Carbon Footprint Of Milk Research Articles

Improving farm profitability also reduces the carbon footprint of milk production in intensive dairy production systems

Standard life cycle assessment and economic analysis methods were used to determine the carbon footprint (CF) of milk production and financial performance of a representative sample of dairy farms in Ontario, Canada to assess if there is a trade-off between these two different sustainability measures. Across the 142 dairy farms, CF of milk varied by about 4-fold, from 0.441 to 1.732 CO2eq kg−1 FPCM, a much larger variation than estimated using spatially disaggregated statistical data. Emissions from enteric fermentation and those resulting from the production and supply of feed were the largest contributors to the CF of milk (44% and 36%, respectively). Dairy profits per cow averaged CA$4848 per year but ranged from CA$2530 to $7151 across sample farms. These financial returns were inversely correlated with the CF of milk production, suggesting that rather than a trade-off between GHG emissions intensity and economic performance, there is instead a synergy of the two sustainability indicators. Using a linear regression approach we find that a reduction in the CF of milk production can be achieved while simultaneously improving the profitability of dairy farms. This synergy was largely determined by farm characteristics related to livestock productivity (e.g. milk production per cow) and feeding practices (e.g. herd level total feed use and reliance on purchased feed). Our results suggest that in the absence of explicit GHG reduction policies targeting dairy farms, the main incentive for reducing farm-level GHG emissions could result from the economic pressure on farmers to increase their profitability per cow or per ha.

Estimation and mitigation of GHG emissions from ruminant livestock in Pakistan

The study examined baseline emissions of greenhouse gases from ruminant livestock in Pakistan for the year 2014 and evaluated feasible interventions for mitigating the sector emissions. Total emissions (as CO2-equivalents) from livestock supply chain from cradle to farm gate were estimated at 431007 × 103 t. Major part (77%) of the emissions was produced by the mixed system and the remaining 23% was contributed by the grazing system. Methane emissions were 62.5% of the total emissions, followed by N2O at 29.4% and CO2 at 8.1%. Bulk of milk (87.6%) and meat (59.4%) was produced by the mixed system, which was associated with three-fold higher emissions at 332248 × 103 t than when they were produced by the grazing system. The emission intensity (kg CO2-eq/kg protein) of milk and meat averaged 183.4 and 443.2 respectively, and ranked higher than the global average values. Buffaloes were responsible for the major proportion of emissions, followed by cattle. Average emissions per animal in buffalo, cattle, sheep and goat were 4.27, 3.27, 0.28 and 0.25 t CO2-eq/year respectively. The emission intensities (kg CO2-eq/kg commodity protein) of both milk and meat remained lower in cattle than buffalo and were calculated as 166.1 and 299.7 in cattle and 189.5 and 527.9 in buffaloes respectively. The carbon footprint of milk and meat in sheep and goats also remained high and averaged 189.0 and 472.6 kg CO2-eq/kg protein respectively. Overall, the emission intensity of meat was slightly higher in the grazing system than mixed system, but remained much higher in non-dairy herds than in dairy herds (1006.6 vs 46.6 kg CO2-eq/kg meat protein). Interventions such as improving diet quality through increased fodder supply, vaccination for adequate health control and genetic improvement reduced emission intensities of milk (kg CO2-eq/kg protein), varying from 20.3% to 36.8% compared with the baseline in dairy cows and buffaloes and this was associated with a positive productivity outcome of enhanced milk production by 25–50%. More significant reduction in emission intensities of milk between 48.1% and 53.1%, together with a 100% increase in milk yield above baseline, resulted from combined application of the three interventions as a single package.

Is low-input dairy farming more climate friendly? A meta-analysis of the carbon footprints of different production systems

