Editing IPCC:AR6/WGI/Chapter-5 (section)

== Cross-Chapter Box 5.2 | Drivers of Atmospheric Methane Changes During 1980–2019 ==

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'''Contributors:''' Prabir K. Patra (Japan/India), Josep G. Canadell (Australia), Frank J. Dentener (European Union, The Netherlands), Xin Lan (United States of America/China), Vaishali Naik (United States of America)

The atmospheric methane (CH <sub>4</sub>) growth rate has varied widely over the past three decades, and the causes have been extensively studied since AR5. The mean growth rate decreased from 15 ± 5 ppb yr <sup>–1</sup> in the 1980s to 0.48 ± 3.2 ppb yr <sup>–1</sup> during 2000–2006 (the so-called quasi-equilibrium phase) and returned to an average rate of 7.6 ± 2.7 ppb yr <sup>–1</sup> in the past decade (2010–2019) (based on data in Figure 5.14). Atmospheric CH <sub>4</sub> grew faster (9.3 ± 2.4 ppb yr <sup>–1</sup>) over the last six years (2014–2019) – a period with prolonged El Niño conditions, which contributed to high CH <sub>4</sub> growth rates consistent with behaviour during previous El Niño events (Figure 5.14b). Because of large uncertainties in both the emissions and sinks of CH <sub>4</sub> , it has been challenging to quantify accurately the methane budget and ascribe reasons for the growth over 1980–2019. In the context of CH <sub>4</sub> emissions mitigation, it is critical to understand if the changes in growth rates are caused by emissions from human activities or by natural processes responding to changing climate. If CH <sub>4</sub> continues to grow at rates similar to those observed over the past decade, it will contribute to decadal scale climate change and hinder the achievement of the long-term temperature goals of the Paris Agreement ([[IPCC:Wg1:Chapter:Chapter-7#7.3.2.2|Section 7.3.2.2]] ; [[#Nisbet--2019|Nisbet et al., 2019]]).

Cross-Chapter Box 5.2, Figure 1 shows the decadal CH <sub>4</sub> budget derived from the Global Carbon Project (GCP)-CH <sub>4</sub> synthesis for 1980s, 1990s and 2000s ([[#Kirschke--2013|Kirschke et al., 2013]]), and for 2010–2017 ([[#Saunois--2020|Saunois et al., 2020]]). The imbalance of the sources and sinks estimated by atmospheric inversions (dark blue bars) can be used to explain the changes in CH <sub>4</sub> concentration increase rates between the decades (Table 5.2).

Since AR5, many studies have discussed the role of different source categories in explaining the increase in CH <sub>4</sub> growth rate since 2007 and a coincident decrease of d <sup>13</sup> C–CH <sub>4</sub> and dD–CH <sub>4</sub> isotopes (Figure 5.13; [[#Rice--2016|Rice et al., 2016]]). Both <sup>13</sup> C and D are enriched in mass-weighted average source signatures for CH <sub>4</sub> emissions from thermogenic sources (e.g., coal mining, oil and gas industry) and pyrogenic (biomass burning) sources, and depleted in biogenic (e.g., wetlands, rice paddies, enteric fermentation, landfill and waste) sources. Proposed hypotheses for CH <sub>4</sub> growth (2007–2017) are inconclusive and vary from a concurrent decrease in thermogenic and increase in wetland and other biogenic emissions ([[#Nisbet--2016|Nisbet et al., 2016]] ; [[#Schwietzke--2016|Schwietzke et al., 2016]]), an increase in emissions from agriculture in the tropics ([[#Schaefer--2016|Schaefer et al., 2016]]), a concurrent reduction in pyrogenic emissions and an increase in thermogenic emissions ([[#Worden--2017|Worden et al., 2017]]), or an emissions increase from biogenic sources and a slower increase in emissions from thermogenic sources compared to inventory emissions ([[#Patra--2016|Patra et al., 2016]] ; [[#Thompson--2018|Thompson et al., 2018]] ; [[#Jackson--2020|Jackson et al., 2020]] ; [[#Chandra--2021|Chandra et al., 2021]]).

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[[File:207a64c729e09a7b3dc27844b35bcd98 IPCC_AR6_WGI_CCBox_5_2_Figure_1.png]]

'''Cross-Chapter Box 5.2, Figure 1 |''' '''Methane sources and sinks for four decades from atmospheric inversions with the budget imbalance''' (source–sink; dark blue bars) (plotted on the left y-axis). Top-down analysis from [[#Kirschke--2013|Kirschke et al. (2013)]] ; [[#Saunois--2020|Saunois et al. (2020)]] . The global CH <sub>4</sub> concentration seen in the black line (plotted on the right y-axis), representing National Oceanic and Atmospheric Administration (NOAA) observed global monthly mean atmospheric CH <sub>4</sub> in dry-air mole fractions for 1983–2019 (Chapter 2, Annex V). Natural sources include emissions from natural wetlands, lakes and rivers, geological sources, wild animals, termites, wildfires, permafrost soils, and oceans. Anthropogenic sources include emissions from enteric fermentation and manure, landfills, waste and wastewater, rice cultivation, coal mining, oil and gas industry, biomass and biofuel burning. The top-down total sink is determined from global mass balance that includes chemical losses due to reactions with hydroxyl (OH), atomic chlorine (Cl), and excited atomic oxygen (O <sup>1</sup> D), and oxidation by bacteria in aerobic soils (Table 5.2). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

A few studies emphasize the role of chemical destruction by hydroxyl (OH; the primary sink of methane), in driving changes in the growth of atmospheric methane abundance, in particular after 2006 ([[#Rigby--2017|Rigby et al., 2017]] ; [[#Turner--2017|Turner et al., 2017]]). Studies applying three-dimensional atmospheric inversion ([[#McNorton--2018|McNorton et al., 2018]]), simple multi-species inversion ([[#Thompson--2018|Thompson et al., 2018]]), as well as empirical methods using a variety of observational constraints based on OH chemistry ([[#Nicely--2018|Nicely et al., 2018]] ; [[#Patra--2021|Patra et al., 2021]]), do not find trends in OH large enough to explain the methane changes post-2006. On the contrary, global chemistry–climate models based on fundamental principles of atmospheric chemistry and known emissions trends of anthropogenic non-methane short-lived climate forcers simulate an increase in OH over this period ([[#Zhao--2019|Zhao et al., 2019]] ; [[#Stevenson--2020|Stevenson et al., 2020]] ; see Section 6.2.3). These contrasting lines of evidence suggest that OH changes may have had a small moderating influence on methane growth since 2007 (''l'' ''ow confidence'').

