Whitepaper on Valuing Methane Emissions Changes in 

Regulatory Benefit-Cost Analysis, Peer Review Charge 

Questions, and Responses
2

Table of Contents

Whitepaper: Valuing Methane Emissions Changes in Regulatory Benefit-Cost Analysis...............3

Peer Review Charge Questions.....................................................................................................13

Review: Karen Fisher-Vanden.......................................................................................................15

Review: John Reilly.......................................................................................................................19

Review: Steven Rose.....................................................................................................................23
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Valuing Methane Emission Changes in Regulatory Benefit-Cost Analysis

1. Introduction

While CO2 is the primary source of anthropogenic greenhouse gas (GHG) emissions contributing to climate 

change, other GHGs such as methane (CH4) are also important contributors.1 The Fifth Assessment Report 

(AR5) of the Intergovernmental Panel on Climate Change (IPCC) concluded that in 2011 the increase in 

atmospheric CO2 concentration since 1750 contributed 1.82 W m-2to global mean radiative forcing, or 

64% of the total radiative forcing from well mixed GHGs, and the direct effect of increased atmospheric

CH4 accounted for 0.48 W m-2

, or 17% of total radiative forcing from well mixed GHGs (Myhre et al. 2013).

In addition, CH4 emissions have indirect impacts on the climate due to their role as a precursor for 

tropospheric ozone and stratospheric water vapor, both of which are potent GHGs. Accounting for these 

indirect effects and the role that emissions of other substances like NOx and VOCs have on CH4

atmospheric concentrations, AR5 estimated that historical anthropogenic emissions of CH4 have 

contributed a total of 0.97 W m-2to global mean radiative forcing, or almost a third of the radiative forcing 

resulting from emissions of well mixed GHGs. Therefore, CH4 emissions are having, and will continue to 

have, a significant role on human well-being through their effect on the climate.

The United States Environmental Protection Agency (EPA) has promulgated several regulations that affect 

CH4 emissions from a variety of sources. For example, the 2012 New Source Performance Standards and 

Amendments to the National Emissions Standards for Hazardous Air Pollutants for the Oil and Natural Gas 

Industry are expected to reduce CH4 emissions by 900,000 metric tons annually.2 Additionally, the 2017-

2025 Light-duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy 

Standards, promulgated jointly with the National Highway Traffic Safety Administration, is expected to 

reduce CH4 emissions by over 100,000 metric tons in 2025 increasing to nearly 500,000 metric tons in 

2050.

3

It is likely that future EPA rulemakings will also impact CH4 emissions.

Consistent with Executive Order 12866, EPA conducts benefit-cost analysis to inform policy makers and 

the public about the economic efficiency of regulatory actions. The value of benefit-cost analysis will, in 

part, be determined by the ability to quantify and monetize the relevant outcomes of the regulatory action 

under investigation in a scientifically and economically defensible manner. EPA has promulgated 

regulations that result in changes in CH4 emissions but has not yet quantified such impacts in its main 

benefit-cost analyses. In sensitivity analyses EPA has considered the benefits of CH4 emissions reductions 

by using the global warming potential (GWP) metric to convert CH4 emissions into carbon dioxide (CO2) 

equivalents which are then valued using the U.S. Government’s (USG) social cost of carbon (SC-CO2) 

 

1

See EPA Endangerment Finding: Endangerment and Cause or Contribute Findings for Greenhouse Gases Under 

Section 202(a) of the Clean Air Act, 74 Fed. Reg. 66,496 (Dec. 15, 2009).

2 http://www.gpo.gov/fdsys/pkg/FR-2012-08-16/pdf/2012-16806.pdf

3 http://www.gpo.gov/fdsys/pkg/FR-2012-10-15/pdf/2012-21972.pdf
4

estimates.4 To date, EPA has not included these indirect CH4 benefit approximations in the main benefitcost analyses due to the well-documented caveats associated with the approach (discussed in Section 2).

While some direct estimates of CH4 emissions mitigation benefits have been presented in the scientific 

literature, EPA has not used them in benefit-cost analyses because they are inconsistent with USG

estimates of the SC-CO2 (discussed in Section 3).

5

While it is anticipated that the USG will continue to improve the models and data it uses to estimate the 

SC-CO2 in accordance with evolving scientific and economic understanding, this paper illustrates how EPA 

could apply the social cost of CH4 (SC-CH4) estimates developed in Marten et al. (2014) to improve upon 

the current treatment of methane impacts in regulatory analysis so that they need not be implicitly 

assigned a value of zero in USG policy assessment. Marten et al. provide the first set of published SC-CH4

estimates that are consistent with the modeling assumptions underlying the USG SC-CO2. This paper 

begins by describing the GWP-based approach to valuing CH4 mitigation benefits on the margin and its

limitations. This discussion is followed by a description of the direct approach to estimating the benefits 

of marginal CH4 emissions reductions, including a summary of Marten et al. and a comparison of direct 

estimates to the GWP-based approach. 

2. Global Warming Potential Approximation Approach

The global warming potential (GWP) for CH4 is a measure of the additional energy retained by the Earth’s 

atmosphere as the result of a pulse of CH4 emissions as compared to a pulse of CO2 emissions. Specifically,

the GWP is the time-integrated global mean radiative forcing from one kg of CH4 emissions compared to 

one kg of CO2 emissions over a given time horizon, such that

 

 







4

4

2

0

,

0

T

CH

CH T T

CO

Q t dt

Q t dt

GWP , (1)

where T is the time horizon and is the contribution to global mean radiative forcing at time t of a 

pulse of gas i at time zero. The time horizon is typically set to 100 years, but others have used alternative 

time horizons, such as 20 or 500 years, and the additional radiative forcing is estimated based on a 

constant background concentration for each gas.

The GWP was developed by the IPCC for their First Assessment Report (IPCC 1990) as a simple and purely

physical metric to provide information about the potential impacts of each non-CO2 GHG relative to CO2

emissions. Under the Kyoto Protocol the GWP was designated for use in translating emissions of non-CO2

GHGs into comparable CO2 equivalents when estimating GHG sources and sinks.6Similarly the United 

 

4 The USG SC-CO2 estimates are commonly referred to as the social cost of carbon but are consistent with a one 

metric ton change in CO2 emissions. 

5 Page 49536 http://www.gpo.gov/fdsys/pkg/FR-2012-08-16/pdf/2012-16806.pdf

6 Decision 2/CP.3 http://unfccc.int/resource/docs/cop3/07a01.pdf#page=31.

Qi t
5

Nations Framework Convention on Climate Change (UNFCCC) requires the use of GWPs with a time 

horizon of 100 years when calculating national GHG inventories.7

The GWPs for CH4 as estimated by the IPCC for both the Fourth Assessment Report (AR4) and AR5 are

presented in Table 1. The estimates presented in AR4 include both direct and indirect effects taking into 

account the feedback of CH4 emissions on its own lifetime and an estimated 40% increase in the radiative 

efficacy of CH4 emissions due to their role as a precursor for tropospheric ozone and stratospheric water 

vapor. The CH4 GWP estimates presented in AR5 also include the indirect effects of CH4 emissions, but the 

increase in radiative efficacy due to these effects was increased to 55% due to new findings on the role of 

CH4 in stratospheric ozone formation. A reassessment of the effect of CH4 on its own lifetime led to an 

increase in the effective perturbation lifetime from 12 years in AR4 to 12.4 years in AR5.

