# White paper on Valuing Me thane Emissions Changes in

R egulatory Benefi t
- Cost Analysis , Peer Review Charge

Questions, and Responses2



## Table of Contents
Whitepaper : Valuing Me thane Emissions Changes in R egulatory Benefi t

- Cost Analysis............... 3

Peer Re view Charge Questions.

.......................................................................................... .......... 13

Review: Karen Fisher

- Van den....

.................................................................... ............................... 15
Review: John Reilly..........................................................................................................

... ... ....... 19

Review: S teven Rose...................................................................................................................

.. 233



## Valuing Methane Emission Changes in Regulatory Benefit

- Cost Analysis

1. Introduction

While CO 2 is the primary source of anthropogenic greenhouse gas (GHG) emissions contributing to climate change, other GHGs such as methane (CH 4 ) 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 CO 2 concentration since 1750 contributed 1.82 W m - 2 to global mean radiative forcing , or 64% of the total radiative forcing from well mixed GHGs , and t he direct effect of increased atmospheric CH 4 accounted for 0.48 W m - 2

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

. In addition, CH 4 emissions have indirect impacts on the climate due to their role as a precursor for tropospheric ozone and stra tospheric 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 CH 4 atmospheric concentrations , AR5 estimated that historical anthropogenic emissions of C H 4 have contribute d a total of 0. 97 W m - 2 to global mean radiative forcing , or almost a third of the radiative forcing resulting from emissions of well mixed GHGs

. Therefore , CH 4 emissions are having, and will continue to have , a significant role on human well

- being through their effect on the climate

. The United State s Environmental Protection Agency (EPA) has promulgated several regulations that affect CH 4 emissions from a variety of sources. For example, the 2012 New Source Performance Standard s and Amendments to the National Emissions Standards for Hazardous Air Pollutants for the Oil and Natural Gas Industry are expected to reduce CH 4 emissions by 900,000 metric tons annually. 2 Additionally, t he 2017

- 2025 Light

- duty Vehicle Greenhouse Gas Emis sion Standards and Corporate Average Fuel Economy Standards , promulgated jointly with the National Highway Traffic Safety Administration, is expected to reduce CH 4 emissions by over 1 00,000 metric tons in 202 5 increasing to nearly 500,000 metric tons in 2050

. 3 It is likely that future EPA rulemakings will also impact CH 4 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 abi lity to quantify and monetize the relevant outcomes of the regulatory action under investigation in a scientifically and economically defensible manner . EPA has promulgated regulations th at r esult in changes in CH 4 emissions but has not yet quantified such impacts in its main benefit

- cost analyses. In sensitivity analyses EPA has considered the benefits of CH 4 emissions reductions by using the global warming potential (GWP) metric to convert C H 4 emissions into carbon dioxide (CO 2 ) equivalents which are then valued using the U.S. Government’s (USG) social cost of carbon (SC

- CO 2 )

1 See EPA E ndangerment Finding: Endangerment and Caus e or Contribute Findings for Greenhouse Gase s 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

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- 16806.pdf
3 http://www.gpo.gov/fdsys/pkg/FR

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estimates. 4 To date, EPA has not included these indirect CH 4 benefit approximations in the main benefit

cost analyses due to the well

- documented caveats associated with the approach (discussed in S ection 2)

. While some direct estimates of CH 4 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

- CO 2 (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

- CO 2 in accordance with evolving scientific and economic understanding, t his paper illustrate s how EPA could apply the social cost of CH 4 (SC

- CH 4 ) estimates developed in Marten et al. (2014) to improve upon the current treatment of methane impacts in regulatory analys i s 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

- CH 4 estimates that are consistent with the modeling assumptions underlying the USG SC

- CO 2 . Th is paper begins by describing the GWP

- based approach to valu ing CH 4 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 CH 4 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 CH 4 is a measure of the additional energy retained by the Earth’s atmosphere as the result of a pulse of CH 4 emissions as compared to a pulse of CO 2 emissions. Specifically , the GWP is the time

- integrated global mean radiative forcing from one kg of CH 4 emissions compared to

one kg of CO 2 emissions over a given time horizon, such that

, ( 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 ti me 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

