3.4.1 Natural N₂O fluxes

“Natural soil baseline” emissions were obtained from the ensemble mean of the eight terrestrial biosphere models that participated in NMIP-2 that run with preindustrial land cover (Table 1): (1) the Canadian Land Surface Scheme including Biogeochemical Cycles (CLASSIC) (Asaadi and Arora, 2021; Melton et al., 2020; Kou-Giesbrecht and Arora, 2022); (2) the Dynamic Land Ecosystem Model (DLEM) (Tian et al., 2015; Xu et al., 2017; You et al., 2022); (3) the E3SM Land Model (ELM) (Zhu et al., 2019); (4) the Integrated Science Assessment Model (ISAM) (Shu et al., 2020; X. Xu et al., 2021); (5) the Land Processes and eXchanges model – Bern (LPX-Bern v1.4) (Lienert and Joos, 2018; Joos et al., 2020); (6) O-CN (Zaehle et al., 2011); (7) Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) (Goll et al., 2017); and (8) the Vegetation Integrated SImulator for Trace gases (VISIT) (Ito et al., 2018).

Table 1Methods, spatial and temporal resolution, and data sources for the synthesis of the global N₂O budget.

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Natural emission from “Inland water, estuaries, and coastal vegetation”, including inland and coastal waters, were obtained from models by Yao et al. (2020), Maavara et al. (2019), Lauerwald et al. (2019), and Marzadri et al. (2021) as well as the meta-analyses by Hu et al. (2016) and Rosentreter et al. (2023). As the data (rivers, lakes, reservoirs, and estuaries) provided by Hu et al. (2016), Maavara et al. (2019), Lauerwald et al. (2019), and Marzadri et al. (2021) are for the year 2000, we assumed that these values are constant during 1980–2020. Yao et al. (2020) provided annual riverine N₂O emissions using DLEM during 1980–2019. Here, we averaged riverine estimates from Yao et al. (2020), Maavara et al. (2019), Hu et al. (2016), and Marzadri et al. (2021), assuming that the estimates of Maavara et al. (2019) and Hu et al. (2016) represent emissions from larger rivers only, while Yao et al. (2020) and Marzadri et al. (2021) also account for emissions from streams and small rivers. Note further that the estimate by Marzadri et al. (2021) is not fully global, as it excludes river systems north of 60° N. Therefore, we did not use this assessment for the regions of Canada, the USA, Russia, and Europe. DLEM also estimated annual N₂O emissions from global reservoirs, and we averaged these estimates with those from Maavara et al. (2019) to represent emissions from reservoirs during 1980–2020. The estimate for global and regional lakes was based on the long-term average values provided by Lauerwald et al. (2019) and an estimate by the DLEM-TAC model (Li et al., 2024). For estuaries, we combined the estimate of Maavara et al. (2019), which relies on a process-based modeling approach, with a new meta-data analysis by Rosentreter et al. (2023). The analysis of Rosentreter et al. (2023) is observation-based and includes the contribution of coastal vegetated ecosystems, a contribution not accounted for in Maavara et al. (2019). Estuaries and coastal vegetation data are from studies published between 1975 and 2020, and we assume fluxes are constant during 1980–2020 (Rosentreter et al., 2023). To disentangle natural and anthropogenic fluxes, we considered the emissions in the year 1900 simulated by DLEM (Yao et al., 2020) as equivalent to the natural emission, assuming that the N load from land was negligible in that period (Kroeze et al., 1999). Using this approach, we estimated that N₂O emissions from natural sources of rivers, reservoirs, lakes, and estuaries accounted for 44 % (36 %–52 %) of the total emissions from inland waters, taking into account all N inputs (i.e., inorganic, organic, dissolved, and particulate forms).

N₂O emissions from continental shelves were calculated using one data-driven estimate and three high-resolution model estimates for various time periods (Resplandy et al., 2024, also see Sect. S7), namely an observation-based estimate that relied on a random forest (RF) algorithm to interpolate N₂O data (Yang et al., 2020), based on a synthesis of over 158 000 observations of the N₂O mixing ratio, partial pressure, and concentration in the surface ocean from the MEMENTO database (MEM-RF) (Kock and Bange, 2015); an estimate relying on the high-resolution configuration (Berthet et al., 2019) of the global ocean–biogeochemical component of CNRM-ESM2-1 (CNRM-0.25°); and two estimates relying on the ECCO-Darwin model run at $\mathrm{1}/\mathrm{3}$° (ECCO-Darwin1) and $\mathrm{1}/\mathrm{6}$° (ECCO-Darwin2), respectively. Considering that ECCO-Darwin1 and ECCO-Darwin2 relied on the same model, their mean N₂O fluxes were used.

Estimates of natural N₂O emissions from open oceans are derived from four global ocean biogeochemistry models, including Bern-3D (Battaglia and Joos, 2018), NEMOv3.6-PISCESv2-gas (Berthet et al., 2023), NEMO-PlankTOM10 (Buitenhuis et al., 2018), and UVic2.9 (Landolfi et al., 2017). Towards the N₂O budget synthesis, modeling groups reported gridded monthly fluxes at a 1°×1° resolution for the 1980–2020 period. Specific details on ocean model configurations and N₂O parameterizations are reported in the individual model publications.

We combined the estimate from lightning with that from atmospheric production into an integrated category “Lightning and atmospheric production” (Kohlmann and Poppe, 1999; Dentener and Crutzen, 1994). We simplified the Lightning and atmospheric production category as purely natural, although atmospheric production is affected to some extent by anthropogenic activities, such as enhancement of the concentrations of the reactive species NH₃ and NO₂. This category is, in any case, very small, and the anthropogenic enhancement effect is uncertain. The estimate of “Surface sink” was obtained from Schlesinger (2013) and Syakila et al. (2010).

3.4.2 Direct emissions from nitrogen additions (agriculture)

Agriculture N₂O emissions consist of four components: “Direct soil emissions”, “Manure left on pasture”, “Manure management”, and “Aquaculture”. Data for direct soil emissions were obtained as the ensemble mean of N₂O emissions from the average of two inventories (EDGAR v7.0 and FAOSTAT), the SRNM and DLEM models, and the NMIP2 and DLEM models. The statistical model SRNM only covers cropland N₂O emissions. Thus, we added the DLEM-based estimate of pasture N₂O emissions into the two estimates of cropland to represent direct agricultural soil emissions (i.e., SRNM/DLEM or NMIP2/DLEM). Manure left on pasture is the ensemble mean of EDGAR v7.0, FAOSTAT, and DLEM. Manure management emissions are the mean of EDGAR v7.0 and FAOSTAT. FAOSTAT emission factors for N additions are based on the 2006 guidelines. Global N flows (i.e., fish feed intake, fish harvest, and waste) in freshwater and marine aquaculture were obtained from Bouwman et al. (2011, 2013a) and Beusen et al. (2016) and based on the IMAGE-GNM aquaculture nutrient budget model for the 1980–2020 period. We then calculated global aquaculture N₂O emissions as a 1.8 % loss of N waste in aquaculture, i.e., the same EF used in Hu et al. (2012) and MacLeod et al. (2019). The uncertainty range of the EF is from 0.5 % (Eggleston et al., 2006) to 5 % (Williams and Crutzen, 2010), the same range used in the UNEP report (Bouwman et al., 2013b).

3.4.3 Emissions from other direct anthropogenic sources

This category includes “Fossil fuel and industry”, “Waste and wastewater”, and “Biomass burning”. Both emissions from fossil fuel and industry and waste and wastewater were calculated as the ensemble means of EDGAR v7.0 and UNFCCC databases. The biomass burning emission is the ensemble mean of FAOSTAT, DLEM, and GFED4s databases. In EDGAR v7.0, the Waste and wastewater category includes “Waste incineration” and “Wastewater handling”. We merged “Transportation”, “Energy”, “Industry”, and “Residential and other sectors” to represent the total emission from fossil fuel and industry. The FAOSTAT emissions database of the Food and Agriculture Organization of the United Nations (FAO) covers emissions of N₂O from agriculture and land use by country and globally, from 1961 to 2020 for agriculture and from 1990 for relevant land-use categories, i.e., cultivation of Histosols, biomass burning, etc., applying only Tier-1 coefficients (Tubiello et al., 2021, 2022; Conchedda and Tubiello, 2020; Prosperi et al., 2020). In addition to the IPCC agriculture burning categories “Burning crop residues” and “Burning savannah”, we included FAOSTAT estimates for N₂O emissions from deforestation fires, forest fires, and peatland fires (Prosperi et al., 2020).

