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. 2026 Oct 27;55(6):e70309. doi: 10.1002/jeq2.70309

Ammonia and methane mitigation from dairy manure using sulfur‐based manure storage additives

Joel S Tinoco 1, Emilia Perez 2, Karrigan Ellison 2, Kayli Tolk 3, Quirine M Ketterings 1, Jason P Oliver 3,✉
PMCID: PMC13714331  PMID: 42947375

Abstract

Dairy manure storage is a major source of greenhouse gas emissions and other air pollutants, including methane (CH4) and ammonia (NH3). Easily deployable mitigation strategies, such as manure storage additives, can help reduce the environmental impact of dairy production. Sulfur‐based manure storage additives, specifically gypsum (CaSO4), have been proposed as low‐cost manure amendments that may influence CH4 emissions; however, their potential to mitigate NH3 emissions and their effectiveness across sulfur dosages remain unclear. This study evaluated two gypsum additives at low and high levels (G1L: 4.23 mg L−1; G1H: 21.15 mg L−1; G2L: 5000 mg L−1; G2H: 25,000 mg L−1) to quantify their effects on NH3 and CH4 emissions from dairy manure over a 12‐week period. Cumulative NH3 and CH4 emissions were measured using the closed‐chamber manure emission system, which consisted of a closed chamber integrated with a multi‐gas Fourier Transform Infrared analyzer, used to measure emissions from bucket‐sized manure storages. Ammonia losses decreased by 27% and 33% in treatments G2L and G2H, respectively, while treatments G1L and G1H showed no significant effect. The effect on CH4 emissions mitigation followed the same pattern, with reductions of 82% and 90% in treatments G2L and G2H, respectively. These results demonstrated a dose–response relationship, in which higher gypsum dosages yielded substantial reductions in NH3 and CH4 emissions. Overall, manure additive treatment using gypsum at sufficient rates offers a practical strategy to mitigate gaseous nitrogen and carbon losses from dairy manure, supporting more sustainable manure management and contributing to climate and air‑quality goals.

Core Ideas

  • Gypsum offers a dual strategy for reducing gaseous nitrogen and carbon losses from manure.

  • Gypsum at sufficient doses reduces ammonia emissions from dairy manure by 27%–33%.

  • Higher gypsum doses suppress methane emissions by 82%–90% in dairy manure.

  • Low gypsum doses show no mitigation, revealing a clear dose‐‑response threshold.

Plain Language Summary

Practical strategies to help dairy farmers support cleaner air and climate goals are needed. In this study, we tested whether adding sulfur‐based manure storage additives, such as gypsum, a common, low‐cost material, could reduce ammonia and methane emissions from stored manure. We applied several gypsum rates and measured gas emissions over 12 weeks. Medium and high rates greatly reduced emissions, cutting ammonia by up to one‐third and methane by up to 90%, while lower rates had little effect. These results show that gypsum additives can be a practical way to limit gas losses during manure storage and advance environmental sustainability efforts.

Abbreviations

FTIR

Fourier transform infrared

SRB

sulfate‐reducing bacteria

TS

total solids

VS

volatile solids

1. INTRODUCTION

Livestock manure management plays a central role in agricultural sustainability because it directly influences nutrient retention and air and water quality (Kupper et al., 2020; Montes et al., 2013). Liquid manure storage is widely used in dairy systems to protect water resources, yet it is also an unintended source of NH3 and CH4 emissions (Harrison et al., 2022; Havlík et al., 2014). Ammonia losses contribute to fine particulate matter (PM2.5) formation, nitrogen deposition, ecosystem eutrophication, and indirect formation of nitrous oxide (N2O). Ammonia emissions can also reduce the nitrogen content of the manure, thereby diminishing its value as a fertilizer. Methane is a potent greenhouse gas that drives climate warming (Dougherty et al., 2017; Gu et al., 2021; Leytem et al., 2011). In the United States, livestock manure accounts for approximately 60% of the NH3 emissions (Aguirre‐Villegas et al., 2024; U.S. Environmental Protection Agency, 2023). Furthermore, manure management accounts for approximately 9% of total CH4 emissions from anthropogenic activities (U.S. Environmental Protection Agency, 2024).

