The EPA also disagrees that the Supreme Court's affirmation of its use of uniform control stringency to define significant contribution does not apply equally to this action. The commenters are mistaken insofar as they suggest that the original CSAPR regulated sources other than EGUs. This rule is identical to the original CSAPR rule in terms of the form of its remedy  -  an emission budget issued to each state, with allowances allocated to EGUs within the state. As in the original CSAPR, each state is free to submit a SIP to replace the FIP indicating that it will meet its emission budget via reductions from other sectors.
      Furthermore, the EPA took a similar partial approach in quantifying interstate transport obligations with respect to the 1997 ozone NAAQS in the original CSAPR rulemaking. In that rule, the EPA's modeling indicated that there would be persistent nonattainment and maintenance problems at some receptors even after imposition of CSAPR's emission reductions. The EPA stated that, because additional emission reductions may be available at higher cost thresholds and from other sectors, such as non-EGUs, the emission reductions quantified in the rule did not necessarily fully quantify certain states' interstate transport obligation with respect to the 1997 ozone NAAQS. Therefore, for states linked to those receptors, the agency concluded that its FIP provided a partial remedy, and that more emission reductions might be required in order to fully satisfy the states' transport obligations. As discussed later, this action now concludes that the EPA has fulfilled its FIP obligation with respect to the 1997 ozone NAAQS.
      Finally, the EPA disagrees with commenters who suggest that the agency's "own delay" in implementing a transport rule to address the 2008 ozone NAAQS led to the current circumstances the states and the EPA now face. Until mid-2014 when the Supreme Court reversed the D.C. Circuit's original vacatur of CSAPR, the governing judicial holding was that the EPA lacked legal authority to promulgate any FIP addressing 2008 ozone transport obligations until the agency first quantified each state's emission reduction obligation, allowed states time to submit SIPs, and acted on those SIPs. In July 2015, the D.C. Circuit issued its final decision generally upholding CSAPR, albeit subject to remand without vacatur of certain state budgets for reconsideration. The agency then proceeded on an expedited basis to issue a proposal to address its FIP obligation with respect to the 2008 ozone NAAQS in the fall of 2015. While commenters and the EPA may agree that it would be best if a full remedy could be possible by the 2017 ozone season such that downwind areas would receive those benefits in time for their Moderate area attainment deadlines, such a remedy simply is not feasible in the existing timeframe.
      As noted previously, CAA section 110(c)(1) directs the EPA to promulgate a FIP "at any time within two years" of its disapproval or finding of failure to submit. For the majority of states affected, that timeframe will not end until 2017 or later, and as mentioned previously, North Carolina compels the EPA to identify upwind reductions and implementation programs to achieve these reductions by the 2017 ozone season. As the EPA has explained, it believes that reductions from other sectors besides EGUs should be evaluated in developing a full remedy, and the agency does not have sufficient information at this time to promulgate such a rule. Therefore, given these circumstances, the agency maintains that only requiring at this time necessary and achievable reductions by the 2017 ozone season is reasonable.
 Why Focus on Eastern States
      The final CSAPR Update focuses on collective contributions of ozone pollution from states in the east. In this action, the EPA is not addressing interstate emission transport in this action for the 11 western contiguous United States. The CSAPR framework builds on previous eastern-focused efforts to address collective contributions to interstate transport, including the NOX Budget Trading Program, CAIR, and the original CSAPR rulemaking. However, for western states, the EPA believes that there may be geographically specific factors to consider in evaluating interstate ozone pollution transport. Accordingly, given the need for near-term 2017 analysis and implementation of the CSAPR Update FIPs, the EPA focused this rulemaking on eastern states where the CSAPR method for assessing collective contribution has proven effective.
      The EPA did not propose CSAPR Update FIPs to address interstate emission transport for western states and it is not finalizing FIPs for any of these states. However, the EPA notes that western states are not relieved of their statutory obligation to address interstate transport under the section 110(a)(2)(D)(i)(I). The EPA and western states, working together, are continuing to evaluate interstate transport obligations on a case-by-case basis. The EPA will fulfill its backstop role with respect to issuing FIPs for western states if and when that becomes necessary. The EPA notes that a 2-year FIP clock has started for New Mexico and California following the July 13, 2015 finding of failure to submit. The EPA notes that analyses developed to support this rule, including air quality modeling and the EPA's assessment of EGU NOX mitigation potential, contain data that can be useful for western states in developing SIPs. The data from these analyses are available in the docket for this rulemaking.
  The proposed CSAPR Update solicited comment on whether to promulgate FIPs to address interstate ozone transport for the 2008 ozone NAAQS for western states, either in this rulemaking or in a subsequent rulemaking. Most commenters generally agreed with the EPA's proposal to exclude western states in this rule given that there may be geographically specific factors to consider in evaluating western states' interstate transport requirements.
 Short-Term NOX Emissions
      In eastern states, the highest measured ozone days tend to occur within the hottest days or weeks of the summer. There tends to be a higher demand for electricity (for instance, to power air conditioners) on hotter days and with this increased power demand, ozone formation can increase causing peak ozone days. In discussions with representatives and officials of eastern states in April 2013 and April 2015, and in several letters to the EPA, officials from states that are part of the Ozone Transport Region (OTR) states suggested that EGU emissions transported from upwind states may disproportionally affect downwind ozone concentrations on peak ozone days in the eastern U.S. These representatives asked that the EPA consider additional peak day limits on EGU NOX emissions.
Comment: The proposed CSAPR Update took comment on whether or not short-term (e.g., peak-day) EGU NOX emissions disproportionately impact downwind ozone concentrations and, if they do, what EGU emission limits would be reasonable complements to the seasonal CSAPR requirement. Most commenters requested that the EPA not impose a short-term limit at this time.
Response: As noted previously, the EPA finds that NOX ozone season trading programs are effective at reducing peak ozone concentrations, and the agency is therefore continuing with a seasonal approach in this final rule. The EPA will continue to look at this matter with an eye towards future rulemakings.
C. Responding to the Remand of CSAPR NOX Ozone Season Emission Budgets
      As noted previously, in EME Homer City II, the D.C. Circuit declared invalid the CSAPR phase 2 NOX ozone season emission budgets of 11 states, holding that those budgets over-control with respect to the downwind air quality problems to which those states were linked for the 1997 ozone NAAQS. 795 F.3d at 129-30, 138. As to ten of these states, the court held that the EPA's 2014 modeling conducted to support the RIA for CSAPR demonstrated that air quality problems at the downwind locations to which those states were linked would resolve by phase 2 of the CSAPR program without further transport regulation (either CAIR or CSAPR). Id. at 129-30. With respect to Texas, the court held that the record reflected that the ozone air quality problems to which the state was linked could be resolved at a lower cost threshold. Id. The court therefore remanded those budgets to the EPA for reconsideration consistent with the court's opinion. Id. at 138. The court instructed the EPA to act "promptly" in addressing these issues on remand. Id. at 132.
      The court's decision explicitly applies to 11 state budgets involved in that litigation: Florida, Maryland, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Texas, Virginia, and West Virginia. Id. at 129-30, 138. The EPA is finalizing FIPs for eight of those states to address interstate transport with respect to the 2008 ozone NAAQS: Maryland, New Jersey, New York, Ohio, Pennsylvania, Texas, Virginia, and West Virginia. The FIPs incorporate revised emission budgets that replace the budgets promulgated in the CSAPR rule to address the 1997 ozone NAAQS, the same budgets remanded by the D.C. Circuit for reconsideration. Further, in this rule, these budgets will be effective for the 2017 ozone season, the same period in which the phase 2 budgets that were invalidated by the court are currently scheduled to become effective. Therefore, this action provides an appropriate and timely response to the court's remand by replacing the phase 2 budgets promulgated in the CSAPR to address the 1997 ozone NAAQS, which were declared invalid by the D.C. Circuit, with budgets developed to address the revised and more stringent 2008 ozone NAAQS.
      For the three remaining original CSAPR ozone season states affected by this portion of the EME Homer City II decision, Florida, North Carolina, and South Carolina, the EPA is not finalizing FIPs because the EPA's analysis performed to support the final rule does not indicate that these states are linked to any identified downwind nonattainment or maintenance receptors with respect to the 2008 ozone standard. Because the 2008 ozone NAAQS is more stringent than the 1997 ozone NAAQS, this modeling necessarily indicates that Florida, North Carolina, and South Carolina are also not linked to any remaining air quality concerns with respect to the 1997 ozone standard for which the states were regulated in the original CSAPR. Accordingly, in order to address the Court's remand with respect to these three states' interstate transport responsibility under the 1997 ozone standard, the EPA is removing these states from the CSAPR ozone season trading program beginning in 2017 when the phase 2 ozone season emission budgets were scheduled to be implemented.
      Comment: Some commenters contend that the D.C. Circuit's remand of the phase 2 ozone season emission budgets in EME Homer City II requires the EPA to calculate new budgets to address the states' transport obligations with respect to the 1997 ozone NAAQS. These commenters contend that the EPA has not fully responded to the court's remand until it quantifies new budgets.
      Response: As described earlier, the D.C. Circuit remanded 10 of CSAPR's ozone season NOX budgets because the EPA's 2014 modeling conducted to support the RIA for CSAPR demonstrated that air quality problems at the downwind locations to which those states were linked would resolve by phase 2 of the CSAPR program without further transport regulation. The court essentially found that, by phase 2 of the CSAPR program, the CSAPR record did not support the EPA's authority to require emission reductions from these 10 states in order to address the 1997 ozone NAAQS. Thus, absent any new analysis demonstrating that these states are linked to downwind air quality problems with respect to the 1997 ozone NAAQS, the EPA does not have the authority to subject these states to the CSAPR NOX ozone season emissions program beginning in 2017 and therefore does not have the authority to calculate new emission budgets for these states to address that standard. For Florida, North Carolina, and South Carolina, the EPA is therefore relieving sources in the states from the obligation to comply with the NOX ozone season trading program in response to the remand. For the remaining seven states, sources located in these states will no longer be subject to the phase 2 NOX ozone season budgets calculated to address the 1997 standard; however, because these states are linked to downwind air quality problems with respect to the 2008 ozone NAAQS, the EPA is promulgating new ozone season NOX emission budgets at 40 CFR 97.810(a). See also 40 CFR 52.38(b)(2)(ii) (relieving sources in all ten of these states of the obligation to comply with the remanded phase 2 NOX ozone season emission budgets after 2016).
      With respect to Texas, because the court determined that the phase 2 ozone season budget was more stringent than necessary to address Texas' interstate transport obligation with respect to the 1997 ozone NAAQS, the EPA removed Texas's budget as a constraint in the 2017 air quality modeling. Even in the absence of this constraint, the updated 2017 air quality modeling shows that the predicted average DVs and maximum DVs are below the level of the 1997 ozone NAAQS for the downwind receptors of concern to which Texas was linked in the original CSAPR rulemaking with respect the 1997 ozone NAAQS. Accordingly, the EPA has concluded that it need not require additional emission reductions from sources in Texas in order to address the state's interstate transport obligation. Thus, sources in Texas will no longer be subject to the phase 2 NOX ozone season budget calculated to address the 1997 standard; however, because Texas is linked to downwind air quality problems with respect to the 2008 ozone NAAQS, the EPA is promulgating a new ozone season NOX emission budget to address that standard at 40 CFR 97.810(a). See also 40 CFR 52.38(b)(2)(ii) (relieving sources in Texas of the obligation to comply with the remanded phase 2 NOx ozone season emission budgets after 2016).
      Separately, various petitioners filed legal challenges in the D.C. Circuit to an EPA supplemental rule that added five states to the CSAPR ozone season trading program, 76 FR 80760 (Dec. 27, 2011). See Public Service Company of Oklahoma v. EPA, No. 12-1023 (D.C. Cir., filed Jan. 13, 2012). The case was held in abeyance during the pendency of the litigation in EME Homer City. The case remains pending in the D.C. Circuit as of the date of signature of this rule. The EPA notes that this rulemaking also promulgates FIPs for all five states added to CSAPR in the supplemental rule: Iowa, Michigan, Missouri, Oklahoma, and Wisconsin. These FIPs incorporate revised emission budgets that replace the budgets promulgated in the supplemental CSAPR rule to address the 1997 ozone NAAQS for these five states and will be effective for the 2017 ozone season. In light of the court's decision in EME Homer City II, the EPA examined the record supporting the CSAPR rulemaking and determined that, like the 10 states discussed earlier, the EPA's 2014 modeling conducted to support the RIA for CSAPR demonstrated that air quality problems at the downwind locations to which four of the states added to CSAPR in the supplemental rule, Iowa, Michigan, Oklahoma, and Wisconsin, were linked would resolve by phase 2 of the CSAPR program without further transport regulation (either CAIR or CSAPR). Accordingly, sources in these states will no longer be subject to the phase 2 NOX ozone season budgets calculated to address the 1997 standard; however, because these states are linked to downwind air quality problems with respect to the 2008 ozone NAAQS, the EPA is promulgating new ozone season NOX emission budgets at 40 CFR 97.810(a). See also 40 CFR 52.38(b)(2)(ii) (relieving sources in these four states of the obligation to comply with the original phase 2 NOX ozone season emission budgets after 2016).
The D.C. Circuit also remanded without vacatur the CSAPR phase 2 SO2 annual emission budgets for four states (Alabama, Georgia, South Carolina, and Texas) for reconsideration. 795 F.3d at 129, 138. This final rule does not address the remand of these CSAPR phase 2 SO2 annual emission budgets. On June 27, 2016, the EPA released a memorandum outlining the agency's approach for responding to the D.C. Circuit's July 2015 remand of the CSAPR phase 2 SO2 annual emission budgets for Alabama, Georgia, South Carolina, and Texas. The memorandum can be found at https://www3.epa.gov/airtransport/CSAPR/pdfs/CSAPR_SO2_Remand_Memo.pdf.
D. Addressing Outstanding Transport Obligations for the 1997 Ozone NAAQS
In the original CSAPR, the EPA noted that the reductions for 11 states may not be sufficient to fully eliminate all significant contribution to nonattainment or interference with maintenance for certain downwind areas with respect to the 1997 ozone NAAQS. The 11 states are: Alabama, Arkansas, Georgia, Illinois, Indiana, Kentucky, Louisiana, Mississippi, Missouri, Tennessee, and Texas. In the original CSAPR, the EPA did not require EGU NOX reductions represented by costs that exceeded $500 per ton because it noted that, at cost thresholds higher than $500 per ton, non-EGU reductions should also be considered. Additionally, the EPA's analysis projected continued nonattainment and maintenance problems at downwind receptors to which these upwind states were linked after implementation of the CSAPR trading programs. Specifically, persistent ozone problems were expected in Baton Rouge, Louisiana; Houston, Texas; and Allegan, Michigan according to the remedy case modeling conducted for the final rule. At that time the EPA did not quantify further ozone season EGU or non-EGU NOX reductions that would be needed in these states to fully resolve the good neighbor obligation under the CAA with respect to the 1997 ozone NAAQS.
To evaluate whether additional emission reductions would be needed in these 11 states to address the states' full good neighbor obligation for the 1997 ozone NAAQS, the EPA reviewed the 2017 air quality modeling conducted for this rule, which includes emission reductions associated with the CSAPR phase 2 ozone season budgets that were not remanded. The modeling included the phase 2 ozone season budgets for 10 of the states listed above - -  all but Texas. For each of these states, the updated 2017 air quality modeling shows that the predicted average DVs and maximum DVs for 2017 are below the level of the 1997 ozone NAAQS for the downwind receptors of concern to which the 11 states were linked in the original CSAPR rulemaking with respect the 1997 ozone NAAQS, meaning that these receptors no longer qualify as either nonattainment or maintenance receptors for that NAAQS. The 2017 air quality modeling also shows that there are no other nonattainment or maintenance receptors to which these states would be linked with respect to the 1997 ozone NAAQS. Thus, the EPA finds that, with implementation of the original CSAPR NOX ozone season emission budgets in the states not subject to the remand, emissions within these ten states no longer significantly contribute to downwind nonattainment or interference with maintenance for the 1997 ozone NAAQS. Thus, the promulgation of the CSAPR NOX ozone season budgets in those states satisfied the EPA's FIP obligation pertaining to the good neighbor provision for the 1997 ozone NAAQS. The EPA further finds that, with implementation of the CSAPR Update NOX ozone season emission budgets, emissions from these ten states also no longer significantly contribute to downwind nonattainment or interference with maintenance for the 1997 ozone NAAQS.
Despite the EPA's conclusion in CSAPR that the 1997 ozone transport problems to which Texas was linked were not fully resolved, the court concluded in EME Homer City II that the  ozone season emission budget finalized for Texas resulted in over-control as to the ozone air quality problems to which the state was linked. 795 F.3d at 129-30. As described earlier, in response to this determination, the EPA removed Texas's phase 2 ozone season budget as a constraint in the 2017 air quality modeling. Even in the absence of this constraint, the updated 2017 air quality modeling shows that the predicted average DVs and maximum DVs are below the level of the 1997 ozone NAAQS for the downwind receptors of concern to which Texas was linked in the original CSAPR rulemaking with respect the 1997 ozone NAAQS. Accordingly, the EPA has concluded that it need not require additional emission reductions from sources in Texas in order to address the states' interstate transport obligation with respect to the 1997 standard, and that the EPA has therefore fully addressed its FIP obligation with respect to Texas. Texas remains subject to the CSAPR Update in this final rulemaking with respect to the 2008 ozone NAAQS.
No Texas emissions were linked to expected ozone problems in Baton Rouge, Louisiana, and Allegan, Michigan. As noted previously receptors for these areas are no longer a concern for the 1997 ozone NAAQS. The EPA finds that Texas emissions no longer contribute significantly to nonattainment in, or interfere with maintenance by, any other state with respect to the 1997 ozone NAAQS. Thus, the EPA no longer has a FIP obligation pertaining to Texas emissions and the good neighbor provision for the 1997 ozone NAAQS.
V. Analyzing Downwind Air Quality and Upwind State Contributions
      In this section, the agency describes the air quality modeling performed consistent with steps 1 and 2 of the CSAPR framework described earlier in order to (1) identify locations where it expects nonattainment or maintenance problems with respect to the 2008 ozone NAAQS for the 2017 analytic year chosen for this final rule, and (2) quantify the contributions from anthropogenic emissions from upwind states to downwind ozone concentrations at monitoring sites projected to be in nonattainment or have maintenance problems for the 2008 ozone NAAQS in 2017.
      This section includes information on the air quality modeling platform used in support of the final rule with a focus on the base year and future base case emission inventories. The EPA also provides the projection of 2017 ozone concentrations and the interstate contributions for 8-hour ozone. The Final Rule AQM TSD in the docket for this rule contains more detailed information on the air quality modeling aspects of this rulemaking.
      The EPA provided two separate opportunities to comment on the air quality modeling platform and air quality modeling results that were used for the proposed CSAPR Update. On August 4, 2015, the EPA published a Notice of Data Availability (80 FR 46271) requesting comment on these data. Specifically, in the NODA, the EPA requested comment on the data and methodologies related to the 2011 and 2017 emissions and the air quality modeling to project 2017 concentrations and contributions. In addition to the comments received via the NODA, the EPA also received comments on emissions inventories and air quality modeling in response to the proposed CSAPR Update. Comments on both the NODA and proposed rule were considered for this final rule.
 Overview of Air Quality Modeling Platform
      For the proposed rule, the EPA performed air quality modeling for three emissions scenarios: a 2011 base year, a 2017 baseline, and a 2017 control case that reflects the emission reductions expected from the rule.