Table 1: Global Warming Potential for CH4

AR58

Time Horizon AR49 No CC 

Feedback

With CC 

Feedback

20 72 84 86

100 25 28 34

500 7.6 -- --

Starting in AR4 the IPCC included climate-carbon (CC) feedbacks in the estimate of the radiative forcing 

projection from the CO2 emissions pulse. This feedback accounted for the weakening of carbon sinks from 

increases in the temperature. However, these feedbacks were not accounted for when estimating the 

additional mean global radiative forcing due to a non-CO2 emissions pulse, which would also have an 

effect on temperature, and in turn carbon sinks. Therefore, in AR5 the IPCC presented estimates both with 

and without the additional radiative forcing from the CC feedback associated with non-CO2 emissions. 

Inclusion of CC feedbacks in calculating the GWP for CH4 increases the estimate from 28 to 34 for a 100 

year time horizon.

2.1 Application of GWP-Based Approach to Benefit-Cost Analysis

The SC-CO2 is an estimate of the monetized damages associated with an incremental increase in CO2

emissions in a given year. It is intended to include (but is not limited to) changes in net agricultural 

productivity, human health, property damages from increased flood risk, and the value of ecosystem 

services. As such, the SC-CO2 is an estimate of the benefits of reducing CO2 emissions at the margin. The 

USG first published SC-CO2 estimates in 2010 following an interagency process that included EPA and 

other executive branch entities. The USG used three integrated assessment models (IAM) to develop SCCO2 estimates and selected four global values for use in regulatory analyses. The USG recently updated 

these estimates using new versions of each IAM and published them in 2013. The 2013 update did not 

 

7 http://unfccc.int/ghg_data/online_help/definitions/items/3817.php

8

Source: Table 8.7 in Myhre et al. (2013).

9

Source: Table 2.14 in Forster et al. (2007).
6

revisit the 2010 modeling decisions (e.g., discount rates, reference case socioeconomic and emission 

scenarios, or equilibrium climate sensitivity). Rather, updates were confined to those IAM modifications

that were implemented by the model developers themselves and subsequently used in the peer-reviewed 

literature. The February 2010 Technical Support Document (TSD)10 provides a complete discussion of the 

methods used to develop the USG SC-CO2 estimates and the November 2013 TSD11 presents and discusses 

the updated estimates. 

The USG has not developed an estimate of the social cost of CH4 emissions for use in regulatory analysis. 

As a result benefit-cost analyses informing U.S. federal rulemakings have not fully considered the benefits 

associated with CH4 emissions mitigation. To understand the potential implication of these omissions, EPA 

has conducted sensitivity analysis in some of its regulatory analyses using the 100-year GWP to convert 

CH4 emission reductions to CO2-equivalents, which are then valued using the SC-CO2. This approach

approximates the social cost of methane (SC-CH4) using the SC-CO2 and the GWP, such that

SC-CH WP 4 G 100 2 SC-CO . (2)

2.2 Limitations of the Global Warming Potential Approach for Valuing CH4 Emissions Changes

The GWP is a simple, transparent, and well-established metric for assessing the relative impacts of nonCO2 emissions compared to CO2 on a purely physical basis. However, the GWP-based approximation of 

the SC-CH4 in (2) has several well-documented limitations (e.g., Reilly and Richards 1993; Schmalensee 

1993; Fankhauser 1994; Marten and Newbold 2012). Gas comparison metrics, such as the GWP, are 

designed to measure the impact of non-CO2 GHG emissions relative to CO2 at a specific point along the 

pathway from emissions to monetized damages (depicted in Figure 1), and this point may differ across 

measures. The GWP measures the cumulative radiative forcing from a perturbation of a non-CO2 GHG 

relative to a perturbation of CO2 over a fixed time horizon. The GWP and other gas comparison metrics

are not ideally suited for use in benefit-cost analyses to approximate the social cost of non-CO2 GHGs 

because they ignore important nonlinear relationships beyond radiative forcing in the chain between 

emissions and damages. These can become relevant because gases have different lifetimes. For example, 

the SC-CO2 takes into account the fact that marginal damages from an increase in temperature are a 

function of existing temperature levels. Another limitation of gas comparison metrics for this purpose is 

that some environmental and socioeconomic impacts are not linked to all of the gases under 

consideration and will therefore be incorrectly allocated. For example, the economic impacts associated 

with increased agricultural productivity due to higher atmospheric CO2 concentrations included in the SCCO2 would be incorrectly allocated to CH4 emissions with the GWP-based valuation approach. 

 

10 http://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf

11 http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/technical-update-social-cost-of-carbon-forregulator-impact-analysis.pdf
7

Figure 1: Path from GHG Emissions to Monetized Damages (Source: Marten et al. (2014))

Furthermore, the assumptions made in estimating the GWP are not consistent with the assumptions 

underlying SC-CO2 estimates in general, including the USG SC-CO2 estimates. For example the 100 year 

time horizon usually used in estimating the GWP is less than the 300 year horizon used in developing the 

USG SC-CO2 estimates. The GWP-approach also treats all impacts within the time horizon equally,

independent of the time at which they occur. This is inconsistent with the role of discounting in economic 

analysis, which accounts for a basic preference for earlier over later gains in utility, the small but positive 

probability of a large global catastrophe (e.g., large asteroid collision, super volcanic eruption, nuclear 

war), and expectations regarding future levels of economic growth. In the case of CH4, which has a 

relatively short lifetime compared to CO2, the temporal independence of the GWP could lead the 

approximation in (2) to underestimate the SC-CH4 with a larger downward bias under higher discount 

rates (Marten and Newbold 2012).12

3. Direct Estimation 

The SC-CH4 can be directly estimated using an integrated assessment model (IAM) similar to the way in 

which the SC-CO2 is estimated. IAMs couple simplified models of atmospheric gas cycles and climate 

systems with highly aggregated models of the global economy and human behavior to represent the 

impacts of GHG emissions on the climate and human welfare. Within IAMs, the equations that represent 

the influence of emissions on the climate are based on scientific assessments, while the equations that 

map climate impacts to human welfare are based on economic research that has studied the effects of 

climate on various market and non-market sectors. Estimating the social cost of emissions for a given GHG 

at the margin involves perturbing the emissions of that gas in a given year and forecasting the increase in 

monetized climate damages relative to the baseline. These incremental damages are then discounted 

back to the perturbation year to represent the marginal social cost of emissions of the specific GHG in that 

year.

Several researchers have directly estimated the social cost of CH4 emissions using IAMs, though the 

number of such estimates is small compared to the large number of SC-CO2 estimates available in the 

literature. Among these published direct estimates there is considerable variation in the models and input 

assumptions. These studies differ in the emission perturbation year, employ a wide range of constant and 

variable discount rate specifications, and consider a range of baseline socioeconomic and emissions 

scenarios that have been developed over the last 20 years. However, as discussed by Marten et al. (2014),

none of the other published estimates of the SC-CH4 are consistent with the USG SC-CO2 estimates, and 

most are likely underestimates due to changes in the underlying science since their publication. Therefore,

Marten et al. provide the first set of direct estimates of the SC-CH4 that are consistent with the USG SCCO2 estimates. 

 

12 We note that the truncation of the time period in the GWP calculation could lead to an overestimate of SC-CH4 

for near term perturbation years in cases where the SC-CO2 is based on a sufficiently low or steeply declining 

discount rate.
8

The estimation approach of Marten et al. (2014) used the same set of three IAMs, five socioeconomicemissions scenarios, equilibrium climate sensitivity distribution, and three constant discount rates used 

to develop the USG SC-CO2 estimates. Marten et al. also used the same aggregation method as the USG

SC-CO2 to distill the 45 distribution of the SC-CH4 produced for each emissions year into four estimates:

the mean across all models and scenarios using a 2.5%, 3%, and 5% discount rate, and the 95th percentile 

of the pooled estimates from all models and scenarios using a 3% discount rate.

