# BASELINE AND NATURAL BACKGROUND VISIBILITY CONDITIONS

C ONSIDERATIONS AND 

# P ROPOSED 

# A PPROACH
TO THE 

# C ALCULATION OF 

# B ASELINE AND 

# N ATURAL 

# B ACKGROUND 

# V ISIBILITY 

# C ONDITIONS AT 

# MANE-VU C LASS 

# I A REAS

Prepared by NESCAUM



## December, 2006ii 

### Members of NESCAUM

Anne Gobin, Bureau Chief Connecticut Department of Environmental Protection, Bureau of Air Management

James P. Brooks, Bureau Director Maine Department of Environmental Protection, Burea u of Air Quality

Barbara Kwetz, Director Massachusetts Department of Environmental Protectio n, Bureau of Waste Prevention

Robert Scott, Director New Hampshire Department of Environmental Services, Air Resources Division

William O’Sullivan, Director New Jersey Department of Environmental Protection, Office of Air Quality Management

David Shaw, Director New York Department of Environmental Conservation, Division of Air Recourses

Stephen Majkut, Chief Rhode Island Department of Environmental Management , Office of Air Resources

Richard A. Valentinetti, Director Vermont Department of Environmental Conservation, A ir Pollution Control Division

Arthur Marin, Executive Director

NESCAUMiii



# BASELINE AND NATURAL BACKGROUND VISIBILITY CONDITIONS

C ONSIDERATIONS AND 

# P ROPOSED 

# A PPROACH
TO THE 

# C ALCULATION OF 

# B ASELINE AND 

# N ATURAL 

# B ACKGROUND 

# V ISIBILITY 

# C ONDITIONS AT 

# MANE-VU C LASS 

# I A REAS

Prepared by NESCAUM



## December, 2006iv



# BASELINE AND NATURAL BACKGROUND VISIBILITY CONDITIONS Considerations and Proposed Approach to the Calculation of Baseline and Natural Background Visi bility Conditions at MANE-VU Class I Areas

Project Manager Gary Kleiman, NESCAUM

Principal Contributors Gary Kleiman, John Graham, NESCAUMv



## Acknowledgements
NESCAUM acknowledges the funding support for this w ork through U.S. EPA agreement number XA-97318101-0 to the Ozone Transport Commission in support of the MANE-VU Regional Planning Organization.

Printed: January, 2007vi

TABLE OF CONTENTS

1. Introduction....................................

................................................... .......................... 1 2. The Default Method..............................

................................................... ................... 2 2.1. Application of the Default Methods ............

................................................... 4 3. The Alternative Method..........................

................................................... ................. 6 3.1. Application of the Alternative Method......... .................................................. 9 4. Recommendations.................................

................................................... ................. 12Baseline and Natural Background Visibility Conditio ns Page 1



## 1. INTRODUCTION The long-term visibility conditions that would exis t in absence of human-caused impairment are referred to as natural background visibility conditions. Accurate assessment of these conditions is important due to their role in determining the uniform rate of progress that states must consider when set ting reasonable progress goals for each mandatory Federal Class I area subject to the Regio nal Haze Rule. Baseline visibility conditions – based on monitored visibility during t he five year baseline period (2000- 2004) – and estimated natural background visibility conditions will determine the uniform rate of progress states will consider when setting reasonable progress goals for any Class I site. In September 2001, the U.S. Environmental Protectio n Agency (EPA) issued draft methodological guidelines for the calculation of na tural background and baseline visibility conditions as well as methods for tracki ng progress relative to the derived uniform rate of progress. EPA subsequently finalize d this draft guidance in September 2003. The final guidance recommends a default metho d and allows for certain refinements that states may wish to pursue in order to make these estimates more representative of a specific Class I area if it is poorly represented by the default method. In the spring of 2006, the IMPROVE Steering Committ ee adopted an alternative formulation of the reconstructed extinction equatio n to address certain aspects of the default calculation method. These aspects were well understood from a scientific perspective and were felt to improve the performanc e of the equation at reproducing observed visibility at Class I sites. This alternat ive formulation of the reconstructed extinction equation was not adopted as a replacemen t to the default method, but as an alternative to the default method for states and RP Os to consider as they proceed with the regional haze planning process. It seems likely tha t most, if not all, RPOs are considering this alternative formulation as the means by which they will calculate baseline conditions, natural background conditions, and track progress t oward the national visibility goals under the Regional Haze Rule. In this report, MANE-VU reviews the default and alt ernative approaches to the calculation of baseline and natural background cond itions and presents a discussion of the principle differences between the methods. In addit ion, the default and alternative methods are applied to each Class I area in or near the MANE-VU region in order to establish differences in baseline conditions, natural background conditi ons, and 2018 uniform progress goals under each approach. The prior MANE-VU position on natural background co nditions was issued in June, 2004 and stated that, “Refinements to other a spects of the default method (e.g., refinements to the assumed distribution or treatmen t of Rayleigh extinction, inclusion of sea salt, and improved assumptions about the chemic al composition of the organic fraction) may be warranted prior to submissions of SIPs depending on the degree to which scientific consensus is formed around a speci fic approach...” Based upon the subsequent reviews conducted by the IMPROVE Steerin g Committee, as well as internal Technical Steering Committee deliberations, MANE-VU is now ready to adopt the alternative reconstructed extinction algorithm for the reasons described in this report.Baseline and Natural Background Visibility Conditio ns Page 2



