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Article

Elevated O3 Reduces Nitrogen Oxide Emissions from Rice Paddy Fields Under Warming

by
Xin Zhong
1,2,
Bo Shang
1,2,*,
Evgenios Agathokleous
1,2,
Yujie Zhang
2,3 and
Zhaozhong Feng
1,2,*
1
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China
2
Key Laboratory of Ecosystem Carbon Source and Sink, China Meteorological Administration (ECSS-CMA), School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
3
Beijing Weather Forecast Center, Beijing 100091, China
*
Authors to whom correspondence should be addressed.
Agronomy 2026, 16(6), 623; https://doi.org/10.3390/agronomy16060623
Submission received: 30 January 2026 / Revised: 4 March 2026 / Accepted: 12 March 2026 / Published: 15 March 2026
(This article belongs to the Section Farming Sustainability)
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Abstract

Elevated tropospheric ozone (O3) and global warming can affect nitrous oxide (N2O) and nitric oxide (NO) emissions from rice paddies, but their interactive effect is poorly understood. Two-year field observations of soil properties were implemented to quantify the impact of elevated O3 and warming on N2O and NO fluxes and identify dominant regulatory factors. Results indicated that elevated O3 reduced N2O and NO fluxes, whereas warming increased N2O and NO fluxes, relative to respective ambient conditions. The combined O3 elevation and warming treatment resulted in reductions in N2O and NO fluxes compared to the warming treatment. The N2O and NO emissions under elevated O3 and warming were primarily associated with significant changes in soil dissolved organic carbon (DOC) and NH4+. Furthermore, under warming treatment, N2O and NO emissions were also linked to significant variations in soil NO3−, but were independent of soil microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and pH. This study found that high O3 concentrations significantly suppress nitrogen oxide emissions from paddy fields under warming. This suppression necessitates the explicit integration of O3 into agroecosystem emission prediction frameworks for accurate estimation of nitrogen oxide fluxes.

1. Introduction

Nitrous oxide (N2O) is a greenhouse gas with significant potency and longevity and an atmospheric residence time of roughly 120 years [1]. Compared to carbon dioxide (CO2), the global warming potential (GWP) of N2O is 273 times higher per kilogram of gas [2]. In addition to facilitating surface temperature increase, N2O can also exacerbate stratospheric ozone (O3) depletion through a series of chemical reactions, leading to heightened ultraviolet radiation at the Earth’s surface [3]. Nitric oxide (NO) is an indirect greenhouse gas and an important precursor to tropospheric O3. Elevated surface concentrations of nitrogen oxides (N2O and NO) disrupt soil invertebrate-mediated decomposition processes, reduce plant photosynthetic efficiency, and ultimately impair carbon (C) sequestration capacity and trophic stability within agroecosystems [4,5].
Much of the world relies on rice as a staple food, with 90% of global rice production coming from Asia [6]. Rice demand is expected to grow by 28% by 2050 [7,8]. In order to meet the needs of paddy fields, a large amount of nitrogen (N) fertilizer must be applied, which leads to significant N2O and NO emissions [9]. Rice paddies account for 11% of the global agricultural N2O emissions [10], while it has been estimated that about 20% of N2O emissions from paddy fields in the world come from China [11]. Although NO emissions from paddy fields are relatively low, 20% of the world’s rice cultivation area is located in China [11], reflecting a large amount of NO emissions, with an average rate of 0.53 ± 0.11 kg N ha−1 yr−1 in China’s paddy fields [4]. The biogenic N2O and NO in soil are mainly derived from nitrification and denitrification processes [12,13]. N2O and NO are produced as intermediate products in the nitrification process, which requires the participation of oxygen (O2). The denitrification process is mainly carried out in the sub-oxic environment, and the NO3− is gradually reduced to NO and N2O [14]. The production of nitrogen oxide emissions from paddy soils is governed by soil temperature, moisture, and substrate concentration, which affect the underlying nitrification and denitrification processes [15], and climate change affects these regulatory factors. Consequently, how climate change influences N2O and NO emissions from paddy soils warrants investigation.
China faces significant challenges with ground-level O3 pollution. Since 2013, the concentration of O3 in the surface layer of China has been elevated, especially in summer [16,17,18]. High O3 exposures not only harm human health and plant growth but also indirectly degrade soil ecosystems through plant-mediated pathways [19,20,21]. Elevated O3 reduces the photosynthetic capacity of plants, inhibits the translocation of photosynthetic products to the belowground part, and changes the structure and function of soil physical and chemical properties as well as of microbial communities [22,23]. Studies indicate that elevated O3 suppresses the input of soil root exudates and litter, thereby diminishing labile soil N and C (e.g., NH4+ and dissolved organic carbon (DOC)) [22,24]. This reduction in substrates and energy in the N cycle, along with decreased microbial activity, consequently inhibits soil N2O and NO production. Previous studies have reported that elevated O3 (42.6 ppb) reduced the average N2O flux from rice paddies by 11.8% compared to the ambient control (33.7 ppb) under fully open-air conditions [25]. In soil, N2O and NO mainly arise from nitrification and denitrification, and elevated O3 is anticipated to have a parallel effect on NO and N2O emissions [26]. However, the underlying mechanisms of nitrogen oxide emissions remain unidentified in previous studies. Hence, the primary determinants controlling N2O and NO fluxes under elevated O3 remain to be elucidated.
Global warming intensifies greenhouse gas emissions from agricultural systems, representing a critical challenge for sustainable food production [27]. It is expected that from 2015 to 2060, the temperature during China’s rice season will rise by about 1.4 °C [27]. Warming governs key processes in soil C and N dynamics. These include increased plant-derived C input in soil, a shift in microbial metabolism from anabolism to catabolism, decreased microbial biomass C (MBC) and microbial biomass N (MBN), and higher DOC and inorganic nitrogen (NH4+ and NO3−) availability, leading to elevated nitrification and denitrification rates and increased soil nitrogen oxide emissions [28,29,30]. An integrated analysis found that under field conditions, 1 °C warming in paddy fields leads to an average increase of 11.7% in N2O emissions [31], and the response of NO emissions in wetlands to warming was similar [26]. However, few studies have examined the response of NO emissions to warming in paddy fields, which presents a research gap.
Warming promotes the emission of O3 precursors (nitrogen oxides (NOx) and volatile organic compounds) and increases tropospheric O3 concentrations [32,33,34]. Warming and elevated tropospheric O3 concentrations often co-occur, particularly in agricultural areas [35]. In wheat fields, high O3 concentration significantly inhibited the warming-induced stimulation of N2O and NO emissions [36,37]. However, paddy and wheat fields differ highly in water management practices, and it remains unclear how the combined treatment of elevated O3 and warming affects nitrogen oxide emissions from paddy fields.
In this study, in situ longitudinal measurements of nitrogen oxide (N2O and NO) emissions from paddy fields were studied under individual and combined treatments of elevated O3 and warming over two consecutive years, within an Ozone–Temperature Free-Air Controlled Elevation system (O3–T–FACE), coupled with measurements of soil properties. We hypothesized that (1) elevated O3 and warming would significantly affect N2O and NO emissions during a specific phase of rice growth, rather than the entire period [37]; (2) since high O3 concentration and warming had opposite effects on soil C and N cycling [24,29], elevated O3 could alleviate the warming-induced stimulation of nitrogen oxides in paddy soil; and (3) the primary driver of nitrogen oxide emissions from paddy fields is the fluctuation in mineral nitrogen substrates (NH4+, NO3−), which fuel the microbial production of these gases in paddy fields.