3.4.4 Indirect emissions from anthropogenic N additions

This category considers N deposition on land and the ocean (“N deposition on land” and “N deposition on ocean”) as well as the N leaching and runoff from upstream (“Inland and coastal waters”). The emission from N deposition on ocean was provided by Suntharalingam et al. (2012) and includes emission from both open oceans and continental shelves, while emission from N deposition on land was the average of two estimates by NMIP2/EDGAR v7.0 and NMIP2. EDGAR v7.0 provided estimates of indirect emissions from both agricultural and non-agricultural sectors; however, here, we sum the ensemble mean of NMIP2 estimates of indirect emissions from agricultural sectors with indirect emissions from the non-agricultural sector of EDGAR v7.0 (i.e., NMIP2/EDGAR v7.0) to represent N-deposition-induced soil emissions from both agricultural and non-agricultural sectors. The N₂O emissions from inland and coastal waters consist of rivers, reservoirs, lakes, estuaries, and continental shelves, which is the ensemble mean of an average of two inventories (EDGAR v7.0 indirect N₂O emissions – leaching and runoff – and FAOSTAT), and the mean of meta-analysis and models. The anthropogenic emission from inland freshwaters estimated by Yao et al. (2020) considered annual N inputs and other environmental factors (i.e., climate, elevated CO₂, and land-cover change). The results in Yao et al. (2020) suggested that 56 % of the total N₂O emissions from rivers, reservoirs, estuaries, and lakes was attributed to anthropogenic N additions. Empirical methods (empirical models and meta-analysis) adopted this ratio to calculate long-term average anthropogenic N₂O emissions from inland waters, consistent with Tian et al. (2020). Seagrass, mangrove, and salt marsh N₂O emissions were updated from Rosentreter et al. (2023).

3.4.5 Perturbation of N₂O fluxes from climate, CO₂, and land-cover change

The estimate of climate and CO₂ effects on emissions was based on eight NMIP2 models, and we used SH1–SH7 and SH1–SH8 to model the effects of CO₂ and climate on global terrestrial soil N₂O emissions (Table 2), respectively. The effect of land-cover change on N₂O dynamics includes the reduction due to the “Long-term effect of reduced mature forest area” and the additional emissions due to the “Post-deforestation pulse effect”. The two estimates were based on the bookkeeping approach and the DLEM model simulation. The bookkeeping method has been developed by Houghton et al. (1983) to account for carbon flows due to land use. In the original bookkeeping model developed by Houghton et al. (1983), land conversion and the affected carbon pools are tracked each year. The initial values of carbon pools are set for each type of land use. Annual changes in carbon pools in areas affected by land-use change or some land management practices (like wood harvest and fire management) are prescribed in the model using response curves, which are usually a function of the age of the newly converted land use. These response curves are specific for each type of land-cover type and land-use change and do not include the effects of environmental changes (Houghton and Castanho, 2023). For each age cohort, it either gains carbon (afforestation or reforestation) or loses carbon (deforestation) until its carbon pools reach a new stable state (the response curve converges). A similar bookkeeping method was developed to account for N₂O emission due to deforestation. Here, different from the original bookkeeping model calculating carbon fluxes through tracking changes in vegetation or soil pools, response curves directly tracking annual N₂O emissions after deforestation, which are also a function of the age of newly converted land use, were developed in our bookkeeping method (for details, please refer to Sect. S9).

Table 2Simulation design of NMIP2.

Note: for historical simulations, “^*” indicates that the forcing during 1850–2020 is included in the simulation, “1901–1920” indicates that the 20-year mean climate condition during 1901–1920 will be used over the entire simulation period, and “1850” indicates that the forcing will be fixed in 1850 over the entire period. Climate data are only available from 1901; we assume the 20-year average value between 1901 and 1920 for the years 1850–1900. N deposition (NDEP) is available only from 1850. N fertilizer (Nfer) before 1910 was zero. Manure N is available only from 1860; we assume manure N at the 1860 value for the years 1850–1860.

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3.4.6 Atmospheric production of reactive nitrogen

N₂O production in the atmosphere is a relatively small component of the global budget. N₂O is produced by the gaseous-phase oxidation of NH₃ in the troposphere; however, there are few published estimates of this source, and it remains poorly constrained. In this paper, we refer to the two known published estimates, which are 0.4 Tg N yr⁻¹ (Kohlmann and Poppe, 1999) and 0.6 (0.3–1.1) Tg N yr⁻¹ (Dentener and Crutzen, 1994), that are derived using global models of atmospheric chemistry and transport. As human activities have greatly affected the atmospheric abundance of NH₃, a significant portion of this source may be considered anthropogenic. Lightning production of NO_x indirectly leads to N₂O emission through its oxidation and subsequent deposition on land and the ocean. A recent study estimated the global lightning production of NO_x to be 9 Tg N yr⁻¹ (Nault et al., 2017), which is larger than previous estimates of 5 (2–8) Tg N yr⁻¹ (Schumann and Huntrieser, 2007). In this study, we assume an effective emission factor of 1 % (De Klein et al., 2006); using the median estimate of 5 Tg N yr⁻¹ of NO_x, we then estimate a global source of N₂O of 0.05 (0.02–0.09) Tg N yr⁻¹. There is also N₂O production from N₂ + O(¹D), which amounts to about 2 % of the atmospheric source in the stratosphere (Estupiñán et al., 2005).

3.5.1 Atmospheric burden and trends from tropospheric observations

The monthly tropospheric N₂O mole fraction and its growth rate are derived from three different atmospheric observational networks: the Advanced Global Atmospheric Gases Experiment (AGAGE; Prinn et al., 2018), the Commonwealth Scientific and Industrial Research Organization (CSIRO; Francey et al., 2003), and the National Ocean and Atmospheric Administration (NOAA; Dutton et al., 2023; Lan et al., 2022). Further information on the three networks' stations, instruments, calibration, and uncertainties as well as access to data are provided in Sect. S12 “Atmospheric N₂O Observation Networks”.

The atmospheric burden and its rate of change during 1980–2020 were derived from mean maritime surface abundance (mole fraction) of N₂O (Prather et al., 2023) with a conversion factor of 4.79 Tg N ppb⁻¹ (Prather et al., 2012). Combining uncertainties in measuring the annual mean surface mole fraction, which are <1 ppb (Dlugokencky et al., 1994), with those of converting surface mole fractions to a global mean abundance, we estimate a ±1.4 % uncertainty in the absolute burden (Prather et al., 2012). The uncertainty in the conversion from parts per billion to teragrams does not affect the trend uncertainty. This uncertainty is estimated to be ±0.2 ppb or ±1 Tg N between any 2 years over any recent period, based on the combined NOAA and AGAGE record of surface N₂O taken from Table 2.1 of the IPCC AR5 (Hartmann et al., 2013). Thus, the uncertainty in the burden change between 2 decades (e.g., 2000s to 2010s) is bounded by ±1 Tg N (<0.1 %).

3.5.2 Atmospheric loss rates and trends from stratospheric observations

The NASA Aura Microwave Limb Sounder (MLS) satellite instrument has provided consistent global measurements of stratospheric N₂O, O₃, and temperature (T) since August 2004. These have been used with simple stratospheric chemistry models to calculate the monthly mean stratospheric loss of N₂O due to photolysis and oxidation by O(¹D) (Prather et al., 2015, 2023; Minschwaner et al., 1998). Tropospheric chemical loss also occurs, although at a very low rate (<1 % of the total) and is, thus, not included in the calculations.

3.5.3 Atmospheric inversion estimates of N₂O emissions and losses

For the TD constraints on both land and ocean N₂O fluxes for the 1998–2020 period, we used estimates from four independent atmospheric inversion frameworks (INVICAT, PyVAR-CAMS, MIROC4-ACTM, and GEOS-Chem), all of which used a Bayesian inversion method (see the Supplement for details on the inversion frameworks).

The inversion frameworks INVICAT and PyVAR-CAMS used the transport models TOMCAT and LMDz5, respectively, which were both driven by ECMWF ERA5 meteorology, while MIROC4-ACTM used the transport model ACTM, which was driven by JRA-55 meteorology, and GEOS-Chem used the transport model of the same name, which was driven by MERRA-2 meteorology. All inversion frameworks assumed that the prior distribution of emissions followed a normal distribution, with the multivariate mean taken from different models and data products, with standard deviations detailed in the Supplement. Specifically, GEOS-Chem, INVICAT, and PyVAR-CAMS built prior flux distributions for natural soil emissions from the terrestrial biospheric model O-CN (Zaehle et al., 2011) and for biomass burning emissions from GFED-v4s (van der Werf et al., 2017). For anthropogenic emissions from agricultural and non-agricultural sectors (excluding biomass burning), estimates from EDGAR v5 were used to build the prior for the 2005–2020 period (as these estimates were only available up to 2015, the emissions for 2016–2020 were estimated based on those of the year 2015), and the estimates from EDGAR-v4.32 were used for the 1997–2004 period. On the other hand, MIROC4-ACTM used the estimate from the terrestrial biospheric model VISIT for natural soil emissions and EDGAR v4.2 estimates for all anthropogenic emissions.

The inversion frameworks used atmospheric observations from ground-based networks, specifically NOAA, AGAGE, and CSIRO (see the Supplement for details).

The atmospheric transport models also calculate the loss of N₂O in the stratosphere by photolysis and oxidation by O(¹D) radicals (Minschwaner et al., 1998). The TD mean posterior estimates for the 18 land regions were calculated by integrating the gridded fluxes at 1°×1° over each region (the fluxes were interpolated from the original model resolution to 1°×1°).