Cross-Chapter Box 5.2 Figure 2 shows that modelled wetland emissions anomalies for all regions did not exhibit statistically significant trends (''high agreement between models, medium evidence''). Thus, the inter-decadal difference of total CH <sub>4</sub> emissions derived from inversion models and wetland emissions, arises mainly from anthropogenic activities. The time series of regional emissions suggest that progress towards atmospheric CH <sub>4</sub> quasi-equilibrium was primarily driven by reductions in anthropogenic (fossil fuel exploitation) emissions in Europe, Russia and temperate North America over 1988–2000. In the global totals, emissions equalled loss in the early 2000s. The growth since 2007 is driven by increasing agricultural emissions from East Asia (1997–2017), West Asia (2005–2017), Brazil (1988–2017) and Northern Africa (2005–2017), and fossil fuel exploitations in temperate North America (2010–2017; [[#Lan--2019|Lan et al., 2019]] ; [[#Crippa--2020|Crippa et al., 2020]] ; [[#Höglund-Isaksson--2020|Höglund-Isaksson et al., 2020]] ; [[#Jackson--2020|Jackson et al., 2020]] ; [[#Chandra--2021|Chandra et al., 2021]]).

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[[File:ffb928ecae70a1c4030ba22700f29ce0 IPCC_AR6_WGI_CCBox_5_2_Figure_2.png]]

'''Cross-Chapter Box 5.2, Figure 2 |''' '''Anomalies in global and regional methane (CH''' <sub>4</sub> ''') emissions for 1988–2017''' . The map in the centre shows mean CH <sub>4</sub> emissions for 2010–2016. Multi-model mean (line) and 1-s standard deviations (shaded) for 2000–2017 are shown for 9 surface CH <sub>4</sub> and 10 satellite XCH <sub>4</sub> inversions, and 22 wetland models or model variants that participated in GCP-CH <sub>4</sub> budget assessment ([[#Saunois--2020|Saunois et al., 2020]]). The results for the period before 2000 are available from two inversions, one using 19 sites ([[#Chandra--2021|Chandra et al., 2021]] ; also used for the 2010–2016 mean emissions map) and one for global totals ([[#Bousquet--2006|Bousquet et al., 2006]]). The long-term mean values for 2010–2016 (common for all GCP–CH <sub>4</sub> inversions), as indicated within each panel separately, are subtracted from the annual-mean time series for the calculation of anomalies for each region. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

There is evidence from emissions inventories at country level and regional scale inverse modelling that CH <sub>4</sub> growth rate variability between 1988 and 2017 is closely linked to anthropogenic activities (''medium agreement''). Isotopic composition observations and inventory data suggest that concurrent emissions changes from both fossil fuels and agriculture are playing roles in the resumed CH <sub>4</sub> growth since 2007 (''high confidence''). Shorter-term decadal variability is predominantly driven by the influence of El Niño–Southern Oscillation on emissions from wetlands and biomass burning (Cross-Chapter Box 5.2, Figure 2), and loss due to OH variations (''medium confidence''), but lacking quantitative contribution from each of the sectors. By synthesizing all available information regionally from a priori (bottom-up) emissions, satellite and surface observations, including isotopic information, and inverse modelling (top-down), the capacity to track and explain changes in, and drivers of, natural and anthropogenic CH <sub>4</sub> regional and global emissions has improved since AR5, but fundamental uncertainties related to OH variations remain unchanged.
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=== 5.2.3 N <sub>2</sub> O: Trends, Variability and Budget ===

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In natural ecosystems, nitrous oxide (N <sub>2</sub> O) is primarily produced as a by-product during the remineralization of organic matter via the primary processes of nitrification and denitrification ([[#Butterbach-Bahl--2013|Butterbach-Bahl et al., 2013]] ; [[#Voss--2013|Voss et al., 2013]]). The net N <sub>2</sub> O production is highly sensitive to local environmental conditions such as temperature, oxygen concentrations, pH and the concentrations of ammonium and nitrate, among others, causing strong variability of N <sub>2</sub> O emissions in time and space, even at small scales. Changes in the atmospheric abundance of N <sub>2</sub> O result largely from the balance of the net N <sub>2</sub> O sources on land and ocean, and the photochemical destruction of N <sub>2</sub> O in the stratosphere.

Since AR5 (WGI, Section 6.4.3), improved understanding of N <sub>2</sub> O sources allows for a more comprehensive assessement of the global N <sub>2</sub> O budget (Table 5.3). This progress is based on extended atmospheric observations ([[#Francey--2003|Francey et al., 2003]] ; [[#Elkins--2018|Elkins et al., 2018]] ; [[#Prinn--2018|Prinn et al., 2018]]), improved atmospheric N <sub>2</sub> O inversions ([[#Saikawa--2014|Saikawa et al., 2014]] ; [[#Thompson--2019|Thompson et al., 2019]]), updated and expanded inventories of N <sub>2</sub> O sources ([[#Winiwarter--2018|Winiwarter et al., 2018]] ; [[#Janssens-Maenhout--2019|Janssens-Maenhout et al., 2019]]), as well as improved bottom-up estimate of freshwater, ocean and terrestrial sources ([[#Martinez-Rey--2015|Martinez-Rey et al., 2015]] ; [[#Landolfi--2017|Landolfi et al., 2017]] ; [[#Buitenhuis--2018|Buitenhuis et al., 2018]] ; [[#Lauerwald--2019|Lauerwald et al., 2019]] ; [[#Maavara--2019|Maavara et al., 2019]] ; [[#Tian--2019|Tian et al., 2019]]).

