The F1 factor incorporates an ecosystem's ability to generate acid neutralizing capacity through base cation supply ([BC]*0) and to neutralize acidifying nitrogen deposition through Neco, both of which are incorporated in the CL term.  As noted above, because Neco can only neutralize nitrogen deposition (oxidized or reduced) there may be rare cases where Neco exceeds the combination of reduced and oxidized nitrogen deposition.  Consequently, to ensure that the AAI equation is applicable in all cases that may occur, equation III-4 is conditional on total nitrogen deposition, {NHx + F3[NOy]}, being greater than Neco.  In rare cases where Neco is greater than {NHx + F3[NOy]}, F2 are F3 would be set equal to 0 in the AAI equation.  The consequence of setting F2 and F3 to zero is simply to constrain the AAI calculation just to SOx, as nitrogen would have no bearing on acidifying contributions in this case.
	The Policy Assessment concludes that equation III- 4 (US EPA, 2011,equation 7-12), which defines the AAI, is ecologically relevant and appropriate for use as the form of a national standard designed to provide protection for aquatic ecosystems from the effects association with acidifying deposition associated with concentrations of oxides of nitrogen and sulfur in the ambient air.  This AAI equation does not, however, in itself, define the spatial areas over which the terms of the equation would apply.  To specify values for factors F1 through F4, it is necessary to define spatial areas over which these factors are determined.  Thus, it is necessary to identify an approach for spatially aggregating water bodies into ecologically meaningful regions across the U.S., as discussed below.
5.	Spatial Aggregation
	As discussed in the Policy Assessment, one of the unique aspects of this form is the need to consider the spatial areas over which values for the F factors in the AAI equation are quantified.  Ecosystems across the U.S. exhibit a wide range of geological, hydrological and vegetation characteristics that influence greatly the ecosystem parameters, Q, BC0[*] and Neco that are incorporated in the AAI.  Variations in ecosystem attributes naturally lead to wide variability in the sensitivities of water bodies in the U.S. to acidification, as well as in the responsiveness of water bodies to changes in acidifying deposition.  Consequently, variations in ecosystem sensitivity, and the uncertainties inherent in characterizing these variations, must be taken into account in developing a national standard.  In developing a secondary NAAQS to protect public welfare, the focus of the Policy Assessment is on protecting sensitive populations of water bodies, not on each individual water body, which is consistent with the Agency's approach to protecting public health through primary NAAQS that focus on susceptible populations, not on each individual.
	The approach used for defining ecologically relevant regions across the U.S. in the Policy Assessment (US EPA, 2011,section 7.2.5) is described below, along with approaches to characterizing each region as acid sensitive or relatively non-acid sensitive.  This characterization facilitates a more detailed analysis and focus on those regions that are relatively more acid sensitive.  This characterization is also used to avoid over-protection in relatively non-acid sensitive regions, regions that would receive limited benefit from reductions in the deposition of oxides of nitrogen and sulfur with respect to aquatic acidification effects.  Approaches to developing representative values for each of the terms in the AAI equation (factors F1 through F4) for each ecologically relevant region for which sufficient data are available are then discussed.  These spatial aggregation approaches are generally applicable to the contiguous United States.  The following discussion also addresses the development of factors for data-limited regions and specifically for Hawaii, Alaska and the U.S. territories.
	Stated more simply, this section discusses appropriate ways to divide the country into ecologically relevant regions; to characterize each region as either acid sensitive or relatively non-acid sensitive; and to determine values of factors F1 through F4 for each region, taking into consideration the acid sensitivity of each region and the availability of relevant data.  For each such region, the AAI would be calculated based on the values of factors F1 through F4 specified for that region.
	In considering approaches to spatial aggregation, the Policy Assessment focuses on methods that have been developed to define ecologically relevant regions, referred to as ecoregions, which are meaningfully related to the factors that are relevant to aquatic acidification.  As noted above, the Policy Assessment did not focus on looking at each individual water body, nor did it focus on aggregating over the entire nation, which would preclude taking into account the inherent variability in atmospheric and ecological factors that fundamentally modify the relationships that are central to the development of an ecologically relevant AAI.
	Based on considering available classification schemes, the Policy Assessment concludes that Omernik's ecoregion classification is the most appropriate method to consider for the purposes of this review.  This classification offers several levels of spatial delineation, has undergone an extensive scientific peer review process, and has explicitly been applied to delineating acid sensitive areas within the U.S.  Further, the Policy Assessment concludes that ecoregion level III (Figure III-1) resolution, with 84 defined ecoregions in the contiguous U.S., is the most appropriate level to consider for this purpose.  The spatial resolution afforded by level III strikes an appropriate balance relative to the reasoning that supports conclusions on indicators, as discussed above.  The Policy Assessment concludes that the most detailed level of resolution (level IV) is not appropriate given the limited data availability to address nearly 1000 subdivisons within that level and the currently evolving nature of level IV regions.  Further, level III ecoregions are preferred to level II in that level III ecoregions, but not level II ecoregions, are largely contiguous in space which allows for a more coherent development of information to quantify the AAI factors and to characterize the concentrations of NOy and SOx in the ambient air within each ecoregion.
	Appendix C of the Policy Assessment includes a description of each level III ecoregion.  The Policy Assessment notes that the use of ecoregions is an appropriate spatial aggregation scheme for this standard focused on deposition-related aquatic acidification effects, while many of the same ecoregion attributes may be applicable in subsequent NAAQS reviews that may address other deposition-related aquatic and terrestrial ecological effects.   Because atmospheric deposition is modified by ecosystem attributes, the types of vegetation, soils, bedrock geology, and topographic features that are the basis of this ecoregion classification approach also will likely be key attributes for other deposition-related effects (e.g., terrestrial acidification, nutrient enrichment) that link atmospheric concentrations to an aquatic or terrestrial ecological indicator.
Figure III-1.  Omernik Ecoregion III areas (http://www.epa.gov/wed/pages/ecoregions).

a.	Ecoregion Sensitivity
	The Policy Assessment used Omernik's original alkalinity data (US EPA, 2011,as section  2) and more recent ANC data to delineate two broad groupings of ecoregions:  acid-sensitive and relatively non-acid sensitive ecoregions.  This delineation was made to facilitate greater focus on those ecoregions with water bodies that generally have greater acid sensitivity and to avoid over-protection in regions with generally less sensitive water bodies.  The approach used to delineate acid-sensitive and relatively non-acid sensitive regions included an initial numerical-based sorting scheme using ANC data, which categorized ecoregions with relatively high ANC values as being relatively non-acid sensitive.  This initial delineation resulted in 29 of the 84 Omernik ecoregions being categorized as acid sensitive.  Subsequently, land use data were also considered to determine to what extent an ecoregion is of a relatively pristine and rural nature by quantifying the degree to which active management practices related to development and agriculture occur in each ecoregion.
	The overall objective is to produce a logical and practical grouping of ecoregions that experience adverse conditions with respect to aquatic acidification and are likely to respond to changes in concentrations of NOy and SOx in the ambient air and to the related deposition levels.  To achieve this goal, a two-step process has been applied, first identifying acid sensitive ecoregions based on water quality data alone, and second identifying among those acid-sensitive ecoregions those with highly developed and managed areas.  These highly developed and managed ecoregions are placed in a non-acid sensitive category to avoid over protection beyond what is requisite to protect public welfare.  More specifically, in determining an ecoregion's acid sensitivity status in step 1, ANC data across the 84 ecoregions are sorted (US EPA, 2011,section 7 ) to determine the number of water bodies within a region with ANC values suggestive of acid sensitivity, so as to screen out regions with an overabundance of high ANC values.  In reviewing the ANC data, the Policy Assessment identified 29 ecoregions that meet two criteria: (1) greater than 5% of water bodies with data with ANC values less than 200 ueq/L and (2) greater than 1% of water bodies with ANC values less than 100 ueq/L.  In step 2, land use data were used to identify those acid sensitive ecoregions with significant managed areas that would not be considered as having a  relatively pristine and rural character.  The percentage of the combination of developed (residential, transportation, industrial and commercial) and agricultural (croplands, pastures, orchards, vineyards) land use was used as an indicator of managed land use area.  Forest cover was used as an indicator of non-managed land use more directly reflecting the pristine quality of a region.  Based on the 2006 National Land Cover Data base (NLCD, http://www.epa.gov/mrlc/nlcd-2006.html), acid sensitive ecoregions would meet both of the following land use data criteria: percent of developed and agricultural area less than 20% combined with forested area greater than 50%.  The combination of steps 1 and 2 identify 22 relatively acid sensitive areas (Table III-1 and Figure III-2).
	Consideration was also given to the use of naturally acidic conditions in defining relatively non-acid sensitive areas.  For example, several of the ecoregions located in plains near the coast exhibit elevated dissolved organic carbon (DOC) levels, which is associated with naturally acidic conditions.  DOC in surface waters is derived from a variety of weak organic acid compounds generated from the natural availability and decomposition of organic matter from biota.   Consequently, high DOC is associated with "natural" acidity, with the implication that a standard intended to protect against atmospheric contributions to acidity is not an area of focus.  The evidence suggests that several of the more highly managed ecoregions in coastal or near coastal transition zones are associated with relatively high DOC values, typically exceeding on average 5 mg/l, compared to other acid sensitive areas.  Although there is sound logic to interpret naturally acidic areas as relatively non-acid sensitive, natural acidity indicators were not explicitly included in defining relatively non-acid sensitive areas as there does not exist a consensus-based quantifiable scientific definition of natural acidity.  Approaches to explicitly define natural acidity likely will be pursued in future reviews of the standard.
Table III-1.   List of 22 Acid-Sensitive Areas
Ecoregion name
Ecoregion number
Ridge and Valley
8.4.1
Northern Appalachian Plateau and Uplands
8.1.3
Piedmont
8.3.4
Western Allegheny Plateau
8.4.3
Southwestern Appalachians
8.4.9
Boston Mountains
8.4.6
Blue Ridge
8.4.4
Ouachita Mountains
8.4.8
Central Appalachians
8.4.2
Northern Lakes and Forests
5.2.1
Maine/New Brunswick Plains and Hills
8.1.8
North Central Appalachians
5.3.3
Northern Appalachian and Atlantic Maritime Highlands
5.3.1
Columbia Mountains/Northern Rockies
6.2.3
Middle Rockies
6.2.10
Wasatch and Uinta Mountains
6.2.13
North Cascades
6.2.5
Cascades

6.2.7
Southern Rockies
6.2.14
Sierra Nevada
6.2.12
Idaho Batholith
6.2.15
Canadian Rockies
6.2.4

Figure III-2.  Acid-sensitive ecoregions identified in grey fill (22 out of 84 ecoregions).