4.1.1 Trends in atmospheric N₂O mole fractions

The three observation networks AGAGE, NOAA, and CSIRO show consistent growth in atmospheric N₂O mole fractions from 315.8 (315.5–316.2) ppb in 2000 to 335.9 (335.6–336.1) ppb in 2022. The mean annual growth rate increased from 0.76 (0.55–0.95) ppb yr⁻¹ in the 2000s to 0.96 (0.79–1.15) ppb yr⁻¹in 2010s with significant seasonal and interannual variation. In 2020 and 2021, the N₂O atmospheric growth rate was 1.33 and 1.38 ppb yr⁻¹, respectively, both higher than any previous observed year (since 1980), and it was more than 30 % higher than the average value in the decade of the 2010s (Fig. 2). As is shown in Fig. 5, the observed N₂O mole fraction in 2020 (333.2, 332.7–333.5 ppb) has exceeded predicted levels across the four illustrative Representative Concentration Pathways (RCPs) (329.2–331.5 ppb) used in CMIP5 (Meinshausen et al., 2011) and the seven illustrative Socioeconomic Pathways (SSPs) (330.5–331.9 ppb) used in CMIP6 (Meinshausen et al., 2020).

Figure 5Comparison between the measured global N₂O mole fractions from the three GHG observing networks and the projected mole fractions from (a) the four illustrative Representative Concentration Pathways (RCPs) in the IPCC Fifth Assessment Report and (b) the seven illustrative Socioeconomic Pathways (SSPs) used in CMIP6.

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4.2.1 Anthropogenic sources

Global anthropogenic emissions during 1980–2020

Global total anthropogenic emissions increased in the last 4 decades, from 4.8 (3.1–7.3) Tg N yr⁻¹ in 1980 to 6.7 (3.3–10.9) Tg N yr⁻¹ in 2020 (Fig. 6). Among all anthropogenic sources, direct emissions from nitrogen additions in the agricultural sector made the largest contribution to the increase, which grew from 2.2 (1.6–2.8) Tg N yr⁻¹ in 1980 to 3.9 (2.9–5.1) Tg N yr⁻¹ in 2020. Indirect N₂O emissions also steadily increased during the study period, from 0.9 (0.7–1.1) Tg N yr⁻¹ in 1980 to 1.3 (0.9–1.6) Tg N yr⁻¹ in 2020. In contrast, other direct anthropogenic emissions did not have a trend, and the total amount fluctuated around 2.1 Tg N yr⁻¹. Perturbed fluxes from climate, CO₂, and land-cover change led to a small increase in the N₂O sink, from −0.4 (−0.9 to 1.0) Tg N yr⁻¹ in 1980 to −0.6 (−2.2 to 1.8) Tg N yr⁻¹ in 2020.

Figure 6Changes in global anthropogenic N₂O emissions (a) and N₂O emissions from different sectors (b–e) during 1980–2020. In each panel, the line represents the mean N₂O emission of different estimates, and the shaded area shows minimum and maximum estimates.

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Direct emissions from nitrogen additions in the agricultural sector (agriculture)

In the past 4 decades, N₂O emissions from all four sources within the agricultural sector significantly increased (Fig. 7), with the largest contribution from direct soil emissions (from 1.1 Tg N yr⁻¹ in 1980 to 2.1 Tg N yr⁻¹ in 2020), followed by manure left on pasture (from 0.9 Tg N yr⁻¹ in 1980 to 1.4 Tg N yr⁻¹ in 2020), aquaculture (from 0.01 Tg N yr⁻¹ in 1980 to 0.12 Tg N yr⁻¹ in 2020), and manure management (from 0.24 Tg N yr⁻¹ in 1980 to 0.26 Tg N yr⁻¹ in 2020).

Figure 7Changes in global direct N₂O emissions from fertilizer and manure applied on agricultural soils (a), manure left on pasture (b), manure management (c), and aquaculture (d) during 1980–2020.

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Direct soil emissions accounted for the largest proportion of emissions from the agriculture sector. All four estimates show a steady increase in direct soil emissions since 1980 (Fig. 7a). Among them, NMIP2/DLEM exhibited the largest magnitude and the fastest increase rate, from 1.1 Tg N yr⁻¹ in 1980 to 2.6 Tg N yr⁻¹ in 2020. By contrast, SRNM/DLEM suggested the slowest increase rate, from 1.0 Tg N yr⁻¹ in 1980 to 1.7 Tg N yr⁻¹ in 2020. The estimates of the two inventories (FAOSTAT and EDGARv7.0) exhibited similar magnitudes and trends, especially after 1990. All three estimates suggested a significant increasing trend for N₂O emissions from manure left on pasture over the 1980–2020 period. Although all methods showed an increasing trend, they had significant differences in magnitude and increase rate (Fig. 7b). FAOSTAT showed the largest magnitude and increase rate, from 1.2 Tg N yr⁻¹ in 1980 to 1.9 Tg N yr⁻¹ in 2020. However, DLEM showed a smaller magnitude and a slower increase rate, from 0.5 Tg N yr⁻¹ in 1980 to 0.9 Tg N yr⁻¹ in 2020. Although the two inventory estimates for emissions from manure management showed similar temporal variations, FAOSTAT has a larger magnitude than EDGARv7.0 (Fig. 7c). According to the IMAGE-GNM aquaculture nutrient budget model, N₂O emissions from aquaculture increased more than 10-fold, from 0.01 Tg N yr⁻¹ in 1980 to 0.12 Tg N yr⁻¹ in 2020 (Fig. 7d).

Other direct anthropogenic sources

Fossil fuel and industry emissions accounted for the largest proportion of N₂O emissions from other direct anthropogenic sources. Estimates from two approaches showed different trends during their overlapping period: EGDARv7.0 had an increasing trend from 0.9 Tg N yr⁻¹ in 1990 to 1.1 Tg N yr⁻¹ in 2020, while EDGAR/UNFCCC did not show a trend with 1.0 Tg N yr⁻¹ in 1990 and 1.0 Tg N yr⁻¹ in 2020 (Fig. 8a). These inventories, however, do not capture a strong increase in emissions from adipic acid production since 2010 (Davidson and Winiwarter, 2023). Both EDGARv7.0 and EDGAR/UNFCCC show a steady and significant increase in N₂O emissions from waste and wastewater. Although EDGAR/UNFCCC shows a larger magnitude than EGDARv7.0, these two inventory estimates display similar growth rates (Fig. 8b). There are large uncertainties in the magnitude and temporal trend in N₂O emissions from biomass burning (Fig. 8c). DLEM and GFED show a larger magnitude of emissions than FAOSTAT. Both DLEM and GFED have a decreasing trend over the overlapping period from 1997 to 2020, but FAOSTAT shows no significant trend during this period.

Figure 8Changes in N₂O emissions from other direct anthropogenic sources between 1980 and 2020: fossil fuel (a), waste and wastewater (b), and biomass burning (c).

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Indirect emissions from anthropogenic nitrogen additions

Global anthropogenic N₂O emissions from inland waters, estuaries, and coastal vegetation continuously increased during 1980–2020 (Fig. 9a). Although all methods revealed an overall increasing trend in emissions, process-based models show a much smaller magnitude and increase rate than the two inventories. According to meta-analysis and models, anthropogenic emissions from inland and coastal waters increased from 0.1 Tg N yr⁻¹ in 1980 to 0.15 Tg N yr⁻¹ in 2020. In contrast, EGDARv7.0 and FAOSTAT showed that emissions increased from 0.33 and 0.35 Tg N yr⁻¹ in 1980 to 0.53 and 0.57 Tg N yr⁻¹ in 2020, respectively. Emissions from N deposition on land also continued to increase during 1980–2020 (Fig. 9b). NMIP2 and NMIP2/EDGAR v7.0 show emissions increasing from 0.6 and 0.4 Tg N yr⁻¹ in 1980 to 0.9 and 0.6 Tg N yr⁻¹ in 2020, respectively.

Figure 9Changes in indirect N₂O emissions from anthropogenic nitrogen additions to inland waters (rivers, lakes, and reservoirs), estuaries, and coastal vegetation (a) as well as N deposition on land (b) during 1980–2020.

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Perturbation fluxes from climate, CO₂, and land-cover change

The spread between different estimates (DLEM and the bookkeeping method) of the post-deforestation pulse effect increased from the 1980s to the 2010s. The post-deforestation pulse effect was 0.8 (0.6–1.1) Tg N yr⁻¹ in 1980 and 0.8 (0.4–1.3) Tg N yr⁻¹ in 2020 (Fig. 10a). In contrast, DLEM and empirical approaches are comparable in terms of the magnitude and temporal changes in the long-term reduction effect of deforestation, with both approaches suggesting a strong long-term reduction effect, which grew from −1.2 (−1.0, −1.4) Tg N yr⁻¹ in 1980 to −1.4 (−1.3, −1.6) Tg N yr⁻¹ in 2020 (Fig. 10b). In general, deforestation had a negative effect on global soil N₂O emissions. However, most NMIP2 models suggested a positive effect of climate change on soil N₂O emissions, although with large uncertainty and significant interannual variation; this positive climate feedback significantly increased during the past 4 decades (Fig. 10c). In contrast to climatic effects, most NMIP2 models suggested a negative effect of rising atmospheric CO₂ concentration on soil N₂O emissions through increasing nitrogen use efficiency and, hence, reducing soil N availability (Fig. 10d). However, NMIP2 models have large discrepancies in the CO₂ fertilization effect on N₂O emissions; ELM and ISAM suggested a positive effect, while all the other models suggest a negative effect.

