Ammonia and Methane Emission Factors from Cattle Operations Expressed As Losses of Dietary Nutrients Or Energy

Review Ammonia and Methane Emission Factors from Cattle Operations Expressed as Losses of Dietary Nutrients or Energy

Zifei Liu *, Yang Liu, James P. Murphy and Ronaldo Maghirang

Department of Biological and Agricultural Engineering, Kansas State University, Manhattan, KS 66056, USA; [email protected] (Y.L.); [email protected] (J.P.M.); [email protected] (R.M.) * Correspondence: [email protected]; Tel.: +1-785-532-3587

Academic Editor: Ryusuke Hatano Received: 15 December 2016; Accepted: 20 February 2017; Published: 23 February 2017

Abstract: The objective of this study was to conduct a systematic review of published literature on ammonia (NH3) and enteric methane (CH4) emissions from beef and dairy cattle operations to obtain statistically representative emission factors based on dietary intakes of nutrients or energy, and to identify major causes of emission variations. NH3 emissions from lagoon or other manure storage facilities were not included in this review. The NH3 and CH4 emission rates, expressed as a percentage losses of dietary nutrients or energy, demonstrated much less variation compared with emission rates expressed in g/animal/day. Air temperature and dietary crude protein (CP) content were identified as two major factors that can affect NH3 emission rates in addition to farm type. Feed digestibility and energy intake were identified as two major factors that can affect CH4 emission rates expressed as a percentage losses of dietary energy. Generally, increasing productivity and feed efficiency represented the greatest opportunity for mitigating NH3 or CH4 emissions per unit of livestock product. Expressing CH4 loss on a digestible energy basis rather than a gross energy intake basis can better represent the large variation among diets and the effects of varying dietary emission mitigation strategies.

Keywords: crude protein content; feeding efﬁciency; nitrogen; forage-to-concentrate ratio; digestibility; digestible energy; feed intake; NH3 and enteric CH4 emissions

1. Introduction Beef and dairy cattle operations emit gases into the atmosphere from animal feed digestion (enteric fermentation) and manure decomposition. Ammonia (NH3) is produced as a by-product of the microbial decomposition of the organic nitrogen (N) compounds in manure, and has been listed as one of the most important atmospheric species emitted from livestock operations in the U.S. due to its impact on ecosystems and air quality concerns [1]. Enteric methane (CH4) is produced by ruminants as a result of microbial breakdown of carbohydrates in the rumen, and enteric CH4 emissions from cattle operations are considered a major contributor to greenhouse gas (GHG) emissions in the U.S. [2]. In addition to environmental concerns, NH3 emissions represent an unproductive loss of dietary nutrients. The fertilizer value of manure is reduced due to N volatilization to the atmosphere as NH3. Similarly, CH4 emissions represent an unproductive loss of dietary energy (Figure1). The U.S. Environmental Protection Agency (EPA) estimated that more than 80% of human-induced NH3 emissions in the U.S. come from livestock production, in which beef and dairy cattle contributed more than half [3]. Enteric fermentation and manure management of livestock production are responsible for 2.2% and 1.1% of the total human-induced GHG emissions in the U.S., respectively, and cattle operations are considered the major contributors within the various livestock species [2].

Agriculture 2017, 7, 16; doi:10.3390/agriculture7030016 www.mdpi.com/journal/agriculture Agriculture 2017, 7, 16 2 of 12

in the U.S., respectively, and cattle operations are considered the major contributors within the various livestock species [2]. With increasingly stringent air pollution regulations and the emerging pressure to regulate agricultural enterprises, there will be a continued need for emission inventories based on reliable and representative emission factors, as well as an increasing demand for mitigation strategies. On the other hand, production efficiency is a contributing factor in reducing the environmental footprint per unit of product. Strategies that increase production efficiency will conserve resources and improve environmental stewardship, and could represent a great opportunity for mitigating NH3 and CH4 emissions per unit of livestock product. In evaluating these mitigation practices, quantifying NH3 and CH4 emissions as a percentage of losses of dietary nutrients or energy would be beneficial. In addition, emission factors based on intakes of dietary nutrients or energy can address the effect of feed intake and reduce uncertainties in estimation of emissions, and also be used as a key parameter in establishing emission inventories. Various emission models have been developed to simulate NH3 and CH4 emissions from beef and dairy cattle operations. Most of the current empirical or statistical models are built from data collected under controlled conditions or from a particular site, and care must be taken when generalizing these models to estimate emissions under different scenarios. The objective of this study was to conduct a systematic review of published literature on NH3 and CH4 emissions from beef and dairy cattle operations in order to obtain statistically representative emission factors based on intakes of dietary nutrients or energy, and to identify major causes of emission variations. The review focused on NH3 emissions from beef feedlots and dairy cattle barns, Agricultureand enteric2017 CH, 7, 164 emissions from cattle. NH3 and CH4 emissions from lagoons or other manure storage2 of 12 facilities were not included in this review.

Figure 1. Gas emissions represent losseslosses ofof nutrientsnutrients andand energyenergy fromfrom cattlecattle operations.operations.

2. Literature Search and Data Analysis With increasingly stringent air pollution regulations and the emerging pressure to regulate agriculturalAn exhaustive enterprises, search there using will multiple be a continued strategies need was for undertaken emission inventories to identify based eligible on studies reliable to and be representativeincluded in the emission review. factors, The literature as well as searches an increasing were demand performed for mitigationin the following strategies. electronic On the otherbibliographic hand, production databases: efficiency AGRICOLA, is a contributing AGRIS, Biological factor in & reducing Agricultural the environmental Index, Biological footprint Abstracts, per unitCAB of Abstracts, product. StrategiesCAB Reviews, that increaseEnvironment production Complete, efficiency Pollution will conserve Abstracts, resources Web of andScience, improve and environmentalGoogle Scholar. stewardship, In each database, and couldan iterative represent process a great was opportunity used to refine for the mitigating search strategy NH3 and through CH4 emissionstesting of perseveral unit search of livestock terms product. and incorporation In evaluating of new these search mitigation terms practices, as new relevant quantifying studies NH 3wereand CHidentified.4 emissions A manual as a percentage search was of losses carried of out dietary for references nutrients or that energy were would cited bein beneficial.the identified In addition, studies. emissionThe inclusion factors criteria based onwere intakes that the of dietary study nutrientsmust report or energy measured can addressNH3 or theenteric effect CH of4 feed emission intake from and reducecattle operations uncertainties and in the estimation emission ofcan emissions, be expressed and as also a percentage be used as of a keyintakes parameter of dietary in establishing nutrients or emissionenergy based inventories. on given Variousinformation. emission The study models must have be been published developed in English to simulate and inclusion NH3 and was CH not4 emissions from beef and dairy cattle operations. Most of the current empirical or statistical models are built from data collected under controlled conditions or from a particular site, and care must be taken when generalizing these models to estimate emissions under different scenarios. The objective of this study was to conduct a systematic review of published literature on NH3 and CH4 emissions from beef and dairy cattle operations in order to obtain statistically representative emission factors based on intakes of dietary nutrients or energy, and to identify major causes of emission variations. The review focused on NH3 emissions from beef feedlots and dairy cattle barns, and enteric CH4 emissions from cattle. NH3 and CH4 emissions from lagoons or other manure storage facilities were not included in this review.

