The GTP of Methane: Modeling Analysis of TemperatureImpacts of Methane and Carbon Dioxide Reductions

Marcus C. Sarofim

Received: 7 May 2008 /Accepted: 28 July 2011 /Published online: 12 August 2011# Springer Science+Business Media B.V. 2011

Abstract The Global Temperature Potential (GTP) hasrecently been proposed as an alternative to the GlobalWarming Potential (GWP). Using two different EarthModels of Intermediate Complexity, we show that thesolution to the 100-year sustained GTP for methane issignificantly larger than the equivalent GWP due to theinclusion of future changes in greenhouse gas concentra-tions in the reference scenario and different atmosphericchemistry assumptions. This result suggests that methanereductions may be undervalued when using GWPs, but thepolicy implications depend on how the objectives ofgreenhouse gas policy are defined.

Keywords Methane . Carbon dioxide . Global warmingpotential . Metrics . Global temperature potential . EMICmodeling

1 Introduction

Many studies have demonstrated that multi-gas policies canbe both more effective and less costly than a policy thatonly addresses carbon dioxide [1, 26, 44]. Rather thanassigning reductions to each gas individually, standardenvironmental economic wisdom suggests that a system

designed around economic instruments such as taxes orpermit trading will enable the invisible hand of the marketto find the most efficient solution to a given constraint byequalizing marginal abatement costs, in the case thatenvironmental impacts are homogeneous and transactioncosts are low [40]. In order to implement such a system, ametric that equates the environmental impacts of differentgases is required. The greenhouse gas (GHG) metric usedin the Kyoto Protocol and in the majority of academicstudies to date is the 100-year Global Warming Potential(GWP). The GWP is a measure of the radiative forcingresulting from a pulse of emissions of 1 kg of a greenhousegas, integrated over 100 years, relative to the integratedradiative forcing of a pulse of 1 kg of CO2 over the sametime period. However, our work and that of otherresearchers suggests that the differences between GHGsare not fully addressed by their GWP exchange value [21,22, 24, 29, 36, 44, 49, 51]. Therefore, a number ofalternative metrics have been proposed, though manyresearchers acknowledge that the GWP may be an adequateif imperfect measure [12, 13].

Some multi-gas approaches have used intertemporaloptimization to dynamically determine the appropriateexchange metric for different gases in order to meet agiven set of constraints [17, 34]: these studies find that thevalue of the metric can change dramatically over time forgases of different lifetimes. Other approaches involvemetrics such as Global Damage Potentials that take intoaccount economic impacts rather than purely physicallybased parameters [25, 42]. Recently, the most prominentalternative metric has been the Global Temperature Poten-tial (GTP) developed by Shine et al. [35]. While Shine et al.discuss both a pulse reduction and a sustained reductionformulation of the GTP, this paper focuses on the sustained(GTPs) version due to its parallels with the politicallyaccepted GWP. The GTPs approach can be described as away to calculate the number of kilograms of CO2 that

Disclaimer: This publication was developed under CooperativeAgreement No. X3 83232801 awarded by the U.S. EnvironmentalProtection Agency to the American Association for the Advancementof Science. It has not been reviewed by EPA. The views expressed inthis document are solely those of the author and do not necessarilyreflect those of the Agency. EPA does not endorse any products orcommercial services mentioned in this publication.

M. C. Sarofim (*)Hosted by the U.S. Environmental Protection AgencyClimate Change Division,AAAS Science and Technology Policy Fellowship,Washington, DC 20008, USAe-mail: msarofim@alum.mit.edu

Environ Model Assess (2012) 17:231–239DOI 10.1007/s10666-011-9287-x

would need to be reduced annually in order to yield thesame temperature after 100 years as the sustained reductionof 1 kg of another GHG. Advantages of the GTP over theGWP include using temperature as a more policy-relevantend point than radiative forcing, and the ability to includemore climate system processes such as climate sensitivityand oceanic heat uptake in calculating the metric value. Arecent IPCC Expert Meeting on the Science of AlternativeMetrics [13] recommended further research into thesemetrics, and specifically highlighted further characteriza-tion of the uncertainties in the GTP metric includingsensitivities to climate processes such as climate sensitivityand carbon cycle responses.