Reducing emissions from manure storage requires mitigation strategies that are both practical and scalable for dairy operations. Technologies such as anaerobic digestion, solid‐liquid separation, and storage covers can substantially reduce emissions, but their adoption is often limited by high capital costs, infrastructure requirements, and management complexity (Ambrose et al., 2023; Hou et al., 2015; Symeon et al., 2025). In contrast, manure additives, which are products applied directly to manure to alter chemical or microbial processes, offer a low‑cost and operationally simple alternative that can be implemented across a wide range of farm sizes (McCrory & Hobbs, 2001; Misselbrook et al., 2016). Gypsum (CaSO4), a sulfur‐based compound already used on some farms mixed into stall bedding, has been proposed as a promising manure additive that can influence CH4 emissions (Sauvé et al., 2025).

Previous studies suggest that gypsum can influence microbial activity and chemical equilibria in manure, with the potential to reduce gaseous losses (Kim et al., 2023; Owusu‐Twum et al., 2025; Sauvé et al., 2025). When gypsum is added to manure, sulfate (SO4 2−) can stimulate sulfate‐reducing bacteria (SRB) (Tomalty et al., 2026). These bacteria use sulfate as an electron acceptor and compete directly with methanogens for substrates such as hydrogen and acetate (Sela‐Adler et al., 2017). As these substrates are channeled to sulfate reduction, they become unavailable for methanogenesis, thereby suppressing CH4 production (Sauvé et al., 2025). The impacts of gypsum additions to slurry on NH3 emissions are less well understood, though in manure composts it is thought that NH3 volatilization can be reduced by the formation of less volatile compounds such as ammonium sulfate (Chu & Talaei, 2025; Voropaev et al., 2021; Xu et al., 2026).

Despite these plausible mechanisms, existing evidence remains limited and highly variable (Chu & Talaei, 2025; Yang et al., 2015). Some studies have shown substantial reductions in CH4 emissions when gypsum is added. For example, Tomalty et al. (2026) reported up to 92% CH4 reduction with approximately 7000 g of gypsum per m3 of manure. Conversely, other studies report lower, inconsistent, or minimal effects. Sauvé et al. (2025) observed up to 28% CH4 reduction with 10,000 g m−3; Owusu‐Twum et al. (2025) noted 46% reduction with 25,000 g m−3; and Peterson et al. (2020) found a 23% decrease using only 62 g m−3. Evidence for NH3 mitigation is even more limited and inconsistent. Some experiments, like those by Owusu‐Twum et al. (2025), showed no significant reduction in NH3 emissions with 25,000 g m−3, while others suggest potential decreases under specific conditions (Chu & Talaei, 2025; Peterson et al., 2020; Voropaev et al., 2021).

Little is known about how gypsum dosage affects NH3 and CH4 simultaneously, and most prior work has focused on single‑gas outcomes, different application rates, or non‑liquid dairy manure substrates. This study evaluates two different gypsum additives at a range of dosages to quantify their effects on NH3 and CH4 emissions from liquid dairy manure. It provides a dose‑‐response assessment of gypsum as a sulfur‐based manure additive for multi‐gas emissions mitigation. This work advances the understanding of manure additive (i.e., gypsum) effects and provides practical guidance for scalable mitigation strategies relevant to climate policy, farm management, and air‐quality objectives.

2. MATERIALS AND METHODS

2.1. Closed‐chamber manure emission system

The closed‐chamber manure emission system consists of a chamber designed to seal to a bucket‐sized manure storage, which is integrated with a multi‐gas Fourier transform infrared (FTIR) analyzer (Gasmet DX4015, Gasmet Technologies Inc.) (Figure 1). The system uses a closed‐flux chamber methodology and was designed based on chambers described by Kienbusch (1986), Parker et al. (2013), and Ussiri and Lal (2013). It was specifically designed to measure gas flux from an 18.9‐L (5‐gal) bucket‐sized manure storage. The half‐sphere stainless‐steel chamber is 7.5 L in volume and has stainless‐steel tube plenums for air sampling and return that connect via Tedlar tubing to the multi‐gas FTIR analyzer. The analyzer operates with a spectrometer resolution of 8 cm−1 and provides continuous multi‑gas quantification with typical measurement accuracy within ±2% of the reading for target gases.

FIGURE 1.

FIGURE 1

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Diagram (left) and photo (right) of the closed‐chamber manure emission system (CCMES). FTIR, Fourier transform infrared.

