methane – Livestock and Poultry Environmental Learning Community

April 7, 2025May 11, 2025

Seasonal greenhouse gas emissions from dairy manure slurry storages in New York State

Due to a technical glitch, the beginning of the recorded presentation was not recorded. Please accept our apologies.

Purpose

As the adoption of dairy manure storage systems has increased as a best management practice for protecting water quality, the anaerobic conditions in these systems has inadvertently led to an increase in emission of the greenhouse gas methane. Current inventory and modeled estimates of this potent greenhouse gas are based on limited datasets, and there is a need for methodologies to better quantify these emissions so that the impacts of storage conditions, manure treatments and seasonality can be better assessed, mitigation strategies can be implemented, and greenhouse gas reduction estimates can be correctly accounted for.

What Did We Do?

We are developing a ground-based, mobile measurement approach where manure storage systems are circled with a backpack methane gas analyzer and measurements are integrated with on-site wind measurements to calculate emission flux rates. Twelve commercial dairy farm manure storage systems, representing a range of herd sizes and pre-storage manure treatments are collaborating on the research. Once per month, each manure storage structure at each site is circled 10 consecutive times with a methane gas analyzer. A drone equipped with a separate methane analyzer is also used to verify ground-based measurements amidst the methane plumes. Divergence (Gauss’s) theorem is then applied to concentration measurements and anemometer wind data to estimate the net rate of methane flux. These observed methane emission fluxes are compared to International Panel of Climate Change (IPCC) modeled emissions as well as state inventories.

What Have We Learned?

We find that this methodology provides a reliable, cost-effective way to estimate methane emissions from manure storages. Observed emissions track modeled emissions with similar magnitudes, though models may be overestimating emissions during the growing season and underestimating during the winter months in this region (Figure 1). While emissions patterns are generally similar for each of the farm sites, with some farms and some individual monthly observational estimates there can be substantial deviation from predicted emission rates.

: Figure 1. Modeled and measured cumulative methane emissions from a dairy manure storage system over a 12-month period.

Future Plans

Evaluation of 2024 field data is ongoing, and we will continue to measure methane around storages with ground-based and drone measurements into the summer of 2025. We will explore plume dynamics and the effects of pre-storage treatments on measured methane emission flux. For select sites, measurements will be expanded to include continuous, open-path laser absorption spectroscopy to verify this novel measurement approach, footprint emissions, and explore the implications of pre-storage manure treatments.

Authors

Presenting & corresponding author

Jason P. Oliver, Dairy Environmental Systems Engineer, Cornell University | PRO-DAIRY, jpo53@cornell.edu

Additional authors

Lauren Ray, Agricultural Sustainability and Energy Engineer, Cornell University | PRO-DAIRY

Eric Leibensperger, Associate Professor, Physics and Astronomy, Ithaca College

Additional Information

https://cals.cornell.edu/pro-dairy/our-expertise/environmental-systems/climate-environment/greenhouse-gas-emissions

https://leibensperger.github.io/

Acknowledgements

Funding for this work was provided by the New York State Department of Agriculture and Markets. Agreement # CM04068CO

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7–11, 2025. URL of this page. Accessed on: today’s date.

April 3, 2025April 4, 2025

Enhancing biogas production through anaerobic co-digestion of aquaculture waste and corn stover

Purpose

Aquaculture production has steadily increased over the past few decades to meet the growing demand driven by population growth. Recirculating aquaculture system (RAS) is a popular technology for fish farming, where water is continuously filtered and reused. The filtration process generates sludge, also called aquaculture waste (AW), comprised of fish feces, uneaten feeds and other metabolites. This sludge can create environmental pollution if not handled properly. Anaerobic digestion (AD) is a waste-to-energy technology that can convert AW into biogas. The digestate produced after AD is nutrient-rich and can be utilized for aquaponic production.

The performance of AD depends on several factors, including substrate characteristics, process conditions, and operational parameters. One critical factor is the carbon-to-nitrogen (C/N) ratio, which significantly influences AD efficiency. The optimal C/N ratio for AD is typically between 20 and 30. However, AW has a low C/N ratio due to its high protein content, which can limit biogas production. To maximize biogas yield, the C/N ratio of AW needs to be adjusted. Co-digesting AW with a high C/N feedstock can help achieve an optimal balance. Corn stover (CS), a high C/N substrate that is abundantly available in the U.S., can be used to enhance AD of AW. Therefore, the aim of this study was to find out the optimum mixing ratio that results in maximum biogas production.

What Did We Do?

In this study, AW was collected from the Aquaculture Research Lab at Purdue University, West Lafayette, IN, and CS was obtained from the Animal Sciences Research and Education Center at Purdue University. A batch experiment was conducted using 24 batch digesters, which were made of 1-L Corning polycarbonate square bottles. Ground CS was mixed with AW at seven different ratios (100:0, 90:10, 70:30, 50:50, 30:70, 10:90, and 0:100) as digester substrate. Digested slurry from a dairy farm manure biogas digester, which operated in mesophilic condition, was used as inoculum. The substrate-to-inoculum ratio was maintained at 1:3. Each digester was fed the feedstock containing 3.75 g volatile solids (VS) and the inoculum containing 11.25 g VS. A 1-L Tedlar bag was connected to each digester to collect biogas. All seven treatments and a blank, which contained only inoculum, were designed in triplicate and set up in an experimental chamber. The experiment was performed for 30 days under mesophilic conditions using two water baths to maintain a constant temperature. The volume and composition of biogas produced from each digester were measured daily and periodically, respectively. The biochemical methane potential for each mixing ratio was calculated by subtracting the biogas produced by the inoculum from the total biogas produced from a digester.

What Have We Learned?

The study showed that biogas production varied with different mixing ratios as shown in Figure 1. Biogas production was higher during the initial period and decreased as the digestion process progressed. Digesters with a higher proportion of AW took less time to produce 90% of the total biogas produced. The cumulative specific biogas production was highest (494.62 mL g−1 VS) for the 50:50 mixing ratio of CS and AW after 30 days of digestion. The methane concentration for all test groups ranged between 50.58% and 57.66%. The 50:50 ratio showed the highest cumulative methane yield (275.98 mL g−1 VS), which was 21.47% and 20.29% higher than the mono-digestion of CS and AW, respectively. The superior performance at this ratio can be attributed to a balanced C/N ratio.

Figure 1: Cumulative biogas and methane yield and methane concentration at different mixing ratios of aquaculture waste (AW) and corn stover (CS). The error bars are standard deviations.

