Keywords

1 Introduction

There is a growing interest in reducing the emission of greenhouse gases (GHGs) into the atmosphere, because of its potential effect on global warming (Moss et al. 2000). Agricultural activities contribute significantly to global GHG emissions. Examples include carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and ammonia (NH3), which are major GHGs contributing to global warming (IPCC 2001). Increasing awareness of environmental problems associated with global warming has brought significant attention to the need to mitigate global warming and protect the environment (Meadows et al. 1992). Minimizing the contamination of air with CO2, CH4, NH3, and N2O and other GHGs that contribute to radiative forcing has been promoted as a possible route for mitigating global warming (Tamminga 1996). The consequences of increasing the atmospheric concentration of GHGs responsible for the radiative forcing are gradual elevation of average global temperatures, altered viability of plants, animals, insects, and microbes with numerous adverse consequences to human well-being. The degree to which these changes are projected to occur is dependent upon reliable GHG policy models with a range of scenarios for the levels of GHG emissions (Moss et al. 2000).

The scientific evidence of anthropogenic interference with the climate system through GHG emissions has led to worldwide research on assessing impacts that could result from potential climate change associated with GHG accumulation (Sejian 2012). As ecosystems are sensitive to climatic changes, it is necessary to examine the likely impacts of climate change on various components within ecosystems to develop a comprehensive understanding of these effects on climate change. While CO2 receives the most attention, methane with the global warming potential of 25 and longer residence time in the atmosphere, is an important GHG (Wuebbles and Hayhoe 2002; Forster et al. 2007). The rising concentration of CH4 is strongly correlated with increasing populations, and currently about 70% of its production arises from anthropogenic sources (Moss et al. 2000; IPCC 2007).

Increase in the global release of CH4 from agricultural sources can be ascribed to growing rice paddies, fermentation of feed by ruminants (enteric CH4), biomass burning, and animal wastes (Sejian et al. 2011). In recent times, CH4 production has been aggravated by large-scale ruminant production (Beauchemin and McGinn 2005). Globally, ruminant livestock are responsible for about 85 Tg (1 Tg = 1012 g = 1 million metric ton) of the 550 Tg CH4 released annually (McGinn et al. 2006). Ruminant animals, particularly cattle (Bos taurus), buffalo (Bubalus bubalis), sheep (Ovis aris), goat (Capra hircus), and camels (Camalus camalis) produce significant amounts of CH4 via anaerobic digestion. This microbial fermentation process, referred to as ‘enteric fermentation’, produces CH4 as a by-product, which is released through eructation, normal respiration, and small quantities as flatus (Lassey 2007; Chhabra et al. 2009).

Measurement of CH4 production in animals requires complex and often expensive equipment. Some models have been developed to specifically predict CH4 emissions from animals (Ellis et al. 2007). At present, mathematical models are used to estimate CH4 emissions from enteric fermentation at a national and global level, based on the guidelines of the intergovernmental panel on climate change (IPCC 2006). However, the accuracy of these models has been widely challenged (Kebreab et al. 2006).

Understanding the relationship of diet to enteric CH4 production is essential to reduce uncertainty in GHG emission inventories and to identify viable reduction strategies. As a result, quantifying and reducing emissions from livestock farms is important in reducing overall CH4 emission. This article reviews the sensitivity of livestock production to climate change in general, while attempting to highlight some important progresses made in predicting accurately the enteric CH4 emissions. As animal production systems are vulnerable to climate change, while also contributing to potential global warming through CH4 and N2O emissions, this review also collates and synthesises the literature on prediction models, estimation methodology, and strategies for reducing CH4 emission from ruminants.

2 The Contribution of CH4 to Global Warming/Climate Change

Increasing concentrations of GHGs in the atmosphere have contributed to an increase in the earth’s atmospheric temperature, an occurrence known as global warming (FAO 2006). Indeed, average global temperatures have risen considerably, and the IPCC (2007) predicts increases of 1.8–3.9°C (3.2–7.1°F) by 2100. Based on the current trends, the earth’s temperature may rise by 1.4–5.8°C by the end of this century. With rare unanimity, the scientific community warns of a more abrupt and greater climatic change in the future (Moss et al. 2000; Gleik et al. 2010).

The GHG emissions from the agriculture sector account for about 25.5% of the total global radiative forcing and over 60% of anthropogenic sources (FAO 2009). Animal husbandry accounts for 18% of GHG emissions that cause global warming. Emission of CH4 is responsible for nearly as much radiative forcing as all other non-CO2 GHG gases combined. While atmospheric concentrations of GHGs have risen by about 39% since the pre-industrial era, CH4 concentration has more than doubled during this period (WHO 2009). Reducing the increase of GHG emissions from agriculture, especially livestock production, should therefore be a top priority, because it could curb warming considerably (McMichael et al. 2007).

The major global warming potential (GWP) of livestock production worldwide comes from the natural life processes of the animals. In fact, CH4 is considered to be the largest potential contributor to the global warming phenomenon (Johnson et al. 2002; Steinfeld et al. 2006). It is an important component of GHG in the atmosphere (Leng 1993; Moss et al. 2000). The development of management strategies to mitigate CH4 emissions from cattle is possible and desirable. Not only can the enhanced utilization of dietary carbon (C) improve feed efficiency and animal productivity, but a decrease in CH4 emissions may also reduce the contribution of ruminant livestock to the global CH4 inventory.