Figure 10Changes in perturbed N₂O fluxes from changes in climate, CO₂, and land cover during 1980–2020. In each panel, the line represents the mean N₂O emission of different estimates, and the shaded area shows minimum and maximum estimates.

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4.2.2 Natural N₂O sources

Emissions from natural soils and open oceans remained relatively steady throughout the study period from 1980 to 2020, with mean estimates fluctuating between 9.9 and 10.3 Tg N yr⁻¹ (minimum estimates: 6.2–7.1 Tg N yr⁻¹; maximum estimates: 12.8–13.6 Tg N yr⁻¹). Natural emissions from all other sources including shelves, inland waters, and lightning and atmospheric production were assumed to be constant during 1980–2020. According to BU approaches, the total natural emissions from these sources were 1.8 (1.0–3.0) Tg N yr⁻¹. The mean value of global N₂O emissions from all of the abovementioned sources fluctuated between 11.7 and 12.1 Tg N yr⁻¹, with an average of 11.9 Tg N yr⁻¹. Global natural N₂O emissions also have a large uncertainty, with the maximum estimates (15.8–16.6 Tg N yr⁻¹) roughly double the minimum estimates (7.1–8.1 Tg N yr⁻¹).

Natural soil N₂O emission baseline

The natural soil N₂O emission baseline represents the preindustrial soil N₂O emissions derived from NMIP2 simulations, driven by potential vegetation/land cover and other environmental factors in the preindustrial period (1850). Global natural soil N₂O emissions are estimated to be 6.4 Tg N yr⁻¹, and they account for 55 % of the total natural emissions. However, N₂O emissions from natural soils estimated by the NMIP2 showed large divergences among eight models. Among the NMIP2 models, ELM had the highest estimate with an average of 8.6 Tg N yr⁻¹, which was more than double the estimate from the CLASSIC model (3.9 Tg N yr⁻¹).

Natural N₂O emission baseline from the open ocean and continental shelves

We also estimated N₂O emissions from the open oceans and continental shelves. Open ocean is the second largest source of natural N₂O emissions, with a global mean value fluctuating between 3.4 and 3.8 Tg N yr⁻¹ during 1980–2020. Open-ocean N₂O emissions were estimated by four ocean models. Among these models, NEMOv3.6-PISCESv2-gas had the highest estimate, with an average of 4.6 Tg N yr⁻¹, while NEMO-PlankTOM10 had the lowest estimate, with an average of 2.8 Tg N yr⁻¹. The four ocean models show different trends in open-ocean emissions. NEMOv3.6-PISCESv2-gas shows a slight increasing trend, whereas the other three models show consistent decreasing trends. In addition to open oceans, shelves are an important source of N₂O emissions that was not quantified in the previous global N₂O budget (Tian et al., 2020). Global shelf N₂O emissions were estimated by two high-resolution models (CNRM and ECCO) and one data product (MEM-RF). The average of the three estimates is 1.2 Tg N yr⁻¹, ranging from 0.6 Tg N yr⁻¹ (ECCO) to 1.6 Tg N yr⁻¹ (MEM-RF).

Natural N₂O emission from inland waters, estuaries, and coastal vegetation

Natural N₂O emissions from inland waters and estuaries were much smaller than emissions from the soils, oceans, and shelves. These emissions have an average value of 0.08 Tg N yr⁻¹, ranging from 0.05 to 0.14 Tg N yr⁻¹. Rivers are the largest source: they emit 0.04 (0.01–0.08) Tg N yr⁻¹ of N₂O and account for 48 % of the natural emissions from inland waters and estuaries. The global natural N₂O emissions from lakes and estuaries were 0.02 (0.01–0.03) and 0.02 (0.02–0.03) Tg N yr⁻¹, respectively.

Lightning, atmospheric production, and natural sinks

The source of reactive N from lightning (and its contribution to N₂O) and the direct production of N₂O from NH₃ in the atmosphere are relatively small, and we have no new estimates in this work. However, synthesizing the available estimates in the scientific literature, we estimate lightning to contribute 0.05 (0.02–0.09) Tg N yr⁻¹ (median and range) (Nault et al., 2017; Schumann and Huntrieser, 2007) and atmospheric production to contribute 0.5 (0.3–1.1) Tg N yr⁻¹ (Kohlmann and Poppe, 1999; Dentener and Crutzen, 1994).

Similarly, the surface sink of N₂O is small. Again, we do not produce a new estimate in this budget and rather only synthesize available estimates from the literature. We estimate the global surface sink to be 0.01 (0.0–0.3) Tg N yr⁻¹.

Figure 11Annual global N₂O emissions during 1997–2020 estimated by four atmospheric inversions (TD models): (a) total global emission, (b) land emission, and (c) ocean emission.

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4.3.1 TD total source

Ensemble estimates across the four atmospheric inversions show that the long-term average global N₂O emissions during 1997–2020 were 16.6 Tg N yr⁻¹ (minimum: 15.5 Tg N yr⁻¹; maximum: 18.2 Tg N yr⁻¹). All four inversions show a significant increasing trend in global N₂O emissions (p<0.05) with a mean rate of increase of 0.10 Tg N yr⁻² (0.08–0.12 Tg N yr⁻²) (Fig. 11a).

TD land emission

The estimates derived from the four inversions show that the land-based emission is the dominant source of N₂O emissions, over ocean sources, and the long-term average land N₂O emission during 1997–2020 was 13.7 Tg N yr⁻¹ (minimum: 12.6 Tg N yr⁻¹; maximum: 15.0 Tg N yr⁻¹), contributing 80 %–85 % of the global N₂O emissions. Land sources dominated the interannual variability in global N₂O emissions and the trend (Fig. 11b). All TD models suggested a significant increasing trend in land N₂O emissions during the study period from 1997 to 2020 (p<0.05), with increase rates ranging from 0.09 to 0.13 Tg N yr⁻², which were higher than the increase rates of prior fluxes (mean: 0.04 Tg N yr⁻²; range: 0.00–0.08 Tg N yr⁻²).

TD ocean emission

The magnitude of N₂O emissions from oceans is much smaller than that from land (Fig. 11c). The mean ocean N₂O emission during 1997–2020 derived from four inversion models was 2.9 Tg N yr⁻¹, ranging from a minimum of 2.7 Tg N yr⁻¹ to a maximum of 3.3 Tg N yr⁻¹. The estimates of MIROC4 were much higher than the estimates of other models. The four inversions show divergent interannual variability, and none suggested a significant trend. The TD estimates of ocean N₂O emission are much smaller than the values estimated by four ocean biogeochemical models, with a global mean value fluctuating between 3.4 and 3.8 Tg N yr⁻¹ during 1980–2020.

4.3.2 TD stratospheric sink

The four inversions have comparable magnitudes of global stratospheric N₂O sink (via photolysis and oxidation by the electronically excited atomic oxygen, O(¹D), in the stratosphere), with an average value of 12.4 Tg N yr⁻¹ (minimum and maximum of 12.2 and 12.7 Tg N yr⁻¹, respectively) for 2000–2020 (Fig. 12). All four inversions found that the global stratospheric N₂O sink increased during 1997–2020 (Fig. 13) in proportion to the growing atmospheric N₂O abundance, with an average rate of increase of 0.05 Tg N yr⁻² (0.03–0.07 Tg N yr⁻²). Differences among the estimates decreased after 2000, likely due to improvements in observation coverage and accuracy but also possibly due to the decreasing influence of the initial mixing ratio fields, which differed among the inversion frameworks. Although the inversions show comparable trends in the sink, they differ with respect to their interannual variability.

Figure 12Global stratospheric N₂O sink estimated by atmospheric inversions and a satellite and photolysis model during 1997–2020.

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Table 3The global N₂O budget (in Tg N yr⁻¹) for the 1980s, the 1990s, the 2000s, the 2010s, and the year 2020.

Notes: BU estimates include four categories of anthropogenic source and one category for natural sources and sinks. The sources and sinks of N₂O are given in teragrams of nitrogen per year (Tg N yr⁻¹). The atmospheric burden is given in teragrams of nitrogen (Tg N). Detailed information on calculating each subcategory is shown in tables in the Supplement. ^a Calculated from satellite observations with a photolysis model (about 1 % of this sink occurs in the troposphere). ^b Calculated from the combined NOAA and AGAGE record of surface N₂O and adopting the uncertainty of the IPCC Fifth Assessment Report (Chap. 6), with a conversion factor of 4.79 Tg N ppb⁻¹.

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Figure 13Comparison of global and regional N₂O emissions estimated using BU and TD approaches. The 18 regions include the United States (USA), Canada (CAN), Central America (CAM), northern South America (NSA), Brazil (BRA), southwestern South America (SSA), Europe (EU), northern Africa (NAF), equatorial Africa (EQAF), southern Africa (SAF), Russia (RUS), Central Asia (CAS), the Middle East (MIDE), China (CHN), Korea and Japan (KAJ), South Asia (SAS), Southeast Asia (SEAS), and Australasia (AUS). The blue lines represent the mean N₂O emission from BU methods, and the shaded areas show minimum and maximum estimates; the red lines represent the mean N₂O emission from TD methods, and the shaded areas show minimum and maximum estimates.