Future Plans

This study is part of a USDA research project to develop a near-zero-pollution aquaculture production system. Future studies on AD for aquaculture production will focus on enhancing biogas yield from AW through various methods of substrate pretreatment and additive use. Additionally, the quality of the digestate from AD of AW will be evaluated for potential application of digestate in aquaponic production.

Authors

Presenting & corresponding author

Ji-Qin Ni, Professor, Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, jiqin@purdue.edu

Additional authors

Rajesh Nandi, PhD student, Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907; Mohit Singh Rana, Postdoctoral Research Associate, Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907

Additional Information

Mirzoyan, N., Tal, Y., Gross, A., 2010. Anaerobic digestion of sludge from intensive recirculating aquaculture systems: Review. Aquaculture 306, 1–6. https://doi.org/10.1016/j.aquaculture.2010.05.028

Acknowledgements

This research was supported by the intramural research program of the U.S. Department of Agriculture, National Institute of Food and Agriculture, Agriculture and Food Research Initiative grant no. 2023-68016-39718.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date.

April 3, 2025April 4, 2025

Optimizing Manure Application Timing for Methane Reduction and Economic Gains through Carbon Credits

Purpose

Methane emissions from manure storages significantly contribute to the livestock industry’s carbon footprint. While various manure management strategies are used to reduce greenhouse gas (GHG) emissions on farms, such as anaerobic digestion and composting, many of these strategies are cost-prohibitive for small-to-medium-sized farms. Strategic manure application timing to limit GHG emissions is a practical, scalable option to reduce methane production in manure storages.

Carbon credits are financial incentives for farmers who adopt practices that reduce greenhouse gas emissions, such as cover crops or methane emissions abatement. These credits can then be sold to companies seeking to offset their emissions. This study evaluates the impact of manure application timing on methane emissions from storages and explores how carbon credits could act as an incentive for farms to employ climate-smart manure management practices. By comparing different manure application strategies (fall, spring, in-season sidedress, and split applications), we assess the methane reductions and improved economics of optimized timing.

What Did We Do?

Methane emissions were estimated using data from a lab-based study conducted by Andersen et al. (2015), who measured methane emissions from deep-pit swine manure at various temperatures. From this data, we created a model incorporating manure production rates and ambient temperature dynamics to predict daily methane emissions from a 4800-head slurry storage and 4800-head deep-pit swine production facility.

Seven application scenarios were compared: fall (November 1), spring (April 15), sidedress (June 1), fall-spring, fall-sidedress, spring-sidedress, and fall-spring-sidedress split applications. Total methane emissions were calculated for each scenario, allowing us to determine the GHG emissions abated by shifting from a fall application to an alternate strategy. An economic assessment was conducted using a $30/metric ton carbon dioxide equivalent (MT CO2e) carbon credit valuation to determine the financial implications of these methane mitigation strategies.

What Have We Learned?

For our swine slurry store model, methane emissions were highest in the single fall application scenario due to the full storage attained during peak summer temperatures, with annual emissions totaling nearly 0.5 MT CO2e/pig-space (Figure 1). Shifting application to spring or sidedress reduced emissions by approximately 50%. Split applications showed a further reduction in emissions by maintaining lower storage volumes throughout the year.

Figure 1: Estimated methane emissions in metric tons of carbon dioxide equivalent (MT CO2e) from slurry storage for fall, spring, sidedress, fall-spring split (F-S), fall-sidedress split (F-SD), spring-sidedress split (S-SD), and fall-spring-sidedress split (F-S-SD) applications.

From an economic perspective, carbon credits significantly enhanced the financial viability of the new application strategies. Carbon credits from abated emissions are projected to bring a maximum of $10/pig-space, or about $74/acre, to the farm annually in the F-S-SD scenario (Table 1). The improved manure application timing can also benefit crop yield, making a spring or sidedress manure application even more economically favorable.

Table 1: Projected carbon credit income for a 4800-head wean to finish swine farm with a slurry storage for fall, spring, sidedress, fall-spring split (F-S), fall-sidedress split (F-SD), spring-sidedress split (S-SD), and fall-spring-sidedress split (F-S-SD) applications.

Fall

Spring

Sidedress

F-S

F-SD

S-SD

F-S-SD

Carbon Credit Income

($/acre)

$ –

$ 33.63

$ 33.71

$ 41.95

$ 45.82

$ 45.69

$ 52.06

Carbon Credit Income

($/pig-space)

$ –

$ 6.50

$ 6.51

$ 8.10

$ 8.85

$ 8.83

$ 10.06

Future Plans

Further research should be conducted to refine the temperature aspect of the model. In the slurry store model, we assume that the manure temperature equals the 10-day average temperature. A study to verify the true manure temperature throughout the year would improve the confidence level of the current model. For deep pit barns, we use measured temperature data from 58 barns over 13 months, but manure temperatures were collected from the manure pump out access port and may not represent average manure temperatures in the barn. Future models to assess differences between deep pit and slurry store emissions will highlight the optimal manure management strategies for limiting GHG emissions.

Using specialized high-clearance irrigation equipment, like the 360 RAIN from 360 Yield Center, could enhance the feasibility of more frequent manure applications, reducing methane emissions while maintaining crop nitrogen availability. Additionally, developing standardized carbon credit protocols for manure management could create opportunities for more producers to monetize methane reduction efforts, further incentivizing climate-smart manure application strategies.

Authors

Presenting author

Jacob R. Willsea, Graduate Research Assistant, Iowa State University Department of Agricultural and Biosystems Engineering

Corresponding author

Daniel S. Andersen, Associate Professor, Iowa State University Department of Agricultural and Biosystems Engineering, dsa@isatate.edu

Additional Information

Andersen, D.S., Van Weelden, M.B., Trabue, S.L., & Pepple, L. M. (2015). Lab-assay for estimating methane emissions from deep-pit swine manure storages. Journal of Environmental Management, 159, 18-26. https://doi.org/10.1016/j.jenvman.2015.05.003

Talkin’ Crap Podcast Episode:

https://talkincrappodcast.buzzsprout.com/2163071/episodes/16472267-timing-is-everything-reducing-methane-emissions-with-manure-management

Andersen Lab Poster Repository:

https://iastate.box.com/s/3kkzdzcjlk9qcfrgbv6mj9x7vdk1v0fp

Acknowledgements

USDA-NRCS

Brent Renner

360 Yield Center

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date.

