Distribution and Production of N2O in the Subtropical Western North Pacific Ocean During the Spring of 2020

Nitrous oxide (N2O) is an important greenhouse gas emitted in significant volumes by the Pacific Ocean. However, the relationship between N2O dynamics and environmental drivers in the subtropical western North Pacific Ocean (STWNPO) remains poorly understood. We investigated the distribution of N2O and its production as well as the related mechanisms at the surface (0–200 m), intermediate (200–1500 m), and deep (1500–5774 m) layers of the STWNPO, which were divided according to the distribution of water masses. We applied the transit time distribution (TTD) method to determine the ventilation times, and to estimate the N2O equilibrium concentration of water parcels last in contact with the atmosphere prior to being ventilated. In the surface layer, biologically derived N2O (ΔN2O) was positively correlated with the apparent oxygen utilization (AOU) (R2 = 0.48), suggesting that surface N2O may be produced by nitrification. In the intermediate layer, ΔN2O was positively correlated with AOU and NO 3 − (R2 = 0.92 and R2 = 0.91, respectively) and negatively correlated with nitrogen sinks (N*) (R2 = 0.60). Hence, the highest ΔN2O value in the oxygen minimum layer suggested N2O production through nitrification and potential denitrification (up to 51% and 25% of measured N2O, respectively). In contrast, the deep layer exhibited a positive correlation between ΔN2O and AOU (R2 = 0.92), suggesting that the N2O accumulation in this layer may be caused by nitrification. Our results demonstrate that the STWNPO serves as an apparent source of atmospheric N2O (mean air−sea flux 2.0 ± 0.3 μmol m-2 d-1), and that nitrification and potential denitrification may be the primary mechanisms of N2O production in the STWNPO. We predict that ongoing ocean warming, deoxygenation, acidification, and anthropogenic nitrogen deposition in the STWNPO may elevate N2O emissions in the future. Therefore, the results obtained here are important for elucidating the relationships between N2O dynamics and environmental changes in the STWNPO and the global ocean.


INTRODUCTION
Since the industrial revolution, atmospheric greenhouse gas (GHG) concentrations have been increasing at unprecedented rates, especially nitrous oxide (N 2 O), which rose from previous concentrations of 270 ppb (pre-industrial revolution) to above 330 ppb (Montzka et al., 2011;Prinn et al., 2018). Generally, N 2 O is considered a significant GHG, similar to carbon dioxide (CO 2 ) and methane (CH 4 ), and it contributes significantly to the global greenhouse effect (Stocker et al., 2014). More specifically, N 2 O is 300 times more potent as a GHG than CO 2 (Jain et al., 2000) and plays a critical role in ozone depletion (Crutzen, 1970). N 2 O is released into the atmosphere from various sources, such as agriculture, industry, the burning of fossil fuels, and other natural sources (Tian et al., 2016). As N 2 O is produced from biological sources in the ocean, oceanic N 2 O emissions play a vital role in the atmospheric N 2 O budget (Bange, 2006). It has been estimated that the N 2 O emitted from the oceans contributes to 35% (3.4 Tg N yr −1 ) of total natural sources (Tian et al., 2020).
Generally, N 2 O is produced in the ocean through two microbial activities: nitrification and denitrification. Nitrification refers to a series of processes in which ammonium (NH + 4 ) is converted to its inorganic form from organic nitrogen (ammonification), which is then oxidized to nitrate (NH + 4 ! NH 2 OH ! NO − 2 ! NO − 3 ) by nitrifiers. During nitrification, N 2 O is produced through two pathways (NH 2 OH ! N 2 O and NO − 2 ! NO ! N 2 O), the latter being termed "nitrifier denitrification" (Codispoti and Christensen, 1985). Nitrification is an aerobic process occuring in almost all oxygen-rich oceans. In this process, N 2 O is produced by ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), which are nitrifiers (Goreau et al., 1980;Löscher et al., 2012). However, when the oxygen concentration is low (below 20 mmol L -1 ), nitrifying bacteria mediate nitrifier denitrification (Poth and Focht, 1985;Wrage et al., 2001). In the euphotic zone, the nitrification rates ranged from 3.7 to 11.3 nmol L -1 d -1 in the western North Pacific Ocean (Yoshikawa et al., 2016;Breider et al., 2019), which is one of the normoxic oceans, in comparison to the rates of 44.5−213 nmol L -1 d -1 in the eastern tropical North Pacific Ocean (Beman et al., 2013). With relatively low nitrification rates, N 2 O surface concentrations in the western North Pacific Ocean remain slightly higher (5.6−8.0 nmol L −1 with saturation of 102−115% at 0−200 m) than the equilibrium values, being produced through nitrification and nitrifier denitrification (Butler et al., 1989;Breider et al., 2015;Yoshikawa et al., 2016;Zhan et al., 2017).
As these regions undergo a combination of nitrification and denitrification, considerably high N 2 O concentrations have been observed (e.g., up to 986 nmol L -1 in the eastern tropical South Pacific Ocean) (Arevalo-Martıńez et al., 2015). Several studies have expanded our knowledge of the oxygen dependence of denitrification in marine environments. Schropp and Schwarz (1983) suggested that N 2 O is produced through potential denitrification in the formation of anaerobic microsites by particles within a nitrate-rich and even well-oxygenated environment. Similarly, in the relatively oxygen-rich Pacific Ocean outside the OMZ, potential denitrification in the microreducing environment created by marine snow in the water column has also been suggested despite aerobic conditions (Yamagishi et al., 2005;Kim et al., 2013). In addition, the coupling of many surface-supplied particles and denitrifiers may contribute to denitrification in the oxygenated Chukchi Shelf waters (Zeng et al., 2017). In addition to potential denitrification within the water column, denitrification occurs in permeable sediments under high oxygen concentrations (even above 100 mmol L -1 ) (Marchant et al., 2017). Denitrification has not been highlighted in the western Pacific Ocean in comparison to other regions where oxygen is depleted. However, these studies in various regions, including the Pacific Ocean, have provided insights into the potential for N 2 O production through denitrification in the western Pacific Ocean.
The subtropical North Pacific Ocean plays a significant role in the air-sea exchange of climate relevant gases (Dore et al., 1998), and drives the largest wind-driven circulation (North Pacific Subtropical Gyre) across the global ocean (Karl, 1999;Talley, 2011). As part of this gyre, the subtropical western North Pacific Ocean (STWNPO) is dominated by western boundary currents of the Kuroshio, Mindanao, and North Equatorial currents . The STWNPO is considered as an oligotrophic region (Corno et al., 2007;Kämpf and Chapman, 2016), comprising an oxygen minimum layer under hypoxic conditions (oxygen <~63 μmol L −1 ), which is characteristic of the Pacific Ocean, as it contains the oldest water in the world (Talley, 2011).
