Tag: manure volatile solids

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A mass balance approach to estimate methane and ammonia emissions from non-ruminant livestock barns

Purpose

Producers are under pressure to demonstrate and document environmental sustainability. Responding to these pressures requires measurements to demonstrate greenhouse gas (GHG) emissions and/or changes over time. Stored manure emissions are a critical piece of livestock agriculture’s contribution to GHG production. Manure sample‐based estimates show promise for estimating methane (CH4) production rates from stored manure but deserve more extensive testing and comparison to farm‐level measurements. Understanding the causes for variability offer opportunity for more realistic and farm‐specific GHG emissions. Improved GHG measurements or estimates will more accurately predict current GHG emission levels, identify mitigation techniques, and focus resources where they are needed. This project offers an innovative approach to improvement of air quality and strengthens engagement by the livestock sector in sustainability discussions.

Although CH4 and ammonia (NH3) emissions from non-ruminant livestock production systems are primarily released from stored manure, current emission inventories (models) do not account for all production and management systems. The purpose of this project was to track flows of nitrogen, volatile solids (VS), and ash into and out of several commercial livestock barns to estimate CH4 and NH3 emissions. Using a mass balance approach, volatile components like nitrogen and volatile solids are supported through simultaneous balances with ash (fixed solids). These mass-balance based estimates can be compared to national inventory emission estimates and serve as sustainability metrics, regulatory reporting, and management decisions.

What Did We Do?

In the initial step of this project, experimental data for VS, the precursor to methane, are compared to fixed estimates in methane emission estimation tools, like the EPA State Greenhouse Gas Inventory Tool (US EPA, 2017).

The litter from a commercial turkey finishing barn housing between 13,000 and 18,000 birds was sampled weekly for one month, with one additional sampling day one month later. VS concentrations were analyzed for each sample and used to estimate total VS production per year assuming six 15,000 bird flocks (Soriano et al., 2022). A range of VS percentage values for deep-pit cattle facilities were taken from Cortus et al. (2021) and converted to total VS production per year. A range of VS concentrations for deep-pit swine manure storage were taken from Andersen et al. (2015) and used to find total VS production per year of that system as well. Next, total VS productions per year were estimated for the same three systems using the State Greenhouse Gas Inventory Tool.

What Have We Learned?

Table 1 summarizes all calculated total VS values and CH4 estimates per year for both the estimation tool and the experimental data. For each of the three systems, the state inventory estimated total VS value falls within the ranges calculated with experimental data, however, the estimates cannot account for the variabilities found within each system. As seen in the experimental total VS values, there can be a large range of VS production due to differences within specific operations of each system. Total VS relates directly to CH4 emissions, so accurate estimates are important for determining greenhouse gas emission potential of a specific operation.

Table 1. All calculated total VS values and CH4 emissions estimates for each of the three systems.
Total VS production (kg/yr) Emissions*
State Inventory Experimental Values m3CH4
Feedlot Steer (500 head) 334,990 260,758 – 1,002,675 1,262**
Grower-Finisher Swine (1,200 head 160,408 107,514  – 216,669 19,050
Turkey (15,000 head) 314,594 206,838 – 359,245 1,699
*Emissions estimates found through the State Greenhouse Gas Inventory Tool
**Feedlot steer emission estimate assumes an open feedlot manure management system

Future Plans

Next steps for this study will include manure sampling at additional commercial turkey barns, deep-pit grower-finisher swine barns, and dairy cattle systems. Similar mass balances will be performed to determine total VS and nitrogen content to calculate CH4 and NH3 emissions from each system. These calculated values will again be compared to outputs of emission estimating tools.

Authors

Anna Warmka, Undergraduate Student, University of Minnesota – Twin Cities, Department of Bioproducts and Biosystems Engineering

Corresponding author email address

warmk011@umn.edu

Additional authors

Erin Cortus, Associate Professor, University of Minnesota – Twin Cities, Department of Bioproducts and Biosystems Engineering

Noelle Soriano, MS Student, University of Minnesota – Twin Cities, Department of Bioproducts and Biosystems Engineering

Melissa Wilson, Assistant Professor, University of Minnesota – Twin Cities, Department of Soil, Water, and Climate

Bo Hu, Professor, University of Minnesota – Twin Cities, Department of Bioproducts and Biosystems Engineering

Additional Information

Andersen, D.S., M.B. Van Weelden, S.L. Trabue, and L.M. Pepple. “Lab-Assay for Estimating Methane Emissions from Deep-Pit Swine Manure Storages.” Journal of Environmental Management 159 (August 2015): 18–26. https://doi.org/10.1016/j.jenvman.2015.05.003.

Cortus, E.L., B.P. Hetchler, M.J. Spiehs, and W.C. Rusche. “Environmental Conditions and Gas Concentrations in Deep-Pit Finishing Cattle Facilities: A Descriptive Study.” Transactions of the ASABE 64, no. 1 (2021): 31–48. https://doi.org/10.13031/trans.14040.

