
[Federal Register Volume 82, Number 4 (Friday, January 6, 2017)]
[Notices]
[Pages 1733-1741]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2017-00058]


-----------------------------------------------------------------------

ENVIRONMENTAL PROTECTION AGENCY

[EPA-HQ-OAR-2016-0751; FRL-9958-02-OAR]


Notice of Availability of the Environmental Protection Agency's 
Preliminary Interstate Ozone Transport Modeling Data for the 2015 Ozone 
National Ambient Air Quality Standard (NAAQS)

AGENCY: Environmental Protection Agency (EPA).

ACTION: Notice of data availability (NODA); request for public comment.

-----------------------------------------------------------------------

SUMMARY: The Environmental Protection Agency (EPA) is providing notice 
that preliminary interstate ozone transport modeling data and 
associated methods relative to the 2015 ozone National Ambient Air 
Quality Standard (NAAQS) are available for public review and comment. 
This information is being provided to help states develop State 
Implementation Plans (SIPs) to address the requirements of Clean Air 
Act (CAA) section 110(a)(2)(D)(i)(I) for the 2015 ozone NAAQS. The 
information available includes: (1) Emission inventories for 2011 and 
2023, supporting data used to develop those emission inventories, 
methods and data used to process emission inventories into a form that 
can be used for air quality modeling; and (2) air quality

[[Page 1734]]

modeling results for 2011 and 2023, base period (i.e., 2009-2013) 
average and maximum ozone design value concentrations, projected 2023 
average and maximum ozone design value concentrations, and projected 
2023 ozone contributions from state-specific anthropogenic emissions 
and other contribution categories to ozone concentrations at individual 
ozone monitoring sites.
    A docket has been established to facilitate public review of the 
data and to track comments.

DATES: Comments must be received on or before 90 days after publication 
in the Federal Register.

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-
OAR-2016-0751, to the Federal eRulemaking Portal: http://www.regulations.gov. Follow the online instructions for submitting 
comments. Once submitted, comments cannot be edited or withdrawn. The 
EPA may publish any comment received to its public docket. Do not 
submit electronically any information you consider to be Confidential 
Business Information (CBI) or other information whose disclosure is 
restricted by statute. Multimedia submissions (audio, video, etc.) must 
be accompanied by a written comment. The written comment is considered 
the official comment and should include discussion of all points you 
wish to make. The EPA will generally not consider comments or comment 
contents located outside of the primary submission (i.e., on the Web, 
Cloud, or other file sharing system). For additional submission 
methods, the full EPA public comment policy, information about CBI or 
multimedia submissions, and general guidance on making effective 
comments, please visit http://www2.epa.gov/dockets/commenting-epa-dockets.
    When submitting comments, remember to:
    1. Identify the notice by docket number and other identifying 
information (subject heading, Federal Register date and page number).
    2. Explain your comments, why you agree or disagree; suggest 
alternatives and substitute data that reflect your requested changes.
    3. Describe any assumptions and provide any technical information 
and/or data that you used.
    4. Provide specific examples to illustrate your concerns, and 
suggest alternatives.
    5. Explain your views as clearly as possible, avoiding the use of 
profanity or personal threats.
    6. Make sure to submit your comments by the comment period deadline 
identified.
    For additional information about the EPA's public docket, visit the 
EPA Docket Center homepage at http://www.epa.gov/epahome/dockets.htm.
    Docket: All documents in the docket are listed in the 
www.regulations.gov index. Although listed in the index, some 
information is not publicly available (e.g., CBI or other information 
whose disclosure is restricted by statute). Certain other material, 
such as copyrighted material, will be publicly available only in hard 
copy. Publicly available docket materials are available either 
electronically in www.regulations.gov or in hard copy at the Air and 
Radiation Docket and Information Center, EPA/DC, WJC West Building, 
Room 3334, 1301 Constitution Ave. NW., Washington, DC. The Public 
Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through 
Friday, excluding legal holidays. The telephone number for the Public 
Reading Room is (202) 566-1744, and the telephone number for the Air 
Docket is (202) 566-1742.

FOR FURTHER INFORMATION CONTACT: For questions on the emissions data 
and on how to submit comments on the emissions-related projection 
methodologies, contact Alison Eyth, Air Quality Assessment Division, 
Environmental Protection Agency, Mail code: C339-02, 109 T.W. Alexander 
Drive, Research Triangle Park, NC 27709; telephone number: (919) 541-
2478; fax number: (919) 541-1903; email: eyth.alison@epa.gov. For 
questions on the preliminary air quality modeling and ozone 
contributions and how to submit comments on the air quality modeling 
data and related methodologies, contact Norm Possiel, Air Quality 
Assessment Division, Environmental Protection Agency, Mail code: C439-
01, 109 T.W. Alexander Drive, Research Triangle Park, NC 27709; 
telephone number: (919) 541-5692; fax number: (919) 541-0044; email: 
possiel.norm@epa.gov.

SUPPLEMENTARY INFORMATION:

I. Background

    On October 26, 2015 (80 FR 65292), the EPA published a rule 
revising the 8-hour ozone NAAQS from 0.075 parts per million (ppm) to a 
new, more protective level of 0.070 ppm. Section 110(a)(1) of the CAA 
requires states to submit SIPs that provide for the implementation, 
maintenance, and enforcement of a NAAQS within 3 years of the 
promulgation of a new or revised standard. Such plans are required to 
address the applicable requirements of CAA section 110(a)(2) and are 
generally referred to as ``infrastructure'' SIPs. Among the 
requirements in CAA section 110(a)(2) that must be addressed in these 
plans is the ``Good Neighbor'' provision, section 110(a)(2)(D)(i)(I), 
which requires states to develop SIPs that prohibit any source or other 
emissions activity within the state from emitting air pollutants in 
amounts that will contribute significantly to nonattainment or 
interfere with maintenance of the NAAQS in another state. With respect 
to the 2015 ozone NAAQS, the Good Neighbor SIPs are due within 3 years 
of promulgation of the revised NAAQS, or by October 26, 2018.
    On October 1, 2015, when EPA Administrator McCarthy signed the 
ozone NAAQS revision, the agency also issued a memorandum \1\ to EPA 
Regional Administrators communicating a process for delivering the 
protections afforded by the revised NAAQS, including implementing CAA 
requirements like the Good Neighbor provision. In that memorandum, the 
EPA emphasized that we will be working with state, local, federal and 
tribal partners to carry out the duties of ozone air quality management 
in a manner that maximizes common sense, flexibility and cost-
effectiveness while achieving improved public health expeditiously and 
abiding by the legal requirements of the CAA.
---------------------------------------------------------------------------