As with other oceans, the STWNPO has undergone significant environmental changes owing to anthropogenic activities (Doney et al., 2012). These anthropogenic activities and subsequent emissions of GHGs into the atmosphere have led to global warming (Von Schuckmann et al., 2016). These changes have increased the atmospheric thermal energy transmitted into the ocean, resulting in ocean warming (Cheng et al., 2019). In particular, ocean warming in the western boundary currents is double in magnitude compared with the average global ocean warming (Wu et al., 2012). This increased thermal energy also acts as the main driver for the deoxygenation of STWNPO (Levin, 2018). Moreover, ocean acidification in the STWNPO has accelerated as atmospheric CO 2 levels increase (Ono et al., 2019). Anthropogenic activities have also driven increased atmospheric nitrogen deposition (AND), significantly impacting the N-limited oligotrophic STWNPO (Kim et al., 2014). In the future, these environmental changes will affect ocean ecosystems and eventually alter N 2 O production and distribution, which are controlled by bacterial communities (nitrification and denitrification). Therefore, it is not only necessary to elucidate the N 2 O production and distribution mechanisms in STWNPO, but also to demonstrate the sensitivity or responsiveness of this region to ongoing environmental changes.
Over the last three decades, several studies have assessed the mechanisms of N 2 O production and distribution in the core of the western North Pacific Ocean (Yoshida et al., 1989;Toyoda et al., 2002;Breider et al., 2015;Yoshikawa et al., 2016) along latitudinal transects (Butler et al., 1989;Zhan et al., 2017). However, these studies have investigated only a few locations of subtropical convergence or only the surface layer, hence, they provide limited information on the mechanisms associated with N 2 O cycling in the STWNPO. Here, we present an in-depth investigation of the overall N 2 O dynamics of the understudied STWNPO. The present study aimed to achieve the following objectives: (1) determine the spatial distributions and production of N 2 O, (2) identify and quantify the factors controlling N 2 O production, (3) determine whether the STWNPO acts as a sink and/or source of atmospheric N 2 O content, and (4) evaluate the relationship between future global changes and the N 2 O dynamics of the STWNPO.

Sampling and Measurements of Physical and Biogeochemical Data
This investigation was conducted in the STWNPO, between 15 and 28°N and 135°E ( Figure 1A) onboard the R/V Isabu, from May 27 th to June 4 th , 2020. Seawater was collected at eight stations ( Figure 1A), and at each station, 24 vertical samples were collected from the surface down to a depth of 5774 m using Niskin bottles on a rosette sampler. At all stations, temperature, salinity, and dissolved oxygen (DO) profiles were determined using an SBE 911 Plus (CTD; Sea-Bird, USA) sensor system attached to a rosette sampler. The accuracies of temperature, conductivity, and oxygen sensors were ± 0.001°C, ± 0.0003 S m -1 , and ± 2% of saturation, respectively. The wind speed above the sea surface (29 m) was also measured using an ultrasonic wind sensor (Ventus, Lufft, Germany) and later converted to a 10 m height following the log wind profile method (Holmes, 2007). The accuracy of the wind sensor is ± 0.2 m s -1 .
To determine nutrient concentrations, seawater samples were collected in 15 mL acid-rinsed bottles and stored at −20°C until further analysis. Nitrate (NO − 3 ) and phosphate (PO 4 3-) were analyzed in the laboratory using a QuAAtro autoanalyzer (Seal Analytical, Germany). The analytical precision of the nutrients was greater than 1%. To determine chlorophyll-a (Chl-a),~4 L of seawater was filtered through 47 mm Whatman GF/F filters and frozen at −80°C. In the laboratory, pigments were extracted using 90% acetone (Ritchie, 2006), and the Chl-a concentrations were measured using a Trilogy Fluorometer (Model # 7200-002, Turner designs, USA) with an analytical precision of ± 0.05 μg L -1 . Seawater samples for pH estimation were collected according to the protocol of Dickson et al. (2007) and were later spectrophotometrically assessed using an unpurified meta-cresol purple indicator (Douglas and Byrne, 2017a;Douglas and Byrne, 2017b) with an accuracy of ± 0.004 pH units.

Determinations of Atmospheric/Dissolved N 2 O
To estimate the historical values of atmospheric N 2 O concentrations, a dataset of atmospheric N 2 O concentrations was aggregated, spanning AD 800 to AD 2020. Data between 800 and 1977, when atmospheric N 2 O had not been monitored, were obtained from studies of Antarctic ice cores (Battle et al., 1996;Schilt et al., 2010). Data from 1979 to 1986 were obtained from the Air Monitoring Program of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Cape Grim, Australia. Although there is a limit to the available information representing the spatial variability of atmospheric N 2 O concentrations for the entire planet, obtaining this information is simultaneously beneficial and the sole data source.
The longitudinal difference in atmospheric N 2 O concentrations in the North Pacific Ocean is insignificant because of the zonally well-mixed atmosphere and lack of strong sources or sinks (Ishijima et al., 2009). However, as N 2 O emissions (e.g., from agriculture, industry, and natural soil) are more significant in the Northern Hemisphere than in the Southern Hemisphere, atmospheric N 2 O is also higher in the Northern Hemisphere than in the Southern Hemisphere (Supplementary Figure S1A). From 1987 to 2020, the mean difference in atmospheric N 2 O concentrations between hemispheres was 1.13 ± 0.59 ppb. Hence, to reflect atmospheric N 2 O over the North Pacific Ocean as accurately as possible, the data between 1987 and 2020 were taken from the air monitoring program run by the NOAA Earth System Research Laboratories (ESRL) in Mauna Loa, Hawaii.
Subsequently, spline interpolation was applied according to time to the total aggregated N 2 O data because it comprised discrete values (Supplementary Figure S1B). However, our approach does not accurately reflect the spatial variability of the dataset before 1987, when atmospheric N 2 O data for the North Pacific Ocean was limited, and may underestimate the equilibrium N 2 O of seawater, expressed as N 2 O eq = N 2 O air • b • P, where N 2 O air is the atmospheric N 2 O level, b is the Bunsen solubility (nmol L −1 atm −1 ) determined from the relationship between the potential temperature and salinity of seawater (Weiss and Price, 1980), and P is the atmospheric pressure (atm). However, for the pre-1980s period, estimating the exact impact of utilizing data from the Southern Hemisphere (i.e., Antarctica and Cape Grim, Australia) is still limited by data availability.