This paper therefore further characterizes the GTP metricin the context of two different Earth System Models ofIntermediate Complexity (EMICs), enabling a more thor-ough examination of the impact on metrics of variousclimate processes than has previously been reported.Specifically, the paper examines the impacts of constantreductions of methane and CO2 emissions on temperaturechange in 2100 under a number of assumptions about futureemission scenarios and climate parameters. Methane hasplayed a prominent role in previous studies on GHGmetrics [11, 12, 42, 49] as methane is the second largestanthropogenic forcing contributor of the greenhouse gases,with higher chemical reactivity in the atmosphere than theother major gases and therefore both a shorter lifetime andmore impacts on other atmospheric constituents such asozone. Methane emissions are projected to continueincreasing in the next couple of decades [30] indicatingthat this gas will have continued importance for near-termclimate policy design. Methane is therefore a naturalsubject for this study.

While the results of this study suggest that the GWP mayunderestimate the importance of methane and that the GTPcan better incorporate some of the complexities of theclimate system, any metric must be evaluated in light of theultimate policy goal [9]. For example, there is not yet clearguidance from policymakers on the relative values of near-term versus long-term temperature change: as the 100-yearGWP itself was a compromise between these values, it isnot clear whether the 100-year GTP more accuratelyreflects the desire of policymakers. The paper discussesthese policy implications in light of the modeling results,raising questions about optimal policy design.

2 Model Descriptions

To study the physical impacts of methane and CO2

reductions, we use two EMICs, the earth system componentof the MIT Integrated Global Systems Model (IGSM)version 2.2 and the Model for the Assessment of

Greenhouse-Gas Induced Climate Change (MAGICC)version 5.3.

The earth system components of the MIT IGSM havebeen described in Sokolov et al. [38]. The atmosphericcomponent is a two-dimensional, 4° zonally averaged land–ocean resolving atmospheric model with 11 vertical levels[39]. The numerics and parameterizations of the physicalprocesses are based upon the Goddard Institute for SpaceStudies GCM [10]. Emissions of reactive gases in urbanareas are aged before release into the larger model based ona reduced form fit to the California Institute of TechnologyUrban Airshed Model [18]. Exports from these urban areasare then combined with emissions from non-urban areas ina chemistry model with 33 species and 53 reactions [46].The detailed chemistry included in this modeling systemenables endogenous determination of the lifetime ofmethane over the next hundred years, which is relevantfor comparisons between reductions in emissions ofmethane and carbon dioxide in this paper. The atmosphereis coupled to an ocean model with an explicit carbon cycleand biological pump [5]. Global land processes arerepresented by a linked set of biogeophysical and biogeo-chemical sub-models in a Global Land Systems framework[31]. Terrestrial water and energy balances are calculated bythe Community Land Model [2]. The Terrestrial EcosystemModel (TEM) of the Marine Biological Laboratory [6, 19]simulates ecosystem carbon CO2 fluxes and storage ofcarbon and nitrogen in vegetation and soils. A detailedcarbon uptake model for projecting carbon dioxide levels inthe future is of similar relevance as the atmosphericchemistry model in terms of methane and carbon dioxidetradeoffs. TEM differs from some ecosystem models in thatit includes the nitrogen cycle: in high CO2 scenarios thiscan lead ecosystems to become nitrogen limited, but in hightemperature scenarios soil nitrogen becomes more labile[37]. The Natural Emissions Model (NEM) described byLiu [16] and Prinn et al. [23], embedded within TEM,simulates natural fluxes of CH4 and N2O from wetlands andhigh-latitude permafrost. Three adjustable climate systemparameters are used for the sensitivity analysis in this study:ocean diffusivity, a parameterization for diffusion of heatand carbon into the deep ocean; climate sensitivity, aparameter for cloud feedback that determines the sensitivityof the model to doubling of CO2; and an aerosol forcingconstant, a measure of forcing from a given aerosol loadingcorresponding to an estimate of sulfate aerosol loading forthe 1980s.

MAGICC version 5.3 is an upwelling-diffusion energy-balance model coupled to a range of gas-cycle models forconcentration projections, described more fully in Wigley etal. [50] and has been designed to be consistent withIntergovernmental Panel on Climate Change (IPCC) FourthAssessment Report (AR4) results. MAGICC includes a

232 M.C. Sarofim

number of adjustable parameters of which three are used inthis study: a climate sensitivity constant reflecting the climateresponse to a doubling of CO2, a Boolean carbon cyclefeedback parameter, and a carbon cycle parameter which canbe set high or low that incorporates uncertainty in both CO2

fertilization and the carbon uptake rate for the ocean.