2. Literature Search and Data Analysis An exhaustive search using multiple strategies was undertaken to identify eligible studies to be included in the review. The literature searches were performed in the following electronic bibliographic databases: AGRICOLA, AGRIS, Biological & Agricultural Index, Biological Abstracts, CAB Abstracts, CAB Reviews, Environment Complete, Pollution Abstracts, Web of Science, and Google Scholar. In each database, an iterative process was used to refine the search strategy through testing of several search terms and incorporation of new search terms as new relevant studies were identified. A manual search was carried out for references that were cited in the identified studies. The inclusion criteria were that the study must report measured NH3 or enteric CH4 emission from cattle operations and the emission can be expressed as a percentage of intakes of dietary nutrients or energy based on given information. The study must be published in English and inclusion was not restricted by study Agriculture 2017, 7, 16 3 of 12 size or publication type. Studies that only reported emissions from manure storage facilities were not included. Two individuals independently conducted the search processes and screened the studies by reading the title and abstract in order to select studies for full review according to the inclusion criteria. The included studies were distributed to a group of reviewers for data extraction. Standard data extraction sheets were developed for consistency. Each study was reviewed in duplicate by two independent reviewers for quality control. As a result of the data review and extraction processes, a database that included treatment means at various common feed and animal combinations from various studies was created and is available for independent scrutiny of the process. For each study, the following general information was recorded: (1) Geographic region: Asia, Europe, North America, Oceania, or South America; (2) Cattle type: beef or dairy; (3) Average weight of animal, kg; (4) Number of animals measured; and (5) Measurement method. For studies that reported NH3 emissions, the following variables were recorded in addition: (1) Farm type: beef feedlot, dairy open-lot, free-stall or tie-stall dairy barns; (2) Dietary crude protein (CP), %; (3) N intake: g/day/animal; (4) Air temperature: outdoor air temperature for beef feedlots or dairy open-lots, indoor air temperature for free-stall/tie-stall dairy barns, ◦C; (5) Ventilation: natural or mechanical; (6) Floor type: solid or slatted; (7) NH3 emission per animal, g/day/animal; and (8) NH3-N loss as a percentage of N intake. For studies that reported CH4 emissions, the following variables were recorded in addition: (1) Breed of animal; (2) Lactation status: lactating or dry; (3) Days in milk: for lactating dairy; (4) Feeding method: grazing or housed; (5) Diet forage-to-concentrate ratio; (6) Fat content in diet, g/kg DM; (7) Energy digestibility of feed (ED), %; (8) General energy intake (GEI), MJ/day/animal; (9) Energy intake level (EIL): calculated as ratio of digestible energy intake to energy requirement for maintenance of cattle; (10) CH4 emission per head, g/day/animal; (11) Ym: percentage of GEI converted to CH4; and (12) Dm: percentage of digestible energy intake converted to CH4. When a study provided treatment means at different conditions (sites), multiple treatment means (data points) were extracted from the study. Treatment means from special feed additive experiments were considered not representative and thus were not included. Normality of the data across studies was evaluated using the Shapiro–Wilk test, and funnel plots were used to detect potential publication bias, using number of animals measured as the y-axis. The MIXED procedures of SAS (SAS for Windows, ver. 9.4, SAS Institute, Cary, NC, USA) were used to investigate effects of various factors. The study effect was treated as a random variable since some studies contain multiple data points. The number of animals contributing to each treatment mean was used as a weighting variable. A backward elimination process was used to remove the confounded terms and to reduce non-significant terms one by one. The data were also classified into various homogeneous subgroups to conduct subgroup analysis based on identified significant factors such as farm type. In each subgroup, regressions were undertaken to quantify the effects of identified important variables, such as air temperature and dietary CP for NH3, and feed digestibility and energy intake for CH4. Significant effects were declared at p-value < 0.05.

3. NH3 Emissions as a Loss of Dietary Nutrients

3.1. Overall Statistics Under practical conditions, only 20% to 35% of the nitrogen (N) fed to a dairy cow is secreted in milk [4,5]. For beef cattle, only 10% to 20% of the N consumed is retained by the animal [6]. Almost all of the remaining N is excreted in urine and feces. The N in the urine is mainly in the form of urea, which can rapidly be converted to NH3 when in contact with the urease enzyme in feces. It has been reported that NH3 emissions from cattle operations could be linearly related with feed N intake [7] and are sensitive to CP in rations [8]. However, in reality, the total N volatilization from manure (primarily Agriculture 2017, 7, 16 4 of 12

inAgriculture the form 2017 of, 7 NH, 16 3) had wide variations, ranging from 5% to 80% of manure N, depending on the4 type of 12 of manure management system [9]. The literatureliterature search search yielded yielded a a total total of of 92 92 papers papers published published from from 1997 1997 to 2016,to 2016, which which included included 173 treatment173 treatment means means of measured of measured NH3 NH-N loss3‐N asloss a percentageas a percentage of N of intake N intake at various at various animal animal and farm and farm type combinationstype combinations for beef for or beef dairy or cattle dairy operations. cattle operations. Distributions Distributions of these treatmentof these treatment means are means presented are inpresented Figure2 .in The Figure average 2. The NH average3-N loss NH as3‐ aN percentage loss as a percentage of N intake of were N intake 53.1%, were 15.6%, 53.1%, 8.4%, 15.6%, and 8.4%, 5.6% forand beef 5.6% feedlots, for beef dairy feedlots, open-lots, dairy free/tie-stall open‐lots, free/tie dairy‐ barnsstall dairy with naturalbarns with ventilation, natural and ventilation, free/tie-stall and dairyfree/tie barns‐stall with dairy mechanical barns with ventilation, mechanical respectively. ventilation, Althoughrespectively. the averageAlthough emission the average rates emission for dairy open-lotsrates for dairy (125.6 open g/day/animal)‐lots (125.6 wereg/day/animal) comparable were with comparable that for beef with feedlots that for (105.9 beef g/day/animal), feedlots (105.9 theg/day/animal), average NH the3-N average loss as NH a percentage3‐N loss as of a percentage N intake for of dairy N intake open-lots for dairy was open less‐lots than was one less third than of thatone third for beef of that feedlots for beef (15.6% feedlots vs. (15.6% 53.1%) vs. because 53.1%) dairy because cattle dairy usually cattle haveusually much have higher much Nhigher intake. N Theintake. NH The3-N NH loss3‐ asN aloss percentage as a percentage of N intake of N for intake dairy for open-lots dairy open was‐ aboutlots was two about times two higher times than higher that forthan free/tie-stall that for free/tie dairy‐stall barns dairy with barns natural with or natural mechanical or mechanical ventilation ventilation when emissions when emissions from manure from storagemanure facilitiesstorage facilities were not were included not (15.6%included vs. (15.6% 8.4% or vs. 5.6%). 8.4% Theor 5.6%). total NH The3-N total loss NH as3 a‐N percentage loss as a ofpercentage N intake of that N intake for dairy that barns for dairy with barns emissions with fromemissions manure from storage manure facilities storage included facilities hasincluded been estimatedhas been estimated to be 20% to to be 55% 20% by to the 55% MidWest by the MidWest Plan Service Plan [ 10Service], which [10], was which even was larger even than larger that than for dairythat for open-lots dairy open (15.6%).‐lots (15.6%). The average The average NH3-N NH loss3‐N as loss a percentage as a percentage of N intake of N intake for dairy for dairy barns barns with mechanicalwith mechanical ventilation ventilation was lower was lower than that than for that dairy for barns dairy withbarns natural with natural ventilation. ventilation. The NH The3-N NH loss3‐ asN aloss percentage as a percentage of N intake of N for intake beef feedlots for beef and feedlots dairy open-lotsand dairy both open demonstrated‐lots both demonstrated a normal distribution. a normal Indistribution. contrast, the In NHcontrast,3-N loss the asNH a3 percentage‐N loss as a of percentage N intake forof N free/tie-stall intake for free/tie dairy‐ barnsstall dairy with barns natural with or mechanicalnatural or mechanical ventilation ventilation demonstrated demonstrated a skewed distribution a skewed distribution with a long with tail on a long the right tail on side, the which right indicatedside, which the indicated heterogeneity the heterogeneity caused by relatively caused by complex relatively inﬂuencing complex influencing factors in free/tie-stall factors in free/tie barns,‐ suchstall barns, as various such manure as various handling manure practices, handling ventilation practices, andventilation ﬂoor types. and Nofloor evidence types. No of publicationevidence of biaspublication was found bias based was found on the based funnel on plots. the funnel plots.

