurately reflected the CH₄ emission calculated based on all 136 hourly samples. This new sampling scheme is simple and more efficient than current sampling practices. Previously reported sampling schemes yielded estimates 9 to 32% higher than the measured CH₄ emission, while our suggested scheme yielded an estimate that was only 5% different from that based on all 136-h samples. The sampling scheme proposed in this study can be used in rice paddy fields in Korea and extended worldwide to countries that use similar farming practices. This sampling scheme will help in producing more accurate global methane budget from rice paddy fields.     

Mitigation Strategy to Contain Methane Emission from Rice-Fields

Methane is primarily a biogenic gas, which is implicated in global climate change. Among all the sources of methane emission, paddy fields form the most dominant source. An experiment was conducted with a common paddy crop (Oryza sativa var. Vishnuparag) by amending the soils with different organic manures and biofertilizers with a view to find out an inexpensive strategy to mitigate methane emission from the rice-fields. The results revealed that there was a seasonal change in the CH₄ flux, registering a peak at heading stage in all treatments. The application of rice straw before flooding and the biofertilizer after flooding enhances CH₄ efflux from the rice-fields significantly, while composts of cowdung and leaves did not stimulate CH₄ production and, rather, decreased CH₄ fluxes. As soil pH and temperature were optimum for methanogenesis, it was likely that the organic C and the redox potential mainly modulated methane production and its emission through rice plants.     

Biotic landfill cover treatments for mitigating methane emissions

Landfill methane (CH₄) emissions have been cited as one ofthe anthropogenic gas releases that can and should be controlledto reduce global climate change. This article reviews recent research that identifies ways to enhance microbial consumptionof the gas in the aerobic portion of a landfill cover. Use of these methods can augment CH₄ emission reductions achievedby gas collection or provide a sole means to consume CH₄ atsmall landfills that do not have active gas collection systems.Field studies indicate that high levels of CH₄ removal can be achieved by optimizing natural soil microbial processes. Further, during biotic conversion, not all of the CH₄ carbonis converted to carbon dioxide (CO₂) gas and released to theatmosphere; some of it will be sequestered in microbial biomass.Because biotic covers can employ residuals from other municipalprocesses, financial benefits can also accrue from avoided costsfor residuals disposal.     

Flux estimates from soil methanogenesis and methanotrophy: Landfills,rice paddies,natural wetlands and aerobic soils

Present and future annual methane flux estimates out of landfills, rice paddies and natural wetlands, as well as the sorption capacity of aerobic soils for atmospheric methane, are assessed. The controlling factors and uncertainties with regard to soil methanogenesis and methanotrophy are also briefly discussed.The actual methane emission rate out of landfills is estimated at about 40 Tg yr^–1. Changes in waste generation, waste disposal and landfill management could have important consequences on future methane emissions from waste dumps. If all mitigating options can be achieved towards the year 2015, the CH₄ emission rate could be reduced to 13 Tg yr^–1. Otherwise, the emission rate from landfills could increase to 63 Tg yr^–1 by the year 2025. Methane emission from rice paddies is estimated at 60 Tg yr^–1. The predicted increase of rice production between the years 1990 and 2025 could cause an increase of the CH₄ emission rate to 78 Tg yr^–1 by the year 2025. When mitigating options are taken, the emission rate could be limited to 56 Tg yr^–1. The methane emission rate from natural wetlands is about 110 Tg yr^–1. Because changes in the expanse of natural wetland area are difficult to assess, it is assumed that methane emission from natural wetlands would remain constant during the next 100 years. Because of uncertainties with regard to large potential soil sink areas (e.g. savanna, tundra and desert), the global sorption capacity of aerobic soils for atmospheric methane is not completely clear. The actual estimate is 30 Tg yr^–1.In general, the net contribution of soils and landfills to atmospheric methane is estimated at 180 Tg yr^–1 (210 Tg yr^–1 emission, 30 Tg yr^–1 sorption). This is 36% of the global annual methane flux (500 Tg yr^–1).     

A comparison of emission calculations using different modeled indicators with 1-year online measurements

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm’s characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow^?1 year^?1) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow^?1 year^?1 (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between ?6.4 % and 10.5 %), compared with findings from the literature.     

Greenhouse gas emissions from forestry,land-use changes,and agriculture in Tanzania

The purpose of the study was to identify and quantify anthropogenic sources and sinks of greenhouse gases from forestry, land-use changes and agriculture in Tanzania. The 1990 inventory revealed that, in the land-use sector, methane (CH₄) and carbon dioxide (CO₂) are the primary gases emitted. Enteric fermentation in livestock production systems is the largest source of CH₄. Although deforestation results in greenhouse gas emissions, the managed forests of Tanzania are a major CO₂ sink.     

Multisource emission retrieval within a biogas plant based on inverse dispersion calculations—a real-life example

Open digestate storage tanks were identified as one of the main methane (CH₄) emitters of a biogas plant. The main purpose of this paper is to determine these emission rates using an inverse dispersion technique in conjunction with open-path tunable diode laser spectroscopy (OP-TDLS) concentration measurements for multisource reconstruction. Since the condition number, a measure of “ill-conditioned” matrices, strongly influences the accuracy of source reconstruction, it is used as a diagnostic of error sensitivity. The investigations demonstrate that the condition number for a given source-sensor configuration in the highly disturbed flow field within the plant significantly depends on the meteorological conditions (e.g., wind speed, stratification, wind direction, etc.). The CH₄ emissions are retrieved by removing unrepresentative periods with high condition numbers, which indicate uncertainty in recovering the individual sources. In a final step, the CH₄ emissions are compared with the maximum biological methane potential (BMP) in the digestate analyzed under laboratory conditions. The retrieved methane emission rates represent an average of 50 % of the maximum BMP of the stored digestate in the winter months, while they comprised an average of 85 % during the measurement campaigns in the summer months. The results indicate that the open tanks have the potential to represent a substantial emission source even during colder periods.