Editing IPCC:AR6/SRCCL/Chapter-2 (section)

=== 2.3.2 Methane ===

<div id="section-2-3-2-1-atmospheric-trends"></div>

<span id="atmospheric-trends"></span>
==== 2.3.2.1 Atmospheric trends ====

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In 2017, the globally averaged atmospheric concentration of CH <sub>4</sub> was 1850 ± 1 ppbv (Figure 2.8A). Systematic measurements of atmospheric CH <sub>4</sub> concentrations began in the mid-1980s and trends show a steady increase between the mid-1980s and early- 1990s, slower growth thereafter until 1999, a period of no growth between 1999 and 2006, followed by a resumption of growth in 2007. The growth rates show very high inter-annual variability with a negative trend from the beginning of the measurement period until about 2006, followed by a rapid recovery and continued high inter- annual variability through 2017 (Figure 2.8B). The growth rate has been higher over the past 4 years ( ''high confidence'' ) (Nisbet et al. 2019 <sup>[[#fn:r602|602]]</sup> ). The trend in δ <sup>13</sup> C-CH <sub>4</sub> prior to 2000 with less depleted ratios indicated that the increase in atmospheric concentrations was due to thermogenic (fossil) CH <sub>4</sub> emissions; the reversal of this trend after 2007 indicates a shift to biogenic sources (Figure 2.8C).

Understanding the underlying causes of temporal variation in atmospheric CH <sub>4</sub> concentrations is an active area of research. Several studies concluded that inter-annual variability of CH <sub>4</sub> growth was driven by variations in natural emissions from wetlands (Rice et al. 2016 <sup>[[#fn:r603|603]]</sup> ; Bousquet et al. 2006 <sup>[[#fn:r604|604]]</sup> ; Bousquet et al. 2011 <sup>[[#fn:r605|605]]</sup> ). These modelling efforts concluded that tropical wetlands were responsible for between 50 and 100% of the inter-annual fluctuations and the renewed growth in atmospheric concentrations after 2007. However, results were inconsistent for the magnitude and geographic distribution of the wetland sources between the models. Pison et al. (2013) <sup>[[#fn:r606|606]]</sup> used two atmospheric inversion models and the ORCHIDEE model and found greater uncertainty in the role of wetlands in inter-annual variability between 1990 and 2009 and during the 1999–2006 pause. Poulter et al. (2017) <sup>[[#fn:r607|607]]</sup> used several biogeochemical models and inventory-based wetland area data to show that wetland CH <sub>4</sub> emissions increases in the boreal zone have been offset by decreases in the tropics, and concluded that wetlands have not contributed significantly to renewed atmospheric CH <sub>4</sub> growth.

The models cited above assumed that atmospheric hydroxyl radical (OH) sink over the period analysed did not vary. OH reacts with CH <sub>4</sub> as the first step toward oxidation to CO <sub>2</sub> . In global CH <sub>4</sub> budgets, the atmospheric OH sink has been difficult to quantify because its short lifetime (about 1 second) and its distribution is controlled by precursor species that have non-linear interactions (Taraborrelli et al., 2012 <sup>[[#fn:r608|608]]</sup> ; Prather et al., 2017 <sup>[[#fn:r609|609]]</sup> ). Understanding of the atmospheric OH sink has evolved recently. The development of credible time series of methyl chloroform (MCF: CH3CCl3) observations offered a way to understand temporal dynamics of OH abundance and applying this to global budgets further weakened the argument for the role of wetlands in determining temporal trends since 1990. Several authors used the MCF approach and concluded that changes in the atmospheric OH sink explained a large portion of the suppression in global CH <sub>4</sub> concentrations relative to the pre-1999 trend (Turner et al. 2017 <sup>[[#fn:r610|610]]</sup> ; Rigby et al. 2013 <sup>[[#fn:r611|611]]</sup> ; McNorton et al. 2016 <sup>[[#fn:r612|612]]</sup> ). These studies could not reject the null hypothesis that OH has remained constant in recent decades and they did not suggest a mechanism for the inferred OH concentration changes (Nisbet et al. 2019 <sup>[[#fn:r613|613]]</sup> ). Nicely et al. (2018) <sup>[[#fn:r614|614]]</sup> used a mechanistic approach and demonstrated that variation in atmospheric OH was much lower than what MCF studies claimed that positive trends in OH due to the effects of water vapour, nitrogen oxides (NOx), tropospheric ozone and expansion of the tropical Hadley cells offsets the decrease in OH that is expected from increasing atmospheric CH <sub>4</sub> concentrations.