      The EPA selected 2011 as the base year to reflect the most recent National Emissions Inventory (NEI). In addition, the meteorological conditions during the summer of 2011 were generally conducive for ozone formation across much of the U.S., particularly the eastern U.S. As described in the AQM TSD, the EPA's guidance for ozone attainment demonstration modeling, hereafter referred to as the modeling guidance, recommends modeling a time period with meteorology conducive to ozone formation for purposes of projecting future year design values. The EPA therefore believes that meteorological conditions and emissions during the summer of 2011 provide an appropriate basis for projecting 2017 ozone concentrations in contributions.
      As noted in section IV, the EPA selected 2017 as the projected analysis year to coincide with the attainment deadline for Moderate areas under the 2008 ozone NAAQS. The agency used the 2017 baseline emissions in its air quality modeling to identify future nonattainment and maintenance locations and to quantify the contributions of emissions from upwind states to 8-hour ozone concentrations at downwind locations. The air quality modeling of the 2017 baseline and 2017 illustrative control case emissions are used to inform the agency's assessment of the air quality impacts resulting from this rule.
      For the final rule modeling, the EPA used the Comprehensive Air Quality Model with Extensions (CAMx) version 6.20 to simulate pollutant concentrations for the 2011 base year and the 2017 future year scenarios. This version of CAMx was the most recent, publicly available version of this model at the time that the EPA performed air quality modeling for this rule. CAMx is a grid cell-based, multi-pollutant photochemical model that simulates the formation and fate of ozone and fine particles in the atmosphere. The CAMx model applications were performed for a modeling region (i.e., modeling domain) that covers the contiguous 48 United States, the District of Columbia, and adjacent portions of Canada and Mexico using a horizontal resolution of 12 x 12 km. A map of the air quality modeling domain is provided in the AQM TSD.
      The 2011-based air quality modeling platform includes 2011 base year emissions, 2017 future year projections of these emissions, and 2011 meteorology for air quality modeling with CAMx. In the remainder of this section, the EPA provides an overview of (1) the 2011 and 2017 emissions inventories, (2) the methods for identifying nonattainment and maintenance receptors along with a list of 2017 baseline nonattainment and maintenance receptors in the eastern U.S., (3) the approach to developing metrics to measure interstate contributions to 8-hour ozone, and (4) the predicted interstate contributions of upwind states to downwind nonattainment and maintenance in the eastern U.S. The EPA also identifies which predicted interstate contributions are at or above the screening threshold described in section IV, which the agency applies in step 2 of the CSAPR framework for purposes of identifying those upwind states that are linked to downwind air quality problems and which merit further analysis with respect to regulation of interstate transport of ozone for purposes of the 2008 ozone standard.
The EPA conducted an operational model performance evaluation of the 2011 modeling platform by comparing the 8-hour daily maximum ozone concentrations predicted during the May through September "ozone season" to the corresponding measured concentrations. This evaluation generally followed the approach described in the modeling guidance. Details of the model performance evaluation are described in the AQM TSD. The model performance results indicate that the 8-hour daily maximum ozone concentrations predicted by the 2011 CAMx modeling platform reflect the corresponding 8-hour observed ozone concentrations in the 12-km U.S. modeling domain. As recommended in the modeling guidance, the acceptability of model performance was judged by considering the 2011 CAMx performance results in light of the range of performance found in recent regional ozone model applications.  These other modeling studies represent a wide range of modeling analyses that cover various models, model configurations, domains, years and/or episodes, and chemical mechanisms. Overall, the ozone model performance results for the 2011 CAMx simulations are within the range found in other recent peer-reviewed and regulatory applications. The model performance results, as described in the AQM TSD, demonstrate that the predictions from the 2011 modeling platform correspond to measured data in terms of the magnitude, temporal fluctuations, and spatial differences for 8-hour daily maximum ozone. These results provide confidence in the ability of the modeling platform to provide a reasonable projection of expected future year ozone concentrations and contributions.
      Comment: The EPA received comments that model performance should be evaluated for the individual days that were used in calculating projected 2017 ozone design values and projected 2017 ozone contributions. Commenters said that, in cases where model performance on these individual days is poor, the impact of the poor performance on projected concentrations and contributions must be investigated and considered in the final results by removing or adjusting these days to account for model bias.
      Response: The EPA is using air quality modeling to provide data for a set of representative days with meteorological conditions conducive for ozone formation and transport for use in projecting ozone design values and for calculating the average contribution metric. As described in sections V.D and V.E of this preamble, EPA is using air quality model predictions in a relative sense for estimating 2017 ozone design values and contributions. In this regard, the approach for projecting future design values is "anchored" by measured concentrations. As stated in the modeling guidance, it is reasoned that factors causing bias (either under or over-predictions) in the base year will also affect the future case. While good model performance remains a prerequisite for use of a model, problems posed by imperfect model performance on individual days are expected to be reduced when using the relative approach. Moreover, there are no universally accepted, generally applicable numerical bright-line criteria for determining which days might be candidates to exclude or adjust based on model performance for specific days at individual sites, as in the approach suggested by the commenter. Thus, the EPA disagrees that such an approach is necessary or appropriate for determining the sets of days used to provide data for projecting 2017 design values and for calculating the average contribution metric.
      The results of the model performance evaluation, as described previously and in the AQM TSD, indicate that ozone predictions from the modeling platform correspond to measured data in terms of the magnitude, temporal fluctuations, and spatial differences for 8-hour daily maximum ozone. Prior court rulings are deferential to modeling choices in this regard. The D.C. Circuit has declined to "invalidate EPA's predictions solely because there might be discrepancies between those predictions and the real world."  The fact that a "model does not fit every application perfectly is not criticism; a model is meant to simplify reality in order to make it tractable."  The court has held that "it is only when the model bears no rational relationship to the characteristics of the data to which it is applied that we will hold that the use of the model was arbitrary and capricious." As demonstrated by the EPA's model performance evaluation, the modeling platform used in this rulemaking provides reasonable projections of expected future year ozone concentrations and contributions, and is thus an appropriate basis on which to base the findings made in this action.
B. Emission Inventories
      The EPA developed emission inventories for this rule including emission estimates for EGUs, non-EGU point sources, stationary nonpoint sources, onroad mobile sources, nonroad mobile sources, wild fires, prescribed fires, and for biogenic emissions that are not the result of human activities. The EPA's air quality modeling relies on this comprehensive set of emission inventories because emissions from multiple source categories are needed to model ambient air quality and to facilitate comparison of model outputs with ambient measurements.
      To prepare the emission inventories for air quality modeling, the EPA processed the emission inventories using the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System version 3.7 to produce the gridded, hourly, speciated, model-ready emissions for input to the CAMx air quality model. Additional information on the development of the emission inventories and on data sets used during the emissions modeling process for the final rule are provided in the TSD "Preparation of Emissions Inventories for the Version 6.3, 2011 Emissions Modeling Platform," hereafter known as the "Final Rule Emissions Modeling TSD." This TSD is available in the docket for this rule and at www.epa.gov/air-emissions-modeling/2011-version-6-air-emissions-modeling-platforms.
      The emission inventories, methodologies, and data used for the proposal air quality modeling were provided for public comment in the August 4, 2015 NODA. Comments received on this NODA and on the proposal were considered for the final rule and the resulting data and procedures are documented in the Final Rule Emissions Modeling TSD.
1. Foundation Emission Inventory Data Sets
      The EPA developed emission data representing the year 2011 to support air quality modeling of a base year from which future air quality could be forecasted. The primary basis for the 2011 inventories used in air quality modeling was the 2011 National Emission Inventory (NEI) version 2 (2011NEIv2), released in March 2015. Documentation on the 2011NEIv2 is available in the 2011 National Emissions Inventory, version 2 TSD available in the docket for this rule and at www.epa.gov/air-emissions-inventories/2011-national-emissions-inventory-nei-documentation. Updates to the 2011NEIv2 were incorporated between the proposed and the final rule in response to comments received on the NODA and on the proposal. The future base case scenario modeled for 2017 includes a representation of changes in activity data and of predicted emission reductions from on-the-books actions, including planned emission control installations and promulgated federal measures that affect anthropogenic emissions. The emission inventories for air quality modeling include sources that are held constant between the base and future years, such as biogenic emissions and emissions from agricultural, wild and prescribed fires. The land use data used for the computation of the biogenic emissions were updated from those used in the proposal modeling to use the 2011 National Land Cover Database (NLCD) along with other updated data sets related to forest species, elevation, and cropland data in response to comments received on the NODA. The base and future year emissions for Canada used for the proposed rule were held constant at 2010 levels. For the final rule, the 2010 inventories were updated to reflect closures of EGUs and reductions to onroad and nonroad mobile source emissions in 2017. Emissions for Mexico represent the year 2018 and were unchanged from the proposed rule inventories.
2. Development of Emission Inventories for EGUs
      Annual NOX and SO2 emissions for EGUs in the 2011NEIv2 are based primarily on data from continuous emission monitoring systems (CEMS), with other EGU pollutants estimated using emission factors and annual heat input data reported to the EPA. For EGUs without CEMS, the EPA used data submitted to the NEI by the states. The final rule inventories include some updates to 2011 EGU stack parameters and emissions made in response to comments on the NODA and proposal. Between proposal and final, additional point sources in the inventory were identified as small EGUs. This resulted in increases to EGU NOx emissions that were offset by equivalent reductions in non-EGU point source NOx emissions in Arkansas, California, Florida, Idaho, Louisiana, Mississippi, New Hampshire, Oregon, and Texas. For more information on the details of how the 2011 EGU emissions were developed and prepared for air quality modeling, see the Final Rule Emissions Modeling TSD.
      The EPA projected future 2017 baseline EGU emissions using version 5.15 of the Integrated Planning Model (IPM) (www.epa.gov/airmarkets/power-sector-modeling). IPM, developed by ICF Consulting, is a state-of-the-art, peer-reviewed, multi-regional, dynamic, deterministic linear programming model of the contiguous U.S. electric power sector. It provides forecasts of least cost capacity expansion, electricity dispatch, and emission control strategies while meeting energy demand and environmental, transmission, dispatch, and reliability constraints. The EPA has used IPM for over two decades to better understand power sector behavior under future business-as-usual conditions and to evaluate the economic and emission impacts of prospective environmental policies. The model is designed to reflect electricity markets as accurately as possible. The EPA uses the best available information from utilities, industry experts, gas and coal market experts, financial institutions, and government statistics as the basis for the detailed power sector modeling in IPM. The model documentation provides additional information on the assumptions discussed here as well as all other model assumptions and inputs.
      To project future 2017 baseline EGU emissions for the CSAPR Update, the EPA adjusted the 2018 IPM version 5.15 base case results to account for three categories of differences between 2017 and 2018. The categories are: 1) adjusting NOX emissions for units with SCRs in 2018 but that are assumed not to operate or be installed in 2017; 2) adding NOX emissions for units that are retiring in 2018 but are projected to operate in 2017; and 3) adjusting NOX emissions for coal-fired units that are projected to convert to natural gas (i.e., "coal-to-gas") in 2018, but are still projected to burn coal in 2017. These adjustments are discussed in greater detail in the IPM documentation found in the docket for this final rule.
      The IPM version 5.15 base case accounts for comments received as a result of the NODAs released in 2013, 2014, and 2015. This base case also accounts for comments received on the proposed CSAPR Update as well as updated environmental regulations. Unlike the modeling for the proposed rule, which was conducted prior to the D.C. Circuit's issuance of EME Homer City II, this projected base case accounts for compliance with the original CSAPR by including as constraints all original CSAPR emission budgets with the exception of remanded phase 2 NOX ozone season emission budgets for 11 states and phase 2 NOX ozone season emission budgets for four additional states that were finalized in the original CSAPR supplemental rule.[,] Specifically, to reflect original CSAPR ozone season NOX requirements, the modeling includes as constraints the original CSAPR NOX ozone season emission budgets for 10 states -- Alabama, Arkansas, Georgia, Illinois, Indiana, Kentucky, Louisiana, Mississippi, Missouri, and Tennessee.
      The IPM projected base case also accounts for the effects of the finalized and effective MATS, New Source Review settlements, and on-the-books state rules through February 1, 2016 impacting SO2, NOX, directly emitted particulate matter, and CO2, and final actions the EPA has taken to implement the Regional Haze Rule. The EPA's IPM base case also includes two federal non-air rules affecting EGUs: the Cooling Water Intake Structure (Clean Water Act section 316(b)) rule and the Coal Combustion Residuals (CCR) rule. The IPM modeling performed for the final CSAPR Update does not include the final Clean Power Plan (CPP). Documentation of IPM version 5.15 is in the docket and available online at www.epa.gov/airmarkets/power-sector-modeling.
Comment: Many comments requested that the agency not include the CPP in the 2017 projections informing policy decisions in this rule. This was in response to our discussion of this topic and request for comment in the proposal preamble and a memorandum to the docket (hereinafter referred to as the "Harvey Memo").  Commenters cited discrete CPP-related outputs in the 2017 modeling results, such as the retirement of model plants, for the proposed CSAPR Update and provided information indicating that retirements of the actual plants represented in the model were not expected to occur by 2017. Commenters specifically requested that EPA should not include the CPP in the base case modeling.
Response: We agree that the CPP should not be included in the base case modeling for this rule.
The EPA recognizes that, in general, including the illustrative modeling of the CPP, as a promulgated rule, in the baseline of the CSAPR Update would accord with typical practice. This typical practice is one common approach for ensuring that all power sector and air quality impacts evaluated in the CSAPR Update analysis are fully incremental to and independent of the impacts of preceding rules. However, the CSAPR requirements will be implemented at least five years before any requirements are applied to sources under the CPP, and there should be no meaningful impact of the CPP on power sector dispatch decisions in the timeframe of the CSAPR requirements, as analyzed here.
In the Harvey Memo prepared for the CSAPR Update proposal, we identified several key factors and uncertainties associated with measuring the effects of the CPP in 2017. We identified simplifying assumptions in the CPP modeling regarding the types of plans states may develop, and noted that the CPP does not have any pre-2022 requirements for sources and provides states and utilities with ample options to minimize near-term impacts. Harvey Memo, at 11-13. Therefore, we observed that in the context of the CPP, the model projected impacts in 2016-2018 are likely overstated due to the modeling structure's perfect foresight of future prices and market conditions that don't reflect real-world uncertainty. Id. at 6. We also noted the likelihood that states would choose implementation pathways that would completely avoid the actions that were forecast in the model to occur by 2018. For these reasons, the modeling results prior to 2020 were not relied upon for the CPP RIA. Id. at 13.
Commenters, particularly the regulated utilities, by and large agreed that these considerations were significant and atypical and urged the agency to exclude the CPP from the CSAPR Update modeling. Thus, while the EPA continues to believe that the modeling analysis for the CPP in the final CPP RIA was useful and reliable with respect to the model years analyzed for that rule (i.e., 2020, 2025, and 2030), we are excluding the CPP from the base case in this action.
 For further discussion of the CPP, see discussion below at Section VII.H.2; see also Harvey Memo, at 5-11.
3. Development of Emission Inventories for Non-EGU Point Sources
      The 2011 non-EGU point sources in the 2011 base case inventory match those in the proposal modeling, except for those sources that were updated as a result of comments including sources in Georgia, Illinois, North Carolina, and Oklahoma. Most changes were a result of the reclassification of sources as EGUs and amount to less than 2 percent of the non-EGU point NOX emissions in each state. The largest change in terms of overall tonnage was 2,800 tons of reduction in Texas, 1,300 of which were offset by increases to the EGU sector and 1,500 tons of which were reductions of railroad equipment emissions based on a comment from the Texas Commission on Environmental Quality. In addition to comments related to emissions, some comments on stack parameters were received and incorporated. Details on the development of the 2011 emission inventories can be found in the Final Rule Emissions Modeling TSD and the 2011NEIv2 TSD.
      Prior to air quality modeling, the emission inventories must be processed into a format that is appropriate for the air quality model to use. Details on the processing of the emissions for 2011 and on the development of the 2017 non-EGU emission inventories are available in the Final Rule Emissions Modeling TSD.
      Projection factors and percent reductions in this rule reflect comments received as a result of the August 4, 2015 NODA and the proposed CSAPR Update. Non-EGU emissions for 2017 also changed from the proposal due to a correction to the order of precedence for the application of control programs. The largest tonnage change from the projected 2017 NOX emissions in the proposal was a 2,200 ton increase in Wisconsin, an 8 percent increase. The largest percentage change to 2017 non-EGU point emissions was a 1,300 ton reduction in Oregon equivalent to 9 percent of non-EGU point emissions in the state and offset by an increase in EGU emissions. The 2017 non-EGU point emissions reflect emission reductions due to national and local rules, control programs, plant closures, consent decrees and settlements. Reductions from several Maximum Achievable Control Technology (MACT) and National Emission Standards for Hazardous Air Pollutants (NESHAP) standards are included. Projection approaches for corn ethanol and biodiesel plants, refineries and upstream impacts represent requirements pursuant to the Energy Independence and Security Act of 2007 (EISA).
      For aircraft emissions at airports, the EPA developed projection factors based on activity growth projected by the Federal Aviation Administration Terminal Area Forecast (TAF) system, published in March 2013.
      Point source and nonpoint oil and gas emissions are projected to 2018 using regional projection factors by product type using Annual Energy Outlook (AEO) 2014 projections to year 2018, the year for which all data sources needed to develop the projections were available. NOX and VOC reductions that are co-benefits to the NESHAP and New Source Performance Standards (NSPS) for Stationary Reciprocating Internal Combustion Engines (RICE) are reflected for select source categories. In addition, Natural Gas Turbines and Process Heaters NSPS NOX controls and NSPS Oil and Gas VOC controls are reflected for select source categories. The projection approach for oil and gas emissions was unchanged from that used for the proposal inventories, with the exception of changes incorporated in response to comments in Colorado, Oklahoma, Texas and Utah and due the correction of an error in the projection factors that had been applied at proposal to oil and gas emissions in Kansas. There were modest changes to NOx emissions in New Mexico and North Dakota as a result of the correction to the order of precedence in the application of control programs. Details on the development of the projected point and nonpoint oil and gas emission inventories are available in the Final Rule Emissions Modeling TSD.
4. Development of Emission Inventories for Onroad Mobile Sources