.
T he GWP was de veloped by the IPCC for their Firs t Assessment Report (IPCC 1990) as a simple and purely physical metric t o provide information about the potential impacts of each non
- CO 2 GHG relative to CO 2 emissions. Under the Kyoto Protocol the GWP was designated for u se in translating emissions of non

- CO 2 GHGs into comparable CO 2 equivalents when estimating GHG sources and sinks. 6 Similarly the United

4 The USG SC

- CO 2 estimates are commonly referred to as the social cost of carbon but are consistent with a one metric ton change in CO 2 emissions.
5 Page 49536 http://www.gpo.gov/fdsys/pkg/FR

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

.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 GWP s for CH 4 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 f eedback of CH 4 emissions on its own lifetime and a n estimated 40% increase in the radiative efficacy of CH 4 emissions due to their role as a precursor for tropospheric ozone and stratosphe ric water vapor

. T he CH 4 GWP estimates presented in AR5 also include the indirect effects of CH 4 emissions, but the increase in radiative efficacy due to these effects was increased to 55% due to new findings on the role of CH 4 in stratospheric ozone formation. A reassessment of the effect of CH 4 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 CH 4

AR5 8
Time Horizon AR4 9 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 CO 2 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
- CO 2 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

- CO 2 emissions. Inclusion of CC feedbacks in calculating the GWP for CH 4 increases the estimate from 28 to 34 for a 100 yea r time horizon.

2. 1 Application of GWP

- Based Approach to Benefit

- Cost Analysis

The SC

- CO 2 is an estimate of the monetized damages associated with an incremental increase in CO 2 emissions in a given year. It is intended to include (but is not limited to) ch anges in net agricultural productivity, human health, property damages from increased flood risk, and the value of ecosystem services. As such, the SC

- CO 2 is an estimate of the benefits of reducing CO 2 emissions at the margin. The USG first published SC

- C O 2 estimates in 2010 following an inter agency process that included EPA and other executive branch entities

. T he USG used three integrated assessment models (IAM) to develop SC

C O 2 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 Sourc e: Table 2.14 in Forster et al. (2007).6

revisit the 2010 modeling decisions (e.g., discount rate s , 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 literat ure. The February 2010 Technical Support Document (TSD) 10 provides a complete discussion of the methods used to develop the USG SC

- CO 2 estimates and the November 2013 TSD 11 presents and discusses the u pdated estimates.

T he USG has not develop ed an estimate of the social cost of CH 4 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 CH 4 emissions mitigation. To understand the potential implicatio n of these omissions, EPA has conducted sensitivity analysis in some of its regulatory analyses using the 100

- year GWP to convert CH 4 emission reductions to CO 2 - equivalents , which are then valued using the SC

- CO 2 . This approach approximat es the social cost of methane (SC

- CH 4 ) using the SC

- CO2 and the GWP, such that

. ( 2 )

2.2 Limitations of the G lobal Warming Potential Approach for Valuing CH 4 Emission s Changes

The GWP is a simple, transparent, and well

- established metric for assessing the relative impacts of non

CO 2 emissions compared to CO 2 on a purely physical basis. However, t he GWP

- based approximation of the SC

- CH 4 in ( 2 ) has several well

- documented limitations ( e.g., Reilly and Richards 1993; Schmalens e e 1993 ; Fankhauser 1994; Marten and Newb old 2012)

. Gas comparison metrics, such as the GWP, are designed to measure the impact of non

- CO 2 GHG emissions relative to CO 2 at a specific point along the pathway from emissions to monetized damages (depicted in Figure 1) , and this point may differ acro ss measures. The GWP measure s the cumulative radiative forcing from a perturbation of a non

- CO 2 GHG relative to a perturbation of CO 2 over a fixed time horizon. T he GWP and other gas comparison metrics are not ideally suited for use in benefit

- cost analyses to approximate the social cost of non

- CO 2 GHGs because they i gnore important nonlinear relationships beyond radiative forcing in the chain between emissions and damages . These can become relevant be cause gases have different lifetimes

. For example, the SC

- C O 2 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 socio economic 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 atmosp heric CO 2 concentrations included in the SC

CO 2 would be incorrectly allocated to CH 4 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