    \1\ Memorandum from Janet McCabe, Acting Assistant 
administrator, Office of Air and Radiation to Regional 
Administrators, Regions 1-10, ``Implementing the 2015 Ozone National 
Ambient Air Quality Standards,'' available at https://www.epa.gov/sites/production/files/2015-10/documents/implementation_memo.pdf.
---------------------------------------------------------------------------

    The memorandum noted that the EPA believes that the Good Neighbor 
provision for the 2015 ozone NAAQS can be addressed in a timely fashion 
using the framework of the Cross-State Air Pollution Rule (CSAPR), 
especially given the court decisions upholding important elements of 
that framework.\2\ The EPA also expressed its intent to issue timely 
information concerning interstate ozone transport for the 2015 ozone 
NAAQS as a first step to help

[[Page 1735]]

facilitate the development of SIPs addressing the Good Neighbor 
provision. The EPA recognizes that the CAA provides that states have 
the primary responsibility to submit timely SIPs, as well as the EPA's 
own backstop role to develop and promulgate Federal Implementation 
Plans (FIPs), as appropriate.
---------------------------------------------------------------------------

    \2\ See EPA v. EME Homer City Generation, L.P., 134 S. Ct. 1584, 
1607 (2014) (holding the EPA's use of uniform oxides of nitrogen 
(NOX) stringency to apportion emission reduction 
responsibilities among upwind states ``is an efficient and equitable 
solution to the allocation problem the Good Neighbor Provision 
requires the Agency to address''); EME Homer City Generation, L.P. 
v. EPA, 795 F.3d 118, 135-36 (D.C. Cir. 2015) (affirming EPA's use 
of air quality modeling to project future nonattainment and 
maintenance receptors and to calculate emissions budgets, and 
holding that the EPA affords independent effect to the ``interfere 
with maintenance'' prong of the Good Neighbor provision in 
identifying maintenance receptors).
---------------------------------------------------------------------------

    This notice includes preliminary air quality modeling data that 
will help states as they develop SIPs to address the cross-state 
transport of air pollution under the CAA's Good Neighbor provision as 
it pertains to the 2015 ozone NAAQS. These data are considered 
preliminary because states may choose to modify or supplement these 
data in developing their Good Neighbor SIPs and/or EPA may update these 
data for the purpose of potential future analyses or regulatory actions 
related to interstate ozone transport for the 2015 ozone NAAQS.
    The EPA has applied what it refers to as the CSAPR framework to 
address the requirements of the Good Neighbor provision for regional 
pollutants like ozone. This framework involves a 4-step process: (1) 
Identifying downwind receptors that are expected to have problems 
attaining or maintaining clean air standards (i.e., NAAQS); (2) 
determining which upwind states contribute to these problems in amounts 
sufficient to ``link'' them to the downwind air quality problems; (3) 
for states linked to downwind air quality problems, identifying upwind 
emissions that significantly contribute to nonattainment or interfere 
with maintenance of the NAAQS by quantifying upwind reductions in ozone 
precursor emissions and apportioning emission reduction responsibility 
among upwind states; and (4) for states that are found to have 
emissions that significantly contribute to nonattainment or interfere 
with maintenance or the NAAQS downwind, adopting SIPs or FIPs that 
eliminate such emissions. The EPA applied this framework in the 
original CSAPR rulemaking (76 FR 48208) to address the Good Neighbor 
provision for the 1997 ozone NAAQS and the 1997 and 2006 fine 
particulate matter (PM2.5) NAAQS. On October 26, 2016 (81 FR 
74504), the EPA again applied this framework in an update to CSAPR 
(referred to as the CSAPR Update) to address the Good Neighbor 
provision for the 2008 ozone NAAQS. This notice provides information 
regarding steps 1 and 2 of the CSAPR framework for purposes of 
evaluating interstate transport with respect to the 2015 ozone NAAQS. 
This preliminary modeling to quantify contributions for the year 2023 
is intended to help inform state efforts to address interstate 
transport with respect to the 2015 ozone NAAQS.
    The year 2023 was used as the analytic year for this preliminary 
modeling because that year aligns with the expected attainment year for 
Moderate ozone nonattainment areas, given that the CAA requires the EPA 
to finalize area designations for the 2015 ozone NAAQS in October 
2017.\3\ See North Carolina v. EPA, 531 F.3d 896, 911-12 (D.C. Cir. 
2008), modified on reh'g, 550 F.3d 1176 (holding the Good Neighbor 
provision requires implementation of emissions reductions be harmonized 
with the applicable downwind attainment dates).
---------------------------------------------------------------------------

    \3\ See 42 U.S.C. 7407(d)(1)(B) (requiring the EPA to finalize 
designations no later than 2 years after promulgation of a new or 
revised NAAQS). On November 17, 2016 (81 FR 81276), the EPA proposed 
to retain its current approach in establishing attainment dates for 
each nonattainment area classification, which run from the effective 
date of designations. This approach is codified at 40 CFR 51.1103 
for the 2008 ozone NAAQs, and the EPA proposed to retain the same 
approach for the 2015 ozone NAAQS. In addition, the EPA proposed the 
maximum attainment dates for nonattainment areas in each 
classification, which for Moderate ozone nonattainment is 6 years.
---------------------------------------------------------------------------