2. Materials and Methods

2.1. Experimental Site

The study was conducted in Wuqiao Town, Yangzhou City, Jiangsu Province, China. Located in a subtropical marine climate zone, the site recorded an average annual temperature of 16.0 °C and precipitation of 1131 mm during 1991–2020. The soil is characterized by a sandy–loam texture, with a soil organic carbon of 14.0 ± 0.8 g kg−1, a pH of 6.5, and a C/N ratio of 10.2.

2.2. The O3–T–FACE System

The O3–T–FACE system consisted of eight plots. Four octagonal rings with a diameter of 14 m (hereinafter called E–O3 rings) were exposed to high O3 concentrations, and the other four identical plots were exposed to ambient O3 concentration (hereinafter called A–O3 rings). All rings were at least 50 m apart from each other to prevent mutual interference in the process of O3 diffusion. In addition, the soils in all rings were uniform, and there was no slope. The O3 concentration was elevated by 50% in the E–O3 rings compared to the A–O3 rings, which was automatically adjusted by a computer software system. O3 elevation was operated daily between 08:00 and 18:00 in the E–O3 rings, but suspended when precipitation occurred. The treatment was applied from 15 July to 27 October in both 2022 and 2023. Due to the different number of rainy days between years, the effective treatment period lasted 84 and 85 days, respectively. During the 2022 rice season, the average daytime 10 h (8:00–O3 concentration (M10) was 56.7 ± 1.5 ppb in the E–O3 rings and 39.2 ± 0.4 ppb in the A–O3 rings. During the 2023 rice season, these values were 44.1 ± 1.0 ppb and 29.5 ± 0.2 ppb, respectively. The O3 concentration was 44.6% and 49.5% higher, respectively, in 2022 than in 2023.
Within each ring, separate 3 × 3 m subplots were established for ambient temperature and warming. The heating system comprised three 2000 W infrared lamps (HS–2420, Kalglo Electronics Inc., Bethlehem, PA, USA; 1.65 m long, 0.14 m wide) arranged triangularly. Positioned 1.5 m above the rice canopy initially, they supplied round-the-clock warming, and their mounting height was maintained according to canopy growth. This study included four treatments: a control (CK) under ambient conditions, an elevated O3 treatment (E–O3), a warming treatment (W), and a combined treatment with both elevated O3 and warming (E–O3W). Each treatment had four replicates. During the 2022 rice season, the average canopy temperatures in the warming subplots and the ambient temperature subplots were 25.2 ± 0.5 °C and 24.1 ± 0.2 °C, respectively. In 2023, the values were 25.7 ± 0.4 °C and 24.2 ± 0.2 °C. Over the two years, canopy temperatures in the warming subplots increased by 1.1 °C and 1.5 °C, respectively. During the 2022 rice season, the average soil temperatures in the warming subplots and the ambient temperature subplots were 26.2 ± 0.5 °C and 25.2 ± 0.5 °C, respectively. In 2023, the values were 25.7 ± 0.3 °C and 24.6 ± 0.3 °C. Over the two years, soil temperatures in the warming subplots increased by 1.0 °C and 1.1 °C, respectively.