- fo r
regulator

- impact

- analysis.pdf7

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

- CO 2 estimates in general, including the USG SC

- CO 2 estimates . For example the 100 year time horizon usually used in estimating the GWP is less than the 300 ye ar horizon used in developing the USG SC

- CO 2 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 acc ount s 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 econo mic growth. In the case of CH 4 , which has a relatively short lifetime compared to CO 2 , the temporal independence of the GWP could lead the approximation in ( 2 ) to underestimate the SC

- CH 4 with a larger downward bias under higher discount rates (Marten and Newbold 2012). 12



### 3. Direct Estimation

T he SC

- CH 4 can be directly estimated using an integrated assessment model (IAM) similar to the way in which the SC

- CO 2 is estimated. IAMs couple simplified models of atmospheric gas cycles and climate systems with highly aggregate d models of the global economy and human behavior to represent the impacts of GHG emissions on the climate and human welfare. Within IAMs, the e quations 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 effect s of climate on various market an d 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 CH 4 emissions using IAMs, though the number of suc h estimates is small compared to the large number of SC

- CO 2 estimates available in the literature. Among these published direct estimates there is considerable variation in the models an d input assumptions. Th es e 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 , a s discussed b y M arten et al. ( 2014 ) , none of the other published estimates of the SC

- CH 4 are consistent with the USG SC

- CO 2 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

- CH 4 that are consistent with the U SG SC

CO 2 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 whe re the SC

- CO 2 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 socioeconomic

emissions scenarios, equilibrium climate sensitivity distri bution, and three constant discount rates used to develop the USG SC

- CO 2 estimates. Marten et al. also used the same aggregation method as the USG SC

- CO 2 to distil l the 45 distribution of the SC

- CH 4 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 95 th 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 th at two of the three IAMs as implemented by the USG are not “turn

- key” ready to estimate the SC

- CH 4 due to their lack of an atmospheric stock

- flow model of CH 4 emissions and their influence on global mean radiative forcing. Instead , two of the three model i mplementations use exogenous projection of aggregate non
- CO 2 radiative forcing , which prevent s the direct perturbation of CH 4 emissions within the models. Therefore , to estimate the SC

- CH 4 Marten et al. applied a simple model to estimate the path of additional radiative forcing from a CH 4 perturbation , which is then added to the exogenous non

- CO 2 radiative forcing projection to estimate the incremental damages compared to the baseline.
The simple model applied by Marten et al. ( 2014 ) used a n exponent ial decay function to project atmospheric CH 4 concentrations from the CH 4 emissions projections in the five so cioeconomic

- emissions scenarios. The y set the average lifetime of CH 4 to 12 years following the findings of the IPCC in AR4. The direct radiative forcing associated with the atmospheric CH 4 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 CH 4 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%.

T he USG SC

- CO 2 modeling exercise assumed that overall radiative forcing from non

- CO 2 sources remains constant past 2100 w ithout 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

- CO 2 ; h owever, estimating the SC

- CH 4 requires explicit projections of baseline CH 4 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

- CO 2 assumption for non

- CO 2 radiative forc ing past 2100 as applying to each gas individually , such that the emissions of each gas f a ll to their respective rate of atmospheric decay . This has the effect of hold ing global mean radiative forcing due to atmospheric CH 4 constant past 2100. Marten et al . show ed that , due to the relatively short lifetime of CH 4 , alternative method s for extrapolating CH 4 emissions past 2100 have only a negligible effect (less than 0.5% ) on the SC

- CH 4 . The SC

- CH 4 estimates developed by Marten et al. ( 2014 ) are presented in Table 2 along with the USG SC

CO 2 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

- CO 2 and SC

- CH 4 Estimates [2007$ per metric ton] (S ource: Marten et al. ( 2014 ))

SC

- CO 2 SC

- CH 4

Year 5.0% Mean 3.0%

Mean 2.5%

Mean 3%

95 th 5.0%

Mean 3.0%

Mean 2.5%

Mean 3%

95 th 2010 11 32 51 89 370 870 1,200 2, 5 00 2015 11 37 57 109 460 1,100 1,400 2, 9 00 2020 12 43 64 128 550 1,200 1,600 3,200 2025 14 47 69 143 6 6 0 1,400 1,800 3,800 2030 16 52 75 159 780 1,600 2,100 4, 3 00 2035 19 56 80 175 9 2 0 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, 5 00 3, 1 00 6 , 9 00