The depletion of δ <sup>13</sup> C <sub>atm</sub> beginning in 2009 could be due to changes in several sources. Decreased fire emissions combined with increased tropical wetland emissions compared to earlier years could explain the δ <sup>13</sup> C perturbations to atmospheric CH <sub>4</sub> sources (Worden et al. 2017 <sup>[[#fn:r615|615]]</sup> ; Schaefer et al. 2016 <sup>[[#fn:r616|616]]</sup> ). However, because tropical wetland emissions are higher in the southern hemisphere, and the remote sensing observations show that CH <sub>4</sub> emissions increases are largely in the north tropics (Bergamaschi et al. 2013 <sup>[[#fn:r617|617]]</sup> ; Melton et al. 2013 <sup>[[#fn:r618|618]]</sup> ; Houweling et al. 2014 <sup>[[#fn:r619|619]]</sup> ), an increased wetland source does not fit well with the southern hemisphere δ <sup>13</sup> C observations. New evidence shows that tropical wetland CH <sub>4</sub> emissions are significantly underestimated, perhaps by a factor of 2, because estimates do not account for release by tree stems (Pangala et al. 2017 <sup>[[#fn:r620|620]]</sup> ). Several authors have concluded that agriculture is a more probable source of increased emissions, particularly from rice and livestock in the tropics, which is consistent with inventory data (Wolf et al. 2017 <sup>[[#fn:r621|621]]</sup> ; Patra et al. 2016 <sup>[[#fn:r622|622]]</sup> ; Schaefer et al. 2016 <sup>[[#fn:r623|623]]</sup> ).

The importance of fugitive emissions in the global atmospheric accumulation rate is growing ( ''medium evidence, high agreement'' ). The increased production of natural gas in the US from the mid 2000s is of particular interest because it coincides with renewed atmospheric CH <sub>4</sub> growth (Rice et al. 2016 <sup>[[#fn:r624|624]]</sup> ; Hausmann et al. 2015 <sup>[[#fn:r625|625]]</sup> ). Reconciling increased fugitive emissions with increased isotopic depletion of atmospheric CH <sub>4</sub> indicates that there are ''likely'' multiple changes in emissions and sinks that affect atmospheric accumulation ( ''medium confidence'' ).

With respect to atmospheric CH <sub>4</sub> growth rates, we conclude that there is significant and ongoing accumulation of CH <sub>4</sub> in the atmosphere ( ''very high confidence'' ). The reason for the pause in growth rates and subsequent renewed growth is at least partially associated with land use and land use change. Evidence that variation in the atmospheric OH sink plays a role in the year-to-year variation of the CH <sub>4</sub> is accumulating, but results are contradictory ( ''medium evidence, low agreement'' ) and refining this evidence is constrained by lack of long-term isotopic measurements at remote sites, particularly in the tropics. Fugitive emissions likely contribute to the renewed growth after 2006 ( ''medium evidence, high agreement'' ). Additionally, the recent depletion trend of <sup>13</sup> C isotope in the atmosphere indicates that growth in biogenic sources explains part of the current growth and that biogenic sources make up a larger proportion of the source mix compared to the period before 1997 ( ''robust evidence, high agreement'' ). In agreement with the findings of AR5, we conclude that wetlands are important drivers of inter- annual variability and current growth rates ( ''medium evidence, high agreement'' ). Ruminants and the expansion of rice cultivation are also important contributors to the current growth trend ( ''medium evidence, high agreement'' ).

<div id="section-2-3-2-1-atmospheric-trends-block-2"></div>

<span id="figure-2.8"></span>
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'''Figure 2.8'''

<span id="globally-averaged-atmospheric-ch4-mixing-ratios-frame-a-and-instantaneous-rates-of-change-frame-b-and-c-isotopevariation-frame-c.-data-sources-noaaesrl-www.esrl.noaa.govgmdccggtrends_ch4-dlugokencky-et-al.-1994-and-schaefer-et-al.-2016."></span>
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'''Globally averaged atmospheric CH4 mixing ratios (Frame A) and instantaneous rates of change (Frame B) and C isotope/variation (Frame C). Data sources: NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends_ch4); Dlugokencky et al. (1994) and Schaefer et al. (2016).'''
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[[File:ba5541e1bc4f3f3fc46c2d300188606f Figure-2.8-1018x1024.jpg]]

Globally averaged atmospheric CH <sub>4</sub> mixing ratios (Frame A) and instantaneous rates of change (Frame B) and C isotope/variation (Frame C). Data sources: NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends_ch4); Dlugokencky et al. (1994) <sup>[[#fn:r626|626]]</sup> and Schaefer et al. (2016) <sup>[[#fn:r627|627]]</sup> .

