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.     

Consequential LCA of switching from maize silage-based to grass-based dairy systems

Purpose

This study aimed to investigate the environmental consequences (on climate change and land use) of an increase in preference for grass-based milk in France using a consequential life cycle assessment (CLCA) approach. This increase in preference was assumed to be satisfied domestically, by converting maize silage-based dairy farms (MS farm) to grass-based dairy farms (G farm) while keeping on-farm usable agricultural area and total milk production of farm constant.

Methods

The possible consequences of an increase in preference for grass-based milk were identified based on cause and effect relationships. The conversion from MS to G farm reduced the use of soybean meal, changed the on-farm cropping pattern and produced more animals but less wheat and no rapeseed. Effects on on-farm soil C were predicted with the RothC model and on global land use change (LUC) with models of global agricultural markets (Global Trade Analysis Project (GTAP) and Landbouw Economisch Instituut Trade Analysis Project (LEITAP)). System expansion using animals from a suckler beef production system was applied to estimate the impacts of milk and animal co-products from the dairy system. Land occupation and climate change impacts were estimated. The consequences of farm conversion were attributed only to the milk, as preference for grass-based milk drove the conversion process.

Results and discussion

The conversion from the MS to G farm increases land occupation and climate change impacts for the G farm, respectively, by 9 and 7 % according to GTAP and 14 and 51 % according to LEITAP. Land occupation and climate change impacts of milk produced by the G farm after conversion increased, respectively, by 82 and 13 % with GTAP and 123 and 97 % with LEITAP relative to those for the MS farm (before conversion). The production of additional wheat and rapeseed outside the G farm increased impacts of the G farm (by 29–69 % depending on impacts and model used). Results indicate that the farm conversion would probably have consequences on global LUC and that it is important to account for this in a LCA approach.

Conclusions

Land use and land use change (LULUC) contributed to the impacts of grass-based milk, and results were highly sensitive to the LULUC model used. The many possible chain-of-event pathways that follow a change in preference for a given product yield high uncertainty in CLCA results. This study only assessed one possible way to meet the increase in preference for grass-based milk; it is necessary to perform a sensitivity analysis to investigate other possible scenarios resulting from this increase in preference.     

The effect of local climate and soil drainage on the environmental impact of grass-based milk production

Purpose

System modelling and life cycle assessment (LCA) were used to assess the climate change, acidification and eutrophication impacts of milk production using spring calving pasture-based system. The objective of the study was to evaluate the effect of climate and soil resources on the environmental impact per unit milk produced at the farm gate from low-cost, grass-based rotational-grazing dairy production.

Methods

A dairy system model, Dairy_sim, designed to identify optimum grass-based spring calving production systems considering the interaction between climate and soil resources was tested using the Irish National Dairy Blueprint and then used to assess regional differences of system management with well, moderately, mixed moderately-poorly and poorly drained soil resources available. Life cycle assessment was used to quantify environmental impacts of climate and soil drainage status. The Dairy_sim output was used as activity data for the LCA model.

Results and discussion

Differences were found in the management tactics influenced by climate and drainage resource. The impact of poor drainage reduced stocking rate, increased housing time and had greater need for later cut silage and more reliance on silage. Climate change, acidification and eutrophication impacts were greater for optimum management on poorly drained soil. The climate change ranged from 1.06 kg CO₂ eq./kg (well drained) to 1.18 kg CO₂ eq./kg (poorly drained) of energy corrected milk (ECM). The acidification and eutrophication ranged from 3.87 to 6.85 g SO₂ eq./kg ECM and 2.69 to 3.64 g PO₄ eq./kg ECM, respectively. Around 50% of poorly drained soil resource can be easily accommodated in dairy systems with little increase in environmental impact, where poor drained portion is utilised for silage.

Conclusions

LCA combined with a system optimization model revealed how dairy farm management practises constrained by poor land resource increased the environmental impact per unit product.

     

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.

