Reducing methane on-farm by feeding diets high in fat may not always reduce life cycle greenhouse gas emissions

Purpose

To consider whether feed supplements that reduce methane emissions from dairy cows result in a net reduction in greenhouse gas (GHG) intensity when productivity changes and emissions associated with extra manufacturing and management are included.

Methods

A life cycle assessment was undertaken using a model farm based on dairy farms in Victoria, Australia. The system boundary included the creation of farm inputs and on-farm activities up to the farm gate where the functional unit was 1 L of fat and protein corrected milk (FPCM). Electricity and diesel (scaled per cow), and fertiliser inputs (scaled on farm size) to the model farm were based on average data from a survey of farms. Fertiliser applied to crops was calculated per area of crop. Animal characteristics were based on available data from farms and literature. Three methane-reducing diets (containing brewers grain, hominy or whole cotton seed) and a control diet (cereal grain) were modelled as being fed during summer, with the control diet being fed for the remainder of the year in all cases.

Results and discussion

Greenhouse gas intensity (kg CO₂-eq/L FPCM) was lower than the control diet when the hominy (97 % compared with control) and brewers grain (98 %) diets were used but increased when the whole cottonseed diet was used (104 %). On-farm GHG emissions (kg CO₂-eq) were lower than the control diet when any of the methane-reducing diets were used (98 to 99.5 % of emissions when control diet fed). Diesel use in production and transport of feed supplements accounted for a large portion (63 to 93 %) of their GHG intensity (kg CO₂-eq/t dry matter). Adjusting fertiliser application, changing transport method, changing transport fuel, and using nitrification inhibitors all had little effect on GHG emissions or GHG intensity.

Conclusions

Although feeding strategies that reduce methane emissions from dairy cows can lower the GHG emissions up to the farm gate, they may not result in lower GHG intensities (g CO₂-eq/L FPCM) when pre-farm emissions are included. Both transport distance and the effect of the feed on milk production have important impacts on the outcomes.     

Production,partial cash flows and greenhouse gas emissions of simulated dairy herds with extended lactations

The transition period is the most critical period in the lactation cycle of dairy cows. Extended lactations reduce the frequency of transition periods, the number of calves and the related labour for farmers. This study aimed to assess the impact of 2 and 4 months extended lactations on milk yield and net partial cash flow (NPCF) at herd level, and on greenhouse gas (GHG) emissions per unit of fat- and protein-corrected milk (FPCM), using a stochastic simulation model. The model simulated individual lactations for 100 herds of 100 cows with a baseline lactation length (BL), and for 100 herds with lactations extended by 2 or 4 months for all cows (All+2 and All+4), or for heifers only (H+2 and H+4). Baseline lactation length herds produced 887 t (SD: 13) milk/year. The NPCF, based on revenues for milk, surplus calves and culled cows, and costs for feed, artificial insemination, calving management and rearing of youngstock, was k€174 (SD: 4)/BL herd per year. Extended lactations reduced milk yield of the herd by 4.1% for All+2, 6.9% for All+4, 1.1% for H+2 and 2.2% for H+4, and reduced the NPCF per herd per year by k€7 for All+2, k€12 for All+4, k€2 for H+2 and k€4 for H+4 compared with BL herds. Extended lactations increased GHG emissions in CO₂-equivalents per t FPCM by 1.0% for All+2, by 1.7% for All+4, by 0.2% for H+2 and by 0.4% for H+4, but this could be compensated by an increase in lifespan of dairy cows. Subsequently, production level and lactation persistency were increased to assess the importance of these aspects for the impact of extended lactations. The increase in production level and lactation persistency increased milk production of BL herds by 30%. Moreover, reductions in milk yield for All+2 and All+4 compared with BL herds were only 0.7% and 1.1% per year, and milk yield in H+2 and H+4 herds was similar to BL herds. The resulting NPCF was equal to BL for All+2 and All+4 and increased by k€1 for H+2 and H+4 due to lower costs for insemination and calving management. Moreover, GHG emissions per t FPCM were equal to BL herds or reduced (0% to −0.3%) when lactations were extended. We concluded that, depending on lactation persistency, extending lactations of dairy cows can have a positive or negative impact on the NPCF and GHG emissions of milk production.     

