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

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

Global warming and mitigation potential of milk and meat production in Lombardy (Italy)

Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin

Many of the climate change mitigation options for dairy systems that aim at optimizing milk production imply a reduced output of meat from these systems. The objective of this study was to evaluate effectiveness of a number of mitigation strategies for dairy systems, taking into account compensation for changes in the amount of beef produced. Four commonly used mitigation strategies for dairy systems were evaluated using an LCA modelling approach: increasing the milk production per cow, extending the productive life span of cows, increasing the calving interval, and changing breed from Holstein Friesian to Jersey. The Dutch dairy system was taken as a case study. For each scenario, analyses were done in two steps. First, effects of the mitigation strategy on production of milk and carcass weight from the dairy system were calculated. Second, GHG emission intensities were calculated for three different functional units (FU): one kg of fat and protein corrected milk (FPCM), one kg of carcass weight (CW), and a fixed amount of milk and beef (i.e. 1 kg FPCM and 40 g CW). In the third FU, in case the amount of CW produced by the dairy system was lower than 40 g per kg FPCM, the remainder was compensated by CW produced in pure beef systems, assuming a GHG emission intensity of 30 kg CO2-eq. per kg CW for pure beef. Results showed a reduction in CW per kg FPCM from the dairy system in all four mitigation strategies. Considering GHG emissions per kg of FPCM only, the strategies reduced emissions by 0.2 to 18.1%. When considering emissions per kg of CW only, emissions were reduced by 12.5 to 48.9%. However, when we used a FU of 1 kg FPCM and 40 g CW, changes in emissions ranged from −0.2 to 3.8%. This was caused by the compensation of the lower CW production from dairy systems by CW from pure beef systems. Differences in emissions per kg FPCM and 40 g CW were smaller when the assumed emission intensity of pure beef was lower. We concluded that the mitigation strategies for dairy systems evaluated in this study were less effective for reduction of GHG emissions from production of milk and beef, when accounting for changes in the amount of beef produced. This study showed that the challenge of reducing GHG emissions of milk and beef production is interrelated. Hence, analyses of GHG emissions related to changes in production of milk and beef requires an integrated approach, beyond the system boundaries of the dairy farm.

It is estimated that enteric methane (CH4) contributes about 70% of all livestock greenhouse gas (GHG) emissions. Several studies indicated that feed additives such as 3-nitrooxypropanol (3-NOP) and nitrate have great potential to reduce enteric emissions. The objective of this study was to determine the net effects of 3-NOP and nitrate on farmgate milk carbon footprint across various regions of the United States and to determine the variability of carbon footprint. A cradle-to-farmgate life cycle assessment was performed to determine regional and national carbon footprint to produce 1 kg of fat- and protein-corrected milk (FPCM). Records from 1,355 farms across 37 states included information on herd structure, milk production and composition, cattle diets, manure management, and farm energy. Enteric CH4, manure CH4, and nitrous oxide were calculated with either the widely used Intergovernmental Panel on Climate Change Tier 2 or region-specific equations available in the literature. Emissions were allocated between milk and meat using a biophysical allocation method. Impacts of nitrate and 3-NOP on baseline regional and national carbon footprint were accounted for using equations adjusted for dry matter intake and neutral detergent fiber. Uncertainty analysis of carbon footprint was performed using Monte Carlo simulations to capture variability due to inputs data. Overall, the milk carbon footprint for the baseline, nitrate, and 3-NOP scenarios were 1.14, 1.09 (4.8% reduction), and 1.01 (12% reduction) kg of CO2-equivalents (CO2-eq)/kg of FPCM across US regions. The greatest carbon footprint for the baseline scenario was in the Southeast (1.26 kg of CO2-eq/kg of FPCM) and lowest for the West region (1.02 kg of CO2-eq/kg of FPCM). Enteric CH4 reductions were 12.4 and 31.0% for the nitrate and 3-NOP scenarios, respectively. The uncertainty analysis showed that carbon footprint values ranged widely (0.88-1.52 and 0.56-1.84 kg of CO2-eq/kg of FPCM within 1 and 2 standard deviations, respectively), suggesting the importance of site-specific estimates of carbon footprint. Considering that 101 billion kilograms of milk was produced by the US dairy industry in 2020, the potential net reductions of GHG from the baseline 117 billion kilograms of CO2-eq were 5.6 and 13.9 billion kilograms of CO2-eq for the nitrate and 3-NOP scenarios, respectively.