This experimental system was designed as a scaled‑down analog of a dairy manure storage, preserving the key physical and biological processes that govern gas emissions. The buckets functioned as “mini‑storages,” allowing us to isolate treatment effects while maintaining the natural dynamics present in full‑scale systems. The buckets were kept open between measurements rather than sealed. This was intentional because open storage is the standard condition on most dairy farms in New York, and leaving the buckets uncovered allowed normal gas exchange between the manure surface and the atmosphere. By avoiding lids, we prevented artificial accumulation of gases at the manure–air interface, ensuring that surface concentrations reflected the same continuous mixing and dispersion that occur in real storages due to wind and natural convection. To avoid distortion of gas behavior caused by changes in manure depth, we maintained a constant volume across all treatments by adding water to compensate for evaporation.

The vertical structure of the manure within the buckets also replicated the stratification observed in actual storages. The lower portion remained under anaerobic conditions, while the upper layers had limited oxygen exposure. This stratification is a critical driver of methane and other gases and maintaining it allowed the microbial processes to proceed as they would in a farm‑scale storage. The manure was not mixed during the experiment. On dairy farms, agitation typically occurs only during pumping, not during routine storage. Leaving the manure undisturbed allowed crust formation, microbial gradients, and gas release patterns to develop naturally. One limitation of this system is the absence of an inoculum layer. Real storages are rarely emptied completely, so residual manure provides an established microbial community that influences subsequent gas production. Overall, the design choices in this bucket system intentionally preserved the core physical, chemical, and biological mechanisms that drive gas emissions in dairy manure storages. This allows the results to be extrapolated to farm conditions while still providing the experimental control needed to evaluate treatment effects.

Core Ideas

  • Gypsum offers a dual strategy for reducing gaseous nitrogen and carbon losses from manure.

  • Gypsum at sufficient doses reduces ammonia emissions from dairy manure by 27%–33%.

  • Higher gypsum doses suppress methane emissions by 82%–90% in dairy manure.

  • Low gypsum doses show no mitigation, revealing a clear dose‐‑response threshold.

2.2. Experimental design

The experiment was conducted at the Large Animal Research and Teaching Unit (LARTU) at Cornell University in Ithaca, NY. Manure was collected from the Cornell Dairy Research & Education Center (CDREC), Harford, NY. The sand‐laden manure was collected from an outdoor manure reception pit that holds manure from 650 mature cows, before it is transferred daily to a long‐term manure storage. A 275‐gal tote of manure was freshly collected and immediately transported to LARTU, where it was homogenized using a drill‑mounted mixer paddle as buckets were filled. Each 20‐L bucket received 18.9 L of manure, leaving approximately 1.1 L of headspace. The initial properties of the manure were: pH of 7.9, 5.4% total solids (TS), and 3.4% volatile solids (VS). These physicochemical properties were also measured at the end of the 83‐day storage period.

Two gypsum additives (G1 and G2) were evaluated. The additive “G1”, SOP Lagoon (SOP Farm), contained 19% sulfur and was described as a commercially available gypsum‑derived product processed using proprietary technology and marketed for emission reduction. The G1 additive manufacturer recommends a specific maintenance dose for regular use of the G1 additive. When first applying G1 additive, a dose five times higher than the maintenance rate should be used as the initial establishment dose. According to these recommendations, we established a low (L) and a high (H) dosage, with the maintenance dose as our low dose and the establishment dose as our high dose (Table 1; treatments G1L and G1H).

TABLE 1.

Treatment groups description—G1 and G2 are two different gypsum products.

Treatment

Additive dosage

(mg L−1 of manure)

 Sulfur content %

Total sulfur added

(mg of S L−1 of manure)
G1L 4.23 19 0.80
G1H 21.15 19 4.02
G2L 5000 17 850
G2H 25,000 17 4250
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Note: G1L: low dose of product G1; G1H: high dose of product G1; G2L: low dose of product G2; G2H: high dose of product G2. NS indicates no significant difference from the control group.

