How does soil carbon sequestration affect greenhouse gas emissions from a sheep farming system? Results of a life cycle assessment case study

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

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.

Environmental performances of Sardinian dairy sheep production systems at different input levels

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

Dairy sheep carbon footprint and ReCiPe end-point study

The body of life cycle assessment (LCA) literature is vast and has grown over the last decade at a dauntingly rapid rate. Many LCAs have been published on the same or very similar technologies or products, in some cases leading to hundreds of publications. One result is the impression among decision makers that LCAs are inconclusive, owing to perceived and real variability in published estimates of life cycle impacts. Despite the extensive available literature and policy need formore conclusive assessments, only modest attempts have been made to synthesize previous research. A significant challenge to doing so are differences in characteristics of the considered technologies and inconsistencies in methodological choices (e.g., system boundaries, coproduct allocation, and impact assessment methods) among the studies that hamper easy comparisons and related decision support. An emerging trend is meta-analysis of a set of results from LCAs, which has the potential to clarify the impacts of a particular technology, process, product, or material and produce more robust and policy-relevant results. Meta-analysis in this context is defined here as an analysis of a set of published LCA results to estimate a single or multiple impacts for a single technology or a technology category, either in a statisticalmore » sense (e.g., following the practice in the biomedical sciences) or by quantitative adjustment of the underlying studies to make them more methodologically consistent. One example of the latter approach was published in Science by Farrell and colleagues (2006) clarifying the net energy and greenhouse gas (GHG) emissions of ethanol, in which adjustments included the addition of coproduct credit, the addition and subtraction of processes within the system boundary, and a reconciliation of differences in the definition of net energy metrics. Such adjustments therefore provide an even playing field on which all studies can be considered and at the same time specify the conditions of the playing field itself. Understanding the conditions under which a meta-analysis was conducted is important for proper interpretation of both the magnitude and variability in results. This special supplemental issue of the Journal of Industrial Ecology includes 12 high-quality metaanalyses and critical reviews of LCAs that advance understanding of the life cycle environmental impacts of different technologies, processes, products, and materials. Also published are three contributions on methodology and related discussions of the role of meta-analysis in LCA. The goal of this special supplemental issue is to contribute to the state of the science in LCA beyond the core practice of producing independent studies on specific products or technologies by highlighting the ability of meta-analysis of LCAs to advance understanding in areas of extensive existing literature. The inspiration for the issue came from a series of meta-analyses of life cycle GHG emissions from electricity generation technologies based on research from the LCA Harmonization Project of the National Renewable Energy Laboratory (NREL), a laboratory of the U.S. Department of Energy, which also provided financial support for this special supplemental issue. (See the editorial from this special supplemental issue [Lifset 2012], which introduces this supplemental issue and discusses the origins, funding, peer review, and other aspects.) The first article on reporting considerations for meta-analyses/critical reviews for LCA is from Heath and Mann (2012), who describe the methods used and experience gained in NREL's LCA Harmonization Project, which produced six of the studies in this special supplemental issue. Their harmonization approach adapts key features of systematic review to identify and screen published LCAs followed by a meta-analytical procedure to adjust published estimates to ones based on a consistent set of methods and assumptions to allow interstudy comparisons and conclusions to be made. In a second study on methods, Zumsteg and colleagues (2012) propose a checklist for a standardized technique to assist in conducting and reporting systematic reviews of LCAs, including meta-analysis, that is based on a framework used in evidence-based medicine. Widespread use of such a checklist would facilitate planning successful reviews, improve the ability to identify systematic reviews in literature searches, ease the ability to update content in future reviews, and allow more transparency of methods to ease peer review and more appropriately generalize findings. Finally, Zamagni and colleagues (2012) propose an approach, inspired by a meta-analysis, for categorizing main methodological topics, reconciling diverging methodological developments, and identifying future research directions in LCA. Their procedure involves the carrying out of a literature review on articles selected according to predefined criteria.« less

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.