    As noted above, this notice meets the EPA's stated intention in the 
October 2015 memorandum to provide information relevant to the Good 
Neighbor provision for the 2015 ozone NAAQS. Specifically, this notice 
evaluates states' contributions to downwind ozone problems relative to 
the screening threshold--equivalent to 1 percent of the NAAQS--that the 
CSAPR framework uses to identify states ``linked'' to downwind air 
quality problems for further consideration to address interstate ozone 
transport. The EPA believes that states will find this information 
useful in their development of Good Neighbor SIPs for the 2015 ozone 
NAAQS, and we seek their comments on it.\4\ The EPA believes that 
states may rely on this or other appropriate modeling, data or analyses 
to develop approvable Good Neighbor SIPs which, as noted previously, 
are due on October 26, 2018. States that act now to address their 
planning obligation pursuant to the Good Neighbor provision would 
benefit from improved ozone air quality both within the state and with 
respect to other states.
---------------------------------------------------------------------------

    \4\ Note that the emissions projections in this NODA are 
consistent with the implementation of various state and federal 
regulations, and that any change to the future implementation of 
these regulations may impact these projections and related findings.
---------------------------------------------------------------------------

    This notice provides an opportunity for review and comment on the 
agency's preliminary ozone transport modeling data relevant for the 
2015 ozone NAAQS.

II. Air Quality Modeling and Related Data and Methodologies

A. Base Year and Future Base Case Emissions

    For this transport assessment, the EPA used a 2011-based modeling 
platform to develop base year and future year emissions inventories for 
input to air quality modeling. This platform included meteorology for 
2011, base year emissions for 2011, and future year base case emissions 
for 2023. The 2011 and 2023 air quality modeling results were used to 
identify areas that are projected to be nonattainment or have problems 
maintaining the 2015 ozone NAAQS in 2023. Ozone source apportionment 
modeling for 2023 was used to quantify contributions from emissions in 
each state to ozone concentrations at each of the projected 
nonattainment and maintenance receptors in that future year.\5\
---------------------------------------------------------------------------

    \5\ The 2023 ozone source apportionment modeling was performed 
using meteorology for the period May through September in order to 
focus on transport when 8-hour ozone concentrations are typically 
high at most locations. This modeling did not include high winter 
ozone concentrations that have been observed in certain parts of the 
Western U.S. which are believed to result from the combination of 
strong wintertime inversions, large NOx and volatile organic 
compound (VOC) emissions from nearby oil and gas operations, 
increased ultraviolet (UV) radiation intensity due to reflection off 
of snow-covered surfaces and potentially other local factors.
---------------------------------------------------------------------------

    The 2011 and 2023 emissions data and the state and federal rules 
included in the 2023 base case are described in detail in the 
documents, ``Preparation of Emissions Inventories for the Version 6.3 
2011 Emissions Modeling Platform''; ``Updates to Emissions Inventories 
for the Version 6.3, 2011 Emissions Modeling Platform for the Year 
2023''; and ``EPA Base Case v.5.16 for 2023 Ozone Transport NODA Using 
IPM Incremental Documentation''; all of which are available in the 
docket for this notice.
    In brief, the 2011 base year emissions and projection methodologies 
used here to create emissions for 2023 are similar to what was used in 
the final CSAPR Update. The key differences between the 2011 
inventories used for the final CSAPR Update and the 2011 inventories 
used for the 2015 ozone NAAQS preliminary interstate transport modeling 
include updates to mobile source and electric generating unit (EGU) 
emissions, the inclusion of fire emissions in Canada and Mexico, and 
updated estimates of anthropogenic emissions for Mexico. The key 
differences in methodologies for projecting non-EGU sector emissions 
(e.g., onroad and nonroad mobile, oil

[[Page 1736]]

and gas, non-EGU point sources) to 2023 as compared to the methods used 
in the final CSAPR Update to project emissions to 2017 include (1) the 
use of data from the U.S. Energy Information Administration Annual 
Energy Outlook 2016 (AEO 2016) to project activity data for onroad 
mobile sources and the growth in oil and gas emissions, (2) additional 
general refinements to the projection of oil and gas emissions, (3) 
incorporation of data from the Mid-Atlantic Regional Air Management 
Association (MARAMA) for projection of non-EGU emissions for states in 
that region, and (4) updated mobile source emissions for California.
    For EGUs, the EPA has included several key updates to the 
Integrated Planning Model (IPM) and its inputs for the agency's 2023 
EGU projections used for the air quality modeling provided in this 
NODA. The updated IPM assumptions incorporated in the EPA's Base Case 
v.5.16 capture several market trends occurring in the power sector 
today, and the 2023 EGU projections reflect a continuation of these 
trends. Notably, natural gas prices remain historically low and are 
expected to remain low in the foreseeable future given that gas 
production and pipeline capacity continue to increase while storage is 
already at an all-time high. These factors have contributed to record-
setting U.S. natural gas production levels for the fifth consecutive 
year in 2015 and record-setting consumption levels for the sixth 
consecutive year. Additionally, electricity demand growth (including 
retail sales and direct use) has slowed in every decade since the 
1950s, from 9.8 percent per year from 1949 to 1959 to 0.5 percent per 
year from 2000 to 2015. This trend is projected to continue: AEO 2016 
projects lower growth than projected in AEO 2015. In addition, these 
updated emission projections account for a continuing decline in the 
cost of renewable energy technologies such as wind and solar, as well 
as the recently extended production and investment tax credits that 
support their deployment. All of these factors result in decreased 
generation and capacity from conventional coal steam relative to EPA's 
EGU analyses that preceded these updated IPM inputs. Over the past 10 
years, coal-fired electricity generation in the U.S. has declined from 
providing roughly half of the nation's supply to about one-third, and 
has been replaced with lower-cost sources such as natural gas, wind, 
and solar.
    The updated EGU projections also include the Clean Power Plan 
(CPP), 80 FR 64662 (October 23, 2015). The modeling for the CSAPR 
Update did not include the CPP due to the former rule's focus on the 
2017 ozone season, see 81 FR at 74529. In the CSAPR Update rulemaking, 
the agency had identified several key factors and uncertainties 
associated with measuring the effects of the CPP in 2017, but explained 
that the EPA ``continues to believe that the modeling for the CPP . . . 
was useful and reliable with respect to the model years analyzed for 
[the CPP] (i.e., 2020, 2025, and 2030).'' Id.. The period of focus for 
the modeling here is in the mid-2020s, which falls within the CPP's 
interim performance period, and the EPA therefore believes it is 
appropriate to include the CPP in the modeling.\6\ The CPP is targeted 
at reducing carbon pollution, but on average, nationwide, the CPP would 
also reduce NOX emissions from EGUs. The agency therefore 
anticipates that, if the CPP were removed from the modeling, the 
overall net effect could be higher levels of NOX emissions, 
on average, and potentially higher ozone concentrations and 
contributions at receptors. However, note that NOX emissions 
from EGUs represent just one part of the total NOX 
inventory. In this regard, for many states it is possible that changes 
in EGU NOX emissions on the order of what might be expected 
in 2023 due to the CPP may have limited impact on the concentration and 
contribution data in this NODA, which are based on total NOX 
emissions.
---------------------------------------------------------------------------

