7.4.1 Methane

7.4.1.1 Biogeochemistry and Budgets of Methane

Atmospheric CH₄ originates from both non-biogenic and biogenic sources. Non-biogenic CH₄ includes emissions from fossil fuel mining and burning (natural gas, petroleum and coal), biomass burning, waste treatment and geological sources (fossil CH₄ from natural gas seepage in sedimentary basins and geothermal/volcanic CH₄). However, emissions from biogenic sources account for more than 70% of the global total. These sources include wetlands, rice agriculture, livestock, landfills, forests, oceans and termites. Emissions of CH₄ from most of these sources involve ecosystem processes that result from complex sequences of events beginning with primary fermentation of organic macromolecules to acetic acid (CH₃COOH), other carboxylic acids, alcohols, CO₂ and hydrogen (H₂), followed by secondary fermentation of the alcohols and carboxylic acids to acetate, H₂ and CO₂, which are finally converted to CH₄ by the so-called methanogenic Archaea: CH₃COOH → CH₄ + CO₂ and CO₂ + 4H₂ → CH₄ + 2H₂O (Conrad, 1996). Alternatively, CH₄ sources can be divided into anthropogenic and natural. The anthropogenic sources include rice agriculture, livestock, landfills and waste treatment, some biomass burning, and fossil fuel combustion. Natural CH₄ is emitted from sources such as wetlands, oceans, forests, fire, termites and geological sources (Table 7.6).

The net rate of CH₄ emissions is generally estimated from three approaches: (1) extrapolation from direct flux measurements and observations, (2) process-based modelling (bottom-up approach) and (3) inverse modelling that relies on spatially distributed, temporally continuous observations of concentration, and in some cases isotopic composition in the atmosphere (top-down approach). The top-down method also includes aircraft and satellite observations (Xiao et al., 2004; Frankenberg et al., 2005, 2006). When the bottom-up approach is used to extrapolate the emissions to larger scales, uncertainty results from the inherent large temporal and spatial variations of fluxes and the limited range of observational conditions. The top-down approach helps to overcome the weaknesses in bottom-up methods. However, obstacles to extensive application of the top-down approach include inadequate observations, and insufficient capabilities of the models to account for error amplification in the inversion process and to simulate complex topography and meteorology (Dentener et al., 2003a; Mikaloff Fletcher et al., 2004a, 2004b; Chen and Prinn, 2005, 2006). Measurements of isotopes of CH₄ (¹³C, ¹⁴C, and ²H) provide additional constraints on CH₄ budgets and specific sources, but such data are even more limited (Bergamaschi et al., 2000; Lassey et al., 2000; Mikaloff Fletcher et al., 2004a, 2004b).

Since the TAR, availability of new data from various measurement networks and from national reporting documents has enabled re-estimates of CH₄ source magnitudes and insights into individual source strengths. Total global pre-industrial emissions of CH₄ are estimated to be 200 to 250 Tg(CH₄) yr^–1 (Chappellaz et al., 1993; Etheridge et al., 1998; Houweling et al., 2000; Ferretti et al., 2005; Valdes et al., 2005). Of this, natural CH₄ sources emitted between 190 and 220 Tg(CH₄) yr^–1, and anthropogenic sources (rice agriculture, livestock, biomass burning and waste) accounted for the rest (Houweling et al., 2000; Ruddiman and Thomson, 2001). In contrast, anthropogenic emissions dominate present-day CH₄ budgets, accounting for more than 60% of the total global budget (Table 7.6).

