Reactive nitrogen (Nr) losses to the air (ammonia [NH3], nitrous oxide [N2O]) and to water (nitrate [NO3-] leaching) have been reported for Canadian agricultural systems. However, there is very little information on N use efficiency (NUE) and reactive N losses for major crop types. The objectives of this study were to evaluate the NUE and reactive N losses for spring wheat, grain corn, and canola from 1981 to 2021 using the Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model. The provincial averages of residual soil N (RSN) at harvest increased by over 3.8-fold for spring wheat, 2.7-fold for canola (grown in Alberta, Saskatchewan and Manitoba), but decreased by 10.8% for corn (mainly grown in Ontario and Quebec) from 1981 to 1985 to 2017-2021. The RSN was higher in Ontario and Quebec than in the Prairie provinces (Alberta, Saskatchewan and Manitoba). The NUE decreased from 1981 to 1985 to 2017-2021 for spring wheat and canola whereas it increased from 40.2% to 58.4% for corn. Over the same period, reactive N losses increased by 86.9% for spring wheat and 65.8% for canola, whereas it decreased by 6.8% for corn. Over the 41-year period, reactive N losses for corn were higher than for spring wheat and canola due in part to higher N inputs and greater precipitation in corn-production regions in Ontario and Quebec compared to spring wheat production in the Prairie provinces. Management practices should first target corn to reduce N losses to the environment while improving NUE and maintaining yields for all three crops.

Manure storage systems enable farmers to apply nutrients at the right time for crop production but are also a source of greenhouse gases. This study analyzed Canadian Farm Management Surveys (conducted in 2017 and 2021) to quantify the prevalence of manure management systems and use of mitigation practices and identify changes over time. The surveys represented the beef, dairy, poultry, and swine sectors fairly well with some exceptions (e.g., underrepresentation of swine in western Canada). Results show a shift towards liquid manure in the dairy sector and dominance of liquid manure in the swine sector and solid manure in beef and poultry sectors. Practices that may reduce emissions include mechanical separation, which gained popularity in the BC dairy sector. A stable minority (10%) of farmers use additives for their manure in some provinces. Anaerobic digestion remains rare (similar to 1% in the dairy sector and less in other sectors). For solid manure, storage for >6 months (many >1 year) was common. Adoption of solid manure active composting was modest at 5%-10%. These baseline data show there is a high potential for further adoption of beneficial management practices that decrease emissions.

Agriculture is a major source of reactive nitrogen (Nr) losses through ammonia (NH3) volatilization, nitrous oxide (N2O) emissions and nitrate (NO3-) leaching. A Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model was developed to estimate the nitrogen (N) balance in soils, including N removals by harvested crops and Nr losses for the years 1981-2016 across Canada. Annual N inputs to farmland include commercial fertilizer N, livestock manure N, symbiotic and asymbiotic biological N fixation and atmospheric N deposition of NOx and NH3. The total annual N input for Canadian farmland was 5528 Gg N (103.2 kg N ha(-1)) in 2016 where N removal by crops and Nr accounted for 72.5 % (74.9 kg N ha(-1)) and 13.4 % (13.9 kg N ha(-1)), respectively. The Nr losses from N2O emissions, NH3 volatilization and NO3- leaching accounted for 64 Gg N (1.2 kg N ha(-1)), 330 Gg N (6.2 kg N ha(-1)) and 348 Gg N (6.5 kg N ha(-1)), which represents between 1.2-6.3 % of total N input. A total of 777 Gg N (14.5 kg N ha(-1)) remained in the soil as surplus N (14.1 % of total N input), which could be available to subsequent crops in dryer regions but might be subject to N2O loss through nitrification or denitrification processes or NO3- leaching following heavy rains in humid regions. Nitrous oxide and ammonia emissions increased over a 36-year period due to increased fertilizer N inputs. The percentage of N inputs that was estimated to be lost as Nr increased from 17.9 % in 1981 to the peak level of 19.8 % in 2001 and then declined to 13.4 % in 2016. Total N removal by crops increased at a greater rate than N input during the 2001-2016 period resulting in an increased N uptake by crops over the last 15 years. The improved management of fertilizer N for agricultural systems represents a key opportunity for both farmers and policy makers to further reduce Nr losses from Canadian farmland without negatively impacting productivity.

Canada's livestock production and human populations are concentrated in southern regions. Understanding spatial and temporal distributions of animals and excreted nutrients is key to optimizing manure resources and minimizing impact of livestock. Here, we identify manureshed concerns and opportunities by reconciling nitrogen supply and demand on a regional and national scale. Data based on national statistics and farm surveys were allocated to homogeneous soil polygons (Soil Landscapes of Canada [SLC]) to quantify changes in nutrient distribution and ammonia (NH3 ) emissions across Canada (1981-2018). Livestock sectors tied to domestic consumption, dairy and poultry, were stable over time and well dispersed. Export driven beef production has moved west since 1981, whereas pig production was prominent in Manitoba, Quebec, and Ontario. Per ha manure N excretion across livestock sectors in 2018 was generally low with 58% and 6% of the SLCs averaging <25 and >100 kg N ha-1 , respectively. Although only 3% of SLCs had average NH3 emissions reaching 16-200 kg ha-1 , most of these were located near cities and emissions spiked in spring when more people might be exposed. The greatest concentrations of nutrients and livestock occurred around the three largest metropolitan areas: Toronto, Montreal-Quebec City, and Vancouver, posing challenges for nutrient recycling and public health. This study shows that as Canadian cities and livestock agriculture grow in southern Canada, so will challenges around food production, human health, and managing nutrients. Livestock and land use strategies are needed to reconcile changing animal sectors and growing populations.

Canadian agriculture produces a diversified supply of food, feed crop and livestock types supporting Canada’s economy. This production uses both fertilizer-N application and biological N-fixation sources, which have increased over time and can be vulnerable to environmental losses in the form of ammonia (NH3) & nitrous oxide (N2O) emissions along with nitrate (NO3-) leaching. This paper reports the spatial and temporal trends in N input, N output and N losses in Canadian farmland with a specific focus on the residual soil N, N2O and NH3 emissions and NO3- leaching loss at the provincial scales from 1981 to 2016. A Canadian Agricultural Nitrogen Budget for Reactive N (CANBNr) model was developed to estimate the soil N balance at 3487 soil landscape of Canada polygons. The CANBNr model estimated soil N export via crop N removal, as well as emissions of N2O and NH3 for different input sources. The NO3- leaching is estimated based on the quantity of residual soil N (RSN) and water drainage derived using the DNDC model. From 1981 to 2016, the N inputs from fertilizer and biological N fixation increased at a greater rate than N exported in harvested crops for all provinces of Canada, which resulted in increased RSN and N losses. In 2016, we concluded that the Prairie provinces (Alberta, Saskatchewan and Manitoba) had lower N losses (N2O, NH3 and NO3-) per hectare of farmland (11.7 kg N ha-1) compared with 43.2 and 76.5 kg N ha-1 in Central Canada (Ontario and Quebec) & Atlantic provinces. However, the Prairie provinces represented 84.3% of the total Canadian farmland (74.3% of total Canadian N input), while central Canada represented only 12.9% of Canadian farmland (21.7% of total Canadian N input). The total N2O loss was 39.5 and 21.0 Gg N, whereas total NH3 loss was 202.3 and 110.2 Gg N in the Prairie and central Canada provinces, respectively, as influenced by both emissions and land area. In the non-growing season, NO3- leaching losses were 97.3 and 87.5 Gg N in the Prairies and central Canada provinces compared with 66.2 and 36.7 Gg N in the growing season as impacted by drainage volumes, soil type and the RSN. Over 36 years, the total fertilizer N increased the most in the Prairies and cased significant increase in RSN and N losses that will require future interventions.

It is generally accepted that land use and land management practices impact climate change through sequestration of carbon in soils, but modulation of surface energy budget can also be important. Using Landsat data to characterize cropland albedos in Canada's three prairie soil zones, this study estimates the atmospheric carbon equivalent drawdown of albedo radiative forcing for three management practices: 1) moving from conventional tillage to no-till, 2) eliminating summer fallow in crop rotations, and 3) growing crops with higher albedos. In a 50-year time horizon, conversion from conventional tillage to no-till results in a total equivalent atmospheric CO2 (CO2-eq) drawdown of 1.0-1.5 kg m(-2), and conversion from summer fallow to crops results in CO2-eq drawdown of 1.1-2.4 kg m(-2). Conversion of summer fallow to crops results in different magnitudes of CO2-eq drawdown depending on specific crops. Lentils, peas, and canola have relatively higher albedo than that of spring wheat and flax; hence, a larger magnitude of CO2-eq drawdown results when they replace summer fallow in the rotation. For the management changes from 1990 to 2019 for the whole Canadian Prairies, albedo changes induced a CO2-eq drawdown of about 179.3 +/- 20.9 Tg due to increased area of no-till, and 101.6 +/- 9.5 Tg due to reduced area under fallow. The study shows that the magnitudes of CO2-eq drawdown due to albedo change are comparable to that due to soil carbon sequestration. Therefore, it is important to account for cropland albedo changes in assessing the potential of agricultural management practices to mitigate climate change.

Surface albedo and soil carbon sequestration are influenced by agricultural management practices which impact the Earth's radiation budget and climate change. In this study we investigate the impact of reduced summer fallowing and reduced tillage in the Canadian Prairies on climate change by estimating the change in radiative forcing due to albedo and soil carbon sequestration. Seasonal variations of albedo, which are dependent on agricultural management practices and soil colour in three soil zones, were derived from 10-day composite 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) data. Using this information, we found an overall increase of surface albedo due to the conversion from summer fallowing to continuous cropping and from conventional tillage (CT) to either no-tillage (NT) or reduced tillage (RT). The increase was dependent on soil brightness, type of vegetation and snow cover. Using data from the Census of Agriculture and taking into consideration both albedo and soil carbon changes, we estimated that from 1981 to 2016, the total radiative forcing for the cropland area in the Canadian Prairies was -405 mu W m(-2) due to the conversion of CT to either NT or RT and about 70% was due to the change in albedo. During the same period, the total radiative forcing was -410 mu W m(-2) due to a reduction in the area under summer fallow and about 62% was due to the change in albedo. The equivalent atmospheric CO2 drawdown from these two management changes from albedo change was about 7.8 and 8.7 Tg CO2 yr(-1), respectively. These results demonstrate that it is important to consider both the changes of soil carbon and surface albedo in evaluating climate change impacts due to agricultural management practices. (C) 2020 Elsevier B.V. All rights reserved.

Thiso chapter presents aircraft-based methods of measuring the flux densities of sensible and latent heat, carbon dioxide, ozone, nitrous oxide, methane, and other trace gases. The main techniques and sensors that are used to measure flux densities with an aircraft are briefly described. Factors that affect the accuracy of those flux density measurements are discussed, including analysis techniques, run lengths, sampling heights, surface and environmental conditions, and data quality assessment. The use of aircraft-based flux density measurements to evaluate the representativeness of tower-based flux measurements is examined. The versatility of aircraft to act as sensor platforms under a wide range of conditions is demonstrated using several interesting examples. Future potential research directions are mentioned.

Alongside the steep reductions needed in fossil fuel emissions, natural climate solutions (NCS) represent readily deployable options that can contribute to Canada’s goals for emission reductions. We estimate the mitigation potential of 24 NCS related to the protection, management, and restoration of natural systems that can also deliver numerous co-benefits, such as enhanced soil productivity, clean air and water, and biodiversity conservation. NCS can provide up to 78.2 (41.0 to 115.1) Tg CO2e/year (95% CI) of mitigation annually in 2030 and 394.4 (173.2 to 612.4) Tg CO2e cumulatively between 2021 and 2030, with 34% available at ≤CAD 50/Mg CO2e. Avoided conversion of grassland, avoided peatland disturbance, cover crops, and improved forest management offer the largest mitigation opportunities. The mitigation identified here represents an important potential contribution to the Paris Agreement, such that NCS combined with existing mitigation plans could help Canada to meet or exceed its climate goals.

The two main sources of CH4 from the agricultural sector are enteric fermentation and manure management systems. Canada uses the IPCC Tier-II methodology to estimate CH4 for its national inventory report of GHG emissions to UNFCCC, which is based on a bottom-up approach using activity data and emission factors obtained through site level experimental measurements. However, because of the presence of wetlands in some agricultural regions, it has been challenging to obtain accurate CH4 emission estimates at a regional scale. This study explores the usefulness of S5P methane product for verifying methane emission estimates in eastern Ontario agricultural land. We investigated the spatiotemporal variability of total column methane mixing ratio, as well as other detailed data layers in the TROPOMI product, such as averaging kernels and a prior profiles. The spatial temporal patterns of wetland methane emission derived from the global WetCHARTs dataset, and a prior knowledge of livestock distribution in the region, are used to interpret S5P methane product. Results showed that TROPOMI methane product provides great spatiotemporal coverage that can be used to verify CH4 emissions from agricultural landscape. This will be useful to reduce methane estimation uncertainties at the regional and national scales.

The discussion of diversified protein sources triggered by the 2019 Canadian Food Guide has implications for Canada’s livestock industry. In response to this discussion, a scenario analysis is conducted on the potential impact of reducing red meat consumption on the greenhouse gas (GHG) emissions from Canadian livestock production. This analysis uses medical recommendations as a proxy for healthy servings of red meat. For simplicity, it was assumed that red meat is either beef or pork and that broilers are the only nonred meat choice. The medical scenario is combined with four livestock production scenarios for these three livestock types. Broiler consumption is allowed to expand to maintain national protein intake in all four scenarios. Under the medical scenario, red meat consumption in Canada would decrease from 2.5 Mt to 1.9 Mt of live weight. A feedlot diet for slaughter cattle, and a 50:50 split of the medically recommended red meat intake of beef and pork (Scenario 1), reduced GHG emissions by 3.9 Mt CO2e from the 20.6 Mt CO2e (carbon dioxide equivalent) for current consumption. Replacing the feedlot beef diet by grass fed beef (Scenario 2) increased GHG emissions by 1.5 Mt CO2e over Scenario 1. Halving the consumption of grass fed beef and increasing pork by 50% (Scenario 3) reduced GHG by 7.7 Mt CO2e. Reverting back to the feedlot diet, and the same 25:75 beef–pork ratio (Scenario 4), increased the GHG emissions reduction to 8.9 Mt CO2e. Without including the emission savings from the medical scenario, GHG reductions from Scenarios 3 and 4 dropped to 3.8 Mt and 5.0 Mt CO2e, respectively. No scenario exceeded the feed grain area required to meet the 2017 consumption of these commodities, but Scenario 2 required more forage area compared to consumption in 2017.

Methane (CH4) is an important greenhouse gas. Emissions from landfills and waste treatment sites are regarded as the third largest anthropogenic source in the world. Precise estimates of CH4 emissions depend on a well-designed sampling procedure and detailed analyses. This study estimates CH4 emissions from a waste treatment site by analyzing the data from a flight, which was carried out in Eastern Ontario, Canada, on May 6, 2011. The CH4 dispersion plume at about 140 m above ground level downwind of the source is analyzed with data from 14 flight tracks. The observation period of about 72 min is characterized by unstable boundary layer conditions, strong wind, and shifting wind direction. To replicate the boundary layer turbulence and the CH4 dispersion during the measurement period, a combined large-eddy simulation (LES) and Lagrangian stochastic (LS) particle dispersion modeling method is used. A preliminary simulation run with mean meteorological variables during the experiment's duration is carried out. The results reproduced the shifts in wind direction well, in addition to the dispersion plume, but in a smaller magnitude in comparison to the measured data. Therefore, two sets of LES runs are carried out to represent the boundary layer turbulence before and after the wind shift. Another deficiency in the LES runs is that the simulated turbulent velocity variances are systematically smaller than the observed counterparts. In response to this discrepancy, additional terms are incorporated into the LS dispersion model so as to represent the turbulence dispersion process better. With these treatments, the LES-LS modeling results replicated the dispersion plume both in lateral width and in concentration distribution shape. Then, by using the simulated relationship between source and concentrations/vertical fluxes in space, the CH4 emission rate of the site is estimated as 2393 (kg CH4 hr(-1)) / 2088 (kg CH4 hr(-1)) respectively.

