Net reductions in greenhouse gas emissions from feed additive use in California dairy cattle.

The livestock industry is one of the main contributors to greenhouse gas emissions and there is an increasing demand for the industry to reduce its carbon footprint. Several studies have shown that feed additives 3-nitroxypropanol and nitrate to be effective in reducing enteric methane emissions. The objective of this study was to estimate the net mitigating effect of using 3-nitroxypropanol and nitrate on total greenhouse gas emissions in California dairy industry. A life cycle assessment approach was used to conduct a cradle-to-farm gate environmental impact analysis based on dairy production system in California. Emissions associated with crop production, feed additive production, enteric methane, farm management, and manure storage were calculated and expressed as kg CO2 equivalents (CO2e) per kg of energy corrected milk. The total greenhouse gas emissions from baseline, 3-nitroxypropanol and nitrate offered during lactation were 1.12, 0.993, and 1.08 kg CO2e/kg energy corrected milk, respectively. The average net reduction rates for 3-nitroxypropanol and nitrate were 11.7% and 3.95%, respectively. In both cases, using the feed additives on the whole herd slightly improved overall carbon footprint reduction compared to limiting its use during lactation phase. Although both 3-nitroxypropanol and nitrate had effects on decreasing the total greenhouse gas emission, the former was much more effective with no known safety issues in reducing the carbon footprint of dairy production in California.

Transparency of Financial Reporting on Greenhouse Gas Emission Allowances: The Influence of Regulation.

This study focuses on the transparency of financial reporting on emission allowances (EA) and greenhouse gas (GHG) emissions within the European Union Emissions Trading Scheme (EU ETS). In particular, the different accounting treatments adopted by standard setters and professionals were analyzed to evaluate the influence of regulation in the transparency of financial reporting on EA and GHG emissions. Based on a sample of 85 companies registered with the Portuguese, Spanish, and French National Plans of Allocation (NPAs), data collected from the annual reports were analyzed for the 2008-2014 period. The results were obtained based on descriptive, logistic regressions and panel data statistical techniques, and they show that better levels of transparency of financial reporting on EA and GHG emissions are conditioned by a variety of accounting policies, which compromises the comparability of the financial information. The adoption of the International Accounting Standards Board (IASB) standards set lead to a greater dispersion in the choice of the accounting approach and a higher probability of not disclosing any information, as well as adopting off-balance sheet policies. Therefore, the regulatory factor is a determinant of the level of transparency of financial reporting on EA and GHG emissions, contributing to reduce strategies of omission.

Climate impact from diet in relation to background and sociodemographic characteristics in the Västerbotten Intervention Programme.

OBJECTIVE: The objective of this study was to examine climate impact from diet across background and sociodemographic characteristics in a population-based cohort in northern Sweden. DESIGN: A cross-sectional study within the Västerbotten Intervention Programme. Dietary data from a 64-item food frequency questionnaire collected during 1996-2016 were used. Energy-adjusted greenhouse gas emissions (GHGE) for all participants, expressed as kg carbon dioxide equivalents/day and 4184 kJ (1000 kcal), were estimated using data from life cycle analyses. Differences in background and sociodemographic characteristics were examined between participants with low and high GHGE from diet, respectively. The variables evaluated were age, BMI, physical activity, marital status, level of education, smoking, and residence. SETTING: Västerbotten county in northern Sweden. PARTICIPANTS: In total, 46 893 women and 45 766 men aged 29-65 years. RESULTS: Differences in GHGE from diet were found across the majority of examined variables. The strongest associations were found between GHGE from diet and age, BMI, education, and residence (all P < 0·001), with the highest GHGE from diet found among women and men who were younger, had a higher BMI, higher educational level, and lived in urban areas. CONCLUSIONS: This study is one of the first to examine climate impact from diet across background and sociodemographic characteristics. The results show that climate impact from diet is associated with age, BMI, residence and educational level amongst men and women in Västerbotten, Sweden. These results define potential target populations where public health interventions addressing a move towards more climate-friendly food choices and reduced climate impact from diet could be most effective.

