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. 2025 Jul 7;54(6):1737–1745. doi: 10.1002/jeq2.70050

Late spring urea application increased apparent carbon dioxide equivalence emissions but fall and summer applications did not

G W Reicks 1, D E Clay 1,✉, S A Clay 1, D R Joshi 2, J Moriles‐Miller 1, S Westhoff 1, S A Bruggeman 3
PMCID: PMC12593255  PMID: 40624768

Abstract

Synchronizing nitrogen (N) fertilizer application with plant N uptake, as opposed to applying earlier, is believed to improve N use efficiency while simultaneously reducing nitrate leaching, ammonia volatilization, and greenhouse gas emissions. However, little research has been conducted to confirm that this is true. Therefore, this study's objective was to determine the effect of urea application date (early fall, mid‐fall, late fall, late spring, early summer, and midsummer) and rate (0 and 224 kg N ha−1) on the apparent carbon dioxide equivalence (CO2ea). This completely randomized field experiment was conducted six times (dates) where each treatment was replicated four times. Soil temperature and moisture along with greenhouse gases (N2O, CO2, and CH4,) were measured every 4 h for 21 days at Aurora, SD, in 2017 and 2018. N2O and CH4 were expressed in carbon dioxide equivalence, and all three gases were summed to CO2ea. Delaying the fertilizer from early to late fall decreased CO2ea from 69,375 to 18,420 g CO2ea (ha × day)−1. During late spring through midsummer, CO2ea were similar for the three application dates and averaged 101,500 g CO2ea (ha × day)−1. This study showed that the lowest CO2ea values for the 3 weeks following the application were associated with applying urea in the fall after the temperatures had decreased to less than 10°C or waiting until early summer. This research suggests that full‐season assessments of fall, spring, and summer urea application dates on CO2ea are warranted.

Core Ideas

  • The apparent carbon dioxide equivalent (CO2ea) was calculated by summing the CO2, N2O, and CH4 emissions.

  • Urea application increased CO2ea during late spring.

  • During spring and summer, soils had lower CH4 emissions but higher CO2 emissions than in fall.

  • The CO2ea following urea application needs to be confirmed with a full‐season assessment.

Abbreviations

CO2e

carbon dioxide equivalence

GHG

greenhouse gas

SOC

soil organic carbon

WFPS

water‐filled pore space

1. INTRODUCTION

Nitrogen (N) fertilizer is a major input in nonleguminous crop production and a direct source of N2O emissions. However, in addition to its direct impact on N2O, it may impact carbon dioxide and methane (CH4) emissions, which have 273 and 28 times the global warming potential of CO2, respectively (Smith et al., 2021). Understanding the sources and mechanisms of these emissions can aid in reducing the direct and indirect impact of N fertilizer on greenhouse gas (GHG) emissions (Dong et al., 2018; Eagle et al., 2017; Nazir et al., 2024).

It is widely believed that applying fertilizer when N demand is highest will simultaneously improve N use efficiency while reducing nitrate leaching, ammonia volatilization, and N2O emissions (Graham & Bly, 2016; Thies et al., 2020; Venterea et al., 2016). However, research supporting this hypothesis is limited. The research that has been conducted suggests that interactions among the soil properties, climatic conditions, and the fertilizer application date and source can increase or decrease the carbon dioxide equivalence (CO2e) (Clark et al., 2020; Holman et al., 2024; Joshi et al., 2022; Thies et al., 2020; Venterea et al., 2010). For example, (1) Clay et al. (1990) showed that the treatment of urea with a nitrification inhibitor can reduce nitrate leaching while increasing ammonia volatilization, (2) Brugler et al. (2025) showed that splitting the fertilizer between preemergence and the corn (Zea mays) V6 growth stage may reduce N2O emissions prior to V6 and increase emissions after V6, and (3) Thies et al. (2020) demonstrated that applying urea in the fall to a silty clay loam soil when soil temperatures are below 10°C may have less ammonia (NH3) volatilization and N2O emissions than spring applied N. Results from these studies indicate that to optimize N efficiency and minimize losses, strategies that optimize timing need to be identified. One area of potential research is to compare fall, spring, and summer applied fertilizers on GHG emissions.

Fall applied fertilizer is of particular interest because fertilizer is often cheaper in the fall (Graham & Bly, 2016; Mueller et al., 2017). Unfortunately, little research has been conducted on the impact of fall applied fertilizer on the CO2e. Filling this gap involves conducting an initial screening of the possible fertilizer application dates followed by future research to conduct a full‐season assessment. Therefore, this study's objective was to determine the effect of urea application date (early fall, mid‐fall, late fall, late spring, early summer, and midsummer) and rate (0 and 224 kg N ha−1) on CO2ea.

2. MATERIALS AND METHODS

This is the third study based on the dataset described below. The first study (Thies et al., 2019) compared the static chamber approach (Venterea & Coulter, 2015) with the near continuous methods used in this study. The second paper (Thies et al., 2020) reported on the impact of fertilizer timing and rate on NH3, N2O, and CO2 emissions. This paper expands on this analysis to include CH4 and CO2ea.