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

- CO 2 estimates. Specifically, the direct estimates woul d be used to value decreases in CH 4 emissions anticipated from the rulemaking. Forecast reductions in CH 4 emissions in a given year resulting from the regulatory action are multiplied by the SC

- CH 4 estimate based on a perturbation in that year. To obtain a present value estimate, th e monetized stream of future CH 4 benefits

are discount ed back to the analysis year using the same discount rate used to estimate the SC

- CH 4 . Specifically, the present value of benefits from a regulatory action leading to reductions in CH 4 emissions

is

, (3)

where r is the discount rate used to estimate the SC

- CH 4 . The SC

- CH 4 estimates would be applied in the same way to calculate CH 4 dis

- benefits of a rulemaking that leads to an increase in CH 4 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 the ir 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 CH 4 is 25

. H owever , based on the direct estimates in Table 2 the so cial cost of CH 4 emissions in 2020 are 25

- 46 times higher than for CO 2 depending on the discount rate. For emissions in 2050 the SC

- CH 4 is 3 1

- 54 times higher than the SC

- CO 2 . Therefore the GWP

- based approach to estimating10

the value of CH 4 emissions based o n the SC

- CO 2 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

- CH 4 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 Standards 13 using both the Marten et al. (2014) SC

- CH 4 estimates and the GWP

- based approach

. T he GWP

- based app roach underestimates the climate co

- benefits of the expected methane emission reductions by 1 4 % to 50% depending on the discount rate assumption.

Table 3. Methane Co

- benefits of 2017

- 2025 Light Duty Vehicle GHG Standards Using Alternative Valuation Method ologies [Billion 2007$] 14

USG Discount rate assumption Using Marten et al. ( 2014 ) SC

- CH 4 GWP

- Based

Approach (AR4 100 Year) % Difference

5% M ean 2.5 1. 2

- 50% 3% M ean 8

. 1 6. 1

- 26% 2.5% M ean 1 1. 6 9.7

- 1 6 % 3% 95 th percentile 2 1

. 9 18.8

- 1 4 %

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 t he current Marten et al. estimates . This occurs for low discount rates and emissions years in the
near term and is due to the higher CH 4 indirect effects and climate

- carb on 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

- CH 4 estimates , and the relative difference between th ose 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 N on - CO 2 

### GHG Emissions
While this white paper focuses on methane, the valuation of other non

- CO 2 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

- CO 2 GHG emissions, specifically N 2 O and HFC

- 134a

. Marten et al. (2014) provides an analysis of the SC

- N 2 O parallel to the ir SC

- CH 4 analysis

. They use the same methodology described for SC

CH 4 , replacing the simple CH 4 atmo spheric gas cycle model with a simple N 2 O atmospheric cycle, and found the directly modeled SC

- N 2 O estimates generally exceed those from the GWP

- based approach.

13 http://www.gpo.gov/fdsys/pkg/FR

- 2012

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- 15/pdf/2012

- 21972.pdf
14 NPV of climate benefits resulting from 2017

- 2050 CH 4 emission reductions , discounted back to 2012 . See RIA, Table 7.1

- 4, http://www.epa.gov/otaq/climate/documents/420r12016.pd f

.11

Their estimates of the SC

- N 2 O are also consistent with the USG SC

- CO 2 estimates and therefore, could also be used to improve the analysis of regulatory actions projected to influence N 2 O 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 at mospheric lifetimes and climate impacts

. It is difficult to determine how directly modeled estimates of SC

- F gases would compare to estimates from the GWP

based 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 t he costs and benefits of r egulatory 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 a pproach to value GHG emission impacts and the previous lack of peer
reviewed SC

- CH 4 estimates consistent with t he USG SC

- CO 2 modeling assumptions, EPA has only monetized the benefits of CH 4 emissions mitigation in sensitivity analys i s. However, Marten et al. (2014)

now provide s a set of published SC

- CH 4 estimates consistent with the USG SC

- CO 2 modeling exercise. As such , the Marten et al. estimates offer a method for improving the analyses of regulatory actions that are projected to influence CH 4 emissions without introducing inconsistency with the manner in which other CO 2 mitigation benefits are valued