3 Scenario Descriptions

A GTPs value can be computationally calculated throughthe use of three simulations: a reference scenario, a scenarioin which CO2 is reduced by a constant quantity from thatreference scenario, and a scenario in which CH4 is alsoreduced by a constant quantity from the reference scenario.

For the MIT IGSM, three reference scenarios werechosen: a business as usual (BAU) scenario, the Level 4stabilization scenario from the U.S. Climate ChangeScience Program (CCSP) Synthesis and Assessment Prod-uct 2.1a [50] (designed to stabilize CO2 at approximately750 ppm and limit forcing from other greenhouse gases toabout 1.4 W/m2 over preindustrial levels) and the Level 2stabilization scenario from CCSP 2.1a (designed to stabilizeCO2 at approximately 550 ppm and limit forcing from othergreenhouse gases to about 1.0 W/m2 over preindustriallevels). The quantity of reductions of CH4 and CO2 fromthese reference scenarios were chosen based on a tradeoffbetween minimizing the perturbation and maximizing thesignal-to-noise ratio. Decadal means were used in order toincrease the signal-to-noise ratio, but long-term controlsimulations indicate that the variability of non-overlappingdecadal means still has a standard deviation of 0.047°C.Based on these considerations, for the methane scenarioannual reductions of 105 Tg of CH4 from each referencescenario for the years 2010 to 2100 were used. As noted byBoucher et al. [3] the oxidation of methane from fossilsources results in net addition to CO2 in the atmosphere, incontrast to biogenic methane in which the carbon in themethane derived from recent CO2 uptake. The IGSM alsodistinguished between fossil sources of methane andbiogenic agricultural sources where methane emissions arebalanced by carbon uptake at the time of release. The CH4

reductions in these scenarios were applied to fossilemissions, with the exception of the last 50 years of the550 ppm CH4 scenario in which fossil emissions werereduced to zero, and therefore, an average of 20% of thereductions came from agricultural methane emissions. Forthe CO2 scenarios, both 600 TgC and 1.8 GtC were used asreduction scenarios from each reference. These scenariosare referenced in the text by noting the reference emissionsscenario (BAU, 750, or 550), the gas being reduced (CH4

or CO2), and, in the case of CO2, the quantity of CO2 beingreduced (600 TgC or 1.8 GtC).

Each of the three different sets of emissions scenarioswas used as inputs to the earth systems model using amedian estimate of climate parameters for the IGSM:climate sensitivity of 3.12°C, diffusion of heat into thedeep ocean of 1.0 cm2/s, and an aerosol forcing parameterof −0.52 W/m2, as based on Forest et al. [8]. In order toexamine the effect of climate parameters on the GTPestimates, the Level 2 emissions scenario was used withfour additional sets of runs. These four sets of runs usedclimate parameters identical to the initial set, except thatone pair of sets used the 90% bounds of climatesensitivities from Forest et al., namely 2.02°C and 4.95°C,and the other pair of sets used the 90% bounds of oceanuptake of 0.13 and 4.08 cm2/s.

Three reference emissions scenarios were used for theMAGICC analysis: the WRE350, WRE550, and WRE750scenarios. These scenarios are designed to achieve CO2

stabilization of 350, 550, or 750 ppm respectively whenusing the default climate parameters (climate sensitivity of3.0°C, ocean diffusivity parameter of 2.3 cm2/s). Non-CO2

gas emission pathways for all three scenarios are designedto achieve the Level 2 CCSP2.1a forcing goal. BecauseMAGICC does not have internal climatic variability, it waspossible to use smaller emissions perturbations: in this case,100 TgC of CO2 and 10 Tg of CH4. Emissions reductionswere applied from 2010 to 2110. For the sensitivity analysisof MAGICC, a set of parameter values were explored: CSof 1.5°C and 6°C, carbon cycle feedback on or off, andcarbon uptake rate either high or low.

