Carbon Footprint of Beef Cattle

ABSTRACT: The carbon footprint of beef cattle is presented for Canada, The United States, The European Union, Australia and Brazil. The values ranged between 8 and 22 kg CO(2)e per kg of live weight (LW) depending on the type of farming system, the location, the year, the type of management practices, the allocation, as well as the boundaries of the study. Substantial reductions have been observed for most of these countries in the last thirty years. For instance, in Canada the mean carbon footprint of beef cattle at the exit gate of the farm decreased from 18.2 kg CO(2)e per kg LW in 1981 to 9.5 kg CO(2)e per kg LW in 2006 mainly because of improved genetics, better diets, and more sustainable land management practices. Cattle production results in products other than meat, such as hides, offal and products for rendering plants; hence the environmental burden must be distributed between these useful products. In order to do this, the cattle carbon footprint needs to be reported in kg of CO(2)e per kg of product. For example, in Canada in 2006, on a mass basis, the carbon footprint of cattle by-products at the exit gate of the slaughterhouse was 12.9 kg CO(2)e per kg of product. Based on an economic allocation, the carbon footprints of meat (primal cuts), hide, offal and fat, bones and other products for rendering were 19.6, 12.3, 7 and 2 kg CO(2)e per kg of product, respectively

The challenge of reconciling bottom-up agricultural methane emissions inventories with top-down measurements

Agriculture is estimated to produce more than 40% of anthropogenic methane (CH4) emissions, contributing to global climate change. Bottom-up, IPCC based methodologies are typically used to estimate the agriculture sector\u2019s contribution, but these estimates are rarely verified beyond the farm gate, due to the challenge of separating interspersed sources. We present flux measurements of CH4, using eddy covariance (EC), relaxed eddy accumulation (REA) and wavelet covariance obtained using an aircraft-based measurement platform and compare these top-down estimates with bottom-up footprint adjusted inventory estimates of CH4 emissions for an agricultural region in eastern Ontario, Canada. Top-down CH4 fluxes agree well (mean \ub1 1 standard error: EC = 17 \ub1 4 mg CH4 m 122 d 121; REA = 19 \ub1 3 mg CH4 m 122 d 121, wavelet covariance = 16 \ub1 3 mg CH4 m 122 d 121), and are not statistically different, but significantly exceed bottom-up inventory estimates of CH4 emissions based on animal husbandry (8 \ub1 1 mg CH4 m 122 d 121). The discrepancy between top-down and bottom-up estimates was found to be related to both increasing fractional area of wetlands in the flux footprint, and increasing surface temperature. For the case when the wetland area in the flux footprint was less than 10% fractional coverage, the top-down and bottom-up estimates were within the measurement error. This result provides the first independent verification of agricultural methane emissions inventories at the regional scale. Wavelet analysis, which provides spatially resolved fluxes, was used to attempt to separate CH4 emissions from managed and unmanaged CH4 sources. Opportunities to minimize the challenges of verifying agricultural CH4 emissions inventories using aircraft flux measuring systems are discussed.Peer reviewed: YesNRC publication: Ye

Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: a Canadian scenario assessment

There is an increasing demand for sustainable agricultural production as part of the transition towards a globally sustainable economy. To quantify impacts of agricultural systems on the environment, life cycle assessment (LCA) is ideal because of its holistic approach. Many tools have been developed to conduct LCAs in agriculture, but they are not publicly available, not open-source, and have a limited scope. Here, a new adaptable open-source tool (Crop.LCA) for carrying out LCA of cropping systems is presented and tested in an evaluation study with a scenario assessment of 4 cropping systems using an agroecosystem model (DNDC) to predict soil GHG emissions. The functional units used are hectares (ha) of land and gigajoules (GJ) of harvested energy output, and 4 impact categories were evaluated: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. DNDC was used to simulate 28 years of cropping system dynamics, and the results were used as input in Crop.LCA. Data were aggregated for each 4-year rotation and statistically analyzed. Introduction of legumes into the cropping system reduced CED by 6%, GWP by 23%, and acidification by 19% per ha. These results highlight the ability of Crop.LCA to capture cropping system characteristics in LCA, and the tool constitutes a step forward in increasing the accuracy of LCA of cropping systems as required for bio-economy system assessments. Furthermore, the tool is open-source, highly transparent and has the necessary flexibility to assess agricultural systems

Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: a Canadian scenario assessment

There is an increasing demand for sustainable agricultural production as part of the transition towards a globally sustainable economy. To quantify impacts of agricultural systems on the environment, life cycle assessment (LCA) is ideal because of its holistic approach. Many tools have been developed to conduct LCAs in agriculture, but they are not publicly available, not open-source, and have a limited scope. Here, a new adaptable open-source tool (Crop.LCA) for carrying out LCA of cropping systems is presented and tested in an evaluation study with a scenario assessment of 4 cropping systems using an agroecosystem model (DNDC) to predict soil GHG emissions. The functional units used are hectares (ha) of land and gigajoules (GJ) of harvested energy output, and 4 impact categories were evaluated: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. DNDC was used to simulate 28 years of cropping system dynamics, and the results were used as input in Crop.LCA. Data were aggregated for each 4-year rotation and statistically analyzed. Introduction of legumes into the cropping system reduced CED by 6%, GWP by 23%, and acidification by 19% per ha. These results highlight the ability of Crop.LCA to capture cropping system characteristics in LCA, and the tool constitutes a step forward in increasing the accuracy of LCA of cropping systems as required for bio-economy system assessments. Furthermore, the tool is open-source, highly transparent and has the necessary flexibility to assess agricultural systems

Continuous Cropping and Moist Deep Convection on the Canadian Prairies

Summerfallow is cropland that is purposely kept out of production during a growing season to conserve soil moisture. On the Canadian Prairies, a trend to continuous cropping with a reduction in summerfallow began after the summerfallow area peaked in 1976. This study examined the impact of this land-use change on convective available potential energy (CAPE), a necessary but not sufficient condition for moist deep convection. All else being equal, an increase in CAPE increases the probability-of-occurrence of convective clouds and their intensity if they occur. Representative Bowen ratios for the Black, Dark Brown, and Brown soil zones were determined for 1976: the maximum summerfallow year, 2001: our baseline year, and 20xx: a hypothetical year with the maximum-possible annual crop area. Average mid-growing-season Bowen ratios and noon solar radiation were used to estimate the reduction in the lifted index (LI) from land-use weighted evapotranspiration in each study year. LI is an index of CAPE, and a reduction in LI indicates an increase in CAPE. The largest reductions in LI were found for the Black soil zone. They were −1.61 ± 0.18, −1.77 ± 0.14 and −1.89 ± 0.16 in 1976, 2001 and 20xx, respectively. These results suggest that, all else being equal, the probability-of-occurrence of moist deep convection in the Black soil zone was lower in 1976 than in the base year 2001, and it will be higher in 20xx when the annual crop area reaches a maximum. The trend to continuous cropping had less impact in the drier Dark Brown and Brown soil zones

Impact of Continuous Cropping on the Diurnal Range of Dew Point Temperature during the Foliar Expansion Period of Annual Crops on the Canadian Prairies

It is important to increase our knowledge of the role of land use in changing the regional climate. This study asked, “Has the increase in continuous cropping over the past 50 years on the Canadian Prairies influenced the daily mean and range of morning dew point temperatures (Td) during the foliar expansion period (from mid-June to mid-July) of annual field crops?” We found that there has been a general increase in the decadal average of mean daily Td and in the range of morning Td from the 1960s to the 2000s. The increase in the observed range of Td between the daily minimum value, which typically occurs near sunrise, and the late morning peak was found to be related to the increase in annual crop acreage and consequent decrease in summerfallow area. The relationship was more significant in the subhumid climatic zone than in the semiarid climatic zone, and it was influenced by whether the region was experiencing either wet, normal, or dry conditions

