Effects of Long-Term Nitrogen Fertilization on Nitrous Oxide Emission and Yield in Acidic Tea (Camellia sinensis L.) Plantation Soils

Abstract

The responses of nitrous oxide (N₂O) emissions to nitrogen (N) application in acidic, perennial agricultural systems, and the factors driving these emissions, remain poorly understood. To address this gap, a 12-year field experiment was conducted to investigate the effects of different N application rates (0, 112.5, 225, and 450 kg N ha⁻¹ yr⁻¹) on N₂O emissions, tea yield, and the associated driving factors in a tea plantation. The study found that soil pH significantly decreased with long-term N application, dropping by 0.32 to 0.85 units. Annual tea yield increased significantly, by 148–243%. N application also elevated N₂O emission fluxes by 33–277%, with notable seasonal fluctuations observed. N₂O flux was positively correlated with N rates, water-filled pore space (WFPS), soil temperature (T_soil), and inorganic N (NH₄⁺-N and NO₃⁻-N), while showing a negative correlation with soil pH. Random forest (RF) modeling identified WFPS, N rates, and Tsoil as the most important variables influencing N₂O flux. The cumulative N₂O emissions for N112.5, N225, and N450 were 1584, 2791, and 45,046 g N ha⁻², respectively, representing increases of 1.33, 2.34, and 3.77 times compared to N0. The N₂O-N emission factors (EF) were 0.35%, 0.71%, and 0.74%, respectively, and increased with higher N rates. These findings highlight the importance of selecting appropriate fertilization timing and improving water and fertilizer management as key strategies for mitigating soil acidification, enhancing nitrogen use efficiency (NUE), and reducing N₂O emissions in acidic tea-plantation systems. This study offers a theoretical foundation for developing rational N fertilizer management practices and strategies aimed at reducing N₂O emissions in tea-plantation soils.

1. Introduction

In recent years, global climate change has become a major focus, especially the impact of global warming caused by increasing greenhouse gases (GHG). Identifying effective strategies to reduce human emissions of these gases has become a key research priority. N₂O is a potent GHG, with an atmospheric lifespan of up to 131 years. It is approximately 298 times more effective at trapping heat than is carbon dioxide (CO₂), and nine times more effective than methane (CH₄) over the period of a century [1]. Agriculture, especially through its application of N fertilizers, is the largest source of N₂O emissions, accounting for 59.4% of anthropogenic N₂O emissions [1]. The tea plant (Camellia sinensis L.) is extensively cultivated in tropical and subtropical regions characterized by acidic soil conditions. China is the largest tea-producing country, with a planting area covering 3.165 million hectares [2]. As a leaf-harvested crop, tea plants require substantial amounts of N to achieve both yield and quality, particularly in amino acid formation. However, excessive N input not only reduces the N use efficiency of tea plants but also poses environmental risks such as N₂O emissions [3]. Furthermore, there is a notable increase in N₂O emissions due to the inhibition of N₂O reductase activity under acidic conditions [4]. Additionally, tea plantations are characterized by periodic pruning, with all material left in situ after each pruning, which may significantly affect N₂O emissions in the presence of N fertilizer. Therefore, it is essential to investigate the impact of N fertilizer application on N₂O emissions and identify the key influencing factors in acidic perennial tea-plantation soils.

Evidence indicates that N₂O emissions from agricultural soils are primarily driven by synthetic N fertilizers and manure, and are expected to increase by about 50% from 2000 to 2050 [5,6]. Tea-plantation soils, which often receive high N supply, are more prone to acidification and become significant sources of N₂O. Tea plantations are characterized by higher N application compared to cereal-cropping systems, with an average of 553 kg N ha⁻¹yr⁻¹ [7,8]. Studies have shown that a high N input rate can directly enhance N₂O emissions [9,10]. Furthermore, a meta-analysis revealed that the elevated N₂O emissions from tea-plantation soils are primarily attributed to their high levels of N application [11]. However, the N₂O emission factor (EF) is still highly uncertain in the current research, particularly regarding those factors that influence it in tea-plantation soils. Previous research has reported that the average N₂O EF in tea plantations is 1.92% [11]. The value significantly exceeds the 1% threshold recommended by the IPCC [12]. However, the relationship between N rates and N₂O EF remains unclear. For example, Gu et al. [13] suggested that the N₂O EF is not directly linked to N rates but is significantly affected by the soil C/N ratio and clay content. In contrast, other studies have reported that higher synthetic N inputs in upland soils can lead to increases in N₂O EF, with emissions growing exponentially as N rates rise. Han et al. [7] observed that N₂O EF increases with the amount of N fertilizer applied in tea plantations. To accurately assess N₂O emissions and develop effective reduction strategies in tea-plantation soils, further research is needed to understand how N fertilizer application rates influence the N₂O emission process and EF in field conditions.

