Fugitive methane emissions from two agricultural biogas plants.

This study quantified fugitive methane (CH4) losses from multiple sources (open digestate storages, digesters and flare) at two biogas facilities over one year, providing a much needed dataset integrating all major loss pathways and changes over time. Losses of CH4 from Facility A were primarily from digestate storage (5.8% of biogas CH4), followed by leakage/venting (5.5%) and flaring (0.2%). At Facility B, losses from digestate storage were higher (10.7%) due to shorter hydraulic retention time and lack of a screwpress. Fugitive emissions from leakage were initially 3.8% but were reduced to 0.6% after the dome membrane was repaired at Facility B. For biogas to have a positive impact on greenhouse gas emissions and provide a low-carbon fuel, it is important to minimize fugitive losses from digestate storage and avoid leakage during abnormal operation (leakage, roof failure).

A gap in nitrous oxide emission reporting complicates long-term climate mitigation.

Nitrous oxide (N2O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N2O emissions. Most national GHG reporting to the United Nations Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N2O pulses in the northcentral region of the United States during early spring and this increases annual N2O emissions from croplands and grasslands reported in the national GHG inventory by 6 to 16%. Considering this, emission accounting in cold climate regions is very likely underestimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N2O increases once CO2 and CH4 are phased out. Hence, the N2O emission underestimate introduces additional risks into meeting long-term climate goals.

Long-term variability in N2O emissions and emission factors for corn and soybeans induced by weather and management at a cold climate site.

Nitrous oxide (N2O) emissions are highly variable in space and time due to the complex interplay between soil, management practices and weather conditions. Micrometeorological techniques integrate emissions over large areas at high temporal resolution. This allows identification of causes of intra- and inter-annual variability of N2O emissions and development of robust emission factors (EF). Here, we investigated factors responsible for variability in N2O emissions during growing and non-growing seasons of corn and soybeans grown in an imperfectly drained silt loam soil, in Ontario, Canada. We used quasi-continuously (at half-hourly to hourly intervals) N2O fluxes measured via the flux-gradient technique over 11 years for corn and 5 years for soybeans and evaluated the uncertainty of default IPCC and Canada-specific EFs. In the growing season, emissions were controlled by soil nitrate content, soil moisture and temperature in the fertilized corn, while moisture and temperature regulated N2O emissions in the unfertilized soybeans. In the non-growing season, nitrogen (N) input from the crop residue did not affect the emissions, pointing to freeze-thaw cycles as mechanisms for enhanced N2O emissions. The non-growing season contribution to annual emissions was 38% in corn and 43% in soybeans. On average, annual emissions were 2.6-fold higher in corn than soybeans. Observed mean N2O EFs were 0.84% (0.12-2.02%) for growing season and 1.69% (0.29-7.32%) for yearly emissions. The growing season EF derived from long-term N2O emissions was 0.9 ± 0.14%. The interannual variability in N2O emissions and EFs can be attributed to management practices and annual weather variability. The default IPCC approach based on overall N input had poorer performance in predicting annual N2O emissions compared to the current Canadian methodology, which includes management and environmental factor in addition to N inputs. The observed emissions were further evaluated with a newly developed growing season N2O emission prediction approach for Canada. However, performance of the approach was poorer than IPCC or the current national Canadian approach. Additional tests of the new national methodology are recommended as well as consideration of non-growing season emissions.

Economic and environmental nitrate leaching consequences of 4R nitrogen management practices including use of inhibitors for corn production in Ontario.

Nitrate (NO3-) leaching has negative human and environmental health consequences that can be attributed to and mitigated by agricultural decision making. The purpose of this study is to examine the economic and environmental nitrogen (N) leaching reduction from 4R (Right Rate, Right Source, Right Time, Right Placement) agricultural management practices, including application methods, timing and rates, and the use of nitrification and urease inhibitors, for Ontario corn production. This study employed an integrated biophysical and economic GIS-based simulation model considering corn yields, prices, and production costs, and environmental losses, under historical weather scenarios, with NO3- leaching constraints. Reducing N application from historical to model optimized agronomic rates sharply lowered corn NO3- leaching from 75.3 to 24.9 kt N per year. Increasing model restrictions on corn NO3- leaching increased the use of broadcast and sidedress application methods compared to injection and lower overall production. They also increased the use of nitrification and urease inhibitors, which increased N use efficiency, because they allowed lower leaching from corn production, for a price. Leaching decreases from restrictions trade-off with ammonia (NH3) volatilization increases, but there was no trade-off with nitrous oxide (N2O) emissions. This highlighted the importance of considering net N losses and production trade-offs by policy decision-makers when developing N loss reduction strategies.