2.3. Field Plot Experimental Design and Management

This study cultivated the common rice variety ‘Nangeng 9108’. Seeds were annually sown on May 20 and transplanted by hand into each subplot on June 25, which was designated as 1 day after transplanting (1 DAT). Rice phenological stages under different treatments are presented in Table S1. One permanent fixed base (0.5 × 0.5 m) was placed within each subplot, and each base with six planted hills was positioned at least 0.5 m from the subplot edge. The same planting density and fertilization practices were adopted both inside and outside the base. Information about the fertilizer management is provided in Table S2. The fields were maintained under continuous flooding from transplanting to late July. Mid-season aeration was implemented from late July to mid-August. After re-flooding, the soil only remained moist and no longer flooded.

2.4. Gas and Soil Sampling

From transplanting until harvest, gas samples were taken weekly, with an additional sample collected within one week after fertilization. Two non-transparent sampling chambers (0.5 × 0.5 × 0.6 m) were mounted onto the fixed base. To ensure an airtight seal, water was added to the edge of the middle chamber and the base, preventing any gas exchange. Gas samples were collected using an automatic sampler (Hilintec Inc., Chengdu, China) at 1, 7, 13, and 19 min after sealing the chamber, and 1 L of gas was sampled and transferred into specialized 1 L multilayer aluminum–film bags (Delin, Dalian, China). N2O and NO concentrations were determined using a gas chromatograph (Agilent 8860; Agilent Technologies, Santa Clara, CA, USA) and a 42i chemiluminescence analyzer (Thermo Fisher Scientific, USA), respectively. Gas concentrations from four time points within the same chamber were fitted to a linear regression with r2 > 0.85 over time, and the flux was calculated from the slope:
F = ρ × ( d c / d t ) × 273 / ( 273 + t ) × H
where F is gas flux (mg m−2 h−1), ρ is gas density under standard state (N2O: 1.25 kg m−3; NO: 1.339 kg m−3), dc/dt is the regression line slope (nL L−1 h−1), t is the chamber temperature in the gas-sampling period (°C), and H is the effective chamber height (m).
The formula for estimating N2O and NO emissions reductions from Chinese rice paddies was as follows:
R = ( A w − A E − O 3 W ) × S
where R represents nitrogen oxide emission reduction, AW is cumulative nitrogen oxide emissions under W treatment, AE-O3W is cumulative nitrogen oxide emissions under E–O3W treatment, and S is China’s rice field area. Data on rice cultivation areas across Chinese provinces were sourced from the National Bureau of Statistics of China website (https://data.stats.gov.cn/) [38].
Soil sampling was conducted in conjunction with gas collection. Before sampling, five points were randomly selected in the circle for testing, and the results showed that the soil composition in the circle was uniform. In addition, there was no slope in the area, and the water management measures were the same. In 2022, soil was sampled weekly, switching to a biweekly schedule in 2023. Per sampling event, each subplot was sampled at 0–15 cm depth with three random soil cores, maintaining a minimum distance of 1 m from any edge or fixed installation. Samples from a given subplot were pooled to form a composite sample. Soil properties were uniform both within and outside the base. Soil moisture content (SMC) is shown in Figure S1 and Table S3. From each composite sample, one aliquot was allocated to archival freezing (−20 °C) and another to air-drying at room temperature, followed by grinding and 2 mm sieving. Soil DOC, NH4+, NO3−, MBC, MBN, and pH were determined separately. Zheng et al. [39] described the determination methods. Soil property data, which have previously been published [40], are presented in Figures S2 and S3.

