Christel Cederberg

System expansion and allocation in life cycle assessment of milk and beef production

Background, Goal and ScopeSystem expansion is a method used to avoid co-product allocation. Up to this point in time it has seldom been used in LCA studies of food products, although food production systems often are characterised by closely interlinked sub-systems. One of the most important allocation problems that occurs in LCAs of agricultural products is the question of how to handle the co-product beef from milk production since almost half of the beef production in the EU is derived from co-products from the dairy sector. The purpose of this paper is to compare different methods of handling co-products when dividing the environmental burden of the milk production system between milk and the co-products meat and surplus calves.Main FeaturesThis article presents results from an LCA of organic milk production in which different methods of handling the co-products are examined. The comparison of different methods of co-product handling is based on a Swedish LCA case study of milk production where economic allocation between milk and meat was initially used. Allocation of the co-products meat and surplus calves was avoided by expanding the milk system. LCA data were collected from another case study where the alternative way of producing meat was analysed, i.e. using a beef cow that produces one calf per annum to be raised for one and a half year. The LCA of beef production was included in the milk system. A discussion is conducted focussing on the importance of modelling and analysing milk and beef production in an integrated way when foreseeing and planning the environmental consequences of manipulating milk and beef production systems.ResultsThis study shows that economic allocation between milk and beef favours the product beef. When system expansion is performed, the environmental benefits of milk production due to its co-products of surplus calves and meat become obvious. This is especially connected to the impact categories that describe the potential environmental burden of biogenic emissions such as methane and ammonia and nitrogen losses due to land use and its fertilising. The reason for this is that beef production in combination with milk can be carried out with fewer animals than in sole beef production systems.Conclusion, Recommendation and PerspectiveMilk and beef production systems are closely connected. Changes in milk production systems will cause alterations in beef production systems. It is concluded that in prospective LCA studies, system expansion should be performed to obtain adequate information of the environmental consequences of manipulating production systems that are interlinked to each other.

Including Carbon Emissions from Deforestation in the Carbon Footprint of Brazilian Beef

Effects of land use changes are starting to be included in estimates of life-cycle greenhouse gas (GHG) emissions, so-called carbon footprints (CFs), from food production. Their omission can lead to serious underestimates, particularly for meat. Here we estimate emissions from the conversion of forest to pasture in the Legal Amazon Region (LAR) of Brazil and present a model to distribute the emissions from deforestation over products and time subsequent to the land use change. Expansion of cattle ranching for beef production is a major cause of deforestation in the LAR. The carbon footprint of beef produced on newly deforested land is estimated at more than 700 kg CO(2)-equivalents per kg carcass weight if direct land use emissions are annualized over 20 years. This is orders of magnitude larger than the figure for beef production on established pasture on non-deforested land. While Brazilian beef exports have originated mainly from areas outside the LAR, i.e. from regions not subject to recent deforestation, we argue that increased production for export has been the key driver of the pasture expansion and deforestation in the LAR during the past decade and this should be reflected in the carbon footprint attributed to beef exports. We conclude that carbon footprint standards must include the more extended effects of land use changes to avoid giving misleading information to policy makers, retailers, and consumers.

Variation in carbon footprint of milk due to management differences between Swedish dairy farms

To identify mitigation options to reduce greenhouse gas (GHG) emissions from milk production (i.e. the carbon footprint (CF) of milk), this study examined the variation in GHG emissions among dairy farms using data from previous CF studies on Swedish milk. Variations between farms in these production data, which were found to have a strong influence on milk CF, were obtained from existing databases of 1051 dairy farms in Sweden in 2005. Monte Carlo (MC) analysis was used to analyse the impact of variations in seven important parameters on milk CF concerning milk yield (energy-corrected milk (ECM) produced and delivered), feed dry matter intake (DMI), enteric CH4 emissions, N content in feed DMI, N-fertiliser rate and diesel used on farm. The largest between-farm variations among the analysed production data were N-fertiliser rate (kg/ha) and diesel used (l/ha) on farm (CV = 31% to 38%). For the parameters concerning milk yield and feed DMI, the CV was approximately 11% and 8%, respectively. The smallest variation in production data was found for N content in feed DMI. According to the MC analysis, these variations in production data led to a variation in milk CF of between 0.94 and 1.33 kg CO2 equivalents (CO2e)/kg ECM, with an average value of 1.13 kg CO2e/kg ECM. We consider that this variation of ±17%, which was found to be based on the used farm data, would be even greater if all Swedish dairy farms were included, as the sample of farms in this study was not totally unbiased. The variation identified in milk CF indicates that a potential exists to reduce GHG emissions from milk production on both the national and farm levels through changes in management. As milk yield and feed DMI are two of the most influential parameters for milk CF, feed conversion efficiency (i.e. units ECM produced/unit DMI) can be used as a rough key performance indicator for predicting CF reductions. However, it must be borne in mind that feeds have different CF due to where and how they are produced.

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.

Modeling Potential Freshwater Ecotoxicity Impacts Due to Pesticide Use in Biofuel Feedstock Production: The Cases of Maize, Rapeseed, Salix, Soybean, Sugar Cane, and Wheat

The inclusion of ecotoxicity impacts of pesticides in environmental assessments of biobased products has long been hampered by methodological challenges. We expanded the pesticide database and the regional coverage of the pesticide emission model PestLCI v.2.0, combined it with the impact assessment model USEtox, and assessed potential freshwater ecotoxicity impacts (PFEIs) of pesticide use in selected biofuel feedstock production cases, namely: maize (Iowa, US, two cases), rapeseed (Schleswig-Holstein, Germany), Salix (South Central Sweden), soybean (Mato Grosso, Brazil, two cases), sugar cane (São Paulo, Brazil), and wheat (Schleswig-Holstein, Germany). We found that PFEIs caused by pesticide use in feedstock production varied greatly, up to 3 orders of magnitude. Salix has the lowest PFEI per unit of energy output and per unit of cultivated area. Impacts per biofuel unit were 30, 750, and 1000 times greater, respectively, for the sugar cane, wheat and rapeseed cases than for Salix. For maize genetically engineered (GE) to resist glyphosate herbicides and to produce its own insecticidal toxin, maize GE to resist glyphosate, soybeans GE to resist glyphosate and conventional soybeans, the impacts were 110, 270, 305, and 310 times greater than for Salix, respectively. The significance of field and site-specific conditions are discussed, as well as options for reducing negative impacts in biofuel feedstock production.

An LCA researcher's wish list - data and emission models needed to improve LCA studies of animal production

The last decade has seen an increase in environmental systems analysis of livestock production, resulting in a significant number of studies with a holistic approach often based on life-cycle assessment (LCA) methodology. The growing public interest in global warming has added to this development; guidelines for carbon footprint (CF) accounting have been developed, including for greenhouse gas (GHG) accounting of animal products. Here we give an overview of methods for estimating GHG emissions, with emphasis on nitrous oxide, methane and carbon from land use change, presently used in LCA/CF studies of animal products. We discuss where methods and data availability for GHGs and nitrogen (N) compounds most urgently need to be improved in order to produce more accurate environmental assessments of livestock production. We conclude that the top priority is to improve models for N fluxes and emissions from soils and to implement soil carbon change models in LCA/CF studies of animal products. We also point at the need for more farm data and studies measuring emissions from soils, manure and livestock in developing countries.

Localising livestock protein feed production and the impact on land use and greenhouse gas emissions.

Livestock farmers in Sweden usually grow feed grains for livestock but import protein feed from outside Sweden. Aside from the economic implications, some environmental issues are associated with this practice. We used life cycle assessment to evaluate the impact of local protein feed production on land use and greenhouse gas emissions, compared with the use of imported protein feed, for pig meat and dairy milk produced in Sweden. Our results showed that local production reduced greenhouse gas emissions by 4.5% and 12%, respectively, for pigs and dairy cows. Land use for feed production in Sweden increased by 11% for pigs and 25% for dairy cows, but total land use decreased for pig production and increased for dairy milk production. Increased protein feed cultivation in Sweden decreased inputs needed for animal production and improved some ecological processes (e.g. nutrient recycling) of the farm systems. However, the differences in results between scenarios are relatively small and influenced to an extent by methodological choices such as co-product allocation. Moreover, it was difficult to assess the contribution of greenhouse emissions from land use change. The available accounting methods we applied did not adequately account for the potential land use changes and in some cases provided conflicting results. We conclude that local protein feed production presents an opportunity to reduce greenhouse gas emissions but at a cost of increasing land occupation in Sweden for feed production.

Climate metrics and the carbon footprint of livestock products: where’s the beef?

