Estimation of methane emission using the CO2 method from dairy cows fed concentrate with different carbohydrate compositions in automatic milking system

Effects of cashew nutshell liquid on milk production and methane emission of dairy cows in a farm condition

This study aimed to clarify the efficacy of cashew nutshell liquid (CNSL) in methane emissions, milk production, and rumen fermentation of lactating cows in practical conditions. Ten Holstein lactating cows were used in a free-stall barn with a milking robot. Two treatments were arranged as control (no CNSL additive, n = 5) or CNSL addition (10 g/day of CNSL, n = 5) for 21 days after the 7-day preliminary period. A sniffer method was applied to predict daily methane production and methane conversion factor (MCF). In vitro, rumen gas production was also tested using the rumen fluid of individual cows. Daily dry matter intake (DMI), eating time, milk production, and methane production were not affected by the CNSL addition. However, methane production per DMI and MCF were lower (p ≤ 0.01) for the CNSL cows than those for the control cows. Ruminal total volatile fatty acid (VFA) concentration and acetate proportion tended to be lower (p < 0.15) for CNSL cows. A tendency to decrease (p < 0.10) in methane was also observed in the in vitro incubation with the rumen fluid obtained from the CNSL cows compared with those from the control cows. These results suggest that adding CNSL to diets could reduce the methane yield of cows in practical conditions.

Variation among individual beef cattle in methane-to-carbon dioxide ratio measured under on-farm conditions using the sniffer method

This study proposed a method for measuring the methane (CH4 )/carbon dioxide (CO2 ) ratio from individual beef cattle under on-farm conditions and estimated the variance components of the CH4 /CO2 ratio. Gas measurements were conducted using 166 Japanese Black cattle group-housed in pens equipped with individual feed bins. The gas containing the animal's breath was measured individually after concentrate feeding by covering the feed bin with a sheet with sampling inlets. Measurements were performed six times (three consecutive days, twice daily) per individual. Most of the sampled gas contained more than 1000 ppm of the mean background-corrected CO2 , suggesting that the method proposed in this study successfully collected sufficient breath concentration to accurately measure the CH4 /CO2 ratio. The between-animal variance accounted for 31.7% of the total variance in the CH4 /CO2 ratio. The results showed that the gas collection method proposed in this study could be a useful tool for measuring the CH4 /CO2 ratio under on-farm conditions. The variance component obtained from this study will help to establish protocols for generating data for genetic evaluation and performing dietary experiments with sufficient statistical power.

Characterising the ground level concentrations of harmful organic and inorganic substances released during major industrial fires, and implications for human health

We report on the concentration ranges and combustion source-related emission profiles of organic and inorganic species released during 34 major industrial fires in the UK. These episodic events tend to be acute in nature and demand a rapid public health risk assessment to indicate the likely impact on exposed populations. The objective of this paper is to improve our understanding of the nature, composition and potential health impacts of emissions from major incident fires and so support the risk assessment process. Real world monitoring data was obtained from portable Fourier Transform Infrared (FTIR) monitoring (Gasmet DX-4030/40) carried out as part of the UK's Air Quality in Major Incidents service. The measured substances include carbon monoxide, sulphur dioxide, nitrogen dioxide, ammonia, hydrogen chloride, hydrogen bromide, hydrogen fluoride, hydrogen cyanide, formaldehyde, 1,3-butadiene, benzene, toluene, xylenes, ethyl benzene, acrolein, phosgene, arsine, phosphine and methyl isocyanate. We evaluate the reported concentrations against Acute Exposure Guideline Values (AEGLs) and Emergency Response Planning Guidelines (ERPGs), as well as against UK, EU and WHO short-term ambient guideline values. Most exceedances of AEGL or ERPG guideline values were at levels likely only to cause discomfort to exposed populations (hydrogen cyanide, hydrogen chloride, hydrogen fluoride and formaldehyde), though for several substances the exceedances could have potentially given rise to more serious health effects (acrolein, phosphine, phosgene and methyl isocyanate). In the latter cases, the observed high concentrations are likely to be due to cross-interference from other substances that absorb in the mid-range of the infrared spectrum, particularly when the ground level plume is very concentrated.

