180 Screening the carbon footprint of intensive Korean dairy cattle farms: Transition towards low emissions’ production system

Climate change is one of the greatest challenges mankind has ever faced and could lead to potentially devastating global problems, with a need for urgent mitigation and adaptation. Agriculture, especially livestock farming, is a major driver of climate change through its contribution to the total emissions of greenhouse gases (GHGs). The dairy sector has been identified as an important source of GHG emissions, mainly via carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). In this study, total CO2 equivalent (CO2e) emissions were assessed from a dairy farm (65 dairy cows) located in Romania using the Cool Farm Tool calculator (CFT). We specifically aimed to calculate: (1) the total CO2 equivalent (CO2e) and CO2e per kg FPCM (fat- and protein-corrected milk); (2) methane emissions from enteric fermentation; (3) GHGs resulting from feeding practices; (4) GHGs from manure management; and (5) a simulation of two different scenarios and their impact on GHG emissions. Our results showed annual GHG emissions of 553,170 kg CO2e, almost half of which were released through enteric fermentation. Lactating cows were the major contributor to total GHG emissions, while heifers released the lowest emissions. The two scenarios simulated in this study showed that both the changes made in dairy diet composition and livestock manure management could result in lower GHG emissions. These results confirm the importance and utility of the CFT for the quantification of GHG emissions in dairy farms and its important role as a decision support tool to guide the adoption of good agricultural practices.

In recent years, the concept of life cycle assessment (LCA) has proven to be useful because of its potential to assess the integral environmental impacts of agricultural products. Developing countries such as India are good candidates for LCA research because of the large contribution of smallholder dairy system to the production of agricultural products such as milk. Therefore, the aim of the present study was to explore the carbon footprint of milk production under the multi-functional smallholder dairy system in Anand district of Gujarat state, western India. A cradle-to-farm gate LCA was performed by covering 60 smallholder dairy farms within 12 geographically distinct villages of the district. The average farm size was 4.0 animals per farm, and the average number of each category of animal was 2.5 lactating cows, 1.4 lactating buffaloes, 1.8 replacement cows, 1.6 replacement buffaloes, 2.0 retired cows, 1.3 retired buffaloes and 1.0 ox per farm. The emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) on CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation and manure management were allocated to fat- and protein-corrected milk (FPCM) on the basis of mass balance, price and digestibility. Emissions of CO2, CH4 and N2O from cattle contributed 11.0%, 75.4% and 13.6%, respectively, to the total greenhouse gas (GHG) emissions. The contribution of CO2, CH4 and N2O from buffalo was 8.2%, 80.5% and 11.3%, respectively, to the total GHG emissions of farms. The average carbon footprint (CF) of cow milk was 2.3, 1.9 and 2.0 kg CO2-eq/kg FPCM on mass, economic and digestibility basis, respectively, whereas for buffalo, milk CF was 3.0, 2.5 and 2.7 kg CO2-eq/kg FPCM, respectively. On the basis of digestibility allocation, emissions from retired (>10 years of age and incapable of or ceased producing milk) cows and buffaloes were 1571.3 and 2556.1 kg CO2-eq/retirement year, respectively. Overall, the CF of milk production under the smallholder dairy system in Anand district was 2.2 kg CO2-eq/kg FPCM, which reduced to 1.7 kg CO2-eq/kg FPCM when milk, manure, finance and insurance were considered as economic functions of the smallholder system. The CF was lower by 65% and 22% for cow and buffalo milk, respectively, than were the estimates of FAO for southern Asia, and this was mainly attributed to difference in the sources of GHG emissions, manure management systems, feed digestibility and milk production data used by FAO.