    \6\ The CPP is stayed by the Supreme Court. West Virginia et al. 
v. EPA, No. 15A773 (U.S. Feb. 9, 2016). It is currently unclear what 
adjustments, if any, will need to be made to the CPP's 
implementation timing in light of the stay.
---------------------------------------------------------------------------

    As noted above, EGU emissions used for the air quality modeling in 
this NODA are based on IPM v5.16 projections. However, states may 
choose to use other EGU projections in developing their Good Neighbor 
SIPs. To continue to update and improve both EPA's and states' EGU 
projections, the EPA and state agencies, with the facilitation of 
multi-jurisdictional organizations (MJOs), have been collaborating in a 
technical engagement process to inform future-year emission projections 
for EGUs. The ongoing information exchange and data comparison have 
facilitated a clearer understanding of the capabilities and constraints 
of various tools and methods. This process will continue to inform how 
the EPA and states produce EGU emission projections to inform efforts 
to reduce ozone transport.
    The EPA observes there are differences between recent emissions and 
generation data and the corresponding future-year projections in this 
NODA. The EPA's modeling directly simulates how future-year energy 
trends and economic signals affect the composition of the fleet. In the 
2023 projections presented in this NODA, the EPA's modeling does not 
project the operation of a number of coal-fired and oil-fired units due 
to simulated future-year economic conditions, whether or not such 
capacity has publicly-released plans to retire.\7\ Some other 
projection methodologies, such as the approach used by the Eastern 
Regional Technical Advisory Committee (ERTAC), purposefully maintain 
the current composition of the fleet except where operators have 
announced expected changes. Comparing these projections is informative 
because there is inherent uncertainty in anticipating any future-year 
composition of the EGU fleet, since analysts cannot know in advance 
exactly which operators will decide to retire which facilities at any 
given time. The EPA is soliciting comments on whether and, if so, how 
different projection techniques for EGUs would affect emissions and air 
quality in a manner that could further assist states with their 
analysis of transported air pollution.
---------------------------------------------------------------------------

    \7\ Note that much of this change in operation is projected to 
occur as early as 2020, which is the first year of the 25-year 
horizon over which EPA's model is optimizing. EPA's modeling adopts 
the assumption of perfect foresight, which implies that agents know 
precisely the nature and timing of conditions in future years (e.g., 
future natural gas supply, future demand) that affect the ultimate 
cost of decisions along the way. With this perfect foresight, the 
model looks throughout the entire modeling horizon and selects the 
overall lowest cost solution for the power sector over that time.
---------------------------------------------------------------------------

B. Air Quality Modeling

    For the final CSAPR Update, EPA used the Comprehensive Air Quality 
Model with Extensions (CAMx) v6.20 as the air quality model. After the 
EPA performed air quality modeling for the final CSAPR Update, Ramboll 
Environ, the CAMx model developer, released an updated version of CAMx 
(version 6.30). In addition, EPA has recently sponsored updates to the 
Carbon Bond chemical mechanism in CAMx v6.30 related to halogen 
chemistry reactions that deplete ozone in marine (i.e., salt water) 
environments. The updated chemistry is included in a new version 6.32 
which the EPA has used for this analysis. Specifically, EPA used CAMx 
v6.32 for the 2011 base year and 2023 future base case air quality 
modeling to identify receptors and quantify contributions for the 2015 
NAAQS transport assessment. Information on this version of CAMx can be 
found in the Release Notes and User's Guide for CAMx v6.30 and in a

[[Page 1737]]

technical report describing the updated halogen chemistry in version 
6.32. These documents can be found in the docket for this notice.\8\ 
Details of the 2011 and 2023 CAMx model applications are described in 
the ``Air Quality Modeling Technical Support Document for the 2015 
Ozone NAAQS Preliminary Interstate Transport Assessment'' (AQM TSD) 
which is available in the docket for this notice.
---------------------------------------------------------------------------

    \8\ CAMx v6.32 is a pre-release version of CAMx v6.40 which is 
expected to be made public by Ramboll Environ in late 2016 or early 
2017.
---------------------------------------------------------------------------