Figure 2. HistogramsHistograms of of NH NH3‐N3-N loss loss as asa percentage a percentage of N of intake N intake for: ( for:a) beef (a) feedlots; beef feedlots; (b) dairy (b) open dairy‐ open-lots;lots; (c) dairy (c) dairybarns barnswith natural with natural ventilation; ventilation; and (d and) dairy (d) dairybarns barns with mechanical with mechanical ventilation. ventilation.

3.2. Effect of Air Temperature

Air temperature can significantly affect NH3 emissions due to its effect on NH3 volatilization and convective mass transfer [11]. Todd [12] reported that summer emissions from a cattle feedyard were about twice as great as in the winter. Regressions were conducted for NH3‐N loss as % of N intake as Agriculture 2017, 7, 16 5 of 12

3.2. Effect of Air Temperature

Air temperature can significantly affect NH3 emissions due to its effect on NH3 volatilization and convective mass transfer [11]. Todd [12] reported that summer emissions from a cattle feedyard were about twice as great as in the winter. Regressions were conducted for NH -N loss as % of N intake Agriculture 2017, 7, 16 3 5 of 12 as a function of air temperature using data from the literature, and fit plots are presented in Figure3. For beefa function feedlot, of dairy air temperature open-lots, using and dairydata from barns the with literature, natural and ventilation, fit plots are the presented NH3-N in loss Figure as % 3. of N intakeFor all beef increased feedlot, with dairy increasing open‐lots, temperature. and dairy barns However, with natural for dairy ventilation, barns the with NH mechanical3‐N loss as ventilation,% of N the effectintake of all air increased temperature with was increasing not significant temperature. (p = 0.48,However,n = 32).for Thisdairy wasbarns likely with due mechanical to the large variationventilation, of emissions the effect dominated of air temperature by various was mechanical not significant ventilation (p = 0.48, conditions,n = 32). This sincewas likely the mechanical due to ventilationthe large system variation design of emissions determines dominated air velocity by various near mechanical the floor, and ventilation thus has conditions, significant since influence the mechanical ventilation system design determines air velocity near the floor, and thus has significant on NH3 emission in dairy barns [11]. The sensitivity of NH3-N loss as a percentage of N intake to influence on NH3 emission in dairy barns [11]. The sensitivity of NH3‐N loss as a percentage of N temperaturesintake to obtainedtemperatures from obtained studies from on dairystudies barns on dairy with barns natural with ventilation natural ventilation was comparable was comparable with that ◦ for open-lotwith that dairy for open barns‐lot (0.46% dairy barns vs. 0.40% (0.46% per vs. 0.40%C), while per °C), the while sensitivity the sensitivity was higher was higher for beef for beef feedlots ◦ (0.72%feedlots per C). (0.72% This per was °C). because This was beef because cattle beef usually cattle have usually lower have N lower intake N intake than dairy than dairy cattle. cattle. In fact, In the sensitivityfact, the of sensitivity NH3 emission of NH3 rateemission in g/d/animal rate in g/d/animal to air to temperature air temperature obtained obtained from from various types types of cattleof operations cattle operations was comparable was comparable with with each each other other (2.33, (2.33, 2.39, 2.39, 2.66 2.66 g/day/animalg/day/animal per per °C, ◦respectively,C, respectively, for beeffor feedlots,beef feedlots, dairy dairy open-lots, open‐lots, and and dairy dairy barns barns with with natural ventilation). ventilation).

FigureFigure 3. Fit 3. plots Fit plots for NHfor NH3-N3‐ lossN loss as as a percentagea percentage of of NN intakeintake (N (Nlossloss%)%) as as a function a function of air of temperature air temperature (T) for:(T) ( afor:) beef (a) beef feedlots; feedlots; (b) ( dairyb) dairy open-lots; open‐lots; and and ( c(c)) dairydairy barns with with natural natural ventilation. ventilation.