The excessive application of N fertilizers significantly increases N₂O emissions from tea-plantation soils [14]. However, N application rates vary widely across different tea-growing regions and cultivation practices. Numerous studies have investigated the impacts of varying N application levels on the N₂O EF through controlled experiments or short-term field observations [15,16]. However, the results demonstrate significant variability and uncertainty. There is a notable lack of long-term field studies examining how different fertilization regimes influence N₂O emissions and EFs in tea-plantation soils. This underscores the necessity for more extensive in situ research to elucidate the complex interactions between N application, soil dynamics, and N₂O emissions in tea-plantation systems.

This study investigates the N₂O emissions, tea yield, and soil properties of a tea plantation subjected to a 12-year field trial with varying N application rates. The purposes of the study were to (1) assess the responses of N₂O emissions, tea yield, and soil properties to long-term N application, and (2) identify key factors driving changes in N₂O emissions flux. We hypothesize that the relationship between N₂O emissions and tea yield in response to N rates is non-linear rather than linear, and that denitrification of the substrate inorganic N (NH₄⁺-N and NO₃⁻-N) is a significant factor influencing N₂O emissions. The findings of this study will enhance our understanding of the impacts of N addition on N₂O emissions in acidic tea-plantation soils, and will serve as a foundation for developing effective management strategies to mitigate N₂O emissions in perennial agricultural systems.

2. Materials and Methods

2.1. Site Description

The field trial was located in Shekou town, Fu’an City, Fujian Province, China (22°22′ N, 119°57′ E, altitude of 46 m) (Figure 1), and was affiliated with the Tea Research Institute of the Fujian Academy of Agricultural Sciences. The site features a subtropical monsoon climate, with a mean annual precipitation (MAP) and temperature (MAT) of 1426 mm and 26 °C from 2013 to 2022. These 10-year datasets were obtained from WorldClim (https://www.worldclim.org) (accessed on 25 June 2024), a global weather and climate data database with high spatial resolution. Additionally, meteorological data for the experimental period (January to December 2023) were collected using a WS-MC01 compact automatic weather station installed on-site (Figure 2). During 2023, daily mean temperatures varied from 2.65 °C to 31.74 °C, with a MAT of 19.72 °C. The MAP for 2023 was 1550.7 mm. The soil at the site is classified as Alisol, which developed from a Quaternary eolian red deposit, and has a loamy clay texture.

The long-term experiment was established in 2009. Each experimental plot consists of a cement pool measuring 200 cm × 90 cm and with a depth of 90 cm (Figure 1c). Five tea bushes were planted in each plot, with a spacing of 30 cm between them. The tea cultivar “Yucui” (You 4) was transplanted in March 2010. At the start of N₂O monitoring (December 2022), the surface (0–20 cm) soil properties were as follows: pH 4.85, soil organic carbon (SOC) 3.69 g kg−¹, total nitrogen (TN) 0.30 g kg⁻¹, available phosphorus (AP) 4.8 mg kg⁻¹, available potassium (AK) 60.3 mg kg⁻¹, and an initial C/N ratio of 12.38.

2.2. Experiment Design

The experiment was conducted using a randomized design with four N fertilizer rates (N0, N112.5, N225, and N450; 0, 112.5, 225, and 450 kg N ha⁻¹ yr⁻¹). Each treatment was replicated three times, with each replicate plot covering an area of 1.8 m², resulting in a total of 12 plots (Figure 1c). For all treatments, P and K fertilizer were applied at rates of 150 kg P₂O₅ ha⁻¹ and 300 kg K₂O ha⁻¹, respectively. Generally, the N (urea) and K (sulfate of potash) fertilizers were applied in three splits: 40% in March, 30% in August, and 30% in November. The P (superphosphate) fertilizer was applied in November as the base fertilizer. All fertilizers were evenly broadcast on the soil surface and then incorporated to a depth of about 5 cm through tillage. In our study, the base fertilizer was applied on 8 December 2022, and top-dressings were applied on 7 March and 10 August 2023.

