From: Culligan, Kevin

Sent: Wednesday, July 22, 2015 8:24 PM

To: Frey, Nathan J.

Cc: Harvey, Reid; Vasu, Amy

Subject: Three sections addressing analytic questions

Nathan,

Per our discussion, attached are three sections addressing the three analytic questions we have

been discussing:

1. Impact of the 3 building blocks (file is bb interactivity)

2. Relationship between 1 and 2 building blocks (file is called section 7 equivalence)

3. Interaction between states with different state plan types (e.g. interaction between rate and

mass (file is patchwork)

- Kevin

<< bb interactivity preamble language 07-22-2015_to DDs.docx >>

<< CPP section VII equivalence language 07-22-2015 to omb.docx >>

<< 2015 07 22 patchwork emissions performance draft 1230draft CLEAN.docx >>The combination of all three building blocks is also of reasonable cost. As described in sections V.C

‐ V.E

and the GHG Mitigation Measures TSD, the EPA determined that each of the three building blocks was

cost

‐ effective. In summary, these estimates are: $23/ton for building block 1, $24/ton for building block

2, and $37/ton for building block 3. The EPA also considered the cost

‐ reasonableness of all three

building blocks if assessed together. The EPA estimates that, together, the three building blocks are able

to achieve CO2 reductions at an average cost of $30/ton. This estimate is based on a an average of the

estimates for each building block, weighted by the total estimated cumulative CO2 reductions for each

of these blocks over the 2022

‐ 2030 period. While it is possible to weight each block by other amounts,

the EPA believes that weighting by cumulative CO2 reductions best reflects the average cost of total

reduction potential across the three building blocks. The EPA considers each of these costs levels

reasonable for purposes of the BSER established for this rule.

The EPA views the weighted average cost estimate as a conservatively high estimate of the cost of

deploying all three building blocks simultaneously. The simultaneous application of all three building

blocks produces interactive dynamics, some of which could increase cost and some of which could

decrease cost represented in the building blocks. For example, one dynamic that would tend to raise

costs (and whose omission would therefore make the weighted average understate costs) is that the

emission reduction measures associated with building blocks 2 and 3 both prioritize the replacement of

higher

‐ cost generation (from affected fossil steam EGUs in the case of building block 2 and from all

affected EGUs in the case of building block 3). The EPA recognizes that the increased magnitude of

emission reduction measures necessitates replacement at more efficient affected EGUs, at a relatively

higher cost; however, this is a consequence of the greater emission reductions that can be achieved by

combining building blocks, not an indication that any individual building block has become more

expensive because of the combined deployment.

Similarly, the EPA recognizes that when building block 1 is combined with the other building blocks, the

combination has the potential to raise the cost of the portion of the overall emission reductions

achievable through heat rate improvements relative to the cost of those same reductions if building

block 1 were implemented in isolation (assuming for purposes of this discussion that the rebound effect

is not an issue and that the affected steam EGUs would in fact reduce their emissions if building block 1

were implemented in isolation). 1 However, we believe that the cost of emission reductions achieved

through heat rate improvements in the context of a three

‐ building block BSER will remain reasonable for

two reasons. First, as discussed in section V.C. below, even when conservatively high investment costs

are assumed, the cost of CO 2 emission reductions achievable through heat rate improvements is low

enough that the cost per ton of CO 2 emission reductions will remain reasonable even if that cost is

substantially increased. Second, although under a BSER encompassing all three building blocks the

volume of coal

‐ fired generation will decrease, that decrease is unlikely to be spread uniformly among all

coal

‐ fired EGUs. It is more likely that some coal

‐ fired EGUs will decrease their generation slightly while

others will decrease their generation by larger percentages or cease operations altogether. We would

1 If an EGU produces less generation output, then an improvement in that EGU’s heat rate and rate of

CO 2 emissions per unit of generation produces a smaller reduction in CO 2 emissions. If the investment

required to achieve the improvement in heat rate and emission rate is the same regardless of the EGU’s

generation output, then the cost per unit of CO 2 emission reduction will be higher when the EGU’s

generation output is lower. Commenters have also stated that operating at lower capacity factors may

cause units to experience deterioration in heat rates.expect EGU owners to take these changes in EGU operating patterns into account when considering

where to invest in heat rate improvements, with the result that there will be a tendency for such

investments to be concentrated in EGUs whose generation output is expected to decrease the least. This

enlightened bias in spending on heat rate improvements

– ‐ that is, focusing investments on EGUs where

such improvements will have the largest impacts and produce the highest returns, given consideration

of projected changes in dispatch patterns

– ‐ will tend to mitigate any deterioration in the cost of CO 2

emission reductions achievable through heat rate improvements.