Identifying hotspots and representative monitoring locations of field scale N2O emissions from agricultural soils: A time stability analysis.

Greenhouse gas sampling from agricultural fields is laborious and time-consuming. Soil and topographical heterogeneity cause spatiotemporal variations, making nitrous oxide (N2O) estimation and management a challenge. Identification of representative monitoring locations, hotspots, and coldspots could facilitate the mitigation of agricultural N2O emissions. The objective of this study was to identify and characterize representative monitoring locations, hotspots, and coldspots of N2O emissions in agricultural fields (Baggs farm; BF and Research North farm; RN) in Cambridge, Ontario, Canada, under humid continental climate. Soil in both fields was classified as Orthic Melanic Brunisol, with some areas categorized as Gleyed Brunisolic Gray Brown Luvisol and Orthic Humic Gleysol. In total, 28 sampling points were selected following conditional Latin hypercube design using topographical parameters (digital elevation, slope, topographical wetness index, and Pennock landform classification). Gas samples were collected over a two-year crop rotation with corn (2019) and soybean (2020). Additional sampling was conducted at BF at spring thaw (2020). Time stability analysis using mean relative difference (MRD) and standard deviation of mean relative difference (SDRD) was performed to test the hypothesis that "simultaneous analysis of spatiotemporal variations in N2O emissions could help to identify and characterize representative monitoring locations, hotspots, coldspots and areas with few hot and cold moments. Most of the hotspots were located at shoulder positions, coldspots, and cold moments at backslope, and representative monitoring points were located at leveled positions or localized depressions. Time stability analysis coupled with multivariate groping analysis supported our hypothesis and helped successfully identify hotspots, coldspots, and representative locations based on landform classification with few exceptions. However, inclusion of additional topographical (curvature, contributing area, aspect) and morphological parameters (texture, thickness of soil horizon, depth to bedrock, and water table) are suggested for consideration in future research to manage variable-rate fertilizer application and mitigate N2O hotspots at landscape level.

Contribution of crop residue, soil, and fertilizer nitrogen to nitrous oxide emissions varies with long-term crop rotation and tillage.

Agriculture is an important contributor to N2O emissions - a potent greenhouse gas - with high peaks occurring when soil mineral nitrogen (N) is high (e.g., after mineralization of organic N and N fertilizer application). Nitrogen dynamics in soil and consequently N2O emissions are affected by crop and soil management practices (e.g., crop rotation and tillage), an effect mostly assessed in the literature through comparisons of total N2O emission. Hence, information is scarce on the effect of these management practices on specific N sources affecting N2O emissions (i.e., N fertilizer, soil, above and belowground crop residues) - a knowledge gap explored in this study with the use of 15N tracers. The isotope approach enabled refinement on global N2O budget by directly determining the emission factors (EF) of above and belowground crop residues that vary in chemical composition and comparison with default EF values (e.g., IPCC EFs). Our experiment was conducted over the full-cycle of long-term crop rotations to (i) compare N2O totals and intensity, under no-tillage and conventional tillage, simple and diverse rotation; (ii) partition total N2O emissions into soil, N fertilizer, above and belowground crop residue N sources; (iii) compare the 12-month EF of crop residue against the default values proposed by IPCC (2019). For the tillage effect, annual N2O emissions were from 1.2- to 2.0-times higher on CT than NT soil due to 40% increased soil N derived N2O emission in CT. The diversified crop rotation emitted 1.3-times higher N2O than the simple rotation over the full-cycle of the rotations, but the effect was due to differences in N fertilizer rate between the rotations since emissions were equivalent when scaled by N rate. Finally, our results suggested that default IPCC EF are overestimated for crop residues under CT and NT, simple and diverse rotations as measured EFs never surpassed 0.1%.

In-Situ Estimation of Soil Water Retention Curve in Silt Loam and Loamy Sand Soils at Different Soil Depths.