The additive “G2” contained 17% sulfur and was characterized as a commercially available gypsum obtained from the recycling of gypsum drywall. Its maintenance dose was established based on the amount used by a dairy farm in New York State, where preliminary observations suggested that its manure storage may generate low CH4 emissions. Given that the farm regularly used gypsum as part of its operation, that rate was considered the maintenance dose. Following the same pattern as G1 dosages, the establishment dose needed to be five times higher than the maintenance dose. Therefore, the high dosage (G2H) was determined by replicating the 1:5 ratio of G1L to G1H, making G2H (establishment dose) five times higher than G2L (maintenance dose) (Table 1; treatments G2L and G2H). The G1L and G2L dosages were administered entirely during the initial week of the experiment, whereas the G1H and G2H dosages were divided into five equal portions and administered weekly over the first5 weeks, with one part applied each week. The first application of the dosages G1H and G2H coincided with the application of the dosages G1L and G2L. Four additive treatments and a control group (no additives applied) were tested simultaneously (n = 3), for a total of 15 buckets monitored throughout the entire experimental period.

No mixing occurred after the buckets were filled with manure at any stage during the experimental period. Furthermore, the additives and water were applied at the surface to avoid artificially altering the condition of the manure and to accurately replicate natural manure storage dynamics throughout the storage period. On day 5, treatments were randomly assigned, and the designated additive was surface‑applied as a solution in 200 mL of distilled water. Although gypsum is not typically added as a slurry in farm settings, dissolving or suspending the additive in water ensured uniform distribution across the manure surface and enabled precise delivery of the intended dosage without disturbing the manure matrix. This approach also ensured consistent application across treatments and prevented localized clumping of dry material, which could otherwise introduce variability in gas emissions. For treatments requiring weekly applications (G1H and G2H), additives were applied on days 12, 19, 26, and 33, for a total of five applications.

All buckets were placed in a controlled‑environment room at LARTU, maintained at approximately 24°C for the duration of the experiment. Since the manure storages remained within this stable indoor environment, the manure temperature closely followed the ambient room temperature with minimal fluctuation over time. This controlled thermal environment ensured that all treatments encountered identical temperature conditions, thereby reducing temperature‑related variations in microbial activity and CH4 production. Additionally, to ensure a consistent manure volume across treatments and to replicate environmental conditions such as rainfall, 200 mL of distilled water without additives was administered weekly to the remaining treatments and the control. Water additions continued weekly for all experimental units after the final additive application.

2.3. Gas measurements and data filtering

Ammonia and CH4 emissions were measured weekly from day 15 to day 83 for a total of nine measurement events. The experiment ran for 83 days, which represented the maximum duration permitted by the availability of the controlled‑environment room where the study was conducted. Gas measurements were collected continuously for the full period allowed by the facility schedule, ensuring consistent monitoring across all treatments. The FTIR gas analyzer was configured to measure gas concentration every 20 s during a measurement cycle, following the recommendation of the manufacturer. The measurements were conducted over a period of 10 min for each experimental unit (comprising 30 data points). Gas flux was calculated utilizing 11 data points, excluding specific initial and final measurements in accordance with the data filtering validation described in the subsequent sections.

Gas concentration measurements often exhibit nonlinear behavior at the beginning and end of chamber closure periods due to mixing effects, pressure disturbances, sensor response time, and shifts in physical or biochemical dynamics (Hutchinson & Mosier, 1981; Livingston et al., 2005). To assess the fit of regression models to determine the change in gas concentration over change in time and ensure accurate flux estimates, a data‐driven statistical validation approach was employed to identify appropriate integration boundaries (t start and t end) for flux computation (Lammirato et al., 2017). The initial data points to omit (t start) and the subsequent points to include (t end), which together define the effective measurement window, were selected based on criteria for linearity and precision (Kulik & Zarov, 2024; Pavelka et al., 2018; Verchot et al., 1999). The coefficient of determination (R 2) for the linear regression was required to be at least 0.95, and the relative standard error (RSE) of the slope could not exceed 20%, consistent with established chamber‑based flux measurement guidelines (Hüppi et al., 2018; Johannesson et al., 2024).

Consequently, to calculate NH3 and CH4 fluxes, the first 3 min of data (the first nine concentration measurements) were excluded to avoid the lag phase (t start = 10). The subsequent 3 min 40 s of data (middle 11 data points) were used for flux estimation (t end = 20). Extending the measurement window beyond this point reduced accuracy because concentration–time relationships often become non‐linear later in the closure period as gas accumulation alters chamber pressure, diffusion gradients, and microbial activity (Hutchinson & Mosier, 1981; Livingston et al., 2005). These end‐effects increase the RSE and lower the coefficient of determination (R 2). The selected interval, therefore, represents the longest duration over which linearity and precision were simultaneously maintained, ensuring robust flux estimates (Lammirato et al., 2017).