2.5. Statistical Analysis

JMP (V11.0) was employed for linear mixed-effect model (LMM) analysis and Tukey’s HSD post hoc test. Each sampling data was analyzed using an LMM to assess the main effects of elevated O3 and “warming” (treated as a continuous variable) on nitrogen oxide fluxes and soil properties, as well as their interaction, with year as a fixed factor and plot as a random factor. Each time-series data was investigated using LMM to parse the main effects of elevated O3, “warming” (treated as a continuous variable), and year, as well as their interactions, with both plots and subplots treated as random effects. Tukey’s HSD post hoc test was used to compare the mean values of each treatment group. Statistical significance was defined as p ≤ 0.05.
R (V4.3.0) was used to construct random forest (RF) models and structural equation models (SEM) [41]. We employed the “rfPermute” (V2.5.5) and “randomForest” (V4.7–1.2) packages to construct a random forest model, using nitrogen oxide fluxes (N2O and NO fluxes) as response variables and soil properties (DOC, MBC, MBN, NH4+, NO3− and pH), along with environmental factors (canopy temperature and soil moisture content) as predictor variables. The output of RF includes an Increase in Mean Squared Error (Increase in MSE) and p-values. A higher Increase in MSE value indicates greater importance of the predictor variable in the model. Permutation-based variable importance analysis identified significant predictors influencing nitrogen oxide fluxes at a level of p ≤ 0.05. Based on RF results, significant predictors were incorporated into a SEM using “elevated O3” and “warming” as exogenous variables, and nitrogen oxide fluxes, soil properties, and environmental factors as endogenous variables. The SEM was constructed with the “lavaan” package (V0.6–19) to evaluate direct and indirect effects of exogenous variables on nitrogen oxide fluxes. Before constructing the SEM, the normality of all endogenous variables was examined, with conversion applied as needed. Model optimal fit was evaluated using the minimum parameter set, with the optimal model determined by non-significant chi-square tests (p > 0.05), a CFI exceeding 0.95, and an RMSEA below 0.05 [42].

3. Results

3.1. Seasonal N2O and NO Fluxes

The CK, E–O3, W, and E–O3W treatments resulted in mean seasonal N2O fluxes of 92.2, 75.8, 107.3, and 88.5 mg m−2 h−1, respectively. There were no significant annual differences in the effects of E–O3 and W on N2O fluxes (Table 1). Compared to CK, N2O fluxes showed significant decreases of 16.7–18.9% under E–O3 and increases of 15.0–17.6% under W. Under warming, elevated O3 significantly suppressed N2O fluxes by 20.2% at 38 DAT in 2023 (Figure 1).
NO flux remained low during the rice flooding period (tillering to jointing stage). At the heading stage in 2022, there was a clear upward trend in NO flux (66 DAT in 2022), which did not appear at the heading stage in 2023 (Figure 2). The CK, E–O3, W, and E–O3W treatments resulted in mean seasonal NO fluxes of 8.7, 7.1, 10.9, and 9.1 mg m−2 h−1, respectively. No significant interannual differences in NO flux were found (Table 1). Compared to CK, NO fluxes showed significant decreases of 15.2–23.0% under E–O3 and increases of 15.2–45.9% under W. Under warming, elevated O3 significantly suppressed NO emission fluxes at 58 DAT in 2023 by 18.9% (Figure 2).

3.2. Effects of Soil Properties on Nitrogen Oxide Emissions

The random forest model indicated that the same significant regulators control both N2O and NO fluxes in paddy fields, and soil microbial biomass carbon (MBC) was a non-significant factor (Figure 3). Structural equation modeling incorporating the significant regulatory factors indicated that elevated O3 directly influenced N2O flux by mediating soil NH4+ and pH (Figure 4a). It also indirectly affected N2O fluxes by influencing NH4+ and NO3− through its impact on soil dissolved organic carbon (DOC) content. Soil DOC can also indirectly affect microbial biomass nitrogen (MBN) through NO3−, and, ultimately, alter N2O fluxes. Warming directly influenced N2O fluxes by mediating soil NH4+. It also indirectly modified N2O fluxes by influencing soil NH4+ through its effects on canopy temperature and soil DOC (Figure 4a). Warming can also affect N2O fluxes by indirectly affecting NO3−, MBN, and pH (Figure 4a). Soil pH and MBN exerted negative total effects on soil N2O fluxes, whereas soil DOC, NH4+, and NO3− exerted positive total effects on N2O fluxes (Figure 4b).
For NO, elevated O3 directly affected NO flux by altering soil pH. It also influenced soil NH4+, NO3−, and MBN by affecting soil DOC, thereby indirectly regulating NO flux (Figure 4c). Warming indirectly affected NO flux by influencing soil moisture content, NH4+, NO3−, MBN, and pH through its effects on canopy temperature and soil DOC (Figure 4c). The total effect of soil properties on NO flux was similar to that observed for N2O (Figure 4d).

3.3. Estimating Nitrogen Oxide Emission Reduction in Chinese Rice Paddies

This study further estimated the potential for nitrogen oxide emissions reduction in Chinese rice paddies under elevated O3 and warming (Figure 5). Elevated O3 and warming reduced N2O emissions by 7.6 and 12.5 Gg N yr−1 (Figure 5b) and NO emissions by 0.7 and 0.7 Gg N yr−1 (Figure 5b) during the rice seasons of 2022 and 2023, respectively. Overall, an estimated annual reduction of 8.3–13.2 Gg N in nitrogen oxide emissions from China’s mainland paddy fields is attributable to the combination of elevated O3 and warming.