The seawater samples used to quantify the dissolved N 2 O concentrations were carefully transferred from the Niskin sampler to 120 mL glass bottles, and 100 mL of saturated HgCl 2 was added to inhibit biological activity. The sample bottles were tightly sealed with rubber stoppers and aluminum caps to avoid interaction with ambient air (Wilson et al., 2018). We used the headspace method with a cavity ring-down spectrometer (CRDS; Model G2308, USA) to estimate the dissolved N 2 O gas in the water samples. This laser-based method uses gas optical absorbance characteristics with a precision of < 7 ppb (Heo et al., 2021). Subsamples were transferred from 120 mL glass bottles into a 100 mL glass gastight syringe, and 40 mL of high-purity N 2 O-free air was then added to the syringe. The sample and N 2 O-free air in the syringe were gas equilibrated using an action shaker (ASA-026-12, ASIA TESTING MACHINE, South Korea). This equilibrated gas (i.e., gas in the headspace of the syringe) was then injected into the CRDS to measure its N 2 O concentrations. The following equation was used to calculate and convert the N 2 O concentrations in the equilibrated gas to dissolved N 2 O concentrations in the seawater samples (Eq. 1): where N 2 O conc. is the dissolved N 2 O concentration in the seawater sample (nmol L -1 ), b is the Bunsen solubility (nmol L −1 atm −1 ) determined from the relationship between the potential temperature and salinity of seawater (Weiss and Price, 1980), х is the dry N 2 O mole fraction (ppb) measured in the headspace, P is the atmospheric pressure (atm), V w is the volume of the seawater sample (mL), V hs is the volume of the headspace phase (mL), R is the gas constant (0.082057 L atm K −1 mol −1 ), and T is the equilibration temperature in Kelvin (K) (Wilson et al., 2018). We determined the measurement accuracy of the N 2 O concentration in seawater by measuring the concentration of N 2 O standard gas once every 15 seawater samples. The standard was certified as 334.1 ppb (± 1%) by the Korean Research Institute of Standards and Science. The ensemble standard deviation of all gas standard measurements was 2.8% (mean: 328.8 ± 2.3 ppb) (Supplementary Figure S2). As the gas standard measurements overlapped with the precision of the certified standard values and the instrument, the seawater samples were measured without any adjustments. In addition, we measured duplicate seawater samples, with a measurement discrepancy of approximately 4%.

Estimations of Excess N 2 O and Transit Time Distribution Ages
Excess N 2 O (DN 2 O), which is the amount of biogeochemically produced N 2 O, was estimated as the difference between the equilibrium N 2 O (N 2 O eq , refer to the section 2.2) and the measured N 2 O concentration (N 2 O measured ) (Yoshinari, 1976;Walter et al., 2006;Kock et al., 2016;Heo et al., 2021) and is expressed as follows: To accurately estimate DN 2 O, we first assessed the time when a water parcel was last in contact with the atmosphere (i.e., ventilation age) using the transit time distribution (TTD) method. Historical N 2 O a i r values varied over time (Supplementary Figure S1B), and given that the Pacific Ocean is the oldest in the world, the age of each water parcel should be considered when selecting a value of N 2 O air for calculations of N 2 O eq away from the surface. The TTD method was initially developed by Waugh et al. (2003) and has been widely applied to various marine environments (e.g., Tanhua et al. (2008); Kim et al. (2013); Sonnerup et al. (2019); Ko and Quay (2020)). Below, we briefly describe how this method was applied in the present study using CFC measurements. In summary, we calculated water mass ages approximately ranging from 0 to 1200 yr. for 0−5774 m (Supplementary Figure S3).
The transit time distribution (TTD) method assumes that inert tracers present at the surface are transported into the ocean interior, and their concentrations are affected by physical processes (e.g., advection and diffusion) (Waugh et al., 2003;Tanhua et al., 2008;Kim et al., 2013). Using this method, ventilation times can be obtained (Waugh et al., 2003). The following equations describe this method: where C(x,t) is the concentration of the inert tracer (i.e., CFCs; see measurement details below) at the interior location (x) and contemporary time (t), C 0 (t-t') is the surface concentration considering the time taken to enter the ocean interior from the surface (t-t'), and t' is the transit time from the surface to the interior location. G(x,t') is the distribution of transit times (i.e., TTD) for a water parcel from its surface of origin to its inner location, and G(x,t')dt' represents the mass fraction of the water parcel that last made contact with the surface of origin from time t' to time (t' + dt'). For a finite domain with nonzero diffusion, the TTD is always positive and ∫ ∞ 0 Gdt 0 equals 1, assuming that all water parcels had surface contact at some time in the past. To characterize the TTD, it can be written in the form of a simple function, the free parameters of which can be estimated from tracer observations using the inverse Gaussian function Waugh et al., 2006) as follows: where t is t'/G as a dimensionless time, G is the mean transit time, and D is the width (spread) of the transit time. G and D can be associated with a one-dimensional model using Peclet number corresponding to Pe = (G/D) 2 = vL/K, where v is the advective flow, L is the transport length, and K is the diffusivity (mixing) Sonnerup et al., 2015). As the inverse Gaussian function can be fully described by two parameters, G and D, the D/G ratio plays an important role in determining TTD age. A higher D/G ratio indicates that physical mixing is vigorous and that the water parcels are older. In contrast, a lower D/G ratio (i.e., closer to zero) indicates that advection is predominant and that the water parcels are younger. To minimize errors when using the TTD method, selecting a suitable D/G ratio for the study area is essential. We used CFC11 and CFC12, collected during the July-August 2016 CLIVAR P09 cruise (Supplementary Figure S3), as inert tracer gases using the TTD method. To identify a suitable D/G ratio for STWNPO, we compiled the D/G ratios that have been applied to various regions (Supplementary Table S1). Ideally, the TTD ages from different tracers should be equal, so we compared the correlations between TTD ages from CFC11 (TTD CFC11 age) and CFC12 (TTD CFC12 age) along with D/G ratios of 0.8, 1.0, and 1.2 (Supplementary Figure S4). For all D/G ratios, the correlation between TTD CFC11 age and TTD CFC12 age was high. We also compared the excess N 2 O (DN 2 O) in the water column, as estimated from the TTD CFC12 ages for each D/G ratio (i.e., DN 2 O 0.8 , DN 2 O 1.0 , and DN 2 O 1.2 ) (Supplementary Table S2). The mean of the differences between DN 2 O 0.8 and DN 2 O 1.0 and between DN 2 O 1.0 and DN 2 O 1.2 was 0.07 ± 0.07 nmol L −1 and 0.09 ± 0.11 nmol L −1 , respectively. The DN 2 O values of the available D/G ratios were not significantly different. Therefore, we used the mean D/G ratio of 1.0. N 2 O saturation (= N 2 O measured /N 2 O eq × 100) was calculated based on N 2 O eq using the water mass age corresponding to D/G ratio of 1.0.
In addition, DN 2 O 1.0 and unmodified DN 2 O (i.e., estimated DN 2 O using a unitary contemporary atmospheric N 2 O concentration) were compared to obtain the error when estimating DN 2 O without considering the water mass age. The mean difference was 1.28 ± 1.12 nmol L -1 , which was 11.3 ± 10.9% compared to the DN 2 O 1.0 (Supplementary Table S2). This suggests that significant distortion may occur when estimating excess N 2 O if the same contemporary atmospheric N 2 O concentration is used for all water depths without considering the water mass age.

Hydrographic Conditions in the STWNPO
The vertical profiles of the hydrographic parameters in the STWNPO are shown in Figures 1B-F, and the distributions of the potential temperature (q) and salinity (S) of the water masses are shown in Figure 2. The distributions of q and S are labeled as N * ( = ½NO − 3 measured − R N:P Â ½PO 3− 4 measured , where R N:P is the Redfield ratio). N* has been widely used as an indicator of nitrogen surplus (e.g., nitrogen fixation) or sinks (e.g., denitrification: NO − 3 ! NO − 2 ! N 2 O/N 2 ), relative to phosphorus (Gruber and Sarmiento, 1997). This study utilized an N:P ratio of 16 ± 1, confirmed by Takahashi et al. (1985) and Anderson and Sarmiento (1994). Given the deviation of this stoichiometric value, the error of N* estimations was 1.65 ± 1.19 mmol L -1 .