      The EPA developed the onroad mobile source emissions for states other than California using the EPA's Motor Vehicle Emissions Simulator, version 2014a (MOVES2014a), a newer version of MOVES than was used in the proposal modeling. The agency computed the emissions within SMOKE by multiplying the MOVES-based emission factors with the appropriate activity data. The agency also used MOVES emission factors to estimate emissions from refueling. Both 2011 and 2017 onroad mobile source activity data and model databases were updated for Ohio, New Jersey, North Carolina, and Texas in response to comments received on the NODA and on the proposed rule. Additional information on the approach for generating the onroad mobile source emissions is available in the Final Rule Emissions Modeling TSD. Onroad mobile source emissions for California were updated from the proposal using emissions submitted by the state in response to comments on the NODA.
      In the future-year modeling for mobile sources, the EPA included all national measures known at the time of modeling. The future scenarios for mobile sources reflect projected changes to fuel usage and onroad mobile control programs finalized as of the date of the model run. In response to comments on the NODA, the EPA developed future year onroad mobile source emission factors and activity data for the final rule modeling that directly represented the year 2017, whereas in the proposal modeling the 2017 emissions were based on adjustments to 2018 emissions. Finalized rules that are incorporated into the mobile source emissions include: Tier 3 Standards (March 2014), the Light-Duty Greenhouse Gas Rule (March 2013), Heavy (and Medium)-Duty Greenhouse Gas Rule (August 2011), the Renewable Fuel Standard (February 2010), the Light Duty Greenhouse Gas Rule (April 2010), the Corporate-Average Fuel Economy standards for 2008-2011 (April 2010), the 2007 Onroad Heavy-Duty Rule (February 2009), and the Final Mobile Source Air Toxics Rule (MSAT2) (February 2007). Impacts of rules that were in effect in 2011 are reflected in the 2011 base year emissions at a level that corresponds to the extent to which each rule had penetrated into the fleet and fuel supply by the year 2011. Local control programs such as the California LEV III program are included in the onroad mobile source emissions. Activity data for onroad mobile sources was projected using AEO 2014. Updated onroad mobile source emissions in California for the final rule modeling of the year 2017 were provided by the California Air Resources Board.
5. Development of Emission Inventories for Commercial Marine Category 3 (Vessel)
      The commercial marine category 3 vessel ("C3 marine") emissions in the 2011 base case emission inventory for this rule are consistent with those in the proposal modeling and are equivalent to those in the 2011NEIv2. These emissions reflect reductions associated with the Emissions Control Area proposal to the International Maritime Organization control strategy (EPA-420-F-10-041, August 2010); reductions of NOX, VOC, and CO emissions for new C3 engines that went into effect in 2011; and fuel sulfur limits that went into effect as early as 2010. The cumulative impacts of these rules through 2017 are incorporated in the 2017 projected emissions for C3 marine sources.
6. Development of Emission Inventories for Other Nonroad Mobile Sources
      To develop the nonroad mobile source emission inventories other than C3 marine for the modeling platform, the EPA used monthly, county, and process level emissions output from the National Mobile Inventory Model (NMIM)  (http://www.epa.gov/otaq/nmim.htm). State-submitted emissions data for nonroad sources were used for Texas and California. For Texas, these emissions are consistent with those in the 2011NEIv2, while the California emissions were consistent with those used in the proposal modeling. Locomotive emissions in Texas and North Carolina in the final rule modeling incorporated updates in response to comments received on the NODA.
      In response to comments received on the NODA and the proposal, the EPA used NMIM to project nonroad mobile emissions directly to 2017, as opposed to adjusting 2018 emissions back to 2017 as was done for the proposal modeling. The nonroad mobile emission control programs include reductions to locomotives, diesel engines and marine engines, along with standards for fuel sulfur content and evaporative emissions. A comprehensive list of control programs included for mobile sources is available in the Final Rule Emissions Modeling TSD.
7. Development of Emission Inventories for Nonpoint Sources
      The emissions for stationary nonpoint sources in the 2011 base case emission inventory are largely consistent with those in the proposal modeling and in the 2011NEIv2, although some updates to Connecticut, Massachusetts, North Carolina, Texas and also to portable fuel container emissions were made in response to comments on the NODA and the proposal. For more information on the nonpoint sources in the 2011 base case inventory, see the Final Rule Emissions Modeling TSD and the 2011NEIv2 TSD.
      Where states provided the EPA with information about projected control measures or changes in nonpoint source emissions, the EPA incorporated those inputs in its projections. Updates to nonpoint emissions in North Carolina, Connecticut, Massachusetts, and Texas were incorporated in response to comments received on the NODA. The EPA included adjustments for state fuel sulfur content rules for fuel oil in the Northeast. Projected emissions for portable fuel containers reflect the impact of projection factors required by the final Mobile Source Air Toxics (MSAT2) rule and the EISA, including updates to cellulosic ethanol plants, ethanol transport working losses, and ethanol distribution vapor losses.
      For the final rule, emissions for nonpoint oil and gas sources were updated in Colorado, Texas, and Oklahoma in response to comments received on the 2015 NODA, and an error was corrected in the projections for Kansas. The EPA developed regional projection factors for nonpoint oil and gas sources by product type based on Annual Energy Outlook (AEO) 2014 projections to year 2018. The agency reflected criteria air pollutant (CAP) co-benefit reductions resulting from the National Emission Standards for Hazardous Air Pollutants (NESHAP) for Reciprocating Internal Combustion Engines (RICE) and NSPS rules and Oil and Gas NSPS VOC controls for select source categories. Additional details on the projections are available in the Final Rule Emissions Modeling TSD.
C. Definition of Nonattainment and Maintenance Receptors
      In this section, the EPA describes how it determines locations where nonattainment or maintenance problems are expected for the 2008 8-hour ozone NAAQS in the 2017 analytic future year chosen for this rule. The EPA then describes how it factored current monitored data into the identification of sites as having either nonattainment or maintenance concerns for the purposes of this rulemaking. These sites are used as the "receptors" for quantifying the contributions of emissions in upwind states to nonattainment and maintenance concerns in downwind locations.
      In this rule, the EPA is relying on the CSAPR approach (as described below) to identify separate nonattainment and maintenance receptors in order to give independent effect to both the "contribute significantly to nonattainment" and the "interfere with maintenance" prongs of section 110(a)(2)(D)(i)(I), consistent with the D.C. Circuit's direction in North Carolina. In its decision on remand from the Supreme Court, the D.C. Circuit confirmed that the EPA's approach to identifying maintenance receptors in CSAPR comported with the court's prior instruction to give independent meaning to the "interfere with maintenance" prong in the good neighbor provision. EME Homer City II, 795 F.3d at 136.
      In CSAPR, the EPA identified nonattainment receptors as those monitoring sites that are projected to have average design values that exceed the NAAQS. The EPA separately identified maintenance receptors as those receptors that would have difficulty maintaining the relevant NAAQS in a scenario that takes into account historical variability in air quality at that receptor. The original CSAPR approach for identifying nonattainment and maintenance receptors relied only upon air quality model projections of measured design values. In the original CSAPR, if the average design value in the analysis year was projected to exceed the NAAQS, then the monitoring site was identified as a nonattainment receptor without consideration of whether the monitoring site is currently measuring "clean data" (i.e., design values below the NAAQS based on the most recent three years of measured data). In prior transport rulemakings, such as the NOX SIP Call and CAIR, the EPA defined nonattainment receptors as those areas that both currently monitor nonattainment and that the EPA projects will be in nonattainment in the future compliance year. The EPA explained that it had the most confidence in its projections of nonattainment for those counties that also measure nonattainment for the most recent period of available ambient data. In the original CSAPR, the EPA was compelled to deviate from this practice of incorporating monitored data into its evaluation of projected nonattainment receptors because the most recent monitoring data then available reflected large emission reductions from CAIR, which the original CSAPR was designed to replace. As recently affirmed by the D.C. Circuit, it was therefore reasonable for the EPA to decide not to compare monitored data reflecting CAIR emissions reductions to its modeling projections that instead excluded CAIR from its baseline.
      As the EPA is not replacing an existing transport program in this CSAPR Update, the agency proposed to once again consider current monitored data as part of the process for identifying projected nonattainment receptors for this rulemaking. The agency received comments supporting the consideration of current monitored data for identifying projected nonattainment receptors. Thus, for the final CSAPR Update the EPA is identifying as nonattainment receptors those monitors that both currently measure nonattainment and that the EPA projects will be in nonattainment in 2017.
      As noted previously, in the original CSAPR, the EPA identified maintenance receptors as those receptors that would have difficulty maintaining the relevant NAAQS in a scenario that takes into account historical variability in air quality at that receptor. The variability in air quality was determined by evaluating the "maximum" future design value at each receptor based on a projection of the maximum measured design value over the relevant base year period.
      The EPA interprets the projected maximum future design value to be a potential future air quality outcome consistent with the meteorology that yielded maximum measured concentrations in the ambient data set analyzed for that receptor. The EPA also recognizes that previously experienced meteorological conditions (e.g., dominant wind direction, temperatures, air mass patterns) promoting ozone formation that led to maximum concentrations in the measured data may reoccur in the future. Therefore, the maximum design value gives a reasonable projection of future air quality at the receptor under a scenario in which such conditions do, in fact, reoccur. The projected maximum design value is used to identify upwind states whose emissions, under those circumstances, could interfere with the downwind area's ability to maintain the NAAQS.
      For the final CSAPR Update, the EPA assesses the magnitude of the maximum projected design value for 2017 at each receptor in relation to the 2008 ozone NAAQS and, where such a value exceeds the NAAQS, the EPA determines that receptor to be a "maintenance" receptor for purposes of defining interference with maintenance, consistent with the method used in CSAPR and upheld by the D.C. Circuit in EME Homer City II. That is, monitoring sites with a maximum projected design value that exceeds the NAAQS are projected to have a maintenance problem in 2017.
      In addition, those sites that are currently measuring clean data, but are projected to be nonattainment based on the average design value (and that, by definition, are projected to have a maximum design value above the standard) are also identified as maintenance-only receptors. Unlike nonattainment receptors, current clean monitored data does not disqualify a receptor from being identified as a maintenance receptor because the possibility of failing to maintain the NAAQS in the future, even in the face of current attainment of the NAAQS, is exactly what the maintenance prong of the good neighbor provision is designed to guard against.
      Comment: The agency received comments that the EPA should not include as a downwind receptor any site that is currently measuring clean data. Commenters also raise concerns with the EPA's reliance on the projected maximum design value to determine whether an area should be identified as a maintenance receptor, particularly where the projected average design value is below the NAAQS. The commenters contend that this approach does not take into account the nationwide trend toward decreasing ozone design values and improving ozone air quality.
      Response:  The EPA disagrees with this comment based on several factors. First, current (i.e., 2013-2015) ozone design values in many portions of the eastern U.S. may be lower than what might otherwise have been expected due to cooler than normal temperatures during the summers of 2013, 2014, and 2015 which led to meteorological conditions which were generally unfavorable for the formation of high ozone concentrations. An examination of historical inter-annual variability in summer meteorological conditions in the East indicates that in spite of the relatively non-conducive meteorological conditions seen in the last 3 years, conditions more favorable to ozone formation have often occurred in the past and are likely to reoccur in the future, therefore leading to the risk of a violation of the NAAQS. See the AQM TSD for more details.
      Second, ambient monitoring data for maintenance sites that are currently measuring attainment suggest that these sites are at risk of violating the NAAQS. Table V.D-3 provides the 2013-2015 design values and the 4[th] highest annual 8-hour daily maximum ozone concentrations used to calculate these design values for each of the maintenance receptors that are currently measuring attainment. The data in Table V.D-3 indicate (1) seven of the nine sites had measured 4[th] high values which exceed the level of the NAAQS in at least one of the years during this 3-year time period and (2) 4[th] high ozone concentration increased from 2014 to 2015 at all but one of these sites. There were increases in measured 4[th] high values between 2013 and 2015 at all but one of these sites (with the highest increase of 22 ppb occurring in Harris County TX), despite the fact that ozone precursor emissions are continuing to trend downward. In addition, preliminary monitoring for 2016 also indicates that ozone has increased, based on 4[th] high values, in 2016 compared to the concentrations that were measured in 2014 at most of the receptor sites. This shows that the influence of meteorology on measured ozone values can overwhelm the general downward trend in emissions. Thus, given the variability of meteorological conditions, there is every reason to believe that these maintenance sites that are currently measuring attainment are at risk of violating the NAAQS in 2017, as projected by the EPA's modeling.
      The EPA believes it is therefore appropriate and reasonable to use the maximum design value to identify receptors that may have maintenance problems in the future. This approach uses measured data in order to establish potential air quality outcomes at each receptor that take into account the variable meteorological conditions present across the entire period of measured data (2009 to 2013). The EPA interprets the maximum future design value to be a potential future air quality outcome consistent with the meteorology that yielded maximum measured concentrations in the ambient data set analyzed for that receptor. The EPA construes the average design value at a receptor to be a reasonable projection of future air quality in that area under "average" conditions. However, the EPA also recognizes that previously experienced meteorological conditions (e.g., dominant wind direction, temperatures, air mass patterns) that promote ozone formation, may recur in the future. The maximum design value gives a reasonable projection of future air quality at the receptor under a scenario in which such conditions do, in fact, recur. It also identifies upwind emissions that under those circumstances could interfere with the downwind area's ability to maintain the NAAQS.
D. Air Quality Modeling to Identify Nonattainment and Maintenance Receptors
      The following is a brief summary of the procedures for projecting future-year 8-hour ozone average and maximum design values to 2017 to determine nonattainment and maintenance receptors. Consistent with the EPA's modeling guidance the agency uses the air quality modeling results in a "relative" sense to project future concentrations. That is, the ratios of future year model predictions to base year model predictions are used to adjust ambient ozone design values up or down depending on the relative (percent) change in model predictions for each location. The modeling guidance recommends using measured ozone concentrations for the 5-year period centered on the base year as the air quality data starting point for future year projections. This average design value is used to dampen the effects of inter-annual variability in meteorology on ozone concentrations and to provide a reasonable projection of future air quality at the receptor under "average" conditions. Because the base year for this rule is 2011, the EPA is using the base period 2009-2013 ambient ozone design value data in order to project 2017 average design values in a manner consistent with the modeling guidance.
      The approach for projecting future ozone design values involved the projection of an average of up to 3 design value periods, which include the years 2009-2013 (design values for 2009-2011, 2010-2012, and 2011-2013). The 2009 - 2011, 2010-2012, and 2011-2013 design values are accessible at www.epa.gov/airtrends/values.html. The average of the 3 design values creates a "5-year weighted average" value. The 5-year weighted average values were then projected to 2017. To project 8-hour ozone design values, the agency used the 2011 base year and 2017 future base-case model-predicted ozone concentrations to calculate relative response factors (RRFs) for the location of each monitoring site. The RRFs were applied to the 2009-2013 average ozone design values and the individual design values for 2009-2011, 2010-2012, and 2011-2013. Details of this approach are provided in the AQM TSD.
      Projected design values that are greater than or equal to 76.0 ppb are considered to be violating the NAAQS in 2017. As noted previously, nonattainment receptors are those sites that are violating the NAAQS based on the most recent measured air quality data and also have projected average design values of 76.0 ppb or greater. Therefore, as an additional step, for those sites that are projected to be violating the NAAQS based on the average design values in 2017, the EPA examined the most recent measured design value data to determine if the site was currently violating the NAAQS. For the final rule, the agency examined ambient data for the 2013-2015 period, which is the most recent available measured design values at the time of this rule.
      Maintenance-only receptors therefore include both (1) those sites with projected average design values above the NAAQS that are currently measuring clean data, and (2) those sites with projected average design values below the level of the NAAQS, but with projected maximum design values of 76.0 ppb or greater. The EPA notes that the 2017 ozone nonattainment receptors are inclusive of areas that, in addition to having projected nonattainment, may have maintenance issues in the future, since the maximum design values for each of these sites is always greater than or equal to the average design value.
      Table V.D-1 contains the ambient 2009-2013 base period average and maximum 8-hour ozone design values, the 2017 projected baseline average and maximum design values, and the ambient 2013-2015 design values for the 6 sites in the eastern U.S. projected to be 2017 nonattainment receptors. Table V.D-2 contains this same information for the 13 maintenance-only sites in the eastern U.S. The design values for all monitoring sites in the U.S. are provided in docket.
Table V.D-1. Average and Maximum 2009-2013 and 2017 Baseline 8-Hour Ozone Design Values and 2013-2015 Design Values (ppb) at Projected Nonattainment Sites in the Eastern U.S. (Nonattainment Receptors)
                                  Monitor ID
                                     State
                                    County
                        Average Design Value 2009-2013
                        Maximum Design Value 2009-2013
                           Average Design Value 2017
                           Maximum Design Value 2017
                            2013-2015 Design Value
                                                                      090019003
Connecticut
Fairfield
                                     83.7
                                      87
                                     76.5
                                     79.5
                                      84
                                                                      090099002
Connecticut
New Haven
                                     85.7
                                      89
                                     76.2
                                     79.2
                                      78
                                                                      480391004
Texas
Brazoria
                                     88.0
                                      89
                                     79.9
                                     80.8
                                      80
                                                                      484392003
Texas
Tarrant
                                     87.3
                                      90
                                     77.3
                                     79.7
                                      76
                                                                      484393009
Texas
Tarrant
                                     86.0
                                      86
                                     76.4
                                     76.4
                                      78
                                                                      551170006
Wisconsin
Sheboygan
                                     84.3
                                      87
                                     76.2
                                     78.7
                                      77