The global warming potential of milk production is a key aspect in the assessment of its eco-efficiency. The carbon footprint summarises the climate-relevant emissions of the production cycle, with this study focussing on the emissions from cradle to farm gate as boundaries. Numerous life cycle assessments were published in recent years, presenting the carbon footprint for different regions, production systems and management scenarios. However, despite the obvious high scientific interest in this topic, general conclusions on the climate-friendliness of contrasting production systems can hardly be drawn and there is no clear answer to the question of whether or not grazing systems provide an overall more climate-friendly alternative to confinement systems.To resolve this discussion, a meta-analysis was applied to a dataset, created with data from a selection of 30 published life cycle assessments, comprising in total 87 carbon footprint values from 15 different countries. After a standardisation process, three production system categories (pasture-based, mixed and confinement) were defined based on feeding parameters. Aside from the comparison of the production systems, the effects of various production variables (pasture and concentrate intake, milk yield per cow, milk yield per kg of metabolic live weight, mineral nitrogen fertilisation, feed efficiency and replacement rate) were analysed. Therefore, linear and level-log mixed models were developed and analyses of covariance performed. As the dataset used for the analysis covered a large range of different intensities per production system, the results are based on a robust analysis and can be extrapolated to any milk production system with known in- and outputs.The results show that increases in milk yield, pasture intake and feed efficiency decreased the carbon footprint of milk significantly, independent of the production system. However, the mitigation potential is limited across production systems with regard to their productivity thresholds. The comparison of the systems without consideration of other production parameters did not reveal any significant differences. When controlling for milk yield, however, the pasture-based system achieved lower carbon footprints compared to the other production systems. Thus, irrespective of the importance of milk yield for emissions and the generally lower milk yields of the pasture-based production system, this system still offers a competitive climate impact.

Carbon Footprint of Milk from Pasture-Based Dairy Farms in Azores, Portugal

The dairy sector is a major contributor to greenhouse gas emissions. Pasture-based dairy production is sometimes credited as environmentally friendlier but is less studied than more intensive production systems. Here we characterize and calculate the carbon footprint (CF), using life cycle assessment, of the “Vacas Felizes” pasture-based milk production system, in the Azores archipelago. Impacts were determined for multiple functional units: mass, energy and nutritional content, farm, area and animal. We performed multivariate analysis to assess the contribution of production parameters to the CF. Finally, we performed a literature review to compare these results with other production systems. Results show that emissions from enteric fermentation, concentrated feed production and (organic and mineral) fertilizer application are the three main sources of impact. Milk yield is a key production feature for the determination of emissions. The average CF is 0.83 kg CO2/kg raw milk. At each milk yield level, the farms are approximately homogeneous. Compared with other studies, “Vacas Felizes” milk has a lower CF than 80 (out of 84) published CFs and on average it is approximately 32% lower.

Assessment and Mitigation of Methane Emissions from Livestock Sector in Pakistan

The study examined Pakistan’s livestock sector to assess the scale of GHG emissions and identified feasible technical interventions through which GHG particularly methane can potentially be reduced. Life Cycle Assessment of emissions from livestock production supply chain for the year 2014 was performed using Global Livestock Environment Assessment Model (GLEAM-i, version 2) developed by FAO. Annual emissions from the livestock sector were estimated at 404.2 million ton CO2 eq., representing carbon dioxide 6.6%, methane 70.6% and nitrous oxide 22.8%. Enteric methane averaged 63.4% of total emissions. Feed production and processing, manure management and energy use contributed 25%, 11% and 1%, respectively to the total sector emissions. Carbon footprint of milk from cows and buffalo was 184.9 against global average of 110.0 kg CO2-eq/kg milk protein and that of beef and mutton was 606.4 against the global average of 235 CO2-eq/kg meat protein. The emission intensity of chicken meat and eggs were lowest 49.6 and 20.8 kg CO2-eq/kg protein, respectively and compared to global averages. Buffaloes produced maximum GHG followed by cattle, goats, sheep and poultry. Mitigation interventions in the form of improved fodder, herd heath and genetics reduced methane intensity ranging from 14.6 to 43.2% compared to baseline. This was associated with 25–100% increase in milk yield and 10–65% in meat supply above baseline scenarios. The strong inverse correlation between methane intensity and milk yield suggested that efforts to enhance productivity reduce carbon footprint of the livestock products thus achieving the dual goals of protecting environment and food security.