The study site was located near Aurora, SD (44° 18′ 20.57″ N, 96° 40′ 14.04″ W), and it was on the border between the Bsh (semiarid) and DFa (continental wet all seasons) Köppen climate groups. The soil was a well‐drained Brandt silty clay loam (Fine‐silty, mixed, superactive, frigid Calcic Hapludolls) (Soil Survey Staff, 2018) on a 0%–2% slope. The parent materials at the site were loess (0–60 cm) over glacial outwash. The surface 15 cm contained 280 g clay kg−1 (28%), 65 g silt kg−1 (65%), 7 g sand kg−1 (7%), and 36 Mg ha−1 (1.8%) of soil organic carbon (SOC). This soil has a textural discontinuity between 60 and 80 cm (silty clay loam to gravel) that slows deep drainage (D) below the discontinuity to near zero during the growing season. The gravimetric water contents at field capacity and the wilting point were approximately 0.315 and 0.177 g g−1, respectively. Additional findings from this study site are reported in Clay et al. (2005, 1996, 2015).

This was a completely randomized study design in which urea was applied at two rates (0 and 224 kg urea‐N ha−1) in early fall (September 21, 2017), mid‐fall (October 11, 2017), late fall (November 1, 2017), late spring (May 1, 2018), early summer (May 22, 2018), and midsummer (June 12, 2018). Each treatment was replicated four times.

2.1. Site preparation and sampling intervals

Soybeans (Glycine max) were planted at the site in May 2017. To prepare the soil for the experiment, the soybeans were terminated by mowing on September 14, 2017, and the terminated crop was removed from the site. N fertilizer had not been applied 1.5 years prior to the start of the experiment. The site had been a combination of tillage and no‐till for several years prior to the study. The experiment was conducted at six different application timings (Table 1), with gas emissions quantified for 21 days following application, except for late fall 2017, which ended after 14 days due to soil freezing. To start each timing, eight experimental units, made up of polyvinyl chloride rings, were inserted 5 cm into the soil. All rings were placed within 2 m of each other during each timing, and the experimental units were weed free. The experiment contained two N rates (0 and 224 kg N ha−1), where urea, 46‐0‐0, was dissolved in 10 mL of water and sprinkled onto the soil surface within each ring. The 0 kg N ha−1 treatment received the same amount of water, without urea. These applications were made on the first date of each application timing. For each subsequent timing, the rings were moved to another location within the trial site.

TABLE 1.

Average 7‐day soil temperatures, soil moisture, and water‐filled pore space (WFPS) for the surface 5 cm, the weekly amounts of rainfall and precipitation totaled over the study periods.

Timing Date range Soil temperature (°C) Soil moisture (cm3 cm−3) WFPS (cm3 cm−3) Precipitation (cm)
Early fall 2017 Sept. 21–27 17.5 0.44 (0.12–0.52) 0.857 11
Sept. 28–Oct. 4 15.2 0.45 (0.36–0.51) 0.877 6.5
Oct. 5–11 11.8 0.45 (0.34–0.49) 0.877 0.2
Average 14.8 0.45 0.870 17.7
Mid‐fall 2017 Oct. 11–18 10.9 0.32 (0.28–0.39) 0.624 0.3
Oct. 19–25 12.2 0.32 (0.25–0.45) 0.643 0
Oct. 26–Nov. 1 4 0.28 (0.18–0.45) 0.643 0.4
Average 9 0.31 0.637 0.7
Late fall 2017 Nov. 1–8 3.3 0.24 (0.23–0.26) 0.468 0.7
Nov. 9–15 2.2 0.24 (0.17–0.32) 0.468 0
Average 2.8 0.24 0.468 0.7
Late spring 2018 May 1–8 12.6 0.37 (0.36–0.41) 0.749 1.3
May 9–15 10.4 0.45 (0.28–0.41) 0.91 2.3
May 16–22 14.4 0.33 (0.30–0.42) 0.668 0
Average 12.5 0.38 0.776 3.6
Early summer 2018 May 22–29 21.9 0.27 (0.20–0.33) 0.546 0.3
May 30–June 5 18.9 0.27 (0.19–0.32) 0.546 1.2
June 6–12 18.5 0.26 (0.19–0.34) 0.526 0.9
Average 19.8 0.27 0.539 2.4
Midsummer 2018 June 12–19 21.1 0.29 (0.22–0.37) 0.546 2.3
June 20–27 18.9 0.34 (0.12–0.56) 0.465 4.2
June 28–July 4 21 0.36 (0.26–0.68) 0.607 3.8
Average 20.3 0.33 0.539 10.3
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Note: The time intervals shown are 0–7, 8–14, and 15–21 days after fertilizer application. The volumetric soil moisture in parenthesis represents the range in values over each study period. This table was modified from Theis et al. (2020).

2.2. GHG measurements

At the start of each fertilizer application timing, the LI‐COR LI‐8100‐104 long‐term opaque chambers (8100‐104 LI‐COR) were placed over each of the eight rings. Each N treatment was replicated four times, and each chamber was programmed to pivot over the enclosure for 15 min every 4 h. This measurement approach was in accordance with others (Brugler et al., 2025; Fiedler et al., 2021; Joshi et al., 2022; Reicks et al., 2021; Thies et al., 2019, 2020). The gas within the chamber was mixed, and a vent equalized the chamber and atmospheric pressures. All eight chambers were connected to a central Picarro Cavity Ringdown Spectrometer (model G2508; Picarro Inc.) that simultaneously measured CH4, N2O, and CO2 concentrations every second for 15 min. Sampling periods were from 0000 to 0230 h, 0400 to 0630 h, 0800 to 1030 h, 1200 to 1430 h, 1600 to 1830 h, and 2000 to 2230 h. The sampling protocols allowed for GHG sampling at the average (0930–1030 h), minimum (0530–0630 h), and maximum air temperatures (1330–1430 h) during each day (Thies et al., 2019). The original chamber sampling order was selected at random but remained constant for each application date. Flux values were calculated based on temporal changes in the gas concentration within the chambers using version 4.01 LI‐COR SoilFluxPro software (v. 4.01; LICOR). Fluxes were corrected for the air volume within each chamber, which has a volume of 314 cm2. Following convention, positive values indicate that the soil was a source, whereas negative flux values showed that the soil was a sink.