Huella de carbono en el Hospital Base de Puerto Montt / Measurement of the carbon footprint at a regional hospital

Background: Measuring the carbon footprint (CF) makes it possible to estimate the contribution of clinical activity to global warming. Aim: To measure the emitter components of CO2 equivalents (CO2e) at the Hospital Base, Puerto Montt (HBPM). Material and methods: Descriptive study with data collected retrospectively between January and December 2016 from the HBPM database. The data analyzes direct and indirect emissions as well as other indirect emissions beyond the organizational limits. Results: Of the 9,660.3 tons of CO2e emitted by the HBPM in 2016, 46% were derived from consumption of electricity, 29% derived from the generation of residues, and 10% from clinical gas consumption, of which Sevoflurane was the greatest contributor. Conclusions: Clinical gases are a significant source of CO2e emissions. Sevoflurane alone is in fourth place in CO2e emissions at the HBPM. Estimating the CF produced by HBPM is the first step in the discussion of measures to reduce the environmental impact of our activity.

The Impacts of Regulations and Financial Development on the Operations of Supply Chains with Greenhouse Gas Emissions.

To establish a micro foundation to understand the impacts of greenhouse gas (GHG) emission regulations and financial development levels on firms' GHG emissions, we build a two-stage dynamic game model to incorporate GHG emission regulations (in terms of an emission tax) and financial development (represented by the corresponding financing cost) into a two-echelon supply chain. With the subgame perfect equilibrium, we identify the conditions to determine whether an emission regulatory policy and/or financial development can affect GHG emissions in the supply chain. We also reveal the impacts of the strictness of GHG emission regulation, the financial development level, and the unit GHG emission rate on the operations of the supply chain and the corresponding profitability implications. Managerial insights are also discussed.

Estimated Global Disease Burden From US Health Care Sector Greenhouse Gas Emissions.

OBJECTIVES: To quantify the increased disease burden caused by US health care sector life cycle greenhouse gas (GHG) emissions of 614 million metric tons of carbon dioxide equivalents in 2013. METHODS: We screened for health damage factors that linked GHG emissions to disease burdens. We selected 5 factors, based on appropriate temporal modeling scales, which reflect a range of possible GHG emissions scenarios. We applied these factors to health care sector emissions. RESULTS: We projected that annual GHG emissions associated with health care in the United States would cause 123 000 to 381 000 disability-adjusted life-years in future health damages, with malnutrition being the largest damage category. CONCLUSIONS: Through their contribution to global climate change, GHG emissions will negatively affect public health because of an increased prevalence of extreme weather, flooding, vector-borne disease, and other effects. As the stewards of global health, it is important for health care professionals to recognize the magnitude of GHG emissions associated with health care itself, and the severity of associated health damages.

Diet-related greenhouse gas emissions assessed by a food frequency questionnaire and validated using 7-day weighed food records.

BACKGROUND: The current food system generates about 25 % of total greenhouse gas emissions (GHGE), including deforestation, and thereby substantially contributes to the warming of the earth's surface. To understand the association between food and nutrient intake and GHGE, we therefore need valid methods to assess diet-related GHGE in observational studies. METHODS: Life cycle assessment (LCA) studies assess the environmental impact of different food items. We linked LCA data expressed as kg carbon dioxide equivalents (CO2e) per kg food product to data on food intake assessed by the food frequency questionnaire (FFQ) Meal-Q and validated it against a 7-day weighed food record (WFR). 166 male and female volunteers aged 20-63 years completed Meal-Q and the WFR, and their food intake was linked to LCA data. RESULTS: The mean GHGE assessed with Meal-Q was 3.76 kg CO2e per day and person, whereas it was 5.04 kg CO2e using the WFR. The energy-adjusted and deattenuated Pearson and Spearman correlation coefficients were 0.68 and 0.70, respectively. Moreover, compared to the WFR, Meal-Q provided a good ranking ability, with 90 % of the participants classified into the same or adjacent quartile according to their daily average CO2e. The Bland-Altman plot showed an acceptable level of agreement between the two methods and the reproducibility of Meal-Q was high. CONCLUSIONS: This is the first study validating the assessment of diet-related GHGE by a questionnaire. The results suggest that Meal-Q is a useful tool for studying the link between food habits and CO2e in future epidemiological studies.

Greenhouse gas emissions and stocks of soil carbon and nitrogen from a 20-year fertilised wheat-maize intercropping system: A model approach.

Accurate modelling of agricultural management impacts on greenhouse gas emissions and the cycling of carbon and nitrogen is complicated due to interactions between various processes and the disturbance caused by field management. In this study, a process-based model, the Soil-Plant-Atmosphere Continuum System (SPACSYS), was used to simulate the effects of different fertilisation regimes on crop yields, the dynamics of soil organic carbon (SOC) and total nitrogen (SN) stocks from 1990 to 2010, and soil CO2 (2007-2010) and N2O (2007-2008) emissions based on a long-term fertilisation experiment with a winter-wheat (Triticum Aestivum L.) and summer-maize (Zea mays L.) intercropping system in Eutric Cambisol (FAO) soil in southern China. Three fertilisation treatments were 1) unfertilised (Control), 2) chemical nitrogen, phosphorus and potassium (NPK), and 3) NPK plus pig manure (NPKM). Statistical analyses indicated that the SPACSYS model can reasonably simulate the yields of wheat and maize, the evolution of SOC and SN stocks and soil CO2 and N2O emissions. The simulations showed that the NPKM treatment had the highest values of crop yields, SOC and SN stocks, and soil CO2 and N2O emissions were the lowest from the Control treatment. Furthermore, the simulated results showed that manure amendment along with chemical fertiliser applications led to both C (1017 ± 470 kg C ha(-1) yr(-1)) and N gains (91.7 ± 15.1 kg N ha(-1) yr(-1)) in the plant-soil system, while the Control treatment caused a slight loss in C and N. In conclusion, the SPACSYS model can accurately simulate the processes of C and N as affected by various fertilisation treatments in the red soil. Furthermore, application of chemical fertilisers plus manure could be a suitable management for ensuring crop yield and sustaining soil fertility in the red soil region, but the ratio of chemical fertilisers to manure should be optimized to reduce C and N losses to the environment.

Limited impact on decadal-scale climate change from increased use of natural gas.

The most important energy development of the past decade has been the wide deployment of hydraulic fracturing technologies that enable the production of previously uneconomic shale gas resources in North America. If these advanced gas production technologies were to be deployed globally, the energy market could see a large influx of economically competitive unconventional gas resources. The climate implications of such abundant natural gas have been hotly debated. Some researchers have observed that abundant natural gas substituting for coal could reduce carbon dioxide (CO2) emissions. Others have reported that the non-CO2 greenhouse gas emissions associated with shale gas production make its lifecycle emissions higher than those of coal. Assessment of the full impact of abundant gas on climate change requires an integrated approach to the global energy-economy-climate systems, but the literature has been limited in either its geographic scope or its coverage of greenhouse gases. Here we show that market-driven increases in global supplies of unconventional natural gas do not discernibly reduce the trajectory of greenhouse gas emissions or climate forcing. Our results, based on simulations from five state-of-the-art integrated assessment models of energy-economy-climate systems independently forced by an abundant gas scenario, project large additional natural gas consumption of up to +170 per cent by 2050. The impact on CO2 emissions, however, is found to be much smaller (from -2 per cent to +11 per cent), and a majority of the models reported a small increase in climate forcing (from -0.3 per cent to +7 per cent) associated with the increased use of abundant gas. Our results show that although market penetration of globally abundant gas may substantially change the future energy system, it is not necessarily an effective substitute for climate change mitigation policy.

Greenhouse gas emissions from the enteric fermentation and manure storage of dairy and beef cattle in China during 1961-2010.

Due to the expanding dairy and beef population in China and their contribution to global CH4 and N2O budgets, a framework considering changes in feed, manure management and herd structure was established to indicate the trends of CH4 and N2O emissions from the enteric formation and manure storage in China׳s beef and dairy production and the underlying driving forces during the period 1961-2010. From 1961 to 2010, annual CH4 and N2O emissions from beef cattle in China increased from 2.18Mt to 5.86Mt and from 7.93kt-29.56kt, respectively, while those from dairy cattle increased from 0.023 to 1.09Mt and 0.12 to 7.90kt, respectively. These increases were attributed to the combined changes in cattle population and management practices in feeds and manure storage. Improvement in cattle genetics during the period increased the bodyweight, required dry matter intake and gross energy and thus resulted in increased enteric CH4 EFs for each category of beef and dairy cattle as well as the overall enteric EFs (i.e., Tier 1 in IPCC). However, for beef cattle, such an impact on the overall enteric EFs was largely offset by the herd structure transition from draft animal-oriented to meat animal-oriented during 1961-2010. Although the CO2-eq of CH4 and N2O from manure storage was less than the enteric emissions during 1961-2010 in China, it tended to increase both in beef and dairy cattle, which was mainly driven by the changes in manure management practices.

Effect of greenhouse conditions on the leaf apoplastic proteome of Coffea arabica plants.

This work describes the coffee leaf apoplastic proteome and its modulation by the greenhouse conditions. The apoplastic fluid (APF) was obtained by leaf vacuum infiltration, and the recovered proteins were separated by 2-DE and subsequently identified by matrix assisted laser desorption/ionization time of flight-mass spectrometry, followed by homology search in EST coffee databases. Prediction tools revealed that the majority of the 195 identified proteins are involved in cell wall metabolism and in stress/defense responses. Although most of the proteins follow the classical secretory mechanism, a low percentage of them seem to result from unconventional secretion (leaderless secreted proteins). Principal components analysis revealed that the APF samples formed two distinct groups, with the temperature amplitude mostly contributing for this separation (higher or lower than 10°C, respectively). Sixty one polypeptide spots allowed defining these two groups and 28 proteins were identified, belonging to carbohydrate metabolism, cell wall modification and proteolysis. Interestingly stress/defense proteins appeared as more abundant in Group I which is associated with a higher temperature amplitude. It seems that the proteins in the coffee leaf APF might be implicated in structural modifications in the extracellular space that are crucial for plant development/adaptation to the conditions of the prevailing environment. BIOLOGICAL SIGNIFICANCE: This is the first detailed proteomic study of the coffee leaf apoplastic fluid (APF) and of its modulation by the greenhouse conditions. The comprehensive overview of the most abundant proteins present in the extra-cellular compartment is particularly important for the understanding of coffee responses to abiotic/biotic stress. This article is part of a Special Issue entitled: Environmental and structural proteomics.

Greenhouse gas fluxes from agricultural soils under organic and non-organic management--a global meta-analysis.

It is anticipated that organic farming systems provide benefits concerning soil conservation and climate protection. A literature search on measured soil-derived greenhouse gas (GHG) (nitrous oxide and methane) fluxes under organic and non-organic management from farming system comparisons was conducted and followed by a meta-analysis. Up to date only 19 studies based on field measurements could be retrieved. Based on 12 studies that cover annual measurements, it appeared with a high significance that area-scaled nitrous oxide emissions from organically managed soils are 492 ± 160 kg CO2 eq. ha(-1) a(-1) lower than from non-organically managed soils. For arable soils the difference amounts to 497 ± 162 kg CO2 eq. ha(-1) a(-1). However, yield-scaled nitrous oxide emissions are higher by 41 ± 34 kg CO2 eq. t(-1) DM under organic management (arable and use). To equalize this mean difference in yield-scaled nitrous oxide emissions between both farming systems, the yield gap has to be less than 17%. Emissions from conventionally managed soils seemed to be influenced mainly by total N inputs, whereas for organically managed soils other variables such as soil characteristics seemed to be more important. This can be explained by the higher bioavailability of the synthetic N fertilisers in non-organic farming systems while the necessary mineralisation of the N sources under organic management leads to lower and retarded availability. Furthermore, a higher methane uptake of 3.2 ± 2.5 kg CO2 eq. ha(-1) a(-1) for arable soils under organic management can be observed. Only one comparative study on rice paddies has been published up to date. All 19 retrieved studies were conducted in the Northern hemisphere under temperate climate. Further GHG flux measurements in farming system comparisons are required to confirm the results and close the existing knowledge gaps.

Time-dependent climate sensitivity and the legacy of anthropogenic greenhouse gas emissions.