2.3. Tea Shoot Sampling and Yield Calculation

In our study, tea shoots with one bud and two leaves were picked by hand, and their fresh weights represented tea yield. Spring tea was obtained from 28 March to 25 April, and autumn tea was obtained from 10 September to 7 October. The annual tea yield was the sum of spring and autumn tea yields.

2.4. Measurement of N₂O Emissions and Calculation of Indicators

The N₂O emissions from the tea-plantation soil were monitored monthly from January to December 2023 to analyze the impacts of different fertilization strategies comprehensively. The frequency of monitoring was increased following fertilization and the precipitation events. The soil N₂O flux was measured using an infrared, laser-based gas analyzer (Li-7810, Li-COR Biosciences, Lincoln, NE, USA), with an optical feedback cavity-enhanced absorption spectroscopy (OF-CEAS) apparatus connected to a Smart Chamber (8200-01 S, Li-COR Biosciences, Lincoln, NE, USA). The Smart Chamber was positioned on the top of PVC collars (5.0 cm × 20 cm; height × diameter). At least two minutes were required per plot to perform the measurement, and an interval of approximately 20 seconds was enforced between two consecutive measurements, based on the observed change in gas concentration. All measurements were taken between 9:00 am and 11:00 am.

Soil N₂O emission flux was estimated using the SoilFluxPro-4.2.1 software, employing the exponential regression method as the primary technique to calculate the soil greenhouse gas diffusion rate [17]. The formula used was

$$\mathrm{c}\left(\mathrm{t}\right)=c_x+\left(c_0-c_x\right)e^{-a(t-t_0)}$$

(1)

where c(t) is the concentration of N₂O inside the test chamber, c_x is the asymptote parameter, and c₀ is the concentration of atmospheric N₂O at the moment the soil chamber is closed.

The soil N₂O emission flux is equivalent to the initial slope of the exponential regression, as demonstrated in Equation (2), i.e., $\left({\displaystyle \frac{{\mathrm{Ə}}_c}{{\mathrm{Ə}}_t}}\right)$:

$${\displaystyle \frac{{\mathrm{Ə}}_c}{{\mathrm{Ə}}_t}}=a(c_x-c_0)$$

(2)

N₂O cumulative emissions were calculated using a linear interpolation approach [18]. This method estimated the N₂O emissions on the non-sampling days between two consecutive sampling days. Subsequently, the total of the daily emissions was calculated to determine the annual cumulative N₂O emission.

$$\mathrm{M}=\sum _{i=1}^n{\displaystyle \frac{F_{i+1}+F_i}{2}}\times \left(d_{i+1}-d_i\right)\times (8.64\times {10}^4{)\times 10}^{-9}\times 28\times {10}^4$$

(3)

where M is the N₂O cumulative emissions during the observation period (g N ha⁻¹), F is the N₂O gas emission rate (nmol m⁻² s⁻¹), i is the observation number, and d_i+1−d_i is the interval in days between successive observations. The constants used are 8.64 × 10⁴ (for converting seconds to days), 10⁻⁹ (for converting nmol to mol), 28 (for converting mol N₂O to the mass of N), and 10⁴ (for converting m² to ha).

The N₂O-N emission factor (EF) is calculated using the following formula [19]:

$$\mathrm{E}\mathrm{F}={\displaystyle \frac{M_{N-}{M}_0}{N}}\times 100\mathrm{\%}$$

(4)

where EF is the N₂O emission factor (%); M_N and M₀ are the cumulative N₂O emissions (g N ha⁻¹) for N-treated and untreated plots, respectively; and N is the applied N amount (g N ha⁻¹).

The yield-scaled N₂O emission (YSNE) (g N₂O-N kg⁻¹ tea shoots) was calculated as follows:

YSNE = E/Y

(5)

where E represents the annual N₂O emission in kg N ha⁻¹, and Y represents the tea yield in kg ha⁻¹.