In contrast with those prior examples, combining the building blocks also produces interactive dynamics

that significantly reduce the cost for CO2 reductions represented in the building blocks (and whose

omission would therefore make the weighted average overstate costs). Foremost among these

dynamics is the stabilization of wholesale power prices. When assessed individually, building blocks 2

and 3 have opposite impacts on wholesale power prices. For example, building block 2 promotes more

utilization of existing NGCC, which (assessed on its own) would increase natural gas consumption and

therefore price, in turn raising wholesale power prices (which are often determined by gas

‐ fired

generators as the power supplier on the margin); this dynamic puts upward pressure on the cost of

achieving CO2 reductions through shifting generation from steam to NGCC. 2 Meanwhile, building block

3 increases RE deployment; because RE generators have very little variable cost, an increase in RE

generation replaces other supply with higher variable cost, which would yield lower wholesale power

prices. Lower wholesale power prices would make further RE deployment less competitive against

generation from existing emitting sources; this dynamic puts upward pressure on the cost of achieving

CO2 reductions through increased RE deployment. 3 Applying building blocks 2 and 3 together produces

significantly more CO 2 reductions at a relatively lower cost because the countervailing nature of these

wholesale power price dynamics mitigates the primary cost drivers for each building block.

The EPA believes the dynamics tending to cause the weighted average above to overstate costs of the

combination of building blocks are greater than the dynamics tending to cause costs to be understated,

and that the weighted average costs are therefore conservatively high. Analysis performed by the EPA

at an earlier stage of the rulemaking supports this conclusion. At proposal, the EPA evaluated the cost

of increasing NGCC utilization (building block 2) and deploying incremental RE generation (building block

3) independently, as well as the cost of simultaneously increasing NGCC utilization and incremental RE

generation. The average cost (in dollar per ton of CO 2 reduced) was less for the combined building block

scenario, showing that the net outcome of the interactivity effects described above is a reduction in cost

per ton compared to cost

‐ effectiveness estimates of the building blocks that do not incorporate this

interactivity. 4

A final reason why EPA considers the weighted

‐ average cost above conservatively high is that simply

combining the building blocks at their full individual stringencies overstates the stringency of the

combined BSER. As discussed in section V.A.3.f and section VI, the BSER reflects the degree of emission

limitation achieved through application of the building blocks in the least stringent region. By definition,

2 The EPA’s cost

‐ effectiveness estimate of $24/ton for building block 2 reflects these market dynamics.

3 The EPA’s cost

‐ effectiveness estimate of $37/ton for building block 3 reflects these market dynamics.

4 Specifically, at proposal the EPA quantified the average cost, in dollar per ton of CO 2 reduced, of building blocks 1,

2, and 3 ($22.5 per ton) to be less than the cost of either building block 2 ($28.9 per ton) or building block 3 ($23.4

per ton) alone.in the other two regions, the BSER is less stringent than the simple combination of the three building

blocks whose stringency is represented in the weighted

‐ average cost above.

In addition to the weighted average cost analysis discussed above, for the regulatory impacts analysis

accompanying this final rule, the EPA has assessed the costs, benefits, and other impacts of deployment

of the final BSER through section 111(d) plans. The analysis reflects transmission and pipeline

capabilities and constraints, fuel market and electricity dispatch dynamics, and seasonal electricity load

requirements. Moreover, the analysis also includes a limited representation of the ability for states to

craft standards of performance that allow the use of emissions trading approaches, which facilitate the

ability of individual affected EGUs to take advantage of instances where other affected EGUs have

opportunities to reduce emissions at lower cost. As described below in section XI, the results indicate

that compliance with standards of performance consistent with the final BSER is readily achievable with

no adverse impacts on electricity system reliability, and that impacts on retail electricity prices are

modest and fall within the range of price variability seen historically in response to changes in factors

such as weather and fuel supply. Further, the costs tend to decline over time as states and regulated

entities take advantage of the available flexibility and expand deployment of more cost

‐ effective

measures (notably demand

‐ side energy efficiency). The EPA considers this analysis strong confirmation

of the reasonableness of the costs of the measures in the three building blocks in combination as the

best system of emission reduction.A. Reconstituting Statewide Rate-based CO

2 Emission Performance Goals

from the Source Category-Specific Emission Performance Rates

In order to provide states flexibility for planning purposes of

developing their plans , the EPA is providing a state-specific

averaging of the subcategory-specific emission performance rates to

determine a statewide goal. While the emission performance rates

reflect the quantification of performance based on the BSER and embody

the reductions estimated under building blocks one, two, and three,

the statewide goals reflect one alternative approach through which

states may choose to adopt and implement those subcategory-specific

performance rates.