Implementing an appropriate metric for the assessment of greenhouse gas emissions from livestock production: A national case study

Livestock farming is of major economic relevance but also severely contributes to environmental impacts, especially greenhouse gas (GHG) emissions such as methane (CH₄; particularly from ruminant production) and nitrous oxide (N₂O; mainly from manure management and soil cultivated for feed production). In this study, we analyse the impact of GHG emissions from Austrian livestock production, using two metrics: a) the commonly used global warming potential (GWP) over 100 years (GWP₁₀₀ in CO₂-equivalents, CO₂-e), and b) the recently introduced metric GWP*, which describes additional warming as a function of the timeline of short-lived GHG emissions (unit CO₂ warming equivalents, CO₂-we). We first compiled the sectoral (i.e. only direct emissions without upstream processes) GWP₁₀₀ for different livestock categories with a focus on dairy cattle, beef cattle and pigs in Austria between 1990 and 2019. We also estimated product-related (i.e. per kg carcass weight or per litre of milk) GWP₁₀₀ values, including upstream processes. We then calculated the corresponding GWP* metrics, both sectoral and product-related, and compared them with the GWP₁₀₀ values. Decreasing livestock numbers and improved production efficiency were found to result in strong sectoral emission reductions from dairy production (–32 % of GWP₁₀₀ from 1990 to 2019) and from pigs (–32 % CO₂-e). This contrasts with low reductions from other livestock categories and even increases for cattle other than dairy cows (+3 % CO₂-e), mainly due to rising suckler cow numbers. Allocated results per kg milk and kg body mass show quite similar results. Using the GWP* metric, the climate impacts of Austrian livestock production are less severe. When assuming constant management and emission intensity over a period of at least 20 years, the CO₂-we (GWP*) is almost 50 % less than CO₂-e (GWP₁₀₀) per kg Austrian raw milk due to the different impacts of the short-lived CH₄. A similar trend applies to an average cattle carcass (-40 % warming impact). The emission reductions of the shrinking Austrian livestock population represent an important contribution to a climate-neutral agriculture: The CH₄ reductions of livestock production during the past 20 years reduce the current total Austrian CO₂-we by 16 %. Continuous CH₄ reduction, as we show it here for Austrian livestock, is an effective option to tackle the climate crisis in the short term. It shall be stressed that a relatively low GWP* should not be interpreted as a concession for further CH₄ emissions but as an actual reduction of (additional) warming.     

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

Purpose

Life 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 methods

Data 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 discussion

The 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.

Conclusions

The 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.     

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 0.10 kg CO₂e 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 0.63 kg CO₂e 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.     

Effect of improved nitrogen management on greenhouse gas emissions from intensive dairy systems in the Netherlands

Dairy systems in Europe contribute to the emissions of the greenhouse gases (GHGs) nitrous oxide (N₂O), methane (CH₄) and carbon dioxide (CO₂). In this paper, the effects of improved nitrogen (N) management on GHG emissions from Dutch dairy farms are determined. The GHG emissions are calculated using the panel on climate change (IPCC) methodology for the Netherlands, an updated and refined IPCC methodology, and a full accounting approach. The changes in dairy farming over the last 20 years, and the consequences for N management are described using detailed farm‐level data, collected in 1985, 1997 and 2002. The selected years represent distinct stages in the implementation of N policies. The changes in N management have reduced the GHG emissions. A reduction of the N surplus per kilogram milk with 1 g N reduced the GHG emissions per kilogram milk with approximately 29 g CO₂‐equivalents. The reduction of the N surpluses was mainly brought about by reduced fertilizer use and reduced grazing time. The use of updated and refined emission factors resulted in higher CH₄ emissions and lower N₂O emissions. On average, the overall emission was 36% higher with the refined method. Full accounting, including all direct and indirect emissions of CH₄, N₂O and CO₂, increased the emission with 36% compared with the refined IPCC methodology. We conclude that the N surplus at farm level is a useful indicator of GHG emissions. A full accounting system as presented in this study may effectively enable farmers to address the issue of emissions of GHGs in their operational management decisions. Both approaches serve their own specific objectives: full accounting at the farm level to explore mitigation options, and the IPCC methods to report changes in GHG emissions at the national level.     