The soil water retention curve (SWRC) shows the relationship between soil water (θ) and water potential (ψ) and provides fundamental information for quantifying and modeling soil water entry, storage, flow, and groundwater recharge processes. While traditionally it is measured in a laboratory through cumbersome and time-intensive methods, soil sensors measuring in-situ θ and ψ show strong potential to estimate in-situ SWRC. The objective of this study was to estimate in-situ SWRC at different depths under two different soil types by integrating measured θ and ψ using two commercial sensors: time-domain reflectometer (TDR) and dielectric field water potential (e.g., MPS-6) principles. Parametric models were used to quantify θ-ψ relationships at various depths and were compared to laboratory-measured SWRC. The results of the study show that combining TDR and MPS-6 sensors can be used to estimate plant-available water and SWRC, with a mean difference of -0.03 to 0.23 m3m-3 between the modeled data and laboratory data, which could be caused by the sensors' lack of site-specific calibration or possible air entrapment of field soil. However, consistent trends (with magnitude differences) indicated the potential to use these sensors in estimating in-situ and dynamic SWRC at depths and provided a way forward in overcoming resource-intensive laboratory measurements.

Dairy manure acidification reduces CH4 emissions over short and long-term.

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.

Increased dairy farm methane concentrations linked to anaerobic digester in a five-year study.

Organic waste materials are sources of anthropogenic methane (CH4 ) emissions. Anaerobic digestion (AD) is a technology that produces biogas from organic waste materials, and CH4 is the primary component of biogas. Unintended emission of CH4 from biogas facilities could undercut the environmental benefits of this technology. The objective of this study was to determine if the implementation of an AD system affected ambient CH4 concentrations ([CH4 ]) on a commercial dairy farm over 5 yr, from before installation into full operation. Concentrations at 4.5-m height on a tower receiving wind that originated from various directions, comprising components of the dairy farm such as the AD facility, crop fields, or main barn, were measured using a closed-path tunable diode laser trace-gas analyzer. In 2012 and 2013, the first 2 yr of AD operation, [CH4 ] was not significantly different than pre-AD levels in 2011 (2.04 ± 0.01 µl L-1 ). However, mean [CH4 ] increased to 2.47 ± 0.03 and 2.48 ± 0.04 µl L-1 in 2014 and 2015, respectively, and the occurrence of high [CH4 ] (>10 µl L-1 ) increased from <0.05% in Year 1 (pre-AD) to 12% in Years 4 and 5. These elevated concentrations were related to an increased use of food waste feedstocks over time and suggest that the biogas system was a source of fugitive CH4 emissions. Food waste materials have a high biogas potential and are a valuable resource that require appropriate facility design and management to fully harness their benefits.

Does overwintering change the inoculum effect on methane emissions from stored liquid manure?

Greenhouse gas (GHG) emissions, especially methane (CH4 ), from manure storage facilities can be substantial. Methane production requires adapted microbial communities ("inoculum") to be present in the manure. Complete removal of liquid dairy manure (thus removing all inoculum) from storage tanks in the spring has been shown to significantly reduce CH4 emissions over the following warm season. This study examined whether the same mitigation effect would occur after fall removal of liquid dairy manure. Emissions of CH4 , nitrous oxide (N2 O), ammonia (NH3 ), and CO2 were measured from six 11.88-m3 tanks equipped with flow-through chambers. There were three inoculated controls (20% inoculum) and three uninoculated treatments, where inoculum was completely removed in the fall/winter (0% inoculum). Direct N2 O and NH3 (indirect N2 O) were minor contributors to the total GHG budget, contributing <2% on a CO2 equivalent (CO2 e) basis. Removal of inoculum led to a 34% decrease in total emissions on a CO2 e basis and to a 29% decrease in the CH4 conversion factor compared with the inoculated control (0.37 vs. 0.52; p = .01). Overall, removing inoculum in the fall reduced CH4 emissions from manure storage tanks; however, fall inoculum removal was less effective than in a previous study where inoculum was removed in the spring. The timing of inoculum removal may affect the efficiency of this CH4 mitigation strategy. However, this method may be impractical for larger manure storage tanks. Further study is required to overcome challenges of time-sensitive, complete inoculum removal from farm-scale storage tanks.

Global Research Alliance N2 O chamber methodology guidelines: Guidelines for gap-filling missing measurements.

Nitrous oxide (N2 O) is a potent greenhouse gas that is primarily emitted from agriculture. Sampling limitations have generally resulted in discontinuous N2 O observations over the course of any given year. The status quo for interpolating between sampling points has been to use a simple linear interpolation. This can be problematic with N2 O emissions, since they are highly variable and sampling bias around these peak emission periods can have dramatic impacts on cumulative emissions. Here, we outline five gap-filling practices: linear interpolation, generalized additive models (GAMs), autoregressive integrated moving average (ARIMA), random forest (RF), and neural networks (NNs) that have been used for gap-filling soil N2 O emissions. To facilitate the use of improved gap-filling methods, we describe the five methods and then provide strengths and challenges or weaknesses of each method so that model selection can be improved. We then outline a protocol that details data organization and selection, splitting of data into training and testing datasets, building and testing models, and reporting results. Use of advanced gap-filling methods within a standardized protocol is likely to increase transparency, improve emission estimates, reduce uncertainty, and increase capacity to quantify the impact of mitigation practices.