C. Information Regarding Potential 2023 Nonattainment and Maintenance 
Sites

    The ozone predictions from the 2011 and 2023 CAMx model simulations 
were used to project 2009-2013 average and maximum ozone design values 
\9\ to 2023 following the approach described in the EPA's draft 
guidance for attainment demonstration modeling.\10\ Using the approach 
in the final CSAPR Update, we evaluated the 2023 projected average and 
maximum design values in conjunction with the most recent measured 
ozone design values (i.e., 2013-2015) to identify sites that may 
warrant further consideration as potential nonattainment or maintenance 
sites in 2023.\11\ If the approach in the CSAPR Update is applied to 
evaluate the projected design values, those sites with 2023 average 
design values that exceed the NAAQS and that are currently measuring 
nonattainment would be considered to be nonattainment receptors in 
2023. Similarly, with the CSAPR Update approach, monitoring sites with 
a projected 2023 maximum design value that exceeds the NAAQS would be 
projected to be maintenance receptors in 2023. In the CSAPR Update 
approach, maintenance-only receptors include both those monitoring 
sites where the projected 2023 average design value is below the NAAQS, 
but the maximum design value is above the NAAQS, and monitoring sites 
with projected 2023 average design values that exceed the NAAQS, but 
for which current design values based on measured data do not exceed 
the NAAQS.
---------------------------------------------------------------------------

    \9\ The ozone design value for a monitoring site is the 3-year 
average of the annual fourth-highest daily maximum 8-hour average 
ozone concentration.
    \10\ The December 3, 2014 ozone, fine particulate matter, and 
regional haze SIP modeling guidance is available at http://www.epa.gov/ttn/scram/guidance/guide/Draft_O3-PM-RH_Modeling_Guidance-2014.pdf.
    \11\ In determining compliance with the NAAQS, ozone design 
values are truncated to integer values. For example, a design value 
of 70.9 parts per billion (ppb) is truncated to 70 ppb which is 
attainment. In this manner, design values at or above 71.0 ppb are 
considered to exceed the NAAQS.
---------------------------------------------------------------------------

    The base period 2009-2013 ambient and projected 2023 average and 
maximum design values and 2013-2015 and preliminary 2014-2016 measured 
design values at individual projected 2023 nonattainment receptor sites 
and maintenance-only receptor sites are provided in Tables 1 and 2, 
respectively.\12\
---------------------------------------------------------------------------

    \12\ The preliminary 2014-2016 design values are based on data 
from the Air Quality System (AQS) and AirNow and have not been 
certified by state agencies. Note that for some sites the 
preliminary 2014-2016 design values are higher than the 
corresponding data for 2013-2015.
---------------------------------------------------------------------------

     
---------------------------------------------------------------------------

    \13\ In this notice, the East includes all states from Texas 
northward to North Dakota and eastward to the East Coast. All states 
in the contiguous U.S. from New Mexico northward to Montana and 
westward to the West Coast are considered, for this notice, to be in 
the West.

  Table 1A--2009-2013 and 2023 Average and Maximum Design Values and 2013-2015 and Preliminary 2014-2016 Design Values (DVs) at Projected Nonattainment
                                                             Receptor Sites in the East \13\
                                                                     [Units are ppb]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                             2009-2013    2009-2013       2023         2023      2013-2015
              Site ID                        County               St         Average DV   Maximum DV   Average DV   Maximum DV       DV       2014-2016
--------------------------------------------------------------------------------------------------------------------------------------------------DV----
240251001..........................  Harford..............  MD............         90.0           93         71.3         73.7           71           73
360850067..........................  Richmond.............  NY............         81.3           83         71.2         72.7           74           76
361030002..........................  Suffolk..............  NY............         83.3           85         71.3         72.7           72           72
480391004..........................  Brazoria.............  TX............         88.0           89         74.4         75.3           80           75
482010024..........................  Harris...............  TX............         80.3           83         71.1         73.5           79           79
482011034..........................  Harris...............  TX............         81.0           82         71.6         72.5           74           73
484392003..........................  Tarrant..............  TX............         87.3           90         73.9         76.2           76           73
484393009..........................  Tarrant..............  TX............         86.0           86         72.0         72.0           78           75
551170006..........................  Sheboygan............  WI............         84.3           87         71.0         73.3           77           79
--------------------------------------------------------------------------------------------------------------------------------------------------------


Table 1B--2009-2013 and 2023 Average and Maximum Design Values and 2013-2015 and Preliminary 2014-2016 Design Values at Projected Nonattainment Receptor
                                                                    Sites in the West
                                                                     [Units are ppb]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                             2009-2013    2009-2013       2023         2023      2013-2015
              Site ID                        County               St         Average DV   Maximum DV   Average DV   Maximum DV       DV       2014-2016
--------------------------------------------------------------------------------------------------------------------------------------------------DV----
60190007...........................  Fresno...............  CA............         94.7           95         78.9         79.1           86           86
60190011...........................  Fresno...............  CA............         93.0           96         77.8         80.3           85           88
60190242...........................  Fresno...............  CA............         91.7           95         79.2         82.0           86           86
60194001...........................  Fresno...............  CA............         90.7           92         73.0         74.0           89           91
60195001...........................  Fresno...............  CA............         97.0           99         79.1         80.8           88           94
60250005...........................  Imperial.............  CA............         74.7           76         72.8         74.1           77           76
60251003...........................  Imperial.............  CA............         81.0           82         78.5         79.5           78           76
60290007...........................  Kern.................  CA............         91.7           96         76.9         80.5           81           87
60290008...........................  Kern.................  CA............         86.3           88         71.2         72.6           78           81
60290014...........................  Kern.................  CA............         87.7           89         72.7         73.8           84           84
60290232...........................  Kern.................  CA............         87.3           89         72.7         74.1           78           77
60311004...........................  Kings................  CA............         87.0           90         71.0         73.5           80           84
60370002...........................  Los Angeles..........  CA............         80.0           82         73.9         75.7           82           86
60370016...........................  Los Angeles..........  CA............         94.0           97         86.8         89.6           92           95

[[Page 1738]]