The primary modeling challenge addressed by Marten et al. (2014) is that two of the three IAMs as 

implemented by the USG are not “turn-key” ready to estimate the SC-CH4 due to their lack of an 

atmospheric stock-flow model of CH4 emissions and their influence on global mean radiative forcing.

Instead, two of the three model implementations use exogenous projection of aggregate non-CO2

radiative forcing, which prevents the direct perturbation of CH4 emissions within the models. Therefore,

to estimate the SC-CH4 Marten et al. applied a simple model to estimate the path of additional radiative 

forcing from a CH4 perturbation, which is then added to the exogenous non-CO2 radiative forcing 

projection to estimate the incremental damages compared to the baseline. 

The simple model applied by Marten et al. (2014) used an exponential decay function to project

atmospheric CH4 concentrations from the CH4 emissions projections in the five socioeconomic-emissions 

scenarios. They set the average lifetime of CH4 to 12 years following the findings of the IPCC in AR4. The 

direct radiative forcing associated with the atmospheric CH4 concentration was estimated using the 

functional relationships presented in the IPCC’s Third Assessment Report and used in AR4. To account for 

the indirect effects of CH4 as a precursor for tropospheric ozone and stratospheric water vapor, Marten 

et al. followed the approach of the IPCC in AR4 of increasing the direct radiative forcing by 40%. 

The USG SC-CO2 modeling exercise assumed that overall radiative forcing from non-CO2 sources remains 

constant past 2100 without specifying the projections for individual GHGs that were implicit in that 

assumption. This broad assumption was sufficient for the purposes of the USG in estimating the SC-CO2;

however, estimating the SC-CH4 requires explicit projections of baseline CH4 emissions to determine the 

atmospheric concentration and radiative forcing off of which to compare the perturbation. Marten et al. 

(2014) chose to interpret the USG SC-CO2 assumption for non-CO2 radiative forcing past 2100 as applying 

to each gas individually, such that the emissions of each gas fall to their respective rate of atmospheric 

decay. This has the effect of holding global mean radiative forcing due to atmospheric CH4 constant past 

2100. Marten et al. showed that, due to the relatively short lifetime of CH4, alternative methods for 

extrapolating CH4 emissions past 2100 have only a negligible effect (less than 0.5%) on the SC-CH4.

The SC-CH4 estimates developed by Marten et al. (2014) are presented in Table 2 along with the USG SCCO2 estimates. For more detailed results and a comparison to other published estimates we refer the 

reader to the discussion in Marten et al.
9

Table 2: SC-CO2 and SC-CH4 Estimates [2007$ per metric ton] (Source: Marten et al. (2014))

SC-CO2 SC-CH4

Year

5.0%

Mean

3.0%

Mean

2.5%

Mean

3%

95th

5.0%

Mean

3.0%

Mean

2.5%

Mean

3%

95th

2010 11 32 51 89 370 870 1,200 2,500

2015 11 37 57 109 460 1,100 1,400 2,900

2020 12 43 64 128 550 1,200 1,600 3,200

2025 14 47 69 143 660 1,400 1,800 3,800

2030 16 52 75 159 780 1,600 2,100 4,300

2035 19 56 80 175 920 1,900 2,300 5,000

2040 21 61 86 191 1,100 2,100 2,600 5,600

2045 24 66 92 206 1,200 2,300 2,900 6,300

2050 26 71 97 220 1,400 2,500 3,100 6,900

3.1 Application of Direct Estimates to Benefit-Cost Analysis

The application of direct estimates from Marten et al. (2014) to benefit-cost analysis of a regulatory action 

is analogous to the use of the SC-CO2 estimates. Specifically, the direct estimates would be used to value 

decreases in CH4 emissions anticipated from the rulemaking. Forecast reductions in CH4 emissions in a 

given year resulting from the regulatory action are multiplied by the SC-CH4 estimate based on a 

perturbation in that year. To obtain a present value estimate, the monetized stream of future CH4 benefits 

are discounted back to the analysis year using the same discount rate used to estimate the SC-CH4.

Specifically, the present value of benefits from a regulatory action leading to reductions in CH4 emissions 

   , 0, , , tE t H

is 

4 ,  

0

SC-CH 1

H

t

t t

t

E r 



    , (3)

where r is the discount rate used to estimate the SC-CH4. The SC-CH4 estimates would be applied in the 

same way to calculate CH4 dis-benefits of a rulemaking that leads to an increase in CH4 emissions.

3.2 Comparison with the Global Warming Approach

The Marten et al. (2014) estimates are based on the conclusions presented in AR4, which was the latest 

assessment available when they conducted their modeling and analysis, and therefore GWP estimates 

based on the same assumptions would provide the most consistent comparison. As noted in Table 1, the 

AR4 100-year GWP for CH4 is 25. However, based on the direct estimates in Table 2 the social cost of CH4

emissions in 2020 are 25-46 times higher than for CO2 depending on the discount rate. For emissions in 

2050 the SC-CH4 is 31-54 times higher than the SC-CO2. Therefore the GWP-based approach to estimating 
10

the value of CH4 emissions based on the SC-CO2 will likely provide an underestimate particularly for higher 

discount rates and future emissions years in this application.

To illustrate the difference between the direct SC-CH4 and GWP-based estimates, Table 3 recalculates the 

methane co-benefits of the EPA 2017-2025 Light-duty Vehicle Greenhouse Gas Emission Standards and 

Corporate Average Fuel Economy Standards13 using both the Marten et al. (2014) SC-CH4 estimates and 

the GWP-based approach. The GWP-based approach underestimates the climate co-benefits of the 

expected methane emission reductions by 14% to 50% depending on the discount rate assumption. 

Table 3. Methane Co-benefits of 2017-2025 Light Duty Vehicle GHG Standards Using Alternative 

Valuation Methodologies [Billion 2007$]14

USG Discount rate 

assumption

Using Marten et al. 

(2014) 

SC-CH4

GWP-Based 

Approach 

(AR4 100 Year)

% Difference

5% Mean 2.5 1.2 - 50%

3% Mean 8.1 6.1 - 26%

2.5% Mean 11.6 9.7 - 16%

3% 95th percentile 21.9 18.8 - 14%

It should be noted that since the Marten et al. (2014) estimates are based on the IPCC AR4 conclusions, 

in some cases the GWP-based approach using AR5 100-year GWP estimates would yield higher benefits 

than the current Marten et al. estimates. This occurs for low discount rates and emissions years in the 

near term and is due to the higher CH4 indirect effects and climate-carbon feedbacks included in the AR5 

GWP estimates. As such, the estimates of Marten et al., by being based on AR4, may be considered 

conservative in these regards. The inclusion of new AR5 findings in the approach of Marten et al. is 

expected to increase the SC-CH4 estimates, and the relative difference between those updated estimates 

and the GWP-based approach using the AR5 100-year GWP are expected to be similar to those discussed 

above. 

4. Valuing Other Non-CO2 GHG Emissions

While this white paper focuses on methane, the valuation of other non-CO2 GHG emissions is relevant to 

EPA regulatory analyses and remains an ongoing area of research. At least one promulgated rulemaking 

to date, the 2017-2025 Light-duty Vehicle Greenhouse Gas Emission Standards, has been expected to 

reduce other non-CO2 GHG emissions, specifically N2O and HFC-134a. Marten et al. (2014) provides an 

analysis of the SC-N2O parallel to their SC-CH4 analysis. They use the same methodology described for SCCH4, replacing the simple CH4 atmospheric gas cycle model with a simple N2O atmospheric cycle, and 

found the directly modeled SC-N2O estimates generally exceed those from the GWP-based approach. 

