Estimation of enteric methane emissions trends (1990–2008) from Manitoba beef cattle using empirical and mechanistic models

Simple SummaryNumerous enteric methane (CH4) mitigation opportunities exist to reduce enteric CH4 and other greenhouse gas emissions per unit of product from ruminants. Research over the past century in genetics, animal health, microbiology, nutrition, and physiology has led to improvements in dairy and beef cattle production. The objectives of this review are to evaluate options that have been demonstrated to mitigate enteric CH4 emissions per unit of products (energy-corrected milk, milk yield, average daily gain, dry matter intake, and gross energy intake) from dairy and beef cattle on a quantitative basis and in a sustained manner, and to integrate approaches in feeding, rumen fermentation profiles, and rumen microbiota changes to emphasize the understanding of these relationships between enteric CH4 emissions and animal productivities.Enteric methane (CH4) emissions produced by microbial fermentation in the rumen resulting in the emission of greenhouse gases (GHG) into the atmosphere. The GHG emissions reduction from the livestock industry can be attained by increasing production efficiency and improving feed efficiency, by lowering the emission intensity of production, or by combining the two. In this work, information was compiled from peer-reviewed studies to analyze CH4 emissions calculated per unit of milk production, energy-corrected milk (ECM), average daily gain (ADG), dry matter intake (DMI), and gross energy intake (GEI), and related emissions to rumen fermentation profiles (volatile fatty acids [VFA], hydrogen [H2]) and microflora activities in the rumen of beef and dairy cattle. For dairy cattle, there was a positive correlation (p < 0.001) between CH4 emissions and DMI (R2 = 0.44), milk production (R2 = 0.37; p < 0.001), ECM (R2 = 0.46), GEI (R2 = 0.50), and acetate/propionate (A/P) ratio (R2 = 0.45). For beef cattle, CH4 emissions were positively correlated (p < 0.05–0.001) with DMI (R2 = 0.37) and GEI (R2 = 0.74). Additionally, the ADG (R2 = 0.19; p < 0.01) and A/P ratio (R2 = 0.15; p < 0.05) were significantly associated with CH4 emission in beef steers. This information may lead to cost-effective methods to reduce enteric CH4 production from cattle. We conclude that enteric CH4 emissions per unit of ECM, GEI, and ADG, as well as rumen fermentation profiles, show great potential for estimating enteric CH4 emissions.

Greenhouse gases inventory and carbon balance of two dairy systems obtained from two methane-estimation methods

Methane emissions along biomethane and biogas supply chains are underestimated

Assessing methane emission from dairy cows : modeling and experimental approaches on rumen microbial metabolism

The Netherlands aims to reduce greenhouse gas emissions by 49% in 2030 compared to 1990. In order to achieve this goal the dairy sector needs to reduce methane (CH4) emissions by 1.0 megaton CO2-equivalents compared to 2017. Approximately 80% of the CH4 emission of the dairy sector originates from enteric CH4. The objectives of this study were therefore: 1) To gain insight into the average enteric CH4 emission and variation of the Dutch dairy herd, 2) to investigate which factors have an influence on the variation, and 3) to compare the measured CH4 emission per farm to the estimated emission using model calculations. In total CH4 production was successfully measured from 791 dairy cows (996 records) of 18 farms throughout the Netherlands for a period of 2 weeks from September 2018 to October 2019 using Greenfeed (C-lock Inc.). The average CH4 production was 437±94 g CH4/cow/day and per kg fat-protein corrected milk 14.4±5.1 g CH4/kg FPCM. According to the Linear Mixed Model analysis fitted with Restricted Maximum Likelihood 49% of the total variation was explained by farm and animal factors: soil type (6%), grazing related to season (3%), lactation stage and parity (32%), the content of urea and lactose in the milk and the lactation value (together 8%). Feed composition and feed quality components did not show a significant effect on the observed variation. A comparison of the average herd emission of single farms revealed no correlations between the CH4 emission measured in this inventory and estimated using model calculations. Further research is required on the effects of fresh grass as well as fresh grass quality, rumen microbiome or genetics on CH4 emission.