Core Ideas

  • The apparent carbon dioxide equivalent (CO2ea) was calculated by summing the CO2, N2O, and CH4 emissions.

  • Urea application increased CO2ea during late spring.

  • During spring and summer, soils had lower CH4 emissions but higher CO2 emissions than in fall.

  • The CO2ea following urea application needs to be confirmed with a full‐season assessment.

The Picarro Cavity Ringdown Spectrometer factory calibration was checked with N2O and CO2 standards at the beginning and end of each experiment. The standards were purchased from Airgas Specialty Gases (Airgas USA LLC). The N2O standards had concentrations of 0.378 and 149 ppm, whereas the CO2 standards had concentrations of 99.91 and 2998 ppm. The equation between the N2O standard and the factory calibrations, conducted prior to and following the experiments, was y = 0.02 + 1.013 × (standard), r 2 = 0.99. The equation between the CO2 standards and the factory calibration was y = −0.288 + 0.994, r 2 = 1.00.

Soil moisture and temperatures for the surface 5 cm were measured in areas adjacent to the chambers using the LI‐COR LI‐8150‐205 Soil Moisture Probe (LI‐COR) and the LI‐COR LI‐8150‐203 Soil Temperature Probe (LI‐COR), respectively. During the experiments, power outages or machine failures resulted in two short gaps (September 21 to 22 and May 1 to 2). Missing information was replaced with time‐appropriate information collected from adjacent chambers having the same treatment.

2.3. Soil sampling

To avoid soil sampling inside the treatment rings during the study, soil samples adjacent to the chambers that were treated identically to soil within the chambers were sampled. Composite (eight cores) surface (0–15 cm) soil samples were collected on days 0, 7, 14, and 21. Samples were air‐dried, ground, sieved, and analyzed for NH4 +‐N and NO3 −1–N (Clay et al., 2005; Kim et al., 2008). The soil bulk density of the surface 15 cm was 1.29 and 1.34 g cm3 for fall samples 2017 and spring/summer samples 2018, respectively. Bulk densities and volumetric water contents were used to calculate the water‐filled pore space (WFPS), using the assumption that soil particle density was 2.65 g cm−3. The bulk densities were then used to convert soil gravimetric values to volumetric values.

2.4. Data analysis

Methane was converted to CO2e by multiplying g CH4 m−2 by 27.9 and N2O emissions were converted to CO2e by multiplying g N2O m−2 by 273 (Smith et al., 2021). The apparent carbon dioxide equivalence (CO2ea) was determined by summing the CO2, CH4, and N2O (all expressed in CO2e) for the 21 days following urea application. The CO2ea term was used because it did not represent the full‐season emissions that could be identified as the CO2e.

Statistical analysis was conducted using the Agricolae package in R Studio (R Core Team, 2023). For the analysis of variance, the daily emission value from each chamber for a given application timing was conducted using a fixed effect model using the analysis of variance (aov) function in R Studio (Posit Team, 2023). Post hoc analysis was conducted using the Duncan test in the Agricolae Package of R Studio (de Mendiburu & Yaseen, 2023). When p‐values were <0.05, means were considered significantly different.

Correlation analysis was conducted between daily emissions and environmental values for fall and spring/summer values. For the fall correlations, information from early and mid‐fall was combined. For the spring/summer correlations, data from the late spring, early summer, and midsummer samples were combined.

3. RESULTS AND DISCUSSION

In 2017, soil temperatures decreased from 14.8°C in early fall to 2.8°C in late fall. Soil temperatures then increased in 2018 from 12.5°C in late spring to 19.8°C in early summer. Early summer and midsummer had similar soil temperatures (Table 1, Figures S1 and S2). These changes are expected in northern soils with a frigid climate regime. The measured soil moisture and calculated WFPS values were dependent on rainfall that varied during the study. For example, rainfall and WFPS were higher during the early fall than the mid‐ or late fall, whereas in 2018, WFPS was higher in the late spring than the early and midsummer.

3.1. Application date by N fertilizer rate interaction on CO2 and CO2ea

The CO2ea was influenced (p < 0.01) by a fertilizer application date and N fertilizer rate interaction (Table 2). This interaction occurred because late spring urea application increased total CO2ea, but the other application dates did not. This CO2ea increase during late spring was driven by a 35% increase in CO2 emissions (compared to unfertilized soil) in response to urea application. Conversely, urea application during midsummer reduced CO2 emissions by 23%. However, increased N2O emissions from the fertilizer during the midsummer offset the reduced CO2 emissions, leading to no significant difference in total CO2e between the fertilized and unfertilized soil.

TABLE 2.

The effect of the fertilizer application date and N rate on CO2ea derived from CO2, N2O, and CH4.