The EPA quantified the potential reductions of the BSER in the

subcategory–specific emission performance rates established in section

VI. These rates themselves reflect the reduction potential expected

under BSER. To e stablish The state goals described in this section

represent, the EPA applied these rates to the baseline levels to

estimate the change in baseline emission performance in each state

that would occur if all sources in the fleet met the subcategoryspecific rates. This step alternative expression of BSER respects

preserves the flexibility of sources to meet the rates in any manner

that they see fit (i.e., through any combination of on - site abatement

technology such, as fuel

- switching and, co-firing, etcwith any level

of generation shifting to lower-emitting sources ) , and does not limit

them to their building block assumptions so long as the ultimate

outcome re spectsflects the BSER performance level as quantified

against this baseline data

. The state goal is simply an averageemission rate across the state’s affected EGUs that is equivalent to

meeting each source category-specific performance rate across the

baseline generation profile on which BSER itself was quantified.

The EPA derived the statewide rate-based CO 2 emission

performance goals by multiplying the fossil steam emission performance

rate by the baseline fossil steam generation in a state and

multiplying the NGCC emission performance rate by the baseline NGCC

generation in a state. The resulting emissions for fossil steam and

NGCC are then added together for each state. This emission total is

divided into that state’s baseline generation values from the likely

affected EGUs in order to develop a state’s rate-based CO 2 emission

performance goal for 2030. This blended rate reflects the collective

emission rate a state may expect to achieve when its baseline fleet of

likely affected EGUs continues to operate at baseline levels while

meeting its subcategory-specific emission performance rates reflecting

the BSER.

This step is repeated for years 2022-2029 using the emission

performance rates calculated for each of those years in the previous

section. The resulting state emission rates for each year 2022-2029

are then averaged together to determine the state’s interim rate-based

emission performance goal. This results in interim and final statewide

goal values unique specific to each state’s historical blendbaseline

profile of fossil steam and NGCC generation ; these average emission

rates represent an emissions performance that is equivalent to the

emissions performance of that baseline profile if it were to meet the

source category-specific performance rates

.The EPA also averages together the annual amounts in increments

of 3 years, 3 years, and 2 years for 2022-2024, 2025-2027, and 2028-

2029 to estimate emission rate averages for those periods that can

provide one illustrative pathway for states to consider in meeting

their interim goals. These three and two year increments are not

regulatory guidelines or equivalents for interim goals, but are rather

an illustrative pathway forof a potential gradual reduction compliance

strategy that states may use to reach their interim and final

statewide goals.

As described in the steps above, the statewide goals represent an

arithmetic combination of the subcategory-specific emission

performance rates, weighted by the historical baseline generation

levels profile upon which the BSER is premised. Consequently, the

statewide goals are equivalent to the CO2 emission performance rates

and are thus an equivalent expression of the BSER.DRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

1 DRAFT TEXT BOX FOR RIA

The impact of the EGs on the marginal cost of generating electricity may differ for affected EGUs if a

state adopts a rate

‐ based or a mass

‐ based plan. Commenters have observed, in the context of the

proposed EG, that the different production incentives for rate and mass

‐ based plans may encourage

greater generation by the affected EGUs in the rate

‐ based state. This is because the rate

‐ based

approach may yield lower marginal costs of electricity generation than the mass

‐ based approach for

some otherwise similar EGUs. In a rate

‐ based program, affected EGUs may emit more if they generate

more, whereas in a mass

‐ based approach, if an affected EGU generates more it must incur the full cost

of increasing its emissions. Some analysts have suggested that this implies that if a state with a rate

‐

based plan shares an electricity market with another state that adopted a mass

‐ based plan, then total

CO 2 emissions may be higher than if both states adopted rate

‐ based plans (Burtraw et al., 2015;

Bushnell et al., 2014). In each case, both states would still be able to demonstrate that their affected

EGUs are in compliance, such that the state is achieving its state goal (or the uniform rates).

In the context of preexisting programs, the effect of differential regulatory structures has been relatively

modest. For example, Schennach (2000) finds that in the early years of the Title IV cap and trade

program, the increase in SO 2 emissions of Phase II units, which historically were subject to emission rate

performance standards, offset the decrease in SO 2 emissions by Phase I units in by about 5%. Gibson

(2015) finds some evidence using Toxic Release Inventory data that commonly owned plants in

neighboring attainment areas increase their emissions when plants in nonattainment areas are

regulated. The EPA’s prospective analysis of the benefits and costs of the Cross

‐ State Air Pollution Rule,

which used IPM, forecast only a small increase in SO 2 emissions from plants that were not subject to the

rule (U.S.EPA 2011). The Regional Greenhouse Gas Initiative (RGGI) produces an annual report

monitoring the trends in on CO2 emissions from electricity generation in the region and imports from

outside of the region. To date, RGGI’s monitoring effort has not identified any significant change in CO 2

emissions or the CO 2 emission rate from non

‐ RGGI electric generation serving load in the RGGI region

(e.g., RGGI 2014). The effect on the relative costs of production across similar sources affected by

different regulatory approaches will, in part, depend on the relative stringency of the different

regulatory approaches, and the emission rate of the EGUs that represent the marginal source of long

‐

run supply.