Discrimination of milk carbon footprints from different dairy farms when using IPCC Tier 1 methodology for calculation of GHG emissions from managed soils

Quantification of the environmental performance of dairy farms should allow comparisons between farms. We assess whether IPCC Tier 1 methodology for emissions from soil management is sufficiently precise to analyse and differentiate the carbon footprint of milk production between practical dairy farms and whether we can correctly identify which farms have the lowest and the highest GHG emissions per product unit, respectively. We used data from 20 Norwegian dairy farms which are very similar in structure, but differ in organic/non-organic management and the share of peat soil of their farmland.We assessed the uncertainty of the carbon footprint by running Monte Carlo simulations with the uncertainty ranges given in Tier 1 of the IPCC guidelines. The carbon footprint is considered different when 95% of all Monte Carlo iterations assume that one farm has higher product-related GHG emissions than the farm in comparison. The uncertainty of results in the single farms, expressed as two-times the standard deviation divided by the median result, ranges between 4.2% and 15.3%. This means that 95% of values in the resulting distribution of one farm are within a range of 4e16% of the median of that farm. Farms can be differentiated when the variation of the carbon footprint is higher than the uncertainty of farm-related emissions. From all 190 direct comparisons of two farms in the tudy, 78% are significantly different.For this uncertainty assessment, it must be established that background processes, especially the datasets for import feed, can be judged covariant in order to prohibit them from influencing the comparison between farms. Secondly, the uncertainty ranges used for the calculation must be appropriate for the assessed systems. We were able to confirm the hypothesis that a significant differentiation of the milk carbon footprint between farms is possible with an IPCC Tier 1 approach for a majority of our comparisons, and found a difference of above 8.7% sufficient to establish significance.

Climate mitigation by dairy intensification depends on intensive use of spared grassland.

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler-beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing-based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10kg CO2 e kg-1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler-beef production to replace reduced dairy-beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler-beef production to the "global beef frontier" in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63kg CO2 e kg-1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from "snapshot" carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.

Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics

Milk production is responsible for emitting a range of greenhouse gases (GHGs), mainly carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4). In Life Cycle Assessments (LCA), the Global Warming Potential with a time horizon of 100 years (GWP100) is used almost universally to aggregate emissions of individual gases into so-called CO2-equivalent emissions that are used to calculate the overall carbon footprint of milk production. However, there is growing awareness that, depending on the purpose of the LCA, metrics other than GWP100 could be justified and some would give a very different weighting for the short-lived gas CH4 relative to the long-lived gases CO2 and N2O when calculating the carbon footprint. Pastoral dairy production systems at different levels of intensification differ in the balance of short- and long-lived GHGs associated with on- and off-farm emissions. Differences in the carbon footprint of different production systems could therefore be highly sensitive to the choice of GHG metric. Here we explore the extent to which alternative GHG metric choices would alter the carbon footprint of New Zealand milk production at different levels of intensification at national, regional and individual farm scales and compared to the carbon footprint of milk of selected European countries. We find that the ranking of different production systems and individual farms in terms of their carbon footprint is relatively robust against the choice of GHG metric, despite significant differences in their utilisation of pastures versus supplementary off-farm feed, fertiliser use and energy consumption at various stages of farm operations. However, there are instances where alternative GHG metric choices would fundamentally change the conclusions of LCA of different production systems, including whether a move towards higher or lower input systems would increase or decrease the average carbon footprint of milk production in New Zealand. Greater transparency about the implications of alternative GHG metrics for LCA, and the often inadvertent and implicit value judgements embedded in these metrics, would help ensure that policy decisions and consumer choices based on LCA indeed deliver the climate outcomes intended by end-users.

1180 Partial carbon footprint of milk and interaction between enteric methane and nitrous oxide emissions in grazing dairy farms: The case of Costa Rica

1180 Partial carbon footprint of milk and interaction between enteric methane and nitrous oxide emissions in grazing dairy farms: The case of Costa Rica

The Milk Supply Chain in Italy’s Umbria Region: Environmental and Economic Sustainability

This article aims to investigate the environmental and economic sustainability of five dairy farms in the Umbria Region (Italy). The study also provides an assessment of aggregate sustainability, which is less investigated with reference to cattle milk both globally and in Italy, through the analysis of the relationship between economic and environmental performance. Primary data were collected through a direct survey carried out in 2014. The environmental assessment was conducted with a Life Cycle Assessment (LCA) “cradle to farm gate” approach, while the economic dimension was evaluated by determining the direct and indirect costs related to the factors involved in the production process. A correlation analysis and a linear regression were performed in order to study the relationship between the carbon footprint (CF) and operating income. The average operating income amounted to 0.03 Euro/L of milk. The CF values of the five companies are contained within a variation range comprised between 0.90 and 1.76 kg CO2 eq/L of milk. The existence of an inverse relationship between the CF of milk and operating income confirms the hypothesis regarding the possibility of implementing strategies aimed at improving performance in both investigated dimensions at the same time, thus increasing the aggregate sustainability.