     

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO₂ equivalents per ton of fat-and-protein-corrected milk (kg CO₂e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO₂e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO₂e/t FPCM for cows with one case of CM, by 69 kg CO₂e/t FPCM for cows with two cases of CM and by 92 kg CO₂e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.     

Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

Purpose

Various approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.

Methods

We applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.

Results and discussion

The typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.

Conclusions

This approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

     

Assessing environmental impacts associated with freshwater consumption along the life cycle of animal products: the case of Dutch milk production in Noord-Brabant

Purpose

The assessment of water footprints of a wide range of products has increased awareness on preserving freshwater as a resource. The water footprint of a product was originally defined by Hoekstra and Hung (2002) as the sum of the volumetric water use in terms of green, blue and grey water along the entire life cycle of a product and, as such, does not determine the environmental impact associated with freshwater use. Recently, several papers were published that describe building blocks that enable assessment of the site-specific environmental impact associated with freshwater use along the life cycle of a global food chain, such as the impact on human health (HH), ecosystem quality (EQ) or resource depletion (RD). We integrated this knowledge to enable an assessment of the environmental impact associated with freshwater use along the life cycle of milk production, as a case for a global food chain.

Material and methods

Our approach innovatively combined knowledge about the main impact pathways of freshwater use in life cycle assessment (LCA), knowledge about site-specific freshwater impacts and knowledge about modelling of irrigation requirements of global feed crops to assess freshwater impacts along the life cycle of milk production. We evaluated a Dutch model farm situated on loamy sand in the province of Noord-Brabant, where grass and maize land is commonly irrigated.

Results and discussion

Production of 1 kg of fat-and-protein corrected milk (FPCM) on the model farm in Noord-Brabant required 66 L of consumptive water. About 76 % of this water was used for irrigation during roughage cultivation, 15 % for production of concentrates and 8 % for drinking and cleaning services. Consumptive water use related to production of purchased diesel, gas, electricity and fertiliser was negligible (i.e. total 1 %). Production of 1 kg of FPCM resulted in an impact on HH of 0.8?×?10^?9 disability adjusted life years, on EQ of 12.9?×?10^?3 m²?×?year and on RD of 6.7 kJ. The impact of producing this kilogram of FPCM on RD, for example, was caused mainly by cultivation of concentrate ingredients, and appeared lower than the average impact on RD of production of 1 kg of broccoli in Spain.

Conclusions

Integration of existing knowledge from diverse science fields enabled an assessment of freshwater impacts along the life cycle of a global food chain, such as Dutch milk production, and appeared useful to determine its environmental hotspots. Results from this case study support earlier findings that LCA needs to go beyond simple water volume accounting when the focus is on freshwater scarcity. The approach used, however, required high-resolution inventory global data (i.e. especially regarding crop yield, soil type and root depth), and demonstrated a trade-off between scientific quality of results and applicability of the assessment method.     

Soil organic matter accounting in the carbon footprint analysis of the wine chain

Purpose

Concerns about global warming led to the calculation of the carbon footprint (CF) left by human activities. The agricultural sector is a significant source of greenhouse gas (GHG) emissions, though cropland soils can also act as sinks. So far, most LCA studies on agricultural products have not considered changes in soil organic matter (SOM). This paper aimed to: (1) integrate the Hénin–Dupuis SOM model into the CF study and (2) outline the impacts of different vineyard soil management scenarios on the overall CF.

Methods

A representative wine chain in the Maremma Rural District, Tuscany (Italy), made up of a cooperative winery and nine of its associated farms, was selected to investigate the production of a non-aged, high-quality red wine. The system boundary was established from vineyard planting to waste management after use. The functional unit (FU) chosen for this study was a 0.75-L bottle of wine, and all data refer to the year 2009. The SOM balance, based on Hénin–Dupuis’ equation, was integrated and run using GaBi4 software. A sensitivity analysis was performed, and four scenarios were developed to assess the impact of vineyard soil management types with decreasing levels of organic matter inputs.