## 2. THE DEFAULT METHOD The default method is explained in detail in Estimating Natural Background Visibility Conditions (U.S.EPA, 2003a) and Guidance for Tracking Progress under the Regional Haze Rule (U.S. EPA, 2003b). Summary information is provided here but the reader should consult the original guidance documen ts for any question on how to apply this method. Estimates of natural visibility impairment due to f ine and coarse particles were derived using the 1990 National Acid Precipitation Assessment Program reported average ambient concentrations of naturally present particl es (Trijonis, 1990). Separate concentration values were given for the eastern and western United States; no finer spatial resolution is available. Average natural ba ckground light extinction due to particles was then calculated using the IMPROVE met hodology and site specific ANNUAL f(RH) values. Worst visibility levels are de rived using the work of Ames and Malm (2001), who estimated the standard deviation o f visibility in deciviews in the eastern U.S. as 3 dv. By assuming a roughly normal distribution of data, the default method adds (subtracts) 1.28*(3 dv) to the average estimated natural background to calculate the 90 th (10 th ) percentile level, which is taken by EPA to be rep resentative of the mean of the 20 percent worst (best) conditions. In the East, the default method for calculating bes t and worst natural background visibility conditions (in dv) for any area in the e astern U.S. uses the following formulae:

P90 = HI +1.28 sd

P10 = HI – 1.28 sd

P90 and P10 represent the 90 th and 10 th percentile, respectively, the Haze Index (HI) represents annual average visibility in units of deciview, and sd is the standard deviation of daily average visibility values throug hout a year, defined by the guidance as 3.0 for the eastern U.S. The Haze Index is calculat ed as shown:

HI =10 ln (bext/10)

The atmospheric extinction, bext, is given by the f amiliar IMPROVE equation (IMPROVE, 2000) in inverse megameters:

bext = (3)f(RH)[sulfate] + (3)f(RH)[nitrate] + (4)[ OMC] + (10)[LAC]

+(1)[SOIL] + (0.6)[CM] + 10

Table 2-1 below provides the default values to be a pplied at all eastern U.S. Class I areas. The result of using these default values in the above equation with an assumed annual average f(RH) value of 3.17 in the northeast ern U.S. (the average of 11 northeastern U.S. sites) is approximately 3.6 dv on the 20 percent best days and 11.3 dv on the 20 percent worst days.Baseline and Natural Background Visibility Conditio ns Page 3

The methods for calculating baseline conditions on the 20 percent best or worst days start by repeating the calculation of the Haze Index (HI) as shown above with the individual species mass concentrations replaced by the actual monitored values for each day during the baseline period. These values should be sorted from highest to lowest for each year in the baseline period. Averages (in dv) for each year can be calculated for HI values associated with the 20 percent most impaired and 20 percent least impaired days. The average HI values for the 20 percent most impai red and 20 percent least impaired days in each year should then be averaged for the f ive consecutive years 2000-2004 to define baseline conditions. One important distincti on between the natural conditions and baseline HI calculations is that the f(RH) values s hown in Table 2-2 for natural conditions estimates are annual averages. EPA has a lso estimated site-specific

Table 2-1. Default parameters used in calculating natural background visibility for sites in the east ern U.S.
Parameter Value Fractional Uncertainty Reference/Comments