b.	Representative Ecoregion-specific Factors
	Having concluded that the Omernik level III ecoregions are an appropriate approach to spatial aggregation for the purpose of a standard to address deposition-related aquatic acidification effects, the Policy Assessment uses those ecoregions to define each of the factors in the AAI equation.  As discussed below, factors F1 through F4 in equation III-4 are defined for each ecoregion by specifying ecoregion-specific values for each factor based on monitored or modeled data that are representative of each ecoregion.
i.	Factor F1
      As discussed above, factor F1 reflects a relative measure of an ecosystem's ability to neutralize acidifying deposition, and is defined as:  F1 = ANClim + CLr/Qr.  The value of F1 for each ecoregion would be based on a representative critical load for the ecoregion (CLr) associated with a single national target ANC level (ANClim, discussed below in section III.D), as well as on a representative runoff rate (Qr).  To specify ecoregion-specific values for the term Qr, the Policy Assessment used the median value of the distribution of Q values that are available for water bodies within each ecoregion.  To specify ecoregion-specific representative values for the term CLr in factor F1, a distribution of calculated critical loads was created for the water bodies in each ecoregion for which sufficient water quality and hydrology data are available.  The representative critical load was then defined to be a specific percentile of the distribution of critical loads in the ecoregion. Thus, for example, using the 90[th] percentile means that within an ecoregion, 90 percent of the water bodies would be expected to have higher calculated critical loads than the representative critical load.  That is, if the representative critical load were to occur across the ecoregion, 90 percent of the water bodies would be expected to achieve the national ANC target or better.
      The specific percentile selected as part of the definition of F1 is an important parameter that directly impacts the representative critical load specified for each ecoregion, and therefore the degree of protectiveness of the standard.   A higher percentile corresponds to a lower critical load and, therefore, to lower allowable ambient air concentrations of NOy and SOx and related deposition to achieve a target AAI level.  In conjunction with the other terms in the AAI equation, alternative forms can be appropriately characterized in part by identifying a range of alternative percentiles.  The choice of an appropriate range of percentiles to consider for acid-sensitive and relatively non-acid sensitive ecoregions, respectively, is discussed below.
(a)	Acid-sensitive Ecoregions
	In identifying percentiles that are appropriate to consider for the purpose of calculating factor F1 for ecoregions characterized as acid sensitive, the Policy Assessment concludes that it is appropriate to focus on the upper part of the distribution of critical loads, so as to ensure that the ecoregion would be represented by relatively more acid sensitive water bodies within the ecoregion.  Specifying factor F1 in this way would help to define a standard that would be protective of the population of acid sensitive water bodies within an ecoregion, recognizing that even ecoregions characterized as acid sensitive may contain a number of individual water bodies that are not acid sensitive.  The Policy Assessment recognizes that there is no basis for independently evaluating the degree of protectiveness afforded by any specific percentile value, since it is the combination of form and level, in conjunction with the indicator and averaging time, which determine the degree of protectiveness of a standard.  In light of this, the Policy Assessment concludes that it is appropriate to consider a range of percentiles, from well above the 50[th] percentile, or median, of the distribution to somewhat below the highest value.  More specifically, the Policy Assessment concludes it is appropriate to consider percentiles in the range of the 70[th] to the 90[th] percentile.  This conclusion is based on the judgment that it would not be appropriate to represent an ecoregion with the highest or near highest critical load, so as to avoid potential extreme outliers that can be seen to exist at the extreme end of the data distributions, which would not be representative of the population of acid sensitive water bodies within the ecoregion.  Also, in considering ecoregions that are inherently acid sensitive, it is judged to be appropriate to limit the lower end of the range for consideration to the 70[th] percentile, a value well above the median of the distribution.
	In considering this conclusion, the CASAC Panel noted that the data bases for calculating critical loads within an ecoregion are not necessarily representative of all water bodies within an ecoregion.  That is, in many ecoregions the lake sampling design used in studies that generated the relevant data may have focused on the relatively more sensitive water bodies within an ecoregion (Russell and Samet, 2011a).  Consequently, a given percentile of the distribution of calculated critical loads, based on sampled water bodies, may not be representative of that percentile of all water bodies across an entire ecoregion.  To the extent that the sampling of water bodies within an ecoregion was skewed toward the relatively more sensitive water bodies, selecting a given percentile from the distribution of available critical loads would result in a somewhat higher percentile of all water bodies within that ecoregion having a higher calculated critical load than the representative critical load value.  Thus, the extent to which study sampling designs have resulted in skewed distributions of calculated critical loads is an uncertainty that is appropriate to consider in selecting a percentile for the purpose of defining the factor F1 in the AAI equation.
(b)	Non-acid sensitive Ecoregions
	With regard to identifying percentiles that are appropriate to consider for the purpose of calculating factor F1 for ecoregions characterized as relatively non-acid sensitive, the Policy Assessment recognizes that while such ecoregions are generally less sensitive to acidifying deposition from oxides of nitrogen and sulfur, they may contain a number of water bodies that are acid sensitive   This category includes ecoregions that are well protected from acidification effects due to natural production of base cations and high ANC levels, as well as naturally acidic systems with limited base cation production and consequently very low critical loads.  Therefore, the use of a critical load that would be associated with a highly sensitive water body in a naturally acidic system would impose a high degree of relative protection in terms of allowable ambient air concentrations of oxides of nitrogen and sulfur and related deposition, while potentially affording little or no public welfare benefit from attempting to improve a naturally acidic system.
	Based on these considerations, the Policy Assessment concludes it is appropriate to consider the use of a range of percentiles that extends lower than the range identified above for acid-sensitive ecoregions.  Consideration of a lower percentile would avoid representing a relatively non-acid sensitive ecoregion by a critical load associated with relatively more acid-sensitive water bodies.  In particular, the Policy Assessment concludes it is appropriate to focus on the median or 50[th] percentile of the distribution of critical loads so as to avoid over-protection in such ecoregions.   Recognizing that relatively non-acid sensitive ecoregions generally are not sampled to the extent that acid-sensitive ecoregions are, it also is appropriate to consider using the median critical load of all relatively non-acid sensitive ecoregions for each such ecoregion.
ii.	Factor F2
	As discussed above, factor F2 is the amount of reduced nitrogen deposition within an ecoregion, including the deposition of both ammonia gas and ammonium ion, and is defined as:  F2 = NHx/Qr.  The Policy Assessment calculated the representative runoff rate, Qr, using a similar approach as noted above for factor F1; i.e., the median value of the distribution of Q values that are available for water bodies within each ecoregion. In the Policy Assessment, 2005 CMAQ model simulations over 12-km grids are used to calculate an average value of NHx for each ecoregion. The NHx term is based on annual average model outputs for each grid cell, which are spatially averaged across all the grid cells contained in each ecoregion to calculate a representative annual average value for each ecoregion. The Policy Assessment concludes that this approach of using spatially averaged values is appropriate for modeling, largely due to the relatively rapid mixing of air masses that typically results in relatively homogeneous air quality patterns for regionally dispersed pollutants.  In addition, there is greater confidence in using spatially averaged modeled atmospheric fields than in using modeled point-specific fields.
	This averaging approach is also used for the air concentration and deposition terms in factors F3 and F4, as discussed below.  The Policy Assessment notes that modeled NHx deposition exhibits greater spatial variability than the other modeled terms in factors F3 and F4.  Recognizing this greater variability, the Policy Assessment concludes that it would be appropriate to consider alternative approaches to specifying the value of NHx.  One such approach might involve the use of more localized and/or contemporaneous modeling in areas where this term is likely to be particularly variable and important.
iii.	Factors F3 and F4
	As discussed above, factors F3 and F4 are the ratios that relate ambient air concentrations of NOy and SOx to the associated deposition, and are defined as follow:  F3 =  TNOy/ Qr  and F4 =  TSOx/ Qr.  TNOy is the transference ratio that converts ambient air concentrations of NOy to deposition of NOy and TSOx is the transference ratio that converts ambient air concentrations of SOx to deposition of SOx.  The representative runoff rate, Qr, is calculated as for factors F1 and F2.  The transference ratios are based on the 2005 CMAQ simulations, using average values for each ecoregion, as noted above for factor F2.  More specifically, the transference ratios are calculated as the annual deposition of NOy or SOx spatially averaged across the ecoregion and divided by the annual ambient air concentration of NOy or SOx, respectively, spatially averaged across the ecoregion.
c.	Factors in Data-limited Ecoregions
	As discussed above in section III.B.5.a, in the Policy Assessment the initial delineation of acid-sensitive and relatively non-acid sensitive ecoregions was based on available ANC and alkalinity data.   Areas not meeting the ANC criteria described above are categorized as relatively non-acid sensitive.  The development of a reasonable distribution of critical loads for water bodies within an ecoregion for the purpose of identifying the representative critical load requires additional data, including more specific water quality data for major cations and anions.  This means that the water bodies that can be used to develop a distribution of critical loads is generally a subset of those water bodies for which ANC data are available   Consequently, there are certain ecoregions with sparse data that are not suitable for developing a distribution of critical loads.
	As noted above, the Policy Assessment judges that it is not appropriate to develop such distributions based on data from less than ten water bodies within an ecoregion.  Twelve such ecoregions, which included only relatively non-acid sensitive ecoregions, were characterized as being data-limited.  For these ecoregions, the Policy Assessment considered alternative approaches to specifying values for the terms CLr and Qr for the purpose of determining values for each of the factors in the AAI equation.  For these data-limited ecoregions, the Policy Assessment judges that it is appropriate to use the median values of CLr and Qr from the distributions of these terms for all other relatively non-acid sensitive ecoregions, rather than attempting to use severely limited data to develop a value for these terms based solely on data from such an ecoregion.  Further, consideration could be given to using a single national default value for all relatively non-acid sensitive ecoregions.  The Policy Assessment notes that this data limitation is not a concern in specifying values for the other terms in the AAI equation for such ecoregions, since those terms are based on data from the 2005 CMAQ model simulation, which covers all ecoregions across the contiguous U.S.
d.	Application to Hawaii, Alaska, and the U.S. Territories
	The above methods for specifying ecoregion-specific values for the factors in the AAI equation apply to those ecoregions within the contiguous U.S.  For areas outside the continental U.S., including Hawaii, Alaska, and the U.S. Territories, there is currently a lack of available data to characterize the sensitivity of such areas, as well as a lack of water body-specific data and CMAQ-type modeling to specify values for the F1 through F4 factors.   Thus, the Policy Assessment has considered possible alternative approaches to specifying values for factors F1 through F4 in the AAI equation for these areas.
	One such approach could be to specify area-specific values for the factors based on values derived for ecoregions with similar acid sensitivities, to the extent that relevant information can be obtained to determine such similarities.  Such an approach would involve conducting an analysis to characterize similarities in relevant ecological attributes between ecoregions in the contiguous U.S. and these areas outside the contiguous U.S. so as to determine the appropriateness of utilizing ecoregion-specific values for the CLr and Qr terms from one or more ecoregions within the contiguous U.S.  This approach would also involve conducting additional air quality modeling for these area that are outside the geographical scope of the currently available CMAQ model simulations, so as to develop the other information necessary to specify values for factors F2 through F4 for these areas.
	A second approach could rely on future data collection efforts to establish relevant ecological data within these areas that, together with additional air quality modeling, could be used to specify area-specific values for factors F1 through F4.  Until such time as relevant data become available, these areas could be treated the same as data-limited ecoregions in the contiguous U.S. that are relatively non-acid sensitive.
	The Policy Assessment concludes that either approach would introduce substantial uncertainties that arise from attempting to extrapolate values based on similarity assumptions or arbitrarily assigning values for factors in the AAI equation that would be applicable to these areas outside the contiguous U.S.  In light of such uncertainties, the Policy Assessment concludes that it would also be appropriate to consider relying on the existing NO2 and SO2 secondary standards in these areas for protection of any potential direct or deposition-related ecological effects that may be associated with the presence of oxides of nitrogen and sulfur in the ambient air.  The Policy Assessment concludes that relying on existing secondary standards in these areas is preferable to using a highly uncertain approach to allow for the application of a new standard based on the AAI in the absence of relevant area-specific data.
6.	Summary of the AAI Form
	With regard to the form of a multi-pollutant air quality standard to address deposition-related aquatic acidification effects, the Policy Assessment concludes that consideration should be given to an ecologically relevant form that characterizes the relationships between the ambient air indicators for oxides of nitrogen and sulfur, the related deposition of nitrogen and sulfur, and the associated aquatic acidification effects in terms of a relevant ecological indicator.  Based on the available information and assessments, consideration should be given to using acid neutralizing capacity (ANC) as the most appropriate ecological indicator for this purpose, in that it provides the most stable metric that is highly associated with the water quality properties that are directly responsible for the principal adverse effects associated with aquatic acidification:  fish mortality and reduced aquatic species diversity.
	The Policy Assessment developed such a form, termed an aquatic acidification index (AAI), using a simple equation to calculate an AAI value in terms of the ambient air indicators of oxides and nitrogen and sulfur and the relevant ecological and atmospheric factors that modify the relationships between the ambient air indicators and ANC.  Recognizing the spatial variability of such factors across the U.S., the Policy Assessment concludes it is appropriate to divide the country into ecologically relevant regions, characterized as acid-sensitive or relatively non-acid-sensitive, and specify the value of each of the factors in the AAI equation for each such region.  Omernik ecoregions, level III, are identified as the appropriate set of regions over which to define the AAI.  There are 84 such ecoregions that cover the continental U.S.  This set of ecoregions is based on grouping a variety of vegetation, geological, and hydrological attributes that are directly relevant to aquatic acidification assessments and that allow for a practical application of an aquatic acidification standard on a national scale.
	The Policy Assessment defines AAI by the following equation:  AAI = F1  -  F2  -  F3[NOy]  -  F4[SOx].  Factors F1 through F4 would be defined for each ecoregion by specifying ecoregion-specific values for each factor based on monitored or modeled data that are representative of each ecoregion.  The F1 factor is also defined by a target ANC value.  More specifically:
	(1)  F1 reflects a relative measure of an ecosystem's ability to neutralize acidifying 	deposition.  The value of F1 for each ecoregion would be based on a representative 	critical load for the ecoregion associated with a single national target ANC level, as well 	as on a representative runoff rate.  The representative runoff rate, which is also used in 	specifying values for the other factors, would be the median value of the distributions of 	runoff rates within the ecoregion.  The representative critical load would be derived from 	a distribution of critical loads calculated for each water body in the ecoregion for which 	sufficient water quality and hydrology data are available.  The representative critical load 	would be defined by selecting a specific percentile of the distribution.
		In identifying a range of percentiles that are appropriate to consider for this 	purpose, regions categorized as acid sensitive were considered separately from regions 	categorized as relatively non-acid sensitive.  For acid sensitive regions, the Policy 	Assessment concludes that consideration should be given to selecting a percentile from 	within the range of the 70[th] to the 90[th] percentile.  The lower end of this range was 	selected to be appreciably above the median value so as to ensure that the critical load 	would be representative of the population of relatively more acid sensitive water bodies 	within the region, while the upper end was selected to avoid the use of a critical load 	from the extreme tail of the distribution which is subject to a high degree of variability 	and potential outliers.  For relatively non-acid sensitive regions, the Policy Assessment 	concludes that consideration should be given to selecting the 50[th] percentile to best 	represent the distribution of water bodies within such a region, or alternatively to using 	the median critical load of all relatively non-acid sensitive areas, recognizing that such 	areas are far less frequently evaluated than acid sensitive areas.  Using either of these 	approaches would avoid characterizing a generally non-acid-sensitive region with a 	critical load that is representative of relatively acid sensitive water bodies that may exist 	within a generally non-acid sensitive region.
      (2)  F2 reflects the deposition of reduced nitrogen.  Consideration should be given to specifying the value of F2 for each region based on the averaged modeled value across the region, using national CMAQ modeling that has been conducted by EPA.  Consideration could also be given to alternative approaches to specifying this value, such as the use of more localized and/or contemporaneous modeling in areas where this term is likely to be particularly variable and important.
      (3)  F3 and F4 reflect transference ratios that convert ambient air concentrations of NOy and SOx, respectively, into related deposition of nitrogen and sulfur.  Consideration should be given to specifying the values for F3 and F4 for each region based on CMAQ modeling results averaged across the region.  We conclude that specifying the values or the transference rations based on CMAQ modeling results alone is preferred to an alternative approach that combines CMAQ model estimates with observational data.
      (4)  The terms [NOy] and [SOx] reflect ambient air concentrations measured at monitoring sites within each region.
	Using the equation, a value of AAI can be calculated for any measured values of ambient NOy and SOx.  For such a NAAQS, the Administrator would set a single, national value for the level of the AAI used to determine achievement of the NAAQS, as discussed below in section III.D.  The ecoregion-specific values for factors F1 through F4 would be specified by EPA based on the most recent data and CMAQ model simulations, and codified as part of such a standard.  These factors would be reviewed and updated as appropriate in the context of each periodic review of the NAAQS.
	The Policy Assessment developed specific F factors for each ecoregion based on the approach discussed above, using alternative percentiles and alternative national target ANC levels.  The results of this analysis for ecoregions characterized as acid sensitive are presented in Table 7-1a-d in the Policy Assessment.
C.	Averaging Time
	As discussed in section 7.3 of the Policy Assessment, aquatic acidification can occur over both long- and short-term timescales.  Long-term cumulative deposition of nitrogen and sulfur is reflected in the chronic acid-base balance of surface waters as indicated by measured annual ANC levels.  Similarly, the use of steady state critical load modeling, which generates critical loads in terms of annual cumulative deposition of nitrogen and sulfur, means that the focus of ecological effects studies based on critical loads is on the long-term equilibrium status of water quality in aquatic ecosystems.  Much of the evidence of adverse ecological effects associated with aquatic acidification, as discussed above in section II.A, is associated with chronically low ANC levels.  Protection against a chronic ANC level that is too low is provided by reducing overall annual average deposition levels for nitrogen and sulfur.
	Reflecting this focus on long-term acidifying deposition, the Policy Assessment developed the AAI that links ambient air indicators to deposition-related ecological effects, in terms of several factors, F1 through F4.  As discussed above, these factors are all calculated as annual average values, whether based on water quality and hydrology data or on CMAQ model simulations.  In the context of a standard defined in terms of the AAI, the Policy Assessment concludes that it is appropriate to consider the same annual averaging time for the ambient air indicators as is used for the factors in the AAI equation.
	We also recognize that short-term (i.e., hours or days) episodic changes in water chemistry, often due to changes in the hydrologic flow paths, can have important biological effects in aquatic ecosystems.  Such short-term changes in water chemistry are termed "episodic acidification."  Some streams may have chronic or base flow chemistry that is generally healthy for aquatic biota, but may be subject to occasional acidic episodes with potentially lethal consequences.  Thus, short-term episodic ecological effects can occur even in the absence of long-term chronic acidification effects.
	Episodic declines in pH and ANC are nearly ubiquitous in drainage waters throughout the eastern U.S.  Episodic acidification can result from several mechanisms related to changes in hydrologic flow paths.  For example, snow can store nitrogen deposited throughout the winter and snowmelt can then release this stored nitrogen, together with nitrogen derived from nitrification in the soil itself, in a pulse that leads to episodic acidification in the absence of increased deposition during the actual episodic acidification event.  The Policy Assessment notes that inputs of nitrogen and sulfur from snowpack and atmospheric deposition largely cycle through soil.  As a result, short-term direct deposition inputs are not necessarily important in episodic acidification.  Thus, as noted in chapter 3 of the ISA, protection against episodic acidity events can be achieved by establishing a higher chronic ANC level.
	Taken together, the above considerations support the conclusion that it is appropriate to consider the use of a long-term average for the ambient air indicators NOy and SOx for an aquatic acidification standard defined in terms of the AAI.  The use of an annual averaging time for NOy and SOx concentrations would be appropriate to provide protection against low chronic ANC levels, which in turn would protect against both long-term acidification and acute acidic episodes.
	The Policy Assessment has also considered interannual variability in both ambient air quality and in precipitation, which is directly related to the deposition of oxides of nitrogen and sulfur from the ambient air.  While ambient air concentrations show year-to-year variability, often the year-to-year variability in precipitation is considerably greater, given the highly stochastic nature of precipitation.  The use of multiple years over which annual averages are determined would dampen the effects of interannual variability in both air quality and precipitation.  For the ambient air indicators, the use of multiple-year averages would also add stability to calculations used to judge whether an area meets a standard defined in terms of the AAI.  Consequently, the Policy Assessment concludes that an annual averaging time based on the average of each year over a consecutive 3 to 5 year period is appropriate to consider for the ambient air indicators NOy and SOx.  In reaching this conclusion, the Policy Assessment notes that in its comments on the second draft Policy Assessment, CASAC  agreed that a 3 to 5 year averaging time was appropriate to consider (Russell and Samet, 2010b).
D.	Level
	As discussed above, the Policy Assessment concludes that ANC is the ecological indicator best suited to reflect the sensitivity of aquatic ecosystems to acidifying deposition from oxides of nitrogen and sulfur in the ambient air.  ANC is an indicator of the aquatic acidification expected to occur given the natural buffering capacity of an ecosystem and the loadings of nitrogen and sulfur resulting from atmospheric deposition.  Thus, the Policy Assessment developed a new standard for aquatic acidification that is based on the use of chronic ANC as the ecological indicator as a component in the AAI.
	The level of the standard would be defined in terms of a single, national value of the AAI.  The standard would be met at a monitoring site when the multi-year average of the calculated annual values of the AAI was equal to or above the specified level of the standard.   The annual values of the AAI would be calculated based on the AAI equation using the assigned ecoregion-specific values for factors F1 through F4 and monitored annual average NOy and SOx concentrations.  Since the AAI equation is based on chronic ANC as the ecological indicator, the level chosen for the standard would reflect a target chronic ANC value.  As noted above, the assigned F factors for each ecoregion would be determined by EPA in the rulemaking to set the NAAQS, based on water quality and hydrology data, CMAQ modeling, the selected percentile that is used to identify a representative critical load within the ecoregion, and the selected level of the standard.  The combination of the form of the standard, discussed above in section III.B, defined by the AAI equation and the assigned values of the F factors in the equation, other elements of the standard including the ambient air indicators (section III.A) and their averaging time (section III.C), and the level of the standard determines the allowable levels of NOy and SOx in the ambient air within each ecoregion.  All of the elements of the standard together determine the degree of protection from adverse aquatic acidification effects associated with oxides of nitrogen and sulfur in the ambient air.  The level of the standard plays a central role in determining the degree of protection provided and is discussed below.
	The Policy Assessment focuses primarily on information that relates degrees of biological impairment associated with adverse ecological effects to aquatic ecosystems to alternative levels of ANC in reaching conclusions regarding the range of target ANC levels that is appropriate to consider for the level of the standard.  The Policy Assessment develops the rationale for identifying a range of target ANC levels that is appropriate to consider by addressing questions related to the following areas:  (1) associations between ANC and pH levels to provide an initial bounding for the range of ANC values to be considered;  (2) evidence that allows for the delineation of specific ANC ranges associated with varying degrees of severity of biological impairment ecological effects;  (3) the role of ANC in affording protection against episodic acidity; (4) implications of the time lag response of ANC to changes in deposition; (5) past and current examples of  target ANC values applied in environmental management practices; and (6) data linking public welfare benefits and ANC.
1.	Association Between pH Levels and Target ANC Levels
	As discussed above in section II.A and more fully in chapter 3 of the Policy Assessment, specific levels of ANC are associated with differing levels of risk of biological impairment in aquatic ecosystems, with higher levels of ANC resulting in lower risk of ecosystem impacts, and lower ANC levels resulting in risk of both higher intensity of impacts and a broader set of impacts.  While ANC is not the causal agent determining biological effects in aquatic ecosystem,  it is a useful metric for determining the level at which a water body is protected against risks of acidification.  There is a direct correlation between ANC and pH levels which, along with dissolved aluminum, are more closely linked to the biological causes of ecosystem response to acidification.
	Because there is a direct correlation between ANC and pH levels, the selection of target ANC levels is informed in part through information on effects of pH as well as direct studies of effects related to ANC.  Levels of pH are closely associated with ANC in the pH range of approximately 4.5 to 7.  Within this range, higher ANC levels are associated with higher pH levels.  At a pH level of approximately 4.5, further reductions in ANC generally do not correlate with pH, as pH levels remain at approximately 4.5 while ANC values fall substantially.  Similarly, at a pH value of approximately 7, ANC values can continue to increase with no corresponding increase in pH.  As pH is the primary causal indicator of effects related to aquatic acidification, this suggests that ANC values below approximately -50 μeq/L (the apparent point in the relationship between pH and ANC where pH reaches a minimum) are not likely to result in further damage.  In addition, ANC values around and above approximately 100 μeq/L (the apparent region in the relationship where pH reaches a maximum) are not likely to confer additional protection.  As a result, the initial focus in the Policy Assessment was on target ANC values in the range of -50 to 100 μeq/L.
2.	ANC Levels Related to Effects on Aquatic Ecosystems
	As discussed above in section II.A, the number of fish species present in a water body has been shown to be positively correlated with the ANC level in the water, with higher values supporting a greater richness and diversity of fish species.  The diversity and distribution of phyto-zooplankton communities also are positively correlated with ANC.
	A summary of effects related to ANC ranges is shown above in Table II-1.  Within the ANC range from approximately -50 to 100 μeq/L, linear and sigmoidal relationships are observed between ANC and ecosystem effects.  On average, fish species richness is lower by one fish species for every 21 μeq/L decrease in ANC in Shenandoah National Park streams (ISA, section <IP_ADDRESS>).  As shown in Table II-1, ANC levels have been grouped into five categories related to expected ecological effects, including categories of acute concern ( <0 μeq/L), severe concern (0-20 μeq/L), elevated concern (20-50 μeq/L), moderate concern (50-100 μeq/L), and low concern (>100 μeq/L).  This categorization is supported by a large body of research completed throughout the eastern U.S. (Sullivan et al., 2006).
	Water bodies with ANC values less than or equal to 0 μeq/L at based flow are chronically acidic. Such ANC levels can lead to complete loss of species and major changes in the ability of water bodies to support diverse biota, especially in water bodies that are highly sensitive to episodic acidification.  Based on the above considerations, the Policy Assessment has focused on target ANC levels no lower than 0 μeq/L.
	As discussed in the Policy Assessment, biota generally are not harmed when ANC values are >100 μeq/L, due to the low probability that pH levels will be below 7.  In the Adirondacks, the number of fish species also peaks at ANC values >100 μeq/L.  This suggests that at ANC levels greater than 100 μeq/L, little risk from acidification exists in many aquatic ecosystems.  At ANC levels below 100 μeq/L, overall health of aquatic communities can be maintained, although fish fitness and community diversity begin to decline.  At ANC levels ranging from 100 down to 50 μeq/L, there is increasing likelihood that the fitness of sensitive species (e.g., brook trout, zooplankton) will begin to decline.  When ANC concentrations are below 50 μeq/L, the probability of acidification increases substantially, and negative effects on aquatic biota are observed, including large reductions in diversity of fish species and changes in the health of fish populations, affecting reproductive ability and fitness, especially in water bodies that are affected by episodic acidification.  While there is evidence that ANC levels above 50 can confer additional protection from adverse ecological effects associated with aquatic acidification in some sensitive ecosystems, the expectation that such incremental protection from adverse effects will continue up to an ANC level of 100 is substantially reduced.  The Policy Assessment concludes that the above considerations support a focus on target ANC levels up to a level greater than 50 μeq/L but below 100 μeq/L, such as up to a level of 75 μeq/L.
	In considering the available scientific evidence, as summarized here and discussed in more detail in the ISA and REA, in its review of the second draft Policy Assessment, CASAC expressed the following views about the range of biological responses that corresponds to this range of ANC levels (i.e., 0-100 μeq/L):
       There will likely be biological effects of acidification at higher ANC values within this range, and there are relatively insensitive organisms that are not impacted at ANC values at the low end of this range.  Adverse effects of acidification on aquatic biota are fairly certain at the low end of this range of ANC and incremental benefits of shifting waters to higher ANC become more uncertain at higher ANC levels.  There is substantial confidence that there are adverse effects at ANC levels below 20 μeq/L, and reasonable confidence that there are adverse effects below 50 μeq/L.  Levels of 50 μeq/L and higher would provide additional protection, but the Panel has less confidence in the significance of the incremental benefits as the level increases above 50 μeq/L. (Russell and Samet, 2010b)