Climate sensitivity measures the response of Earth's surface temperature to changes in forcing. The response depends on various climate processes that feed back on the initial forcing on different timescales. Understanding climate sensitivity is fundamental to reconstructing Earth's climatic history as well as predicting future climate change. On timescales shorter than centuries, only fast climate feedbacks including water vapor, lapse rate, clouds, and snow/sea ice albedo are usually considered. However, on timescales longer than millennia, the generally higher Earth system sensitivity becomes relevant, including changes in ice sheets, vegetation, ocean circulation, biogeochemical cycling, etc. Here, I introduce the time-dependent climate sensitivity, which unifies fast-feedback and Earth system sensitivity. I show that warming projections, which include a time-dependent climate sensitivity, exhibit an enhanced feedback between surface warming and ocean CO2 solubility, which in turn leads to higher atmospheric CO2 levels and further warming. Compared with earlier studies, my results predict a much longer lifetime of human-induced future warming (23,000-165,000 y), which increases the likelihood of large ice sheet melting and major sea level rise. The main point regarding the legacy of anthropogenic greenhouse gas emissions is that, even if the fast-feedback sensitivity is no more than 3 K per CO2 doubling, there will likely be additional long-term warming from slow climate feedbacks. Time-dependent climate sensitivity also helps explaining intense and prolonged warming in response to massive carbon release as documented for past events such as the Paleocene-Eocene Thermal Maximum.

Application of dynamic models to estimate greenhouse gas emission by wastewater treatment plants of the pulp and paper industry.

Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid-anaerobic/aerobic-biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ± 30, ± 19, and ± 17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ± 6, ± 7, and ± 4 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.

The energy burden and environmental impact of health services.

OBJECTIVES: We reviewed the English-language literature on the energy burden and environmental impact of health services. METHODS: We searched all years of the PubMed, CINAHL, and ScienceDirect databases for publications reporting energy consumption, greenhouse gas emissions, or the environmental impact of health-related activities. We extracted and tabulated data to enable cross-comparisons among different activities and services; where possible, we calculated per patient or per event emissions. RESULTS: We identified 38 relevant publications. Per patient or per event, health-related energy consumption and greenhouse gas emissions are quite modest; in the aggregate, however, they are considerable. In England and the United States, health-related emissions account for 3% and 8% of total national emissions, respectively. CONCLUSIONS: Although reducing health-related energy consumption and emissions alone will not resolve all of the problems of energy scarcity and climate change, it could make a meaningful contribution.

The effect of lactation length on greenhouse gas emissions from the national dairy herd.

Many governments have signed up to greenhouse gas emission (GHGE) reduction programmes under their national climate change obligations. Recently, it has been suggested that the use of extended lactations in dairy herds could result in reduced GHGE. Dairy GHGE were modelled on a national basis and the model was used to compare emissions from lactations of three different lengths (305, 370 and 440 days), and a current 'base' scenario on the basis of maintaining current milk production levels. In addition to comparing GHGE from the average 'National Herd' under these scenarios, results were used to investigate how accounting for lactations of different lengths might alter the estimation of emissions calculated from the National Inventory methodology currently recommended by Intergovernmental Panel on Climate Change. Data for the three lactation length scenarios were derived from nationally recorded dairy performance information and used in the GHGE model. Long lactations required fewer milking cows and replacements to maintain current milk yield levels than short ones, but GHGEs were found to rise from 1214 t of CO2 equivalent (CE)/farm per year for lactations of 305 days to 1371 t CE/farm per year for 440-day lactations. This apparent anomaly can be explained by the less efficient milk production (kg milk produced per kg cow weight) found in later lactation, a more pronounced effect in longer lactations. The sensitivity of the model to changes in replacement rate, persistency and level of milk yield was investigated. Changes in the replacement rate from 25% to 20% and in persistency by −10% to +20% resulted in very small changes in GHGE. Differences in GHGE due to the level of milk yield were much more dramatic with animals in the top 10% for yield, producing about 25% less GHGE/year than the average animal. National Inventory results were investigated using a more realistic spread of lactation lengths than recommended for such calculations using emissions calculated in the first part of the study. Current UK emission calculations based on the National Inventory were 329 Gg of methane per year from the dairy herd. Using the national distribution of lactation lengths, this was found to be an underestimate by about 10%. This work showed that the current rise in lactation length or a move towards calving every 18 months would increase GHGE by 7% to 14% compared with the current scenario, assuming the same milk yield in all models. Increased milk yield would have a much greater effect on reducing GHGE than changes to lactation length, replacement rate or persistency. National Inventory methodology appears to underestimate GHGE when the distribution of lactation lengths is considered and may need revising to provide more realistic figures.