The influence of breath concentration in the gas sample on the accuracy of methane to carbon dioxide ratio using the sniffer method in dairy cows

The purpose of this study was to investigate the carbon dioxide (CO₂ ) concentration in the sampled gas to avoid low concentration of breath while measuring the methane (CH₄ )/CO₂ ratio using the sniffer method. This study also assessed the effect of selective elimination by applying the threshold of CO₂ concentration to the CH₄ /CO₂ ratio. The gas measurement in the automatic milking system was conducted with 26 multiparous Holstein cows using an electric fan to manipulate the CO₂ concentration in the sampled gas. Four different thresholds of the background-corrected CO₂ concentrations (0, 0.025, 0.05, and 0.1%) were applied to every 1-s value of the individual gas measurement. Subsequently, three different upper limits of the proportion of eliminated values (none, 0.5, and 0.33) were applied to the individual records per milking. The results showed that the sampled gas must contain more than 0.1% of the corrected CO₂ concentration to enable accurate calculation of the CH₄ /CO₂ ratio. It is recommended that at least half of the values in the data be larger than the threshold of the corrected CO₂ concentration for unbiased measurement of the CH₄ /CO₂ ratio.

Development of an equation to estimate the enteric methane emissions from Holstein dairy cows in Canada

The aim of this study was to use dietary factors, including the type of fats, and animal characteristics, to predict enteric methane (CH4) emissions from dairy cows under Canadian conditions. For this purpose, 193 individual observations from six different trials assessing the impact of dietary modification on enteric CH4 production were analyzed. Animal [milk yield (MY), milk fat content, milk protein content, days in milk, body weight (BW), and dry matter intake (DMI)] and dietary variables [organic matter, crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), starch, ether extract (EE), rumen-inert fat, and unprotected fat (EE – rumen-inert fat)] were tested. A 5-fold cross validation was used to obtain the following equation: CH4 (g d−1) = −1260.4 + 1.9 × MY (kg d−1) + 62.8 × milk fat (%) –18.4 × milk protein (%) + 11.0 × DMI (kg d−1) + 0.3 × BW (kg) + 58.3 × NDF (% of DM) − 0.8 × NDF2 (% of DM) + 1.9 × starch (% of DM) − 2.5 × EE – rumen-inert fat (% of DM). The mean estimate from the proposed equation (474 g CH4 cow−1 d−1; r = 0.83, RMSE = 40.0) was close to the observed mean emission (476 g CH4 cow−1 d−1). The proposed model has a higher precision to predict CH4 emission from cows fed typical Canadian diets than other models, and it can be used to evaluate CH4 mitigation strategies.

Estimating Herd-Scale Methane Emissions from Cattle in a Feedlot Using Eddy Covariance Measurements and the Carbon Dioxide Tracer Method

Measurements of methane (CH) emissions from ruminants could provide invaluable data to reduce uncertainties in the global CH budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The main objective of this study was to evaluate a new CO tracer (COT) approach that combined CH and CO atmospheric concentrations with eddy covariance (EC) CO flux measurements to estimate CH emissions from cattle in a feedlot. A closed-path EC system was used to measure CH and CO fluxes from a feedlot in Kansas. The EC flux measurements were scaled from landscape to animal scale using footprint analyses. Emissions of CH from the cattle were also estimated using the COT approach and measured CO and CH concentration, and scaled EC CO fluxes. The CH and CO concentration ratios showed a distinct diel trend with greater values during the daytime. Average monthly CH emission estimates using the COT approach ranged from 72 to 127 g animal d, which was consistent with the values reported in other studies that had similar animal characteristics. The COT method CH emission estimates showed good agreement with scaled CH EC fluxes (slope = 0.9 and = 0.8) for cold and dry months. However, the agreement between the two techniques was significantly reduced (slope = 1.5 and = 0.6) during wet and warm months. On average, the COT method CH emission estimates were 3% greater than the EC CH emissions. Overall, our results suggest that the COT method can be used to estimate enteric feedlot CH emissions.