These results demonstrated that the distributions of q, S, NO − 3 , and DO between 0 and 200 m depths were the warmest, highly saline, and N-depleted (i.e., oligotrophic) over the study period. In particular, at shallow depths (0-200 m), St. 1 to St. 4, located in the southern region, had a higher mean q (26.34°C), maximum S (35.05 psu), and lower mean DO (195.11 μmol L −1 ), compared to St. 5 to St. 8, which were located in the northern region and had a mean q of 21.97°C, maximum S of 34.96 psu, and mean DO of 205.71 μmol L −1 . These hydrographic variations are likely the reason for the different water masses being part of the surface waters of the STWNPO, that is, the North Pacific Subtropical Underwater (NPSTUW) (Suga et al., 2000;O'Connor et al., 2002;Behrens et al., 2018) in the southern region and the North Pacific Subtropical Mode Water (NPSTMW) (Hanawa and Talley, 2001;Oka, 2009;Rainville et al., 2014) in the northern region. The NPSTMW had higher average NO − 3 (1.56 μmol L −1 ) and Chl-a (0.13 μg L −1 ) concentrations in the northern region, relative to the southern region (1.10 μmol L −1 of NO − 3 and 0.11 μg L −1 of Chl-a). However, in terms of chlorophyll as an indicator of primary productivity, both regions exhibited overall low productivity in the STWNPO during this study ( Figures 1E, F).
In contrast to the upper layer, the intermediate profiles (200-1500 m) in this study showed sharp fluctuations in physicochemical parameters. A pycnocline appeared just below the surface, which is a typical characteristic of North Pacific Central Water (NPCW) (Emery, 2001;Behrens et al., 2018), with an extensive range of q (10-22°C) and S (34.2-35.2 psu) ( Figures 1B, C, 2). In addition, just below the NPCW, the North Pacific Intermediate Water (NPIW) was observed with the lowest S in this study (~34.15 psu) ( Figure 1C) (Talley, 1993;Behrens et al., 2018). The NPIW is ventilated by the Okhotsk Sea or an adjacent subpolar gyre with a low S and high DO. However, NPIW which had lower DO (107.56 ± 32.96 μmol L −1 ) than the overlying NPCW (186.12 ± 8.11 μmol L −1 ) ( Figure 1D) was due to its long residence time (Talley, 2011). In this study, under the NPIW, the Pacific Deep Water (PDW) was observed to have minimum DO concentrations ( Figure 1D) over an extensive range of depths (800-3000 m), and these core conditions were considered hypoxic (<63 μmol L −1 ) (Amakawa et al., 2009;Talley, 2011;Behrens et al., 2018). PDW was also identified as having the maximum nutrient concentration, which was inversely proportional to the DO concentration ( Figures 1D, E) (Talley, 2011), along with its minimum N* signature ( Figure 2). As the PDW is formed by upwelling, diffusion, and continued mixing with adjacent waters, its attributes become less characteristic toward the southern region ( Figures 1D, E) (Talley, 2011).  The water layer beneath the PDW, the Lower Circumpolar Deep Water (LCDW) (Emery, 2001;Kawano et al., 2006;Talley, 2011), was observed to have minimal q (~1.2°C) and high S (~34.68 psu). The LCDW was composed of the densest and most homogeneous waters and was also identified by higher DO and N* and lower nutrient content than the PDW ( Figures 1D, E, 2).
Considered together, our results demonstrate that during the investigation (spring, 2020), the STWNPO comprised six different water masses (NPSTUW, NPSTMW, NPCW, NPIW, PDW, and LCDW) and exhibited strong hydrographic variations (see Supplementary Table S3). To better understand N 2 O dynamics in this study, we divided the water column into three layers according to the vertical distribution of the water masses:  Figure 3A). The variations in N 2 O in the southern region where the NPSTUW exerted influence and in the northern region where the NPSTMW exerted influence ranged from 6.4 nmol L −1 to 9.6 nmol L −1 and from 6.7 nmol L −1 to 9.5 nmol L −1 , respectively. Although the N 2 O concentration was slightly lower in the southern region (mean N 2 O 0-200m southern : 7.4 ± 0.9 nmol L −1 ) than in the northern region (mean N 2 O 0-200m northern : 7.8 ± 0.7 nmol L −1 ), the average N 2 O saturation was higher in the southern region (120.4 ± 6.4%) than in the northern region (113.9 ± 4.4%) (Supplementary Figure S5). The dependence of solubility on temperature can explain these variations in N 2 O concentrations.
Prior to 2010, the N 2 O surface concentrations observed in the vicinity of the Western North Pacific tended to be lower (~5.6 nmol L −1 ), but remained slightly supersaturated compared to equilibrium values (Butler et al., 1989;Yoshida et al., 1989;Toyoda et al., 2002). However, recent observations have indicated that surface N 2 O concentrations increase with increasing latitude-for example, N 2 O concentrations in tropical regions were~6.0 nmol L −1 and those at 30°N were under 8.0 nmol L −1 (Zhan et al., 2017). In addition, other reports from a nearby station (30°N, 145°E) reported that values increase from the surface (~6.6 nmol kg −1 ) toward the euphotic zone limit (~10 nmol kg −1 ) (Breider et al., 2015;Yoshikawa et al., 2016).
In   (Figures 1D, 3A). Below the core depths, N 2 O concentration tended to decrease as DO concentration increased with depth. Our observations are consistent with the findings of previous studies. An earlier study reported higher N 2 O concentrations (~50 nmol L −1 ) at similar latitudes in the eastern region (160°E) of the PDW (Butler et al., 1989), with decreasing DO concentrations toward the southeast. Toyoda et al. (2002) and Breider et al. (2015) also reported similar N 2 O profiles in the intermediate layer of nearby stations. However, the maximum N 2 O was higher in the latter by approximately 42 nmol kg −1 (approximately 43.2 nmol L -1 at a density of 27.4 kg m -3 ) and the DO was lower (approximately 40 mmol L −1 ).
In contrast, the N 2 O concentrations of the PDW in the deep layer showed a gradually decreasing trend (~23.9 ± 2.1 nmol L −1 ) with increasing depth and DO concentrations ( Figure 3A). Additionally, with a stable physicochemical environment ( Figure 1B-E), the underlying LCDW comprised homogeneous N 2 O distributions (20.8 ± 1.1 nmol L −1 and 171.8 ± 9.5%) (Supplementary Figure S5). These results are consistent with previous studies, where N 2 O concentrations in the deep layer decreased with increasing depth and converged to approximately 20 nmol kg −1 (approximately 20.6 nmol L -1 at an average depth of 27.74 kg m -3 ) . Moreover, in the deep layers (depths below 2000 m), the N 2 O concentrations of the North Atlantic Ocean (i.e., 13.6 ± 2.3 nmol L −1 ) were lower than those in the North Pacific Ocean, indicating an accumulation of N 2 O in deep waters over time (Bange and Andreae, 1999).
