Purpose The need to assess the sustainability attributes of the United States beef industry is underscored by its importance to food security locally and globally. A life cycle assessment (LCA) of the US beef value chain was conducted to develop baseline information on the environmental impacts of the industry includ`ing metrics of the cradle-to-farm gate (feed production, cow- calf, and feedlot operations) and post-farm gate (packing, case-ready, retail, restaurant, and consumer) segments. Methods Cattle production (cradle-to-farm gate) data were obtained using the integrated farm system model (IFSM) supported with production data from the Roman L. Hruska US Meat Animal Research Center (USMARC). Primary data for the packing and case-ready phases were obtained from packers that jointly processed nearly 60% of US beef while retail and restaurant primary data represented 8 and 6%, respectively, of each sector. Consumer data were obtained from public databases and literature. The functional unit or consumer benefit (CB) was 1 kg of consumed, boneless, edible beef. The relative environmental impacts of processes along the full beef value chain were assessed using a third party validated BASF Corporation Eco-Efficiency Analysis methodology. Results and discussion Value chain LCA results indicated that the feed and cattle production phases were the largest contributors to most environmental impact categories. Impact metrics included water emissions (7005 L diluted water eq/CB), cumulative energy demand (1110 MJ/CB), and land use (47.4 m a eq/CB). Air emissions were acidification potential (726 g SO eq/CB), photochemical ozone creation potential (146.5 g C H eq/CB), global warming potential (48.4 kg CO eq/CB), and ozone 2 4 2 depletion potential (1686 μg CFC eq/CB). The remaining metrics calculated were abiotic depletion potential (10.3 mg Ag eq/CB), consumptive water use (2558 L eq/CB), and solid waste (369 g municipal waste eq/CB). Of the relative points adding up to 1 for each impact category, the feed phase contributed 0.93 to the human toxicity potential. Conclusions This LCA is the first of its kind for beef and has been third party verified in accordance with ISO 14040:2006a and 14044:2006b and 14045:2012 standards. An expanded nationwide study of beef cattle production is now being performed with region-specific cattle production data aimed at identifying region-level benchmarks and opportunities for further improvement in US beef sustainability. . . Keywords Beef footprints Beef production emissions Beef Responsible editor: Peter Rudolf Saling sustainability Beef value chain Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11367-018-1464-6) contains supplementary material, which is available to authorized users. 1 Introduction * Senorpe Asem-Hiablie Meeting growing and changing consumer demands while email@example.com minimizing negative environmental and social impacts is a current challenge facing beef as well as other livestock indus- Pasture Systems and Watershed Management Research Unit, US tries. The USA is currently the world’s largest beef-producing Department of Agriculture—Agricultural Research Service, University Park, PA 16802, USA country raising close to 20% of the world’sannual supplywith 10% of the world’s cattle population (USDA-FAS 2015). BASF Corporation, 100 Park Avenue, Florham Park, NJ 07932, USA Environmental impacts and resource use have been studied for various segments of the US beef value chain, but a com- Formerly of National Cattlemen’s Beef Association, 9110 East Nichols Ave., Suite 300, Centennial, CO 80112, USA prehensive cradle-to-grave life cycle assessment (LCA) has Int J Life Cycle Assess not been completed (Dudley et al. 2014; Ghafoori et al. 2006; impacts of the beef value chain were evaluated in terms of the Lupo et al. 2013; Pelletier et al. 2010; Roop et al. 2014; cradle-to-farm gate (feed production, cow-calf, and feedlot Stackhouse-Lawson et al. 2012). As one of the most complex operations) and post-farm gate (packer, case-ready, retail, food systems in the world, a comprehensive LCA of beef is consumer, and restaurant) segments. Impacts of the produc- particularly challenging. tion of resource inputs such as fertilizer and packaging were A nationwide LCA was initiated under the US Beef included. While cattle production data were farm-specific, Sustainability Research Program to establish baseline impact packing and other post-farm gate data were representative of metrics and identify areas for improvement along the beef the entire US beef industry. Cattle production data were ob- value chain. Primary cradle-to-farm gate inventory data were tained from USMARC because of the extensive high-quality obtained from the Roman L. Hruska US Meat Animal data available. Their production system followed commercial Research Center (USMARC; the largest agricultural animal practices. research facility in the USA) as modeled and supported by the integrated farm system model (IFSM; USDA-ARS, 1.2 Functional unit University Park, PA). The IFSM is a process-level whole-farm simulation model used to evaluate environmental impacts of The functional unit was defined for the purposes of this study dairy and beef production systems (Rotz et al. 2006, 2012). as the consumer benefit (CB), a unit of which was 1 kg of The model has been evaluated and used to represent opera- consumed, boneless, edible beef in the USA. This represented tions of varying sizes, landscapes, and climates (Belflower an average of all beef cuts, i.e., the impact allocated to meat et al. 2012;Chianese etal. 2009a, b; Corson et al. 2007; was divided by the total of all edible beef obtained. Boneless Deak et al. 2010; Ghebremichael and Watzin 2011; Salim beef was chosen in order to evaluate beef-specific impacts. et al. 2005; Sedorovich et al. 2007; Stackhouse-Lawson The dressing percentage (carcass yield) at harvest was based et al. 2012;Stackhouse et al. 2012; Waldrip et al. 2014). The on industry averages of 62% for finished cattle and 50% for relative environmental impacts of processes along the full beef culled cows and bulls. Accounting for losses at the packing value chain were assessed using a third party validated BASF and case-ready phases from fat and bone removal and shrink Corporation (BASF SE, Ludwigshafen, Germany) Eco- (33%), retail phase losses from shrinkage and spoilage (7%), Efficiency Analysis (EEA) methodology based on the and consumer phase losses from cooking, spoilage, and plate International Organization for Standardization (ISO 2006a) waste (20%) resulted in 29% as the portion of live weight 14040 standards (Saling et al. 2002; Uhlman and Saling consumed as edible beef (Table 1). Therefore, a live weight 2010). of 3.45 kg resulted in 1 kg of consumed beef. Percentage losses were obtained from USDA-ERS (2012a) and primary data as shown in Table 1. That not consumed was treated as 1.1 Goal and scope definition by-products or handled as waste where a small portion of the various impacts was allocated to by-products. The overall goal of this LCA was to provide a baseline of the environmental impacts of current practices along the US beef value chain. The specific aim was to quantify the sustainabil- ity impacts associated with the production and consumption of 2Methods 1 kg of consumed beef for a representative system in the USA. The target audience included the beef industry and its stake- The life cycle EEA of beef was performed using the BASF holders, consumers, and public. methodology (BASF SE, Ludwigshafen, Germany), which The scope of this study was a cradle-to-grave assessment of follows ISO 14040:2006a and 14044:2006a standards for the sustainability of a US beef supply chain. Environmental LCAs and ISO 14045:2012 for EEA. The analysis was Table 1 Yield of carcass from Description Percent Source live animal (dressing percentage) and value chain losses used in Dressing percentage, finished cattle 62 USDA-ERS (2012a) calculating the functional unit (consumer benefit) in US beef life Dressing percentage, cull cattle 50 USDA-ERS (2012a) cycle impact assessment Losses in packing and case-ready phases (fat, bone, and shrink) 33 USDA-ERS (2012a) Loss in retail phase (fat, bone, shrink) 7 Primary retail data Loss in consumer phase (cooking losses, spoilage, plate waste) 20 USDA-ERS (2012a) Portion of live weight consumed as edible beef 29 Calculated Twenty-four percent of beef comes from cull animals with 76% from finished cattle Int J Life Cycle Assess validated and verified by NSF International under Protocol 2.1 System boundaries P352 Parts A (BASF 2013a)and B(BASF 2015), respective- ly. Data sources included reported and IFSM-simulated cattle Figure 1 shows a schematic of the system boundaries of the production data (Rotz et al. 2013), life cycle inventory data- life cycle impact analysis. Cattle originating as cull animals bases, public databases, expert opinion, and primary process- from the dairy industry as well as beef imports and exports ing and use data. Environmental impact was measured by the were not included in the production system. Feed imports following metrics: consumption of non-renewable raw mate- were also excluded as all feed was produced within the rials or abiotic depletion potential (ADP), cumulative energy USMARC production system. Of the total national major feed demand (CED), consumptive water use (CWU), land use, and grains supply reported by the USDA-ERS (2017) which in- human toxicity potential (HTP) of materials used. Air, solid cluded use for other livestock species as well as food and waste, and water emissions were also quantified. Air emis- industrial uses, less than 12% was imported at the time of this sions included acidification potential (AP), global warming study. Capital, equipment, buildings, infrastructure, and mate- potential (GWP), ozone depletion potential (ODP), and pho- rials for repairs and maintenance were excluded from the tochemical ozone creation potential (POCP). Particulate mat- study as they are not usually included in LCAs of agricultural ter was not included in the current study due to lack of indus- commodities, goods, and services due to their insignificant try data, complexity in characterization, and resulting unavail- effects. Impacts that contributed < 1% individually as specific ability of standard LCA procedures. Figure 1 shows a sche- components or unit operations or < 3% in total as a group of matic of the main components of the life cycle impact analy- components or processes to the overall value chain were gen- sis. Summaries of the data and sources are provided in related erally excluded from the LCA. Among these were office and tables and the Supplementary Information. administrative impacts, employee commutes, cattle veterinary PRE-HARVEST (Feed, Cow-Calf, Finishing) POST-HARVEST Transport Transport Harvest Land & crop Herd Labor Soil properties Weather Machinery management management Transport Restaurant Crop growth and development Retail Case- ready Soil Crop Transport SALCA IFSM harvest Heavy metals in fertilizer (process level At-home runoff and leaching simulation) Transport Consumption Storage Manure Animal growth and production Waste Disposal Transport Transport Eco-Profiles (Life Cycle Inventories) Life Cycle Impact Assessment Cumulative Energy Land use Abiotic Depletion Potential Consumptive Water Toxicity Potential Emissions Demand (MJ/CB) (m a /CB) (norm. points/CB) (kg/CB) Use (L eq/CB) Water Solid Waste Air (L grey water eq/CB) (g/CB) Acidification Global Warming Ozone Photochemical Ozone Potential Potential Depletion Potential Creation Potential (g SO eq/CB) (kgCO -eq/CB) (mg CFC -eq/CB) (g C H -eq/CB) 2 2 11 2 4 Fig. 1 An overview of the US beef life cycle analysis including inputs and outputs of phases, and impacts measured Int J Life Cycle Assess medicines, and retailer and consumer use of cleaning phase. The inventories were compiled from primary industry compounds. data, the BASF life cycle inventory database, Boustead Model Version 5.1.2600.2180 (Boustead 2005), and Ecoinvent 2.2 Data sources and input information Version 2.2 (Frischknecht et al. 2005). All primary data obtained from packing plants, case-ready, Required inventory data included resource use and emissions and restaurants were obtained by providing each study partner for feed and cattle production and packing, case-ready, retail, with spreadsheets listing all inputs going into the system for restaurant, and consumer phases. Feed and cattle primary data which they provided the input values. The details of all pri- were developed through reports of the USMARC and simu- mary data cannot be listed for confidentiality reasons. Neither lation of its production system (Rotz et al. 2013). This re- can the extensive inventory of materials and resources from search facility provided high-quality and extensive manage- BASF’s database used in this study because this would be ment data that were difficult to obtain otherwise from the impractical and this also has propriety concerns. This paper’s industry. The crop, feed, and animal management practices intention is to provide sufficient detail and to adhere to quality of this facility were characteristic of those practiced in the standards required for dissemination of findings to stake- Great Plains (this region stretches north to south of the central holders and the interested public. Therefore, the study USA and encompasses western Texas and eastern New underwent critical review by a third party, NSF Mexico through North Dakota and eastern Montana) where International, and is reported as Protocol P352 Parts A most cattle are produced. An exception to this similarity was (BASF 2013a)andB(BASF 2015). Through this peer review greater irrigation use at the USMARC to grow feed crops and process, the study was verified and approved as valid. pasture compared to the rest of the industry. Another differ- ence, albeit negligible when considering environmental im- 2.2.1 Feed production pact, was a greater labor involvement in production at this federal research facility. Due to the region-specific nature of The feed production phase studied the life cycle of feed pro- production practices across the USA resulting from differ- duced and purchased for cattle consumption at the USMARC. ences in climate, available resources, and culture, the Based on year 2011 records, the USMARC produced feed USMARC facility is not meant to represent all beef produc- crops on 2108 ha of irrigated land and maintained 9713 ha tion systems in the nation. It does, though, provide a general of unirrigated pasture to feed the cattle produced. Feed crops representation of beef cattle production in the USA. included alfalfa/grass hay and silage, corn silage, high mois- Biological and physical processes of the beef cattle produc- ture corn, and dry corn grain. Feed purchased to supplement tion system were simulated with the IFSM, and the predicted the farm’s production included 1790 t (dry matter) of wet performance of the operation was found to agree well with distiller’s grain (WDGS). Crop growth, feed utilization, and production records of the research center (Rotz et al. 2013). nutrient cycling were simulated with IFSM using daily weath- The full operation was simulated as three components: feed er conditions on the crop farm during the study period (Rotz production, cow-calf production, and feedlot finishing. The et al. 2013). Resource utilization, operation timeliness, crop accuracy of the IFSM predictions for feed production and losses, and feed quality were predicted based on reported till- use, energy use, and production costs (within 1% of reported age, planting, harvesting, and storage practices. Nutrient flows values in 2011) justified its use for this study (Rotz et al. traced through the farm predicted environmental losses in- 2013). The USMARC and IFSM simulations primarily pro- cluding reactive nitrogen (NH ,NO ,andN O), phospho- 3 3 2 vided resource and farm input data as well as direct emissions rous, and net greenhouse gas (CO ,CH ,and N O) emissions. 2 4 2 in feed and cattle production from which life cycle inventories Emission factors obtained from IFSM simulations directly were derived. related to crop production and additional field emissions de- The post-farm gate assessment consisting of the packing, rived using recommendations of the Intergovernmental Panel case-ready, retail, restaurant, and consumer phases, used pri- on Climate Change (IPCC 2006) are presented in Table 2. mary data from industry and information from public data- Cattle manure used to fertilize the farm and pastureland was bases, literature review, and when necessary expert opinion. generated within the USMARC and therefore had no associ- Various data were collected between 2011 and 2013. All feed, ated pre-chain impacts. Rotz et al. (2013)provide adetailed cattle, and packing phase data were representative of 2011 description of the USMARC facility and IFSM simulations. management practices, while primary retail and restaurant da- Land use change impacts on greenhouse gas emissions can be ta were from 2013. Case-ready data from study partners were substantial in areas where forests are transformed into farms from 2011 and 2013. Specific details of the sources of input for feed crop production. As cattle feed in the USA are not data are given in the relevant sections below. Impacts of re- typically sourced from such areas, land use change was not source use and emission outputs were quantified using life considered as an important contributor to the GWP in this cycle inventories of inputs, processes, and outputs of each study. Int J Life Cycle Assess Table 2 Emission rates from fertilizer and manure application on feed crops used in US beef life cycle impact assessment Emission type Rate Source Runoff loss (corn fields only) 0.15 g P/kg P applied IFSM simulation 0.60 g N/kg N applied IFSM simulation Air emissions (direct + corn crop residue) 0.20 g N O/kg applied IFSM simulation N fertilizer leaching 30% of N applied IPCC (2006) Leached N to N O-N 0.75% (2.25 kg N O-N /kg fertilizer N applied) IPCC (2006) 2 2 CO from urea 200 g CO -C /kg (NH ) CO applied IPCC (2006) 2 2 2 2 CO from limestone 120 g CO -C/kg CaCO applied IPCC (2006) 2 2 3 Volatilization of NH from fertilizer-N 100 g NH /kg N applied IPCC (2006) 3 3 N O-N = annual direct N O-N emissions produced from soil amendment (urea or limestone) decomposition, kg N O-N/year 2 2 2 CO -C emission = annual C emissions from soil amendment (urea or limestone) decomposition, kg C/year Purchased corn for WDGS was ascribed Ecoinvent profiles systems, and pre-chain impacts for their production and use (Table S1, Electronic Supplementary Material) representative were included. of the Iowa corn-belt region which unlike the USMARC- cultivated corn was not irrigated. The average transportation roundtrip distances assumed for purchased corn to the distill- 2.2.2 Cattle production ery for WDGS production were 400 km and that of WDGS from the distillery to the USMARC was 32 km. As WDGS is a Cattle production, consisting of cow-calf and feedlot opera- by-product of corn-based bioethanol distillation, an economic tions, followed the life cycle of cattle from birth to harvest. In allocation was used to determine its impacts. This was done 2011, USMARC maintained 5050 calves, 5498 cows, 285 by deducting the drying energy from the life cycle inventory bulls, and 1180 replacement heifers in the cow-calf operation of 1 kg of dried distiller grains with solubles (DDGS) and and 3724 cattle were finished in the feedlot (Rotz et al. 2013). multiplying the weight of the DDGS by 1.55 (Bonnardeaux In the cow-calf operation, cattle were grazed on pasture (a 2007) to reflect the weight of WDGS. The bioethanol profile small part of which received irrigation) and fed hay and silage was adjusted to represent Iowa corn production yields, and the during winter. Weaned calves were moved to a feedlot where WDGS profile was created by allocating 21% of the distilla- they received a high-forage backgrounding diet of hay and tion process and pre-chain impacts based on economic alloca- distiller’s grain for 3 months and then were put on a high- tion using ethanol, WDGS, and DDGS pricing which were grain finishing diet of corn grain, corn silage, and distiller’s US$0.54/kg, US$0.09/kg, and US$0.24/kg at the time of the grain for another 7 months. At 16 months of age, cattle were study. harvested with an average weight of 581 kg. Also included in The chemical oxygen demand (COD) for pesticides the harvest were cull cows and bulls from the cow-calf phase (Table S1, Electronic Supplementary Material) was calculated of the operation (Rotz et al. 2013). using their chemical formula (C, O, N, and H stoichiometry). Supplementary feed was accounted for in this phase, Runoff and leaching emissions of heavy metals, including whereas all grazed and harvested forage and grains were in- those from fertilizer application, were obtained using the cluded in the feed production phase. Enteric CH and CH , 4 4 Swiss Agricultural Life Cycle Assessment (SALCA) Heavy N O, and NH emissions from excreted feces and urine and 2 3 Metals calculator (Freiermuth 2006). As SALCA did not in- phosphorous and nitrogen runoff losses from pastureland were clude options for selecting US specific soil characteristics, simulated with the cattle operations. Drinking water was sup- German values were substituted to simulate representative plied by USMARC wells, which accounted for the consump- heavy metal dynamics (such as heavy metal percolation, de- tive water used by the livestock. Energy used for pumping position, and leaching rates) in the soil. This assumption was drinking water and its associated pre-chain impacts was also not seen to have a meaningful impact in the results as the accounted for in this phase. representative soil type used was similar to US agricultural Transportation of calves and cows within USMARC oper- soils. ations was minimal with no effect on the LCA’s results. Irrigation was used to produce all feed crops and some Generally, transportation impacts have been found to be rela- pasture on the USMARC operation. Irrigation-associated im- tively low in beef cattle systems in the USA even when cattle pacts included CWU sourced from on-farm wells with a small were transported over long distances (Rotz et al. 2015). The amount (1%) from surface water. Electricity and natural gas minor effect of cattle transportation to the packing plant was were both used to pump water through center pivot irrigation included in the packing phase. Int J Life Cycle Assess Enteric CH emitted by cattle was the only form of biogen- For water use and cleaning chemicals, input values were as- ic carbon included in the analysis. The carbon in the enteric sumed to be 10% of the reported use of the packing facilities CH emitted was assumed to be assimilated from CO in the based on knowledge of this facility’s operators and industry 4 2 atmosphere during crop growth. To account for the assimila- experts. End-of-life impacts of 96.5% of the packaging mate- tion and avoid double counting, a 1 CO eq credit was applied rial were attributed to the retail or consumer phases. The study to the global warming potential (GWP) factor of CH (thus boundary did not include the 3.5% of corrugated cardboard utilizing a GWP of 24 CO eq for methane as opposed to the that was recycled (following cutoff allocation rules). standard factor of 25 CO eq). The major inputs for the cattle phase’s life cycle inventory are shown in Table S2 (Electronic 2.2.5 Retail Supplementary Material). The retail phase represented distribution and marketing of 2.2.3 Packing beef to the consumer. Primary data (Table S4,Electronic Supplementary Material) were obtained from three retailers The packing phase of the value chain processes live animals ranging in size and representing 8% of the total retailed US into edible beef. Primary and calculated input data describing beef. As the retail operations included sales other than beef, an operational emissions and waste (Table S3,Electronic economic allocation was performed based on the ratio of beef Supplementary Material) were obtained from site visits and to total store sales. For refrigerated sales, allocations of refrig- interviews with three packers who collectively processed 60% erant leakage and electricity use were refined using averages of the US beef harvested annually. For equity in representa- of ICF (2005), USEPA (2011, 2012), and FMI (2012)data. tion, the packers studied represented both small and large- scale operations and their weighted averages (based on weight 2.2.6 Consumer of beef processed by each size of operation) were used. Primary transportation data for cattle, packaging (paper and The consumer phase included consumer impacts from trans- plastics), liquid CO , and wastes of the packing phase were portation to the retail store and beef consumption at home. used, and their average transport distance of 2033 km was Transportation considered the ratio of beef to total supermar- assigned to all other raw materials and supplies. The by- ket purchases, and cooking was based on the average beef products of beef (including hides, offal, blood, tallow, bones, cooking preference of the consumer in relation to the average and bone meal) received an economic allocation of 11.7% of energy required to cook 1 kg of consumed beef while consid- the production and packing impacts based on primary sales ering the percentages of electric or gas stoves. Public informa- data obtained from the collaborating packers. The COD emis- tion and data gathered from literature were used to calculate sions (Table S3, Electronic Supplementary Material) were cal- national averages of consumer-phase inventory inputs culated using the C, O, N, and H stoichiometry of the relevant (Table S4, Electronic Supplementary Material) related to con- compounds. sumer repackaging of beef, transportation (USDOT 2011), End-of-life impacts of 96% of each packaging material refrigeration electrical energy consumption (AHAM 2011), (plastic and corrugated cardboard packaging containing 30% cooking energy (USEIA 2005), and beef waste (USDA-ERS recycled fiber) were assigned to the case-ready or retail phase 2012b). Volumetric allocation based on the typical US con- as these materials entered either phase directly from the pack- sumer’s diet (considered to consist of 12.7% meat by volume) ing phase whose waste profile received the remaining 4% of followed by the application of economic purchasing factors to the packaging plastics’ end-of-life impacts. The remaining 4% derive the beef portion of meat consumed was used to allocate of corrugated cardboard was recycled and had no further im- impacts related to consumer beef refrigeration (USDA-ERS pacts attributed to it following cutoff allocation rules. 2005). 2.2.4 Case-ready 2.2.7 Restaurant The case-ready phase further processes primal cuts of beef The restaurant phase studied impacts of beef sold to con- into consumer-ready packaged cuts. Based on data from the sumers in restaurants and used primary data from quick- case-ready study partners, 63% of US beef was assumed to be service and casual sit-down restaurants representing nearly packaged in the case-ready phase. Primary data were obtained 6% of US beef sold in restaurants. As restaurants typically sell from a packer with a case-ready operation and a stand-alone other consumables in addition to beef, an economic allocation case-ready operation (Table S3, Electronic Supplementary factor calculated as the ratio of beef sold to total restaurant Material). Input data were also received from a collaborating sales was used. It was also assumed that 53 and 47% of US packer with case-ready operations where energy input, pack- beef consumption were in restaurants and at home, respective- ly, based on industry data (Meat Solutions, Inc. 2014). System aging, consumable items, and waste were directly reported. Int J Life Cycle Assess inputs in the restaurant phase are listed in Table S5 (Electronic of fuels to generate electricity, a life cycle inventory was as- Supplementary Material). sembled for each type contributing to the national grid. The contribution of each fuel type to the national grid was based on 2.2.8 Recycling and waste the 2011 US Energy Information Administration’s data on electricity generation by energy source. Losses during the Packaging of beef was assumed to be done either in the case- conversion of electrical energy to steam and line losses of ready phase (for sale at retail) or by the retailer. Footprints of electricity were included. The gross bioenergy content of feed- the 30% recycled fiber in the corrugated cardboard used by stock (energy released through combustion of feed biomass) most of the post-farm facilities surveyed were obtained from was included but not the solar energy required for its produc- pre-defined profiles in Ecoinvent which also took into consid- tion. The gross bioenergy for corn silage, corn grain, alfalfa eration the item’s production processes and appropriate allo- silage and hay, and grass from managed and natural pastures cations. Of post-farm packaging other than cardboard, dispos- ranged from 17.8 to 18.6 MJ/kg dry matter (Ecoinvent Version al was assumed to be 82 and 18% in landfills and incinerators, 2.2; Frischknecht et al. 2005). No weighting factors were ap- respectively, with energy recovered from that incinerated plied to the CED. (USEPA 2010). Additionally, a modified Ecoinvent profile Consumptive water use (L eq/CB) quantified withdrawn was given to waste packaging disposed in municipal and solid freshwater lost from the watershed of origin in a product’slife waste landfills to remove accounting for contaminants such as cycle via evaporation, absorption into products and waste, or heavy metals that were originally part of the municipal waste transfer out of the watershed (Pfister et al. 2009). Water stress Ecoinvent profile but not found in beef packaging waste. indices (WSIs) obtained from Pfister et al. (2009) and served While all direct waste generated at each phase of the value as midpoint characterization factors applied to the volume of chain was evaluated based on its final fate and degradation absolute CWU (L abs/CB) to obtain the CWU (L eq/CB). after emissions to water and air, solid waste associated with Coefficients defining absolute CWU represented the con- the production of resource inputs was assessed based on its sumptive fraction of the water used in a given process and final disposal (i.e., recycling, incineration, or landfilling). were taken as midpoint ranges from USGS consumptive water Finally, the cutoff method was applied for impacts from incin- data (Solley et al. 1998). These included cropping (70%), eration, as the impacts from incineration were assumed to be livestock (55%), industrial (25%), and thermoelectric power attributed to the energy consumer (i.e., purchaser of the elec- (50%). For example, in crop production, 100 L of water used tricity generated from incineration). for irrigation was 70 L absolute consumed (70% loss to evapo- transpiration and runoff from the watershed) multiplied by the 2.3 Environmental impact metrics water stress index of 0.499 giving an equivalent of 35 L eq/ CB. Abiotic depletion potential (kg Ag eq/CB) measured the ef- Human toxicity potential (dimensionless) quantified possi- fects of raw material use on the availability of natural reserves. ble toxic effects of material exposure on human health pre- As described by Uhlman and Saling (2010), the mass of basic chain, along the value chain, and material disposals within raw materials from each resource needed to manufacture a study boundaries (Landsiedel and Saling 2002). The produc- product was weighted by a factor consisting of the quantity tion, use, and disposal of all materials relevant to the beef of each material’s geologic reserves and life span as defined value chain were inventoried and assigned scores between 0 by the USGS (Guinée et al. 2002) given current global extrac- and 1000 based on hazard statements (H-phrases) from safety tion rates for all uses. Thus, materials with lower reserves and/ data sheets according to the Globally Harmonized System of or higher consumption rates received higher weightings. Classification and Labelling of Chemicals (Table S7, Sustainably managed renewable resources had a weighting Electronic Supplementary Material; adapted from Landsiedel factor of B0^ to indicate infinite reserves. Information on de- and Saling 2002). Based on expert opinion, the scores were mand and available reserves were obtained from national min- further modified, normalized, and weighted considering expo- eral commodity statistics (USGS 2012) and fossil energy re- sure conditions, substance’s persistence, and exposure risk as serve data (BP 2012). Table S6 (Electronic Supplementary described in BASF (2013a). The sum of the products of the Material) provides a list of essential raw materials considered, quantities of each substance used and their calculated scores their global reserves, and assigned weighting factors. was found. Finally, materials were assigned weightings of 20, Cumulative energy demand (MJ/CB) was the sum of all 70, and 10%, based on the possibility of exposure at the pro- energy needed for the production, use, and disposal of a prod- duction, use, and disposal phases, respectively. Pre-chain H- uct as well as the energy content of the product. All individual phrases were considered in the production phase of resource energy sources (e.g., biomass, coal, lignite, natural gas, nucle- inputs only. The heaviest weighting of 70% was assigned to ar, oil, and wind) measured in MJ/CB were summed to obtain Buse^ as it is at this stage that the highest risk of personal exposure was expected. When a substance’ the CED per CB. As electricity companies use an assortment s use occurred as Int J Life Cycle Assess part of its production and no disposal occurred because it was hazardous waste (mainly earth) stayed on site for fillings and used up with the value chain, an integration of the weighting therefore were assigned a disposal cost of zero (Table S10, factors yielded a value B100^; thus, weighting was irrelevant. Electronic Supplementary Material). Land use (m a eq/CB, where a = time in years) was con- Water emission (L diluted water eq/CB) was based on crit- sidered in terms of both occupation and change (transforma- ical volumes defined as the contaminant concentration multi- tion). A series of occupations taking place at different time plied by a dilution factor (the reciprocal of a regional regula- periods made up the transformation. Land use was calculated tory maximum emission concentration) for each contaminant as the total area of land and the degree of development re- (Table S11, Electronic Supplementary Material). Total vol- quired to provide the CB. The degree of land development umes of water discharged from wastewater treatment plants was based on the ecosystem damage potential (EDP) which and directly to surface waters were considered. The contami- was assigned based on the level of occupation or transforma- nants included in the BASF EEA method were NH ,total-N, 3− tion and provides indicators of biodiversity as estimated from and PO , as well as heavy metals, hydrocarbons (including 2− − the species richness of vascular plants (Koellner and Scholz detergents and oils), and SO .Also includedwere Cl ,ad- 2008). Categories of land use occupations and transformations sorbable organically bound halogens, and COD. In order to from one use type to another were described by the EDP determine total water emissions, the sum of all critical vol- (Table S8, Electronic Supplementary Material; Frischknecht umes was found and then normalized to aid aggregation of et al. 2005) following an established BASF methodology. The all parameters into a single value (Saling et al. 2002). land use classes included native vegetation, arable, permanent crop, pasture and meadow, urban, industrial, mineral extrac- tion site, traffic areas, dump sites, and water areas. 2.4 Qualitative uncertainty and sensitivity analyses Air emissions had four main categories (Table S9, Electronic Supplementary Material). Acidification potential All data sources used for this study were ranked as high (pri- (kg SO eq) included SO ,NO ,NH , and HCl emissions mary data) to medium (literature review and industry average) 2 x x 3 (Saling et al. 2002). Global warming potential (kg CO eq) quality. The feed, cow-calf, and finishing phases were ana- included anthropogenic CO ,CH ,N O, and halocarbons lyzed with primary data obtained from USMARC and IFSM 2 4 2 (HC), with each gas adjusted by their 100-year GWP simulations and were ranked as high to medium quality. (Forster et al. 2007;IPCC 2006). Ozone depletion potential Although observed farm environmental data were unavailable of HC was reported as kg CFC eq. Photochemical ozone cre- with which to make model comparisons of impact metrics, ation potential considered those emissions responsible for proper modeling of production systems in IFSM has been ground-level ozone, including non-methane volatile organic shown in previous studies to produce accurate predictions of compounds (NM-VOC) and CH measured in kg C H eq emissions (Rotz et al. 2006, 2010; Stackhouse-Lawson et al. 4 2 2 (Heijungs et al. 1992). 2012). The IFSM simulations of feed production over local Solid waste impact (kg municipal waste eq/CB) considered weather conditions, energy use, and production costs fell with- materials disposed in a landfill or incinerated. These materials in 1% of reported values (Rotz et al. 2013). were placed in five categories based on their potential envi- Both the packing and case-ready phase data were ranked as ronmental effects. The categories were municipal waste, haz- high quality. The retail and restaurant data were primary; how- ardous waste (as defined by the Resource Conservation and ever, economic allocations were done resulting in a high to Recovery Act), construction waste (non-hazardous waste ma- medium-quality classification. Data for the consumer phase terials generated during building or demolition), mining (non- was described as medium quality having been taken from hazardous earth or overburden generated during raw materials literature and industry reports. A review of the system inputs extraction), and radioactive waste (as defined by the showed data to be complete and representative of current in- International Atomic Energy Agency). Existing life cycle in- dustry practices; thus, no critical uncertainties were identified ventories provided waste information for the production of so as to impact the study’s results and conclusions. resource inputs, while the inventory for the value chain was Sensitivity analyses were done to account for specific developed from the primary waste profile data provided by integrated processes along the value chain. Three alterna- industry partners. As there were no standardized assessment tive scenarios were studied independently and compared criteria at the time of this study, individual impacts were with the base analysis. For two scenarios, analysis of wet weighted by the normalized average disposal cost of each distiller’s grains by mass allocation (scenario 1) and en- waste category in a landfill compiled internally by BASF ergy allocation (scenario 2) was compared to the econom- (Table S10, Electronic Supplementary Material) and then ic allocation used in the base analysis. In a third scenario, summed to an overall solid waste impact. Any special waste analysis of consumer refrigeration by economic allocation categories from mining raw material inputs were treated ac- (scenario 3) was compared to the volumetric allocation of the base analysis. cording to the specific category’s requirements, while the non- Int J Life Cycle Assess 3 Results and discussion quantities were used by the restaurant and consumer phases, largely due to the high energy needs for transportation, refrig- Over the full value chain, cattle production impacts dominated eration, and cooking. Smaller impacts of the packing and case- with the feed production, cow-calf, and finishing phases hav- ready phases on the environmental metrics rose from combus- ing the most influence on a majority of the environmental tion in electricity production, on-site boiler use, and pre-chain categories. In a similar study assessing the life cycle impacts emissions of packaging material (corrugated cardboard and of Australian red meat exported to the USA, Wiedemann et al. low density polyethylene (LDPE)) production. (2015) also observed that the feed and cattle phases had the The CWU estimate was 2558 L eq/CB based on a water highest environmental impacts and resource use. Levels of stress index of 0.499, while the absolute CWU was 5126 L eq/ impacts of either feed or cattle phases were highest for 10 of CB (Table 3). Most of the CWU (98%) went into irrigating the 12 environmental metrics (Fig. 2 and Table 3). feed crops (Fig. 2). Other minor contributors to CWU were the restaurant phase (0.55%) and pre-chain water consumption, particularly in the production of electricity and corrugated 3.1 Resource use cardboard. To reduce CWU, more efficient use of irrigation must be adopted to reduce the amount of water withdrawn to Metrics related to resource use included ADP, CED, CWU, meet crop needs. Greater use of non-irrigated pasture and and land use. On a weighted basis, Zn use in the animal phase rangeland, increased cropping efficiency, and incorporation as an essential mineral had the greatest ADP. While the ADP of by-products such as distiller’s grains in cattle feed are prac- of Zn appears minor at 6.2 mg Ag eq/CB, the prevailing rates tices that could contribute to reduced irrigation requirements. of extraction of Zn in relation to economically available global Land use was highest at the feed production phase requir- reserves were high enough to be considered of substantial ing 97% of the total land area of 47.4 m a eq/CB assessed for impact. Fossil energy in the form of natural gas, oil, and coal the value chain (Table 3 and Fig. 2). Major land users were used for fertilizer production, utilities, and transportation col- pasture (which required 31.5 m a eq/CB or 69% of the 97%) lectively followed Zn in ADP (Fig. 3). Uranium also showed and crop land required for animal feed production. Pre-chain some importance. All other minerals including phosphorus cardboard packaging production also made small contribu- had a relatively low contribution to ADP. The ADP estimated tions in terms of land use for tree growth. Total weighted land for the entire beef value chain was 10.3 mg Ag eq/CB. use may decline through increased crop and pasture yields It was estimated that 80.3 and 0.6% of the calculated total allowing greater feed production per unit of land area. value chain CED (1100 MJ/CB) were bio-based renewable Packaging optimization may also reduce the trees needed and non-bio-based renewable energy, respectively, while and the fossil fuel extraction required in pre-chain production non-renewables made up 19.1%. The majority of the CED both leading to reduced land use. (80%) was associated with the gross bioenergy of the animal feed. The bio-energy of the major feeds (corn, corn silage, alfalfa, and grass) ranged between 17.8 and 18.6 MJ/kg dry 3.2 Emissions matter (Ecoinvent 2.2; BASF, 2015). As this energy is a bio- logical necessity for the animals, opportunities for energy re- The assessed values of the various air emission subcategories ductions would have to be explored in other energy types. Of were AP (726 g SO eq/CB), GWP (48.4 kg CO eq/CB), 2 2 the fossil energy consumed along the value chain, the highest POCP (146.5 g C H eq/CB), and ODP (1686 μgCFC eq/ 2 4 11 Fig. 2 Percentage contributions Cumulative Energy Demand of the various phases to each Abiotic Depletion Potential measured environmental impact of beef production and Consumptive Water Use consumption Global Warming Potential Photochemical Ozone Creation Potential Acidification Potential Ozone Depletion Potential Water Emissions Solid Waste Land Use Human Toxicity Potential 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Feed Cow-Calf Feedlot Packing Case-Ready Retail Consumer Restaurant Int J Life Cycle Assess Table 3 Environmental impact metrics quantified in the life cycle assessment of US beef where 1 unit of consumer benefit (CB) is equivalent to 1 kg of consumed, boneless, edible beef in the USA Impact Units Phase Total beef value chain Feed Cow-calf Finish Packing Case ready Retail Consumer Restaurant Abiotic depletion potential mg Ag eq/CB 1.51 3.95 2.68 0.24 0.16 0.14 0.59 1.01 10.3 Cumulative energy demand MJ/CB 988.0 11.6 6.0 11.4 8.3 6.6 29.3 48.4 1110 Consumptive water use L eq/CB 2506 11.9 11.2 3.7 1.9 1.7 6.8 14.0 2558 Absolute consumptive L abs./CB 5023 23.9 22.5 7.5 3.9 3.4 13.7 28.1 5126 water use Human toxicity potential norm.tox.pts. 0.93 0.034 0.027 0.003 0.002 0.001 0.001 0.002 1.0 Land use m a eq/CB 45.8 0.3 0.7 0.1 0.2 0.0 0.1 0.2 47.4 Acidification potential g SO eq/CB 127.4 359.2 210.7 2.6 1.7 2.3 7.8 13.9 726 Global warming potential kg CO eq/CB 7.42 28.51 6.39 0.55 0.27 0.46 2.01 2.83 48.4 Ozone depletion potential μgCFC eq/CB 121.4 0.1 1.4 36.9 336.6 180.7 0.9 1008 1686 Photochemical ozone gC H eq/CB 136.9 6.8 1.8 0.2 0.2 0.1 0.2 0.4 146.5 2 4 creation potential Solid wastes g municipal waste 91.3 101.4 21.5 45.1 7.0 10.1 25.3 67.3 369 eq/CB Water emissions L diluted water 6127 17.9 2.4 126.1 484.9 2.2 198.8 45.9 7005 eq/CB CB) (Table 3). Manure and urine excretions and feed crop therangesof8.14CO eq/kg live weight (14.8 CO eq/kg 2 2 fertilization were responsible for the high AP (primarily NH carcass weight) to 16.2 CO eq/kg live weight (29.5 kg 3 2 emission) of the cow-calf, finishing, and feed phases with CO eq/kg carcass weight). Roop et al. (2014)reported green- contributions of 50, 29, and 18%, respectively. Other major house gas emissions for beef cattle production and processing AP contributors were emissions from fossil fuel combustion in the Pacific Northwest as 18.8 ± 0.86 kg CO eq/kg pack- related to electricity production, on-site boiler use at packing aged beef. The range in values is a result of the differences in plants, transportation, and pre-chain impacts from corrugated system types and modeling assumptions. In our study, the cardboard production. cradle to farm gate GWP was within the range of other pub- Greenhouse gas emissions at the farm gate have been the lished studies at 10.9 kg CO eq/kg live weight or 18.5 kg most reported of US beef cattle environmental impacts. CO eq/kg carcass weight (Rotz et al. 2013). Studies by Dudley et al. (2014), Lupo et al. (2013), and Enteric CH emission from cattle production was the lead- Pelletier et al. (2010) in the Central, Northern Great Plains, ing contributor (47%) to total GWP of the value chain. In a and Upper Midwest USA, respectively, estimated values in farm gate impact analysis, Pelletier et al. (2010) also estimated that approximately 42% of greenhouse gases emitted by main- taining beef cattle on pasture was attributable to enteric CH 0.99% 0.78% emissions while 37 and 21%, respectively, were from feed production and manure emissions. The next highest contribu- 3.64% tor to the total GWP was N O (27%) produced from manure Zinc 2 8.14% Gas on pastureland, fertilized crop land, and feedlots. Refrigerant Oil leakage at the retail and restaurant phases and cooking at the Uranium 9.76% Coal restaurant and consumer phases together contributed nearly Copper 10% to the total GWP (Table 3). Phosphorus as P The photochemical ozone creation potential (POCP) was Lignite 59.80% Iron most influenced by volatile organic carbon (VOC) emissions Bauxite 16.89% from fermented feeds including silage, high moisture corn Manganese grain, and distiller’s grain primarily fed to cattle on feedlots. Titanium Lime Enteric CH emissions from the cattle phases also contributed, Silver but this contribution was low due to the relatively low reac- NaCl tivity of CH . Sulfur 4 In the feed production phase, increased crop yields Fig. 3 Abiotic depletion potential (ADP) by resource included in the US resulting in decreased fertilizer application and lesser beef life cycle assessment Int J Life Cycle Assess emissions from fertilizer pre-chain production as well as over- 3.4 Sensitivity analyses all higher production efficiency per hectare of feed might de- crease AP and GWP. Greater use of distiller’sgrain cande- Distiller’s grain has come to be an important feed for cattle crease AP but will likely increase ADP, GWP, and ODP. production; therefore, the procedure used to allocate impacts Moreover, feeding distiller’s grain allows beneficial use of a between the by-products in ethanol production was given fur- by-product resulting in reductions in natural resources used ther consideration. The base analysis used an economic allo- which bodes well for CWU, land use, and emissions to water cation which assigned 21% of the bioethanol distillation envi- while providing environmental benefits outside of the beef ronmental burden to WDGS. As an alternative, a mass alloca- value chain. tion was used which placed 62% of the environmental burden Ozone depletion potential was primarily associated with on WDGS based on a distillation conversion ratio of 479 kg post-farm gate processes. The greatest contributor was the WDGS to 299 kg bioethanol (or 378 L bioethanol, given restaurant phase with 60% of ODP (Table 3). The use of ha- bioethanol’s density is 0.79 kg/L). This increased the burden logenated hydrocarbons in the restaurant, case-ready, and re- placed on the feed phase. Total value chain impacts included a tail phases and pre-chain emissions related to the production 4% increase in GWP (Fig. 4a) and a 53% increase in water of LDPE and vinyl gloves contributed most to the ODP. emissions (Fig. 4b). Energy content allocation was also con- The feed phase accounted for 90% of total value chain sidered, and this also resulted in 21% of the bioethanol distil- emissions to water, which was estimated as 7005 L diluted lation environmental burden being attributed to WDGS (Lory water eq/CB (Fig. 1 and Table 3). Contributors were 34% et al. 2008). One of the main reasons economic allocation was from nitrogen runoff and leaching, 33% from heavy metal chosen for calculating impacts of WDGS was because this runoff and leaching, and 19% from phosphorous runoff. approach was used for by-products in the harvesting phase Minor water emissions also came from pastureland runoff and therefore provided consistency. Furthermore, using and leaching. Wastewater from packing and case-ready existing pricing, the economic allocation scenario was further phases, pre-chain corrugated cardboard production impacts, supported by the energy allocation as resulting impacts of both and landfill leachate from waste disposal contributed notably approaches proved to be the same. to post-farm phase water emissions. The highest pollutant load Allocation effects were also determined for the burdens of to water arises from feed production; hence, increased effi- retail and consumer refrigeration and retail refrigerant leakage. ciency in fertilizer and pesticide use is recommended to reduce Volumetric allocation was originally chosen following ISO runoff and leachate losses. Greater use of by-product and standards which gave preference to a physical allocation pro- waste-product feeds may also reduce water emissions by re- viding representation was logical and data were available. The ducing feed crop production. use of economic allocation showed a 3% increase in GWP The estimated solid waste impact per CB of beef was 369 g (Fig. 4c) due to the increased impact of refrigerant leakage municipal waste eq, and this was mainly from production of as well as a 2% increase in the total value chain CED com- resource inputs as direct wastes generated within the value pared to volumetric allocation (Fig. 4d). However, as the chain were analyzed according to their final degradation. A weighted impact of the retail and consumer environmental major contributor to the solid waste value was pre-chain pro- metrics was not high, little change was observed in the total duction of dicalcium phosphate used in cattle feed supple- environmental impacts of the value chain. ments. Others were related to the production of electricity and the main transport fuels, diesel, and gasoline. The contri- 3.5 Impact reduction opportunities bution of the pre-chain production of inputs at each phase to the solid waste generated are shown in Fig. 2 and Table 3. Many opportunities exist for reducing the environmental im- pacts throughout the life cycle of beef. A thorough evaluation 3.3 Human toxicity and ranking of opportunities is beyond the scope of this cur- rent analysis, but these results do give some insight toward the The feed production phase accounted for 93.0% of the total more important or effective possible strategies. The primary value chain HTP, while the cow-calf and finish phases each sources or contributors vary greatly among the metrics used to contributed 3.4 and 2.7%, respectively (Fig. 2 and Table 3). quantify impact. Therefore, the most promising opportunities The main HTP contributors were the manufacturing and im- for reducing life cycle impacts depends upon the one or more pacts of fertilizer and pesticide application. Production of re- metrics considered to be most important or their ranking in source inputs and value chain fossil energy (coal, diesel, and importance. natural gas) use were also major contributors. Technological When extrapolating these data to other production systems improvements that enhance fertilizer use efficiency may re- and regions, importance will vary among the metrics consid- duce fertilizer needs, while reduced fossil fuel use would pro- ered. For example, some regions (Midwest and Eastern USA) vide HTP reductions. are wetter than others (Western USA) and thus require less Int J Life Cycle Assess Fig. 4 Environmental impacts of (c) (a) different EEA scenarios for beef. 0) a GWP determined using economic (base) and mass allocation of WDGS (scenario 1). b Water emissions using economic (base) and mass allocation of WDGS (scenario 1). c GWP using volumetric (base) and economic allocation for consumer refrigeration (scenario 3). d CED using volumetric (base) and economic allocation 0 0 for consumer refrigeration Base analysis Scenario 3 Base analysis Scenario 1 (scenario 3) 16,000 (d) 1,150 (b) 14,000 Restaurant 1,100 12,000 Consumer 10,000 Retail 1,050 8,000 Case-Ready 1,000 Packing 6,000 Finish 4,000 Cowcalf 2,000 Feed 0 900 Base analysis Scenario 1 Base analysis Scenario 3 water use; however, leaching and runoff of nutrients are higher supplement. Thus, more efficient use of this supplement can for the former (Asem-Hiablie et al. 2015, 2016, 2017). In reduce this impact. Global warming potential primarily results regions with large dairy herds where cull dairy calves are from the production of enteric methane and secondarily from incorporated into the beef herds, allocation of impacts of the nitrous oxide and methane emissions from manure. breeding herd to dairy reduces the environmental footprints of Acidification potential primarily results from ammonia emis- the beef produced (Capper 2011; Stackhouse-Lawson et al. sions from cattle manure. More efficient cattle production re- 2012;Rotz etal. 2015). Clearly, each region has its own duces both of these potentials. Maintaining breeding stock for unique opportunities for improvements. Ongoing studies are a full year to obtain a calf contributes a large portion of these using regional data to further identify these opportunities impacts. Thus, increasing calving rate and reducing death loss (Rotz et al. 2015). are potential benefits. Improving the rate of gain to finish Of the 11 metrics considered in our current analysis, feed cattle in a shorter period is of benefit because cattle impacts production was the major contributor in six (Fig. 2). In each of are directly related to the length of their life cycle. Closely these, feed production contributed about 90% or more of the related is an improvement in feed efficiency to obtain more total life cycle impact. Thus improvements in feed production gain per unit of feed consumed. More efficient feeding of and use appear as an important opportunity. A specific oppor- protein can also reduce the nitrogen excreted by cattle, which tunity is to increase crop and pasture yields to obtain more will reduce ammonia and nitrous oxide emissions. Alternative feed per unit of land. Improvement in the efficiency of fertil- cattle housing and manure handling practices can reduce emis- izer and pesticide use would reduce the need for these re- sions, but these major changes would not be economically sources as well as reduce their losses to the environment. viable for most producers. For example, use of a free-stall barn Less dependence upon irrigation or more efficient irrigation with an enclosed manure storage and subsurface injection of strategies in crop and pasture production could greatly reduce manure may greatly reduce ammonia, nitrous oxide, and CWU with some reduction in water emissions. Reduced till- methane emissions, but use of this technology would greatly age in crop establishment would reduce runoff and the asso- increase the cost of production compared to the use of an open ciated loss of nutrients; however, the USMARC production feedlot. system already uses minimum tillage practices. Post-farm gate processes are a predominate source of im- Cattle are a major contributor in three of the remaining pact in only 2 of the 11 metrics considered (ODP and solid impact categories (ADP, GWP, and AP, Fig. 2). Cattle’sim- waste, Fig. 2). Reduction in ODP can be obtained primarily through reduced use and emission of halogenated pact on ADP is primarily due to the feeding of zinc L diluted water-eq/CB kg CO -eq/CB MJ/CB kg CO eq/CB 2- Int J Life Cycle Assess hydrocarbons, primarily in the restaurant sector. This would as the packing and case-ready phases have been adopted by include reduced loss of refrigerants and less use of aerosols. some processors. These include biogas capture from wastewa- Solid waste is well distributed across all phases of the beef life ter lagoons at packing plants, increased natural gas use in lieu cycle. Benefits would be received through less waste of the of fuel oil, packaging optimizations, and improvements in beef product and more efficient use and recycling of packag- water use efficiency. ing materials. The restaurant, case-ready, and retail phases contributed Recent improvements at the post-farm phases offer oppor- more than 90% of the total ODP. This is attributed to haloge- tunities for further modest decreases in the overall value chain nated hydrocarbons used in refrigeration and pre-chain emis- impacts (BASF 2013b). In the packing phase, biogas genera- sions from the production of LDPE and vinyl gloves used in tion and recovery from wastewater lagoons and switching the restaurant phase. from fuel oil to natural gas use are reducing direct fossil ener- This study provides a benchmark for a more comprehen- gy use and impacts associated with the production of resource sive and descriptive national beef LCA. Ongoing studies are inputs that contribute to CED, ADP, GWP, POCP, AP, solid gathering information on region-specific feed and cattle man- waste generation, and land use. agement practices, which provide a basis for a more extensive Packaging optimizations in the packing and case-ready evaluation of cattle production throughout the USA. These phases are also reducing packaging (corrugated cardboard more comprehensive data will be used along with the packing, and LDPE) needs, transportation requirements, landfill case-ready, retail, and consumer data to better define a nation- wastes, as well as related pre-chain processes, which result al LCA of beef. in reduced CED, ADP, CWU, GWP, POCP, ODP, ADP, water emissions, and land use. Recent improvements in water use efficiency at the packing phase and case-ready phase packag- Open Access This article is distributed under the terms of the Creative ing optimizations also contribute to declines in water use Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, (BASF, 2013b). Further adoption of these and other practices distribution, and reproduction in any medium, provided you give can improve the sustainability of beef. appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 4 Conclusions References In this environmental assessment of a US beef full value chain system, the feed and cattle phases contributed the greatest AHAM (2011) Average household refrigerator energy use, volume, and impacts in most categories studied. Feed production price over time. Association of Home Appliance Manufacturers, accounted for 90% or greater of water emissions, POCP, Washington, D.C. http://www.appliance-standards.org/sites/default/ HTP, land use, CWU, and CED. Improved crop yields and files/Refrigerator%20Graph_July_2011.PDF. Accessed 29 more efficient use of fertilizer, pesticides, and other resource May 2015 inputs will help mitigate these impacts. Greater use of by- Asem-Hiablie S, Rotz CA, Stout R, Dillon J, Stackhouse-Lawson K (2015) Management characteristics of cow-calf, stocker, and product feeds may also lower impacts of the feed phase. finishing operations in Kansas, Oklahoma, and Texas. Prof Anim However, feeding of by-products should be well managed to Sci 31(1):1–10 prevent impacts such as increased NH and N O emissions 3 2 Asem-Hiablie S, Rotz CA, Stout R, Stackhouse-Lawson K (2016) from overfeeding protein. Management characteristics of beef cattle production in the Northern Plains and Midwest regions of the United States. Prof The cow-calf and finishing phases had the highest AP due Anim Sci 32:736–749 to NH emission from cattle feces and urine. Ammonia from Asem-Hiablie S, Rotz CA, Stout R, Fisher K (2017) Management char- fertilizer application in the feed phase also contributed signif- acteristics of beef cattle production in the western United States. Prof icantly. Abiotic resource use was highest at the cow-calf and Anim Sci 33:461–471 finishing phases primarily due to the feeding of Zn supple- BASF (2013a) Submission for verification of Eco-efficiency Analysis Under NSF Protocol P352, Part A. U.S. Beef –Phase 1 Eco- ments. The majority of the remaining ADP was attributed to efficiency Analysis. BASF Corporation, Florham Park http://www. fossil energy used to produce fertilizers and fuel for utilities nsf.org/newsroom_pdf/BASF_NCBA_US_Beef_Industry_ and transportation. Phase1_may2013.pdf. Accessed09June2017 The feed and cattle phases contributed substantially to BASF (2013b) More sustainable beef optimization project phase 1 final CED and GWP through bio-based renewable energy and en- report. BASF Corporation, Florham Park http://www. beefissuesquarterly.com/CMDocs/BeefResearch/Sustainability% teric CH emissions, respectively. These sources are associat- 20Completed%20Project%20Summaries/NCBA%20Phase%201% ed with the animal’s physiological functions and are currently 20Final%20Report_Amended%20with%20NSF%20Verified% challenging to manage. Opportunities for energy conservation 20Report_for_posting_draft%20WM_KS.pdf. Accessed 09 November 2017 and GWP reduction in other segments of the value chain such Int J Life Cycle Assess BASF (2015) Submission for verification of Eco-Efficiency Analysis Guinée JB, Gorrée M, Heijungs R, Huppes G, Kleijn R, de Koning A, van Oers L, Sleeswijk AW, Suh S, de Haes HAU, de Bruijn H, van Duin under NSF Protocol P352, Part B. U.S. beef – Phase 2 Eco- Efficiency Analysis. BASF Corporation, Florham Park http:// R, Huijbregts MAJ (2002) Handbook on life cycle assessment. www.beefissuesquarterly.com/CMDocs/BeefResearch/ Operational guide to the ISO standards. I: LCA in perspective. IIa: Sustainability%20Completed%20Project%20Summaries/BASF_ Guide. IIb: Operational annex. III: Scientific background. Kluwer NCBA%20US%20Beef%20Industry%20Phase2_%20NSF% Academic Publishers, Dordrecht ISBN 1–4020–0228-9. http://cml. 20EEA%20Analysis%20Report_FINAL.pdf. Accessed 18 April leiden.edu/research/industrialecology/researchprojects/finished/ 2015 new-dutch-lca-guide.html#reports-in-the-english-language-last- Belflower JB, Bernard JK, Gattie DK, Hancock DW, Risse LM, Rotz CA update-3-july-2002. Accessed05232015 (2012) A case study of the potential environmental impacts of dif- Heijungs R, Guinée JB, Huppes G, Lankreijer RM, Udo de Haes HA, ferent dairy production systems in Georgia. Agric Syst 108:84–93. Wegener Sleeswijk A, Ansems AMM, Eggels PG, van Duin R, de https://doi.org/10.1016/j.agsy.2012.01.005 Goede HP (1992) Environmental life cycle assessment of products: Bonnardeaux J (2007) Potential uses for distillers grains. Department of guide and backgrounds (Part 1). CML, Leiden https://openaccess. Agriculture and Food. Government of Western Australia, South leidenuniv.nl/handle/1887/8061. Accessed05292015 Perth15pp ICF Consulting (2005) Revised draft analysis of U.S. commercial super- Boustead LCI database (2005) Ver. 5.1.2600.2180. Boustead Consulting market refrigeration systems. Prepared for the U.S. EPA stratospher- Ltd., Horsham ic protection division. https://www.epa.gov/sites/production/files/ BP (2012) BP statistical review of world energy. BP, London https:// documents/EPASupermarketReport_PUBLIC_30Nov05.pdf www.bp.com/en/global/corporate/energy-economics/statistical- Accessed 29 May 2015 review-of-world-energy/downloads.html.Accessed03January IPCC (2006) Guidelines for national greenhouse inventories, Volume 4. Chapter 11: N O emissions from managed soils, and CO emissions 2 2 Capper JL (2011) The environmental impact of beef production in the from lime and urea application. http://www.ipcc-nggip.iges.or.jp/ United States: 1977 compared with 2007. J Anim Sci 89(12):4249– public/2006gl/pdf/4_Volume4/V4_11_Ch11_N2O&CO2.pdf Accessed 29 May 2015 Chianese DS, Rotz CA, Richard TL (2009a) Simulation of carbon diox- ISO (2006a) ISO 14040: environmental management—life cycle assess- ide emissions from dairy farms to assess greenhouse gas reduction ment—principles and framework. ISO, Geneva http://wwwisoorg/ strategies. Trans ASABE 52:1301–1312 iso/catalogue_detail?csnumber=37456 Accessed 29 June 2015 Chianese DS, Rotz CA, Richard TL (2009b) Simulation of methane ISO (2006b) ISO 14044: Environmental management—life cycle assess- emissions from dairy farms to assess greenhouse gas reduction strat- ment—requirements and guidelines. ISO, Geneva http://www.iso. egies. Trans ASABE 52:1313–1323 org/iso/catalogue_detail?csnumber=38498. Accessed 29 June 2015 Corson MS, Rotz CA, Skinner RH, Sanderson MA (2007) Adaptation ISO (2012) ISO 14045: Environmental management—eco-efficiency as- and evaluation of the integrated farm system model to simulate sessment of product systems—principles, requirements and guide- temperate multiple-species pastures. Agric Syst 94:502–508 lines. ISO, Geneva http://www.iso.org/iso/catalogue_detail? Deak A, Hall MH, Sanderson MA, Rotz A, Corson M (2010) Whole- csnumber=38498. Accessed 06 29 2015 farm evaluation of forage mixtures and grazing strategies. Agron J Koellner T, Scholz R (2008) Assessment of land use impacts on the 102:1201–1209 natural environment. Int J Life Cycle Assess 13:32–48 Dudley QM, Liska AJ, Watson AK, Erickson GE (2014) Uncertainties in Landsiedel R, Saling P (2002) Assessment of toxicological risks for life life cycle greenhouse gas emissions from US beef cattle. J Clean cycle assessment and eco-efficiency analysis. Int J Life Cycle Prod 75:31–39 Assess 7:261–268 FMI (2012) Supermarket sales: supermarket sales by department—per- Lory JA, Massey RE, Fulhage CD, Shannon MD, Belyea RL, Zulovich cent of total supermarket sales. Food Marketing Institute. http:// JM (2008) Comparing the feed, fertilizer, and fuel value of distiller's www.fmi.org/docs/facts-figures/grocerydept.pdf?sfvrsn=2. grains. Crop Manag 7(1). https://doi.org/10.1094/CM-2008-0428- Accessed 29 May 2015 01-RV Forster P, Ramaswamy V, Artaxo P, Berntsen T, Betts R, Fahey DW, Lupo CD, Clay DE, Benning JL, Stone JJ (2013) Life-cycle assessment Haywood J, Lean J, Lowe DC, Myhre G, Nganga J, Prinn R, of the beef cattle production system for the northern great plains, Raga G, Schulz M, Van Dorland R (2007) Changes in atmospheric USA. J Environ Qual 42:1386–1394 constituents and in radiative forcing. In: Solomon S, Qin D, Meat Solutions, Inc. (2014) Technomic foodservice volumetric study; Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller Freshlook/IRI categorized by VMMeat system; meat solutions an- HL (eds) Climate change 2007: the physical science basis. nual beef consumption report, prepared for the beef checkoff. Contribution of working group I to the fourth assessment report of Unpublished internal document the intergovernmental panel on climate change. Cambridge Pelletier N, Pirog R, Rasmussen R (2010) Comparative life cycle envi- University Press, Cambridge, pp 129–234 ronmental impacts of three beef production strategies in the upper Freiermuth R (2006) Modell zur Berechnung der Schwermetall-flüsse in Midwestern United States. Int J Life Cycle Assess 103:380–389 der Landwirtschaftlichen Ökobilanz. SALCA-Schwermetall. Pfister S, Koehler A, Hellweg S (2009) Assessing the environmental Agroscope, Zurich http://www.agroscope.admin.ch/oekobilanzen/ impacts of freshwater consumption in LCA. Environ Sci Technol 01199/08185/index.html?lang=en. Accessed 29 May 2015 43:4098–4104 Frischknecht R, Jungbluth N, Althaus HJ, Doka G, Dones R, Heck T, Roop DJ, Shrestha DS, Saul DA, Newman S (2014) Cradle-to-gate life Hellweg S, Hischier R, Nemecek T, Rebitzer G, Spielmann M cycle assessment of regionally produced beef in the northwestern (2005) The ecoinvent database: overview and methodological US. Trans ASABE 57:927–935 framework. Int J Life Cycle Assess 10:3–9 Ghafoori E, Flynn PC, Checkel MD (2006) Global warming impact of Rotz CA, Oenema J, van Keulen H (2006) Whole farm management to electricity generation from beef cattle manure: a life cycle assess- reduce nutrient losses from dairy farms: a simulation study. Appl ment study. Int J Green Energy 3:257–270 Eng Agric 22(5):773–784 Ghebremichael LT, Watzin MC (2011) Identifying and controlling critical Rotz CA, Montes F, Chianese DS (2010) The carbon footprint of dairy sources of farm phosphorus imbalances for Vermont dairy farms. production systems through partial life cycle assessment. J Dairy Sci Agric Syst 104:551–561 93:1266–1282 Int J Life Cycle Assess Rotz CA, Corson MS, Chianese DS, Montes F, Hafner SD, Coiner CU USDA-ERS (2012b) Food availability dataset. USDA Economic Research Service. http://wwwersusdagov/data-products/ (2012) Integrated farm system model: reference manual. University Park, USDA Agricultural Research Service http://www.ars.usda. commodity-consumption-by-population-characteristicsaspx. gov/SP2UserFiles/Place/19020000/ifsmreference.pdf.Accessed 29 Assessed 28 April 2015 May 2015 USDA-ERS (2017) Feed grains data: yearbook tables. USDA Economic Rotz CA, Isenberg BJ, Stackhouse-Lawson KR, Pollak EJ (2013) A Research Service. http://www.ers.usda.gov/data-products/feed- simulation-based approach for evaluating and comparing the envi- grains-database/feed-grains-yearbook-tables.aspx. Accessed 25 ronmental footprints of beef production systems. J Anim Sci 91: October 2017 5427–5437 USDA-FAS (2015) Summary: major traders and US trade of beef, pork, Rotz CA, Asem-Hiablie S, Dillon J, Bonifacio H (2015) Cradle-to-farm and poultry. USDA Foreign Agricultural Service. http://apps.fas. gate environmental footprints of beef cattle production in Kansas, usda.gov/psdonline/circulars/livestock_poultry.pdf.Assessed28 Oklahoma, and Texas. J Anim Sci 93:2509–2519 April 2015 Salim J, Dillon C, Saghaian S, Hancock D (2005) Economic response of USDOT (2011) 2009 National household travel survey. US Department site-specific management practices on alfalfa production quantity of Transportation. http://nhts.ornl.gov/2009/pub/stt.pdf. Accessed and quality. In: Cox S (ed) Precision livestock farming ‘05: proceed- 29 May 2015 ings of the 2nd European conference on precision livestock farming USEIA (2005) 2005 Residential consumption energy survey (RECS). US June 9–12 2005. Wageningen Academic Publishers, Uppsala, pp Energy Information Administration http://wwweiagov/ 241–247 consumption/residential/data/2005/. Accessed 29 May 2015 Saling P, Kicherer A, Dittrich-Krämer B, Wittlinger R, Zombik W, USEPA (2010) Municipal solid waste generation, recycling, and disposal Schmidt I, Schrott W, Schmidt S (2002) Eco-efficiency analysis by in the United States: facts and figures for 2010. US Environmental BASF: the method. Int J Life Cycle Assess 7:203–218 Protection Agency. http://www.nrc.gov/docs/ML1409/ Sedorovich DM, Rotz CA, Vadas PA, Harmel RD (2007) Simulating ML14094A389.pdf. Accessed 29 May 2015 management effects on phosphorus loss from farming systems. USEPA (2011) Profile of an average U.S. supermarket’s greenhouse gas Trans ASABE 50:1443–1453 impacts from refrigeration leaks compared to electricity consump- Solley WB, Pierce RR, Perlman HA (1998) Estimated use of water in the tion. US Environmental Protection Agency. https://www.epa.gov/ United States in 1995 U.S. Geological Survey Circular 1200 U.S. sites/production/files/documents/gc_averagestoreprofile_final_ Dept. of the Interior, U.S. Geological Survey, Branch of Information june_2011_revised_1.pdf. Accessed 09 January, 2018 Services USEPA (2012) Supermarkets: an overview of energy use and energy Stackhouse KR, Rotz CA, Oltjen JW, Mitloehner FM (2012) Growth- efficiency opportunities. US Environmental Protection Agency. promoting technologies decrease the carbon footprint, ammonia https://www.energystar.gov/sites/default/files/buildings/tools/SPP% emissions, and costs of California beef production systems. J 20Sales%20Flyer%20for%20Supermarkets%20and%20Grocery% Anim Sci 90:4656–4665 20Stores.pdf. Accessed 29 May 2015 Stackhouse-Lawson KR, Rotz CA, Oltjen JW, Mitloehner FM (2012) USGS (2012) Mineral commodity summaries 2012: U.S. Geological Carbon footprint and ammonia emissions of California beef produc- Survey. https://minerals.usgs.gov/minerals/pubs/mcs/2012/ tion systems. J Anim Sci 90:4641–4655 mcs2012.pdf. Accessed 05 Jan 2018 Uhlman BW, Saling P (2010) Measuring and communicating sustainabil- Waldrip HM, Rotz CA, Hafner SD, Todd RW, Cole NA (2014) Process- ity through eco-efficiency analysis. Chem Eng Prog 106:17–26 based modeling of ammonia emission from beef cattle feedyards USDA-ERS (2005) Daily intake of food at home and away from home: with the integrated farm systems model. J Environ Qual 43:1159– 2003-2004. USDA Economic Research Service. http://www. ersusdagov/data-products/food-consumption-and-nutrient- intakesaspx. Accessed 29 May 2015 Wiedemann S, McGahan E, Murphy C, Yan MJ, Henry B, Thoma G, USDA-ERS (2012a) Loss-adjusted food availability for meat, poultry, Ledgard S (2015) Environmental impacts and resource use of fish, eggs, and nuts. USDA Economic Research Service. http:// Australian beef and lamb exported to the USA determined using life www.ers.usda.gov/data-products/food-availability-(per-capita)- cycle assessment. J Clean Prod 94:67–75 data-system/.aspx.Accessed 29 May 2015
The International Journal of Life Cycle Assessment – Springer Journals
Published: May 30, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera