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This study quantified fugitive methane (CH

This study quantified the distribution of animals by farm size for portions of the dairy, beef, swine, and poultry sectors using the 2016 Census of Agriculture. Results showed that the distribution of farm sizes and animal populations were skewed or bimodal and varied by livestock type and by province. Thus, the average farm size has little meaning. Recognizing farm size diversity is important for developing effective policies and programs, conducting appropriate research, and developing practices and technologies to support farms of all sizes.

Extruded waste wood was subjected to microbial pre-treatment using two bacterial strains, Petronet Alfa and Petronet Omega. In phase one, the effects of strain type and dose, and incubation temperature on hydrolysis were investigated through measuring the amount of dissolved glucose content after hydrolysis. In phase two, biomethane potential (BMP) assays were conducted for microbially pre-treated wood waste under the optimum conditions obtained in phase one. Results showed that the effect of strain dose, temperature, and aeration on released glucose were statistically significant at p-value of 0.05 level. At the optimum conditions of using Petronet Omega at a dose of 5.0 g/L and 37 °C, the microbial pre-treatment could increase the amount of dissolved glucose by as much as 205%. The findings of BMP assays showed improvement in biogas production as a result of the substrate pre-treatment by Petronet Alfa and Petronet Omega where a biomethane yield of 54.4 and 49.1 mL CH4/g VS were obtained, respectively, which correspond to 88.9 and 70.2% increase compared with the control. Among four kinetic models tested, the modified Gompertz model demonstrated the best performance and showed that the lag phase was significantly reduced due to microbial pre-treatment of substrate.

Highlights Studies of electricity use were reviewed, representing five continents. Considering all farm types, electricity use averaged 7.7 kWh 100 kg-1 milk and 612 kWh cow-1 y-1. Pasture-based dairy systems used less electricity than barn-based systems (475 vs. 769 kWh cow-1 y-1). By combining several conservation technologies there is potential to reduce electricity demand by one-third. Dairy farms can reach net zero electricity by combining renewable energy production with conservation. Abstract. This review summarizes electricity use on dairy farms, with a focus on how energy is used, energy use indices (EUI), conservation strategies, and generation of renewable energy to reach net zero. EUI of electricity consumption varied between the identified studies primarily based on farm management system (confined, pasture-based), housing type (tie-stall, free-stall), and region (North America, Europe, Asia, Africa, Oceania). The highest electricity usage was associated with milking and milk cooling systems, which, on average, accounted for 23% and 22% of total electricity use, respectively. Energy use scaled per cow (EUIc) was lower, on average, for pasture-based dairy systems than for confined systems (475 vs. 769 kWh cow-1 y-1). Considering milk production, the average EUI scaled to milk (EUIm) was lower for pasture-based systems (6.6 kWh 100 kg-1) than for confined systems 9.2 kWh 100 kg-1. Considering all non-irrigated farm types, EUIm averaged 7.7 kWh 100 kg-1 and EUIc averaged 612 kWh cow-1 y-1. There was a large range of EUI, with higher values associated with automated milking systems and irrigation. Electricity consumption by the global dairy sector (excluding irrigation) was estimated using the average EUIm at approximately 64.2 TWh y-1. The main conservation technologies include variable speed drives (milk vacuum pumps, milking systems, fans), pre-cool heat exchangers, refrigeration heat recovery systems, energy-efficient light fixtures (compact fluorescents, light emitting diodes), and efficient ventilation (high-volume low-speed fans). Theoretical savings of up to 32% overall could be achieved by combining several technologies. Feedback from electricity monitoring can inform dairy farmers of their energy use pattern to guide decisions to reduce consumption. Tools for predicting energy use and related costs on dairy farms, which can indicate potential energy savings from operational changes, were reviewed. By combining conservation methods with renewable energy from biogas or solar, many dairy farms can produce enough electricity to reach net zero electricity. For example, a hypothetical barn-based 250 milking-cow dairy farm consumed 1021 kWh cow-1 y-1, on average, and could produce approximately 1095 kWh cow-1 y-1 using a biodigester or 960 kWh cow-1 y-1 using rooftop photovoltaic solar panels. Keywords: Conservation, Dairy footprint, Electricity use, Electricity partitioning, Energy utilization index, Renewable energy.

Methane emissions from liquid manure management in Canada are an important greenhouse gas source. A wide range of seasonal temperatures, distribution of livestock farms, and various management practices in Canada means that regional methane conversion factors (MCF) that account for spatially discrete climate and management should be used. This study explores the impacts of using the 2019 IPCC Refinement methodology on estimates of MCFs across Canada. MCFs were calculated for 3403 locations across Canada using historical weather data, with varying management parameters at each location (emptying efficiency, timing, and frequency of manure removal). Sensitivity to two model parameters was also evaluated (minimum manure temperature, damping factor). Results showed the influence of climate, as average MCF in each ecozone ranged from 0.27 in the Mixedwood Plains to 0.15 in the Taiga. Further climate variation within ecozones was evident. For example, the MCF range within Mixedwood Plains was 0.17 to 0.33. The MCF reduction by improving management was evident as the average MCF in Canada was 0.15 for triannual removal, 0.21 for biannual removal, 0.28 for one-time removal in spring, and 0.32 for one-time removal in fall. Emptying efficiency was found to be critical; for example, the average MCF for triannual removal with 100% efficiency was 0.14 but increased to 0.15 at 95%, 0.17 at 85%, and 0.30 at 50% efficiency. The damping factor had higher sensitivity in terms of model parameters because it influences peak manure temperature in summer before manure removal. Our results suggest that the average MCF in Canada will be similar to the 2006 IPCC value, but that using the 2019 IPCC Refinement provides a greater ability to represent the variations in climate and management regionally across the country. This will improve accuracy and enable inventory practitioners to reflect regional farm management changes in national methane emission estimates.

Acidification with sulphuric acid and cleaning residual manure in tanks are promising practices for reducing methane (CH4), which is a potent greenhouse gas. To date, no data are available on CH4 reductions from acidifying only residual manure (rather than all manure). Moreover, long-term effects of manure acidification (i.e. inoculating ability of previously acidified residual manure in the subsequent storages) are not known. To address these gaps, fresh manure (FM; 150 mL) combined with treated or untreated inoculum (30 mL) were anaerobically incubated at 17°C, 20°C, and 23°C for 116 d. Acidified treatments, regardless of location of acid addition, reduced CH4 production by 81% at 17°C, 78% at 20°C, and 19% at 23°C compared to the control (untreated FM and untreated inoculum). To test long-term acidification effects, FM was inoculated with manure that had been acidified 6-months prior. This created comparable CH4 production to FM with no inoculum and reduced CH4 production by 99% at 17°C and 20°C, and 49% at 23°C compared to the control. Results indicate that residual slurries of acidified manure become poor inoculants in subsequent storage, hence manure acidification has a long-term treatment effect in reducing CH4 production. This could reduce how often acidification is needed in dairy manure tanks and also increasing its cost-effectiveness for farmers.

A novel laboratory method was developed to control soil freeze–thaw cycles and study the effects of freezing intensity on soil conditions and N2O emissions. The method created unidirectional freeze–thaw (top-down), similar to field conditions. Soil was placed in boxes that were insulated on the sides, heated from the bottom, and left open on the top. Snow was placed on the soil surface, and the boxes were placed in separate climate-controlled chambers to freeze (−9 °C) and thaw (5 °C). The method was used in an experiment to evaluate the links between freezing degree days (FDD), soil water content, carbon (C) and nitrogen (N) transformations, and N2O emissions. Results showed that N2O emissions were greatest from soils that experienced more freezing, with the 185 FDD treatment emitting significantly more N2O than the 50 FDD treatment (17.7 vs. 7.7 mg N2O-N m−2d−1). Peaks in soil water content during thaw preceded peaks in N2O flux, but increasing water content by simulating rain (in addition to snow melt) did not increase N2O emissions compared with snow melt alone. Extractable soil C and N increased in the top 5 cm when soils froze; however, greater emissions were not linked to greater C and N concentrations at individual points in time. Higher N2O emissions at 134 and 185 FDD were associated with greater C exposure (i.e., extractable soil C concentration integrated over time) than the 50 FDD treatment.

HighlightsEvaporation from clear water, manure, and separated liquid manure was 4.6 mm d-1 on average.Straw, foam, geotextile, and roof covers decreased evaporation by 54%, 53%, 31%, and 21%, respectively.Albedo was highest for floating foam covers and lowest for metal roof covers.Straw, foam, and geotextile increased manure temperature compared to uncovered manure. ABSTRACT. Evaporation is a key component of the surface energy budget of liquid manure. Models rely on accurate energy budgets to predict manure temperature, which in turn is used to model temperature-dependent greenhouse gas emissions from liquid manure storages. Due to lack of data, it has been assumed that liquid manure has similar evaporative properties to water; however, this assumption may be inaccurate. Many factors, including manure crusting, covers, and turbidity, are all likely to affect the surface energy budget and the evaporation rate. This experiment investigated the differences in evaporation between eight treatments, including water, dyed water, raw and separated liquid manure, and four commonly used covers (straw, geotextile, foam, and roof), by measuring weekly evaporation. Albedo, surface temperatures, and internal temperatures were also measured to determine treatment effects. Over the 10-week study, no significant difference was found between the evaporation rates of water, raw manure, and separated liquid manure, with an average rate of 4.6 mm d-1. Notably, the raw manure did not form a consistent surface crust, which may explain the similarities in evaporation rates in this study and is unlikely to represent manure with a crust. Overall, covers significantly decreased evaporative losses by between 21% and 54% compared to uncovered raw manure. Average evaporation rates of the covered treatments were 1.9 mm d-1 for straw cover, 2.0 mm d-1 for foam cover, 2.9 mm d-1 for geotextile cover, and 3.4 mm d-1 under a roof cover. Similarities between each treatment and water as well as between the four covered treatments and the uncovered raw manure were found using linear regression on weekly evaporation. Generally, the uncovered treatments were more similar and could be predicted (high R2) by multiple linear regression with environmental variables, while the covered treatments differed more and were not as well predicted (lower R2). Results from this study can help adjust evaporation rates in biophysical models to improve estimates of manure temperature, tank holding capacity, and emission predictions. Keywords: Evaporation, Dairy manure, Liquid manure, Manure covers, Manure management.

Standard life cycle assessment and economic analysis methods were used to determine the carbon footprint (CF) of milk production and financial performance of a representative sample of dairy farms in Ontario, Canada to assess if there is a trade-off between these two different sustainability measures. Across the 142 dairy farms, CF of milk varied by about 4-fold, from 0.441 to 1.732 CO2eq kg−1 FPCM, a much larger variation than estimated using spatially disaggregated statistical data. Emissions from enteric fermentation and those resulting from the production and supply of feed were the largest contributors to the CF of milk (44% and 36%, respectively). Dairy profits per cow averaged CA$4848 per year but ranged from CA$2530 to $7151 across sample farms. These financial returns were inversely correlated with the CF of milk production, suggesting that rather than a trade-off between GHG emissions intensity and economic performance, there is instead a synergy of the two sustainability indicators. Using a linear regression approach we find that a reduction in the CF of milk production can be achieved while simultaneously improving the profitability of dairy farms. This synergy was largely determined by farm characteristics related to livestock productivity (e.g. milk production per cow) and feeding practices (e.g. herd level total feed use and reliance on purchased feed). Our results suggest that in the absence of explicit GHG reduction policies targeting dairy farms, the main incentive for reducing farm-level GHG emissions could result from the economic pressure on farmers to increase their profitability per cow or per ha.

Liquid dairy manure storages are sources of methane (CH), nitrous oxide (NO), and ammonia (NH) emissions. Both CH and NO are greenhouse gases (GHGs), whereas NH is an indirect source of NO emissions. Manure acidification is a strategy used to reduce NH emissions from swine manure; however, limited research has expanded this strategy to reducing CH and NO emissions by acidifying dairy manure. This study compared control dairy manure (pH 7.4) with two treatments of acidified manure using 70% sulfuric acid (HSO). These included a medium pH treatment (pH 6.5, 1.4 mL acid L manure) and a low pH treatment (pH 6, 2.4 mL acid L manure). Emissions were measured using replicated mesoscale manure tanks (6.6 m) enclosed by large steady state chambers. Both CH and NO were continuously measured (June-December 2017) using tunable diode laser trace gas analyzers. Ammonia emissions were measured three times weekly for 24 h using acid traps. On a CO equivalent basis, the medium pH treatment reduced total GHG emissions by 85%, whereas the low pH treatment reduced emissions by 88%, relative to untreated (control) manure. Total CH emissions were reduced by 87 and 89% from medium and low pH tanks, respectively. Ammonia emissions were reduced by 41 and 53% from medium and low pH tanks, respectively. Additional research is necessary to make acidification an accessible option for farmers by optimizing acid dosage. More research is need to describe the manure buffering capacity and emission reductions and ultimately find the best approaches for treating farm-scale liquid dairy manure tanks.

There is an incentive for dairy farmers to maximize crop production while minimizing costs and environmental impacts. In cold climates, farmers have limited opportunity to balance field activities and manure storage requirements while limiting nutrient losses. A revised DeNitrification DeComposition (DNDC) model for simulating tile drainage was used to investigate fertilizer scenarios when applying dairy slurry or urea on silage corn ( L.) to examine N losses over a multidecadal horizon at locations in eastern Canada and the US Midwest. Management scenarios included timing (spring, fall, split, and sidedress) and method of application (injected [10 cm], incorporated [5 cm], and broadcast). Reactive N losses (NO from drainage and runoff, NO, and NH) were greatest from broadcast, followed by incorporated and then injected applications. Among the fertilizer timing scenarios, fall manure application resulted in the greatest N loss, primarily due to increased N leaching in non-growing-season periods, with 58% more N loss per metric ton of silage than spring application. Split and sidedress mineral fertilizer had the lowest N losses, with average reductions of 9.5 and 4.9%, respectively, relative to a single application. Split application mitigated losses more so than sidedress by reducing the soil pH shift due to urea hydrolysis and NH volatilization during the warmer June period. This assessment helps to distinguish which fertilizer practices are more effective in reducing N loss over a long-term time horizon. Reactive N loss is ranked across 18 fertilizer management practices, which could assist farmers in weighing the tradeoffs between field trafficability, manure storage capacity, and expected N loss.

Dairy rotations rely on corn silage, which is estimated to have significant nitrous oxide (N2O) emissions. This study examined whether including legumes within rotations can reduce N2O emissions from the soil surface and dissolved in tile-drainage water. Emissions of N2O were measured from the soil surface and in tile drainage. Cropping systems were: corn–corn (CC), corn + cover crop-corn (C + cc), soybean–corn (SC) and alfalfa–alfalfa (AA) on a clay soil. Liquid dairy manure provided 2-year total N inversely related to legume cropping: 310 (CC), 280 (C + cc), 110 (SC), 50 kg N ha−1 (AA). Losses of N2O via tile drainage were 0.1–0.3% of total emissions. Ratios of N2O-N to NO3−-N in drainage were at least 63% lower than the IPCC default value (0.0075). Reductions of N2O emissions were only observed from established alfalfa in year 2. Compared to the SC treatment, which had the highest emissions in year 2, the AA treatment had 62% lower surface N2O and 88% lower dissolved N2O flux. Alfalfa had low yield in the first year, which led to high yield-scaled N2O emissions; thus, alfalfa may need to be grown 4 years to achieve a similar average yield scaled emission factor as CC. Silage corn had consistently high yield, averaging 317 kg ha−1 yr−1 for N yield, which was 36% higher than AA. As a result, CC had the lowest N2O emissions scaled by N-yield over the 2 years, averaging 2.6% of N-yield, which was 59% lower than AA on average.

Open dumpsites that receive municipal solid waste are potentially significant sources of greenhouse gas (GHG) emissions into the atmosphere. There is little data available on emissions from these sources, especially in the unique climate and management of central Africa. This research aimed at quantifying CH4, N2O and CO2 emissions from two open dumpsites in Cameroon, located in Mussaka-Buea, regional headquarters of the South West Region and in Mbellewa-Bamenda, regional headquarters of the North West Region. Emissions were measured during the wet season (May 2015 and August 2016) at the Mussaka and Mbellewa dumpsites respectively. Dumpsite surfaces were partitioned into several zones for emission measurements, based on the current activity and the age of the waste. Static flux chambers were used to quantify gas emission rates thrice a day (mornings, afternoons and evenings). Average emissions were 96.80 ± 144 mg CH4 m−2 min−1, 0.20 ± 0.43 mg N2O m−2 min−1 and 224.78 ± 312 mg CO2 m−2 min−1 in the Mussaka dumpsite, and 213.44 ± 419 mg CH4 m−2 min−1, 0.15 ± 0.15 mg N2O m−2 min−1 and 1103.82 ± 1194 mg CO2 m−2 min−1 at the Mbellewa dumpsite. Emissions as high as 1784 mg CH4 m−2 min−1, 2.3 mg N2O m−2 min−1 and 5448 mg CO2 m−2 min−1 were measured from both dumpsites. Huge variations observed in emissions between the different zones on the waste surface were likely a result of the heterogeneous nature of the waste, different stages in waste decomposition and different environmental conditions within the waste. Management activities that disturb waste, such as spreading and compressing potentially increase gas emissions, while covering waste with a layer of soil potentially mitigate gas emissions. Recommendations were for dumpsites to be upgraded to sanitary landfills, and biogas production from such landfills should be exploited to reduce CH4 emissions.

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values 20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

National inventories of methane (CH4) emission from manure management are based on guidelines from the Intergovernmental Panel on Climate Change using country-specific emission factors. These calculations must be simple and, consequently, the effects of management practices and environmental conditions are only crudely represented in the calculations. The intention of this review is to develop a detailed understanding necessary for developing accurate models for calculating CH4 emission from liquid manure, with particular focus on the microbiological conversion of organic matter to CH4. Themes discussed are (a) the liquid manure environment; (b) methane production processes from a modeling perspective; (c) development and adaptation of methanogenic communities; (d) mass and electron conservation; (e) steps limiting CH4 production; (f) inhibition of methanogens; (g) temperature effects on CH4 production; and (h) limits of existing estimation approaches. We conclude that a model must include calculation of microbial response to variations in manure temperature, substrate availability and age, and management system, because these variables substantially affect CH4 production. Methane production can be reduced by manipulating key variables through management procedures, and the effects may be taken into account by including a microbial component in the model. When developing new calculation procedures, it is important to include reasonably accurate algorithms of microbial adaptation. This review presents concepts for these calculations and ideas for how these may be carried out. A need for better quantification of hydrolysis kinetics is identified, and the importance of short- and long-term microbial adaptation is highlighted.

Simple Summary Livestock farms often store liquid manure until it can be used to fertilize crops. During anaerobic storage, the manure produces methane, which is a greenhouse gas. Many livestock farms add special chemical products to the manure that are said to control odours or increase fertilizer value. We wanted to know if these additives change the amount of methane produced. Two additives that are commonly used by farmers in many countries were tested in the laboratory. We mixed liquid dairy manure with different amounts of these products and measured the amount of methane produced over 30 to 90 days. Results were then compared to the same manure without any product. These tests were done at two temperatures, around 37 °C (a typical biodigester temperature), and 20 °C (a typical manure storage temperature). We also compared the chemical and physical properties of manure. We found that adding these products did not change the amount of methane produced, and it did not change the chemical and physical properties of the manure related to methane production. These findings suggest that farms using these products can be expected to have normal methane emissions from stored manure. Abstract Liquid manure is a significant source of methane (CH4), a greenhouse gas. Many livestock farms use manure additives for practical and agronomic purposes, but the effect on CH4 emissions is unknown. To address this gap, two lab studies were conducted, evaluating the CH4 produced from liquid dairy manure with Penergetic-g® (12 mg/L, 42 mg/L, and 420 mg/L) or AgrimestMix® (30.3 mL/L). In the first study, cellulose produced 378 mL CH4/g volatile solids (VS) at 38 °C and there was no significant difference with Penergetic-g® at 12 mg/L or 42 mg/L. At the same temperature, dairy manure produced 254 mL CH4/g VS and was not significantly different from 42 mg/L Penergetic-g®. In the second lab study, the dairy manure control produced 187 mL CH4/g VS at 37 °C and 164 mL CH4/g VS at 20 °C, and there was no significant difference with AgrimestMix (30.3 mL/L) or Penergetic-g® (420 mg/L) at either temperature. Comparisons of manure composition before and after incubation indicated that the additives had no effect on pH or VS, and small and inconsistent effects on other constituents. Overall, neither additive affected CH4 production in the lab. The results suggest that farms using these additives are likely to have normal CH4 emissions from stored manure.

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.

Global demand for food and energy pushes the agrifood sector to increase production which, in turn, increases pressures on ecosystems. An integrated approach is essential to cope with agro-environmental challenges and ensure sustainable agricultural productions. The current study follows the principles of industrial ecology and explores potential greenhouse gas mitigation practices by considering multiple agricultural sectors as complementary industries. The focus of the study was the production of meat, considering the dairy and beef industries as complementary sectors. They were studied as an integrated system in order to evaluate how these two meat production systems can contribute at reducing environmental impacts and make agricultural productions more sustainable. We use Canada as an example because it has two very different meat production systems: Western Canada raise beef cattle quasi-exclusively and has relatively few dairy cattle; in contrast, Eastern Canada, has a balanced production of beef and dairy cattle (about 50/50). This situation provides an ideal opportunity to achieve the objective of this study. Calculations were based on the Unified Livestock Industry and Crop Emissions Estimation System (ULICEES) calculator. Our results show synergy between integrated beef and dairy systems in Eastern Canada resulted in a 22% lower carbon footprint (CF) of meat compared to the scenario where meat was only produced by the beef industry. A scenario where western Canada would have equal size dairy and beef populations indicated that western meat CFs would be 31% lower than its current levels. This study illustrates how complementary multi-product agricultural production systems acting in synergy can increase production efficiencies compared to specialized single-product systems. It shows that such production strategy represents one of the great opportunities to reduce the environmental impacts from agricultural production systems.

Anaerobic digestion (AD) and solid-liquid separation (SLS) are manure treatment strategies used on dairy farms. These treatments change manure characteristics, such as pH, dry matter, and total ammoniacal nitrogen (TAN) which affect ammonia (NH3) emissions after field application. This study used eight wind tunnels (1 m2 each) to compare the effects of application season and dairy manure treatment (AD vs SLS) on NH3 emissions. The highest cumulative NH3 emissions were seen in the spring from the AD manure treatment, which had higher TAN and pH compared to SLS. On the other hand, when normalized by TAN application rate there was no significant difference between AD and SLS manure in either spring (52 and 54% of TAN after 22 d, respectively) or fall (26% and 27% of TAN after 15 d, respectively). This suggests that if farmers adjusted application rates based on TAN content, NH3 emissions from applied AD manure could be minimized. Results were compared to the Ammonia Loss from Field Applied Manure (ALFAM) model. The model characterized the temporal pattern of emissions reasonably well in spring, but not fall. The model generally overestimated NH3 emissions during the first 24 h after application, and underestimated emissions after incorporation from day 2 to 22.

Conventional manure storages are an important source of methane (CH4), a potent greenhouse gas. Anaerobic digestion is an alternative manure management practice potentially able to provide environmental benefits, including the reduction of CH4 emissions from slurry storage. This study was conducted at a commercial farm in Ontario where a biodigester system became operational in May 2012. The purpose was to quantify year-round CH4 emissions from a digestate storage tank, examine the relationship between emissions and its driving factors, and compare these results to a similar emissions dataset from untreated manure measured during one year before the biodigester became operational. A micrometeorological mass balance approach was used to measure CH4 fluxes. Total annual CH4 emissions from digestate were 1.0 kg m−3 y−1, which was 85% lower compared to untreated manure. Monthly average volatile solids (VS) mass in the storage tank was 73 ± 24 Mg for digestate and 107 ± 30 Mg for manure, representing a 32% VS reduction in the tank, suggesting that lower emissions were not only due to VS mass reduction after biodigestion and solid-liquid separation. The annual CH4 emissions scaled by VS were 26 g kg−1 VS y−1 for digestate and 76 g kg−1 VS y−1 for manure, suggesting that VS in the digestate were less suitable for CH4 production (less digestible). This was also verified when investigating the relationship between fluxes and its driving factors: VS concentration did not correlate with CH4 emissions per volume for digestate (r = 0.37; p = 0.29), but did for untreated manure (r = 0.95; p = 0.002). However, the correlation of temperature with emission was stronger for digestate than manure at all depths with no lag, especially at 2 m depth (r = 0.98, p

The effects of manure management practices on ammonia (NH3) emissions were evaluated using a micrometeorological technique at four contrasting dairy storage facilities: untreated raw manure slurry (RM), solid-liquid separation with storage of separated liquids (SL), anaerobic digestion of manure and off-farm materials (AD), and anaerobic digestion with solid-liquid separation and storage of the liquid fraction (ADL). Annual average NH3 emissions per surface area were lowest for RM (2.7 g m−2 d−1), followed by SL (4.5 g m−2 d−1), AD (10.0 g m−2 d−1), and ADL (15.5 g m−2 d−1). Lower NH3 emissions from the RM storage were partly due to the 30 cm thick surface crust which formed on the storage surface in summer (wood shavings was used as bedding). Greater surface crusting at the AD storage compared to the ADL storage was also likely the reason for higher emissions at the ADL storage. Relationships between NH3 emissions, temperature, and wind-speed were observed at all sites but were strongest at sites with minimal crusting (SL, ADL) and weak at the RM storage with a crust cover. Total NH3 emissions from each storage facility (kg y−1) did not simply track the differences in fluxes; rather, facilities with greater storage (RM, AD, ADL) had higher emissions than the facility with less storage (SL) due to removal of solids and more frequent field application. Overall, bedding material, manure processing, and storage management all have important effects on NH3 emissions from manure storage.

Liquid dairy manure storage is favourable for methane (CH4) production and a significant source of this greenhouse gas. Manure storage in cold climates faces large temperature variations over the course of a year, and added on-farm complexities in manure loading require year-round measurements which are currently lacking. The objectives of this study were to 1) quantify CH4 emissions from farm-scale liquid dairy manure storage in a cold climate, 2) investigate the effect of manure temperature on CH4 emissions, and 3) compare measured CH4 emissions with values derived from the USEPA temperature model. Methane fluxes were measured from Aug 2010 to early Nov 2011 on a commercial farm in Ontario, Canada, using a micrometeorological mass balance method which relied on 3 towers with air intakes at 4 heights placed around the storage tank. Manure temperature and volatile solid content (VS) were also measured. Monthly CH4 emissions scaled by VS decreased from 43.8 g CH4 kg−1 VS in Sep 2010 to 5.3 g CH4 kg−1 VS in Jan 2011, and were correlated with temperature (r2 = 0.94). Manure temperature increased starting in Feb 2011, but the increase in CH4 emissions was delayed to Jul 2011. Hence, the response of CH4 emissions to temperature showed a hysteretic pattern where emissions in the warming branch after the winter (Apr-Jun) were significantly lower than emissions in the cooling branch after the summer (Sep-Nov) despite similar temperatures. The temperature model predicted emissions during the cooling phase well, but overpredicted emissions during the warming phase, indicating other limiting factors for microbial CH4 production. Thus, the annual predicted CH4 emissions were about 2.3× larger than the measured values. The newly observed hysteresis effect should be considered when predicting CH4 emissions from stored manure.

Stored liquid dairy manure is a hotspot for methane (CH) emission, thus effective mitigation strategies are required. We assessed sodium persulfate (NaSO), potassium permanganate (KMnO), and sodium hypochlorite (NaOCl) for impacts on the abundance of microbial communities and CH production in liquid dairy manure. Liquid dairy manure treated with different rates (1, 3, 6, and 9 g or mL L slurry) of these chemicals or their combinations were incubated under anoxic conditions at 22.5 ± 1.3°C for 120 d. Untreated and sodium 2-bromoethanesulfonate (BES)-treated manures were included as negative and positive controls, respectively, whereas sulfuric acid (HSO)-treated manure was used as a reference. Quantitative real-time polymerase chain reaction was used to quantify the abundances of bacteria and methanogens on Days 0, 60, and 120. Headspace CH/CO ratios were used as a proxy to determine CH production. Unlike bacterial abundance, methanogen abundance and CH/CO ratios varied with treatments. Addition of 1 to 9 g L slurry of NaSO and KMnO reduced methanogen abundance (up to ∼28%) and peak CH/CO ratios (up to 92-fold). Except at the lowest rate, chemical combinations also reduced the abundance of methanogens (up to ∼17%) and CH/CO ratios (up to ninefold), although no impacts were observed when 3% NaOCl was used alone. With slurry acidification, the ratios reduced up to twofold, whereas methanogen abundance was unaffected. Results suggest that NaSO and KMnO may offer alternative options to reduce CH emission from stored liquid dairy manure, but this warrants further assessment at larger scales for environmental impacts and characteristics of the treated manure.

Accurately accounting for water budgets within regional agroecosystems is becoming an increasingly important practice, as both climate change and water consumption pressures have the potential for influencing agro-productivity and other water use activities. In this study, water budget measurements from 10 rainfed experimental sites across Canada were utilized to evaluate the performance of three models for their water partitioning capabilities: denitrification–decomposition (DNDC), Holos, and versatile soil moisture budget (VSMB). To assess the likely model performance at an upscaled national level, the models were applied at the site level with no water component-specific calibration. Evapotranspiration (ET) was found to be the dominate component of the water budget at the prairie sites (89%–149% of precipitation) (i.e., in comparison to runoff, tile drainage, and deep percolation), while both ET (37%–73% of precipitation) and drainage (19%–61% of precipitation) represented most of the water outflow bud...

A numerical model was used to predict effects of different liquid manure storage designs and management practices on manure temperature (Tm). Manure storage designs included various tank diameters, proportion of the storage above-ground, addition of a roof, and floating covers (synthetic or straw). Manure management practices included the frequency of manure removal, manure agitation, and the depth of manure remaining after removal. Results showed that smaller diameter tanks with a greater depth had lower peak Tm. There was no appreciable effect on Tm from constructing a storage tank above-ground vs in-ground. Adding a roof decreased peak Tm for spring manure removal, but not autumn removal. Floating synthetic covers with high solar absorptivity (i.e. dark colour) greatly increased peak Tm, whereas straw covers had the opposite effect—decreasing peak Tm. Removing manure twice per year (spring and autumn) or once annually in spring led to shallower manure depth in summer and greater peak Tm; in contrast, once annual autumn removal had greater depth and lower peak Tm in summer. Manure agitation during the warm season increased peak Tm substantially for autumn manure removal, and slightly for spring removal. Leaving less manure in storage after spring removal led to a more rapid increase in Tm and a higher peak Tm in summer. Overall, the study highlights that manure storage design and management practices can greatly affect Tm, with peak Tm being increased or decreased up to 8°C in some scenarios. These findings emphasize that Tm is dynamic and that air temperature is an overly simplistic surrogate for Tm. Thus, it is important that studies examining greenhouse gas emissions from liquid manure also measure manure temperature. Insights from the study may guide future research linking liquid manure storage design and management to Tm and related effects on greenhouse gases such as methane.

Agro-ecosystem models, such as the DNDC (DeNitrification and DeComposition) model are useful tools when assessing the sustainability of agricultural management. Accuracy in soil temperature estimations is important as it regulates many important soil biogeochemical processes that lead to greenhouse gas emissions (GHG). The objective of this study was to account for the effects of snow cover in terms of the measured snow depth (mm of water), soil texture and crop management in temperate latitudes in order to improve the surface soil temperature mechanism in DNDC and thereby improve GHG predictions. The estimation of soil temperature driven by the thermal conductivity and heat capacity of the soil was improved by considering the soil texture under frozen and unfrozen conditions along with the effects of crop canopy and snow depth. Calibration of the developed model mechanisms was conducted using data from Alfred, ON under two contrasting soil textures (sandy loam vs. clay). Independent validation assessments were conducted using soil temperatures at different depths for contrasting managements for two field sites located in Canada (Guelph, ON and Glenlea, MB). The validation results indicated high model accuracy (R 2 > 0.90, EF ≥ 0.90, RMSE 2 O emissions during spring thaw and provide a foundation for future studies aimed at improving simulations in DNDC for better representations of other biogeochemical processes.

Limited information is available in the literature on greenhouse gas (GHG) quantification from livestock production systems in Africa. Therefore, this project was carried out to generate baseline emission factors of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) from broiler and layer barns with building design typical of Cameroon. Emissions were measured from two broiler barns during the entire production cycles and a layer barn for a limited period using flux chambers. Methane emission factors from the broiler barns with mud and cement floors were 0.96 ± 1.04 and 0.36 ± 0.17 mg bird−1 hr−1 respectively, and 0.76 ± 0.56 mg bird−1 hr−1 from the layer barn with cement floor. Nitrous oxide emission from the broiler barns with mud and cement floors were 12.94 ± 10.11 and 1.68 ± 1.02 mg bird−1 hr−1 respectively, and 0.21 ± 0.28 mg bird−1 hr−1 from the layer barn. Carbon dioxide emission factors from the broiler barns with mud and cement floors were 9327 ± 3508 and 25526 ± 6904 mg bird−1 hr−1 respectively, and 8942 ± 36756 mg bird−1 hr−1 from the layer barn. When scaled per livestock unit (LU), where 1 LU is 500 kg bird weight, CH4 emissions were 0.16 ± 0.17 and 0.06 ± 0.03 g LU−1 hr−1 from the broiler barns, and 0.19 ± 0.14 g LU−1 hr−1 from the layer barn. Nitrous oxide emissions were 2.16 ± 1.69 and 0.28 ± 0.17 g LU−1 hr−1 from the broiler barns, and 0.05 ± 0.07 g LU−1 hr−1 from the layer barn. Broilers reared in management systems with wood shavings on mud floor had relatively high CH4 and N2O emissions compared to broilers on wood shavings and cement floor, with the contrary observed for CO2. The emissions N2O were significantly higher from broiler barns compared to layer barns. Emissions were higher in the mornings compared to later periods of the day. Given the observed results, GHG emission mitigation strategies need to be customised for each building design and management system.

Tillage and crop residue management can have large impacts on soil organic carbon (SOC) sequestration, as well as additional feedbacks on crop productivity and agricultural sustainability. The objectives of this study were to (i) evaluate the effects of summer fallow, legume green manure, pea or canola in rotation with spring wheat on crop yields, biomass production and SOC dynamics (0–15 cm) from six long-term cropping systems under semiarid conditions in western Canada, (ii) calibrate and validate three process-based models (DNDC, DayCent and DSSAT) using experimental data, and (iii) investigate the long-term impacts of tillage (no-tillage (NT) vs. conventional tillage (CT)) and straw residue (returned vs. removal) on SOC changes from diverse rotation systems. Over the experimental period from 1987 to 2015, the average wheat yields in Wheat (W)-Canola (C)–W-Pea (P) and legume green manure (LGM)-W-W rotations increased by 33.5 and 10.8%, respectively, compared to the continuous wheat (ContW) cropping systems. Higher SOC sequestration rates were found under ContW, LGM-W-W and W–C–W–P cropping systems mainly due to higher residue C input and larger nitrogen (N) inputs/fixation when compared to fallow-wheat systems. All three models performed “fair” to “good” in simulating crop yield, biomass and SOC content over time across all treatments. DSSAT had the lowest errors of prediction for yields (e.g., normalized RMSE (nRMSE) ≤ 27.2%, index of agreement (d) ≥ 0.79), while DNDC had better estimates of SOC content (e.g., nRMSE ≤ 4.5%, d ≥ 0.74). Long-term scenario analysis demonstrated that the mean annual changes in SOC across rotations based on model ensemble ranged from 0.03 Mg C ha−1 y−1 under CT with straw removal to 0.31 Mg C ha−1 y−1 under NT with straw returned. Predicted SOC sequestration potential of NT was relatively small compared to crop straw return for all rotation systems. This study suggests that diverse crop rotations which include canola and legume crops have the potential to store more SOC than traditional wheat-based cropping (e.g., fallow-wheat, ContW) for the semiarid prairies of Canada. These diverse rotations are already becoming more common and can help to enhance crop yields and maximize SOC sequestration when they are coupled with NT and residue management.

Water use (i.e., pumped water) was measured over a full year on a small dairy farm consisting of ~34 lactating and ~39 nonlactating animals (calves, heifers, and dry cows). Crop production was rain fed and was not included in the analysis. Animals were housed in a tie-stall barn during the winter and cool season (mid-October to mid-May) and outdoors in a yard or pasture during the warm season. Annual average water use was 5,180 L/d, with 82% being drinking water and 18% for milking system cleaning. Distinct diurnal patterns of drinking water intake were observed for each animal group, which differed when cows were located indoors or outdoors. Seasonal changes in water intake were significant. Nonlactating animals accounted for 27% of whole-farm water intake in the summer (July–September). In the warm season, herd-scale milk production declined while water consumption increased. As a result, the whole-farm water used per liter of milk had a strong positive correlation with monthly average temperature humidity index (THI) and could have been additionally influenced by other factors such as herd composition, precipitation, feed intake, forage quality and availability, and day length. When THI was below 50, water use ranged from 4.3 to 4.8 L/kg of milk, and it increased to a maximum of 6.7 L/kg at a THI of 68. The annual average water use was 5.35 L/kg of milk. This study demonstrates that the water used per kilogram of milk produced was affected not only by changes in water use but also by changes in herd-scale milk production.

Recent developments in composting technology enable dairy farms to produce their own bedding from composted manure. This management practice alters the fate of carbon and nitrogen; however, there is little data available documenting how gaseous emissions are impacted. This study measured in-situ emissions of methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O), and ammonia (NH3) from an on-farm solid-liquid separation system followed by continuously-turned plug-flow composting over three seasons. Emissions were measured separately from the continuously-turned compost phase, and the compost-storage phase prior to the compost being used for cattle bedding. Active composting had low emissions of N2O and CH4 with most carbon being emitted as CO2-C and most N emitted as NH3-N. Compost storage had higher CH4 and N2O emissions than the active phase, while NH3 was emitted at a lower rate, and CO2 was similar. Overall, combining both the active composting and storage phases, the mean total emissions were 3.9×10-2gCH4kg-1 raw manure (RM), 11.3gCO2kg-1 RM, 2.5×10-4g N2O kg-1 RM, and 0.13g NH3 kg-1 RM. Emissions with solid-separation and composting were compared to calculated emissions for a traditional (unseparated) liquid manure storage tank. The total greenhouse gas emissions (CH4+N2O) from solid separation, composting, compost storage, and separated liquid storage were reduced substantially on a CO2-equivalent basis compared to traditional liquid storage. Solid-liquid separation and well-managed composting could mitigate overall greenhouse gas emissions; however, an environmental trade off was that NH3 was emitted at higher rates from the continuously turned composter than reported values for traditional storage.

A numerical model was developed to determine the year-round temperature distribution within liquid manure storages, which is relevant for modelling temperature-dependent greenhouse gas and ammonia emissions. The model considers net short and long-wave radiation, heat conduction through walls and floor, surface convective heat transfer, evaporative heat loss, and manure loading. The model was implemented and validated for a circular concrete storage tank (40 m diameter; 2.5 m depth) on a dairy farm in Ontario, Canada, where it is assumed that heat transfer occurs in horizontal and vertical directions, and is symmetric in the angular direction. Annual root mean square error (RMSE), Nash–Sutcliffe model efficiency, coefficient of determination, and average bias between model estimates and measured values were 2.4 °C, 0.91, 0.95, and 0.12 °C, respectively. The model performed best in summer and autumn (lowest RMSE), which are the most important seasons for modelling temperature, as both temperature and manure volume are highest, leading to the greatest opportunity for gaseous emissions. A sensitivity analysis indicated that the most significant parameters were solar absorptivity, manure depth, incoming manure temperature, emissivity, and wind-speed. For every unit increase in depth (m), incoming manure temperature (°C), or wind-speed (m s −1 ), the peak summer temperature changed by −7.3, 0.3, or −2.4 °C, respectively. Parameters with little effect on temperature were the manure solids content and thermal conductivity of soil around the sides and the bottom of the tank. Results show that heat transfer is primarily 1-dimensional, and a simplified 1-D model would be sufficient for future applications.

A water footprint considers both the water volumes involved in production processes and the resulting waste water generated. The grey water (GW) footprint represents the volume of fresh water required to assimilate pollutants to acceptable concentrations—a concept proposed by the water footprint network—but it faces several difficulties when applied to agricultural production systems. Crop production cannot be fully controlled and it is weather-dependent, which greatly affects the year-to-year GW calculations. In this study, we examined the effect of time step on the calculation of annual GW footprints by utilizing 30 years of daily average nitrate-nitrogen (NO 3 -N) concentrations in drainage water (both leachate and runoff water derived from a process-based model) from corn and soybean production systems. For each crop year, the volume of water required to assimilate NO 3 -N to an acceptable threshold concentration (i.e. −1 ) was calculated over different time steps (daily, weekly, monthly, seasonally and yearly), and each case was summed to an annual GW value. Daily average NO 3 -N concentrations in the effluent water were generally below the acceptable threshold concentrations, with intermittent exceedances. Thus, the fields often provided their own ‘dilution’ water, and annual average concentrations were only 2.0 mg L −1 and 0.4 mg L −1 for corn and soybean, respectively. The GW footprint varied significantly when calculated for different time steps. The greatest annual footprint occurred when calculated daily (shortest time step). The GW footprint for corn ranged from 2.7 × 10 3 m 3 ha −1 , or 2700 mm of water, when estimated daily to zero for the yearly time step. For soybean it ranged from 0.5 × 10 3 m 3 ha −1 , or 500 mm of water, to zero. The GW footprint results are therefore highly dependent on the time step of calculation. The effect of this issue extends beyond crop production as it is exported and amplified through feed rations to affect the GW footprint from animal production. To be able to reconcile these problems, the GW calculation pathways should be reconsidered and standardized.

Assessment of the impact of climate change on agricultural sustainability requires a robust full system estimation of the interdependent soil-plant-atmospheric processes coupled with dynamic farm management. The simplification or exclusion of major feedback mechanisms in modelling approaches can significantly affect model outcomes. Using a biogeochemical model, DNDCv.CAN, at three case-study locations in Canada, we quantified the impact of using commonly employed simplified modelling approaches on model estimates of crop yields, soil organic carbon (SOC) change and nitrogen (N) losses across 4 time periods (1981-2010, 2011-2040, 2041-2070, and 2071-2100). These approaches included using climate with only temperature and precipitation data, annual re-initialization of soil status, fixed fertilizer application rates, and fixed planting dates. These simplified approaches were compared to a more comprehensive reference approach that used detailed climate drivers, dynamic planting dates, dynamic fertilizer rates, and had a continuous estimation of SOC, N and water budgets. Alternative cultivars and rotational impacts were also investigated. At the semi-arid location, the fixed fertilizer, fixed planting date, and soil re-initialization approaches reduced spring wheat (Triticum aestivum L.) yield estimates by 40%, 25%, and 29%, respectively, in the 2071-2100 period relative to the comprehensive reference approach. At both sub-humid locations, the re-initialization of soil status significantly altered SOC levels, N leaching and N runoff in all three time periods from 2011 to 2100. At all locations, SOC levels were impacted when using simplified approaches relative to the reference approach, except for the fixed fertilizer approach at the sub-humid locations. Results indicate that simplified approaches often lack the necessary characterization of the feedbacks between climate, soil, crop and management that are critical for accurately assessing crop system behavior under future climate. We recommend that modellers improve their capabilities of simulating expected changes in agronomy over time and employ tools that consider robust soil-plant-atmospheric processes.

Effective management of dairy manure is important to minimize N losses from cropping systems, maximize profitability, and enhance environmental sustainability. The objectives of this study were (i) to calibrate and validate the DeNitrification-DeComposition (DNDC) model using measurements of silage corn ( L.) biomass, N uptake, soil temperature, tile drain flow, NO leaching, NO emissions, and soil mineral N in eastern Canada, and (ii) to investigate the long-term impacts of manure management under climate variability. The treatments investigated included a zero-fertilizer control, inorganic fertilizer, and dairy manure amendments (raw and digested). The DNDC model overall demonstrated statistically "good" performance when simulating silage corn yield and N uptake based on normalized RMSE (nRMSE)10%, index of agreement ()0.9, and Nash-Sutcliffe efficiency (NSE)0.5. In addition, DNDC, with its inclusion of a tile drainage mechanism, demonstrated "good" predictions for cumulative drainage (nRMSE20%,0.8, and NSE0.5). The model did, however, underestimate daily drainage flux during spring thaw for both organic and inorganic amendments. This was attributed to an underestimation of soil temperature and soil water under frequent soil freezing and thawing during the 2013-2014 overwinter period. Long-term simulations under climate variability indicated that spring applied manure resulted in less NO leaching and NO emissions than fall application when manure rates were managed based on crop N requirements. Overall, this study helped highlight the challenges in discerning the short-term climate interactions on fertilizer-induced N losses compared with the long-term dynamics under climate variability.

Cattle production is an important source of greenhouse gas (GHG) emissions which affects the environment. While emissions have mostly been quantified from barns and manure storage facilities, little information is available on emissions from outdoor sleeping areas, especially in Africa. This project was carried out in two beef cattle farms (Banshe and Menteh) in Cameroon, with the aim of quantifying GHG emissions from the outdoor sleeping areas. The sleeping areas were fenced with planks and the floor was bare soil covered mainly with cattle manure. Gas emission rates were measured when the cattle were on pasture using 2 non-steady state flux chambers during the wet season for 1 week in each farm. Manure dry matter, determined using method 1648 of the U.S. Environmental Protection Agency, was in the range of 28–38% while the volatile solid content was in the range of 41–57%. Emission hotspots and hot moments were observed with large variations in time and location. The methane (CH4) emissions were 4.04 ± 4.3 and 1.85 ± 1.7 mg m−2 min−1 in Banshe and Menteh, respectively. The nitrous oxide (N2O) emissions were 0.008 ± 0.02 and 0.049 ± 0.06 mg m−2 min−1 in Banshe and Menteh, respectively. The sleeping area with high CH4 emissions was associated with low N2O emissions and vice versa. The carbon dioxide (CO2) to CH4 emission ratios were high; ∼7 for Banshe and ∼15 for Menteh, indicating more aerobic conditions. The total GHG (CH4 + N2O) emission rates were 139.7 and 77.5 mg CO2e m−2 min−1 in Banshe and Menteh, respectively. This indicated that CH4 contributed 98 and 81% of the total GHG in Banshe and Menteh, respectively. This shows that mitigation strategies should be geared more towards CH4 in the sleeping areas in this study during the wet season. The GHG emission factors estimated in this research were the first of its kind in Cameroon, and can be used as a basis for planning management practices that mitigate emissions. Keywords: Beef cattle, Cattle manure, Corral, Livestock, Solid manure, Volatile solids