3 Sources of CH4 Emission

CH4 is emitted from a variety of anthropogenic and natural sources (Wuebbles and Hayhoe 2002; Rotz et al. 2010). The anthropogenic sources include fossil fuel production and exploitation, animal husbandry, including manure storage (Chianese et al. 2009), paddy rice cultivation, biomass burning, and waste management (Kumaraswamy et al. 2000; Mosier et al. 2004). Other sources of methane emission are predominantly natural sources, including wetlands, gas hydrates, permafrost, termites, oceans, freshwater bodies, non-wetland soils, volcanos, and wildfires (Breas et al. 2001).

4 Enteric Emission of CH4 by Livestock

Domestic animal production increased sharply since the 1990s due to policies encouraging large-scale livestock production, improvements in feeding technology, and market requirements (Yang et al. 2003; Sejian and Saumya 2011). Improved animal feeding techniques have had a marked impact on livestock production over the past few decades. In ruminants, a significant amount of fermentation takes place in the rumen, resulting in relatively large CH4 emissions per unit of feed energy consumed. Capturing and burning methane produced by methanogens in manure lagoons, and regulation of dairy diet to reduce enteric CH4 emission are among effective strategies that could be employed to reduce enteric CH4 production. Pseudo-ruminants (e.g. horses) and monogastric animals (e.g. pigs) do not support the same level of feed fermentation, and consequently emissions from these animals are relatively low. Synthesis in Table 16.1 depicts world ruminant livestock population.

Table 16.1 Global domesticated ruminant population (106) and their respective distribution across major continents (Adapted from FAO 2008)
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Among farm animals, cattle population contributes the most toward enteric CH4 production (Johnson and Johnson 1995). Enteric fermentation emissions for cattle are estimated by multiplying the emission factor for each species by the relevant cattle populations. The emission factors are an estimate of the amount of CH4 produced (kg) per animal, and are based on animal and feed characteristics, average energy requirement of the animal, the average feed intake, and the quality of the feed consumed (Sejian et al. 2011a). The district on county level emission from enteric fermentation is computed as a product of the livestock population under each category and its emission coefficient (Chhabra et al. 2009; Sejian and Naqvi 2011a). However, emission coefficients are country-specific, and should conform to IPCC guidelines (IPCC 2007).

4.1 Enteric Fermentation: Process Description

Enteric fermentation is the digestive process in herbivore animals by which carbohydrates are broken down by microorganisms into simple molecules for absorption into the bloodstream (Sejian and Saumya 2011). CH4 is produced as a waste product of this fermentation process. CH4 production through enteric fermentation is of concern worldwide for its contribution to the accumulation of greenhouse gases in the atmosphere, as well as its waste of fed energy for the animal. CH4 is produced in the rumen and hindgut of animals by a group of Archaea known collectively as methanogens, which belong to the phylum Euryarcheota. Among livestock, CH4 production is greatest in ruminants, as methanogens are able to produce CH4 freely through the normal process of feed digestion. Ruminant animals are the principal source of emissions, because they produce the maximum CH4 per unit of feed consumed. What makes ruminant animals unique is their ‘fore-stomach’ or rumen, a large, muscular organ. The rumen is characterized as a large fermentation vat where approximately 200 species and strains of microorganisms are present. The microbes ferment the plant material consumed by the animal through a process known as enteric fermentation. Figure 16.1 describes the enteric CH4 emission from different feed components by the various rumen methanogen species. The products of this fermentation provide the animal with the nutrients it needs for survival, enabling them to subsist on coarse plant material. CH4 is produced as a byproduct of the fermentation and is expelled. Monogastric animals produce small amounts of CH4 as the result of incidental fermentation that takes place during the digestion process. Non-ruminant herbivores produce CH4 at a rate that is of between monogastric and ruminant animals. Although these animals do not have a rumen, significant fermentation takes place in the large intestine, allowing significant digestion and use of plant material.

Fig. 16.1
figure 1

Enteric methane emission from different feed components. Different feed components, such as starch, cell wall polymers, and proteins, are broken down to simpler sugars and carbon skeleton by primary fermentor microbes in the rumen. These simpler sugars are converted into volatile fatty acids by both primary and secondary fermentor microbes. This VFAs are acted upon by methanogen microbes in the rumen to produce methane

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CH4 producing bacteria reside in the reticulo-rumen and large intestine of ruminant livestock. These bacteria, commonly referred to as methanogens, use a range of substrates produced during the primary stages of fermentation to produce CH4, thus creating generated energy required for their growth. All methanogen species can utilize hydrogen ions (H2) to reduce CO2 in the production of CH4 as this reaction is thermodynamically favorable to the organisms. Availability of H2 in the rumen is determined by the proportion of end products resulting from fermentation of the ingested feed. Processes that yield propionate and cell dry matter act as net proton-using reactions, whereas a reaction that yields acetate results in a net proton increase. Other substrates available to methanogens include formate, acetate, methanol, methylamines, dimethyl sulfide, and some alcohols; however, only formate has been documented as an alternative CH4 precursor in the rumen. Figure 16.2 describes the mechanism of CH4 production during digestion process in the rumen.