March 30, 2025May 11, 2025

Laboratory estimation of methane emission rates from Midwest dairy manure samples representing common manure types and storage conditions

Purpose

Methane (CH4) emissions from manure storage are a substantial contributor to the cradle-to-farmgate climate footprint for many dairy farms, especially for farms storing manure as liquid or slurry (Rotz et al., 2021). Dairy systems handle, treat, and store manure in various ways. In combination with environmental conditions, these differences in manure-related structures and processes potentially cause substantial farm-to-farm variability in CH4 production and intensity. However, few methods are available to estimate CH4 emissions specific to a manure storage or farm system.

To enable estimation of CH4 emission rate per unit of manure (methane emission rate, MER), research by Andersen et al. (2015) tested a laboratory assay on swine manure from deep pits. These authors showed that MER was related to manure chemical composition and varied across the year, with the highest values recorded in late fall. Our research aimed to build on Andersen et al. (2015) by testing dairy rather than swine manure to 1) compare MER across a variety of manure types, storage types, and typical storage durations, 2) examine seasonal differences in MER, and 3) quantify farm-to-farm and storage-to-storage variation in MER. Ultimately, we expected to illustrate how the MER laboratory assay could be used in estimating farm-specific CH4 emission rates from dairy manure storages.

What Did We Do?

We partnered with 27 dairies in the U.S. Upper Midwest with liquid and slurry manure storages. At approximately 2–4-month intervals throughout 2024, we collected composite samples (n = 208) representing various manure types, typical storage durations, and storage types. Most samples were whole manure (n = 165, 79%) or liquid separated manure (n = 34, 16%), with remaining samples representing flush water and digestate. Samples represented areas where manure was stored for short durations (≤1 mo.; n = 120, 58%) and long durations (>1 mo.; n = 88, 42%). Most long-term storage was unroofed, and most short-term storage was roofed. Samples represented transfer pits (n = 84, 40%), unroofed basins or pits (n = 67, 32%), and below-building pits (n = 30, 14%), among other storage types. Samples were distributed evenly across seasons for most farms, except that fewer samples were collected during winter due to outdoor storages freezing over.

For the MER assay, we incubated 75.06 ± 0.02 g (mean ± standard error) of manure at 72°F in triplicate 100 mL serum bottles for 2.99 ± 0.01 days. Then, we measured gas displacement with a syringe and headspace CH4 concentration with gas chromatography (Agilent 490 Micro GC, Agilent Technologies, Inc., Santa Clara, CA). We calculated MER as the average CH4 emission (mL) at 72°F per liter of manure per day. To examine differences due to manure type, typical storage duration, storage type, and season, we fit linear mixed models to log-transformed MER, then back-transformed model-implied means and standard errors. Additionally, we examined variance components attributable to individual storages and farms in relation to the residual variance. Storage-to-storage differences explained a small amount of total variance, so the random effect of storage was removed. Significance was declared at p<0.05.

What Have We Learned?

Across samples, the MER was highly variable and right-skewed (mean = 37, median = 21, standard deviation = 45 mL CH4 L-1 d-1; Figure 1), with a small fraction of extremely high values (maximum = 236 mL CH4 L-1 d-1). In contrast with our expectations, we found no effect of manure type, typical storage duration, and storage type on MER. Season influenced MER (F [3, 183.4] = 11.3, p < 0.001), with Fall samples exhibiting a larger MER compared with other seasons (Table 1). Larger MERs in Fall samples were driven by greater gas volume and CH4 concentrations in headspace; model-implied means of both variables nearly doubled in Fall compared with other seasons. Considering that all samples were incubated at the same temperature during the MER assay, greater MER during Fall may indicate that these samples had more abundant and active methanogen populations. Additionally, differences in chemical and physical properties of manure may have enhanced substrate availability for methanogenesis in Fall samples relative to other seasons.

Table 1. Results of a laboratory assay to estimate methane emission rate from dairy manure samples (n = 208) by incubating at 72°F in serum bottles for 3 days.
	Model-Implied Mean (Confidence Interval)
Variable	Spring	Summer	Fall	Winter
Volume displacement, mL	14 (3, 25)	16 (4, 27)	26 (14, 37)	13 (0, 26)
Headspace methane, %	5 (3, 10)	8 (5, 16)	14 (8, 26)	6 (3, 12)
Methane emission rate, mL CH4 L-1 d-1	13 (7, 25)	22 (11, 43)	41 (21, 79)	15 (7, 33)

Although our results illustrated that the mean MER was generally similar across categories of manure types, storage durations, and storage types, we found that between-farm differences accounted for 18% of the total variance in MER. In other words, samples from the same farm were correlated on average 0.18. This suggests that there are farm-to-farm differences in MER that were not explained by the predictors we considered as fixed effects.

Figure 1. Methane emission rates of samples (n = 208 points) showing the median and first and third quartiles (box) with whiskers 1.5 times the interquartile range.

Future Plans

In future work on this project, we plan to explore if between-farm differences in MER can be explained by other farm meta-data such as bedding type, manure removal frequency, storage volume, and surface area of manure. Additionally, we will explore relationships between manure chemical composition (total solids, volatile solids, total nitrogen) and MER. Similar to Andersen et al. (2015), we are examining the temperature sensitivity of methanogenesis in different sample types. In subsequent work, we may consider relating MER to other chemical constituents in manure samples related to substrate availability (e.g., fiber fractions) or fermentation end-products (e.g., volatile fatty acids).

Authors

Presenting author

MaryGrace Erickson, Postdoctoral Associate, University of Minnesota

Corresponding author

Erin Cortus, Associate Professor and Extension Engineer, University of Minnesota, ecortus@umn.edu

Additional author

Noelle Cielito Soriano, Ph.D. Candidate, University of Minnesota

Additional Information

Andersen, D. S., Van Weelden, M. B., Trabue, S. L., & Pepple, L. M. (2015). Lab-assay for estimating methane emissions from deep-pit swine manure storages. Journal of Environmental Management, 159, 18–26. https://doi.org/10.1016/j.jenvman.2015.05.003

Rotz, A., Stout, R., Leytem, A., Feyereisen, G., Waldrip, H., Thoma, G., Holly, M., Bjorneberg, D., Baker, J., Vadas, P., & Kleinman, P. (2021). Environmental assessment of United States dairy farms. Journal of Cleaner Production, 315, 128153. https://doi.org/10.1016/j.jclepro.2021.128153

Acknowledgements

We thank the farms who participated in this research for providing samples and data. Additionally, we are grateful to Kevin Bourgeault, Seth Heitman, Sabrina Mueller, and Jacob Olson for contributing to sampling and laboratory analysis. This research is supported by USDA NIFA Award 2023-68008-39859, and the Minnesota Rapid Agricultural Response Fund.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date.