. These estimates can and should be updated if and when the modeling assumptions underlying the USG SC

- CO 2 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

- CO 2 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

- CO 2 estimates are updated.12



### References

Fankhauser, S., 1994. The soc ial 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. Schul z 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 Sc ientific 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 CH 4 and N 2 O Mitigation Benefits Consistent with the U.S. Government’s SC

- CO 2 Estimates. Climate Policy. Publish ed 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 20 13: 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. C omparing 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 CH 4 emissions but ha s not yet quantified such impacts in its main benefit

- cost analyses. Direct estimates of the benefits of mitigating CH 4 emissions have been presented in the scientific literature, but EPA has not used the se estimates in benefit

- cost analyses because they a re inconsistent with U

. S

. G overnment (USG) estimates of the social cost of carbon dioxide ( SC

- CO 2 ). 16 A recently published paper ( Marten et al. 2014) presents estimates of the social cost of CH 4 (SC

- CH 4 ) that

are consistent with USG estimates of the SC

- CO 2 . While it is anticipated that the USG will continue to improve the models and data it uses to estimate the SC

- CO 2 in accordance with evolving scientific and economic understanding , th e enclosed paper illustrates how EPA could apply the SC

- CH 4 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 a ssessment

. Consistent with EPA’s peer review guidance, the Agency is see king 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

- CH 4 estimates provided in Marten et al. ( 2014 ) as designed to measure the monetized value of the climate impacts from marginal changes in CH 4 emissions in a way that is appropriate for use in benefit

- cost analysis of regulatory actions projected to change CH 4 emissions?

2. Do you agree that the Marten et al. SC

- CH 4 estimates a re consistent with the USG SC

- C O 2 estimates?

3. Do you agree with EPA’s characterization of the limitations of using the global warming potential (GWP) to approximate the SC

- CH 4 (and other non

- CO 2 GHGs)?

4. Do you agree wit h EPA’s assessment that direct estimates of the SC

- CH 4 , as developed by Marten et al. , are more appropriate for monetizing changes in CH 4 emissions than using the GWP to scale the USG SC

- CO 2 ?

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

- CO 2 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

- for

regulator

- impact

- analysis.pdf.14

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

- benefits) to society from reductions (increases) in CH 4 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 CH 4 to benefit

- cost analysis for regulations , do your answers for the questions above hold for the application of the social cost of N 2 O estimates provided in Marten et al.?

7. Are there implementation issues not addressed in the paper that EPA should consider before applying the Mart en 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 CH 4 

### emissions but ha s not yet quantified such impacts in its main benefit

- cost analyses. Direct estimates of the benefits of mitigating CH 4 

### emissions have been presented in the scientific literature, but EPA has not used the se estimates in benefit

- cost analyses because they a re inconsistent with U

. S

. G overnment (USG) estimates of the social cost of carbon dioxide ( SC

- CO 2 

### ). 1 

### A recently published paper ( Marten et al. 2014) presents estimates of the social cost of CH 4 

### (SC

- CH 4 

### ) that are consistent with USG estimates of the SC

- CO 2 

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

- CO 2 

### in accordance with evolving scientific and economic understanding , th e enclosed paper illustrates how EPA could apply the SC

- CH 4 

### 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 a ssessment

. Consistent with EPA’s peer review guidance, the Agency is see king 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

- CH 4 

### estimates provided in Marten et al. ( 2014 ) as designed to measure the monetized value of the climate impacts from marginal changes in CH 4 

### emissions in a way that is appropriate for use in benefit

- cost analysis of regulatory actions projected to change CH 4 

### 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 exam ple of how the SC

- CH 4 

### 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

- CO 2 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

- for

regulator

- impact

- analysis.pdf.