The relationship between DN 2 O and other biogeochemical tracers, represented by the apparent oxygen utilization (AOU = [DO] eq (q, S) − [DO] measured ) and N*, has been widely used to estimate the biogeochemical production and/or consumption of N 2 O in various marine environments (Nevison et al., 2003;Forster et al., 2009;Zhang et al., 2015;Chen et al., 2021). The AOU is typically interpreted as the amount of DO consumed during remineralization (Redfield et al., 1963;Sarmiento and Gruber, 2006), and a positive correlation between DN 2 O and AOU indicates that nitrification (NH + 4 !NO − 2 !NO − 3 ) is the main pathway for DN 2 O production (Yoshinari, 1976;Nevison et al., 2003). In addition, a negative correlation between DN 2 O and N* indicates N 2 O production via denitrification (Yamagishi et al., 2005;Kock et al., 2016).
The distribution of surface N 2 O increased with depth, with slightly supersaturated values relative to equilibrium values. Higher N 2 O concentrations than the N 2 O capacity of seawater within the surface layer indicated that excess N 2 O (i.e., DN 2 O) was produced within the water column. In addition, fluctuations in physical parameters (i.e., temperature and salinity) could be responsible for the supersaturated N 2 O observed within the surface layer. Because the rate of N 2 O exchange is slower than that of heat exchange, a discrepancy between gas and thermal equilibrium may occur in the mixed layer, resulting in the N 2 O supersaturation of surface water (Zhan et al., 2017).
To investigate the biological effects on N 2 O dynamics, we evaluated the linear relationships between DN 2 O and AOU ( Figure 3B) and the linear relationship between DN 2 O and NO − 3 (Supplementary Figure S6). However, in the mixed layer, the AOU may have been distorted because of biological activity (photosynthesis) and interactions with the atmosphere. The correlation between DN 2 O and AOU in the 0-200 m layer was weaker (R 2 = 0.39, Supplementary Figure S7) than that (R 2 = 0.48) for the 100-200 m layer. Therefore, we set a depth of 100 m as the boundary of the mixed layer (Yoon et al., 2022), and discussed the results below 100 m. In the surface layer, DN 2 O had relatively strong correlations with AOU and NO − 3 (R 2 = 0.48 and R 2 = 0.34, respectively) ( Figure 3B and Supplementary Figure S6). Generally, nitrification in the surface layer is limited by the photoinhibition of nitrifying microorganisms and competition with phytoplankton for ammonia (Lomas and Lipschultz, 2006). Several studies have suggested the possibility of nitrification within the euphotic zone (Wankel et al., 2007;Rafter and Sigman, 2016;Stephens et al., 2020). Therefore, DN 2 O-AOU and NO − 3 correlations suggested that the slightly supersaturated N 2 O of the surface layer during this investigation may be due to the products derived from nitrification within the euphotic zone, and gradually increasing nitrification near the boundary of the euphotic zone. Recent observations of N 2 O production reinforce this suggestion via nitrification at a nearby location (30°N, 145°E) (Breider et al., 2015;Yoshikawa et al., 2016). In addition, the DN 2 O of the surface layer included both in-situ produced N 2 O and transported N 2 O. Approximately 30-50% of the surface DN 2 O may originate from production within the subsurface water at 100-300 m in the subtropical North Pacific Ocean (Popp et al., 2002;Breider et al., 2015).
The highest N 2 O concentration and saturation levels found in the intermediate layer in this investigation suggest that N 2 O production was vigorous. In addition, the correlation between DN 2 O and AOU and between DN 2 O and NO − 3 was significant (R 2 = 0.92 and R 2 = 0.91, respectively) ( Figure 3B and Supplementary Figure S6). In addition, a negative correlation between DN 2 O and N* was evaluated in this layer, where denitrification signals were most likely to be detected, and the correlation between DN 2 O and N* was relatively strong (R 2 = 0.60) ( Figure 3C). These results suggest that nitrification and denitrification may contribute to the DN 2 O production in the intermediate layer, as discussed in the next section. Yoshida et al. (1989) were the first to suggest that both nitrification and denitrification are potential sources of N 2 O through isotopic composition analysis of the western Pacific Ocean (WPO). Similarly, other studies have observed nitrification as a significant source of the highest N 2 O levels Breider et al., 2015).
Supersaturated N 2 O in the deep layer was not as high as in the intermediate layer, but a significant amount of N 2 O was observed Heo et al. N  in this study. We determined that the relationships between DN 2 O and AOU and between DN 2 O and NO − 3 were strongly linear (positively correlated at R 2 = 0.92 and R 2 = 0.81, respectively) ( Figure 3B and Supplementary Figure S6). The relatively homogeneous N 2 O concentrations and hydrographic conditions at the bottom, and the tendency of N 2 O and AOU (and NO − 3 ) to increase with shallower depths suggest that nitrification is the primary source of N 2 O accumulation in the deep layer.
Is it Possible to Enhance N 2 O Production via Water-Column Denitrification in the Oxygen Minimum Layer?
The significant correlation between N 2 O and N* in the intermediate layer is likely represented by the N 2 O production signal via denitrification (hereafter referred to as 'potential denitrification'). However, despite hypoxic conditions, the oxygen concentration in the oxygen minimum layer was higher than that in the oxygen minimum zone (DO < 20 μmol L -1 ) (Paulmier and Ruiz-Pino, 2009), where denitrification usually occurs (Bianchi et al., 2012). A possible explanation for potential denitrification in the open ocean is the formation of 'micro-reducing environments' provided by marine snow (Kim et al., 2013).
As aggregates descend through the water column, they entangle fine suspended particles and accumulate more in the intermediate layer (Alldredge et al., 1990). In the oxygen minimum layer, especially under hypoxic conditions, oxygen influx to the aggregates may be lower. These conditions may form a more favorable reducing microenvironment (Shanks and Reeder, 1993) and allow potential denitrification in the microzones despite aerobic conditions (Li and Peng, 2002). Indeed, aggregates consisting of not only nitrifiers but also denitrifiers on the suspended particles were observed, suggesting that the suspended particles may provide a niche in which coupled nitrification and denitrification processes can occur (Zhu et al., 2018). Yamagishi et al. (2005) also suggested the possibility of denitrification within microzones of aggregates despite the aerobic conditions in the North Pacific Ocean (44°N, 155°W).