Results and discussion

SOM accounting reduced the overall CF of one wine bottle from 0.663 to 0.531 kg CO₂-eq/FU. The vineyard planting sub-phase produced a loss of SOM while, in the pre-production and production sub-phases, the loss/accumulation of SOM was related to the soil management practices. On average, soil management in the production sub-phase led to a net accumulation of SOM, and the overall vineyard phase was a sink of CO₂. Residue incorporation and grassing were identified as the main factors affecting changes in SOM in vineyard soils.

Conclusions

Our results showed that incorporating SOM accounting into the wine chain’s CF analysis changed the vineyard phase from a GHG source to a modest net GHG sink. These results highlighted the need to include soil C dynamics in the CF of the agricultural product. Here, the SOM balance method proposed was sensitive to changes in management practices and was site specific. Moreover, we were also able to define a minimum data set for SOM accounting. The EU recognises soil carbon sequestration as one of the major European strategies for mitigation. However, specific measures have yet to be included in the CAP 2020. It would be desirable to include soil in the new ISO 14067—Carbon Footprint of Products.     

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.     

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.     

Environmental life cycle assessment of a dairy product: the yoghurt

Purpose

The dairy sector covers multiple activities related to milk production and treatment for alimentary uses. Different dairy products are available in the markets, with yoghurt being the second most important in terms of production. The goal of this study was to analyse from a cradle-to-grave approach the environmental impacts and energy balance derived from the yoghurt (solid, stirred and drinking yoghurts) manufacture process in a specific dairy factory processing 100 % Portuguese raw milk.

Methods

The standard framework of life cycle assessment (LCA) was followed and inventory data were collected on site in the dairy factory and completed using the literature and databases. The following impact categories were evaluated adopting a CML method: abiotic depletion (ADP), acidification (AP), eutrophication (EP), global warming (GWP), ozone layer depletion (ODP), land competition (LC) and photochemical oxidants formation (POFP), with the energy analysis carried out based on the cumulative non-renewable fossil and nuclear energy demand (CED). A mass allocation approach was considered for the partitioning of the environmental burdens between the different products obtained since not only yoghurts are produced but also dairy fodder.

Results and discussion

The key processes from an environmental point of view were identified. Some of the potential results obtained were in line with other specific related studies where dairy systems were assessed from an LCA perspective. The production of the milk-based inputs (i.e. raw milk, concentrated and powdered milk) was the main factor responsible of the environmental loads and energy requirements, with remarkable contributions of 91 % of AP, 92 % of EP and 62 % of GWP. Other activities that have important environmental impacts include the production of the energy requirements in the dairy factory, packaging materials production and retailing. Potential alternatives were proposed in order to reduce the contributions to the environmental profile throughout the life cycle of the yoghurt. These alternatives were based on the minimisation of milk losses, reductions of distances travelled and energy consumption at retailing and household use, as well as changes to the formulation of the animal feed. All of these factors derived from light environmental reductions.

Conclusions

The main reductions of the environmental impact derived from yoghurt production can be primarily obtained at dairy farms, although important improvements could also be made at the dairy factory.     

Carbon sequestration in LCA,a proposal for a new approach based on the global carbon cycle; cases on wood and on bamboo

Purpose

There are many recent proposals in life cycle assessment (LCA) to calculate temporary storage of carbon in bio-based products. However, there is still no consensus on how to deal with the issue. The main questions are: how do these proposals relate to each other, to what extent are they in line with the classical LCA method (as defined in ISO 14044) and the global mass balances as proposed by the IPCC, and is there really a need to introduce a discounting system for delayed CO₂ emissions?

Methods

This paper starts with an analysis of the widely applied specification of PAS 2050 and the ILCD Handbook, both specifying the credit for carbon sequestration as ‘optional’ in LCA. From this analysis, it is concluded that these optional calculations give rather different results compared to the baseline LCA method. Since these optional calculations are not fully in line with the global carbon mass balances, a new calculation method is proposed. To validate the new method, two cases (one on wood and one bamboo products) are given. These cases show the practical application and the consequences of the new approach. Finally, the main issue is evaluated and discussed: is it a realistic approach to allocate less damage to the same emission, when it is released later in time?