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We also provide an independent estimate of the stratospheric sink based on satellite observations and a photolysis model. This estimate likewise showed that the sink increased, from 12.8 Tg N yr⁻¹ in the 1990s to 14.0 Tg N yr⁻¹ in the 2010s (Table 3), with higher annual loss rates than estimated by the inversions and an average loss of 13.4 Tg N yr⁻¹ for 2005–2021. This estimate also showed large quasi-biennial interannual variability with an amplitude of 7 %. More interestingly, over this time period, the abundance of N₂O in the middle stratosphere, where the greatest loss of N₂O occurs, was increasing at a rate of 5.0±1.2 % per decade, which is faster than the increase in the tropospheric abundance of 2.9±0.0 % per decade. This resulted in a greater loss of N₂O (i.e., more than proportionate to the mean atmospheric increase) and, thus, a decrease in the mean atmospheric lifetime (burden divided by loss) of 2.1±0.7 % per decade, from 119.3 years in the 2000s to 117 years in the 2010s (Prather et al., 2023; also see Table 3). These changes are thought to be a result of an increase in the intensity of the Brewer–Dobson circulation (BDC), which would transport N₂O more rapidly from the troposphere into the mid-stratosphere. An increase in the intensity of BDC is predicted by climate models (Oberländer-Hayn et al., 2016). However, we note that none of the atmospheric inversions found a significant trend in the atmospheric lifetime (although the total loss increased; Fig. 12), and more research is needed to identify why there is this discrepancy.

4.4.1 Global N₂O budget in recent decade (2010–2019)

The BU and TD approaches give remarkably consistent estimates of global total N₂O emissions in the 2010s, with values of 18.2 (10.6–25.9) Tg N yr⁻¹ and 17.4 (15.8–19.2) Tg N yr⁻¹ (Fig. 1, Table 3), respectively. However, the BU estimate shows a large uncertainty range, in part because of the spread of estimates from process-based models. TD approaches estimate that the stratospheric sink (i.e., N₂O losses via photolysis and reaction with O(¹D) in the stratosphere) for the 2010s was 12.6 (12.3–12.9) Tg N yr⁻¹. However, the atmospheric sink estimate based on satellite observations and a photolysis model for the 2010s was 13.4 (12.3–14.5) Tg N yr⁻¹. The imbalance of sources and sinks of N₂O derived from the averaged BU and TD estimates is 4.7 Tg N yr⁻¹. This imbalance agrees well with the observed increase in atmospheric abundance of N₂O between 2010 and 2019 of 4.6 (4.5–4.7) Tg N yr⁻¹. Based on the BU-based estimates, natural sources contributed 65 % of total emissions (11.8, 7.3–15.9 Tg N yr⁻¹) during this period. Specifically, the natural soil flux contributed the most, with the decadal mean of 6.4 (3.9–8.6) Tg N yr⁻¹, followed by the open-ocean emissions (3.5, 2.5–4.7 Tg N yr⁻¹), shelf emissions (1.2, 0.6–1.6 Tg N yr⁻¹), lightning and atmospheric production (0.6, 0.3–1.2 Tg N yr⁻¹), and natural emissions from inland waters and estuaries (0.1, 0.0–0.1 Tg N yr⁻¹) (Fig. 1).

Anthropogenic sources contributed, on average, 35 % to the total N₂O emissions (6.5, 3.2–10.0 Tg N yr⁻¹) in the 2010s. Direct emissions from nitrogen additions in agriculture were 3.6 (2.7–4.8) Tg N yr⁻¹, contributing 56 % of the total anthropogenic emissions (Table 3). Emissions from other direct anthropogenic sources made the second largest contribution, with a decadal mean of 2.1 (1.8–2.4) Tg N yr⁻¹. Indirect emissions from anthropogenic nitrogen additions contributed 19 % of the total anthropogenic emissions, with a decadal mean of 1.2 (0.9–1.6) Tg N yr⁻¹. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions (−0.6, −2.1 to 1.2 Tg N yr⁻¹), mainly because of the negative effects of reduced mature forest area (−1.4, −1.6 to −1.3 Tg N yr⁻¹) and increasing CO₂ concentration (−0.7, −1.5 to −0.3 Tg N yr⁻¹).

4.4.2 Decadal trend in the global N₂O budget

Global N₂O emissions estimated by the BU and TD approaches were comparable in magnitude during the overlapping period from 1997 to 2020, but TD estimates implied a larger interannual variability and a faster rate of increase (Fig. 13a). BU and TD approaches diverge when estimating the magnitude of land emissions compared with ocean emissions, although they are consistent with respect to trends (Fig. 13b). According to the BU approaches, global N₂O emissions increased from 17.4 Tg N yr⁻¹ (10.3–24.0 Tg N yr⁻¹) in 1997 to 18.5 Tg N yr⁻¹ (10.6–27.0 Tg N yr⁻¹) in 2020, with an average increase rate of 0.043 Tg N yr⁻² (p<0.05). In contrast, TD approaches suggested that global emissions increased from 15.4 Tg N yr⁻¹ (13.9–16.7 Tg N yr⁻¹) in 1997 to 17.0 Tg N yr⁻¹ (16.6–17.4 Tg N yr⁻¹) in 2020, implying a higher increase rate of 0.085 Tg N yr⁻² (p<0.05). The BU estimate during 1997–2010 was on average 1.6 Tg N yr⁻¹ higher than the TD estimate. However, after 2010, the difference in the magnitude of emissions between the two approaches is smaller, due to the rapid increase in the TD estimates. From the year 1980, BU approaches suggested a significant increase in global N₂O emissions that was primarily driven by anthropogenic sources (Table 3). Satellite and photolysis models estimate that the atmospheric N₂O burden increased from 1528 Tg N in the 2000s to 1570 in the 2010s and 1592 Tg N in 2020, which is comparable to estimates by atmospheric chemistry transport models, showing an increase in the atmospheric N₂O burden from 1527 (1504–1545) Tg N in the 2000s to 1606 (1592–1621) Tg N in 2020.

Figure 14Ensembles of regional anthropogenic N₂O emissions over the 1980–2020 period. The bar chart in the center shows the total changes in regional and global N₂O emissions during the study period from 1980 to 2020. Error bars indicate the 95 % confidence interval for the average of the changes. A Mann–Kendall test was performed to establish any trends globally and for each region over the 1980–2020 period. The changes were calculated from the annual change rate (Tg N yr⁻²), determined from a linear regression, multiplied by 40 years. All regions except Australasia and the USA show a significant increasing or decreasing trend in the estimated ensemble N₂O emissions during 1980–2020. An asterisk (*) denotes significance at the P<0.05 level.

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4.5.1 United States of America (USA)

For the USA, the TD estimates show higher total N₂O emissions than the BU estimates over the 1997–2020 period (Fig. 13c), with 1.00 (0.69–1.39) and 0.82 (0.31–1.42) Tg N yr⁻¹, respectively. Both approaches suggest that the total N₂O emissions from the USA remained relatively stable during 1997–2020. Based on the BU estimates, changes in climate, CO₂, and land cover caused emission decline over 1980–2020. The flux fluctuated between −0.30 and −0.12 Tg N yr⁻¹, with an average of −0.20 Tg N yr⁻¹. Indirect emissions from anthropogenic nitrogen additions increased from 0.11 Tg N yr⁻¹ in 1980 to 0.13 Tg N yr⁻¹ in 1995 and then decreased to 0.10 Tg N yr⁻¹ in 2020. Direct emissions from nitrogen additions in agriculture increased from 0.25 Tg N yr⁻¹ in 1980 to 0.30 Tg N yr⁻¹ in 2020. However, the increase in direct agricultural emissions was offset by the trend in emissions from other direct anthropogenic sources, which decreased from 0.26 Tg N yr⁻¹ in 1980 to 0.19 Tg N yr⁻¹ in 2020. The total anthropogenic N₂O emissions slightly increased during 1980–2020, at an average rate of $\mathrm{0.6}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻². This increase primarily occurred during 1980–1997 (Fig. 14).

In the 2010s, the BU estimates (0.81, 0.29–1.43 Tg N yr⁻¹) were on average 0.22 Tg N yr⁻¹ lower than the TD estimates (1.03, 0.71–1.45 Tg N yr⁻¹) (Fig. 15). According to the BU results, natural sources contributed 48 % of total emissions (0.39, 0.22–0.65 Tg N yr⁻¹) during this period. Direct emissions from nitrogen additions in agriculture were 0.30 (0.18–0.38) Tg N yr⁻¹, contributing 37 % of the total emissions. Emissions from other direct anthropogenic sources made the second largest contribution to anthropogenic emissions, with a decadal mean of 0.21 (0.18–0.23) Tg N yr⁻¹. Indirect emissions from anthropogenic nitrogen additions contributed 14 % of the total anthropogenic emissions, with a decadal mean of 0.11 (0.07–0.14) Tg N yr⁻¹. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.19 Tg N yr⁻¹ and range of −0.37 to 0.03 Tg N yr⁻¹. Recent study has indicated that N₂O emissions could be increased by freeze–thaw cycles (Del Grosso et al., 2022) and tillage practices (Lu et al., 2022). Our BU estimates did not consider freeze–thaw cycles or tillage practices and, thus, may have underestimated N₂O emissions.