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.     

Does increasing milk yield per cow reduce greenhouse gas emissions? A system approach

Milk yield per cow has continuously increased in many countries over the last few decades. In addition to potential economic advantages, this is often considered an important strategy to decrease greenhouse gas (GHG) emissions per kg of milk produced. However, it should be considered that milk and beef production systems are closely interlinked, as fattening of surplus calves from dairy farming and culled dairy cows play an important role in beef production in many countries. The main objective of this study was to quantify the effect of increasing milk yield per cow on GHG emissions and on other side effects. Two scenarios were modelled: constant milk production at the farm level and decreasing beef production (as co-product; Scenario 1); and both milk and beef production kept constant by compensating the decline in beef production with beef from suckler cow production (Scenario 2). Model calculations considered two types of production unit (PU): dairy cow PU and suckler cow PU. A dairy cow PU comprises not only milk output from the dairy cow, but also beef output from culled cows and the fattening system for surplus calves. The modelled dairy cow PU differed in milk yield per cow per year (6000, 8000 and 10 000 kg) and breed. Scenario 1 resulted in lower GHG emissions with increasing milk yield per cow. However, when milk and beef outputs were kept constant (Scenario 2), GHG emissions remained approximately constant with increasing milk yield from 6000 to 8000 kg/cow per year, whereas further increases in milk yield (10 000 kg milk/cow per year) resulted in slightly higher (8%) total GHG emissions. Within Scenario 2, two different allocation methods to handle co-products (surplus calves and beef from culled cows) from dairy cow production were evaluated. Results showed that using the 'economic allocation method', GHG emissions per kg milk decreased with increasing milk yield per cow per year, from 1.06 kg CO2 equivalents (CO2eq) to 0.89 kg CO2eq for the 6000 and 10 000 kg yielding dairy cow, respectively. However, emissions per kg of beef increased from 10.75 kg CO2eq to 16.24 kg CO2eq due to the inclusion of suckler cows. This study shows that the environmental impact (GHG emissions) of increasing milk yield per cow in dairy farming differs, depending upon the considered system boundaries, handling and value of co-products and the assumed ratio of milk to beef demand to be satisfied.     

Comparison of farm-level greenhouse gas emissions in transhumance and semi-intensive sheep production systems in continental rangelands

Despite their predominance worldwide, few studies have been conducted to look at the impact of sheep production systems relying on transhumance practices in arid and continental conditions, on farm-level greenhouse gas (GHG) emissions. Using Turkey as an example, this paper examines on farm-level GHG emissions calculated for two contrasting sheep production systems under arid and continental climate conditions. Production and management data were obtained through face-to-face interviews carried out on 10 transhumance and 15 semi-intensive meat sheep farms in Turkey. A total of seven GHG emission estimates were then calculated for each farm with the Agricultural Resource Efficiency Calculator (AgRECalc©) tool; i) total Carbon Dioxide (CO2) from energy use (kg CO2e), ii) total Carbon Dioxide equivalent (CO2e) from methane (kg CO2e), iii) total CO₂e from nitrous oxide (kg CO₂e), iv) whole farm and enterprise CO₂e emissions (kg CO₂e), v) net emission from land use (kg CO₂e), vi) whole farm CO₂e emissions per kg of farm output (kg CO₂e/kg output), vii) product CO₂e emissions (meat): kg CO₂e / kg live weight, and viii) farm output (kg of sheep). Multivariate analyses (using R software) were carried out to compare both farm types and their respective carbon emissions. The total farm output per ewe was lower in the transhumance farms (7.4 kg/ewe) than in the semi-intensive farms (7.7 kg/ewe). The kg CO₂e per kg of output was also lower for the transhumance farms (46.2 kg CO₂e) than for the semi-intensive ones (56.5 kg CO₂e). This trend was similar for the amount of CO₂e per kg of live weight produced (20.8 kg and 25.4 kg for the transhumance and the semi-intensive farms, respectively). Despite overall net emissions from land use being greater on average for the transhumance farms, once measured per hectare, they were found to be lower than those for the semi-intensive farms. This study provides a reference point for different sheep production systems’ GHG emission impact in continental rangelands in Turkey.     