 

13 http://www.gpo.gov/fdsys/pkg/FR-2012-10-15/pdf/2012-21972.pdf

14 NPV of climate benefits resulting from 2017-2050 CH4 emission reductions, discounted back to 2012. See RIA, 

Table 7.1-4, http://www.epa.gov/otaq/climate/documents/420r12016.pdf.
11

Their estimates of the SC-N2O are also consistent with the USG SC-CO2 estimates and therefore, could also 

be used to improve the analysis of regulatory actions projected to influence N2O emissions. 

EPA currently does not have directly modeled estimates of the social cost of F-gases, which include a wide 

variety of gases spanning a broad range of atmospheric lifetimes and climate impacts. It is difficult to 

determine how directly modeled estimates of SC-F gases would compare to estimates from the GWPbased approach, given the limited number of published estimates at the moment and diversity of gases 

in this category. 

5. Concluding Remarks

As directed by Executive Orders 12866 and 13563, EPA must use the best available scientific, technical, 

economic, and other information to quantify the costs and benefits of regulatory actions. Rigorous 

evaluation of costs and benefits has been a core tenet of the EPA rulemaking process for decades. Due to 

limitations of the GWP-based approach to value GHG emission impacts and the previous lack of peerreviewed SC-CH4 estimates consistent with the USG SC-CO2 modeling assumptions, EPA has only 

monetized the benefits of CH4 emissions mitigation in sensitivity analysis. However, Marten et al. (2014)

now provides a set of published SC-CH4 estimates consistent with the USG SC-CO2 modeling exercise. As

such, the Marten et al. estimates offer a method for improving the analyses of regulatory actions that are 

projected to influence CH4 emissions without introducing inconsistency with the manner in which other 

CO2 mitigation benefits are valued. These estimates can and should be updated if and when the modeling 

assumptions underlying the USG SC-CO2 estimates are updated to reflect the conclusions of IPCC AR5 or 

other evolving scientific and economic knowledge.

15

 

15 The Office of Management and Budget (OMB) recently provided an opportunity for public comment on the 

updated November 2013 USG SC-CO2 TSD, in addition to the public comment opportunities available through 

particular rulemakings. OMB is currently reviewing the comments received. Any revision to the underlying 

modeling assumptions will be addressed separately as the SC-CO2 estimates are updated.
12

References

Fankhauser, S., 1994. The social costs of greenhouse gas emissions: an expected value approach. The 

Energy Journal 15 (2), 157–184.

Forster, P., V. Ramaswamy, P. Artaxo, T. Berntsen, R. Betts, D.W. Fahey, J. Haywood, J. Lean, D.C. Lowe, 

G. Myhre, J. Nganga, R. Prinn, G. Raga, M. Schulz and R. Van Dorland, 2007: Changes in Atmospheric 

Constituents and in Radiative Forcing. In: Climate Change 2007: The Physical Science Basis. Contribution 

of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

[Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. 

Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 

IPCC, 1990: Climate Change: The Intergovernmental Panel on Climate Change Scientific Assessment 

[Houghton, J.T., G.J. Jenkins, and J.J. Ephraums (eds.)]. Cambridge University Press, Cambridge, United 

Kingdom and New York, NY, USA, 364 pp.

Marten, A.L., Newbold, S.C., 2012. Estimating the social cost of non-CO2 GHG emissions: methane and 

nitrous oxide. Energy Policy 51, 957-972

Marten, A.L., Kopits, E.A., Griffiths, C.W., Newbold, S.C., Wolverton, A. 2014. Incremental CH4 and N2O 

Mitigation Benefits Consistent with the U.S. Government’s SC-CO2 Estimates. Climate Policy. Published 

online: 20 May 2014.

Myhre, G., D. Shindell, F.-M. Bréon, W. Collins, J. Fuglestvedt, J. Huang, D. Koch, J.-F. Lamarque, D. Lee, 

B. Mendoza, T. Nakajima, A. Robock, G. Stephens, T. Takemura and H. Zhang. 2013: Anthropogenic and 

Natural Radiative Forcing. In: Climate Change 2013: The Physical Science Basis. Contribution of Working 

Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T. F., 

D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P. M. Midgley 

(eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Reilly, J., Richards, K., 1993. Climate change damage and the trace gas index issue. Environmental and 

Resource Economics 3 (1), 41–61.

Schmalensee, R., 1993. Comparing Greenhouse gases for policy purposes. The Energy Journal 14 (1), 

245–256.
13

Document Title: Valuing Methane Emission Changes in Regulatory Benefit-Cost Analysis

Approximate Length: 10 pages 

Supporting Materials: Marten et al. (2014) (36 pages excluding Appendices)

Abstract and Charge Questions:

Consistent with Executive Order 12866, EPA conducts benefit-cost analysis to inform policy makers and 

the public about the potential economic implications of regulatory actions. EPA has promulgated 

regulations that result in changes in CH4 emissions but has not yet quantified such impacts in its main 

benefit-cost analyses. Direct estimates of the benefits of mitigating CH4 emissions have been presented 

in the scientific literature, but EPA has not used these estimates in benefit-cost analyses because they are 

inconsistent with U.S. Government (USG) estimates of the social cost of carbon dioxide (SC-CO2).16 A

recently published paper (Marten et al. 2014) presents estimates of the social cost of CH4 (SC-CH4) that 

are consistent with USG estimates of the SC-CO2. While it is anticipated that the USG will continue to 

improve the models and data it uses to estimate the SC-CO2 in accordance with evolving scientific and 

economic understanding, the enclosed paper illustrates how EPA could apply the SC-CH4 estimates from

Marten et al. to improve upon the current treatment of methane impacts in regulatory impact analysis 

(RIA) so that they need not be implicitly assigned a value of zero in policy assessment. Consistent with 

EPA’s peer review guidance, the Agency is seeking review of the application of these new benefit 

estimates to regulatory analysis before using them in an RIA. Specifically we seek guidance on the 

following questions:

1. Has EPA correctly interpreted the SC-CH4 estimates provided in Marten et al. (2014) as designed 

to measure the monetized value of the climate impacts from marginal changes in CH4 emissions 

in a way that is appropriate for use in benefit-cost analysis of regulatory actions projected to 

change CH4 emissions?

2. Do you agree that the Marten et al. SC-CH4 estimates are consistent with the USG SC-CO2

estimates?

3. Do you agree with EPA’s characterization of the limitations of using the global warming potential 

(GWP) to approximate the SC-CH4 (and other non-CO2 GHGs)?

4. Do you agree with EPA’s assessment that direct estimates of the SC-CH4, as developed by Marten 

et al., are more appropriate for monetizing changes in CH4 emissions than using the GWP to scale 

the USG SC-CO2?

 

16 See the February 2010 Technical Support Document (TSD) and November 2013 TSD Update for a complete 

discussion of the methods used to develop the USG SC-CO2 estimates: 

http://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf, 

http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/technical-update-social-cost-of-carbon-forregulator-impact-analysis.pdf.
14

5. Are there other existing approaches for monetizing the benefits (or dis-benefits) to society from 

reductions (increases) in CH4 emissions that should be considered in regulatory analysis?