### 2

and which I expand on in my response s below . A key issue that I would like to raise here is that these measures are only appropriate for marginal changes in CH 4 

### . 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 soc ial cost measures like this.

2. Do you agree that the Marten et al. SC

- CH 4 

### estimates a re consistent with the USG SC

C O 2 

### estimates?
“Consistent” can have many interpretations. I will say that the Marten et al. SC

- CH 4 

### estimates are computed in a similar way as the SC

- CO 2 

### estimates, so in this regard, the two estimates are “consistent.” However, CO 2 

### is more explicitly modeled in the three models than CH 4 

### so in this regard they are not “consistent.” However, this incons istency 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 th e limitations of using the global warming potential (GWP) to approximate the SC

- CH 4 

### (and other non

- CO 2 

### GHGs)?
The review document (and Marten et al ) discusses a number of problem s that arise when GWP is used to approximate SC

- CH 4 

### : (1) in the introduction and in section 2 , the authors point out that the indirect effects of CH 4 

### , 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 b etween emissions and damages

— e.g., increased agricultural productivity due to CO 2 

### fertilization would be in correctly attributed to CH 4 

### if the GWP was used; (3) GWP does not account for differences in time horizons between gases — e. g., since C H 4 

### has a shorter lifetime than CO 2 

### , the GWP approach would underestimate the SC

- CH 4 

### . 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 bia ses. However, the temporal iss ue 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 issue s.

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

- CH 4 

### , as developed by Marten et al. , are more appropriate for monetizing changes in CH 4 

### emissions than using the GWP to scale the USG SC

- CO 2 

### ?

### 3

As discussed in my response to question 3 above, I agree that the di rect 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 CH 4



### ; thus, the authors were forced to develop a separate model to project the path of radiative forcing from a CH 4 

### perturbation, and then incorporate this path into the IAM exogenously. As a result, indirect or feedback effects are missed. F o r 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 rea sons outlined in the review document . However, the EPA should continue to seek improv ements 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 CH 4 

### 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 distrib utional effects that can only be capture d 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. Mo deling the econom y as one monolithic sector implies

, for instance, perfect substitutability across subsectors which will underestimate the cost of damages

. It also assume s perfect trade which can also underestimate the cost of damages

. ( See Chapter 6 of the IPCC WGIII Fifth Assessment Report which highlights some of the se biases that arise with alternative model characteris tics).
The use of these simplified models for SC estimates, I be lieve, is a large source of the criticisms we ’ ve seen with respect to the SCC reports. The use of m ore 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 CH 4 

### to benefit

- cost analysis for regulations , do your answers for the questions above hold for the application of the social cost of N 2 

### O es timates 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 the se SC es timates. These shortcoming are not specific to any gas.
(1) A s discussed in my response to question 1 , these estimates are not appropriate for evaluating lar ge (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 so me 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 C 4 

### H and N 2 

### O mitigation benefits cons istent with the US Government's SC

- CO 2 

### 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 N 2 

### O) that is consistent with the establi shed basis for estimating a social cost of carbon previously developed by EPA.

1. Has EPA correctly interpreted the SC

- CH 4 

### estimates provided in Marten et al. (2014) as designed to measure the monetized value of the climate impacts from marginal changes in CH 4 

### emissions in a way that is appropriate for use in benefit

- cost analysis of regulatory actions projected to change CH 4 

### 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 mo re 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 t he method includes the fact that abiogenic methane decays into CO 2 

### and hence may represent an additional impact of methane release. (Biogenic methane also decays into CO 2 

### but if that methane is derived from plant material that regrows it would then not rep resent an addition of CO 2 

### to the atmosphere.)

2. Do you agree that the Marten et al. SC

- CH 4 

### estimates are consistent with the USG SC

- CO 2 

### estimates?
While there is considerable controversy about how to estimate a Social Cost of Carbon from a theoretical stan dpoint 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

- CH 4 

### (and other non

- CO 2 

### GHGs)?
I agree that using GWP’s to scale the social cost of carbon would be theoretically inconsistent. As the EPA (no date) pape r 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 e ffects 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 relativ e to the Social Cost of Carbon as estimated in the Marten et al (2014) paper. (This was a conclusion Reilly and Richards (1 993) reached.) With a ver y 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

- CO 2 

### estimates in general, including the USG SC

- CO 2 

### 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

- CO 2 

### 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 ov er 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 CH

4 

### , which has a relatively short lifetime compared to CO 2 

### , the temporal independence of the GWP could lead the approximation in (2) to underestimate the SC

- CH 4 

### 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 whe re the SC

- CO 2 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

- CO 2 

### 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 arri ve 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 i s 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 prefere nce 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 thi ngs 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 o f 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