Trends in greenhouse gas emissions from consumption and production of animal food products – implications for long-term climate targets

To analyse trends in greenhouse gas (GHG) emissions from production and consumption of animal products in Sweden, life cycle emissions were calculated for the average production of pork, chicken meat, beef, dairy and eggs in 1990 and 2005. The calculated average emissions were used together with food consumption statistics and literature data on imported products to estimate trends in per capita emissions from animal food consumption. Total life cycle emissions from the Swedish livestock production were around 8.5 Mt carbon dioxide equivalents (CO₂e) in 1990 and emissions decreased to 7.3 Mt CO₂e in 2005 (14% reduction). Around two-thirds of the emission cut was explained by more efficient production (less GHG emission per product unit) and one-third was due to a reduced animal production. The average GHG emissions per product unit until the farm-gate were reduced by 20% for dairy, 15% for pork and 23% for chicken meat, unchanged for eggs and increased by 10% for beef. A larger share of the average beef was produced from suckler cows in cow–calf systems in 2005 due to the decreasing dairy cow herd, which explains the increased emissions for the average beef in 2005. The overall emission cuts from the livestock sector were a result of several measures taken in farm production, for example increased milk yield per cow, lowered use of synthetic nitrogen fertilisers in grasslands, reduced losses of ammonia from manure and a switch to biofuels for heating in chicken houses. In contrast to production, total GHG emissions from the Swedish consumption of animal products increased by around 22% between 1990 and 2005. This was explained by strong growth in meat consumption based mainly on imports, where growth in beef consumption especially was responsible for most emission increase over the 15-year period. Swedish GHG emissions caused by consumption of animal products reached around 1.1 t CO₂e per capita in 2005. The emission cuts necessary for meeting a global temperature-increase target of 2° might imply a severe constraint on the long-term global consumption of animal food. Due to the relatively limited potential for reducing food-related emissions by higher productivity and technological means, structural changes in food consumption towards less emission-intensive food might be required for meeting the 2° target.     

Water footprint and economic water productivity assessment of eight dairy cattle farms based on field measurement

Water scarcity prevailing in the drylands is threatening the sustainability of livestock production systems. The water footprint (WF) indicator was proposed as a metric of water use. This study aimed to determine the WF and the economic water productivity (EWP) of 1 kg of fat and protein-corrected milk (FPCM) in eight dairy farms (n = 8; animals = 117 ± 62; area = 198 ± 127; 95% confidence level) in northern Tunisia. Then, to assess the effects of three simulation scenarios targeting the reduction of the WF of milk production (scenario A: using triticale silage to replace, on DM basis, the silage of maize, sorghum or ray-grass; scenario B: reducing by 56% the wastage of water devoted to milking, cooling, cleaning and servicing; scenario C: using concentrate feeds imported from Brazil and Argentina instead of that imported from France). A year-round monitoring of on-farm practices was performed using water-meters and recording equipment installed in key locations in the target dairy farms: (i) water used for feed production, (ii) cow watering, (iii) servicing water, (v) crop and forage production and (iv) economic and production performance were controlled by water source (green and blue). Over the eight farms evaluated, milk production consumed on average 1.36 ± 0.41 m³/kg FPCM, of which 0.93 ± 0.40 m³/kg FPCM was green water and 0.42 ± 0.30 m³/kg FPCM was blue water. However, virtual water of 1 kg FPCM averaged 43% ± 14.3%. Water used for feed production for lactating cows represents approximately 87% ± 6% of the total WF of milk production. However, drinking and servicing water contributed by 3.75% ± 2% and 9% ± 5% to the total WF of milk, respectively. The EWP assessment revealed that the selected dairy farms had a relatively small gross margin per m³ of water averaging US$ 0.05 ± 0.04. The variation in WF of milk was mainly associated with diets’ ingredients, which affected milk productivity and water consumption. Scenario analysis indicated that using feed with less water requirements or importing feeds from countries where its water consumption is low could reduce consumptive water use for milk production by up to 16%. The efficient use of servicing water could reduce blue WF of milk by up to 4%. The implementation of these measures would lead to potential total water savings in the Tunisian dairy sector of 646 million m³ per year (30%).     