6. Although the focus of this review is on the application of estimates of the social cost of CH4 to 

benefit-cost analysis for regulations, do your answers for the questions above hold for the

application of the social cost of N2O estimates provided in Marten et al.? 

7. Are there implementation issues not addressed in the paper that EPA should consider before 

applying the Marten et al. estimates in regulatory analysis?
1

Document Title: Valuing Methane Emission Changes in Regulatory Benefit-Cost Analysis

Approximate Length: 10 pages 

Supporting Materials: Marten et al. (2014) (36 pages excluding Appendices)

Abstract and Charge Questions:

Consistent with Executive Order 12866, EPA conducts benefit-cost analysis to inform policy 

makers and the public about the potential economic implications of regulatory actions. EPA has 

promulgated regulations that result in changes in CH4 emissions but has not yet quantified such 

impacts in its main benefit-cost analyses. Direct estimates of the benefits of mitigating CH4

emissions have been presented in the scientific literature, but EPA has not used these estimates

in benefit-cost analyses because they are inconsistent with U.S. Government (USG) estimates of 

the social cost of carbon dioxide (SC-CO2).1A recently published paper (Marten et al. 2014) 

presents estimates of the social cost of CH4 (SC-CH4) that are consistent with USG estimates of 

the SC-CO2. While it is anticipated that the USG will continue to improve the models and data it 

uses to estimate the SC-CO2 in accordance with evolving scientific and economic understanding, 

the enclosed paper illustrates how EPA could apply the SC-CH4 estimates from Marten et al. to 

improve upon the current treatment of methane impacts in regulatory impact analysis (RIA) so 

that they need not be implicitly assigned a value of zero in policy assessment. Consistent with 

EPA’s peer review guidance, the Agency is seeking review of the application of these new 

benefit estimates to regulatory analysis before using them in an RIA. Specifically we seek 

guidance on the following questions:

1. Has EPA correctly interpreted the SC-CH4 estimates provided in Marten et al. (2014) as 

designed to measure the monetized value of the climate impacts from marginal changes 

in CH4 emissions in a way that is appropriate for use in benefit-cost analysis of 

regulatory actions projected to change CH4 emissions?

I have read both Marten et al. (2014) and the review document and feel that the review 

document provides an accurate summary of the issues and methodologies discussed in 

Marten et al. (2014). I feel that Table 3 of the review document provides a nice example 

of how the SC-CH4 estimates from Marten et al. (2014) could be used in BCAs of 

proposed regulations and underscores the bias that arises if a GWP-based approach is 

used rather than the direct approach proposed by Marten et al. (2014).

There, of course, is a whole host of issues that arise when applying any social cost 

measure to regulatory analyses, which have been extensively discussed in the literature 

 

1

See the February 2010 Technical Support Document (TSD) and November 2013 TSD Update for a complete 

discussion of the methods used to develop the USG SC-CO2 estimates: 

http://www.whitehouse.gov/sites/default/files/omb/inforeg/for-agencies/Social-Cost-of-Carbon-for-RIA.pdf, 

http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/technical-update-social-cost-of-carbon-forregulator-impact-analysis.pdf.
2

and which I expand on in my responses below. A key issue that I would like to raise here 

is that these measures are only appropriate for marginal changes in CH4. These 

measures are not designed to be used to evaluate non-marginal changes in methane 

emissions (or any other gas, for that matter). Therefore, caution must be used when 

applying social cost measures like this.

2. Do you agree that the Marten et al. SC-CH4 estimates are consistent with the USG SCCO2 estimates?

“Consistent” can have many interpretations. I will say that the Marten et al. SC-CH4

estimates are computed in a similar way as the SC-CO2 estimates, so in this regard, the 

two estimates are “consistent.” However, CO2 is more explicitly modeled in the three 

models than CH4 so in this regard they are not “consistent.” However, this inconsistency 

is due to limitations of the models and I feel that Marten et al. have taken appropriate 

steps to address these limitations the best way possible. However, gaps still remain and 

should be recognized.

3. Do you agree with EPA’s characterization of the limitations of using the global warming 

potential (GWP) to approximate the SC-CH4 (and other non-CO2 GHGs)?

The review document (and Marten et al) discusses a number of problems that arise when 

GWP is used to approximate SC-CH4: (1) in the introduction and in section 2, the authors 

point out that the indirect effects of CH4, as a precursor to tropospheric ozone and 

stratospheric water vapor, can amplify radiative forcing significantly (which would not 

be captured in the GWP); (2) GWP ignores important nonlinear relationships beyond 

radiative forcing in the chain between emissions and damages—e.g., increased 

agricultural productivity due to CO2 fertilization would be incorrectly attributed to CH4 if 

the GWP was used; (3) GWP does not account for differences in time horizons between 

gases—e.g., since CH4 has a shorter lifetime than CO2, the GWP approach would 

underestimate the SC-CH4.

Although all three are technically correct, I feel that (1) and (2) could be addressed to a 

certain extent (although not perfectly) by adjusting the GWP to account for these biases. 

However, the temporal issue raised in (3) seems more difficult to address through simple 

adjustments to the GWP. 

In sum, I agree with the authors that problems exist and that the direct approach in 

theory is the best way to avoid these issues.

4. Do you agree with EPA’s assessment that direct estimates of the SC-CH4, as developed 

by Marten et al., are more appropriate for monetizing changes in CH4 emissions than 

using the GWP to scale the USG SC-CO2?
3

As discussed in my response to question 3 above, I agree that the direct approach is 

likely a superior approach to the indirect GWP approach. However, it should be noted 

that the direct approach has issues as well. Namely, as discussed in section 3, most 

models do not include an atmospheric stock-flow model of CH4; thus, the authors were 

forced to develop a separate model to project the path of radiative forcing from a CH4

perturbation, and then incorporate this path into the IAM exogenously. As a result, 

indirect or feedback effects are missed. For instance, climate change impacts on 

agriculture will affect methane emissions.

In sum, no approach is perfect but in my opinion, the “direct” approach used by Marten 

et al is preferred to the indirect GWP approach for the reasons outlined in the review 

document. However, the EPA should continue to seek improvements to the direct 

approach put forth by Marten et al.

5. Are there other existing approaches for monetizing the benefits (or dis-benefits) to 

society from reductions (increases) in CH4 emissions that should be considered in 

regulatory analysis?

My complaint with past SC measures is the use of highly aggregated and stylized models 

to monetize the benefits of reductions. By using models that represent the global 

economy as one aggregate sector, we are missing important subsector interactions and 

distributional effects that can only be captured with a more disaggregated model, such 

as a computable general equilibrium model. My sense would be that these SC would be 

much higher if a more disaggregated model was used. Modeling the economy as one 

monolithic sector implies, for instance, perfect substitutability across subsectors which 

will underestimate the cost of damages. It also assumes perfect trade which can also 

underestimate the cost of damages. (See Chapter 6 of the IPCC WGIII Fifth Assessment 

Report which highlights some of these biases that arise with alternative model 

characteristics).

The use of these simplified models for SC estimates, I believe, is a large source of the 

criticisms we’ve seen with respect to the SCC reports. The use of more sophisticated 

economic models (like those used in the IPCC) is needed, in my opinion. 

6. Although the focus of this review is on the application of estimates of the social cost of 

CH4 to benefit-cost analysis for regulations, do your answers for the questions above 

hold for the application of the social cost of N2O estimates provided in Marten et al.? 

Yes.

