Enteric methane (CH 4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH 4 is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH 4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH 4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH 4 production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH 4 prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH 4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH 4 emission conversion factors for specific regions are required to improve CH 4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH 4 yield and intensity prediction, information on milk yield and composition is required for better estimation.

Holstein cows housed in a modified tie-stall barn were used to determine the effect of feeding diets with different forage-to-concentrate ratios (F:C) on performance and emission of CH(4), CO(2) and manure NH(3)-N. Eight multiparous cows (means ± standard deviation): 620 ± 68 kg of body weight; 52 ± 34 d in milk and 8 primiparous cows (546 ± 38 kg of body weight; 93 ± 39 d in milk) were randomly assigned to 1 of 4 air-flow controlled chambers, constructed to fit 4 cows each. Chambers were assigned to dietary treatment sequences in a single 4 × 4 Latin square design. Dietary treatments, fed as 16.2% crude protein total mixed rations included the following F:C ratio: 47:53, 54:46, 61:39, and 68:32 [diet dry matter (DM) basis]. Forage consisted of alfalfa silage and corn silage in a 1:1 ratio. Cow performance and emission data were measured on the last 7 d and the last 4 d, respectively of each 21-d period. Air samples entering and exiting each chamber were analyzed with a photo-acoustic field gas monitor. In a companion study, fermentation pattern was studied in 8 rumen-cannulated cows. Increasing F:C ratio in the diet had no effect on DM intake (21.1 ± 1.5 kg/d), energy-corrected milk (ECM, 37.4 ± 2.2 kg/d), ECM/DM intake (1.81 ± 0.18), yield of milk fat, and manure excretion and composition; however, it increased milk fat content linearly by 7% and decreased linearly true protein, lactose, and solids-not-fat content (by 4, 1, and 2%, respectively) and yield (by 10, 6, and 6%, respectively), and milk N-to-N intake ratio. On average 93% of the N consumed by the cows in the chambers was accounted for as milk N, manure N, or emitted NH(3)-N. Increasing the F:C ratio also increased ruminal pH linearly and affected concentrations of butyrate and isovalerate quadratically. Increasing the F:C ratio from 47:53 to 68:32 increased CH(4) emission from 538 to 648 g/cow per day, but had no effect on manure NH(3)-N emission (14.1 ± 3.9 g/cow per day) and CO(2) emission (18,325 ± 2,241 g/cow per day). In this trial, CH(4) emission remained constant per unit of neutral detergent fiber intake (1g of CH(4) was emitted for every 10.3g of neutral detergent fiber consumed by the cow), but increased from 14.4 to 18.0 g/kg of ECM when the percentage of forage in the diet increased from 47 to 68%. Although the pattern of emission within a day was distinct for each gas, emissions were higher between morning feeding (0930 h) and afternoon milking (1600 h) than later in the day. Altering the level of forage within a practical range and rebalancing dietary crude protein with common feeds of the Midwest of the United States had no effects on manure NH(3)-N emission but altered CH(4) emission.

Abstract. We use 7 years (2010–2016) of methane column observations from the Greenhouse Gases Observing Satellite (GOSAT) to examine trends in atmospheric methane concentrations over North America and infer trends in emissions. Local methane enhancements above background are diagnosed in the GOSAT data on a 0.5∘×0.5∘ grid by estimating the local background as the low (10th–25th) percentiles of the deseasonalized frequency distributions of the data for individual years. Trends in methane enhancements on the 0.5∘×0.5∘ grid are then aggregated nationally and for individual source sectors, using information from state-of-science bottom-up inventories. We find that US methane emissions increased by 2.5±1.4  % a−1 (mean ± 1 standard deviation) over the 7-year period, with contributions from both oil–gas systems (possibly unconventional oil–gas production) and from livestock in the Midwest (possibly swine manure management). Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent. The US emission trends inferred from the GOSAT data account for about 20 % of the observed increase in global methane over the 2010–2016 period.