Comparative methane estimation from cattle based on total CO2 production using different techniques

The objective of this study was to compare the precision of CH₄ estimates using calculated CO_{2 (HP)} by the CO₂ method (CO₂T) and measured CO₂ in the respiration chamber (CO₂R). The CO₂R and CO₂T study was conducted as a 3 × 3 Latin square design where 3 Dexter heifers were allocated to metabolic cages for 3 periods. Each period consisted of 2 weeks of adaptation followed by 1 week of measurement with the CO₂R and CO₂T. The average body weight of the heifer was 226 ± 11 kg (means ± SD). They were fed a total mixed ration, twice daily, with 1 of 3 supplements: wheat (W), molasses (M), or molasses mixed with sodium bicarbonate (Mbic). The dry mater intake (DMI; kg/day) was significantly greater (P < 0.001) in the metabolic cage compared with that in the respiration chamber. The daily CH₄ (L/day) emission was strongly correlated (r = 0.78) between CO₂T and CO₂R. The daily CH₄ (L/kg DMI) emission by the CO₂T was in the same magnitude as by the CO₂R. The measured CO₂ (L/day) production in the respiration chamber was not different (P = 0.39) from the calculated CO₂ production using the CO₂T. This result concludes a reasonable accuracy and precision of CH₄ estimation by the CO₂T compared with the CO₂R.

Enteric methane emissions from low- and high-residual feed intake beef heifers measured using GreenFeed and respiration chamber techniques

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.

Models for predicting enteric methane emissions from dairy cows in North America, Europe, and Australia and New Zealand

There are several models in the literature for predicting enteric methane (CH4 ) emissions. These models were often developed on region or country-specific data and may not be able to predict the emissions successfully in every region. The majority of extant models require dry matter intake (DMI) of individual animals, which is not routinely measured. The objectives of this study were to (i) evaluate performance of extant models in predicting enteric CH4 emissions from dairy cows in North America (NA), Europe (EU), and Australia and New Zealand (AUNZ) and (ii) explore the performance using estimated DMI. Forty extant models were challenged on 55, 105, and 52 enteric CH4 measurements (g per lactating cow per day) from NA, EU, and AUNZ, respectively. The models were ranked using root mean square prediction error as a percentage of the average observed value (RMSPE) and concordance correlation coefficient (CCC). A modified model of Nielsen et al. (Acta Agriculturae Scand Section A, 63, 2013 and 126) using DMI, and dietary digestible neutral detergent fiber and fatty acid contents as predictor variables, were ranked highest in NA (RMSPE = 13.1% and CCC = 0.78). The gross energy intake-based model of Yan et al. (Livestock Production Science, 64, 2000 and 253) and the updated IPCC Tier 2 model were ranked highest in EU (RMSPE = 11.0% and CCC = 0.66) and AUNZ (RMSPE = 15.6% and CCC = 0.75), respectively. DMI of cows in NA and EU was estimated satisfactorily with body weight and fat-corrected milk yield data (RMSPE < 12.0% and CCC > 0.60). Using estimated DMI, the Nielsen et al. (2013) (RMSPE = 12.7 and CCC = 0.79) and Yan et al. (2000) (RMSPE = 13.7 and CCC = 0.50) models still predicted emissions in respective regions well. Enteric CH4 emissions from dairy cows can be predicted successfully (i.e., RMSPE < 15%), if DMI can be estimated with reasonable accuracy (i.e., RMSPE < 10%).