3.3. Effect of Dietary Crude Protein (CP) Content 3.3. Effect of Dietary Crude Protein (CP) Content Another important factor that affects NH3 emissions is dietary CP. For beef feedlots, open‐lot Another important factor that affects NH emissions is dietary CP. For beef feedlots, open-lot dairy barns and dairy barns with natural ventilation,3 the NH3 emission rates were significantly dairyaffected barns and by dairyboth air barns temperature with natural and dietary ventilation, CP (p the < 0.05). NH3 Whenemission both rates air temperature were signiﬁcantly and dietary affected by bothCP airwere temperature included in andregression, dietary the CP sensitivity (p < 0.05). of emission When both rates air to temperature dietary CP obtained and dietary for various CP were includedtypes in of regression, cattle operations the sensitivity was 9.9, of12.7, emission and 10.4 rates g∙day to− dietary1∙animal CP−1 per obtained 1% CP, for respectively, various types for beef of cattle feedlots, dairy open‐lots and free/tie‐stall dairy barns with natural ventilation. The result indicated that, for every one percentage point increase in dietary CP (e.g., from 14% to 15%), an increase of 9.9 Agriculture 2017, 7, 16 6 of 12 operationsAgriculture 2017 was, 7, 16 9.9, 12.7, and 10.4 g·day−1·animal−1 per 1% CP, respectively, for beef feedlots, dairy6 of 12 open-lots and free/tie-stall dairy barns with natural ventilation. The result indicated that, for every one percentageto 12.7 g/day/animal point increase in NH in3 dietary emission CP rates (e.g., can from be 14% expected. to 15%), This an increase was comparable of 9.9 to 12.7 with g/day/animal the results of Bougouin et al. [13], which concluded that a unit increase in dietary CP resulted in a 10.2 in NH3 emission rates can be expected. This was comparable with the results of Bougouin et al. [13], g/day/animal increase in NH3 emissions from dairy operations. The effect of dietary CP on NH3 which concluded that a unit increase in dietary CP resulted in a 10.2 g/day/animal increase in NH3 emissions for free/tie‐stall dairy barns with mechanical ventilation was not observed, possibly due to emissions from dairy operations. The effect of dietary CP on NH3 emissions for free/tie-stall dairy barnsthe large with variation mechanical in emissions ventilation dominated was not observed, by mechanical possibly ventilation due to the conditions. large variation For beef in emissions feedlots dominatedand dairy barns by mechanical with natural ventilation ventilation, conditions. higher dietary For CP beef not feedlots only resulted and dairy in higher barns NH with3 emission natural rates but also corresponded with higher NH3‐N loss as percentage of N intake, although the effect ventilation, higher dietary CP not only resulted in higher NH3 emission rates but also corresponded was not statistically significant at α = 0.05 level (p = 0.31 and 0.14, respectively, for beef feedlots and with higher NH3-N loss as percentage of N intake, although the effect was not statistically signiﬁcant at αdairy= 0.05 barns level with (p = natural 0.31 and ventilation). 0.14, respectively, Figure for 4 demonstrates beef feedlots andthe effect dairy of barns dietary with CP natural on NH ventilation).3 emission rate as well as on the NH3‐N loss as percentage of N intake for beef feedlots when dietary CP was the Figure4 demonstrates the effect of dietary CP on NH 3 emission rate as well as on the NH3-N loss asonly percentage factor considered of N intake in forthe beefregression. feedlots The when results dietary were CP in was agreement the only with factor the considered report that in thethe regression.proportion Theof total results N excreted were in in agreement urine was with positively the report related that with the proportion dietary CP of [14]. total Huhtanen N excreted et al. in urine[15] once was estimated positively that related 84% with of the dietary incremental CP [14]. N Huhtanen intake was et excreted al. [15] once in urine. estimated The excess that 84% CP offed the to incrementalthe animal Nis intakemostly was voided excreted as urea in urine. in urine, The excess and thus CP fed will to theresult animal in increased is mostly voidedpercentage as urea of inN urine,excreted and in thus urine will and result increased in increased percentage percentage of N loss of N as excreted NH3. The in effect urine of and dietary increased CP on percentage NH3‐N loss of as a percentage of N intake for dairy open‐lots was not observed, possibly due to the limited number N loss as NH3. The effect of dietary CP on NH3-N loss as a percentage of N intake for dairy open-lots wasof data not observed,points in literature. possibly due More to thestudies limited on numberdairy open of data‐lots pointsusing various in literature. dietary More CP studies levels are on dairyneeded open-lots to better using evaluate various the effect dietary of CP dietary levels CP. are needed to better evaluate the effect of dietary CP.

FigureFigure 4.4. FitFit plotsplots forfor ((aa)) NH NH33 emissionemission raterate andand ((bb)) NH NH33-N‐N lossloss asas aa percentagepercentage of of N N intake intake (N (Nlossloss%) asas aa functionfunction ofof dietarydietary crudecrude proteinprotein (CP)(CP) forfor beefbeef feedlots. feedlots.

3.4.3.4. Other Factors ThatThat AffectAffect NHNH33 Emission

ThereThere areare many many other other factors factors that that can can affect affect NH3 NHemissions3 emissions from cattlefrom operations,cattle operations, such as manuresuch as handlingmanure handling practices practices (scraping (scraping or flushing), or flushing), manure removalmanure removal frequency, frequency, floor types floor (solid types or (solid slatted), or barnslatted), types barn (free-stall types or tie-stall),(free‐stall ventilation or tie of‐stall), barns, ventilation wind speed/solar of barns, radiation/precipitation wind speed/solar for open-lots,radiation/precipitation etc. It is very difficultfor open to‐lots, quantify etc. It and is very generalize difficult the to effects quantify of theseand generalize factors with the the effects limited of amountthese factors of data with in literature, the limited and amount many of of data these in factors literature, were and confounded many of these with each factors other. were As confounded mentioned earlier,with each the other. NH3-N As loss mentioned as a percentage earlier, ofthe N NH intake3‐N forloss dairy as a barnspercentage with mechanicalof N intake ventilationfor dairy barns was lowerwith mechanical than that for ventilation dairy barns was with lower natural than ventilation. that for dairy The barns effect ofwith ventilation natural ventilation. type was confounded The effect byof ventilation barn type. Onetype possiblewas confounded reason for by lower barn type. emissions One possible from barns reason with for mechanical lower emissions ventilation from is barns that 72%with of mechanical the barns withventilation mechanical is that ventilation 72% of the were barns tie-stall with mechanical barns, while ventilation 96% of the were barns tie with‐stall natural barns, ventilationwhile 96% wereof the free-stall barns with barns natural in the dataventilation analyzed. were The free beddings‐stall barns typically in the used data in analyzed. tie-stall barns The canbeddings separate typically urine and used feces in andtie‐stall thus reducebarns can NH 3separateproduction urine [16 and], and feces the emittingand thus surface reduce area NH of3 production [16], and the emitting surface area of tie‐stall barns was often less than that of free‐stall barns [17]. Another reason could be that mechanical ventilation can reduce moisture in barns and thus reduce NH3 emissions. Generally, the NH3‐N loss as a percentage of N intake for free/tie‐stall Agriculture 2017, 7, 16 7 of 12

Agriculturetie-stall barns 2017, 7 was, 16 often less than that of free-stall barns [17]. Another reason could be that mechanical7 of 12 ventilation can reduce moisture in barns and thus reduce NH3 emissions. Generally, the NH3-N loss as dairya percentage barns demonstrated of N intake for much free/tie-stall larger dairyvariation barns than demonstrated that for beef much feedlots. larger variation The coefficients than that forof variationbeef feedlots. were The 0.3, coefﬁcients 0.5, 0.6, and of 1.1 variation for beef were feedlots, 0.3, 0.5, dairy 0.6, open and 1.1‐lots, for free/tie beef feedlots,‐stall dairy dairy barns open-lots, with naturalfree/tie-stall ventilation, dairy barnsand free/tie with‐ naturalstall dairy ventilation, barns with and mechanical free/tie-stall ventilation. dairy barns The with larger mechanical variation andventilation. the skewed The distribution larger variation with long and tails the skewed on the right distribution side in Figure with long 2c,d tailsindicated on the that right there side may in be considerable room for reducing NH3 emission with improved management practices in free/tie‐ Figure2c,d indicated that there may be considerable room for reducing NH 3 emission with improved stallmanagement dairy barns, practices especially in free/tie-stall in barns with dairy mechanical barns, especially ventilation. in barns When with mechanicaldeveloping ventilation.mitigating strategies,When developing for open mitigating‐lot dairy strategies, barns and for beef open-lot feedlots, dairy managing barns and beefN intake feedlots, and managing improving N intake feed efficiencyand improving seem feedto represent efﬁciency the seem greatest to represent opportunities. the greatest For opportunities.free/tie‐stall dairy For free/tie-stallbarns, improving dairy ventilationbarns, improving design ventilationand management design practices and management could be practicesmore effective. could be more effective.