Towards an improved methodology for modelling climate change impacts on cropping systems in cool climates.

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.

Modifying fertilizer rate and application method reduces environmental nitrogen losses and increases corn yield in Ontario.

Nitrogen (N) use in corn production is an important driver of nitrous oxide (N2O) emissions and 4R (Right source, Right rate, Right time and Right place) fertilizer practices have been proposed to mitigate emissions. However, combined 4R practices have not been assessed for their potential to reduce N2O emissions at the provincial-scale while also considering trade-offs with other N losses such as leaching or ammonia (NH3) volatilization. The objectives of this study were to develop, validate, and apply a Denitrification-Decomposition model framework at 270 distinct soil-climate regions in Ontario to simulate corn yield and N2O emissions across eleven fertilizer management scenarios during 1986-2015. The results show that broadcasting fertilizer at the surface without incorporation had the highest environmental N loss which was primarily caused by NH3 volatilization. When injected at planting or at sidedress, the NH3 loss was reduced considerably. However, because more N was left in the soil, injection and sidedressing induced more losses by nitrate leaching and N2O emissions. Reduction of N rate as proposed by the DNDC model did not affect crop yield but decreased leaching and N2O emissions. Addition of inhibitors promoted a further reduction in N2O emission (11-16%) although lesser than the reduction in N rate. Overall, our results emphasize that N rate adjustment following improvements in placement, use of inhibitors, and application timings can mitigate N2O emissions by 42-57% and result in 3-4% greater yields compared to baseline scenario in Ontario corn production.

Greenhouse Gas Mitigation through Dairy Manure Acidification.

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.

A 1-year greenhouse gas budget of a peatland exposed to long-term nutrient infiltration and altered hydrology: high carbon uptake and methane emission.

Long-term increased nutrient influx into normally nutrient-limited peatlands in combination with altered hydrological conditions may threaten a peatland's carbon storage function and affect its greenhouse gas (GHG) budget. However, in situ studies on the effects of long-term altered conditions on peatland functioning and GHG budgets are scarce. We thus quantified GHG fluxes in a peatland exposed to enhanced water level fluctuations and long-term nutrient infiltration in Ontario, Canada, via eddy-covariance and flux chamber measurements. The peatland was a prominent sink of - 680 ± 202 g carbon dioxide (CO2) and a source of 22 ± 8 g methane (CH4) m-2 year-1, resulting in a negative radiative forcing of - 80 g CO2 eq. m-2 y-1. During the growing season CH4 fluxes were constantly high (0.1 g m-2 s-1). Further, on three dates, we measured nitrous oxide (N2O) fluxes and observed a small flux of 2.2 mg m-2 day-1 occurring during the thawing period. Taking the studied ecosystem as a model system for other peatlands exposed to long-term increased nutrient infiltration and enhanced water level fluctuations, our data suggest that such peatlands can maintain their carbon storage function and CO2 sequestration may outweigh emissions of CH4.

Reduction in Methane Emissions From Acidified Dairy Slurry Is Related to Inhibition of Methanosarcina Species.

Liquid dairy manure treated with sulfuric acid was stored in duplicate pilot-scale storage tanks for 120 days with continuous monitoring of CH4 emissions and concurrent examination of changes in the structure of bacterial and methanogenic communities. Methane emissions were monitored at the site using laser-based Trace Gas Analyzer whereas quantitative real-time polymerase chain reaction and massively parallel sequencing were employed to study bacterial and methanogenic communities using 16S rRNA and methyl-coenzyme M Reductase A (mcrA) genes/transcripts, respectively. When compared with untreated slurries, acidification resulted in 69-84% reductions of cumulative CH4 emissions. The abundance, activity, and proportion of bacterial communities did not vary with manure acidification. However, the abundance and activity of methanogens (as estimated from mcrA gene and transcript copies, respectively) in acidified slurries were reduced by 6 and 20%, respectively. Up to 21% reduction in mcrA transcript/gene ratios were also detected in acidified slurries. Regardless of treatment, Methanocorpusculum predominated archaeal 16S rRNA and mcrA gene and transcript libraries. The proportion of Methanosarcina, which is the most metabolically-diverse methanogen, was the significant discriminant feature between acidified and untreated slurries. In acidified slurries, the relative proportions of Methanosarcina were ≤ 10%, whereas in untreated slurries, it represented up to 24 and 53% of the mcrA gene and transcript libraries, respectively. The low proportions of Methanosarcina in acidified slurries coincided with the reductions in CH4 emissions. The results suggest that reduction of CH4 missions achieved by acidification was due to an inhibition of the growth and activity of Methanosarcina species.