[SULFATE] 0.23 μg/m 3 200% Trijonis, 1990 [NITRATE] 0.10 μg/m 3 200% Trijonis, 1990 [OC] 1.0 μg/m 3 200% Trijonis, 1990 [LAC] 0.02 μg/m 3 250% Trijonis, 1990 [SOIL] 0.50 μg/m 3 200% Trijonis, 1990 [CM] 3.0 μg/m 3 200% Trijonis, 1990 f(RH) ~3.2 15% Varies by site (see Table 2-2) Organic multiplier 1.4 50% [OMC]=1.4*[OC]



### σ S/N 3.0 m 2 /g 33% Hegg, 1997; IMPROVE, 2000; Malm, 2000



### σ OC 4.0 m 2 /g 30% Hegg 1997; Trijonis 1990



### σ EC 10.0 m 2 /g 40% Malm, 1996



### σ soil 1.0 m 2 /g 25% Trijonis, 1990



### σ coarse 0.6 m 2 /g 33% IMPROVE, 2000 Rayleigh 10 Mm -1 20 % Varies with altitude/season sd (standard deviation of daily visibility) 3.0 dv 16% Ames and Malm, 2001

10 th , 90 th percentile adjustment 1.28 15% Regulation calls for mean of top twenty percent, not 90 th percentile Parameters used in potential refinements [NaCl] ~0.5 50% Varies by site, IMPROVE



### σ NaCl 2.5 m 2 /s 16% Haywood, 1999 f(RH) NaCl ~3.2 33% Assumed same as S, N Note: The mass estimates presented above are based on estimates of fine particulate concentrations tha t would exist in absence of any manmade pollution (including Mexican and Canadian emissions) consistent with planning r equirements of the Regional Haze Rule. MANE-VU accepts this as an appropriate planning goal and intends to consider the contribution of international transport in deciding what controls are “reasonable ” under the regional haze program.Baseline and Natural Background Visibility Conditio ns Page 4

climatological mean monthly average values of f(RH) that are provided in an appendix to its guidance (EPA, 2003b) and used for the individu al HI calculations for baseline conditions.



### 2.1. Application of the Default Methods The Class I areas in the MANE-VU region that are su bject to the requirements of the Regional Haze Rule are: Acadia National Park, M aine; Brigantine Wilderness (within the Edwin B. Forsythe National Wildlife Refuge), Ne w Jersey; Great Gulf Wilderness, New Hampshire; Lye Brook Wilderness, Vermont; Moose horn Wilderness (within the Moosehorn National Wildlife Refuge), Maine; Preside ntial Range – Dry River Wilderness, New Hampshire; and Roosevelt Campobello International Park, New Brunswick. In addition to these Class I areas, we c onsider several nearby Class I areas where MANE-VU states may be contributing to visibil ity impairment. These Class I areas include: Dolly Sods Wilderness and the Otter Creek Wilderness in West Virginia as well as Shenandoah National Park and the James Rive r Face Wilderness in Virginia. MANE-VU understands that it is the responsibility o f the appropriate VISTAS states to establish estimates of natural visibility condition s and reasonable progress goals for these areas. It is anticipated, however, that subsequent consultations will occur with those MANE-VU states that may be affecting visibility in these areas. MANE-VU has therefore calculated estimates of natural backgroun d visibility conditions at the nearby sites using MANE-VU approved methods in order to fa cilitate future consultations. The only factor in the default method that varies b y site is the climatological annual mean relative humidity adjustment factor. Ta ble 2-2 lists this value for the Class I sites of interest and the resulting best 20 percent and worst 20 percent estimates of natural visibility conditions. The variation among sites us ing the default method is purely a function of differences in climatological annual me an relative humidity, with southern and coastal sites being more humid than inland or e levated sites.Baseline and Natural Background Visibility Conditio ns Page 5

Table 2-2. Site-specific relative humidity adjustme nt factors, best and worst (default) estimates of natural background visibilit y conditions.