As Frey et al. (2020) found that the addition of particulate organic matter increased N 2 O production by denitrification, high availability of NO − 3 increases N 2 O production through denitrification (Weier et al., 1993;Ji et al., 2015). Furthermore, the high NO − 3 concentration in the oxygen minimum layer may provide easy access to NO − 3 . Marchant et al. (2017) also suggested that denitrification aids in respiration under aerobic conditions when the electron acceptor and donor concentrations fluctuate over short temporal and spatial scales, as in permeable environments. This background and our results support potential denitrification. However, it is necessary to exclude the possibility of alternative explanations for the potential denitrification signals, although there is no direct evidence to support the occurrence of potential denitrification in the intermediate layer in the study area. First, the low N* values and high N 2 O concentrations in the intermediate layer are likely due to the influence of the NPIW, which may transport denitrification signals from the eastern North Pacific Ocean, where oxygen is completely depleted in oxygen-deficient zones. Although the NPIW contained relatively low N* values and high N 2 O concentrations at depths adjacent to the oxygen minimum layer, the core of the NPIW exhibited N* of -1.09 mmol L -1 (Figures 2, 3A). We determined that the N* minimum (-7.28 mmol L -1 ) and N 2 O maximum (35.3 nmol L −1 ) values were identified in the oxygen minimum layer occupied by the PDW (Figures 1D, 3). Moreover, while the NPIW core was found at~600 m (salinity minimum in Figure 1C), the lowest N* signals appeared at~1250 m, dominating the PDW. These results indicate that NPIW is not a significant contributor to potential denitrification signals.
Second, the N* technique can not distinguish between denitrification signals from the water column and sedimentary interactions, assuming that all nitrate sinks result from potential denitrification. Hence, we focused on the intermediate layer, which has no direct contact with the bottom layer. Nevertheless, as the PDW originates from the upwelling of bottom water and a mixture of deep waters (Talley, 2011), the water mass history that may involve substantial exposure to the sediment needs to be considered. If the interaction with the sediment affects the signal, the N* value decreases as it approaches the bottom. However, the core of the LCDW contained a relatively high N* value (-2.68 mmol L -1 ), and low N 2 O concentrations (20.0 nmol L −1 ) (Figures 2, 3A) compared to the PDW. These results suggest that the influence of NPIW and sedimentary interactions were not significant contributors to the potential denitrification signals in the oxygen minimum layer.
Based on these N 2 O mechanisms (i.e., nitrification and potential denitrification), we attempted to estimate the fractions of N 2 O production derived from physical and biogeochemical processes in the intermediate layer. N 2 O is derived from two physical processes. First, the dissolved N 2 O concentration of a water parcel can interact with the atmosphere in the surface layer, thereby contributing to the internal N 2 O concentration. Second, mixing with water parcels originating from other surface layers can contribute to the internal N 2 O concentration as the water parcels move from the surface layer to an internal location.
The biological processes involved in N 2 O dynamics in the ocean include nitrification and denitrification. Nitrification is a remineralization process, which consumes oxygen (AOU) and produces N 2 O as a by-product. Freing et al. (2009) used DN 2 O/ AOU as a quantitative indicator of N 2 O production through nitrification. In contrast, denitrification uses nitrate as an electron acceptor instead of oxygen in oxygen-deficient environments, thereby losing nitrogen. Accordingly, N* represents the nitrogen lost compared with phosphate through denitrification. As denitrification also produces N 2 O as a by-product, the relationship between N* and DN 2 O was used as an indicator of N 2 O production through denitrification (Kock et al., 2016;Fenwick et al., 2017).
Before calculating these fractions, we made the following assumptions: (1) N 2 O derived from physical processes is maintained in equilibrium with the atmosphere before ventilation of the water parcels and (2) N 2 O derived from biogeochemical processes is produced only through nitrification and potential denitrification. Although diverse processes interact in the ocean environment, we focused on evaluating these assumptions. The fractions of N 2 O produced were calculated as follows: where N 2 O measured is the measured N 2 O concentration, N 2 O Physical is the N 2 O concentration derived from the physical process (i.e., N 2 O eq ), N 2 O Nitrification and N 2 O Potential denitrification are N 2 O produced by nitrification and potential denitrification, r DN20:AOU and r DN20:N* are the linear regression slopes between DN 2 O and AOU and between DN 2 O and N*, respectively ( Figure 3B), and Zi is the depth (Z) at each station (i). The relationships between DN 2 O and AOU and between DN 2 O and N* were based on N 2 O production according to the oxygen consumption rate through nitrification and N 2 O production according to the nitrate sink through denitrification, respectively. The errors in r DN20:AOU and r DN20:N* were ±7.1% and ±19.3%, respectively, at a confidence level of 95%. Nitrification is a remineralization process, which consumes oxygen, in turn provides nitrate (NO − 3 ) to the water column. Because NO − 3 is also a by-product of nitrification, the linear regression slope between DN 2 O and NO − 3 (i.e., r DN 2 O : NO − 3 ) represents N 2 O production through nitrification. The error in r DN 2 O : NO − 3 was ±7.5% at a confidence level of 95%. To ensure the reliability of the slopes in estimating N 2 O production derived from biogeochemical processes, we compiled a list of slopes obtained for diverse regions (Supplementary Table S4). The slopes of the STWNPO were lower than those in other regions known to have higher productivity (e.g., the eastern tropical Pacific Ocean and eastern tropical Atlantic Ocean). The N 2 O distributions and biogeochemical tracer slopes for the tropical and subtropical North Atlantic Ocean were similar to those in our observations for STWNPO. Although their extremes differ, the two regions show similar hydrographic trends because the upper circulations in both regions are mainly driven by the wind (Talley, 2011). These environments influence N 2 O dynamics and may explain the similar results observed in both regions. Therefore, we assumed that the slope values observed in this study were acceptable for use in our assessment.
The mean fractions of N 2 O production in the intermediate layer were estimated using the AOU and NO − 3 observations (Supplementary Figure S8). Although there was a slight variation in the fraction values between the AOU and NO − 3 , the trend was so similar that we employed the estimations obtained using the AOU. Given the error of r DN20:AOU the error for estimating N 2 O Nitrification was ±1.8%. Given the errors of N* and r DN20:N* , the errors for estimating N 2 O Potential denitrification were ±6.9% and ±3.1%, respectively. Accordingly, the combined uncertainty in N 2 O Potential denitrification was estimated to be ±12.4%. Among the total N 2 O concentrations within the intermediate layer, the fractions of biogeochemically derived N 2 O were greater than those of physical processes. Because of the influence of the oxygen minimum layer in the intermediate water column, N 2 O production from potential denitrification in this study was higher at high latitudes, where lower DO was observed (Supplementary Figure S8). The fractions of N 2 O produced by potential denitrification in biogeochemical processes range from 17 to 25%, suggesting that N 2 O may be produced by potential denitrification in hypoxic waters.