Fig. 16.2
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Mechanism of enteric CH4 production during digestion in the rumen. This figure describes the process of methane production in the rumen. From feed components, initially glucose is produced and from glucose VFAs are produced. Acetate and butyrate are hydrogen providers while propionate is hydrogen consumer. Based on the proportion of end product of digestion methane is produced in the rumen

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The principal methanogens in the bovine rumen utilize hydrogen and carbon dioxide, but there is a group of methanogens of the genus Methanosarcina that grows slowly on H2 and CO2 and therefore maintains a distinct niche by utilizing methanol and methylamines to produce CH4 (Sejian and Naqvi 2011a). Formate, which is formed in the production of acetate, can also be used as a substrate for methanogenesis, although it is often converted quickly into H2 and CO2 instead. Volatile fatty acids (VFA) are not commonly used as substrates for methanogenesis as their conversion into H2 and CO2 is a lengthy process, which is inhibited by rumen turnover. Therefore, methanogenesis often uses the C and CO2 produced by carbohydrate fermentation, as VFAs are formed. By removing H2 from the ruminal environment as a terminal step of carbohydrate fermentation, methanogens allow the microorganisms involved in fermentation to function optimally and support the complete oxidation of substrates (Sejian and Naqvi 2011a). The fermentation of carbohydrates results in the production of H2 and if this end product is not removed, it can inhibit metabolism of rumen microorganisms.

5 CH4 Emission in Developed and Developing Countries

The global production and consumption of farm animals and their products are increasing significantly and are predicted to continue up until ~2050. This increase comes at a time when it is recognized that the world is facing a crisis about the impact of humans on the planet’s climate (Sejian et al. 2011a). Animal products have a high GWP per kg compared to most plant-derived foods (FAO 2008). In addition to enteric fermentation, which is the major source of CH4 emission, meat and dairy production and consumption also contribute significantly to the emission of GHGs in developed countries (Eshel and Martin 2006; Ogino et al. 2007 Comparatively, due to intensive animal production, developed countries tend to record higher CH4 emission than their developing counterparts do.

Thus, developed countries have the highest emissions factors per animal while Asia, North, and Sub-Saharan Africa have the lowest (USEPA 1994). Among dairy cows, the temperate mixed farming production system has the highest emissions factors, reflecting higher levels of milk production. In light of this, emissions per unit of product can be used to identify opportunities for reducing CH4 emissions from enteric fermentation.

The emission of CH4 is quantified by its conversion rate, which differs among developed and developing countries. The conversion rate in developed countries is 4% for feedlot cattle and 6% for other cattle (Lassey et al. 1997). Better-digested feeds with higher energy value result in lower conversion rates. The CH4 conversion rate in developing countries is also 6% for dairy cows and young cattle, and 7% for non-dairy cattle with the exception of stall-fed animals (Lassey et al. 1997). Grazing cattle have a conversion rate of 6%, except for grazing cattle in tropical Africa, which have a rate of 7% because of the poor quality forage. These estimates are based on the general feed characteristics and production practices observed in many developed and developing countries.

The data on GHG emissions from animal production depend on the natural life processes of the animals. However, these processes are difficult to control without reducing productivity. Hence, overproduction of livestock is likely to have a negatively impact on overall food production given the accompanying damages to the environment, such as more frequent droughts, floods, storms, and harvest failures. This calls for better-planned and well-managed reduction in worldwide production and consumption of meat and milk products to mitigate global warming. Global trends indicate that overproduction and consumption of animal products (meat, milk, and eggs) in high-income, developed countries may be nearing its peak and further increase in production may be unsustainable due to population growth and environmental concerns (Gold and Porritt 2004). While low-income countries and some fast-developing countries are expected to continue their rapid growth in animal production and consumption, it is essential that emission of livestock-related GHGs is monitored and controlled in the short-term.

6 Factors Influencing CH4 Production

Factors that influence enteric methane production outlined in Fig. 16.3 indicate that CH4 production varies with microbial species and livestock breed. Consequently, breeding of livestock on the basis of CH4 production in an effort to reduce enteric CH4 emissions without compromising animal productivity is possible (Hegarty et al. 2007). Rumen pH plays a major role in determining the predominant microbial population, which has a direct bearing on CH4 gas emission (Erfle et al. 1982). Reduction of ruminal pH can decrease ruminal CH4, which can improve feed utilization in the ruminant animals (Lana et al. 1998). The ratio of ruminal acetate: propionate in vivo is highly influenced by the capacity of the bacteria to produce CH4 in vitro. Cattle with low acetate: propionate ratios also have low ruminal pH values, and in vitro experiments corroborate the concept that pH has a major impact on CH4 production and acetate: propionate ratio (Lana et al. 1998; Sejian et al. 2011a).

Fig. 16.3
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Factors influencing methane output from enteric fermentation. These factors can be broadly categorized into animal, feed, rumen, and environmental factors

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Methanogens that thrive on and within rumen ciliate protozoa may account for up to 37% of the rumen CH4 emissions (Hegarty et al. 2007). In the absence of protozoa, rumen CH4 emissions are reduced by up to 13% on the average depending on the diet. Decreased CH4 emissions from protozoa-free rumen may be a consequence of reduced ruminal dry matter digestion, decreased methanogen population, altered pattern of volatile fatty acid production, decreased hydrogen availability, and increased partial pressure of oxygen in the rumen (Yoon and Stern 1995). Decline in methanogenesis associated with removal of protozoa is strung on high concentrate diets, because protozoa are relatively more important sources of hydrogen on starch diets, and many starch-fermenting bacteria do not produce hydrogen. Because protozoa also decrease the supply of protein available to the host animal, their elimination offers benefits in both decreasing GHG emissions and potentially increasing feed conversion ratio in livestock production (Hegarty 1999; Sejian et al. 2011a).