Long-term Trends in Corn Yields and Soil Carbon under Diversified Crop Rotations.

Agricultural practices such as including perennial alfalfa ( L.), winter wheat ( L.), or red clover ( L.) in corn ( L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process-based biogeochemical models such as DeNitrification-DeComposition (DNDC) capture the beneficial effects of diversified cropping systems is unclear. To calibrate and validate DNDC for simulation of observed trends in corn yield and SOC, we used long-term trials: continuous corn (CC) and corn-oats ( L.)-alfalfa-alfalfa (COAA) for Woodslee, ON, 1959 to 2015; and CC, corn-corn-soybean [ (L.) Merr.]-soybean (CCSS), corn-corn-soybean-winter wheat (CCSW), corn-corn-soybean-winter wheat + red clover (CCSW+Rc), and corn-corn-alfalfa-alfalfa (CCAA) for Elora, ON, 1981 to 2015. Yield and SOC under 21st century conditions were projected under future climate scenarios from 2016 to 2100. The DNDC model was calibrated to improve crop N stress and was revised to estimate changes in water availability as a function of soil properties. This improved yield estimates for diversified rotations at Elora (mean absolute prediction error [MAPE] decreased from 13.4-15.5 to 10.9-14.6%) with lower errors for the three most diverse rotations. Significant improvements in yield estimates were also simulated at Woodslee for COAA, with MAPE decreasing from 24.0 to 16.6%. Predicted and observed SOC were in agreement for simpler rotations (CC or CCSS) at both sites (53.8 and 53.3 Mg C ha for Elora, 52.0 and 51.4 Mg C ha for Woodslee). Predicted SOC increased due to rotation diversification and was close to observed values (58.4 and 59 Mg C ha for Elora, 63 and 61.1 Mg C ha for Woodslee). Under future climate scenarios the diversified rotations mitigated crop water stress resulting in trends of higher yields and SOC content in comparison to simpler rotations.

Sodium Persulfate and Potassium Permanganate Inhibit Methanogens and Methanogenesis in Stored Liquid Dairy 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.

Targeting Bacteria and Methanogens To Understand the Role of Residual Slurry as an Inoculant in Stored Liquid Dairy Manure.

Microbial communities in residual slurry left after removal of stored liquid dairy manure have been presumed to increase methane emission during new storage, but these microbes have not been studied. While actual manure storage tanks are filled gradually, pilot- and farm-scale studies on methane emissions from such systems often use a batch approach. In this study, six pilot-scale outdoor storage tanks with (10% and 20%) and without residual slurry were filled (gradually or in batch) with fresh dairy manure, and methane and methanogenic and bacterial communities were studied during 120 days of storage. Regardless of filling type, increased residual slurry levels resulted in higher abundance of methanogens and bacteria after 65 days of storage. However, stronger correlation between methanogen abundance and methane flux was observed in gradually filled tanks. Despite some variations in the diversity of methanogens or bacteria with the presence of residual slurry, core phylotypes were not impacted. In all samples, the phylum Firmicutes predominated (∼57 to 70%) bacteria: >90% were members of ClostridiaMethanocorpusculum dominated (∼57 to 88%) archaeal phylotypes, while Methanosarcina gradually increased with storage time. During peak flux of methane, Methanosarcina was the major player in methane production. The results suggest that increased levels of residual slurry have little impact on the dominant methanogenic or bacterial phylotypes, but large population sizes of these organisms may result in increased methane flux during the initial phases of storage.IMPORTANCE Methane is the major greenhouse gas emitted from stored liquid dairy manure. Residual slurry left after removal of stored manure from tanks has been implicated in increasing methane emissions in new storages, and well-adapted microbial communities in it are the drivers of the increase. Linking methane flux to the abundance, diversity, and activity of microbial communities in stored slurries with different levels of residual slurry can help to improve the mitigation strategy. Mesoscale and lab-scale studies conducted so far on methane flux from manure storage systems used batch-filled tanks, while the actual condition in many farms involves gradual filling. Hence, this study provides important information toward determining levels of residual slurry that result in significant reduction of well-adapted microbial communities prior to storage, thereby reducing methane emissions from manure storage tanks filled under farm conditions.