Considerable evidence of climate change associated with emissions of greenhouse gases (GHG) has resulted in international efforts to reduce GHG emissions. The agriculture sector contributes about 8% of GHG emissions in Canada mostly through methane (CH4) and nitrous oxide (N2O). The objective of this paper was to compile an integrative review of CH4 and N2O emissions from livestock by taking a whole cycle approach from enteric fermentation to manure treatment and storage, and field application of manure. Basic microbial processes that result in CH4 production in the rumen and hindgut of animals were reviewed. An overview of CH4 and N2O production processes in manure, and controlling factors are presented. Most of the studies conducted in relation to enteric fermentation were in dairy and beef cattle. To date, research has focussed on GHG emissions from the stored manures of dairy, beef cattle and swine; therefore, we focus our review on these. Several methods used to measure GHG emissions from livestock and stored manure were reviewed. A comparison of methods showed that there were agreements between most of the techniques but some systematic differences were also observed. Additional studies with comprehensive comparisons of methodologies are needed in order to allow for comparison of results obtained from studies using contrasting methodologies. The need to standardize measurement methods and reporting to facilitate comparison of results and data integration was identified. Prediction equations are often used to calculate GHG emissions. Various types of mathematical approaches, such as statistical models, mechanistic models and estimates calculated from emission factors, and studies that compare various types of models are discussed herein. A lack of process-based models describing GHG emissions from manure during storage was identified. A brief description of mitigation strategies focussing on recent studies is given. Reduction in CH4 emissions from ruminants through the addition of fats in diets and the use of more starch was achieved and a transient beneficial effect of ionophores was reported. Grazing management and genetic selection also hold promise. Studies focussed on manure treatment options that thave been suggested to reduce gas fluxes from manure storage, composting, anaerobic digestion (AD), diet manipulation, covers and solid-liquid separation, were reviewed. While some of these options have been shown to decrease GHG emissions from stored manure, different studies have obtained conflicting results, and additional research is needed to identify the most promising options. GHG emissions from pasture and croplands after manure application have been the subject of several experimental and modelling studies, but few of these have linked field emissions to diet manipulation or manure treatments. Further work focussing on the entire cycle of GHG formation from feed formulation, animal metabolism, excreta treatment and storage, to field application of manure needs to be conducted. Key words: Greenhouse gases, enteric methane, nitrous oxide, manure management

The objectives of this study were to evaluate the relationship between residual feed intake (RFI; g/d) and enteric methane (CH) production (g/kg DM) and to compare CH and carbon dioxide (CO) emissions measured using respiration chambers (RC) and the GreenFeed emission monitoring (GEM) system (C-Lock Inc., Rapid City, SD). A total of 98 crossbred replacement heifers were group housed in 2 pens and fed barley silage ad libitum and their individual feed intakes were recorded by 16 automated feeding bunks (GrowSafe, Airdrie, AB, Canada) for a period of 72 d to determine their phenotypic RFI. Heifers were ranked on the basis of phenotypic RFI, and 16 heifers (8 with low RFI and 8 with high RFI) were randomly selected for enteric CH and CO emissions measurement. Enteric CH and CO emissions of individual animals were measured over two 25-d periods using RC (2 d/period) and GEM systems (all days when not in chambers). During gas measurements metabolic BW tended to be greater ( ≤ 0.09) for high-RFI heifers but ADG tended ( = 0.09) to be greater for low-RFI heifers. As expected, high-RFI heifers consumed 6.9% more feed ( = 0.03) compared to their more efficient counterparts (7.1 vs. 6.6 kg DM/d). Average CH emissions were 202 and 222 g/d ( = 0.02) with the GEM system and 156 and 164 g/d ( = 0.40) with RC for the low- and high-RFI heifers, respectively. When adjusted for feed intake, CH yield (g/kg DMI) was similar for high- and low-RFI heifers (GEM: 27.7 and 28.5, = 0.25; RC: 26.5 and 26.5, = 0.99). However, CH yield differed between the 2 measurement techniques only for the high-RFI group ( = 0.01). Estimates of CO yield (g/kg DMI) also differed between the 2 techniques ( ≤ 0.03). Our study found that high- and low-efficiency cattle produce similar CH yield but different daily CH emissions. The 2 measurement techniques differ in estimating CH and CO emissions, partially because of differences in conditions (lower feed intakes of cattle while in chambers, fewer days measured in chambers) during measurement. We conclude that when intake of animals is known, the GEM system offers a robust and accurate means of estimating CH emissions from animals under field conditions.