	The Policy Assessment concludes that the above considerations, including the views of CASAC, provide support for focusing on target ANC levels in the range of 20 to 75 μeq/L.
3.	Consideration of Episodic Acidity
	As discussed in the Policy Assessment, across the broad range of ANC values from 0 to 100 μeq/L, ANC affords protection against the likelihood of decreased pH (and associated increases in Al) during long or short periods.  In general, the higher the ANC within this range, the lower the probability of reaching low pH levels where direct effects such as increased fish mortality occur, as shown in Table 3-1 of the Policy Assessment.  Accordingly, greater protection would be achieved by target chronic ANC values set high enough to avoid pH depression to levels associated with elevated risk.
	The specific relationship between ANC and the probability of reaching pH levels of elevated risk varies by water body and fish species.  ANC levels below 20 μeq/L are generally associated with high probability of low pH, leading to death or loss of fitness of biota that are sensitive to acidification (US EPA, 2008, section <IP_ADDRESS>; US EPA, 2009, section <IP_ADDRESS>).  At these levels, during episodes of high acidifying deposition, brook trout populations may experience lethal effects.  In addition, the diversity and distribution of zooplankton communities decline sharply at ANC levels below 20 μeq/L.  Overall, there is little uncertainty that significant effects on aquatic biota are occurring at ANC levels below 20 μeq/L.
	It is clear that at ANC levels approaching 0 μeq/L (Table II-1), there is significant impairment of sensitive aquatic ecosystems with almost complete loss of fish species.  Avoiding ANC levels approaching 0 μeq/L is particularly relevant to episodic spikes in acidity that occur during periods of rapid snow melt and during and after major precipitation events.  Since the ANC range considered in the Policy Assessment reflects average, long-term base flow values, it is appropriate to consider protecting against episodic drops in ANC values to a level as low as 0 μeq/L.  Staddard et al. (2003) noted on average a 30 μeq/L depression of ANC between spring and summer time values, indicating the need to maintain higher base flow ANC levels to protect against ANC levels below 0 μeq/L.  The above considerations do not provide support for a target chronic ANC level as low as 0 μeq/L for a standard that would protect against significant harm to aquatic ecosystems, including harm from episodic acidification.  The Policy Assessment concludes that these considerations also support a lower end of the range for consideration no lower than 20 μeq/L.
	The CASAC agreed with this conclusion in its comments on the second draft Policy Assessment (Russell and Samet, 2010b).  CASAC noted that "there are clear and marked biological effects at ANC values near 0 μeq/L, so this is probably not an appropriate target value" for the AAI.  With regard to the likelihood of impairment of aquatic ecosystems due to episodic acidification, in terms of specific target levels for chronic ANC, CASAC expressed the following view:
      	Based on surface waters studied in the Northeast, decreases in ANC associated with snowmelt [are] approximately 50 μeq/L.  Thus, based on these studies, a long term ANC target level of 75 μeq/L would generally guard against effects from episodic acidification down to a level of about 25 μeq/L. (Russell and Samet, 2010b)