In 2022, New York (NY) had over 620 000 dairy cows producing more than 7 million Mg (15 billion lb) of milk, ranking fifth in dairy producing states in the United States. The objectives of this work were to (1) estimate total farm-gate greenhouse gas (GHG) emissions and GHG emission intensity (GHGei) of 36 medium to large (>300 mature cows) commercial NY dairies, (2) determine the contribution of main GHGs (on-farm methane [CH4], nitrous oxide [N2O], and carbon dioxide [CO2], plus embedded emissions [CO2 equivalents; CO2eq]) and sources (enteric fermentation, feed production, manure management, grazing, fuel and energy) to farm-gate GHGei, and (3) identify key performance indicators (KPIs) driving farm-gate GHGei. Assessments were done for 2022 using The Cool Farm Tool. Farm size ranged from 345 to 6 350 head of predominantly Holstein cows with animal densities between 1.76 and 4.85 animal units ha-1 (0.71 to 1.96 AU ac-1) and heifer to cow ratios between 0.02 and 0.49. Herds produced an average fat and protein corrected milk (FPCM) yield of 12.7 Mg (29 000 lb) FPCM cow-1 per year using 64% homegrown feed. Total FPCM production was 873 000 Mg (1.92 billion lb), representing approximately 12% of total NY milk production in 2022. The GHGei ranged from 0.63 to 1.06 kg CO2eq kg FPCM-1 (mean GHGei = 0.86kg CO2eq kg FPCM-1). Methane was the biggest contributor, accounting for 60% of total GHG emissions on average, with enteric CH4 as the largest contributor (45% of total farm emissions). Among farms, feed production emissions accounted for about 25%, with approximately 7% from homegrown feed production. Manure management practices accounted for about 20% of emissions and explained the largest amount of variation in GHGei among farms. Potential KPIs for GHGei included manure management system, heifer to cow ratio, herd feed consumption intensity, percentage of homegrown feed, and crop nutrient source (fertilizer versus manure). Emission intensity reflected the high proportion of good quality homegrown feed, careful nutrient management and use of manure treatment systems (covered liquid slurry storages, anaerobic digesters) on several dairies. The influence of replacement rate and heifer to cow ratio on animal density, herd feed consumption intensity, and subsequent GHGei requires more detailed analysis. The farms in this study represent a considerable proportion of NY's 2022 FPCM production. Greater participation by smaller farms is necessary to draw conclusions for NY's dairy industry as a whole.

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

Livestock production contributes to greenhouse gas (GHG) emissions. However, there is a considerable variability in the carbon footprint associated with livestock production. Site specific estimates of GHG emissions are needed to accurately focus GHG emission reduction efforts. A holistic approach must be taken to assess the environmental impact of livestock production using appropriate geographical scale. The objective of this study was to determine baseline GHG emissions from dairy production in South Dakota using a life cycle assessment (LCA) approach. A cradle-to-farm gate LCA was used to estimate the GHG emissions to produce 1 kg of fat and protein corrected milk (FPCM) in South Dakota. The system boundary was divided into feed production, farm management, enteric methane, and manure management as these activities are the main contributors to the overall GHG emissions. The production of 1 kg FPCM in South Dakota dairies was estimated to emit 1.23 kg CO2 equivalents. The major contributors were enteric methane (46%) and manure management (32.7%). Feed production and farm management made up 14.1 and 7.2%, respectively. The estimate is similar to the national average but slightly higher than the California dairy system. The source of corn used in the dairies influences the footprint. For example, South Dakota corn had fewer GHG emissions than grain produced and transported in from Iowa. Therefore, locally and more sustainably sourced feed input will contribute to further reducing the environmental impacts. Improvements in efficiency of milk production through better genetics, nutrition animal welfare and feed production are expected to further reduce the carbon footprint of South Dakota dairies. Furthermore, anaerobic digesters will reduce emissions from manure sources.