The recommendation in the 2019 Canada Food Guide to diversify protein sources in the human diet could lead to less red meat consumption by Canadians. The main goal of this paper was to assess the potential impact of the reduction in red meat consumption on the carbon footprint of Canadian livestock production. Beef, pork and broilers were used to represent Canadian carcass based food commodities. Three scenarios for allowable red meat (beef and pork) consumption were tested based on medical recommendations of 15.9, 23.7 and 27.6 kg (boneless weight) per capita per year. Maintaining national dietary protein intake at 0.39 Mt was the main boundary condition for the projected reduction of red meat. A spreadsheet model was used to interpolate published Greenhouse Gas emission estimates from 1981 to 2006 for beef, pork and broiler production to 2017. This model accounted for the life cycles, age-gender categories, and supporting crop complexes of each livestock type. Three production scenarios based on two different apportionments of allowable red meat to beef and pork, and two alternative beef diets, were combined with the three medical scenarios to formulate nine projected consumption recommendations. These projections generated the slaughter animal live weights, Greenhouse Gas emissions from their production, and their protein contents. All nine scenarios required a major expansion of broiler production to satisfy the required national protein intake. The amounts by which the nine scenarios reduced Greenhouse Gas emissions ranged from 0% to 31% of the 32.6 Mt of total national CO(2)e emissions for the production of these three commodities in 2017. (c) 2020 Published by Elsevier Ltd.

It is uncertain whether process-based models are currently capable of simulating the complex soil, plant, climate, manure management interactions that influence soil nitrous oxide (N2O) emissions from perennial cropping systems. The objectives of this study were (1) to calibrate and evaluate the DeNitrification DeComposition (DNDC) model using multi-year datasets of measured nitrous oxide (N2O) fluxes, soil moisture, soil inorganic nitrogen, biomass and soil temperature from managed grasslands applied with manure slurry in contrasting climates of Canada, and (2) to simulate the impact of different manure management practices on N2O emissions including slurry application i) rates (for both single vs. split); and ii) timing (e.g., early vs. late spring). DNDC showed "fair" to "excellent" performance in simulating biomass (4.7% <= normalized root mean square error (NRMSE) <= 29.8%; -9.5% <= normalized average relative error (NARE) <= 16.1%) and "good" performance in simulating soil temperature (13.2% <= NRMSE < 18.1%; -0. 7% <= NARE <= 10.8%) across all treatments and sites. However, the model only showed "acceptable" performances in estimating soil water and inorganic N contents which was partially attributed to the limitation of a cascade water sub-model and inaccuracies in simulating root development/uptake. Although, the DNDC model only demonstrated "fair" performance in simulating daily N2O fluxes, it generally captured the impact of the timing and rate of slurry application and soil texture (loam vs. sandy loam) on total N2O emissions. The DNDC model simulated N2O emissions from spring better than split manure application (fall and spring) at the Manitoba site partially due to the overestimation of available substrates for microbial denitrification from fall application during the wet spring periods. Although DNDC performed adequately for simulating most of the manure management impacts considered in this study we recommend improvements in the simulation of soil freeze-thaw cycles, manure decomposition dynamics, soil water storage, rainfall canopy interception, and microbial denitrification and nitrification activities in grasslands. Crown Copyright (C) 2019 Published by Elsevier B.V.