4.5.2 Canada (CAN)

BU approaches suggested a larger magnitude of total N₂O emissions from Canada than TD approaches over the 1997–2020 period (Fig. 13d), with values of 0.29 (0.05–0.69) and 0.12 (0.06–0.19) Tg N yr⁻¹, respectively. BU and TD estimates also showed divergent trends: TD estimates decreased at a rate of $-\mathrm{1.5}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², whereas BU estimates increased at a rate of $\mathrm{0.7}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻². According to the BU results, the increase in total N₂O emissions from Canada was mainly driven by the direct emissions from nitrogen additions in agriculture, which increased from 0.02 Tg N yr⁻¹ in 1980 to 0.05 Tg N yr⁻¹ in 2020. Perturbed fluxes from changes in climate, CO₂, and land cover showed an overall increase from 0.00 Tg N yr⁻¹ in 1980 to 0.02 Tg N yr⁻¹ in 2020. Indirect N₂O emissions from Canada were relatively stable during the study period, while emissions from other direct anthropogenic sources had large interannual variability (Fig. 14).

In the 2010s, the BU estimates of Canada's total N₂O emissions (0.29, 0.07–0.69 Tg N yr⁻¹) were over 2 times higher than the TD estimates (0.12, 0.06–0.20 Tg N yr⁻¹) (Fig. 15). According to the BU results, natural sources contributed 59 % of total emissions (0.17, 0.04–0.43 Tg N yr⁻¹) during this period. Direct emissions from nitrogen additions in agriculture were 0.05 (0.03–0.06) Tg N yr⁻¹, contributing 15 % of the total emissions. Emissions from other direct anthropogenic sources and indirect emissions from anthropogenic nitrogen additions were 0.04 (0.02–0.08) and 0.02 (0.02–0.03) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.01 Tg N yr⁻¹ and a range of −0.04 to 0.09 Tg N yr⁻¹.

4.5.3 Central America (CAM)

TD and BU estimates are comparable with respect to the magnitudes and trends of N₂O emissions from Central America (Fig. 13e), with mean values of 0.42 (0.21–0.64) and 0.35 (0.25–0.47) Tg N yr⁻¹ for the BU and TD approaches, respectively. During 1997–2020, the rate of increase of the BU estimates ($\mathrm{4.7}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²) was higher than that of TD estimates ($\mathrm{2.5}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²). Emissions from other direct anthropogenic sources increased from 0.03 Tg N yr⁻¹ in 1980 to 0.15 Tg N yr⁻¹ in 2020 and were the major driver of the increase in N₂O emissions from Central America. Direct agricultural emissions increased during the study period, from 0.08 Tg N yr⁻¹ in 1980 to 0.11 Tg N yr⁻¹ in 2020. Indirect emissions and perturbed fluxes from changes in climate, CO₂, and land cover were relatively stable during this period (Fig. 14).

The BU and TD approaches gave comparable estimates of total N₂O emissions from Central America in the 2010s, with values of 0.46 (0.24–0.68) and 0.36 (0.24–0.48) Tg N yr⁻¹ for the BU and TD approaches (Fig. 15), respectively. Natural sources contributed 37 % of total emissions (0.17, 0.07–0.26 Tg N yr⁻¹) during this period. Emissions from other direct anthropogenic sources contributed 39 % of the total emissions (0.18, 0.17–0.18 Tg N yr⁻¹). Direct and indirect emissions were 0.11 (0.07–0.14) and 0.02 (0.02–0.03) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.02 Tg N yr⁻¹ and a range of −0.10 to 0.07 Tg N yr⁻¹.

4.5.4 Northern South America (NSA)

TD approaches suggested a larger magnitude of total N₂O emissions from northern South America than BU approaches over the 1997–2020 period (Fig. 13f), with respective values of 0.55 (0.34–0.98) and 0.40 (0.04–1.08) Tg N yr⁻¹ for each approach. During 1997–2020, the increase rate of the TD estimates ($\mathrm{2.2}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²) was higher than that of BU estimates ($\mathrm{0.8}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²). Direct agricultural emissions made the largest contribution to the increase in N₂O emissions from northern South America, increasing from 0.04 Tg N yr⁻¹ in 1980 to 0.07 Tg N yr⁻¹ in 2020 (Fig. 14). N₂O emissions from the other three anthropogenic sectors did not have a significant trend during 1980–2020.

The BU estimates in the 2010s (0.41, 0.03–1.09 Tg N yr⁻¹) were on average 0.17 Tg N yr⁻¹ lower than the TD estimates (0.58, 0.35–1.06 Tg N yr⁻¹) (Fig. 15). The average natural emission was 0.35 Tg N yr⁻¹ in the 2010s, contributing 85 % of total emissions. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.07 (0.05–0.09), 0.02 (0.01–0.02), and 0.01 (0.01–0.02) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.04 Tg N yr⁻¹ and a range of −0.19 to 0.10 Tg N yr⁻¹.

4.5.5 Brazil (BRA)

The average total N₂O emission from Brazil estimated by the BU approaches was 1.21 Tg N yr⁻¹, ranging from 0.26 to 2.32 Tg N yr⁻¹ (Fig. 13g), which was lower than the TD estimates (1.42, 1.18–1.75 Tg N yr⁻¹). Both approaches detected a notable increasing trend in total N₂O emissions during 1997–2020. TD approaches suggested a higher increase rate ($\mathrm{11.6}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²) than BU approaches ($\mathrm{4.3}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²). Direct agricultural emissions, which increased from 0.13 Tg N yr⁻¹ in 1980 to 0.32 Tg N yr⁻¹ in 2020, made the largest contribution to the increase in N₂O emissions from Brazil (Fig. 14). Indirect emissions also showed an increase from 0.03 Tg N yr⁻¹ in 1980 to 0.06 Tg N yr⁻¹ in 2020. Emissions from other anthropogenic sources and perturbed fluxes from changes in climate, CO₂, and land cover did not have an obvious trend during the study period.

The TD estimates in the 2010s (1.51, 1.40–1.79 Tg N yr⁻¹) were on average 0.28 Tg N yr⁻¹ higher than the BU estimates (1.23, 0.24–2.41 Tg N yr⁻¹) (Fig. 15). According to the BU results, the average natural emission was 0.95 Tg N yr⁻¹ in the 2010s, contributing 77 % of total emissions. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.28 (0.22–0.35), 0.09 (0.06–0.11), and 0.05 (0.02–0.07) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.14 Tg N yr⁻¹ and a range of −0.48 to 0.25 Tg N yr⁻¹.

4.5.6 Southwest South America (SSA)

BU and TD estimates are consistent with respect to the magnitude of the total N₂O emissions from southwestern South America during 1997–2020, with values of 0.55 (0.18–1.03) and 0.51 (0.40–0.63) Tg N yr⁻¹ (Fig. 13h), respectively. TD estimates increased at a rate of $\mathrm{5.3}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² over 1997–2020, whereas BU estimates did not have an obvious trend during this period. Among the four anthropogenic sectors, direct agricultural emissions had the largest increase, from 0.10 Tg N yr⁻¹ in 1980 to 0.15 Tg N yr⁻¹ in 2020 (Fig. 14). Indirect emissions also increased from 0.02 Tg N yr⁻¹ in 1980 to 0.03 Tg N yr⁻¹ in 2020. Perturbed fluxes from changes in climate, CO₂, and land cover had a decreasing trend, while emissions from other sectors fluctuated over the study period.

The BU and TD approaches gave similar estimates of total N₂O emissions from southwestern South America in the 2010s, with values of 0.55 (0.19–1.04) and 0.55 (0.44–0.67) Tg N yr⁻¹ (Fig. 15), respectively. The mean natural emission was 0.39 Tg N yr⁻¹ in the 2010s, accounting for 71 % of total emissions. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.14 (0.09–0.19), 0.05 (0.03–0.06), and 0.03 (0.01–0.03) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.05 Tg N yr⁻¹ and a range of −0.16 to 0.08 Tg N yr⁻¹.

4.5.7 Europe (EU)

The BU estimates suggest that Europe had the largest decrease rate of regional N₂O emissions among the 18 regions, and the average decrease rate during 1980–2020 was $-\mathrm{13.3}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² (Fig. 13i). For the 1997–2020 period, this decreasing trend, as estimated by the BU approaches, slowed down ($-\mathrm{7.7}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻²), whereas the TD approach suggests a small increase of $\mathrm{1.6}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² (Fig. 13i). Emissions from other direct anthropogenic sources (including fossil fuel and industry, waste and wastewater, and biomass burning), which decreased from 0.51 Tg N yr⁻¹ in 1980 to 0.18 Tg N yr⁻¹ in 2020, made the largest contribution to the decreasing trend in N₂O emissions from Europe. Direct agricultural emissions and indirect emissions show overall decreasing trends from 0.46 and 0.16 Tg N yr⁻¹ in 1980 to 0.38 and 0.12 Tg N yr⁻¹ in 2020, respectively, mainly due to a reduction in fertilizer use after the collapse of the Soviet Union (Tian et al., 2022). However, the decreasing trend in direct agricultural emissions has leveled off since the 2000s. Perturbed fluxes from changes in climate, CO₂, and land cover decreased during 1980–1985 and then slowly increased (Fig. 14).