Evaluating all possible start points helped identify when the gas concentration increase became reliably linear (t start) (Figure 2). Each nested line in Figure 2A,C represents a different number of points excluded from the endpoint, and the R 2 value obtained by progressively omitting additional initial data points. When lines are close to converge and remain consistently above the 0.95 threshold, it indicates that the selected t start falls within a region where the concentration increase is stable and well‑described by a linear model, confirming that the chosen measurement window is appropriate for calculating flux (Hutchinson & Livingston, 1993; Kulik & Zarov, 2024).

FIGURE 2.

FIGURE 2

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(A) and (C) represent the sensitivity of the determination coefficient (R 2) to the selection of the linear measurement window for ammonia (NH3) and methane (CH4) flux, respectively. (B) and (D) represent the impact of measurement window selection on the precision of NH3 and CH4 flux, respectively, expressed as relative standard error (RSE, %). Each data series represents a fixed number of points removed from the end of the measurement duration, while the x‐axis indicates the number of points removed from the start. The figure illustrates how shortening the measurement window from both the beginning (x‐axis) and the end (legend series) affects the stability and error of the calculated flux slope.

The selection of the optimal window was defined by the lowest RSE, thereby reducing measurement uncertainty associated with heterogeneous substrates such as manure (Figure 2B,D). Given that RSE serves as the primary metric for slope uncertainty, prioritizing the minimum RSE (<20) ensured the highest confidence in the derived slope, leading to a more precise flux estimation. The optimal t end is identified at the point where the RSE reaches its global minimum within the linear region, with a validated R2 (Hüppi et al., 2018; Hutchinson & Livingston, 1993).

This validation framework outlines the methodological requirements for estimating NH3 and CH4 emissions from dairy manure. By combining objective statistical metrics (R 2 and RSE), this approach provided a validated method for measuring gas fluxes in a closed chamber. This method ensures that the estimated gas flux was based on the most accurate, linearly validated portion of the concentration data, resulting in reliable, justifiable emission measurements from the manure source.

2.4. Gas flux calculations

The gas flux was determined according to Collier et al. (2014) and Pihlatie et al. (2013) by analyzing the increase in concentration over time, using the following equation:

GasFlux=dydx×PR×T×V×1106×MW×3600×168×1Vm (1)

where GasFlux is the calculated gas flux (g m−3 week−1); dy is the change in gas concentration (ppm); dx is the change in time (s); P is the pressure within the chamber (atm); R is the ideal gas constant (0.08206 L atm mol−1 K−1); T is the temperature (K); V is the volume of the headspace, chamber, tubing, and analyzer sample cell (m3), the factor 1×10−6 is used to convert from ppm to moles; MW is the molecular weight of the gas (g mol−1); the factor 3600 converts seconds to hours; the factor 168 converts hour to week; and Vm is the volume of manure (m3). Cumulative gas emissions (g m−3) were calculated using the trapezoidal rule, with linear interpolation of fluxes between sampling events and integration of the area under the flux‐time curve (Parkin, 2008; Smith & Dobbie, 2001). A baseline flux of zero was assumed on Day 0, corresponding to the initial filling of the experimental units.

2.5. Statistical analysis

Statistical analyses were conducted in R (version 4.4.1). Treatment effects were evaluated using analysis of variance (ANOVA), and Tukey's HSD test was used for post hoc comparisons. Statistical significance was defined as p < 0.05. Cumulative emissions were used as the response variable in the ANOVA models.

3. RESULTS

Gypsum additive treatments showed clear dose‑dependent responses (Table 2). The emission profiles of NH3 and CH4 showed distinct temporal patterns over the 83‑day experiment (Figure 3). From day 15, the NH3 fluxes of G2L and G2H were lower than those of the control group and remained consistently lower throughout the rest of the trial, whereas the fluxes of G1L and G1H did not differ from those of the control group. Peak NH3 flux occurred between days 40 and 55, after which emissions declined across all treatments (Figure 3A).

TABLE 2.