2.5. Measurement of Environmental Factors

The data for air temperature and precipitation at the experimental site were obtained from a meteorological observatory located at the experimental station. The soil temperature was measured using a digital thermometer following N₂O monitoring. The soil sample was collected from a 0–10 cm depth using a stainless-steel corer (inner diameter 5 cm), and triplicates were collected from each plot. The collected sample was dried in an oven at 105 °C for 48 h to determine the soil gravimetric water content (GWC), and the GWC was then converted to water-filled pore space (WFPS) as follows:

WFPS (%) = GWC × bulk density/(1 − bulk density/2.65) × 100%

(6)

where GWC represents the gravimetric water content (%), bulk density is the bulk density of the soil of each plot, and 2.65 represents the accepted particle density of the soil.

To assess soil pH and the inorganic N (NH₄⁺ and NO₃⁻), soil samples were collected around PVC collars 20 cm in diameter and at a depth of 10 cm following N₂O monitoring. Surface soil (0–10 cm depth) samples were collected using a 3 cm diameter auger. Each time, a total of 12 composite samples were taken, each composed of three cores randomly selected from different locations within a plot. Each composite sample was thoroughly mixed, and stones, plant debris, and roots were manually removed. The soil was then passed through a 2 mm sieve and divided into two parts. One was immediately analyzed for NH₄⁺ and NO₃⁻, while the other part was air-dried and used to measure soil pH.

Soil pH was measured using the potentiometric method with a water-to-soil ratio of 2.5:1. NH₄⁺ and NO₃⁻ were extracted by shaking the soil with 2 M KCl at a soil-to-solution ratio of 1:10 (w/v) for one hour, and their concentrations were determined using continuous flow analysis (Seal Analytical AA3, Norderstedt, Germany).

2.6. Statistical Analysis

One-way analysis of variance (ANOVA) was employed to assess significant differences (p < 0.05) in soil properties, tea yield, YSNE, and EF and cumulative N₂O emission across four different N application rates. Pearson correlation analysis was performed to assess the relationship between N₂O flux and various environmental factors, including T_soil, WFPS, pH, NH₄⁺-N, and NO₃⁻-N. Additionally, random forest (RF) modeling was used to identify the most important soil variables for the prediction of N₂O emission under fertilization. All statistical analyses were performed using the R platform (version 4.1.2), with the ‘stats’ package for one-way ANOVA and Pearson correlation, and the ‘randomforest’ package for RF modeling.

3. Results

3.1. Changes in T_soil, WFPS, Soil pH, and Inorganic N Under Different N Rates

The T_soil and WFPS (10 cm depth) were continuously monitored throughout the whole experimental period (Figure 3). The observed T_soil values for each treatment were as follows: 4.81–28.66 °C (N0), 7.54–30.31 °C (N112.5), 2.82–30.31 °C (N225), and 7.07–30.61 °C (N450). The corresponding mean T_soil values were 19.94 °C (N0), 20.02 °C (N112.5), 19.96 °C (N225), and 20.27 °C (N450). The WFPS ranges varied as follows: 35.68–76.04% (N0), 25.71–53.93% (N112.5), 23.13–52.15% (N225), and 21.41–56.67% (N450). Additionally, the mean WFPS values were significantly lower under the N application treatments, compared to the control (p < 0.05).

The seasonal fluctuation in soil pH under N fertilization showed an initial increase followed by a steady decrease (Figure 4a). On average, the annual mean soil pH values in the N112.5, N225, and N450 treatments were significantly lower, by 10.16%, 16.68%, and 20.89%, respectively (p < 0.05), compared to the N0 treatment. A significant negative correlation was observed between the annual mean soil pH and N rates (R² = 0.82, p < 0.01) (Figure S1a).

