National inventories of methane (CH 4 ) emission from manure management are based on guidelines from the Intergovernmental Panel on Climate Change using countryspecific emission factors. These calculations must be simple and, consequently, the effects of management practices and environmental conditions are only crudely represented in the calculations. The intention of this review is to develop a detailed understanding necessary for developing accurate models for calculating CH 4 emission from liquid manure, with particular focus on the microbiological conversion of organic matter to CH 4 . Themes discussed are (a) the liquid manure environment; (b) methane production processes from a modeling perspective; (c) development and adaptation of methanogenic communities; (d) mass and electron conservation; (e) steps limiting CH 4 production; (f) inhibition of methanogens; (g) temperature effects on CH 4 production; and (h) limits of existing estimation approaches. We conclude that a model must include calculation of microbial response to variations in manure temperature, substrate availability and age, and management system, because these variables substantially affect CH 4 production. Methane production can be reduced by manipulating key variables through management procedures, and the effects may be taken into account by including a microbial component in the model. When developing new calculation procedures, it is important to include reasonably accurate algorithms of microbial adaptation. This review presents concepts for these calculations and ideas for how these may be carried out. A need for better quantification of hydrolysis kinetics is identified, and the importance of short-and long-term microbial adaptation is highlighted.
Gaseous emissions from livestock production are complex mixtures including ammonia, methane, volatile organic compounds (VOC) and H 2 S. These contribute to eutrophication, reduced air quality, global warming and odor nuisance. It is imperative that these gases are mitigated in an environmentally sustainable manner. We present the discovery of a microbial inhibitor combo consisting of tannic acid and sodium fluoride (TA-NaF), which exhibits clear synergistic inhibition of ammonia production in pure bacteria culture and in pig manure while simultaneously inhibiting methane and odorant (H 2 S and VOC) emissions. In laboratory headspace experiments on pig manure, we used proton-transfer-reaction mass spectrometry and cavity ring-down spectroscopy to measure the effect of TA-NaF on gaseous emissions. Ammonia emission was reduced by more than 95%, methane by up to ~99% and odor activity value by more than 50%. Microbial community analysis and gas emission data suggest that TA-NaF acts as an efficient generic microbial inhibitor, and we hypothesize that the synergistic inhibitory effect on ammonia production is related to tannic acid causing cell membrane leakage allowing fluoride ions easy access to urease.
Reduced sulfur compounds emitted from livestock production cause odor nuisance for local residents. The microbial processes responsible for this are not well described in swine manure and a method for monitoring the biological processes is necessary to develop strategic abatement technologies. In this study, Proton-Transfer-Reaction Mass Spectrometry and isotope-labeled sulfate were combined and applied to elucidate the sulfur processes in swine manure with high time resolution. We successfully monitored reduction of isotope S labeled sulfate into correspondingS hydrogen sulfide and found that some of the S hydrogen sulfide was further methylated intoS methanethiol. The isotope patterns in reduced sulfur compounds together with usage of inhibitors enabled us to calculate a sulfate reduction rate of 1.03 ± 0.18 mM/day equivalent to 76.9 ± 3.0% of total hydrogen sulfide emissions. Cysteine degradation constituted 20.2 ± 2.7% of the total hydrogen sulfide produced and the remaining hydrogen sulfide came from demethylation of methanethiol and dimethyl sulfide. Another source to methanethiol, besides hydrogen sulfide methylation, was methionine degradation, which contributed with 78.3 ± 2.5% of the methanethiol production, whereas the remaining 21.7 ± 2.5% came from hydrogen sulfide methylation. This study suggests, therefore, that emissions of odorous sulfur compounds from swine manure can be reduced by inhibiting methionine degradation and sulfate reduction.
Liquid manure (slurry) from livestock releases methane (CH4) that contributes significantly to global warming. Existing models for slurry CH4 production—used for mitigation and inventories—include effects of organic matter loading, temperature, and retention time but cannot predict important effects of management, or adequately capture essential temperature-driven dynamics. Here we present a new model that includes multiple methanogenic groups whose relative abundance shifts in response to changes in temperature or other environmental conditions. By default, the temperature responses of five groups correspond to those of four methanogenic species and one uncultured methanogen, although any number of groups could be defined. We argue that this simple mechanistic approach is able to describe both short- and long-term responses to temperature where other existing approaches fall short. The model is available in the open-source R package ABM (https://github.com/sashahafner/ABM) as a single flexible function that can include effects of slurry management (e.g., removal frequency and treatment methods) and changes in environmental conditions over time. Model simulations suggest that the reduction of CH4 emission by frequent emptying of slurry pits is due to washout of active methanogens. Application of the model to represent a full-scale slurry storage tank showed it can reproduce important trends, including a delayed response to temperature changes. However, the magnitude of predicted emission is uncertain, primarily as a result of sensitivity to the hydrolysis rate constant, due to a wide range in reported values. Results indicated that with additional work—particularly on the magnitude of hydrolysis rate—the model could be a tool for estimation of CH4 emissions for inventories.
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