4.4. Enteric Enteric CH CH44 EmissionsEmissions as as a a Loss Loss of of Dietary Dietary Energy Energy

4.1.4.1. Overall Overall Statistics Statistics

SinceSince CH CH44 representsrepresents an an unproductive unproductive loss loss of of dietary dietary energy, energy, one one of of the the predominant enteric enteric CHCH44 emissionemission estimation estimation procedures procedures is isdriven driven by by first first estimating estimating daily daily gross gross energy energy intake intake (GEI) (GEI) by individualby individual animals animals and andthen then multiplying multiplying the GEI the by GEI an by estimate an estimate of “methane of “methane conversion conversion factor (Y factorm)”, which(Ym)”, whichranges rangesfrom 2% from to 2% 11% to 11%of GEI of GEIin literature. in literature. An An alternative alternative approach approach is is to to express express CH 4 conversionconversion factors factors on on a a digestible energy basis. D Dmm waswas defined defined as as percentage percentage of of digestible digestible energy energy intakeintake converted converted to to CH CH44.. Typical Typical ruminant ruminant diets diets contain contain about about 18.4 18.4 MJ MJ of of gross gross energy energy (GE) (GE) per per kg kg of of drydry matter matter (DM) (DM) and and CH CH4 4hashas energy energy content content of of 55.65 55.65 MJ/kg MJ/kg [18]. [18 Therefore,]. Therefore, a typical a typical Ym value Ym value of 6% of corresponds6% corresponds to 19.8 to 19.8g CH g4 CH/kg 4DM/kg intake. DM intake. Assuming Assuming the energy the energy digestibility digestibility of feed of is feed 65%, is a 65%, Ym value a Ym ofvalue 6.5% of corresponds 6.5% corresponds to a Dm to value a Dm ofvalue 10%. of 10%. TheThe literature literature search search yielded yielded a a total total of of 89 89 papers published from from 1992 1992 to to 2015, which which included included 217217 treatment treatment means means of of measured measured enteric CH 4 lossloss as as a a percentage percentage of of dietary dietary energy energy intake intake at at various various animalanimal and and farm farm type type combinations combinations for beef or dairy cattle operations. The treatment means of Ym oror DDmm werewere obtained obtained from from these these studies studies directly directly or or calculated calculated based based on on given given information. information. Distributions Distributions ofof these these treatment treatment means means are are presented presented in in Figure Figure 55.. No significantsignificant differencedifference waswas observedobserved betweenbetween beefbeef and and dairy dairy cattle cattle for for Y Ym m(p (=p 0.79)= 0.79) or D orm D (pm =( 0.93).p = 0.93). Grazing Grazing cattle cattle had higher had higher Ym than Ym housedthan housed cattle (7.3%cattle (7.3%vs. 6.1%, vs. 6.1%,p < 0.01),p < 0.01), but D butm was Dm wasnot notsignificantly significantly affected affected by by feeding feeding method method (p (p == 0.56). 0.56). The The differencedifference in Y Ym betweenbetween grazing grazing and and housed housed cattle cattle could could be be due due to to the the effect effect of of feed feed digestibility. digestibility. No No evidenceevidence of of publication publication bias bias was was found found based on the funnel plot.

Figure 5. Histograms of CH4 conversion factors on gross energy intake (GEI) or digestible energy Figure 5. Histograms of CH4 conversion factors on gross energy intake (GEI) or digestible energy basis: (a) Ym: CH4 loss as a percentage of GEI; and (b) Dm: CH4 loss as a percentage of digestible energy basis: (a)Ym: CH4 loss as a percentage of GEI; and (b)Dm: CH4 loss as a percentage of digestible intake.energy intake.

4.2. Effect of Feed Digestibility Increasing the proportion of concentrate in the diet will likely increase animal productivity and thus decrease enteric CH4 emission per unit of animal product even though the absolute CH4 emissions Agriculturemay not be2017 reduced, 7, 16 [19–21]. The default values of Ym provided by the Intergovernmental Panel8 of on 12 Climate Change (IPCC) [9] are 3.0% ± 1.0% for feedlot cattle that are fed diets containing 90% or more orconcentrates, more concentrates, and 6.5% and± 1.0% 6.5% for ± dairy 1.0% cows for dairy and cattle cows that and are cattle primarily that are fed primarily low quality fed crop low residues quality cropand by-products. residues and Analysis by‐products. of data acrossAnalysis studies of data showed across that lowerstudies forage-to-concentrate showed that lower ratio forage in diets‐to‐ concentrategenerally resulted ratio in in diets lower generally Ym and D resultedm (p < 0.01 in forlower both Y Ym mandand D Dmm (p). < The 0.01 least for squaresboth Ym mean and ofDm Y).m Thefor leastcattle squares that were mean fed dietsof Ym containing for cattle that 90% were or more fed concentratesdiets containing was 90% 3.8% or± more0.5%, concentrates which was higher was 3.8% than ±the 0.5%, 3.0% which± 1.0% was provided higher than by the the IPCC 3.0% [9 ±]. 1.0% In contrast, provided the by least the squares IPCC [9]. mean In contrast, of Ym for the cattle least that squares were meanfed diets of Y containingm for cattle 10% that orwere less fed concentrates diets containing was 7.3% 10%± or0.4%. less concentrates Lower forage-to-concentrate was 7.3% ± 0.4%. ratio Lower in foragediets corresponded‐to‐concentrate to higherratio in digestibility. diets corresponded Typical feed to energy higher digestibility digestibility. in U.S. Typical was 66.7% feed for energy dairy digestibilitycows and 82.5% in U.S. for feedlotwas 66.7% cattle for in dairy 2012 [2cows]. For and grazing 82.5% cattle, for feedlot forage cattle digestibility in 2012 is [2]. mainly For affectedgrazing cattle,by stage forage of maturity digestibility and forageis mainly species affected in addition by stage to of environmental maturity and conditionsforage species [22, 23in ].addition Increased to environmentalforage digestibility conditions is expected [22,23]. to Increased decrease entericforage digestibility CH4 emission is expected per unit ofto animaldecrease products enteric CH [21].4 emissionBased on per the unit 51 studies of animal included products in [21]. this Based review, on the the average51 studies feed included energy in digestibility this review, the for average grazing feedcattle energy was 58.8%, digestibility 68.0%, for and grazing 70.2% cattle in North was America,58.8%, 68.0%, Europe, and and70.2% Oceania, in North respectively, America, Europe, which providedand Oceania, an explanation respectively, for which the higher provided Ym in an North explanation America for as comparedthe higher with Ym in Europe North and America Oceania as (7.7%compared vs. 6.6% with and Europe 5.7%). and The Oceania observed (7.7% higher vs. 6.6% Ym for and grazing 5.7%). cattle The observed as compared higher with Y housedm for grazing cattle wascattle expected as compared since with grazing housed cattle cattle generally was expected had lower since feed grazing digestibility cattle generally than most had housed lower cattle. feed digestibilityRegressions werethan most conducted housed for cattle. Ym and Regressions Dm as a function were conducted of feed energy for Ym digestibility and Dm as a usingfunction data of fromfeed energyliterature digestibility including using both houseddata from and literature grazing including cattle studies, both andhoused fit plots and grazing are presented cattle studies, in Figure and6. Asfit plots shown are in presented Figure6,D inm Figuredemonstrated 6. As shown a much in Figure better 6, fit D thanm demonstrated Ym to reflect a the much effect better of feed fit than energy Ym 4 todigestibility reflect the oneffect CH of4 emissions. feed energy digestibility on CH emissions.

