2.3.2 Atmospheric Methane

This section describes the current global measurement programmes for atmospheric CH₄, which provide the data required for the understanding of its budget and for the calculation of its RF. In addition, this section provides data for the pre-industrial levels of CH₄ required as the accepted reference level for these calculations. Detailed analyses of CH₄ budgets and its biogeochemistry are presented in Section 7.4.

Methane has the second-largest RF of the LLGHGs after CO₂ (Ramaswamy et al., 2001). Over the last 650 kyr, ice core records indicate that the abundance of CH₄ in the Earth’s atmosphere has varied from lows of about 400 ppb during glacial periods to highs of about 700 ppb during interglacials (Spahni et al., 2005) with a single measurement from the Vostok core reaching about 770 ppb (see Figure 6.3).

In 2005, the global average abundance of CH₄ measured at the network of 40 surface air flask sampling sites operated by NOAA/GMD in both hemispheres was 1,774.62 ± 1.22 ppb.^[8] This is the most geographically extensive network of sites operated by any laboratory and it is important to note that the calibration scale it uses has changed since the TAR (Dlugokencky et al., 2005). The new scale (known as NOAA04) increases all previously reported CH₄ mixing ratios from NOAA/GMD by about 1%, bringing them into much closer agreement with the Advanced Global Atmospheric Gases Experiment (AGAGE) network. This scale will be used by laboratories participating in the WMO’s GAW programme as a ‘common reference’. Atmospheric CH₄ is also monitored at five sites in the NH and SH by the AGAGE network. This group uses automated systems to make 36 CH₄ measurements per day at each site, and the mean for 2005 was 1,774.03 ± 1.68 ppb with calibration and methods described by Cunnold et al. (2002). For the NOAA/GMD network, the 90% confidence interval is calculated with a Monte Carlo technique, which only accounts for the uncertainty due to the distribution of sampling sites. For both networks, only sites in the remote marine boundary layer are used and continental sites are not included. Global databases of atmospheric CH₄ measurements for these and other CH₄ measurement programmes (e.g., Japanese, European and Australian) are maintained by the CDIAC and by the WDCGG in the GAW programme.

Present atmospheric levels of CH₄ are unprecedented in at least the last 650 kyr (Spahni et al., 2005). Direct atmospheric measurements of the gas made at a wide variety of sites in both hemispheres over the last 25 years show that, although the abundance of CH₄ has increased by about 30% during that time, its growth rate has decreased substantially from highs of greater than 1% yr^–1 in the late 1 70s and early 1980s (Blake and Rowland, 1988) to lows of close to zero towards the end of the 1990s (Dlugokencky et al., 1998; Simpson et al., 2002). The slowdown in the growth rate began in the 1980s, decreasing from 14 ppb yr^–1 (about 1% yr^–1) in 1984 to close to zero during 1999 to 2005, for the network of surface sites maintained by NOAA/GMD (Dlugokencky et al., 2003). Measurements by Lowe et al. (2004) for sites in the SH and Cunnold et al. (2002) for the network of GAGE/AGAGE sites show similar features. A key feature of the global growth rate of CH₄ is its current interannual variability, with growth rates ranging from a high of 14 ppb yr^–1 in 1998 to less than zero in 2001, 2004 and 2005. (Figure 2.4)

Figure 2.4. Recent CH_4 concentrations and trends. (a) Time series of global CH_4 abundance mole fraction (in ppb) derived from surface sites operated by NOAA/GMD (blue lines) and AGAGE (red lines). The thinner lines show the CH_4 global averages and the thicker lines are the de-seasonalized global average trends from both networks. (b) Annual growth rate (ppb yr^–1) in global atmospheric CH_4 abundance from 1984 through the end of 2005 (NOAA/GMD, blue), and from 1988 to the end of 2005 (AGAGE, red). To derive the growth rates and their uncertainties for each month, a linear least squares method that takes account of the autocorrelation of residuals is used. This follows the methods of Wang et al. (2002) and is applied to the de-seasonalized global mean mole fractions from (a) for values six months before and after the current month. The vertical lines indicate ±2 standard deviation uncertainties (95% confidence interval), and 1 standard deviation uncertainties are between 0.1 and 1.4 ppb yr^–1 for both AGAGE and NOAA/GMD. Note that the differences between AGAGE and NOAA/GMD calibration scales are determined through occasional intercomparisons.

The reasons for the decrease in the atmospheric CH₄ growth rate and the implications for future changes in its atmospheric burden are not understood (Prather et al., 2001) but are clearly related to changes in the imbalance between CH₄ sources and sinks. Most CH₄ is removed from the atmosphere by reaction with the hydroxyl free radical (OH), which is produced photochemically in the atmosphere. The role of OH in controlling atmospheric CH₄ levels is discussed in Section 2.3.5. Other minor sinks include reaction with free chlorine (Platt et al., 2004; Allan et al., 2005), destruction in the stratosphere and soil sinks (Born et al., 1990).