4.	Consideration of Ecosystem Response Time
	The Policy Assessment notes that when considering a standard level to protect against aquatic acidification, it is appropriate to take into account both the time period to recovery as well as the potential for recovery in acid-sensitive ecoregions.  Ecosystems become adversely impacted by acidifying deposition over long periods of time and have variable time frames and abilities to recover from such perturbations. Modeling presented in the REA (US EPA, 2009, section 4.2.4) shows the estimated ANC values for Adirondack lakes and Shenandoah streams under pre-acidification conditions and indicates that for a small percentage of lakes and streams, natural ANC levels would have been below 50 μeq/L.  Therefore, for these water bodies, reductions in acidifying deposition are not likely to achieve an ANC of 50 μeq/L or greater.  Conversely, for some lakes and streams the level of perturbation from long periods of acidifying deposition has resulted in very low ANC values compared to estimated natural conditions. For such water bodies, the time to recovery would be largely dependent on future inputs of acidifying deposition.
	Setting a standard level in terms of a target chronic ANC level is based on the long-term response of aquatic ecosystems.  The time required for a water body to achieve the target ANC level -- given a decrease in ambient air concentrations of NOy and SOx and related acidifying deposition such that the critical load for a target ANC is not exceeded  -  is often decades if not centuries.  In recognition of the potential public welfare benefits of achieving the target ANC in a shorter time frame, the concept of target loads had been developed.  Target loads represent the depositional loading that is expected to achieve a particular level of the ecological indicator by a given time.  For example, to achieve an ANC level of 20 μeq/L by 2030, it might be necessary to specify a higher target ANC level of, for example, 50 μeq/L, such that the depositional loading would be reduced more quickly than would occur if the depositional loading was based on achieving a target ANC level of 20 μeq/L as a long-term equilibrium level.  In this example, the target ANC of 50 μeq/L would ultimately be realized many years later.
	The above considerations have implications for selecting an appropriate standard level, in that the standard level affects not only the ultimate degree of protection that would be afforded by the standard, but also the time frame in which such protection would be realized.  However, the Policy Assessment recognizes that there is a great deal of heterogeneity in response times among water bodies and that there is only very limited information from dynamic modeling that would help to quantify recovery time frames in areas across the country.  As a consequence, quantification of a general relationship between critical loads associated with a specific long-term target ANC level and target loads associated with achieving the target ANC level within a specific time frame is not currently possible.  Thus, while the time frame for recovery is an important consideration in selecting an appropriate range of levels to consider, the Policy Assessment concludes that it can only be considered in a qualitative sense at this time.
5.	Prior Examples of Target ANC Levels
	A number of regional organizations, states, and international organizations have developed critical load frameworks to protect against acidification of sensitive aquatic ecosystems.  In considering the appropriate range of target ANC levels for consideration in this review, it is informative to evaluate the target ANC levels selected by these different organizations, as well as the rationale provided in support of the selected levels.  Chapter 4 of the Policy Assessment provides a detailed discussion of how critical loads have been developed and used in other contexts.  Specific target values and their rationales are summarized below.
	The UNECE has developed critical loads in support of international emissions reduction agreements.  As noted in chapter 4 of the Policy Assessment, critical loads were established to protect 95 percent of surface waters in Europe from an ANC less than 20 ueq/L based on protection of brown trout.  Individual countries have set alternative ANC targets; for example, Norway targets an ANC of 30 ueq/L based on protection of Atlantic salmon.
Several states have established target ANC or pH values related to protection of lakes and streams from acidification.  While recognizing that some lakes in the Adirondacks will have a naturally low pH, the state of New York has established a target pH value of 6.5 for lakes that are not naturally below 6.5.  As noted above, this level is associated with an ANC value that is likely to be between 20 and 50 ueq/L or possibly higher.  New Hampshire and Vermont have set ANC targets of 60 ueq/L and 50 ueq/L, respectively.  Tennessee has established site-specific target ANC values based on assessments of natural acidity, with a default value of 50 ueq/L when specific data are not available.
	Taken together, these policy responses to concerns about ecological effects associated with aquatic acidification indicate that target ANC values between 20 and 60 μeq/L have been selected by states and other nations to provide protection of lakes and streams in some of the more sensitive aquatic ecosystems.
6.	Consideration of Public Welfare Benefits
	The point at which effects on public welfare become adverse is not defined in the CAA.  Characterizing a known or anticipated adverse effect to public welfare is an important component of developing any secondary NAAQS.  According to the CAA, welfare effects include:
       ...effects on soils, water, crops, vegetation, manmade materials, animals, wildlife, weather, visibility, and climate, damage to and deterioration of property, and hazards to transportation, as well as effect on economic values and on personal comfort and well-being, whether caused by transformation, conversion, or combination with other air pollutants. (CAA, section 302(h)).