Application date N rate (kg N ha−1) CO2 a N2O CH4 Total CO2ea
g CO2ea (ha × day)−1
Early fall 0 66,578 4901 −48.5 71,431
Early fall 224 61,816 5810 −35 67,591
p‐value   0.67 0.5 0.4 0.77
Mid‐fall 0 42,554 1366 −45.1 43,875
Mid‐fall 224 49,482 1908 −54.3 51,336
p‐value   0.53 0.67 0.57 0.54
Late fall 0 11,306 120 −51.3 11,375
Late fall 224 20,639 120 −45.5 20,714
p‐value   0.49 0.99 0.8 0.49
Late spring 0 80,998 5403 −93.6 86,307
Late spring 224 109,463 6539 −94.9 115,907
p‐value   0.01 0.4 0.94 0.03
Early summer 0 111,059 987 −107 111,939
Early summer 224 89,777 2294 −64.6 92,006
p‐value   0.08 0.35 0.01 0.12
Midsummer 0 112,303 958 −90.1 113,171
Midsummer 224 86,536 3773 −64.9 90,244
p‐value   0.03 0.05 0.12  0.08
0 76,188 2486 −72.6 78,601
224 69,601 3407 −59.9 72,948
  p‐value 0.16 0.08 0.03 0.25
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Note: The total CO2ea is also provided.

Abbreviation: CO2ea, apparent carbon dioxide equivalence.

It is unclear why urea application increased CO2 emissions during late spring but decreased emissions in midsummer. Others have also observed higher CO2 emissions following soil thawing (Balewa et al., 2022; Reicks et al., 2021; Sennett et al., 2024; Su et al., 2024). One theory is that soil thawing, which normally occurs during March, can increase dissolved SOC concentrations, which can be subsequently mineralized and emitted as CO2 (Badewa et al., 2022; Maharjan et al., 2013). Since South Dakota soil temperatures typically remain cool through April, with minimal biological activity, the effects from thawing on CO2 emissions may have occurred in late spring (May 1–22). Ramirez et al. (2010) also reported an increase in CO2 emissions from urea applications but reported a decrease in CO2 emissions from non‐urea N fertilizers. These differences may be attributed to urea hydrolysis increasing the soil pH, which in turn increased dissolved SOC, followed by the mineralization and subsequent releases of the CO2 derived from the dissolved SOC (Clay et al., 1995; Clay et al., 1996; Curtin et al., 2016; Fender et al., 2012; Fiedler et al., 2021; Joshi et al., 2024; Liu et al., 1995; Sullivan et al., 2013).

The fertilizer application date findings suggest CO2ea can be minimized by applying the N in the fall when the soil temperatures are <10°C or during the summer. Others have reported that climatic conditions can impact emissions. For example, Brugler et al. (2025) reported urea to not increase CO2 emissions during the dry cool year of 2021 but increase CO2 emissions during the wet warmer year of 2022. While there is a general perception that N losses are greater in a fall application compared to spring applied N application, these results indicate that full‐season assessments of all possible application timings are warranted.

3.2. Application date effect on CH4, CO2, and CO2ea emissions

Fertilizer application timing influenced the relationships between the emitted gases. For example, in the fall and spring, a negative relationship was observed between CH4 and CO2 emissions (Table 4). This relationship indicates that increased CO2 (and CO2ea) emissions were often associated with decreased CH4 emissions (increasingly negative values). This was apparent during spring/summer when CO2 emissions were at their highest but CH4 emissions were at their lowest value (Table 3). During the fall, these trends reversed, and CO2 emissions were at their lowest and CH4 at their highest value. Others have reported that CO2 emissions increase with temperatures (Basheer et al., 2024; Buragiene et al., 2019), which we only observed during the fall. For example, CO2 emissions and CO2ea decreased from early fall to late fall. This decrease was attributed to soil temperatures that decreased from 14.8°C to 2.8°C over this period (Tables 1 and 3). However, there were no significant differences between late spring, early summer, and midsummer, even though the soil temperature rose from 12.5°C to 20.3°C. This was also shown in Table 4 where a correlation was observed between soil temperature and CO2 emissions during early and mid‐fall, but not during spring and summer.

TABLE 4.

Correlation coefficients (r) between soil temperature (°C), average daily CH4 emissions (g CO2ea ha−1), average daily CO2 emissions (g CO2ea ha−1), average daily N2O emissions (g CO2ea ha−1), average daily NH3 (g NH3‐N ha−1) emissions, soil NO3 − (kg‐N ha−1), and soil NH4 + (kg N ha−1) for fall (early fall and mid‐fall) and spring (early, mid‐, and late spring samples combined).

WFPS Soil temperature CH4 CO2 N2O NH3 Soil NO3 −
Early and mid‐fall
Soil temperature 0.49
CH4 0.31 −0.10
CO2 0.27 a 0.64 a −0.76
N2O 0.75 a 0.72 a −0.01 0.31
NH3 −0.07 a 0.23 a −0.21 0.30 −0.09
Soil NO3 − 0.30 0.16 0.19 0.00 0.44 0.18
Soil NH4 + −0.59 −0.33 −0.03 −0.25 −0.51 0.12 0.02
Spring and summer
Soil temperature −0.76
CH4 0.25 0.05
CO2 −0.16 a 0.13 a −0.50
N2O 0.69 a −0.60 a 0.09 −0.14
NH3 0.10 a −0.13 a 0.13 0.09 0.12
Soil NO3 − 0.05 −0.09 0.28 −0.25 0.44 0.14
Soil NH4 + −0.38 0.31 0.43 −0.26 0.05 0.22 0.63
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Note: Values in bold font are significant at p < 0.05.

Abbreviations: CO2ea, apparent carbon dioxide equivalence, WFPS, water‐filled pore space.

a

Originally reported in Thies et al. (2020).

TABLE 3.

The impact of fertilizer application timing on apparent carbon dioxide equivalence (CO2ea).