4 Characterization of Greenhouse Gas ExchangeMetrics Using two Climate Models

Previous modeling results using the MIT IGSM showedlarge temperature discrepancies between different GWPequivalent scenarios [28, 29]. The GTP-sustained (GTPs)methodology described in Shine et al. [35] is used in orderto more quantitatively analyze these discrepancies anddetermine their root causes. As discussed by Shine et al.,for time periods that are long compared to lifetimes of thegases, and in the case where a number of simplifyingassumptions are made such as constant lifetimes for gases,the analytic solution of the GTPs and the analytical solutionof the GWP both reduce to the ratio of the forcingmultiplied by the lifetime for the gas in question and thereference gas. Therefore, it is not surprising that the GWPand the GTPs are similar even for shorter lifetimes: Shine etal. derived a GTPs for methane of 24 analytically and avalue of 25 using a simple energy-balance model, comparedin their paper to the IPCC Third Assessment GWP estimateof 22. Shine et al. note that use of more complex models“would allow inclusion of different scenarios of back-

The GTP of Methane 233

ground concentration of gases, non-linear relationshipsbetween concentration and radiative forcing and even formore sophisticated treatment of the chemical processes”though they caution that these “exact” indices would beunlikely to be useful for policy purposes. In this section, weshow by use of two such more complex models that theindices derived with complex models can differ significantlyfrom both the Shine estimates and the standard GWP, wherethe magnitude of the difference depends on a number ofdifferent underlying assumptions.

In order to understand the results from the MIT IGSM, itis useful to understand the expected results; 1 Tg of CH4 isjust under 6 Tg carbon equivalent using the IPCC SARGWP of 21 (the GWP value still used in most major policyapplications). Based on the approximate equivalence of aGWP and the GTP-sustained, it would therefore beexpected that the ratio of temperature differentials after100 years from a reduction of 600 TgC of CO2 compared to105 Tg of CH4 would be about 1, and the ratio oftemperature reductions from 1.8 GtC compared to areduction of 105 Tg of CH4 would be about 3 (yielding aGTPs of 21). Table 1 shows the seven different GTPsestimates calculated using the 3 emissions scenarios and theclimate parameter sensitivity analysis based on the Level 2or 550 ppm scenario. The estimates derived from thesescenarios are all larger than the expected values. Table 2shows details useful to understand the impacts of thereduction scenarios, namely temperature changes, gasconcentrations, total natural methane emissions, and radia-tive forcings for the three reference emissions scenarios andthe CO2 and CH4 perturbations of those scenarios.

A number of factors explain the differences between theGTPs calculated by the IGSM and either the standard GWPor the Shine GTPs estimates. The largest single contributingfactor results from not assuming constant backgroundconcentrations: the forcing resulting from a marginalincrease in CO2 concentrations is not linear with thebackground concentration, being closer to a logarithmicrelationship. For the 550 ppm emissions scenarios, theforcing resulting from a 50-ppm decrease in CO2 istherefore approximately 22% less than it would have beenhad the reference scenario been a constant 379 ppm. This

result is similar to the range of 15% to 32% found byWuebbles et al. [51] when examining the sensitivity ofGWPs to radiative forcing non-linearities due to variousCO2 emission scenarios. Another factor leading to thedifference between the calculated GTP and the analyticalGTP is due to chemistry of methane: increases in methaneemissions lead to longer methane lifetimes as the methanesink (the OH radical) is consumed, and also lead to theproduction of ozone, another greenhouse gas. The IPCCuses a “perturbation lifetime” of 12 years that is meant tocapture the lifetime feedback effect, but the IGSM usesendogenous chemistry in order to calculate methaneconcentrations over time. Finally, as noted by Boucher etal. [3], including the oxidation product of methane canincrease the effective GWP by up to 10%. In the 550 ppmscenarios shown in Table 2, the 550-CH4 scenario has aCH4 concentration that is 524 ppb less than the concentra-tion in the 550-REF scenario, whereas the use of a 12-yearlifetime rather than a full chemistry model would haveresulted in a change of only 471 ppb. The methane lifetimeby the end of the century in the 550-CH4 scenario is almost9% lower than in the 550-REF scenario. The ozonedecrease resulting from the reduction of methane emissionsis 1.6 ppb, which corresponds to a 33% increase in forcingover the direct CH4 forcing, compared to a 25% adjustmentfactor used for ozone effects in the IPCC GWP calculations.In addition to direct radiative effects, the IGSM includes theimpact of ozone on ecosystems, and therefore on carbonuptake, as was shown in Felzer et al. [7]. Resulting mainlyfrom this effect, there is an additional average of 34 TgCuptake per year by the TEM ecosystem model over theperiod of the run in the 550-CH4 scenario compared withthe 550-REF scenario. Finally, the reduction in carbonemissions from methane oxidation is about 70 TgC per yearfor a 105-Tg CH4 emissions reduction.