 
60371201...........................  Los Angeles..........  CA............         90.0           90         80.3         80.3           84           85
60371701...........................  Los Angeles..........  CA............         84.0           85         78.3         79.2           89           90
60376012...........................  Los Angeles..........  CA............         97.3           99         86.5         88.0           94           96
60379033...........................  Los Angeles..........  CA............         90.0           91         76.7         77.5           89           90
60392010...........................  Madera...............  CA............         85.0           86         71.7         72.6           81           83
60650012...........................  Riverside............  CA............         97.3           99         83.0         84.4           92           93
60651016...........................  Riverside............  CA............        100.7          101         85.1         85.3           98           97
60652002...........................  Riverside............  CA............         84.3           85         72.2         72.8           81           81
60655001...........................  Riverside............  CA............         92.3           93         79.4         80.0           87           87
60656001...........................  Riverside............  CA............         94.0           98         78.4         81.7           90           91
60658001...........................  Riverside............  CA............         97.0           98         86.7         87.6           92           95
60658005...........................  Riverside............  CA............         92.7           94         82.9         84.1           85           91
60659001...........................  Riverside............  CA............         88.3           91         73.3         75.6           84           86
60670012...........................  Sacramento...........  CA............         93.3           95         74.1         75.4           80           83
60710005...........................  San Bernardino.......  CA............        105.0          107         96.3         98.1          102          108
60710012...........................  San Bernardino.......  CA............         95.0           97         84.4         86.2           88           91
60710306...........................  San Bernardino.......  CA............         83.7           85         75.5         76.7           86           86
60711004...........................  San Bernardino.......  CA............         96.7           98         89.7         91.0           96          100
60712002...........................  San Bernardino.......  CA............        101.0          103         92.9         94.7           97           97
60714001...........................  San Bernardino.......  CA............         94.3           97         86.0         88.5           88           91
60714003...........................  San Bernardino.......  CA............        105.0          107         94.1         95.9          101          101
60719002...........................  San Bernardino.......  CA............         92.3           94         79.8         81.2           86           86
60719004...........................  San Bernardino.......  CA............         98.7           99         88.5         88.7           99          104
60990006...........................  Stanislaus...........  CA............         87.0           88         73.6         74.5           82           83
61070009...........................  Tulare...............  CA............         94.7           96         75.8         76.9           89           89
61072010...........................  Tulare...............  CA............         89.0           90         72.6         73.4           81           82
--------------------------------------------------------------------------------------------------------------------------------------------------------


   Table 2A--2009-2013 and 2023 Average and Maximum Design Values and 2013-2015 and Preliminary 2014-2016 Design Values at Projected Maintenance-Only
                                                               Receptor Sites in the East
                                                                     [Units are ppb]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                             2009-2013    2009-2013       2023         2023      2013-2015
              Site ID                        County               St         Average DV   Maximum DV   Average DV   Maximum DV       DV       2014-2016
--------------------------------------------------------------------------------------------------------------------------------------------------DV----
90013007...........................  Fairfield............  CT............         84.3           89         69.4         73.2           83           81
90019003...........................  Fairfield............  CT............         83.7           87         70.5         73.3           84           85
90099002...........................  New Haven............  CT............         85.7           89         69.8         72.5           78           76
260050003..........................  Allegan..............  MI............         82.7           86         68.8         71.5           75           74
261630019..........................  Wayne................  MI............         78.7           81         69.6         71.7           70           72
360810124..........................  Queens...............  NY............         78.0           80         69.9         71.7           69           69
481210034..........................  Denton...............  TX............         84.3           87         70.8         73.0           83           80
482010026..........................  Harris...............  TX............         77.3           80         68.6         71.0           68           68
482011039..........................  Harris...............  TX............         82.0           84         73.0         74.8           69           67
482011050..........................  Harris...............  TX............         78.3           80         69.5         71.0           71           70
--------------------------------------------------------------------------------------------------------------------------------------------------------


   Table 2B--2009-2013 and 2023 Average and Maximum Design Values and 2013-2015 and Preliminary 2014-2016 Design Values at Projected Maintenance-Only
                                                               Receptor Sites in the West
                                                                     [Units are ppb]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                             2009-2013    2009-2013       2023         2023      2013-2015
              Site ID                        County               St         Average DV   Maximum DV   Average DV   Maximum DV       DV       2014-2016
--------------------------------------------------------------------------------------------------------------------------------------------------DV----
60295002...........................  Kern.................  CA............         84.3           91         70.4         76.0           85           88
60296001...........................  Kern.................  CA............         84.3           86         70.6         72.0           79           81
60372005...........................  Los Angeles..........  CA............         78.0           82         70.6         74.3           74           83
61070006...........................  Tulare...............  CA............         81.7           85         69.1         71.8           84           84
61112002...........................  Ventura..............  CA............         81.0           83         70.7         72.4           77           77
80350004...........................  Douglas..............  CO............         80.7           83         69.6         71.6           79           77
80590006...........................  Jefferson............  CO............         80.3           83         70.5         72.9           79           77
80590011...........................  Jefferson............  CO............         78.7           82         69.7         72.7           80           80
--------------------------------------------------------------------------------------------------------------------------------------------------------


[[Page 1739]]

D. Information Regarding Quantification of Ozone Contributions

    The EPA performed nationwide, state-level ozone source 
apportionment modeling using the CAMx Ozone Source Apportionment 
Technology/Anthropogenic Precursor Culpability Analysis (OSAT/APCA) 
technique \14\ to provide information regarding the expected 
contribution of 2023 base case NOX and VOC emissions from 
all sources in each state to projected 2023 ozone concentrations at 
each air quality monitoring site. In the source apportionment model 
run, we tracked the ozone formed from each of the following 
contribution categories (i.e., ``tags''):
---------------------------------------------------------------------------