4. Discussion

In this study, the fluxes of nitrogen oxides (N2O and NO) in paddy fields fluctuated greatly across different rice growth stages (Figure 1 and Figure 2). Nitrogen oxide emissions exhibited an upward trend after booting and panicle fertilization as well as during the filling stage [25,43]. The production of biogenic N2O and NO in soil originates primarily from the processes of nitrification and denitrification [44]. Re-irrigation and fertilization after mid-season aeration (35–45 DAT in 2022 and 2023) stimulated nitrogen cycle-related microbial activity, and urea hydrolysis to NH4+ provided substrates that enhanced N2O and NO production (40–50 DAT in 2022 and 2023) [38]. The paddy soil remained moist but unflooded after booting, and panicle fertilization further stimulated emissions (65–70 DAT in 2022). During the filling stage, the decomposition of rice ineffective tiller residues and fine roots contributed to increased plant-derived C input [45], stimulating microbial activity and N2O emissions. However, no increase in nitrogen oxide emissions was observed after fertilization at the tillering stage (10 DAT in 2022 and 2023). The soil was flooded at the tillering stage, which reduced the supply of O2 during nitrification. The flooded layer hindered the diffusion of nitrogen oxides into the atmosphere, and the N2O and NO produced by denitrification were further reduced to nitrogen (N2); thus, there was no large amount of nitrogen oxide emission from the tillering stage to the jointing stage [12,13]. Additionally, due to the continuous precipitation between 60 and 80 DAT in 2023, the field water accumulation was severe, resulting in no obvious nitrogen oxide emission after applying fertilizer.

4.1. Effects of Elevated O3 on Nitrogen Oxide Emissions in Paddy Fields

Elevated O3 significantly reduced nitrogen oxide fluxes in paddy fields, and there was no significant difference between different years (Table 1). Compared to CK, E–O3 significantly reduced N2O fluxes by 18.3%, which was similar to the reduction reported by another study (−17.8%) [46], but higher than that reported by Tang et al. (−11.8%) [25]. This discrepancy might occur because the average O3 exposure concentration in the elevated O3 subplots of this study (50.4 ppb) was higher than the concentration in the previous study (42.6 ppb), and the duration of high concentration O3 exposure during the day in this study (10 h) was higher than that in the previous study (7 h) [25]. E–O3 also significantly reduced NO flux by 17.9%, which was lower than a previous wheat field study (−34.6%) [37]. This may be caused by different O3 concentrations between rice and wheat seasons. The ambient (44.4 ppb) and elevated (64.7 ppb) O3 concentrations in the wheat field study were higher than the respective (34.4 and 50.4 ppb) O3 concentrations in the rice field study. The increase in O3 concentration in wheat fields (20.3 ppb) was higher than that in rice fields (16.0 ppb) [37]. Elevated O3 limited crop photosynthetic capacity and growth [47], and significantly reduced crop biomass (including both aboveground and belowground biomass) [25]. In the previous study with wheat in this experimental site, aboveground biomass of wheat was significantly reduced under elevated O3 [48,49], which may lead to a significant reduction in plant-derived soil C input. Secondly, elevated O3 typically lessens photosynthetic products allocated to the belowground part, reduces root exudates, and weakens the metabolic capacity of heterotrophic microorganisms [50], eventually leading to a decrease in soil active carbon and nitrogen content [24]. Thirdly, elevated O3 may affect plant size, which influences stomatal number and ultimately alters gas transport. Therefore, future studies can focus on changes in the aboveground parts of plants.
Soil microorganisms are considered to be limited by C availability [51]. Low soil C input leads to a decrease in the substrates used by microorganisms for their own synthesis, and the assimilation ability is weakened, resulting in a decrease in soil MBC and MBN content (Figure S2). Furthermore, reduced microbial decomposition function could lead to decreased active carbon (DOC) and mineral nitrogen (NH4+) content (Figures S2 and S3), thus inhibiting the nitrification process. Conversely, elevated O3 increased soil NO3− content (Figure S3), which may support the denitrification rate [24]. However, E–O3 was not observed to promote nitrogen oxide emissions in this study, possibly because (1) nitrogen oxides in paddy fields are mainly emitted during the non-flooded period after the jointing stage of rice (Figure 1 and Figure 2), and favorable O2 conditions ensure that nitrogen oxides are mainly produced by nitrification processes; and (2) elevated O3 reduces the plant demand for nitrogen, and more NO3− is leached downward rather than providing a substrate for the denitrification process [24]. Meanwhile, elevated O3 increased soil pH of paddy fields, leading to greater nitrogen volatilization via the NH3 pathway [52], thereby reducing nitrogen oxide emissions. SEM analysis revealed that soil pH and MBN exerted negative effects on nitrogen oxide emissions from paddy fields, while soil DOC, NH4+, and NO3− exhibited positive effects (Figure 4). Additionally, elevated O3 had a significant effect on nitrogen oxide fluxes after the rice tillering stage (Figure 1 and Figure 2), thereby supporting our hypothesis (1) that elevated O3 significantly affected nitrogen oxide fluxes only during a part of rice growth, rather than across the entire growth period. However, after the tillering stage, elevated O3 did not always significantly reduce the fluxes, which may be due to the varying magnitude of the effect of elevated O3 on soil properties across different stages (Figures S2 and S3). Specifically, elevated O3 significantly influenced soil DOC and NH4+ content (Table 1). Consequently, elevated O3 primarily reduced nitrogen oxide emissions from paddy fields by decreasing soil DOC and NH4+ concentrations.