Table V.D-2. Average and Maximum 2009-2013 and 2017 Baseline 8-Hour Ozone Design Values and 2013-2015 Design Values (ppb) at Sites in the Eastern U.S. that are Projected Maintenance-Only Receptors
                                  Monitor ID
                                     State
                                    County
                        Average Design Value 2009-2013
                        Maximum Design Value 2009-2013
                           Average Design Value 2017
                           Maximum Design Value 2017
                            2013-2015 Design Value
                                                                      090010017
Connecticut
Fairfield
                                     80.3
                                      83
                                     74.1
                                     76.6
                                      81
                                                                      090013007
Connecticut
Fairfield
                                     84.3
                                      89
                                     75.5
                                     79.7
                                      83
                                                                      211110067
Kentucky
Jefferson
                                     85.0
                                      85
                                     76.9
                                     76.9
                                      N/A
                                                                      240251001
Maryland
Harford
                                     90.0
                                      93
                                     78.8
                                     81.4
                                      71
                                                                      260050003
Michigan
Allegan
                                     82.7
                                      86
                                     74.7
                                     77.7
                                      75
                                                                      360850067
New York
Richmond
                                     81.3
                                      83
                                     75.8
                                     77.4
                                      74
                                                                      361030002
New York
Suffolk
                                     83.3
                                      85
                                     76.8
                                     78.4
                                      72
                                                                      390610006
Ohio
Hamilton
                                     82.0
                                      85
                                     74.6
                                     77.4
                                      70
                                                                      421010024
Pennsylvania
Philadelphia
                                     83.3
                                      87
                                     73.6
                                     76.9
                                      73
                                                                      481210034
Texas
Denton
                                     84.3
                                      87
                                     75.0
                                     77.4
                                      83
                                                                      482010024
Texas
Harris
                                     80.3
                                      83
                                     75.4
                                     77.9
                                      79
                                                                      482011034
Texas
Harris
                                     81.0
                                      82
                                     75.7
                                     76.6
                                      74
                                                                      482011039
Texas
Harris
                                     82.0
                                      84
                                     76.9
                                     78.8
                                      69

