Literature DB >> 20809221

Measurement and prediction of enteric methane emission.

Veerasamy Sejian1, Rattan Lal, Jeffrey Lakritz, Thaddeus Ezeji.   

Abstract

The greenhouse gas (GHG) emissions from the agricultural sector account for about 25.5% of total global anthropogenic emission. While CO(2) receives the most attention as a factor relative to global warming, CH(4), N(2)O and chlorofluorocarbons (CFCs) also cause significant radiative forcing. With the relative global warming potential of 25 compared with CO(2), CH(4) is one of the most important GHGs. This article reviews the prediction models, estimation methodology and strategies for reducing enteric CH(4) emissions. Emission of CH(4) 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 CH(4) 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 CH(4) prediction models to identify mitigation strategies for reducing the overall CH(4) emissions. A synthesis of the available literature suggests that the mechanistic models are superior to empirical models in accurately predicting the CH(4) 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 CH(4) emissions starting from whole animal chambers to sulfur hexafluoride (SF6) tracer techniques. The latest technology developed to estimate CH(4) more accurately is the micrometeorological mass difference technique. Because the conditions under which animals are managed vary greatly by country, CH(4) 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 CH(4) 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.

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Year:  2010        PMID: 20809221     DOI: 10.1007/s00484-010-0356-7

Source DB:  PubMed          Journal:  Int J Biometeorol        ISSN: 0020-7128            Impact factor:   3.787


  38 in total

1.  The carbon footprint of dairy production systems through partial life cycle assessment.

Authors:  C A Rotz; F Montes; D S Chianese
Journal:  J Dairy Sci       Date:  2010-03       Impact factor: 4.034

2.  Effect of essential oil active compounds on rumen microbial fermentation and nutrient flow in in vitro systems.

Authors:  L Castillejos; S Calsamiglia; A Ferret
Journal:  J Dairy Sci       Date:  2006-07       Impact factor: 4.034

3.  The role of pH in regulating ruminal methane and ammonia production.

Authors:  R P Lana; J B Russell; M E Van Amburgh
Journal:  J Anim Sci       Date:  1998-08       Impact factor: 3.159

4.  Methane emissions from beef cattle: effects of fumaric acid, essential oil, and canola oil.

Authors:  K A Beauchemin; S M McGinn
Journal:  J Anim Sci       Date:  2006-06       Impact factor: 3.159

5.  The effect of a condensed tannin-containing forage on methane emission by goats.

Authors:  R Puchala; B R Min; A L Goetsch; T Sahlu
Journal:  J Anim Sci       Date:  2005-01       Impact factor: 3.159

6.  Manipulating enteric methane emissions and animal performance of late-lactation dairy cows through concentrate supplementation at pasture.

Authors:  D K Lovett; L J Stack; S Lovell; J Callan; B Flynn; M Hawkins; F P O'Mara
Journal:  J Dairy Sci       Date:  2005-08       Impact factor: 4.034

7.  Model for estimating enteric methane emissions from United States dairy and feedlot cattle.

Authors:  E Kebreab; K A Johnson; S L Archibeque; D Pape; T Wirth
Journal:  J Anim Sci       Date:  2008-06-06       Impact factor: 3.159

8.  Methane emissions of beef cattle on forages: efficiency of grazing management systems.

Authors:  H Alan DeRamus; Terry C Clement; Dean D Giampola; Peter C Dickison
Journal:  J Environ Qual       Date:  2003 Jan-Feb       Impact factor: 2.751

9.  Methane output and diet digestibility in response to feeding dairy cows crude linseed, extruded linseed, or linseed oil.

Authors:  C Martin; J Rouel; J P Jouany; M Doreau; Y Chilliard
Journal:  J Anim Sci       Date:  2008-05-09       Impact factor: 3.159

10.  Methane emissions from cattle.

Authors:  K A Johnson; D E Johnson
Journal:  J Anim Sci       Date:  1995-08       Impact factor: 3.159

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  1 in total

1.  Sound management may sequester methane in grazed rangeland ecosystems.

Authors:  Chengjie Wang; Guodong Han; Shiping Wang; Xiajie Zhai; Joel Brown; Kris M Havstad; Xiuzhi Ma; Andreas Wilkes; Mengli Zhao; Shiming Tang; Pei Zhou; Yuanyuan Jiang; Tingting Lu; Zhongwu Wang; Zhiguo Li
Journal:  Sci Rep       Date:  2014-03-24       Impact factor: 4.379

  1 in total

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