The rapid increase in the atmospheric concentrations of greenhouse gases (GHGs) has given rise to international commitments to reduce GHG emissions such as the Kyoto Protocol and the Paris Climate Agreement. If countries are going to be successful in meeting their commitments and help reduce the impact of climate change, it is essential that all sectors of the economy be part of the solution. In Canada, the agriculture sector, which encompasses a wide array of production systems and commodities, accounts for about 12% of the anthropogenic GHG emissions. Numerous techniques have been developed to quantify GHG emissions from the agriculture sector. The data collected have been used to calculate the carbon footprints of a wide range of agricultural products and to develop indicators to help formulate climate change mitigation and adaptation policies for the sector. It is well known that agricultural soils have lost large quantities of carbon in the past. With some of the changes in management practices, agricultural soils in some regions have now become significant sinks of carbon. The agriculture sector is responsible for carbon dioxide emissions associated with fertilizer production, farm fieldwork operations, machinery supply and a variety of other smaller sources. It is also the biggest anthropogenic source of methane and nitrous oxide. If we are to promote the consumption of low carbon products, it is then important to have an accurate estimate of the GHG emissions associated with their production. Carbon footprint estimates vary substantially depending on the units and what is included in the calculations. Recent estimates of the carbon footprints per unit protein for animal products ranged from 215 kg CO2e for sheep to 15 kg CO2e for poultry–broiler meat. As expected, the carbon footprints per unit protein of plant products are substantially less. Some examples are presented on how the sharing of the environmental burden reduces the magnitude of the carbon footprints of certain products and how environmental indicators can be used to develop policies. These results highlight opportunities for climate change mitigation by consumers and producers of agricultural products in Canada.

Agricultural soils in Canada have been observed to emit a large pulse of nitrous oxide (N2O) gas during the spring thaw, representing a large percentage of the annual emissions. We report on three years of spring thaw N2O flux measurements taken at three Alberta agricultural sites: a crop production site (Crop), cattle winter-feeding site (WF), and a cattle winter-grazing site (WG). Soil fluxes were calculated with a micrometeorological technique based on the vertical gradient in N2O concentration above each site measured with an open-path (line-averaging) FTIR gas detector. The Crop and WG sites showed a clear N2O emission pulse lasting 10 to 25 days after thawing began. During this pulse there was a strong diurnal cycle in emissions that paralleled the cycle in near-surface soil temperature. The emission pulse was less pronounced at the WF site. The average spring thaw losses (over 25 to 31 days) were 5.3 (Crop), 7.0 (WF), and 8.0 (WG) kg N2O-N ha−1, representing 1 to 3.5% of the annual nitrogen input to the sites. These large losses are higher than found in most previous western Canadian studies, and generally higher than the annual losses estimated from the Intergovernmental Panel on Climate Change and Canadian National Inventory Report calculations. The high N2O losses may be explained by high soil nitrate levels which promoted rapid denitrification during thawing. The application of a high resolution (temporal) micrometeorological technique was critical to revealing these losses.

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.

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's 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 +/- 1 standard error: EC = 17 +/- 4 mg CH4 m(-2) d(-1); REA = 19 +/- 3 mg CH4 m(-2) d(-1), wavelet covariance = 16 +/- 3 mg CH4 m(-2) d(-1)), and are not statistically different, but significantly exceed bottom-up inventory estimates of CH4 emissions based on animal husbandry (8 +/- 1 mg CH4 m(-2) d(-1)). 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.

This paper describes fossil fuel energy use for on-farm transportation, heating of farm buildings, electricity generation, machinery supply and the spreading of manure. These four terms describe the barnyard energy budget. Calculations for this energy budget were driven by population data for beef and dairy cattle, hogs and poultry in Canada. Prior to comparing this energy budget for 2001 and 2011, the year-to-year trends from 1990 to 2014 were analysed. The declines in all livestock populations, except poultry, between 2001 and 2011 reduced the size of the Canadian barnyard energy budget from 25 PJ to 22 PJ. The resulting change in the fossil CO2 emissions between 2001 and 2011 was from 1.62 MtCO2 to 1.36 MtCO2. A sensitivity analysis based on future elimination of coal for generating electricity, introduction of electric pickup trucks (e-pickups) and increased use of electric heat, reduced fossil CO2 emissions during 2011 from dairy farms by 29%, beef farms by 24%, hog farms by 19% and poultry by 13%. The most affected provinces by this test were Alberta and Saskatchewan because of the heavy dependence on coal in electricity generation in these two provinces. This scenario test suggests a Canada-wide potential reduction of 0.30 MtCO2. A second sensitivity test based on a Canada-wide 20% reallocation of protein production from beef to pork revealed a very modest potential to actually reduce barnyard fossil CO2 emissions by 0.09 MtCO2 for Canada.

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.