Other explanations for the difference between theanalytical GTPs and the values calculated in this studyhave to do with timing of temperature reductions. Figure 1shows a plot of temperature change relative to the referencerun for the CH4 perturbations and the 600 TgC CO2

perturbation simulations (perturbations that would havebeen expected to be equivalent in 2100 given a GTPs of21). Methane reductions always result in more near-termtemperature reductions than equivalent CO2 reductions, andthese near-term temperature reductions will trigger anumber of positive feedbacks such as changes in naturalwetlands emissions and changes in ocean uptake due toreduced stratification. In the case of the 550-CH4 scenario,the reduction in NEM CH4 emissions compared to thereference is 300 Tg between 2010 and 2100 of which 90 Tgcomes in the first 50 years. The 550-CO2-600 TgC scenarioleads to a reduction compared to the reference of only70 Tg of natural methane emissions between 2010 and

Scenario GTPs

BAU 46

750 ppm 54

550 ppm 42

CS=4.95°C 60

CS=2.02°C 39

Kv=4.08 cm2/s 93

Kv=0.13 cm2/s 27

Table 1 GTPs derived by theMIT IGSM using emissionsreductions of either 105 Tg/yearCH4 or 1.8 GtC/year CO2 from2010–2100 compared to areference scenario

A correction term of 0.82 wasincluded to compensate for thescenario length being less than afull 100 years

234 M.C. Sarofim

2100. The 550-CO2-1.8 GtC scenario results in a reductionof 200 Tg of natural CH4, but only 10 Tg of thosereductions are in the first 50 years. CO2 reductions due toincreased ocean uptake at lower temperatures average about6 TgC per year in the 550-CH4 scenario. Both the increasedocean uptake and TEM uptake occur mainly in the firstseveral decades after the emissions change.

Total CO2 concentrations in 2100 in all the methanereductions scenarios are 4 to 5 ppm lower than in therespective reference scenarios, equivalent to almost100 ppb additional methane reductions (using the simpli-fied forcing expressions from the IPCC Third AssessmentReport), due to the combination of ozone-ecosysteminteractions, increased ocean uptake, and reduced CO2

from methane oxidation.

For the 550 ppm scenarios, the GTPs has been calculatedto be 42, or about 84% larger than the IPCC AR4 100-yearGWP estimate of 25. Summing all the effects quantified inthe previous paragraph (22% from including an increasingbackground concentration rather than a constant one, 11%from a methane lifetime which is more sensitive toemissions changes, 6% from greater ozone production bymethane than assumed by the IPCC, 3% from naturalmethane response feedbacks and 21% from increased CO2

uptake divided into 13% from including CO2 from methaneoxidation, 7% from ozone-ecosystem interactions, and 1%from ocean carbon uptake feedbacks) would account for a63% increase in GTPs, explaining much of the differencebetween the calculated GTPs and the GTPs expected basedon existing GWP calculations. An additional contributionresults from an increased transformation of SO2 into sulfatein the 550-CH4 scenario due to the increase in hydroxylradical concentrations, a mechanism recently addressed inShindell et al. [32]. Note that the GTP would be slightlylower for carbon neutral biogenic methane emissionscompared to fossil fuel methane emissions.