While the text above lists a number of welfare effects, the NAAQS is aimed at protection from adverse effects to public welfare.  Consideration of adversity to public welfare in the context of the secondary NAAQS for oxides of nitrogen and sulfur can be informed by information about losses in ecosystem services associated with acidifying deposition and the potential economic value of those losses, as summarized above in section II.C and discussed more fully in chapter 4 of the Policy Assessment.
	Ecosystem service losses at alternative ANC levels are difficult to enumerate.  However, in general there are categories of ecosystem services, discussed in chapter 4 of the Policy Assessment, that are related to the specific ecosystem damages expected to occur at alternative ANC levels.  Losses in fish populations due to very low ANC (below 20 μeq/L) are likely associated with significant losses in value for recreational and subsistence fishers.  Many acid sensitive lakes are located in areas with high levels of recreational fishing activity.  For example, in the northeastern U.S., where nearly 8 percent of lakes are considered acidic, more than 9 percent of adults participate in freshwater fishing, with an estimated value of approximately $5 billion in 2006.  This suggests that improvements in lake fish populations are likely associated with significant recreational fishing value.
	As discussed in the Policy Assessment, inland surface waters also provide cultural services such as aesthetic and existence value and educational services.  To the extent that piscivorous birds and other wildlife are harmed by the absence of fish in these waters, hunting and birdwatching activities are likely to be adversely affected.  A case study of the value to New York residents of improving the health of lakes in the Adirondacks found significant willingness to pay for those improvements.  When scaled to evaluate the improvement in lake health from achieving ANC values of  20 to 50 μeq/L, the study implies benefits to the New York population roughly on the order of $600 million per year (in constant 2007$).  The survey administered in this study recognized that participants were thinking about the full range of services provided by the lakes in question  -  not just the recreational fishing services.  Therefore the estimates of willingness to pay include resident's benefits for potential hunting and birdwatching activities and other ancillary services. These results are just for New York populations.  The Policy Assessment concludes that if similar benefits exist for improvements in other acid sensitive lakes, the economic value to U.S. populations could be very substantial, suggesting that, at least by one measure of impact on public welfare, impacts associated with ANC less than 50 μeq/L may be adverse to public welfare.
7.	Summary of Alternative Levels
	Based on all the above considerations, the Policy Assessment concludes that consideration should be given to a range of standard levels from 20 to 75 μeq/L.  The available evidence indicates that target ANC levels below 20 μeq/L would be inadequate to protect against substantial ecological effects and potential catastrophic loss of ecosystem function in some sensitive aquatic ecosystems.  While ecological effects occur at ANC levels below 50 μeq/L in some sensitive ecosystems, the degree and nature of those effects are less significant than at levels below 20 μeq/L.  Levels at and above 50 μeq/L would be expected to provide additional protection, although uncertainties regarding the potential for additional protection from  adverse ecological effects are much larger for target ANC levels above about 75 μeq/L, as effects are generally appreciably less sensitive to changes in ANC at such higher levels.
	In reaching this conclusion in the Policy Assessment, consideration was given to the extent to which a target ANC level within this range would protect against episodic as well as long-term ecological effects.  Levels in the mid- to upper part of this range would be expected to provide greater protection against short-term, episodic peaks in aquatic acidification, while lower levels within this range would give more weight to protection from long-term rather than episodic acidification.  Similarly, levels in the mid- to upper part of this range would be expected to result in shorter time periods for recovery given the lag in ecosystem response in some sensitive ecosystems relative to levels in the lower part of this range.  The Policy Assessment also note that this range encompasses target ANC values that have been established by various States and regional and international organizations to protect against acidification of aquatic ecosystems.
	The Policy Assessment recognizes that the level of the standard together with the other elements of the standard, including the ambient air indicators, averaging time, and form, determine the overall protectiveness of the standard.  Thus, consideration of a standard level should reflect the strengths and limitations of the evidence and assessments as well as the inherent uncertainties in the development of each of the elements of the standard.  The implications of considering alternative standards, defined in terms of alternative combinations of levels and percentile values that are a critical component of factor F1 in the form of the standard, are discussed below in section III.E.  Key uncertainties in the various components of the standard are summarized and considered below in section III.F.
E.	Combined Alternative Levels and Forms
	To provide some perspective on the implications of various alternative standards, the Policy Assessment presented the number of acid-sensitive ecoregions that would likely not meet various sets of alternative standards.  The alternative standards considered were based on combinations of alternative target ANC levels, within the range of 20 to 75 ueq/L, and alternative forms, characterized by alternative representative percentiles within the range of the 70[th] to 90[th] percentile.  These alternative standards are also defined in terms of the other elements of the standard:  ambient air indicators NOy and SOx, discussed above in section III.A; other elements of the form of the standard, including ecoregion-specific values for factors F1 through F4 in the AAI equation, discussed above in section III.B.5; and an annual averaging time for NOy and SOx, discussed above in section III.C.  With regard to the averaging time, the assessment did not consider multi-year averaging of the calculated annual AAI values due to data limitations, including, for example, the lack of CMAQ modeling for multiple consecutive years.  In this assessment, we characterize an ecoregion as likely not meeting a given alternative standard if the calculated AAI value is less than the target ANC level of the standard, recognizing that higher AAI values are more protective than lower values.
	The results of this assessment are presented in Table 7-1a-d in the Policy Assessment for a subset of ecoregions including those characterized as acid sensitive.  Calculated annual AAI values at the ecoregion level are shown for each alternative standard considered.  Based on these AAI values, Table 7-2 in the Policy Assessment summarizes the number of acid-sensitive ecoregions that would likely not meet each of the alternative standards considered.   Calculated AAI values for all ecoregions categorized as relatively non-acid sensitive are shown in Table D-5 in Appendix D of the Policy Assessment.  In all cases, these relatively non-acid sensitive ecoregions were estimated to meet all of the alternative standards considered in this assessment.
	As described above, the AAI values presented in Table 7-1a-d of the Policy Assessment are based in part on data from 2005 CMAQ model simulations, which was used to generate values for F2 through F4 in the AAI equation, as well as to estimate annual average ambient air concentrations of NOy and SOx that reflect recent air quality in the absence of currently available monitored concentrations in sensitive ecoregions across the country.  Water quality and hydrology data from water bodies within each ecoregion were also used in calculating the AAI values.  Such data were initially used to calculate critical loads for each water body with sufficient data within an ecoregion so as to identify the n[th] percentile critical load representative of the ecoregion used in calculating the F1 factor for the ecoregion.  As expected, the number of ecoregions that likely would not meet alternative standards increases with increasing percentile values and target ANC levels (US EPA, 2011, Table 7-2).  Out of 22 acid-sensitive ecoregions, the number of ecoregions that would likely not meet the alternative standards  ranges from 22 for the most protective alternative standard considered (75 ueq/L, 90[th] percentile) to 4 for the least protective alternative standard (20 ueq/L, 70[th] percentile).  It is apparent that both the percentile and the level chosen have a strong influence, over the ranges considered, in determining the number of areas that would likely not meet this set of alternative standards.
	The Policy Assessment observes that there is one grouping of these acid-sensitive ecoregions that would likely not meet almost all combinations of level and form under consideration (US EPA, 2011, Table 7-2 and Appendix D).  This group is made up of southern Appalachian mountain areas, including North Central Appalachians, 5.3.3; Ridge and Valley, 8.4.1; Central Appalachians, 8.4.2; Blue Ridge, 8.4.4; and Southwestern Appalachians, 8.4.9.   In addition, these ecoregions exhibit the highest amounts of exceedance relative to alternative standards.
	The Northern Appalachian and Atlantic Maritime Highlands (5.3.1), which includes the Adirondacks, and the Northern Lakes and Forests (5.2.1) of the upper midwest exhibit similar patterns with respect to in the role of level and percentile in identifying regions not likely to meet alternative standards, although there are considerably fewer cases compared to the regions in the Appalachians.
	In the mountainous west, the Sierra Nevada (6.2.12), Idaho Batholith (6.2.15) and the Cascades (6.2.7) ecoregions likely would not meet alternative standards in fewer cases relative to eastern regions, with the Sierra Nevada ecoregion exhibiting relatively greater sensitivity compared to all western regions.  Only in the upper part of the ranges of level and percentile do regions in the northern and central Rockies likely not meet alternative standards.
	In considering these findings, the Policy Assessment observes that the standard as defined by the AAI behaves in an intuitively logical manner.  That is, an increase in ecoregions likely not to meet the standard is associated with higher alternative levels and percentiles, both of which contribute to a lower regionally representative critical load.  Moreover, the areas of known adverse aquatic acidification effects are identified, mostly in high elevation regions or in the northern latitudes -- the Adirondacks, Shenandoahs, northern midwest lakes and the mountainous west.  These results reflect the first application of a nationwide model that integrates water quality and atmospheric processes at a national scale and provides findings that are consistent with our basic understanding of the extent of aquatic acidification across the U.S.  What is particularly noteworthy is that this model is not initialized with a starting ANC based on water quality data, which likely would result in a reproduction of water quality observations.  Rather, this standard reflects the potential of the changes in atmospheric concentrations of NOy and SOx to induce long-term sustained changes in surface water systems.  The Policy Assessment notes that the fact that the patterns of adversity based on applying this standard are commensurate with what is observed in surface water systems provides confidence in the basic underlying formulation of the standard.
	The Policy Assessment notes that the Appalachian mountain regions merit further inspection as they stand out as areas with the largest relative exceedances from a national perspective.  Water quality data from these regions as well as an emissions sensitivity CMAQ simulation were considered to better understand the simulated behavior of these regions.  The maps and tables in appendix D of the Policy Assessment include paired comparisons of the CMAQ 2005 and emissions sensitivity simulations.  The emissions sensitivity simulation reflects domain-wide reductions in NOy and SOx emissions of 48% and 42%, respectively, relative to 2005 base year emissions.  The Policy Assessment assumes that this emissions sensitivity simulation is indicative of future conditions.
	The emissions sensitivity results project that many of the regions that likely would not meet the alternative standards based on recent air quality, especially at alternative levels of 20 and 35 ueq/L, would likely meet such standards in the future year scenario for the Appalachian mountain regions.  It is apparent that the AAI calculations are especially sensitive to changes in SOx emissions as the Appalachian regions have the highest SOx concentrations and deposition rates (US EPA, 2011,section 2), and the AAI equation  responds as expected to modeled reductions in SOx.  The emissions sensitivity scenario is a prospective application of the standard, in the sense that rules derived from the air quality management process result in reductions of NOy and SOx emissions.   Expected emission changes over the next two decades should be far greater than the 42 and 48% SOx and NOy reductions used in this analysis, with a consequent further reduction in areas that would likely not meet alternative standards.
	The Appalachian mountain regions generally have low DOC levels, average runoff rates, moderately low base cation supply and highly elevated sulfate concentrations.  Collectively, those attributes do not suggest naturally acidic conditions as the availability of anthropogenic contributions of mineral acids is likely responsible for observed low ANC values in those regions.
	The Policy Assessment notes the Sierra Nevada region as an interesting case study, as it has some of the lowest critical load values nationally (US EPA, 2011, Table D-3).  Water quality data indicate extremely low sulfate, as expected given the relatively low SO2 emissions in the western U.S.   Extremely low base cation supply and low Neco, which mitigate the effect of nitrogen deposition, explain the low critical load values.  Low Neco values appear to associate well with high elevation western U.S. regions, perhaps reflecting the more arid and reduced vegetation density relative to eastern U.S. regions. The proximity to high level nitrogen emissions combined with very low base cation supply explains the cases where the Sierra region likely does not meet alternative standards.  Because Neco values are low in the Sierras, the system responds effectively to reductions of NOx emissions, as illustrated in the maps and tables of Appendix D of the Policy Assessment.  Although Neco affords protection from the acidifying effects of nitrogen deposition, the availability of excessive nitrogen neutralization capacity also means that reductions in nitrogen are not as effective as reductions in SOx in reducing the calculated AAI.
	In reviewing these results, the Policy Assessment observes that the analysis of the alternative combinations of level and form presented provide context for considering the impact of different standards.   Since the AAI equation has been newly developed in the Policy Assessment, these examples of estimated exceedances help to address the question of whether the AAI equation responds in a reasonable manner with regard to identifying areas of concern and to prospective changes in atmospheric conditions likely to result from future emissions reduction strategies.  The Policy Assessment concludes that the behavior of the AAI calculations is both reasonable and explainable, which the Policy Assessment concludes serves to increase confidence in considering a standard defined in terms of the AAI.
F.	Characterization of Uncertainties
	This section summarizes discussions of the results of analyses and assessments, presented more fully in the Policy Assessment (US EPA, 2011, section 7.6 and Appendices F and G), intended to address the relative confidence associated with the linked atmospheric-ecological effects system described above.  An overview of uncertainties is presented in the context of the major structural components underlying the standard, as well as with regard to areas of relatively high uncertainty.  The section closes with a discussion of data gaps and uncertainties associated with the use of ecological and atmospheric modeling to specify the factors in the AAI equation, which can be used to guide future field programs and longer-term research efforts.
1.	Overview of Uncertainty
	 As discussed in the Policy Assessment (US EPA, 2011,Table 7-3), there is relatively low uncertainty with regard to the conceptual formulation of the overall structure of the AAI-based standard that incorporates the major associations linking biological effects to air concentrations.  Based on the strength of the evidence that links species richness and mortality to water quality, the associations are strongly causal and without any obvious confounding influence.  The strong association between the ecosystem indicator (ANC) and the causative water chemistry species (dissolved aluminum and hydrogen ion) reinforces the confidence in the linkage between deposition of nitrogen and sulfur and effects.  This strong association between ANC and effects is supported by a sound mechanistic foundation between deposition and ANC.  The same mechanistic strength holds true for the relationship between ambient air levels of nitrogen and sulfur and deposition, which completes the linkage from ambient air indicators through deposition to ecological effects.
	There are relatively higher uncertainties, however, in considering specific elements within the structure of an AAI-based standard, including the deposition of SOx, NOy, and NHx as well as the critical load-related component, each of which can vary within and across ecoregions.  Overall system uncertainty relates not just to the uncertainty in each such element, but also to the combined uncertainties that result from linking these elements together within the AAI-based structure.  Some of these elements  -  including, for example, dry deposition, pre-industrial base cation production, and reduced nitrogen deposition  -  are estimated with less confidence than other elements (US EPA, 2011, Table 7.3).  The uncertainties associated with all of these elements, and the combination of these elements through the AAI equation, are discussed below and in the following sections related to measured data gaps and modeled processes for both air quality and water quality.
	The lack of observed dry deposition data is constrained by resources and the lack of efficient measurement technologies.  Progress in reducing uncertainties in dry deposition will depend on improved atmospheric concentration data and direct deposition flux measurements of the relevant suite of NOy and SOx species.
      Pre-industrial base cation productivity by definition is not observable.  Contemporary observations and inter-model comparisons are useful tools that would help reduce the uncertainty in estimates of preindustrial base cation productivity used in the AAI equation.  In characterizing contemporary base cation flux using basic water quality measurements (i.e., major anioni and cation species as defined in equation 2.11 in the Policy Assessment), it is reasonable to assume that a major component of contemporary base cation flux is associated with pre-industrial weathering rates.  To the extent that multiple models converge on similar solutions, greater confidence in estimating pre-industrial base cation production would be achieved.
	Characterization of reduced nitrogen (NHx) deposition has been evolving over the last decade.  The relatively high uncertainty in characterizing NHx deposition is due to both the lack of field measurements and the inherent complexity of characterizing NHx with respect to source emissions and dry deposition.  Because ammonia emissions are generated through a combination of man-made and biological activities, and ammonia is semi-volatile, the ability to characterize spatial and temporal distributions of NHx concentrations and deposition patterns is challenging.  While direct measurement of NHx deposition is resource intensive because of the diffuse nature of sources (i.e., area-wide and not point sources), there have been more frequent deposition flux studies, relative to other nitrogen species, that enable both the estimation of emissions and dry deposition.  Also, while ammonia has a relatively high deposition velocity and traditionally was thought to deposit close to the emissions release areas, the semi-volatile nature of ammonia results in re-entrainment back into the lower boundary layer resulting in a more dispersed concentration pattern exhibiting transport type characteristics similar to longer lived atmospheric species.  These inherent complexities in source characterization and ambient concentration patterns raise the uncertainty level of NHx in general.  However, the Policy Assessment notes that progress is being made in measuring ammonia with cost efficient samplers and anticipates the gradual evolution of a spatially robust ammonia sampling network that would help support analyses to reduce underlying uncertainties in NHx deposition.  Also, from an aquatic acidification perspective, NHx is not as important a driver relative to NOy and SOx in the mountainous areas in the eastern U.S.  However, the relative importance of NHx is likely to increase over time, in light of air quality rules in place designed to reduce emissions of NOy and SOx.
2.	Uncertainties Associated with Data Gaps
	In summarizing uncertainties with respect to available measurement data and the use of ecological and atmospheric models, the Policy Assessment indentified data gaps and model uncertainties in relative terms by comparing, for example, the relative richness of data between geographic areas or environmental media.  With regard to relevant air quality measurements, the Policy Assessment notes that such measurements are relatively sparse in the western U.S.  While the spatial extent of CASTNET coverage has gradually incorporated western U.S. locations with support from the National Parks Service (NPS), the relative density of monitoring sites is much less than that in the eastern U.S.  This relative disparity in spatial density of monitors is exacerbated as air quality patterns in the mountainous west generally exhibit greater spatial heterogeneity due to dramatic elevation gradients that impact meteorology and air mass flow patterns.  Similarly, water quality data coverage is far more comprehensive in the eastern U.S. relative to the west
	Measurements of NOy notably are lacking in both eastern and western acid-sensitive ecoregions.  This adds uncertainty to the use of the AAI equation as the lack of NOy data limits efforts to evaluate air quality modeling of NOy that is the basis for quantifying factor F3 in the AAI equation.  The lack of NOy measurements also limits efforts to characterize the variability and representativeness of modeled NOy concentrations within and across ecoregions.  Currently, the Agency's ability to define the protection likely to be afforded by alternative standards (in terms of alternative levels and percentiles) is compromised by the lack of a full set of ambient air quality indicator measurements, notably including NOy, throughout sensitive ecoregions across the U.S.
	Further, obtaining measurement of the dominant species that comprise NOy (HNO3, true NO2, NO, p - NO3, and PAN) would be useful to evaluate performance of NOy samplers.  Beyond the more well known dominant components of NOy, research efforts would be needed to characterize total reactive nitrogen that may include significant amounts of organically-bound nitrogen (beyond PAN) which is poorly understood with regard to emission sources and concentration levels.
      Field measurements of NHx have been extremely limited, but have begun to be enhanced through the National Atmospheric Deposition Program's (NADP) passive ammonia network (AMoN).  AMoN measures ammonia at over 50 sites, with more than 35 at CASTNET locations.  Enhanced spatial coverage of reduced nitrogen measurements, particularly to understand within and across ecoregion variability, and the inclusion of some continuous observations would provide a better understanding of the uncertainty in the F2 factor in the AAI equation and of the s representativeness of modeled NHx deposition within and across ecoregions.
	With regard to water quality data, the Policy Assessment notes that such data are typically limited relative to air quality data sets, and are also relatively sparse in the western U.S.  The TIME/LTM water quality sampling program  in the eastern U.S. (as described in chapter 2 of the Policy Assessment) is an appropriate complement to national air monitoring programs as it affords consistency across water bodies in terms of sampling frequency and analysis protocols.  Consideration should be given to extending the TIME/LTM design to all acid sensitive ecoregions, with priority for areas in the western mountains that are data limited and showing initial signs of adversity particularly with respect to aquatic acidification.  The lack of a regulatory requirement for TIME/LTM often jeopardizes funding support of this resource that is especially valuable and cost effective.  While there are several state and local agency water quality data bases, it is unclear the extent to which differences in sampling, chemical analysis and reporting protocols would impact the use of such data for the purpose of better understanding the degree of protectiveness that would be afforded by an AAI-based standard within sensitive ecoregions across the country.  In addition, our understanding of water quality in Alaska and Hawaii and the acid sensitivity of their ecoregions is particularly limited.
	Water quality data and modeling support the standard setting process.  As more water bodies are sampled, the critical load data bases would expand, enabling clearer delineation of ecoregion representative critical loads in terms of the n[th] percentile.  This would provide more refined characterization of the degree of protection afforded by a given standard.  Longer term, the availability of water quality trend data (annual to monthly sampled) would support accountability assessments that examine if an ecoregion's response to air management efforts is as predicted by earlier model forecasting.  The most obvious example is the long-term response of water quality ANC change to changes in calculated AAI, deposition, ambient NOy and SOx concentrations, and emissions.  In addition, water quality trends data provide a basis for evaluating and improving the parameterizations of processes in critical load models applied at the ecoregion scale related to nitrogen retention and base cation supply.  A better understanding of soil processes, especially in the southern Appalachians, would enhance efforts to examine the variability within ecoregions of the soil-based adsorption and exchange processes which moderate the supply of major cations and anions to surface waters and strongly influence the response of surface water ANC to changes in deposition of nitrogen and sulfur.
3.	Uncertainties in Modeled Processes
	As discussed in the Policy Assessment, from an uncertainty perspective, gaps in field measurement data are related to uncertainties in modeled processes and in the specific application of such models.  As noted above, processes that are embodied in an AAI-based standard are modeled using the CMAQ atmospheric model and steady state ecological models.  These models are characterized in the Integrated Science Assessment as being well established and they have undergone extensive peer review.  Nonetheless, the application of these models for purposes of specifying the factors in the AAI equation, on an ecoregion scale, is a new application that introduces uncertainties, as noted below, especially in areas with limited observational data that can be used to evaluate this specific application.  Understanding uncertainties in relevant modeled process thus involves consideration of the uncertainties associated with applying each model as well as the combination of these uncertainties as the models are applied in combination within the AAI framework.
      With regard to the application of CMAQ for purposes of use in an AAI-based standard, the modeling of dry deposition has been identified as having a relatively high degree of uncertainty.  Due to a combination of system complexity and resource constraints, there is no routine observational basis for directly comparing modeled dry deposition and measurements.  Periodic dry deposition flux experiments covering a variety of vegetation, surfaces and meteorology across seasons would enable a more robust evaluation of modeled deposition of nitrogen and sulfur.  Given the difficulty in acquiring dry deposition observations, it becomes especially important to evaluate the model's ability to capture temporal and spatial ambient air patterns of individual nitrogen and sulfur species which are used to drive dry deposition calculations in models.  For example, reducing a generally acknowledged positive bias in model-predicted SO2 relative to observations is especially relevant to the AAI-based standard, as SO2 deposition is a dominant contributor to total acidifying deposition in the eastern U.S.  With respect to oxidized nitrogen, observations of individual NOy species are important as air quality models calculate the individual deposition of each species.  The modeled transference ratios, TNOy and TSOx used in factors F3 and F4 rely on CMAQ's ability to characterize both deposition and concentration.   Consequently, a better understanding of the variability of these factors within and across ecoregions could be achieved by improved availability of measured ambient concentrations and deposition observations.
	Steady state biogeochemical ecosystem modeling is used to develop critical load estimates that are incorporated in the AAI equation through factor F1.  Consequently, the Policy Assessment notes that an estimate of the temporal response of surface water ANC to deposition and air concentration changes is not directly available.  Lacking a predicted temporal response impairs the ability to conduct accountability assessments down to the effects level.  Accountability assessments would examine the response of each step in the emissions source through air concentration  -  deposition -- surface water quality  -  biota continuum.  The steady state assumption at the ecosystem level does not impair accountability assessments through the air concentration/deposition range of that continuum. However, in using steady state ecosystem modeling, several assumptions are made relative to the long-term importance of processes related to soil adsorption of major ions and ecosystem nitrogen dynamics.  Because these models often were developed and applied in glaciated areas with relatively thin and organically rich soils, their applicability is relatively more uncertain in areas such as those in the non-glaciated clay-based soil regions of the central Appalachians.  Consequently, it is desirable to develop the information bases to drive simple dynamic ecosystem models that incorporate more detailed treatment of subsurface processes, such as adsorption and exchange processes and sulfate absorption.
4.	Applying Knowledge of Uncertainties
	An understanding of the relative uncertainties in a system assists in setting priorities for data collection efforts and research, with the expectation that such efforts would reduce uncertainties over time and afford greater confidence in applications of an AAI-based standard.   Because of the uniquely wide breadth of pollutants and environmental media addressed by an AAI-based multi-pollutant standard, there are a wide range of uncertainties that are important to consider relative to single pollutant standards that typically address only direct effects of ambient air exposures.  For an AAI-b ased standard, an improved understanding of the uncertainties across the various modeled processes at the ecoregion scale would lead to greater confidence in the degree of protection afforded by the standard.
	The Policy Assessment notes that there is generally low uncertainty with regard to the conceptual development and related major components of this standard.  In recognizing the scientific soundness of the basic structure of this standard, the Policy Assessment notes that future efforts would be appropriately directed at expanding the availability of relevant data for ecoregion-specific evaluation and application of the relevant modeling of ecological and atmospheric processes, as identified above.  Such efforts would further support consideration of an AAI-based standard and would guide field studies and analyses designed to improve the longer-term confidence in such a standard.
G.	CASAC Advice
	The CASAC has advised EPA concerning the Integrated Science Assessment, the Risk and Exposure Assessment, and the Policy Assessment.  CASAC has endorsed EPA's interpretation of the science embodied in the Integrated Science Assessment and the assessment approaches and conclusions incorporated in the Risk and Exposure Assessment.
	Most recently, CASAC has considered the information in the final Policy Assessment in providing its recommendations on the review of the new multi-pollutant standard developed in that document and discussed above (Russell and Samet, 2011a).  In so doing, CASAC has expressed general support for the conceptual framework of the standard based on the underlying scientific information, as well as for the conclusions in the Policy Assessment with regard to indicators, form, averaging time, and level of the standard that are appropriate for consideration by the Agency in reaching decisions on the review of the secondary NAAQS for oxides of nitrogen and sulfur:
      The final Policy Assessment clearly sets out the basis for the recommended ranges for each of the four elements (indicator, averaging time, level and form) of a potential NAAQS that uses ambient air indicators to address the combined effects of oxides of nitrogen and oxides of sulfur on aquatic ecosystems, primarily streams and lakes. As requested in our previous letters, the Policy Assessment also describes the implications of choosing specific combinations of elements and provides numerous maps and tabular estimates of the spatial extent and degree of severity of NAAQS exceedances expected to result from possible combinations of the elements of the standard.