    \14\ As part of this technique, ozone formed from reactions 
between biogenic VOC and NOX with anthropogenic 
NOX and VOC are assigned to the anthropogenic emissions.
---------------------------------------------------------------------------

     States--anthropogenic NOX and VOC emissions 
from each of the contiguous 48 states and the District of Columbia 
tracked individually (emissions from all anthropogenic sectors in a 
given state were combined);
     Biogenics--biogenic NOX and VOC emissions 
domain-wide (i.e., not by state);
     Boundary Concentrations--concentrations transported into 
the modeling domain from the lateral boundaries;
     Tribes--the emissions from those tribal lands for which we 
have point source inventory data in the 2011 NEI (we did not model the 
contributions from individual tribes);
     Canada and Mexico--anthropogenic emissions from sources in 
the portions of Canada and Mexico included in the modeling domain 
(contributions from Canada and Mexico were not modeled separately);
     Fires--combined emissions from wild and prescribed fires 
domain-wide (i.e., not by state); and
     Offshore--combined emissions from offshore marine vessels 
and offshore drilling platforms (i.e., not by state).
    The CAMx source apportionment model simulation was performed for 
the period May 1 through September 30 using the 2023 future base case 
emissions and 2011 meteorology for this time period. The hourly 
contributions \15\ from each tag were processed to obtain the 8-hour 
average contributions corresponding to the time period of the 8-hour 
daily maximum concentration on each day in the 2023 model simulation. 
This step was performed for those model grid cells containing 
monitoring sites in order to obtain 8-hour average contributions for 
each day at the location of each site. The model-predicted 
contributions were applied in a relative sense to quantify the 
contributions to the 2023 average design value at each site. Additional 
details on the source apportionment modeling and the procedures for 
calculating contributions can be found in the AQM TSD. The resulting 
2023 contributions from each tag to each monitoring site are provided 
in a file in the docket for this notice.\16\ The largest contributions 
from each state to 2023 downwind nonattainment receptors and to 
downwind maintenance-only receptors are provided in Tables 3-1 and 3-2, 
respectively.
---------------------------------------------------------------------------

    \15\ Ozone contributions from anthropogenic emissions under 
``NOX-limited'' and ``VOC-limited'' chemical regimes were 
combined to obtain the net contribution from NOX and VOC 
anthropogenic emissions in each state.
    \16\ The file containing the contributions is named: ``2015 O3 
NAAQS Transport Assessment_Design Values & Contributions.''

        Table 3-1--Largest Contribution From Each State to Downwind 8-Hour Ozone Nonattainment Receptors
                                                 [Units are ppb]
----------------------------------------------------------------------------------------------------------------
                                                    Largest                                           Largest
                                                 contribution                                      contribution
                 Upwind states                   to a downwind            Upwind states            to a downwind
                                                 nonattainment                                     nonattainment
                                                   receptor                                          receptor
----------------------------------------------------------------------------------------------------------------
Alabama.......................................            0.37  Montana.........................            0.09
Arizona.......................................            0.74  Nebraska........................            0.37
Arkansas......................................            1.16  Nevada..........................            0.62
California....................................            0.19  New Hampshire...................            0.01
Colorado......................................            0.32  New Jersey......................           11.73
Connecticut...................................            0.43  New Mexico......................            0.18
Delaware......................................            0.55  New York........................            0.19
District of Columbia..........................            0.70  North Carolina..................            0.43
Florida.......................................            0.49  North Dakota....................            0.15
Georgia.......................................            0.38  Ohio............................            2.38
Idaho.........................................            0.07  Oklahoma........................            2.39
Illinois......................................           14.92  Oregon..........................            0.61
Indiana.......................................            7.14  Pennsylvania....................            9.11
Iowa..........................................            0.43  Rhode Island....................            0.00
Kansas........................................            1.01  South Carolina..................            0.16
Kentucky......................................            2.15  South Dakota....................            0.08
Louisiana.....................................            2.87  Tennessee.......................            0.52
Maine.........................................            0.01  Texas...........................            1.92
Maryland......................................            1.73  Utah............................            0.24
Massachusetts.................................            0.05  Vermont.........................            0.00
Michigan......................................            1.77  Virginia........................            5.04
Minnesota.....................................            0.43  Washington......................            0.15
Mississippi...................................            0.56  West Virginia...................            2.59
Missouri......................................            1.20  Wisconsin.......................            0.47
                                                                Wyoming.........................            0.31
----------------------------------------------------------------------------------------------------------------


[[Page 1740]]


         Table 3-2--Largest Contribution From Each State to Downwind 8-Hour Ozone Maintenance Receptors
                                                 [Units are ppb]
----------------------------------------------------------------------------------------------------------------
                                                    Largest                                           Largest
                                                 contribution                                      contribution
                 Upwind states                   to a downwind            Upwind states            to a downwind
                                                  maintenance                                       maintenance
                                                   receptor                                          receptor
----------------------------------------------------------------------------------------------------------------
Alabama.......................................            0.48  Montana.........................            0.11
Arizona.......................................            0.52  Nebraska........................            0.41
Arkansas......................................            2.20  Nevada..........................            0.43
California....................................            2.03  New Hampshire...................            0.02
Colorado......................................            0.25  New Jersey......................            8.65
Connecticut...................................            0.36  New Mexico......................            0.41
Delaware......................................            0.38  New York........................           15.36
District of Columbia..........................            0.08  North Carolina..................            0.43
Florida.......................................            0.22  North Dakota....................            0.13
Georgia.......................................            0.31  Ohio............................            3.82
Idaho.........................................            0.16  Oklahoma........................            1.30
Illinois......................................           21.69  Oregon..........................            0.17
Indiana.......................................            6.45  Pennsylvania....................            6.39
Iowa..........................................            0.60  Rhode Island....................            0.02
Kansas........................................            0.64  South Carolina..................            0.15
Kentucky......................................            1.07  South Dakota....................            0.06
Louisiana.....................................            3.37  Tennessee.......................            0.69
Maine.........................................            0.00  Texas...........................            2.49
Maryland......................................            2.20  Utah............................            1.32
Massachusetts.................................            0.11  Vermont.........................            0.01
Michigan......................................            1.76  Virginia........................            2.03
Minnesota.....................................            0.34  Washington......................            0.11
Mississippi...................................            0.65  West Virginia...................            0.92
Missouri......................................            2.98  Wisconsin.......................            1.94
                                                                Wyoming.........................            0.92
----------------------------------------------------------------------------------------------------------------