The single largest CH₄ source is natural wetlands. Recent estimates combine bottom-up and top-down fluxes, and global observations of atmospheric CH₄ concentrations in a three-dimensional Atmospheric Transport and Chemical Model (ATCM) simulation (Chen and Prinn, 2005, 2006). In these estimates, southern and tropical regions account for more than 70% of total global wetland emissions. Other top-down studies that include both direct observations and ¹³C/¹²C ratios of CH₄ suggest greater emissions in tropical regions compared with previously estimates (Mikaloff Fletcher et al., 2004a, 2004b; Xiao et al., 2004; Frankenberg et al., 2006). However, several bottom-up studies indicate fewer emissions from tropical rice agriculture (Li et al., 2002; Yan et al., 2003; Khalil and Shearer 2006). Frankenberg et al. (2005, 2006) and Keppler et al. (2006) suggest that tropical trees emit CH₄ via an unidentified process. The first estimate of this source was 10 to 30% (62–236 Tg(CH₄) yr^–1) of the global total, but Kirschbaum et al. (2006) revise this estimate downwards to 10 to 60 Tg(CH₄) yr^–1. Representative ¹³C/¹²C ratios (δ¹³C values) of CH₄ emitted from individual sources are included in Table 7.6. Due to isotope fractionation associated with CH₄ production and consumption processes, CH₄ emitted from each source exhibits a measurably different δ¹³C value. Therefore, it is possible, using mixing models, to constrain further the sources of atmospheric CH₄.

Geological sources of CH₄ are not included in Table 7.6. However, several studies suggest that significant amounts of CH₄, produced within the Earth’s crust (mainly by bacterial and thermogenic processes), are released into the atmosphere through faults and fractured rocks, mud volcanoes on land and the seafloor, submarine gas seepage, microseepage over dry lands and geothermal seeps (Etiope and Klusman, 2002; Etiope, 2004; Kvenvolden and Rogers, 2005). Emissions from these sources are estimated to be as large as 40 to 60 Tg(CH₄) yr^–1.

The major CH₄ sinks are oxidation by OH in the troposphere, biological CH₄ oxidation in drier soil, and loss to the stratosphere (Table 7.6). Oxidation by chlorine (Cl) atoms in the marine atmospheric boundary layer is suggested as an additional sink for CH₄, possibly constituting an additional loss of about 19 Tg(CH₄) yr^–1 (Gupta et al., 1997; Tyler et al., 2000; Platt et al., 2004; Allan et al., 2005). However, the decline in the growth rate of atmospheric CH₄ concentration since the TAR shows no clear correlation with change in sink strengths over the same period (Prinn et al., 2001, 2005; Allan et al., 2005). This trend has continued since 1993, and the reduction in the CH₄ growth rate has been suggested to be a consequence of source stabilisation and the approach of the global CH₄ budget towards steady state (Dlugokencky et al., 1998, 2003). Thus, total emissions are likely not increasing but partitioning among the different sources may have changed (see Section 2.3). Consequently, in the Fourth Assessment Report (AR4) the sink strength is treated as in the TAR (576 Tg(CH₄) yr^–1). However, the AR4 estimate has been increased by 1% (to 581 Tg(CH₄) yr^–1) to take into account the recalibration of the CH₄ scale explained in Chapter 2. The main difference between TAR and AR4 estimates is the source-sink imbalance inferred from the annual increment in concentration. The TAR used 8 ppb yr^–1 for a period centred on 1998 when there was clearly an anomalously high growth rate. The present assessment uses 0.2 ppb yr^–1, the average over 2000 to 2005 (see Section 2.3 and Figure 2.4). Thus, using the CH₄ growth rate for a single anomalous year, as in the TAR, gives an anomalously high top-down value relative to the longer-term average source. For a conversion factor of 2.78 Tg(CH₄) per ppb and an atmospheric concentration of 1,774 ppb, the atmospheric burden of CH₄ in 2005 was 4,932 Tg, with an annual average increase (2000–2005) of about 0.6 Tg yr^–1. Total average annual emissions during the period considered here are approximately 582 Tg(CH₄) yr^–1.

Uncertainty in this estimate may arise from several sources. Uncertainty in the atmospheric concentration measurement, given in Chapter 2 as 1,774 ± 1.8 ppb in 2005, is small (about 0.1%). Uncertainty ranges for individual sink estimates are ±103 Tg(CH₄) (20%), ±15 Tg(CH₄) (50%), ±8 Tg(CH₄) (20%) for OH, soil and stratospheric loss, respectively (as reported in the Second Assessment Report). The use of a different lifetime for CH₄ (8.7 ± 1.3 years) leads to an uncertainty in overall sink strength of ±15%. Thus, the top-down method used in AR4 is constrained mainly by uncertainty in sink estimates and the choice of lifetime used in the mass balance calculation.