4.2. Effects of Warming on Nitrogen Oxide Emissions in Paddy Fields

Warming significantly increased nitrogen oxide emissions from paddy fields, regardless of the year (Table 1). W significantly increased N2O flux by 16.3% in paddy fields, compared to CK. This increase was higher than that reported in previous integrated analyses [31]. This discrepancy may stem from the fact that there was an 11.7% increase in paddy field N2O emissions in response to a 1 °C temperature rise in the previous study, whereas the canopy temperature in this study increased by an average of 1.1–1.5 °C. Similarly to N2O, W significantly increased NO flux in paddy fields by 15.6%, which was significantly lower than its effect on NO flux in wheat fields (an increase of ˃55%) [37]. This difference is likely attributable to contrasting water management practices between paddy and wheat croplands, as the water layer in paddies may attenuate the positive impact of warming on NO emissions [53]. However, W had no significant effect on soil moisture content in this study (Table S3), indicating that soil water was not a primary driver of nitrogen oxide emissions in paddy fields.
Warming can directly alter soil microbial activity and metabolism, and also influence subsurface processes through plant-mediated effects [29]. When other growth limitations are absent, moderate warming can enhance plant biomass, thereby increasing the input of plant litter and root exudates to soil [54,55]. Under warming, the energy demand of soil microorganisms for self-maintenance increases [56], and the activity of related enzymes is enhanced [57]. This leads to the transformation of microbial cycle from anabolism to catabolism, and the enhancement of microbial mineralization ability, that is, the decrease in soil MBC and MBN content and the increase in soil DOC, NH4+, and NO3− content (Figures S2 and S3). The increase in mineralized N availability under warming provides substrate for nitrification and denitrification, while soil DOC supplies C for microorganisms, ultimately enhancing soil nitrogen oxides production. Concurrently, the consumption of O2 driven by soil MBC and MBN metabolism provides energy and anerobic conditions for denitrification [58], further promoting denitrification. SEM results in this study support this perspective (Figure 4). Similar to the elevated O3 treatment, warming had a significant effect on nitrogen oxide flux after the rice tillering stage (Figure 1 and Figure 2). Additionally, warming significantly affected soil DOC, NH4+ and NO3− concentrations (Table 1), suggesting that warming primarily enhances nitrogen oxide emissions from paddy fields partly through elevated DOC, NH4+ and NO3− availability.

4.3. Effect of Combined Treatment on Nitrogen Oxide Emissions in Paddy Fields

Compared with W, the combination of E–O3 and W significantly suppressed N2O and NO fluxes by 17.5% and 11.0%, respectively. Notably, under warming in 2023, elevated O3 significantly reduced N2O fluxes at 38 DAT and reduced NO fluxes at 58 DAT (Figure 1 and Figure 2). These results indicate that elevated O3 can inhibit the warming-induced enhancement of nitrogen oxide emissions from paddy fields, supporting hypothesis (2). Compared with W, the combination of E–O3 and W increased MBC, MBN and pH, and weakened the soil nitrogen cycle. Additionally, the combined treatment reduced soil DOC and NH4+ contents, and reduced energy support and substrate supply for nitrification. Although soil NO3− content was slightly increased, it was beneficial to the denitrification process, but the combined treatment reduced the content of DOC and NH4+ in soil, which was the main reason for the decrease in nitrogen oxide flux in the paddy field. However, the dynamics of the functional genes and enzymatic activities governing nitrification and denitrification remain unexamined in this study. Therefore, more detailed mechanisms underlying the effect of the combined treatment on nitrogen oxide emissions from paddy fields remain to be further studied and demonstrated.
Multi-factor experiments are important to study the response of ecosystems to global change. However, the response results are complex, and different factors affect the results, including additive, antagonistic and synergistic effects; thus, in situ observations are needed [59]. An antagonistic effect of elevated O3 and warming on paddy field nitrogen oxide emissions is demonstrated in this study, consistent with earlier observations in wheat systems [37]. The results showed that elevated O3 inhibited the stimulation of the emission of nitrogen oxides by warming in paddy fields and reduced the net emission of greenhouse gases, thus resulting in lower global warming potential of paddy fields in areas with severe O3 pollution. O3 is a major pollutant in China [60], particularly during summer [61]. Based on the rice planting area in various provinces of China, this study estimated the emission reduction of nitrogen oxides in paddy fields under combined treatment compared with warming (Figure 5). Results showed that the total nitrogen oxide emission reductions in 2022 and 2023 were 8.31 and 13.24 Gg N yr−1, respectively. The emission reduction effect of high O3 concentration is clear; thus, anthropogenic reduction targets could be moderated in severely O3-polluted regions. Furthermore, mechanistic models incorporating soil C and N dynamics have been widely used to predict nitrogen oxide emissions [62,63]. This study is helpful to parameterize relevant models, thus lowering the uncertainty associated with paddy field nitrogen oxide emission predictions.