Table V.D-3. Ambient Ozone Design Values for 2013-2015 and the 4[th] Highest 8-Hour Daily Maximum Ozone Concentrations (ppb) for Each Maintenance-Only Receptor that is Currently Measuring Attainment.

                                  Monitor ID
                                     State
                                    County
                            2013-2015 Design Value
                            2013 4th Highest Value
                            2014 4th Highest Value
                            2015 4th Highest Value
211110067
Kentucky
Jefferson
                                      N/A
                                      N/A
                                      70
                                      76*
240251001
Maryland
Harford
                                      71
                                      72
                                      67
                                      74
260050003
Michigan
Allegan
                                      75
                                      78*
                                      77*
                                      72
360850067
New York
Richmond
                                      74
                                      69
                                      68
                                      77*
361030002
New York
Suffolk
                                      72
                                      72
                                      66
                                      78*
390610006
Ohio
Hamilton
                                      70
                                      69
                                      70
                                      72
421010024
Pennsylvania
Philadelphia
                                      73
                                      68
                                      72
                                      79*
482011034
Texas
Harris
                                      74
                                      69
                                      66
                                      88*
482011039
Texas
Harris
                                      69
                                      69
                                      63
                                      77*
*Indicates 4[th] highest values that exceed the NAAQS.

Comment: The EPA received comments on the approach for projecting future year design values for monitoring sites located in certain coastal areas (i.e., monitoring sites located in southern Connecticut along Long Island Sound, in Wisconsin and Michigan along Lake Michigan and in Maryland along the Chesapeake Bay). Some commenters said that the relative response factors for coastal sites should be based on modeled ozone in the grid cell containing the monitoring site or "land" cells only, rather than the grid cell with the highest 2011 base case modeled value from among the 3 by 3 matrix of grid cells surrounding the monitoring site (i.e., the 3 x 3 matrix approach). Some commenters said that using the 3 x 3 approach for coastal sites can result in the use of modeled data from grid cells over water, which the commenters claim are not representative of the location of the monitor. These commenters contend that modeled values from "over water" cells are biased high and will overstate projected 2017 design values at coastal sites. In this regard, the commenters said EPA should consider using the modeled data in the grid cell containing the monitoring site or use the highest value in "over land" grid cells adjacent to the monitoring site.
       Commenters examined model performance in the grid cell that contained the monitor and also compared these measured values to the "highest" modeled value in the 3 x 3 grid cell matrix surrounding the monitoring site. They contend that higher modeled ozone concentrations from the 3 x 3 matrix overstate concentrations measured at the monitoring site and, as a result, commenters claim that using the 3 x 3 modeled values will lead to inaccurate future model projections.
Response: EPA first notes that the modeling guidance recommends calculating relative response factors based on the highest values in the vicinity of the monitoring site (i.e., the 3 x 3 matrix approach) in part because limitations in the inputs and model physics can affect model precision at the grid cell level. Allowing some leeway in the precision of the predicted location of daily maximum ozone concentrations can help assure that possibly artificial, fine scale variations do not inadvertently impact an assessment of modeled ozone response. In addition, monitors are sometimes located very close to the border of two or more grid cells. For both of these reasons, choosing to calculate the model response from the nearby grid cell with the highest modeled ozone value is likely to be most representative of model response during high measured ozone conditions. In addition, coastal sites by the nature of their location near large water bodies often measure ozone concentrations in air from over the water when winds are blowing from the water to the land. Such wind flows can occur as part of a broader "synoptic scale" wind pattern and/or during more local scale onshore wind flows associated with a "sea breeze", "sound breeze", "lake breeze", or "bay breeze" depending on the nature of the adjacent body of water. Thus, it is appropriate to consider modeled values from both "over water" and "over land" grid cells to represent ozone concentrations which may impact monitoring sites in coastal areas.
      The commenters also compared measured ozone values at monitoring locations to the highest modeled concentrations in the 3 x 3 grid cells surrounding the monitor and found that modeled ozone in grid cells over the water (where there are no monitoring sites) often "over predicted" the measured values at the monitors. The commenters claim that this will lead to an overstatement of future year design values and inaccurate future year values. The EPA finds no basis for this conclusion. First, the components of the modeling system used for this final rule, (i.e., the photochemical grid model, the meteorological model, emissions models, and input data) are based on state-of-the-science methods and data that are designed to represent the physical and chemical processes associated with the formation, transport, and fate of ozone and precursor pollutants. The intent of the model evaluation is to use available measurements to gain confidence in the use of the modeling system not only to predict concentrations for times and locations where there are measurements, but also to provide credible estimates of base year concentrations in other locations which can be used to project future year concentrations. Second, the EPA is not using the absolute modeled concentrations to determine future year (2017) design values. As described in the preamble and the AQM TSD, the EPA projects future year design values based on the percent change (i.e., relative response) in ozone using predictions from a model simulation for 2011 and predictions from a corresponding model simulation for 2017. The relative response factors based on the modeled data from the 3 x 3 matrix approach are applied to measured ozone design value.
		For the final rule, the EPA performed an analysis that compared the 2017 projected design values based on applying the 3 x 3 matrix approach recommended in EPA's modeling guidance to an approach that relies exclusively on modeled values in the grid cell containing the monitoring  (i.e., monitor-cell approach). This analysis was performed for ozone monitoring sites nationwide including the coastal sites of concern to commenters. A data file with the projected 2017 design values using the 3 x 3 matrix approach and the monitor-cell approach at individual monitoring sites can be found in the docket.
In our analysis we examined the data separately for each of four groupings of monitoring sites: (1) all sites nationwide, (2) all sites in the East, (3) all nonattainment and maintenance receptors identified in this rule, and (4) the set of coastal sites of particular concern to the commenters together with a coastal site in Harford Co., MD that is also receptor for this final rule. The specific set of 8 coastal sites analyzed as a separate group include Fairfield Co., CT sites 090010017, 090013007, and 090019003, New Haven Co., CT 090093002, Baltimore Co., MD 240053001, Harford Co., MD 240251001, Allegan Co., MI, 260050003, and Sheboygan Co, WI 551170006. Note that all of these sites, except for the site in Baltimore Co., MD are receptors for this final rule. The results indicate that the 3 x 3 approach results in lower or equivalent projected 2017 design values compared to the monitor-cell approach at 76 percent of the monitoring sites nationwide. That is, at a majority of the monitoring sites, the 3 x 3 approach which relies on the highest base year concentrations in the vicinity of the monitoring site tends to be more responsive to emissions reductions than only using data from the grid cell containing the monitor. For the Eastern U.S., 75 percent of the monitoring sites had lower projected 2017 design values with the 3 x 3 approach, compared to the monitor-cell approach. At 14 of the 19 nonattainment and maintenance receptors for this rule, the 3 x 3 approach design value is either lower or within 0.5 ppb of the corresponding value from the monitor-cell approach. Finally, for the 8 coastal sites, the 3 x 3 approach on balance does not result in an overall notable bias compared to the monitor-cell approach. Specifically, at half of these sites the 3 x 3 approach design value is lower or within 0.5 ppb of the corresponding value from the monitor-cell approach. EPA does not believe that it would be appropriate to use the 3 x 3 approach for some coastal receptors and the single monitor-cell approach for other coastal receptors, depending solely on the outcome as to which approach yields lower future design value at an individual receptor site. Based on the results of this analysis the EPA continues to believe that the 3 x 3 approach is appropriate for projecting design values for this rule and provides for regional consistency in the projection methodology across all sites.
      Comment: Commenters contend that the EPA is not appropriately considering international emissions in the process of identifying downwind nonattainment and maintenance receptors.  The commenters cite CAA section 179B and contend that it requires the Administrator to approve plans that would be sufficient to attain or maintain the NAAQS but for emissions emanating from outside of the U.S. They therefore contend that, where a receptor in the EPA's modeling would attain or maintain the standard when international emissions are accounted for, the EPA has no authority to require emissions from upwind states pursuant to section 110(a)(2)(D)(i)(I). Commenters state that such reduction requirements would constitute the over-control of emissions from upwind states.
      The commenters explicitly recommend that the EPA exclude the projected contributions from Canada and Mexico from the projected design values before comparing the projections to the NAAQS for purposes of identifying receptors. Commenters further recommend that the EPA exclude a "conservatively calculated" 5 percent of EPA-estimated contributions attributable to the anthropogenic fraction of boundary concentrations. The commenters propose that this approach would result in fewer receptors and relieve upwind states of the obligation to make emission reductions associated with these receptors.
      Response:  The EPA disagrees with commenters that section 179B of the Clean Air Act obviates the good neighbor obligations imposed upon states by section 110(a)(2)(D)(i)(I) of the Act.
      First, commenters misunderstand the provisions of section 179B. Section 179B permits the EPA to approve an attainment plan or plan revision for areas that could attain the relevant NAAQS by the statutory attainment date "but for" emissions emanating from outside the U.S.  When applicable, this CAA provision relieves states from imposing control measures on emissions sources in the state's jurisdiction beyond those necessary to address reasonably controllable emissions from within the U.S. Specifically, CAA section 179B(a) provides that the EPA shall approve a plan for such an area if: (i) the plan meets all other applicable requirements of the CAA, and (ii) the submitting state can satisfactorily demonstrate that "but for emissions emanating from outside the United States," the area would attain and maintain the relevant NAAQS. In addition, CAA section 179B(b) applies specifically to the ozone NAAQS and provides that if a state demonstrates that an ozone nonattainment area would have timely attained the NAAQS by the applicable attainment date "but for emissions emanating from outside of the United States," then the area can avoid extension of the ozone attainment dates pursuant to CAA section 181(a)(5), the application of fee provisions of CAA section 185, and the mandatory reclassification provisions under CAA section 181(b)(2) for areas that fail to attain the ozone NAAQS by the applicable attainment date.
      Commenters fail to acknowledge that, even if an area is impacted by emissions from outside the U.S., CAA section 179B does not affect the designations process.  The designations process is meant to protect public health and welfare. Designating an area nonattainment for a particular NAAQS ensures that the public is informed that the air quality in a specific area exceeds the standard. Congress determined that in nonattainment areas, there should be adequate safeguards to protect public health and welfare. For example Congress required such areas to have nonattainment new source review permitting programs, to ensure that air quality is not further degraded. Accordingly, areas with design values above the NAAQS are designated nonattainment and classified with a classification as indicated by actual ambient air quality. As a result of designation and classification, the state is subject to the applicable requirements, including nonattainment new source review, conformity, and other measures prescribed for nonattainment areas by the CAA. Section 179B of the CAA does not provide for any relaxation of mandatory emissions control measures (including contingency measures) or the prescribed emissions reductions; it only eliminates the obligation for an attainment demonstration that demonstrates attainment and maintenance of the NAAQS, which is conditioned upon the state meeting all other attainment plan requirements, and voids certain consequences of an area's failure to attain, including mandatory reclassifications.
      CAA section 179B also does not alter the CAA's general construct expressed in subpart 1 of part D that states with nonattainment areas are expected to adopt reasonable emissions controls to lessen emissions of criteria pollutants to promote citizen health protection. The construct ensures that states will take reasonable actions to mitigate the public health impacts of exposure to ambient levels of pollution that violate the NAAQS by imposing reasonable control measures on the sources that are within the jurisdiction of the state regardless of impacts from interstate or international emissions. The primary purpose of part D of Title I of the CAA is to achieve emission reductions so that people living in a nonattainment area receive the public health protection intended by the NAAQS.
      In sum, section 179B provides an important tool that provides states relief from the requirement to demonstrate attainment -- and from the more stringent planning requirements that would result from failure to attain -- in areas where, even though the air agency has taken appropriate measures to address air quality in the influenced area, emissions from outside of the U.S. prevent attainment. The provision does not absolve states of the obligation to impose reasonable emission controls even where states can demonstrate that the area would attain "but for" the impact of international emissions. The commenters do not explain why, given the obligation of downwind states with designated nonattainment areas to impose reasonable controls on emissions, upwind states should not also be subject to a similar obligation to take certain reasonable steps to reduce emissions impacting those downwind areas.
      The commenters have not explained why the terms of section 179B require its application to EPA's evaluation of upwind state's interstate transport obligations. Section 179B is located in subpart D of title I, which addresses plan requirements for designated nonattainment areas. As just described, the specific terms of section 179B outline which nonattainment area requirements will and will not apply upon approval of a section 179B demonstration, none of which apply directly to upwind states via section 110(a)(2)(D)(i)(I). In particular, the good neighbor provision does not require upwind areas to "demonstrate attainment and maintenance" of the NAAQS. Rather, the statute requires upwind states to prohibit emissions which will "contribute significantly to nonattainment" or "interfere with maintenance" of a NAAQS.  As discussed further in section IV.B.1, while upwind states must address their fair share of downwind air quality problems, the EPA has not interpreted this provision to hold upwind areas responsible for bringing downwind areas into attainment. Therefore, the relief provided by section 179B(a) and (b) from the obligation to demonstrate attainment, extension of the attainment date, and mandatory reclassifications, is simply not applicable to downwind states.
      Even if section 179B were in some manner applicable to upwind states' transport obligations, the EPA does not believe that the contribution of international emissions should impact EPA's identification of downwind nonattainment and maintenance receptors affected by the interstate transport of emissions.  These receptors represent areas that the EPA projects will have difficulty attaining and maintaining the NAAQS, and which therefore require adequate safeguards to protect public health and welfare. The EPA therefore does not agree that, when identifying downwind air quality problems for purposes of interstate transport, section 179B requires that we subtract the contributions of international emissions from the projected design values. This would be inconsistent with EPA's approach to area designations and is simply not required by the plain language of the statute. Moreover, such an interpretation would allow downwind and upwind areas to make no efforts to address clear violations of the NAAQS, leaving the area's citizens to suffer the health and environmental consequences of such inaction.
      Moreover, just as any state with a nonattainment area  -  including downwind states  -  must take reasonable steps to control emissions even where an area is impacted by international emissions, the EPA believes that it is appropriate for upwind states to also adopt reasonable emissions controls to lessen the impact of emissions generated in their state and subsequently transported to downwind areas.  As noted in Section IV of the preamble, the EPA does not view the obligation under the good neighbor provision as a requirement for upwind states to bear all of the burden for resolving downwind air quality problems. Rather, it is an obligation that upwind and downwind states share responsibility for addressing air quality problems.  If, after implementation of reasonable emissions reductions by an upwind state, a downwind air quality problem persists, whether due to international emissions or emissions originating within the downwind state, the EPA can relieve the upwind state of the obligation to make additional reductions to address that air quality problem. But the statute does not absolve the upwind state of the obligation to make reasonable reductions in the first instance.
      The EPA took just such an approach in the original CSAPR rulemaking when calculating annual SO2 emissions budgets for states linked to downwind PM2.5 air quality problems. There, the EPA imposed budgets based on a level of control stringency equivalent to $2,300 per ton of SO2 emissions. Despite the persistence of downwind air quality problems to which certain upwind states were linked, the EPA concluded that this level of control stringency represented the upwind states' full transport obligation with respect to the PM2.5 standards and additional controls were not reasonable because significant reductions could not be achieved at higher costs. 76 FR 48208, 48257-259.
      Accordingly, the EPA also does not agree that imposing emission reductions on upwind states linked to areas affected by international emissions based on the implementation of reasonable control measures would result in over-control.  As discussed in section VII.D of the preamble, the emissions reductions required by this rulemaking are based on relatively modest investments in turning on and optimizing already existing SCRS and installing a limited amount of combustion controls, which is feasibly and reasonably achieved by the 2017 ozone season. Moreover, the emissions reductions required by this rulemaking do not fully resolve most of the air quality problems identified in this rule.  As discussed further in section VI.D, the D.C. Circuit has identified those circumstances that would constitute over-control pursuant to CAA section 110(a)(2)(D)(i)(I), and those circumstances are not present here.
E. Pollutant Transport from Upwind States
1. Air Quality Modeling to Quantify Upwind State Contributions
      This section documents the procedures the EPA used to quantify the impact of emissions from specific upwind states on 2017 8-hour design values for identified downwind nonattainment and maintenance receptors. The EPA used CAMx photochemical source apportionment modeling to quantify the impact of emissions in specific upwind states on downwind nonattainment and maintenance receptors for 8-hour ozone. CAMx employs enhanced source apportionment techniques that track the formation and transport of ozone from specific emissions sources and calculates the contribution of sources and precursors (NOX and VOC) to ozone for individual receptor locations. The strength of the photochemical model source apportionment technique is that all modeled ozone at a given receptor location in the modeling domain is tracked back to specific sources of emissions and boundary conditions to fully characterize culpable sources.
      The EPA performed nationwide, state-level ozone source apportionment modeling using the CAMx Ozone Source Apportionment Technology/Anthropogenic Precursor Culpability Analysis (OSAT/APCA) technique to quantify the contribution of 2017 baseline NOX and VOC emissions from all sources in each state to projected 2017 ozone concentrations at air quality monitoring sites. The EPA continues to believe that the OSAT/APCA tool is the most appropriate source apportionment technique for quantifying contributions for the purposes of this rule because it is constructed to provide source culpability data to inform the design of emissions control strategies. In the source apportionment model run, the EPA tracked the ozone formed from each of the following contribution categories (i.e., "tags"):
*	States  -  anthropogenic NOX and VOC emissions from each state 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;
*	Tribes  -  the emissions from those tribal lands with point source inventory data in the 2011 NEI (contributions from individual tribes were not modeled);
*	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 contribution modeling provided contributions to ozone from anthropogenic NOX and VOC emissions in each state, individually. The contributions to ozone from chemical reactions between biogenic NOX and VOC emissions were modeled and assigned to the "biogenic" category. The contributions from wild fire and prescribed fire NOX and VOC emissions were modeled and assigned to the "fires" category. The contributions from the "biogenic", "offshore", and "fires" categories are not assigned to individual states nor are they included in the state contributions.
      The CAMx OSAT/APCA model run was performed for the period May 1 through September 30 using the projected 2017 baseline emissions and 2011 meteorology for this time period. The hourly contributions 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 2017 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 on the days with high modeled concentrations in 2017 were then applied in a relative sense to quantify the contributions to the 2017 average design value at each site. The resulting 2017 average contributions from each tag to each monitoring site in the eastern and western U.S. along with additional details on the source apportionment modeling and the procedures for calculating contributions can be found in the AQM TSD.
      The average contribution metric is intended to provide a reasonable representation of the contribution from individual states to the projected 2017 design value, based on modeled transport patterns and other meteorological conditions generally associated with modeled high ozone concentrations at the receptor. An average contribution metric constructed in this manner is beneficial since the magnitude of the contributions is directly related to the magnitude of the design value at each site.
	The largest contribution from each state in the East to any single 8-hour ozone nonattainment receptor in a downwind state is provided in Table V.E-1. The largest contribution from each state in the East to any single 8-hour ozone maintenance-only receptor in a downwind state is also provided in Table V.E-1.
Table V.E-1. Largest Contribution to Downwind 8-Hour Ozone Nonattainment and Maintenance Receptors for Each State in the Eastern U.S.