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.

How can grass-based dairy farmers reduce the carbon footprint of milk?

The Irish dairy industry aims to increase milk production from grass-based farms following the removal of the EU milk-quota system, but is also required to minimise greenhouse gas (GHG) emissions to meet European reduction targets. Consequently, the sector is under increasing pressure to reduce GHG emissions per unit of milk, or carbon footprint (CF). Therefore, the goal of the present study was to determine the main sources of the CF of grass-based milk production and to identify mitigation strategies that can be applied to reduce farm footprints. In total, the CF of milk was estimated for 62 grass-based dairy farms in 2014. The method used to quantify GHG emissions was a life cycle assessment (LCA), independently certified to comply with the British standard for LCA (PAS 2050). The LCA method was applied to calculate annual on- and off-farm GHG emissions associated with dairy production until milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk on the basis of the economic value of dairy products and expressed per kilogram of fat- and protein-corrected milk to estimate CF. Enteric methane was the main source of the CF of milk (46%), followed by emissions from inorganic N fertilisers (16%), manure (16%) and concentrate feedstuffs (8%). The mean CF of milk from the 62 farms was 1.26 kg of CO2-eq per kilogram of fat- and protein-corrected milk, but varied from 0.98 kg to 1.67 kg as measured using the 95% confidence interval. The CF of milk was correlated with numerous farm attributes, particularly N-fertiliser, the percentage of grazed grass in the diet, and production of milk solids. Grass-based dairy farmers can significantly improve these farm attributes by increasing herd genetic merit, extending the length of the grazing season and optimising N fertiliser use and, thereby, reduce the CF of milk.

Ration Balancing: A Practical Strategy for Reducing Enteric Methane Emission and Carbon Footprint of Milk in India: A Review

Enteric methane is the largest contributor to the total greenhouse gas emissions from agricultural sector. It is closely related to the feed regime and the productivity of dairy animals. Life cycle assessment study indicated that the extensive dairy production system with low milk yields has higher carbon footprint of milk than more intensive system with higher milk yields. In this paper, various methane mitigation strategies have been discussed under Indian feeding and management conditions. These strategies are mainly focused on feeding, breeding and rumen manipulation which can be broadly grouped into those that increase animal productivity and those that directly modify rumen fermentation so that less methane is produced in total. However, most of these strategies are not practically and commercially applicable for reducing methane emissions in large ruminants under field conditions owing to their various limitations. Further, many of these strategies require years of research before practical application and commercially viable products or technologies are available. For India, enteric methane mitigation strategy should be cost-effective and address socio-economic issues. Ration balancing helps in improving productivity and reducing enteric methane emissions in cows and buffaloes at farmers’ doorstep. A life cycle assessment study of milk production in India indicated that a significant reduction in carbon footprint of milk has been observed after feeding a balanced ration. Thus, improving animal productivity through ration balancing with available feed resources could be a most practical strategy for reducing enteric methane emissions and carbon footprint of milk production in India.

Ration balancing at farmers' doorstep: a climate-smart strategy for sustainable increase in livestock productivity in developing countries.

Abstract In recent years, the share of developing countries in global milk production has increased significantly. Despite the breakthroughs in milk production, average productivity of livestock is quite low in the region, mainly because of imbalanced feeding in terms of protein, energy and minerals. Farmers do not have adequate knowledge, resources and skills to formulate a least cost balanced ration. Feed shortages notwithstanding in the region, considerable potential exists for improving livestock productivity and reducing the carbon footprint of milk by ration balancing with available feed resources. The National Dairy Development Board of India has developed a user-friendly ration balancing software for preparing a least cost balanced ration, using available feed resources and area-specific mineral mixtures. To educate farmers, a large-scale ration balancing programme has been implemented in different states of India. Various studies indicate that ration balancing has resulted in an increase in farmers' net daily income by increasing milk yield or milk fat, while reducing feeding costs. Ration balancing has also helped improve feed conversion efficiency and microbial protein synthesis, while reducing enteric methane emissions. A study on the cradle-to-farm gate life cycle assessment of lifetime milk production indicated that enteric methane is the largest contributor to the carbon footprint of milk. A significant reduction in the carbon footprint of milk has been observed when feeding a balanced ration. The present review summarizes the application of ration balancing approach at the farmers' doorstep that could serve as a climate-smart strategy for achieving sustainable increases in livestock productivity in developing countries.