Effects of nitrogen fertilisation rate and maturity of grass silage on methane emission by lactating dairy cows

Grass silage is typically fed to dairy cows in temperate regions. However, in vivo information on methane (CH₄) emission from grass silage of varying quality is limited. We evaluated the effect of two rates of nitrogen (N) fertilisation of grassland (low fertilisation (LF), 65 kg of N/ha; and high fertilisation (HF), 150 kg of N/ha) and of three stages of maturity of grass at cutting: early maturity (EM; 28 days of regrowth), mid maturity (MM; 41 days of regrowth) and late maturity (LM; 62 days of regrowth) on CH₄ production by lactating dairy cows. In a randomised block design, 54 lactating Holstein–Friesian dairy cows (168±11 days in milk; mean±standard error of mean) received grass silage (mainly ryegrass) and compound feed at 80 : 20 on dry matter basis. Cows were adapted to the diet for 12 days and CH₄ production was measured in climate respiration chambers for 5 days. Dry matter intake (DMI; 14.9±0.56 kg/day) decreased with increasing N fertilisation and grass maturity. Production of fat- and protein-corrected milk (FPCM; 24.0±1.57 kg/day) decreased with advancing grass maturity but was not affected by N fertilisation. Apparent total-tract feed digestibility decreased with advancing grass maturity but was unaffected by N fertilisation except for an increase and decrease in N and fat digestibility with increasing N fertilisation, respectively. Total CH₄ production per cow (347±13.6 g/day) decreased with increasing N fertilisation by 4% and grass maturity by 6%. The smaller CH₄ production with advancing grass maturity was offset by a smaller FPCM and lower feed digestibility. As a result, with advancing grass maturity CH₄ emission intensity increased per units of FPCM (15.0±1.00 g CH₄/kg) by 31% and digestible organic matter intake (33.1±0.78 g CH₄/kg) by 15%. In addition, emission intensity increased per units of DMI (23.5±0.43 g CH₄/kg) by 7% and gross energy intake (7.0±0.14% CH₄) by 9%, implying an increased loss of dietary energy with advancing grass maturity. Rate of N fertilisation had no effect on CH₄ emissions per units of FPCM, DMI and gross energy intake. These results suggest that despite a lower absolute daily CH₄ production with a higher N fertilisation rate, CH₄ emission intensity remains unchanged. A significant reduction of CH₄ emission intensity can be achieved by feeding dairy cows silage of grass harvested at an earlier stage of maturity.     

Carbon footprint and land requirement for dairy herd rations: impacts of feed production practices and regional climate variations

Feed production is a significant source of greenhouse gas (GHG) emissions from dairy production and demands large arable and pasture acreage. This study analysed how regional conditions influence GHG emissions of dairy feed rations in a life cycle perspective, that is the carbon footprint (CF) and the land area required. Factors assessed included regional climate variations, grass/clover silage nutrient quality, feedstuff availability, crop yield and feed losses. Using the Nordic feed evaluation model NorFor, rations were optimised for different phases of lactation, dry and growing periods for older cows, first calvers and heifers by regional feed advisors and combined to annual herd rations. Feed production data at farm level were based on national statistics and studies. CF estimates followed standards for life cycle assessment and used emissions factors provided by IPCC. The functional unit was ‘feed consumption to produce 1 kg energy corrected milk (ECM) from a cow with annual milk yield of 9 900 kg ECM including replacement animals and feed losses’. Feed ration CF varied from 417 to 531 g CO₂ e/kg ECM. Grass/clover silage contributed more than 50% of total GHG emissions. Use of higher quality silage increased ration CF by up to 5% as a result of an additional cut and increased rates of synthetic N-fertiliser. Domestically produced horse bean (Vicia faba), by-products from the sugar industry and maize silage were included in the rations with the lowest CF, but horse bean significantly increased ration land requirement. Rations required between 1.4 to 2 m² cropland and 0.1 to 0.2 m²/kg semi-natural grassland per kg ECM and year. Higher yield levels reduced ration total CF. Inclusion of GHG emissions from land use change associated with Brazilian soya feed significantly increased ration CF. Ration CF and land use depended on ration composition, which was highly influenced by the regional availability and production of feedstuffs. The impact of individual feedstuffs on ration CF varies due to, for example, cultivation practices and climate conditions and feedstuffs should therefore be assessed in a ration and regional perspective before being used to decrease milk CF. Land use efficiency should be considered together with ration CF, as these can generate goal conflicts.     