The composition of diet fed to the livestock is another important factor, which influences CH4 emission (McCrabb et al. 1997), especially from enteric fermentation in lactating dairy cows. For instance, the proportion of forage in livestock diet and the source of grain influence enteric CH4 production by ruminants (Beauchemin and McGinn 2005). The amounts of digestible nutrients especially the carbohydrate fraction is used to estimate CH4 emission from livestock with high precision. Conversely, a diet rich in fat reduces CH4 formation in the rumen (Jentsch et al. 2007). Puchala et al. (2005) identified the potential of condensed tannins in forages to reduce CH4 emission by ruminants. The level of CH4 emission is positively correlated with live weight, dry matter intake (DMI), milk yield (MY), and feeding level (Yan et al. 2006). To enhance productivity, manipulation of dietary composition of cattle feed is a nutritional management strategy with potential to reduce CH4 production by dairy cows (Yan et al. 2006).

There are several feed supplements, which significantly alter the level of CH4 emission (Leng 1991; Moss et al. 1995). However, additional feed supplement should be used with caution as they can reduce animal productivity when the wrong dosage is administered (Beauchemin and McGinn 2006; Foley et al. 2009). Incremental inclusion of malic acid in beef cattle diets results in linear reductions of both the total daily emission of CH4 and its emissions expressed per unit of DMI. Nevertheless, the dietary inclusion of malate is also associated with a decline in DMI in both studies (Martin and Streeter 1995). This could potentially decrease animal performance, with consequent increases in lifetime CH4 emission owing to extended slaughter age. Therefore, further in vivo research is required to clarify the long-term effects of malate supplementation on CH4 emission, animal performance, and productivity (Foley et al. 2009). Beauchemin and McGinn (2006) demonstrated that canola oil (Brassica campestris L) can be used to reduce CH4 emissions from cattle, but animal performance may be compromised due to lower feed intake and decreased fiber digestibility. Essential oils have no effect on CH4 emissions, whereas fumaric acid causes potentially beneficial changes in ruminal fermentation although with no measurable reductions in its emissions. Certain fats and oils are potential natural CH4 reducing feed compounds, and are effective even at common dietary proportions (Machmuller et al. 1998). McGinn et al. (2004) demonstrated that sunflower (Helianthus annuus L) oil, ionophores, and possibly some yeast products can be used to decrease the gross energy loss as CH4 from cattle, however, fiber digestibility is impaired with oil supplementation.

Research involving in vitro and in vivo experiments indicates that high grain feeding reduces CH4 emission in farm animals. (Lana et al. 1998; Hristov et al. 2001). There are two possible reasons for this viz., reduced methanogenesis and lower acetate: propionate ratio (Christophersen et al. 2008). Not only enhanced utilization of dietary C can improve feed utilization efficiency and animal productivity, but also a decrease in CH4 emissions can reduce the contribution of ruminant livestock to the global CH4 inventory (Johnson and Johnson 1995). Using best management practices (BMPs), the emission of CH4 per unit of animal weight gain reduces significantly. Management-intensive grazing (MIG) is a BMP that offers the potential for more efficient utilization of grazed forage crops via controlled rotational grazing and more efficient conversion of forage into meat and milk (DeRamus et al. 2003).

As highlighted above, there are several factors, which play important roles in influencing enteric fermentation, hence CH4 emission. There is an urgent need to understand these factors better, with a view to decreasing GHG emissions (Beauchemin and McGinn 2005).

7 Prediction of CH4 Emission by Emission Models

CH4 production is generally predicted on the basis of equations involving DMI, intake of carbohydrates, digestibility and intake of dietary energy, animal size, milk components, and digestibility of dietary components (Sejian et al. 2011b). The models developed for the prediction of CH4 emission can be classified into two principal groups: (i) empirical (statistical) models, which directly relate nutrient intake to CH4 output, and (ii) dynamic mechanistic models that attempt to simulate CH4 emissions based on a mathematical description of ruminal fermentation biochemistry (Kebreab et al. 2006). Synthesis in Table 16.2 depicts the merits and demerits of the empirical and mechanistic models.

Table 16.2 The merits and demerits of empirical and mechanistic prediction models for methane emission
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7.1 Empirical Models

Although many statistical models have been fairly successful in predicting CH4 production, many variables in these models are not commonly measured, which may lead to difficulties in predicting CH4 production outside the range of values used for model development (Johnson et al. 1996; Sejian and Rajni 2011). These problems may be addressed by using equations with common input variables and by developing models with minimum input variables from multiple sources. The limitation of using some of the extant models, such as the equation of Moe and Tyrrell (1979), is the difficulty in obtaining reliable model input variables, which might have compromised the predictive ability of the model in the study. Ellis et al. (2007) formulated the most widely accepted equations, which could be useful to the livestock industry for accurately predicting CH4 production from a minimum set of inputs. Although the extant models evaluated performed well, the new equations developed in the study were more user-friendly and reliable than the extant models, as a result, it is a preferable model for generating national CH4 emissions inventory. Synthesis in Table 16.3 depicts different types of regression/prediction equations for enteric methane emission.

Table 16.3 Examples of regression/prediction equations for methane emission
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7.2 Mechanistic Models

Synthesis in Table 16.4 describes the various emission models available to predict enteric methane emission for farm households. Yan et al. (2000) improved on the earlier representation of methanogenesis in the mechanistic model, and outlined some likely reasons for the differences between observed and predicted values for CH4 production. One of these is the error attributable to dietary composition, not only in the analysis, but also due to variation in nutrient composition between samples of the same feedstock. This knowledge of the dietary components is a prerequisite for successful use of the models to compare the effect of different feeds on CH4 production (Palliser and Woodward 2002). Nonlinear mechanistic model of CH4 production provides a significant opportunity to enhance scientific capacity to estimate CH4 emissions from cattle (Mills et al. 2003; Kebreab et al. 2008). In addition, researchers have identified that mechanistic models can be used to generate Ym values, which can be applied in national CH4 emission inventory models. It was suggested that if incentives were introduced to mitigate CH4 emissions at a farm level, mechanistic models would be excellent tools to make reliable estimates of enteric CH4 emissions. The advantage of mechanistic models compared with empirical models is that mitigation options implemented at a farm or national level can be assessed for their effectiveness.