Simple SummaryIn this study, we evaluated methane emissions from dairy cows fed grass or corn silage diets supplemented with rapeseed oil. Enteric methane emissions decreased on adding rapeseed oil to the diet, but methane emissions from feces of dairy cows fed diets supplemented with rapeseed oil did not differ. Thus, no trade-offs were observed between enteric and fecal methane emissions due to forage type or addition of rapeseed oil to diets fed to Swedish dairy cows.This study evaluated potential trade-offs between enteric methane (CH4) emissions and CH4 emissions from feces of dairy cows fed grass silage or partial replacement of grass silage with corn silage, both with and without supplementation of rapeseed oil. Measured data for eight dairy cows (two blocks) included in a production trial were analyzed. Dietary treatments were grass silage (GS), GS supplemented with rapeseed oil (GS-RSO), GS plus corn silage (GSCS), and GSCS supplemented with rapeseed oil (GSCS-RSO). Feces samples were collected after each period and incubated for nine weeks to estimate fecal CH4 emissions. Including RSO (0.5 kg/d) in the diet decreased dry matter intake (DMI) by 1.75 kg/d. Enteric CH4 emissions were reduced by inclusion of RSO in the diet (on average 473 vs. 607 L/d). In 9-week incubations, there was a trend for lower CH4 emissions from feces of cows fed diets supplemented with RSO (on average 3.45 L/kg DM) than cows with diets not supplemented with RSO (3.84 L/kg DM). Total CH4 emissions (enteric + feces, L/d) were significantly lower for the cows fed diets supplemented with RSO. Total fecal CH4 emissions were similar between treatments, indicating no trade-offs between enteric and fecal CH4 emissions.

A study was conducted to determine whether enteric methane (CH4) emissions from growing feedlot cattle fed backgrounding diets based on barley silage could be reduced through grain supplementation. A second objective was to determine the effects of feed intake on CH4 emissions. Eight Angus beef heifers (initial and final body weight, 328 ± 28 and 430 ± 29 kg) were used. The experiment was designed as a split-plot crossover with two diets and two 8-week periods. The main plot was the diet [dry matter (DM) basis]: high forage (70% barley silage, 30% barley-based concentrate) or high grain (30% barley silage, 70% corn-based concentrate). The sub-plot was the feeding level: unrestricted (ad libitum feed intake, 5% orts) or restricted (65% of ad libitum intake) feed intake. Methane emissions were measured during each sub-plot over 3 d using whole animal chambers. Changing the forage to concentrate ratio and substituting barley for corn did not affect CH4 emissions (141.5 g d-1; P = 0.26), and the average emission was about 10% higher than the emission calculated using the International Panel on Climate Change (IPCC) Tier 1 approach. Methane conversion rate was also similar for both diets [6.23% of gross energy intake (GEI), P = 0.29], and was similar to the value of 6.0 used in the IPCC Tier 2 approach to calculating CH4 emissions from cattle. Restricting intake reduced CH4 emissions (169 vs. 114 g d-1; P &lt; 0.002), with the reduction in CH4 proportional to the decline in intake. Level of intake relative to maintenance energy requirements was moderately inversely related (r = -0.30; P = 0.04) to CH4 (% GEI). The proportion of GEI lost as CH4 declined by 0.77 percentage units per unit increase in level of intake above maintenance. This study shows that supplementing barley-silage-based diets with corn grain to increase diet quality has only small effects on reducing CH4 emissions. In contrast, maximizing feed intake above maintenance energy requirements increases daily CH4 emissions, but improves efficiency of CH4 conversion because CH4, as a percentage of GEI, declined. Thus, feeding cattle for maximum gain is an important CH4 mitigation strategy for the cattle industry as it reduces the proportion of feed energy lost as CH4 each day, as well as, reduces the number of days to market and associated CH4 production. Key words: Cattle, methane, greenhouse gasses

The objective of this study was to estimate enteric methane (CH4) emissions of the Canadian cattle population using the International Panel on Climate Change (IPCC) Tier-2 methodology. Estimates were then compared with IPCC Tier-1 methodology and data from Canadian research studies (CRS). Animal inventory data for the Canadian beef and dairy cattle herd was obtained from Statistics Canada. Information on cattle performance and feeding practices were obtained from provincial cattle specialists via a survey, as well as various published reports. Methane emissions from dairy and beef cattle in Canada for 2001 were 173 030 t yr-1 or 3.6 Mt CO2 eq. and 763 852 t yr-1 or 16.0 Mt CO2 eq., respectively, using Tier-2 methodology. Emissions for dairy cattle ranged from 708 t yr-1 in Newfoundland to 62 184 t yr-1 in Ontario. Emissions for beef cattle ranged from 191 t yr-1 in Newfoundland to 356 345 t yr-1 in Alberta. The national emission factors (kg CH4 yr-1) using IPCC Tier-2 were 73, 126, 90, 94, 40, 75, 63 and 56 for dairy heifers, dairy cows, beef cows, bulls, calves &lt; 1yr, beef heifer replacements, heifers &gt; 1 yr, and steers &gt; 1yr, respectively. Emission factors (kg CH4 yr-1) for the above classes of cattle using IPCC Tier-1 were 56, 118, 72, 75, 47, 56, 47 and 47, respectively. The values were 15.1% higher to 25.3% lower than those obtained using IPCC Tier-2 methodology. When IPCC Tier-2 emission factors were compared with CRS, they were 12.3% lower to 32.6% higher than those obtained using the Tier-2 methodology. In conclusion, national estimates of enteric emissions from the Canadian cattle industry using Tier-1 and Tier-2 methodologies, as well as CRS, differ depending on the methodology used. Tier-2 methodology does allow for the inclusion of information other than population data, including feeding strategies, as well as duration of time in a given production environment. Additional research is required to establish the extent to which feed energy is converted to methane for those production scenarios for which there is no published data. Key words: IPCC Tier-2, IPCC Tier-1, enteric fermentation, cattle, methane, emission factor, methane conversion rate

Enteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to: 1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in combination with rumen propionate molar proportion (for research of more refined purposes) substantially improved prediction performance (RSR = 0.57) on a smaller dataset. On the contrary, for young sheep (<1-year-old), the universal models could be applied, instead of age-specific models, if DMI and BW were included. Universal models showed similar prediction performances to the diet- and region-specific models. However, optimal prediction equations led to different regression coefficients (i.e. intercepts and slopes) for universal, age-specific, diet-specific, and region-specific models with predictive implications. Equations for CH4 yield led to low prediction performances, with DMI being negatively and BW and OMD positively correlated with CH4 yield. In conclusion, predicting sheep CH4 production requires information on DMI and prediction accuracy will improve national and global inventories if separate equations for young and adult sheep are used with the additional variables BW, OMD and rumen propionate proportion. Appropriate universal equations can be used to predict CH4 production from sheep across different diets and climatic conditions.