Carbon footprint of milk production under smallholder dairying in Anand district of Western India: a cradle-to-farm gate life cycle assessment

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.

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

Mitigating greenhouse gas (GHG) emissions per unit of milk or the carbon footprint (CF) of milk is a key issue for the European dairy sector given rising concerns over the potential adverse effects of climate change. Several strategies are available to mitigate GHG emissions, but producing milk with a low CF does not necessarily imply that a dairy farm is economically viable. Therefore, to understand the relationship between the CF of milk and dairy farm economic performance, the farm accountancy network database of a European Union nation (Ireland) was applied to a GHG emission model. The method used to quantify GHG emissions was life cycle assessment (LCA), which was independently certified to comply with the British standard for LCA. The model calculated annual on- and off-farm GHG emissions from imported inputs (e.g., electricity) up to the point milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk based on the economic value of dairy farm products and expressed per kilogram of fat- and protein-corrected milk (FPCM). The results showed for a nationally representative sample of 221 grass-based Irish dairy farms in 2012 that gross profit averaged €0.18/L of milk and €1,758/ha and gross income was €40,899/labor unit. Net profit averaged €0.08/L of milk and €750/ha and net income averaged €18,125/labor unit. However, significant variability was noted in farm performance across each financial output measure. For instance, net margin per hectare of the top one-third of farms was 6.5 times higher than the bottom third. Financial performance measures were inversely correlated with the CF of milk, which averaged 1.20kg of CO2-eq/kg of FPCM but ranged from 0.60 to 2.13kg of CO2-eq/kg of FPCM. Partial least squares regression analysis of correlations between financial and environmental performance indicated that extending the length of the grazing season and increasing milk production per hectare or per cow reduced the CF of milk and increased farm profit. However, where higher milk production per hectare was associated with greater concentrate feeding, this adversely affected the CF of milk and economic performance by increasing both costs and off-farm emissions. Therefore, to mitigate the CF of milk and improve economic performance, grass-based dairy farms should not aim to only increase milk output, but instead target increasing milk production per hectare from grazed grass.

Carbon footprint of milk from sheep farming systems in Northern Spain including soil carbon sequestration in grasslands

The link between climate change and livestock production has made carbon footprint based on life cycle assessment a world-wide indicator to assess and communicate the amount of greenhouse gases emitted per unit of product. Nevertheless, the majority of studies have not included soil carbon sequestration in the carbon footprint calculations. Especially in grasslands, soil carbon sequestration might be a potential sink to mitigate greenhouse gas emissions in the livestock sector. However, there is no commonly accepted methodology on how to include soil carbon sequestration in carbon footprint calculations. In this study, the carbon footprint of sheep milk was estimated from 12 farms in Northern Spain. Before taken into account contribution from soil carbon sequestration in the calculation, the carbon footprint values varied from 2.0 to 5.2 kg CO2 eq. per kg Fat and Protein Corrected Milk (FPCM). Milk from semi-intensive systems with foreign breeds kept indoors had significantly lower carbon footprint than milk from semi-extensive systems with local breeds and grazing in mountain uplands during summer. However, no difference was found in the carbon footprint of sheep milk from different systems and breeds when soil carbon sequestration was included in the calculations. Four different approaches to estimate and include soil carbon sequestration in the carbon footprint calculations were tested. This study highlights the importance of including soil carbon sequestration in the carbon footprint calculations. Furthermore, it highlights the climate mitigation potential of the grazing systems.

Integration of ecosystem services into the carbon footprint of milk of South German dairy farms