Similarly, the annual mean contents of NH₄⁺-N (R² = 0.77, p < 0.01) and NO₃⁻-N (R² = 0.79, p < 0.01) exhibited significant positive correlations with N rates (Figure S1b,c). The N0 treatment had minimal impacts on the seasonal variation of NH₄⁺-N and NO₃⁻-N contents (Figure 4b,c), while N fertilization significantly increased the fluctuation of these nutrients. Under N fertilization, soil NH₄⁺-N and NO₃⁻-N contents were significantly higher than in the N0 treatment (p < 0.05). Specifically, soil NH₄⁺-N levels in the N112.5, N225, and N450 treatments were 2.31, 4.87, and 8.16 times higher than in the N0 treatment, and the NO₃⁻-N were 2.01, 3.09, and 3.93 times higher. Furthermore, continuous monitoring showed that after spring fertilization, NH₄⁺-N content in the 0–10 cm soil layer peaked between 7 and 20 days, while NO₃⁻-N content values reached their maximum at points between 20 and 30 days. In contrast, after autumn fertilization, NH₄⁺-N content peaked within 2 to 6 days, and NO₃⁻-N content peaked between 8 and 17 days. For base fertilization, NH₄⁺-N peaked at 6 to 12 days, and NO₃⁻-N peaked between 30 and 38 days.

3.2. Changes in N₂O Flux and Cumulative N₂O Emissions Under Different N Rates

The N₂O emission flux in tea-plantation soil varied with different N rates (Figure 5). The N0 treatment exhibited a relatively low flux, ranging from 0.006 to 0.516 nmol m⁻² s⁻¹, with an annual mean of 0.130 nmol m⁻² s⁻¹. Brief emission peaks occurred after rainfall and temperature increases. In contrast, N fertilizer treatments showed consistent patterns, with three annual peaks following fertilization, influenced by environmental factors. After spring top-dressing (7 March), seasonal drought suppressed N₂O emissions until rainfall events (19–23 March) led to rapid increases, peaking in the interval of 3–7 April. This spring peak was higher than those in other periods. Following autumn top-dressing and base fertilization, N₂O emissions rose quickly within two days, peaking 4 to 11 days later with two to three emission maxima. N fertilizer significantly increased N₂O emission, with higher application rates leading to greater emissions. Mean fluxes for N112.5, N225, and N450 treatments were 0.209, 0.385, and 0.649 nmol m⁻² s⁻¹, respectively, −1.61, 2.96, and 4.99 times higher than the N0 treatment.

Furthermore, annual cumulative N₂O emissions also rose with higher N rates (Figure 5). The N0 treatment resulted in 1195.14 g N₂O-N ha⁻¹, while the N112.5, N225, and N450 treatments yielded 1584, 2791, and 4504 g N₂O-N ha⁻¹, respectively, which are approximately 1.33, 2.34, and 3.77 times higher than the N0 treatment. A significant quadratic relationship was observed between cumulative N₂O emissions and N rates (R² = 0.94, p < 0.01) (Figure S2).

3.3. Tea Yield, YSNE, and N₂O EF Under Different N Rates

Different N rates significantly affected tea yield (Figure 6). Compared to the N0 treatment, spring tea yields increased by 157.34%, 152.65%, and 255.70% under the N112.5, N225, and N450 treatments, respectively. A quadratic relationship was observed between yield and N rates (R² = 0.86, p < 0.01). Autumn tea yields also rose by 127.65%, 208.82%, and 216.72% with the same treatments, following a similar quadratic trend (R² = 0.78, p < 0.01). Overall, annual tea yield improved by 37.48%, 241.32%, and 270.91% with increasing N rates, showing a strong quadratic correlation (R² = 0.90, p < 0.01).

Long-term N input significantly affected the Yield-Scaled Nitrogen Efficiency (YSNE), which decreased by 47.57% and 14.56% for the N112.5 and N225 treatments, respectively, compared to N0 (p < 0.05) (

Table 1. The yield-scaled N₂O emissions (YSNE) and direct N₂O emission factors (EF; %) for a tea plantation under different levels of N application during the experimental period.

N Application Rates (kg N ha−1 yr−1)	YSNE (gN2O-N kg−1 tea)	N2O-EF (%)
0	1.03 ± 0.06 ab
112.5	0.54 ± 0.04 c	0.35 ± 0.07 b
225	0.88 ± 0.1 b	0.71 ± 0.09 a
450	1.11 ± 0.02 a	0.73 ± 0.01 a
ANOVA
F-value	16.69	10.53
p-value	<0.01	<0.05

Values are shown as means ± standard errors (n = 3). Different lowercase letters indicate significant differences among treatments according to Tukey’s post hoc test (p < 0.05).