                                 Upwind State
        Largest Downwind Contribution to Nonattainment Receptors (ppb)
         Largest Downwind Contribution to Maintenance Receptors (ppb)
                                      AL
                                     0.99
                                     0.73
                                      AR
                                     1.00
                                     2.07
                                      CT
                                     0.00
                                     0.46
                                      DE
                                     0.38
                                     1.32
                                      DC
                                     0.07
                                     0.86
                                      FL
                                     0.71
                                     0.75
                                      GA
                                     0.60
                                     0.62
                                      IL
                                     17.90
                                     23.61
                                      IN
                                     6.49
                                     12.32
                                      IA
                                     0.58
                                     0.81
                                      KS
                                     1.13
                                     1.22
                                      KY
                                     0.68
                                     10.88
                                      LA
                                     3.01
                                     3.20
                                      ME
                                     0.00
                                     0.01
                                      MD
                                     2.12
                                     5.22
                                      MA
                                     0.12
                                     0.06
                                      MI
                                     2.62
                                     1.27
                                      MN
                                     0.40
                                     0.36
                                      MS
                                     0.81
                                     0.79
                                      MO
                                     1.67
                                     3.78
                                      NE
                                     0.35
                                     0.27
                                      NH
                                     0.02
                                     0.02
                                      NJ
                                     9.52
                                     11.90
                                      NY
                                     18.50
                                     18.81
                                      NC
                                     0.51
                                     0.50
                                      ND
                                     0.06
                                     0.22
                                      OH
                                     1.83
                                     3.78
                                      OK
                                     2.24
                                     1.62
                                      PA
                                     9.28
                                     14.61
                                      RI
                                     0.03
                                     0.01
                                      SC
                                     0.15
                                     0.30
                                      SD
                                     0.08
                                     0.12
                                      TN
                                     0.50
                                     1.82
                                      TX
                                     2.18
                                     2.64
                                      VT
                                     0.01
                                     0.01
                                      VA
                                     1.92
                                     5.21
                                      WV
                                     1.04
                                     3.31
                                      WI
                                     0.33
                                     2.52