Results and discussion

This paper proposes a new approach based on the global carbon cycle and land-use change, translated to the level of individual products in LCA. It is argued that only a global growth of forest area and a global growth of application of wood in the building industry contribute to extra carbon sequestration, which might be allocated as a credit to the total market of wood products in LCA. This approach is different from approaches where temporary storage of carbon in trees is directly allocated to a product itself.

Conclusions

In the proposed approach, there seems to be no need for a discounting system of delayed CO₂ emissions. The advantage of wood and wood-based products can be described in terms of land-use change on a global scale in combination with a credit for heat recovery at the end-of-life (if applicable).     

Social life cycle assessment of average Irish dairy farm

Purpose

The majority of sustainability studies of dairy farms focused on environmental performance and profitability; however, social aspect has been hardly assessed. This study aims to investigate the social impacts of dairy farm via a case study using a social life cycle assessment framework.

Methods

The assessment was carried out applying the social LCA Guideline by UNEP-SETAC. Nineteen suitable social indicators were selected from four stakeholder categories of the guideline. Characterization and normalization were further developed based on data availability. National farm survey data was used as foreground data for farm activities, supplemented with background data from public database and life cycle working environment (LCWE) data by Gabi database. All indicators were divided into three groups: functional unit-related quantitative indicators, non-functional unit-related quantitative indicators and semi-quantitative indicators.

Results and discussion

Irish dairy farming has positive social impacts on value chain actors and society, predominantly positive impacts for local community and generally positive values for workers. The main negative impacts are health and safety issue, equal opportunity for workers, and safe and healthy living conditions for the local community. Possible actions to improve the social performance include introducing more efficient and robotic milk production systems; applying better handling methods and using real time decision support to operational management for emissions reduction.

Conclusions

This study is the first attempt of social LCA in Ireland. It demonstrated a possible method to carry out SLCA for Irish dairy sector. The results identified the positive and negative social hotspot of dairy farm with recommendation for future improvement.

     

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.     

Including CO<Subscript>2</Subscript>-emission equivalence of changes in land surface albedo in life cycle assessment. Methodology and case study on greenhouse agriculture

Purpose  

Climate change impacts in life cycle assessment (LCA) are usually assessed as the emissions of greenhouse gases expressed with the global warming potential (GWP). However, changes in surface albedo caused by land use change can also contribute to change the Earth’s energy budget. In this paper we present a methodology for including in LCA the climatic impacts of land surface albedo changes, measured as CO₂-eq. emissions or emission offsets.     

Climate change impacts on life cycle greenhouse gas (GHG) emissions savings of biomethanol from corn and soybean

Purpose

The purpose of this study is to assess and calculate the potential impacts of climate change on the greenhouse gas (GHG) emissions reduction potentials of combined production of whole corn bioethanol and stover biomethanol, and whole soybean biodiesel and stalk biomethanol. Both fuels are used as substitutes to conventional fossil-based fuels. The product system includes energy crop (feedstock) production and transportation, biofuels processing, and biofuels distribution to service station.

Methods

The methodology is underpinned by life cycle thinking. Crop system model and life cycle assessment (LCA) model are linked in the analysis. The Decision Support System for Agrotechnology Transfer – crop system model (DSSAT-CSM) is used to simulate biomass and grain yield under different future climate scenarios generated using a combination of temperature, precipitation, and atmospheric CO₂. Historical weather data for Gainesville, Florida, are obtained for the baseline period (1981–1990). Daily minimum and maximum air temperatures are projected to increase by +2.0, +3.0, +4.0, and +5.0 °C, precipitation is projected to change by ±20, 10, and 5 %, and atmospheric CO₂ concentration is projected to increase by +70, +210, and +350 ppm. All projections are made throughout the growing season. GaBi 4.4 is used as primary LCA modelling software using crop yield data inputs from the DSSAT-CSM software. The models representation of the physical processes inventory (background unit processes) is constructed using the ecoinvent life cycle inventory database v2.0.