A new estimation of global soil greenhouse gas fluxes using a simple data-oriented model.

Soil greenhouse gas fluxes (particularly CO(2), CH(4), and N(2)O) play important roles in climate change. However, despite the importance of these soil greenhouse gases, the number of reports on global soil greenhouse gas fluxes is limited. Here, new estimates are presented for global soil CO(2) emission (total soil respiration), CH(4) uptake, and N(2)O emission fluxes, using a simple data-oriented model. The estimated global fluxes for CO(2) emission, CH(4) uptake, and N(2)O emission were 78 Pg C yr(-1) (Monte Carlo 95% confidence interval, 64-95 Pg C yr(-1)), 18 Tg C yr(-1) (11-23 Tg C yr(-1)), and 4.4 Tg N yr(-1) (1.4-11.1 Tg N yr(-1)), respectively. Tropical regions were the largest contributor of all of the gases, particularly the CO(2) and N(2)O fluxes. The soil CO(2) and N(2)O fluxes had more pronounced seasonal patterns than the soil CH(4) flux. The collected estimates, including both the previous and the present estimates, demonstrate that the means of the best estimates from each study were 79 Pg C yr(-1) (291 Pg CO(2) yr(-1); coefficient of variation, CV = 13%, N = 6) for CO(2), 21 Tg C yr(-1) (29 Tg CH(4) yr(-1); CV = 24%, N = 24) for CH(4), and 7.8 Tg N yr(-1) (12.2 Tg N(2)O yr(-1); CV = 38%, N = 11) for N(2)O. For N(2)O, the mean of the estimates that was calculated by excluding the earliest two estimates was 6.6 Tg N yr(-1) (10.4 Tg N(2)O yr(-1); CV = 22%, N = 9). The reported estimates vary and have large degrees of uncertainty but their overall magnitudes are in general agreement. To further minimize the uncertainty of soil greenhouse gas flux estimates, it is necessary to build global databases and identify key processes in describing global soil greenhouse gas fluxes.

Life-cycle assessment of greenhouse gas emissions from dairy production in Eastern Canada: a case study.

The objective of this study was to conduct a life-cycle assessment (LCA) of greenhouse gas (GHG) emissions from a typical nongrazing dairy production system in Eastern Canada. Additionally, as dairying generates both milk and meat, this study assessed several methods of allocating emissions between these coproducts. An LCA was carried out for a simulated farm based on a typical nongrazing dairy production system in Quebec. The LCA was conducted over 6 yr, the typical lifespan of dairy cows in this province. The assessment considered 65 female Holstein calves, of which 60 heifers survived to first calving at 27 mo of age. These animals were subsequently retained for an average of 2.75 lactations. Progeny were also included in the analysis, with bulls and heifers in excess of replacement requirements finished as grain-fed veal (270 kg) at 6.5 mo of age. All cattle were housed indoors and fed forages and grains produced on the same farm. Pre-farm gate GHG emissions and removals were quantified using Holos, a whole-farm software model developed by Agriculture and Agri-Food Canada and based on the Intergovernmental Panel for Climate Change Tier 2 and 3methodologies with modifications for Canadian conditions. The LCA yielded a GHG intensity of 0.92 kg of CO(2) Eq/kg of fat- and protein-corrected milk yield. Methane (CH(4)) accounted for 56% of total emissions, with 86% originating from enteric fermentation. Nitrous oxide accounted for 40% of total GHG emissions. Lactating cows contributed 64% of total GHG emissions, whereas calves under 12 mo contributed 10% and veal calves only 3%. Allocation of GHG emissions between meat and milk were assessed as (1) 100% allocation to milk, (2) economics, (3) dairy versus veal animals, and (4) International Dairy Federation equation using feed energy demand for meat and milk production. Comparing emissions from dairy versus veal calves resulted in 97% of the emissions allocated to milk. The lowest allocation of emissions to milk (78%) was associated with the International Dairy Federation equation. This LCA showed that greatest reductions in GHG emissions would be achieved by applying mitigation strategies to reduce enteric CH(4) from the lactating cow, with minimal reductions being achievable in young stock. Choice of coproduct allocation method can also significantly affect the relative allocation of GHG emissions to milk and meat.