      We believe this final PA is appropriate for use in determining a secondary standard to help protect aquatic ecosystems from acidifying deposition of oxides of sulfur and nitrogen. EPA staff has done a commendable job developing the innovative Aquatic Acidification Index (AAI), which provides a framework for a national standard based on ambient concentrations that also takes into account regional differences in sensitivities of ecosystems across the country to effects of acidifying deposition. (Russell and Samet, 2011a)

	CASAC also recommended that as EPA moves forward in the regulatory process "some attention should be given to our residual concern that the available data may reflect the more sensitive water bodies and thus, the selection of percentiles of waterbodies to be protected could be conservatively biased" (Russell and Samet, 2011a).  In additional, CASAC found some improvements could be made to the uncertainty analysis, as noted below.
With respect to indicators, CASAC supports the use of SOx and NOy as ambient air indicators (discussed above in section III.A) and ANC as the ecological indicator (discussed above in section III.B.1):
	The use of total reactive oxidized nitrogen (NOy) and sulfur oxides (SOx) as atmospheric  indicators of oxidized nitrogen (N) and sulfur (S) atmospheric concentrations is well justified.  The use in the Aquatic Acidification Index (AAI) of NOy and SOx as atmospheric indicators of N and S concentrations is useful and corresponds with other efforts by EPA. As we have stated previously, CASAC also agrees that acid neutralizing capacity (ANC) is the most appropriate ecological indicator of aquatic ecosystem response and resiliency to acidification. (Russell and Samet, 2011a)
	With respect to the form of the standard (discussed above in section III.B), CASAC stated the following:
      EPA has developed the AAI, an innovative "form" of the NAAQS itself that incorporates the multi-pollutant, multi-media, environmentally modified, geographically variable nature of SOx/NOy deposition-related aquatic acidification effects. With the caveats noted below, CASAC believes that this form of the NAAQS as described in the final Policy Assessment is consistent with and directly reflective of current scientific understanding of effects of acidifying deposition on aquatic  ecosystems. (Russell and Samet, 2011a)

      CASAC agrees that the spatial components of the form in the Policy Assessment are reasonable and that use of Omernick's ecoregions (Level III) is appropriate for a secondary NAAQs intended to protect the aquatic environment from acidification . . . (Russell and Samet, 2011a)

	The "caveats" noted by CASAC include a recognition of the importance of continuing to evaluate the performance of the CMAQ and ecological models to account for model uncertainties and to make the model-dependent factors in the AAI more transparent.  In addition, CASAC noted that the role of DOC and its effects on ANC would benefit from further refinement and clarification (Russell and Samet, 2011a).  While CASAC expressed the view that the "division of ecoregions into `sensitive' and `non-sensitive' subsets, with a more protective percentile applied to the sensitive areas, also seems reasonable" (Russell and Samet, 2011a), CASAC also noted that there was the need for greater clarity in specifying how appropriate screening criteria would be applied in assigning ecoregions to these categories. Further, CASAC identified potential biases in critical load calculations and in the regional representativeness of available water chemistry data, leading to the observation that a given percentile of the distribution of estimated critical loads may be protective of a higher percentage of surface waters in some regions (Russell and Samet, 2011a).
	With respect to averaging time (discussed above in section III.C), CASAC stated the following:
      Considering the cumulative nature of the long-term adverse ecological effects and the year-to-year variability of atmospheric conditions (mainly in the amount of precipitation), CASAC concurs with EPA that an averaging time of three to five years for the AAI parameters is appropriate. A longer averaging time would mask possible trends of AAI, while a shorter averaging time would make the AAI being more influenced by the conditions of the particular years selected. (Russell and Samet, 2011a)

	With respect to level as well as the combination of level and form as they are presented as alternative standards (discussed above in sections III.D-E), CASAC stated the following:
      CASAC agrees with EPA staff's recommendation that the "level" of the alternative AAI standards should be within the range of 20 and 75 μeq/L. We also recognize that both the "level" and the form of any AAI standard are so closely linked in their effectiveness that these two elements should be considered together. (Russell and Samet, 2011a)

       When considered in isolation, it is difficult to evaluate the logic or implications of selecting from percentiles (70th to 90th) of the distribution of estimated critical loads for lakes in sensitive ecoregions to determine an acceptable amount of deposition for a given ecoregion. However, when these percentile ranges are combined with alternative levels within the staff-recommended ANC range of 20 to 75 microequivalents per liter (μeq/L), the results using the AAI point to the ecoregions across the country that would be expected to require additional protection from acidifying deposition.  Reasonable choices were made in developing the form.  The number of acid sensitive regions not likely to meet the standard will be affected both by choice of ANC level and the percentile of the distribution of critical loads for lakes to meet alternative ANC levels in each region.  These combined recommendations provide the Administrator with a broad but reasonable range of minimally to substantially protective options for the standard. (Russell and Samet, 2011a)

