A dominance analysis of greenhouse gas emissions, beef output and land use of German dairy farms

Greenhouse gas emissions and land use from confinement dairy farms in the Guanzhong plain of China – using a life cycle assessment approach

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

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.

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.

Is there a joint lever? Identifying and ranking factors that determine GHG emissions and profitability on dairy farms in Bavaria, Germany

In the context of global climate change, carbon footprint (CF) becomes an important sustainability indicator for dairy production systems. To mitigation the CF of the dairy sector, insight into greenhouse gases (GHG) emissions from individual farms is required. The objective of this study was to determine the primary contributors to GHG emissions at the farm-gate level, expressed as a carbon dioxide equivalents (CO2-eq), to produce one kg of fat-and protein corrected milk (FPCM). Primary data about farms’ management and feeding practices were collected from twelve dairy farms that belong to Gyeonggi-do province, which represent the most important region for milk production in South Korea. Allocation of GHG emissions between meat and milk was assessed as a physical allocation, 98% allocated to milk and 2% to meat (surplus of calves and culled cows). The CF of the evaluated farms averaged to 0.61 CO2-eq/kg of FPCM and ranged from 0.49 to 0.78 CO2-eq/kg of FPCM. Results indicated that the largest source of GHG comes mostly from enteric fermentation (83%), followed by manure management (6%), manure and fertilizer land application (8%) and energy consumption (3%). By type of gas emitted, methane accounted for 86% of total emissions, originating from enteric fermentation and manure management. Nitrous oxide and carbon dioxide accounted for 11.6 % and 2.8% of total GHG emissions, respectively. Lactating cows contributed by 70% of total GHG emissions, whereas dry cows, heifers and calves contributed by 5, 22 and 3%, respectively. Differences in GHG emissions from the evaluated farms could be explained by differences in feed quality and management practices through manure and fertilizers application on cropland. This study contributes to identify the main sources of GHG production in dairy farms, which can help to define mitigation strategies towards the transition to neutral carbon emissions of the dairy sector.

Environmental impact and economic performance of Norwegian dairy farms.

PurposeVariability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.MethodsData from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.Results and discussionBoth inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5 × 102 g CO2−eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.ConclusionsThe combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

Greenhouse gas balance of mountain dairy farms as affected by grassland carbon sequestration

Carbon footprint and mitigation strategies among heterogeneous dairy farms in Paraná, Brazil

Relating the carbon footprint of milk from Irish dairy farms to economic performance

Evaluation of a feeding strategy to reduce greenhouse gas emissions from dairy farming: The level of analysis matters

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.

Environmental assessment of United States dairy farms

Effect of production system and farming strategy on greenhouse gas emissions from commercial dairy farms in a life cycle approach