Methane and nitrous oxide emissions from Canadian dairy farms and mitigation options: An updated review

This review examined methane (CH4) and nitrous oxide (N2O) mitigation strategies for Canadian dairy farms. The primary focus was research conducted in Canada and cold climatic regions with similar dairy systems. Meta-analyses were conducted to assess the impact of a given strategy when sufficient data were available. Results indicated that options to reduce enteric CH4from dairy cows were increasing the dietary starch content and dietary lipid supplementation. Replacing barley or alfalfa silage with corn silage with higher starch content decreased enteric CH4per unit of milk by 6%. Increasing dietary lipids from 3% to 6% of dry matter (DM) reduced enteric CH4yield by 9%. Strategies such as nitrate supplementation and 3-nitrooxypropanol additive indicated potential for reducing enteric CH4by about 30% but require extensive research on toxicology and consumer acceptance. Strategies to reduce emissions from manure are anaerobic digestion, composting, solid–liquid separation, covering slurry storage and flaring CH4, and reducing methanogen inoculum by complete emptying of slurry storage at spring application. These strategies have potential to reduce emissions from manure by up to 50%. An integrated approach of combining strategies through diet and manure management is necessary for significant GHG mitigation and lowering carbon footprint of milk produced in Canada.

Effects of concentrate crude protein content on nutrient digestibility, energy utilization, and methane emissions in lactating dairy cows fed fresh-cut perennial grass

Although many studies have investigated mitigation strategies for methane (CH₄) output from dairy cows fed a wide variety of diets, research on the effects of concentrate crude protein (CP) content on CH₄ emissions from dairy cows offered fresh grass is limited. The present study was designed to evaluate the effects of cow genotype and concentrate CP level on nutrient digestibility, energy utilization, and CH₄ emissions in dairy cows offered fresh-grass diets. Twelve multiparous lactating dairy cows (6 Holstein and 6 Holstein × Swedish Red) were blocked into 3 groups for each breed and assigned to a low-, medium-, or high-CP concentrate diet [14.1, 16.1, and 18.1% CP on a dry matter (DM) basis, respectively], in a 3-period changeover study (25d per period). Total diets contained (DM basis) 32.8% concentrates and 67.2% perennial ryegrass, which was harvested daily. All measurements were undertaken during the final 6d of each period: digestibility measurements for 6d and calorimetric measurements in respiration chambers for 3d. Feed intake and milk production data were reported in a previous paper. We observed no significant interaction between concentrate CP level and cow genotype on any parameter. Concentrate CP level had no significant effect on any energy utilization parameter, except for urinary energy output, which was positively related to concentrate CP level. Similarly, concentrate CP content had no effect on CH₄ emission (g/d), CH₄ per kg feed intake, or nutrient digestibility. Cross breeding of Holstein cows significantly reduced gross energy, digestible energy, and metabolizable energy intake, heat production, and milk energy output. However, cow genotype had no significant effect on energy utilization efficiency or CH₄ parameters. Furthermore, the present study yielded a value for gross energy lost as CH₄ (5.6%) on fresh grass-based diets that was lower than the widely accepted value of 6.5%. The present findings indicate that reducing concentrate CP content from 18.1 to 14.1% may not be a successful way of alleviating CH₄ emissions from lactating dairy cows offered good-quality fresh grass, but grazing cows could be offered a low-CP concentrate without compromising energy utilization efficiency. Further research is needed to investigate whether larger differences in dietary CP content may yield positive results.

Differential response to stocking rates and feeding by two genotypes of Holstein-Friesian cows in a pasture-based automatic milking system