Table 16.4 Examples of prediction models for methane emission
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7.3 Whole Farm Model

Computer simulation can provide a cost-effective and efficient method of estimating CH4 emissions from dairy farms and analyzing effects of management strategies on emissions. Invariably all whole farm models (WFM) are mechanistic models. A commonly used simulation is that proposed by Rotz et al. (2007). The model is an integrated farm system model (IFSM), which is a potential tool for simulating whole farm emissions of CH4 and evaluating the overall impact of management strategies used to reduce CH4 emissions. The IFSM was further refined into a process-based whole farm simulation including major components for soil processes, crop growth, tillage, planting, and harvest operations, feed storage, feeding, herd production, manure storage, and economics (Rotz et al. 2009). Incorporation of the CH4 module with IFSM in addition to modules simulating N2O emissions, provides an important tool for evaluating the overall impact of management strategies used to reduce GHG emissions in dairy farms.

Farm system simulation framework (FSSF) is another type of WFM, which uses pasture growth and cow metabolism for predicting CH4 emissions in dairy farms. Also included in the WFM is climate and management information. Other examples of WFMs include those developed by Neil et al. (1997), Sherlock et al. (1997), Sherlock and Bright (1999), and Bright et al. (2000); however, these models are adequate only for predicting CH4 production by non-lactating Holstein cows. Prediction rates for lactating cows are less accurate and WFMs currently described in the literature seem inappropriate (IPCC 1997). Hence, development of WFMs is required for the prediction of nutrient and GHG emissions and to get better estimate of enteric CH4 production (Sejian and Singh 2011). Currently available WFMs may incorrectly estimate CH4 emission levels, because they cannot broadly predict enteric CH4 emissions as affected by DMI and diet. The low prediction accuracy of CH4 equations in current WFMs may introduce substantial errors in the calculation of GHG emissions, thereby leading to incorrect mitigation recommendations. If regression equations examined here and elsewhere continue to explain only a small fraction of the variations in observed values, moving toward regression equations including more nutritional informations and details on a subanimal level, or toward a dynamic mechanistic description of enteric CH4 emission, will improve predictions (Ellis et al. 2010; Sejian et al. 2011b).

8 Estimation Methodologies for Enteric CH4 Emission

There is a growing interest in changing the management strategies to reduce enteric CH4 production without negatively influencing animal productivity. This theme has been the focus of much research to improve environmental sustainability from an agricultural standpoint. However, accurate CH4 measurements are required for identifying mitigation strategies that can discriminate among treatments relevant to on-farm conditions (Lassey 2008). Several techniques are used to quantify enteric CH4 emissions including whole animal chambers (Grainger et al. 2007), and SF6 tracer technique (Pinares-Patiño et al. 2008; McGinn et al. 2009).

Measurement of CH4 emissions from individual animals has traditionally been made with open-circuit respiration chambers, which are highly accurate and reliable for animals offered indoor diets (Sejian and Saumya 2011). However, these chambers are not as suitable for evaluating emissions for grazing animals. A new technique that makes use of an inert gas (SF6) has recently been developed for determining CH4 emissions from cattle and sheep under grazing conditions. The SF6 tracer technique enables the determination of enteric CH4 emissions from both individual as well as on a large number of animals (Vlaming et al. 2007). This technique is based on the use of a controlled release bolus containing SF6 gas, which is inserted into the animal’s rumen (DeRamus et al. 2003). This technique slowly samples the mixed eructated and respired air from the animal, generally over a 24-h period. This air sample is then analyzed for the ratio of CH4:SF6 concentration, and the ratio is multiplied by the known release rate of SF6 emitted from a permeation tube placed in the rumen (Pinares-Patiño et al. 2008). This technique is extremely useful for examining grazing management influences on enteric CH4 emissions (Pinares-Patiño et al. 2007). In addition, the authors concluded that the SF6 tracer technique can be used with a reasonable degree of accuracy for inventory purposes and for evaluating the effects of mitigation strategies on CH4 emissions.

A more flexible technique for quantifying emissions is to model the dispersion of a target gas from the source (Flesch et al. 2004), so that a downwind concentration of gas can establish the emission rate. This “inverse-dispersion” technique has the advantage of simplicity, as it requires only a single gas concentration measurement and basic wind information (McGinn et al. 2006). However, several important factors must be considered to get accurate results from this technique. These factors include: (1) ambient conditions including landscape with clearly defined wind regime as well as not having other nearby emission sources; (2) duration of measurement; (3) period specific measurements (while ignoring periods known to be problematic for inverse-dispersion calculations), and (4) lactation specific concentration measurement.

A micrometeorological mass difference technique is used to measure CH4 production by cattle in pasture and feedlot conditions (Harper et al. 1999). Measurements are made continuously under field conditions, semiautomatically for several days. The method permits a relatively large number of cattle to be sampled. These techniques do not infringe on the measurement being made, and are generally nonintrusive (Laubach and Kelliher 2004). Limitations include light winds, rapid wind direction changes, and high precision CH4 gas concentration measurement. The mass difference method provides a useful tool for ‘undisturbed’ measurements on the influence of feedstuffs and nutritional management practices on CH4 production from animals and for developing improved management practice for enhanced environmental quality (Harper et al. 1999).