2. Application of Screening Threshold
      Once the EPA  has quantified the magnitude of the contributions from each upwind state to downwind nonattainment and maintenance receptors, it then uses an air quality screening threshold to identify upwind states that contribute to downwind ozone concentrations in amounts sufficient to "link" them to the downwind nonattainment and maintenance receptors and justify further analysis of potential emission reductions to address significant contribution to nonattainment and interference with maintenance of the 2008 ozone NAAQS in other states. As discussed previously in section IV, the EPA is establishing an air quality screening threshold calculated as one percent of the 2008 ozone NAAQS. Specifically, the agency has calculated an 8-hour ozone value for this air quality threshold of 0.75 ppb.
      States in the East whose contributions to a specific receptor meet or exceed the screening threshold are considered linked to that receptor; those states' ozone contributions and emissions (and available emission reductions) are analyzed further, as described in section VI, to determine whether and what emissions reductions might be required from each state. States in the East whose contributions are below the threshold are not included in the rule and are considered to make insignificant contributions to projected downwind air quality problems. Accordingly, as discussed in section IV, the EPA has determined that sources in these states need not make any further emissions reductions in order to address the good neighbor provision with respect to the 2008 ozone NAAQS.
      Based on the maximum downwind contributions identified in Table V.E-1, the following states contribute at or above the 0.75 ppb threshold to downwind nonattainment receptors: Alabama, Arkansas, Illinois, Indiana, Kansas, Louisiana, Maryland, Michigan, Mississippi, Missouri, New Jersey, New York, Ohio, Oklahoma, Pennsylvania, Texas, Virginia, and West Virginia. Based on the maximum downwind contributions in Table V.D-1, the following states contribute at or above the 0.75 ppb threshold to downwind maintenance-only receptors: Arkansas, Delaware, District of Columbia, Florida, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maryland, Michigan, Mississippi, Missouri, New Jersey, New York, Ohio, Oklahoma, Pennsylvania, Tennessee, Texas, Virginia, West Virginia, and Wisconsin. In the proposed rule North Carolina was linked to a maintenance receptor in Baltimore Co., MD (site 240053001). North Carolina was not linked to any other receptor in the proposal. In the final rule modeling, this site is no longer projected to be a receptor because the 2017 average and maximum design values for this site are projected to be below the level of the NAAQS, and North Carolina is not linked to any other nonattainment or maintenance receptor, based on the final rule modeling.
      Comment: The EPA received comments that the version of CAMx used for the proposal modeling (CAMx v6.11) did not include the most recent halogen chemistry that would affect ozone concentrations in saltwater marine atmospheres and transport of ozone from Florida to receptors in Texas. The commenter said that the EPA should include this chemistry in modeling for the final rule.
      Response: In the EPA's 2017 modeling for the final rule, Florida is modeled to have an average contribution at the 0.75 ppb threshold to the 2017 design values at two receptors in Houston (i.e., Harris County sites 482010024 and 482011034). A report by the CAMx model developer on the impact of modeling with the latest CAMx halogen chemistry indicates that the updated chemistry results in lower modeled ozone in air transported over saltwater marine environments for multiple days. Specifically, the report notes that on days with multi-day transport across the Gulf of Mexico, modeling with the updated chemistry could lower 8-hour daily maximum ozone concentrations by up to 2 to 4 ppb in locations in eastern Texas, including Houston. Air parcel trajectories for individual days used in the EPA's calculation of the contribution from Florida to the Houston receptors confirm that on days with high modeled transport from Florida to the receptors in Houston, air travels for multiple days over the Gulf of Mexico from Florida before reaching the receptors in Houston (see the AQM TSD for more details).
      In the final rule modeling, the EPA was not able to explicitly account for the updated chemistry because this chemistry had not yet been included by the model developer in the source apportionment tool in CAMx at the time the modeling was performed for this rule. However, because Florida's maximum contribution to receptors in Houston is exactly at the 0.75 ppb threshold, the agency believes that if it had performed the final rule modeling with the updated halogen chemistry, Florida's contribution would likely be below this threshold. Therefore, the EPA is not including Florida in the final rule because it finds that Florida's contribution to downwind nonattainment and maintenance receptors is insignificant when this updated halogen chemistry is considered. As described in the AQM TSD, the source-receptor transport pattern between Florida and Houston involving multi-day transport over the Gulf of Mexico is unique such that modeling with the updated halogen chemistry would not be expected to affect linkages from other upwind states to receptors in Houston or any other linkages from upwind states to downwind nonattainment and maintenance receptors for this final rule.
      Based on the EPA's application of the 0.75 ppb threshold, the linkages between each upwind state and downwind nonattainment receptors and maintenance-only receptors in the eastern U.S. are provided in Table V.E-2 and Table V.E-3, respectively.
Table V.E-2. Linkages between Each Upwind State and Downwind Nonattainment Receptors in the Eastern U.S.