    In CSAPR and the CSAPR Update, the EPA used a contribution 
screening threshold of 1 percent of the NAAQS to identify upwind states 
that may significantly contribute to downwind nonattainment and/or 
maintenance problems and which warrant further analysis to determine if 
emissions reductions might be required from each state to address the 
downwind air quality problem. The EPA determined that 1 percent was an 
appropriate threshold to use in the analysis for those rulemakings 
because there were important, even if relatively small, contributions 
to identified nonattainment and maintenance receptors from multiple 
upwind states mainly in the eastern U.S. The agency has historically 
found that the 1 percent threshold is appropriate for identifying 
interstate transport linkages for states collectively contributing to 
downwind ozone nonattainment or maintenance problems because that 
threshold captures a high percentage of the total pollution transport 
affecting downwind receptors.
    Based on the approach used in CSAPR and the CSAPR Update, upwind 
states that contribute ozone in amounts at or above the 1 percent of 
the NAAQS threshold to a particular downwind nonattainment or 
maintenance receptor would be considered to be ``linked'' to that 
receptor in step 2 of the CSAPR framework for purposes of further 
analysis in step 3 to determine whether and what emissions from the 
upwind state contribute significantly to downwind nonattainment and 
interfere with maintenance of the NAAQS at the downwind receptors. For 
the 2015 ozone NAAQS, the value of a 1 percent threshold would be 0.70 
ppb. The individual upwind state to downwind receptor ``linkages'' and 
contributions based on a 0.70 ppb threshold are identified in the AQM 
TSD for this notice.
    The EPA notes that, when applying the CSAPR framework, an upwind 
state's linkage to a downwind receptor alone does not determine whether 
the state significantly contributes to nonattainment or interferes with 
maintenance of a NAAQS to a downwind state. While the 1 percent 
screening threshold has been traditionally applied to evaluate upwind 
state linkages in eastern states where such collective contribution was 
identified, the EPA noted in the CSAPR Update that, as to western 
states, there may be geographically specific factors to consider in 
determining whether the 1 percent screening threshold is appropriate. 
For certain receptors, where the collective contribution of emissions 
from one or more upwind states may not be a considerable portion of the 
ozone concentration at the downwind receptor, the EPA and states have 
considered, and could continue to consider, other factors to evaluate 
those states' planning obligation pursuant to the Good Neighbor 
provision.\17\ However, where the collective contribution of emissions 
from one or more upwind states is responsible for a considerable 
portion of the downwind air quality problem, the CSAPR framework treats 
a contribution from an individual state at or above 1 percent of the 
NAAQS as significant, and this reasoning applies regardless of where 
the receptor is geographically located.
---------------------------------------------------------------------------

    \17\ See, e.g., 81 FR 31513 (May 19, 2016) (approving Arizona 
Good Neighbor SIP addressing 2008 ozone NAAQS based on determination 
that upwind states would not collectively contribute to a 
considerable portion of the downwind air quality problem).
---------------------------------------------------------------------------

III. Analytic Information Available for Public Comment

    The EPA has placed key information related to the air quality model 
applications into the electronic docket for this notice. This 
information includes the AQM TSD, an Excel file which contains the 
2009-2013 base period and 2023 projected average and maximum ozone 
design values at individual monitoring sites and the

[[Page 1741]]

ozone contributions to individual monitoring sites from anthropogenic 
emissions in each state and from the other individual categories 
included in the source apportionment modeling. Also in the docket for 
this notice are a number of emission summaries by sector, state, 
county, source classification code, month, unit, day, and control 
program. In addition, the raw emission inventory files, ancillary data, 
and scripts used to develop the air quality model-ready emissions which 
are not in a format accepted by the electronic docket are available 
from the Air Emissions Modeling Web site for the Version 6.3 Platform 
at https://www.epa.gov/air-emissions-modeling/2011-version-63-platform. 
Electronic copies of the emissions and non-emissions air quality 
modeling input files, the CAMx v6.32 model code and run scripts, and 
the air quality modeling output files from the 2011 and 2023 air 
quality modeling performed for the 2015 NAAQS ozone transport 
assessment can be obtained by contacting Norm Possiel at 
possiel.norm@epa.gov.
    The EPA is requesting comment on the components of the 2011 air 
quality modeling platform, the methods for projecting 2023 ozone design 
value concentrations and the methods for calculating ozone 
contributions. The EPA is also seeking comment on the methods used to 
project emissions to future years, where 2023 is an example of such a 
year. Specifically, comments are requested regarding new datasets, 
impacts of existing and planned federal, state, and local control 
programs on emissions, and new methods that could be used to prepare 
more representative emissions projections. That is, EPA is seeking 
comments on the projection approach and data sets that are potentially 
useful for computing projected emissions. Commenters wishing to comment 
on inventory projection methods should submit to the docket comments 
that describe an alternative approach to the existing methods, along 
with documentation describing why that method is an improvement over 
the existing method. Summaries of the base and projected future year 
emission inventories are provided in the docket to aid in the review of 
these data. As indicated above, the comment period for this notice is 
90 days from the date of publication in the Federal Register.

    Dated: December 28, 2016.
Stephen Page,
Director, Office of Air Quality Planning and Standards.
[FR Doc. 2017-00058 Filed 1-5-17; 8:45 am]
 BILLING CODE 6560-50-P