McGinn et al. (2006) used a backward Lagrangian Stochastic (bLS) dispersion technique where plume gas concentrations are measured several hundred meters downwind of a dairy farm. The bLS dispersion technique is a useful approach for measuring whole farm emissions (e.g., dairies and feedlots) and emissions from well-defined point sources within the farm. In addition, this technique is useful in evaluating mitigation strategies, is nonintrusive, less labor-intensive, and is much easier to implement than most techniques. Furthermore, using the bLS dispersion technique in conjunction with global positioning system (GPS) may have application for monitoring enteric CH4 emissions from grazing cattle herds in large pad docks (McGinn et al. 2009).

9 Mitigation Strategies for Reducing CH4 Production

Any reduction strategies must be confined to the following general framework viz., development priority, product demand, infrastructure, livestock resource, and local resources (Sejian et al. 2011a). The most attractive emissions mitigation projects must balance the needs in all of these areas, so that, no one factor creates a constraint on continued improvement in production efficiency, and the resulting CH4 emissions reductions. Within this framework, CH4 emissions mitigation options for enteric fermentation can encompass a wide range of activities across these areas (Sejian and Indu 2011). However, underlying these activities must be specific options for improving the production efficiency of the livestock. Without these options, CH4 emissions cannot be reduced. A range of reduction strategies to reduce enteric methane production outlined in Fig. 16.4 are briefly discussed below.

Fig. 16.4
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Various strategies to reduce enteric methane production. These mitigation strategies can be grouped into three broader category-managemental, nutritional and advanced strategies (Source Sejian et al. 2011b)

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9.1 Reduction of Livestock Numbers

Reducing livestock numbers may be the best possible way for countries that hold large livestock population and are committed to reducing GHG emission from animal sources. Nevertheless, countries, which are heavily dependent on their livestock industries for generation of national income, imposition of regulations aimed at reducing livestock numbers would be economically unacceptable. Reducing livestock numbers through normal market processes can be effective. For example, in New Zealand, sheep farming has become less profitable since ~1990, and farmers have reduced sheep numbers and used the land for alternative enterprises, such as forestry (Ulyatt and Lassey 2001). Sheep populations have been reduced from 57.9 million in 1990 to 45.2 million in 2000, while dairy cattle and beef cattle population have increased slightly. The net outcome was a decline in ruminant CH4 emission from 1.45 to 1.31 Tg/year from 1990 to 2000. This change in stock numbers, predominantly a reflection of the profitability of sheep farming, implies that New Zealand is in a position to meet its commitments to the UNFCCC. However, livestock population may respond positively to improved economic conditions. However, if sheep farming become more profitable an increase in stock numbers and thus CH4 emission become most probable.

9.2 Management Strategies

Adoption of the basic livestock management principles offers the best opportunity for improving production efficiency while also reducing emissions (Sejian and Naqvi 2011b). Within the context of these livestock management principles, specific techniques for improving production efficiency and reducing CH4 emissions include the following: (1) enhanced nutrition through mechanical and chemical feed processing, (2) balanced nutrition through strategic supplementation, (3) intake of production enhancing agents, (4) improved production through enhanced genetic characteristics, (5) increased production efficiency through improved reproduction, and (6) improved grassland and rangeland management (USEPA 1993).

There is a wide range of management practices that improve animal productivity, with concomitant reduction in CH4 emission per unit animal product (Naqvi and Sejian 2011). Genetic selection of animals that consume less feed or produce less CH4 per unit of feed is a management strategy that may be used to reduce enteric CH4 emissions. Improving the efficiency of ruminant animal performance will generally lead to a reduction of CH4 emitted per unit of animal product. There are two aspects of this practice: genetic improvement of the animals to achieve more products per unit of feed intake and dietary manipulation via increased feed intake and appropriate feed composition (Ulyatt and Lassey 2001). These authors also suggested that increasing feed intake decreases the CH4 emission per unit of feed intake. Increased intake of the same diet to a cow increases milk production, but decreases CH4 emitted per unit of milk (Kirchgessner et al. 1995). The probable reason for this could be that as intake increases, the CH4 emission associated with the essential but non-productive requirements for maintenance is diluted. Dietary manipulations aimed at reducing CH4 emission include decreasing dietary fiber and increasing starch and lipid (Beauchemin and McGinn 2006). Generally, diets of higher digestibility have these characteristics (Johnson et al. 2002). Treatment of animals with growth promoting substances can increase production efficiency. Examples of such substances are bovine somatotrophin (bST), ionophores, and anabolic steroids. All these techniques use dilution of maintenance requirements to achieve reduced CH4 emission. Their maximum effectiveness in terms of reducing CH4 emission would be in maintaining present levels of animal production with fewer animals, or in increasing animal production with the same number of animals. This would provide the farmer with options for land use that should improve productivity.

Differences in the digestive anatomy or physiology of individual animals, or between breeds can result in differences in CH4 production (Robertson and Waghorn 2002). The natural variation among animals in the quantity of feed eaten per unit of liveweight gain can be exploited to breed animals that consume less feed than the unselected population while achieving a desired rate of growth (Hegarty 2001). Thus, the concept of residual feed intake (RFI) was developed and used by Boadi et al. (2004a). In addition, there are large differences in emission per unit of feed intake between animals. Such differences between animals are real and can persist for some time (Lassey et al. 1997). Implementing proper grazing management practises to improve the quality of pastures increases animal productivity and has a significant effect on reducing CH4 emission from fermentation in the rumen. Management-intensive grazing (MIG) is an effective form of grazing BMPs. As a result, the CH4 emissions per unit of product as well as total emissions into the atmosphere are reduced (DeRamus et al. 2003; Naqvi and Sejian 2011).