The human perturbation of the natural nitrogen cycle through the use of synthetic fertilizers and manure, as well as nitrogen deposition resulting from land-based agriculture and fossil fuel burning has been the largest driver of the increase in atmospheric N <sub>2</sub> O of 31.0 ± 0.5 ppb (10%) between 1980 and 2019 (''robust evidence'' , ''high agreement'') ([[#Tian--2020|Tian et al., 2020]]). The long atmospheric lifetime of N <sub>2</sub> O implies that it will take more than a century before atmospheric abundances stabilize after the stabilization of global emissions. The rise of atmospheric N <sub>2</sub> O is of concern, not only because of its contribution to the anthropogenic radiative forcing (Chapter 7) but also because of the importance of N <sub>2</sub> O in stratospheric ozone loss ([[#Ravishankara--2009|Ravishankara et al., 2009]] ; [[#Fleming--2011|Fleming et al., 2011]] ; W. [[#Wang--2014|]] [[#Wang--2014|Wang et al., 2014]]).

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==== 5.2.3.1 Atmosphere ====

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The tropospheric abundance of N <sub>2</sub> O was 332.1 ± 0.4 ppb in 2019 (Figure 5.15), which is 23% higher than pre-industrial levels of 270.1 ± 6.0 ppb (''robust evidence, high agreement''). Current estimates are based on atmospheric measurements with high accuracy and density ([[#Francey--2003|Francey et al., 2003]] ; [[#Elkins--2018|Elkins et al., 2018]] ; [[#Prinn--2018|Prinn et al., 2018]]), and pre-industrial estimates are based on multiple ice-core records [[IPCC:Wg1:Chapter:Chapter-2#2.2.3.2.3|Section 2.2.3.2.3]]). The average annual tropospheric growth rate was 0.85 ± 0.03 ppb yr <sup>–1</sup> <sub></sub> during the period 1995 to 2019 (Figure 5.15a). The atmospheric growth rate increased by about 20% between the decade 2000–2009 and the most recent decade of 2010–2019 (0.95 ± 0.04 ppb yr <sup>–1</sup>) (''robust evidence, high agreement''). The growth rate in 2010–2019 was also higher than during 1970–2000 (0.6–0.8 ppb yr <sup>–1</sup> ; [[#Ishijima--2007|Ishijima et al., 2007]]) and the 30-year period prior to 2011 (0.73 ± 0.03 ppb yr <sup>–1</sup>), as reported by AR5. New evidence since AR5 (WGI, Section 6.4.3) confirms that, in the tropics and subtropics, large interannual variations in the atmospheric growth rate are negatively correlated with the multivariate ENSO index (MEI) and associated anomalies in land and ocean fluxes ([[#Ji--2019|Ji et al., 2019]] ; [[#Thompson--2019|Thompson et al., 2019]] ; S. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]]) (Figure 5.15a).

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[[File:8269d59e29a66c0307693bea2ae395f8 IPCC_AR6_WGI_Figure_5_15.png]]

'''Figure 5.15 |''' '''Changes in atmospheric nitrous oxide (N''' <sub>2</sub> '''O) and its isotopic composit''' '''ion since 1940''' . '''(a)''' Atmospheric N <sub>2</sub> O abundance (parts per billion, ppb) and growth rat (ppb yr <sup>–1</sup>); '''(b)''' δ <sup>15</sup> N of atmospheric N <sub>2</sub> O; and '''(c)''' alpha-site <sup>15</sup> N–N <sub>2</sub> O. Estimates are based on direct atmospheric measurements in the Advanced Global Atmospheric Gases Experiment (AGAGE), Commonwealth Scientific and Industrial Research Organisation (CSIRO), and National Oceanic and Atmospheric Administration (NOAA) networks ([[#Prinn--2000|Prinn et al., 2000]] , 2018; [[#Francey--2003|Francey et al., 2003]] ; [[#Hall--2007|Hall et al., 2007]] ; [[#Elkins--2018|Elkins et al., 2018]]), archived air samples from Cape Grim, Australia ([[#Park--2012|Park et al., 2012]]), and firn air from the North Greenland Ice Core Project (NGRIP) Greenland and H72 Antarctica ([[#Ishijima--2007|Ishijima et al., 2007]]), Law Dome Antarctica ([[#Park--2012|Park et al., 2012]]), as well as a collection of firn ice samples from Greenland ([[#Prokopiou--2017|Prokopiou et al., 2017]] , 2018). Shading in (a) is based on the multivariate El Niño–Southern Oscillation (ENSO) index, with red indicating El Niño conditions ([[#Wolter--1998|Wolter and Timlin, 1998]]). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

As assessed by SRCCL ([[#IPCC--2019a|IPCC, 2019a]]), combined firn, ice, air and atmospheric measurements show that the <sup>15</sup> N/ <sup>14</sup> N isotope ratio (''robust evidence'' , ''high agreement'') and the predominant position of the <sup>15</sup> N atom in atmospheric N <sub>2</sub> O (''limited evidence'' , ''low agreement'') in N <sub>2</sub> O has changed since 1940 (Figure 5.15b, c) whereas they were relatively constant in the pre-industrial period ([[#Ishijima--2007|Ishijima et al., 2007]] ; [[#Park--2012|Park et al., 2012]] ; [[#Prokopiou--2017|Prokopiou et al., 2017]] , 2018). The SRCCL concluded that this change indicates a shift in the nitrogen-substrate available for denitrification, and the relative contribution of nitrification to the global N <sub>2</sub> O source (''robust evidence'' , ''high agreement''), which are associated with increased fertilizer use in agriculture ([[#Park--2012|Park et al., 2012]] ; [[#Snider--2015|Snider et al., 2015]] ; [[#Prokopiou--2018|Prokopiou et al., 2018]]).