In addition, the N 2 O production rates (i.e., r DN20:AOU and r DN20:N* ) of water masses adjacent to the oxygen minimum layer were compared to investigate the potential N 2 O contribution during the mixing of the water masses (Supplementary Table  S5). The NPIW overlying the upper boundary of the oxygen minimum layer exhibited a relatively high r DN20:AOU (0.11) and r DN20:N* (-1.35). Compared with the production rates in the intermediate layer, the NPIW may contribute approximately 55% of N 2 O N i t r i fi c a ti o n and 37% of N 2 O Potential denitrification in proportion to the mixing ratio. The PDW in the deep layer, which is underlying the lower boundary of the oxygen minimum layer, also exhibited higher r DN20:AOU (0.16) and r DN20:N* (-0.84) and may contribute 64% of N 2 O Nitrification and 27% of N 2 O Potential denitrification in proportion to mixing ratio. For global biological N 2 O estimation (Freing et al., 2012), the impact of denitrification on N 2 O production was considered to occur only in the Arabian Sea and eastern tropical Pacific Ocean. In the oxygen minimum layer of the Arabian Sea and eastern tropical North and South Pacific, the fractions of N 2 O produced through denitrification ranged up to 89%, 35%, and 14%, respectively. They produced higher estimates of the fractions in the Arabian Sea and eastern tropical North Pacific Ocean and lower fractions in the eastern tropical South Pacific Ocean than the present estimates for the STWNPO, where we observed higher DO concentrations in the oxygen minimum layer.
These differences may be attributed to several factors that were not considered in the present study. Non-constant remineralization ratios, including N:P, can vary with depth. The N:P ratio in the Pacific Ocean has been reported to be approximately 12-14 and 15-16 between 1000 and 3000 m and 3000-4000 m, respectively, which influences N* (Anderson and Sarmiento, 1994). However, the present estimation was performed using a constant Redfield ratio of 16, and the preformed nutrients were not considered. Furthermore, as N* is indirect evidence for denitrification, our estimations using N* involve uncertainty. Our estimates could not distinguish N 2 O production via nitrifier denitrification, although nitrifier denitrification is known to contribute to N 2 O production in STWNPO (Breider et al., 2015;Yoshikawa et al., 2016). In addition, we simplified the physical processes involved in the N 2 O dynamics. Significant uncertainties likely accompany these factors. However, as providing the possibility of potential denitrification in the STWNPO is still crucial in the global N cycle, future studies involving tracers such as nitrogen and oxygen isotopes and information on aggregate microzones are needed.

Estimation of N 2 O Flux STWNPO Source or Sink?
To determine whether the STWNPO was a source or sink for atmospheric N 2 O during this investigation, we used the air-sea gas exchange equation presented below: where½N 2 O surface water is the N 2 O concentration in the surface water adjacent to the atmosphere and k w is the gas transfer velocity (cm h −1 ). k w was determined by physical factors (i.e., temperature and wind speed at 10 m). It is significantly influenced by the wind speed because it is proportional to the exponent of the wind speed. During this survey, the maximum wind speed observed at St. 8 was nearly double the overall average wind speed (Supplementary Table S6). Weighted mean wind data (e.g., wind speed data for the 60 days prior to sampling) are sometimes used to avoid overestimating short-term weather fluctuations, such as gusts (Fenwick et al., 2017;Zhan et al., 2021). Although this approach reduces the impact of meteorological changes, it does not accurately reflect hydrographical changes in the ocean. We used average wind speed during the survey to obtain better observation-based results. In addition, to mitigate the differences in k w owing to dynamic wind speed intensities, we used three k w models with different exponents of wind speed, as follows: where WM1999, N2000, and W2014 represent the model references (i.e., Wanninkhof and McGillis (1999), WM1999; Nightingale et al. (2000), N2000; Wanninkhof (2014), W2014), U 10 is the wind speed 10 m above the sea surface. Sc is the Schmidt number, defined as the kinematic viscosity/molecular diffusion (Bergman et al., 2011). The empirical equation proposed by Wanninkhof (2014) was used to calculate the Schmidt number. The three k w models are widely used for ocean environments and have been verified to yield reasonable results [e.g., in the Bering Sea and Southern Ocean (Chen et al., 2014); in the Gulf of Mexico (Kim, 2018); in the STWNPO (Zhan et al., 2017)]. In addition to N 2 O flux due to gusts, we directly compared N 2 O fluxes using three k w models to assess how wind influences N 2 O flux estimations in terms of N 2 O dynamics.  Table S7). Excluding St. 8 (where it was windy during the observations), the average N 2 O flux of the stations was 1.5 ± 0.2 μmol m −2 d −1 , and in contrast, the St. 8 flux was comparatively high (5.6 ± 1.3 μmol m −2 d −1 ). Although the N 2 O saturation at St. 8 was comparatively lower than at lower latitudes (see Section 3.2), the high N 2 O flux would be due to intense wind speeds. This suggests that in STWNPO, surface waters are already supersaturated with N 2 O and could release more N 2 O into the atmosphere during physical stress.
The N 2 O fluxes of the STWNPO varied with time and the estimation methods used. Butler et al. (1989) estimated that N 2 O fluxes ranged from 0.04 to 0.13 μmol m −2 d −1 in the subtropical gyre of the West Pacific Ocean. In that study, the average surface anomaly was lower (~2.5%). In general, open oceans at low latitudes, such as the tropical and subtropical Pacific Ocean, have low variability, and their effects on N 2 O dynamics are small. For example, simulated seasonal variations in parameters related to N 2 O dynamics showed little variation in STWNPO (30°N, 145°E) (Yoshikawa et al., 2016). The N 2 O flux fluctuated slightly higher in winter, but this was because of the wind speed. The surface N 2 O of the STWNPO originates from N 2 O production through nitrification, and the nitrate concentration also shows little seasonal variation. For there to be some effect on existing N 2 O dynamics, a relatively large event must occur. Butler et al. (1989) highlighted El Niño as an event present in their study. El Niño, which is a natural climate variability in the Pacific Ocean, can reduce the upward diffusion of rich subsurface N 2 O by suppressing upwelling, which consequently reduces N 2 O efflux (Cline et al., 1987;Ji et al., 2019). The present study area is distant from this interannual event centered on the equator, which may have caused the differences in the results.
In addition, Zhan et al. (2017) estimated N 2 O fluxes in STWNPO using the k W2014 w method. Their flux estimations were higher (14.8 ± 2.8 μmol m −2 d −1 ) than the present result, despite the surface saturation anomaly being similar (~8%). As we calculated the N 2 O flux analogously (i.e., following Eqs. 8-11), the difference between our flux values and those of Zhan et al. (2017) are most likely due to differences in wind speed around the time of sampling. Some attempts have been made to estimate N 2 O flux in the western North Pacific using the isotopic mass balance method (Breider et al., 2015;Yoshikawa et al., 2016). Their findings showed that the N 2 O distributions in the subtropical and subarctic regions were similar (~6-8 nmol kg −1 ) and higher (~10-11.9 nmol kg −1 ) than those in our results, and the N 2 O fluxes were lower in the subtropical region (0.5-0.9 μmol m −2 d −1 ) than in the subarctic region (~6.3 μmol m −2 d −1 ), but the overall flux values were lower than those in the present observation. Although the spatial and temporal variability of N 2 O production in the STWNPO is very low, our study showed different results related to N 2 O flux compared with other studies. These variations could be the reasons for the different approaches to estimating the N 2 O fluxes in the ocean environment.