Accounting for inter-annual <Emphasis Type="Italic">variability</Emphasis> of farm activity data for calculation of greenhouse gas emissions in dairy farming

Purpose

This study examines the inter-annual variability of production data in an organic dairy farm and its effect on the estimation of product-related greenhouse gas emissions (GHG) using a detailed material flow model. It is believed that the examination of only one production year may not adequately reflect temporal representativeness and may therefore lead to unreliable results. The current study also provides a method to deal with variability when temporal representativeness cannot be ensured.

Methods

All material flows related to milk production from six consecutive milk years in an organic dairy farm in northern Germany were analysed. The milk yield of the 75 to 91 cows varied between 5418 and 7102 kg energy corrected milk (ECM) per cow and year. GHG emissions were estimated using calculation guidelines from the International Dairy Federation (IDF) and the Intergovernmental Panel on Climate Change (IPCC). Emissions were calculated in the Flow Analysis and Resource Management (FARM) model ensuring mass balances for nitrogen and phosphorous in every subsection of the model. Based on the variability of crop yields, the number of years for representative average data was calculated as well as an uncertainty when only a limited number of years was available.

Results and discussion

Estimated GHG emissions varied between 0.88 and 1.09 kg CO₂-eq kg^?1 ECM^?1 (mean, standard deviation of the mean = 0.97 and 0.07 kg CO₂-eq kg^?1 ECM^?1). Emissions from ruminant digestion had the highest contribution (50.9 ± 2.3) percent in relation to overall product-related GHG emissions. Direct emissions from soil showed the highest coefficient of variation (36%) due to simultaneous changes in fertilization amount, crop yield and milk yield which showed no significant direct relationship. The number of years needed to be assessed for representative average yields was between 27 and 215 years for clover grass and maize silage, respectively. When performing a sensitivity analysis based on the variability of crop yields, the assessed farm showed reliable results with average data of at least 4 years.

Conclusions

Temporal representativeness should be dealt with explicitly in GHG assessments for dairy farming. If the representativeness of crop yields cannot be ensured, an uncertainty bandwidth of the results based on variability of yields can provide a basis for comparing different farms or farming systems. This approach could also be extended to other variabilities in dairy farming for more reliability of results.

     

Farm-level emission intensities of smallholder cattle (Bos indicus; B. indicus–B. taurus crosses) production systems in highlands and semi-arid regions

Ruminants are central to the economic and nutritional life of much of sub-Saharan Africa, but cattle are now blamed for having a disproportionately large negative environmental impact through emissions of greenhouse gas (GHG). However, the mechanism underlying excessive emissions occurring only on some farms is imperfectly understood. Reliable estimates of emissions themselves are frequently lacking due to a paucity of reliable data. Employing individual animal records obtained at regular farm visits, this study quantified farm-level emission intensities (EIs) of greenhouse gases of smallholder farms in three counties in Western Kenya. CP was chosen as the functional unit to capture the outputs of both milk and meat. The results showed that milk is responsible for 80–85% of total CP output. Farm EI ranged widely from 20 to >1 000 kg CO₂-eq/kg CP. Median EIs were 60 (Nandi), 71 (Bomet), and 90 (Nyando) kg CO₂-eq/kg. Although median EIs referenced to milk alone (2.3 kg CO₂-eq/kg milk) were almost twice that reported for Europe, up to 50% of farms had EIs comparable to the mean Pan-European EIs. Enteric methane (CH₄) contributed >95% of emissions and manure ～4%, with negligible emissions attributed to inputs to the production system. Collecting data from individual animals on smallholder farms enabled the demonstration of extremely heterogeneous EI status among similar geographical spaces and provides clear indicators on how low EI status may be achieved in these environments. Contrary to common belief, our data show that industrial-style intensification is not required to achieve low EI. Enteric CH₄ production overwhelmingly drives farm emissions in these systems and as this is strongly collinear with nutrition and intake, an effort will be required to achieve an “efficient frontier” between feed intake, productivity, and GHG emissions.     