Although mountain dairy cattle farming systems are pivotal for the economy, as well as for social and environmental aspects. They significantly contribute to the rural development which is currently strongly prioritized in the common EU agricultural policy, at the same time they are also increasingly criticized for having relatively high environmental impacts per kg of product, such as greenhouse gas emissions. Consequently, the aim of this study was to assess and compare the environmental efficiency of 2 common alpine dairy farming systems, with focus on the effects of grazing, considering the seasonal variability in feeding at individual cow level and farm management over a 3-year period. This study focuses on alpine farming systems but can be considered to represent well other topographically disadvantaged mountain areas. An intensively managed and globally dominating production system (high-input), aiming at high milk yield through relatively intensive feeding and the use of the high-yielding dual-purpose Simmental cattle, permanently confined in stables, was compared with a forage-based production system (low-input), based on seasonal grazing and the use of the autochthonous dual-purpose breed Tyrolean Grey. For the present analysis, a data set with information on feed intake and diet composition as well as animal productivity at individual cow level, and farm management data based on multiyear data recording was used. Four impact categories were quantified for 3 consecutive years: Global Warming Potential (GWP100), Acidification Potential (AP), Marine Eutrophication Potential (MEP), and Land Use (LU, m2yr and Pt, with the latter additionally considering the Soil Quality Index). Besides being attributed to 1 kg of fat and protein corrected milk (FPCM), these impact categories were also related to 1 m2 of on-farm area. Due to limited agronomic options beyond forage production and pasture use in alpine regions, net provision of protein was calculated for both farming systems to assess food supply and quantify the respective food-feed competition. Overall, the low-input farming system had greater environmental efficiency in terms of MEP per kg FPCM, as well as MEP and AP per m2 than the high-input system. LU was found to be consistently higher for the high-input than for the low-input system, the GWP100 per kg of FPCM was lower for the high-input system. Additionally, pasture access had a significant effect on the reduction of environmental impacts. Lastly, the net protein provision was slightly negative for the high-input system and marginally positive for the low-input system, indicating a lower food-feed competition for the latter. Future studies should also address the social and economic aspects of the farming systems, to offer a comprehensive overview of the 3 key factors necessary for achieving more sustainable farming systems, particularly in disadvantaged marginal regions such as mountain areas.

A life cycle assessment (LCA) study of a transition from semiintensive to semi-extensive Mediterranean dairy sheep farm suggests that the latter has a strong potential for offsetting greenhouse gas (GHG) emissions through the soil C sequestration (Cseq) in permanent grasslands. The extensification process shows clear environmental advantage when emission intensity is referred to the area-based functional unit (FU). Several LCA studies reported that extensive livestock systems have greater GHG emissions per mass of product than intensive one, due to their lower productivity. However, these studies did not account for soil Cseq of temporary and permanent grasslands, that have a strong potential to partly mitigate the GHG balance of ruminant production systems. Our LCA study was carried out considering the transition from a semiintensive (SI) towards a semi-extensive (SE) production system, adopted in a dairy sheep farm located in North-Western Sardinia (Italy). Impact scope included enteric methane emissions, feed production, on-farm energy use and transportation, infrastructures as well as the potential C sink from soil Cseq compared to emission intensity. In order to provide a more comprehensive analysis, we used the following FUs: 1 kg of fat and protein corrected milk (FPCM) and 1 ha of utilised agricultural area (UAA). We observed that the extensification of production system determined contrasting environmental effects when using different FUs accounting for soil Cseq. When soil Cseq in emission intensity estimate was included, we observed slightly lower values of GHG emissions per kg of FPCM in the SI production system (from 3.37 to 3.12 kg CO2 equivalents – CO2-eq), whereas a greater variation we observed in the SE one (from 3.54 to 2.90 kg CO2-eq). Considering 1 ha of UAA as FU and including the soil Cseq, the emission intensity in SI moved from 6257 to 5793 kg CO2-eq, whereas values varied from 4020 to 3299 kg CO2-eq in SE. These results indicated that the emission intensity from semi-extensive Mediterranean dairy sheep farms can be considerably reduced through the soil Cseq, although its measurement is influenced by the models used in the estimation. Highlights - Extensification of dairy sheep systems provides an environmental benefit when soil C sequestration is considered. - Extensification of dairy sheep systems determines lower environmental impact per hectare of utilized agricultural area. - Enteric methane emissions are the main source of GHG emissions of the sheep milk life cycle. - Carbon sequestration in permanent grasslands can considerably contribute to climate change mitigation.