In practice, determining the direction and magnitude of the effect of variation in state plan type on

sector wide emissions, relative to the two illustrative plan scenarios evaluated in this RIA, would be

difficult. The first challenge is defining the appropriate benchmark upon which to make the comparison

(i.e., the illustrative plan that all states adopt in the uniform policy scenario). Determining the change in

sectoral costs and emissions for the situation in which a subset of states then adopted a different type

of plan would require many additional assumptions regarding which states adopt the other plan type

instead and the specific features of those plans. The effect on the relative costs of generation across

states will be sensitive to these analytical choices, and therefore so will the results regarding the

direction and magnitude of state plan variation on aggregate sectoral costs and emissions. At the outset

there is a lack of information as to what design features states might adopt in their plans and in turn

what patterns of spatial and plan variation would be most appropriate to consider.

The mere existence of variation among the design of state plans would not be sufficient to conclude that

there will be a notable change in emissions relative to a case with less variation. The ultimate impact ofDRAFT DELIBERATIVE

– DO NOT CITE OR QUOTE

2 the variation will depend upon the specific plan approaches, the state’s goals, and the states’ existing

generating fleets, the transmission grid, spatial variation in future electricity demand, and the degree of

ERC and allowance trading available within the system, amongst other variables.

Some commenters provided analyses that suggest under certain assumptions about specific patterns of

variation in plans across states there may be higher CO 2 emissions than in the case where there is less

state flexibility in plans type and therefore such variation in plan type would not occur. Other modeling

choices regarding the specific pattern of variation in the plans that may adopt, or the plan assumed to

be adopted by all states in their analysis, may have reasonably led to different conclusions. In the

specific case of this rulemaking, states are afforded significant options in some dimensions of their

plans, but less so in other dimensions in order to protect the environmental integrity of the rule, and

this may influence the choice of a particular plan. It is not expected that all states will find it necessarily

more advantageous to adopt rate

‐ based approaches, as some commenters’ analyses might be taken to

imply. For example, the mass

‐ based approach allows states to separate which affected sources receive

allowances from the overall environmental objective of the program, which is not possible under rate

‐

based approaches, where the overall stringency of the approach is influenced by the emission rate

standards assigned to each affected source. In the case of rate

‐ based plans, only states that adopt the

uniform rates may trade with other states unless further demonstrations are made. This final

rulemaking also requires that states adopting mass

‐ based plans include a method for addressing leakage

to new fossil

‐ fired generation. If states adopt programs to address leakage within their state, those

programs may lead to reduced generation by EGUs in neighboring rate

‐ based states (relative to the

scenario where those plans were not in place).

References

Burtraw, Dallas, Karen Palmer, Sophie Pan, and Anthony Paul. 2015. A Proximate Mirror: Greenhouse

Gas Rules and Strategic Behavior under the U.S. Clean Air Act

. Resources for the Future Discussion Paper

15

‐ 02. March 2015.

Bushnell, James B., Stephen P. Holland, Jonathan E. Hughes, Christopher R. Knittel. 2015. Strategic Policy

Choice in State

‐ Level Regulation: The EPA's Clean Power Plan. National Bureau of Economic Research

Working Paper No. w21259. June, 2015.

Gibson, Matthew. 2015. Regulation

‐ induced pollution substitution. Working Paper. Accessed July 22,

2015: http://econweb.ucsd.edu/~magibson/pd fs/MGibson_pollution_substitution.pdf

Regional Greenhouse Gas Initiative (RGGI). 2014. CO 2 Emissions from Electricity Generation and Imports

in the Regional Greenhouse Gas Initiative: 2012 Monitoring Report. August 11, 2014. Accessed July 22,

2015: http://www.rggi.org/docs/Documents/El ec_monitoring_report_2012_15_08_11.pdf

Schennach, Susanne M., 2000. “Appendix: Effect of Title IV on SO 2 Emissions and Heat Input.” In:

Markets for Clean Air: The U.S. Acid Rain Program. by A. Denny Ellerman, Paul L. Joskow, Richard

Schmalensee, Juan

‐ Pablo Montero and Elizabeth Bailey. Cambridge University Press:New York.

U.S.EPA. 2011. Regulatory Impact Analysis for the Federal Implementation Plans to Reduce Interstate

Transport of Fine Particulate Matter and Ozone in 27 States; Correction of SIP Approvals for 22 States.

U.S. EPA Office of Air and Radiation, June 2011.