Figure 6. Fit plots for (a)Y) Ym (CH(CH44 lossloss as as a a percentage percentage of GEI) and (b)D) Dm (CH(CH44 lossloss as as a a percentage percentage of digestible energy intake) as a function of feed energy digestibility.

4.3. Effect of Energy Intake

Enteric fermentation and hence Ym waswas also also affected by feed intake. Kujawa [24] [24] and Diarra [25] [25] reported that Ym variedvaried from from 8% 8% to to 11% 11% when when measured measured at at restricted restricted feed feed intakes intakes and and from from 5% to to 6% 6% when measured at ad libitum intake. Johnson and Johnson [26] [26] stated stated that that as feed feed intake intake increased, increased, the Y m decreaseddecreased by by about about 1.6 1.6 percent percent-units‐units per each level of intake above maintenance. Sauvant and GigerGiger-Reverdin‐Reverdin [27] [27] reported a linearlinear decrease inin YYmm with increasing feed intake. Feed digestibility and intakeintake levellevel could could affect affect each each other. other. Increasing Increasing feed feed digestibility digestibility could could help help to increase to increase intake intake level, level, and, conversely, excessive intake could reduce digestibility [27–29]. Generally, high digestibility did not necessarily result in a high intake level, but low digestibility usually resulted in a low intake level. However, a strong relationship between them has not been documented [26]. In this review, the energy intake level (EIL) was defined as the ratio of digestible energy intake to energy requirement for maintenance of cattle and was used to evaluate the effect of feed intake. It was calculated for all reviewed studies when needed information was available. The energy requirement for maintenance (NEm) was estimated using an equation from the IPCC [9]: Agriculture 2017, 7, 16 9 of 12 and, conversely, excessive intake could reduce digestibility [27–29]. Generally, high digestibility did not necessarily result in a high intake level, but low digestibility usually resulted in a low intake level. However, a strong relationship between them has not been documented [26]. In this review, the energy intake level (EIL) was deﬁned as the ratio of digestible energy intake to energy requirement for maintenance of cattle and was used to evaluate the effect of feed intake. It was calculated for all reviewed studies when needed information was available. The energy requirement Agriculture 2017, 7, 16 9 of 12 for maintenance (NEm) was estimated using an equation from the IPCC [9]:

NE = Cf × (Weight)0.75, (1) NEmm = Cfii × (Weight)0.75, (1) inin whichwhich Cf Cfi isi is a coefficienta coefficient that that varies varies for each for animaleach animal category. category. Assuming Assuming the efficiency the ofefficiency conversion of conversionof digestible of energy digestible to metabolisable energy to metabolisable energy (ME) energy is 0.82 (ME) and is the 0.82 efficiency and the efficiency of conversion of conversion of ME to ofNE MEm ranges to NEm from ranges 0.64 from to 0.70 0.64 [30 to], 0.70 when [30], the when ME available the ME available in feed intake in feed equals intake the equals ME required the ME requiredfor maintenance, for maintenance, the corresponding the corresponding EIL is around EIL is around 1.74 to 1.90.1.74 to Both 1.90. Y Bothm and Ym D andm decreased Dm decreased with withincreasing increasing EIL ( pEIL< 0.01(p < 0.01 for both for both Ym andYm and Dm )D asm) expectedas expected when when EIL EIL was was the the only only factor factor considered considered in inthe the regression regression (Figure (Figure7). 7).

Figure 7. FitFit plots for ( a))Y Ym (CH(CH44 lossloss as as a a percentage percentage of GEI) and ( b)D) Dm (CH(CH44 lossloss as as a a percentage percentage of digestible energy intake) as a function of energy intake level (EIL).

When effects of EIL and and energy energy digestibility digestibility of of feed feed were were both both included included in in a a two two-factor‐factor analysis, analysis, increasing EIL reduced Ym (p = 0.02), but the effect of feed energy digestibility was no longer increasing EIL reduced Ym (p = 0.02), but the effect of feed energy digestibility was no longer significant significant (p = 0.07). A significant effect of digestibility on CH4 emission could not be demonstrated (p = 0.07). A significant effect of digestibility on CH4 emission could not be demonstrated possibly due possibly due to the limitations of the Ym approach. The limitations of the Ym approach have been to the limitations of the Ym approach. The limitations of the Ym approach have been noted [21,31,32]. notedBoadi [21,31,32]. and Wittenberg Boadi [and31] fedWittenberg low, medium [31] fed and low, high medium quality and forage high to quality dairy forage and beef to cattledairy and beef cattle and reported no statistical differences in Ym, but greater emissions with the lower quality reported no statistical differences in Ym, but greater emissions with the lower quality forages were forages were observed when expressed on digestible energy intake basis. Based on this review, Dm observed when expressed on digestible energy intake basis. Based on this review, Dm was significantly was significantly affected by both EIL and feed energy digestibility in a two‐factor analysis (p < 0.01 affected by both EIL and feed energy digestibility in a two-factor analysis (p < 0.01 for both effects). for both effects). An interaction effect was also observed (p < 0.01). The following regression model An interaction effect was also observed (p < 0.01). The following regression model (Equation (2)) was (Equation (2)) was developed based on data from all studies that provided Dm, energy digestibility developed based on data from all studies that provided Dm, energy digestibility and EIL (n = 100, and EIL (n = 100, R‐Square = 0.54). Based on the regression model, the sensitivity of Dm to feed energy R-Square = 0.54). Based on the regression model, the sensitivity of Dm to feed energy digestibility digestibility decreased as EIL increased. On the other hand, the sensitivity of Dm to EIL decreased as decreased as EIL increased. On the other hand, the sensitivity of Dm to EIL decreased as feed energy feed energy digestibility increased: digestibility increased:

Dm = 40.69 − 43.84 × ED − 4.870 × EIL + 6.368 × ED × EIL, (2) Dm = 40.69 − 43.84 × ED − 4.870 × EIL + 6.368 × ED × EIL, (2) where ED is feed energy digestibility, ranging from 0.33 to 0.84; EIL is energy intake level of cattle, measured as the ratio of digestible energy intake to the energy requirement for maintenance of cattle, ranging from 0.89 to 7.47; and Dm is percentage of digestible energy intake converted to CH4.