Application date N rate (kg N ha−1) CO2 N2O CH4 Total CO2ea
g CO2ea (ha × day)−1
Early fall 64,037b 4902a −41.8a 69,375b
Mid‐fall 45,862c 1498b −49.7a 47,475c
Late fall 18,482d 164b −47.5a 18,424d
Late spring 95,061a 5465a −94.2b 100,967a
Early summer 100,247a 1501b −85.8b 101,831a
Midsummer 99,249a 2165b −77.5b 101,565a
p‐value <0.01 <0.01 <0.01 <0.01
0 76,188 2486 −74.5 78,607
224 69,601 3407 −59.9 72,954
p‐value 0.16 0.08 0.03 0.25
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Note: Values within the same column followed by a different letter are different at p < 0.05. Values in bold indicate a significant main effect (p < 0.05) for the given variable.

High soil moisture levels during early fall, which were >0.85 WFPS for all 3 weeks (Table 1), may have contributed to the increased CH4 emissions relative to late spring (Table 3), even though these two timings had similar soil temperatures. van den Pol‐van Dasselaar et al. (1998) reported that the soil moisture range for maximum CH4 oxidation was between 20% and 35% (w/w), and that when soil moisture contents exceeded 50%, CH4 flux increased. These results were attributed to an anaerobic environment that was less favorable for methane oxidation and more favorable for methane‐producing methanogens (Bodelier & Laanbroek, 2004; Su et al., 2024). In our study, a positive correlation was shown between soil moisture and CH4 emissions for the fall and spring/summer application dates (Table 4).

3.3. N application effect on CH4 flux

In this study, CH4 emissions were 24.4% lower in the 0 than the 224 kg N ha−1 treatment (Table 3). These findings were attributed to the same enzyme, methane monooxygenase, catalyzing methane oxidation to methanol and ammonia oxidation to hydroxylamine (Aronson & Helliker, 2010; Arp et al., 2002). Therefore, when N is applied to the soil, methanotrophs can switch from CH4 to NH4 + as a substrate. When this happens, CH4 fluxes can increase. Evidence that this occurred was the positive correlations between CH4 emissions and soil NH4 + levels for the fall and spring/summer fertilizer application dates (Table 4). Aronson and Helliker (2010) suggested that this switch can occur when NH4 + fertilizer is applied at rates greater than 100 kg N ha−1 year−1.

3.4. Methane oxidation ability to offset N2O emissions

In central North America, many farms have a corn (Z. mays) followed by soybean (G. max) annual crop rotation. Our analysis suggests that during the soybean year when fertilizer is not applied, 9%–10% of the N2O emissions could be offset by reduced CH4 emissions during the early summer and midsummer (Table 3). However, it is important to note that the total CO2ea offset was practically zero from methane emission reductions. In a production setting, sufficient quantities of crop residue are often produced to offset all CO2 emissions from the soil. For example, Clay et al. (2015) reported a net positive SOC addition over a 5‐year period under three different continuous corn management systems at this same location. These findings are important and indicate the CH4 oxidation and crop residue additions should be considered when calculating CO2e.

4. SUMMARY

The results from this study showed that the N fertilizer application date impacts CO2ea. The CO2ea was higher for spring‐applied N but not for fertilizer applied at the other timings. The results from this study also showed that well‐drained agricultural soils can reduce GHG emissions by serving as a net CH4 sink (i.e., consuming more CH4 than emitting). CH4 oxidation was 84% greater during spring (May 1 to July 4, 2018) than during fall (September 21 to November 14, 2017). Across the N fertilizer rates and application timings, CH4 oxidation offset soil N2O emissions by 4.6% when both gases were adjusted to CO2e. During early and midsummer, CH4 oxidation offset N2O emissions by 9.6% when N fertilizer was not applied, and by 3.1% when N was applied. Findings from this study suggest that because fertilizer application date impacts CO2ea, full‐season research is warranted.

AUTHOR CONTRIBUTIONS

G. W. Reicks: Data curation; formal analysis; investigation; software; writing—original draft. D. E. Clay: Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; project administration; resources; supervision; validation; writing—original draft; writing—review and editing. S. A. Clay: Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; project administration; resources; supervision; validation; writing—original draft; writing—review and editing. D. R. Joshi: Data curation; formal analysis; investigation; software. J. Moriles‐Miller: Data curation; investigation; methodology. S. Westhoff: Visualization; writing—review and editing. S. A. Bruggeman: Data curation; investigation; methodology.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Supporting information

Supplementary Figure 1. A graphical depiction of the CH4 emission data collected during three fall timings in 2017 and three spring/summer timings in 2018. Urea was applied on the first date of application timing, which were early fall (September 21–October 11), mid‐fall (October 11–November 1), late fall (November 1–November 15), late spring (May 1–May 22), early summer (May 22–June 12), and midsummer (June 12–July 4). Each CH4 datapoint is an average of the four LI‐COR chambers from a given daily sampling period (i.e., from 0000 to 0230 h). There were six sampling periods per day.

Supplementary Figure 2. A graphical depiction of the CO2 emission data collected during three fall timings in 2017 and three spring/summer timings in 2018. Urea was applied on the first date of application timing, which were early fall (September 21–October 11), mid‐fall (October 11–November 1), late fall (November 1–November 15), late spring (May 1–May 22), early summer (May 22–June 12), and midsummer (June 12–July 4). Each CO2 datapoint is an average of the four LI‐COR chambers from a given daily sampling period (i.e., from 0000 to 0230 h). There were six sampling periods per day.

JEQ2-54-1737-s001.docx (1MB, docx)

ACKNOWLEDGMENTS

Partial support for this document was provided by South Dakota State University, NSF (2202706, 2026431), South Dakota Soybeans Research and Promotion Council, DOE, and USDA‐NRCS (69‐3A75‐285). The use of trade names is for the convenience of the reader and does not imply endorsement by the author.