The throughput of automatic milking systems (AMS) is likely affected by differential traffic behavior and subsequent effects on the milking frequency and milk production of cows. This study investigated the effect of increasing stocking rate and partial mixed ration (PMR) on the milk production, dry matter intake (DMI), feed conversion efficiency (FCE) and use of AMS by two genotypes of Holstein-Friesian cows in mid-lactation. The study lasted 8 weeks and consisted in a factorial arrangement of two genotypes of dairy cattle, United States Holstein (USH) or New Zealand Friesian (NZF), and two pasture-based feeding treatments, a low stocking rate system (2 cows/ha) fed temperate pasture and concentrate, or a high stocking rate system (HSR; 3 cows/ha) fed same pasture and concentrate plus PMR. A total of 28 cows, 14 USH and 14 NZF, were used for comparisons, with 12 cows, six USH and six NZF, also used for tracking of animal movements. Data were analyzed by repeated measure mixed models for a completely randomized design. No differences (P>0.05) in pre- or post-grazing herbage mass, DMI and FCE were detected in response to increases in stocking rate and PMR feeding in HSR. However, there was a significant (P<0.05) grazing treatment×genotype×week interaction on milk production, explained by differential responses of genotypes to changes in herbage mass over time (P<0.001). A reduction (P<0.01) in hours spent on pasture was detected in response to PMR supplementation in HSR; this reduction was greater (P=0.01) for USH than NZF cows (6 v. 2 h, respectively). Regardless of the grazing treatment, USH cows had greater (P=0.02) milking frequency (2.51 v. 2.26±0.08 milkings/day) and greater (P<0.01) milk yield (27.3 v. 16.0±1.2 kg/day), energy-corrected milk (24.8 v. 16.5±1.0 kg/day), DMI (22.1 v. 16.6±0.8 kg/day) and FCE (1.25 v. 1.01±0.06 kg/kg) than NZF cows. There was also a different distribution of milkings/h between genotypes (P<0.001), with patterns of milkings/h shifting (P<0.001) as a consequence of PMR feeding in HSR. Results confirmed the improved FCE of grazing dairy cows with greater milk production and suggested the potential use of PMR feeding as a tactical decision to managing HSR and milkings/day in AMS farms.

Individual variation and repeatability of methane production from dairy cows estimated by the CO₂ method in automatic milking system

The objectives of this study were to investigate the individual variation, repeatability and correlation of methane (CH4) production from dairy cows measured during 2 different years. A total of 21 dairy cows with an average BW of 619 ± 14.2 kg and average milk production of 29.1 ± 6.5 kg/day (mean ± s.d.) were used in the 1st year. During the 2nd year, the same cows were used with an average BW of 640 ± 8.0 kg and average milk production of 33.4 ± 6.0 kg/day (mean ± s.d.). The cows were housed in a loose housing system fitted with an automatic milking system (AMS). A total mixed ration was fed to the cows ad libitum in both years. In addition, they were offered concentrate in the AMS based on their daily milk yield. The CH4 and CO2 production levels of the cows were analysed using a Gasmet DX-4030. The estimated dry matter intake (EDMI) was 19.8 ± 0.96 and 23.1 ± 0.78 (mean ± s.d.), and the energy-corrected milk (ECM) production was 30.8 ± 8.03 and 33.7 ± 5.25 kg/day (mean ± s.d.) during the 1st and 2nd year, respectively. The EDMI and ECM had a significant influence (P<0.001) on the CH4 (l/day) yield during both years. The daily CH4 (l/day) production was significantly higher (P<0.05) during the 2nd year compared with the 1st year. The EDMI (described by the ECM) appeared to be the key factor in the variation of CH4 release. A correlation (r=0.54) of CH4 production was observed between the years. The CH4 (l/day) production was strongly correlated (r=0.70) between the 2 years with an adjusted ECM production (30 kg/day). The diurnal variation of CH4 (l/h) production showed significantly lower (P<0.05) emission during the night (0000 to 0800 h). The between-cows variation of CH4 (l/day, l/kg EDMI and l/kg ECM) was lower compared with the within-cow variation for the 1st and 2nd years. The repeatability of CH4 production (l/day) was 0.51 between 2 years. In conclusion, a higher EDMI (kg/day) followed by a higher ECM (kg/day) showed a higher CH4 production (l/day) in the 2nd year. The variations of CH4 (l/day) among the cows were lower than the within-cow variations. The CH4 (l/day) production was highly repeatable and, with an adjusted ECM production, was correlated between the years.