The BU and TD approaches gave comparable estimates of European N₂O emissions in the 2010s, with values of 1.00 (0.45–1.57) and 0.86 (0.49–1.36) Tg N yr⁻¹ (Fig. 15), respectively. According to the BU results, natural sources only contributed 26 % of total emissions (0.26, 0.11–0.52 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.38 (0.32–0.44), 0.19 (0.15–0.24), and 0.13 (0.08–0.16) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.03 Tg N yr⁻¹ and a range of −0.21 to 0.22 Tg N yr⁻¹.

4.5.8 Northern Africa (NAF)

For northern Africa, TD approaches suggested a larger magnitude of the total N₂O emissions than BU approaches over the 1997–2020 period (Fig. 13j), with values of 1.01 (0.52–1.32) and 0.69 (0.18–1.27) Tg N yr⁻¹, respectively. Both approaches suggest that N₂O emissions from northern Africa significantly increased during 1997–2020, and the increase rates estimated by the BU and TD approaches were $\mathrm{4.9}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{4.7}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Direct emissions increased from 0.10 Tg N yr⁻¹ in 1980 to 0.27 Tg N yr⁻¹ in 2020, making the largest contribution to the increase in N₂O emissions from northern Africa (Fig. 14). Indirect emissions also significantly increased from 0.02 Tg N yr⁻¹ in 1980 to 0.04 Tg N yr⁻¹ in 2020. In contrast, other anthropogenic emissions decreased from 0.12 Tg N yr⁻¹ in 1980 to 0.11 Tg N yr⁻¹ in 2020. N₂O fluxes caused by changes in climate, CO₂, and land cover remained relatively stable during 1980–2020.

In the 2010s, the BU estimates (0.72, 0.17–1.30 Tg N yr⁻¹) were on average 0.32 Tg N yr⁻¹ lower than the TD estimates (1.04, 0.54–1.31 Tg N yr⁻¹) (Fig. 15). Natural sources accounted for 44 % of total emissions (0.32, 0.07–0.60 Tg N yr⁻¹) during this period. Direct emissions from nitrogen additions in agriculture were 0.23 (0.09–0.34) Tg N yr⁻¹, contributing 32 % of the total emissions. Emissions from other direct anthropogenic sources made the second largest contribution to anthropogenic emissions, with a decadal mean of 0.11 (0.08–0.14) Tg N yr⁻¹. Indirect emissions and perturbed fluxes from changes in climate, CO₂, and land cover were 0.04 (0.02–0.06) Tg N yr⁻¹, and 0.02 (−0.10 to 0.16), respectively.

4.5.9 Equatorial Africa (EQAF)

Similar to northern Africa, TD approaches suggested a larger magnitude of total N₂O emissions from equatorial Africa than BU approaches over the 1997–2020 period (Fig. 13k), with values of 1.45 (1.15–1.78) and 1.36 (0.36–2.22) Tg N yr⁻¹, respectively. Both approaches suggested that N₂O emissions from equatorial Africa significantly increased during 1997–2020, and the increase rates estimated by the BU and TD approaches were $\mathrm{4.4}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{2.1}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻¹, respectively. Direct emissions more than tripled during the study period, from 0.07 Tg N yr⁻¹ in 1980 to 0.22 Tg N yr⁻¹ in 2020, dominating the increase in N₂O emissions from equatorial Africa (Fig. 14). Indirect emissions also steadily increased from 0.04 Tg N yr⁻¹ in 1980 to 0.06 Tg N yr⁻¹ in 2020. On the contrary, perturbed fluxes from changes in climate, CO₂, and land cover showed an overall decreasing trend with large interannual variability. Emissions from other anthropogenic sources showed relatively stable values.

The BU and TD approaches gave comparable estimates of N₂O emissions from equatorial Africa in the 2010s, with values of 1.38 (0.38–2.28) and 1.50 (1.15–1.80) Tg N yr⁻¹ (Fig. 15), respectively. According to the BU results, natural emissions were the dominant component, accounting for 71 % of total emissions (0.98, 0.42–1.32 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.18 (0.13–0.25), 0.26 (0.19–0.34), and 0.05 (0.03–0.08) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.09 Tg N yr⁻¹ and a range of −0.40 to 0.29 Tg N yr⁻¹.

4.5.10 Southern Africa (SAF)

BU and TD estimates are consistent with respect to the magnitude of the total N₂O emissions from southern Africa during 1997–2020, at 0.61 (0.13–1.09) and 0.58 (0.33–0.86) Tg N yr⁻¹ (Fig. 13l), respectively. TD estimates increased at a rate of $\mathrm{4.5}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² over 1997–2020, whereas BU estimates did not show an obvious trend during this period. According to the BU results, direct agricultural emissions increased from 0.05 Tg N yr⁻¹ in 1980 to 0.08 Tg N yr⁻¹ in 2020, while emissions from other anthropogenic sources slightly decreased from 0.19 Tg N yr⁻¹ in 1980 to 0.17 Tg N yr⁻¹ in 2020. Both indirect emissions and perturbed fluxes from changes in climate, CO₂, and land cover had no significant trend (Fig. 14).

BU and TD approaches gave consistent estimates of total N₂O emissions from southern Africa in the 2010s, with values of 0.62 (0.13–1.10) and 0.61 (0.35–0.87) Tg N yr⁻¹ for the BU and TD approaches (Fig. 15), respectively. Natural emissions were the dominant components, accounting for 61 % of total emissions (0.38, 0.13–0.61 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.07 (0.05–0.09), 0.19 (0.17–0.23), and 0.02 (0.01–0.03) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.05 Tg N yr⁻¹ and a range of −0.24 to 0.14 Tg N yr⁻¹.

4.5.11 Russia (RUS)

During 1997–2020, the average total N₂O emission from Russia estimated by the BU approaches was 0.74 Tg N yr⁻¹, ranging from 0.15 to 1.84 Tg N yr⁻¹ (Fig. 13m), which was much higher than the estimates of TD approaches (0.36, 0.18–0.52 Tg N yr⁻¹). Both approaches suggested that Russia's total N₂O emissions increased during 1997–2020, and the increase rates estimated by the BU and TD approaches were $\mathrm{1.2}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{1.7}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Direct agricultural emissions, other direct emissions, and indirect emissions had divergent trends before and after 1997. From 1980 to 1997, N₂O emissions from all three of these sectors decreased. After 1997, direct agricultural emissions and other direct emissions had an overall increasing trend, while indirect emissions remained relatively stable. Perturbed fluxes from changes in climate, CO₂, and land cover remained relatively stable with large interannual variability (Fig. 14).

In the 2010s, the BU estimates (0.74, 0.15–1.84 Tg N yr⁻¹) were on average 0.36 Tg N yr⁻¹ higher than the TD estimates (0.38, 0.18–0.59 Tg N yr⁻¹) (Fig. 15). Natural sources accounted for 64 % of total emissions (0.47, 0.12–1.22 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.06 (0.05–0.07), 0.10 (0.04–0.18), and 0.05 (0.03–0.07) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.05 Tg N yr⁻¹ and a range of −0.10 to 0.30 Tg N yr⁻¹.

4.5.12 Central Asia (CAS)

TD approaches suggested a larger magnitude of total N₂O emissions from Central Asia than BU approaches over the 1997–2020 period (Fig. 13n), with values of 0.19 (0.10–0.29) and 0.14 (0.01–0.27) Tg N yr⁻¹, respectively. BU and TD estimates were consistent with respect to the trend in total N₂O emissions during 1997–2020, with increase rates of $\mathrm{1.9}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{2.0}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Direct emissions increased from 0.05 Tg N yr⁻¹ in 1980 to 0.07 Tg N yr⁻¹ in 2020, making the largest contribution to the increase in N₂O emissions from Central Asia. Other direct emissions and indirect emissions had no significant trend. Fluxes from changes in climate, CO₂, and land cover showed an overall increasing trend with large interannual variability (Fig. 14).

In the 2010s, the TD estimates (0.20, 0.10–0.32 Tg N yr⁻¹) were on average 0.05 Tg N yr⁻¹ higher than the BU estimates (0.15, 0.01–0.30 Tg N yr⁻¹) (Fig. 15). Natural sources accounted for 30 % of total emissions (0.04, 0.01–0.11 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.06 (0.02–0.08), 0.02 (0.01–0.02), and 0.02 (0.01–0.03) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.02 Tg N yr⁻¹ and a range of −0.04 to 0.07 Tg N yr⁻¹.

4.5.13 The Middle East (MIDE)

BU and TD estimates are comparable with respect to the magnitude of the total N₂O emissions from the Middle East during 1997–2020, with values of 0.27 (0.11–0.45) and 0.30 (0.25–0.36) Tg N yr⁻¹ (Fig. 13o), respectively. BU and TD estimates were consistent regarding the trend in total N₂O emissions during 1997–2020, with increase rates of $\mathrm{4.4}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{3.9}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. According to the BU results, direct agricultural emissions increased from 0.07 Tg N yr⁻¹ in 1980 to 0.13 Tg N yr⁻¹ in 2020. Emissions from other anthropogenic sources (fossil fuel and industry, particularly) had the largest increase, from 0.03 Tg N yr⁻¹ in 1980 to 0.10 Tg N yr⁻¹ in 2020. Indirect emissions also continuously increased from 0.02 Tg N yr⁻¹ in 1980 to 0.04 Tg N yr⁻¹ in 2020. Perturbed fluxes from changes in climate, CO₂, and land cover had no significant trend (Fig. 14).