Reicks, G. W. , Clay, D. E. , Clay, S. A. , Joshi, D. R. , Moriles‐Miller, J. , Westhoff, S. , & Bruggeman, S. A. (2025). Late spring urea application increased apparent carbon dioxide equivalence emissions but fall and summer applications did not. Journal of Environmental Quality, 54, 1737–1745. 10.1002/jeq2.70050

Assigned to Associate Editor Amitava Chatterjee.

REFERENCES

  1. Aronson, E. L. , & Helliker, B. R. (2010). Methane flux in non‐wetland soils in response to nitrogen addition: A meta‐analysis. Ecology, 91, 3242–3251. 10.1890/09-2185.1 [DOI] [PubMed] [Google Scholar]
  2. Arp, D. J. , Sayavedra‐Soto, L. A. , & Hommes, N. G. (2002). Molecular biology and biochemistry of ammonia oxidation by Nitrosomonas europaea . Archives of Microbiology, 178(4), 250–255. 10.1007/s00203-002-0452-0 [DOI] [PubMed] [Google Scholar]
  3. Badewa, E. A. , Yeung, C. C. , Rezanezhad, F. , Whalen, J. K. , & Oelbermann, M. (2022). Spring freeze–thaw stimulates greenhouse gas emissions from agricultural soil. Frontiers in Environmental Science, 10, Article 909683. 10.3389/fenvs.2022.909683 [DOI] [Google Scholar]
  4. Basheer, S. , Wang, X. , Farooque, A. A. , Nawaz, R. A. , Pang, T. , & Neokye, E. O. (2024). A review of greenhouse gas emissions from agricultural soil. Sustainability, 16(11), 4789. 10.3390/su16114789 [DOI] [Google Scholar]
  5. Bodelier, P. L. , & Laanbroek, H. J. (2004). Nitrogen as a regulatory factor of methane oxidation in soils and sediments. FEMS Microbial Ecology, 47(3), 265–277. 10.1016/S0168-6496(03)00304-0al [DOI] [PubMed] [Google Scholar]
  6. Brugler, S. , Clay, D. E. , Joshi, D. , Rizzo, D. M. , Clay, S. A. , Nleya, T. , & Hatfield, G. (2025). Does splitting the nitrogen rate for corn (Zea mays) reduce the carbon dioxide equivalence? Agronomy Journal, 117(1), e70025. 10.1002/agj2.70025 [DOI] [Google Scholar]
  7. Buragienė, S. , Šarauskis, E. , Romaneckas, K. , Adamavičienė, A. , Kriaučiūnienė, Z. , Avižienytė, D. , Marozas, V. , & Naujokienė, V. (2019). Relationship between CO2 emissions and soil properties of differently tilled soils. Science of the Total Environment, 662, 786–795. 10.1016/j.scitotenv.2019.01.236 [DOI] [PubMed] [Google Scholar]
  8. Clark, J. D. , Fernández, F. G. , Camberato, J. J. , Carter, P. R. , Ferguson, R. B. , Franzen, D. W. , Kitchen, N. R. , Laboski, C. A. M. , Nafziger, E. D. , Sawyer, J. E. , & Shanahan, J. F. (2020). Weather and soil in the US Midwest influence the effectiveness of single‐ and split‐nitrogen applications in corn production. Agronomy Journal, 112(6), 5288–5299. 10.1002/agj2.20446 [DOI] [Google Scholar]
  9. Clay, D. E. , Clay, S. A. , Liu, Z. , & Harper, S. S. (1995). Leaching of dissolved organic C in soil following anhydrous ammonia application. Biology and Fertility of Soils, 19, 10–14. 10.1007/BF00336339 [DOI] [Google Scholar]
  10. Clay, D. E. , Clay, S. A. , Lyon, D. J. , & Blumenthal, J. M. (2005). 13C discrimination in corn grain can be used to separate and quantify yield losses due to water and nitrogen stresses. Weed Science, 53, 23–29. 10.1614/WS-04-070R1 [DOI] [Google Scholar]
  11. Clay, D. E. , Clay, S. A. , Moorman, T. B. , Brix‐Davis, K. , Scholes, K. A. , & Bender, A. R. (1996). Temporal variability of organic C and nitrate in a shallow aquifer. Water Research, 30, 559–568. 10.1016/0043-1354(95)00198-0 [DOI] [Google Scholar]
  12. Clay, D. E. , Malzer, G. L. , & Anderson, J. L. (1990). Tillage and dicyandiamide influence nitrogen fertilizer immobilization, remineralization, and utilization by maize. Biology and Fertility of Soils, 9, 220–225. 10.1007/BF00336229 [DOI] [Google Scholar]
  13. Clay, D. E. , Reicks, G. , Carlson, C. G. , Moriles‐Miller, J. , Stone, J. J. , & Clay, S. A. (2015). Tillage and corn residue harvesting impact surface and subsurface carbon sequestration. Journal of Environmental Quality, 44, 803–809. 10.2134/jeq2014.07.0322 [DOI] [PubMed] [Google Scholar]
  14. Curtin, D. , Peterson, M. E. , & Anderson, C. R. (2016). pH‐dependence of soil organic solubility: Base type effects on dissolved organic C, N, P, and S in soil with contrasting mineralogy. Geoderma, 271, 161–172. 10.1016/j.geoderma.2016.02.009 [DOI] [Google Scholar]
  15. de Mendiburu, F. , & Yaseen, M. (2023). agricolae: Statistical Procedures for Agricultural Research (R package Version 1, 3‐7) [Computer software]. CRAN. https://cran.rproject.org/package=agricolae [Google Scholar]
  16. Dong, D. , Kou, Y. , Yang, W. , Chen, G. , & Xu, H. (2018). Effects of urease and nitrification inhibitors on nitrous oxide emissions and nitrifying/denitrifying microbial communities in a rainfed maize soil: A 6‐year field observation. Soil & Tillage Research, 180, 82–90. 10.1016/j.still.2018.02.010 [DOI] [Google Scholar]