Relationships between methane emission of Holstein Friesian dairy cows and fatty acids,volatile metabolites and non-volatile metabolites in milk

This study investigated the relationships between methane (CH₄) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH₄ production was 406±37.0 g/day, CH₄ yield was 24.1±1.87 g/kg DMI and CH₄ intensity was 16.4±1.91 g/kg FPCM. The observed CH₄ emissions were compared with the CH₄ emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH₄ production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH₄ production and CH₄ yield, whereas for CH₄ intensity MFA, NV and V were all included. These models predicted CH₄ production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (C_b) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH₄ emission, and furthermore that including V (CH₄ intensity only) and NV increases the CH₄ emission prediction potential. This holds particularly for the prediction model for CH₄ intensity.     

Global environmental costs of China's thirst for milk

China has an ever‐increasing thirst for milk, with a predicted 3.2‐fold increase in demand by 2050 compared to the production level in 2010. What are the environmental implications of meeting this demand, and what is the preferred pathway? We addressed these questions by using a nexus approach, to examine the interdependencies of increasing milk consumption in China by 2050 and its global impacts, under different scenarios of domestic milk production and importation. Meeting China's milk demand in a business as usual scenario will increase global dairy‐related (China and the leading milk exporting regions) greenhouse gas (GHG) emissions by 35% (from 565 to 764 Tg CO_2eq) and land use for dairy feed production by 32% (from 84 to 111 million ha) compared to 2010, while reactive nitrogen losses from the dairy sector will increase by 48% (from 3.6 to 5.4 Tg nitrogen). Producing all additional milk in China with current technology will greatly increase animal feed import; from 1.9 to 8.5 Tg for concentrates and from 1.0 to 6.2 Tg for forage (alfalfa). In addition, it will increase domestic dairy related GHG emissions by 2.2 times compared to 2010 levels. Importing the extra milk will transfer the environmental burden from China to milk exporting countries; current dairy exporting countries may be unable to produce all additional milk due to physical limitations or environmental preferences/legislation. For example, the farmland area for cattle‐feed production in New Zealand would have to increase by more than 57% (1.3 million ha) and that in Europe by more than 39% (15 million ha), while GHG emissions and nitrogen losses would increase roughly proportionally with the increase of farmland in both regions. We propose that a more sustainable dairy future will rely on high milk demanding regions (such as China) improving their domestic milk and feed production efficiencies up to the level of leading milk producing countries. This will decrease the global dairy related GHG emissions and land use by 12% (90 Tg CO_2eq reduction) and 30% (34 million ha land reduction) compared to the business as usual scenario, respectively. However, this still represents an increase in total GHG emissions of 19% whereas land use will decrease by 8% when compared with 2010 levels, respectively.     

Cattle feed or bioenergy? Consequential life cycle assessment of biogas feedstock options on dairy farms