Since AR5 (WGI, Section 6.4.3), the mean atmospheric lifetime of N <sub>2</sub> O has been revised to 116 ± 9 years ([[#Prather--2015|Prather et al., 2015]]). The small negative feedback of the N <sub>2</sub> O lifetime to increasing atmospheric N <sub>2</sub> O results in a slightly lower residence time (109 ± 10 years) of N <sub>2</sub> O perturbations compared with that assessed by AR5 (118–131 years) ([[#Prather--2015|Prather et al., 2015]]). The dominant N <sub>2</sub> O loss occurs through photolysis and oxidation by O(1D) radicals in the stratosphere and amounts to approximately 13.1 (12.4–13.6) TgN yr <sup>–1</sup> ([[#Minschwaner--1993|Minschwaner et al., 1993]] ; [[#Prather--2015|Prather et al., 2015]] ; [[#Tian--2020|Tian et al., 2020]]).

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==== 5.2.3.2 Anthropogenic N <sub>2</sub> O Emissions ====

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The AR5 (WGI, Section 6.4.3) and SRCCL ([[IPCC:Wg1:Chapter:Chapter-2#2.3.3|Section 2.3.3]]) concluded that agriculture is the largest anthropogenic source of N <sub>2</sub> O emissions. Since SRCCL (2.3.3), a new synthesis of inventory-based and modelling studies shows that the widespread use of synthetic fertilizers and manure on cropland and pasture, manure management and aquaculture resulted in 3.8 (2.5–5.8) TgN yr <sup>–1</sup> (average 2007–2016) (''robust evidence, high agreement'') (Table 5.3; [[#Winiwarter--2018|Winiwarter et al., 2018]] ; [[#FAO--2019|FAO, 2019]] ; [[#Janssens-Maenhout--2019|Janssens-Maenhout et al., 2019]] ; [[#Tian--2020|Tian et al., 2020]]). Observations from field-measurements ([[#Song--2018|Song et al., 2018]]), inventories ([[#Wang--2020|Wang et al., 2020]]) and atmospheric inversions ([[#Thompson--2019|Thompson et al., 2019]]) further corroborate the assessment of SRCCL that there is a non-linear relationship between N <sub>2</sub> O emissions and nitrogen input, implying an increasing fraction of fertilizer lost as N <sub>2</sub> O with larger fertilizer excess (''medium evidence'' , ''high agreement''). Several studies using complementary methods indicate that agricultural N <sub>2</sub> O emissions have increased by more than 45% since the 1980s (''high confidence'') (Figure 5.16 and Table 5.3; [[#Davidson--2009|Davidson, 2009]] ; [[#Winiwarter--2018|Winiwarter et al., 2018]] ; [[#Janssens-Maenhout--2019|Janssens-Maenhout et al., 2019]] ; [[#Tian--2020|Tian et al., 2020]]), mainly due to the increased use of nitrogen fertilizer and manure. N <sub>2</sub> O emissions from aquaculture are among the fastest rising contributors of N <sub>2</sub> O emissions, but their overall magnitude is still small in the overall N <sub>2</sub> O budget ([[#Tian--2020|Tian et al., 2020]]).

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[[File:6f0779b71e8fa59d513466d8418a459c IPCC_AR6_WGI_Figure_5_16.png]]

'''Figure 5.16 |''' '''Decadal mean nitrous oxide (N''' <sub>2</sub> '''O) emissions for 2007–2016 and its change since 1850 based on process-model projections''' . The total effect, including that from anthropogenic nitrogen additions (atmospheric deposition, manure addition, fertilizer use and land-use), is evaluated against the background flux driven by changes in atmospheric carbon dioxide (CO <sub>2</sub>) concentration, and climate change. Fluxes are derived from the N <sub>2</sub> O model intercomparison project ensemble of terrestrial biosphere models ([[#Tian--2019|Tian et al., 2019]]) and three ocean biogeochemical models ([[#Landolfi--2017|Landolfi et al., 2017]] ; [[#Battaglia--2018a|Battaglia and Joos, 2018a]] ; [[#Buitenhuis--2018|Buitenhuis et al., 2018]]). Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

The principal non-agricultural anthropogenic sources of N <sub>2</sub> O are industry, specifically chemical processing, wastewater, and the combustion of fossil fuels (Table 5.3). Industrial emissions of N <sub>2</sub> O mainly due to nitric and adipic acid production have decreased in North America and Europe since the widespread installation of abatement technologies in the 1990s (Pérez-Ram '''ί''' rez et al., 2003; [[#Lee--2011|Lee et al., 2011]] ; [[#Janssens-Maenhout--2019|Janssens-Maenhout et al., 2019]]). There is still considerable uncertainty in industrial emissions from other regions of the world with contrasting trends between inventories ([[#Thompson--2019|Thompson et al., 2019]]). Globally, industrial emissions and emissions from fossil fuel combustion by stationary sources, such as power plants, as well as smaller emissions from mobile sources (e.g., road transport and aviation) have remained nearly constant between the 1980s and 2007–2016 (''medium evidence'' , ''medium agreement'') ([[#Winiwarter--2018|Winiwarter et al., 2018]] ; [[#Janssens-Maenhout--2019|Janssens-Maenhout et al., 2019]] ; [[#Tian--2020|Tian et al., 2020]]). Wastewater N <sub>2</sub> O emissions, including those from domestic and industrial sources, have increased from 0.2 (0.1–0.3) TgN yr <sup>–1</sup> to 0.35 (0.2–0.5) TgN yr <sup>–1</sup> between the 1980s and 2007–2016 ([[#Tian--2020|Tian et al., 2020]]).

Biomass burning from crop residue burning, grassland, savannah and forest fires, as well as biomass burnt in household stoves, releases N <sub>2</sub> O during the combustion of organic matter. Updated inventories since AR5 (WGI, Section 6.4.3) result in a lower range of the decadal mean emissions of 0.6 (0.5–0.8) TgN yr <sup>–1</sup> ([[#van%20der%20Werf--2017|van der Werf et al., 2017]] ; [[#Tian--2020|Tian et al., 2020]]). The attribution of grassland, savannah or forest fires to natural or anthropogenic origins is uncertain, preventing a separation of the biomass burning source into natural and anthropogenic.