March 24, 2025May 11, 2025

Methane leakage imaging, detection, and quantification from dairy manure biogas capture systems

Purpose

One of the key reasons to implement manure anaerobic digestion (AD) to energy or an impermeable cover and flare (CF) system is to reduce greenhouse gas (GHG) emissions, especially methane (CH4), a potent GHG that makes up most of the US agricultural footprint. These systems that process or store manure, commonly liquid dairy or swine manure, are often referred to as biogas capture systems because they keep oxygen out and contain the manure gases that form primarily from the breakdown of organic matter by microorganisms. The biogas captured is then directed through collection pipes to a utilization system, where the goal is to convert the methane to the less potent carbon dioxide (CO2) via either combustion or electrochemical conversion. For AD systems, the biogas collected is consistent enough to burn or convert for useful energy. For CF systems, particularly those used in the Northeast and Upper Midwest, the biogas collected under the liquid manure storage cover is highly variable throughout the day and year, making it more suitable to flare the methane in the biogas rather than harvest energy. Biogas capture systems must be operated and maintained to avoid methane leaks and venting, particularly to realize their carbon reduction value that can often be monetized. Tools to easily identify point-source biogas losses, such as an optical gas imaging (OGI) camera, are still relatively costly for a bioenergy operation, however they can be used to periodically survey and conduct find it and fix it campaigns to repair and correct problems that may have gone unseen to the naked eye. The ability to better understand where and how biogas leaks and vents occur in AD and CF systems enables better design, operation, maintenance, and public confidence.

What Did We Do?

Twelve biogas capture systems operating on commercial dairy farms in NYS were surveyed once per quarter for at least a year for point-source methane losses using an optical gas imaging (OGI) camera (Teledyne FLIR GF77 uncooled) tuned to the infrared spectrum wavelength range (7 – 8.5 micrometers) where methane gas is absorbed. Any methane loss visualized with the OGI camera was recorded and its characteristics described and reported back to the farm or system owner. Other observations about the methane loss were recorded and losses were measured and/or quantified when feasible. The apparent size of the biogas loss was recorded, primarily by distinguishing between OGI visibility in “normal” camera mode versus “high sensitivity mode (HSM)”. Unique losses versus repeated (by visit) were tracked, indicating ease and motivation to correct the loss. Biogas vents were distinguished from biogas leaks, by characterizing a leak as an unknown or unintended biogas loss during normal operation. Biogas venting was considered loss that occurred by design during abnormal operating conditions, such as overpressure in the digester vessel that could not be immediately corrected with flaring excess biogas.

What Have We Learned?

This work is continuing through this year, and eight sites are completed so far. The results from those sites, that include four AD to energy systems (three electricity generation and one biomethane production) and four CF dairy manure storage systems, have generally highlighted that AD systems experience biogas venting more than biogas leaking whereas CF systems experience more leaking than venting. The number of unique biogas losses found was higher in CF systems than in AD systems, which may be due to their much larger biogas capture surface area that is also susceptible to damage from wind, wildlife, and thermal stress. Additionally, the biogas collection and flare struggle with variable biogas flow, quality, and operational robustness that results in lack of combustion during prolonged periods of the year. Another observation, which requires additional data collection from AD to biomethane systems to have confidence in, is that AD to electricity systems can result in biogas venting and/or unnoticed leaking when the biogas produced is greater than what the installed electric capacity can utilize. Additionally, most if not all AD to biomethane systems are instrumented to detect and measure biogas losses as part of their verification requirements for carbon market programs, making it less likely for losses to go unnoticed or unaddressed.

Future Plans

A methane loss detection protocol for both AD to energy systems and CF manure storage systems was developed by Cornell CALS PRO-DAIRY that has been improved during this project and will continue to evolve. Once the full 12 sites are completed, the protocol will be shared more broadly for reference, and best practices recommended for operations and maintenance to prevent, find, and correct biogas losses. Follow on work may include additional methane loss detection with total loss measurement of AD vessels and manure storage covers, to verify assumed loss rates used as defaults in GHG accounting.

Authors

Presenting & corresponding author

Lauren Ray, Sr. Extension Associate, Cornell University – PRO-DAIRY, LER25@cornell.edu

Additional authors

Jason P. Oliver, Dairy Environmental Systems Engineer, Cornell University PRO-DAIRY;

Peter Wright, Agricultural Engineer, Cornell University

Additional Information

https://cals.cornell.edu/pro-dairy/our-expertise/environmental-systems/climate-environment

Acknowledgements

This work is sponsored by the New York State Department of Agriculture and Markets. Special thanks to our collaborating dairy farms and biogas capture system operators.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2025. Title of presentation. Waste to Worth. Boise, ID. April 7-11, 2025. URL of this page. Accessed on: today’s date.

April 21, 2022November 18, 2024

Greenhouse gas impacts resulting from co-digestion of dairy manure with community substrates

Purpose

The US Dairy industry established a voluntary environmental stewardship goal to achieve greenhouse gas (GHG) neutrality by 2050 among farmers and processors collectively. Manure management and enteric emissions combined account for approximately 70% of the GHG footprint of the US dairy industry, with nearly equal contributions from each (Thoma, 2013). There are multiple manure management systems used by dairy farmers in the Northeast and Upper Midwest that substantially impact GHG emissions. Quantification of GHG emissions for different manure management systems is necessary to compare options and strategies that can be applied to reduce GHG, especially methane, to move toward sustainability and reach the targets set by industry and governments.

Methane is the primary GHG emitted from the long-term storage of dairy manure, a water quality best management practice employed by many dairy farms today. Landfills are also a significant source of methane emission primarily due to degradation of organic waste, notably pre- and post-consumer food wastes (community substrates). Methane is a highly potent GHG that impacts warming by 25 – 28 times as much as carbon dioxide (CO₂) on a 100-year global warming potential (GWP) time scale (US EPA). However, because methane has a lifespan in the atmosphere of around 12 years, it has been accounted for on a 20-year GWP scale (84 times the impact of CO₂) by the State of New York (Climate Leadership and Community Protection Act). Manure management systems that substantially reduce methane, such as the co-digestion of manure with food waste, can achieve significant reductions of the GHG emissions associated with milk production.