On‐farm anaerobic digestion (AD) of wastes and crops can potentially avoid greenhouse gas (GHG) emissions, but incurs extensive environmental effects via carbon and nitrogen cycles and substitution of multiple processes within and outside farm system boundaries. Farm models were combined with consequential life cycle assessment (CLCA) to assess plausible biogas and miscanthus heating pellet scenarios on dairy farms. On the large dairy farm, the introduction of slurry‐only AD led to reductions in global warming potential (GWP) and resource depletion burdens of 14% and 67%, respectively, but eutrophication and acidification burden increases of 9% and 10%, respectively, assuming open tank digestate storage. Marginal GWP burdens per Mg dry matter (DM) feedstock codigested with slurry ranged from –637 kg CO₂e for food waste to +509 kg CO₂e for maize. Codigestion of grass and maize led to increased imports of concentrate feed to the farm, negating the GWP benefits of grid electricity substitution. Attributing grass‐to‐arable land use change (LUC) to marginal wheat feed production led to net GWP burdens exceeding 900 kg CO₂e Mg^?1 maize DM codigested. Converting the medium‐sized dairy farm to a beef‐plus‐AD farm led to a minor reduction in GWP when grass‐to‐arable LUC was excluded, but a 38% GWP increase when such LUC was attributed to marginal maize and wheat feed required for intensive compensatory milk production. If marginal animal feed is derived from soybeans cultivated on recently converted cropland in South America, the net GWP burden increases to 4099 kg CO₂e Mg^?1 maize DM codigested – equivalent to 55 Mg CO₂e yr^?1 per hectare used for AD‐maize cultivation. We conclude that AD of slurry and food waste on dairy farms is an effective GHG mitigation option, but that the quantity of codigested crops should be strictly limited to avoid potentially large international carbon leakage via animal feed displacement.     

Livestock greenhouse gas emissions and mitigation potential in Europe

The livestock sector contributes considerably to global greenhouse gas emissions (GHG). Here, for the year 2007 we examined GHG emissions in the EU27 livestock sector and estimated GHG emissions from production and consumption of livestock products; including imports, exports and wastage. We also reviewed available mitigation options and estimated their potential. The focus of this review is on the beef and dairy sector since these contribute 60% of all livestock production emissions. Particular attention is paid to the role of land use and land use change (LULUC) and carbon sequestration in grasslands. GHG emissions of all livestock products amount to between 630 and 863 Mt CO₂e, or 12–17% of total EU27 GHG emissions in 2007. The highest emissions aside from production, originate from LULUC, followed by emissions from wasted food. The total GHG mitigation potential from the livestock sector in Europe is between 101 and 377 Mt CO₂e equivalent to between 12 and 61% of total EU27 livestock sector emissions in 2007. A reduction in food waste and consumption of livestock products linked with reduced production, are the most effective mitigation options, and if encouraged, would also deliver environmental and human health benefits. Production of beef and dairy on grassland, as opposed to intensive grain fed production, can be associated with a reduction in GHG emissions depending on actual LULUC emissions. This could be promoted on rough grazing land where appropriate.     

Intensification of dairy production can increase the GHG mitigation potential of the land use sector in East Africa

Sub‐Saharan Africa (SSA) could face food shortages in the future because of its growing population. Agricultural expansion causes forest degradation in SSA through livestock grazing, reducing forest carbon (C) sinks and increasing greenhouse gas (GHG) emissions. Therefore, intensification should produce more food while reducing pressure on forests. This study assessed the potential for the dairy sector in Kenya to contribute to low‐emissions development by exploring three feeding scenarios. The analyses used empirical spatially explicit data, and a simulation model to quantify milk production, agricultural emissions and forest C loss due to grazing. The scenarios explored improvements in forage quality (Fo), feed conservation (Fe) and concentrate supplementation (Co): FoCo fed high‐quality Napier grass (Pennisetum purpureum), FeCo supplemented maize silage and FoFeCo a combination of Napier, silage and concentrates. Land shortages and forest C loss due to grazing were quantified with land requirements and feed availability around forests. All scenarios increased milk yields by 44%–51%, FoCo reduced GHG emission intensity from 2.4 ± 0.1 to 1.6 ± 0.1 kg CO₂eq per kg milk, FeCo reduced it to 2.2 ± 0.1, whereas FoFeCo increased it to 2.7 ± 0.2 kg CO₂eq per kg milk because of land use change emissions. Closing the yield gap of maize by increasing N fertilizer use reduced emission intensities by 17% due to reduced emissions from conversion of grazing land. FoCo was the only scenario that mitigated agricultural and forest emissions by reducing emission intensity by 33% and overall emissions by 2.5% showing that intensification of dairy in a low‐income country can increase milk yields without increasing emissions. There are, however, risks of C leakage if agricultural and forest policies are not aligned leading to loss of forest to produce concentrates. This approach will aid the assessment of the climate‐smartness of livestock production practices at the national level in East Africa.