BU and TD approaches gave consistent estimates of total N₂O emissions from the Middle East in the 2010s, with values of 0.29 (0.12–0.49) and 0.32 (0.26–0.39) Tg N yr⁻¹ for the BU and TD approaches (Fig. 15), respectively. Natural emissions were 0.04 (0.02–0.08 Tg N yr⁻¹), accounting for 15 % of total emissions during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.12 (0.05–0.21), 0.09 (0.07–0.10), and 0.03 (0.02–0.04) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.01 Tg N yr⁻¹ and a range of −0.04 to 0.05 Tg N yr⁻¹.

4.5.14 China (CHN)

BU and TD approaches agreed very well regarding the magnitudes and trends of N₂O emissions from China. Both approaches suggested that China's total N₂O emissions significantly increased during 1997–2020, and the increase rates estimated by the BU and TD approaches were $\mathrm{12.6}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{16.5}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻¹, respectively (Fig. 13p). According to the BU results, China's total N₂O emissions increased from 0.76 Tg N yr⁻¹ in 1980 to 1.38 Tg N yr⁻¹ in 2020. Direct emissions from N additions in agriculture made the largest contribution to the increase in China's N₂O emissions, which increased from 0.29 Tg N yr⁻¹ in 1980 to 0.71 Tg N yr⁻¹ in 2016 and then decreased to 0.64 Tg N yr⁻¹ in 2020 due to decreased N fertilizer application (Fig. 14). Both indirect emissions and other direct emissions continuously increased, from 0.09 and 0.11 Tg N yr⁻¹ in 1980 to 0.24 and 0.27 Tg N yr⁻¹ in 2020, respectively. The total anthropogenic N₂O emissions from China increased at an average rate of $\mathrm{18.9}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² during 1980–2020, which was the largest among the 18 regions and contributed 40 % of the increase in global anthropogenic N₂O emissions.

The BU and TD approaches gave consistent estimates of China's total N₂O emissions in the 2010s, with values of 1.41 (0.82–2.23) and 1.33 (1.06–1.60) Tg N yr⁻¹ for the BU and TD approaches (Fig. 15), respectively. According to the BU results, natural sources only contributed 21 % of total emissions (0.29, 0.20–0.51 Tg N yr⁻¹) during this period. Nitrogen additions in agriculture were the dominant source of N₂O emissions, contributing 48 % of the total emissions (0.68, 0.48–1.03 Tg N yr⁻¹). Emissions from other direct anthropogenic sources and indirect emissions from anthropogenic nitrogen additions were 0.23 (0.23–0.23) and 0.24 (0.17–0.28) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.03 Tg N yr⁻¹ and a range of −0.25 to 0.18 Tg N yr⁻¹.

4.5.15 Korea and Japan (KAJ)

TD approaches suggested a smaller magnitude of total N₂O emissions from Korea and Japan than BU approaches over the 1997–2020 period (Fig. 13q), with values of 0.06 (0.03–0.11) and 0.11 (0.06–0.16) Tg N yr⁻¹, respectively. Both approaches suggested that total N₂O emissions from Korea and Japan decreased during 1997–2020, and the decrease rates estimated by the BU and TD approaches were $-\mathrm{1.4}\times {\mathrm{10}}^{-\mathrm{3}}$ and $-\mathrm{0.5}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Other direct emissions (fossil fuel and industry, particularly) dominated the temporal variations in N₂O emissions from Korea and Japan, which increased from 0.04 Tg N yr⁻¹ in 1980 to 0.08 Tg N yr⁻¹ in 1997 and then decreased to 0.04 Tg N yr⁻¹ in 2020. Emissions from agriculture, indirect sources, and perturbed fluxes remained relatively stable during 1997–2020 (Fig. 14).

In the 2010s, BU estimates (0.10, 0.05–0.15 Tg N yr⁻¹) of total N₂O emissions were on average 0.04 Tg N yr⁻¹ higher than the TD estimate (0.06, 0.04–0.11 Tg N yr⁻¹) (Fig. 15). Natural sources accounted for 26 % of total emissions (0.03, 0.00–0.05 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.03 (0.02–0.04), 0.04 (0.04–0.04), and 0.01 (0.01–0.02) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.01 Tg N yr⁻¹ and a range of −0.02 to 0.01 Tg N yr⁻¹.

4.5.16 South Asia (SAS)

BU and TD estimates are comparable in terms of both the magnitude and trend of the total N₂O emissions from South Asia (Fig. 13r). During 1997–2020, the magnitudes of total N₂O emissions estimated by the BU and TD approaches were 1.04 (0.35–1.80) and 1.21 (0.96–1.56) Tg N yr⁻¹, respectively. Both approaches suggested that the total N₂O emissions from South Asia significantly increased during 1997–2020, and the increase rates estimated by the BU and TD approaches were $\mathrm{17.7}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{20.2}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Direct emissions from nitrogen additions in agriculture made the largest contribution to the increase in N₂O emissions in South Asia, which increased from 0.19 Tg N yr⁻¹ in 1980 to 0.55 Tg N yr⁻¹ in 2020 due to increased N fertilizer application (Fig. 14). Other direct emissions and indirect emissions also significantly increased, from 0.06 and 0.06 Tg N yr⁻¹ in 1980 to 0.14 and 0.17 Tg N yr⁻¹ in 2020, respectively. Fluxes from changes in climate, CO₂, and land cover showed an overall increasing trend with large interannual variability.

BU estimates (1.15, 0.41–2.06 Tg N yr⁻¹) were on average 0.21 Tg N yr⁻¹ lower than the TD estimate in the 2010s (1.36, 1.05–1.84 Tg N yr⁻¹) (Fig. 15). Natural sources accounted for 28 % of total emissions (0.32, 0.12–0.56 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.49 (0.25–0.75), 0.13 (0.13–0.13), and 0.15 (0.10–0.19) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall positive effect on N₂O emissions, with a mean value of 0.06 Tg N yr⁻¹ and a range of −0.19 to 0.43 Tg N yr⁻¹.

4.5.17 Southeast Asia (SEAS)

TD approaches suggested a smaller magnitude of the total N₂O emissions from Southeast Asia than BU approaches over the 1997–2020 period (Fig. 13s), with values of 0.69 (0.50–1.02) and 0.92 (0.24–2.04) Tg N yr⁻¹, respectively. Both approaches suggested that total N₂O emissions from Southeast Asia increased during 1997–2020, and the rates of increase estimated by the BU and TD approaches were $\mathrm{5.1}\times {\mathrm{10}}^{-\mathrm{3}}$ and $\mathrm{2.3}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻², respectively. Direct agricultural emissions, other direct emissions, and indirect emissions significantly increased during the study period, from 0.09, 0.08, and 0.04 Tg N yr⁻¹ in 1980 to 0.30, 0.11, and 0.12 Tg N yr⁻¹ in 2020, respectively. Meanwhile, perturbed fluxes from changes in climate, CO₂, and land cover significantly decreased from −0.07 Tg N yr⁻¹ in 1980 to −0.12 Tg N yr⁻¹ in 2020 (Fig. 14).

The BU and TD approaches gave comparable estimates of the total N₂O emissions from Southeast Asia in the 2010s, with values of 0.95 (0.24–2.09) and 0.72 (0.51–1.12) Tg N yr⁻¹ for the BU and TD approaches (Fig. 15), respectively. Natural sources accounted for 62 % of total emissions (0.59, 0.24–1.30 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.26 (0.20–0.35), 0.11 (0.09–0.14), and 0.10 (0.06–0.14) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.12 Tg N yr⁻¹ and a range of −0.35 to 0.16 Tg N yr⁻¹.

4.5.18 Australasia (AUS)

BU and TD estimates are comparable in terms of the magnitude of the total N₂O emissions from Australasia during 1997–2020 (Fig. 13t). The magnitudes of the total N₂O emissions estimated by the BU and TD approaches were 0.43 (0.01–0.92) and 0.52 (0.21–0.72) Tg N yr⁻¹, respectively. TD estimates increased at a rate of $\mathrm{4.4}\times {\mathrm{10}}^{-\mathrm{3}}$ Tg N yr⁻² over 1997–2020, whereas BU estimates did not show a notable trend during this period (Fig. 13t). According to the BU results, direct agricultural emissions increased from 0.08 Tg m yr⁻¹ in 1980 to 0.09 Tg N yr⁻¹ in 2020, while emissions from all the other three anthropogenic sectors remained stable (Fig. 14).

In the 2010s, the magnitudes of total N₂O emissions estimated by the BU and TD approaches were 0.42 (0.01–0.91) and 0.53 (0.20–0.71) Tg N yr⁻¹, respectively. Natural sources accounted for 59 % of total emissions (0.25, 0.05–0.50 Tg N yr⁻¹) during this period. Direct agricultural emissions, other direct emissions, and indirect emissions were 0.09 (0.06–0.11), 0.08 (0.06–0.11), and 0.01 (0.01–0.02) Tg N yr⁻¹, respectively. Changes in climate, CO₂, and land cover had an overall negative effect on N₂O emissions, with a mean value of −0.01 Tg N yr⁻¹ and a range of −0.17 to −0.17 Tg N yr⁻¹ (Fig. 15).