	CASAC also commented on EPA's uncertainty analysis, and provided advice on areas requiring further clarification in the proposed rule and future research.  CASAC found it "difficult to judge the adequacy of the uncertainty analysis performed by EPA because of lack of details on data inputs and the methodology used, and lack of clarity in presentation" (Russell and Samet, 2011a).  In particular, CASAC identified the need for more thorough model evaluations of critical load and atmospheric modeling, recognizing the important role of models as they are incorporated in the form of the standard.  In light of the innovative nature of the standard developed in the Policy Assessment, CASAC identified "a number of areas that should be the focus of further research" (Russell and Samet, 2011a).  While CASAC recognized that EPA staff was able to address some of the issues in the Policy Assessment, they also noted areas "that would benefit from further study or consideration in potential revisions or modifications to the form of the standard."  Such research areas include "sulfur retention and mobilization in the soils, aluminum availability, soil versus water acidification and ecosystem recovery times."  Further, CASAC encouraged future efforts to monitor individual ambient nitrogen species, which would help inform further CMAQ evaluations and the specification of model-derived elements in the AAI equation (Russell and Samet, 2011a).
H.	Administrator's Proposed Conclusions
	Having concluded that the existing NO2 and SO2 secondary standards are neither sufficiently protective nor appropriate to address deposition-related effects associated with oxides of nitrogen and sulfur (section II.D above), the Administrator has considered whether it is appropriate at this time to set a new multi-pollutant standard for that purpose.  In particular, she has focused on the new standard developed in the Policy Assessment and reviewed by CASAC, as discussed above.  In so doing, the Administrator first considered the extent to which there is a scientific basis for development of such a standard, specifically with regard to a standard that would provide protection from deposition-related aquatic acidification in sensitive aquatic ecosystems in areas across the country.  As discussed above, the Administrator notes that the Integrated Science Assessment concludes that the available scientific evidence is sufficient to infer a causal relationship between acidifying deposition of nitrogen and sulfur in aquatic ecosystems, and that the deposition of oxides of nitrogen and sulfur both cause such acidification under current conditions in the U.S.   Further, the Integrated Science Assessment concludes that there are well-established water quality and biological indicators of aquatic acidification as well as well-established models that link deposition, water quality, and effects on ecosystem biota, and that ecosystem sensitivity to acidification varies across the country according to present and historic nitrogen and sulfur deposition as well as geologic, soil, vegetative, and hydrologic factors.  Based on these considerations, the Administrator agrees with the conclusion in the Policy Assessment, and supported by CASAC, that there is a strong scientific basis for development of such a standard.
	The Administrator also recognizes that the conceptual framework for an ecologically relevant, multi-pollutant standard, which was initially explored in the Risk and Exposure Assessment and further developed in the Policy Assessment, builds on the information in the Integrated Science Assessment.  She notes that the structure of the standard addresses the combined effects of deposition from oxides of nitrogen and sulfur by characterizing the linkages between ambient concentrations, deposition, and aquatic acidification, and that the structure of the standard takes into account relevant variations in these linkages across the country.  Further, she recognizes the standard depends on atmospheric and ecological modeling to specify the terms of an equation that incorporates these linkages.  This equation, which defines an aquatic acidification index (AAI), has the effect of translating spatially variable ecological effects into a national standard.  She recognizes that while the standard is innovative and unique, the structure of the standard is well grounded in the science underlying the relationships between ambient concentrations of oxides of nitrogen and sulfur and the aquatic acidification related to deposition of nitrogen and sulfur associated with such ambient concentrations.
	While the Administrator recognizes the strong scientific foundation for the structure of the AAI standard, she also recognizes a number of inherent uncertainties and complexities that are relevant to the question of whether it is appropriate at this time to set such a standard.  As discussed above, these uncertainties and complexities generally relate not to the structure of the standard, but to the quantification of the various elements of the standard, such as the F factors discussed earlier in this section and their representativeness at an ecoregion scale.  These uncertainties and complexities currently limit efforts to characterize the degree of protectiveness that would be afforded by such a standard, within the ranges of levels and forms identified in the Policy Assessment, and the representativeness of F factors in the AAI equation described above and in the Policy Assessment.  These important uncertainties have been generally categorized as limitations in available field data as well as uncertainties that are related to reliance on the application of ecological and atmospheric modeling at the ecoregion scale to specify the various elements of the AAI.
	With regard to data limitations, the Administrator observes that there are several important limitations in the available data upon which elements of the AAI are based.  For example, while ambient measurements of NOy are made as part of a national monitoring network, the monitors are not located in locations that are representative of sensitive aquatic ecosystems.  While air and water quality data are generally available in areas in the eastern U.S., there is relatively sparse coverage in mountainous western areas where a number of sensitive aquatic ecosystems are located.  Further, even in areas where relevant data are available, small sample sizes impede efforts to characterize the representativeness of the available data, which was noted by CASAC as being of particular concern.  Also, measurements of reduced forms of nitrogen are available from only a small number of monitoring sites, and emission inventories for reduced forms of nitrogen used in atmospheric modeling are subject to considerable uncertainty.
	With regard to uncertainties related to the use of ecological and atmospheric modeling, the Administrator notes in particular that model results are difficult to evaluate due to a lack of relevant observational data.  For example, relatively large uncertainties are introduced by a lack of data with regard to pre-industrial environmental conditions and other parameters that are necessary inputs to critical load models that are the basis for factor F1 in the AAI equation.  Also, observational data are not generally available to evaluate the modeled relationships between nitrogen and sulfur in the ambient air and associated deposition, which are the basis for the other factors (i.e., F2, F3, and F4) in the AAI equation.
	In combination, these limitations and uncertainties result in a considerable degree of uncertainty as to how well the quantified elements of the AAI standard would predict the actual relationship between varying ambient concentrations of oxides of nitrogen and sulfur and steady state ANC levels across the distribution of water bodies within the various ecoregions in the U.S.  Because of this, there is considerable uncertainty as to the actual degree of protectiveness that such a standard would provide, especially for acid-sensitive ecoregions.  The Administrator recognizes that the AAI equation, with factors quantified as discussed above and described more fully in the Policy Assessment, generally performs well in identifying areas of the country that are sensitive to such acidifying deposition and indicates, as expected, that lower ambient levels of oxides of nitrogen and sulfur would lead to higher calculated AAI values.  However, the uncertainties discussed here concern the actual degree of protection that would be afforded such areas by any specific target ANC level and percentile of water bodies that would be chosen in setting a new AAI standard.
	In considering these uncertainties, the Administrator notes that CASAC acknowledged that important uncertainties remain that would benefit from further study and data collection efforts, which might lead to potential revisions or modifications to the form of the standard developed in the Policy Assessment.  She also notes that CASAC encouraged the Agency to engage in future monitoring and model evaluation efforts to help inform the specification of model-derived elements in the AAI equation.
	Based on the above considerations, the Administrator has strong reservations about the appropriateness of setting a new multi-pollutant standard to address deposition-related effects of oxides of nitrogen and sulfur on aquatic acidification at this time.  Setting a NAAQS generally involves consideration of the degree of uncertainties in the science and other information, such as gaps in the relevant data and, in this case, limitations in the evaluation of the application of relevant ecological and atmospheric models at an ecoregion scale.  The issue here is the appropriate public welfare policy judgment to be made in light of the specific circumstances in this review.  As noted above, it is not a question of uncertainties about the scientific soundness of the structure of the AAI, but instead uncertainties in the quantification and representativeness of the elements of the AAI as they vary in ecoregions across the country.  At present, these uncertainties interfere with understanding the degree of protectiveness that would be afforded various ecoregions across the country by a new standard defined in terms of a specific nationwide target ANC level and a specific percentile of water bodies for acid-sensitive ecoregions.  The Administrator has considered whether these uncertainties could be appropriately accounted for by choosing either a more or less protective target ANC level and percentile of water bodies than would otherwise be chosen if the uncertainties did not substantially limit the confidence that can appropriately be ascribed to the quantification of the AAI elements.  However, in the Administrator's judgment, the uncertainties are of such nature and magnitude that there is no reasoned way to choose such a specific nationwide target ANC level or percentile of water bodies that would appropriately account for the uncertainties, since neither the direction nor the magnitude of change from the target level and percentile that would otherwise be chosen can reasonably be ascertained at this time.
	Based on the above considerations, the Administrator judges that the current limitations in relevant data and the uncertainties associated with specifying the elements of the AAI based on modeled factors are of such nature and degree as to prevent her from reaching a reasoned decision such that she is adequately confident as to what level and form (in terms of a selected percentile) of such a standard would provide an intended degree of protection of public welfare.  	While acknowledging that CASAC supported moving forward to establish the standard developed in the Policy Assessment, the Administrator also observes that CASAC supported conducting further field studies that would better inform the continued development or modification of such as standard.  Given the large uncertainties and complexities inherent in quantifying the elements of such a standard, largely deriving from the unprecedented nature of the standard under consideration in this review, and having fully considered CASAC's advice, the Administrator provisionally concludes that it is premature to set a new, multi-pollutant secondary standard for oxides of nitrogen and sulfur at this time, and as such she is not proposing such a new secondary standard.
	Instead, the Administrator determines that the Agency should undertake a field pilot program to gather additional data, and that it is appropriate that such a program be undertaken before, rather than after, reaching a decision to set such a standard.  As described below in section IV, the purpose of the program is to collect and analyze data so as to enhance our understanding of the degree of protectiveness that would likely be afforded by a standard based on the AAI as developed in the Policy Assessment.  Data generated by this field program will also support development of an appropriate monitoring network that would work in concert with such a standard to result in the intended degree of protection.  The data and analyses generated as a result of this program will serve to inform the next review of the NAAQS for oxides of nitrogen and sulfur.
	Based on the above considerations, the Administrator is deferring the setting of a new multi-pollutant secondary standard in this review, and is proposing not to set such a secondary standard at this time.  In reaching this decision, the Administrator recognizes that the new NO2 and SO2 primary 1-hour standards set in 2010, while not ecologically relevant, will nonetheless result in reductions in oxides of nitrogen and sulfur that will directionally benefit the environment by reducing NOy and SOx deposition to sensitive ecosystems.  The Administrator observes that any such environmental benefits will occur as a result of strategies designed to meet the new primary standards, and that in this case no additional benefit would result from setting new secondary standards identical to those new primary standards.
	Having reached this decision, the Administrator also recognizes that a new, innovative AAI-based standard would raise significant implementation issues that would need to be addressed consistent with the CAA requirements for implementation-related actions following the setting of a new NAAQS.  It will take time to address these issues, during which the Agency will be conducting a field pilot program to gather relevant data and the environment will benefit from reductions in oxides of nitrogen and sulfur resulting from the new NO2 and SO2 primary standards, as noted above, as well as reductions expected to be achieved from EPA's proposed Transport Rule and Mercury and Air Toxics standards.  These implementation-related issues are discussed in more detail below in section IV.A.5.
	The Administrator solicits comment on all aspects of this proposed decision, including the framework and elements of a multi-pollutant standard for oxides of nitrogen and sulfur to address deposition-related effects on sensitive ecosystems, with a focus on aquatic acidification, and the uncertainties and complexities associated with the development of such a standard at this time.  The Administrator also solicits comment on the field pilot program and related monitoring methods as discussed below in section IV.
IV.	Field Pilot Program and Ambient Monitoring
      This section describes EPA's plans for a field pilot program and the evaluation of monitoring methods for ambient air indicators of oxides of nitrogen (NOy) and oxides of sulfur (SOx) to implement the Administrator's decision to undertake such a field monitoring program in conjunction with her decision to propose not to set a new multi-pollutant secondary standard in this review, as discussed above in section III.H.  As noted above and discussed below in section IV.A, the field pilot program is intended to collect and analyze data so as to enhance our understanding of the degree of protectiveness that would likely be afforded by a standard based on the AAI as developed in the Policy Assessment.  Data generated by this field program would also support development of an appropriate monitoring network that would work in concert with such a standard to result in the intended degree of protection.  As discussed below in section IV.B, the evaluation of monitoring methods focuses on the development of Federal Reference Methods/Federal Equivalent Methods (FRM/FEM) for NOy and SOx.  EPA notes that the monitoring program described here is intended to supplement existing monitoring programs and will require additional resources.
A.	Field Pilot Program
	This section presents the objectives of a field pilot program (section IV.A.1) that would gather relevant field data over a five-year period in a sample of 3 to 5 sensitive ecoregions across the country.  An overview of the scope and structure of the field program, with a focus on measurements of ambient air indicators of oxides of nitrogen and sulfur, is presented in section IV.A.2.  Section IV.A.3 explains the role of additional complementary measurements beyond the ambient air indicators that would be included in the program, and section IV.A.4 discusses a parallel longer-term research agenda, both of which are guided by the uncertainties discussed above in section III.  Section IV.A.5 identifies implementation challenges presented by an AAI-based standard that could be addressed in parallel with a field pilot program.  Section IV.A.6 discusses engagement with stakeholder groups as part of the planned pilot program.
1.	Objectives
      Consideration of a new multi-pollutant standard to address deposition-related effects on sensitive aquatic ecoregions raises unique challenges relative to those typically raised in reviews of existing NAAQS for which an established network of FRM/FEMs, designed to measure the indicator pollutant, is generally available.  The primary goal of this field pilot program, and the related monitoring program discussed in section IV.B, is to enhance our understanding of the degree of protectiveness that would likely be afforded by a standard based on the AAI, as described above in section III, through the following objectives:
        (1)  evaluate measurement methods for the ambient air indicators of NOy and SOx and consider designation of such methods as FRMs;
        (2)  examine the variability and improve characterization of concentration and deposition patterns of oxides of nitrogen and sulfur, as well as reduced forms of nitrogen, within and across a number of sensitive ecoregions across the country;
        (3)  develop updated ecoregion-specific factors (i.e., F1 through F4) for the AAI equation based in part on new observed air quality data within the sample ecoregions as well as on updated nationwide air quality model results and expanded critical load data bases, and explore alternative approaches for developing such representative factors;
        (4)  calculate ecoregion-specific AAI values using observed NOy and SOx data and updated ecoregion-specific factors to examine the extent to which the sample ecoregions would meet a set of alternative AAI-based standards;
        (5)  develop air monitoring network design criteria for an AAI-based standard;
        (6)  assess the use of total nitrate measurements as a potential alternative indicator for oxides of nitrogen;
        (7)  supoprt related longer-term research efforts, including enhancements to and evaluation of modeled dry deposition algorithms; and
        (8)  facilitate stakeholder engagement in addressing implementation issues associated with possible future adoption of an AAI-based standard.
2.	Overview of Field Pilot Program
	The CASTNET program (Figure IV-1) affords an available infrastructure relevant to an AAI-based standard, given the location of sites in some acid-sensitive ecoregions and various measurements of sulfur and nitrogen species.  The EPA plans to use CASTNET sites in selected acid-sensitive ecoregions to serve as the platform for this pilot program, potentially starting in late 2012 and extending through 2018.  CASTNET sites in three to five ecoregions in acid-sensitive areas would collect NOy and SOx (i.e., SO2 and p-SO4) measurements over a five-year period.  The initial step in developing a data base of observed ambient air indicators for oxides of nitrogen and sulfur requires the addition of NOy samplers at the pilot study sites so that a full complement of indicator measurements are available to calculate AAI values.  These CASTNET sites would also be used to make supplemental observations useful for evaluation of CMAQ's characterization of factors F2  - F4 in the AAI equation.
      The selected ecoregions would account for geographic variability by including regions from across the U.S., including the east, upper midwest and west.  Each selected region would have at least two existing CASTNET sites.  Each of the pilot CASTNET sites would be used to verify the performance of the established methods, data retrieval and reporting procedures, and application of the measurements into the AAI equation.

Figure IV-1.  Location of CASTNET sites in relation to acid sensitive ecoregions.

      Over the course of this five-year pilot program, the most current national air quality modeling, based on the most current national emissions inventory, would be used to develop an updated set of F2  -  F4 factors.  A parallel multi-agency national critical load data base development effort would be used as the basis for calculating updated F1 factors.  As discussed above in section III.B, these factors would be based on average parameter values across an ecoregion.  Using this new set of F factors, observations of NOy and SOx derived from the pilot program, averaged across each ecoregion, would be used to calculate AAI values in the sample ecoregions.   The data from the pilot program would also be used to examine alternative approaches to generating representative air quality values, such as examining the appropriateness of spatial averaging in areas of high spatial variability.
3 . 	Complementary Measurements
      Complementary measurements may be performed at some sites in the pilot network to reduce uncertainties in the recommended methods and better characterize model performance and application to the AAI.  The CASAC Air Monitoring and Methods Subcommittee (AMMS) advised EPA that such supplemental measurements were of critical importance in a field measurement program related to an AAI-based standard (Russell and Samet, 2011b).
      Candidate complementary measurements to address sulfur, in addition to those provided by the CASTNET filter pack (CFP), include trace gas continuous SO2 and speciated PM2.5 measurements. The co-located deployment of a continuous SO2 analyzer with the CFP SO2 will provide test data for determining suitability of continuous SO2 measurements as an FEM, as well as producing valuable time series data for model evaluation purposes.  The weekly averaging time provided by the CFP adequately addresses the annual-average basis of an AAI-based secondary standard, but would not be applicable to short-term (i.e., 1-hour) average associated with the primary SO2 standard.  Conversely, because of the low concentrations associated with many acid-sensitive ecoregions, existing SO2 FRMs designated for use in determining compliance with the primary standard would not necessarily be appropriate for use in conjunction with an AAI-based secondary standard.
      Co-locating the PM2.5 sampler used in the EPA Chemical Speciation Network and the IMPROVE network at pilot network sites would allow for characterizing the relationship between the CFP-derived p-SO4 and the speciation samplers used throughout the state and local air quality networks.  Note that CASTNET already has several co-located IMPROVE chemical speciation samplers.  Because the AAI equation is based on concentration of p-SO4, the original motivation for capturing all particle size fractions is not as important relative to simply capturing the concentration of total p-SO4.
      Candidate measurements to complement oxidized nitrogen measurements, in addition to the CFP, include a mix of continuous and periodic sampling for the dominant NOy species, namely NO, true NO2, PAN, HNO3, and p-NO3.  While there are several approaches to acquiring these measurements, perhaps the most efficient strategy would take advantage of the available CFP total nitrate, and add a three-channel chemiluminescence instrument that will cycle between NOy, true NO2 and NO by adding photolytic detection for true NO2.  Other options for measuring true NO2 would include adding either a stand-alone photolytic or cavity ring-down spectroscopy instrument.  Measurements of PAN may be acquired either on a periodic basis through canister sampling and subsequent laboratory analysis or through emerging in-situ sampling and analysis methods.  Although the CFP yields a reliable measurement of total nitrate, t-NO3 (i.e., the sum of HNO3 and p-NH4) value, strong consideration may be given to direct measurement of HNO3, which has the highest deposition velocity of all the dominant NOy species.  Similar to the use of continuous SO2 data, these speciated NOy data serve two purposes by evaluating total NOy instrument behavior and air quality model evaluation.  The measurement of individual NOy species can be used to generate site-specific NOy values for comparison to modeled NOy, and will likely provide insight into and improvement of modeled dry deposition.
      The CASAC AMMS (Russell and Samet, 2011b) recommended that EPA consider the use of t-NO3 obtained from CASTNET sampling as an indicator for NOy, reasoning that t-NO3 is typically a significant fraction of deposited oxidized nitrogen in rural environments and CASTNET measurements are widely available.  Collection of this data would support further consideration of using the CFP for t-NO3 as the indicator of oxides of nitrogen for use in an AAI-based secondary standard.
      The CASAC AMMS also recommended that total NHx (NH3 and p-NH4) be considered as a proxy for reduced nitrogen species, reasoning that the subsequent partitioning to NH3 and p-NH4 may be estimated using equilibrium chemistry calculations. Reduced nitrogen measurements are used to evaluate air quality modeling which is used in generating factor F2. Additional studies are needed to determine the applicability of NHx measurements and calculated values of NH3 and NH4 to the AAI.