US EPA, OAR. “State Inventory and Projection Tool.” Data and Tools, June 30, 2017. https://www.epa.gov/statelocalenergy/state-inventory-and-projection-tool.

Soriano, N.C., A.M. Warmka, E.L. Cortus, M.L. Wilson, B. Hu, K.A. Janni. “A mass balance approach to estimate ammonia and methane emissions from a commercial turkey barn.” unpublished (2022).

Acknowledgements

This research was supported by the Rapid Agricultural Response Fund. We also express appreciation to farmer cooperators who allowed us to collect data on their farms and shared their observations with us.

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Spatial and temporal variabilities of manure composition in a commercial turkey barn

Purpose

A mass balance approach to estimate gas emissions is based on tracking inflows and outflows from the barn boundary with losses assumed to be aerial emissions from the barn. This method is reliant on high-quality data to obtain representative emission values. Some considerations for this include spatial and temporal variability of manure composition in a turkey barn. Farm management styles and bird behavior may influence the location of manure accumulation and distribution. Thus, our objective for this work was to identify spatial and temporal differences of manure composition in the barn. The results from this work may have implications for sampling procedures for emission estimation using a mass balance approach.

What Did We Do?

The system in this study was a commercial turkey finishing barn that housed between 13,000 to 18,000 birds and used wood shavings as bedding. Birds were moved into the barn at 5-weeks old and were 13 weeks old by the end of the sampling period. There were no birds in the barn during the first week of sampling. Bird growth was constantly changing as birds matured, which would affect manure production and possibly manure composition. For this reason, weekly samples were taken over a one-month period, with one additional sampling day one month after to capture these changes.

For sampling purposes, the barn area was divided into seven different lanes based on locations of feeder and waterer lines, as well as existing “lanes” implemented by the farm staff in their distribution of litter. Litter samples were aggregated from cores at seven different locations along an individual lane. Manure samples were analyzed for moisture, volatile solids (VS), ash, and nitrogen (N) content. Manure density and depth measurements were also recorded during sampling to track manure accumulation over time.

Figure 1: Barn layout depicting the seven lanes from which aggregated litter samples were collected.

What Have We Learned?

Moisture, volatile solids (wet basis), and ash content (wet basis) differed by position in the barn. Higher moisture content was observed at the waterer and feeder lines (shown in solid lines) compared to the middle barn area (shown in dashed lines). Water spillage and defecation occurred most frequently at these lanes, which aligns with results shown in Figure 1.

Figure 2. Measured litter moisture content in the middle barn areas compared to the waterer and feeder lanes.
Figure 3. Measured ash content in the middle barn areas compared to the waterer and feeder lanes. A similar trend was observed for volatile solids content.

Ash (Figure 3) and volatile solids (not pictured) concentrations shared the same trend, where litter in the middle barn area had higher ash and VS concentrations compared to the waterer and feeder lanes. Areas with higher moisture content should have lower ash and volatile solids concentrations, and so this result was expected. These results are shown in Figure 2.

The N content in the middle barn area was generally higher than N at the waterer and feeder lanes, except for x2. This was unexpected as birds were observed to defecate most frequently around the waterer and feeder lanes, and so a higher N content was expected at these lanes, compared to the middle of the barn. The range of results, however, was comparable to literature and standard values, as well as results from a commercial lab test, as shown in Figure 4. This value was determined using the Dumas method at a commercial lab and describes the N content of a manure sample taken shortly after barn cleanout.

Figure 4. N content at different locations in the barn.

Temporal changes in manure composition were observed in the first two weeks of sampling for ash and volatile solids which were around the time the birds were first moved into the barn. Shortly after, ash and volatile solids concentrations stayed the same. For nitrogen, a general decrease was observed over time for all lanes during the weekly sampling period. Litter was also added between days 28 and 56 which may explain the general increase in N content between days 28 and 56. Overall, these results suggest that weekly sampling over a one-month period may be too frequent to discern any changes in manure composition.  The one-month sampling period may also be too short. Manure management decisions such as barn clean-out schedules, litter additions, and removals may reveal more discernable changes in manure composition.

Future Plans

This data will be used to calculate N, volatile solids and ash mass from the manure, and applied to a mass balance for N and CH4 emission calculation from the turkey barn. Knowledge of spatial differences in manure composition would be useful for emission estimation from specific areas in the barn. It can also be used for overall barn emission estimation, with possibility of calculation of emission contributions from different areas in the barn.

Authors

Presenting author

Noelle Soriano, MS Student, University of Minnesota – Twin Cities

Corresponding author

Erin Cortus, Associate Professor, University of Minnesota-Twin Cities

Corresponding author email address

ecortus@umn.edu

Additional Authors

Anna Warmka, Undergraduate student, University of Minnesota- Twin Cities

Melissa Wilson, Assistant Professor, University of Minnesota- Twin Cities

Bo Hu, Professor, University of Minnesota- Twin Cities

Kevin Janni, Professor, University of Minnesota -Twin Cities

Acknowledgements

This research was supported by the Rapid Agricultural Response Fund. We also want to express appreciation to farmer cooperators who allowed us to collect data and shared their observations with us.

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