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<div id="section-2-3-2-2-land-use-effects"></div>

<span id="land-use-effects"></span>
==== 2.3.2.2 Land use effects ====

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Agricultural emissions are predominantly from enteric fermentation and rice, with manure management and waste burning contributing<br />
small amounts (Figure 2.9). Since 2000, livestock production has been responsible for 33% of total global emissions and 66% of agricultural emissions (EDGAR 4.3.2 database, May 2018; USEPA 2012 <sup>[[#fn:r628|628]]</sup> ; Tubiello et al. 2014 <sup>[[#fn:r629|629]]</sup> ; Janssens-Maenhout et al. 2017b <sup>[[#fn:r630|630]]</sup> ). Asia has the largest livestock emissions (37%) and emissions in the region have been growing by around 2% per year over the same period.

North America is responsible for 26% and emissions are stable; Europe is responsible for around 8% of emissions, and these are decreasing slightly (&lt;1% per year). Africa is responsible for 14%, but emissions are growing fastest in this region at around 2.5% y <sup>–1</sup> . In Latin America and the Caribbean, livestock emissions are decreasing at around 1.6% per year and the region makes up 16% of emissions.

Rice emissions are responsible for about 24% of agricultural emissions and 89% of these are from Asia. Rice emissions are increasing by 0.9% per year in that region. These trends are predicted to continue through 2030 (USEPA 2013 <sup>[[#fn:r631|631]]</sup> ).

Upland soils are a net sink of atmospheric CH <sub>4</sub> , but soils both produce and consume the gas. On the global scale, climatic zone, soil texture and land cover have an important effect on CH <sub>4</sub> uptake in upland soils (Tate 2015 <sup>[[#fn:r632|632]]</sup> ; Yu et al. 2017 <sup>[[#fn:r633|633]]</sup> ; Dutaur and Verchot 2007 <sup>[[#fn:r634|634]]</sup> ). Boreal soils take up less than temperate or tropical soils, coarse textured soils take up more CH <sub>4</sub> than medium and fine textured soils, and forests take up more than other ecosystems. Low levels of nitrogen fertilisation or atmospheric deposition can affect the soil microbial community and stimulate soil CH <sub>4</sub> uptake in nitrogen-limited soils, while higher fertilisation rates decrease uptake (Edwards et al. 2005 <sup>[[#fn:r635|635]]</sup> ; Zhuang et al., 2013 <sup>[[#fn:r636|636]]</sup> ). Globally, nitrogen fertilisation on agricultural lands may have suppressed CH <sub>4</sub> oxidation by as much as 26 Tg between 1998 and 2004 ( ''low confidence, low agreement'' ) (Zhuang et al., 2013 <sup>[[#fn:r637|637]]</sup> ). The effect of nitrogen additions is cumulative and repeated fertilisation events have progressively greater suppression effects ( ''robust evidence, high agreement'' ) (Tate 2015 <sup>[[#fn:r638|638]]</sup> ). Other factors such as higher temperatures, increased atmospheric concentrations and changes in rainfall patterns stimulate soil CH <sub>4</sub> consumption in unfertilised ecosystems. Several studies (Yu et al. 2017 <sup>[[#fn:r639|639]]</sup> ; Xu et al. 2016 <sup>[[#fn:r640|640]]</sup> ; Curry 2009 <sup>[[#fn:r641|641]]</sup> ) have shown that globally, uptake has been increasing during the second half of the 20th century and is expected to continue to increase by as much as 1 Tg in the 21st century, particularly in forests and grasslands ( ''medium evidence, high agreement'' ).