5. Conclusions

Nitrogen oxide emissions from paddy fields were significantly influenced by both elevated O3 and warming. Elevated O3 and warming played contrasting roles, with the former suppressing and the latter stimulating the emissions of nitrogen oxides. Elevated O3 led to a significant reduction in soil DOC and NH4+ content, whereas warming had the opposite effect. Moreover, warming significantly increased soil NO3− content, while neither treatment significantly affected soil MBC, MBN, or pH. The key driver of nitrogen oxide emissions was a significant alteration in soil DOC, NH4+ and NO3−. High O3 concentration significantly inhibited or tended to inhibit the stimulating effect of warming on nitrogen oxide emissions from paddy fields. Compared to warming alone, the combination of elevated O3 and warming produced a significant reduction in nitrogen oxide emissions from paddies. Therefore, the suppressive impact of elevated O3 must be accounted for in predictive models of paddy field nitrogen oxide emissions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy16060623/s1, Figure S1: Soil moisture content during the 2022–2023 rice growing season. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. The value of each factor represents the p-value; Figure S2: soil dissolved organic carbon (DOC; (a,b)), microbial biomass carbon (MBC; (c,d)), and microbial biomass nitrogen (MBN; (e,f)) content at different growth stages of rice in 2022–2023. The left panel represents 2022, and the right panel represents 2023. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. The value of each factor represents the p-value. Data reported in [40] are shown here. Figure S3: Soil NH4+ (a,b), NO3− (c,d), and pH (e,f) content at different growth stages of rice in 2022–2023. The left panel represents 2022, and the right panel represents 2023. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. The value of each factor represents the p-value. Data reported in [40] are shown here. Figure S4: Emission reductions in N2O and NO in provinces of mainland China during 2022–2023. For explanations of provincial abbreviations, see Table S4. Table S1: phenology of rice under elevated O3 and warming treatments; Table S2: fertilization during the growing season of rice; Table S3: the average soil moisture content during the rice growing seasons of 2022–2023; Table S4: abbreviations of provinces in mainland China.

Author Contributions

X.Z.: Investigation, Data Curation, Formal Analysis, and Writing—Original Draft. B.S.: Writing—Review and Editing, Methodology, and Funding Acquisition. E.A.: Data Curation, Writing—Review and Editing, and Funding Acquisition. Y.Z.: Investigation and Data Curation. Z.F.: Supervision, Conceptualization, Funding Acquisition, and Writing—Review and Editing. All authors have read and agreed to the published version of the manuscript.

Funding

The research was supported by the National Natural Science Foundation of China (grant numbers: W2532031 and 42377117), and the project of Jiangsu Provincial Department of Science and Technology (No. BE2023400).

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.