The climate parameter sensitivity analysis enablesinvestigation of the dependence of the GTPs on variousaspects of the climate system, taking into account theuncertainty introduced by climate noise. The results suggestthat GTP is positively correlated with climate sensitivityand ocean diffusivity. The correlation with climate sensi-tivity is likely due to the various positive feedbacks, such asnatural emissions and reductions in ocean uptake withhigher temperatures. The correlation with the ocean uptakediffusivity is likely due to a reduced lifetime of CO2

resulting from high diffusivity: in the high Kv case the 550-CO2-1.8 GtC scenario results in a change of 40 ppm CO2,compared to 50 ppm in the median Kv case and 54 ppm inthe low Kv case. This effect is slightly counterbalanced bythe lower CO2 concentration in the reference (and therefore

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2000 2020 2040 2060 2080 2100

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BAU-CO2750CO2550CO2BAU-CH4750CH4550CH4

Fig. 1 Decadal average global mean temperature change due toemissions reductions of 600 TgC of CO2 (solid lines) or 105 Tg ofCH4 (dashed lines) relative to the appropriate reference (BAUscenario—red, 750-ppm scenario—blue, 550-ppm scenario—green)

Table 2 Climatic changes due to emissions reductions of either 105 Tg/year CH4 or 1.8 GtC/year CO2 from 2010 to 2100

ΔT (°C) CO2 (ppm) CH4 (ppb) O3 (ppb) NEM CH4 Gt ΔCO2 forcing ΔCH4 forcing

550-REF 2.39 554 1,892 35.4 12.52 2.15 0.02

550-CO2-1.8 GtC 2.11 504 1,893 35.8 12.33 1.53 0.02

550-CH4 2.16 549 1,368 33.8 12.22 2.10 −0.19750-REF 3.46 706 2,285 36.2 13.07 3.81 0.16

750-CO2-1.8 GtC 3.14 654 2,289 36.6 12.90 3.27 0.16

750-CH4 3.13 702 1,731 35.0 12.87 3.76 −0.04BAU-REF 5.22 871 3,830 38.0 13.92 5.4 0.63

BAU-CO2-1.8 GtC 4.86 816 3,843 38.5 13.75 4.94 0.63

BAU-CH4 4.90 867 3,189 37.4 13.76 5.37 0.45

Average global mean temperature change is the average of 2091–2100 minus 1991–2000, average CO2, CH4, and O3 concentration reported in thedecade 2091–2100, total natural CH4 emissions from the NEM module between 2010 and 2100, and change in CO2 and CH4 forcing in W/m2

from 2010 to 2100

The GTP of Methane 235

a smaller forcing penalty). The GTP increases unevenlywith increases in emissions—most of the feedback effectsare stronger with higher emissions, but for the effect ofhigher background concentrations the change in forcingpenalty depends on how CO2 emissions increase incomparison to CH4 emissions—the large increase in theCH4 background concentration in the BAU scenariosresults in a smaller GTPs than in the 750 ppm scenarios.

The complexity that makes the IGSM model attractivefor realistic simulations makes it difficult to tease out subtleeffects and requires significant computational resources.Performing a similar analysis with the publically availableMAGICC model enables a demonstration that theseconclusions are valid for more than one model, eliminatesthe problem of internal variability, and allows moreexploration of parameters.

For the MAGICC model, the GTP was derived bymultiplying the ratio of the change in temperature of themethane perturbation scenario and CO2 perturbation sce-nario in 2100 by 36.7, where 36.7 is the number ofkilograms of CO2 reduced per kilogram of CH4 reduced.The GTPs estimates derived from the MAGICC model weresomewhat smaller than the GTP estimates from the IGSM(Table 3)—for the 550 ppm reference scenario, the GTPsresult from the model is 40.3 compared to the IGSM resultof 46—but still significantly larger than the value of 25expected from considering the IPCC AR4 GWP estimates.Of the positive feedbacks discussed for the IGSM,MAGICC does not include a natural ecosystems componentor ozone impacts on ecosystems, and the MAGICC CH4

lifetime is fairly similar to the IPCC estimate of aperturbation lifetime of 12.0 years. However, MAGICCdoes include the feedback of temperature change on thecarbon cycle and the logarithmic forcing factor. The forcingresulting from changes in ozone concentrations is 33% ofthe forcing change from methane, similar in magnitude tothe ozone effects seen in the IGSM (and also larger than theIPCC adjustment factor).