What Did We Do?

The GHG emissions resulting from the anaerobic co-digestion of raw dairy manure and community substrate (i.e., food processing waste mixture diverted from landfilling) in an equal mass of each (total mass basis) were calculated as part of a larger study comparing eight different manure management systems. The community substrate was modeled as 50% ice cream and 50% dog food by mass. Methane and nitrous oxide emissions were calculated with equations that use the mass flow of volatile solids (VS) and nitrogen through the co-digestion manure management system that included digestate solid-liquid separation using a screw press and the long-term storage of separated liquid. Carbon dioxide and methane associated with system energy use and energy production as pipeline-quality renewable natural gas (RNG), as well as landfill organics diversion were also calculated. The parasitic energy use (heat and electricity) of the digester and related manure management and biogas upgrading equipment was supplied on an average annual load basis by a portion of the biogas produced. The total net GHGs were summed using a CO₂-equivalent (CO_2e) methodology (both GWP₁₀₀and GWP₂₀ were computed) and normalized on a per lactating cow per year basis. A sensitivity analysis of eleven variables was conducted to quantify the impact of each on the net GHG result.

What Have We Learned?

The co-digestion system net annual GHG impact was calculated to be −16 metric tons (MT) CO_2e cow^-1 (GWP₁₀₀) and −43 MT CO_2e cow^-1 (GWP₂₀). For the co-digestion mixture analyzed (50% liquid dairy manure, 25% ice cream, and 25% dog food), the anaerobic digester biogas production was 4 times greater than the biogas production for manure alone (on a per lactating cow basis). This significant energy production potential contributed an offset of 3.9 MT CO₂ cow^-1 year^-1, assuming the net RNG after supplying the system’s parasitic energy usage displaced the CO₂ emissions from combusting approximately 380 gallons of diesel. In comparison, a methane leakage (or loss) of 2% from the digester to RNG system was equivalent to 18% of the energy offset at GWP₁₀₀ (0.7 MT CO_2e cow^-1 year^-1) and 62% at GWP₂₀ (2.4 MT CO_2e cow^-1 year^-1). Despite the greater contribution of methane leakage at GWP₂₀ on a CO_2e basis, the methane offset from landfilling the community substrate also substantially increased, resulting in just a 5 – 6% increase in the net annual GHG (remaining net negative) when methane leakage was varied from 1 to 3% under both GWP time scales. The methane leakage amount was also the most sensitive variable studied for the co-digestion system and the relatively low impact on total net GHG indicates the effectiveness of this type of manure management system as a tool to reach net GHG neutrality.

Future Plans

A next step in the assessment of co-digestion of dairy manure and food waste diverted from landfills is to continue improvement of our Cornell Dairy Digester Simulation Tool that predicts biogas production from a variety of food wastes combined in different quantities with dairy manure. This tool will also allow for the economic feasibility analysis of different co-digestion system sizes and substrate mixtures, inclusive of tipping fee variation and energy generation options (electricity and RNG) and associated values. This work will help farmers assess the feasibility of implementing or participating in a co-digestion system for manure management.

In future work contingent on funding, we plan to conduct comprehensive field measurements of methane emissions from the long-term storage of raw manure, separated manure liquid, and digested effluent. The equations that calculate methane are gross and depend on volatile solid content and degradability of the stored material, as well as temperature and retention time. Verification of these equations and inputs will give more confidence in utilizing bottom-up calculations of GHGs from manure management practices.

Authors

Lauren Ray, Extension Support Specialist III, Cornell PRO-DAIRY Dairy Environmental Systems Program

Corresponding author email address

LER25@cornell.edu

Additional authors

Curt A. Gooch, Sustainable Dairy Product Owner, Land O’Lakes – Truterra; Peter E. Wright, Extension Associate, Cornell PRO-DAIRY Dairy Environmental Systems Program

Additional Information

More information on related work can be found on the Cornell University PRO-DAIRY website under Environmental Systems: https://cals.cornell.edu/pro-dairy/our-expertise/environmental-systems.

Thoma, G., J. Popp, D. Shonnard, D. Nutter, M. Matlock, R. Ulrich, W. Kellogg, D. S. Kim, Z. Neiderman, N. Kemper, F. Adom, and C. East. (2013). Regional analysis of greenhouse gas emissions from USA dairy farms: A cradle to farm-gate assessment of the American dairy industry circa 2008. Int. Dairy J. 31:S29–S40. https://doi.org/10.1016/j.idairyj.2012.09.010.

US EPA, https://www.epa.gov/ghgemissions/understanding-global-warming-potentials. Accessed 2/24/2022.

Climate Leadership and Community Protection Act. 2020. New York State Senate Bill S6599.

Acknowledgements

The Coalition for Renewable Natural Gas and the New York State Department of Agriculture and Markets provided a portion of the financial resources to support the development of this work.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2022. Title of presentation. Waste to Worth. Oregon, OH. April 18-22, 2022. URL of this page. Accessed on: today’s date.

April 21, 2022November 18, 2024

Emission of ammonia, hydrogen sulfide, and greenhouse gases following application of aluminum sulfate to beef feedlot surfaces

Purpose

Alum has been successfully used in the poultry industry to lower ammonia (NH₃) emission from the barns. However, it has not been evaluated to reduce NH₃ on beef feedlot surfaces. Additionally, it is not known how it would affect other common emissions from beef feedlot surfaces. The purpose of this study was to determine the effect of adding aluminum sulfate to beef feedlot surfaces on NH₃, hydrogen sulfide (H₂S), carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emissions.

What Did We Do?

Eight feedlot pens (30 animals per pen) at the U.S. Meat Animal Research Center feedlot were utilized. The pens had a central mound constructed on manure and soil and 3 m concrete apron by the feed bunk and cattle were fed a corn-silage based diet. Four pens (30 cattle/pen) had 10% (g g^-1) alum applied to the 6 meters immediately behind the concrete bunk apron and four did not receive alum. The amount of alum added to the area was determined on a mass basis for a depth of 5 cm of feedlot surface material (FSM) using the estimated density of feedlot surface material for Nebraska feedlots (1.5 g cm⁻³). On sampling days, six representative grab samples were collected from the feedlot surface from the six-meter area behind the bunk apron in each pen; samples were combined within pen to make three representative replicates per pen (N=24). Each of the three pooled samples per pen were measured for pH, NH₃, H₂S, CH₄, CO₂, and N₂O using petri dishes and wind tunnels in an environmental chamber at an ambient temperature of 25°C (77°F) and 50% relative humidity. Flux measurements for NH₃, H₂S, CH_4,CO₂, and N₂O flux were measured for 15 minutes using Thermo Fisher Scientific 17i, 450i, 55i, 410iQ, and 46i gas analysis instruments, respectively. Samples were analyzed at day -1, 0, 5, 7, 12, 14, 19, 21, and 26.

