Predict Methane Emissions Research Articles

Prediction of methane emissions from dairy cows using multiple regression analysis

The UK is bound by the UN Framework Convention on climate change to reduce methane emissions to below 1990 levels by the year 2000. The Kyoto protocol requires a further cut of 12.5% by 2010. Ruminants are estimated to produce 74 Tg of methane per year (Benchar et al. 1998) which represents about 15% of total emissions (Crutzen et al., 1986). Therefore any reduction in the release of methane gas by enteric fermentation from the dairy herd is environmentally important. The objective of this study was to use data obtained from calorimetry trials to generate multiple regression equations predicting the levels and variability of methane emissions from dairy cows.

Methane emission from free-ranging sheep: a comparison of two measurement methods

Methane emissions from a flock of 14, 1-year old sheep grazing on a grass and legume pasture were measured using a micrometeorological mass-balance method and a sulphur hexaflouride (SF 6) tracer technique. The former measured the mean emission, over 45 min intervals, from all the sheep within a fenced 24 m×24 m enclosure, from the enrichment of methane (CH 4) in air as it passed over the sheep. The tracer technique measured emissions from a subset of 7 individual animals over 24 h periods from measurements of CH 4 and SF 6 concentrations in air exhaled by the sheep, and from the known rate of release of SF 6 from small permeation tubes placed in the animals’ rumens. Both methods gave highly similar results for 4 out of 5 days. When the species composition of dietary intake was steady during the last two days of measurement, the mean emission rate from the mass-balance method was 11.9±1.5 (SEM) g CH 4 sheep -1 d -1, while the rate from the tracer technique was 11.7±0.4 (SEM) g CH 4 sheep -1 d -1. These rates are for sheep with mean live mass of 27 kg, with a measured dry matter intake of 508 g sheep -1 d -1 and pasture dry matter digestibility of 69.5%. There was close agreement between these measurements and estimates from algorithms used to predict methane emissions from sheep for the Australian National Greenhouse Gas Inventory.

Prediction of methane emissions from beef cattle in tropical production systems

The northern beef cattle herd accounts for more than half of Australia’s beef cattle population, and is a major source of anthropogenic methane emissions for Australia. National Greenhouse Gas Inventory predictions of methane output from Australian beef cattle are based on a predictive equation developed for British breeds of sheep and cattle offered temperate forage-based diets. However, tropical forage diets offered to cattle in northern Australia differ markedly from temperate forage-based diets used in the United Kingdom to develop the predictive equations. In this paper we review recent respiration chamber measurements of daily methane production for Brahman cattle offered a tropical forage or high grain diet, and compare them with values predicted using methodologies of the Australian National Greenhouse Gas Inventory Committee and the Intergovernmental Panel on Climate Change. We conclude that a reliable inventory of methane emissions for cattle in northern Australia can only be achieved after a wider range of tropical forage species has been investigated. Some opportunities for reducing methane emissions of beef cattle by dietary manipulation are discussed.

A semi‐empirical model of methane emission from flooded rice paddy soils

AbstractReliable regional or global estimates of methane emissions from flooded rice paddy soils depend on an examination of methodologies by which the current high variability in the estimates might be reduced. One potential way to do this is the development of predictive models. With an understanding of the processes of methane production, oxidation and emission, a semi‐empirical model, focused on the contributions of rice plants to the processes and also the influence of environmental factors, was developed to predict methane emission from flooded rice fields. A simplified version of the model was also derived to predict methane emission in a more practical manner. In this study, it was hypothesized that methanogenic substrates are primarily derived from rice plants and added organic matter. Rates of methane production in flooded rice soils are determined by the availability of methanogenic substrates and the influence of environmental factors. Rice growth and development control the fraction of methane emitted. The amount of methane transported from the soil to the atmosphere is determined by the rates of production and the emitted fraction. Model validation against observations from single rice growing seasons in Texas, USA demonstrated that the seasonal variation of methane emission is regulated by rice growth and development. A further validation of the model against measurements from irrigated rice paddy soils in various regions of the world, including Italy, China, Indonesia, Philippines and the United States, suggests that methane emission can be predicted from rice net productivity, cultivar character, soil texture and temperature, and organic matter amendments.

Methane emissions from sheep

A total of 1137 observations from sheep of different age fed with rations of different composition were collected from the literature. This study used measures of methane emissions from sheep under different feeding conditions to compute regression equations to predict methane emissions from ration descriptive variables. It was also tested whether the material validated other common prediction equations. Methane emissions from all sheep averaged 22.15 g day −1. For growing sheep and adult sheep they equalled 23.16 g day −1 and 20.48 g day −1, respectively, with significant differences ( P ≤ 0.05). The percentage loss of methane (% of gross energy intake) averaged 7.22, 7.23 and 7.22%, respectively. Methane emissions increased ( P ≤ 0.05) with increasing live weight, feeding level measured as multiples of maintenance and digestibility of dry matter and decreased for rations with wider ratios of crude fibre intake and intake of N-free extracts. Crude fibre content in the ration and energy density of the ration showed no clearly identifiable effect on methane emissions.

96/01399 Simulator for degasification, methane emission prediction and mine ventilation

96/01399 Simulator for degasification, methane emission prediction and mine ventilation

Predicting Methane Emission from Bryophyte Distribution in Northern Canadian Peatlands

A predictive model for bryophyte distribution, water table position, and seasonal mean methane (CH4) emission was developed for two areas of northern peatland: the Clay Belt of Ontario and the Labrador Trough of Quebec. Water table position and CH4 flux were the most important environmental variables in canonical correspondence analyses (CCA) of bryophyte data. Water chemistry constituted a second environmental gradient, independent of hydrology and CH4 flux. Weighted averaging regression and calibration were used to develop a model for predicting log CH4 flux from bryophyte distribution. The model showed an increase in log CH4 flux from hummock to carpet and pool species, corresponding with a decrease in height above the mean water table position. The exceptions were rich—fen pool species, which had low CH4 flux optima in spite of their moisture status. Tolerances were greatest for mid—hummock species and least for carpet and pool species. No overlap in tolerances occurred between hummock and pool species, suggesting that species at either end of the height gradient are the best predictors of CH4 flux. Error analyses showed that bryophytes are equally as effective as water table position for predicting mean CH4 flux even though bryophytes are only surrogates for the degree of anaerobism/aerobism in the peat profile. Bryophytes are distributed in well—defined zones along microtopgraphic gradients; they integrate long—term changes in the water table, which fluctuates on a daily and season basis along with CH4 flux, and may be more easily mapped with remote—sensing techniques. Bryophytes, however, are only useful for predicting CH4 flux within a region; similar species values cannot be extrapolated to other northern peatlands where different climatic and biogeochemical factors may result in different ranges of CH4 emission. The model may be used in paleoreconstructions of methane emission and for biological monitoring of climate change.

A simple process-based model to predict methane emission from flooded fields

A simple process-based model to predict methane emission from flooded fields

Parameters for predicting methane emission from the exposed surface of coal seams

Parameters for predicting methane emission from the exposed surface of coal seams