  17. Eagle, A. J. , Olander, L. P. , Locklier, K. L. , Heffernan, J. B. , & Bernhardt, E. S. (2017). Fertilizer management and environmental factors drive N2O and NO3 losses in corn: A meta‐analysis. Soil Science Society of America Journal, 81(5), 1191–1202. 10.2136/sssaj2016.09.0281 [DOI] [Google Scholar]
  18. Fender, A.‐C. , Pfeiffer, B. , Gansert, D. , Leuschner, C. , Daniel, R. , & Jungkunst, H. F. (2012). The inhibiting effect of nitrate fertilisation on methane uptake of a temperate forest soil is influenced by labile carbon. Biology and Fertility of Soils, 48, 621–631. 10.1007/s00374-011-0660-3 [DOI] [Google Scholar]
  19. Fiedler, D. J. , Clay, D. E. , Joshi, D. R. , Engel, A. , Marzano, S. Y. , Jakubowski, D. , Bhattarai, D. , Reese, C. L. , Bruggeman, S. A. , & Clay, S. A. (2021). CO2 and N2O emissions and microbial community structure from fields that include salt‐affected soils. Journal of Environmental Quality, 50(3), 567–579. 10.1002/jeq2.20223 [DOI] [PubMed] [Google Scholar]
  20. Graham, C. , & Bly, A. (2016). Corn nitrogen timing . In Clay D. E., Carlson C. G., Clay S. A., & Byamukama E. (Eds.), iGrow corn: Best management practices (pp. 20‐1–20‐5). South Dakota State University. https://extension.sdstate.edu/sites/default/files/2019‐09/S‐0003‐20‐Corn.pdf [Google Scholar]
  21. Holman, J. D. , Ruiz Diaz, D. A. , Obour, A. K. , & Assefa, Y. (2024). Nitrogen fertilizer source, rate, placement, and application timing effect on sorghum (grain and forage) and corn grain yields. Agrosystems, Geosciences & Environment, 7(1), e20469. 10.1002/agg2.20469 [DOI] [Google Scholar]
  22. Joshi, D. R. , Miller, J. , Westhoff, S. , Reicks, G. , Daigh, A. , & Clay, D. E. (2022). Quantification and machine learning based N2O‐N and CO2‐C emissions predictions from a decomposing rye cover crop. Agronomy Journal, 116, 795–809. 10.1002/agj2.21185 [DOI] [Google Scholar]
  23. Joshi, D. R. , Moriles‐Miller, J. , Clay, S. A. , Reicks, G. , Westhoff, S. , & Clay, D. E. (2024). Rye cover crop had a nitrogen credit one year after termination. Journal of Soil Water and Conservation, 79, 261–267. 10.2489/jswc.2024.00097 [DOI] [Google Scholar]
  24. Kim, K.‐I. , Clay, D. E. , Carlson, C. G. , Clay, S. A. , & Trooien, T. (2008). Do synergistic relationships between nitrogen and water influence the ability of corn to use nitrogen derived from fertilizer and soil? Agronomy Journal, 100, 551–556. 10.2134/agronj2007.0064 [DOI] [Google Scholar]
  25. Liu, Z. , Clay, S. A. , Clay, D. E. , & Harper, S. S. (1995). Ammonia impacts on atrazine leaching through undisturbed soil columns. Journal of Environmental Quality, 24, 1170–1173. 10.2134/jeq1995.00472425002400060017x [DOI] [Google Scholar]
  26. Maharjan, B. , Venterea, R. T. , & Rosen, C. (2013). Fertilizer and irrigation management effects on nitrous oxide emissions and nitrate leaching. Agronomy Journal, 106(2), 703–714. 10.2134/agronj2013.0179 [DOI] [Google Scholar]
  27. Mueller, S. M. , Camberato, J. J. , Messina, C. , Shanahan, J. , Zhang, H. , & Vyn, T. J. (2017). Late‐split nitrogen applications increased maize plant nitrogen recovery but not yield under moderate to high nitrogen rates. Agronomy Journal, 109(6), 2689–2699. 10.2134/agronj2017.05.0282 [DOI] [Google Scholar]
  28. Nazir, M. J. , Li, G. , Nazir, M. M. , Zulfiqar, F. , Siddique, K. H. M. , Iqbal, B. , & Du, D. (2024). Harnessing soil carbon sequestration to address climate change challenges in agriculture. Soil & Tillage Research, 237, 105959. 10.1016/j.still.2023.105959 [DOI] [Google Scholar]
  29. Posit Team . (2023). RStudio: Integrated Development Environment for R. Posit software. PBC. http://www.rstudio.com/ [Google Scholar]
  30. R Core Team . (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.r‐project.org [Google Scholar]
  31. Ramirez, K. S. , Craine, J. M. , & Fierer, N. (2010). Nitrogen fertilization inhibits soil microbial respiration regardless of the form of nitrogen applied. Soil Biology and Biochemistry, 42, 2336–2338. 10.1016/j.soilbio.2010.08.032 [DOI] [Google Scholar]
  32. Reicks, G. W. , Clay, D. E. , Clay, S. A. , Joshi, D. R. , Moriles‐Miller, J. , Westhoff, S. , Daigh, A. L. , & Bruggeman, S. A. (2021). Winter cereal rye cover crop decreased nitrous oxide emissions during early spring. Agronomy Journal, 113, 3900–3909. 10.1002/agj2.20658 [DOI] [Google Scholar]