Results and discussion

Under current baseline climate condition, net greenhouse gas (GHG) emissions savings per hectare from corn-integrated biomethanol synthesis (CIBM) and soybean-integrated biomethanol synthesis (SIBM) were calculated as ?8,573.31 and ?3,441 kg CO₂-eq. ha^?1 yr^?1, respectively. However, models predictions suggest that these potential GHG emissions savings would be impacted by changing climate ranging from negative to positive depending on the crop and biofuel type, and climate scenario. Increased atmospheric level of CO₂ tends to minimise the negative impacts of increased temperature.

Conclusions

While policy measures are being put in place for the use of renewable biofuels driven by the desire to reduce GHG emissions from the use of conventional fossil fuels, climate change would also have impacts on the potential GHG emissions reductions resulting from the use of these renewable biofuels. However, the magnitude of the impact largely depends on the biofuel processing technology and the energy crop (feedstock) type.     

How does co-product handling affect the carbon footprint of milk? Case study of milk production in New Zealand and Sweden

Purpose  

This paper investigates different methodologies of handling co-products in life cycle assessment (LCA) or carbon footprint (CF) studies. Co-product handling can have a significant effect on final LCA/CF results, and although there are guidelines on the preferred order for different methods for handling co-products, no agreed understanding on applicable methods is available. In the present study, the greenhouse gases (GHG) associated with the production of 1 kg of energy-corrected milk (ECM) at farm gate is investigated considering co-product handling.     

Regional carbon footprint analysis of dairy feeds for milk production in the USA

Purpose

A greenhouse gas emissions analysis (carbon footprint) was conducted for cultivation, harvesting, and production of common dairy feeds used for the production of dairy milk in the USA. The goal was to determine the carbon footprint (grams CO₂ equivalents (gCO₂e)/kg of dry feed) in the USA on a regional basis, identify key inputs, and make recommendations for emissions reduction.

Methods

Commonly used dairy feeds in the USA, such as soybeans, alfalfa, corn, and others, were identified based on a recent literature review and information from dairy farm surveys. The following input data for the cultivation and harvesting of dairy feeds were collected for five US regions: crop production data, energy input, soil amendments, and crop protection chemicals. Life cycle inventory input data were mainly collected from the US Department of Agriculture National Agricultural Statistical Service on a state-by-state basis as well as from state extension services forage crop budget estimates. In addition to consulting other life cycle assessment studies and published articles and reports, this cradle-to-farm gate carbon footprint analysis was conducted using the Ecoinvent? unit processes in SimaPro version 7.1? (PRé Consultants 2009).

Results

The final carbon footprint results (gCO₂e/kg of dry dairy feed) varied regionally depending on a number of factors such as lime and fertilizer application rates. The average national US carbon footprint results of the main feeds were: corn grain (390), corn silage (200), dried distillers grains with solubles (910 dry mill, 670 wet mill), oats (850), soybeans (390), soybean meal (410), winter wheat (430), alfalfa hay (170), and forage mix (160).

Conclusions and recommendations

The southeast dairy region generally showed a relatively high level of carbon footprint for most feeds, and this is attributable to the higher application rates of both synthetic fertilizers and lime. The highest contributor to carbon footprint for most regions (apart from soybeans and soybean meal) was due to the application of inorganic nitrogen fertilizer. Efficient transfer of knowledge to farmers with regards to fertilizer best management practices such as precision application of farm nutrients may contribute significantly to reducing regional crop carbon footprints.     