7. Are there implementation issues not addressed in the paper that EPA should consider 

before applying the Marten et al. estimates in regulatory analysis?
4

I am not sure I would characterize these as “implementation” issues, but I do want to 

take this opportunity to stress the importance of being forthcoming with the 

shortcomings of these SC estimates. These shortcoming are not specific to any gas. 

(1) As discussed in my response to question 1, these estimates are not appropriate for 

evaluating large (non-marginal) changes in emissions of any of these gases.

(2) As discussed in my response to question 5, the SC values will be underestimated due 

to the use of highly aggregated models.

(3) These estimates do not take into account extreme or threshold events, which could 

amplify the estimates significantly.

(4) These estimates will be biased downward due to the omissions of nonmarket values 

and omitted impacts, and will be biased upward due to the lack of adaptation 

responses (although FUND does account for some of this).
John Reilly, MIT December 28, 2014

This report is a response to a request from Katherine Kiel (Dec. 10, 2014) to review 

a draft EPA (no date) paper, “Valuing Methane Emission Changes in Regulatory 

Benefit-Cost Analysis.” As part of the request I was provided with the 7 charge 

questions repeated below in italics, the EPA paper, and the paper: Alex L. Marten, 

Elizabeth A. Kopits, Charles W. Griffiths, Stephen C. Newbold, and Ann Wolverton, 

2014 (on line) Incremental C4H and N2O mitigation benefits consistent with the US 

Government's SC-CO2 Estimates, Climate Policy, which forms the basis for estimates 

provided in the draft EPA paper.

The basic objective of the EPA paper was to outline a process for establishing a 

social cost of methane (and possibly N2O) that is consistent with the established 

basis for estimating a social cost of carbon previously developed by EPA.

1. Has EPA correctly interpreted the SC-CH4 estimates provided in Marten et al. 

(2014) as designed to measure the monetized value of the climate impacts from 

marginal changes in CH4 emissions in a way that is appropriate for use in 

benefit-cost analysis of regulatory actions projected to change CH4 emissions?

The Marten et al. (2014) paper follows closely the original social cost of 

carbon approach developed by the EPA, using the same 3 IA models, 

expanding them to include methane and nitrous oxide. EPA’s interpretation 

of the paper appears to be correct. The main addition was an explicit 

treatment of the lifetime of methane (and nitrous oxide). The formulation 

used is obviously a simplification of complex atmospheric chemistry but has 

been used in earlier publications and likely approximates a more complex 

representation. The ad hoc increase in radiative forcing to account for 

indirect effects is another simplification, and obviously has substantial 

impacts on the estimates. It is justified by the IPCC indirect estimates. It is 

not clear that the method includes the fact that abiogenic methane decays 

into CO2 and hence may represent an additional impact of methane release. 

(Biogenic methane also decays into CO2 but if that methane is derived from 

plant material that regrows it would then not represent an addition of CO2 to 

the atmosphere.)

2. Do you agree that the Marten et al. SC-CH4 estimates are consistent with the 

USG SC-CO2 estimates?

While there is considerable controversy about how to estimate a Social Cost 

of Carbon from a theoretical standpoint as well as the empirical foundation 

for such an estimate, the method put forward by Marten et al. (2014) is 

theoretically and empirically consistent with the original Social Cost of 

Carbon estimates developed by EPA. 
John Reilly, MIT December 28, 2014

3. Do you agree with EPA’s characterization of the limitations of using the global 

warming potential (GWP) to approximate the SC-CH4 (and other non-CO2

GHGs)?

I agree that using GWP’s to scale the social cost of carbon would be 

theoretically inconsistent. As the EPA (no date) paper discusses, the Social 

Cost of Carbon method appropriately uses a discount rate to weight damages 

at different points in time, whereas the GWP approach stops at radiative 

forcing and then uses an arbitrary time horizon to truncate the effects, 

weighting effects in each year equally. This leads to the controversy about 

which GWP time horizon to use. Of course this controversy is not completely 

avoided as it resurfaces as a controversy about the appropriate discount rate. 

It appears to turn out that given the time path of damages the 100-year GWP 

of methane is very similar to the Social Cost of Methane relative to the Social 

Cost of Carbon as estimated in the Marten et al (2014) paper. (This was a 

conclusion Reilly and Richards (1993) reached.) With a very different path of 

damages this result may not hold. For that reason as EPA imagines updating 

these estimates, and for theoretical consistency, using the Marten et al. 

(2014) method for arriving at a Social Cost of methane (or nitrous oxide) 

appears much more defensible.

While it does not affect the basic conclusions, I have some issues with the 

paragraph in EPA (no date) repeated below in italics, especially the sentences 

highlighted here in bold.

Furthermore, the assumptions made in estimating the GWP are not 

consistent with the assumptions underlying SC-CO2 estimates in general, 

including the USG SC-CO2 estimates. For example the 100 year time 

horizon usually used in estimating the GWP is less than the 300 

year horizon used in developing the USG SC-CO2 estimates. The 

GWP-approach also treats all impacts within the time horizon equally, 

independent of the time at which they occur. This is inconsistent with 

the role of discounting in economic analysis, which accounts for a 

basic preference for earlier over later gains in utility, the small but 

positive probability of a large global catastrophe (e.g., large 

asteroid collision, super volcanic eruption, nuclear war), and 

expectations regarding future levels of economic growth. In the 

case of CH4, which has a relatively short lifetime compared to CO2, the 

temporal independence of the GWP could lead the approximation in 

(2) to underestimate the SC-CH4 with a larger downward bias 

under higher discount rates (Marten and Newbold 2012).1 

 

1 We note that the truncation of the time period in the GWP calculation could lead to an overestimate 

of SC-CH4 for near term perturbation years in cases where the SC-CO2 is based on a sufficiently low 

or steeply declining discount rate.
John Reilly, MIT December 28, 2014

Regarding the inconsistency of the 100- and 300-year horizons: Yes, I 

suppose this is true but there really is no direct comparison. In the economic 

analysis one hopefully has a far enough time horizon so that with discounting 

it is irrelevant. In some sense choice of discount rate is a substitute for the 

choice of time horizon—the higher the discount rate the shorter the time 

horizon. In a final version of this paper I might rephrase this as something 

like. In the USG SC-CO2 estimates a 300-year time horizon was used, long 

enough to minimize its effects on estimates given the discount rates used. In 

contrast the GWP approach is to truncate estimates at different time horizons (20-

, 100-, 500-years), treating all impacts within the time horizon equally, 

independent of the time at which they occur. I think this gets across the point you 

want to make without directly suggesting that the 100-year and 300-year horizons 

are inconsistent (when in fact that is not even comparable.)

Then the second emboldened sentence raising a huge set of issues and 

controversies. I think the sentence would be best deleted. The discount rate 

should not theoretically include the risk of catastrophe. Risks should be 

separately evaluated with a risk-free discount rate to arrive at an “expected” social 

cost of carbon, perhaps with a utility function that more heavily weights bad 

outcomes. While an observed rate of return can include a risk premium based on 

a specific assessment of the risk (and time profile of the risk) it is inappropriate to 

apply a risk premium to a discount rate and then apply that risk-adjusted rate to 

many different investment profiles. Here, different characterizations of when 

catastrophes may occur. Embedding risk into the discount rate in this manner is 

little different than using GWP’s with truncated time horizons to implicitly give 

different weights (1 or 0) to damages occurring at different times. And while in a 

Ramsey model the discount rate is approximately the sum of the pure rate of time 

preference plus the growth rate that again is calculation under certainty so using 

“expected growth” is inconsistent. Then you have the Weitzman argument that 

with uncertainty in the appropriate discount rate, one should use a declining rate. 