The objective of this study was to estimate the carbon footprint (CF) of milk production (in kg of CO2 equivalents (CO2e) per kg of fat and protein corrected milk (FPCM)) in dairy farms of the San Martín region, in the Peruvian Amazon. A cradle-to-farm gate characterization and analysis were carried out on eight representative dairy farms. Greenhouse gas (GHG) emissions were estimated using equations, following the 2019 refinement of the 2006 IPCC Guidelines. The results showed an average milk production of 9.7 ± 0.82 L milk/cow/day, Gyr x Holstein crosses as the predominant breed, use of cultivated grasses such as Brachiaria brizantha, living fences (Guazuma ulmifolia Lam) as the predominant silvopastoral arrangement, and low level of external inputs such as feed or grain additives. In relation to CF, an average value of 2.26 ± 0.49kg CO2e/kg FPCM was obtained, with enteric fermentation being the most important source (1.81 ± 0.51kg CO2e/kg FPCM), followed by manure management, land use, and energy/transport (0.26 ± 0.06, 0.14 ± 0.04, and 0.05 ± 0.04kg CO2e/kg FPCM, respectively). Differences were found between farmers, obtaining lower CF values (1.76 vs 3.09kg CO2e/kg FPCM) on farms with better feed quality, higher production levels, and a higher percentage of lactating animals compared to dry cows. It is concluded that dairy farms in the Peruvian Amazon region can reduce their emissions if they improve their current feeding practices.

Smallholder dairy farms face enormous challenges in increasing milk production while mitigating greenhouse gas (GHG) emissions, thereby enhancing climate resilience. The carbon footprint (CF) of smallholder milk production is expected to increase with increasing demand for dairy products under the business-as-usual scenario. This study estimates the carbon footprint of smallholder milk production and examines variation across farms using data from 480 households to identify viable options for mitigating GHG emissions. We applied a cradle to farm-gate life cycle assessment (LCA) approach to examine the effects of farming systems on GHG emission intensities across intensification gradients of smallholder farms (SHF) from four potential dairy districts in the central highlands of Ethiopia. According to our findings, enteric fermentation was the primary source of GHG emissions, and methane(CH4) emissions from enteric fermentation and manure management accounted for the majority of total emissions across farms. The estimated average CF varies depending on farming systems, global warming potential (GWP), and allocation methods used. When GHG emissions were allocated to multiple products using economic allocation and based on IPCC (2007)and IPCC (2014)GWPs, the overall average CF of milk production was 1.91 and 2.35kg CO2e/kg fat and protein-corrected milk (FPCM), respectively. On average, milk accounted for 72% of total greenhouse gas emissions. In terms of farm typology, rural SHF systems produced significantly more CF per kg of milk than urban and peri-urban SHF systems. Variations in milk yield explained more than half of the variation in GHG emissions intensity at the farm level. Feed digestibility and feed efficiency had a negative and significant (P < 0.01) association with CF of SHF. Our findings suggested that improving feed digestibility and feed efficiency by increasing the proportion of concentrate and improved forage as well as chemically upgrading straw and crop residue could provide an opportunity to both increase milk yield and reduce the CF of milk production of SHF in the study area. Supporting SHF to realize strategies contributing to climate-resilient dairy development require interventions at several levels in the dairy value chain.

Jayasundara, S. and Wagner-Riddle, C. 2014. Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991. Can. J. Anim. Sci. 94: 155–173. For identifying opportunities for reducing greenhouse gas (GHG) emissions from milk production in Ontario, this study analyzed GHG intensity of milk [kg CO2 equivalents kg−1 fat and protein corrected milk (FPCM)] in 2011 compared with 1991 considering cow and crop productivity improvements and management changes over this period. It also assessed within-province variability in GHG intensity of milk in 2011 using county-level data related to milk production. After allocating whole-farm GHG emissions between milk and meat using an allocation factor calculated according to the International Dairy Federation equation, GHG intensity of Ontario milk was 1.03 kgCO2eq kg−1 FPCM in 2011, 22% lower than that in 1991 (1.32 kg CO2eq kg−1 FPCM). Greenhouse gas sources directly associated with dairy cattle decreased less (21 and 14% for enteric fermentation and manure management, respectively) than sources associated with feed crop production (30 to 34% for emissions related to N inputs and farm-field work). Proportions of GHG contributed from different life cycle activities did not change, with enteric fermentation contributing 46%, feed crop production 34%, manure management 18% and milking and related activities 2%. Within province, GHG intensity varied from 0.89 to 1.36 kg CO2eq kg−1 FPCM, a variation inversely correlated with milk productivity per cow (kg FPCM sold cow−1 year−1). The existence of a wide variation is strong indication for potential further reductions in GHG intensity of Ontario milk through the identification of practices associated with high efficiency.