                                 Upwind State
                       Downwind Nonattainment Receptors
                                      AL
Tarrant Co, TX (484392003)
Tarrant Co, TX (484393009)

                                      AR
Brazoria Co, TX (480391004)

                                      IL
Brazoria Co, TX (480391004)
Sheboygan Co, WI (551170006)

                                      IN
Fairfield Co, CT (090019003)
Sheboygan Co, WI (551170006)

                                      KS
Tarrant Co, TX (484392003)
Sheboygan Co, WI (551170006)

                                      LA
Brazoria Co, TX (480391004)
Tarrant Co, TX (484392003)
Tarrant Co, TX (484393009)

Sheboygan Co, WI (551170006)

                                      MD
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      MI
Fairfield Co, CT (090019003)
Sheboygan Co, WI (551170006)

                                      MS
Brazoria Co, TX (480391004)

                                      MO
Brazoria Co, TX (480391004)
Sheboygan Co, WI (551170006)

                                      NJ
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      NY
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      OH
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      OK
Tarrant Co, TX (484392003)
Tarrant Co, TX (484393009)
Sheboygan Co, WI (551170006)
                                      PA
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      TX
Sheboygan Co, WI (551170006)

                                      VA
Fairfield Co, CT (090019003)
New Haven Co, CT (090099002)

                                      WV
Fairfield Co, CT (090019003)

Table V.E-3. Linkages between Each Upwind States and Downwind Maintenance-Only Receptors in the Eastern U.S.

                                 Upwind State
                        Downwind Maintenance Receptors
                                      AR
Allegan Co, MI (260050003)
Harris Co, TX (482011039)

                                      DE
Philadelphia Co, PA (421010024)

                                      DC
Harford Co, MD (240251001)

                                      IL
Jefferson Co, KY (211110067)
Harford Co, MD (240251001)
Allegan Co, MI (260050003)

Suffolk Co, NY (361030002)
Hamilton Co, OH (390610006)
Philadelphia Co, PA (421010024)

Harris Co, TX (482011039)

                                      IN
Fairfield Co, CT (090013007)
Jefferson Co, KY (211110067)
Harford Co, MD (240251001)

Allegan Co, MI (260050003)
Richmond Co, NY (360850067)
Suffolk Co, NY (361030002)

Hamilton Co, OH (390610006)
Philadelphia Co, PA (421010024)

                                      IA
Allegan Co, MI (260050003)

                                      KS
Allegan Co, MI (260050003)

                                      KY
Harford Co, MD (240251001)
Richmond Co, NY (360850067)
Hamilton Co, OH (390610006)

Philadelphia Co, PA (421010024)

                                      LA
Denton Co, TX (481210034)
Harris Co, TX (482010024)
Harris Co, TX (482011034)

Harris Co, TX (482011039)

                                      MD
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Richmond Co, NY (360850067)

Suffolk Co, NY (361030002)
Philadelphia Co, PA (421010024)

                                      MI
Fairfield Co, CT (090013007)
Jefferson Co, KY (211110067)
Harford Co, MD (240251001)

Suffolk Co, NY (361030002)
Hamilton Co, OH (390610006)

                                      MS
Harris Co, TX (482011039)

                                      MO
Allegan Co, MI (260050003)
Hamilton Co, OH (390610006)
Harris Co, TX (482011034)

Harris Co, TX (482011039)

                                      NJ
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Richmond Co, NY (360850067)

Suffolk Co, NY (361030002)
Philadelphia Co, PA (421010024)

                                      NY
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)

                                      OH
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Jefferson Co, KY (211110067)

Harford Co, MD (240251001)
Richmond Co, NY (360850067)
Suffolk Co, NY (361030002)

Philadelphia Co, PA (421010024)

                                      OK
Allegan Co, MI (260050003)
Denton Co, TX (481210034)
Harris Co, TX (482011034)

Harris Co, TX (482011039)

                                      PA
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Harford Co, MD (240251001)

Richmond Co, NY (360850067)
Suffolk Co, NY (361030002)

                                      TN
Hamilton Co, OH (390610006)
Philadelphia Co, PA (421010024)

                                      TX

Harford Co, MD (240251001)
Allegan Co, MI (260050003)
 Hamilton Co, OH (390610006)

Philadelphia Co, PA (421010024)

                                      VA
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Harford Co, MD (240251001)

Richmond Co, NY (360850067)
Suffolk Co, NY (361030002)
Philadelphia Co, PA (421010024)
                                      WV
Fairfield Co, CT (090010017)
Fairfield Co, CT (090013007)
Harford Co, MD (240251001)

Richmond Co, NY (360850067)
Suffolk Co, NY (361030002)
Hamilton Co, OH (390610006)

Philadelphia Co, PA (421010024)

                                      WI
Allegan Co, MI (260050003)

      The EPA's modeling to quantify upwind state EGU NOX emission budgets, described in section VI, used a more recent IPM version 5.15 base case projection as compared to the IPM projection used for air quality modeling described here in section V. This more recent IPM base case reflects minor updates to IPM model inputs. Because this more recent IPM base case projection was not used for the air quality modeling for the final rule, the aforementioned results do not account for updates which are subsequently included in the budget-setting analysis. In order to ensure that the budget-setting base case projection would not change any conclusions drawn from the air quality modeling, the EPA performed an assessment of the budget-setting base case using a method that relied on the EPA's air quality modeling contribution data as well as projected ozone concentrations from the EPA's 2017 illustrative policy case developed for the Regulatory Impact Analysis. For more information about these methods, refer to the Ozone Transport Policy Analysis Final Rule TSD. This assessment shows no change in the set of nonattainment or maintenance receptors identified here in section V. In addition to evaluating the status of downwind receptors identified for the rule, the EPA evaluated whether the budget-setting base case would reduce ozone contributions from upwind states to the extent that a previously linked state would have a maximum contribution less than the one percent threshold. This assessment shows that with the budget-setting base case, all previously identified states are expected to remain linked (i.e., contribute greater than or equal to one percent of the NAAQS) to at least one downwind nonattainment or maintenance receptor. Therefore, using the budget-setting base case for the final rule does not impact the scope of states linked to downwind nonattainment or maintenance receptors relative to the modeled base case.
      Additionally, after the emissions and air quality modeling for the final rule were already underway, Pennsylvania published a new RACT rule that would require EGU and non-EGU NOX reductions starting on January 1, 2017. The EPA recognizes that the implementation of this final state rule will precede the first control period for the final CSAPR Update rule. The agency believes it is reasonable to evaluate the potential influence of the Pennsylvania RACT rule on downwind receptors and state linkages identified for this final rule prior to evaluating any further EGU NOX reductions for the CSAPR Update rule. Therefore, because Pennsylvania's new RACT rule was not represented explicitly in the emission inventory and air quality modeling already underway, the EPA first added an evaluation of emissions and air quality impacts expected to result from Pennsylvania's RACT rule before then evaluating air quality impacts of the further reductions that might be required under the CSAPR Update rule at each uniform control stringency identified. The EPA estimates that, for the adjusted historical emission level including Pennsylvania RACT, no nonattainment or maintenance receptors identified in section V dropped below 76 ppb and Pennsylvania's contribution to downwind ozone problems did not drop below one percent of the NAAQS. Therefore, the identified receptors and linked upwind states in section V remain unchanged.

VI. Quantifying Upwind State EGU NOX Emission Budgets to Reduce Interstate Ozone Transport for the 2008 NAAQS
 Introduction
      This section describes the EPA's methodology for quantifying emission budgets to reduce interstate emission transport for the 2008 ozone NAAQS. The CSAPR Update emission budgets limit allowable emissions and represent the emission levels that remain after each state makes EGU NOX emission reductions that are necessary to reduce interstate ozone transport for the 2008 NAAQS. The EPA's assessment of upwind state emission budgets in this rule reflects analysis of uniform NOX emission control stringency. Each level of uniform NOX control stringency represents an estimated marginal cost per ton of NOX reduced and is characterized by a set of pollution control measures. The EPA applies a multi-factor test, the same multi-factor test that was used in the original CSAPR, to evaluate increasing levels of uniform NOX control stringency. The multi-factor test considers cost, available emission reductions, and downwind air quality impacts to determine the appropriate level of uniform NOX control stringency that addresses the impacts of interstate transport on downwind nonattainment or maintenance receptors. The uniform NOX emission control stringency, represented by marginal cost, also serves to apportion the reduction responsibility among collectively-contributing upwind states. This approach to quantifying upwind state emission reduction obligations using uniform cost was reviewed by the Supreme Court in EPA v. EME Homer City Generation, which held that using such an approach to apportion emission reduction responsibilities among upwind states that are collectively responsible for downwind air quality impacts "is an efficient and equitable solution to the allocation problem the Good Neighbor Provision requires the Agency to address." 134 S.Ct. at 1607.
There are four stages in developing the multi-factor test to quantify upwind state emission budgets as to the 2008 ozone NAAQS: (1) identify levels of uniform NOX control stringency (represented by an estimated marginal cost of control that is applied across linked upwind states); (2) evaluate NOX emission reductions and corresponding NOX emission budgets (i.e., remaining allowable emissions after reductions are made) at each identified level of uniform control stringency; (3) assess air quality improvements resulting at each level of control; and (4) select a level of control stringency by applying the multi-factor test to consider cost, available emission reductions, and downwind air quality impacts, including ensuring that the budgets do not unnecessarily over-control relative to the contribution threshold or downwind air quality.
The multi-factor evaluation informs the EPA's determination of appropriate EGU NOX ozone season emission budgets necessary to reduce emissions that significantly contribute to nonattainment or interfere with maintenance of the 2008 ozone NAAQS for the 2017 ozone season and subsequent control periods. For most CSAPR Update states, the emission reductions achieved through implementation of these budgets will partially satisfy the EPA's good neighbor FIP obligation to fully prohibit emissions that contribute to downwind air quality problems with respect to the 2008 ozone NAAQS pursuant to CAA section 110 (a)(2)(D)(i)(I).  For one state, Tennessee, the emission reductions achieved through implementation of its emission budget will fully satisfy the EPA's good neighbor FIP obligation for the 2008 ozone NAAQS. Section VII describes the EPA's approach to implementing these emission budgets through updates to the CSAPR NOX ozone season trading program.
 Levels of Uniform Control Stringency

      The following subsections describe the EPA's analysis to establish levels of uniform control stringency for EGU and non-EGU point sources. Each level of uniform NOX control stringency is characterized by a set of pollution control measures and represents an estimated marginal cost per ton of NOX reduced. This section summarizes the EPA's findings when assessing NOX reduction strategies and cost.
      As described in section IV of this preamble, the EPA is quantifying near-term ozone season NOX emission reductions to reduce interstate emission transport for the 2008 ozone NAAQS in order to assist downwind states with meeting the impending July 20, 2018 Moderate area attainment date. Although this final rule does not require or impose any specific technology standards on affected sources, the EPA limited its analysis of potential NOX reductions in each upwind state to those that could be feasibly implemented for the 2017 ozone season, which is the last full ozone season prior to the July 20, 2018 attainment date. This approach ensures that the emission budgets are achievable for the 2017 ozone season. The EPA did not further analyze potential NOX reductions from strategies that were deemed infeasible to implement for the 2017 ozone season for purposes of quantifying upwind state emission budgets, but the EPA anticipates considering those controls in any future action that may be necessary to address upwind states' full emission reduction obligations with respect to the 2008 ozone standard. For more details on these assessments, refer to the EGU NOX Mitigation Strategies Final Rule TSD and the Assessment of Non-EGU NOX Emission Controls, Cost of Controls, and Time for Compliance Final Rule TSD in the docket for this rule.
 1. EGU NOX Mitigation Strategies