Continuous Cropping and Moist Deep Convection on the Canadian Prairies

Summerfallow is cropland that is purposely kept out of production during a growing season to conserve soil moisture. On the Canadian Prairies, a trend to continuous cropping with a reduction in summerfallow began after the summerfallow area peaked in 1976. This study examined the impact of this land-use change on convective available potential energy (CAPE), a necessary but not sufficient condition for moist deep convection. All else being equal, an increase in CAPE increases the probability-of-occurrence of convective clouds and their intensity if they occur. Representative Bowen ratios for the Black, Dark Brown, and Brown soil zones were determined for 1976: the maximum summerfallow year, 2001: our baseline year, and 20xx: a hypothetical year with the maximum-possible annual crop area. Average mid-growing-season Bowen ratios and noon solar radiation were used to estimate the reduction in the lifted index (LI) from land-use weighted evapotranspiration in each study year. LI is an index of CAPE, and a reduction in LI indicates an increase in CAPE. The largest reductions in LI were found for the Black soil zone. They were −1.61 ± 0.18, −1.77 ± 0.14 and −1.89 ± 0.16 in 1976, 2001 and 20xx, respectively. These results suggest that, all else being equal, the probability-of-occurrence of moist deep convection in the Black soil zone was lower in 1976 than in the base year 2001, and it will be higher in 20xx when the annual crop area reaches a maximum. The trend to continuous cropping had less impact in the drier Dark Brown and Brown soil zones

District Scale GHG Emission Indicators for Canadian Field Crop and Livestock Production

The three main farm products from Canadian agriculture, i.e., proteins, vegetable oils, and carbohydrates, account for 98% of the land in annual crops in Canada. The intensities and efficiencies of these field crops in relation to their Greenhouse Gas (GHG) emissions were assessed for their value as land use change indicators. To facilitate spatial comparisons, this assessment was carried out at the Ecodistrict (ED) scale. The Unified Livestock Industry and Crop Emissions Estimation System (ULICEES) model was modified to operate at the ED scale, and used to quantify the GHG emission intensity of protein. GHG emissions were also calculated for plant products not used for livestock feed. The livestock GHG emissions and GHG-protein intensities estimated using ED scale inputs to ULICEES were reasonably close to GHG-protein intensities generated by the version of ULICEES driven by provincial scale census data. Carbohydrates were split into two groups, i.e., whether or not they supported livestock. Annual farm product data at 5-year intervals were used to generate GHG emissions from all farm operations. The range of GHG emissions from all farm operations in Western Canada was from 42 to 54 Mt CO2e between in 1991 and 2011, while GHG emissions from livestock ranged from 22 to 34 Mt CO2e over the same period. The Eastern Canadian GHG emissions from all farm operations declined gradually from 24 to 22 Mt CO2e over the period, with most of the eastern GHG emissions being from livestock. Ruminant livestock accounted for most of the livestock GHG emissions, particularly in the west. Provincial scale GHG emission efficiencies of the four farm product groups were assessed on a per-unit of GHG emissions basis for 2006. The most GHG-efficient province for protein was Ontario, whereas the most GHG-efficient province for all three plant products was Saskatchewan. The coastal provinces were the least GHG-efficient sources of all four farm product groups

A Comparison of the Greenhouse Gas Emissions From the Sheep Industry With Beef Production in Canada

Sheep production in Canada is a small industry in comparison to other livestock systems. Because of the potential for expansion of the sheep industry in Canada, the GHG emissions budget of this industry was assessed in this paper. The GHG emissions from Canadian lamb production were compared with those from the Canadian beef industry using the ULICEES model. The GHG emission intensity of the Canadian lamb industry was 21% higher than lamb production in France and Wales, and 27% higher than northern England. Enteric methane accounts for more than half of the GHG emissions from sheep in Canada. The protein based GHG emission intensity is 60% to 90% higher for sheep than for beef cattle in Canada. The GHG emission intensity for sheep in Eastern Canada is higher than for sheep in Western Canada. Protein based GHG emission intensity is more sensitive to the difference between sheep and beef than LW based emission intensity. This paper demonstrated that protein based GHG emission intensity is a more meaningful indicator for comparing different livestock species than live weight (LW) based GHG emission intensity