Reported estimates of CH 4 emissions from ruminants and manure management are up to 2 times higher in atmospheric top-down calculations than in bottom-up (BU) inventories. We explored this discrepancy by estimating CH 4 emissions of 2 dairy facilities in California with US Environmental Protection Agency (US EPA) methodology, which is used for BU inventories, and 3 independent measurement techniques:(1) open-path measurements with inverse dispersion modeling (hereafter open-path), (2) vehicle measurements with tracer flux ratio method, and (3) aircraft measurements with the closed-path method. All 3 techniques were used to estimate whole-facility CH 4 emissions during 3 to 6 d per farm in the summer of 2016. In addition, open-path was used to estimate whole-facility CH 4 emissions over 13 to 14 d per farm in the winter of 2017. Our objectives were to (1) compare whole-facility CH 4 measurements utilizing the different measurement techniques, (2) compare whole-facility CH 4 measurements to US EPA inventory methodology estimates, and (3) compare CH 4 emissions between 2 dairies. Whole-facility CH 4 estimates were similar among measurement techniques. No seasonality was detected for CH 4 emissions from animal housing, but CH 4 emissions from liquid manure storage were 3 to 6 times greater during the summer than during the winter measurement periods. The findings confirm previous studies showing that whole-facility CH 4 emissions need to be measured throughout the year to estimate and evaluate annual inventories. Open-path measurements for liquid manure storage emissions were similar to monthly US EPA estimates during the summer, but not during the winter measurement periods. However, the numerical difference was relatively small considering yearly emission estimates. Manure CH 4 emissions contributed 69 to 79% and 26 to 47% of whole-facility CH 4 emissions during the summer and winter measurement periods, respectively. Methane yields from animal housing were similar between farms (on average 20.9 g of CH 4 /kg of dry matter intake), but CH 4 emissions normalized by volatile solids (VS) loading from liquid manure storage (g of CH 4 per day/kg of VS produced by all cattle per day) at 1 dairy were 1.7 and 3.5 times greater than at the other during the summer (234 vs. 137 g of CH 4 /kg of VS) and winter measurement periods (78 vs. 22 g of CH 4 /kg of VS), respectively. We attributed much of this difference to the proportion of manure stored in liquid (anaerobic) form, and suggest that manure management practices that reduce the amount of manure solids stored in liquid form could significantly reduce dairy CH 4 emissions.

Two trials were conducted simultaneously to study the effects of varying alfalfa silage (AS) to corn silage (CS) ratio in diets formulated to avoid excess protein or starch on lactating dairy cow performance, digestibility, ruminal parameters, N balance, manure production and composition, and gaseous emissions [carbon dioxide (CO2), methane (CH4), and ammonia-N (NH3-N)]. In trial 1 all measurements, except gas emissions, were conducted on 8 rumen-cannulated cows in replicated 4×4 Latin squares. In trial 2, performance and emissions were measured on 16 cows randomly assigned to 1 of 4 air-flow controlled chambers in a 4×4 Latin square. Dietary treatments were fed as total mixed rations with forage-to-concentrate ratio of 55:45 [dietary dry matter (DM) basis] and AS:CS ratios of 20:80, 40:60, 60:40, and 80:20 (forage DM basis). Measurements were conducted the last 3d of each 21-d period. Treatments did not affect DM intake, DM digestibility, and milk/DM intake. However, responses were quadratic for fat-and-protein-corrected milk, fat, and protein production, which reached predicted maxima for AS:CS ratio of 50:50, 49:51, and 34:66, respectively. Nitrogen use efficiency (milk N/N intake) decreased from 31 to 24g/100g as AS:CS ratio increased from 20:80 to 80:20. Treatments did not alter NH3-N/milk-N but tended to have a quadratic effect on daily NH3-N emission. Treatments had a quadratic effect on daily CH4 emission, which was high compared with current literature; they influenced CH4 emission per unit of neutral detergent fiber (NDF) intake and tended to influence CO2/NDF intake. Ruminal acetate-to-propionate ratio and total-tract NDF digestibility increased linearly with increasing AS:CS ratio. In addition, as AS:CS ratio increased from 20:80 to 80:20, NDF digested increased linearly from 2.16 to 3.24kg/d, but CH4/digested NDF decreased linearly from 270 to 190g/kg. These 2 counterbalancing effects likely contributed to the observed quadratic response in daily CH4 emission, which may have been influenced also by increasing starch with increasing CS in the diet as reflected by the increased ruminal propionate molar proportion. Overall, production performances were greatest for the intermediate AS:CS ratios (40:60 and 60:40), but daily excretion of urine, manure, fecal N, urinary urea N, and urinary N decreased with increasing proportion of CS in the diet, whereas daily CH4 emission was reduced for the 2 extreme AS:CS ratios (20:80 and 80:20). However, the proportion of AS and CS in the diet did not affect CH4/fat-and-protein corrected milk.

