Devon E. Worth

Impact of management strategies on the global warming potential at the cropping system level

Estimating the greenhouse gas (GHG) emissions from agricultural systems is important in order to assess the impact of agriculture on climate change. In this study experimental data supplemented with results from a biophysical model (DNDC) were combined with life cycle assessment (LCA) to investigate the impact of management strategies on global warming potential of long-term cropping systems at two locations (Breton and Ellerslie) in Alberta, Canada. The aim was to estimate the difference in global warming potential (GWP) of cropping systems due to N fertilizer reduction and residue removal. Reducing the nitrogen fertilizer rate from 75 to 50 kg N ha(-1) decreased on average the emissions of N2O by 39%, NO by 59% and ammonia volatilisation by 57%. No clear trend for soil CO2 emissions was determined among cropping systems. When evaluated on a per hectare basis, cropping systems with residue removal required 6% more energy and had a little change in GWP. Conversely, when evaluated on the basis of gigajoules of harvestable biomass, residue removal resulted in 28% less energy requirement and 33% lower GWP. Reducing nitrogen fertilizer rate resulted in 18% less GWP on average for both functional units at Breton and 39% less GWP at Ellerslie. Nitrous oxide emissions contributed on average 67% to the overall GWP per ha. This study demonstrated that small changes in N fertilizer have a minimal impact on the productivity of the cropping systems but can still have a substantial environmental impact.

Coupling of winter climate transitions to snow and clouds over the Prairies

Using data from 13 climate stations on the Canadian Prairies, together with opaque cloud cover and daily snow depth, to analyze the winter climate transitions with snow, we find that a snow cover acts as a fast climate switch. Surface temperature falls by about 10 K with fresh snowfall and rises by a similar amount with snowmelt, while the daily range of relative humidity falls to around 5–15% with snow cover. These are robust climate signals. For every 10% decrease in days with snow cover over the Canadian Prairies, the mean October to April climate is warmer by about 1.4 K. Stratifying by daily mean opaque cloud cover across snow transitions shows the rapid shift within 5 days from a diurnal cycle dominated by shortwave cloud forcing to one dominated by longwave cloud forcing. We calculate the change in the surface radiative budget with snow using surface albedo data from the Moderate Resolution Imaging Spectroradiometer and station longwave data. We find that with the fall-winter snow transitions, the surface radiative heating is reduced by 50 Wm−2, with 69% coming from the reduced net shortwave flux, resulting from the increased surface albedo and a small increase in effective cloud albedo, and 31% from a reduced incoming longwave flux. This drop in surface radiative heating is sufficient to produce a drop in the surface radiometric skin temperature of 11 K. We find that in winter, the monthly mean diurnal climate is more closely coupled to the diurnal shortwave forcing than the mean diurnal climate.

The Protein-based GHG Emission Intensity for Livestock Products in Canada

Assessments of the total greenhouse gas (GHG) emissions and emission intensities had been carried out prior to this analysis for dairy, beef, pork, and poultry in Canada. The GHG emission intensities of these industries were based on different units of food produced. In this paper, the GHG emission intensities of the four livestock industries were compared on the basis of the weight of protein produced. The protein-based emission intensity for beef was almost four times as high as the GHG emission intensity for milk production. The emission intensities of pork production were lower than the emissions from milk production because of lower CH4 emissions. Broilers had the lowest GHG emission intensity of all five livestock commodities. The next lowest GHG intensity was for egg production. The differences between the egg and broiler intensities cannot be attributed to any one GHG. The number of breeding animals that must be maintained in order to produce one animal for slaughter is much higher for cattle than for swine or poultry. The slow means of reproduction of beef cattle is a better explanation for the observed difference between the GHG emission intensities of ruminants and non-ruminants than is enteric methane.

Climate coupling between temperature, humidity, precipitation, and cloud cover over the Canadian Prairies

This analysis uses over 50 years of hourly observations of temperature, relative humidity, and opaque cloud cover and daily precipitation from 11 climate stations across the Canadian Prairies to analyze the monthly, seasonal, and long-term climate coupling in the warm season. On climate time scales, temperature depends on cloud forcing, while relative humidity depends on precipitation. The monthly climate depends on both opaque cloud cover for the current month and precipitation for both the present and past 2 months in summer. Multiple linear regression shows that anomalies of opaque cloud and precipitation explain 60–80% of the variance in the diurnal temperature range, afternoon relative humidity, and lifting condensation level on monthly time scales. We analyze the internal coupling of diurnal climate observables as a further guide to evaluating models. We couple the statistics to simplified energy and water budgets for the Prairies in the growing season. The opaque cloud observations have been calibrated against the incoming shortwave and longwave fluxes. We estimate that the drydown of total water storage on the landscape damps 56% of precipitation anomalies for the growing season on large spatial scales, although this drydown increases evapotranspiration. This couples the climatological surface fluxes to four key observables: cloud forcing, precipitation, temperature, and humidity. We estimate a climatological evaporative fraction of 0.61 for the Prairies. The observational relationships of the coupled Prairie climate system across time scale will be useful for evaluating these coupled processes in models for weather and seasonal forecasting and climate simulation.

A Greenhouse Gas and Soil Carbon Model for Estimating the Carbon Footprint of Livestock Production in Canada

Simple Summary We developed a model to estimate the carbon footprint of Canadian livestock production. To include long term soil carbon storage and loss potential we introduced a payback period concept. The model was tested by reallocating 10% only of the protein production from a ruminant to a non ruminant source to minimize the risk of including rangeland or marginal lands. This displacement generated residual land which was found to play a major role in the potential mitigation of GHG emissions. The model will allow land use policies aimed at reducing the agricultural GHG emissions to be assessed. Abstract To assess tradeoffs between environmental sustainability and changes in food production on agricultural land in Canada the Unified Livestock Industry and Crop Emissions Estimation System (ULICEES) was developed. It incorporates four livestock specific GHG assessments in a single model. To demonstrate the application of ULICEES, 10% of beef cattle protein production was assumed to be displaced with an equivalent amount of pork protein. Without accounting for the loss of soil carbon, this 10% shift reduced GHG emissions by 2.5 TgCO2e y−1. The payback period was defined as the number of years required for a GHG reduction to equal soil carbon lost from the associated land use shift. A payback period that is shorter than 40 years represents a net long term decrease in GHG emissions. Displacing beef cattle with hogs resulted in a surplus area of forage. When this residual land was left in ungrazed perennial forage, the payback periods were less than 4 years and when it was reseeded to annual crops, they were equal to or less than 40 years. They were generally greater than 40 years when this land was used to raise cattle. Agricultural GHG mitigation policies will inevitably involve a trade-off between production, land use and GHG emission reduction. ULICEES is a model that can objectively assess these trade-offs for Canadian agriculture.

Sources of uncertainty in the IPCC Tier 2 Canadian livestock model

Estimates of uncertainties are essential when comparing the greenhouse gas (GHG) emissions from a variety of sources. Monte Carlo Simulation (MCS) was applied to estimate the uncertainties in methane emissions and the methane emission intensities from livestock in Canada, calculated using the Intergovernmental Panel on Climate Change (IPCC) methodology. National methane emissions from enteric fermentation and manure management in 2008 were 21·2 and 4·3 Teragram CO 2 equivalents (Tg CO 2 e) with uncertainties of 38 and 73%, respectively. The methane emission intensities (kg of CO 2 e per kg of live animal weight) were 5·9, 0·9 and 4·9 from Canadian beef, swine and lamb, respectively, with overall uncertainties of 44, 99 and 101%, defined as the 95% confidence interval relative to the mean. A sensitivity analysis demonstrated that IPCC default parameters such as the methane conversion rate ( Y m ), the coefficient for calculating net energy for maintenance (Cf i ) and the methane conversion factor (MCF) were the greatest sources of uncertainty. Canadian agricultural methane emissions are usually calculated by province and by animal subcategories. However, the IPCC default parameters can be assumed to be correlated among regions and animal subcategories; therefore values are assigned at the national scale for the main cattle categories (dairy and non-dairy cattle). When it was assumed that these parameters were uncorrelated at the regional scale, the overall uncertainties were reduced to 20 and 48% for enteric fermentation and manure management, respectively, and assuming that parameters were uncorrelated at the animal subcategory scale reduced uncertainties to 13 and 41% for enteric fermentation and manure management, respectively. When the uncertainty is assigned at the most disaggregated level, even doubling the uncertainty of key parameters such as Y m and Cf i , only increased the national uncertainties to 22 and 52% for enteric fermentation and manure management, respectively. The current analysis demonstrated the importance of obtaining parameters specific to regions and animal subcategories in order to estimate GHG emissions more accurately and to reduce the uncertainties in agricultural GHG inventories. It also showed that assumptions made in the calculation of uncertainties can have a large influence on the uncertainty estimates.

LCA of animal production

Human development is reliant on the Earth’s ecosystems to provide energy and nutrients. However, through the use of fossil fuels, humans can now override or shortcut many of these natural cycles. In effect, humankind has created its own pseudo-ecosystem, driven primarily by economic rather than environmental processes. Our reliance on economic and distancing from ecological principles lies at the heart of many of our agricultural–environmental problems. Solutions to these problems will therefore be found through a closer integration of anthropogenic processes and biogeochemical cycles.

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 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 and in the range of morning from the 1960s to the 2000s. The increase in the observed range of 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.