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.

Environmental assessment of small-scale dairy farms with multifunctionality in mountain areas

Several studies on the environmental impacts of livestock enterprises are based on the application of life cycle assessments (LCA). In Alpine regions, soil carbon sequestration can play an important role in reducing environmental impacts. However, there is no official methodology to calculate this possible reduction. Biodiversity plays an important role in the Alpine environment and is affected by human activities, such as cattle farming. Our aim was to estimate the carbon footprint (CF) of four different dairy production systems (different in breeds and feeding intensity) by using the LCA approach. The present study included 44 dairy Alpine farms located in the autonomous province of Bolzano in northern Italy. Half of the farms (n = 22) kept Alpine Grey and the other half (n = 22) Brown Swiss cattle. Within breeds, the farms were divided by the amount of concentrated feed per cow and day into high concentrate (HC) and low concentrate (LC). This resulted in 11 Alpine Grey low concentrate (AGLC) farms feeding an average amount of 3.0 kg concentrated feed/cow/day and 11 Alpine Grey high concentrate (AGHC) farms with an average amount of 6.3 kg concentrated feed/cow/day. Eleven farms kept Brown Swiss cows with an average amount of 3.7 kg concentrated feed/cow/day (BSLC) and another 11 farms feeding on average 7.6 kg concentrated feed/cow/day (BSHC). CF for the four systems was estimated using the LCA approach. The functional unit was 1 kg of fat and protein corrected milk (FPCM). Furthermore, two methodologies have been applied to estimate soil carbon sequestration and effect on biodiversity. The system with the lowest environmental impact in terms of CF was BSHC (1.14 kg CO2-eq/kg of FPCM), while the most impactful system was the AGLC group (1.55 kg CO2-eq/kg of FPCM). Including the CF reduction due to soil carbon sequestered from grassland, it decreased differently for the two applied methods. For all four systems, the main factor for CF was enteric emission, while the main pollutant was biogenic CH4. Conversely, AGLC had the lowest impact when the damage to biodiversity was considered (damage score = 0.41/kg of FPCM, damage to ecosystem diversity = 1.78 E-07 species*yr/kg FPCM). In comparison, BSHC had the greatest impact in terms of damage to biodiversity (damage score = 0.56/kg of FPCM, damage to ecosystem diversity = 2.49 E-07 species*yr/kg FPCM). This study indicates the importance of including soil carbon sequestration from grasslands and effects on biodiversity when calculating the environmental performance of dairy farms.

Effective lactation yield: A measure to compare milk yield between cows with different dry period lengths

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.

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

In the face of the unfolding climate crisis, the role and importance of reducing Greenhouse gas (GHG) emissions from the building sector is increasing. This study investigates the global trends of GHG emissions occurring across the life cycle of buildings by systematically compiling life cycle assessment (LCA) studies and analysing more than 650 building cases. Based on the data extracted from these LCA studies, the influence of features related to LCA methodology and building design is analysed. Results show that embodied GHG emissions, which mainly arise from manufacturing and processing of building materials, are dominating life cycle emissions of new, advanced buildings. Analysis of GHG emissions at the time of occurrence, shows the upfront ‘carbon spike’ and emphasises the need to address and reduce the GHG ‘investment’ for new buildings. Comparing the results with existing life cycle-related benchmarks, we find only a small number of cases meeting the benchmark. Critically reflecting on the benchmark comparison, an in-depth analysis reveals different reasons for cases achieving the benchmark. While one would expect that different building design strategies and material choices lead to high or low embodied GHG emissions, the results mainly correlate with decisions related to LCA methodology, i.e. the scope of the assessments. The results emphasize the strong need for transparency in the reporting of LCA studies as well as need for consistency when applying environmental benchmarks. Furthermore, the paper opens up the discussion on the potential of utilizing big data and machine learning for analysis and prediction of environmental performance of buildings.