Farm level environmental assessment of organic dairy systems in the U.S.

Greenhouse gas emission intensities of grass silage based dairy and beef production: A systems analysis of Norwegian farms

Carbon footprint of dairy goat milk production in New Zealand

The dairy sector is urged to reduce environmental impacts, such as greenhouse gas (GHG) emissions. But dairy farms not only produce milk: surplus calves and culled cows also yield meat as co-product. To split environmental impacts between milk and meat, a biophysical allocation method proposed by the International Dairy Federation (IDF) is currently used. Its applicability to farms with large meat-to-milk output ratios (beef-to-milk ratio, BMR) may be limited and lead to wrong conclusions when assessing GHG emissions and mitigation measures at farm level.To overcome these limitations, we developed a biophysical allocation approach based on the net energy requirement for milk and meat production according to internationally agreed energy requirements for dairy cows. Both the enhanced and the existing allocation methods were tested on an international dataset that included farms with a large range of BMR, as can be found in dual-purpose production systems or on farms with low milk productivity. The results from the international dataset reveal that the allocation factor does not substantially change for production systems with low BMR. For BMR up to 0.03 kg live weight (LW)/kg of fat- and protein-corrected milk (FPCM), the maximum deviation in the allocation factor between the two methods was 0.047. For larger BMR, the developed method still allocated relevant shares of emissions to meat while the standard approach did not. The developed method is less sensitive to shifts in BMR, especially for low-performing dairy farms.In addition, both methods were tested on a dataset of 46 Swiss dairy farms. By increasing the longevity of cows (one additional lactation), the impacts of altered BMR on the modelled GHG emissions and their allocation on milk and meat could be assessed. Increased longevity resulted in fewer cows to be replaced, decreased emissions from the rearing of replacement stock (-444 kg CO2-equivalents/cow/year) and lower meat output (-61 kg LW/cow/year), as fewer cows were culled. Consequently, a larger share of emissions was allocated to milk. While the standard biophysical allocation approach did not result in reduced GHG emissions per kg of milk (+0.002 kg CO2-equivalents/kg FPCM), the newly developed approach generated a modest (-0.022 kg CO2-equivalents/kg FPCM), although not significant reduction.The effects of GHG mitigation measures that affect BMR are thus represented more accurately than when applying the standard approach. Based on the presented data, we encourage the revision of currently used international standards for allocating environmental impacts to milk and meat.

Jayasundara, S. and Wagner-Riddle, C. 2014. Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991. Can. J. Anim. Sci. 94: 155-173. For identifying opportunities for reducing greenhouse gas (GHG) emissions from milk production in Ontario, this study analyzed GHG intensity of milk [kg CO2 equivalents kg-1 fat and protein corrected milk (FPCM)] in 2011 compared with 1991 considering cow and crop productivity improvements and management changes over this period. It also assessed within-province variability in GHG intensity of milk in 2011 using county-level data related to milk production. After allocating whole-farm GHG emissions between milk and meat using an allocation factor calculated according to the International Dairy Federation equation, GHG intensity of Ontario milk was 1.03 kgCO2eq kg-1 FPCM in 2011, 22% lower than that in 1991 (1.32 kg CO2eq kg-1 FPCM). Greenhouse gas sources directly associated with dairy cattle decreased less (21 and 14% for enteric fermentation and manure management, respectively) than sources associated with feed crop production (30 to 34% for emissions related to N inputs and farm-field work). Proportions of GHG contributed from different life cycle activities did not change, with enteric fermentation contributing 46%, feed crop production 34%, manure management 18% and milking and related activities 2%. Within province, GHG intensity varied from 0.89 to 1.36 kg CO2eq kg-1 FPCM, a variation inversely correlated with milk productivity per cow (kg FPCM sold cow-1 year-1). The existence of a wide variation is strong indication for potential further reductions in GHG intensity of Ontario milk through the identification of practices associated with high efficiency.

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

Greenhouse gas emission profiles of European livestock sectors