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The objective was to study repeatability and sources of variation in feed conversion efficiency [FCE, milk kg/kg dry matter intake (DMI)] of lactating cows in mid to late lactation. Trials 1 and 2 used 16 cows (106 to 368 d in milk) grouped in 8 pairs of 1 high- and 1 low-FCE cow less than 16 d in milk apart. Trial 1 determined the repeatability of FCE during a 12-wk period. Trial 2 quantified the digestive and metabolic partitioning of energy and N with a 3-d total fecal and urine collection and measurement of CH4 and CO2 emission. Trial 3 studied selected ruminal methanogens in 2 pairs of cows fitted with rumen cannulas. Cows received a single diet including 28% corn silage, 27% alfalfa silage, 17% crude protein, and 28% neutral detergent fiber (dry matter basis). In trial 1, mean FCE remained repeatedly different and averaged 1.83 and 1.03 for high- and low-FCE cows, respectively. In trial 2, high-FCE cows consumed 21% more DMI, produced 98% more fat- and protein-corrected milk, excreted 42% less manure per kilogram of fat- and protein-corrected milk, but emitted the same daily amount of CH4 and CO2 compared with low-FCE cows. Percentage of gross energy intake lost in feces was higher (28.6 vs. 25.9%), but urinary (2.76 vs. 3.40%) and CH4 (5.23 vs. 6.99%) losses were lower in high- than low-FCE cows. Furthermore, high-FCE cows partitioned 15% more of gross energy intake toward net energy for maintenance, body gain, and lactation (37.5 vs. 32.6%) than low-FCE cows. Lower metabolic efficiency and greater heat loss in low-FCE cows might have been associated in part with greater energy demand for immune function related to subclinical mastitis, as somatic cell count was 3.8 fold greater in low- than high-FCE cows. As a percentage of N intake, high-FCE cows tended to have greater fecal N (32.4 vs. 30.3%) and had lower urinary N (32.2 vs. 41.7%) and greater milk N (30.3 vs. 19.1%) than low-FCE cows. In trial 3, Methanobrevibacter spp. strain AbM4 was less prevalent in ruminal content of high-FCE cows, which emitted less CH4 per unit of DMI and per unit of neutral detergent fiber digested than low-FCE cows. Thus lower digestive efficiency was more than compensated by greater metabolic efficiencies in high- compared with low-FCE cows. There was not a single factor, but rather a series of mechanisms involved in the observed differences in efficiency of energy utilization of the lactating cows in this study.

Significance Agricultural methane emissions must be decreased by 11 to 30% of the 2010 level by 2030 and by 24 to 47% by 2050 to meet the 1.5 °C target. We identified three strategies to decrease product-based methane emissions while increasing animal productivity and five strategies to decrease absolute methane emissions without reducing animal productivity. Globally, 100% adoption of the most effective product-based and absolute methane emission mitigation strategy can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in methane. On a regional level, Europe but not Africa may be able to meet their contribution to the 1.5 °C target, highlighting the different challenges faced by high- and middle- and low-income countries.