4.4. Other Factors That Affect CH4 Emission

Breed of cattle could be another factor that can affect enteric CH4 emissions. The least squares mean of Ym for Holstein cattle is 5.3% (n = 52). The limited data in literature showed that Thai native, Brown Swiss and Brahman cattle reported higher Ym than Holstein cattle, while Nellore cattle reported lower Ym than Holstein cattle. Fat supplementation has been proposed to reduce CH4 emission [33,34], but the microbiological mechanism was not well known. Increasing fat content may decrease digestibility [35] and increase energy intake level. The effect of fat content in diets on CH4 Agriculture 2017, 7, 16 10 of 12 where ED is feed energy digestibility, ranging from 0.33 to 0.84; EIL is energy intake level of cattle, measured as the ratio of digestible energy intake to the energy requirement for maintenance of cattle, ranging from 0.89 to 7.47; and Dm is percentage of digestible energy intake converted to CH4.

4.4. Other Factors That Affect CH4 Emission

Breed of cattle could be another factor that can affect enteric CH4 emissions. The least squares mean of Ym for Holstein cattle is 5.3% (n = 52). The limited data in literature showed that Thai native, Brown Swiss and Brahman cattle reported higher Ym than Holstein cattle, while Nellore cattle reported lower Ym than Holstein cattle. Fat supplementation has been proposed to reduce CH4 emission [33,34], but the microbiological mechanism was not well known. Increasing fat content may decrease digestibility [35] and increase energy intake level. The effect of fat content in diets on CH4 emission could be related to its effects on feed digestibility and energy intake level of cattle. The lactation status of dairy cows could also affect CH4 emission indirectly by affecting energy intake level, since, generally, energy intake level of lactating cows is higher than that of dry cows, and it decreases with increasing days in milk. For grazing cattle, geographic region can affect CH4 emission indirectly by affecting feed digestibility. As mentioned before, North America reported lower digestibility and thus higher Ym as compared with Europe and Oceania.

5. Conclusions

The NH3 and CH4 emission expressed as percentage losses of dietary nutrients or energy both demonstrated much less variation compared with emission rates expressed in g/animal/day. In reality, protein is often fed to livestock above the requirements for growth and maintenance. Improving nutrient management at the farm level and reducing protein intake have been considered as relatively easy ways of reducing NH3 emissions from cattle operations [36]. The NH3-N loss as a percentage of N intake was significantly different for various types of farms. Air temperature and dietary CP content were identified as two major factors that can affect NH3 emission in addition to farm type. In developing NH3 mitigation strategies, generally, managing N intake and improving feed efficiency seem to represent the greatest opportunities. In contrast, the larger variation and the skewed distribution of data in the literature indicated that there may be considerable room for reducing existing NH3 emission with improved management practices in free/tie-stall dairy barns, especially in barns with mechanical ventilation. Feed digestibility and energy intake were identified as two major factors that can affect CH4 emission expressed as percentage losses of dietary energy. Generally, higher energy digestibility of feed and higher energy intake level of cattle resulted in lower percentage of digestible energy intake converted to CH4. Increasing productivity and feed efficiency represent the greatest opportunity for mitigating CH4 emissions per unit of livestock product. However, expressing enteric CH4 energy production on GEI does not have the capacity to fully reflect the effects of diet quality and composition. Compared with the Ym approach, the use of CH4 conversion factor on a digestible energy basis (Dm) can better represent the large variation among diets and the effects of varying dietary emission mitigation strategies.

Acknowledgments: This study is contribution No. 17-223-J from the Kansas Agricultural Experiment Station. Publication of this article was funded in part by the Kansas State University Open Access Publishing Fund. Author Contributions: Zifei Liu and Yang Liu processed and analyzed the data. Zifei Liu wrote the paper. James P. Murphy and Ronaldo Maghirang reviewed and edited the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. National Research Council (NRC) of the National Academies. Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs; National Academies Press: Washington, DC, USA, 2003. Agriculture 2017, 7, 16 11 of 12