Evaluating the carbon footprint of Chilean organic blueberry production

Purpose

Chile is the second largest blueberry producer and exporter worldwide. At the global level, there is a lack of information by means of field data about greenhouse gas emissions from organic cultivation of this fruit. This study obtains a resource use inventory and assesses the cradle-to-farm gate carbon footprint (CF) of organic blueberry (Vaccinium corymbosum) production in the main cultivation area of Chile in order to identify CF key factors and to provide improvement measures.

Methods

The method used in this study follows the ISO 14040 framework and the main recommendations in the PAS 2050 guide as well as its specification for horticultural products PAS 2050-1. Primary data were collected for three consecutive production seasons from five organic Chilean blueberry orchards and calculations conducted with the GaBi 4 software. Agricultural factors such as fertilizers, pesticides, fossil fuels, electricity, materials, machinery, and direct land use change (LUC) are included. Only three orchards present direct LUC.

Results and discussion

The direct LUC associated with the conversion from annual crops to perennial crops is a key factor in the greenhouse gas removals from the orchards. When accounting for direct LUC, the CF of organic blueberry production in the studied orchards ranges from removals (reported as negative value) of ?0.94 to emissions of 0.61 kg CO₂-e/kg blueberry. CF excluding LUC ranges from 0.27 to 0.69 kg CO₂-e/kg blueberry. The variability in the results of the orchards suggests that the production practices have important effects on the CF. The factors with the greatest contribution to the greenhouse emissions are organic fertilizers followed by energy use causing, on average, 50 and 43 % of total emissions, respectively.

Conclusions

The CF of the organic blueberry orchards under study decreases significantly when taking into account removals related to LUC. The results highlight the importance of reporting separately the greenhouse gas (GHG) emissions from LUC. The CF of blueberry production could be reduced by optimizing fertilizer application, using cover crops and replacing inefficient tractors and large irrigation pumps. The identification of improvement measures would be a useful guide for changing grower practices.

     

Potential for optimized production and use of rapeseed biodiesel. Based on a comprehensive real-time LCA case study in Denmark with multiple pathways

Purpose

Several factors contribute to the current increased focus on alternative fuels such as biodiesel, including an increasing awareness of the environmental impact of petrochemical (PC) oil products such as PC diesel, the continuously increasing price of PC oil, and the depletion of PC oil. For these reasons, the European Union has enacted a directive requiring each member state to ensure that the share of energy from renewable sources in transport be at least 10 % of the final consumption of energy by 2020 (The European Parliament and the Council 2009). This LCA study assesses the specific environmental impacts from the production and use of biodiesel as it is today (real-time), based on rapeseed oil and different types of alcohols, and using technologies that are currently available or will be available shortly. Different options are evaluated for the environmental improvement of production methods. The modeling of the LCA is based on a specific Danish biodiesel production facility.

Methods

The functional unit is “1,000 km transportation for a standard passenger car.” All relevant process stages are included, such as rapeseed production including carbon sequestration and N₂O balances, and transportation of products used in the life cycle of biodiesel. System expansion has been used to handle allocation issues.

Results and discussion

The climate change potential from the production and use of biodiesel today is 57 kg CO₂-eq/1,000 km, while PC diesel is 214 kg CO₂-eq/1,000 km. Options for improvement include the increased use of residual straw from rapeseed fields for combustion in a power plant where carbon sequestration is considered, and a change in transesterification from a conventional process to an enzymatic process when using bioethanol instead of PC methanol. This research also evaluates results for land use, respiratory inorganics potential, human toxicity (carc) potential, ecotoxicity (freshwater) potential, and aquatic eutrophication (N) potential. Different sources for uncertainty are evaluated, and the largest drivers for uncertainty are the assumptions embedded into the substitution effects. The results presented should not be interpreted as a blueprint for the increased production of biodiesel but rather as a benchmarking point for the present, actual impact in a well-to-wheels perspective of biodiesel, with options for improving production and use.

Conclusions

Based on this analysis, we recommend investigating additional options and incentives regarding the increased use of rape straw, particularly considering the carbon sequestration issues (from the perspective of potential climate change) of using bioalcohol instead of PC alcohol for the transesterification process.