The world population is expected to grow to about 10 billion in 2050. To supply the future human population with food while sustaining a liveable planet, food should be produced sustainably. One of the most urgent environmental issues is climate change, induced by greenhouse gas (GHG) emissions. The dairy sector is a large contributor to GHG emissions. Important GHGs related to milk production are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), mainly emitted during feed production, enteric fermentation, and manure management. Diseases in dairy cows can reduce milk production, reproduction performance and longevity, and increase the amount of discarded milk. The objectives of this thesis were to estimate the impact of diseases (subclinical ketosis, clinical mastitis, and foot lesions) on GHG emissions, and to understand the relation between impact of diseases on GHG emissions and economic performance. First, a dynamic stochastic simulation model was developed to simulate the dynamics of the diseases and the associated production losses (reduced milk production, discarded milk, a prolonged calving interval, and removal (culling or dying on the farm)) per cow during one lactation. This model was combined with a life cycle assessment to quantify the impact of diseases on GHG emissions per ton fat-and-protein-corrected milk (kg CO2equivalents/t FPCM) from cradle to farm gate. Processes included were feed production, enteric fermentation, and manure management. The emissions of GHGs of cows with a disease increased on average by 21 (2.3%) kg CO2e/t FPCM per case of subclinical ketosis, by 58 (6.2%) kg CO2e/t FPCM per case of clinical mastitis, by 4 (0.4%) kg CO2e/ t FPCM per case of digital dermatitis, by 39 (4.3%) kg CO2e/ t FPCM per case of white line disease, and by 33 (3.6%) kg CO2e/ t FPCM per case of sole ulcer. An economic analyses was performed to estimate the costs of subclinical ketosis and related diseases. The total costs of subclinical ketosis were €130 per case per year. Comparing the impact of production contributors from a GHG emissions and economic perspective showed that a reduction in milk production had the highest impact on the economic performance, whereas removal and discarded milk had the highest impact on increase in GHG emissions. Prevalence, pathogen type, farm management (e.g. culling, feed, and manure), and prices (e.g. milk and feed) will affect the impact of production contributors on GHG emissions and economic performance. Therefore, specific farm analyses are needed to estimate the impact of diseases for a specific dairy farm. Diseases in dairy cows increase GHG emissions by approximately 0.4 Mton per year, which equals 15% of the Dutch governmental goal of GHG emission reductions in agriculture in 2030. Reducing diseases can decrease GHG emissions, can increase the income of the farmer, and can improve animal welfare. Therefore, reducing diseases can contribute to sustainable development of the dairy sector.

A diachronic study of greenhouse gas emissions of French dairy farms according to adaptation pathways

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.

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

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.

Quantifying the impact of energy consumption sources on GHG emissions in major economies: A machine learning approach

Energy-related GHG emission in agriculture of the European countries: An application of the Generalized Divisia Index

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 (&amp;gt;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.