  33. Sennett, L. B. , Brin, L. D. , Goyer, C. , Zebarth, B. J. , & Burton, D. L. (2024). Effects of soil water content at freezing, thaw temperature, and snowmelt infiltration on N2O emissions and denitrifier gene and transcript abundance during a single freeze‐thaw event. Biology and Fertility of Soils, 60(4), 577–591. 10.1007/s00374-024-01817-w [DOI] [Google Scholar]
  34. Smith, C. , Nicholls, Z. R. J. , Armour, K. , Collins, W. , Forster, P. , Meinshausen, M. , Palmer, M. D. , & Watanabe, M. (2021). The Earth's energy budget, climate feedbacks, and climate sensitivity supplementary material. In Masson‐Delmotte V., Zhai P., Pirani A., Connors S. L., Péan C., Berger S., Caud N., Chen Y., Goldfarb L., Gomis M. I.,Huang M., Leitzell K., Lonnoy E., Matthews J. B. R., Maycock T. K., Waterfield T., Yelekçi O., Yu R., & Zhou B. (Eds.), Climate change 2021: The physical science basis. Contribution of working group I to the sixth assessment report of the Intergovernmental Panel on Climate Change (p. 16). IPCC. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Chapter07_SM.pdf [Google Scholar]
  35. Soil Survey Staff . (2018). Web soil survey. United States Department of Agriculture Natural Resources Conservation Service. https://websoilsurvey.sc.egov.usda.gov/ [Google Scholar]
  36. Su, Y. , Liu, W. , Rahaman, M. H. , Chen, Z. , & Zhai, J. (2024). Methane emission from water level fluctuation zone of the Three Gorges Reservoir: Seasonal variation and microbial mechanism. Science of the Total Environment, 912, 168935. 10.1016/j.scitotenv.2023.168935 [DOI] [PubMed] [Google Scholar]
  37. Sullivan, B. W. , Selmants, P. C. , & Hart, S. C. (2013). Does dissolved organic carbon regulate biological methane oxidation in semiarid soils? Global Change Biology, 19, 2149–2157. 10.1111/gcb.12201 [DOI] [PubMed] [Google Scholar]
  38. Thies, S. , Bruggeman, S. , Clay, S. A. , Mishra, U. , Hatfield, G. , Kumar, S. , & Clay, D. E. (2019). Midmorning point sampling may not accurately represent nitrous oxide emission following fertilizer application. Soil Science Society of America Journal, 83, 339–347. 10.2136/sssaj2018.08.0313 [DOI] [Google Scholar]
  39. Thies, S. , Joshi, D. R. , Bruggeman, S. A. , Clay, S. A. , Mishra, U. , Morile‐Miller, J. , & Clay, D. E. (2020). Fertilizer timing affects nitrous oxide, carbon dioxide, and ammonia emissions from soil. Soil Science Society of America Journal, 84, 115–130. 10.1002/saj2.20010 [DOI] [Google Scholar]
  40. van den Pol‐van Dasselaar, A. , van Beusichem, M. L. , & Oenema, O. (1998). Effects of soil moisture content and temperature on methane uptake by grasslands on sandy soils. Plant and Soil, 204, 213–222. 10.1023/A:1004371309361 [DOI] [Google Scholar]
  41. Venterea, R. T. , & Coulter, J. A. (2015). Split application of urea does not decrease and may increase nitrous oxide emissions in rainfed corn. Agronomy Journal, 107(1), 337–348. Portico. 10.2134/agronj14.0411 [DOI] [Google Scholar]
  42. Venterea, R. T. , Coulter, J. A. , & Dolan, M. S. (2016). Evaluation of intensive “4R” strategies for decreasing nitrous oxide emissions and nitrogen surplus in rainfed corn. Journal of Environmental Quality, 45, 1186–1195. 10.2134/jeq2016.01.0024 [DOI] [PubMed] [Google Scholar]
  43. Venterea, R. T. , Dolan, M. S. , & Ochsner, T. E. (2010). Urea decreases nitrous oxide emissions compared with anhydrous ammonia in a Minnesota corn cropping system. Soil Science Society of America Journal, 74(2), 407–418. 10.2136/sssaj2009.0078 [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1. A graphical depiction of the CH4 emission data collected during three fall timings in 2017 and three spring/summer timings in 2018. Urea was applied on the first date of application timing, which were early fall (September 21–October 11), mid‐fall (October 11–November 1), late fall (November 1–November 15), late spring (May 1–May 22), early summer (May 22–June 12), and midsummer (June 12–July 4). Each CH4 datapoint is an average of the four LI‐COR chambers from a given daily sampling period (i.e., from 0000 to 0230 h). There were six sampling periods per day.

Supplementary Figure 2. A graphical depiction of the CO2 emission data collected during three fall timings in 2017 and three spring/summer timings in 2018. Urea was applied on the first date of application timing, which were early fall (September 21–October 11), mid‐fall (October 11–November 1), late fall (November 1–November 15), late spring (May 1–May 22), early summer (May 22–June 12), and midsummer (June 12–July 4). Each CO2 datapoint is an average of the four LI‐COR chambers from a given daily sampling period (i.e., from 0000 to 0230 h). There were six sampling periods per day.

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