There are many potential opportunities for mitigating CH4 through microbial intervention in the rumen, such as: targeting methanogens with antibiotics, bacteriocins, or phage; removing protozoa from the rumen; development of alternative sinks for H2 such as reductive acetogenesis (Ulyatt and Lassey 2001). There is considerable evidence that the rumen can function satisfactorily in the absence of methanogens (Joblin 1999). Given that CH4 results from microbial activity, the animal can only have an impact on this variation through interactions with the microbes directly, through the diet selected, or through control of the fermenter (rumen) conditions (Ulyatt and Lassey 2001). Animal effects on fermentation could include saliva, feed processing, or flow rate through the rumen. It is possible that the animal impact on fermentation is genetically determined and if this is the case, it may be possible to create market opportunities that can be used to select low CH4 emitters. Several CH4 oxidizing bacteria have been isolated from the rumen and when added to the rumen fluid in vitro, decrease CH4 accumulation in the rumen (Boadi et al. 2004a). In the long term, however, CH4 oxidizers from gut sources could be screened for their activity in the rumen to reduce the proportion of CH4.

9.3 Nutritional Strategies

Diet modification is one way in which the cattle industry can reduce its contribution to GHG emissions (Beauchemin and McGinn 2006; Sejian et al. 2011c). It has been accepted generally that digestibility is maximized when optimum levels of NH3 is maintained in the rumen (Bowman et al. 1992). Supplying NH3 can, therefore, greatly increase digestive efficiency and utilization of available energy. NH3 can be supplied via urea, chicken manure, or soluble protein that degrades in the rumen. In addition to NH3, there are some nutrients that must be present in the diet to support the microbe population in the rumen. The most common nutrients required are sulfur (S) and phosphorus (P), although this may vary greatly with region. In addition, molasses provides the energy needed to realize the improved microbial growth that can result from enhanced ammonia levels. Molasses nutrient blocks (MNBs) have been used as a supplement in many countries with encouraging results of increased milk yield by 20–30%; increased growth rate of 80–200% and increased reproductive efficiency. Based on these results, CH4 emissions per unit product are expected to be reduced by up to 40% (Leng 1991). Bowman et al. (1992) reported that strategic supplementation of dairy animals with MNBs may reduce CH4 emissions by 25%.

Improving the nutritive value of the feed given to grazing animals by balancing the diet with concentrates, or by breeding improved pasture plants, may reduce CH4 emission. The proportion of concentrate within the diet is negatively correlated with CH4 emissions (Yan et al. 2000; Lovett et al. 2005). Increased concentrate supplementation decreases enteric CH4 production, increases proportion of propionate in rumen VFA and therefore reduces hydrogen for CH4 synthesis. Indeed increasing the digestibility of pasture for grazing ruminants is the most practical means of reducing their CH4 emissions (Hegarty 1999). If animal numbers do not decrease in response to the improved productivity, however, then emissions from the sector may increase rather than decrease (Hegarty 2002). Waghorn et al. (2002) observed that the impact of condensed tannins on rumen methanogenesis is small, although significant. Furthermore, legumes reduce CH4 emissions when fed at comparable intake levels (Beever et al. 1985).

9.4 Chemical Inhibitors of Methanogenesis

Several mechanisms influence the availability of H2 in the rumen and subsequent production of enteric CH4 emissions by cattle. Processes that yield propionate act as net proton-using reactions while those that yield acetate result in a net increase in protons. That is, the proportion of volatile fatty acids, specifically acetate, propionate; produced as a consequence of microbial fermentation in the rumen has a significant influence on CH4 production. If precursors of propionate are added to the diet, they should reduce CH4 production by removing some of the H2 produced during ruminal fermentation (O’Mara 2004). Another mechanism by which CH4 production may be reduced during the rumen fermentation process is through the provision of alternative hydrogen acceptors or sinks.

A wide range of chemicals are available that may reduce rumen methanogenesis (Johnson and Johnson 1995; Mathison 1997). Organic acids, such as malate, fumarate, citrate, succinate, etc., are propionate precursors. Experiments conducted in vitro (Martin and Streeter 1995; Ulyatt and Lassey 2001) and in vivo (Newbold et al. 2002) show that addition of organic acids to the diet reduces CH4 production, in a dose dependent manner (Martin and Streeter 1995). Thus, a feed additive or ingredient that reduces CH4 emissions from cattle fed high-forage diets could have an important impact on reducing the emissions from the livestock sector (Beauchemin and McGinn 2006). Adding 4.6% of canola oil, a source of unsaturated fat, to a high-forage diet is an effective suppressant of CH4, with daily emissions decreased by 32% and emissions as a percentage of gross energy intake decreased by 21%. McGinn et al. (2004) also reported reduced CH4 production after supplementing the feed with sunflower oil and monensin. Halogenated CH4 analogs, such as, chloroform, CCl4, chloral hydrate, bromochloromethane, and bromoethanesulphonic acid are potent CH4 inhibitors (McCrabb et al. 1997).