). However, there was no significant difference between the N0 and N450 treatments. Additionally, the N₂O EF increased with higher N rates, i.e., N112.5 (0.35%) < N225 (0.71%) < N450 (0.74%). Significant differences in EF were observed between the N225, N450, and N0 treatments, but not between N225 and N450.

3.4. Driving Factors for Influencing N₂O Flux in Tea Plantations

Pearson correlation analysis showed that the N₂O emission flux was significantly positively correlated with N rates, soil WFPS, T_soil, and inorganic N contents (NH₄⁺-N and NO₃⁻-N) (Figure 7a). Conversely, it was significantly negatively correlated with soil pH. The correlation between soil N₂O flux and environmental factors varied with different N rates (Figure S3). Under the N0 treatment, N₂O flux was significantly correlated with T_soil, WFPS, and pH. For the N112.5 and N225 treatments, N₂O flux was only significantly correlated with T_soil and WFPS. In the N450 treatment, NH₄⁺-N and NO₃⁻-N also exhibited significant correlations with N₂O flux, in addition to T_soil and WFPS.

The RF model further demonstrated that soil environmental factors significantly influenced N₂O flux changes, with an R² value of 45.2% (p < 0.001) (Figure 7b). Key factors contributing to N₂O flux were soil WFPS (%IncMSE = 27.11%, p < 0.01), N rates (%IncMSE = 20.57%, p < 0.01), and T_soil (%IncMSE = 13.60%, p < 0.01).

4. Discussion

Nitrogen is a vital mineral nutrient for plants, and applying N fertilizer is essential for boosting tea yield and regulating quality. In this study, we found that tea yield increased with higher N application rates (0 to 450 kg ha⁻¹) (Figure 6), which is consistent with previous findings [20]. However, the impacts of N application on tea plants and soils are complex, as N-containing compounds in tea directly affect its color, aroma, and taste. Long-term N application significantly alters soil properties, notably causing a marked decrease in soil pH (Figure 4). Excessive N use leads to H⁺ accumulation, accelerating soil acidification—a major issue in tea plantations [21]. Moreover, low pH reduces nitrous oxide reductase (NOS) activity, hindering the conversion of N₂O to N₂ and resulting in N₂O accumulation and higher emissions [4,22]. To mitigate these effects, tea production must adhere to N fertilizer limits based on desired yield and quality. This approach can slow soil acidification and reduce N₂O emissions, which is crucial for sustainable tea cultivation.

N₂O is produced through both nitrification and denitrification, which occur simultaneously in soils [22]. This study found a strong positive correlation between N₂O flux and soil NH₄⁺-N and NO₃⁻-N (Figure 7), which is consistent with previous findings showing that N fertilizers increase these nutrient levels [23], thereby promoting nitrification and denitrification and subsequently increasing N₂O emissions [24]. However, our research also revealed that the relationship between N rates and N₂O emissions is not straightforward. For example, high N treatment (N450) showed significant correlations, while other treatments did not. This suggests that at lower N levels, rapid uptake of NH₄⁺-N and NO₃⁻-N by tea roots limits the accumulation of these nutrients in the soil, potentially explaining the lack of significant correlations under these conditions. Additionally, environmental factors such as soil temperature and humidity influence N₂O emissions, particularly at lower N levels, where they may overshadow the impact of inorganic N content. Therefore, optimizing the absorption of N fertilizers by tea plants and minimizing residual NH₄⁺-N and NO₃⁻-N levels in the soil are effective strategies for reducing N₂O emissions in tea plantations.

Numerous studies have demonstrated that soil moisture is a critical factor affecting N₂O emission from tea-plantation soils. It affects soil aeration, redox potential, nutrient availability, and microbial activity, thereby impacting nitrification, denitrification, and N₂O production. The optimal soil moisture for N₂O emissions is typically between 60% and 80% of the WFPS [25]. When soil NO₃⁻-N levels are high, precipitation often triggers significant N₂O emissions [26]. Machon et al. [27] observed a significant N₂O emission peak in tea-plantation soils following rainfall, indicating that rainfall acts as a trigger for these emissions. In this study, N₂O fluxes were significantly positively correlated with soil WFPS across all treatments (Figure 7). In early to mid-March, seasonal drought conditions reduced both soil moisture and N₂O emissions (Figure 2). However, subsequent rainfall improved soil moisture, leading to a rapid increase in N₂O emission. Therefore, effective water management and integrated water–fertilizer strategies are essential for mitigating N₂O emission in tea plantations.