Impact of gypsum additives on cumulative ammonia and methane emissions from dairy manure. G1 and G2 are two different gypsum products.

Treatment

Final cumulative NH3

(g m−3)

NH3

mitigation

(%)

Final cumulative CH4

(g m−3)

CH4

mitigation

(%)
Control 76 – 1415 –
G1L 79 NS 1457 NS
G1H 78 NS 1386 NS
G2L 55 28 259 82
G2H 51 33 140 90
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Note: G1L: low dose of product G1; G1H: high dose of product G1; G2L: low dose of product G2; G2H: high dose of product G2. NS indicates no significant difference from the control group.

FIGURE 3.

FIGURE 3

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(A) weekly ammonia (NH3) flux, (B) cumulative NH3 emissions, (C) weekly methane (CH4) flux, and (D) cumulative CH4 emissions from manure over an 83‐day experiment period (68‐day measurement period) as influenced by gypsum additives. Symbols represent the mean of three replications (n = 3), and error bars indicate the standard error of the mean. In panels (B) and (D), different lowercase letters to the right of the final data points indicate significant differences between treatments at the end of the study. G1 and G2 are two different gypsum products. G1L: low dose of product G1; G1H: high dose of product G1; G2L: low dose of product G2; G2H: high dose of product G2.

Cumulative NH3 losses from treatments G2L and G2H were significantly lower than those of the control group, reducing cumulative NH3 emissions by 27% and 37%, respectively (Figure 3B). Treatments G1L and G1H did not differ significantly from the control, indicating that lower application rates did not alter overall nitrogen loss. Although G2H achieved the greatest numerical reduction, its effect was not statistically different from that of G2L, indicating that a fivefold increase in dosage does not correspond to an equivalent reduction in emissions.

Methane emissions followed a pattern characterized by a lag phase of approximately 35 days. The control group and G1 treatments exhibited an increase in CH4 emissions after the lag phase, with CH4 fluxes increasing from day 35 through day 55. In contrast, G2L and G2H maintained low CH4 fluxes throughout the study. Differences in CH4 fluxes between the G2 treatments and the control group became evident from day 40 (Figure 3C).

G2 treatments showed greater mitigation potential for cumulative CH4 emissions than G1 treatments (Figure 3D). The cumulative CH4 emissions of the G2L and G2H treatments were significantly lower than those of the control group, reducing emissions by 82% and 90%, respectively. Cumulative CH4 emissions for the Control reached 1415 g m−3 compared with 259 g m−3 and 140 g m−3 for G2L and G2H, respectively. In contrast, G1 treatments showed no significant reduction relative to the control.

4. DISCUSSION

Reducing NH3 and CH4 emissions from dairy manure represents an important opportunity to advance the sustainability of dairy production systems. This study demonstrates that gypsum, when applied at sufficient sulfur concentrations, can substantially reduce both gases, offering a promising dual‑benefit mitigation strategy. The higher dose treatments (G2L and G2H) consistently lowered NH3 and CH4 emissions relative to the control, whereas the lower dose treatments (G1L and G1H) showed no significant effect. These results highlight the importance of dosage in determining the effectiveness of sulfur‑based manure amendments.

The mechanisms by which gypsum reduces NH3 emissions may involve several interconnected chemical and microbial processes. First, gypsum supplies sulfate ions that interact with ammonium (NH4) to form less‐volatile complexes, such as ammonium sulfate (Kim et al., 2023; Tubail et al., 2008). These complexes reduce the pool of free NH3, thus reducing volatilization (Kirchmann & Witter, 1989; Sigurdarson et al., 2018). Second, the sulfate component can undergo microbial oxidation and hydrolysis reactions that generate hydrogen ions, lowering manure pH. Since NH3 volatilization escalates exponentially beyond pH 7, even slight reductions in pH can significantly suppress NH3 losses. This pH‑driven mechanism is well documented across slurry systems (Freney et al., 1981; Körner et al., 2001; Neerackal et al., 2017). Final manure characterization supported this mechanism. TS and VS levels declined across all treatments due to microbial decomposition, while the pH levels varied with gypsum dose. The pH of the control and G1 treatments showed less than a 1% change from their initial values, whereas the G2 treatments decreased by approximately 5%, making them more acidic than the control and G1 treatments. These changes over time align with the gas emission patterns observed in this experiment.