Allocation of greenhouse gas emissions (GHG) in Life Cycle Assessments (LCA) is challenging especially when multi-functionality of dairy farms, which do not only produce milk but also meat is considered. Moreover, some farms fulfill a wide range of additional services for society such as management of renewable natural resources as well as preservation of biodiversity and cultural landscapes. Due to the increasing degradation of ecosystems many industrialized as well as developing countries designed payment systems for environmental services.This study examines different allocation methods of GHG for a comparatively large convenience sample of 113 dairy farms located in grassland-based areas of southern Germany. Results are carbon footprints of 1.99 kg CO2eq/kg of fat and protein corrected milk (FPCM) on average if “no allocation” for coupled products is performed. “Physical allocation” results in 1.53 kg CO2eq/kg FPCM and “conventional economic allocation” in 1.66 kg CO2eq/kg FPCM on average if emissions are apportioned between milk and meat. Economic allocation which includes ecosystem services for society based on the farm net income as a new aspect in this study results in a carbon footprint of 1.5 kg CO2eq/kg FPCM on average. System expansion that puts greater emphasis on coupled beef production accounts for a carbon footprint of 0.68 kg CO2eq/kg FPCM on average.Intense milk production systems with higher milk yields show better results based on “no allocation”, “physical allocation” and “conventional economic allocation”. By contrast, economic allocation, which takes into account ecosystem services favors extensive systems, especially in less favored areas. This shows that carbon footprints of dairy farms should not be examined one-dimensionally based on the amount of milk and meat that is produced on the farm. Rather, a broader perspective is necessary that takes into account the multi-functionality of dairy farms especially in countries where a wide range of ecosystem services is provided.

Carbon footprints of food production in China (1979–2009)

A carbon footprint accounting of food production is useful for acquainting policy makers with both the potentials and the challenges of GHG mitigation in agriculture. In this study, a hybrid Economic Input-Output and Life Cycle Assessment (EIO-LCA) model was developed to investigate the carbon footprint of Chinese food production from 1979 to 2009. The change patterns and compositions of emission sources, impacts of urbanization, carbon footprint and carbon emission factors of 15 food types were examined. Research results indicate that the total carbon footprint of food production had doubled in those three decades, alongside rapid urbanization. The emission sources showing the most dramatic increases were synthetic fertilizer, direct energy use, enteric fermentation and manure management. Among all types of food, the carbon footprint of rice production increased most, and the carbon footprint of milk, bovine meat, fruit and vegetable production also grew rapidly due to increasing yields. There was an overall decreasing trend for carbon emission factors of rice, vegetable, fruit and animal-food production from 1979 to 2009. Notably, the carbon emission factors of most vegetable food production rebounded after hitting bottom in 1999 due principally to enhanced agricultural input. Compared with the U.S.A., China had a higher ratio of indirect carbon footprint in its food production system, which showed high material input and energy intensity. China had smaller carbon emission factors from rice and pigmeat production, but larger carbon emission factors from bovine meat production than the U.S.A., indicating the relative strengths and weaknesses of Chinese food-production technology. Mitigation solutions rely upon better balancing the dietary structure, improving the productivity of animal foods, and reducing agricultural inputs, especially synthetic fertilizer.

An appraisal of carbon footprint of milk from commercial grass-based dairy farms in Ireland according to a certified life cycle assessment methodology

PurposeLife cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass-based farms are usually limited to small numbers of farms (<30) and rarely certified to international standards, e.g. British Standards Institute publicly available specification 2050 (PAS 2050). The goals of this study were to quantify CF of milk from a large sample of grass-based farms using an accredited PAS 2050 method and to assess the relationships between farm characteristics and CF of milk.Materials and methodsData was collected annually using on-farm surveys, milk processor records and national livestock databases for 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fed into a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model in CO2 equivalents (CO2-eq) and allocated economically between dairy farm products, except exported crops. Carbon footprint of milk was estimated by expressing GHG emissions attributed to milk per kilogram of fat and protein-corrected milk (FPCM). The Carbon Trust tested the LCA model for non-conformities with PAS 2050. PAS 2050 certification was achieved when non-conformities were fixed or where the effect of all unresolved non-conformities on CF of milk was < ±5 %.Results and discussionThe combined effect of LCA model non-conformities with PAS 2050 on CF of milk was <1 %. Consequently, PAS 2050 accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO2-eq/kg of FPCM, but varied from 0.87 to 1.72 kg of CO2-eq/kg of FPCM. Although some farm attributes had stronger relationships with CF of milk than the others, no attribute accounted for the majority of variation between farms. However, CF of milk could be reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacement rate (R 2 = 0.75). Management changes can be applied simultaneously to improve each of these traits. Thus, grass-based farmers can potentially significantly reduce CF of milk.ConclusionsThe certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approach to quantify CF of milk at a farm or national level. The application of the certified model highlighted a wide range between the CF of milk of commercial farms. However, differences between farms’ CF of milk were explained by variation in various aspects of farm performance. This implies that improving farm efficiency can mitigate CF of milk.