caa a22 4500 44536694X CHVBK 20180317142933.0 cr unu---uuuuu 170323e20110101xx s 000 0 eng 10.1007/s00484-010-0356-7 doi (NATIONALLICENCE)springer-10.1007/s00484-010-0356-7 Measurement and prediction of enteric methane emission [Elektronische Daten] [Veerasamy Sejian, Rattan Lal, Jeffrey Lakritz, Thaddeus Ezeji] The greenhouse gas (GHG) emissions from the agricultural sector account for about 25.5% of total global anthropogenic emission. While CO2 receives the most attention as a factor relative to global warming, CH4, N2O and chlorofluorocarbons (CFCs) also cause significant radiative forcing. With the relative global warming potential of 25 compared with CO2, CH4 is one of the most important GHGs. This article reviews the prediction models, estimation methodology and strategies for reducing enteric CH4 emissions. Emission of CH4 in ruminants differs among developed and developing countries, depending on factors like animal species, breed, pH of rumen fluid, ratio of acetate:propionate, methanogen population, composition of diet and amount of concentrate fed. Among the ruminant animals, cattle contribute the most towards the greenhouse effect through methane emission followed by sheep, goats and buffalos, respectively. The estimated CH4 emission rate per cattle, buffaloe, sheep and goat in developed countries are 150.7, 137, 21.9 and 13.7 (g/animal/day) respectively. However, the estimated rates in developing countries are significantly lower at 95.9 and 13.7 (g/animal/day) per cattle and sheep, respectively. There exists a strong interest in developing new and improving the existing CH4 prediction models to identify mitigation strategies for reducing the overall CH4 emissions. A synthesis of the available literature suggests that the mechanistic models are superior to empirical models in accurately predicting the CH4 emission from dairy farms. The latest development in prediction model is the integrated farm system model which is a process-based whole-farm simulation technique. Several techniques are used to quantify enteric CH4 emissions starting from whole animal chambers to sulfur hexafluoride (SF6) tracer techniques. The latest technology developed to estimate CH4 more accurately is the micrometeorological mass difference technique. Because the conditions under which animals are managed vary greatly by country, CH4 emissions reduction strategies must be tailored to country-specific circumstances. Strategies that are cost effective, improve productivity, and have limited potential negative effects on livestock production hold a greater chance of being adopted by producers. It is also important to evaluate CH4 mitigation strategies in terms of the total GHG budget and to consider the economics of various strategies. Although reductions in GHG emissions from livestock industries are seen as high priorities, strategies for reducing emissions should not reduce the economic viability of enterprises. ISB, 2010 Global warming potential nationallicence Prediction models for enteric CH4 nationallicence Respiratory chamber nationallicence SF6 nationallicence Whole farm model nationallicence Sejian Veerasamy Adaptation Physiology Laboratory, Division of Physiology & Biochemistry, Central Sheep & Wool Research Insitute, 304501, Avikanagar, Via-Jaipur, Rajasthan, India aut Lal Rattan Carbon Management and Sequestration Centre, School of Environment and Natural Resources, The Ohio State University, 43210, Columbus, OH, USA aut Lakritz Jeffrey Department of Veterinary Clinical Sciences, The Ohio State University, Columbus, OH, USA aut Ezeji Thaddeus Department of Animal Sciences, The Ohio State University & OARDC, 44691, Wooster, OH, USA aut International Journal of Biometeorology Springer-Verlag 55/1(2011-01-01), 1-16 0020-7128 55:1<1 2011 55 484 https://doi.org/10.1007/s00484-010-0356-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00484-010-0356-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sejian Veerasamy Adaptation Physiology Laboratory, Division of Physiology & Biochemistry, Central Sheep & Wool Research Insitute, 304501, Avikanagar, Via-Jaipur, Rajasthan, India aut NATIONALLICENCE 700 1- Lal Rattan Carbon Management and Sequestration Centre, School of Environment and Natural Resources, The Ohio State University, 43210, Columbus, OH, USA aut NATIONALLICENCE 700 1- Lakritz Jeffrey Department of Veterinary Clinical Sciences, The Ohio State University, Columbus, OH, USA aut NATIONALLICENCE 700 1- Ezeji Thaddeus Department of Animal Sciences, The Ohio State University & OARDC, 44691, Wooster, OH, USA aut NATIONALLICENCE 773 0- International Journal of Biometeorology Springer-Verlag 55/1(2011-01-01), 1-16 0020-7128 55:1<1 2011 55 484 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer