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Changes in the production of Australian cotton lint are expected to have a direct environmental impact, as well as indirect impacts related to co-product substitution and induced changes in crop production. The environmental consequences of a 50% expansion or contraction in production were compared to Australian cotton production’s current environmental footprint. Both were then assessed to investigate whether current impacts are suitable for predicting the environmental impact of a change in demand for cotton lint. A consequential life cycle assessment (LCA) model of Australian cotton lint production (cradle-to-gin gate) was developed using plausible scenarios regarding domestic regions and technologies affected by changes in supply, with both expansion (additional cotton) and contraction (less cotton) being modelled. Modelling accounted for direct impacts from cotton production and indirect impacts associated with changes to cotton production, including co-product substitution and changes to related crops at regional and global scales. Impact categories assessed included climate change, fossil energy demand, freshwater consumption, water stress, marine and freshwater eutrophication, land occupation and land-use change. For both the expansion and contraction scenarios, the changes to climate change impacts (including iLUC) and water impacts were less than would be assumed from current production as determined using attributional LCA. However, the opposite was true for all other impact categories, indicating trade-offs across the impact categories. Climate change impacts under both scenarios were relatively minor because these were largely offset by iLUC. Similarly, under the contraction scenario, water impacts were dominated by indirect impacts associated with regional crops. A sensitivity analysis showed that the results were sufficiently robust to indicate the quantum of changes that could be expected. A complex array of changes in technologies, production regions and related crops were required to model the environmental impacts of a gross change in cotton production. Australian cotton lint production provides an example of legislation constraining the direct water impacts of production, leading to a contrast between impacts estimated by attributional and consequential LCA. This model demonstrated that indirect products and processes are important contributors to the environmental impacts of Australian cotton lint.

Purpose Garment production and use generate substantial environmental impacts, and the care and use are key determinants of cradle-to-grave impacts. The present study investigated the potential to reduce environmental impacts by applying best practices for garment care combined with increased garment use. A wool sweater is used as an example because wool garments have particular attributes that favour reduced environmental impacts in the use phase. Methods A cradle-to-grave life cycle assessment (LCA) was used to compare six plausible best and worst-case practice scenarios for use and care of a wool sweater, relative to current practices. These focussed on options available to consumers to reduce impacts, including reduced washing frequency, use of more efficient washing machines, reduced use of machine clothing dryers, garment reuse by multiple users, and increasing number of garment wears before disposal. A sixth scenario combined all options. Worst practices took the worst plausible alternative for each option investigated. Impacts were reported per wear in Western Europe for climate change, fossil energy demand, water stress and freshwater consumption. Results and discussion Washing less frequently reduced impacts by between 4 and 20%, while using more efficient washing machines at capacity reduced impacts by 1 to 6%, depending on the impact category. Reduced use of machine dryer reduced impacts by Conclusions Wool sweaters have potential for long life and low environmental impact in use, but there are substantial differences between the best, current and worst-case scenarios. Detailed information about garment care and lifespans is needed to understand and reduce environmental impacts. Opportunities exist for consumers to rapidly and dramatically reduce these impacts. The fashion industry can facilitate this through garment design and marketing that promotes and enables long wear life and minimal care.

Purpose The textiles industry is a substantial contributor to environmental impacts through the production, processing, use, and end-of-life of garments. Wool is a high value, natural, and renewable fibre that is used to produce a wide range of garments, from active leisure wear to formal wear, and represents a small segment of the global fashion industry. Woollen garments are produced by long, global value chains extending from the production of ‘greasy’ wool on sheep farms, through processing to garment make-up, retail, consumer use, and end-of-life. To date, there have been limited life cycle assessment (LCA) studies on the environmental impacts of the full supply chain or use phase of garments, with the majority of wool LCA studies focusing on a segment of the supply chain. This study aimed to address this knowledge gap via a cradle-to-grave LCA of a woollen garment. Methods This study investigated greenhouse gas (GHG) emissions, fossil fuel energy, and water stress associated with the production, use, and end-of-life of a lightweight woollen sweater (300-g wool), together with inventory results for freshwater consumption and land occupation. Primary datasets were used for the wool production and wool processing stages, while primary datasets relating to consumer garment use were supplemented with literature data. Impacts were calculated and reported per garment wear event. Results and discussion Impacts per wear were 0.17 (± 0.02) kg CO2-e GHG, 0.88 (± 0.18) MJ fossil energy, and 0.96 (± 0.42) H2O-e water stress. Fossil fuel energy was dominated by wool processing, with substantial contributions of energy also arising from retail and garment care. Greenhouse gas emissions from wool production (farming) contributed the highest proportion of impacts, followed by lower contributions from processing and garment care. Contributions to water stress varied less across the supply chain, with major contributions arising from production, processing, and garment use. Conclusions Opportunities to improve the efficiency of production, processing, and garment care exist, which could also reduce resource use and impacts from wool. However, the number of garment wear events and length of garment lifetime was found to be the most influential factor in determining garment impacts. This indicated that consumers have the largest capacity to influence the sustainability of their woollen garments by maximising the active garment lifespan which will reduce overall impacts.

Little is known regarding manure nutrient deposition in free range egg layer facilities. Consequently, a significant knowledge gap exists regarding how to best manage soil nutrient loading on these farms. Here, we report on soil nutrient properties across 14 Australian free range farms. Electromagnetic-induction (EM) mapping was performed at each farm to select soil sample locations which were collected at an average depth of 30 cm. EM data exhibited promising relationships with key soil properties. Measured soil properties were highly variable between and within farms. Soil nitrate-N (NO3-N) and Colwell-P (Col-P) concentrations ranged from 1 to 529 mg N kg−1 and 11 to 1856 mg P kg−1. Average NO3-N and Col-P concentrations across farms were 100 mg N kg−1 and 250 mg P kg−1 which exceed typical background nutrient levels and exceed requirements for dryland crop or pasture production. Farms with trees exhibited 2.6 × and 2.1 × greater NO3-N and Col-P concentrations than farms with no trees (P

Agri-food industries such as chicken meat production face increasing pressure to quantify and improve their environmental performance over time, while simultaneously increasing production to meet global demand. Using life cycle assessment, this study aimed to quantify resource use, environmental impacts and hotspots for Australian chicken meat production using updated inventories and new methods. Two contrasting states; Queensland, and South Australia, and two housing systems; conventional and free range were analysed to indicate the variation expected between regions and systems. Lower impacts were observed per kilogram of chicken meat produced in South Australia compared to Queensland for fossil fuel energy, greenhouse gas (including land use and direct land use change) and fresh water consumption (18.1 and 21.4 MJ, 2.8 and 3.4 kg CO 2 -e, 38 and 111 L respectively), but not arable land or stress weighted water use (22.5 and 14 m 2 , 36 and 26 L H 2 O-e respectively). Feed production was the largest contributor to all impact categories, and also showed the largest variation between regions, highlighting the importance of spatially specific feed grain datasets to determine resource use and greenhouse gas from chicken meat production. While the feed conversion ratio was lower in South Australia, this was found to be less significant than differences related to crop yield, irrigation water use and the use of imported feed ingredients, suggesting that incremental improvements in feed conversion ratio will result in lower impacts only when feed inputs and production systems do not change. Fresh water consumption was lower in South Australia, but did not correlate with stress weighed water use (lower in Queensland), highlighting that volumetric water use is not a reliable indicator of the impact of water use. We did not observe substantial differences between conventional and free range production when feed related differences were removed, because key productivity factors such as feed conversion ratio were similar between the two housing types in Australia. While results were found to vary between regions, total greenhouse gas emissions were low from these Australian supply chains, and resource use was moderate. Expansion of the study to include additional regions and impact categories is recommended in future benchmarking studies.

Increasing the use of each product, most often called longer lifespans, is an effective environmental strategy. This article discusses how garment lifespans can be described in order to be measured and compared. It answers two sub-questions: (1) what to measure (units), and (2) how to measure (methods). We introduce and define terms related to clothing lifespans and contribute to discussions about an appropriate functional unit for garments in life cycle assessments (LCA) and other environmental accounting tools. We use a global wardrobe survey to exemplify the units and methods. Clothing lifespans can be described and measured in years, the number of wears, cleaning cycles, and users. All have an independent value that show different and central aspects of clothing lifespans. A functional unit for LCAs should emphasise both the number of wears for all users as well as the service lifespan in years. Number of wears is the best measure for regular clothing, while number of years is most suited for occasion wear, because it is important to account for the need of more garments to cover all the relevant occasions during a specified time period. It is possible to study lifespan via carefully constructed surveys, providing key data relating to actual garment use. This work was supported by Australian wool growers and the Australian Government through Australian Wool Innovation Limited (AWI), contract number 4500012208, and the Research Council of Norway, project number 303080.

Over the past three decades major changes have occurred in Australia's beef industry, affecting productivity and potentially the amount of resources used and environmental impacts from production. Using a life cycle assessment (LCA) approach with a ‘cradle-to-farm gate’ boundary the changes in greenhouse gas (GHG) emission intensity and key resource use efficiency factors (water use, fossil fuel energy demand and land occupation) are reported for the 30 years from 1981 to 2010, for the Australian beef industry. The analysis showed that over the three decades since 1981 there has been a decrease in GHG emission intensity (excluding land use change emissions) of 14% from 15.3 to 13.1 kg CO2-e/kg liveweight (LW). The improvement was largely due to efficiency gains through heavier slaughter weights, increases in growth rates in grass-fed cattle, improved survival rates and greater numbers of cattle being finished on grain. However, the increase in supplement and grain use on farms, and the increase in feedlot finishing, resulted in a twofold increase in fossil fuel energy demand for beef production over the same time. Fresh water consumption for beef production dropped to almost a third from 1465 L/kg LW in 1981 to 515 L/kg LW in 2010. Three contributing factors for this dramatic reduction in water use were: (i)an increase in the competitive demand for irrigation water, resulting in a transfer away from pasture for cattle to higher value industries such as horticulture, (ii) an initiative to cap free flowing artesian bores in the rangelands, and (iii) an overall decline in water available for agriculture compared to industrial and domestic uses. While there was higher uncertainty relating to estimates of land occupation and emissions from land use (LU) and direct land use change (dLUC), an inventory of land occupation indicated a decline in non-arable land occupation of about 19%, but a sevenfold increase in land occupation for feed production, albeit from a low base in 1981. GHG emissions associated with LU and dLUC for grazing were estimated to have declined by around 42% since 1981, due largely to legislated restrictions on broad-scale deforestation which were introduced progressively between 1996 and 2006. This paper discusses the prospects and challenges for further gains in resource use efficiency and reductions in greenhouse gas intensity for Australian beef production.

This paper describes part of the first detailed environmental life cycle assessment (LCA) of Australian red meat (beef and sheep meat) production. The study was intended to assist the methodological development of life cycle impact assessment by examining the feasibility of new indicators for natural resource management (NRM) issues relevant to soil management in agricultural LCA. This paper is intended to describe the NRM indicators directly related to agricultural soil chemistry. Three nutrient management indicators—nitrogen (N), phosphorus (P) and potassium (K) balances—were estimated on the basis of 1 kg of hot standard carcass weight (HSCW) for three grazing properties in Australia. We also examined a soil acidification indicator based on the effects of agricultural practices. The N balance for the grazing properties varied from a loss of 28 g N/kg HSCW to an accumulation of 170 g N/kg HSCW. For comparison, the N content of cattle is about 24 g/kg liveweight. The main contributors to these changes were the growth of N-fixing pastures (or lack thereof) and the application of fertilisers. The P and the K balances showed similar results, varying from a 3.9-g loss to a 19-g accumulation of P and a 4-g loss to a 95-g accumulation of K per kilogram HSCW. Decisions about pasture management were also reflected in the results of the soil acidification indicator. We also identified that soil erosion at the grazing properties is a significant component of nutrient losses. The results suggest that reducing the leaching of soil N might be the best way to balance the N budget without causing acidification. The NRM indicators developed can be benchmarked against other production systems as the application of these indicators progresses.

Life cycle assessment (LCA) and life cycle inventory (LCI) practice needs to engage with the debate on water use in agriculture and industry. In the case of the red meat sector, some of the methodologies proposed or in use cannot easily inform the debate because either the results are not denominated in units that are meaningful to the public or the results do not reflect environmental outcomes. This study aims to solve these problems by classifying water use LCI data in the Australian red meat sector in a manner consistent with contemporary definitions of sustainability. We intend to quantify water that is removed from the course it would take in the absence of production or degraded in quality by the production system. The water used by three red meat supply systems in southern Australia was estimated using hybrid LCA. Detailed process data incorporating actual growth rates and productivity achieved in two calendar years were complemented by an input–output analysis of goods and services purchased by the properties. Detailed hydrological modelling using a standard agricultural software package was carried out using actual weather data. The model results demonstrated that the major hydrological flows in the system are rainfall and evapotranspiration. Transferred water flows and funds represent small components of the total water inputs to the agricultural enterprise, and the proportion of water degraded is also small relative to the water returned pure to the atmosphere. The results of this study indicate that water used to produce red meat in southern Australia is 18–540 L/kg HSCW, depending on the system, reference year and whether we focus on source or discharge characteristics. Two key factors cause the considerable differences between the water use data presented by different authors: the treatment of rain and the feed production process. Including rain and evapotranspiration in LCI data used in simple environmental discussions is the main cause of disagreement between authors and is questionable from an environmental impact perspective because in the case of some native pastoral systems, these flows may not have changed substantially since the arrival of Europeans. Regarding the second factor, most of the grain and fodder crops used in the three red meat supply chains we studied in Australia are produced by dryland cropping. In other locations where surface water supplies are more readily available, such as the USA, irrigation of cattle fodder is more common. So whereas the treatment of rain is a methodological issue relevant to all studies relating water use to the production of red meat, the availability of irrigation water can be characterised as a fundamental difference between the infrastructure of red meat production systems in different locations. Our results are consistent with other published work when the methodological diversity of their work and the approaches we have used are taken into account. We show that for media claims that tens or hundreds of thousands of litres of water are used in the production of red meat to be true, analysts have to ignore the environmental consequences of water use. Such results may nevertheless be interesting if the purpose of their calculations is to focus on calorific or financial gain rather than environmental optimisation. Our approach can be applied to other agricultural systems. We would not suggest that our results can be used as industry averages. In particular, we have not examined primary data for northern Australian beef production systems, where the majority of Australia’s export beef is produced.

Greenhouse gas emissions from beef production are a significant part of Australia's total contribution to climate change. For the first time an environmental life cycle assessment (LCA) hybridizing detailed on-site process modeling and input−output analysis is used to describe Australian red meat production. In this paper we report the carbon footprint and total energy consumption of three supply chains in three different regions in Australia over two years. The greenhouse gas (GHG) emissions and energy use data are compared to those from international studies on red meat production, and the Australian results are either average or below average. The increasing proportion of lot-fed beef in Australia is favorable, since this production system generates lower total GHG emissions than grass-fed production; the additional effort in producing and transporting feeds is effectively offset by the increased efficiency of meat production in feedlots. In addition to these two common LCA indicators, in this paper we also quantify solid waste generation and a soil erosion indicator on a common basis. Refereed/Peer-reviewed

Utilisation of water, energy and land resources is under pressure globally because of increased demand for food, fibre and fuel production. Australian pork production utilises these resources both directly to grow and process pigs, and indirectly via the consumption of feed and other inputs. With increasing demand and higher costs associated with these resources, supply chain efficiency is a growing priority for the industry. This study aimed to quantify fresh water consumption, stress-weighted water use, fossil fuel energy use and land occupation from six case study supply chains and the national herd using a life cycle assessment approach. Two functional units were used: 1 kg of pork liveweight (LW) at the farm-gate, and 1 kg of wholesale pork (chilled, bone-in). At the farm-gate, fresh water consumption from the case study supply chains ranged from 22.2 to 156.7 L/kg LW, with a national average value of 107.5 L/kg LW. Stress-weighted water use ranged from 6.6 to 167.5 L H2O-e /kg LW, with a national average value of 103.2 L H2O-e /kg LW. Fossil fuel energy demand ranged from 12.9 to 17.4 MJ/kg LW, with a national average value of 14.5 MJ/kg LW, and land occupation ranged from 10.9 to 16.1 m2/kg LW, with a national average value of 16.1 m2/kg LW and with arable land representing 97% to 99% of total land occupation. National average impacts associated with production of wholesale pork, including impacts from meat processing, were 184 ± 43 L fresh water consumption, 172 ± 53 L H2O-e stress-weighted water, 27 ± 2.6 MJ fossil fuel energy demand and 25.9 ± 5.5 m2 land/kg wholesale pork. Across all categories through to the wholesale product, resource use was highest from the production of feed inputs, indicating that improving feed conversion ratio is the most important production metric for reducing the resource use. Housing type and energy generation from manure management also influence resource use requirements and may offer improvement opportunities.

Grain finishing of cattle has become increasingly common in Australia over the past 30 years. However, interest in the associated environmental impacts and resource use is increasing and requires detailed analysis. In this study we conducted a life cycle assessment (LCA) to investigate impacts of the grain-finishing stage for cattle in seven feedlots in eastern Australia, with a particular focus on the feedlot stage, including the impacts from producing the ration, feedlot operations, transport, and livestock emissions while cattle are in the feedlot (gate-to-gate). The functional unit was 1 kg of liveweight gain (LWG) for the feedlot stage and results are included for the full supply chain (cradle-to-gate), reported per kilogram of liveweight (LW) at the point of slaughter. Three classes of cattle produced for different markets were studied: short-fed domestic market (55–80 days on feed), mid-fed export (108–164 days on feed) and long-fed export (>300 days on feed). In the feedlot stage, mean fresh water consumption was found to vary from 171.9 to 672.6 L/kg LWG and mean stress-weighted water use ranged from 100.9 to 193.2 water stress index eq. L/kg LWG. Irrigation contributed 57–91% of total fresh water consumption with differences mainly related to the availability of irrigation water near the feedlot and the use of irrigated feed inputs in rations. Mean fossil energy demand ranged from 16.5 to 34.2 MJ lower heating values/kg LWG and arable land occupation from 18.7 to 40.5 m2/kg LWG in the feedlot stage. Mean greenhouse gas (GHG) emissions in the feedlot stage ranged from 4.6 to 9.5 kg CO2-e/kg LWG (excluding land use and direct land-use change emissions). Emissions were dominated by enteric methane and contributions from the production, transport and milling of feed inputs. Linear regression analysis showed that the feed conversion ratio was able to explain >86% of the variation in GHG intensity and energy demand. The feedlot stage contributed between 26% and 44% of total slaughter weight for the classes of cattle fed, whereas the contribution of this phase to resource use varied from 4% to 96% showing impacts from the finishing phase varied considerably, compared with the breeding and backgrounding. GHG emissions and total land occupation per kilogram of LWG during the grain finishing phase were lower than emissions from breeding and backgrounding, resulting in lower life-time emissions for grain-finished cattle compared with grass finishing.

Greenhouse gas (GHG) and ammonia emissions are important environmental impacts from meat chicken houses. This study measured ammonia (NH3), nitrous oxide (N2O) and methane (CH4) in two trials from paired, commercial meat chicken houses using standard (control) and mitigation strategies. In Trial 1, emissions from houses with standard litter depth of 47 mm (LD47) or increased litter depth of 67 mm (LD67) were compared. When standardised to a 42-day-old bird, emissions were 11.9 g NH3/bird, 0.30 g N2O/bird and 0.16 g CH4/bird from the LD47 and 11.7 g NH3/bird, 0.69 g N2O/bird and 0.12 g CH4/bird from the LD67. Emissions per kilogram of manure N were 0.14 and 0.11 for NH3-N, 0.003 and 0.005 N2O-N and CH4 conversion factors were 0.08% and 0.05%. Total direct and indirect GHG emissions reported in carbon dioxide equivalents were found to be higher in LD67 in response to the elevated direct N2O emissions. Trial 2 compared the impact of reduced crude protein (CP19.8) and a standard diet (CP21.3) developed using least-cost ration formulation, on emissions. Emissions per bird for the CP19.8 diet were 7.7 g NH3/bird, 0.39 g N2O/bird and 0.14 g CH4/bird, while emissions from birds fed the CP21.3 diet were 10.6 g NH3/bird, 0.42 g N2O/bird and 0.19 g CH4/bird. Significant differences were observed only in the NH3 results, where emissions were reduced by 27% for the low-CP diet. Because of the low emission levels, total mitigation potential from indirect GHG emissions was relatively small in Trial 2, corresponding to 11 t carbon dioxide equivalents/year per million birds.

This study conducted a life cycle assessment (LCA) investigating energy, land occupation, greenhouse gas (GHG) emissions, fresh water consumption and stress-weighted water use from production of export lamb in the major production regions of New South Wales, Victoria and South Australia. The study used data from regional datasets and case study farms, and applied new methods for assessing water use using detailed farm water balances and water stress weighting. Land occupation was assessed with reference to the proportion of arable and non-arable land and allocation of liveweight (LW) and greasy wool was handled using a protein mass method. Fossil fuel energy demand ranged from 2.5 to 7.0 MJ/kg LW, fresh water consumption from 58.1 to 238.9 L/kg LW, stress-weighted water use from 2.9 to 137.8 L H2O-e/kg LW and crop land occupation from 0.2 to 2.0 m2/kg LW. Fossil fuel energy demand was dominated by on-farm energy demand, and differed between regions and datasets in response to production intensity and the use of purchased inputs such as fertiliser. Regional fresh water consumption was dominated by irrigation water use and losses from farm water supply, with smaller contributions from livestock drinking water. GHG emissions ranged from 6.1 to 7.3 kg CO2-e/kg LW and additional removals or emissions from land use (due to cultivation and fertilisation) and direct land-use change (due to deforestation over previous 20 years) were found to be modest, contributing between –1.6 and 0.3 kg CO2-e/kg LW for different scenarios assessing soil carbon flux. Excluding land use and direct land-use change, enteric CH4 contributed 83–89% of emissions, suggesting that emissions intensity can be reduced by focussing on flock production efficiency. Resource use and emissions were similar for export lamb production in the major production states of Australia, and GHG emissions were similar to other major global lamb producers. The results show impacts from lamb production on competitive resources to be low, as lamb production systems predominantly utilised non-arable land unsuited to alternative food production systems that rely on crop production, and water from regions with low water stress.

Mitigation of agricultural greenhouse gas emissions is a target area for the Australian Government and the pork industry. The present study measured methane (CH4), nitrous oxide (N2O) and ammonia (NH3) from a deep-litter piggery and litter stockpile over two trials in southern New South Wales, to compare emissions from housing pigs on deep litter with those of pigs from conventional housing with uncovered anaerobic effluent-treatment ponds. Emissions were measured using open-path Fourier transform infrared spectrometry, in conjunction with a backward Lagrangian stochastic model. Manure excretion was determined by mass balance and emission factors (EFs) were developed to report emissions relative to volatile solids and nitrogen (N) input. Nitrous oxide emissions per animal unit (1 AU = 500 kg liveweight) from deep-litter sheds were negligible in winter, and 8.4 g/AU.day in summer. Ammonia emissions were 39.1 in winter and 52.2 g/AU.day in summer, while CH4 emissions were 16.1 and 21.6 g/AU.day in winter and summer respectively. Emission factors averaged from summer and winter emissions showed a CH4 conversion factor of 3.6%, an NH3-N EF of 10% and a N2O-N EF of 0.01 kg N2O-N/kg N excreted. For the litter stockpile, the simple average of summer and winter showed an EF for NH3-N of 14%, and a N2O-N EF of 0.02 kg N2O-N/kg-N of spent litter added to the stockpile. We observed a 66% and 80% decrease in emissions from the manure excreted in litter-based housing with litter stockpiling or without litter stockpiling, compared with conventional housing with an uncovered anaerobic effluent-treatment pond. This provides a sound basis for mitigation strategies that utilise litter-based housing as an alternative to conventional housing with uncovered anaerobic effluent-treatment ponds.

In the Australian pork industry, manure is the main source of greenhouse gases (GHG). In conventional production systems, effluent from sheds is transferred into open anaerobic ponds where the effluent is typically stored for many months, with the potential of generating large quantities of GHG. The present study measured methane (CH4), nitrous oxide (N2O) and ammonia (NH3) emissions from a conventional anaerobic effluent pond (control), a short hydraulic retention-time tank (short HRT, mitigation) and from the animal housing for a flushing piggery in south-eastern Queensland, over two 30-day trials during summer and winter. Emissions were compared to determine the potential for a short HRT to reduce emissions. Average CH4 emissions from the pond were 452 ± 37 g per animal unit (AU; 1 AU = 500 kg liveweight) per day, during the winter trial and 789 ± 29 g/AU.day during the summer trial. Average NH3 emissions were 73 ± 8 g/AU.day during the winter trial and 313 ± 18 g/AU.day during the summer trial. High emission factors during summer will be temperature driven and influenced by the residual volatile solids and nitrogen (N) deposited in the pond during winter. Average NH3 emissions from the piggery shed were 0.707 ± 0.050 g/AU.day and CH4 emissions were 0.344 ± 0.116 g/AU.day. The N2O concentrations from both the pond and shed were close to, or below, the detection limits. Total emissions from the short HRT during the winter and summer trials, respectively, were as follows: CH4 10.65 ± 0.616 mg/AU.day and 4108 ± 473 mg/AU.day; NH3-N 1.15 ± 0.07 mg/AU.day and 29.8 ± 2.57 mg/AU.day; N2O-N 0.001 ± 0.00052 mg/AU.day and 5.9 ± 0.321 mg/AU.day. On the basis of a conservative analysis of CH4 emissions relative to the inflow of volatile solids, and NH3 and N2O emissions as a fraction of the excreted N, GHG emissions were found to be 79% lower from the short-HRT system. This system provides a potential mitigation option to reduce GHG emissions from conventional pork production in Australia.

Agricultural industries are under increasing pressure to measure and reduce greenhouse gas emissions from the supply chain. The Australian pork industry has established proactive goals to improve greenhouse-gas (GHG) performance across the industry, but while productivity indicators are benchmarked by industry, similar data have not previously been collected to determine supply chain GHG emissions. To assess total GHG emissions from Australian pork production, the present study conducted a life-cycle assessment of six case study supply chains and the national herd for the year 2010. The study aimed to determine total GHG emissions and hotspots, and to determine the mitigation potential from alternative manure treatment systems. Two functional units were used: 1 kg of pork liveweight (LW) at the farm gate, and 1 kg of wholesale pork (chilled, bone-in) ready for packaging and distribution. Mean GHG emissions from the case study supply chains ranged from 2.1 to 4.5 kg CO2-e/kg LW (excluding land-use (LU) and direct land use-change (dLUC) emissions). Emissions were lowest from the piggeries that housed grower-finisher pigs on deep litter and highest from pigs housed in conventional systems with uncovered anaerobic effluent ponds. Mean contribution from methane from effluent treatment was 64% of total GHG at the conventional piggeries. Nitrous oxide arose from both grain production and manure management, comprising 7–33% of the total emissions. The GHG emissions for the national herd were 3.6 kg CO2-e/kg LW, with the largest determining factor on total emissions being the relative proportion of pigs managed with high or low emission manure management systems. Emissions from LU and dLUC sources ranged from 0.08 to 0.7 kg CO2-e/kg LW for the case study farms, with differences associated with the inclusion rate of imported soybean meal in the ration and feed-conversion ratio. GHG intensity (excluding LU, dLUC) from the national herd was 6.36 ± 1.03 kg CO2-e/kg wholesale pork, with the emission profile dominated by methane from manure management (50%), followed by feed production (27%) and then meat processing (8%). Inclusion of LU and dLUC emissions had a minor effect on the emission profile. Scenarios testing showed that biogas capture from anaerobic digestion with combined heat and power generation resulted in a 31–64% reduction in GHG emissions. Finishing pigs on deep litter as preferred to conventional housing resulted in 38% lower GHG emissions than conventional finishing.

Greenhouse gas and ammonia emissions are important environmental impacts from manure management in the layer-hen industry. The present study aimed to quantify emissions of nitrous oxide (N2O), methane (CH4) and ammonia (NH3) from layer-hen manure stockpiles, and assess the use of an impermeable cover as an option to mitigate emissions. Gaseous emissions of N2O, CH4 and NH3 were measured using open-path FTIR spectroscopy and the emission strengths were inferred using a backward Lagrangian stochastic model. Emission factors were calculated from the relationship between gaseous emissions and stockpile inputs over a 32-day measurement period. Total NH3 emissions were 5.97 ± 0.399 kg/t (control) and 0.732 ± 0.116 kg/t (mitigation), representing an 88% reduction due to mitigation. Total CH4 emissions from the mitigation stockpile were 0.0832 ± 0.0198 kg/t. Methane emissions from the control and N2O emissions (control and mitigation) were below detection. The mass of each stockpile was 27 820 kg (control) and 25 120 kg (mitigation), with a surface area of ~68 m2 and a volume of ~19 m3. Total manure nitrogen (N) and volatile solids (VS) were 25.2 and 25.8 kg/t N, and 139 and 106 kg/t VS for the control and mitigation stockpiles respectively. Emission factors for NH3 were 24% and 3% of total N for the control and mitigation respectively. Methane from the mitigation stockpile had a CH4 conversion factor of 0.3%. The stockpile cover was found to reduce greenhouse gas emissions by 74% compared with the control treatment, primarily via reduced NH3 and associated indirect N2O emissions.

In life cycle assessment studies, greenhouse gas (GHG) emissions from direct land-use change have been estimated to make a significant contribution to the global warming potential of agricultural products. However, these estimates have a high uncertainty due to the complexity of data requirements and difficulty in attribution of land-use change. This paper presents estimates of GHG emissions from direct land-use change from native woodland to grazing land for two beef production regions in eastern Australia, which were the subject of a multi-impact life cycle assessment study for premium beef production. Spatially- and temporally consistent datasets were derived for areas of forest cover and biomass carbon stocks using published remotely sensed tree-cover data and regionally applicable allometric equations consistent with Australia’s national GHG inventory report. Standard life cycle assessment methodology was used to estimate GHG emissions and removals from direct land-use change attributed to beef production. For the northern-central New South Wales region of Australia estimates ranged from a net emission of 0.03 t CO2-e ha–1 year–1 to net removal of 0.12 t CO2-e ha–1 year–1 using low and high scenarios, respectively, for sequestration in regrowing forests. For the same period (1990–2010), the study region in southern-central Queensland was estimated to have net emissions from land-use change in the range of 0.45–0.25 t CO2-e ha–1 year–1. The difference between regions reflects continuation of higher rates of deforestation in Queensland until strict regulation in 2006 whereas native vegetation protection laws were introduced earlier in New South Wales. On the basis of liveweight produced at the farm-gate, emissions from direct land-use change for 1990–2010 were comparable in magnitude to those from other on-farm sources, which were dominated by enteric methane. However, calculation of land-use change impacts for the Queensland region for a period starting 2006, gave a range from net emissions of 0.11 t CO2-e ha–1 year–1 to net removals of 0.07 t CO2-e ha–1 year–1. This study demonstrated a method for deriving spatially- and temporally consistent datasets to improve estimates for direct land-use change impacts in life cycle assessment. It identified areas of uncertainty, including rates of sequestration in woody regrowth and impacts of land-use change on soil carbon stocks in grazed woodlands, but also showed the potential for direct land-use change to represent a net sink for GHG.

Australia is one of the two largest exporting nations for beef and lamb in the world and the USA is a major export market for both products. To inform the Australian red meat industry regarding the environmental performance of exported food products, this study conducted the first multi-impact analysis of Australian red meat export supply chains including all stages through to warehousing in the USA. A large, integrated dataset based on case study farms and regional survey was used to model beef and lamb from major representative production regions in eastern Australia. Per kilogram of retail-ready red meat, fresh water consumption ranged from 441.7 to 597.6 L across the production systems, stress-weighted water use from 108.5 to 169.4 L H2O-e, fossil energy from 28.1 to 46.6 MJ, crop land occupation from 2.5 to 29.9 m2 and human edible protein conversion efficiency ranged from 7.9 to 0.3, with major differences observed between grass finished and grain finished production. GHG emissions excluding land use and direct land use change ranged from 16.1 to 27.2 kg CO2-e per kilogram, and removals and emissions from land use and direct land use change ranged from −2.4 to 8.7 kg CO2-e per kilogram of retail retail ready meat. Process based life cycle assessment shows that environmental impacts and resource use were highest in the farm and feedlot phase. Transportation contributed ≤5% of greenhouse gas emissions, water and land, confirming that food miles is not a suitable indicator of environmental impacts for red meat transported by ocean shipping. The contribution of international transportation to total energy demand was higher, ranging from 14 to 23%. These beef and lamb supply chains were found to rely on small volumes of water from stressed water catchments, and occupied only small amounts of crop land suited to other food production systems. Production of high quality protein foods for human consumption used only small amounts of protein from human edible grain.

Purpose: Methodology of co-product handling is a critical determinant of calculated resource use and environmental emissions per kilogram (kg) product but has not been examined in detail for different sheep production systems. This paper investigates alternative approaches for handling co-production of wool and live weight (LW, for meat) from dual purpose sheep systems to the farm-gate. Methods: Seven methods were applied; three biophysical allocation (BA) methods based on protein requirements and partitioning of digested protein, protein mass allocation (PMA), economic allocation (EA) and two system expansion (SE) methods. Effects on greenhouse gas (GHG) emissions, fossil energy demand and land occupation (classified according to suitability for arable use) were assessed using four contrasting case study (CS) farm systems. A UK upland farm (CS 1) and a New Zealand hill farm (CS 2) were selected to represent systems focused on lamb and coarse-textured wool for interior textiles. Two Australian Merino sheep farms (CS 3, CS 4) were selected to represent systems focused on medium to superfine garment wool, and lamb. Results and discussion: Total GHG emissions per kilogram total products (i.e. wool + LW) were similar across CS farms. However, results were highly sensitive to the method of co-product handling. GHG emissions based on BA of wool protein to wool resulted in 10–12 kg CO2-e/kg wool (across all CS farms), whereas it increased to 24–38 kg CO2-e/kg wool when BA included a proportion of sheep maintenance requirements. Results for allocation% generated using EA varied widely from 4 % (CS 1) to 52 % (CS 4). SE using beef as a substitution for sheep meat gave the lowest, and often negative, GHG emissions from wool production. Different methods were found to re-order the impacts across the four case studies in some instances. A similar overall pattern was observed for the effects of co-product handling method on other impact categories for three of the four farms. Conclusions: BA based on protein partitioning between sheep wool and LW is recommended for attributional studies with the PMA method being an easily applied proxy for the more detailed BA methods. Sensitivity analysis using SE is recommended to understand the implications of system change. Sensitivity analysis using SE is recommended to investigate implications of choosing alternative products or systems, and to evaluate system change strategies in which case consequential modelling is appropriate. To avoid risks of burden shifting when allocation methods are applied, results should be presented for both wool and LW.

Australia is the largest supplier of fine apparel wool in the world, produced from diverse sheep production systems. To date, broad scale analyses of the environmental credentials of Australian wool have not used detailed farm-scale data, resulting in a knowledge gap regarding the performance of this product. This study is the first multiple impact life cycle assessment (LCA) investigation of three wool types, produced in three geographically defined regions of Australia: the high rainfall zone located in New South Wales (NSW HRZ) producing super-fine Merino wool, the Western Australian wheat-sheep zone (WA WSZ) producing fine Merino wool, and the southern pastoral zone (SA SPZ) of central South Australia, producing medium Merino wool. Inventory data were collected from both case study farms and regional datasets. Life cycle inventory and impact assessment methods were applied to determine resource use (energy and water use, and land occupation) and GHG emissions, including emissions and removal associated with land use (LU) and direct land use change (dLUC). Land occupation was divided into use of arable and non-arable land resources. A comparison of biophysical allocation and system expansion methods for handling co-production of greasy wool and live weight (for meat) was included. Based on the regional analysis results, GHG emissions (excluding LU and dLUC) were 20.1 ± 3.1 (WA WSZ, mean ± 2 S.D) to 21.3 ± 3.4 kg CO 2 -e/kg wool in the NSW HRZ, with no significant difference between regions or wool type. Accounting for LU and dLUC emissions and removals resulted in either very modest increases in emissions (0.3%) or reduced net emissions by 0–11% depending on pasture management and revegetation activities, though a higher degree of uncertainty was observed in these results. Fossil fuel energy demand ranged from 12.5 ± 4.1 in the SA SPZ to 22.5 ± 6.2 MJ/kg wool (WA WSZ) in response to differences in grazing intensity. Fresh water consumption ranged from 204.3 ± 59.1 in the NSW HRZ to 393.7 ± 123.8 L/kg wool in the WA WSZ, with differences primarily relating to climate. Stress-weighted water use ranged from 11.0 ± 3.0 (SA SPZ) to 74.6 ± 119.5 L H 2 O-e/kg wool (NSW HRZ) and followed an opposite trend to water consumption in response to the different levels of water stress across the regions. Non-arable grazing land was found to range from 55% to almost 100% of total land occupation. Different methods for handling co-production of greasy wool and live weight changed estimated total GHG emissions by a factor of three, highlighting the sensitivity to this methodological choice and the significance of meat production in the wool supply chain. The results presented improve the understanding of environmental impacts and resource use in these wool production regions as a basis for more detailed full supply chain analysis.