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1 1 III. Rationale for Proposed Decision on Alternative Multi - pollutant Approach to 2 Secondary Standards for Aquatic Acidification 3 Having reached the conclusion that the current NO 2 and SO 2 secondary standards are not 4 adequate to provide appropriate protection against deposition

- related effects associated with 5 oxides of nitrogen and sulfur, the Administrator then considered what new multi

- pollutant 6 standard might be appropriate, at this time , to address such effects on public welfare. The 7 Administrator recognizes that the inherentl y complex and variable linkages between ambient 8 concentrations of nitrogen and sulfur oxides, the related deposited forms of nitrogen and sulfur, 9 and the ecological responses that are associated with public welfare effects call for consideration 10 of an ecologically

relevant design of a standard that reflects these linkages. The Administrator 11 also recognizes that characterization of such complex and variable linkages will necessaril y 12 require consideration of information and analy ses that have important limitations and 13 uncertainties. 14 Despite its complexity, an ecologicall y relevant multi

- pollutant standard to address 15 deposition

- related effects could still appropriatel y be defined in terms of the same basic elements 16 that are used to define any NAAQS

– indicator, form, averaging time, and level. The form 17 would incorporate additional structural elements that reflect relevant multi

- pollutant and 18 multimedia attributes. Th ese structural elements include the use of an ecological indicator, tied 19 to the ecological effect we are focused on, and other elements that account for ecologically 20 relevant factors other than ambient air concentrations. All of these elements would be ne eded to 21 enable a linkage from ambient air indicators to the ecological indicator to define an ecologicall y 22 relevant standard. As a result, such a standard would necessaril y be more complex than the 23

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2 NAAQS that have been set historically to address effects associated with ambient concentrations 1 of a single pollutant. 2 More specificall y, the Administrator considered an ecologicall y relevant multi

- pollutant 3 standard to address effects associated with acidifying deposition related to ambient 4 concentrations of o xides of nitrogen and sulfur in sensitive aquatic ecosy stems. This focus is 5 consistent with the information presented in the ISA, REA, and Policy Assessment which 6 highlighted the sufficiency of the quantity and quality

of the available evidence and assess ments 7 associated with aquatic acidification relative to the information and assessments available for 8 other deposition

- related effects, including terrestrial acidification and aquatic and terrestrial 9 nutrient enrichment. Based on its review of these docum ents, CASAC agreed that aquatic 10 acidification should be the focus for developing a new multi

- pollutant standard in this review. In 11 reaching conclusions about an air quality standard designed to address deposition

- related aquatic 12 acidification effects, the Administrator also recognizes that such a standard may also provide 13 some degree of protection against other deposition

- related effects. 14 As discussed in chapter 7 of the Policy Assessment, the development of a new multi

15 pollutant standard to address depos ition

- related aquatic acidification effects recognizes the need 16 for consideration of a nationally applicable standard for protection against adverse effects of 17 aquatic acidification to public welfare, while recognizing the complex and heterogeneous 18 interac tions between ambient air concentrations of nitrogen and sulfur oxides, the related 19 deposition of nitrogen and sulfur, and associated ecological responses. The development of such 20 a standard also needs to take into account the limitations and uncertaintie s in the available 21 information and anal ys es upon which characterization of such interactions are based. The 22 approach used in the Policy Assessment also recognizes that while such a standard would be 23

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3 national in scope and coverage, the effects to public we lfare from aquatic acidification will not 1 occur to the same extent in all locations in the U.S., given the inherent variability of the 2 responses of aquatic s ys tems to the effects of acidifying deposition. 3 As discussed above in section II, many locations i n the U.S. are naturall y protected 4 against acid deposition due to underl yi ng geological conditions. Likewise, some locations in the 5 U.S., including lands managed for commercial agriculture and forestry , are not likely to be 6 negativel y impacted b y current levels of nitrogen and sulfur deposition. As a result, while a new 7 ecologicall y relevant secondary standard would apply everywhere, it would be structured to 8 account for differences in the sensitivity of ecos ystems across the country. This would allow fo r 9 appropriate protection of sensitive aquatic ecosy stems, which are relativel y pristine and wild and 10 generall y in rural areas, and the services provided by such sensitive ecos ys tems, without 11 requiring more protection than is needed elsewhere. 12 As discuss ed below, the multi

- pollutant standard developed in the Policy Assessment 13 would employ

(1) NOy and SOx as the atmospheric ambient air indicators; (2) a form that takes 14 into account variable factors, such as atmospheric and ecos ys tem conditions that modify the 15 amounts of deposited nitrogen and sulfur; the distinction between oxidized and reduced forms of 16 nitrogen; effects of deposited nitrogen and sulfur on aquatic ecosy stems in terms of the 17 ecological indicator ANC; and the representativeness of water bodie s within a defined spatial 18 area; (3) a multi

- year averaging time, and (4) a standard level defined in terms of a single, 19 national target ANC value that, in the context of the above form, identifies the levels of 20 concentrations of NOy and SOx in the ambient air that would meet the standard. The form of 21 such a standard has been defined b y an index, termed an aquatic acidification index (AAI), 22 which reflects the relationship between ambient concentrations of NOy and SOx and aquatic 23

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4 acidification effects that result from nitrogen and sulfur deposition related to these ambient 1 concentrations. 2 In presenting the considerations associated with such an air quality standard to address 3 deposition

- related aquatic acidification effects, the following sections focus on each element of 4 the standard, including indicator (section III

. A), form (section III

. B), averaging time (section 5 III
. C), and level (section III

. D). Alternative combinations of levels and forms are discussed in 6 section III.E. Considerations related to important uncertainties inherent in such an approach are 7 discussed in section III

. F. Advice from CASAC on such a new standard is presented in section 8 III.G. The Administrator’s proposed decisions on such a new standard are presented in section 9 III.H. 10 A. Am bient Air Indicators 11 In considering alternative ambient air indicators, the Policy Assessment primarily

focuses 12 on the important attribute of association. Association in a broad sense refers to how well an 13 ambient air indicator relates to the ecological effects of interest by virtue of both the framework 14 that links the ambient indicator and effects and the empirical evidence that quantifies the 15 linkages. The Policy Assessment also considers how measurable or quantifiable an indicator is 16 to enable its use as an effective indicator of relevant ambient air concentrations. 17 As discussed above in section II.C, the Policy Assessment concludes that indicators other 18 than NO 2 and SO 2 should be considered as the appropriate indicators of oxides of nitrogen and 19 sulfur in the ambient air for protection against the acidification effects associated with deposition 20 of the associated nitrogen and sulfur. This conclusion is based on the reco gnition that all forms 21 of nitrogen and sulfur in the ambient air contribute to deposition and resulting acidification, and 22 as such, NO 2 and SO 2 are incomplete indicators. In principle, the ambient indicators should 23

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5 represent the species that are associate d with oxides of nitrogen and sulfur in the ambient air and 1 can contribute acidifying deposition. This includes both the species of oxides of nitrogen and 2 sulfur that are directl y emitted as well as species transformed in the atmosphere from oxides of 3 nitrogen and sulfur that retain the nitrogen and sulfur atoms from directly emitted oxides of 4 nitrogen and sulfur. All of these compounds are associated with oxides of nitrogen and sulfur in 5 the ambient air and can contribute to acidifying deposition. 6 Th e Policy

Assessment focuses in particular on the various compounds with nitrogen or 7 sulfur atoms that are associated with oxides of nitrogen and sulfur, because the acidifying 8 potential is specific to nitrogen and sulfur, and not other atoms (e.g., H, C, O ) whether derived 9 from the original source of oxides of nitrogen and sulfur emissions or from atmospheric 10 transformations. For example, the acidifying potential of each molecule of NO 2 , NO, HNO 3 or 11 PAN is identical, as is the potential for each molecule o f SO 2 or ion of particulate sulfate, p - SO 4 . 12 Each atom of sulfur affords twice the acidifying potential of each atom of nitrogen. 13 1. Oxides of Sulfur 14 As discussed in the Policy Assessment (US EPA, 2011, section 7.1.1), oxides of sulfur 15 include the gases sulfur monoxide (SO), sulfur dioxide (SO 2 ), sulfur trioxide (SO 3 ), disulfur 16 monoxide (S 2 O), and particulate

- phase sulfur compounds [referred to as SO 4 ] that result from 17 gas - phase sulfur oxides interacting with particles. However, the sum of SO 2 and SO 4 do es 18 represent virtually

the entire ambient air mass of sulfur that contributes to acidification. In 19 addition to accounting for virtually all the potential for acidification from oxidized sulfur in the 20 ambient air, there are reliable methods to monitor the concentrations of SO 2 and particulate SO 4 . 21 In addition, much of the data used to develop the technical basis for the standard developed in 22

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6 the Policy

Assessment is based on monitoring or modeling of these species. 1 The Policy 1 Assessment concludes that th e sum of SO 2 and SO 4 , referred to as SOx, are appropriate ambient 2 air indicators of oxides of sulfur because they represent virtually

all of the acidification potential 3 of ambient air oxides of sulfur and there are reliable methods suitable for measuring S O 2 and 4 SO 4 . 5 2. Oxides of Nitrogen 6 As discussed in the Policy Assessment (US EPA, 2011, section 7.1.2), total reactive 7 oxidized nitrogen, NOy , as defined in chapter 2 of the Policy Assessment, incorporates basicall y 8 all of the oxidized nitrogen species that have acidifying potential and as such, NOy should be 9 considered as an appropriate indicator f or oxides of nitrogen. NOy is an aggregate measure of 10 NO and NO 2 and all of the reactive oxidized products of NO and NO 2 . That is, NOy is a group 11 of nitrogen compounds in which all of the compounds are either an oxide of nitrogen or 12 compounds in which th e nitrogen atoms came from oxides of nitrogen. NOy is especiall y 13 relevant as an ambient indicator for acidification in that it both relates to the oxides of nitrogen in 14 the ambient air and also represents the acidification potential of all oxidized nitrog en species in 15 the ambient air, whether an oxide of nitrogen or derived from oxides of nitrogen. 16 There are currently available reliable methods of measuring aggregate NOy . The term 17 “aggregate” measure means that the NO Y , as measured, is not based on meas uring each 18 individual species of NOy and calculating an NOy value b y summing the individual species. 19 Rather, as described in chapter 2 of the Policy Assessment, current measurement techniques 20 process all of the individual NOy species to produce a single aggregate measure of all of the 21

1 As discussed in chapter 2 of the P olicy A ssessment , SO 2 and particulate SO 4 are routinely measured in ambient air mo nitoring networks, although only CASTNET filter packs do not intentionally exclude p article size fractions. The CMAQ treatment of SOx is the simple addition of both species, which are treated explicitly in the model formulation. All particle size fractions are included in the CMAQ SOx estimates.

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7 nitrogen atoms associated with any NOy species. Consequently , the NOy measurement 1 effectivel y provides the sum of all individual species, but the identity of the individual species is 2 lost. As discussed above, the accounting for the individual nitrogen atoms is an accounting of 3 the ambient air acidification potential of oxides of nitrogen and their transformation products and 4 therefore the most relevant ambient indicator for aquatic acidification effects associated with 5 oxi des of nitrogen. 6 This loss of the information on individual species motivated consideration of alternative 7 or more narrowl y defined indicators for oxides of nitrogen in the Policy Assessment. 8 Consideration of a subset of NOy species was based on the f ollowing reasoning. First, the actual 9 dry deposition of nitrogen is determined on an individual species basis by multiplying the species 10 concentration times a species

- specific deposition velocity and then summed to develop an 11 estimate of total dry deposition. Consequently, the use of individual ambient species has the 12 potential to be more consistent with the underlying science of deposition and, therefore, has the 13 potential to allow for a more rigorous evaluation of dry deposition with specialized field s tudies. 14 In addition, there has been a suggestion of focusing onl y on the most quickly depositing NOy 15 species, such as HNO 3 , as contributions from other NOy species such as NO 2 may be negligible. 16 These alternative indicators are discussed below. 17 The Poli cy

Assessment considers the relative merits of using each individual NOy 18 species as part of a group of indicators. In so doing, it was first noted that dry deposition of NOy 19 is treated as the sum of the deposition of each individual species in advanced process - based air 20 quality

models like CMAQ, as described in chapter 2 of the Policy Assessment. Conceptually 21 one could extend this process

- based approach b y using all NO Y species individually as separate 22 indicators for oxides of nitrogen and requiring, for example, measurements of each of the 23

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8 species, including the dominant species of HNO 3 , particulate nitrate (p

-NO 3 ) , true NO 2 , NO, and 1 PAN. The potential attraction of using individual species would be the reliance on actual 2 deposition velocities. This co uld have more phys ical meaning in comparison to a constructed 3 model of aggregate deposition of NOy , which is difficult to evaluate with observations because 4 of the assimilation of many species with disparate deposition behavior. The Policy Assessment 5 note s that the major drawback of using individual NOy species as the indicators is the lack of 6 reliable measurement techniques, especiall y for PAN and NO 2 in rural locations, which renders 7 the use of virtuall y any i ndividual NOy species, except for NO and perh aps p -NO 3 , as 8 functionally

inadequate from a measurement perspective. 9 The Policy

Assessment next considered the relative merits of using a subset of NOy 10 species as the indicators for oxides of nitrogen, as was discussed above for oxides of sulfur. To 11 the extent that certain species provide relativel y minor contributions to total NOy deposition, it 12 may

be appropriate to consider excluding them as part of the indicator. As discussed in chapter 2 13 of the Policy

Assessment, each nitrogen species within the ar ray of NOy species has species

14 specific dry

deposition velocities. For example, the deposition velocity of HNO 3 is much 15 greater than the velocity for nitrogen dioxide and, consequentl y, for a similar ambient air 16 concentration, HNO 3 contributes more depos ition of acidifying nitrogen relative to nitrogen 17 dioxide. In transitioning from source

- oriented urban locations to rural environments, the ratio of 18 the concentrations of HNO 3 and PAN to NO 2 increases. 19 Based on the reasoning that a larger fraction of the deposited NO Y is accounted for by 20 total nitrate (the sum of HNO 3 and p -NO 3 ), a surrogate for the more rapidly depositing fraction 21 of NOy , combined with the availability of reliable total nitrate measurements through the Clean 22 Air Status and Trends Network ( CASTNET ) , the Policy Assessment considered using total 23

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9 nitrate as the indicator for oxides of nitrogen ( US EPA, 2011, appendix E ). Nitrate would be 1 expected to correlate well with total reactive oxidized nitrogen deposition relative to NO Y (US 2 EPA, 2011 , chapter 2 ) , despite the inherent noise associated with variable contributions of low 3 deposition velocity

species (e.g., NO 2 ) that may have relatively

high ambient concentrations. 4 However, modeling simulations suggest that NOy may be a more robust indicat or, relative to 5 HNO 3 , in terms of relating absolute changes in ambient air concentrations to changes in nitrogen 6 deposition driven by changes in ambient concentrations of oxides of nitrogen (US EPA, 7 2011, Figure 2
- 32 ). 8 Based on the above considerations, th e Policy Assessment concludes that total reactive 9 oxidized nitrogen, NOy , should be considered as the appropriate ambient indicator for oxides of 10 nitrogen based on its direct relationship to oxides of nitrogen in the ambient air and its direct 11 relationship to deposition associated with aquatic acidification. Because NOy represents all of 12 the potentially

acidifying oxidized nitrogen species in the ambient air, it is appropriatel y 13 associated with the deposition of potentially acidifyingcompounds associated with oxides of 14 nitrogen in the ambient air. In addition, there are reliable methods available to measure NOy

. 15 Measurement of each individual species of NOy , or the measurement of only a subset of species 16 of NOy , is less appropriate because there are not reliable measurements methods available to 17 measure all of the individual species of NOy and a subset of species would fail to account for 18 significant portions of the oxidized reactive nitrogen that relates to acidification. 2 19 B. Form 20 Based on the evidence of the aquatic acidification effects caused by the deposition of 21 NOy

and SOx, the Policy

Assessment (US EPA, 2011, section 7.2) presents the development of a 22

2 The P olicy A ssessment also note s that NO Y is a useful measurement for model evaluation purposes , which is especially important, recognizing the unique role that CMAQ play s in the development of this standard, as described below in section III.B
.

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10 new form that is ecologically relevant for addressing such effects. The conceptual design for the 1 form of such a standard includes three main components: an ecological indicator, deposition 2 metrics that relate to the ecological indicator, and a function that relates ambient air indicators to 3 deposition metrics. Collectivel y, these three components li nk the ecological indicator to ambient 4 air indicators, as illustrated above in Fig II
- 1. 5 The simplified flow diagram in Figure II
- 1 compresses the various atmospheric, 6 biological, and geochemical processes associated with acidifying deposition to aquatic 7
ecos ys tems into a simplified conceptual picture. The ecological indicator (left box) is related to 8 atmospheric deposition through biogeochemical ecosy stem models (middle box), which 9 associate a target deposition load to a target ecological indicator. Once a target deposition is 10 established, associated allowable air concentrations are determined (right box) through the 11 relationships between concentration and deposition that are embodied in air quality models such 12 as CMAQ. The following discussion describes the development and rationale for each of these 13 components, as well as the integration of these components into the full expression of the form 14 of the standard using the concept of a national AAI that represents a target ANC level as a 15 function of ambi ent air concentrations. Spatial aggregation issues associated with defining each 16 of the terms of this index are also addressed below. 17 The AAI is designed to be an ecologically relevant form of the standard that determines 18 the levels of NOy

and SOx in th e ambient air that would achieve a target ANC limit for the U.S. 19 The intent of the AAI is to weight atmospheric concentrations of oxides of nitrogen and sulfur b y 20 their propensity

to contribute to acidification through deposition, given the fundamental 21
ac idifying potential of each pollutant, and to take into account the ecological factors that govern 22 acid sensitivity

in different ecosy stems. The index also accounts for the contribution of reduced 23

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11 nitrogen to acidification. Thus, the AAI encompasses those attributes of specific relevance to 1 protecting ecos ys tems from the acidifying potential of ambient air concentrations of NOy and 2 SOx. 3 1. Ecological Indicator 4 In considering alternative ecological indicators, the Policy Assessment again primarily 5 focuses on the attribute of association. In the case of an ecological indicator for aquatic 6 acidification, association refers to the relationship between the indicator and adverse effects as 7 discussed in section II. Because of the conceptual structure of the form of this standard (Figure 8 III
- 1), this particular ecological indicator must also link up in a meaningful and quantifiable 9 manner with acidifying atmospheric deposition. In effect, the ecological indicator for aquatic 10 acidification is the bridge between biological impairment and deposition of NOy and SOx. 11 This section presents the rationale in the Policy Assessment for selecting acid 12 neutralizing capacity (ANC) as the appropriate ecological indicator for consideration. 13 Recognizing that ANC is not itself the causative or toxic agent for adverse aquatic acidification 14 effects, the rationale for using ANC as the relevant ecological indicator is based on the 15 fol lowing: 16 (1) ANC is directly associated with the causative agents, pH and dissolved aluminum, both 17 through empirical evidence and mechanistic relationships; 18 (2) Empirical evidence shows very clear and strong relationships between adverse effects 19 and ANC; 20 (3) ANC is a m ore reliable indicator from a modeling perspective, allowing use of a body of 21 studies and technical analy ses related to ANC and acidification to inform the 22 development of the standard; and 23

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12 (4) ANC literally

embodies the concept of acidification as posed by the basic principles of 1 acid base chemistry and the measurement method used to estimate ANC and, therefore, 2 serves as a direct index to protect against acidification. 3 4 Ecological indicators of acidification in aquatic ecosy stems can be chemical or biologic al 5 components of the ecosystem that are altered b y the acidifying effects of nitrogen and sulfur 6 deposition. A desirable ecological indicator for aquatic acidification is one that is measurable or 7 estimable, linked causally to deposition of nitrogen and su lfur, and linked causally , either 8 directly

or indirectl y to ecological effects known or anticipated to adversely affect public 9 welfare. 10 As summarized in chapter 2 of the Policy Assessment, atmospheric deposition of NOy 11 and SOx causes aquatic acidification through the input of strong acid anions (e.g., NO 3 - and 12 SO 4 2
- ) that ultimately shifts the water chemistry equilibrium toward increased hydrogen ion 13 levels (or decreased pH). The anions are deposited either directly to the aquatic ecos ys tem or 14 indirectly via transformation through soil nitrification processes and subsequent drainage from 15 terrestrial ecos ys tems. In other words, when these anions are mobilized in the terrestrial soil, 16 they

can leach into adjacent water bodies. Aquatic acidification is indi cated by changes in the 17 surface water chemistry of ecos ys tems. In turn, the alteration of surface water chemistry has been 18 linked to negative effects on the biotic integrity of freshwater ecos ys tems. There is a suite of 19 chemical indicators that could be us ed to assess the effects of acidifying deposition on lake or 20 stream acid

- base chemistry . These indicators include acid neutralizing capacity (ANC); 21 alkalinity

(ALK); base neutralizing capacity, commonly referred to as acidity

(ACY); surface 22

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13 water pH; concentrations of trivalent aluminum, Al +3 ; and concentrations of major anions (SO 4 2
- , 1 NO 3 - ), cations (Ca2+ , Mg +2 , K+ ), or sums of cations or anions. 2 ANC and ALK are very similar quantities and are used interchangeabl y in the literature 3 and for some of the analy ses presented in this document. Both ANC and ALK are defined as the 4 amount of strong acid required to reach a specified equivalence point. For acid

- base solutions, 5 an equivalence point can be thought of as the point at which the addition of strong aci ds (i.e., 6 titration) is no longer neutralized by the solution. This explains the term acid neutralizing 7 capacity , or ANC, as ANC relates directly to the capacity of a s ys tem to neutralize acids. The 8 differences between ANC and ALK are based on operation al definitions and subject to various 9 interpretations. ANC is preferred over ALK as the body of scientific evidence has focused on 10 ANC and effects relationships. ALK is more widely associated with more general 11 characterizations of water quality such as the relative hardness of water associated with 12 carbonates. 13 Indictors such as the concentrations of specific anions, cations, or their groupings, while 14 relevant to acidification processes, are not robust acidification indicators as it is the relative 15 balance of cations and anions that is more directly associated with acidification. That balance is 16 captured b y ANC and ALK. Acidity, ACY, is the coverse of ANC and indicates how much 17 strong base it takes to reach an equivalence point. Because ACY is not us ed in most ecosy stem 18 assessments, the body of information relating ACY to effects is too limited to serve as a basis for 19 an appropriate ecological indicator. Aluminum and other metals are causative toxic agents that 20 directly

impair biological functions. However, aluminum, or metals in general, have high 21 variability

in concentrations that can be linked to effects, often at extremely low levels which in 22 some cases approach detectability limits, exhibit rapid transient responses, and are often 23

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14 confounded b y the presence of other toxic metals. These concerns limit the use of metals as 1 reliable and measurable ecological indicators. Hydrogen ion (H + ) concentrations, using their 2 negative logarithmic values, or pH, are well correlated with adverse effects, as dis cussed above 3 in section II.A, and determine the solubility of metals such as aluminum. However, pH is not a 4 preferred acidification indicator due to its highl y transient nature and other concerns, as 5 discussed below. 6 Having reasoned that ANC is a pref erred indicator to ALK, ACY, individual metals or 7 groupings of ions, the Policy Assessment considers the relative merits of ANC compared to pH, 8 which is a well recognized indicator of acidity and a more direct causative agent with regard to 9 adverse effects . First, the linkage between ANC and pH is considered in recognition of the 10 causative association between pH and effects. 11 ANC is not the direct causative toxic agent impacting aquatic species diversity . The 12 scientific literature generally emphasizes th e links between pH and adverse effects as described 13 above in section II.A. It is important, therefore, to consider the extent to which ANC and pH are 14 well related from a mechanistic perspective as well as through empirical evidence. ANC and 15 pH are co
- d ependent on each other based on the requirement that all solutions are electrically 16 neutral, meaning that any solution must satisfy the condition that all negatively charged species 17 must be balanced b y all positively charged species. ANC is defined as th e difference between 18 strong anions and cations (US EPA, 2011 , equation 7

- 13). 19 While the chemistry can be complex, the co

- dependency between ANC and pH is 20 explained by

recognizing that positively charged hydrogen, H + , is incorporated in the charge 21 balance relationships related to the overall solution chemistry which also defines ANC. The 22 positive, directional co

- dependency (i.e., ANC and pH increase together) is further explained in 23

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15 concept as ANC reflects how much strong acid (i.e., how much hydrogen ion) it takes to titrate to 1 an equivalence point. Strong observed correlations between pH and ANC as described in the 2 Policy

Assessment support these mechanistic relationships. 3 As discussed above in section II.A, there are well established examples of ANC 4 correlating strongl y with a variety of ecological effects which are summarized in the Policy 5 Assessment (US EPA, 2011, Table 3

- 1). Because pH and ANC are well correlated and linearl y 6 dependent over the pH ranges (4.5

- 6) where adverse ecological effects are observed, evidence of 7 clear associations exist between ANC and adverse ecological effects as described in the Policy 8 Assessment. In large measure, this dependence between pH and ANC and the relationship of 9 both pH and ANC to effects, speak directly to the appropriateness of ANC with respect to its use 10 as an ecological indicator. 11 Thus, there is a clear association between ANC and ecological effects, although there is a 12 more direct causal relationship between pH and effects. Nonetheless, ANC is preferred as an 13 ecological indicator based on its superior ability to provide a linkage with deposition in a 14 meaningful and quantifiable manner, a role that is served far more effectively by ANC than b y 15 pH. While both ANC and pH are clearly associated with the e ffects of concern, ANC is superior 16 in linking these effects to deposition. 17 The Policy

Assessment notes that the basis for this conclusion is that acidifying 18 atmospheric deposition of nitrogen and sulfur is a direct input of potential acidity (ACY), or, in 19 terms of ANC, such deposition is relevant to the major anions that reduce the capacity of a water 20 body

to neutralize acidity. Consequently , there is a well defined linear relationship between 21 potential acidifying deposition and ANC. This ANC

- depositio n relationship facilitates the 22 linkage between ecos ys tem models that calculate an ecological indicator and the atmospheric 23

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16 deposition of NOy

and SOx. On the other hand, there is no direct linear relationship between 1 deposition and pH. While acid inputs f rom deposition lower pH, the relationship can be 2 extremely

nonlinear and there is no direct connection from a modeling or mass balance 3 perspective between the amount of deposition entering a s ys tem and pH. The term “mass 4 balance” underlies the basic formulation of any physical modeling construct, for atmospheric or 5 aquatic s ys tems, and refers to the accounting of the flow of mass into a s ys tem, the 6 transformation to other forms, and the loss due to flow out of a s ys tem and other removal 7 processes. ANC is a conserved property. This means that ANC in a water body can be 8 accounted for b y knowledge of how much ANC initially exists, how much flows in and is 9 deposited, and how much flows out. In contrast, hydrogen ion concentration in the water, the 10 basis for pH, is not a conserved property as its concentration is affected b y several factors such 11 as temperature, atmospheric pressure, mixing conditions of a water body, and the levels of 12 several other chemical species in the s ys tem. The disadvantage of pH lackin g conservative 13 properties is that there is a very complex connection between changes in ambient air 14 concentrations of NOy and SOx and pH. 15 The discussion of basic water chemistry of natural sy stems in chapter 2 of the Policy 16 Assessment provides further de tails on why pH is not a conserved quantity and is subject to rapid 17 transient response behavior that makes it difficult to use as a reliable and functional ecological 18 indicator. The observed pH

- to - ANC relationship (US EPA, 2011, figure 7
- 2 ) partiall y expl ains 19 the concern with pH responding too abruptl y. In the region where pH ranges roughly from 4.5 20 to 6 and is of greatest relevance to effects (US EPA, 2011, figure 7

- 4 ), there clearly is more 21 sensitivity

of pH to changes in ANC in the ANC range from approximately 0 to 50 μeq/L . A 22 focus on this part of the ANC

- to - pH relationship shows that ANC associates well with pH in a 23

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17 fairl y linear manner. However, the pH range from 4.5 to 6 also includes one of the very steepest 1 parts of the slope relating pH as a function of ANC , where ANC ranges down below 0 μeq/L, 2 which is subject to very rapid change in ANC, or deposition inputs. This part of the relationship 3 coincides with reduced levels of ANC and hence with reduced ability to neutralize acids and 4 moderate p H fluctuations. This response behavior can be extended to considering how pH 5 would change in response to deposition, or ambient concentrations, of NOy and SOx, which can 6 be viewed as “ANC

- like” inputs. 7 In summary , because ANC clearl y links both to bio logical effects of aquatic acidification 8 as well as to acidifying inputs of NOy and SOx deposition, the Policy Assessment concludes that 9 ANC is an appropriate ecological indicator for relating adverse aquatic ecosystem effects to 10 acidifying atmospheric dep osition of SOx and NOy , and is preferred to other potential indicators. 11 In reaching this conclusion, the Policy Assessment notes that in its review of the first draft Policy 12 Assessment, CASAC concluded that “information on levels of ANC protective to fish and other 13 aquatic biota has been well developed and presents probably the lowest level of uncertainty in 14 the entire methodology” (Russell and Samet, 2010a). In its more recent review of the second 15 draft Policy

Assessment, CASAC agreed “that acid neutrali zing capacity is an appropriate 16 ecological measure for reflecting the effects of aquatic acidification” (Russell and Samet, 2010b; 17 p. 4). 18 2. Linking ANC to Deposition 19 There is evidence to support a quantified relationship between deposition of nitrogen and 20 sulfur and ANC. This relationship was anal yz ed in the REA for two case study areas, the 21 Adirondack and Shenandoah Mountains, based on time

- series modeling and observed trends. 22

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18 In the REA anal ys is, long

- term trends in surface water nitrate, sulfate and ANC were modeled 1 using Model of Acidification of Groundwater in Catchment (MAGI C) for the two case study 2 areas. These data were used to compare recent surface water conditions in 2006 with 3 preindustrial conditions (i.e. preacidification 1860). The results showed a marked increase in the 4 number of acid impacted lakes, characterized as a decrease in ANC levels, since the onset of 5 anthropogenic nitrogen and sulfur deposition, as discussed in chapter 2 of the Policy Assessment. 6 In the REA, more recent trends in ANC, over the period from 1990 to 2006, were assessed using 7 monitoring data collected at the two case study areas. In both case study areas, nitrate and 8 sulfate deposition decreased over this time period. In the Adirondack Mountains, this 9 corresp onded to a decreased concentration of nitrate and sulfate in the surface waters and an 10 increase in ANC (US EPA, 2009, section 4.2.4.2). In the Shenandoah Mountains, there was a 11 slight decrease in nitrate and sulfate concentration in surface waters corresp onding to modest 12 increase in ANC from 50 ueq/Lin 1990 to 67 ueq/L in 2006 (US EPA, 2009, section 13 4.2.4.3 , Appendix 4, and section 3.4). 14 In the REA, the quantified relationship between deposition and ANC was investigated 15 using ecos ys tem acidification mode ls, also referred to as acid balance models or critical loads 16 models (US EPA, 2011 , section 2 and US EPA, 2009, section 4 and Appendix 4). These models 17 quantify

the relationship between deposition of nitrogen and sulfur and the resulting ANC in 18 surface waters based on an ecos ys tem’s inherent generation of ANC and ability to neutralize 19 nitrogen deposition through biological and phys ical processes. A critical load is defined as the 20 amount of acidifying atmospheric deposition of nitrogen and sulfur beyond wh ich a target ANC 21 is not reached. Relatively high critical load values imply that an ecos ys tem can accommodate 22

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19 greater deposition levels than lower critical loads for a specific target ANC level. Ecos ys tem 1 models that calculate critical loads form the b asis for linking deposition to ANC. 2 As discussed in chapter 2 of the Policy Assessment, both dy

namic and steady

state 3 models calculate ANC as a function of ecos ys tem attributes and atmospheric nitrogen and sulfur 4 deposition, and can be used to calculat e critical loads. Steady state models are time invariant 5 and reflect the long term consequences associated with an ecos ys tem reaching equilibrium under 6 a constant level of atmospheric deposition. Dy namic models are time variant and take into 7 account th e time dependencies inherent in ecos ys tem hydrology , soil and biological processes. 8 Dy namic models like MAGI C can provide the time series response of ANC to deposition 9 whereas steady state models provide a single ANC relationship to any fixed deposition level. 10 Dy namic models naturally

are more complex than steady state models as they

attempt to capture 11 as much of the fundamental biogeochemical processes as practicable, whereas steady state 12 models depend on far greater parameterization and generalization of processes that is afforded, 13 somewhat, b y not having to accounting for temporal variability. 14 The Policy

Assessment notes that steady state models are capable of addressing the 15 question of what does it take to reach and sustain a specific level of ANC
. Dy namic models are 16 also capable of addressing that question, but can also address the question of how long it takes to 17 achieve that result. Dy namic models afford the ability for more comprehensive treatment of a 18 variety of processes throughout the s urface, soil and bedrock layers within an ecos ys tem. For 19 example, steady

state models treat sulfate as a mobile anion throughout the sy stem, meaning that 20 the sulfate that is deposited to a watershed enters the water column and is not influenced by soil 21 ad sorption or cation exchange. Dy namic models can incorporate these time variant processes. 22 The use of a steady state model treating sulfate as totally mobile does not necessarily conflict 23

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20 with the possibility

of sulfate acting as a less than mobile ion at certain times. The steady state 1 assumption is premised on the long term behavior of sulfate which can undergo periods of net 2 adsorption followed b y periods of net desorption which can balance out over time. The Policy 3 Assessment recognizes that as the richness of the available data increases, in terms of parameters 4 and spatial resolution, the incorporation of dy namic modeling approaches in the standard setting 5 process should become more feasible. In determining an appropriate modeling approach for the 6 development of a NAAQS in this review, the Policy Assessment considers both the relevance of 7 the question addressed as well as the ability to perform modeling that provides relevant 8 information for geographic areas across the country. 9 Dy

namic models require a large amount of catchment level

- specific data relative to 10 steady

state models. Because of the time invariant nature of steady state models, the data 11 requirements that integrate across a broad spectrum of ecos ys tem processes is achievable and 12 availab le now at the national level. Water quality data to support steady state models currently 13 exist for developing a national data base for modeling nearl y 10,000 catchments in the 14 contiguous U.S. In contrast, the data needs to support dy namic models for national

- scale 15 anal ys es simply

are not available at this time. Further, the information provided by steady state 16 modeling would be sufficient to develop and analyze alternative NAAQS and the kind of 17 protection they

would afford. While it would be of interes t to also obtain information about how 18 much time it would take for a target ANC level to be achieved, the absence of such information 19 does not preclude developing and evaluating alternative NAAQS using the AAI structure. Based 20 on the above considerations, the Policy Assessment concludes that at this time steady state 21 critical load modeling is an appropriate tool for linking long

- term ANC levels to atmospheric 22 deposition of nitrogen and sulfur for development of an AAI that has national applicability

. 23

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21 A s teady state model is used to define the critical load, which is the amount of 1 atmospheric deposition of nitrogen (N) and sulfur (S) beyond which a target ANC is not 2 achieved and sustained. 3 It is expressed as: 3 4 CLANClim (N + S) = ([BC] 0 *

- [ANC lim ]) Q + Nec o (III

- 1) 5 6 Where: 7 CLANClim (N + S) is the critical load of deposition, with units of equivalent charge/(area

- time); 8 [BC] 0 * is the natural contribution of base cations from weathering, soil processes and 9 preindustrial deposition, with units of equivalent charge/volume; 10 [ANC

lim ] is the target ANC value, with units of equivalent charge/volume; 11 Q is the catchment level runoff rate governed b y water mass balance and dominated by 12 precipitation, with units of distance/time; and 13 Neco is the amount of nitrogen deposition that is effectivel y neutralized by a variety of biological 14 (e.g., nutrient uptake) and phy sical processes, with units of equivalent charge/ (area

- time). 15 16 Equation III

- 1 is a modified expression that adopts the basic formulation of the steady 17 state models that are described in chapter 2 of the Policy Assessment. More detailed discussion 18 of the rationale, assumptions and derivation of equation III

- 1, as well as all of the equations in 19 this section, are included in Appendix B of the Policy Ass essment. The equation simply reflects 20 the amount of deposition of nitrogen and sulfur from the atmosphere, CLANClim (N + S) , that is 21 associated with a sustainable long

- term ANC target, [ANC lim ] , given the capacity of the natural 22

3 This section discusses the linkages between d eposition of nitrogen and sulfur and ANC. Section III.B.3 then discusses the linkages between atmospheric concentrations of NOy and SOx and deposition of nitrogen and sulfur

.

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22 sy stem to generate ANC, [B C] 0 * , and the capacity of the natural s ys tem to neutralize nitrogen 1 deposition, Neco . This expression of critical load is valid when nitrogen deposition is greater 2 than Neco. 4 The runoff rate, Q , allows for balancing mass in the two environmental mediums

– 3 atmosphere and catchment. This critical load expression can be focused on a single water s ys tem 4 or more broadl y. To extend applicability of the critical load expression (equation III

- 1) from the 5 catchment level to broader spatial areas, the terms Q r and CLr, are used, which are the runoff rate 6 and critical load, respectively , of the region over which all the atmospheric terms in the equation 7 are defined. 8 In considering the contributions of SOx or NOy species to acidification, it is useful to 9 think of every

depositing nitrogen atom as supplying one equivalent charge unit and every sulfur 10 atom as depositing two charge units. The Policy Assessment uses equivalent charge per volume 11 as a normalizing tool in place of the more familiar metrics such as mass or moles per volume. 12 This allows for a clearer explanation of many of the relationships between atmospheric and 13
ecos ys tem processes that incorporate mass and volume unit conventions somewhat specific to 14 the environmental media of concern (e.g., m 3 for air and liter for liquid water). Equivalent 15 charge reflects the chemistry equilibrium fundamentals that assume electroneutrality , or 16 balancing charge where the sum of cations alway s equals the sum of anions. 17 As presented above, the terms S and N in the CLANClim (N + S) term broadly represent all 18 species of sulfur or nitrogen that can contribute to acidifying deposition. This follows 19 conventions used in the scientific literature that addresses critical loads, and it reflects all 20 possible acidifying contributions from any sulfur or nitrogen species. For all practical purposes, 21 S reflects SOx as described above, the sum of sulfur dioxide gas and particulate sulfate. 22

4 Because Neco is only relevant to nitrogen deposition, in rare cases where Neco is greater than the total nitrogen deposition, the critical load would be defined only in terms of acidifying deposition of sulfur and the Neco term in equation III

- 1 wo uld be set to zero.

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23 However, N in equation III

- 1 includes both oxidized forms, consistent with the ambie nt 1 indicator, NOy , in addition to the reduced nitrogen species, ammonia and ammonium ion, 2 referred to as NHx. NHx is included in the critical load formulation because it contributes to 3 potentially

acidifying nitrogen deposition. Consequently , from a mas s balance or modeling 4 perspective, the form of the standard needs to account for NHx, as described below. 5 3. Linking Deposition to Ambient Air Indicators 6 The last major component of the form illustrated in Figure III

- 1 addresses the linkage 7 between depos ition of nitrogen and sulfur and concentrations of the ambient air indicators, NOy 8 and SOx. To link ambient air concentrations with deposition, the Policy Assessment defines a 9 transference ratio, T, as the ratio of total wet and dry deposition to ambient concentration, 10 consistent with the area and time period over which the standard is defined. To express 11 deposition of NOy

and SOx in terms of NOy and SOx ambient concentrations, two transference 12 ratios were defined, where T SOx equals the ratio of the comb ined dry and wet deposition of SOx 13 to the ambient air concentration of SOx, and TNOy equals the ratio of the combined dry and wet 14 deposition of NOy

to the ambient air concentration of NOy

. 15 As described in Chapter 7 of the Policy Assessment, reduced forms of nitrogen (NH X ) are 16 included in total nitrogen in the critical load equation, III

- 1. Reduced forms of nitrogen are 17 treated separately , as are NOy and SOx, and the transference ratios are applied. This results in 18 the following critical load expression that is defined explicitly in terms of the indicators NOy and 19 SOx: 20 21 CLANClim (N + S) = ([BC] 0 *

- [ANC lim ]) Q + Neco = [NOy

]T NOy + [SOx

]T SOx + NHx (III

- 2) 22 23

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24 This is the same equation as III

- 1, with the deposition associated with the critical load translated 1 to deposition from ambient air concentrations via transference ratios. In addition, deposition of 2 reduced nitrogen, oxidize nitrogen and oxidized sulfur are treated separatel y. 3 Transference ratios are a modeled construct, and therefore cannot be compared directl y to 4 measurable quantities. There is an analogy to deposition velocity, as a transference ratio is 5 basically

an aggregated weighted average of the deposition velocities of all contributing species 6 across dry

and wet deposition, and transference ratio units are expressed as distance/time. 7 However, wet deposition commonly is not interpreted as the product of a concentration times a 8 velocity . Direct wet deposition observations are available which integrate all of the processes, 9 regardless of how wel l they may be understood, related to wet deposition into a measurable 10 quantity . There are reasonable analogies between the processes governing dry and wet 11 deposition, from a fundamental mass transfer perspective. In both cases there is a transfer of 12
mass between the dry ambient phase and another medium, either a surface or vegetation in the 13 case of dry

deposition, or a rain droplet or cloud in the case of wet precipitation. The specific 14 thermody

namic properties and chemical/biological reactions that gover n the transfer of dry

mass 15 to plants or aqueous droplets differ, but either process can be based on conceptualizing the 16 product of a concentration, or concentration difference, times a mass transfer coefficient which is 17 analogous to the basic dry depositio n model: dry deposition = concentration x velocity ( US 18 EPA, 2011, Appendix F ). 19 Transference ratios require estimates of wet deposition of NOy and SOx, dry

deposition 20 of NOy

and SOx, and ambient air concentrations of NOy and SOx. Possible sources of 21 in formation include model estimates or a combination of model estimates and observations, 22 recognizing that dry deposition is a modeled quantity that can use observed or modeled estimates 23

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25 of concentration. The limited amount of NOy measurements in acid

- sensi tive areas as well as 1 the combination of representative NOy , SO 2 and SO 4 observations generally preclude the use of 2 observations for development of a standard that is applicable nationall y. 3 The Policy

Assessment considers a blending of observations and mo dels to take 4 advantage of their relative strengths; e.g., combining the NADP wet deposition observations, 5 modeled dry

deposition, and a mix of modeled and observed concentrations, using the model for 6 those species not measured or measured with very sparse spatial coverage. A potential 7 disadvantage of mixing and matching observations and model estimates is to lose consistency 8 afforded b y using just modeling alone. A modeling platform like CMAQ is based on adhering to 9 consistent treatment of mass conservati on, by linking emission inputs with air concentrations and 10 concentrations to deposition. Inconsistencies from combining processes from different anal ytical 11 platforms increase the chance that mass (of nitrogen or sulfur) would unintentionally be 12 increased or decreased as the internal checking that assures mass conservation is lost. 13 Transference ratios incorporate a broad suite of atmospheric processes and consequentl y 14 an anal ytical approach that instills consistency in the linkage of these processes is preferable to 15 an approach lacking such inherent consistency . This contention does not mean that observations 16 alone, if available, could not be used, but suggests that the inconsistencies in combining models 17 and observations for the purposes of developing tr ansference ratios has the potential for creating 18 unintended artifacts. 19 While there is a reasonable conceptual basis for the concept of an aggregated deposition 20 velocity

referred to in the Policy

Assessment as a transference ratio, there is very limite d ability 21 to compare observed and calculated ratios. This is because the deposition velocity is dependent 22 on individual species, and the mass transfer processes of wet and dry removal, while 23

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26 conceptuall y similar, are different. Consequently, there does n ot exist a meaningful approach to 1 measure such an aggregated or lumped parameter. Therefore, at this time, the evaluation of 2 transference ratios is based on sensitivity studies, anal ys is of variability, and comparisons with 3 other models, as described in Appendix F of the Policy Assessment. 4 As discussed in Appendix F, the interannual variability, as well as the sensitivity to 5 emission changes of roughly 50%, result s in changes of transference ratios of approximately 5
- 6 10%. Part of the reason for this i nherent stability is due to the co

- dependence of concentration 7 and deposition. For example, as concentrations are reduced as a result of emissions reductions, 8 deposition in turn is reduced since deposition is a direct linear function of concentration leading 9 to negligible impact on the deposition

- to - concentration ratio. Likewise, an overestimate of 10 concentration likely does not induce a bias in the transference ratio. While it is important to 11 continue to improve the model’s ability to match ambient concentrations in time and space, the 12 bias of a modeled estimate of concentration relative to observations does not necessaril y result in 13 a bias in a calculated transference ratio. In effect, this consideration of bias cancellation reduces 14 the sensitivity

of transference ratios to model uncertainties and affords increased confidence in 15 the stability

of these ratios. Based on the series of sensitivity and variability anal ys es, the Policy 16 Assessment concludes that the transference ratios are relativel y stable an d provide a sound 17 metric for linking deposition and concentration in the form of the standard. 18 As discussed in the policy Assessment, transference ratios are dependent on the platform 19 upon which they

are constructed. Comparisons of transference ratios constructed from different 20 modeling platforms do exhibit significant differences. While this divergence of results may be 21 explained by

a variety of differences in process treatments, input fields and incommensurabilities 22 in species definitions and spatial configurations, it does suggest two very important conclusions. 23

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27 First, the idea of using multipl e platforms for different parts of the country may be problematic 1 as there does not exist a reliable approach to judge acceptance which is almost alway s based on 2 comparisons to observations. Second, since transference ratios are based on concentrations an d 3 deposition, as the uncertainties in each of those components are reduced, the relative uncertainty 4 in the ratios also is reduced. This means that basic improvements in the model’s ability to 5 reproduce observed wet deposition and ambient concentration fi elds enhance the relative 6 confidence in the constructed transference ratios. Similarly, as in

- situ dry deposition flux 7 measurements become available that enable a more rigorous evaluation and diagnosis of 8 modeled dry

deposition processes, the expected imp roved treatment of dry deposition also would 9 increase confidence in transference ratios. Finally, deposition is directl y related to ambient air 10 concentrations. Models like CMAQ rel y on the concentration

- to - deposition linkage to calculate 11 deposition, whic h is the foundation for broadl y based and robust assessments addressing 12 atmospheric deposition. In principle, the use of a modeled constructed transference ratio is based 13 on the same premise b y which we use models to estimate deposition in the first place

. 14 The shortage of widel y available ambient air observations and the fact that estimates of 15 dry deposition requires modeling, collectively suggests that a unified modeling platform is the 16 best approach for constructing transference ratios. The Policy Asse ssment ( US EPA, 17 2011, section 2) considers CMAQ and other models, such as CAMx and the Canada’s AURAMS 18

- A Unified Regional Air

- quality Modeling S ys tem (Smy

the et al., 2008), and concludes that 19 CMAQ is the preferred modeling platform for constructing transference ratios for purposes of 20 developing a new secondary standard for consideration. This conclusion reflects the view that 21 for the purposes of defining tran sference ratios, a modeling platform should (1) be a multiple 22 pollutant model recognizing the myriad of connections across pollutant categories that directly 23

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28 and indirectl y impact nitrogen and sulfur characterization, (2) include the most comprehensive 1 sci entific treatments of atmospheric processes that relate directly and indirectly

to characterizing 2 concentrations and deposition, (3) have an infrastructure capability that accommodates the 3 inclusion of improved scientific treatments of relevant processes a nd important input fields, and 4 (4) undergo frequent reviews regarding the adequacy of the underlying science as well as the 5 appropriateness in applications. The CMAQ platform exhibits all these characteristics. It has 6 been (and continues to be) extensive ly evaluated for several pollutant categories, is supported by 7 a central infrastructure of EPA scientists, with considerable interfacing with the scientific 8 research communities in academia and industry , whose mission is to improve and evaluate the 9 CMAQ p latform. More directly , CMAQ, and its predecessor versions, has a long track record 10 going back to the NAPAP in the 1980’s of specific improvements in deposition processes, which 11 are described in Appendix F of the Policy Assessment. 12 4. Aquatic Acidificatio n Index 13 Having established the various expressions that link atmospheric deposition of nitrogen 14 and sulfur to ANC and the transference ratios that translate atmospheric concentrations to 15 deposition of nitrogen and sulfur, the Policy Assessment derives the following expression of 16 these linkages, which separates reduced forms of nitrogen, NHx, from oxidized forms: 17 18 ANCcalc = {ANClim + CL r /Qr }

– NHx/Qr - T NOy [NOy ]/ Qr - T SOx[SOx ]/ Qr (III

- 3) 19 20 Equation III

- 3 is the basic expression of the form of a standard that translates the 21 conceptual framework into an explicit expression that defines ANC as a function of the ambient 22 air indicators, NOy and SOx. This equation calculates an expected ANC valu e based on ambient 23

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29 concentrations of NOy

and SOx. The calculated ANC will differ from the target ANC (ANClim) 1 depending on how much the nitrogen and sulfur deposition associated with NOy, SOx, and NHx 2 differs from the critical load associated with just ac hieving the target ANC. Based on equation 3 III
- 3, the Policy

Assessment defines an aquatic acidification index (AAI) that is more simply 4 stated using terms that highlight the ambient air indicators: 5 6 AAI = F1

– F2

– F3[NOy ]

– F4[SOx

] (III

- 4) 7 8 where the AAI represents the long term (or steady state) ANC level associated with ambient air 9
c oncentrations of NOy and SOx. The factors F1 through F4 convey three attributes: a relative 10 measure of the ecos ys tem’s ability to neutralize acids (F1), the acidifying potential of reduced 11 nitrogen deposition (F2), and the deposition

- to - concentration translators for NOy (F3) and SOx 12 (F4). 13 Specificall y: 14 F1 = ANClim + CL r /Qr ; 15 F2 = NHx/ Qr = NHx deposition divided by Q r ; 16 F3 = TNOy/ Qr ; TNOy is the transference ratio that converts ambient air concentrations of NOy to 17 deposition of NOy ; and 18 F4 = T SOx/ Qr ; T SOx is the transference ratio that converts ambient air concentrations of SOx to 19 deposition of SOx. 20 All of these factors include representative Qr to maintain unit (and mass) consistency between 21 the AAI and the terms on the right side of equation III

- 4. 22

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30 The F1 factor is the target ANC level plus the amount of deposition (critical load) the 1
ecos ys tem can receive and still achieve the target level. It incorporates an ecosy stem’s ability to 2 generate acid neutralizing capacity through base cation supply ([BC] * 0 ) and to neutralize 3 acidifying nitrogen deposition through Neco, both of which are incorporated in the CLterm. As 4 noted above, because Neco can onl y neutralize nitrogen deposition (oxidized or reduced) there 5 may be rare cases where Neco exceeds the combination of reduced and oxidized nitrogen 6 deposition. Consequently , to ensure that the AAI equation is applicable in all cases that may 7 occur, equation III

- 4 is conditional on total nitrogen deposition, {NHx + F3[NOy]}, being 8 greater than Neco. In rare cases where Neco is greater than {NHx + F3[NOy]}, F2 , F3 , and 9 Neco w ould be set equal to 0 in the AAI equation. The consequence of setting F2 and F3 to zero 10 is simply

to constrain the AAI calculation just to SOx, as nitrogen would have no bearing on 11 acidifying contributions in this case. 12 The Policy

Assessment concludes that equation III

- 4 (US EPA, 2011, equation 7

- 12), 13 which defines the AAI, is ecologicall y relevant and appropriate for use as the form of a national 14 standard designed to provide protection for aquatic ecos ys tems from the effects association with 15 acidifying deposition associated with concentrations of oxides of nitrogen and sulfur in the 16 ambient air. This AAI equation does not, however, in itself, define the spatial areas over which 17 the terms of the equation would apply . To specify values for factors F1 through F4, it is 18 necessary

to define spatial areas over which these factors are determined. Thus, it is necessary to 19 identify

an approach for spatially aggregating water bodies into ecologically meaningful regions 20 across the U.S., as discussed below. 21 5. Spa tial Aggregation 22

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31 As discussed in the Policy Assessment, one of the unique aspects of this form is the need 1 to consider the spatial areas over which values for the F factors in the AAI equation are 2 quantified. Ecos ys tems across the U.S. exhibit a wide range of geological, hydrological and 3 vegetation characteristics that influence greatl y the ecos ys tem parameters, Q, BC 0 * and Neco that 4 are incorporated in the AAI. Variations in ecos ys tem attributes naturall y lead to wide variability 5 in the sensitivities of water bodies in the U.S. to acidification, as well as in the responsiveness of 6 water bodies to changes in acidifying deposition. Consequently , variations in ecosy stem 7 sensitivity, and the uncertainties inherent in characterizing these variations, must be taken into 8 account in developing a national standard. In developing a secondary NAAQS to protect public 9 welfare, the focus of the Policy Assessment is on protecting sensitive populations of water 10 bodies, not on each individual water body, which is con sistent with the Agency ’s approach to 11 protecting public health through primary NAAQS that focus on susceptible populations, not on 12 each individual. 13 The approach used for defining ecologicall y relevant regions across the U.S. in the Policy 14 Assessment (US E PA, 2011, section 7.2.5) is described below, along with approaches to 15 characterizing each region as acid sensitive or relatively non - acid sensitive. This 16 characterization facilitates a more detailed anal ys is and focus on those regions that are relativel y 17
m ore acid sensitive. This characterization is also used to avoid over

- protection in relatively non 18 acid sensitive regions, regions that would receive limited benefit from reductions in the 19 deposition of oxides of nitrogen and sulfur with respect to aquatic acidification effects. 20 Approaches to developing representative values for each of the terms in the AAI equation 21 (factors F1 through F4) for each ecologically relevant region for which sufficient data are 22 available are then discussed. These spatial aggre gation approaches are generall y applicable to 23

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32 the contiguous United States. The following discussion also addresses the development of 1 factors for data

- limited regions and specifically for Hawaii, Alaska and the U.S. territories. 2 Stated more simply , this section discusses appropriate way s to divide the country into 3 ecologicall y relevant regions; to characterize each region as either acid sensitive or relativel y 4
non - acid sensitive; and to determine values of factors F1 through F4 for each region, taking into 5 consideration the acid sensitivity of each region and the availability of relevant data. For each 6 such region, the AAI would be calculated based on the values of factors F1 through F4 specified 7 for that region. 8 In considering approaches to spatial aggregation, the Policy Assessment focuses on 9 methods that have been developed to define ecologically relevant regions, referred to as 10 ecoregions, which are meaningfull y related to the factors that are relevant to aquatic 11 acidification. As noted above, the P olicy Assessment did not focus on looking at each individual 12 water body, nor did it focus on aggregating over the entire nation, which would preclude taking 13 into account the inherent variability in atmospheric and ecological factors that fundamentall y 14 modi fy

the relationships that are central to the development of an ecologically relevant AAI. 15 Based on considering available classification schemes, the Policy Assessment concludes 16 that Omernik’s ecoregion classification is the most appropriate method to con sider for the 17 purposes of this review. This classification offers several levels of spatial delineation, has 18 undergone an extensive scientific peer review process, and has explicitly been applied to 19 delineating acid sensitive areas within the U.S. Further, the Policy Assessment concludes that 20 ecoregion level III (Figure III
- 1 ) resolution, with 84 defined ecoregions in the contiguous U.S., 5 21 is the most appropriate level to consider for this purpose. The spatial resolution afforded b y 22 level III strikes an appropriate balance relative to the reasoning that supports conclusions on 23

5 We note that an 85 th area within Omernik’s Ecoregion Level III is currently being developed for California

.

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33 indicators, as discussed above. The Policy Assessment concludes that the most detailed level of 1 resolution (level IV) is not appropriate given the limited data availability to address nearl y 1000 2 subdivisons within that level and the currently evolving nature of level IV regions. Further, level 3 III ecoregions are preferred to level II in that level III ecoregions, but not level II ecoregions, are 4 largel y contiguous in space which allows for a more coherent development of information to 5 quantify

the AAI factors and to characterize the concentrations of NOy and SOx in the ambient 6 air within each ecoregion. 7 Appendix C of the Policy Assessment includes a description of each level III e coregion. 8 The Policy

Assessment notes that the use of ecoregions is an appropriate spatial aggregation 9 scheme for this standard focused on deposition

- related aquatic acidification effects, while many 10 of the same ecoregion attributes may be applicable in s ubsequent NAAQS reviews that may 11 address other deposition

- related aquatic and terrestrial ecological effects. Because atmospheric 12 deposition is modified by ecos ys tem attributes, the ty pes of vegetation, soils, bedrock geology , 13 and topographic features th at are the basis of this ecoregion classification approach also will 14 likely

be key attributes for other deposition

- related effects (e.g., terrestrial acidification, nutrient 15 enrichment) that link atmospheric concentrations to an aquatic or terrestrial ecol ogical indicator. 16

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34 Figure III - 1 . Omernik Ecoregion III areas ( http://www.epa.gov/wed/pages/ecoregions ). 1 2
a. Ecoregion Sensitivity 3 The Policy

Assessment used Omernik’s original alkalinity data ( US EPA, 2011, as section 4 2 ) and more recent ANC data to delineate two broad groupings of ecoregions: acid

- sensitive and 5 relativel y non - acid sensitive ecoregions. This delineation was made to facilitate greater focus on 6 those ecoregions with water bodies that generall y have greater acid sensitivity and to avoid over

7 protection in regions with generall y less sensitive water bodies. The approach used to delineate 8 acid

- sensitive and relatively non - acid sensitive regions included an initial numerical

- based 9 sorti ng scheme using ANC data, which categorized ecoregions with relatively high ANC values 10

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35 as being relativel y non - acid sensitive. This initial delineation resulted in 29 of the 84 Omernik 1 ecoregions being categorized as acid sensitive. Subsequently , land us e data were also considered 2 to determine to what extent an ecoregion is of a relatively pristine and rural nature by quantifying 3 the degree to which active management practices related to development and agriculture occur in 4 each ecoregion. 5 The overal l objective is to produce a logical and practical grouping of ecoregions that 6 experience adverse conditions with respect to aquatic acidification and are likely to respond to 7 changes in concentrations of NOy and SOx in the ambient air and to the related deposition 8 levels. To achieve this goal, a two

- step process has been applied, first identifying acid sensitive 9 ecoregions based on water quality data alone, and second identifying among those acid

- sensitive 10 ecoregions those with highl y developed and managed areas. These highl y developed and 11 managed ecoregions are placed in a non

- acid sensitive category to avoid over protection beyond 12 what is requisite to protect public welfare. More specificall y, in determining an ecoregion’s acid 13 sensitivity

status in step 1, ANC data across the 84 ecoregions are sorted ( US EPA, 2011, section 14 7 ) to determine the number of water bodies within a region with ANC values suggestive of acid 15 sensitivity, so as to screen out regions with an overabundance of high ANC values. In re viewing 16 the ANC data, the Policy Assessment identified 29 ecoregions that meet two criteria: (1) greater 17 than 5% of water bodies with data with ANC values less than 200 μeq/Land (2) greater than 1% 18 of water bodies with ANC values less than 100 μeq/L . In step 2, land use data were used to 19 identify

those acid sensitive ecoregions with significant managed areas that would not be 20 considered as having a relatively pristine and rural character. The percentage of the 21 combination of developed (residential, tran sportation, industrial and commercial) and 22 agricultural (croplands, pastures, orchards, vineyards) land use was used as an indicator of 23

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36 managed land use area. Forest cover was used as an indicator of non

- managed land use more 1 directly

reflecting the pristine quality of a region. Based on the 2006 National Land Cover Data 2 base (NLCD, http://www.epa.gov/mrlc/nlcd

- 2006.html ), acid sensitive ecoregions would meet 3 both of the following land use data criteria: percent of developed and agricultural area less than 4 20% combined with forested area greater than 50%. The combination of steps 1 and 2 identify 5 22 relativel y acid sensi tive areas (Table III

- 1 and Figure III
- 2 ). 6 Consideration was also given to the use of naturally acidic conditions in defining 7 relativel y non - acid sensitive areas. For example, several of the ecoregions located in plains near 8 the coast exhibit elevated dissolved organic carbon (DOC) levels, which is associated with 9 naturally

acidic conditions. DOC in surface waters is derived from a variety of weak organic 10 acid compounds generated from the natural availability and decomposition of organic matter 11 from b iota. Consequently , high DOC is associated with “natural” acidity , with the implication 12 that a standard intended to protect against atmospheric contributions to acidity is not an area of 13 focus. The evidence suggests that several of the more highl y manag ed ecoregions in coastal or 14 near coastal transition zones are associated with relatively high DOC values, ty

picall y exceeding 15 on average 5 mg/l, compared to other acid sensitive areas. Although there is sound logic to 16 interpret naturally

acidic areas as relatively non - acid sensitive, natural acidity indicators were not 17 explicitly

included in defining relativel y non - acid sensitive areas as there does not exist a 18
consensus - based quantifiable scientific definition of natural acidity . Approaches to explicitly 19 define natural acidity likely will be pursued in future reviews of the standard. 20

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37 Table III - 1
. List of 22 Acid - Sensitive Areas Ecoregion nam e 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 1

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38 1 Figure III - 2 . Acid

- sensitive ecoregions identified in grey fill (22 out of 84 ecoregions). 2 3 b. Representative Ecoregion

-specific Factors 4 Having concluded that the Omernik level III ecoregions are an appropriate approach to 5 spatial aggregation for the purpose of a standard to address deposition

- related aquatic 6 acidification effects, the Policy Assessment uses those ecoregions to define each of the factors in 7 the AAI equation. As discussed below, factors F1 through F4 in equation III

- 4 are defined for 8 each ecoregion by

specifyingecoregion

- specific values for each factor based on monitored or 9 modeled data that are representative of each ecoregion. 10

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39 i. Factor F1 1 As discussed above, factor F1 reflects a relative measure of an ecos ys tem’s ability to 2 neutralize acidifying deposition, and is defined as: F1 = ANClim + CL r /Qr . The value of F1 for 3 each ecoregion would be based on a representative critical load for the ecoregion (CLr) 4 associated with a single national target ANC level (ANClim, discussed below in section III.D), 5 as well as on a representative runoff rate (Q r). To specify ecoregion

- specific values for the term 6 Q r , the Policy

Assessment used the median value of the distribution of Q values that are available 7 for water bodies within each ecoregion. To specify ecoregion

- specific representative values for 8 the term CLr in factor F1, a distribution 6 of calculated critical loads was created for the water 9 bodies in each ecoregion for which sufficient water quality and h ydrology

data are available. 7 10 The representative critical load was then defined to be a specific percentile of the distribution of 11 critical loads in the ecoregion. Thus, for example, using the 90 th percentile means that within an 12 ecoregion, 90 percent of the water bodies would be expected to have higher calculated critical 13 loads than the representative critical load. That is, if the representative critical load were to 14 occur across the ecoregion, 9 0 percent of the water bodies would be expected to achieve the 15 national ANC target or better. 16 The specific percentile selected as part of the definition of F1 is an important parameter 17 that directly

impacts the representative critical load specified for ea ch ecoregion, and therefore 18 the degree of protectiveness of the standard. A higher percentile corresponds to a lower critical 19 load and, therefore, to lower allowable ambient air concentrations of NOy and SOx and related 20

6 T he distribution of critical loads was based on CL values calculated with Neco at the lake level. Consideration could also be given to using a distribution of CLs without Neco and adding the ecoregion averag e Neco value to the nth percentile critical load. This would avoid cases where the lake

- level Neco value potentially could be greater than total nitrogen deposition. The CL at the lake level represents the CL for the lake to achieve the specified nationa l target ANC value. 7 The Policy Assessment judge d the data to be sufficient for this purpose if data are available from more than 10 water bodies in an ecoregion.

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40 deposition to achieve a target AAI level. In conjunction with the other terms in the AAI 1 equation, alternative forms can be appropriatel y characterized in part b y i dentifying a range of 2 alternative percentiles. The choice of an appropriate range of percentiles to consider for acid

3 sensitive and relativel y non - acid sensitive ecoregions, respectivel y, is discussed below. 4 ( a ) Acid

-sensitive Ecoregions 5 In identifying percentiles that are appropriate to consider for the purpose of calculating 6 factor F1 for ecoregions characterized as acid sensitive, the Policy Assessment concludes that it 7 is appropriate to focus on the lower (more sensitive) part of the distribution of critical loads, so 8 as to ensure that the ecoregion would be represented by relativel y more acid sensitive water 9 bodie s within the ecoregion. Specifying factor F1 in this way would help to define a standard 10 that would be protective of the population of acid sensitive water bodies within an ecoregion, 11 recognizing that even ecoregions characterized as acid sensitive may co ntain a number of 12 individual water bodies that are not acid sensitive. The Policy Assessment recognizes that there 13 is no basis for independently evaluating the degree of protectiveness afforded by any specific 14 percentile value, since it is the combination of form and level, in conjunction with the indicator 15 and averaging time, which determine the degree of protectiveness of a standard. In light of this, 16 the Policy

Assessment concludes that it is appropriate to consider a range of percentiles, from 17 well ab ove the 50 th percentile, or median, of the distribution to somewhat below the highest 18 value (in terms of sensitivity ; a high degree of sensitivity corresponds to a low value for critical 19 load) . More specificall y, the Policy Assessment concludes it is appropriate to consider 20 percentiles in the range of the 70 th to the 90 th percentile (of sensitivity) . This conclusion is based 21 on the judgment that it would not be appropriate to represent an ecoregion with the lowest or 22
near lowest critical load, so as to av oid potential extreme outliers that can be seen to exist at the 23

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41 extreme end of the data distributions, which would not be representative of the population of acid 1 sensitive water bodies within the ecoregion and could lead to an overl y protective standard

. At 2 the same time , in considering ecoregions that are inherentl y acid sensitive, it is judged to be 3 appropriate to limit the lower end of the range for consideration to the 70 th percentile, a value 4 well above the median of the distribution , so that a subs tantial majority of acid

- sensitive water 5 bodies are protected

. 6 In considering this conclusion, the CASAC Panel noted that the data bases for calculating 7 critical loads within an ecoregion are not necessarily representative of all water bodies within an 8 ecoregion. That is, in many ecoregions the lake sampling design used in studies that generated 9 the relevant data may have focused on the relatively more sensitive water bodies within an 10 ecoregion (Russell and Samet, 2011 a). Consequently , a given percentile of the distribution of 11 calculated critical loads, based on sampled water bodies, may not be representative of that 12 percentile of all water bodies across an entire ecoregion. To the extent that the sampling of water 13 bodies within an ecoregion was skew ed toward the relativel y more sensitive water bodies, 14 selecting a given percentile from the distribution of available critical loads would result in a 15 somewhat higher percentile of all water bodies within that ecoregion having a higher calculated 16 critical load than the representative critical load value. Thus, the extent to which study sampling 17 designs have resulted in skewed distributions of calculated critical loads is an uncertainty that is 18 appropriate to consider in selecting a percentile for the purpo se of defining the factor F1 in the 19 AAI equation. 20 ( b ) Non

- acid sensitive Ecoregions 21 With regard to identifying percentiles that are appropriate to consider for the purpose of 22 calculating factor F1 for ecoregions characterized as relativel y non - acid sensitive, the Policy 23

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42 Assessment recognizes that while such ecoregions are generall y less s ensitive to acidifying 1 deposition from oxides of nitrogen and sulfur, they may contain a number of water bodies that 2 are acid sensitive This category includes ecoregions that are well protected from acidification 3 effects due to natural production of base cations and high ANC levels, as well as naturall y acidic 4 sy stems with limited base cation production and consequently very low critical loads. Therefore, 5 the use of a critical load that would be associated with a highl y sensitive water body in a 6 naturall y acidic s ys tem would impose a high degree of relative protection in terms of allowable 7 ambient air concentrations of oxides of nitrogen and sulfur and related deposition, while 8 potentially

affording little or no public welfare benefit from attempting to i mprove a naturally 9 acidic s ys tem. 10 Based on these considerations, the Policy Assessment concludes it is appropriate to 11 consider the use of a range of percentiles that extends lower than the range identified above for 12 acid

- sensitive ecoregions. Considerati on of a lower percentile would avoid representing a 13 relativel y non - acid sensitive ecoregion by a critical load associated with relatively more acid

14 sensitive water bodies. In particular, the Policy Assessment concludes it is appropriate to focus 15 on the me dian or 50 th percentile of the distribution of critical loads so as to avoid over

- protection 16 in such ecoregions. Recognizing that relativel y non - acid sensitive ecoregions generall y are not 17 sampled to the extent that acid

- sensitive ecoregions are, it also is appropriate to consider using 18 the median critical load of all relativel y non - acid sensitive ecoregions for each such ecoregion. 19 ii. Factor F2 20 As discussed above, factor F2 is the amount of reduced nitrogen deposition within an 21 ecoregion, i ncluding the deposition of both ammonia gas and ammonium ion, and is defined as: 22 F2 = NHx/ Qr . The Policy Assessment calculated the representative runoff rate, Q r , using a 23

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43 similar approach as noted above for factor F1; i.e., the median value of the distribution of Q 1 values that are available for water bodies within each ecoregion. In the Policy Assessment, 2005 2 CMAQ model simulations over 12

- km grids are used to calculate an average value of NHx for 3 each ecoregion. The NHx term is based on annual average m odel outputs for each grid cell, 4 which are spatially

averaged across all the grid cells contained in each ecoregion to calculate a 5 representative annual average value for each ecoregion. The Policy Assessment concludes that 6 this approach of using spatially averaged values is appropriate for modeling, largel y due to the 7 relativel y rapid mixing of air masses that typicall y results in relativel y homogeneous air quality 8 patterns for regionall y dispersed pollutants. In addition, there is greater confidence in u sing 9 spatially

averaged modeled atmospheric fields than in using modeled point

- specific fields. 10 This averaging approach is also used for the air concentration and deposition terms in 11 factors F3 and F4, as discussed below. The Policy Assessment notes that modeled NHx 12 deposition exhibits greater spatial variability than the other modeled terms in factors F3 and F4. 13 Recognizing this greater variability , the Policy Assessment concludes that it would be 14 appropriate to consider alternative approaches to specif yi ng the value of NHx. One such 15 approach might involve the use of more localized and/or contemporaneous modeling in areas 16 where this term is likel y to be particularly variable and important. 17 iii. Factors F3 and F4 18 As discussed above, factors F3 and F4 are the ratios that relate ambient air concentrations 19 of NOy

and SOx to the associated deposition, and are defined as follow: F3 = TNOy / Qr and F4 20 = T SOx/ Qr . TNOy is the transference ratio that converts ambient air concentrations of NOy to 21 deposition of NOy

and T SOx is the transference ratio that converts ambient air concentrations of 22 SOx to deposition of SOx. The representative runoff rate, Q r , is calculated as f or factors F1 and 23

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44 F2. The transference ratios are based on the 2005 CMAQ simulations, using average values for 1 each ecoregion, as noted above for factor F2. More specifically , the transference ratios are 2 calculated as the annual deposition of NOy or SOx spatially

averaged across the ecoregion and 3 divided by

the annual ambient air concentration of NOy or SOx, respectively , spatiall y averaged 4 across the ecoregion. 5
c. Factors in Data

- limited Ecoregions 6 As discussed above in section III.B.5.a, in the Poli cy Assessment the initial delineation of 7 acid

- sensitive and relatively non - acid sensitive ecoregions was based on available ANC and 8 alkalinity

data. Areas not meeting the ANC criteria described above are categorized as 9 relativel y non - acid sensitive. The development of a reasonable distribution of critical loads for 10 water bodies within an ecoregion for the purpose of identifying the representative critical load 11 requires additional data, including more specific water quality data for major cations and anio ns. 12 This means that the water bodies that can be used to develop a distribution of critical loads is 13 generall y a subset of those water bodies for which ANC data are available Consequently , there 14 are certain ecoregions with sparse data that are not suita ble for developing a distribution of 15 critical loads. 16 As noted above, the Policy Assessment judges that it is not appropriate to develop such 17 distributions based on data from less than ten water bodies within an ecoregion. Twelve such 18 ecoregions, which in cluded only relativel y non - acid sensitive ecoregions, were characterized as 19 being data

- limited. For these ecoregions, the Policy Assessment considered alternative 20 approaches to specifying values for the terms CLr and Q r for the purpose of determining valu es 21 for each of the factors in the AAI equation. For these data

- limited ecoregions, the Policy 22 Assessment judges that it is appropriate to use the median values of CLr and Q r from the 23

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45 distributions of these terms for all other relatively non

- acid sensitive ecoregions, rather than 1 attempting to use severely limited data to develop a value for these terms based solel y on data 2 from such an ecoregion. Further, consideration could be given to using a single national default 3 value for all relativel y non - acid sen sitive ecoregions. The Policy Assessment notes that this data 4 limitation is not a concern in specifying values for the other terms in the AAI equation for such 5 ecoregions, since those terms are based on data from the 2005 CMAQ model simulation, which 6
covers all ecoregions across the contiguous U.S. 7 d. Application to Hawaii, Alaska, and the U.S. Territories 8 The above methods for specifying ecoregion

- specific values for the factors in the AAI 9 equation appl y to those ecoregions within the contiguous U.S. Fo r areas outside the continental 10 U.S., including Hawaii, Alaska, and the U.S. Territories, there is currentl y a lack of available 11 data to characterize the sensitivity of such areas, as well as a lack of water body

- specific data and 12 CMAQ
- ty

pe modeling to spe cify

values for the F1 through F4 factors. Thus, the Policy 13 Assessment has considered possible alternative approaches to specifying values for factors F1 14 through F4 in the AAI equation for these areas. 15 One such approach could be to specify area - specific values for the factors based on 16 values derived for ecoregions with similar acid sensitivities, to the extent that relevant 17 information can be obtained to determine such similarities. Such an approach would involve 18 conducting an analy sis to characterize s imilarities in relevant ecological attributes between 19 ecoregions in the contiguous U.S. and these areas outside the contiguous U.S. so as to determine 20 the appropriateness of utilizing ecoregion

- specific values for the CLr and Q r terms from one or 21
more ecoregions within the contiguous U.S. This approach would also involve conducting 22 additional air quality modeling for these area that are outside the geographical scope of the 23

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46 currentl y available CMAQ model simulations, so as to develop the other information necessary 1 to specify

values for factors F2 through F4 for these areas. 2 A second approach could rely on future data collection efforts to establish relevant 3 ecological data within these areas that, together with additional air quality modeling, could be 4
us ed to specify

area - specific values for factors F1 through F4. Until such time as relevant data 5 become available, these areas could be treated the same as data

- limited ecoregions in the 6 contiguous U.S. that are relatively non - acid sensitive. 7 The Policy Assessment concludes that either approach would introduce substantial 8 uncertainties that arise from attempting to extrapolate values based on similarity assumptions or 9 arbitraril y assigning values for factors in the AAI equation that would be applicable to these 10 areas outside the contiguous U.S. In light of such uncertainties, the Policy Assessment 11 concludes that it would also be appropriate to consider rel yi ng on the existing NO 2 and SO 2 12 secondary

standards in these areas for protection of any potential direct or deposition

- related 13 ecological effects that may be associated with the presence of oxides of nitrogen and sulfur in the 14 ambient air. The Policy Assessment concludes that rel yi ng on existing secondary standards in 15 these areas is preferable to using a highl y uncertain approach to allow for the application of a 16 new standard based on the AAI in the absence of relevant area

- specific data. 17 6. Summary of the AAI Form 18 With regard to the form of a multi

- pollutant air quality standard to address deposition

19 related aquatic acidification effects, the Policy Assessment concludes that consideration should 20 be given to an ecologically relevant form that characterizes the relationships between the 21 ambient air indicators for oxides of nitrogen and sulfur, the relate d deposition of nitrogen and 22 sulfur, and the associated aquatic acidification effects in terms of a relevant ecological indicator. 23

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47 Based on the available information and assessments, consideration should be given to using acid 1 neutralizing capacity (ANC) as the most appropriate ecological indicator for this purpose, in that 2 it provides the most stable metric that is highl y associated with the water quality properties that 3 are directl y responsible for the principal adverse effects associated with aquatic ac idification: 4 fish mortality

and reduced aquatic species diversity

. 5 The Policy

Assessment developed such a form, termed an aquatic acidification index 6 (AAI), using a simple equation to calculate an AAI value in terms of the ambient air indicators of 7 oxide s and nitrogen and sulfur and the relevant ecological and atmospheric factors that modify 8 the relationships between the ambient air indicators and ANC. Recognizing the spatial 9 variability

of such factors across the U.S., the Policy Assessment concludes it is appropriate to 10 divide the country

into ecologicall y relevant regions, characterized as acid

- sensitive or relativel y 11
non - acid

- sensitive, and specify the value of each of the factors in the AAI equation for each such 12 region. Omernik ecoregions, level II I, are identified as the appropriate set of regions over which 13 to define the AAI. There are 84 such ecoregions that cover the continental U.S. This set of 14 ecoregions is based on grouping a variety of vegetation, geological, and hydrological attributes 15 th at are directly

relevant to aquatic acidification assessments and that allow for a practical 16 application of an aquatic acidification standard on a national scale. 17 The Policy

Assessment defines AAIby the following equation: AAI = F1

– F2

– 18 F3[NO y]

– F4[S O x ]. Factors F1 through F4 would be defined for each ecoregion b y specifying 19 ecoregion

- specific values for each factor based on monitored or modeled data that are 20 representative of each ecoregion. The F1 factor is also defined b y a target ANC value. More 21 specificall y: 22

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48 (1) F1 reflects a relative measure of an ecos ys tem’s ability to neutralize acidifying 1 deposition. The value of F1 for each ecoregion would be based on a representative 2 critical load for the ecoregion associated with a single national target ANC level, as well 3 as on a representative runoff rate. The representative runoff rate, which is also used in 4 specifying values for the other factors, would be the median value of the distributions of 5 runoff rates within the ecoregion. The representative critical load would be derived from 6 a distribution of critical loads calculated for each water body in the ecoregion for which 7 sufficient water quality and hydrology data are available. The representative critical load 8 would be defined b y s electing a specific percentile of the distribution. 9 In identifying a range of percentiles that are appropriate to consider for this 10 purpose, regions categorized as acid sensitive were consi dered separatel y from regions 11 categorized as relativel y non - acid sensitive. For acid sensitive regions, the Policy 12 Assessment concludes that consideration should be given to selecting a percentile from 13 within the range of the 70 th to the 90 th percentil e. The lower end of this range was 14 selected to be appreciably above the median value so as to ensure that the critical load 15 would be representative of the population of relatively more acid sensitive water bodies 16 within the region, while the upper end was selected to avoid the use of a critical load 17 from the extreme tail of the distribution which is subject to a high degree of variability 18 and potential outliers. For relativel y non - acid sensitive regions, the Policy Assessment 19 concludes that consideration should be given to selecting the 50 th percentile to best 20 represent the distribution of water bodies within such a region, or alternatively to using 21 the median critical load of all relativel y non - acid sensitive areas, recognizing that such 22
areas are far less frequently evaluated than acid sensitive areas. Using either of these 23

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49 approaches would avoid characterizing a generally non - acid

- sensitive region with a 1 critical load that is representative of relatively acid sensitive water bodies that may e xist 2 within a generall y non - acid sensitive region. 3 (2) F2 reflects the deposition of reduced nitrogen. Consideration should be given to 4 specifying the value of F2 for each region based on the averaged modeled value across 5 the region, using national CMAQ modeling that has been conducted b y EPA. 6 Consideration could also be given to alternative approaches to specifying this value, such 7 as the use of more localized and/or contemporaneous modeling in areas where this term is 8 likely

to be particularl y variabl e and important. 9 (3) F3 and F4 reflect transference ratios that convert ambient air concentrations of NO y 10 and SO x , respectivel y, into related deposition of nitrogen and sulfur. Consideration 11 should be given to specifyingthe values for F3 and F4 for eac h region based on CMAQ 12 modeling results averaged across the region. We conclude that specifying the values or 13 the transference rations based on CMAQ modeling results alone is preferred to an 14 alternative approach that combines CMAQ model estimates with obs ervational data. 15 (4) The terms [NO y] and [SO x ] reflect ambient air concentrations measured at 16 monitoring sites within each region. 17 Using the equation, a value of AAI can be calculated for any measured values of ambient 18 NOy

and SOx. For such a NAAQS, the Administrator would set a single, national value for the 19 level of the AAI used to determine achievement of the NAAQS, as discussed below in section 20 III.D. The ecoregion

- specific values for factors F1 through F4 would be specified by EPA based 21 on the most recent data and CMAQ model simulations, and codified as part of such a standard. 22

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50 These factors would be reviewed and updated as appropriate in the context of each periodic 1 review of the NAAQS. 2 The Policy

Assessment developed specific F factors for each ecoregion based on the 3 approach discussed above, using alternative percentiles and alternative national target ANC 4 levels. The results of this analy sis for ecoregions characterized as acid sensitive are presented in 5 Table 7

- 1a
- d in the Policy Assessment. 6 C. Averaging Time 7 As discussed in section 7.3 of the Policy Assessment, aquatic acidification can occur over 8 both long

- and short

- term timescales. L ong - term cumulative deposition of nitrogen and sulfur is 9 reflected in the chronic acid

- base balance of surface waters as indicated by measured annual 10 ANC levels. Similarly , the use of steady state critical load modeling, which generates critical 11 loads in terms of annual cumulative deposition of nitrogen and sulfur, means that the focus of 12 ecological eff

ects studies based on critical loads is on the long

- term equilibrium status of water 13 quality

in aquatic ecos ys tems. Much of the evidence of adverse ecological effects associated 14 with aquatic acidification, as discussed above in section II.A, is associated with chronicall y low 15 ANC levels. Protection against a chronic ANC level that is too low is provided by reducing 16 overall annual average deposition levels for nitrogen and sulfur. 17 Reflecting this focus on long

- term acidifying deposition, the Policy Assessment 18 developed the AAI that links ambient air indicators to deposition

- related ecological effects, in 19 terms of several factors, F1 through F4. As discussed above, these factors are all calculated as 20 annual average values, whether based on water quality and h ydrology data or on CMAQ model 21 simulations. In the context of a standard defined in terms of the AAI, the Policy Assessment 22

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51 concludes that it is appropriate to consider the same annual averaging time for the ambient air 1 indicators as is used for the factors in the AAI equation. 2 We also recognize that short

- term (i.e., hours or day s) episodic changes in water 3 chemistry , often due to changes in the hydrologic flow paths, can have important biological 4 effects in aquatic ecos ys tems. Such short

- term changes in water chemistry are termed “episodic 5 acidification.” Some streams may have chronic or base flow chemistry that is generall y healthy 6 for aquatic biota, but may be subject to oc casional acidic episodes with potentially lethal 7 consequences. Thus, short

- term episodic ecological effects can occur even in the absence of 8 long

- term chronic acidification effects. 9 Episodic declines in pH and ANC are nearl y ubiquitous in drainage waters throughout the 10 eastern U.S. Episodic acidification can result from several mechanisms related to changes in 11 hydrologic flow paths. For example, snow can store nitrogen deposited throughout the winter 12 and snowmelt can then release this stored nitrogen, t ogether with nitrogen derived from 13 nitrification in the soil itself, in a pulse that leads to episodic acidification in the absence of 14 increased deposition during the actual episodic acidification event. The Policy Assessment notes 15 that inputs of nitrogen and sulfur from snowpack and atmospheric deposition largel y c ycl e 16 through soil. As a result, short

- term direct deposition inputs are not necessarily important in 17 episodic acidification. Thus, as noted in chapter 3 of the I SA, protection against episodic acidity 18 events can be achieved by establishing a higher chronic ANC level. 19 Taken together, the above considerations support the conclusion that it is appropriate to 20 consider the use of a long

- term average for the ambient air indicators NOy and SOx for an 21 aquatic acidification standard defined in terms of the AAI. The use of an annual averaging time 22 for NOy

and SOx concentrations would be appropriate to provide protection against low chronic 23

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52 ANC levels, which in turn would protect against both long

- term a cidification and acute acidic 1 episodes. 2 The Policy

Assessment has also considered interannual variability in both ambient air 3 quality

and in precipitation, which is directl y related to the deposition of oxides of nitrogen and 4 sulfur from the ambient air. While ambient air concentrations show ye ar - to - ye ar variability , 5 often the year - to - ye ar variability in precipitation is considerabl y greater, given the highl y 6 stochastic nature of precipitation. The use of multiple years over which annual averages are 7 det ermined would dampen the effects of interannual variability in both air quality

and 8 precipitation. For the ambient air indicators, the use of multiple

- ye ar averages would also add 9 stability

to calculations used to judge whether an area meets a standard de fined in terms of the 10 AAI. Consequentl y, the Policy Assessment concludes that an annual averaging time based on 11 the average of each year over a consecutive 3 to 5 year period is appropriate to consider for the 12 ambient air indicators NOy and SOx. In reach ing this conclusion, the Policy Assessment notes 13 that in its comments on the second draft Policy Assessment, CASAC agreed that a 3 to 5 year 14 averaging time was appropriate to consider (Russell and Samet, 2010b). 15 D. Level 16 As discussed above, the Policy Ass essment concludes that ANC is the ecological 17 indicator best suited to reflect the sensitivity of aquatic ecos ys tems to acidifying deposition from 18 oxides of nitrogen and sulfur in the ambient air. ANC is an indicator of the aquatic acidification 19 expected t o occur given the natural buffering capacity of an ecos ys tem and the loadings of 20 nitrogen and sulfur resulting from atmospheric deposition. Thus, the Policy Assessment 21 developed a new standard for aquatic acidification that is based on the use of chronic ANC as the 22 ecological indicator as a component in the AAI. 23

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53 The level of the standard would be defined in terms of a single, national value of the 1 AAI. The standard would be met at a monitoring site when the multi

- ye ar average of the 2 calculated annual values of the AAI was equal to or above the specified level of the standard. 8 3 The annual values of the AAI would be calculated based on the AAI equation using the assigned 4 ecoregion

- specific values for factors F1 through F4 and monitored annual average NOy and SOx 5 concentrations. Since the AAI equation is based on chronic ANC as the ecological indicator, the 6 level chosen for the standard would reflect a target chronic ANC value. As noted above, the 7 assigned F factors for each ecoregion would be determined by EPA in the rulemaking to set the 8 NAAQS, based on water quality and h ydrology data, CMAQ modeling, the selected percentile 9 that is used to identify a representative critical load within the ecoregion, and the selected level 10 of the standard. The combination of the form of the standard, discussed above in section III.B, 11 defined b y the AAI equation and the assigned values of the F factors in the equation, other 12 elements of the standard including the ambient air indicators (section III.A) and their averaging 13 time (section III.C), and the level of the standard determines the allowable levels of NOy and 14 SOx in the ambient air within each ecoregion. All of the elements of the standard together 15 determine the degree of protection from adverse aquatic acidificatio n effects associated with 16 oxides of nitrogen and sulfur in the ambient air. The level of the standard play s a central role in 17 determining the degree of protection provided and is discussed below. 18 The Policy

Assessment focuses primaril y on information that relates degrees of 19 biological impairment associated with adverse ecological effects to aquatic ecos ys tems to 20 alternative levels of ANC in reaching conclusions regarding the range of target ANC levels that 21 is appropriate to consider for the level of the s tandard. The Policy Assessment develops the 22

8 Unlike other NAAQS, where the standard is met when the relevant value is at or below the l evel of the standard since a lower standard level is more protective, in this case a higher standard level is more protective.

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54 rationale for identifying a range of target ANC levels that is appropriate to consider by 1 addressing questions related to the following areas: (1) associations between ANC and pH levels 2 to provide an initial bo unding for the range of ANC values to be considered; (2) evidence that 3 allows for the delineation of specific ANC ranges associated with varying degrees of severity of 4 biological impairment ecological effects; (3) the role of ANC in affording protection against 5 episodic acidity ; (4) implications of the time lag response of ANC to changes in deposition; (5) 6 past and current examples of target ANC values applied in environmental management 7 practices; and (6) data linking public welfare benefits and ANC. 8 1. Association Between pH Levels and Target ANC Levels 9 As discussed above in section II.A and more full y in chapter 3 of the Policy Assessment, 10 specific levels of ANC are associated with differing levels of risk of biological impairment in 11 aquatic ecosy st ems, with higher levels of ANC resulting in lower risk of ecosy stem impacts, and 12 lower ANC levels resulting in risk of both higher intensity of impacts and a broader set of 13 impacts. While ANC is not the causal agent determining biological effects in aquatic ecos ys tem, 14 it is a useful metric for determining the level at which a water body is protected against risks of 15 acidification. There is a direct correlation between ANC and pH levels which, along with 16 dissolved aluminum, are more closel y linked to the b iological causes of ecosy stem response to 17 acidification. 18 Because there is a direct correlation between ANC and pH levels, the selection of target 19 ANC levels is informed in part through information on effects of pH as well as direct studies of 20 effects related to ANC. Levels of pH are closely associated with ANC in the pH range of 21 approximately

4.5 to 7. Within this range, higher ANC levels are associated with higher pH 22 levels. At a pH level of approximately 4.5, further reductions in ANC generally do not correlate 23

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55 with pH, as pH levels remain at approximately 4 .5 while ANC values fall substantially

. 1 Similarly, at a pH value of approximately 7, ANC values can continue to increase with no 2 corresponding increase in pH. As pH is the primary causal indicator of effects related to aquatic 3 acidification, this suggest s that ANC values below approximately

- 50 μeq/L (the apparent point 4 in the relationship between pH and ANC where pH reaches a minimum) are not likely to result in 5 further damage. In addition, ANC values around and above approximately 100 μeq/L(the 6 apparent region in the relationship where pH reaches a maximum) are not likely to confer 7 additional protection. As a result, the initial focus in the Policy Assessment was on target ANC 8 values in the range of

- 50 to 100 μeq/L

. 9 2. ANC Levels Related to Effects o n Aquatic Ecosystems 10 As discussed above in section II.A, the number of fish species present in a water body has 11 been shown to be positively correlated with the ANC level in the water, with higher values 12 supporting a greater richness and diversity of fis h species. The diversity and distribution of 13 phy to - zooplankton communities also are positively correlated with ANC. 14 A summary of effects related to ANC ranges is shown above in Table II

- 1. Within the 15 ANC range from approximately

- 50 to 100 μeq/L, linear and sigmoidal relationships are 16 observed between ANC and ecos ys tem effects. On average, fish species richness is lower b y one 17 fish species for every 21 μeq/Ldecrease in ANC in Shenandoah National Park streams (I SA, 18 section 3.2.3.4). As shown in Table II
- 1, ANC levels have been grouped into five categories 19 related to expected ecological effects, including categories of acute concern ( <0 μeq/L), severe 20 concern (0

- 20 μeq/L), elevated concern (20

- 50 μeq/L), moderate concern (50

- 100 μeq/L), and 21 low concern (>100 μeq/L). This categorization is supported by a large body

of research 22 completed throughout the eastern U.S. (Sullivan et al., 2006). 23

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56 Water bodies with ANC values less than or equal to 0 μeq/Lat based flow are chronicall y 1 acidic. Such ANC levels can lead to complete loss of species and major changes in the ability of 2 water bodies to support diverse biota, especiall y in water bodies that are highly sensitive to 3 episodic acidification. Based on the above considerations, the Policy Assessment has focu sed on 4 target ANC levels no lower than 0 μeq/L. 5 As discussed in the Policy Assessment, biota generally are not harmed when ANC values 6 are >100 μeq/L , due to the low probability that pH levels will be below 7. In the Adirondacks, 7 the number of fish specie s also peaks at ANC values >100 μeq/L. This suggests that at ANC 8 levels greater than 100 μeq/L , little risk from acidification exists in many aquatic ecos ys tems. At 9 ANC levels below 100 μeq/L , overall health of aquatic communities can be maintained, alth ough 10 fish fitness and community diversity begin to decline . At ANC levels ranging from 100 down to 11 50 μeq/L , there is increasing likelihood that the fitness of sensitive species (e.g., brook trout, 12 zooplankton) will begin to decline. When ANC concentrati ons are below 50 μeq/L , the 13 probability

of acidification increases substantially , and negative effects on aquatic biota are 14 observed, including large reductions in diversity of fish species and changes in the health of fish 15 populations, affecting reproductive ability and fitness, especiall y in water bodies that are affected 16 by episodic acidification. While there is evidence that ANC levels above 50 can confer 17 additional protection from adverse ecological effects associated with aquatic acidification in 18
som e sensitive ecos ys tems, the expectation that such incremental protection from adverse effects 19 will continue up to an ANC level of 100 is substantially reduced. The Policy

Assessment 20 concludes that the above considerations support a focus on target ANC lev els up to a level 21 greater than 50 μeq/L but below 100 μeq/L , such as up to a level of 75 μeq/L. 22

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57 In considering the available scientific evidence, as summarized here and discussed in 1 more detail in the ISA and REA, in its review of the second draft Policy Assessment, CASAC 2 expressed the following views about the range of biological responses that corresponds to this 3 range of ANC levels (i.e., 0

- 100 μeq/L): 4 There will likel y be biological effects of acidification at higher ANC values 5 within this range, and there are relatively insensitive organisms that are not 6 impacted at ANC values at the low end of this range. Adverse effects of 7 acidification on aquatic biota are fairl y certain at the low end of this range of 8 ANC and incremental benefits of shifting water s to higher ANC become 9 more uncertain at higher ANC levels. There is substantial confidence that 10 there are adverse effects at ANC levels below 20 μeq/L , and reasonable 11 confidence that there are adverse effects below 50 μeq/L . Levels of 50 12 μeq/Land highe r would provide additional protection, but the Panel has less 13 confidence in the significance of the incremental benefits as the level 14 increases above 50 μeq/L. (Russell and Samet, 2010b) 15 16 The Policy

Assessment concludes that the above considerations, inc luding the views of 17 CASAC, provide support for focusing on target ANC levels in the range of 20 to 75 μeq/L

. 18 3. Consideration of Episodic Acidity 19 As discussed in the Policy Assessment, across the broad range of ANC values from 0 to 20 100 μeq/L , ANC afford s protection against the likelihood of decreased pH (and associated 21 increases in Al) during long or short periods. In general, the higher the ANC within this range, 22 the lower the probability of reaching low pH levels where direct effects such as increased fish 23 mortality

occur, as shown in Table 3

- 1 of the Policy Assessment. Accordingl y, greater 24 protection would be achieved b y target chronic ANC values set high enough to avoid pH 25 depression to levels associated with elevated risk. 26 The specific relation ship between ANC and the probability of reaching pH levels of 27 elevated risk varies b y water body and fish species. ANC levels below 20 μeq/Lare generall y 28 associated with high probability of low pH, leading to death or loss of fitness of biota that are 29

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58 sensitive to acidification (US EPA, 2008 , section 5.2.2.1; US EPA, 2009 , section 5.2.1.2). At 1 these levels, during episodes of high acidifying deposition, brook trout populations may 2 experience lethal effects. In addition, the diversity and distribution of zooplankton communities 3 decline sharpl y at ANC levels below 20 μeq/L. Overall, there is little uncertainty that significant 4 effects on aquatic biota are occurring at ANC levels below 20 μeq/L

. 5 It is clear that at ANC levels approaching 0 μeq/L (Table II
- 1), there is significant 6 impairment of sensitive aquatic ecos ys tems with almost complete loss of fish species. Avoiding 7 ANC levels approaching 0 μeq/Lis particularl y relevant to episodic spikes in acidity that occur 8 during periods of rapid snow melt and during and after major precipitation events. Since the 9 ANC range considered in the Policy Assessment reflects average, long

- term base flow values, it 10 is appropriate to consider protecting against episodic drops in ANC values to a level as low as 0 11 μeq/L. Staddard et al. (2003) noted on average a 30 μeq/Ldepression of ANC between spring 12 and summer time values, indicating the need to maintain higher base flow ANC levels to protect 13 against ANC levels below 0 μeq/L . The above considerations do not provid e support for a target 14 chronic ANC level as low as 0 μeq/Lfor a standard that would protect against significant harm to 15 aquatic ecosy stems, including harm from episodic acidification. The Policy Assessment 16 concludes that these considerations also support a lower end of the range for consideration no 17 lower than 20 μeq/L . 18 The CASAC agreed with this conclusion in its comments on the second draft Policy 19 Assessment (Russell and Samet, 2010b). CASAC noted that “there are clear and marked 20 biological effects at ANC values near 0 μeq/L, so this is probably not an appropriate target 21 value” for the AAI. With regard to the likelihood of impairment of aquatic ecos ys tems due to 22

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59 episodic acidification , in terms of specific target levels for chronic ANC, CASAC expressed the 1 following view: 2 Based on surface waters studied in the Northeast, decreases in ANC 3 associated with snowmelt [are] approximately 50 μeq/L . Thus, based on these 4 studies, a long term ANC target level of 75 μeq/L would generall y guard against 5 effects from episodic acidification down to a level of about 25 μeq/L . (Russell and 6 Samet, 2010b) 7 8 9 10 4. Consideration of Ecosystem Response Time 11 The Policy

Assessment notes that when considering a standard level to protect against 12 aquatic acidification, it is appropriate to take into account both the time period to recovery as 13 well as the potential for recovery in acid

- sensitive ecoregions. Ecos ys tems become adversel y 14 impacted b y acidif

yi ng depo sition over long periods of time and have variable time frames and 15 abilities to recover from such perturbations. Modeling presented in the REA (US EPA, 2009 , 16 section 4.2.4) shows the estimated ANC values for Adirondack lakes and Shenandoah streams 17 under pre - acidification conditions and indicates that for a small percentage of lakes and streams, 18 natural ANC levels would have been below 50 μeq/L . Therefore, for these water bodies, 19 reductions in acidifying deposition are not likely to achieve an ANC of 50 μeq/Lor greater. 20 Conversel y, for some lakes and streams the level of perturbation from long periods of acidifying 21 deposition has resulted in very low ANC values compared to estimated natural conditions. For 22 such water bodies, the time to recovery would be l argel y dependent on future inputs of acidifying 23 deposition. 24 Setting a standard level in terms of a target chronic ANC level is based on the long

- term 25 response of aquatic ecosy stems. The time required for a water body to achieve the target ANC 26 level

-- gi ven a decrease in ambient air concentrations of NOy and SOx and related acidifying 27

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60 deposition such that the critical load for a target ANC is not exceeded

– is often decades if not 1 centuries. In recognition of the potential public welfare benefits of achi eving the target ANC in 2 a shorter time frame, the concept of target loads had been developed. Target loads represent the 3 depositional loading that is expected to achieve a particular level of the ecological indicator by a 4 given time. For example, to achi eve an ANC level of 20 μeq/Lby 2030, it might be necessary to 5 specify

a higher target ANC level of, for example, 50 μeq/L , such that the depositional loading 6 would be reduced more quickly than would occur if the depositional loading was based on 7 achieving a target ANC level of 20 μeq/L as a long

- term equilibrium level. In this example, the 8 target ANC of 50 μeq/L would ultimately be realized many

years later. 9 The above considerations have implications for selecting an appropriate standard level, in 10 that the standard level affects not only the ultimate degree of protection that would be afforded 11 by the standard, but also the time frame in which such protection would be realized. However, 12 the Policy

Assessment recognizes that there is a great deal of hetero geneity in response times 13 among water bodies and that there is only very limited information from dy namic modeling that 14 would help to quantify recovery time frames in areas across the country . As a consequence, 15 quantification of a general relationship between critical loads associated with a specific long

16 term target ANC level and target loads associated with achieving the target ANC level within a 17 specific time frame is not currentl y possible. Thus, while the time frame for recovery is an 18 important consi deration in selecting an appropriate range of levels to consider, the Policy 19 Assessment concludes that it can only be considered in a qualitative sense at this time. 20 5. Prior Examples of Target ANC Levels 21 A number of regional organizations, states, and international organizations have 22 developed critical load frameworks to protect against acidification of sensitive aquatic 23

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61 ecos ys tems. In considering the appropriate range of target ANC levels for considerati on in this 1 review, it is informative to evaluate the target ANC levels selected b y these different 2 organizations, as well as the rationale provided in support of the selected levels. Chapter 4 of the 3 Policy

Assessment provides a detailed discussion of how critical loads have been developed and 4 used in other contexts. Specific target values and their rationales are summarized below. 5 The UNECE has developed critical loads in support of international emissions reduction 6 agreements. As noted in chapter 4 of the Policy Assessment, critical loads were established to 7 protect 95 percent of surface waters in Europe from an ANC less than 20 μeq/L based on 8 protection of brown trout. Individual countries have set alternative ANC targets; for example, 9 Norway

targets an ANC of 30 μeq/Lbased on protection of Atlantic salmon. 10 Several states have established target ANC or pH values related to protection of lakes and 11 streams from acidification. While recognizing that some lakes in the Adirondacks will have a 12 naturally

l ow pH, the state of New York has established a target pH value of 6.5 for lakes that 13 are not naturally

below 6.5. As noted above, this level is associated with an ANC value that is 14 likely

to be between 20 and 50 μeq/L or possibl y higher. New Hampshire an d Vermont have set 15 ANC targets of 60 μeq/L and 50 μeq/L , respectively . Tennessee has established site

- specific 16 target ANC values based on assessments of natural acidity , with a default value of 50 μeq/L 17 when specific data are not available. 18 Taken togethe r, these policy responses to concerns about ecological effects associated 19 with aquatic acidification indicate that target ANC values between 20 and 60 μeq/Lhave been 20 selected b y states and other nations to provide protection of lakes and streams in some o f the 21 more sensitive aquatic ecosy stems. 22 6. Consideration of Public Welfare Benefits 23

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62 The point at which effects on public welfare become adverse is not defined in the CAA. 1 Characterizing a known or anticipated adverse effect to public welfare is an impor tant 2 component of developing any secondary

NAAQS. According to the CAA, welfare effects 3 include: 4 ...effects on soils, water, crops, vegetation, manmade materials, animals, 5 wildlife, weather, visibility , and climate, damage to and deterioration of 6 property, and hazards to transportation, as well as effect on economic values and 7 on personal comfort and well

- being, whether caused by transformation, 8 conversion, or combination with other air pollutants. (CAA, section 302(h)). 9 10 Consideration of adversity to public welfare in the context of the secondary NAAQS for oxides 11 of nitrogen and sulfur can be informed b y information about losses in ecosystem services 12 associated with acidifying deposition and the potential economic value of those losses, as 13 summarized above i n section II. C and discussed more full y in chapter 4 of the Policy 14 Assessment. 15 Ecosy stem service losses at alternative ANC levels are difficult to enumerate. However, 16 in general there are categories of ecos ys tem services, discussed in chapter 4 of the Policy 17 Assessment, that are related to the specific ecos ys tem damages expected to occur at alternative 18 ANC levels. Losses in fish populations due to very low ANC (below 20 μeq/L) are likel y 19 associated with significant losses in value for recreational and subsistence fishers. Many acid 20 sensitive lakes are located in areas with high levels of recreational fishing activity . For example, 21 in the northeastern U.S., where nearl y 8 percent of lakes are considered acidic, more than 9 22 percent of adults participate in freshwater fishing, with an estimated value of approximately $5 23 billion in 2006. This suggests that improvements in lake fish populations may be associated with 24 significant recreational fishing value. 25

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63 As discussed in the Policy Assessment, inland sur face waters also provide cultural 1 services such as aesthetic and existence value and educational services. To the extent that 2 piscivorous birds and other wildlife are harmed b y the absence of fish in these waters, hunting 3 and birdwatching activities are l ikel y to be adversely affected. A case study of the value to New 4 York residents of improving the health of lakes in the Adirondacks found significant willingness 5 to pay

for those improvements. When scaled to evaluate the improvement in lake health from 6
a chieving ANC values of either 20 or 50 μeq/L , the study implies benefits to the New York 7 population roughl y on the order of $ 3 00
- 900 million per year (in constant 2007$) . The survey 8 administered in this study recognized that participants were thinking about the full range of 9 services provided b y the lakes in question

– not just the recreational fishing services. Therefore 10 the estimates of willingness to pay include resident’s benefits for potential hunting and 11 birdwatching activities and other ancillary services. These results are just for New York 12 populations. The Policy Assessment concludes that if similar benefits exist for improvements in 13 other acid sensitive lakes, the economic value to U.S. po pulations could be very substantial, 14 suggesting that, at least by one measure of impact on public welfare, impacts associated with 15 ANC less than 50 μeq/Lmay be adverse to public welfare. 16 7. Summary of Alternative Levels 17 Based on all the above considerati ons, the Policy Assessment concludes that 18 consideration should be given to a range of standard levels from 20 to 75 μeq/L . The available 19 evidence indicates that target ANC levels below 20 μeq/L would be inadequate to protect against 20 substantial ecological effects and potential catastrophic loss of ecos ys tem function in some 21 sensitive aquatic ecosy stems. While ecological effects occur at ANC levels below 50 μeq/Lin 22 some sensitive ecos ys tems, the degree and nature of those effects are less significant than at 23

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64 levels below 20 μeq/L. Levels at and above 50 μeq/Lwould be expected to provide additional 1 protection, although uncertainties regarding the potential for additional protection from adverse 2 ecological effects are much larger for target ANC levels abo ve about 75 μeq/L , as effects are 3 generall y appreciably less sensitive to changes in ANC at such higher levels. 4 In reaching this conclusion in the Policy Assessment, consideration was given to the 5 extent to which a target ANC level within this range would protect against episodic as well as 6 long

- term ecological effects. Levels in the mid

- to upper part of this range would be expected to 7 provide greater protection against short

- term, episodic peaks in aquatic acidification, while lower 8 levels within this range would give more weight to protection from long

- term rather than 9 episodic acidification. Similarly , levels in the mid

- to upper part of this range would be expected 10 to result in shorter time periods for recovery given the lag in ecos ys tem response in some 11 sensitive ecos ys tems relative to levels in the lower part of this range. The Policy Assessment 12 also note that this range encompasses target ANC values that have been established by various 13 States and regional and international organizations to protec t against acidification of aquatic 14
ecos ys tems. 15 The Policy

Assessment recognizes that the level of the standard together with the other 16 elements of the standard, including the ambient air indicators, averaging time, and form, 17 determine the overall protecti veness of the standard. Thus, consideration of a standard level 18 should reflect the strengths and limitations of the evidence and assessments as well as the 19 inherent uncertainties in the development of each of the elements of the standard. The 20 implication s of considering alternative standards, defined in terms of alternative combinations of 21 levels and percentile values that are a critical component of factor F1 in the form of the standard, 22

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65 are discussed below in section III.E. Key uncertainties in the various components of the standard 1 are summarized and considered below in section III.F. 2 E. Combined Alternative Levels and Forms 3 To provide some perspective on the implications of various alternative multi

- pollutant, 4 AAI
- based standards, the Policy Assessm ent presented the number of acid

- sensitive ecoregions 5 that would likely

not meet various sets of alternative standards. The alternative standards 6 considered were based on combinations of alternative target ANC levels, within the range of 20 7 to 75 μeq/L , and alternative forms, characterized by alternative representative percentiles within 8 the range of the 70 th to 90 th percentile. These alternative standards are also defined in terms of 9 the other elements of the standard: ambient air indicators NOy and SOx , discussed above in 10 section III.A; other elements of the form of the standard, including ecoregion

- specific values for 11 factors F1 through F4 in the AAI equation, discussed above in section III.B.5; and an annual 12 averaging time for NOy and SOx, discussed a

bove in section III.C. With regard to the averaging 13 time, the assessment did not consider multi

- ye ar averaging of the calculated annual AAI values 14 due to data limitations, including, for example, the lack of CMAQ modeling for multiple 15 consecutive ye ars. In this assessment, we characterize an ecoregion as likely not meeting a given 16 alternative standard if the calculated AAI value is less than the target ANC level of the standard, 17 recognizing that higher AAI values are more protective than lower values. 18 Th e results of this assessment are presented in Table 7

- 1a
- d in the Policy Assessment for 19 a subset of ecoregions including those characterized as acid sensitive. Calculated annual AAI 20 values at the ecoregion level are shown for each alternative standard con sidered. Based on these 21 AAI values, Table 7

- 2 in the Policy Assessment summarizes the number of acid

- sensitive 22

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66 ecoregions that would likely not meet each of the alternative standards considered. 9 Calculated 1 AAI values for all ecoregions categorized as r elatively non - acid sensitive are shown in Table D

- 5 2 in Appendix D of the Policy Assessment. In all cases, these relatively non - acid sensitive 3 ecoregions were estimated to meet all of the alternative standards considered in this assessment. 4 As described a bove, the AAI values presented in Table 7

- 1a
- d of the Policy Assessment 5 are based in part on data from 2005 CMAQ model simulations, which was used to generate 6 values for F2 through F4 in the AAI equation, as well as to estimate annual average ambient air 7
c oncentrations of NOy and SOx that reflect recent air quality in the absence of currentl y 8 available monitored concentrations in sensitive ecoregions across the country . Water quality and 9 hydrology

data from water bodies within each ecoregion were also used in calculating the AAI 10 values. Such data were initially used to calculate critical loads for each water body with 11 sufficient data within an ecoregion so as to identify the nth percentile critical load representative 12 of the ecoregion used in calculating the F1 factor for the ecoregion. As expected, the number of 13 ecoregions that likel y would not meet alternative standards increases with increasing percentile 14 values and target ANC levels (US EPA, 2011, Table 7

- 2 ). Out of 22 acid

- sensitive ecoregions, 15 the number of ecoregions that would likely not meet the alternative standards ranges from 22 for 16 the most protective alternative standard considered (75 μeq/L , 90 th percentile) to 4 for the least 17 protective alternative standard (20 μeq/L, 70 th percentile). It is apparent that both the percentile 18 and the level chosen have a strong influence, over the ranges considered, in determining the 19 number of areas that would likely not meet this set of alternative standards. 20

9 Ta

bles 7

- 1a
- d and 7

- 2 in the Policy Assessment present assessment results for 29 ecoregions that had been initially characteriz ed as acid sensitive. Subsequently, based on a broader set of criteria used to characterize ecoregions as acid sensitive, as discussed above in section III.B.5.a, the set of ecoregions characterized as acid sensitive was narrowed to include 22 ecoregions.

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67 The Policy

Assessment observes that there is one grouping of these acid

- sensitive 1 ecoregions that would likely not meet almost all combinations of level and form under 2 consideration (US EPA, 2011, Table 7

- 2 and Appendix D ). This group is made up of southern 3 Appalachian mountain areas, including North Central Appalachians, 5.3.3; Ridge and Valley , 4 8.4.1; Central Appalachians, 8.4.2; Blue Ridge, 8.4.4; and Southwestern Appalachians, 8.4.9. In 5 addition, these ecoregions exhibit the highest amounts of exceedance relative to alternative 6 standards. 7 The Northern Appalachian and Atlantic Maritime Highlands (5.3.1), which includes the 8 Adirondacks, and the Northern Lakes and Forests (5.2.1) of the upper midwest exhibit similar 9 patterns with respect to in the role of level and percentile in identifying region s not likely to meet 10 alternative standards, although there are considerably fewer cases compared to the regions in the 11 Appalachians. 12 In the mountainous west, the Sierra Nevada (6.2.12), Idaho Batholith (6.2.15) and the 13 Cascades (6.2.7) ecoregions likely w ould not meet alternative standards in fewer cases relative to 14 eastern regions, with the Sierra Nevada ecoregion exhibiting relatively greater sensitivity 15 compared to all western regions. Onl y in the upper part of the ranges of level and percentile do 16 reg ions in the northern and central Rockies likel y not meet alternative standards. 17 In considering these findings, the Policy Assessment observes that the standard as 18 defined b y the AAI behaves in an intuitively logical manner. That is, an increase in ecoregions 19 likely

not to meet the standard is associated with higher alternative levels and percentiles, both of 20 which contribute to a lower regionally representative critical load. Moreover, the areas of known 21 adverse aquatic acidification effects are identified, mostly in high elevation regions or in the 22 northern latitudes

-- the Adironda cks, Shenandoahs, northern midwest lakes and the mountainous 23

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68 west. These results reflect the first application of a nationwide model that integrates water 1 quality

and atmospheric processes at a national scale and provides findings that are consistent 2 with our basic understanding of the extent of aquatic acidification across the U.S. What is 3 particularl y noteworthy is that this model is not initialized with a starting ANC based on water 4 quality

data, which likely would result in a reproduction of water quality observations. Rather, 5 this standard reflects the potential of the changes in atmospheric concentrations of NOy and SOx 6 to induce long

- term sustained changes in surface water s ys tems. The Policy Assessment notes 7 that the fact that the patterns of adv ersity based on applying this standard are commensurate with 8 what is observed in surface water s ys tems provides confidence in the basic underlying 9 formulation of the standard. 10 The Policy

Assessment notes that the Appalachian mountain regions merit further 11 inspection as they

stand out as areas with the largest relative exceedances from a national 12 perspective. Water quality data from these regions as well as an emissions sensitivity CMAQ 13 simulation were considered to better understand the simulated behavior of these regions. The 14 maps and tables in appendix D of the Policy Assessment include paired comparisons of the 15 CMAQ 2005 and emissions sensitivity simulations. The emissions sensitivity simulation reflects 16 domain

- wide reductions in NOy and SOx emissions of 48% and 42%, respectively , relative to 17 2005 base year emissions. The Policy Assessment assumes that this emissions sensitivity 18 simulation is indicative of future conditions. 19 The emissions sensitivity results project that many of the regions that l ikel y would not 20 meet the alternative standards based on recent air quality , especiall y at alternative levels of 20 21 and 35 μeq/L , would likely meet such standards in the future year scenario for the Appalachian 22 mountain regions. It is apparent that the AAI calculations are especiall y sensitive to changes in 23

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69 SOx emissions as the Appalachian regions have the highest SOx concentrations and deposition 1 rates (US EPA, 2011, section 2), and the AAI equation responds as expected to modeled 2 reductions in SOx. The e missions sensitivity scenario is a prospective application of the 3 standard, in the sense that rules derived from the air quality management process result in 4 reductions of NOy

and SOx emissions. Expected emission changes over the next two decades 5 should be far greater than the 42 and 48% SOx and NOy reductions used in this analy sis, with a 6 consequent further reduction in areas that would likely not meet alternative standards. 7 The Appalachian mountain regions generally have low DOC levels, average runoff rates, 8 moderatel y low base cation supply and highl y elevated sulfate concentrations. Collectively, 9 those attributes do not suggest naturall y acidic conditions as the availability of anthropogenic 10 contributions of mineral acids is likely responsible for ob served low ANC values in those 11 regions. 12 The Policy

Assessment notes the Sierra Nevada region as an interesting case study , as it 13 has some of the lowest critical load values nationally (US EPA, 2011, Table D

- 3 ). Water quality 14 data indicate extremel y l ow s ulfate, as expected given the relativel y low SO 2 emissions in the 15 western U.S. Extremely low base cation suppl y and low Neco, which mitigate the effect of 16 nitrogen deposition, explain the low critical load values. Low Neco values appear to associate 17 wel l with high elevation western U.S. regions, perhaps reflecting the more arid and reduced 18 vegetation density

relative to eastern U.S. regions. The proximity to high level nitrogen 19 emissions combined with very low base cation supply

explains the cases where the Sierra region 20 likely

does not meet alternative standards. Because Neco values are low in the Sierras, the 21 sy stem responds effectively to reductions of NOx emissions, as illustrated in the maps and tables 22 of Appendix D of the Policy Assessment. Althou gh Neco affords protection from the acidifying 23

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70 effects of nitrogen deposition, the availability of excessive nitrogen neutralization capacity also 1 means that reductions in nitrogen are not as effective as reductions in SOx in reducing the 2 calculated AAI. 3 In reviewing these results, the Policy Assessment observes that the anal ys is of the 4 alternative combinations of level and form presented provide context for considering the impact 5 of different standards. Since the AAI equation has been newl y developed in the Policy 6 Assessment, these examples of estimated exceedances help to address the question of whether 7 the AAI equation responds in a reasonable manner with regard to identifying areas of concern 8 and to prospective changes in atmospheric conditions likely to result from future emissions 9 reduction strategies. The Policy Assessment concludes that the behavior of the AAI calculations 10 is both reasonable and explainable, which the Policy Assessment concludes serves to increase 11 confidence in considering a stand ard defined in terms of the AAI. 12 F. Characterization of Uncertainties 13 This section summarizes discussions of the results of anal ys es and assessments, presented 14 more fully

in the Policy

Assessment (US EPA, 2011 , section 7.6 and Appendices F and G), 15 intended to address the relative confidence associated with the linked atmospheric

- ecological 16 effects sy stem described above. An overview of uncertainties is presented in the context of the 17 major structural components underl yi ng the standard, as well as with regard to areas of relativel y 18 high uncertainty. The section closes with a discussion of data gaps and uncertainties associated 19 with the use of ecological and atmospheric modeling to specify the factors in the AAI e quation, 20 which can be used to guide future field programs and longer

- term research efforts. 21 1. Overview of Uncertainty 22

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71 As discussed in the Policy Assessment (US EPA, 2011, Table 7
- 3), there is relativel y low 1 uncertainty with regard to the conceptual formulation of the overall structure of the AAI

- based 2 standard that incorporat es the major associations linking biological effects to air concentrations. 3 Based on the strength of the evidence that links species richness and mortality to water quality , 4 the ass ociations are strongl y causal and without any obvious confounding influence. The strong 5 association between the ecosy stem indicator (ANC) and the causative water chemistry species 6 (dissolved aluminum and hydrogen ion) reinforces the confidence in the linkage between 7 deposition of nitrogen and sulfur and effects . This strong association between ANC and effects 8 is supported by

a sound mechanistic foundation between deposition and ANC. The same 9 mechanistic strength holds true for the relationship between am bient air levels of nitrogen and 10 sulfur and deposition, which completes the linkage from ambient air indicators through 11 deposition to ecological effects. 12 There are relativel y higher uncertainties, however, in considering specific elements 13 within the structure of an AAI
- based standard, including the deposition of SOx, NOy , and NHx 14 as well as the critical load

- related component, each of which can vary within and across 15 ecoregions. Overall sy stem uncertainty relates not just to the uncertainty in each s uch element, 16 but also to the combined uncertainties that result from linking these elements together within the 17 AAI
- based structure. Some of these elements

– including , for example, dry deposition, pre

18 industrial base cation production , and reduced nitrog en deposition

– are estimated with less 19 confidence than other elements (US EPA, 2011, Table 7.3 ). The uncertainties associated with all 20 of these elements, and the combination of these elements through the AAI equation, are 21 discussed below and in the following sections related to measured data gaps and modeled 22 processes for both air quality and water quality

. 23

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72 The lack of observed dry deposition data is constrained b y resources and the lack of 1 efficient measurement technologies. Progress in reducing uncertainties in dry deposition will 2 depend on improved atmospheric concentration data and direct deposition flux measurements of 3 the relevant suite of NOy and SOx species

. 4 Pre
- industrial base cation productivity by definition is not observable. Contemporary 5 observations and inter

- model comparisons are useful tools that would help reduce the uncertainty 6 in estimates of preindustrial base cation productivity used in the AAI equation

. In characterizing 7 contemporary

base cation flux using basic water quality measurements (i.e., major anioni and 8 cation species as defined in equation 2.11 in the Policy Assessment) , it is reasonable to assume 9 that a major component of contemporary base cation flux is associated with pre

- industrial 10 weathering rates. To the extent that multiple models converge on similar solutions, greater 11 confidence in estimating pre

- industrial base cation production would be achieved. 12 Characterization of reduced nitrogen (NHx) deposition has been evolving over the last 13 decade. The relativel y h igh uncertainty in characterizing NHx deposition is due to both the lack 14 of field measurements and the inherent complexity of characterizing NHx with respect to source 15 emissions and dry

deposition. Because ammonia emissions are generated through a combination 16 of man

- made and biological activities, and ammonia is semi

- volatile, the ability to characterize 17 spatial and temporal distributions of NHx concentration s and deposition patterns is challenging. 18 While direct measurement of NHx deposition is resource intensive because of the diffuse nature 19 of sources (i.e., area

- wide and not point sources), there have been more frequent deposition flux 20 studies, relative to other nitrogen species, that enable the estimation of both emissions and dry 21 deposition. Also, wh ile ammonia has a relativel y high deposition velocity and traditionally was 22 thought to deposit close to the emissions release areas, the semi

- volatile nature of ammonia 23

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73 results in re

- entrainment back into the lower boundary layer resulting in a more disper sed 1 concentration pattern exhibiting transport ty pe characteristics similar to longer lived atmospheric 2 species. These inherent complexities in source characterization and ambient concentration 3 patterns raise the uncertainty level of NHx in general. However, the Policy Assessment notes 4 that progress is being made in measuring ammonia with cost efficient samplers and anticipates 5 the gradual evolution of a spatially robust ammonia sampling network that would help support 6 anal ys es to reduce underlyinguncert ainties in NHx deposition. Also, from an aquatic 7 acidification perspective, NHx is not as important a driver as NOy and SOx in the mountainous 8 areas in the eastern U
. S. However, the relative importance of NHx is likely to increase over 9 time, in light of air quality rules in place designed to reduce emissions of NOy and SOx. 10 2. Uncertainties Associated with Data Gaps 11 In summarizing uncertainties with respect to available measurement data and the use of 12 ecological and atmospheric models, the Policy Assessm ent indentified data gaps and model 13 uncertainties in relative terms by comparing, for example, the relative richness of data between 14 geographic areas or environmental media. With regard to relevant air quality measurements, the 15 Policy

Assessment notes that such measurements are relativel y sparse in the western U.S. While 16 the spatial extent of CASTNET coverage has gradually incorporated western U.S. locations with 17 support from the National Parks Service (NPS), the relative density of monitoring sites is mu ch 18 less than that in the eastern U.S. This relative disparity in spatial density

of monitors is 19 exacerbated as air quality patterns in the mountainous west generally exhibit greater spatial 20 heterogeneity

due to dramatic elevation gradients that impact met eorology and air mass flow 21 patterns. Similarly , water quality data coverage is far more comprehensive in the eastern U.S. 22 relative to the west 23

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74 Measurements of NOy

notably are lacking in both eastern and western acid

- sensitive 1 ecoregions. This adds uncer tainty to the use of the AAI equation as the lack of NOy data limits 2 efforts to evaluate air quality model ing of NOy that is the basis for quantifying factor F3 in the 3 AAI equation . The lack of NOy measurements also limits efforts to characterize the variability 4 and representativeness of modeled NOy concentrations within and across ecoregions

. Currently , 5 the Agency ’s ability to define the protection likely to be afforded by

alternative standards (in 6 terms of alternative levels and percentiles) is comp romised by the lack of a full set of ambient air 7 quality

indicator measurements , notably including NOy , throughout sensitive ecoregions across 8 the U.S

. 9 Further, obtaining measurement of the dominant species that comprise NOy ( HNO 3 , true 10 NO 2 , NO , p
–

NO 3 , and PAN) would be useful to evaluate performance of NOy samplers. 11 Be yond the more well known dominant components of NOy , research efforts would be needed to 12 characterize total reactive nitrogen that may include significant amounts of organicall y- b ound 13 ni trogen (beyond PAN) which is poorly understood with regard to emission sources and 14 concentration levels. 15 Field measurements of NHx have been extremel y limited, but have begun to be enhanced 16 through the National Atmospheric Deposition Program’s (NADP) passi ve ammonia network 17 (AMoN). AMoN measures ammonia at over 50 sites, with more than 35 at CASTNET locations. 18 Enhanced spatial coverage of reduced nitrogen measurements , particularl y t o understand within 19 and across ecoregion variability , and the inclusion o f some continuous observations would 20 provide a better understanding of the uncertainty in the F2 factor in the AAI equation and of the 21 representativeness of modeled NHx deposition within and across ecoregions. 22

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75 With regard to water quality data, the Policy Assessment notes that such data are 1 ty picall y limited relative to air quality data sets, and are also relativel y sparse in the western U.S. 2 The TIME/LTM water quality sampling program in the eastern U.S. (as described in chapter 2 3 of the Policy

Assessment) is an appropriate complement to national air monitoring programs as it 4 affords consistency

across water bodies in terms of sampling frequency and anal ys is protocols. 5 Consideration should be given to extending the TIME/L TM design to all acid sensitive 6 ecoregions, with priority for areas in the western mountains that are data limited and showing 7 initial signs of adversity particularl y with respect to aquatic acidification. The lack of a 8 regulatory

requirement for TIME/LTM often jeopardizes funding suppo rt of this resource that is 9 especiall y valuable and cost effective. While there are several state and local agency water 10 quality

data bases, it is unclear the extent to which differences in sampling, chemical analy sis 11 and reporting protocols would impact the use of such data for the purpose of better 12 understanding the degree of protectiveness that would be afforded b y an AAI
- based standard 13 within sensitive ecoregions across the country . In addition, our understanding of water quality in 14 Alaska and Hawaii and the acid sensitiv ity of their ecoregions is particularly limited

. 15 Water quality data and modeling support the standard setting process. As more water 16 bodies are sampled, the critical load data bases would expand, enabling clearer delineation of 17 ecoregion representative critical loads in terms of the nth percentile. This w ould provide more 18 refined characterization of the degree of protection afforded by a given standard. Longer term, 19 the availability

of w ater quality

trend data (annual to monthly sampled) would support 20 accountability

assessments that examine if an ecoregion’s response to air management efforts is 21 as predicted b y earlier model forecasting. The most obvious example is the long

- term response 22 of water quality

ANC change to changes in calculated AAI, deposition, ambient NOy and SOx 23

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76 concentrations, and emissions. In addition, water quality trends data provide a basis for 1 evaluating and improving the parameterizations of processes in critical lo ad models applied at 2 the ecoregion scale related to nitrogen retention and base cation suppl y. A better understanding 3 of soil processes , especially in the southern Appalachians, would enhance efforts to examin e the 4 variability

within ecoregions of the soi l

- based adsorption and exchange processes which 5 moderate the suppl y of major cations and anions to surface waters and strongl y influence the 6 response of surface water ANC to changes in deposition of nitrogen and sulfur. 7 3. Uncertainties in Modeled Processes 8 As discussed in the Policy Assessment, from an uncertainty perspective, gaps in field 9 measurement data are related to uncertainties in modeled processes and in the specific 10 application of such models

. As noted above, processes that are embodied in an AAI
- based 11 standard are modeled using the CMAQ atmospheric model and steady state ecological models. 12 These models are characterized in the Integrated Science Assessment as being well established 13 and they

have undergone extensive peer review. Nonetheless, the application of these models for 14 purposes of specifying the factors in the AAI equation, on an ecoregion scale, is a new 15 application that introduces uncertainties, as noted below, especially in areas with limited 16 observational data that can be used to ev aluate this specific application. Understanding 17 uncertainties in relevant modeled process thus involves consideration of the uncertainties 18 associated with appl yi ng each model as well as the combination of these uncertainties as the 19 models are applied in c ombination within the AAI framework. 20 With regard to the application of CMAQ for purposes of use in an AAI

- based standard, 21 the modeling of dry deposition has been identified as having a relativel y high degree of 22 uncertainty. Due to a combination of sy stem complexity and resource constraints, there is no 23

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77 routine observational basis for directl y comparing modeled dry deposition and measurements. 1 Periodic dry

deposition flux experiments covering a variety of vegetation, surfaces and 2 meteorology

across seasons would enable a more robust evaluation of modeled deposition of 3 nitrogen and sulfur. Given the difficulty in acquiring dry deposition observations, it becomes 4 especiall y important to evaluate the model’s ability to capture temporal and spatial ambient air 5 patterns of individual nitrogen and sulfur species which are used to drive dry deposition 6 calculations in models. For example, reducing a generall y acknowledged positive bias in model

7 predicted SO 2 relative to observations is especiall y relevant to the AAI
- based standard, as SO 2 8 deposition is a dominant contributor to total acidifyingdeposition in the eastern U.S. With 9 respect to oxidized nitrogen, observations of individual NOy species are important as air quality 10 models calculate the individual deposi tion of each species. The modeled transference ratios, 11 TNOy and T SOx used in factors F3 and F4 rel y on CMAQ’s ability to characterize both deposition 12 and concentration. Consequently , a better understanding of the variability of these factors 13 within and across ecoregions could be achieved b y improved availability of measured ambient 14 concentration s and deposition observations. 15 Steady

state biogeochemical ecos ys tem modeling is used to develop critical load 16 estimates that are incorporated in the AAI equation through factor F1. Consequently , the Policy 17 Assessment notes that an estimate of the temporal response of surface water ANC to deposition 18 and air concentration changes is not directly available. Lacking a predicted temporal response 19 impairs the ability

to conduct accountability assessments down to the effects level. 20 Accountability

assessments would examine the response of ea ch step in the emissions source 21 through air concentration

– deposition

-- surface water quality
– biota continuum. The steady 22 state assumption at the ecosy stem level does not impair accountability assessments through the 23

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78 air concentration/deposition range of that continuum. However, i n using steady state ecos ys tem 1 modeling, several assumptions are made relative to the long

- term importance of processes 2 related to soil adsorption of major ions and ecos ys tem nitrogen dyn amics. Because these models 3 often were developed and applied in glaciated areas with relativel y thin and organicall y rich 4 soils, their applicability is relativel y more uncertain in areas such as those in the non

- glaciated 5 clay

- based soil regions of the central Appalachians. Consequently , it i s desirable to develop the 6 information bases to drive simple dy namic ecos ys tem models that incorporate more detailed 7 treatment of subsurface processes, such as adsorption and exchange processes and sulfate 8 absorption. 9 4. Applying Knowledge of Uncertainties 10 An understanding of the relative uncertainties in a sy stem assists in setting priorities for 11 data collection efforts and research, with the expectation that such efforts would reduce 12 uncertainties over time and afford greater confidence in applications of an AAI
- based standard. 13 Because of the uniquel y wide breadth of pollutants and environmental media addressed b y an 14 AAI
- based multi

- pollutant standard, there are a wide range of uncertainties that are important to 15 consider relative to single pollutant stan dards that ty picall y address onl y direct effects of ambient 16 air exposures. For an AAI
- based standard, a reduction of the uncertainties across the various 17 modeled processes at the ecoregion scale would lead to greater confidence in the degree of 18 protection afforded b y the standard. 19 The Policy

Assessment notes that there is general ly low uncertainty with regard to the 20 conceptual development and related major components of this standard. In recognizing the 21 scientific soundness of the basic structure of this standard, the Policy Assessment notes that 22 future efforts would be appropriatel y directed at expanding the availability of relevant data for 23

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79 ecoregion

- specific e valuati on and application of the relevant modeling of ecological and 1 atmospheric processes, as identified above . Such efforts would further support consideration of 2 an AAI
- based standard and would guide field studies and anal ys es designed to improve the 3 longer

- term confidence in such a standard. 4 G. CASAC Advice 5 The CASAC has advised EPA concer ning the Integrated Science Assessment, the Risk 6 and Exposure Assessment, and the Policy Assessment. CASAC has endorsed EPA’s 7 interpretation of the science embodied in the Integrated Science Assessment and the assessment 8 approaches and conclusions incorpo rated in the Risk and Exposure Assessment

. 9 Most recentl y, CASAC has considered the information in the final Policy Assessment in 10 providing its recommendations on the review of the new multi

- pollutant standard developed in 11 that document and discussed above (Russell and Samet, 2011 a). In so doing, CASAC has 12 expressed general support for the conceptual framework of the standard based on the underl yi ng 13 scientific information, as well as for the conclusions in the Policy Assessment with regard to 14 indicators, f

orm, averaging time, and level of the standard that are appropriate for consideration 15 by the Agency

in reaching decisions on the review of the secondary NAAQS for oxides of 16 nitrogen and sulfur: 17 The final Policy Assessment clearl y s ets out the basis for the recommended ranges 18 for each of the four elements (indicator, averaging time, level and form) of a 19 potential NAAQS that uses ambient air indicators to address the combined effects 20 of oxides of nitrogen and oxides of sulfur on aquatic ecos ys tems, primaril y 21 streams and lakes. As requested in our previous letters, the Policy Assessment also 22 describes the implications of choosing specific combinations of elements and 23 provides numerous maps and tabular estimates of the spatial e xtent and degree of 24 severity of NAAQS exceedances expected to result from possible combinations of 25 the elements of the standard. 26 27 We believe this final PA is appropriate for use in determining a secondary 28 standard to help protect aquatic ecos ys tems from ac idifying deposition of oxides 29

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80 of sulfur and nitrogen. EPA staff has done a commendable job developing the 1 innovative Aquatic Acidification Index (AAI), which provides a framework for a 2 national standard based on ambient concentrations that also takes into account 3 regional differences in sensitivities of ecosy stems across the country to effects of 4 acidifying deposition. (Russell and Samet, 2011 a) 5 6 CASAC also recommended that as EPA moves forward in the regulatory process “some 7 attention should be given to o ur residual concern that the available data may reflect the more 8 sensitive water bodies and thus, the selection of percentiles of waterbodies to be protected could 9 be conservativel y biased” (Russell and Samet, 2011 a). In additional, CASAC found some 10 impro vements could be made to the uncertainty analy sis, as noted below. 11 With respect to indicators, CASAC supports the use of SOx and NOy as ambient air indicators 12 (discussed above in section III.A) and ANC as the ecological indicator (discussed above in 13 sectio n III.B.1): 14 The use of total reactive oxidized nitrogen (NOy) and sulfur oxides (SOx) as atmospheric 15 indicators of oxidized nitrogen (N) and sulfur (S) atmospheric concentrations is well justified. 16 The use in the Aquatic Acidification Index (AAI) of NOy and SOx as atmospheric indicators of 17 N and S concentrations is useful and corresponds with other efforts by EPA. As we have stated 18 previously , CASAC also agrees that acid neutralizing capacity (ANC) is the most appropriate 19 ecological indicator of aquatic ecos ys tem response and resiliency to acidification. (Russell and 20 Samet, 2011 a) 21 With respect to the form of the standard (discussed above in section III.B), CASAC 22 stated the following: 23 EPA has developed the AAI, an innovative “form” of the NAAQS itself that 24 incorporates the multi

- pollutant, multi

- media, environmentally modified, 25 geographically variable nature of SOx/NOy deposition

- related aquatic 26 acidification effects. With the caveats noted below, CASAC believes that this 27 form of the NAAQS as described in the final Policy Assessment is consistent with 28

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81 and directl y reflective of current scientific understanding of effects of acidifying 1 deposition on aquatic ecosy stems. (Russell and Samet, 2011 a) 2 3 CASAC agrees that the spatial components of the form in the P olicy Assessment 4 are reasonable and that use of Omernick’s ecoregions (Level III) is appropriate for 5 a secondary

NAAQs intended to protect the aquatic environment from 6 acidification . . . (Russell and Samet, 2011 a) 7 8 The “caveats” noted b y CASAC include a recognition of the importance of continuing to 9 evaluate the performance of the CMAQ and ecological models to account for model 10 uncertainties and to make the model

- dependent factors in the AAI more transparent. In addition, 11 CASAC noted that the role of DOC and its effects on ANC would benefit from further 12 refinement and clarification (Russell and Samet, 2011 a). While CASAC expressed the view that 13 the “division of ecoregions into ‘sensitive’ and ‘non

- sensitive’ subsets, with a more protective 14 percentile app lied to the sensitive areas, also seems reasonable” (Russell and Samet, 2011 a), 15 CASAC also noted that there was the need for greater clarity in specifying how appropriate 16 screening criteria would be applied in assigning ecoregions to these categories. Furt her, CASAC 17 identified potential biases in critical load calculations and in the regional representativeness of 18 available water chemistry data, leading to the observation that a given percentile of the 19 distribution of estimated critical loads may be protective of a higher percentage of surface waters 20 in some regions (Russell and Samet, 2011 a). 21 With respect to averaging time (discussed above in section III.C), CASAC stated the 22 following: 23 Considering the cumulative nature of the long

- term adverse ecological effects and 24 the year - to - year variability of atmospheric conditions (mainly in the amount of 25 precipitation), CASAC concurs with EPA that an averaging time of three to five 26 ye ars for the AAI parameters is appropriate. A longer averaging time would mask 27 possible trends of AAI, while a shorter averaging time would make the AAI being 28

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82 more influenced b y the conditions of the particular years selected. (Russell and 1 Samet, 2011 a) 2 3 With respect to level as well as the combination of level and form as they are presented 4 as alternative standards (discussed above in sections III.D

- E), CASAC stated the following: 5 CASAC agrees with EPA staff’s recommendation that the “level” of the 6 alternative AAI standards should be within the range of 20 and 75 μeq/L. We also 7 recognize that both the “level” and the form of any AAIstandard are so closely 8 linked in their effectiveness that these two elements should be considered 9 together. (Russell and Samet, 2011 a) 10 11 When considered in isolation, it is difficult to evaluate the logic or implications 12 of selecting from percentiles (70th to 90th) of the distribution of estimated critical 13 loads for lakes in sensitive ecoregions to determine an acceptable amount of 14 deposition for a given ecoregion. However, when these percentile ranges are 15 combined with alternative levels within the staff

- recommended ANC range of 20 16 to 75 microequivalents per liter (μeq/L), the results using the AAI point to the 17 ecoregions across the country that would be expected to require additional 18 protection from acidifying deposition. Reasonable choices were made in 19 developing the form. The number of acid sensitive regions not likely to meet the 20 standard will be affected both by choice of ANC level and the percentile of the 21 distribution of critical loads for lakes to meet alternative ANC levels in each 22 region. These combined recommendations provide the Administrator with a 23 broad but reasonable range of minimally to substantially

protective options fo r the 24 standard. (Russell and Samet, 2011 a) 25 26 CASAC also commented on EPA’s uncertainty analysis, and provided advice on areas 27 requiring further clarification in the proposed rule and future research. CASAC found it 28 “difficult to judge the adequacy of the uncertainty anal ys is performed by EPA because of lack of 29 details on data inputs and the methodology used, and lack of clarity

in presentation” (Russell and 30 Samet, 2011 a). In particular, CASAC identified the need for more thorough model evaluations 31 of critical load and atmospheric modeling, recognizing the important role of models as they are 32 incorporated in the form of the standard. In light of the innovative nature of the standard 33 developed in the Policy Assessment, CASAC identified “a number of areas th at should be the 34

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83 focus of further research” (Russell and Samet, 2011 a). While CASAC recognized that EPA staff 1 was able to address some of the issues in the Policy Assessment, they

also noted areas “that 2 would benefit from further study or consideration in potential revisions or modifications to the 3 form of the standard.” Such research areas include “sulfur retention and mobilization in the 4 soils, aluminum availability , soil versus water acidification and ecos ys tem recovery times.” 5 Further, CASAC encourag ed future efforts to monitor individual ambient nitrogen species, 6 which would help inform further CMAQ evaluations and the specification of model

- derived 7 elements in the AAI equation (Russell and Samet, 2011 a). 8 H. Administrator’s Proposed Conclusions 9 Havi ng concluded that the existing NO 2 and SO 2 secondary standards are neither 10 sufficiently

protective nor appropriate to address deposition

- related effects associated with 11 oxides of nitrogen and sulfur (section II.D above), the Administrator has considered wh ether it is 12 appropriate at this time to set a new multi

- pollutant standard for that purpose , with a structure 13 that would better reflect the available science regarding acid deposition

. Inconsidering this, she 14 recognizes that such an appropriate standard , for purposes of section 109(b) and (d) of the 15 CAA , 11 must in her judgment be requisite to protect public welfare, such that it would be neither 16 more nor less stringent that necessary for that purpose. In particular, she has focused on the new 17 standard de veloped in the Policy Assessment and reviewed by CASAC, as discussed above. In 18 so doing, the Administrator first considered the extent to which there is a scientific basis for 19 development of such a standard, specificall y with regard to a standard that would provide 20 protection from deposition

- related aquatic acidification in sensitive aquatic ecos ys tems in areas 21 across the country . As discussed above, the Administrator notes that the Integrated Science 22

11 Section 109(d)( 1) requires that “...the Administrator shall complete a thorough revie w...and shall make such revisions in such criteria and standards and promulgate such new standards as may be appropriate under

... subsection 109(b) of this section.” [em phasis added]

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84 Assessment concludes that the available scientific evi dence is sufficient to infer a causal 1 relationship between acidifying deposition of nitrogen and sulfur in aquatic ecos ys tems, and that 2 the deposition of oxides of nitrogen and sulfur both cause such acidification under current 3 conditions in the U.S. Further, the Integrated Science Assessment concludes that there are well

4 established water quality and biological indicators of aquatic acidification as well as well

5 established models that address deposition, water quality , and effects on ecosy stem biota, an d 6 that ecos ys tem sensitivity to acidification varies across the country according to present and 7 historic nitrogen and sulfur deposition as well as geologic, soil, vegetative, and hydrologic 8 factors. Based on these considerations, the Administrator agrees with the conclusion in the 9 Policy

Assessment, and supported by CASAC, that there is a strong scientific basis for 10 development of a standard with the general structure presented in the Policy Assessment

. 11 The Administrator also recognizes that the conceptu al framework for an ecologically 12 relevant, multi

- pollutant standard, which was initially explored in the Risk and Exposure 13 Assessment and further developed in the Policy Assessment, builds on the information in the 14 Integrated Science Assessment. She notes that the structure of the standard addresses the 15 combined effects of deposition from oxides of nitrogen and sulfur b y characterizing the linkages 16 between ambient concentrations, deposition, and aquatic acidification, and that the structure of 17 the standard takes into account relevant variations in these linkages across the country . She 18 recognizes that while the standard is innovative and unique, the structure of the standard is well 19 grounded in the science underlying the relationships between ambient concentrations of oxides 20 of nitrogen and sulfur and the aquatic acidification related to deposition of nitrogen and sulfur 21 associated with such ambient concentrations. 22

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85 While the Administrator recognizes the strong scientific foundation for the structure of an 1 AAI
- based standard, she also recognizes that the standard depends on atmospheric and 2 ecological modeling , based on appropriate data, to specify the terms of an equation that 3 incorporates the linkages between ambient concentrations, deposition, and aquatic acidification. 4 This equation, which defines an aquatic acidification index (AAI), has the effect of translating 5 spatially

variable ecological effects into a potential national standard. With respect to 6 establishing the specific terms of this equation, th ere are a number of inherent uncertainties and 7 complexities that are relevant to the question of whether it is appropriate under section 109 to set 8
a specific AAI

- based standard at this time , recognizing that such a standard must be requisite to 9 protect pu

blic welfare without being either more or less stringent than necessary for this purpose

. 10 As discussed above, these uncertainties and complexities generall y relate not to the structure of 11 the standard, but to the quantification of the various elements of the standard, such as the F 12 factors discussed earlier in this section and their representativeness at an ecoregion scale

. These 13 uncertainties and complexities currentl y limit efforts to characterize the degree of protectiveness 14 that would be afforded by s uch a standard, within the ranges of levels and forms identified in the 15 Policy

Assessment, and the representativeness of F factors in the AAI equation described above 16 and in the Policy

Assessment. These important uncertainties have been generall y categori zed as 17 limitations in available field data as well as uncertainties that are related to reliance on the 18 application of ecological and atmospheric modeling at the ecoregion scale to specify the various 19 elements of the AAI. 20 With regard to data limitations, the Administrator observes that there are several 21 important limitations in the available data upon which elements of the AAI are based. For 22 example, while ambient measurements of NOy are made as part of a national monitoring 23

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86 network, the monitors are not located in locations that are representative of sensitive aquatic 1
ecos ys tems. While air and water quality data are generall y available in areas in the eastern U.S., 2 there is relativel y sparse coverage in mountainous western areas where a number of sensiti ve 3 aquatic ecosy stems are located. Further, even in areas where relevant data are available, small 4 sample sizes impede efforts to characterize the representativeness of the available data, which 5 was noted b y CASAC as being of particular concern. Also, me asurements of reduced forms of 6 nitrogen are available from only a small number of monitoring sites, and emission inventories for 7 reduced forms of nitrogen used in atmospheric modeling are subject to considerable uncertainty. 8 With regard to uncertainties related to the use of ecological and atmospheric modeling, 9 the Administrator notes in particular that model results are difficult to evaluate due to a lack of 10 relevant observational data. For example, relatively large uncertainties are introduced by a lack 11 of data with regard to pre

- industrial environmental conditions and other parameters that are 12 necessary

inputs to critical load models that are the basis for factor F1 in the AAI equation. 13 Also, observational data are not generall y available to evaluate the modeled relationships 14 between nitrogen and sulfur in the ambient air and associated deposition, which are the basis for 15 the other factors (i.e., F2, F3, and F4) in the AAI equation. 16 In combination, these limitations and uncertainties result in a considerable degree of 17 uncertainty as to how well the quantified elements of the AAI standard would predict the actual 18 relationship between varying ambient concentrations of oxides of nitrogen and sulfur and steady 19 state ANC levels across the distribution of wat er bodies within the various ecoregions in the U.S. 20 Because of this, there is considerable uncertainty as to the actual degree of protectiveness that 21 such a standard would provide, especiall y for acid

- sensitive ecoregions. The Administrator 22 recognizes th at the AAI equation, with factors quantified in the ranges discussed above and 23

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87 described more full y in the Policy Assessment, generall y performs well in identifying areas of 1 the country

that are sensitive to such acidifying deposition and indicates, as exp ected, that lower 2 ambient levels of oxides of nitrogen and sulfur would lead to higher calculated AAI values. 3 However, the uncertainties discussed here are critical for determining the actual degree of 4 protection that would be afforded such areas b y any s pecific target ANC level and percentile of 5 water bodies that would be chosen in setting a new AAI

- based standard , and thus for determining 6 an appropriate AAI

- based standard that meets the requirements of section 109

. 7 In considering thes e uncertainties, the Administrator notes that CASAC acknowledged 8 that important uncertainties remain that would benefit from further study and data collection 9 efforts, which might lead to potential revisions or modifications to the form of the standard 10 dev eloped in the Policy Assessment. She also notes that CASAC encouraged the Agency to 11 engage in future monitoring and model evaluation efforts to help inform the specification of 12 model

- derived elements in the AAI equation. 13 Based on the above considerations , the Administrator has determined that it is not 14 appropriate under section 109 to set a new multi

- pollutant standard to address deposition

- related 15 effects of oxides of nitrogen and sulfur on aquatic acidification at this time. Setting a NAAQS 16 generall y i nvolves consideration of the degree of uncertainties in the science and other 17 information, such as gaps in the relevant data and, in this case, limitations in the evaluation of the 18 application of relevant ecological and atmospheric models at an ecoregion s cale

. As noted 19 above, the issue here is not a question of uncertainties about the scientific soundness of the 20 structure of the AAI, but instead uncertainties in the quantification and representativeness of the 21 elements of the AAI as they vary in ecoregion s across the country . At present, these 22 uncertainties prevent an understanding of the degree of protectiveness that would be afforded to 23

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88 various ecoregions across the country by a new standard defined in terms of a specific 1 nationwide target ANC level and a specific percentile of water bodies for acid

- sensitive 2 ecoregions , and thus prevent identification of an appropriate standard

. The Administrator has 3 considered whether these uncertainties could be appropriatel y accounted for by choosing either a 4 more or less protective target ANC level and percentile of water bodies than would otherwise be 5 chosen if the uncertainties did not sub stantially limit the confidence that can appropriatel y be 6 ascribed to the quantification of the AAI elements. However, in the Administrator’s judgment, 7 the uncertainties are of such nature and magnitude that there is no reasoned way to choose such a 8 speci fic nationwide target ANC level or percentile of water bodies that would appropriatel y 9 account for the uncertainties, since neither the direction nor the magnitude of change from the 10 target level and percentile that would otherwise be chosen can reasonabl y be ascertained at this 11 time. 12 Based on the above considerations, the Administrator judges that the current limitations 13 in relevant data and the uncertainties associated with specifying the elements of the AAI based 14 on modeled factors are of such nature and degree as to prevent her from reaching a reasoned 15 decision such that she is adequatel y confident as to what level and form (in terms of a selected 16 percentile) of such a standard would provide any particular intended degree of protection of 17 public welfar e that the Administrator determined satisfied the requirements to set an appropriate 18 standard under section 109

. While acknowledging that CASAC supported moving forward to 19 establish the standard developed in the Policy Assessment, the Admini strator also observes that 20 CASAC supported conducting further field studies that would better inform the continued 21 development or modification of such a standard. Given the large uncertainties and complexities 22 inherent in quantifying the elements of such a standard, largely deriving from the unprecedented 23

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89 nature of the standard under consideration in this review, and having fully considered CASAC’s 1 advice, the Administrator provisionally concludes that it is premature to set a new, multi

2 pollutant secondary standard for oxides of nitrogen and sulfur at this time, and as such she is 3 proposing not to set such a new secondary standard. 4 While it is premature to set such a multi

- pollutant standard at this time , the Administrator 5 determines that the Agency shoul d undertake a field pilot program to gather additional data, and 6 that it is appropriate that such a program be undertaken before, rather than after, reaching a 7 decision to set such a standard. As described below in section IV, the purpose of the program i s 8 to collect and anal yz e data so as to enhance our understanding of the degree of protectiveness 9 that would likely

be afforded by

a standard based on the AAI as developed in the Policy 10 Assessment. This will provide additional information to aid the Agency in considering an 11 appropriate multi

- pollutant standard , specificall y with respect to the acidifyingeffects of 12 deposition of oxides of nitrogen and sulfur. Data generated by this field program will also 13 support development of an appropriate monitoring network that would work in concert with such 14 a standard to result in the intended degree of protection. The data and analy ses generated as a 15 result of this program will serve to inform the next review of the NAAQS for oxides of nitrogen 16 and sulfur. The information generated during the field program can also be used to help state 17 agencies and EPA better understand how an AAI

- based standard w ould work in terms of the 18 implementatio n of such a standard. 19 Based on the above considerations, the Administrator is proposing not to set a new multi

20 pollutant AAI
- based secondary standard for oxides of nitrogen and sulfur in this review. In 21 reaching this decision, the Administrator recognizes that the new NO 2 and SO 2 primary 1
- hour 22 standards set in 2010, while not ecologically relevant for a secondary

standard , will nonetheless 23

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90 result in reductions in oxides of nitrogen and sulfur that will directionally benefit the 1 environment by

reducing NOy

and SOx deposition to sensitive ecosy stems. EPA is proposing to 2 revise the secondary standards by

adding secondary stan dards identical to the NO 2 and SO 2 3 primary

1
- hour standards set in 2010. While this will not add secondary standards of an 4 ecologicall y relevant form to address deposition

- related effects , it will directionally provide 5 some degree of additional protection . This is consistent with the view that the current secondary 6 standards are neither sufficiently protective nor appropriate in form, but that it is not appropriate 7 to propose to set a new, ecologically relevant multi

- pollutant secondary standard at this time, for 8 all of the reasons discussed above

. 9 While not a basis for this decision, the Administrator also recognizes that a new, 10 innovative AAI

- based standard would raise significant implementation issues that would need to 11 be addressed consistent with the CAA requirements for implementation

- related actions following 12 the setting of a new NAAQS. It will take time to address these issues, during which the Agency 13 will be conducting a field pilot program to gather relevant data and the environment will benefit 14 from reductions in oxides of nitrogen and sulfur resulting from the new NO 2 and SO 2 primary 15 standards, as noted above , as well as reductions expected to be achieved from EPA’s proposed 16 Transport Rule and Mercury and Air Toxics standards. These implementation

- related issues are 17 discussed in more detail below in section IV.A.5. 18 The Administrator solicits comment on all aspects of this proposed decision, including 19 the framework and elements of a multi

- pollutant standard for oxides of nitrogen and sulfur to 20 address deposition

- related effects on sensitive ecosy stems, with a focus on aquatic acidification, 21 and the uncertainties and complexities associated with the development of such a standard at this 22

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91 time. The Administrator also solicits comment on the field pilot program and related monitoring 1 methods as discussed below in section IV. 2 IV. Field Pilot Program and Ambient Monitoring 3 This section describes EPA’s plans for a field pilot program and the evaluation of 4 monitoring methods for ambient air indicators of oxides of nitrogen (NOy) and oxides of sulfur 5 (SOx) to implement the Administrator’s decision to undertake such a field monitoring program 6 in conjunction with her decision to propose not to set a new multi

- pollutant secondary standard 7 in this review, a s discussed above in section III.H. As noted above and discussed below in 8 section IV.A, the field pilot program is intended to collect and analyze data so as to enhance our 9 understanding of the degree of protectiveness that would likely be afforded by a s tandard based on 10 the AAI as developed in the Policy Assessment. Data generated by this field program would also 11 support development of an appropriate monitoring network that would work in concert with such a 12 standard to result in the intended degree of protection. As discussed below in section IV.B, the 13 evaluation of monitoring methods focuses on the development of Federal Reference 14 Methods/Federal Equivalent Methods (FRM/FEM) for NOy and SOx. EPA notes that the 15 monitoring program described here is inten ded to be coordinated with EPA’s CASTNET as a 16 supplement to existing monitoring programs and is beyond the scope of the current CASTNET 17 program. 18 A. Field Pilot Program 19 This section presents the objectives of a field pilot program (section IV.A.1) that would 20 gather relevant field data over a five

- ye ar period in a sample of 3 to 5 sensitive ecoregions across 21 the country . An overview of the scope and structure of the field program, with a focus on 22 measurements of ambient air indicators of oxides of nitrogen and sulfur , is presented in section 23 IV .A.2. Section IV.A.3 explains the role of additional complementary measurements beyond the 24

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92 ambient air indicators that would be included in the program, and section IV.A.4 discusses a 1 parallel longer

- term res earch agenda, both of which are guided b y the uncertainties discussed 2 above in section III. Section IV.A.5 identifies implementation challenges presented b y an AAI
3 based standard that could be addressed in parallel with a field pilot program. Section IV. A.6 4 discusses engagement with stakeholder groups as part of the planned pilot program. 5 1. Objectives 6 Consideration of a new multi

- pollutant standard to address deposition

- related effects on 7 sensitive aquatic ecoregions raises unique challenges relative to those typically raised in reviews 8 of existing NAAQS for which an established network of FRM/FEM monitor s, designed to 9
measure the indicator pollutant , is generall y available. The primary goal of this field pilot 10 program, and the related monitoring program discussed in section IV.B, is to enhance our 11 understanding of the degree of protectiveness that would likely be afforded by

a standard based 12 on the AAI, as described above in section III, so as to aid the Agency in considering an 13 appropriate multi

- pollutant standard that would be requisite to protect public welfare consistent 14 with section 109 of the CAA , through the following objectives: 15 (1) evaluate measurement methods for the ambient air indicator s of NOy and SOx and 16 consider designation of such methods as FRMs; 17 (2) examine the variability and improve characterization of concentration and 18 deposition patterns of oxides of nitrogen and sulfur, as well as reduced forms of 19 nitrogen, within and across a number of sensitive ecoregions across the country ; 20 (3) develop updated ecoregion

- specific factors (i.e., F1 through F4) for the AAI 21 equation based in part on new observed air quality data within the sample ecoregions 22 as well as on u pdated nationwide air quality model results and expanded critical load 23

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93 data bases , and explore alternative approaches for developing such representative 1 factors; 2 (4) calculate ecoregion

- specific AAI values using observed NOy and SOx data and 3 updated ecore gion

- specific factors to examine the extent to which the sample 4 ecoregions would meet a set of alternative AAI

- based standards; 5 (5) develop air monitoring network design criteria for an AAI

- based standard; 6 (6) assess the use of total nitrate measurements as a potential alternative indicator for 7 oxides of nitrogen; 8 (7) support related longer

- term research efforts, including enhancements to and 9 evaluation of modeled dry deposition algorithms; and 10 (8) facilitate stakeholder engagement in addressing implementation issues associated 11 with possible future adoption of an AAI

- based standard. 12 2. Overview of Field Pilot Program 13 The CASTNET program (Figure IV
- 1) affords an available infrastructure relevant to an 14 AAI
- based standard, given the location of sites in so me acid

- sensitive ecoregions and various 15 measurements of sulfur and nitrogen species. The EPA plans to use CASTNET sites in selected 16 acid

- sensitive ecoregions to serve as the platform for this pilot program, potentially starting in 17 late 2012 and extending through 2018. CASTNET sites in three to five ecoregions in acid

18 sensitive areas would collect NOy and SOx (i.e., SO 2 and p

- SO 4 ) measurements over a five

- ye ar 19 period . The initial step in developing a data base of observed ambient air indicators for oxide s of 20 nitrogen and sulfur requires the addition of NOy samplers at the pilot study sites so that a full 21 complement of indicator measurements are available to calculate AAIvalues . These CASTNET 22

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94 sites would also be used to make supplemental observations use ful for evaluation of CMAQ’s 1 characterization of factors F2

–F4 in the AAI equation. 2 The selected ecoregions would account for geographic variability b y including regions 3 from across the U.S., including the east, upper midwest and west. Each selected regi on would 4 have at least two existing CASTNET sites. Each of the pilot CASTNET sites would be used to 5 evaluate the performance of the established methods, data retrieval and reporting procedures 6 used in the AAI equation. 7 8

9 Figure IV - 1. Location of CASTNET sites in relation to acid sensitive ecoregions. 10
11

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95 Over the course of this five

- year pilot program, the most current national air quality 1 modeling , based on the most current national emissions inventory , would be used to develop an 2 updated set of F 2

– F4 factors. A parallel multi

- agency national critical load data base 3 development effort would be used as the basis for calculating updated F1 factors. As discussed 4 above in section III.B, these factors would be based on average parameter values across an 5 ecoregion. Using this new set of F factors, observations of NOy and SOx derived from the pilot 6 program , averaged across each ecoregion, would be used to calculate AAI values in the sample 7 ecoregions

. The data from the pilot program would also be used to examine alternative 8 approaches to generating representative air quality values, such as examining the appropriateness 9 of spatial averaging in areas of high spatial variability

. 10 3 . Complementary Measurements 11 Complementary measurements may

be performed at some sites in the pilot network to 12 reduce uncertainties in the recommended methods and better characterize model performance 13 and application to the AAI. The CASAC Air Monitoring and Methods Subcommittee (AMMS) 14 advised EPA that such supplemental measurements were of critical importance in a field 15 measurement program related to an AAI
- based standard (Russell and Samet, 2011 b ). 16 Candidate complementary measurements to address sulfur, in addition to those provided 17 by the CASTNET filter pack (CFP), include trace gas continuous SO 2 and speciated PM 2.5 18 measurements. The co

- located deploy ment of a continuous SO 2 analy zer with the CFP for SO 2 19 will provide test data for determining suitability of continuous SO 2 measurements as an FEM, as 20 well as producing valuable time series data for model evaluation purposes. The weekl y 21 averaging time provided by the CFP adequatel y address es the annual

- average basis of an AAI
22 based secondary standard, but would not be app licable to short

- term (i.e., 1

- hour) average s 23

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96 associated with the primary SO 2 standard. Conversely , because of the low concentrations 1 associated with many acid

- sensitive ecoregions, existing SO 2 FRMs designated for use in 2 determining compliance with the p rimary standard would not necessarily be appropriate for use 3 in conjunction with an AAI

- based secondary standard

. 4 Co
- locating the PM 2.5 sampler used in the EPA Chemical Speciation Network and the 5 IMPROVE network at pilot network sites would allow for ch aracterizing the relationship 6 between the CFP

- derived p - SO 4 and the speciation samplers used throughout the state and local 7 air quality

networks. Note that CASTNET already has several co

- located IMPROVE chemical 8 speciation samplers. Because the AAI equation is based on concentration of p - SO 4 , the original 9 motivation for capturing all particle size fractions is not as important relative to simply capturing 10 the concentration of total p - SO 4 . 11 Candidate measurements to complement oxidized nitrogen measurements, in addition to 12 the CFP, include a mix of continuous and periodic sampling for the dominant NOy species, 13 namely

NO, true NO 2 , PAN, HNO 3 , and p -NO 3 . While there are several approaches to acquiring 14 these measurements, perhaps the most efficient strategy would take advantage of the available 15 CFP for total nitrate, and add a three

- channel chemiluminescence instrument that will cycle 16 between NOy , true NO 2 and NO b y adding photolytic detection for true NO 2 . Other options for 17 measuring true NO 2 would include adding either a stand

- alone photol ytic or cavity ring

- down 18 spectroscop y instrument. Measurements of PAN may be acquired either on a periodic basis 19 through canister sampling and subsequent laboratory anal ys is or through emerging in

- situ 20 sampling and anal ys is methods. Although the CFP yields a reliable measurement of total nitrate, 21 the t -NO 3 (i.e., the sum of HNO 3 and p

-NH 4 ) value, strong consideration may be given to direct 22 measurement of HNO 3 , which has the highest deposition velocity of all the dominant NOy 23

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97 species. Similar to the use of continuous SO 2 data, these speciated NOy data serve two purposes : 1 evaluating total NOy instrument behavior and ev aluating air quality model s . The measurement 2 of individual NOy

species can be used to generate site

- specific NOy values for comparison to 3 modeled NOy , and will likely provide insight into and improvement of modeled dry deposition. 4 The CASA C AMMS (Russell and Samet, 2011 b ) recommended that EPA consider the 5 use of t -NO 3 obtained from CASTNET sampling as an indicator for NOy , reasoning that t -NO 3 is 6 ty picall y a significant fraction of deposited oxidized nitrogen in rural environments and 7 CASTNET measurements are widel y available. Collection of this data would support further 8 consideration of using the CFP for t -NO 3 as the indicator of oxides of nitrogen for use in an AAI

9 based secondary

standard. 10 The CASAC AMMS also recommended that total NHx (NH 3 and p

-NH 4 ) be considered 11 as a prox y for reduced nitrogen species, reasoning that the subsequent partitioning to NH 3 and p

12 NH 4 may

be estimated using equilibrium chemistry calculations. Reduced nitrogen 13 measurements are used to evaluate air quali ty modeling which is used in generating factor F2. 14 Additional studies are needed to determine the applicability of NHx measurements and 15 calculated values of NH 3 and NH 4 to the AAI. 16 The additional supplemental measurements of speciated NOy , continuous SO 2 and NHx 17 will be used in future air quality modeling evaluation efforts. Because there often is significant 18 lag in the availability of contemporary

emissions data to drive air quality modeling, the complete 19 use of these data sets will extend beyond the fi ve - year collection period of the pilot program. 20 Consequently , the immediate application of those data will address instrument performance 21 comparisons that explore the feasibility of using continuous SO 2 instruments in rural 22 environments, and using the spe ciated NOy data to assess NOy

instrument performance. 23

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98 Although contemporary

air quality

modeling will lag behind measurement data availability , the 1 observations can be used in deposition models to compare observed transference ratios with the 2 previously calculated transference ratios to test temporal stability of the ratios. 3 An extended water quality sampling effort should parallel the air quality measurement 4 program to address some of the uncertainties related to factor F1 and the representativeness o f 5 the nth percentile critical load as discussed in section III. B.5.b.i. The objective of the water 6 quality

sampling would be to develop a larger data base of critical loads in each of the pilot 7 ecoregions such that the nth percentile can adequately be characterized in terms of representing 8 all water bodies. Opportunities to leverage and perhaps enhance existing ecosystem modeling 9 efforts enabling more advanced critical load modeling and improved methods to estimate base 10 cation production would be pursued. For example, areas with ongoing research studies 11 producing data for dynamic critical load modeling would be considered when selecting the pilot 12 ecoregions. 13 4. Complementary areas of research 14 The EPA recognizes that a source of uncertainty in an AAI
- based secondary standard that 15 would not be directl y addressed in the pilot program stems from the uncertainty in the model 16 used to link atmospheric concentrations to dry deposition fluxes. Currently, there are no ongoing 17 direct dry

deposition measurem ent studies at CASTNET sites that can be used to evaluate 18 modeled results. It was strongl y recommended b y CASAC AMMS that a comprehensive 19 sampling

- intensive study be conducted in at least one, preferabl y two sites in different 20 ecoregions to assess charact erization of dry deposition of sulfur and nitrogen. These sites would 21 be the same as those for the complementary measurements described above, but they would 22 afford an opportunity to also complement dry

deposition process research that benefits from the 23

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99 ambient air measurements collected in the pilot program. The concerns regarding uncertainties 1 underlying an AAI

- based secondary standard suggest that research that includes dry deposition 2 measurements and evaluation of dry deposition models should be a high priority

. 3 Similar leveraging should be pursued with respect to ecosy stem research activities. For 4 example, studies that capture a suite of soil, vegetation, hydrological, and water quality 5 properties that can help evaluate more advanced critical load mo dels would complement the 6 atmospheric

- based pilot program. In concept, such studies could provide the infrastructure for 7 true multi

- pollutant , multi

- media “super” sites assuming the planning, coordination , and resource 8 facets can be aligned. While this discussion emphasizes the opportunity of leveraging ongoing 9 research efforts, consideration could be given to explicitly including related research components 10 directly

in the pilot program. 11 5. Implementation challenges 12 The CAA requires that once a NAAQS is established, designation and implementation 13 must move forward. With a standard as innovative as the AAI

- based standard considered in this 14 review, the Administrator believes that its success will be greatl y improved if, while additional 15 data are being col lected to reduce the uncertainties discussed above, the implementing agencies 16 and other stakeholders have an opportunity to discuss and thoroughl y understand how such a 17 standard would work. And since, as noted above, emissions reductions that are directi onally 18 correct to reduce aquatic acidification will be occurring as a result of other CAA programs, the 19 Administrator believes that this period of further discussion will not delay progress but w i ll 20 ensure that once implementation is triggered, agencies wi ll be prepared to implement it 21 successfull y. 22 Consideration of an AAI

- based secondary standard for oxides of nitrogen and sulfur 23

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100 would present significant implementation challenges because it involves multiple, regionall y1 dispersed pollutants and relativel y complex compliance determinations . The anticipated 2 implementation challenges fall into three main categories: monitoring and compliance 3 determinations for area designations, pre

- constru ction permit application analy ses of individual 4 source impacts, and State Implementation Plan (SIP) development. Several overarching 5 implementation questions that we anticipate will be addressed in parallel with the field pilot 6 program’s five

- ye ar data co llection period include: 7 (1) What are the appropriate monitoring network density and siting requirements to 8 support a compliance s ys tem based on ecoregions? 9 (2) Given the unique spatial nature of the secondary standard (e.g., ecoregions), what are 10 the appropriate parameters for est ablishing nonattainment areas? 11 (3) How can new or modified major sources of oxides of nitrogen and oxides of sulfur 12 emissions assess their ambient impacts on the standard and demonstrate that they are not 13 causing or contrib uting to a violation of the NAAQS f or preconstruction permitting? To 14 what extent d oes the fact that a single source may be impacting multiple areas complicate 15 this assessment and how can these additional complexities best be addressed? 16 (4) What additional tools, information, and planning structures are needed to assist states 17 with SIP development, including the assessment of interstate pollutant transport and 18 deposition? 19 (5 ) Would transportation conformity appl y in nonattainment and maintenance areas for 20 this secondary standard, and, if it does, would satisfying requirements that apply for 21 related primary standards ( e.g., ozone, PM 2.5 , and NO 2 ) be demonstrated to satisfy 22 requirements for this secondary standard? 23

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101 6. Final monitoring plan development and stakeholder participation 1 The existing CASTNET sampling site infrastructure provides an effective means of 2 quickly

and efficiently

deploying a monitoring program to support potential implementation of 3 an AAI
- based secondary standard, and also provides an additional opportunity for federall y 4 managed networks to collaborate and support the states, local agencies and Tribes (SLT) in 5 determining compliance with a secondary standard. A collaborative effort would help to 6 optimize limited federal and SL T monitoring funds and would be beneficial to all involved. 7 CASTNET is already a stakeholder

- based program with over 20 participants and contributors, 8 including federal, state and tribal partners. 9 The CASAC AMMS generall y endorsed the technical approaches used in CASTNET, but 10 concerns were raised b y i ndividual representatives of State agencies concerning the perception of 11 EPA
- controlled management aspects of CASTNET and data ownership. Potential approaches to 12 resolve these issues will be developed and evaluated in existing NACAA/EPA ambient air 13 monitoring workgroups. The EPA Office of Air and Radiation (which includes the Office of Air 14 Quality

Planning Standards, OAQPS; and the Office of Atmospheric Program’s Clean Air 15 Markets Division, OAP

- CAMD), and their partners on the NACAA monitor steering committee 16 will develop a prioritized specific plan that identifies the 3

- 5 ecoregions and the instrumentation 17 to be deployed. EPA anticipates that a cost estimate of the plan with priorities and options will 18 be developed b y J anuary , 2012. Although this pilot program is focused on data collection, the 19 plan will include details of the data anal ys is approaches as well as a vehicle that incorporates 20 engagement from those within EPA and SLTs to foster progress on the implementation questions 21 noted above in section IV.A. 5. 22

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102 If an AAI

- based secondary standard were to be set in the future, deploy ment of a full 1 national network would follow th e pilot monitoring program. The number of sites deployed in 2 the network will lead to increased confidence in capturing spatial patterns of air quality. 3 Recognizing that this section presents the general elements of the field pilot programs, EPA 4 intends t o develop a more detailed field pilot program plan through a process that will engage the 5 air quality

management and research (atmospheric and ecos ys tem) communities , as well as other 6 federal agencies, state and local agencies , and non - government based centers of expertise. The 7 EPA is seeking comment and input on all aspects of this field pilot program. 8

. B. Evalu ation of Monitoring Methods 9 The EPA generally relies on monitoring methods that have been designated as FRMs or 10 FEMs for the purpose of determining the attainment status of areas with regard to existing 11 NAAQS. Such FRMs or FEMs are generall y required to measure the air quality indicators that 12 are compared to the level of a standard to assess compliance with a NAAQS. Prior t o their 13 designation b y EPA as FRM/FEMs through a rulemaking process, these methods must be 14 determined to be applicable for routine field use and need to have been experimentally validated 15 by meeting or exceeding specific accuracy , reproducibility, and reli ability criteria established b y 16 EPA for this purpose. As discussed above in section III .A, the ambient air indicators being 17 considered for use in an AAI

- based standard include SO 2 , particulate sulfate (p

- SO 4 ), and total 18 reactive oxides of nitrogen (NOy). 19 The CASTNET provides a well established infrastructure that would meet the basic 20 location and measurement requirements of an AAI

- based secondary standard given the rural 21 placement of sites in acid sensitive areas. In addition, CFPs currentl y provide very economical 22

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103 weekl y, integrated average concentration measurements of SO 2 , p - SO 4 , ammonium ion (NH 4 ) 1 and t -NO 3 , the sum of HNO 3 and p -NO 3 . 2 While routinely operated instruments that measure SO 2 , p - SO 4 , NOy and/or t -NO 3 exist, 3 instruments that measure p - SO 4 , NOy , t -NO 3 , or the CFP for SO 2 have not been designated b y 4 EPA as FRMs or FEMs The EPA’s ORD has initiated work that will support future FRM 5 designations b y EPA for SO 2 and p

- SO 4 measurements based on the CFP . Such a designation by 6 EPA could be done f or the purpose of facilitating consistent research related to an AAI

- based 7 standard and/or in conjunction with setting and supporting an AAI
- based secondary standard. 8 Based on extensive review of literature and available data, the EPA has identified 9 potential methods that appear suitable for measuring each of the three components of the 10 indicators. These three methods are being considered as new FRMs to be used for measuring the 11 ambient concentrations of the three components that would be needed to deter mine compliance 12 with an AAI

- based secondary standard. 13 For the SO 2 and p

- SO 4 measurements, EPA is considering the CFP method, which 14 provides weekl y average concentration measurements for SO 2 and p

- SO 4 . This method has been 15 used in the EPA’s CASTNET monitoring network for 15 years, and strongly indicates that it will 16 meet the requirements for use as an FRM for the SO 2 and p

- SO 4 concentrations for an AAI

- based 17 secondary standard. 18 Although the CFP method would provide measurements of both the SO 2 and p

- SO 4 19 components in a unified sampling and anal ys is procedure, individual FRMs will be considered 20 for each. The EPA recognizes that an existing FRM to measure SO 2 concentrations using ultra

21 violet fluorescence (UVF) exists (40 CFR Part 50, Appendix A

- 1) for the purpose of monitoring 22 compliance for the primary SO 2 NAAQS. However, several factors suggest that the CFP method 23

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104 would be superior to that UVF FRM for monitoring compliance with an AAI

- based secondary 1 standard and will be discussed in more detail below. 2 For monitoring the NOy component, a continuous anal yz er for measuring NOy is 3 commerciall y available and is considered to be suitable for use as an FRM. This method is 4 similar in design to the existing NO 2 FRM (described in 40 CFR Part 50, Appendix F), which is 5 based on the ozone chemiluminescence measurement technique. The method is adapted to and 6 further optimized to measure all oxides of nitrogen (NOy). However, this NOy method requires 7 further evaluation before it can be full y confirmed as a suita ble FRM. The EPA is currentl y 8 completing a full scientific assessment of the NOy method to determine whether it would be 9 appropriate to consider for designation by EPA as an FRM. Specific details on these three 10 methods are given below. 11 On February 16, 2011, EPA presented this set of potential FRMs to the CASAC AMMS 12 for their consideration and comment. In response, the CASAC AMMS stated that, overall, it 13 believes that EPA’s planned evaluation of methods for measuring NOy , SO 2 and p

- SO 4 as 14
ambient air indicators are suitable approaches in concept. On supporting the CFP method as a 15 potential FRM for SO 2 , CASAC stated that they felt that the CFP is adequate for measuring 16 long

- term average SO 2 gas concentrations in rural areas with low levels (less than 5 ppbv) and is 17 therefore suitable for consideration as an FRM. For p

- SO 4 , CASAC generally supports the use 18 of the CFP as a potential FRM for measuring p

- SO 4 for an AAI

- based secondary standard. The 19 method has been relatively well

- characterized and evaluated, and it has a documented, long

- term 20 track record of successful use in a field network designed to assess spatial patterns and long

- term 21 trends. 22

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105 On supporting the photometric NOy method as a potential FRM, CASAC concluded that 1 the existing NO y method is generall y an appropriate approach for the indicator. However, 2 CASAC agrees that additional characterization and research is needed to fully understand the 3 method in order to designate it as a FRM. The EPA is now soliciting public comment on these 4 methods as to their adequacy , suitability , and relative merits as FRMs for purposes of monitoring 5 to determine compliance with an AAI

- based secondary standard. 6 1. Potential FRMs for SO2 and p

- SO 4 7 The CFP is a combined, integrated sampling and analy sis method based on the well

8 established measurement technology that has been used extensively in EPA’s CASTNET 9 monitoring network (see http://www.epa.gov/castnet). This method is in current use at over 80 10 monitoring sites and has been in use at not less than 40 sites for over 15 ye ars. This method 11 employ s a relativel y simple and inexpensive sampler and uses four 47

- mm filters placed in an 12 open - faced filter pack to simul taneously collect integrated filter samples for the SO 2 and p

- SO 4 13 components. In addition, the CFP is also capable of the collection of t

-NO 3 , the sum of HNO 3 14 and p -NO 3 . 15 The first stage of the filter pack assembly contains a Teflon® filter that collects p - SO 4 2
- 16 and p -NO 3 , the second stage contains a nyl on filter that collects SO 2 (as SO 4 2
- ) and HNO 3 , and 17 the third stage contains two cellulose fiber filters impregnated with potassium carbonate (K 2 CO 3 ) 18 that collect any remaining SO 2 (as SO 4 2
- ). The sampler collects one

- week integrated samples at a 19 very

low, controlled flow rate (1.5 or 3 L/min) in an attempt simulate actual deposition. Weekly 20 averaged SO 2 and p

- SO 4 concentrations could then be averaged over a 1

- year period to calculate 21 annual average value s. 22

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106 Upon sample completion, the species

- specific filters are extracted, with subsequent 1 anal ys is by

the well

- established and documented ion chromatographic (IC) anal ytical technique. 2 During the IC anal ys is, an aliquot of a filter extract is injected into a stream of eluent (ion 3 chromatograph y mobile phase, generall y a millimolar

- strength solution of carbonate

4 bicarbonate) and passed through a series of ion exchangers. The anions of interest are separated 5 on the basis of their relative affinities for a low capacity and the strongl y basic anion exchanger 6 (guard and separator column). The separated anions are directed onto a cation exchanger 7 (suppressor column) where they are converted to their highl y conductive acid form, and the 8 eluent is converted to a weakl y conductive form. The now

- separated anions, each in their acid 9 form, are measured b y conductivity . They are identified on the basis of retention time compared 10 to that of standards and quantified by measurement of peak area compared to the peak areas o f 11 calibration standards. 12 Calibration and quality assurance for the method are applied to the sample filters, the 13 anal ytical processes, and the flow rate measurement and control aspects of the sampler. Overall 14 method performance is ty pically assessed w ith collocated samplers. These quality assurance 15 techniques are routinel y used and have proved adequate for other types of FRMs and equivalent 16 methods in air monitoring network service. 17 The measurement and analy tical procedures and past performance data a ssociated with 18 the C FP method are well documented and available through Quality Assurance Performance 19 Plans (QAPPs), Standard Operating Procedures ( SOPs ) and annual reports (US EPA, 2010a and 20 2010b). The accumulated database on the CFP method is substanti al and indicates that the 21 method is sound, stable and has good reliability in routine, field operation. Data quality 22 assessment results show the method to have good reproducibility , with collocated and anal ytical 23

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107 precision values in the range of 2%

– 10% (excluding very low concentration measurements near 1 the method detection limits; US EPA 2010b). 2 Data quality objectives (DQOs) for a new FRM would be based upon current DQOs 3 being used for this method by EPA’s OAP/CAMD and the National Park Service (NPS), the 4 federal managers of CASTNET (US EPA, 2010a). In its current state, the CFP method is 5 expected to meet or exceed (as past CASTNET data have indicated; US EPA, 2010b) the 6 expected FRM DQOs, even when deplo ye d in new monitoring networks outside of CASTNET. 7 In addition, CASTNET samples have agreed favorably with other measures of SO 2 and p

- SO 4 in 8 comparison studies. For example, in direct comparison with an annular denuder sampler (ADS) 9 method, CASTNET/ADS ratios for SO 2 and p

- SO 4 were generall y on the order of 0.9

- 1.1 10 (Lavery

et al, 2009; Sickles et al, 1999; Sickles et al, 2008) , thus illustrating the accuracy of the 11 CFP method in the determination of long

- term average SO 2 and p

- SO 4 concentrations. The EPA 12 believes that the CFP method would be fully adequate as an FRM in determining yearl y average 13 SO 2 and p

- SO 4 concentrations for compliance determination purposes. 14 The EPA recognizes that an existing FRM for SO 2 has proven adequate for the purposes 15 of monitoring compliance for the primary SO 2 NAAQS , specifically the newly

- promulgated 1
- 16 hour standard. However, this FRM is better suited to the shorter

- term, higher concentration 17 primary

and secondary

SO 2 NAAQS, and there is substantial uncertainty as to the adequacy of 18 this SO 2 FRM for monitoring the lower concentrations relevant to determining compliance with 19 an AAI
- based secondary standard. The performance specifications for SO 2 FRM anal yz ers (40 20 CFR Part 53, Table B

- 1) require a lower detectable limit (LDL) of 0.002 ppm for the standard 21 measurement range and 0.001 ppm for the lower measurement range. These requirements 22 correspond to mass per unit volume concentrations of 5.24 and 2.62 μg/m 3 , respectivel y. 23

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108 Analy sis of 2009 CASTNET data shows that of the 84 CASTNET sampling sites, 63 measured 1
annual average SO 2 concentrations below even the lower of these LDL requirements of 2.62 2 μg/m 3 for the lower range SO 2 FRM (US EPA, 2010a). In addition, 11 of the 84 sites measured 3 annual (2009) average SO 2 concentrations very near or below the manufacturers’ reported 4 detection limits for trace level UVF SO 2 monitors. Further, it is likely that the number of sites 5 with annual average SO 2 concentration below both the SO 2 FRM LDL and the manufacturers 6 reported detection limits will increase due to expected declines in mean SO 2 concentrations (US 7 EPA, 2010b). For these reasons, EPA is considering the CFP method for use as the FRM for 8 monitoring the SO 2 component of an ambient air indicator for oxides of sulfur, with a 9 recommendation for additional study and data collection to further evaluate the possible 10 applicability

of the continuous UVF SO 2 FRM for this purpose. 11 2. Potential FRM for NOy 12 Atmospheri c concentrations of NOy are measured continuously by an analyzer that 13 photometrically

measures the light intensity , at wavelengths greater than 600 nanometers (nm), 14 resulting from the chemiluminescent reaction of ozone (O 3 ) with NO in sampled air. This 15
me thod is very

similar to the chemiluminescence NO/NO 2 anal yz ers widely used to collect NO 2 16 monitoring data for determining compliance with the NO 2 NAAQS. The various oxides of 17 nitrogen species, excluding NO, are first quantitatively reduced to NO by

means of a catal ytic 18 converter. These species include NO 2 , HNO 2 , PANs, HNO 3 and p -NO 3 . The NO, which 19 commonly

exists in ambient air, passes through the converter unchanged, and, when combined 20 with the NO resulting from the catal ytic conversion of the other oxi des of nitrogen, a 21 measurement of the total NOy concentration results. To maximize the conversion of the more 22 chemicall y active oxides of nitrogen species, the converter is located externally , at or near the air 23

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109 sample inlet probe. This location minimize s losses of these active species that could otherwise 1 occur from chemical reactions and wall losses in the sample inlet line. 2 The NOy

anal yz er is a suitable, commerciall y produced continuous chemiluminescence 3 anal yz er that includes an ozone generator, a re action cell, a photometric detector, wavelength 4 filters as necessary

to reduce sensitivity

to wavelengths below 600 nm, a pump and flow control 5 sy stem to draw atmospheric air through the converter and into the reaction cell, a suitable 6 converter, a s ys tem to control the operation of the anal yz er, and appropriate electronics to 7 process and quantitatively scale the photometric signals. The converter contains a catal ys t such 8 as moly

bdenum and is heated to an optimum temperature designed to optimize the conver sion of 9 the various oxides of nitrogen to NO. It is connected to the anal yz er via suitable lengths of 10 Teflon® tubing. Hourly NOy measurements obtained by the anal yz er would be averaged over 11 the same 7

- day

period used by

the CFP method to measure the SO 2 and p

- SO 4 components, with 12 further averaging over a 1

- ye ar period

. 13 Commercial NOy analyzers are currentl y available, and the anal yz ers have been used for 14 a variety of monitoring applications. During the 2006 TexAQS Radical and Aerosol 15 Measurement Project (TRAMP), Luke et. al. , 2010, compared measured NOy concentrations 16 obtained with an NOy instrument based upon the above mentioned methodology with the sum of 17 measured individual NOy species (i.e., NOyi = NO+NO 2 +HNO 3 +PANs+HNO 2 +p -NO 3 ). This 18 comparison yi elde d excellent overall agreement during both day ([NOy](ppb) = [NOyi ](ppb) × 19 1.03

– 0.42; r2 = 0.9933) and night time ([NOy](ppb) = [NOyi ](ppb) × 1.01

– 0.18; r2 = 0.9975) 20 periods ( Luke et al , 2010 ). The results of this study show that this NOy method is capable of the 21 accurate determination of all the atmosphericall y relevant NOy components, resulting in an 22 accurate determination of total NOy concentrations. NOy

instruments have been routinel y 23

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110 op erated in networks such as SEARCH, dating back several years. In addition, state monitoring 1 agencies across the U.S. have begun, starting in 2009, the routine operation of commercially 2 available NOy

instrumentation in anticipation of EPA’s NCore network transitioning to full 3 operation in 2011. 4 These initial assessments described above are promising and indicate that the photometric 5 NOy method appears to be accurate, reliable, and capable of routine network operation. As a 6 result, the method is most like ly capable for use as an FRM for determining atmospheric NOy 7 concentrations as a component in determining compliance with an AAI

- based secondary 8 standard. However, as described below, this continuous method for NOy requires additional 9 time for further evaluation before it can be full y confirmed for adoption as a FRM. The EPA has 10 identified measurement uncertainties and some remaining science questions associated with this 11 method. Among these are (a) the ability of the method to capture all components of NOy 12 relevant to nitrogen deposition, (b) the efficiency of the moly

bdenum converter in converting all 13 oxides of nitrogen to NO for detection (excluding NO 2 , as this conversion is already well 14 documented), (c) appropriate inlet height specifications to minimize any bias associated with 15 vertical concentration gradients of key NOy components, (d) identification and quantification of 16 potential measurement interferences in the NOy determination, and (e) development and 17 demonstration of effective calibration/chal lenge procedures to best represent the various 18 mixtures of NOy

components that are expected to be present in the different air sheds across the 19 U.S. 20 To address these NOy method uncertainties and to fully assess this method for use as the 21 NOy

FRM, EPA has d eveloped a detailed research plan ( Russell and Samet, 2011b) which was 22 presented to the CASAC AMMS on February 16, 2011. In response, CASAC recognized the 23

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111 need for, and supported the general outline of EPA’s research plan to evaluate the NOy method 1 for po tential designation as an FRM (US EPA, 2011). In addition, the CASAC AMMS 2 suggested additional areas of research associated with the photometric NOy method that warrant 3 further assessment prior to final designation of the method as the NOy FRM. These inc lude 4 operation of the method during extremel y low temperature conditions to investigate possible 5 condensation in sample lines, method detection limits relative to low levels expected in remote 6 areas, and ambient

- based method evaluations in various air shed s across the U.S. In response to 7 these CASAC AMMS suggestions, EPA is carrying out studies, in addition to the tasks outlined 8 in the research plan, for the NOy method. The results of these studies will likely take a year or 9 more to become available. As noted previousl y, EPA anticipates that these results will be 10 favorable and will confirm the adequacy of the NOy

method as a suitable FRM for determining 11 compliance with an AAI

- based secondary standard. 12 V. Statutory and Executive Order Reviews 13 A. Executive Order 12866: Regulatory Planning and Review and Review and Executive 14 Order 13563: Improving Regulation and Regulatory Review 15 Under Executive Order 12866 (58 FR 51735, October 4, 1993), this action is a 16

“ significant regulatory action

. ” Accordingl y, EPA submitted this action to the Office of 17 Management and Budget (OMB) for review under Executive Orders 12866 and 13563 (76 FR 18 3821, January

21, 2011), and any changes made in response to OMB recommendations have 19 been documented in the do cket for this action. 20 B. Paperwork Reduction Act 21 This action does not impose an information collection burden under the provisions of the 22 Paperwork Reduction Act, 44 U.S.C. 3501 et seq. Burden is defined at 5 CFR 1320.3(b). There 23

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112 are no information colle ction requirements directly associated with the establishment of a 1 NAAQS under section 109 of the CAA. 2 C. Regulatory Flexibility Act 3 For purposes of assessing the impacts of today ’s rule on small entities, small entity is 4 defined as: (1) a small business that is a small industrial entity as defined by

the Small Business 5 Administration’s (SBA) regulations at 13 CFR 121.201; (2) a small governmental jurisdiction 6 that is a government of a city , county, town, school district or special district with a population of 7 less than 50,000; and (3) a small organization that is any not - for

- profit enterprise which is 8 independentl y owned and operated and is not dominant in its field. 9 After considering the economic impacts of today's proposed rule on small entities, I 10
c ertify

that this action will not have a significant economic impact on a substantial number of 11 small entities. This proposed rule will not impose any requirements on small entities. Rather, 12 this rule establishes national standards for allowable concentrations of oxides of nitrogen and 13 sulfur in ambient air as required b y section 109 of the CAA. See also American Trucking 14 Associations v. EPA. 175 F. 3d at 1044

- 45 (NAAQS do not have significant impacts upon small 15 entities because NAAQS themselves impose no regulations upon small entities). We continue to 16 be interested in the potential impacts of the proposed rule on small entities and welcome 17 comments on issues related to such impacts 18 D. Unfunded Mandates Reform Act 19 Title II of the Unfunded Mandates Refo rm Act of 1995 (UMRA), Public Law 104

- 4, 20 establishes requirements for Federal agencies to assess the effects of their regulatory actions on 21 State, local, and Tribal governments and the private sector. Under section 202 of the UMRA, 22 EPA generall y must prepare a written statement, including a cost

- benefit analy sis, for proposed 23

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113 and final rules with “Federal mandates” that may result in expenditures to State, local, and Tribal 1 governments, in the aggregate, or to the private sector, of $100 million or more in any 1 year. 2 Before promulgating an EPA rule for which a written statement is needed, section 205 of the 3 UMRA generally

requires EPA to identify and consider a reasonable number of regulatory 4 alternatives and to adopt the least costly , most cost - effective or least burdensome alternative that 5 achieves the objectives of the rule. The provisions of section 205 do not apply when they

are 6 inconsistent with applicable law. Moreover, section 205 allows EPA to adopt an alternative 7 other than the least costly, most cost - effective or least burdensome alternative if the 8 Administrator publishes with the final rule an explanation why that alternative was not adopted. 9 Before EPA establishes any regulatory

requirements that may

significantl y or uniquely affect 10 small gover

nments, including Tribal governments, it must have developed under section 203 of 11 the UMRA a small government agency plan. The plan must provide for notifying potentiall y 12 affected small governments, enabling officials of affected small governments to have meaningful 13 and timely

input in the development of EPA regulatory proposals with significant Federal 14 intergovernmental mandates, and informing, educating, and advising small governments on 15 compliance with the regulatory requirements. 16 This action contains no Federal mandates under the provisions of Title II of the 17 Unfundated Mandates Reform Act of 1995 (UMRA), 2 U.S.C. 1531

- 1538 for State, local, or 18 tribal governments or the private sector. Therefore, this action is not subject to the requirements 19 of secti ons 202 or 205. Furthermore, as indicated previously , in setting a NAAQS EPA cannot 20 consider the economic or technological feasibility of attaining ambient air quality standards; 21 although such factors may be considered to a degree in the development of St ate plans to 22 implement the standards. See also American Trucking Associations v. EPA, 175 F. 3d at 1043 23

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114 (noting that because EPA is precluded from considering costs of implementation in establishing 1 NAAQS, preparation of a Regulatory Impact Analy sis pursu ant to the Unfunded Mandates 2 Reform Act would not furnish any information which the court could consider in reviewing the 3 NAAQS). Accordingl y, EPA has determined that the provisions of sections 202, 203, and 205 of 4 the UMRA do not apply to this proposed d ecision. The EPA acknowledges, however, that any 5 corresponding revisions to associated SIP requirements and air quality surveillance requirements, 6 40 CFR part 51 and 40 CFR part 58, respectivel y, might result in such effects. Accordingl y, 7 EPA will addres s, as appropriate, unfunded mandates if and when it proposes any revisions to 40 8 CFR parts 51 or 58. 9 E. Executive Order 13132: Federalism 10 This proposed rule does not have federalism implications. It will not have substantial 11 direct effects on the States, on the relationship between the national government and the States, 12 or on the distribution of power and responsibilities among the various levels of government, as 13 specified in Executive Order 13132 because it does not contain legally binding requirements

. 14 Thus, the requirements of Executive Order 13132 do not apply to this rule. 15 EPA believes, however, that this proposed rule may be of significant interest to State 16 governments. A s also noted in section E (above) on UMRA, EPA recognizes that States will 17 h ave a substantial interest in this rule and any corresponding revisions to associated SIP 18 requirements and air quality surveillance requirements, 40 CFR part 51 and 40 CFR part 58, 19 respectivel y. Therefore, in the spirit of Executive Order 13132 and consis tent with EPA policy 20 to promote communications between EPA and State and local governments, EPA specificall y 21 solicits comment on this proposed rule from State and local officials. 22 F. Executive Order 13175: Consultation and Coordination with Indian Tribal Governments 23

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115 Executive Order 13175, entitled “Consultation and Coordination with Indian Tribal 1 Governments” (65 FR 67249, November 9, 2000), requires EPA to develop an accountable 2 process to ensure “meaningful and timely input by tribal officials in the dev elopment of 3 regulatory

policies that have tribal implications.” This rule concerns the establishment of 4 national standards to address the public welfare effects of o xides of n itrogen and s ulfur

. 5 This action does not have Tribal implications, as specified in Executive Order 13175 (65 6 FR 67249, November 9, 2000). It does not have a substantial direct effect on one or more Indian 7 tribes, since tribes are not obligated to adopt or implement any NAAQS . Thus, Executive Order 8 13175 does not apply to this rule. 9 G. Executive Order 13045: Protection of Children from Environmental Health &Safety 10 Risks 11 This action is not subject to EO 13045 because it is not an economicall y significant rule 12 as defined in EO 12866. 13 H. Executive Order 13211: Actions that Significantly Affect Energy Supply, Distribution or 14 Use 15 This action is not a “significant energy action” as defined in Executive Order 13211 (66 16 FR 28355, May

22, 2001), because it is not likely to have a s ignificant adverse effect on the 17 supply , distribution, or use of energy

. This action concerns the establishment of national 18 standards to address the public welfare effects of oxides of nitrogen and sulfur. This action does 19 not prescribe specific polluti on control strategies by which these ambient standards will be met. 20 Such strategies will be developed b y States on a case
- by

- case basis, and EPA cannot predict 21 whether the control options selected b y States will include regulations on energy suppliers, 22 di stributors, or users. 23

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116 I. National Technology Transfer and Advancement Act 1 Section 12(d) of the National Technology Transfer and Advancement Act of 1995 2 (NTTAA), Public Law No. 104

- 113, 12(d) (15 U.S.C. 272 note) directs EPA to use voluntary 3 consensus stan dards in its regulatory activities unless to do so would be inconsistent with 4 applicable law or otherwise impractical. Voluntary consensus standards are technical standards 5 (e.g., materials specifications, test methods, sampling procedures, and business p ractices) that are 6 developed or adopted b y voluntary consensus standards bodies. The NTTAA directs EPA to 7 provide Congress, through OMB, explanations when the Agency decides not to use available and 8 applicable voluntary consensus standards. 9 The EPA is no t aware of any voluntary

consensus standards that are relevant to the 10 provisions of this proposed rule. The EPA welcomes any feedback on such standards that may 11 be applicable. 12 J. Executive Order 12898: Federal Actions to Address Environmental Justice in Minority 13 Populations and Low

-Income Populations 14 Executive Order 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive policy 15 on environmental justice. Its main provision directs federal agencies, to the greatest extent 16 practicable and permitte d by law, to make environmental justice part of their mission by 17 identifying and addressing, as appropriate, disproportionately high and adverse human health or 18 environmental effects of their programs, policies, and activities on minority populations and l ow 19 income populations in the United States. 20 EPA has determined that this proposed rule will not have disproportionatel y high and 21 adverse human health or environmental effects on minority or low

- income populations because it 22 retain s the level of environm ental protection for all affected populations without having any 23

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117 disproportionately

high and adverse human health or environmental effects on any population, 1 including any minority or low

- income population. 2 3 References 4 Baker JP; Bernard DP; Christensen SW; Sale MJ. 1990. Biological effects of changes in surface water acid

- base 5 chemistry. (State of science / technology report #13).Washington DC: National Acid Precipitation 6 Assessment Program (NAPAP). 7 Bulger AJ; Cosby BJ; Webb JR. 2000. Current, reconstructed past, and projected future status of brook trout 8 ( Salvelinus fontinalis ) streams in Virginia. Can J Fish Aquat Sci, 57, 1515

- 1523. 9 Banzhaf, S., D. Burtraw , D. Evans, and A. Krupnick. 2006. “Valuation of Natural Resource Improvements in the 10 Adirondacks.” L and Economics 82:445
- 464. 11 Lavery, T.F. C.M. Rogers, R. Baumgardner, and K.P. Mishoe. 2009. Intercomparison of Clean Air Status and 12 Trends Network Nitrate and Nitric Acid Measurements with Data from Other Monitoring Programs . J . Air 13 & Waste Manage. Assoc. , 59, 214
- 226. 14 Lien L; Raddum GG; Fjellheim A. 1992. Critical loads for surface waters: invertebrates and fish. (Acid rain research 15 report no 21). Oslo, Norway : Norwegian Institute for Water Research. 16 Luke, W.T. , P.K. Barry, L. Lefer, J. Flynn, B. Rappenglüc k, M. Leuchner, J.E. Dibb, L.D. Ziemba, C.H. Anderson, 17 and M. Buhr. 2010. Measurements of primary trace gases and NO Y com position in Houston, Texas. 18 Atmospheric Environment , 44, 4068
- 4080. 19 MacAvoy SW; Bulger AJ. 1995. Survival of brook trout (Salvelinus fo ntinalis) embryos and fry in streams of 20 different acid sensitivity in Shenandoah National Park, USA. Water Air Soil Pollut, 85, 445

- 450. 21 McNulty SG; Cohen EC; Myers JAM; Sullivan TJ; Li H. 2007. Estimates of critical acid loads and exceedances for 22 forest soils across the conterminous United States. Environ Pollut, 149, 281

- 292. 23 NAP AP. 1990. Acid Deposition: State of Science and Technology. National Acid Precipitation Assessment 24 Program. Office of the Director, Washington, DC. 25 NAP AP. (2005). National acid precipitation assessment program report to Congress: An integrated assessment. 26 http://www.esrl.noaa.gov/csd/aqrs/reports/napapreport05.pdf. Silver Spring, MD: National Acid 27 Precipitation Assessment Program (NAPAP); Committee on Environment and Natural Res ources (CENR) 28 of the National Science and Technology Council (NSTC). 29 NRC (National Research Council). 2004 . Air quality management in the United States. Washington, DC: National 30 Research Council (NRC); The National Academies Press. 31 Russell, A and J. M. Samet, 2010a. Review of the Policy Assessment for the Review of the Secondary National 32 Ambient Air Quality Standard for NOx and SOx: First Draft. EPA

- CASAC
- 10
- 014. 33 Russell, A and J. M. Samet, 2010b. Review of the Policy Assessment for the Review of the Second ary National 34 Ambient Air Quality Standard for NOx and SOx: Second Draft. EPA

- CASAC
- 11
- 003. 35

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118 Russell, A and J. M. Samet, 2011. Review of the Policy Assessment for the Revie w of the Secondary National 1 Ambient Air Quality Standard for NOx and SOx: FINAL. EPA

- C ASAC
- 11
- 005. 2 Russell and Samet, 2011b Review of EPA Draft Documents on Monitoring and Methods for Oxides of Nitrogen 3 (NOx) and Sulfur (SOx) http://yosemite.epa.gov/sab/sabpeople.ns f/WebCommittees/CASAC 4 Sickles II, J.E. , L. L. Hodson, and L. M. Vorburger. 1999
. Evaluation of the filter pack for long

- duration sampling 5 of ambient air

. Atmospheric Environment , 33, 2187
- 2202. 6 Sickles II, J.E. and D.S. Shadwick. 2008. Comparison of partic ulate sulfate and nitrate at collocated CASTNET and 7 IMPROVE sites in the eastern US

. Atmospheric Environment , 42, 2062
- 2073. 8 Smyth SC, W. Jiang, and H. Roth. 2008. A comparative performance evaluation of the AURAMS and CMAQ air 9 quality modeling systems. Atmos Envir 43:1059

- 1070. 10 Stoddard J; Kahl JS; Deviney FA; DeWalle DR; Driscoll CT; Herlihy AT; Kellogg JH; Murdoch PS; Webb JR; 11 Webster KE. (2003). Response of surface water chemistry to the Clean Air Act Amendments of 1990 (No. 12 EPA 620/R

- 03/001). Research Triangle Park, NC; National Health and Environmental Effects Research 13 Laboratory; Office of Research and Development; U.S. Environmental Protection Agency. 14 Sullivan TJ; Driscoll CT; Cosby BJ; Fernandez IJ; Herlihy AT; Zhai J; Stemberger R; Snyder KU; Suth erland JW; 15 Nierzwicki

- Bauer SA; Boylen CW; McDonnell TC; Nowicki NA. 2006. Assessment of the extent to which 16 intensively studied lakes are representative of the Adirondack Mountain region. (Final Report no 06

- 17 17).Corvallis, OR; prepared by Environmental Ch emistry, Inc. for: Albany, NY; Environmental Monitoring 18 Evaluation and Protection Program of the New York State Energy Research and Development Authority 19 (NYSERDA). 20 US EPA, 1973. “Effects of Sulfur Oxide in the Atmosphere on Vegetation”. Revised Chapter 5 of Air Quality 21 Criteria For Sulfur Oxides. U.S. Environmental Protection Agency. Research Triangle Park, N.C. EPA

- R3
- 22 73
- 030. 23 US EPA. 1982. Review of the National Ambient Air Quality Standards for Sulfur Oxides: Assessment of Scientific 24 and Technical Information . OAQPS Staff Paper. EPA

- 450/5

- 82
- 007. U.S. Environmental Protection 25 Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. 26 US EPA, 1984a. The Acidic Deposition Phenomenon and Its Effects: Critical Assessment Review Papers. Volume I 27 Atmospheric Sciences. EPA

- 600/8

- 83
- 016AF. Office of Research and Development, Washington, DC 28 US EPA, 1984b. The Acidic Deposition Phenomenon and Its Effects: Critical Assessment Review Papers. Volume 29 II Effects Sciences. EPA

- 600/8

- 83
- 016BF. Office of Research and Development, Washington, DC 30 US EPA, 1985. The Acidic Deposition Phenomenon and Its Effects: Critical Assessment Document. EPA

- 600/8

- 31 85/001. Office of Research and Development, Washington, DC 32 US EPA. 1995a. Review of the National Ambi ent Air Quality Standards for Nitrogen Dioxide: Assessment of 33 Scientific and Technical Information . OAQPS Staff Paper. EPA

- 452/R

- 95
- 005. U.S. Environmental 34 Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. Septemb er. 35 US EPA. 1995b. Acid Deposition Standard Feasibility Study Report to Congress. U.S. Environmental Protection 36 Agency, Washington, DC. EPA

- 430/R

- 95
- 001a. 37 US EPA 2007. Integrated Review Plan for the Secondary National Ambient Air Quality Standards for Nitr ogen 38 Dioxide and Sulfur Dioxide . U.S. Environmental Protection Agency, Research Triangle Park, NC, EPA

39 452/R

- 08
- 006. 40

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119 US EPA 2008. Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur Ecological Criteria (Final 1 Report). U.S. Environmental P rotection Agency, Washington, D.C., EPA/600/R

- 08/082F, 2008. 2 US EPA 2009. Risk and Exposure Assessment for Revie w of the Secondary National Ambient Air Quality 3 Standards for Oxides of Nitrogen and Oxides of Sulfur

- Main Content

- Final Report. U.S. Environm ental 4 Protection Agency, Washington, D.C., EPA

- 452/R

- 09
- 008a 5 US EPA, 2010a. CASTNET Quality Assurance Project Plan, Revision 7.0, October 2010, 6 http://java.epa.gov/castnet/ 7 US EPA, 2010b. CASTNET Annual Reports, 2004
- 2009, http://java.epa.gov/castnet/ 8 US EPA 2011. Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for 9 Oxides of Nitrogen and Oxides of Sulfur. U.S. Environmental Prote ction Agency, Washington, D.C., EPA

10 452/R

- 11
- 005a. 11 US EPA, 2011b. Federal Reference Methods for NO y and p

- SO 4 for the New Combined NO x and SO x Secondary 12 NAAQS Research Plan, EPA/600/1

- 11/002 January 20, 2011. 13 Wolff, G. T. 1993. CASAC closure letter for the 1993 Criteria Document for Oxides of Nitrogen addressed to U.S. 14 EPA Administrator Carol M. Browner dated September 30, 1993. 15 Wolff, G. T. 1995. CASAC closure letter for the 1995 OAQPS Staff Paper addressed to U.S. EPA Administrator 16 Carol M. Browner dat ed August 22, 1995. 17 18 List of Subjects in 40 CFR Part 50 19 Environmental protection, Air pollution control, Carbon monoxide, Lead, Nitrogen 20 dioxide, Ozone, Particulater matter, Sulfur oxides. 21 22

________________________________ 23 Dated: July

12, 2011 24 25 26 Lisa P. Jackson, 27 Administrator 28 29

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120 For the reasons set forth in the preamble, part 50 of chapter 1 of title 40 of the code of 1 Federal regulations is proposed to be amended as follows: 2
3
PART 50 - NATIONAL PRIMARY AND SECONDARY AMBIENT AIR QUALITY 4 STANDARDS 5
1. The authority citation for part 50 continues to read as follows: 6 Authority : 42 U.S.C. 7401, et seq. 7
8
2. Section 50.5 is amended by revising paragraphs (b) and (c) and b y adding paragraphs (d) and 9 (e) to read as follows: 10 §50. 5 National secondary am bient air quality standards for sulfur oxides (sulfur dioxide). 11 * * * * * 12 (b) The level of the national secondary 1
- hour ambient air quality standard for oxides of sulfur is 13 75 parts per billion (ppb, which is 1 part in 1,000,000,000), measured in the ambient air as sulfur 14 dioxide (SO 2 )

. 15 (c) The levels of the standards shall be measured by a reference method based on Appendix A

- 1 16 or A
- 2 of this part, or b y a Federal Equivalent Method (FEM) designated in accordance with part 17 53 of this chapter. 18 (d) To demonstrate attainment with the 3

- hour secondary standard, the second

- highest 3

- hour 19 average must be based upon hourly data that are at least 75 percent complete in each calendar 20 quarter. A 3
- hour block average shall be considered valid only if all three hourly

averages for 21

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121 the 3

- hour period are available. If onl y one or two hourly averages are available, but the 3

- hour 1 average would exceed the level of the standard when zeros are substituted for the missing values, 2 subject to the rounding rule of par agraph (a) of this section, then this shall be considered a valid 3 3
- hour average. In all cases, the 3

- hour block average shall be computed as the sum of the 4 hourly

averages divided by

3. 5 (e) The 1

- hour secondary standard is met at an ambient air quality monitoring site when the 6 three

- ye ar average of the annual 99 th percentile of the daily maximum 1

- hour average 7 concentrations is less than or equal to 75 ppb, as determined in accordance with Appendix T of 8 this part. 9 10
3. Section 50.11 is amended by deleting paragraphs (f) and (g) and revis ing paragraphs (a) 11 through (e) to read as follows: 12 §50.11 National primary and secondary ambient air quality standards for oxides of 13 nitrogen (with nitrogen dioxide as the indicator). 14 (a) The level o f the national primary and secondary annual ambient air quality standard s for 15 oxides of nitrogen is 53 parts per billion (ppb, which is 1 part in 1,000,000,000), annual average 16 concentration, measured in the ambient air as nitrogen dioxide. 17 (b) The level o f the national primary and secondary 1
- hour ambient air quality standard s for 18 oxides of nitrogen is 100 ppb, 1

- hour average concentration, measured in the ambient air as 19 nitrogen dioxide. 20 (c) The levels of the standards shall be measured by : 21

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122 (1) a referen ce method b ased on appendix F to this part; or 1 (2) a Federal equivalent method (FEM) designated in accordance with part 53 of this chapter. 2 (d) The annual primary and secondary standard s are met when the annual average concentration 3 in a calendar ye ar is less than or equal to 53 ppb, as determined in accordance with Appendix S 4 of this part for the annual standard. 5 ( e ) The 1

- hour primary and secondary standard s are met when the three

- ye ar average of the 6 annual 98 th percentile of the daily maximum 1

- hour average concentration is less than or equal to 7 100 ppb, as determined in accordance with Appendix S of this part for the 1

- hour standard. 8
9 4. Appendix S is amended as follows: 10 a. by

revising paragraph 1.(a), 11 b. by

revising the definition of “Design values” under paragraph 1.(c), 12 c. by revising paragraph 2.(b), 13 d. by

revising paragraphs 3.1(a) through (d), 14 e. by

revising paragraphs 3.2(a) through (e), 15 f. by

revising paragraph 4.1(b), 16 g. b y revising paragraph 4.2 (c), 17 h. by

revis ing paragraph 5.1(b), and 18

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12 3 i. by revising paragraph 5.2(b) to read as follows: 1 Appendix S to Part 50

—Interpretation of the Primary and Secondary National Ambient 2 Air Quality Standards for Oxides of Nitrogen (Nitrogen Dioxide) 3 1. General. 4 (a) This appendix explains the data handling conventions and computations necessary for 5 determining when the primary and secondary national ambient air quality standards for oxides of 6 nitrogen as measured b y nitrogen dioxide (“NO 2 NAAQS”) specified in § 50.11 are met. 7 Nitrogen dioxide (NO 2 ) is measured in the ambient air by a Federal reference method (FRM) 8 based on appendix F to this part or b y a Federal equivalent method (FEM) designated in 9 accordance with part 53 of this chapter. Data handling and computation procedures to be used in 10 making comparisons between reported NO 2 concentrations and the levels of the NO 2 NAAQS 11 are specified in the following sections. 12 * * * * * 13 (c) The terms used in this appendix are defined as follows: 14 * * * * * 15 Design values are the metrics ( i.e. , statistics) that are compared to the NAAQS levels to 16 determine compliance, calculated as specified in section 5 of this appendix. The design values 17 for the primary and secondary NAAQS are: 18 (1) The annual mean value for a monitoring site for one year (referred to as the “ annual primary 19 or secondary standard design value ”). 20

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124 (2) The 3

- ye ar average of annual 98 th percentile daily maximum 1

- hour values for a monitoring 1 site (referred to as the “ 1
- hour primary or secondary standard design value ”). 2 * * * * * 3 2. Requirements for Data Used for Comparisons with the NO 2 NAAQS and Data 4 Reporting Considerations. 5 * * * * * 6 (b) When two or more NO 2 monitors are operated at a site, the state may in advance designate 7 one of them as the primary monitor. If the state has not made this designation, the Administrator 8 will make the designation, either in advance or retrospectivel y. Design values will be developed 9 using onl y th e data from the primary monitor, if this results in a valid design value. If data from 10 the primary

monitor do not allow the development of a valid design value , data solely from the 11 other monitor(s) will be used in turn to develop a valid design value , if this results in a valid 12 design value . If there are three or more monitors, the order for such comparison of the other 13 monitors will be determined by the Administrator. The Administrator may combine data from 14 different monitors in different ye ars for the purpose of developing a valid 1

- hour primary or 15 secondary

standard design value, if a valid design value cannot be developed solely with the data 16 from a single monitor. However, data from two or more monitors in the same year at the same 17 site will not be combined in an attempt to meet data completeness requirements, except if one 18 monitor has phy sicall y replaced another instrument permanentl y , in which case the two 19 instruments will be considered to be the same monitor, or if the state has switched the 20 desi gnation of the primary monitor from one instrument to another during the year . 21

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125 * * * * * 1 3. Comparisons with the NO 2 NAAQS. 2 3.1 The Annual Primary and Secondary NO 2 NAAQS. 3 (a) The annual primary and secondary NO 2 NAAQS are met at a site when the valid annual 4 primary

standard design value is less than or equal to 53 parts per billion (ppb). 5 (b) An annual primary or secondary standard design value is valid when at least 75 percent of the 6 hours in the year are reported. 7 (c) An annual primary or secondary

standard design value based on data that do not meet the 8 completeness criteria stated in section 3.1(b) may also be considered valid with the approval of, 9 or at the initiative of, the Administrator, who may consider factors su ch as monitoring site 10 closures/moves, monitoring diligence, the consistency and levels of the valid concentration 11 measurements that are available, and nearb y concentrations in determining whether to use such 12 data. 13 (d) The procedures for calculating the annual primary and secondary standard design values are 14 given in section 5.1 of this appendix. 15 3.2 The 1

- hour Primary and Secondary NO 2 NAAQS. 16 (a) The 1

- hour primary or secondary NO 2 NAAQS is met at a site when the valid 1

- hour primary 17 or secondary standard design value is less than or equal to 1 00 parts per billion (ppb). 18 (b) An NO 2 1
- hour primary or secondary standard design value is valid if it encompasses three 19 consecutive calendar years of complete data. A year meets data completeness requirements 20 when all 4 quarters are complete. A quarter is complete when at least 75 percent of the sampling 21 day s for each quarter have complete data. A sampling day has complete data if 75 percent of the 22

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126 hourly concentration values, including state

- flagged data affected by exceptional events which 1 have been approved for exclusion by the Administrator, are reported

. 2 (c) In the case of one, two, or three ye ars that do not meet the completeness requirements of 3 section 3.2(b) of this appendix and thus would normally not be u seable for the calculation of a 4 valid 3
- ye ar 1
- hour primary or secondary standard design value, the 3
- ye ar 1
- hour primary or 5 secondary standard design value shall nevertheless be considered valid if one of the following 6 conditions is true. 7 (i) At least 7 5 percent of the days in each quarter of each of three consecutive years have at least 8 one reported hourl y value, and the design value calculated according to the procedures specified 9 in section 5.2 is above the level of the primary or secondary

1
- hour standard. 10 (ii) (A) A 1
- hour primary or secondary standard design value that is below the level of the 11 NAAQS can be validated if the substitution test in section 3 .2 (c)(i i ) (B) results in a “test design 12 value” that is below the level of the NAAQS. The test substitut es actual ‘‘ high ’’ reported dail y 13 maximum 1

- hour values from the same site at about the same time of the year ( specifically , in 14 the same calendar quarter) for unknown values that were not successfully measured . Note that 15 th e test is merely

diagn ostic in nature, intended to confirm that there is a very high likelihood 16 that the original design value (the one with less than 75 percent data capture of hours b y day and 17 of day s by

quarter) reflects the true under

- NAAQS
- level status for that 3

- year peri od; the result 18 of th is data substitution test (the ‘‘test design value”, as defined in section 3 .2 (c)(i i ) (B)) is not 19 considered the actual design value. For this test , substitution is permitted only if there are at least 20 200 day s across the three matching quarters of the three years under consideration (which is 21 about 75 percent of all possible daily values in those three quarters) for which 75 percent of the 22 hours in the day , including state

- flagged data affected by exceptional events which have been 23

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127 appro ved for exclusion by the Administrator, have reported concentrations. However, maximum 1 1
- hour values from day s with less than 75 percent of the hours reported shall also be considered 2 in identifying the high value to be used for substitution. 3 (B) The substitution test is as follows: Data substitution will be performed in all quarter periods 4 that have less than 75 percent data capture but at least 50 percent data capture , including state

5 flagged data affected b y exceptional events which have been approved fo r exclusion by the 6 Administrator ; if any quarter has less than 50 percent data capture then this substitution test 7 cannot be used

. Identify for each quarter (e.g., January

- March) the highest reported daily 8 maximum 1

- hour value for that quarter , excluding state - flagged data affected by exceptional 9 events which have been approved for exclusion by the Administrator, looking across those three 10 months of all three years under consideration

. All daily maximum 1

- hour values from all day s in 11 the quarter period sh all be considered when identifying this highest value, including day s with 12 less than 75 percent data capture. If after substituting the highest non - excluded reported dail y 13 maximum 1

- hour value for a quarter for as much of the missing dail y data in the mat ching 14 deficient quarter( s ) as is needed to make them 100 percent complete, the procedure in section 5.2 15 yi elds a recalculated 3

- ye ar 1
- hour standard “test design value” below the level of the standard, 16 then the 1

- hour primary or secondary standard design v alue is deemed to have passed the 17 diagnostic test and is valid, and the level of the standard is deemed to have been met in that 3

- 18 ye ar period. As noted in section 3 .2 (c)(i), in such a case, the 3

- ye ar design value based on the 19 data actually

reported, not the ‘‘test design value’’, shall be used as the valid design value. 20 (iii) (A) A 1
- hour primary or secondary standard design value that is above the level of the 21 NAAQS can be validated if the substitution test in section 3 .2 (c)(i ii ) (B) results in a “test design 22 value” that is above the level of the NAAQS. The test substitut es actual ‘‘ low” reported dail y 23

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128 maximum 1

- hour values from the same site at about the same time of the year ( specifically , in 1 the same three months of the calendar) for unknown values that were not successfull y measured

. 2 Note that th e test is merely diagnostic in nature, intended to confirm that there is a very high 3 likelihood that the original design value (the one with less than 75 percent data capture of hours 4 by day and of days by

quarter) reflects the true above

-NAAQS
- level status for that 3

- ye ar period; 5 the result of th is data substitution test (the ‘‘test design value”, as defined in section 6 3 .2 (c)(i ii ) (B)) is not considered the actual design value. For this test , substitution is permitted 7 only if there are a minimum number of available daily data points from which to identify the low 8 quarter - specific daily maximum 1

- hour values, specificall y if there are at least 200 day s across 9 the three matching quarters of the three years under consideration (which is about 75 percent of 10 all possible daily

values in those three quarters) for which 75 percent of the hours in the day have 11 reported concentrations. Only day s with at least 75 percent of the hours reported shall be 12 considered in identifying the low value to be used for substitution. 13 (B) The substitution test is as follows: Data substitution will be performed in all quarter periods 14 that have less than 75 percent data capture. Identify for each quarter (e.g., January

- March) the 15 lowest reported daily maximum 1

- hour value for that quarter , looking across those three months 16 of all three ye ars under consideration

. All daily maximum 1

- hour values from all day s with at 17 least 75 percent capture in the quarter period shall be considered when identifying this lowest 18 value. If after substituting the lowest reported daily maximum 1

- hour value for a quarter for as 19 much of the missing daily data in the matching deficient quarter ( s ) as is needed to make them 75 20 percent complete, the procedure in sec tion 5.2 yi elds a recalculated 3

- year 1
- hour standard “test 21 design value” above the level of the standard, then the 1

- hour primary or secondary standard 22 design value is deemed to have passed the diagnostic test and is valid, and the level of the 23

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129 standard i s deemed to have been exceeded in that 3

- ye ar period. As noted in section 3 .2 (c)(i), in 1 such a case, the 3

- ye ar design value based on the data actually reported, not the ‘‘test design 2 value’’, shall be used as the valid design value. 3 (d) A 1
- hour primary or secondary standard design value based on data that do not meet the 4 completeness criteria stated in 3.2(b ) and also do not satisfy section 3.2(c), may

also be 5 considered valid with the approval of, or at the initiative of, the Administrator, who may consider 6 factors such as monitoring site closures/moves, monitoring diligence, the consistency and levels 7 of the valid concentration measurements that are available, and nearb y concentrations in 8 determining whether to use such data. 9 (e ) The procedures for calculating the 1

- hour primary and secondary standard design values are 10 given in section 5.2 of this appendix. 11 4. Rounding Conventions. 12 4.1 Rounding Conventions for the Annual Primary and Secondary NO 2 NAAQS. 13 * * * * * 14 (b) The annual prim ary or secondary standard design value is calculated pursuant to section 5.1 15 and then rounded to the nearest whole number or 1 ppb (decimals 0.5 and greater are rounded up 16 to the nearest whole number, and any decimal lower than 0.5 is rounded down to the n earest 17 whole number). 18 4.2 Rounding Conventions for the 1

- hour Primary and Secondary NO 2 NAAQS. 19 * * * * * 20 (c) The 1

- hour primary or secondary standard design value is calculated pursuant to section 5.2 21 and then rounded to the nearest whole number or 1 ppb (decimals 0.5 and greater are rounded up 22

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130 to the nearest whole number, and any decimal lower than 0.5 is rounded down to the nearest 1 whole number). 2 5. Calculation Procedures f or the Primary and Secondary NO 2 NAAQS. 3 5.1 Procedures for the Annual Primary and Secondary NO 2 NAAQS 4 * * * * * 5 (b) The annual primary or secondary standard design value for a site is the valid annual mean 6 rounded according to the conventions in section 4.1. 7 5.2 Calculation Procedures f or the 1

- hour Prim ary and Secondary NO 2 NAAQS
. 8 * * * * * 9 (b) The 1

- hour primary or secondary standard design value for a site is the mean of the three 10 annual 98 th percentile values, rounded according to the conventions in section 4. 11
* * * * * 12
13 5. Appendix T is amended as follows: 14 a. by

revising paragraph 1.(a), 15 b. by

revising the definition of “Design values” under paragraph 1.(c), 16 c. by revising paragraph 2.(b), 17 d. by

revising paragraphs 3.(a) through (e), 18 e. by

revising paragraph 4.(c), an d 19 f. by

revising paragraph 5.(b) to read as follows: 20

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131 Appendix T to Part 50

—Interpretation of the Primary and Secondary National Ambient 1 Air Quality Standards for Oxides of Sulfur ( Sulfur Dioxide ) 2 1. General. 3 (a) This appendix explains the data handling conventions and computations necessary for 4 determining when the primary and secondary national ambient air quality standards for Oxides 5 of Sulfur as measured b y Sulfur Dioxide (“ SO 2 NAAQS”) specified in § 50.17 and §50.5 (b), 6 respectivel y, are met at an ambient air quality monitoring site

. Sulfur Dioxide ( SO 2 ) is measured 7 in the ambient air b y a Federal reference method (FRM) based on appendix A
- 1 or A
- 2 to this 8 part or b y a Federal equivalent method (FEM) designated in accordance with part 53 of this 9 chap ter. Data handling and computation procedures to be used in making comparisons between 10 reported SO 2 concentrations and the levels of the SO 2 NAAQS are specified in the following 11 sections. 12
* * * * * 13 (c) The terms used in this appendix are de fined as follows: 14 * * * * * 15 Design values are the metrics ( i.e. , statistics) that are compared to the NAAQS levels to 16 determine compliance, calculated as specified in section 5 of this appendix. The design value for 17 the primary and secondary 1
- hour NAAQS is the 3

- ye ar average of annual 99 th percentile daily 18 maximum 1

- hour values for a monitoring site (referred to as the “ 1
- hour primary standard design 19 value ”). 20

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132 * * * * * 1 2. Requirements for Data Used for Compariso ns with the SO 2 NAAQS and Data 2 Reporting Considerations. 3
* * * * * 4 (b) Data from two or more monitors from the same year at the same site reported to EPA under 5 distinct Pollutant Occurrence Codes shall not be combined in an attempt to meet data 6 completeness requirements

. The Administrator will combine annual 99 th percentile dail y 7 maximum concentration values from different monitors in different ye ars, selected as described 8 here, for the purpose of developing a valid 1

- hour primary or second ary standard design value. 9 If more than one of the monitors meets the completeness requirement for all four quarters of a 10 ye ar, the steps specified in section 5(a) of this appendix shall be applied to the data from the 11 monitor with the highest average of the four quarterly completeness values to derive a valid 12 annual 99 th percentile daily maximum concentration. If no monitor is complete for all four 13 quarters in a ye ar, the steps specified in section 3(c) and 5(a) of this appendix shall be applied to 14 the d ata from the monitor with the highest average of the four quarterl y completeness values in 15 an attempt to derive a valid annual 99 th percentile daily maximum concentration. This paragraph 16 does not prohibit a monitoring agency from making a local designatio n of one phy sical monitor 17 as the primary

monitor for a Pollutant Occurrence Code and substituting the 1

- hour data from a 18 second ph ys ical monitor whenever a valid concentration value is not obtained from the primary 19 monitor; if a monitoring agency substitut es data in this manner, each substituted value must be 20 accompanied b y an AQS qualifier code indicating that substitution with a value from a second 21 phy sical monitor has taken place. 22

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133 * * * * * 1 3. Comparisons with the 1
- hour Primary and Secon dary SO 2 NAAQS. 2 (a) The 1

- hour primary or secondary SO 2 NAAQS is met at an ambient air quality monitoring 3 site when the valid 1

- hour primary or secondary standard design value is less than or equal to 75 4 parts per billion (ppb). 5 (b) An SO 2 1
- hour primary or secondary standard design value is valid if it encompasses three 6 consecutive calendar years of complete data. A year meets data completeness requirements 7 when all 4 quarters are complete. A quarter is complete when at least 75 percent of the sampling 8 day s for each quarter have complete data. A sampling day has complete data if 75 percent of the 9 hourly

concentration values, including State

- flagged data affected b y exceptional events which 10 have been approved for exclusion by the Administrator, are repor ted. 11 (c) In the case of one, two, or three ye ars that do not meet the completeness requirements of 12 section 3(b) of this appendix and thus would normally not be useable for the calculation of a 13 valid 3
- ye ar 1
- hour primary or secondary standard design value , the 3
- ye ar 1
- hour primary or 14 secondary standard design value shall nevertheless be considered valid if one of the following 15 conditions is true. 16 (i) At least 75 percent of the days in each quarter of each of three consecutive years have at least 17 one rep orted hourl y value, and the design value calculated according to the procedures specified 18 in section 5 is above the level of the primary or secondary

1
- hour standard. 19 (ii) (A) A 1
- hour primary or secondary standard design value that is equal to or below th e level 20 of the NAAQS can be validated if the substitution test in section 3(c)(i i ) (B) results in a “test 21 design value” that is below the level of the NAAQS. The test substitut es actual ‘‘ high ’’ reported 22 daily

maximum 1

- hour values from the same site at ab out the same time of the year ( specifically , 23

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134 in the same calendar quarter) for unknown values that were not successfully measured . Note that 1 th e test is merely

diagnostic in nature, intended to confirm that there is a very high likelihood 2 that the original design value (the one with less than 75 percent data capture of hours b y day and 3 of day s by

quarter) reflects the true under

- NAAQS
- level status for that 3

- year period; the result 4 of th is data substitution test (the ‘‘test design value”, as defined in sec tion 3(c)(i i ) (B)) is not 5 considered the actual design value. For this test , substitution is permitted only if there are at least 6 200 day s across the three matching quarters of the three years under consideration (which is 7 about 75 percent of all possible d aily values in those three quarters) for which 75 percent of the 8 hours in the day , including State

- flagged data affected b y exceptional events which have been 9 approved for exclusion by the Administrator, have reported concentrations. However, maximum 10 1
- hour values from day s with less than 75 percent of the hours reported shall also be considered 11 in identifying the high value to be used for substitution. 12 (B) The substitution test is as follows: Data substitution will be performed in all quarter periods 13 that have less than 75 percent data capture but at least 50 percent data capture, including State

14 flagged data affected b y exceptional events which have been approved for exclusion by the 15 Administrator ; if any quarter has less than 50 percent data capture then this substitution test 16 cannot be used

. Identify for each quarter (e.g., January

- March) the highest reported daily 17 maximum 1

- hour value for that quarter, excluding State

- flagged data affected by exceptional 18 events which have been approved for exclusion by the Administrator, looking across those three 19 months of all three years under consideration

. All daily maximum 1

- hour values from all day s in 20 the quarter period shall be considered when identifying this highest value, including day s with 21 less than 75 perc ent data capture. If after substituting the highest reported daily maximum 1

- hour 22 value for a quarter for as much of the missing daily data in the matching deficient quarter ( s ) as is 23

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135 needed to make them 100 percent complete, the procedure in section 5 yi el ds a recalculated 3

- 1 ye ar 1
- hour standard “test design value” less than or equal to the level of the standard, then the 1

- 2 hour primary or secondary standard design value is deemed to have passed the diagnostic test 3 and is valid, and the level of the standard is deemed to have been met in that 3

- ye ar period. As 4 noted in section 3(c)(i), in such a case, the 3

- ye ar design value based on the data actually 5 reported, not the ‘‘test design value’’, shall be used as the valid design value. 6 (iii) (A) A 1
- hour primary or secondary standard design value that is above the level of the 7 NAAQS can be validated if the substitution test in section 3(c)(i ii ) (B) results in a “test design 8 value” that is above the level of the NAAQS. The test substitut es actual ‘‘ low” reported d ail y 9 maximum 1

- hour values from the same site at about the same time of the year ( specifically , in 10 the same three months of the calendar) for unknown hourly values that were not successfully 11 measured . Note that th e test is merely diagnostic in nature, int ended to confirm that there is a 12 very

high likelihood that the original design value (the one with less than 75 percent data capture 13 of hours b y day and of days b y quarter) reflects the true above

-NAAQS
- level status for that 3

- 14 ye ar period; the result of th is data substitution test (the ‘‘test design value”, as defined in section 15 3(c)(i ii ) (B)) is not considered the actual design value. For this test , substitution is permitted only 16 if there are a minimum number of available dail y data points from which to identify the low 17 quarter - specific daily maximum 1

- hour values, specificall y if there are at least 200 day s across 18 the three matching quarters of the three years under consideration (which is about 75 percent of 19 all possible daily

values in those three quarter s) for which 75 percent of the hours in the day have 20 reported concentrations. Only day s with at least 75 percent of the hours reported shall be 21 considered in identifying the low value to be used for substitution. 22

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136 (B) The substitution test is as follows: Data substitution will be performed in all quarter periods 1 that have less than 75 percent data capture. Identify for each quarter (e.g., January

- March) the 2 lowest reported daily maximum 1

- hour value for that quarter , looking across those three months 3 of all three ye ars under consideration

. All daily maximum 1

- hour values from all day s with at 4 least 75 percent capture in the quarter period shall be considered when identifying this lowest 5 value. If after substituting the lowest reported daily maximum 1

- hour value for a quarter for as 6 much of the missing daily data in the matching deficient quarter ( s ) as is needed to make them 75 7 percent complete, the procedure in section 5 yi elds a recalculated 3

- year 1
- hour standard “test 8 design value” above the level of the standard, then the 1

- hour primary or secondary standard 9 design value is deemed to have passed the diagnostic test and is valid, and the level of the 10 standard is deemed to have been exceeded in that 3

- ye ar period. As noted in section 3(c)(i), in 11 such a case, the 3

- ye ar design value based on the data actually reported, not the ‘‘test design 12 value’’, shall be used as the valid design value. 13 (d) A 1
- hour primary or secondary

standard design value based on data that do not meet the 14 completeness criteria stated in 3(b ) and also do not satisfy section 3(c), may

also be considered 15 valid with the approval of, or at the initiative of, the Administrator, who may consider factors 16 such as monitoring site closures/moves, monitoring diligen ce, the consistency and levels of the 17 valid concentration measurements that are available, and nearb y concentrations in determining 18 whether to use such data. 19 (e ) The procedures for calculating the 1

- hour primary or secondary standard design values are 20 given in section 5 of this appendix. 21 4. Rounding Conventions for the 1

- hour Primary and Secondary SO 2 NAAQS. 22

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137 * * * * * 1 (c) The 1

- hour primary or secondary standard design value is calculated pursuant to section 5 2 and then rounded to the nearest whole number or 1 ppb (decimals 0.5 and greater are rounded up 3 to the nearest whole number, and any decimal lower than 0.5 is rounded down to the nearest 4 whole number). 5 5. Calculation Procedures f or the 1

- hour Primary and Secondary SO 2 NAAQS. 6 * * * * * 7 (b) The 1

- hour primary or secondary standard design value for an ambient air quality monitoring 8 site is the mean of the three annual 99 th percentile values, rounded according to the conventions 9 in section 4. 10