Northern peatlands (40–70°N) are a significant source of atmospheric CH <sub>4</sub> , emitting about 48 TgCH <sub>4</sub> , or about 10% of the total emissions to the atmosphere (Zhuang et al. 2006 <sup>[[#fn:r642|642]]</sup> ; Wuebbles and Hayhoe 2002 <sup>[[#fn:r643|643]]</sup> ). CH <sub>4</sub> emissions from natural northern peatlands are highly variable, with the highest rate from fens ( ''medium evidence, high agreement'' ). Peatland management and restoration alters the exchange of CH <sub>4</sub> with the atmosphere ( ''medium evidence, high agreement'' ). Management of peat soils typically converts them from CH <sub>4</sub> sources to sinks (Augustin et al. 2011 <sup>[[#fn:r644|644]]</sup> ; Strack and Waddington 2008 <sup>[[#fn:r645|645]]</sup> ; Abdalla et al. 2016 <sup>[[#fn:r646|646]]</sup> ) ( ''robust evidence, high agreement'' ). While restoration decreases CO <sub>2</sub> emissions (Section 4.9.4), CH <sub>4</sub> emissions often increase relative to the drained conditions ( ''robust evidence, high agreement'' ) (Osterloh et al. 2018 <sup>[[#fn:r647|647]]</sup> ; Christen et al. 2016 <sup>[[#fn:r648|648]]</sup> ; Koskinen et al. 2016 <sup>[[#fn:r649|649]]</sup> ; Tuittila et al. 2000 <sup>[[#fn:r650|650]]</sup> ; Vanselow-Algan et al. 2015 <sup>[[#fn:r651|651]]</sup> ; Abdalla et al. 2016 <sup>[[#fn:r652|652]]</sup> ). Drained peatlands are usually considered to be negligible methane sources, but they emit CH <sub>4</sub> under wet weather conditions and from drainage ditches (Drösler et al. 2013 <sup>[[#fn:r653|653]]</sup> ; Sirin et al. 2012 <sup>[[#fn:r654|654]]</sup> ). While ditches cover only a small percentage of the drained area, emissions can be sufficiently high that drained peatlands emit comparable CH <sub>4</sub> as undrained ones ( ''medium evidence, medium agreement'' ) (Sirin et al. 2012 <sup>[[#fn:r655|655]]</sup> ; Wilson et al. 2016 <sup>[[#fn:r656|656]]</sup> ).

Because of the large uncertainty in the tropical peatland area, estimates of the global flux are highly uncertain. A meta-analysis of the effect of conversion of primary forest to rice production showed that emissions increased by a factor of four ( ''limited evidence, high agreement'' ) (Hergoualc’h and Verchot, 2012 <sup>[[#fn:r657|657]]</sup> ). For land uses that required drainage, emissions decreased by a factor of three ( ''limited evidence, high agreement'' ).There are no representative measurements of emissions from drainage ditches in tropical peatlands.

<div id="section-2-3-2-2-land-use-effects-block-2"></div>

<span id="figure-2.9"></span>
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'''Figure 2.9'''

<span id="average-agricultural-ch4-emissions-estimates-from-1990.-sub-sectorial-agricultural-emissions-are-based-on-the-emissions-database-for-global-atmospheric-research-edgar-v4.3.2-janssens-maenhout-et-al.-2017a-faostat-tubiello-et-al.-2013-and-national-ghgi-data-grassi-et-al.-2018.-ghgi-data-are-aggregate-values-for-the-sector.-note-that-edgar-data-are-complete-only-through"></span>
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'''Average agricultural CH4 emissions estimates from 1990. Sub-sectorial agricultural emissions are based on the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2; Janssens-Maenhout et al. 2017a); FAOSTAT (Tubiello et al. 2013); and National GHGI data (Grassi et al. 2018). GHGI data are aggregate values for the sector. Note that EDGAR data are complete only through […]'''
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[[File:36b982b2b8d180f89286cbcde6c789c0 Figure-2.9-1024x599.jpg]]

Average agricultural CH <sub>4</sub> emissions estimates from 1990. Sub-sectorial agricultural emissions are based on the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2; Janssens-Maenhout et al. 2017a <sup>[[#fn:r658|658]]</sup> ); FAOSTAT (Tubiello et al. 2013 <sup>[[#fn:r659|659]]</sup> ); and National GHGI data (Grassi et al. 2018 <sup>[[#fn:r660|660]]</sup> ). GHGI data are aggregate values for the sector. Note that EDGAR data are complete only through 2012; the data in the right-hand panel represent the three years 2010–2012 and are presented for comparison.

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<span id="nitrous-oxide"></span>