The livestock sector is estimated to account for 15% of global greenhouse gas (GHG) emissions, 80% of which originate from ruminant animal systems due to high emissions of methane (CH4) from enteric fermentation and manure management. However, recent analyses have argued that the carbon footprint (CF) of ruminant meat and dairy products are substantially reduced if one adopts alternative metrics for comparing emissions of GHGs-e.g., the 100 year global temperature change potential (GTP(100)), instead of the commonly used 100 year global warming potential (GWP(100))-due to a lower valuation of CH4 emissions. This raises the question of which metric to use. Ideally, the choice of metric should be related to a climate policy goal. Here, we argue that basing current GHG metrics solely on temperature impact 100 years into the future is inconsistent with the current global climate goal of limiting warming to 2 degrees C, a limit that is likely to be reached well within 100 years. A reasonable GTP value for CH4, accounting for current projections for when 2 degrees C warming will be reached, is about 18, leading to a current CF of 19 kg CO2-eq. per kilo beef (carcass weight, average European system), 20% lower than if evaluated using GWP(100). Further, we show that an application of the GTP metric consistent with a 2 degrees C climate limit leads to the valuation of CH4 increasing rapidly over time as the temperature ceiling is approached. This means that the CF for beef would rise by around 2.5% per year in the coming decades, surpassing the GWP based footprint in only ten years. Consequently, the impact on the livestock sector of substituting GTPs for GWPs would be modest in the near term, but could potentially be very large in the future due to a much higher (>50%) and rapidly appreciating CF.

Challenges in developing regionalized characterization factors in land use impact assessment: impacts on ecosystem services in case studies of animal protein production in Sweden

PurposeThe UNEP-SETAC Life Cycle Initiative has recently developed a guideline framework for land use impact assessment. This article evaluates the feasibility and highlights the challenges of applying a set of methods that adhere to this framework, and identifies the strengths and weaknesses of the indicators used in these methods, for the purpose of supporting further methodological development.MethodsThe methods were tested in two case studies of animal protein production in Sweden: dairy milk and pork. The reference situations were defined as the potential natural vegetation. County-level characterization factors (CFs) were calculated and occupation impacts were assessed for five ecosystem services, using six ecosystem service indicators: carbon flow change, groundwater recharge, mechanical filtration capacity, physicochemical filtration capacity, soil loss, and soil organic carbon, at two geographic scales: county and biome. Strengths and weaknesses of the ecosystem service indicators were identified using an evaluation framework for selected quality characteristics: representativeness, reliability, feasibility, and transparency.Results and discussionOccupation impacts at the two geographic scales, and for the two production cases, differ both in absolute numbers, and—for mechanical and physicochemical filtration capacity—in the ranking of cases. Results at both geographic scales indicate positive effects—or lower negative impacts—in protein production from dairy milk compared to pork, due to grass production on dairy farms, and lower use of land per unit protein. However, some of the observed benefits may be exaggerated due to challenges in adequately representing the reference situations. Most indicators were assigned medium or high degrees of representativeness, feasibility, and transparency, but several were assigned low degrees of reliability, due to the weak scientific basis upon which they were selected, low degrees of accuracy, and insufficient information on how they should be assessed.ConclusionsOccupation impact results should be interpreted with caution due to challenges in applying the methods and use of indicators with identified weaknesses. The most challenging part of developing regionalized CFs was finding suitable land areas from which to derive representative data to parameterize the reference situations. More research is needed to provide adequate support to life cycle assessment practitioners who wish to calculate regionalized CFs and to address the identified weaknesses.

Nitrogen flows on organic and conventional dairy farms: a comparison of three indicators

This paper analyzes nitrogen (N) flows on organic and conventional dairy farms in Sweden, and compares three indicators for the N pollution associated with the milk: (1) the farm-gate N surplus, (2) the chain N surplus, and (3) the N footprint. We find that, compared to indicators based on N surplus, the N footprint is a more understandable indicator for the N pollution associated with a product. However, the N footprint is not a replacement for the often-used farm-gate N surplus per unit area, since the two indicators give different information. An uncertainty analysis shows that, despite the large dataset, 1566 conventional and 283 organic farms, there is substantial uncertainty in the indicator values, of which a large part is due to possible bias in estimates of biological N fixation (BNF). Hence, although the best estimate is that conventional milk has 10–20% higher indicator values than organic, it is conceivable that improved estimates of BNF will change that conclusion. All three indicators simplify reality by aggregating N flows over time and space, and of different chemical forms. Thus, they hide many complexities with environmental relevance, which means that they can be misleading for decision-makers. This motivates further research on the relation between N surpluses and N footprints, and actual environmental damages.