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==== 5.2.3.3 Emissions from Ocean, Inland Water Bodies and Estuaries ====

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Since AR5 (WGI, Section 6.4.3), new estimates of the global ocean N <sub>2</sub> O source derived from ocean biogeochemistry models are 3.4 (2.5–4.3) TgN yr <sup>–1</sup> for the period 2007–2016 (Figure 5.16; [[#Manizza--2012|Manizza et al., 2012]] ; [[#Suntharalingam--2012|Suntharalingam et al., 2012]] ; [[#Martinez-Rey--2015|Martinez-Rey et al., 2015]] ; [[#Landolfi--2017|Landolfi et al., 2017]] ; [[#Buitenhuis--2018|Buitenhuis et al., 2018]] ; [[#Tian--2020|Tian et al., 2020]]). This is slightly lower than climatological estimates from empirically based methods and surface ocean data syntheses ([[#Bianchi--2012|Bianchi et al., 2012]] ; S. [[#Yang--2020|]] [[#Yang--2020|Yang et al., 2020]]). Nitrous oxide processes in coastal upwelling zones continue to be poorly represented in global estimates of marine N <sub>2</sub> O emissions ([[#Kock--2016|Kock et al., 2016]]), but may account for an additional 0.2–0.6 TgN yr <sup>–1</sup> of the global ocean source ([[#Seitzinger--2000|Seitzinger et al., 2000]] ; [[#Nevison--2004|Nevison et al., 2004]]).

In the oxic ocean (&gt;97% of ocean volume), nitrification is believed to be the primary N <sub>2</sub> O source ([[#Freing--2012|Freing et al., 2012]]). In sub-oxic ocean zones ([[#5.3|Section 5.3]]), where denitrification prevails, higher N <sub>2</sub> O yields and turnover rates make these regions potentially significant sources of N <sub>2</sub> O ([[#Arévalo-Martínez--2015|Arévalo-Martínez et al., 2015]] ; [[#Babbin--2015|Babbin et al., 2015]] ; [[#Ji--2015|Ji et al., 2015]]). The relative proportion of ocean N <sub>2</sub> O from oxygen-minimum zones is highly uncertain ([[#Zamora--2012|Zamora et al., 2012]]). Estimates derived from in situ sampling, particularly in the eastern tropical Pacific, suggest significant fluxes from these regions, and potentially account for up to 50% of the global ocean source ([[#Codispoti--2010|Codispoti, 2010]] ; [[#Arévalo-Martínez--2015|Arévalo-Martínez et al., 2015]] ; [[#Babbin--2015|Babbin et al., 2015]]). However, recent global-scale analyses estimate lower contributions (4–7%, [[#Battaglia--2018b|Battaglia and Joos, 2018b]] ; [[#Buitenhuis--2018|Buitenhuis et al., 2018]]). Further investigation is required to reconcile these estimates and provide improved constraints on the N <sub>2</sub> O source from low-oxygen zones.

Atmospheric deposition of anthropogenic N on oceans can stimulate marine productivity and influence ocean emissions of N <sub>2</sub> O. New ocean model analyses since AR5 (WGI, 6.4.3), suggest a relatively modest global potential impact of 0.01–0.32 TgN yr <sup>–1</sup> (pre-industrial to present-day) equivalent to 0.5–3.3% of the global ocean N <sub>2</sub> O source ([[#Suntharalingam--2012|Suntharalingam et al., 2012]] ; [[#Jickells--2017|Jickells et al., 2017]] ; [[#Landolfi--2017|Landolfi et al., 2017]]). However, larger proportionate impacts are predicted in nitrogen-limited coastal and inland waters downwind of continental pollution outflow, such as the Northern Indian Ocean ([[#Jickells--2017|Jickells et al., 2017]] ; [[#Suntharalingam--2019|Suntharalingam et al., 2019]]).

Inland waters and estuaries are generally sources of N <sub>2</sub> O as a result of nitrification and denitrification of dissolved inorganic nitrogen, however, they can serve as N <sub>2</sub> O sinks in specific conditions ([[#Webb--2019|Webb et al., 2019]]). Since AR5 (WGI, 6.4.3), improved emissions factors, including their spatio-temporal scaling, and consideration of transport within the aquatic system allows for better constraint of these emissions ([[#Murray--2015|Murray et al., 2015]] ; [[#Hu--2016|Hu et al., 2016]] ; [[#Lauerwald--2019|Lauerwald et al., 2019]] ; [[#Maavara--2019|Maavara et al., 2019]] ; [[#Kortelainen--2020|Kortelainen et al., 2020]] ; [[#Yao--2020|Yao et al., 2020]]). Despite uncertainties because of the side effects of canals and reservoirs on nutrient cycling, these advances permit attribution of a fraction of inland water N <sub>2</sub> O emissions to anthropogenic sources ([[#Tian--2020|Tian et al., 2020]]), which contributes to the increased anthropogenic share of the global N <sub>2</sub> O source in this report compared to AR5 ([[#Ciais--2013|Ciais et al., 2013]]). As an indirect consequence of agricultural nitrogen use and waste-water treatment, the anthropogenic emissions from inland waters have increased by about a quarter (0.1 TgN yr <sup>–1</sup>) between the 1980s and 2007–2016 ([[#Tian--2020|Tian et al., 2020]]).