And bringing up things like asteroid collisions and such just seems distracting 

here.

Finally, I guess the last emboldened statement is true but it took me a long time to 

figure it out. A higher discount rate, as compared to a lower rate, will lead to a 

lower social cost of carbon (or methane). So concluding that it will underestimate 

the Social Cost of Methane seemed initially backward. Further a higher discount 

rate, while lowering the social cost of both gases, will tend to raise the Social Cost 

of Methane relative to that of carbon. But I guess if I fully parse this sentence, 

you are saying that taking a specific GWP-horizon (e.g 100 years) and deriving a 

SC of methane by applying it to your existing SC of carbon, then if you were to 

do this the right way with a high discount rate—that SC of methane would be 

higher then that derived using the shorthand method. Maybe there is a clearer 

way to say this...but then I’m not sure why this is important. There seems to be a 

concern about underestimating the methane value. You could just as easily say, 
John Reilly, MIT December 28, 2014

that methane would be overvalued for low discount rates. I’d think you just want 

the CS of carbon and methane to be consistent and unbiased in either direction.

4. Do you agree with EPA’s assessment that direct estimates of the SC-CH4, as 

developed by Marten et al., are more appropriate for monetizing changes in 

CH4 emissions than using the GWP to scale the USG SC-CO2?

Yes, see above.

5. Are there other existing approaches for monetizing the benefits (or disbenefits) to society from reductions (increases) in CH4 emissions that should be 

considered in regulatory analysis?

Not of which I am aware. As the Reilly and Richards (1993) paper referred to 

in the Marten et al. (2014) paper the multiple impacts of these different 

gases, beyond climate change, could in principle be incorporated into the 

analysis but that raises further complications. E.g. CO2 has some benefit to 

crop growth (disputed) but ozone (of which methane is a precursor) has not 

only climate implications but also damages to crops and health. However, 

with all the recognized limitations to the empirical foundation for the SC 

estimates, the chosen approach is theoretically sound.

6. Although the focus of this review is on the application of estimates of the social 

cost of CH4 to benefit-cost analysis for regulations, do your answers for the 

questions above hold for the application of the social cost of N2O estimates 

provided in Marten et al.? 

Yes, the method is equally applicable to N2O.

7. Are there implementation issues not addressed in the paper that EPA should 

consider before applying the Marten et al. estimates in regulatory analysis?

As the paper itself points out, the current approach of using a social cost of 0 

is clearly not right and so whatever the limitations of existing methods its 

seems better to use something rather than nothing. Of course one could use 

a value that is so high that zero would be preferable, but I don’t see that error 

here. More to the point: Accepting the Social Cost of Carbon estimates, this 

approach consistently applies the concept to methane (and potentially other 

GHGs).

John Reilly

MIT
Peer Review of EPA Proposed Methodology “Valuing Methane Emission Changes in Regulatory 

Benefit-Cost Analysis”

Steven Rose, Ph.D., Energy and Environmental Analysis Research Group, EPRI

January 15, 2015

This is an extremely challenging research area due to the breadth of physical and social sciences 

represented and the vast uncertainty inherent in modeling global biophysical and economic systems for 

centuries to come. EPA should be commended for seeking peer review feedback. Peer review is 

important for producing scientifically defensible results and instilling public confidence. However, given 

the regulatory importance of the social cost of greenhouse gas estimates, a different peer review 

process should be pursued going forward that will increase public confidence in the ultimate outcome

(see suggestion at the end of my comments). 

For this review activity, EPA requested peer review feedback on seven charge questions. Below I have 

responded to each. Overall, I am concerned about moving forward with direct non-CO2 social cost 

estimates based on the USG SC-CO2 methodology before having a peer reviewed SC-CO2 methodology.

Responses to EPA Charge Questions

1. Has EPA correctly interpreted the SC-CH4 estimates provided in Marten et al. (2014) as designed 

to measure the monetized value of the climate impacts from marginal changes in CH4 emissions 

in a way that is appropriate for use in benefit-cost analysis of regulatory actions projected to 

change CH4 emissions?

Yes, the Marten et al. SC-CH4 estimates are derived with marginal global methane pulses and as 

such would be conceptually appropriate for valuing incremental changes in global methane 

emissions such as those likely to result from U.S. regulatory actions. However, as discussed 

below, there are computational issues with the specific Marten et al. SC-CH4 estimates that 

need to be considered; and, implementation issues associated with using the SC-CH4 estimates 

to value regulatory action methane changes.

2. Do you agree that the Marten et al. SC-CH4 estimates are consistent with the USG SC-CO2

estimates?

The Marten et al. estimates are mostly consistent with the USG SC-CO2 estimates. They are 

consistent in a variety of ways with the USG SC-CO2 estimates due to the common experimental 

design (e.g., same three integrated assessment (IA) models, uncertainty specification, scenario 

runs, and results aggregation procedure). However, they do not appear to be entirely 

consistent, and the implications are not clear to me. For instance, the simple model used to 

compute CH4 concentrations and radiative forcing is different from the modeling used to 

construct non-CO2 forcing for the PAGE and DICE model’s USG SC-CO2 reference and pulse 

scenarios. It is not clear to me whether this is a big deal. One would want to compare reference 

and incremental perturbation responses for all the EMF-22 emissions scenarios. Marten et al. 

makes some comparison to MAGICC 5.3, but doesn’t comment on reference scenario 

differences (that could impact SC-CO2 estimates) or on the differences for higher and lower 
emissions scenarios. Another inconsistency is the implementation of the CH4 and CO2

perturbations. The CO2 perturbations in the USG SC-CO2 calculations vary by model, differing in 

temporal implementation and magnitude (see Section 5 in Understanding the Social Cost of 

Carbon: A Technical Assessment, http://epri.co/3002004657). In DICE, a 1 GtC shock was added 

over the decade which straddles year t, in FUND, a 1 million metric ton carbon (1 MtC) shock 

was added to every year within a decade from year t forward, and in PAGE, 100 billion metric 

tons of CO2 (100 GtCO2, 27 GtC) was distributed evenly over the decades preceding and 

subsequent to year t.

1

In Marten et al. however, the CH4 perturbation was a 1 MtCH4 pulse in a 

single year t.

More importantly, while consistency is the driving motivation for the Marten et al. paper, it 

creates a serious problem. The Marten et al. SC-CH4 estimates inherit all the issues associated 

with the USG SC-CO2 estimates. Overall, consistency with the USG SC-CO2 methodology is a 

scientifically pragmatic and laudable objective for SC-CH4 calculations. However, it requires that 

the SC-CO2 methodology be scientifically sound. However, the USG SC-CO2 methodology, and 

the IA models themselves, have not undergone peer review; and, a number of fundamental 

issues have been identified that could merit and motivate revisions to the USG SC-CO2

methodology (and resulting SC-CO2 & SC-CH4 estimates). Scientifically, it would be inappropriate 

at this stage to propagate issues with the SC-CO2 methodology by moving forward with the 

proposed Marten et al. (2014) SC-CH4 (and SC-N2O) estimates. Unfortunately, consistency alone 

is not adequate justification for using the Marten et al. estimates. A peer reviewed SC-CO2

methodology is needed before creating consistent SC-X estimates for non-CO2 gases. See reply 

below to Charge Question #4 for some of the important issues that need to be considered.

3. Do you agree with EPA’s characterization of the limitations of using the global warming potential 

(GWP) to approximate the SC-CH4 (and other non-CO2 GHGs)?

