emission – Livestock and Poultry Environmental Learning Community

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.

What did we do?

A laboratory study was conducted to determine effects of pen location, moisture, and temperature on emissions of volatile organic compounds (VOC). Feedlot surface material (FSM) was obtained from pens where cattle were fed a diet containing 30% wet distillers grain plus soluble (WDGS). The FSM were collected from the bunk, drainage, and mound areas within three feedlot pens. The FSM were mixed with water to represent dry, wet, or saturated conditions and then incubated at temperatures of 5, 15, 25 and 35ºC. A wind tunnel and TD GC/MS were used to quantify emissions of eight volatile fatty acids (VFA), five aromatics and two volatile sulfur compounds (VSC).

graph showing experiment results. Contribution to total odor activity value (OAV) for each feedlot pen location, moisture condition, and temperature. All within treatment odor activity values sum to 100%.

What have we learned?

Evaluation of emissions as affected by the specified environmental conditions was performed on individual compounds which were normalized using an odor activity value (OAV). When the odor compounds were normalized with respect to their activity value, many of the measured compounds contributed minimally to the overall odor activity. Approximately 10% of the OAV was contributed by three VFAs and one aromatic (4-methylphenol) compound. The VSC contributed the most with 87.3% of the total OAV.

More than half of the OAV occurred at the base of the mound with the bunk and drainage contributing approximately equally to the remainder. The frequent wetting and drying cycles occurring near the base of the mound may contribute to a more diverse microbial population when compared with the chronically wet to saturated conditions existing behind the feed bunk.

The addition of water significantly increased the OAV. Approximately 92% of the OAV was accounted for by wet and saturated conditions. In general, the addition of water decreased emissions of VFA and aromatics, and increased the emission of sulfides. Two possible causes were offered. First, the greater solubility of the VFA and aromatics allowed them to be retained in the solution fraction of the FSM and not be emitted. Second, the addition of water results in an anaerobic environment and reducing conditions, which are conducive to production of VSC.

Temperature significantly affected OAV with over 60% of the total OAV occurring at 35ºC. The 35ºC temperature increased each odor compounds with the impact being the greatest for VSCs. It appears from this study, odor emissions are greatest during warm (i.e. > 25ºC) wet periods and from specific location within the pen.

Authors

Bryan L. Woodbury, Agricultural Engineer, USDA-ARS, U.S. Meat Animal Research Center, Clay Center, NE bryan.woodbury@ars.usda.gov

John E. Gilley, Agr. Eng, USDA-ARS. David B. Parker, Prof., Life, Earth and Environ. Sci., West Texas A&M University. David B. Marx, Prof, Statistics, Univ. of NE. Roger A. Eigenberg, Agr. Eng., USDA-ARS, U.S.

Additional information

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. 2015. Title of presentation. Waste to Worth: Spreading Science and Solutions. Seattle, WA. March 31-April 3, 2015. URL of this page. Accessed on: today’s date.