Acknowledgments

The authors would like to thank the anonymous reviewers for their critical comments and suggestions for improving this manuscript.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Seasonal N2O fluxes during the 2022–2023 rice season. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. Each value represents the mean ± standard error (n = 4). Blue asterisks indicate significant differences between the elevated O3 and the control; red asterisks indicate significant differences between the warming and the control; triangles indicate significant interactive effects of elevated O3 and warming. Differences are significant at p ≤ 0.05.
Figure 1. Seasonal N2O fluxes during the 2022–2023 rice season. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. Each value represents the mean ± standard error (n = 4). Blue asterisks indicate significant differences between the elevated O3 and the control; red asterisks indicate significant differences between the warming and the control; triangles indicate significant interactive effects of elevated O3 and warming. Differences are significant at p ≤ 0.05.
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Figure 2. Seasonal NO fluxes during the 2022–2023 rice season. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. Each value represents the mean ± standard error (n = 4). Blue asterisks indicate significant differences between the elevated O3 and the control; red asterisks indicate significant differences between the warming and the control; triangles indicate significant interactive effects of elevated O3 and warming. Differences are significant at p ≤ 0.05.
Figure 2. Seasonal NO fluxes during the 2022–2023 rice season. CK, E–O3, W, and E–O3W indicate control, elevated O3, warming, and combined elevated O3 and warming, respectively. Each value represents the mean ± standard error (n = 4). Blue asterisks indicate significant differences between the elevated O3 and the control; red asterisks indicate significant differences between the warming and the control; triangles indicate significant interactive effects of elevated O3 and warming. Differences are significant at p ≤ 0.05.
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Figure 3. Variable importance in random forest models for N2O (a) and NO (b) fluxes. The percentage Increase in MSE (Increase in Mean Squared Error) indicates variable importance, with higher values representing greater importance. An asterisk denotes that the variable is a significant driver of N2O or NO fluxes at the level of p ≤ 0.05. T: canopy temperature; SMC: soil moisture content; DOC: dissolved organic carbon; MBC: microbial biomass carbon; MBN: microbial biomass nitrogen.
Figure 3. Variable importance in random forest models for N2O (a) and NO (b) fluxes. The percentage Increase in MSE (Increase in Mean Squared Error) indicates variable importance, with higher values representing greater importance. An asterisk denotes that the variable is a significant driver of N2O or NO fluxes at the level of p ≤ 0.05. T: canopy temperature; SMC: soil moisture content; DOC: dissolved organic carbon; MBC: microbial biomass carbon; MBN: microbial biomass nitrogen.
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Figure 4. Structural equation models illustrating the effects of elevated O3 and warming on N2O and NO fluxes. The (left panel) shows the structural equation model, while the (right panel) displays the standardized total effects for each soil property. T: rice canopy temperature; SMC: soil moisture content; DOC: dissolved organic carbon; MBN: microbial biomass nitrogen. Numbers adjacent to arrows are indicative of the strength of the causal relationship. The significance levels are * p ≤ 0.05, ** p ≤ 0.01, and *** p ≤ 0.001.
Figure 4. Structural equation models illustrating the effects of elevated O3 and warming on N2O and NO fluxes. The (left panel) shows the structural equation model, while the (right panel) displays the standardized total effects for each soil property. T: rice canopy temperature; SMC: soil moisture content; DOC: dissolved organic carbon; MBN: microbial biomass nitrogen. Numbers adjacent to arrows are indicative of the strength of the causal relationship. The significance levels are * p ≤ 0.05, ** p ≤ 0.01, and *** p ≤ 0.001.
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Figure 5. Estimating elevated O3-induced reduction in nitrogen oxide emissions from Chinese paddy fields under warming. (a) Rice planting area by province in mainland China; (b) Nitrogen oxide emission reductions in mainland China. For explanations of provincial abbreviations, see the Supplementary Materials (Table S4). Identical letters on the bar indicate no significant differences between years for any variable.
Figure 5. Estimating elevated O3-induced reduction in nitrogen oxide emissions from Chinese paddy fields under warming. (a) Rice planting area by province in mainland China; (b) Nitrogen oxide emission reductions in mainland China. For explanations of provincial abbreviations, see the Supplementary Materials (Table S4). Identical letters on the bar indicate no significant differences between years for any variable.
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Table 1. Effect of elevated O3, warming and year on N2O flux, NO flux and soil properties during the 2022–2023 rice seasons.
Table 1. Effect of elevated O3, warming and year on N2O flux, NO flux and soil properties during the 2022–2023 rice seasons.
Fixed Effectp-Value
N2O FluxNO FluxDOCNH4+NO3−MBCMBNpH
O3<0.01<0.010.010.020.410.740.100.15
W<0.01<0.01<0.01<0.01<0.010.150.200.51
Year0.25<0.01<0.01<0.01<0.01<0.01<0.010.54
O3 × W0.140.610.330.250.510.880.620.88
O3 × Year0.350.960.940.990.870.680.58<0.01
W × Year0.990.48<0.01<0.01<0.010.760.57<0.01
O3 × W × Year0.630.810.820.610.370.720.910.48
Note: O3 and W indicate elevated O3 and warming, respectively. DOC: dissolved organic carbon; MBC: microbial biomass carbon; MBN: microbial biomass nitrogen. Bold font indicates significant effects.
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Zhong, X.; Shang, B.; Agathokleous, E.; Zhang, Y.; Feng, Z. Elevated O3 Reduces Nitrogen Oxide Emissions from Rice Paddy Fields Under Warming. Agronomy 2026, 16, 623. https://doi.org/10.3390/agronomy16060623

AMA Style

Zhong X, Shang B, Agathokleous E, Zhang Y, Feng Z. Elevated O3 Reduces Nitrogen Oxide Emissions from Rice Paddy Fields Under Warming. Agronomy. 2026; 16(6):623. https://doi.org/10.3390/agronomy16060623

Chicago/Turabian Style

Zhong, Xin, Bo Shang, Evgenios Agathokleous, Yujie Zhang, and Zhaozhong Feng. 2026. "Elevated O3 Reduces Nitrogen Oxide Emissions from Rice Paddy Fields Under Warming" Agronomy 16, no. 6: 623. https://doi.org/10.3390/agronomy16060623

APA Style

Zhong, X., Shang, B., Agathokleous, E., Zhang, Y., & Feng, Z. (2026). Elevated O3 Reduces Nitrogen Oxide Emissions from Rice Paddy Fields Under Warming. Agronomy, 16(6), 623. https://doi.org/10.3390/agronomy16060623

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