Simple SummaryEnteric methane (CH4) emissions are a global concern and have been associated with climate change. Thus, sustainable, easily applicable CH4 mitigation strategies should be in place without having an adverse effect on animal productivity. We (i) developed a series of dairy cattle enteric CH4 production (g/d) and yield (g/kg of dry matter intake, DMI) models using combined (lactating and non-lactating cows) and lactating data, (ii) investigated the effects of monensin on enteric CH4 emissions in dairy cattle, and (iii) evaluated the proposed and published models. Monensin reduced daily CH4 production and CH4 yield by 5.4% and 4.0%, respectively. Further, long-term in vivo studies on monensin feeding of ≤24 mg/kg DM with CH4 measurements taken to account for bacterial adaptation in the rumen are needed. Overall, DMI is the significant driver of CH4 emissions in dairy cattle and a model that included DMI, dietary forage proportion, and the quadratic term of dietary forage proportion was the best model for both combined (lactating and non-lactating) and lactating cows. The methane yield was best predicted with dietary forage only for combined data, while a combination of dietary forage proportion, milk fat, and milk protein yields was the best model for lactating cows. This indicates that the inclusion of dietary composition along with DMI can provide a better CH4 production prediction in dairy cattle. The selected developed models outperformed the published models.Greenhouse gas emissions, such as enteric methane (CH4) from ruminant livestock, have been linked to global warming. Thus, easily applicable CH4 management strategies, including the inclusion of dietary additives, should be in place. The objectives of the current study were to: (i) compile a database of animal records that supplemented monensin and investigate the effect of monensin on CH4 emissions; (ii) identify the principal dietary, animal, and lactation performance input variables that predict enteric CH4 production (g/d) and yield (g/kg of dry matter intake DMI); (iii) develop empirical models that predict CH4 production and yield in dairy cattle; and (iv) evaluate the newly developed models and published models in the literature. A significant reduction in CH4 production and yield of 5.4% and 4.0%, respectively, was found with a monensin supplementation of ≤24 mg/kg DM. However, no robust models were developed from the monensin database because of inadequate observations under the current paper’s inclusion/exclusion criteria. Thus, further long-term in vivo studies of monensin supplementation at ≤24 mg/kg DMI in dairy cattle on CH4 emissions specifically beyond 21 days of feeding are reported to ensure the monensin effects on the enteric CH4 are needed. In order to explore CH4 predictions independent of monensin, additional studies were added to the database. Subsequently, dairy cattle CH4 production prediction models were developed using a database generated from 18 in vivo studies, which included 61 treatment means from the combined data of lactating and non-lactating cows (COM) with a subset of 48 treatment means for lactating cows (LAC database). A leave-one-out cross-validation of the derived models showed that a DMI-only predictor model had a similar root mean square prediction error as a percentage of the mean observed value (RMSPE, %) on the COM and LAC database of 14.7 and 14.1%, respectively, and it was the key predictor of CH4 production. All databases observed an improvement in prediction abilities in CH4 production with DMI in the models along with dietary forage proportion inclusion and the quadratic term of dietary forage proportion. For the COM database, the CH4 yield was best predicted by the dietary forage proportion only, while the LAC database was for dietary forage proportion, milk fat, and protein yields. The best newly developed models showed improved predictions of CH4 emission compared to other published equations. Our results indicate that the inclusion of dietary composition along with DMI can provide an improved CH4 production prediction in dairy cattle.

Rising global temperatures have intensified the urgency to reduce greenhouse gas (GHG) emissions from anthropogenic sources, including agricultural methane (CH4). CH4 is a potent GHG produced as a byproduct of ruminal fermentation in cattle. CH4 warms the atmosphere 28 times more than carbon dioxide (CO₂) over a 100-year period, making it a critical GHG mitigation target. Multiple approaches are being developed, but the beef cattle industry lacks solutions that effectively reach ~80% of bovine CH4 emissions produced in extensive, pasture-based systems, e.g., the cow-calf and stocker segments. One promising approach is a methane-reducing vaccine. Methane-reducing vaccines stimulate the production of anti-methanogen antibodies. These antibodies potentially enter the rumen, bind to their methanogen targets, and inhibit ruminal methanogenesis, thereby reducing enteric CH4 emissions. The objective of this trial was to assess the effect of a proto-type vaccine on growth performances, gas flux, and feeding behavior in beef cattle. Thirty Angus crossbred steers (n = 30; 451 ± 11 kg) were blocked by body weight (BW) and stratified by breed before being randomly assigned to one of two treatments: control (n = 20) or vaccine-treated (n = 10). Animals received a prime-boost vaccine regimen (2 mL, each) administered subcutaneously on days 0 and 21. Animals were housed in three pens, each equipped with three electronic feed bunks (Vytelle, Lenexa, KS) for recording individual feed intake and feeding behavior, as well as one GreenFeed emission monitoring system (C-lock Inc., Rapid City, SD) for measuring CH4 emissions. Weekly BW, daily feed intake, and gas emissions were measured over an 84-day period. Statistical analyses were conducted in JMP Pro v.16 (SAS Institute Inc., Cary, NC), with individual animals as the experimental unit, and treatment as a fixed effect. There were no significant differences in average daily gain (ADG), initial BW, mid-test metabolic BW (BW⁰·⁷⁵), DMI, alfalfa pellet intake or gain: feed (P &amp;gt; 0.05). The vaccine-treated group had 15% lower (P = 0.0050) CH4 production (g/d), 18% lower (P = 0.0038), CH4 intensity (g/kg BW 0.75) and 13% lower (P = 0.0149) CH4 yield emissions (g/kg DMI) compared to the control. However, CO2 production (g/d), CO2 yield (g/kg DMI) and H2 production (g/d) did not differ (P &amp;gt; 0.05). Bunk visit (BV) duration was also similar between groups (P &amp;gt; 0.05). However, the vaccine-treated group had fewer BV per day (P = 0.0292) and a longer BV head-down duration per day (P = 0.0105), with a tendency for a slower eating rate (P = 0.0697) compared to control. These results highlight the potential of vaccination as a strategy to mitigate enteric CH4 production in beef cattle without negatively impacting growth performance.