What Have We Learned?

Addition of alum lowered pH of FSM from 8.3 to 4.8 (p < 0.01) and the pH remained lower in alum-treated pens for 26 days (p < 0.01). Although the pH remained low, NH₃ flux was only lower (p < 0.01) at day 0 and day 5 for alum-treated pens compared to the pens with no alum treatment. Nitrous oxide emission was not affected by alum treatment (6.2 vs 5.7 mg m^-2 min^-1, respectively for 0 and 10% alum treated pens). Carbon dioxide emission was lower for alum-treated pens than non-treated pens from day 5 until the end of the study (p < 0.05), perhaps due to suppressed microbial activity from the lower pH. Hydrogen sulfide emission was higher (p < 0.05) from alum-treated feedlot surface material (0.8 mg m^-2 min^-1) compared to non-treated feedlot surface material (0.3 mg m^-2 min^-1), likely due to addition of sulfate with alum. Methane emission was also higher in alum-treated pens (173.6 mg m^-2 min^-1) than non-treated pens (81.4 mg m^-2 min^-1). The limited reduction in NH₃, along with increased H₂S and CH₄ emission from the FSM indicates that alum is not a suitable amendment to reduce emissions from beef feedlot surfaces.

Table 1. pH, ammonia (NH₃), hydrogen sulfide (H₂S), methane (CH₄), carbon dioxide (CO₂) and nitrous oxide (N₂O) emission from feedlot surface material treated with 0 or 10% alum (g g^-1 mass basis).
	pH		NH₃ (mg m^-2 min^-1)		H₂S (mg m^-2 min^-1)		CH₄ (mg m^-2 min^-1)		CO₂ (mg m^-2 min^-1)		N₂O (mg m^-2 min^-1)
Day	0% Alum	10% Alum	0% Alum	10% Alum	0% Alum	10% Alum	0% Alum	10% Alum	0% Alum	10% Alum	0% Alum	10% Alum
-1	8.1	8.3	229.6^d	515.9^c	0.3	0.4	136.3^x	73.4^w	4,542	3,234	3.1	4.2
0	8.3^a	4.8^b	163.0^c	32.4^d	0.2^f	1.8^e	43.1^x	193.8^w	4,372	5,294	2.9	1.8
5	8.5^a	6.3^b	279.5^c	83.6^d	0.4	0.5	84.1^x	309.5^w	404^y	1,347^z	6.0	6.8
7	8.6^a	6.7^b	120.2	130.0	0.6^f	1.2^e	53.4	61.7	468^y	1,903^z	15.3	10.9
12	8.6^a	7.2^b	418.0	320.3	0.3	0.3	104.5	145.7	3,742^y	1,939^z	3.3	8.0
14	8.9^a	7.6^b	229.0	145.5	0.2	0.4	25.4^x	180.7^w	4,203^y	2,018^z	11.5	9.3
19	8.6^a	7.5^b	228.0	225.1	0.1^f	1.1^e	132.3^x	254.7^w	5,999^y	3,116^z	6.9	5.8
21	8.4^a	7.2^b	232.0	257.0	0.5	0.8	81.9^x	250.0^w	4,324^y	2,477^z	2.2	1.9
26	8.6^a	8.0^b	584.5^c	319.9^d	0.1^f	0.7^e	72.2	92.9	5,534^y	3,540^z	4.7	2.9
Within a parameter and day, different superscripts indicate a significant difference (p < 0.05) between the emissions from the feedlot surface material treated with 0% and 10% alum.

Future Plans

Future research will evaluate the use of aluminum chloride instead of aluminum sulfate to lower pH of FSM and retain nitrogen. Additionally, microbial amendments are being evaluated to determine if they can reduce gaseous emissions from the feedlot surface.

Authors

Presenting author

Mindy J. Spiehs, Research Animal Scientists, USDA ARS Meat Animal Research Center

Corresponding author

Bryan L. Woodbury, Agricultural Engineer, USDA ARS Meat Animal Research Center

Corresponding author email address

bryan.woodbury@usda.gov

Additional Information

For additional information about the use of alum as a feedlot surface amendment, readers are direct to the following: Effects of using aluminum sulfate (alum) as a surface amendment in beef cattle feedlots on ammonia and sulfide emissions. 2022. Sustainability 14(4): 1984 – 2004. https://doi.org/10.3390/su14041984

Acknowledgements

The authors wish to acknowledge USMARC technicians Alan Kruger and Jessie Clark for their assistance with data collection and analysis.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2022. Title of presentation. Waste to Worth. Oregon, OH. April 18-22, 2022. URL of this page. Accessed on: today’s date.

April 30, 2019November 18, 2024

Production of Greenhouse Gases, Ammonia, Hydrogen Sulfide, and Odorous Volatile Organic Compounds from Manure of Beef Feedlot Cattle Implanted with Anabolic Steroids

Animal production is part of a larger agricultural nutrient recycling system that includes soil, water, plants, animals and livestock excreta. When inefficient storage or utilization of nutrients occurs, parts of this cycle become overloaded. The U.S. Beef industry has made great strides in improving production efficiency with a significant emphasis on improving feed efficiency. Improved feed efficiency results in fewer excreted nutrients and volatile organic compounds (VOC) that impair environmental quality. Anabolic steroids are used to improve nutrient feed efficiency which increases nitrogen retention and reduces nitrogen excretion. This study was conducted to determine the methane (CH₄), carbon dioxide (CO₂), nitrous oxide (N₂O), odorous VOCs, ammonia (NH₃), and hydrogen sulfide (H₂S) production from beef cattle manure and urine when aggressive steroid implants strategies were used instead of moderate implant strategies.

What Did We Do?

