We examined the dependence of the distribution of atmospheric d¹³C-CH₄ on the KIEs associated with various CH₄ sinks (i.e., OH, Cl, O(¹D), and soil bacteria). We also investigated the changes in both mixing ratio and d¹³C of CH₄ observed between the years 1989 to 1993 by considering changes in the strengths of these sinks and the relative likelihood of postulated changes in CH₄ sources. In doing so, we used the general features of observed d¹³C-CH₄ data as reported by Tyler et al. [1993] for Niwot Ridge and Lowe et al. [1994] for Baring Head and the then-recent data from the NOAA/CMDL network of measurement stations reported in Dlugokencky et al. [1994] which indicated that CH₄ growth rate, easily discernible between about 1978 and 1990 (e.g., Rasmus-sen and Khalil [1981]; Steele et al. [1987 and 1992]; Blake and Rowland [1988]), had nearly leveled off (almost no net change was observed between 1991 and 1992).

To assess the effects of KIEs in the CH₄ loss processes, we successively added KIEs to the reference loss function (simulation A1) which included only the KIE of the reaction of CH₄ with OH. Additional simulations were named A2 (soil sink KIE included) and A3 (soil and Cl sink included). In the simulation, the generally accepted values for all CH₄ loss KIEs were used. They were as follows: k₁₂/k₁₃ = 1.0054 for the OH sink with no temperature dependence over the range of atmospheric temperatures simulated [Cantrell et al., 1990], k₁₂/k₁₃ = 1.022 for the soil sink again with no temperature dependence [Tyler et al., 1994], and k₁₂/k₁₃ = 1.043 · exp(6.455/T) for the Cl sink, where T is in Kelvin [Saueressig et al., 1995].

Figure 2. Calculated steady state (a) surface latitudinal distributions and (b) vertical profiles of d13C-CH4 values at 50°N for January for the three cases A1, A2, and A3. See text for more details. [Adapted from Gupta et al., 1996]

Figure 2a shows the calculated steady state latitudinal distributions of d¹³C-CH₄ at the surface. The calculations show that the inclusion of KIEs of CH₄ sinks other than OH has a significant effect on modeled distributions of d¹³C of atmospheric CH₄. In the simulation shown, the estimated source function from Table 1 was purposely chosen to match model-calculated and observed CH₄ mixing and carbon isotope ratios at 40°N and 40°S for case A3. Another similar source function could have been chosen to match observations to model output using case A1 or A2, the point being that any reasonable source function will result in differences of approximately 2 ppm for surface d¹³C-CH₄ values as the KIEs above are added successively as in Figure 2a. From this it is clear that determining values for KIEs of all CH₄ reactions can be as important as determining an accurate CH₄ source function. The magnitude of the carbon KIE as well as the strength of the overall chemical sink both must be considered when evaluating d¹³C of CH₄.

Figure 2b shows the steady state calculated vertical profiles of d¹³C-CH₄ at 50N for the month of January for three cases A1, A2, and A3. Inclusion of a KIE due to Cl enriched d¹³C at 18 km by 0.95 ppm compared to the corresponding surface value, whereas the enrichment was only 0.31 when this KIE was omitted. Because CH₄ reaction with Cl is the sink with the largest carbon KIE, it has a significant effect on atmospheric d¹³C-CH₄ vertically in spite of its much smaller effect on total atmospheric CH₄ oxidation. Even so, comparisons between model-calculated and observed differences between surface and upper air sample d¹³C values were discrepant. The difference in d¹³C-CH₄ between stratospheric and surface level air observed by Brenninkmeijer etal. [1995], Wahlen etal. [1989a], and our own measurements from the NASA AASE-II program was larger than could be accounted for by Gupta et al. [1996] in model calculations using the sink magnitudes and KIE values described.

The 2D model in Gupta et al. [1996] has also been used to help explain the abrupt changes in CH₄ mixing ratio growth rate in the period from 1989 to 1993. The use of CH₄ isotopic data provides an important check on any explanation because any postulated change in CH₄ sources must simultaneously account for changing trends in d¹³C-CH₄ as well as in CH₄ mixing ratio. Once again, features of the observed d¹³C-CH₄ data as reported for Niwot Ridge [Tyler et al., 1993] and for Baring Head [Lowe etal., 1994] over the time period in question were compared to model simulations to explain the causes of atmospheric CH₄ changes.