The results of the climate parameter sensitivity analysisin MAGICC are somewhat consistent with the sensitivityanalysis used for the IGSM. In MAGICC, GTPs is slightlysensitive to CS: changing the CS from 3°C to 6°C increasesthe WRE550 GTPs by 2.5. Turning the carbon cycle

feedback off reduces the central case GTPs to 38.3, andalso reduces the sensitivity to CS by two thirds. Thisdependence of sensitivity of the GTP to CS on carbon cyclefeedbacks adds support to the hypothesis that the correla-tion between GTP and CS is due in part to carbon cyclefeedbacks in these models such as reduced ocean mixingrates (and therefore carbon uptake) at high temperatures. InMAGICC Kv relates to heat uptake alone, and so does nothave the large effect seen in the IGSM—the sensitivity toKv is much smaller than the sensitivity to CS (not shown).On the other hand, with the high carbon uptake setting, theGTPs in the central case increases by 3.2: in this case, theCO2 perturbation simulation reduces the CO2 concentrationin 2110 by only 2.53 ppm rather than 2.96 ppm. Thedifferent GTPs derived from the three emission scenariosshow that the largest single factor identified in thissensitivity study is the effect resulting from the non-linearrelationship of the CO2 forcing resulting from changes inthe background concentration. However, even GTPs calcu-lations using the WRE350 scenario result in a value of31.5, which is still about 25% larger than a GWP value of25. In the WRE350 scenario, both methane and CO2

concentrations are less than current levels by 2110, and theforcing effects due to the reduced background concentra-tions of both gases nearly cancel out (calculating the neteffect shows that it should be responsible for an increase ofonly 3% to the GTP compared to a case where methane andCO2 concentrations stayed constant).

In addition to direct temperature effects, methane andCO2 emission reductions both have secondary effects notcaptured by either GTPs or GWP metrics. Methane-relatedozone levels have health effects [48] and direct agriculturalimpacts in addition to the CO2 uptake and radiative forcingeffects, and the effects of methane on the hydroxyl radicalwill alter the lifetime of a number of other atmosphericpollutants. Ancillary emissions from the fossil fuel sourcesthat produce CO2 also have health effects, and in addition,CO2 emissions have direct ocean acidification implicationsas well as direct effects on agriculture and ecosystems dueto fertilization effects.

Therefore, this work demonstrates that under mostrealistic scenarios, a GWP of 21 (or even 25 as in Shineet al. or the IPCC AR4) for methane significantly under-values methane in terms of century timescale temperaturereductions resulting from constant emissions reductions.This underestimation comes in large part from five effects:non-linear forcing from CO2 due non-constant backgroundconcentrations, including the oxidation of methane intoCO2, increased methane lifetime sensitivity to changes inmethane emissions, inclusion of ozone-ecosystem interac-tions, and higher ozone production than assumed by theIPCC. These results are sensitive to changes in climatesensitivity, carbon uptake by the oceans and ecosystems,

Table 3 GTPs derived from the MAGICC model using emissionsreductions of either 10 Tg/year CH4 or 100 TgC/year CO2 from 2010to 2110 compared to a reference scenario

CS=1.5°C CS=3.0°C CS=6.0°C

WRE350 30.8 31.5 34.5

WRE550 38.6 40.3 42.8

WRE750 42.9 44.5 46.9

236 M.C. Sarofim

and emissions scenarios. Future work might examine thesensitivity of CH4 chemistry (and therefore GTP) todifferent scenarios of NOx or CO emissions [11]. Addi-tionally, it would be valuable to propagate uncertaintiesthrough the model in a full Monte Carlo approach, andinclude additional uncertain parameters such as chemistryand ecosystem uncertainties, in order to more fully explorethe parameter space [15, 47]. Note that a complex systemsuch as the climate is not fully described by any individualmodel.

5 Policy Implications

To summarize, it has been shown using two differentmodels that the calculated GTPs for methane is significantlylarger in modeling systems which account for factors suchas changing future concentrations and complex earthsystems interactions. Because the GTPs is a parallel metricto the GWP for methane, this suggests that the GWP formethane might also undervalue methane reductions. Arecent analysis by Tanaka et al. [41] came to a similarconclusion regarding undervaluation of methane, in theircase based on evaluating what GWP choices would bestreflect historical temperature change. However, because thevalue of a metric depends on the purpose for which it isdesigned, such a conclusion of undervaluation woulddepend on the judgment of policymakers.