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==== 5.2.3.4 Emissions and Sinks in Non-agricultural Land ====

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Soils are the largest natural source of N <sub>2</sub> O, arising primarily from nitrogen processing associated with microbial nitrification and denitrification (Table 5.3; [[#Butterbach-Bahl--2013|Butterbach-Bahl et al., 2013]] ; [[#Snider--2015|Snider et al., 2015]]). Under some conditions, soils can also act as a net sink of N <sub>2</sub> O, but this effect is small compared to the overall source ([[#Schlesinger--2013|Schlesinger, 2013]]). Since AR5 (WGI, Section 6.4.3), improved global process-based models ([[#Tian--2019|Tian et al., 2019]]) suggest a present-day source of 6.7 (5.3–8.1) TgN yr <sup>–1</sup> (2007–2016 average), which is consistent with the estimate in AR5. Process-based models and inventory-based methods show that increased N deposition has enhanced terrestrial N <sub>2</sub> O emissions by 0.8 (0.4–1.4 TgN yr <sup>–1</sup>) relative to approximately pre-industrial times, and by 0.2 (0.1–0.2) TgN yr <sup>–1</sup> between the 1980s and 2007–2016 (''limited evidence'' , ''medium agreement'') (Figure 5.16; [[#Tian--2019|Tian et al., 2019]]). This estimate is at the high end of the range reported in AR5 (WGI, Section 6.4.3). Model projections further show that global warming has led to increased soil N <sub>2</sub> O emissions of 0.8 (0.3–1.3) TgN yr <sup>–1</sup> since approximately pre-industrial times, of which about half occurred since the 1980s (''limited evidence'' , ''high agreement'') ([[#Tian--2019|Tian et al., 2019]] , 2020).

The SRCCL assessed that deforestation and other forms of land-use change significantly alter terrestrial N <sub>2</sub> O emissions through emission pulses following conversions, generally resulting in long-term reduced emissions in unfertilized ecosystems (''medium evidence, high agreement''). This conclusion is supported by a recent study demonstrating that the deforestation-pulse effect is offset by the effect of reduced area of mature tropical forests ([[#Tian--2020|Tian et al., 2020]]).

Uncertainties remain in process-based models with respect to their ability to capture the complicated responses of terrestrial N <sub>2</sub> O emissions to rain pulses, freeze–thaw cycles and the net consequences of elevated levels of CO <sub>2</sub> accurately ([[#Tian--2019|Tian et al., 2019]]). Emerging literature suggests that permafrost thaw may contribute significantly to arctic N <sub>2</sub> O emissions ([[#Voigt--2020|Voigt et al., 2020]]), but these processes are not yet adequately represented in models and upscaling to large-scale remains a significant challenge.

<div id="5.2.3.5" class="h3-container"></div>

<span id="n-2-o-budget"></span>
==== 5.2.3.5 N <sub>2</sub> O Budget ====

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The synthesis of bottom-up estimates of N <sub>2</sub> O sources (Sections 5.2.3.2–5.2.3.4 and Figure 5.17) yields a global source of 17.0 (12.2 to 23.5) TgN yr <sup>–1</sup> for the years 2007–2016 (Table 5.3). This estimate is comparable to AR5, but the uncertainty range has been reduced primarily due to improved estimates of ocean and anthropogenic N <sub>2</sub> O sources. Since AR5 (WGI, Section 6.4.3), improved capacity to estimate N <sub>2</sub> O sources from atmospheric N <sub>2</sub> O measurements by inverting models of atmospheric transport provides a new and independent constraint for the global N <sub>2</sub> O budget ([[#Saikawa--2014|Saikawa et al., 2014]] ; [[#Thompson--2019|Thompson et al., 2019]] ; [[#Tian--2020|Tian et al., 2020]]). The decadal mean source derived from these inversions is remarkably consistent with the bottom-up global N <sub>2</sub> O budget for the same period, however, the split between land and ocean sources based on atmospheric inversions is less constrained, yielding a smaller land source of 11.3 (10.2 to 13.2) TgN yr <sup>–1</sup> and a larger ocean source of 5.7 (3.4 to 7.2) TgN yr <sup>–1</sup> , respectively, compared to bottom-up estimates.

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[[File:f57d2c2590e8bcd70a228730cd6cefc3 IPCC_AR6_WGI_Figure_5_17.png]]

'''Figure 5.17 |''' '''Global nitrous oxide (N''' <sub>2</sub> '''O) budget (2007–2016).''' Values and data sources as in Table 5.3. The atmospheric stock is calculated from mean N <sub>2</sub> O concentration, multiplying a factor of 4.79 ± 0.05 Tg ppb <sup>–1</sup> ([[#Prather--2012|Prather et al., 2012]]). Pool sizes for the other reservoirs are largely unknown. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

Supported by multiple studies and extensive observational evidence (Sections 5.2.3.2–5.2.3.4 and Figure 5.17), anthropogenic emissions contributed about 40% (7.3; uncertainty range: 4.2 to 11.4 TgN yr <sup>–1</sup>) to the total N <sub>2</sub> O source in 2007–2016 (''high confidence''). This estimate is larger than in AR5 (WGI, 6.4.3) due to a larger estimated effect of nitrogen deposition on soil N <sub>2</sub> O emissions and the explicit consideration of the role of anthropogenic nitrogen in determining inland water and estuary emissions.

Based on bottom-up estimates, anthropogenic emissions from agricultural nitrogen use, industry and other indirect effects have increased by 1.7 (1.0 to 2.7) TgN yr <sup>–1</sup> between the decades 1980–1989 and 2007–2016, and are the primary cause of the increase in the total N <sub>2</sub> O source (''high confidence''). Atmospheric inversions indicate that changes in surface emissions, rather than in the atmospheric transport or sink of N <sub>2</sub> O, are the cause for the increased atmospheric growth rate of N <sub>2</sub> O (''robust evidence, high agreement'') ([[#Thompson--2019|Thompson et al., 2019]]). However, the increase of 1.6 (1.4 to 1.7) TgN yr <sup>–1</sup> in global emissions between 2000–2005 and 2010–2015 based on atmospheric inversions is somewhat larger than bottom-up estimates over the same period, primarily because of differences in the estimates of land-based emissions.

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'''Table 5.3 |''' '''Global N''' <sub>2</sub> '''O budget (units TgN y''' '''r''' –1 ''') averaged over the 1980s, 1990s, 2000s as well as the recent decade starting in 2007''' . Uncertainties represent the assessed range of source/sink estimates. All numbers are reproduced from [[#Tian--2020|Tian et al. (2020)]] based on a compilation of inventories, bottom-up models, as well as atmospheric inversions. For detailed information on datasets, see Data Table 5.SM.6.