The total global CH₄ source is relatively well known but the strength of each source component and their trends are not. As detailed in Section 7.4, the sources are mostly biogenic and include wetlands, rice agriculture, biomass burning and ruminant animals. Methane is also emitted by various industrial sources including fossil fuel mining and distribution. Prather et al. (2001) documented a large range in ‘bottom-up’ estimates for the global source of CH₄. New source estimates published since then are documented in Table 7.6. However, as reported by Bergamaschi et al. (2005), national inventories based on ‘bottom-up’ studies can grossly underestimate emissions and ‘top-down’ measurement-based assessments of reported emissions will be required for verification. Keppler et al. (2006) reported the discovery of emissions of CH₄ from living vegetation and estimated that this contributed 10 to 30% of the global CH₄ source. This work extrapolates limited measurements to a global source and has not yet been confirmed by other laboratories, but lends some support to space-borne observations of CH₄ plumes above tropical rainforests reported by Frankenberg et al. (2005). That such a potentially large source of CH₄ could have been missed highlights the large uncertainties involved in current ‘bottom-up’ estimates of components of the global source (see Section 7.4).

Several wide-ranging hypotheses have been put forward to explain the reduction in the CH₄ growth rate and its variability. For example, Hansen et al. (2000) considered that economic incentives have led to a reduction in anthropogenic CH₄ emissions. The negligible long-term change in its main sink (OH; see Section 2.3.5 and Figure 2.8) implies that CH₄ emissions are not increasing. Similarly, Dlugokencky et al. (1998) and Francey et al. (1999) suggested that the slowdown in the growth rate reflects a stabilisation of CH₄ emissions, given that the observations are consistent with stable emissions and lifetime since 1982.

Relatively large anomalies occurred in the growth rate during 1991 and 1998, with peak values reaching 15 and 14 ppb yr^–1, respectively (about 1% yr^–1). The anomaly in 1991 was followed by a dramatic drop in the growth rate in 1992 and has been linked with the Mt. Pinatubo volcanic eruption in June 1991, which injected large amounts of ash and (sulphur dioxide) SO₂ into the lower stratosphere of the tropics with subsequent impacts on tropical photochemistry and the removal of CH₄ by atmospheric OH (Bekki et al., 1994; Dlugokencky et al., 1996). Lelieveld et al. (1998) and Walter et al. (2001a,b) proposed that lower temperatures and lower precipitation in the aftermath of the Mt. Pinatubo eruption could have suppressed CH₄ emissions from wetlands. At this time, and in parallel with the growth rate anomaly in the CH₄ mixing ratio, an anomaly was observed in the ¹³C/¹²C ratio of CH₄ at surface sites in the SH. This was attributed to a decrease in emissions from an isotopically heavy source such as biomass burning (Lowe et al., 1997; Mak et al., 2000), although these data were not confirmed by lower frequency measurements from the same period made by Francey et al. (1999).

For the relatively large increase in the CH₄ growth rate reported for 1998, Dlugokencky et al. (2001) suggested that wetland and boreal biomass burning sources might have contributed to the anomaly, noting that 1998 was the warmest year globally since surface instrumental temperature records began. Using an inverse method, Chen and Prinn (2006) attributed the same event primarily to increased wetland and rice region emissions and secondarily to biomass burning. The same conclusion was reached by Morimoto et al. (2006), who used carbon isotopic measurements of CH₄ to constrain the relative contributions of biomass burning (one-third) and wetlands (two-thirds) to the increase.

Based on ice core measurements of CH₄ (Etheridge et al., 1998), the pre-industrial global value for CH₄ from 1700 to 1800 was 715 ± 4 ppb (it was also 715 ± 4 ppb in 1750), thus providing the reference level for the RF calculation. This takes into account the inter-polar difference in CH₄ as measured from Greenland and Antarctic ice cores.

The RF due to changes in CH₄ mixing ratio is calculated with the simplified yet still valid expression for CH₄ given in Ramaswamy et al. (2001). The change in the CH₄ mixing ratio from 715 ppb in 1750 to 1,774 ppb (the average mixing ratio from the AGAGE and GMD networks) in 2005 gives an RF of +0.48 ± 0.05 W m^–2, ranking CH₄ as the second highest RF of the LLGHGs after CO₂ (Table 2.1). The uncertainty range in mixing ratios for the present day represents intra-annual variability, which is not included in the pre-industrial uncertainty estimate derived solely from ice core sampling precision. The estimate for the RF due to CH₄ is the same as in Ramaswamy et al. (2001) despite the small increase in its mixing ratio. The spectral absorption by CH₄ is overlapped to some extent by N₂O lines (taken into account in the simplified expression). Taking the overlapping lines into account using current N₂O mixing ratios instead of pre-industrial mixing ratios (as in Ramaswamy et al., 2001) reduces the current RF due to CH₄ by 1%.

Collins et al. (2006) confirmed that line-by-line models agree extremely well for the calculation of clear-sky instantaneous RF from CH₄ and N₂O when the same atmospheric background profile is used. However, GCM radiation schemes were found to be in poor agreement with the line-by-line models, and errors of over 50% were possible for CH₄, N₂O and the CFCs. In addition, a small effect from the absorption of solar radiation was found with the line-by-line models, which the GCMs did not include (Section 10.2).