There is an increasing interest in exploiting natural products as feed additives to manipulate enteric fermentation and possibly reduce CH4 emissions from livestock (Wenk 2003). Essential oils can interact with microbial cell membranes and inhibit the growth of some gram-positive and gram-negative bacteria. As a result of such inhibition, the addition of some plant extracts to the rumen results in an inhibition of deamination and methanogenesis, resulting in lower ammonia N, CH4, and acetate, and in higher propionate and butyrate concentrations (Boadi et al. 2004b; Calsamiglia et al. 2007). Data from in vitro and in vivo experiments involving essential oil indicate that these are antimethanogenic agents leading to reduction in CH4 production (Busquet et al. 2006; Castillejos et al. 2006). Supply of lipids from linseed (Linum usitatissimum) significantly decreased the amount of CH4 emitted by dairy cows. Linseed fatty acid offers a promising dietary means to depress ruminal methanogenesis. The form of linseed fatty acid greatly influences CH4 output from dairy cows (Martin et al. 2008). Polyunsaturated fatty acid decreases CH4 through a toxic effect on microorganisms involved in fiber digestion and hydrogen production, such as protozoa (Doreau and Ferlay 1995) and cellulolytic bacteria (Nagaraja et al. 1997).

Ionophores, such as monensin and lasalocid also reduce CH4 emission (Johnson and Johnson 1995). In the rumen, ionophores increase the proportion of gram-positive bacteria, resulting in a shift in fermentation acids from acetate and butyrate to propionate, consequently CH4 production is reduced (NRC 2001). However, the rumen microbes adapt to the additives within two weeks (Saa et al. 1993; O’Mara 2004). Monensin supplementation can reduce CH4 production by 25% (Tedeschi et al. 2003).

Defaunating agents, like manoxol, teric, alkanate 3SL3 and sulphosuccinate can reduce CH4 emission (Mathison et al. 1998). They act by disrupting the close symbiotic relationship between methanogenic bacteria and protozoa. One method by which defaunation can be brought about is the addition of certain oils/fats (Machmuller et al. 1998; Hegarty 1999). The magnitude of reduction in CH4 output following dietary supplementation of fats/oils is source-dependent, with coconut (Cocos nucifera) oil identified as being very effective (Lovett et al. 2005; Jordan et al. 2004). However, the use of defaunation to decrease CH4 production from ruminants would have to be balanced against the effects on fiber and protein metabolism in the rumen (Gworgwor et al. 2006).

The main problems with chemical additives are the following: (i) some are toxic to the animal and rumen microflora thereby reducing digestion and food intake, (ii) some have short-lived effects, because the rumen microbes adapt, they are mainly volatile hence, difficult to administer, and (iii) some are expensive, and may not meet consumer product acceptance.

9.5 Immunization

The most noteworthy achievement with regards to reducing CH4 production in livestock is the development of a vaccine containing an antigen derived from methanogenic bacteria (Gworgwor et al. 2006) and an immunogenic preparation which reduces the activity of rumen protozoa (Baker et al. 1997). Such vaccines are potent in providing a cost-effective treatment for reducing CH4 emission and enhancing animal production. In light of these, Baker (1995) and Shu et al. (1999) proposed that it may be possible to immunize ruminants against their own methanogens with associated decrease in CH4 output and that such an approach could reduce the members of streptococci and lactobacilli in the rumen.

10 Conclusions

This chapter addresses enteric CH4 production from livestock and its mitigation strategies. It describes factors influencing CH4 production, prediction models, and estimation methodologies for identifying different strategies to reduce such emissions. There are urgent needs to understand the various factors affecting variability in enteric CH4 production to decrease GHG emission inventories and to identify viable GHG reduction strategies. Considerable progress has been made in the design of simulation models for predicting CH4 emissions and the latest integrated farm system models offer greater capacity to predict more accurately GHG emissions with the incorporation of climatic and management information. Although the reduction in GHG emissions from livestock industries is of high priority, strategies for reducing emissions should not reduce the economic viability of the livestock industry.

The reduction of enteric CH4 emissions from livestock by the selection of more feed-efficient animals based on their estimated breeding value offers a novel way of reducing the CH4 emissions without compromising animal growth rate. Decreasing feed losses to CH4 emission in the cattle industry can represent an improvement in feed efficiency. Therefore, mitigating CH4 losses from cattle have both environmental and economic benefits. Improved knowledge of quantitative nutrition provides powerful tools to develop concepts to undertake a wide range of problem-oriented research with the goal of curbing emissions by livestock farms. Many authors have recommended on-farm practises, such as genetic selection for production traits, feed testing, and ration balancing, using CH4 inhibitors to reduce enteric CH4 emissions with concomitant reduction in feed costs. Several other CH4 reduction strategies are at various stages of investigation, such as the use of feed additives, ionophores, defaunation, and vaccination. Pending an improved understanding of the global impact of these mitigation strategies on livestock, there are grounds for optimism that in the medium term, more effective strategies may become available to supplement those presently available. Finally, more consideration must be given to total farm GHG emissions from enteric fermentation. As low-income countries and some fast-developing countries are expected to continue their rapid growth in animal production, it is essential that the growth of global livestock-related GHG emissions is restricted in the short term to reduce the effects of CH4 on global temperatures.

11 The Scope of Future Research

There is new need for further concerted research on methane emission by livestock and its mitigation. For instance, there are several new and more advanced CH4 mitigation options, including the addition of probiotics, acetogens, bacteriocins, archaeal viruses, organic acids, and plant extracts to the diet, as well as immunization and genetic selection of animals. Although these new strategies are promising, more research is needed for validation purposes and to assess in vivo their effectiveness in reducing CH4 production in dairy animals. In addition, there is a need to improve the efficacy of current strategies both economically, for livestock production and increasing their capacity to limit emissions. Vaccine development against methanogens is promising and calls for concerted research efforts if this strategy is to become a reality. The development of biomarkers to identify low CH4 emission animals or low CH4-producing bacteria also merits further investigation. Future developments in the area of modeling must accompany any improved understating of the underlying rumen biology. Furthermore, the need to develop simpler and more accurate models compatible with current trends in computer technology cannot be overemphasized.