{| class="wikitable"
|-
! colspan="2"|
! AR6 1980–1989

(TgN yr <sup>–1</sup>)

! AR6 1990–1999

(TgN yr <sup>–1</sup>)

! AR6 2000–2009

(TgN yr <sup>–1</sup>)

! AR6 (2007–2016)

(TgN yr <sup>–1</sup>)

! AR5 (2006–2011)

(TgN yr <sup>–1</sup>)

|-
! colspan="7"| '''B''' '''ottom-up Budget'''

|-
| colspan="7"| '''Anthro''' '''pogenic sources'''

|-
|
| Fossil fuel combustion and Industry

| 0.9 (0.8 to 1.1)

| 0.9 (0.9 to 1.0)

| 1.0 (0.8 to 1.0)

| 1.0 (0.8 to 1.1)

| 0.7 (0.2 to 1.8)

|-
|
| Agriculture (incl. aquaculture)

| 2.6 (1.8 to 4.1)

| 3.0 (2.1 to 4.8)

| 3.4 (2.3 to 5.2)

| 3.8 (2.5 to 5.8)

| 4.1 (1.7 to 4.8)

|-
|
| Biomass and biofuel burning

| 0.7 (0.7 to 0.7)

| 0.7 (0.6 to 0.8)

| 0.6 (0.6 to 0.6)

| 0.6 (0.5 to 0.8)

| 0.7 (0.2 to 1.0)

|-
|
| Wastewater

| 0.2 (0.1 to 0.3)

| 0.3 (0.2 to 0.4)

| 0.3 (0.2 to 0.4)

| 0.4 (0.2 to 0.5)

| 0.2 (0.1 to 0.3)

|-
|
| Inland water, estuaries, coastal zones

| 0.4 (0.2 to 0.5)

| 0.4 (0.2 to 0.5)

| 0.4 (0.2 to 0.6)

| 0.5 (0.2 to 0.7)

|
|-
|
| Atmospheric nitrogen deposition on ocean

| 0.1 (0.1 to 0.2)

| 0.1 (0.1 to 0.2)

| 0.1 (0.1 to 0.2)

| 0.1 (0.1 to 0.2)

| 0.2 (0.1 to 0.4)

|-
|
| Atmospheric nitrogen deposition on land

| 0.6 (0.3 to 1.2)

| 0.7 (0.4 to 1.4)

| 0.7 (0.4 to 1.3)

| 0.8 (0.4 to 1.4)

| 0.4 (0.3 to 0.9)

|-
|
| Other indirect effects from CO <sub>2</sub> , climate and land-use change

| 0.1 (–0.4 to 0.7)

| 0.1 (–0.5 to 0.7)

| 0.2 (–0.4 to 0.9)

| 0.2 (–0.6 to 1.1)

|
|-
|
| '''Tota''' '''l anthropogenic'''

| '''5.6 (3.6 to 8.7)'''

| '''6.2 (3.9 to 9.6)'''

| '''6.7 (4.1 to 10.3)'''

| '''7.3 (4.2 to 11.4)'''

| '''6.3 (2.6 to 9.2)'''

|-
| colspan="7"| '''Natural so''' '''urces and sinks'''

|-
|
| Rivers, estuaries, and coastal zones

| 0.3 (0.3 to 0.4)

| 0.3 (0.3 to 0.4)

| 0.3 (0.3 to 0.4)

| 0.3 (0.3 to 0.4)

| 0.6 (0.1 to 2.9)

|-
|
| Open oceans

| 3.6 (3.0 to 4.4)

| 3.5 (2.8 to 4.4)

| 3.5 (2.7 to 4.3)

| 3.4 (2.5 to 4.3)

| 3.8 (1.8 to 9.4)

|-
|
| Soils under natural vegetation

| 5.6 (4.9 to 6.6)

| 5.6 (4.9 to 6.5)

| 5.6 (5.0 to 6.5)

| 5.6 (4.9 to 6.5)

| 6.6 (3.3 to 9.0)

|-
|
| Atmospheric chemistry

| 0.4 (0.2 to 1.2)

| 0.4 (0.2 to 1.2)

| 0.4 (0.2 to 1.2)

| 0.4 (0.2 to 1.2)

| 0.6 (0.3 to 1.2)

|-
|
| Surface sink

| –0.01 (–0.3 to 0)

| –0.01 (–0.3 to 0)

| –0.01 (–0.3 to 0)

| –0.01 (–0.3 to 0)

| –0.01 (–1 to 0)

|-
|
| '''Total natural'''

| '''9.9 (8.5''' – '''12.2)'''

| '''9.8 (8.3–12.1)'''

| '''9.8 (8.2''' – '''12.0)'''

| '''9.7 (8.0''' – '''12.0)'''

| '''11.6 (5.5–23.5)'''

|-
| colspan="2"| '''Total b''' '''ottom-up source'''

| '''15.5 (12.1 to 20.9)'''

| '''15.9 (12.2 to 21.7)'''

| '''16.4 (12.3 to 22.4)'''

| '''17.0 (12.2 to 23.5)'''

| '''17.9 (8.1 to 30.7)'''

|-
| colspan="2"| '''Obser''' '''ved growth rate'''

|
| '''3.7 (3.7 to 3.7)'''

| '''4.5 (4.3 to 4.6)'''

| '''3.6 (3.5 to 3.8)'''

|-
| colspan="2"| '''Inferred str''' '''atospheric sink'''

|
| '''12.9 (12.2-13.5)'''

| '''13.1 (12.4–13.6)'''

| '''14.3 (4.3 to 28.7)'''

|-
| colspan="7"| '''Atmosp''' '''heric inversion'''

|-
|
| Atmospheric loss

|
| 12.1 (11.4 to 13.3)

| 12.4 (11.7 to 13.3)

|
|-
|
| Total source

|
| 15.9 (15.1 to 16.9)

| 16.9 (15.9 to 17.7)

|
|-
|
| Imbalance

|
| 3.6 (2.2 to 5.7)

| 4.2 (2.4 to 6.4)

|
|}

<div id="5.2.4" class="h2-container"></div>

<span id="the-relative-importance-of-co-2-ch-4-and-n-2-o"></span>
=== 5.2.4 The Relative Importance of CO <sub>2</sub> , CH <sub>4</sub> , and N <sub>2</sub> O ===