Two groups of beef steers (60 animals per group) were implanted using two levels of implants (moderate or aggressive). This was replicated three times, twice with spring-born calves and once with fall-born calves, for a total of 360 animals used during the study. Both moderate and aggressive treatment groups received the same initial implant that contain 80 mg trenbolone acetate and 16 mg estradiol. At second implant, steers in the moderate group received an implant that contained 120 mg trenbolone acetate and 24 mg estradiol, while those in the aggressive group received an implant that contained 200 mg trenbolone acetate and 20 mg estradiol. Urine and feces samples were collected individually from 60 animals that received a moderate implant and 60 animals that received an aggressive implant at each of three sampling dates (Spring and Fall 2017 and Spring 2018). Within each treatment, fresh urine and feces from five animals were mixed together to make a composite sample slurry (2:1 ratio of manure:urine) and placed in a petri dish. There were seven composite mixtures for each treatment at each sampling date. Wind tunnels were used to pull air over the petri dishes. Ammonia, carbon dioxide, and nitrous oxide concentrations were measured using an Innova 1412 Photoacoustic Gas Analyzer. Hydrogen sulfide and methane were measured using a Thermo Fisher Scientific 450i and 55i, respectively. Gas measurements were taken a minimum of six times over 24- to 27-day sampling periods.

What Have We Learned?

Flux of ammonia, hydrogen sulfide, methane, nitrous oxide, and total aromatic volatile organic compounds were significantly lower when an aggressive implant strategy was used compared to a moderate implant strategy. However, the flux of total branched-chained volatile organic compounds from the manure increased when aggressive implants were used compared to moderate implants. Overall, this study suggests that air quality may be improved when an aggressive implant is used in beef feedlot animals.

Table 1. Overall average flux of compounds from manure (urine + feces) from beef feedlot cattle implanted with a moderate^a or aggressive^b anabolic steroid.
	Hydrogen Sulfide	Ammonia	Methane	Carbon Dioxide	Nitrous Oxide	Total Sulfides^c	Total SCFA^d	Total BCFA^e	Total Aromatics^f
	µg m^-2 min^-1	——–mg m^-2 min^-1——–
Moderate	4.0±0.1	2489.7±53.0	117.9±4.0	8795±138	8.6±0.1	0.7±0.1	65.2±6.6	5.9±0.5	2.9±0.3
Aggressive	2.7±0.2	2186.4±46.2	104.0±3.8	8055±101	7.4±0.1	0.8±0.1	63.4±5.7	7.6±0.8	2.1±0.2
P-value	0.01	0.04	0.01	0.01	0.01	0.47	0.83	0.05	0.04
^aModerate treatment = 120 mg trenbolone acetate and 24 mg estradiol at second implant; ^bAggressive treatment = 200 mg trenbolone acetate and 20 mg estradiol at second implant; ^cTotal sulfides = dimethyldisulfide and dimethyltrisulfide; ^dTotal straight-chained fatty acids (SCFA) = acetic acid, propionic acid, butyric acid, valeric acid, hexanoic acid, and heptanoic acid; ^eTotal branch-chained fatty acids (BCFA) = isobutyric acid and isovaleric acid; ^fTotal aromatics = phenol, 4-methylphenol, 4-ethylphenol, indole, and skatole

Future Plans
Urine and fecal samples are being evaluated to determine the concentration of steroid residues in the livestock waste and the nutrient content (nitrogen, phosphorus, potassium and sulfur) of the urine and feces.

Authors

mindy.spiehs@ars.usda.gov Mindy J. Spiehs, Research Animal Scientist, USDA ARS Meat Animal Research Center, Clay Center, NE

Bryan L. Woodbury, Agricultural Engineer, USDA ARS Meat Animal Research Center, Clay Center, NE

Kristin E. Hales, Research Animal Scientist, USDA ARS Meat Animal Research Center, Clay Center, NE

Additional Information

Will be included in Proceedings of the 2019 Annual International Meeting of the American Society of Agricultural and Biological Engineers.

USDA is an equal opportunity provider and employer.

Acknowledgements

The authors wish to thank Alan Kruger, Todd Boman, Bobbi Stromer, Brooke Compton, John Holman, Troy Gramke and the USMARC Cattle Operations Crew for assistance with data collection.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.

April 30, 2019November 18, 2024

Production of Greenhouse Gases and Odorous Compounds from Manure of Beef Feedlot Cattle Fed Diets With and Without Ionophores

Ionophores are a type of antibiotics that are used in cattle production to shift ruminal fermentation patterns. They do not kill bacteria, but inhibit their ability to function and reproduce. In the cattle rumen, acetate, propionate, and butyrate are the primary volatile fatty acids produced. It is more energetically efficient for the rumen bacteria to produce acetate and use methane as a hydrogen sink rather than propionate. Ionophores inhibit archaea forcing bacteria to produce propionate and butyrate as hydrogen sinks rather than working symbiotically with methanogens to produce methane as a hydrogen sink. Numerous research studies have demonstrated performance advantages when ionophores are fed to beef cattle, but few have considered potential environmental benefits of feeding ionophores. This study was conducted to determine if concentrations of greenhouse gases, odorous volatile organic compounds (VOC), ammonia, and hydrogen sulfide from beef cattle manure could be reduced when an ionophore was fed to finishing cattle.

What Did We Do?

Four pens of feedlot cattle were fed an ionophore (monensin) and four pens received no ionophore (n=30 animals/pen). Samples were collected six times over a two-month period. A minimum of 20 fresh fecal pads were collected from each feedlot pen at each collection. Samples were mixed within pen and a sub-sample was placed in a small wind-tunnel. Duplicate samples for each pen were analyzed. Ammonia, carbon dioxide (CO₂), and nitrous oxide (N₂O) concentrations were measured using an Innova 1412 Photoacoustic Gas Analyzer. Hydrogen sulfide (H₂S) and methane (CH₄) were measured using a Thermo Fisher Scientific 450i and 55i, respectively.

What Have We Learned?