The magnitude of NH3 reduction observed here (28%–33%) aligns with the results reported by Owusu‐Twum et al. (2025) who evaluated the impact of sulfur‐based compounds, including sulfuric acid and lactogypsum. The mechanisms underlying the reduction of NH3 emissions require a period to establish chemical equilibria and microbial activity patterns. In this study, these effects were evident from day 40 onward, when the difference between the NH3 fluxes from the G2 treatments and the control group became distinct. This observation is consistent with the dynamic nature and response time involved in pH adjustment and ammonium complex formation (Kim et al., 2023; Kirchmann & Witter, 1989; Tubail et al., 2008).

For methane, the similarity in performance between the G2 treatments (82% vs. 90% CH4 reduction) suggests that a plateau effect may have been reached at the G2L treatment dose. Although the reductions observed here exceed those reported by Sauvé et al. (2025), the underlying pattern is consistent: sulfate‑based additives exhibit nonlinear dose responses, with diminishing returns once sulfate availability exceeds the metabolic capacity of SRB. The reductions in CH4 emissions in this study likely reflect the characteristics of the manure, the storage conditions, and the extended duration of the trial, all of which favor SRB establishment (Matos Pereira Lima et al., 2025; Sauvé et al., 2025).

These findings are also consistent with studies showing that sulfate‑based amendments such as sulfuric acid, aluminum sulfate, and lactogypsum can reduce CH4 emissions by 67%–91% in cattle slurry (Matos Pereira Lima et al., 2025; Owusu‐Twum et al., 2025). The mechanism of sulfur‐based manure additives is well established: sulfate serves as an alternative terminal electron acceptor, enabling SRB to outcompete methanogens for hydrogen and acetate. Once SRB dominates hydrogen utilization, methanogenesis is strongly suppressed (Matos Pereira Lima et al., 2025; Sauvé et al., 2025).

Research indicates that this competitive shift becomes more prominent after 30–50 days of storage, which aligns with the period during which differences between G2 treatments and control group fluxes were observed in this study (Matos Pereira Lima et al., 2025; Owusu‐Twum et al., 2025; Prado et al., 2020). The CH4 peak observed in the control and G1 treatments around day 50 aligns with the typical progression of methanogenic activity once anaerobic conditions stabilize and fermentable substrates accumulate (Owusu‐Twum et al., 2025; Prado et al., 2020). In contrast, the absence of a peak in the G2 treatments reflects stronger stimulation of SRB at higher sulfate dosages, which suppress methanogenesis throughout the storage period by outcompeting methanogens for shared substrates (Matos Pereira Lima et al., 2025; Sauvé et al., 2025).

The limited effectiveness of G1L and G1H contrasts with some studies reporting CH4 reductions at similar dosages. Chiodini et al. (2023) reported a 75% reduction in CH4 emissions using a dosage of 4 mg of SOP Lagoon, a gypsum‐derived product, per liter of slurry (4 g m−3). Peterson et al. (2020) observed that using the same additive at rates of 30–60 mg of SOP Lagoon per L of manure led to a reduction in CH4 emissions of up to 23%. This indicates a diminished mitigation potential compared to the findings of Chiodini et al. (2023), even when employing a dosage 15 times higher.

Several factors may account for the discrepancy observed between results obtained using a similar product at comparable rates. Manure characteristics may vary significantly across studies due to different cow diets and bedding materials, which affect TS and VS, and microbial communities in manure, requiring different amounts of sulfur to shift microbial competition. The characterization of TS content, as reported by Peterson et al. (2020), Chiodini et al. (2023), and this study, was 0.27%, 8.43%, and 5.4%, respectively, thereby demonstrating differences among the manures used and influencing treatment responses.

These differences in initial solids content are relevant because TS and VS determine the quantity of degradable organic matter available for methanogenesis. Manures with higher TS and VS contain a greater amount of fermentable substrate, which can support increased methane production unless microbial competition shifts markedly toward SRB (Ma et al., 2017; Sela‐Adler et al., 2017; Yi et al., 2014). Conversely, manure with a very low solids content may produce less methane, regardless of the additive dose, due to reduced substrate availability (Ma et al., 2017; Yi et al., 2014; Zhu et al., 2026). Consequently, the effects of treatment may vary or be less evident. Additionally, pH influences this process: lower pH levels diminish methanogenic activity regardless of the additive dose, and the treatment's impact may differ from that observed in manure at higher pH (Larson et al., 2026; Sokolov et al., 2019). Therefore, variations in initial TS, VS, and pH across studies can lead to inconsistent methane responses, even when gypsum is applied at comparable rates.