In addition, soil temperature is widely recognized as a key factor influencing nitrification and denitrification processes, with optimal ranges of 25–35 °C and 30–67 °C, respectively [28]. However, our study found that the correlation between N₂O flux and T_soil diminishes with higher N input. Specifically, significant positive correlations with T_soil were observed in the control and low-to-medium N treatments (N112.5 and N225). In contrast, this correlation was not significant in the high N treatment (N450). This suggests that tea plantations, as artificial ecosystems, are strongly influenced by human management practices regarding N₂O emissions. In the N450 treatment, the high levels of soil inorganic N likely played a dominant role in N₂O emissions, potentially overshadowing the effect of T_soil.

The application rate of N fertilizer is a crucial factor in regulating soil N₂O emissions in tea plantations, and this study has extensively investigated its impact. The significant increase in annual cumulative N₂O emissions under N treatments compared to the N0 treatment confirms the strong positive effect of N fertilization on N₂O emissions in tea plantations. This finding is consistent with previous findings which indicated that higher N application rates lead to increased annual N₂O emissions, with the N application rate being the most influential factor controlling these emissions [11].

While higher N application can boost tea yields, the NUE of tea plants typically ranges from only 25% to 30% [29], indicating that a significant portion of the applied N remains unutilized. Excessive N fertilizer leads to elevated soil NH₄⁺-N and NO₃⁻-N levels, providing abundant substrates for nitrification and denitrification, and thus intensifying N₂O emissions [30,31]. Additionally, excessive N can cause significant soil acidification [21], which may activate denitrifying bacteria and inhibit nitrous oxide reductase activity [4], further accelerating N₂O production and release. Notably, this study found that N₂O emissions increase gradually at low N levels but rise sharply once a certain threshold is exceeded. This highlights the importance of N management strategies, such as selecting fertilizers that tea plants can readily absorb, and optimizing the timing, placement, and quantity of fertilizer applications based on the growth characteristics of tea plants. These practices can enhance NUE and effectively reduce N₂O emissions [32].

In our study, the N₂O EF increased with higher N rates, ranging from 0.35% to 0.74% (Table 1). However, these values are significantly lower than the previously reported average N₂O EF of 1.92% for Chinese tea-plantation soils [33]. The global N-induced N₂O EF for tea plantations shows even greater variability, spanning from 0.1% to 11.5%, with an average of 2.31% [11]. This wide range underscores the complexity of N₂O emissions in agricultural soils, which are influenced by a multitude of interacting factors, including soil properties (such as total N content and C/N ratio), management practices (like irrigation and fertilization), and other environmental variables. While our findings are consistent with previous studies showing that N₂O EF increases with higher N application rates [33], other research suggests that in tea plantations, the N₂O EF is primarily driven by soil C/N ratio and clay content rather than the N application rate [34]. Consequently, accurately estimating the current N₂O EF in tea-plantation soils remains a highly uncertain practice due to the complex interplay of the various factors affecting N₂O emission mechanisms under field conditions.

In addition to these abiotic factors, multiple biotic factors, such as soil microbes, soil enzyme activities, and soil rhizosphere processes, play important roles in regulating soil N₂O production. Future studies should comprehensively analyze the effects of biotic and abiotic factors on the soil N₂O emissions of acidic tea-plantation systems.

5. Conclusions

In this study, soil pH significantly decreased with increasing N rates, while tea yields increased. The N₂O flux, cumulative emissions, and EF also rose significantly with higher N rates and showed notable seasonal fluctuations. The N₂O flux was positively correlated with N rates, WFPS, T_siol, and inorganic N, and negatively correlated with soil pH. RF modeling further identified WFPS, N rates, and T_siol as key factors influencing N₂O flux. To optimize tea production, it is essential to adhere to N application limits tailored to the target yields for different tea varieties. Selecting N fertilizers that tea plants can readily absorb and utilize is crucial. Additionally, optimizing the timing of fertilizer application based on the specific characteristics of tea production and improving the water–fertilizer integration are key strategies. These approaches can help mitigate soil acidification, enhance NUE, and reduce N₂O emissions in acidic tea plantations.