Table 1. Overall average concentration of compounds from feces of beef feedlot cattle fed diets with and without monensin.
	Hydrogen Sulfide	Ammonia	Methane	Carbon Dioxide	Nitrous Oxide	Total Sulfides^a	Total SCFA^b	Total BCFA^c	Total Aromatics^d
	µg L^-1	—————-mg L^-1—————-
No Monensin	87.3±2.2	1.0±0.2	4.3±0.1	562.5±2.2	0.4±0.0	233.4±18.3	421.6±81.9	16.8±3.1	83.7±6.4
Monensin	73.9±1.4	1.1±0.2	3.2±0.2	567.1±2.1	0.5±0.0	145.5±10.9	388.9±32.5	20.3±2.3	86.4±5.6
P-value	0.30	0.40	0.01	0.65	0.21	0.01	0.79	0.48	0.75
^aTotal sulfides = dimethyldisulfide and dimethyltrisulfide; ^bTotal straight-chained fatty acids (SCFA) = acetic acid, propionic acid, butyric acid, valeric acid, hexanoic acid, and heptanoic acid; ^cTotal branch-chained fatty acids (BCFA) = isobutyric acid and isovaleric acid; ^dTotal aromatics = phenol, 4-methylphenol, 4-ethylphenol, indole, and skatole

Total CH₄ concentration decreased when monensin was fed. Of the VOCs measured, only total sulfide concentration was lower for the manure from cattle fed monensin compared to those not fed monensin. Ammonia, N₂O, CO₂, H₂S, and all other odorous VOC were similar between the cattle fed monensin and those not fed monensin. The results only account for concentration of gases emitted from the manure and do not take into account any urinary contributions, but indicate little reduction in odors and greenhouse gases when monensin was fed to beef finishing cattle.

Future Plans

A study is planned for April – July 2019 to measure odor and gas emissions from manure (urine and feces mixture) from cattle fed with and without monensin. Measurements will also be collected from the feedlot surface of pens with cattle fed with and without monensin.

Authors

Mindy J. Spiehs, Research Animal Scientist, USDA ARS Meat Animal Research Center, Clay Center, NE

mindy.spiehs@ars.usda.gov

Bryan L. Woodbury, Agricultural Engineer, USDA ARS Meat Animal Research Center, Clay Center, NE

Kristin E. Hales, Research Animal Scientist, USDA ARS Meat Animal Research Center, Clay Center, NE

Additional Information

Dr. Hales also looked at growth performance and E. coli shedding when ionophores were fed to finishing beef cattle. This work is published in Journal of Animal Science.

Hales, K.E., Wells, J., Berry, E.D., Kalchayanand, N., Bono, J.L., Kim, M.S. 2017. The effects of monensin in diets fed to finishing beef steers and heifers on growth performance and fecal shedding of Escherichia coli O157:H7. Journal of Animal Science. 95(8):3738-3744. https://pubmed.ncbi.nlm.nih.gov/28805884/.

USDA is an equal opportunity provider and employer.

Acknowledgements

The authors wish to thank Alan Kruger, Todd Boman, and the USMARC Cattle Operations Crew for assistance with data collection.

The authors are solely responsible for the content of these proceedings. The technical information does not necessarily reflect the official position of the sponsoring agencies or institutions represented by planning committee members, and inclusion and distribution herein does not constitute an endorsement of views expressed by the same. Printed materials included herein are not refereed publications. Citations should appear as follows. EXAMPLE: Authors. 2019. Title of presentation. Waste to Worth. Minneapolis, MN. April 22-26, 2019. URL of this page. Accessed on: today’s date.

March 5, 2019March 20, 2019

Aeration to Improve Biogas Production by Recalcitrant Feedstock

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Purpose

Why aerate biogas digesters?

Most agricultural waste is largely composed of polymers such as lignin and complex carbohydrates that are slowly or nearly completely non-degradable in anaerobic environments. An example of such a waste is chicken litter in which wood chips, rice hulls, straw and sawdust are commonly employed bedding materials. This makes chicken litter a poor candidate for anaerobic digestion because of inherently poor digestibility and, as a consequence, low gas production rates.

Previous studies, however, have shown that the addition of small amounts of air to anaerobic digestates can improve degradation rates and gas production. These studies were largely performed at laboratory-scale with no provision to keep the added air within the anaerobic sludge.

What Did We Do?

Picture of 4 digesters with sprayer tanks Four digesters were constructed out of 55 gallon sprayer tanks. The digestate was 132 L in volume with a dynamic headspace of 76 L. At the bottom of each tank a manifold was constructed from ½” PVC pipe in an “H” configuration and with a volume of approximately 230 mL. The bottom of the manifold had holes drilled in it to allow exchange with the sludge. Tanks were fed 400 g of used top dressing chicken litter (wood shaving bedding) obtained from a local producer (averaging 40% moisture and 15% ash) in 2 L of water through a port in the tank [labeled “1” in figure]. Two hundred mL of air were fed to the manifold through a flow meter [2] 0, 1, 4, or 10 times daily in 15-minute periods at widely spaced intervals by means of an air pump and rotary timer [4]. A gas port [3] at the top of the tank allowed for sampling and led to a wet tip flow meter (wettipflowmeters.com) to measure gas production. Digestate samples were taken out of a side port [5] for measurement of water quality and dissolved gases and overflow was discharged from the tank by means of a float switch wired in line with a ½” PVC electrically actuated ball valve.

Seven dried and weighed tulip poplar disks were added to each tank at the beginning of the experiment. At the end of the experiment, the disks were cleaned and dried for three days at 105 ⁰C before re-weighing. Dissolved and headspace gases were measured on a gas chromatograph equipped with FID, ECD, and TCD detectors. Water quality was measured by standard APHA methods.

What Have We Learned?

Graph of chemical oxygen demand per liter and graph of liters of biogas per day

Adding 800 mL of air daily increased biogas production by an average of 73.4% compared to strictly anaerobic digestate. While adding 200 mL of air daily slightly increased gas production, adding 2 L per day decreased gas production by 16.7%.

Aerating the sludge improved chemical oxygen demand (COD) with the greatest benefit occurring at 2,000 mL added air per day. As noted, however, this decreased gas production in the control indicating toxicity to the anaerobic sludge.

The experiment was stopped after 148 days. When the tanks were opened, there was widespread fungal growth both on the surface of the digestate and the wood disks in the aerated tanks [left], whereas non-aerated tanks showed little evidence of fungal growth [right]. While wood disks subjected to all treatments lost significant mass (t-test, α=0.05), disks in the anaerobic tank lost the least amount of weight on average (6.3 g) while all other treatments lost over 7 g weight on average.

Future Plans

Research on other feedstocks and aeration regimes are being conducted as are 16s and 18s community analyses.

Corresponding author (name, title, affiliation)

John Loughrin, Research Chemist, Food Animal Environmental Research Systems, USDA-ARS, 2413 Nashville Rd. B5, Bowling Green, KY 42104

Corresponding author email address

John.loughrin@ars.usda.gov.

Other Authors

Karamat Sistani, Supervisory Soil Scientist, Food Animal Environmental Research Systems. Nanh Lovanh, Environmental Engineer, Food Animal Environmental Research Systems.