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The total influence of anthropogenic greenhouse gases (GHGs) on the Earth’s radiative balance is driven by the combined effect of those gases, and the three most important – carbon dioxide (CO <sub>2</sub>), methane (CH <sub>4</sub>), nitrous oxide (N <sub>2</sub> O) – were discussed in the previous sections. This section compares the balance of the sources and sinks of these three gases and their regional net flux contributions to the radiative forcing. CO <sub>2</sub> has multiple residence times in the atmosphere – from one year to many thousands of years (Box 6.1 in [[#Ciais--2013|Ciais et al., 2013]]) – and N <sub>2</sub> O has a mean lifetime of 116 years. They are both long-lived GHGs, while CH <sub>4</sub> has a lifetime of 9.1 years and is considered a short-lived GHG (see [[IPCC:Wg1:Chapter:Chapter-2|Chapter 2]] for lifetime of GHGs, [[IPCC:Wg1:Chapter:Chapter-6|Chapter 6]] for CH <sub>4</sub> chemical lifetime, and [[IPCC:Wg1:Chapter:Chapter-7|Chapter 7]] for effective radiative forcing of all GHGs).

Figure 5.18 shows the contribution to radiative forcing of CO <sub>2</sub> , CH <sub>4</sub> , N <sub>2</sub> O, and the halogenated species since the 1900s to more recent decades. For the period 1960–2019, the relative contribution to the total effective radiative forcing (ERF) was 63% for CO <sub>2</sub> , 11% for CH <sub>4</sub> , 6% for N <sub>2</sub> O, and 17% for the halogenated species (Chapter 7; Figure 5.18). The systematic decline in the relative contribution to ERF for CH <sub>4</sub> since 1850 is caused by a slower increase rate of CH <sub>4</sub> in the recent decades, at 6, 10 and 5 ppb yr <sup>–1</sup> during 1850–2019, 1960–2019 and 2000–2019, respectively, in comparison with the increasing rate of CO <sub>2</sub> (at 0.7, 1.6 and 2.2 ppm yr <sup>–1</sup> , respectively) and N <sub>2</sub> O (at 0.4, 0.7 and 0.9 ppb yr <sup>–1</sup> , respectively; Figure 5.4). Owing to the shorter lifetime of CH <sub>4</sub> , the effect of a reduction in the emissions increase rate on the ERF increase is evident at inter-decadal time scales.

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[[File:84c5e7cc6a8405220dc64e9d2535e0c7 IPCC_AR6_WGI_Figure_5_18.png]]

'''Figure 5.18 |''' '''Contributions of carbon dioxide (CO''' <sub>2</sub> '''), methane (CH''' <sub>4</sub> '''), nitrous oxide (N''' <sub>2</sub> '''O) and halogenated species to the total effective radiative forcing (ERF) increases in 2019 since 1850, 1960 and 2000, respectively''' . ERF data are taken from [[IPCC:Wg1:Chapter:Annex-iii|Annex III]] (based on calculations from Chapter 7). Note that the sum of the ERFs exceeds 100% because there are negative ERFs due to aerosols and clouds. Further details on data sources and processing are available in the chapter data table (Table 5.SM.6).

Atmospheric abundance of GHGs is proportional to their emissions-loss budgets in the Earth’s environment. There are multiple metrics to evaluate the relative importance of different GHGs for the global atmospheric radiation budget and the socio-economic impacts ([[IPCC:Wg1:Chapter:Chapter-7#7.6|Section 7.6]]). Metrics for weighting emissions are further developed in AR6 WGIII. Figure 5.19 shows the regional emissions of the three main GHGs. For North Asia, Europe, Temperate North America and West Asia, the most dominant GHG source is CO <sub>2</sub> (''high confidence'') (Figure 5.19) while, for East Asia, South Asia, South East Asia, Tropical South America, Temperate North America and Central Africa, the source is CH <sub>4</sub> (Figure 5.19). The N <sub>2</sub> O emissions are dominant in regions with intense use of nitrogen fertilizers in agriculture. Only boreal North America showed net sinks of CO <sub>2</sub> , while close to flux neutrality is observed for North Asia, Southern Africa, and Australasia. Persistent emissions of CO <sub>2</sub> are observed for Tropical and South America, northern Africa, and South East Asia (''medium confidence''). The ''medium confidence'' arises from large uncertainties in the estimated non-fossil fuel CO <sub>2</sub> fluxes over these regions due to the lack of high-quality atmospheric measurements.

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[[File:6c194ad7d7408a230161b3930730cfc2 IPCC_AR6_WGI_Figure_5_19.png]]

'''Figure 5.19 |''' '''Regional distributions of net fluxes of carbon dioxide (CO''' <sub>2</sub> '''), methane (CH''' <sub>4</sub> '''), nitrous oxide (N''' <sub>2</sub> '''O) on the Earth’s surface.''' The region divisions, shown as the shaded map, are made based on ecoclimatic characteristics of the land. The fluxes include those from anthropogenic activities and natural causes that result from responses to anthropogenic greenhouse gases and climate change (feedbacks) as in the three budgets shown in Sections 5.2.1.5, 5.2.2.5, and 5.2.3.5. The CH <sub>4</sub> and N <sub>2</sub> O emissions are weighted by arbitrary factors of 50 and 500, respectively, for depiction by common y-axes. Fluxes are shown as the mean of the inverse models as available from Thompson et al. (2019); Friedlingstein et al. (2020); Saunois et al. (2020). Further details on data sources and processing are available in the chapter data Table (Table 5.SM.6).

<div id="5.3" class="h1-container"></div>

<span id="ocean-acidification-and-deoxygenation"></span>