This paper raises a number of possible implications andoptions for greenhouse gas policies. The first option is toadjust the GWP of methane using the GTPs as calculated inthis paper. However, as Shine et al. [35] noted, it would bedifficult to come to agreement on a single value derivedfrom complex carbon cycle or chemistry models. Whichmodel should be used? What reference emissions scenarioand set of climate parameters? Alternatively, additional orupdated correction factors for the methane GWP can beimplemented that would take into account future concen-tration scenarios, larger methane lifetimes, ozone effects,and other factors identified in this study. However, a highervalue for methane would be in contrast to the arguments ofTol et al. [42] who argued that the GWP of methane isalready too high both because near-term methane reduc-tions do not contribute to the ultimate objective of Article 2of the Framework Convention on Climate Change of long-term stabilization of GHGs, and because methane abate-ment measures are often temporary whereas carbon dioxidereductions in many cases require structural changes, withthe reasoning that CO2 reductions in the near termeffectively lead to continued reductions and thereforeshould be further encouraged.

The second option is to change nothing: this might beappropriate if it was decided that the relative radiative

forcing over 100 years resulting from the pulse of emissionsof two GHGs (the GWP) is a better measure of what isimportant than the temperature change in 100 years result-ing from the sustained emissions reduction of the twoGHGs. Additionally, it is possible that the current system is“good enough” [22], or that the benefits of using a moreefficient metric may be small compared to the politicalcosts of negotiating an alternative to the present GWP [12].Transparency and ease of use have both been cited asattractions of the GWP, and even its abstract nature waslisted a possible benefit in a policy context [33].

A third option is to incorporate the scientific issuesraised in this paper into an alternative metric that betteraccounts for the impacts of both the near-term rate ofchange and the long-term magnitude of change. Examplesof such metrics might include the Manne and Richelsforward looking model system using both rate of changeand absolute temperature change constraints [17] ormodifying the Reilly and Richards economics basedapproach [25] by explicitly incorporating damage functionswhich address both rate and magnitude of change. Whileboth the Reilly and Richards and the Manne and Richelsapproaches are improvements over the GWP and GTP interms of better incorporation of climate impacts, they bothrequire increased computational complexity and additionalmodeling assumptions, exacerbating the difficulties ofagreeing on a single metric value. Additionally, some ofthe assumptions used for these approaches result in metricswhose values vary dramatically over time, which, while itmight more accurately reflect the nature of the climateproblem, may not be compatible with a political systemwhose inertia is demonstrated by the continuing use of theIPCC Second Assessment Report GWPs almost a decadeafter the Third Assessment Report published new GWPestimates.

Finally, there is a fourth option. Metrics are designed tocompare apples to apples: a decision could be made thattwo substances have sufficiently different impacts andproperties that they should not be measured with the samemetric or addressed by the same policy mechanisms. Inaddition to the lifetime issue, there is also the issue that formany sources, methane emissions are more difficult toquantify than emissions of fossil fuel CO2 [4]. While manypollutants are well suited to economic instruments such ascap and trade or tax mechanisms, there are cases whencommand and control mechanisms can be superior [45],especially in the case of poorly observed emissions [20,27]. Historical precedent offers some cause for optimism inthe case of methane control by non-market mechanisms -the United States and the European Union both instituteddomestic policies that successfully reduced methane emis-sions during the 1990s without the need for any bindinginternational commitments, mainly through reductions in

The GTP of Methane 237

emissions of coal mine methane and landfill methane [43].Meanwhile, the long-term problem of climate change is inlarge part a CO2 problem, and it would be appropriate tocreate incentives in the near term that discourage locking inCO2 intensive infrastructure. These factors have led toproposals to separate gases into long-lived and short-livedbaskets from researchers such as Daniel et al. [13] andJackson [14].

As noted in the IPCC Expert Meeting [13], the optimalchoice of a metric requires a clearly defined objective. Thispaper has demonstrated a number of reasons why the GWPmay undervalue methane reductions if the GTPs metricaccurately reflects the objectives of policymakers. Howev-er, even in the case where the GTPs is not adopted, thefactors identified in this paper such as appropriate use ofreference emissions scenarios and inclusion of more of theatmospheric chemistry of methane can be relevant for mostGHG comparison metrics, or even for determining emis-sions targets for multiple, separate GHG baskets.

Acknowledgments We thank Andrei Sokolov for the assistance inrunning model simulations during the revision process, as well as theeditors and reviewers for feedback that led to significant improve-ments in the manuscript.

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