The STWNPO serves as an apparent source of atmospheric N 2 O. However, like many other regions worldwide, this region is undergoing various climatic changes that may affect N 2 O dynamics. To understand the variation in N 2 O flux in the STWNPO, we compared the present results with those from other regions dominated by different N 2 O dynamics (Figure 4 and Supplementary Table S8). The N 2 O flux in global ocean conditions fluctuates, but the average flux of a normoxic ocean is estimated to be under 1 μmol m −2 d −1 (Naqvi et al., 2010). N 2 O flux values tended to be higher in the coastal region than in the open ocean ( Figure 4). However, they were occasionally significantly higher in the several regions characterized by high productivity and depleted oxygen (upwelling region). In an upwelling environment, subsurface water is directed toward the surface, accompanied by accumulated N 2 O. This condition also provides a nutrient-rich environment with low DO and triggers high productivity and remineralization. The depletion of oxygen produces N 2 O from nitrification and denitrification. As N 2 O is also consumed by further denitrification (N 2 O ! N 2 ) in oxygen-depleted waters, relatively low N 2 O emissions (but still high compared with normal oceans) into the atmosphere were observed in the eastern tropical South Pacific Ocean at 12.7-30.7 μmol m −2 d −1 (Farıás et al., 2009). Nevertheless, significant N 2 O effluxes in the upwelling region have been recorded at up to 3243 μmol m −2 d −1 (Naqvi et al., 2006;Arevalo-Martıńez et al., 2015;Fenwick and Tortell, 2018;Ji et al., 2019;Morgan et al., 2019). In addition, N 2 O effluxes (2.3 ± 2.7 mmol m -2 d -1 ) were emitted from the southern Chukchi Sea (Heo et al., 2021), which is a highly productive area (Bates and Mathis, 2009). Here, N 2 O was derived from nitrification in the water  Supplementary Table S8. column, and upward transport originated from nitrification or denitrification in the sediment due to the shallow depths, despite oxic environmental conditions.

Implications for Future Studies
Based on our results, we speculated on the implications of ocean warming, deoxygenation, acidification, and anthropogenic nitrogen deposition (AND) on the overall N 2 O dynamics of STWNPO. Since 1900, the western boundary current of the North Pacific Ocean has experienced two-fold greater warming trends than the global average (Wu et al., 2012). Ocean warming is a significant driver of deoxygenation (Levin, 2018), the Oyashio region (NPIW origin) has undergone deoxygenation and increased stratification. The deoxygenation originating therein has propagated into the interior of the North Pacific Ocean (Sasano et al., 2018). The intermediate water column of the middle-and high-latitude North Pacific may lose more oxygen in the future (Bopp et al., 2017). These environmental changes could expand the oxygen minimum layer of STWPO. In addition, ocean acidification in the STWNPO has accelerated in recent years (Ono et al., 2019), and evidence of acidification was observed in this investigation (Supplementary Figure S9).
Furthermore, AND has also been increasing because of human activities that disturb the N cycle in the western North Pacific Ocean (Kim et al., 2014).
The increase in the thermal energy transmitted into the western Pacific Ocean, where N 2 O is slightly supersaturated due to its production via nitrification ( Figure 5), decreases gas solubility. Subsequently, the increased N 2 O efflux into the atmosphere can accelerate the greenhouse effect (positive feedback). The expansion of the oxygen minimum layer could potentially elevate denitrification-based N 2 O production (positive feedback) ( Figure 5). Decreased pH conditions in the ocean also decrease nitrification and N 2 O production (Beman et al., 2011). For instance, recent reports have observed decreases in N 2 O production from 44% to 2.4% (Rees et al., 2016), and from 72.38 to 50.77% , along with decreased pH values. Further, in the western North Pacific Ocean, acidified conditions decreased nitrification but increased N 2 O production through the ammonia-oxidizing archaeal process (Breider et al., 2019) and which has also been observed in a variety of other environments, including in freshwater and upwelling regions (Frame et al., 2017). Despite this evidence, apparent inhibition of nitrification by acidification has been observed in the Pacific and A B FIGURE 5 | (A) Typical vertical profiling of potential temperature (q), salinity (S), and oxygen (DO) concentration during this investigation from the STWNPO.
(B) Schematic representation of N 2 O dynamics in this study. The green and yellow solid arrows represent nitrification and potential denitrification processes, respectively, the green dotted arrows represent the nitrifier denitrification process, and the thickness of the arrows depicts the proportion of the N 2 O production and associated mechanisms within each layer. The red dashed and blue dash-dotted lines represent positive and negative feedback for N 2 O dynamics, respectively. The blue, green, and yellow columns of the pie chart represent the approximate fractions of N 2 O produced through physical (P), nitrification (N), and denitrification (D) processes in the thermocline/oxygen minimum layer (OML), respectively. The estimated N 2 O production for each station is given in the Supplementary Figure S8.
Atlantic oceans (Beman et al., 2011), suggesting that accelerating acidification in the western North Pacific may decrease nitrification rates and N 2 O production (negative feedback) ( Figure 5). AND stimulates productivity by supplying limited nutrients and it consequently elevates nitrification and N 2 O production (positive feedback) (Suntharalingam et al., 2012). Atmospheric dust deposition, the vehicle for AND, directly acidifies the seawater. Nitrification elevated by AND-driven productivity also provides a greater H + concentration in the water column, leading to ocean acidification (negative feedback) (Doney et al., 2007;Sarma et al., 2021). Therefore, AND exerts a combination of positive and negative effects on N 2 O production in STWNPO. However, our present speculations lack direct observations of related parameters, making it difficult to determine a causal relationship. With regard to these speculations, future studies must focus on the impacts of climate change to better understand N 2 O dynamics and the associated air-sea gas exchange in STWNPO.

SUMMARY AND CONCLUSIONS
We investigated the distribution of N 2 O concentrations and their production and controlling mechanisms (N 2 O dynamics) on the surface (0-200 m), intermediate (200-1500 m), and deep layers (1500-5774 m) of the STWNPO. N 2 O concentrations were slightly oversaturated in the surface layer relative to the atmospheric equilibrium and tended to increase with depth. The low DN 2 O in the surface layer was produced by nitrification. In the intermediate layer, N 2 O distribution corresponded with oxygen consumption. Therefore, the maximum N 2 O concentration was observed at the core of the oxygen minimum layer. However, unlike that in the surface column, a significant amount of DN 2 O was produced through nitrification and potential denitrification. The deeper layer exhibited higher DO and lower N 2 O concentrations, and nitrification was the main source of N 2 O in the deep layer. Our results demonstrated that the STWNPO served as an apparent source of atmospheric N 2 O, although not to the extent as the regions known to be N 2 O hotspots. As STWNPO has been characterized by ongoing ocean changes (e.g., ocean warming, deoxygenation, acidification, and atmospheric nitrogen deposition), further clarification is required to understand the N 2 O dynamics of future climate change scenarios. As the present investigation was limited, it is difficult to predict how these environmental changes may affect the future N 2 O dynamics of STWNPO. Therefore, further studies must focus on the N 2 O dynamics associated with environmental changes in the STWNPO region.

DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.