The methodology 1 provided by the Intergovernmental Panel on Climate Change (IPCC) guidelines is widely used for estimating CH4 and N2O production by cattle, but the reference value is only distinguished between developed and developing countries, with large uncertainties. The objective of this study was to calculate the CH4 and N2O emissions factor by dairy and beef cattle, and the emissions in the Hubei province according to the recommendations of IPCC (2006) using regional farm management data. CH4 emission factors from enteric fermentation in Hubei province was 81.560 kg CH4/head/year for dairy cattle with CH4 emissions of 930.844 kg. CH4 and N2O emission factors from manure management were 0.408 kg/head/year and 1.307 kg/head/year for dairy cattle. The greenhouse gas emissions from breeding cows in Hubei Province in 2012 was 950.418 kg. In general, CH4 emission estimates using Tier 2 (IPCC, 2006) were slightly lower than those from Tier 1, mainly due to use of lower emission factors, especially for CH4 emitted from manure management The main CH4 emission source was enteric fermentation, being 99.512% of livestock CH4 emissions. Direct emission was the largest component of total N2O emission (56.695%).

Simple SummaryThe objective of this study was to investigate variability in enteric methane (CH4) emission rate and emissions per unit of milk among dairy cows on commercial farms in the UK. A large dataset of enteric CH4 measurements from individual cows was obtained from 18 farms across the UK. We conclude that changes in CH4 emissions appear to occur across and within lactations, but ranking of a herd remains consistent, which is useful for obtaining CH4 spot measurements.The aim of this study was to investigate variability in enteric CH4 emission rate and emissions per unit of milk across lactations among dairy cows on commercial farms in the UK. A total of 105,701 CH4 spot measurements were obtained from 2206 mostly Holstein-Friesian cows on 18 dairy farms using robotic milking stations. Eleven farms fed a partial mixed ration (PMR) and 7 farms fed a PMR with grazing. Methane concentrations (ppm) were measured using an infrared CH4 analyser at 1s intervals in breath samples taken during milking. Signal processing was used to detect CH4 eructation peaks, with maximum peak amplitude being used to derive CH4 emission rate (g/min) during each milking. A multiple-experiment meta-analysis model was used to assess effects of farm, week of lactation, parity, diet, and dry matter intake (DMI) on average CH4 emissions (expressed in g/min and g/kg milk) per individual cow. Estimated mean enteric CH4 emissions across the 18 farms was 0.38 (s.e. 0.01) g/min, ranging from 0.2 to 0.6 g/min, and 25.6 (s.e. 0.5) g/kg milk, ranging from 15 to 42 g/kg milk. Estimated dry matter intake was positively correlated with emission rate, which was higher in grazing cows, and negatively correlated with emissions per kg milk and was most significant in PMR-fed cows. Mean CH4 emission rate increased over the first 9 weeks of lactation and then was steady until week 70. Older cows were associated with lower emissions per minute and per kg milk. Rank correlation for CH4 emissions among weeks of lactation was generally high. We conclude that CH4 emissions appear to change across and within lactations, but ranking of a herd remains consistent, which is useful for obtaining CH4 spot measurements.