- CH 4 

### , as developed by Marten et al., are more appropriate for monetizing changes in CH 4 

### emissions than using the GWP to scale the USG SC

- CO 2 

### ?
Yes, see above.

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

benefits) to society from reductions (increases) in CH 4 

### 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, b eyond climate change, could in principle be incorporated into the analysis but that raises further complications. E.g. CO 2 

### has some benefit to crop growth (disputed) but ozone (of which methane is a precursor) has not only climate implications but also da mages 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 CH

4 

### to benefit

- cost analysis for regulations, do your answers for the questions above hold for the application of the social cost of N 2 

### O estimates provided in Marten et al.?
Yes, the method is equally applicable to N2O.

7. Are there implementation issu es 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 limitation s 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 fo r centuries to come. EPA should be c ommended for seeking peer review feedback

. Peer review is i mportant for p roducing 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

- CO 2 social cost estimates based on the USG SC

- CO 2 methodology before having a peer reviewed SC

- CO 2 methodol ogy.

**R esponses**  **to EPA Charge Questions** 

1. Has EPA correctly interpreted the SC

- CH 4 estimates provided in Marten et al. (2014) as designed to measure t he monetized value of the climate impacts from marginal changes in CH 4 emissions in a way that is appropriate for use in benefit

- cost analysis of regulatory actions projected to change CH 4 emissions?
Yes, the Marten et al

. SC

- CH 4 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 issu es with the specific Marten et al. SC

- CH 4 estimates that need to be considered ; and, implementation issues associated with using the SC

- CH 4 estimates to value regulatory action methane changes

.
2. Do you agree that the Marten et al. SC

- CH 4 estimates are consistent with the USG SC

- CO 2 estimates?

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

- CO 2 estimates

. They are consistent in a variety of ways with the USG SC

- CO 2 estimates due to the common experimental design (e.g., same three integrated assessment ( IA ) models
, uncertaint

y specification, scenario
runs , and results aggregation procedure ). H owever , they do not appear to be entirely consistent , and the implications are not clear to me . For instance, the simple model used to compute CH 4 concentrations and radiative forcing is different from the modeling used to construct non

- CO 2 forcing for the PAGE and DICE model ’ s USG SC

- CO 2 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 commen t on reference scenario differences (that could impact SC

- CO 2 estimates) or on the differences for higher and loweremissions scenarios. Another inconsistency is the implementation of the CH 4 and CO 2

perturbations. The CO 2 perturbations in the USG SC

- CO 2 calcu lation s 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 CO 2 (100 GtCO 2 , 27 GtC) was distributed evenly over the decades preceding and subsequent to year t

. 1 In Marten et al. however, the CH 4 perturbation was a 1 MtCH 4 pulse in a single year t

.
M ore importantly, while consistency is the driving motivation for the Marten et al. paper, it creates a serious problem. T he Marten et al. SC

- CH 4 estimates inherit all the issues associated with the USG SC

- CO 2 estimates. Overall, consistency with the USG SC

- CO 2 methodology is a scientifically pragmatic and laudable objective for SC

- CH 4 calculations. However, it requires that t he SC

- CO 2 methodology be scientifically sound. However, t he USG SC

- CO 2 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

- CO 2 methodology (and resulting SC

- CO 2 & SC

- CH 4 estimates). Scientifically, it would be inappropriate at this stage to propagate issues with the SC

- CO 2 methodology by moving forward with the proposed Marten et al. (2014) SC

- CH 4 (and SC

- N 2 O) estimates. Unfortunately, consistency alone is not adequate justification for using the Marten et al

. estimates . A peer reviewed SC

-

CO 2 methodology is needed before creating consistent SC

- X estimates for non

- CO 2 gases. See reply below to Charge Question # 4 fo r 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

- CH 4 (and other non

- CO 2 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

- CH 4 esti mates 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

- CH 4 , as developed by Marten et al., are more appropriate for monetizing changes in CH 4 emissions than using the GWP to scale the USG SC

- CO 2 ?