Table 2: Comparison of change in d13C of CH4 and its growth rate derived from simulations B1, B2, B3. Simulation*** or Observation   Change in d13C-CH4 (‰/yr)* Change in CH4 Growth Rate (ppb / year)**   40N 40S 40N 40S B1 — decrease in 13C-heavy CH4 source in NH   -0.07   -0.02   -8   -1 B2 — decrease in 13C-heavy CH4 source in SH   -0.08   -0.12   -1   -4 B3 — B1 + B2 conditions + slight increase in 13C-light CH4 sources globally   -0.20   -0.19   -8   -3 Observation -0.20 ~-0.20 -9.8 -3.4 * changes calculated by the end of Dec., 1993 relative to Dec., 1991, model simulations from Gupta et al. [1996], observations from Tyler et al. [1993] and Lowe et al. [1994] ** changes calculated by the end of Dec., 1992 relative to Dec., 1991, model simulations from Gupta et al. [1996], observations from Dlugokencky et al. [1994] *** all simulations include changes in OH concentration brought about by ozone depletion and the eruption of Mt. Pinatubo

As shown in Table 2, CH₄ growth rate reported in both the Northern and Southern Hemispheres for 1992 was accompanied by reported decreases in d¹³C-CH₄ in each hemisphere. Model simulations B1, B2, and B3 were designed to compare various explanations for the decrease in CH₄ growth rate. One can see that no single explanation (including decreased loss of CH₄ from former USSR pipelines and gas fields proposed by Dlugokencky et al. [1994] and changes in seasonal biomass burning patterns in the Southern Hemisphere proposed by Lowe et al. [1994]), but rather a combination of changes in both light and heavy sources of CH₄, coupled with recent changes in OH concentration brought about by ozone depletion and the eruption of Mt. Pinatubo, were needed to explain changes in the observed CH₄ mixing ratio observed in that time period.

Although isotopic information has provided major constraints on the global CH₄ budget and its sources and sink processes, there are several areas where more investigations are needed. For one thing, we need to arrive at consensus values for the KIEs of the CH₄ sinks. For example, currently there are two determinations for the carbon KIE in the reaction between CH₄ and O(¹D). Davidson et al. [1987] reported that the carbon KIE of O(¹D) is very small (i.e., ~1.001 at 297 K) on the basis of one measurement made during the course of investigating the CH₄ + OH reaction. More recently, Saueressig et al. [1998] reported it as 1.0115±0.0006 (2s) at 295 K.

More KIE studies may be one key to resolving the discrepancy between observed and calculated d¹³C-CH₄ values in the upper atmosphere. This discrepancy is currently very large at 11-13 km and gets worse with increasing altitude (i.e., 2D model generated d¹³C-CH₄ values from Bergamaschi et al. [1996] are not in agreement with measured values from Sugawara et al. [1997] for upper stratospheric samples). It would also help to have more upper air samples measured for CH₄ mixing and isotope ratio. To that end we recently began a collaboration with Profs. D.R. Blake and F.S. Rowland at UC Irvine to measure CH₄ mixing ratio and d¹³C in air samples collected by aircraft. Thus far we have participated in the NASA missions GTE PEM-Tropics A (samples for isotopic analysis were taken from 2° to 27°S latitude at sea level to 11.3 km) and SONEX (over the Atlantic Ocean between 38° and 66°N at altitudes of 3 to 12 km).

Finally, a source function with seasonally-resolved magnitudes of both source strength and isotope ratio is not presently available. Therefore, although it is possible to provide a match within a few 0.10 ppm between observed and calculated d¹³C-CH₄ values at the few surface locations reported on globally, one obtains only a relatively poor match between measured seasonal differences in d¹³C-CH₄ at either of two sites representing mid Northern and Southern Hemispheric surface CH₄ and model-calculated intra-annual differences [e.g. Gupta et al., 1996; Tyler et al., 1999]. A source function which includes seasonal changes in the d¹³C of emitted CH₄ requires additional measurements designed to study processes controlling the isotopic signature of CH₄ sources [Reeburgh, 1996]. Better global coverage of the surface in the form of routine measurements at many more sites, all of which have been intercalibrated against each other, would also allow for better resolution of the source function. Fixed surface sites and shipboard sampling transects such as those reported on by Lowe et al. [1999] would both contribute toward this coverage.

This article has offered several examples of how stable carbon isotopic measurements help determine the behavior of CH₄, a key greenhouse gas. Continued studies of atmospheric CH₄ and its sources and sinks using stable isotope measurements are in order. More atmospheric measurement data (better global coverage at the surface and many more above-surface observations), improved CH₄ source functions for the models (based on additional source/sink studies), and agreed upon KIEs of CH₄ loss processes will all contribute to further understanding of the CH₄ budget. Ultimately, this is of critical importance because most researchers believe that human-induced changes in CH₄ sources brought about by increasing population will increase global CH₄ emissions unless mitigation strategies are attempted for some of the anthropogenically controlled sources (Intergovernmental Panel on Climate Change, 1996). Deciding which strategies and policies to mitigate CH₄ emission are feasible, which are working, and what the societal impacts are will depend on measurements and models such as those described here which help to understand the CH₄ atmospheric budget, its changes over time, and its link to natural and managed ecosystems.

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