2. United States Environmental Protection Agency (USEPA). Inventory of US Greenhouse Gas Emissions and Sinks: 1990–2012. 2014. Available online: https://www3.epa.gov/climatechange/Downloads/ ghgemissions/US-GHG-Inventory-2014-Main-Text.pdf (accessed on 22 February 2017). 3. United States Environmental Protection Agency (USEPA). 2008 National Emissions Inventory, Version 3. Technical Support Document. 2013. Available online: https://www.epa.gov/sites/production/files/2015- 07/documents/2008_neiv3_tsd_draft.pdf (accessed on 22 February 2017). 4. Jonker, J.S.; Kohn, R.A.; High, J. Dairy herd management practices that impact nitrogen utilization efficiency. J. Dairy Sci. 2002, 85, 1218–1226. [CrossRef] 5. Liu, Z.; Powers, W.; Oldick, B.; Davidson, J.; Meyer, D. Gas emissions from dairy cows fed typical diets of midwest, south, and west regions of the United States. J. Environ. Qual. 2012, 41, 1228–1237. [CrossRef] [PubMed] 6. Cole, N.A.; Todd, R.W. Nitrogen and phosphorus balance of beef cattle feedyards. In Proceedings of the Texas Animal Manure Management Issues Conference, Texas AgriLife Extension, Round Rock, TX, USA, 29 September 2009; pp. 17–24. 7. James, T.; Meyer, D.; Esparza, E.; Depeters, E.J.; Perez-Monti, H. Effects of dietary nitrogen manipulation on ammonia volatilization from manure from Holstein heifers. J. Dairy Sci. 1999, 82, 2430–2439. [CrossRef] 8. Todd, R.W.; Cole, N.A.; Rhoades, M.B.; Parker, D.B.; Casey, K.D. Daily, monthly, seasonal, and annual ammonia emissions from southern High Plains cattle feedyards. J. Environ. Qual. 2011, 40, 1090–1095. [CrossRef][PubMed] 9. Intergovernmental Panel on Climate Change (IPCC). IPCC Guidelines for National Greenhouse Gas Inventories; Agricultural, Forestry and Other Land Use; Institute for Global Environmental Strategies (IGES): Hayama, Japan, 2006; Volume 4. 10. MidWest Plan Service (MWPS). Manure Storages; Manure management system series; MWPS-18, Section 2: Ames, IA, USA, 2001. 11. Rong, L.; Nielsen, P.V.; Zhang, G. Effects of airflow and liquid temperature on ammonia mass transfer above an emission surface: Experimental study on emission rate. Bioresour. Tech. 2009, 100, 4654–4661. [CrossRef] [PubMed] 12. Todd, R.W.; Cole, N.A.; Clark, R.N.; Flesch, T.K.; Harper, L.A.; Baek, B.H. Ammonia emissions from a beef cattle feedyard on the southern High Plains. Atmos. Environ. 2008, 42, 6797–6805. [CrossRef] 13. Bougouin, A.; Leytem, A.B.; Dijkstra, J.; Dungan, R.S.; Kebreab, E. Nutritional and environmental effects on ammonia emissions from dairy cattle housing: A meta-analysis. J. Environ. Qual. 2016, 45, 1123–1132. [CrossRef][PubMed] 14. Waldrip, H.M.; Todd, R.W.; Cole, N.A. Prediction of nitrogen excretion by beef cattle: A meta-analysis. J. Anim. Sci. 2013, 91, 4290–4302. [CrossRef][PubMed] 15. Huhtanen, P.; Nousiainen, J.I.; Rinne, M.; Kytola, K.; Khalili, H. Utilization and partition of dietary nitrogen in dairy cows fed grass silage-based diets. J. Dairy Sci. 2008, 91, 3589–3599. [CrossRef][PubMed] 16. Misselbrook, T.H.; Powell, J.M. Influence of bedding material on ammonia emissions from cattle excreta. J. Dairy Sci. 2005, 88, 4304–4312. [CrossRef] 17. Monteny, G.J.; Erisman, J.W. Ammonia emission from dairy cow buildings: A review of measurement techniques, influencing factors, and possibilities for reduction. Neth. J. Agric. Sci. 1998, 46, 225–247. 18. Commonwealth Scientific and Industrial Research Organisation (CSIRO). Nutrient Requirements of Domesticated Ruminants; CSIRO Publishing: Melbourne, Australia, 2007. 19. McGeough, E.J.; O’Kiely, P.; Hart, K.J.; Moloney, A.P.; Boland, T.M.; Kenny, D.A. Methane emissions, feed intake, performance, digestibility and rumen fermentation of finishing beef cattle offered whole-crop wheat silages differing in grain content. J. Anim. Sci. 2010, 88, 2703–2716. [CrossRef][PubMed] 20. Aguerre, M.J.; Wattiaux, M.A.; Powell, J.M.; Broderick, G.A.; Arndt, C. Effect of forage-to-concentrate ratio in dairy cow diets on emission of methane, carbon dioxide, and ammonia, lactation performance, and manure excretion. J. Dairy Sci. 2011, 94, 3081–3093. [CrossRef][PubMed] 21. Hristov, A.N.; Oh, J.; Lee, C.; Meinen, R.; Montes, F.; Ott, T.; Firkins, J.; Rotz, A.; Dell, C.; Adesogan, A.; et al.

Mitigation of Greenhouse Gas Emissions in Livestock Production—A Review of Technical Options for Non-CO2 Emissions; FAO Animal Production and Health Paper; Food and Agriculture Organization of the United Nations: Rome, Italy, 2013. Agriculture 2017, 7, 16 12 of 12

22. West, J.W. Factors which Influence Forage Quality and Effectiveness in Dairy Rations. In Proceedings of the Western Canadian Dairy Seminar (USA); 1998. Available online: http://www.wcds.ca/proc/1998/ch13.htm (accessed on 22 February 2017). 23. Bruinenberg, M.H.; Valk, H.; Korevaar, H.; Struik, P.C. Factors affecting digestibility of temperate forages from seminatural grasslands: A review. Grass Forage Sci. 2002, 57, 292–301. [CrossRef] 24. Kujawa, M.A. Energy Partitioning in Steers Fed Cottonseed Hulls or Sugar Beet Pulp. Ph.D. Thesis, Colorado State University, Ann Arbor, MI, USA, 1994. 25. Diarra, B. Net Energy Value of Soybean Hulls as Feed for Sheep. Ph.D. Thesis, Colorado State University, Ann Arbor, MI, USA, 1994. 26. Johnson, K.A.; Johnson, D.E. Methane Emissions from Cattle. J. Anim. Sci. 1995, 73, 2483–2492. [CrossRef] [PubMed] 27. Sauvant, D.; Giger-Reverdin, S. Modelling of digestive interactions and methane production in ruminants. Prod. Anim. 2009, 22, 375–384. 28. National Research Council. Nutrient Requirements of Dairy Cattle, 7th ed.; National Academies Press: Washington, DC, USA, 2001. 29. Huhtanen, P.; Rinne, M.; Nousiainen, J. A meta-analysis of feed digestion in dairy cows. 2. The effects of feeding level and diet composition on digestibility. J. Dairy Sci. 2009, 92, 5031–5042. [CrossRef][PubMed] 30. Agricultural Research Council (Great Britain). The Nutrient Requirements of Ruminant Livestock: Technical Review (No. 2); Commonwealth Agricultural Bureaux: Slough, UK, 1980. 31. Boadi, D.A.; Wittenberg, K.M. Methane production from dairy and beef heifers fed forages differing in nutrient density using the sulphur hexafluoride (SF6) tracer gas technique. Can. J. Anim. Sci. 2002, 82, 201–206. [CrossRef] 32. Kennedy, P.M.; Charmley, E. Methane yields from Brahman cattle fed tropical grasses and legumes. Anim. Prod. Sci. 2012, 52, 225–239. [CrossRef] 33. Grainger, C.; Williams, R.; Clarke, T.; Wright, A.D.G.; Eckard, R.J. Supplementation with whole cottonseed causes long-term reduction of methane emissions from lactating dairy cows offered a forage and cereal grain diet. J. Dairy Sci. 2010, 93, 2612–2619. [CrossRef][PubMed] 34. Moate, P.J.; Williams, S.R.O.; Grainger, C.; Hannah, M.C.; Ponnampalam, E.N.; Eckard, R.J. Influence of cold-pressed canola, brewers grains and hominy meal as dietary supplements suitable for reducing enteric methane emissions from lactating dairy cows. Anim. Feed Sci. Technol. 2011, 166–167, 254–264. [CrossRef] 35. Doreau, M.; Chilliard, Y.; Bauchart, D.; Michalet-Doreau, B.; Fléchet, J.; Lefaivre, R.; Legay, C.; Meyer, M.; Ollier, A. Influence of different fat supplements on digestibility and ruminal digestion in cows. Ann. Zootech. INRA/EDP Sci. 1991, 40, 19–30. [CrossRef] 36. Smits, M.C.J.; Monteny, G.J.; van Duinkerken, G. Effect of nutrition and management factors on ammonia emission from dairy cow herds: Models and field observations. Livest. Prod. Sci. 2003, 84, 113–123. [CrossRef]

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).