C onceptually, direct estimates of SC

- CH 4 are more appropriate than using GWPs to value CH 4 emissions changes associated with US regulatory actions . Practically, however, is another issue. It depends on the scientific soundness of the SC

- CH 4 estimation methodology. Unfortunately, t he current USG SC

- CO 2 methodology , and therefore the proposed SC

- CH 4 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

- CO 2 modeling that coded up in dividual

1 Note that with PAGE, the emissions pulse is initially introduced as a uniform increase in average an nual CO 2 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 emission s in both the decades preceding and following year t

.components of the models and ran dia gnostic scenarios ( Understanding the Social Cost of Carbon: A Technical Assessment
, http://epri.co/3002004657 ) . From the analyses

, we identified a number of fundamental issue s with the USG SC

- CO 2 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, climat

e 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 the ir representation within each model and across models

— e.g., agricultural CO 2 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. R easonable alternative specifications, additional uncertainties, and some variation that is artificial due to, for instance, difference in model implement ation. Together, the se 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 raise s an issue about the statistical comparability of results produced by the three different models. Statistical comparability and independence is required for USG SC

- CO 2 approach which combines 1 50,000 results from the three IA models into a distribution in order to derive a single USG SC

-

CO 2 for a given year and discount rate

. d. The current USG SC

- CO 2 estimates may not be robust (i.e., insensitive to alternative assumptions) given that (i) the study find s the underlying climate and damage r esults 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 find s reason able alternative s to the assumptions and modeling used in the USG SC

CO 2 experiment.

e. Issues with the overall ex perimental design , in particular the use of multi ple model s, which creates the consistency and comparability challenges and issues noted previously.

B ased on these findings, the study makes a number of recommen dations that could help increase scientific and public confidence in the SC

- CO 2 results :

a. Internal ly review the modeling to evaluate differences, improve comparability and uncertainty repres

entation, and enhance robustness

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

- model approach

.c. Evaluate robust ness to reasonable alternative assumptions and modeling to insure that the results are stable.

d. Peer review the approa ch and the models used. The USG SC

- CO 2 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. A dditional documentation and justification for methodological choices to fac ilitate communications & interpretation, and increase public confidence

.
f. A pplication guidance to insure proper application of USG SC

- CO 2 estimates.

Other researchers

, of course, have also identified issues with the current USG SC

- CO 2 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 call ed 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 CH 4 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 CH 4 to benefit

- cost analysis for regulations, do your answers for the questi ons above hold for the application of the social cost of N 2 O estimates provided in Marten et al.?

Yes , I have similar concerns about the Marten et al. SC

- N 2 O estimates and would be reluctant to move forward with the Marten et al. SC

- N 2 O and SC

- CH 4 estimat

es

.
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

- CH 4 ( and SC

- N 2 O ) estimates, there are a few issues regarding use of SC

- CH 4 and SC

- N 2 O 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

- CH 4 and SC

- N 2 O estimates

, which reflect the marginal value of **net global** changes in methane an d 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 complianc

e costs. Third, current USG guidance to use all SC

- CO 2 estimates will presumably be the same for SC

- CH 4 and SC

- N 2 O estimates

. As such, the guidance needs to be expanded to provide direction on how agencies should u se the multiple resulting CO 2 ( CH 4 , or N 2 O

) benefit estimates in benefi t

- 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

- CO 2 methodology (and the subsequent
non

- CO 2 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 i s a useful means of soliciting scientific feedback , but not a sub stitute for the review process needed (and described above).

**References**
Arrow, K., Cropper, M., Gollier, C., Groom, B., Heal, G., Newell, R., Weitzman, M. (2013). Determining 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 ov er 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: Modeling cli mate change impacts and associated economic damages

. US Environmental Protection Agency/US Department of Energy. Retrieved from http:// yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE

- 0564

- 115.pdf/$file/EE

- 0564

- 115.pdf Pizer , W., M. Adler
, J. Aldy
, D. Anthoff
, M. Cropper
, K. Gillingham
, M. Greenstone
, B. Murray
, R. Newell
, R. Richels
, A. Rowell
, S. Waldhoff

, J. Wiener (2014). Using and improving the social cost of carbon, Science 5: 1189

- 1190. Warren, R., Mastrandrea, M. D., Hope, C., & H of, A. F. (2010). Variation in the climatic response to SRES emissions scenarios in integrated assessment models. Climatic Change
, 102 , 671

– 785.