Additionally, the practice of mixing or agitating manure prior to measuring gas concentration, as described by Chiodini et al. (2023), may impact microbial activity, manure characteristics, and gas‐exchange dynamics, in contrast to conditions typically observed in manure storage on dairy farms in New York. In such storage settings, mixing generally occurs immediately before spreading rather than throughout the storage period. In this experiment, mixing was not performed to accurately simulate real storage conditions during the summer storage period, which is considered the period between spring spreading and fall spreading. During this summer period, CH4 emissions are expected to be the highest of the year; consequently, if a representative mitigation potential is achieved with the treatment during this period, the mitigation of gas emissions becomes more impactful on the cumulative yearly emissions. Together, these factors suggest that sulfate thresholds for effective CH4 suppression are influenced by substrate characteristics, management practices, and storage conditions.

While sulfate‑based amendments offer substantial mitigation potential, they also introduce considerations related to hydrogen sulfide (H2S) production. Increased sulfate availability can stimulate SRB activity, potentially elevating H2S concentrations under certain conditions. Although H2S was monitored as part of the safety protocol in this study and did not reach levels of concern, the potential for increased H2S generation should be acknowledged, particularly in enclosed or poorly ventilated storage environments and during agitation events (Fabian‐Wheeler et al., 2017). Future work should evaluate H2S dynamics alongside NH3 and CH4 to ensure that mitigation strategies do not introduce new occupational or environmental risks.

5. CONCLUSIONS

This study shows that gypsum can significantly reduce NH3 and CH4 emissions from dairy manure, offering a practical dual‑benefit strategy. Application rates of 5 g of gypsum (17% S) per liter of manure or higher lowered NH3 losses from dairy manure by 28%–33% and reduced cumulative CH4 emissions by 82%–90%. In contrast, the lower‑dose treatments (G1L and G1H) were ineffective, underscoring a clear dose‑‐response threshold below which sulfate availability is insufficient to influence nitrogen or carbon transformation pathways.

Overall, this work provides evidence that gypsum, a sulfur‐based manure additive, can be an effective tool for integrated mitigation of gaseous nitrogen and carbon emissions in dairy systems, thereby supporting the development of practical approaches to sustainable manure management. Future research should focus on optimizing application rates and evaluating economic feasibility and interactions with other management practices, including additive combinations.

AUTHOR CONTRIBUTIONS

Joel S. Tinoco: Conceptualization; data curation; formal analysis; investigation; methodology; software; visualization; writing—original draft; writing—review and editing. Emilia Perez: Data curation; Investigation; methodology; visualization; writing—review and editing. Karrigan Ellison: Data curation; methodology; resources; writing—review and editing. Kayli Tolk: Data curation; methodology; resources; writing—review and editing. Quirine M. Ketterings: Conceptualization; supervision; validation; visualization; writing—review and editing. Jason P. Oliver: Conceptualization; funding acquisition; investigation; methodology; project administration; supervision; validation; visualization; writing—review and editing.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

ACKNOWLEDGMENTS

This work was supported by Cornell Atkinson Center for Sustainability, The Nature Conservancy, and the Environmental Defense Fund. We are grateful to Dr. Joseph R. Sanford for his early support in understanding the operation and calibration of the gas analyzer, as well as for his guidance on the use of buckets as manure containers. Thanks to María José Oviedo Ventura for her invaluable support during this project. This research was conducted using facilities and other resources provided by the Department of Animal Science, College of Agriculture and Life Sciences, Cornell University.

Tinoco, J. S. , Perez, E. , Ellison, K. , Tolk, K. , Ketterings, Q. M. , & Oliver, J. P. (2026). Ammonia and methane mitigation from dairy manure using sulfur‐based manure storage additives. Journal of Environmental Quality, 55, e70309. 10.1002/jeq2.70309

Assigned to Associate Editor Qianying Yi.

DATA AVAILABILITY STATEMENT

Datasets are available from the corresponding author upon reasonable request.

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Data Availability Statement

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