Yes, conceptually, I agree with the limitations noted. However, practically, there are 

methodological issues that should be re-considered, and potentially revised, before one can 

legitimately begin to claim that the SC-CH4 estimates are improvements over GWP application. 

See reply to Charge Question 4. 

4. Do you agree with EPA’s assessment that direct estimates of the SC-CH4, as developed by Marten 

et al., are more appropriate for monetizing changes in CH4 emissions than using the GWP to 

scale the USG SC-CO2? 

Conceptually, direct estimates of SC-CH4 are more appropriate than using GWPs to value CH4

emissions changes associated with US regulatory actions. Practically, however, is another issue. 

It depends on the scientific soundness of the SC-CH4 estimation methodology. Unfortunately, 

the current USG SC-CO2 methodology, and therefore the proposed SC-CH4 methodology, has not 

been peer reviewed to establish scientific soundness, and as noted, fundamental issues with the 

current methodology have been identified. For instance, we recently completed and published a 

very extensive technical assessment of the USG SC-CO2 modeling that coded up individual 

 

1

Note that with PAGE, the emissions pulse is initially introduced as a uniform increase in average annual CO2

emissions over the given period associated with year t. However, within PAGE’s climate model, emissions for years 

t-1 and t are averaged. Thus, the emissions pulse enters PAGE’s carbon cycle as uniform (but half-sized) increases 

in average annual emissions in both the decades preceding and following year t.
components of the models and ran diagnostic scenarios (Understanding the Social Cost of 

Carbon: A Technical Assessment, http://epri.co/3002004657). From the analyses, we identified a 

number of fundamental issues with the USG SC-CO2 approach that should be considered:

a. Significant structural & response differences across models that need to be evaluated to 

determine whether they are providing useful information or are differences to reconcile or 

address explicitly as an uncertainty. For instance, the models do not consider the same sets 

of emissions and radiative forcing categories—the drivers for projected temperature. The 

models also have stark differences in key pieces of the climate modeling (e.g., the carbon 

cycle, climate sensitivity, climate feedbacks, and projected climate change uncertainty), with 

some elements excluded entirely from some models. Furthermore, unique model specific 

factors dominate results in the damage components and therefore raise questions about 

their representation within each model and across models—e.g., agricultural CO2

fertilization, cooling energy demand, global damages dominated by China, regional scaling 

of damages, rapidly growing global non-economic damages, potential discontinuity 

damages, and damages that increase quadratically with temperature. Finally, the study also 

finds dramatic differences in estimated damages across models for comparable regions and 

sectors that are not explored or explained.

b. Reasonable alternative specifications, additional uncertainties, and some variation that is 

artificial due to, for instance, difference in model implementation. Together, these findings 

suggest the need to revisit the representation of uncertainty in the experimental design. 

c. Inconsistencies across modeling, as well as inter-model dependency, that raises an issue 

about the statistical comparability of results produced by the three different models. 

Statistical comparability and independence is required for USG SC-CO2 approach which 

combines 150,000 results from the three IA models into a distribution in order to derive a 

single USG SC-CO2 for a given year and discount rate.

d. The current USG SC-CO2 estimates may not be robust (i.e., insensitive to alternative 

assumptions) given that (i) the study finds the underlying climate and damage results from 

the models (e.g., concentrations, radiative forcing, temperature, and sector and regional 

specific damages over time) to be very sensitive to alternative assumptions, and (ii) the 

study finds reasonable alternatives to the assumptions and modeling used in the USG SCCO2 experiment. 

e. Issues with the overall experimental design, in particular the use of multiple models, which 

creates the consistency and comparability challenges and issues noted previously.

Based on these findings, the study makes a number of recommendations that could help 

increase scientific and public confidence in the SC-CO2 results: 

a. Internally review the modeling to evaluate differences, improve comparability and 

uncertainty representation, and enhance robustness.

b. Revisit the experimental design, especially given the challenges with the multi-model 

approach.
c. Evaluate robustness to reasonable alternative assumptions and modeling to insure that the 

results are stable. 

d. Peer review the approach and the models used. The USG SC-CO2 approach is novel and peer 

review would be valuable and practical. Model review would also be practical given the 

regulatory use of the models.

e. Additional documentation and justification for methodological choices to facilitate 

communications & interpretation, and increase public confidence.

f. Application guidance to insure proper application of USG SC-CO2 estimates.

Other researchers, of course, have also identified issues with the current USG SC-CO2 approach. 

Marten et al. cite a number of studies (Arrow et al., 2013; Kopp & Mignone 2012; Marten, 2011; 

O’Neil, 2010; Warren, Mastrandrea, Hope, & Hof, 2010). And recently, the scientific community 

has called for a more scientific process with greater scientific community engagement and 

formal peer review (Pizer et al., 2015).

5. Are there other existing approaches for monetizing the benefits (or dis-benefits) to society from 

reductions (increases) in CH4 emissions that should be considered in regulatory analysis?

Global temperature potentials could be considered, but they would have similar time period 

issues as GWPs.

6. Although the focus of this review is on the application of estimates of the social cost of CH4 to 

benefit-cost analysis for regulations, do your answers for the questions above hold for the 

application of the social cost of N2O estimates provided in Marten et al.? 

Yes, I have similar concerns about the Marten et al. SC-N2O estimates and would be reluctant to 

move forward with the Marten et al. SC-N2O and SC-CH4 estimates.

7. Are there implementation issues not addressed in the paper that EPA should consider before 

applying the Marten et al. estimates in regulatory analysis?

Yes, in addition to the issues raised in my comments above regarding the Marten et al. SC-CH4

(and SC-N2O) estimates, there are a few issues regarding use of SC-CH4 and SC-N2O values. First, 

in regulatory applications, it will be essential to estimate net global changes in emissions due to 

proposed rules in order to appropriately utilize SC-CH4 and SC-N2O estimates, which reflect the 

marginal value of net global changes in methane and nitrous oxide respectively. Second, it will 

be important to think about consistency in the underlying assumptions in benefit and cost 

calculations, e.g., those used for computing social costs of GHGs, GHG emissions reductions, and 

compliance costs. Third, current USG guidance to use all SC-CO2 estimates will presumably be 

the same for SC-CH4 and SC-N2O estimates. As such, the guidance needs to be expanded to 

provide direction on how agencies should use the multiple resulting CO2 (CH4, or N2O) benefit 

estimates in benefit-cost analyses and regulation proposal decisions.

Additional comment
Given the regulatory importance of the social cost of greenhouse gas estimates, a more extensive and

public peer review process should be pursued going forward that will give the public greater confidence 

in the ultimate values. Specifically, peer review of the USG SC-CO2 methodology (and the subsequent 

non-CO2 social cost methodologies) should be a public process with a scientific review panel (created 

through a public selection process) that produces a single report reflecting the panel’s critique and 

recommendations. This sort of review process is typical for important regulatory metrics and 

methodologies, and a key function of groups like EPA’s Science Advisory Board. The peer review I’m

participating in here is a useful means of soliciting scientific feedback, but not a substitute for the review 

process needed (and described above).

References

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benefits and costs for future generations. Science, 341, 349–350.

Kopp, R. E., B.K. Mignone (2012). The U.S. government’s social cost of carbon estimates after their first 

two years: Pathways for improvement. Economics, 6(15), 1–41.

Marten, A. L. (2011). Transient temperature response modeling in IAMs: The effects of over 

simplification on the SCC. Economics, 5, 2011–2018.

O’Neill, B. (2010). Multi-century scenario development and socioeconomic uncertainty. In Improving the 

assessment and valuation of climate change impacts for policy and regulatory analysis: 

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