MANE-VU Mandatory Federal Class I Area f(RH) Best Visibility (dv) Worst Visibility (dv)

Maine Acadia National Park 3.34 3.77 11.45

Moosehorn Wilderness 3.15 3.68 11.36 Roosevelt Campobello International Park, New Brunswick 3.16 3.68 11.37

New Hampshire Great Gulf Wilderness 3.01 3.63 11.30 Presidential Range – Dry River Wilderness 3.02 3.65 11.30 New Jersey Brigantine Wilderness 2.97 3.60 11.28

Vermont Lye Brook Wilderness 2.91 3.57 11.25

Nearby Mandatory Federal Class I Area Virginia James River Face Wilderness 2.93 3.56 11.26

Shenandoah National Park 2.95 3.57 11.27 West Virginia Dolly Sods Wilderness 3.06 3.64 11.32

Otter Creek Wilderness 3.06 3.65 11.32Baseline and Natural Background Visibility Conditio ns Page 6



## 3. THE ALTERNATIVE METHOD According to EPA guidance, “[T]he default approach to estimating natural visibility conditions presented in this document is adequate for the development of progress goals for the first implementation period under the regional haze rule” (U.S. EPA, 2003a). However, the guidance does leave the d oor open for individual states or RPOs to adopt their own methods for calculating nat ural background (or baseline conditions) if they can demonstrate that the change from the default represents a significant refinement that better characterizes na tural visibility (or baseline) conditions at a specific Class I site.

Table 2-3. Site-specific best and worst (default) e stimates of baseline visibility conditions (2000-2004). MANE-VU Mandatory Federal Class I Area Best Visibility (dv) Worst Visibility (dv)

Maine Acadia National Park 8.06 22.34

Moosehorn Wilderness 8.48 21.18 Roosevelt Campobello International Park, New Brunswick 8.48 21.18

New Hampshire Great Gulf Wilderness 7.50 22.25 Presidential Range – Dry River Wilderness 7.50 22.25 New Jersey Brigantine Wilderness 13.72 27.60

Vermont Lye Brook Wilderness 6.20 23.70

Nearby Mandatory Federal Class I Area Virginia James River Face Wilderness 14.35 27.72

Shenandoah National Park 11.34 27.88 West Virginia Dolly Sods Wilderness 12.70 27.64

Otter Creek Wilderness 12.70 27.64Baseline and Natural Background Visibility Conditio ns Page 7

In response to a number of concerns raised with res pect to the use of the default methods for Regional Haze Rule compliance (Lowentha l and Kumar, 2003; Ryan et al., 2005), the IMPROVE Steering Committee established a subcommittee to review the default approach and recommend refinements to addre ss criticisms and improve the performance for tracking progress under the Haze Ru le. The details presented below come from that subcommittee’s summary report and a review of potential refinements by Hand and Malm (2005). The recommended revised algorithm is shown in the e quation below with revised terms in bold font. The total sulfate, nitrate, and organic carbon compound concentrations are each split into two fractions, representing sma ll and large size distributions of those components. Although not explicitly shown in the eq uation, the organic mass concentration used in this new algorithm is 1.8 tim es the organic carbon mass concentration, which is changed from 1.4 times the carbon mass concentration as used for input in the current IMPROVE algorithm. New terms h ave been added for sea salt (important for coastal locations) and for absorptio n by NO 2 (only used where NO 2 data are available). Site-specific Rayleigh scattering i s calculated for the elevation and annual average temperature of each of the IMPROVE monitori ng sites.

Bext ≈ 2.2 x f

S (RH) x [Small Sulfate] + 4.8 x f L (RH) x [Large Sulfate] + 2.4 x f

S (RH) x [Small Nitrate] + 5.1 x f L (RH) x [Large Nitrate] + 2.8 x [Small Organic Mass] + 6.1 x [Large Organic Mass] + 10 x [Elemental Carbon Mass] + 1 x [Fine Soil Mass ] + 1.7 x f

SS (RH) x [Sea Salt Mass] + 0.6 x [Coarse Mass] + Rayleigh Scattering (site specific) + 0.33 x [NO 2 (ppb)]

The apportionment of the total concentration of su lfate compounds into the concentrations of the small and large size fraction s is accomplished using the following equations.

The same equations are used to apportion total nitr ate and total organic mass concentrations into the small and large size fracti ons.

Sea salt is calculated as 1.8 x [ Chloride ], or 1.8 x [ Chlorine ] if the chloride measurement is below detection limits, missing, or invalid. The algorithm uses three water growth adjustment terms as shown in Figure 3- 1 and Table 3-1. They are for use 

## [ ] [ ] [ ] 3 / 20

, rga m g Sulfate Total for Sulfate Total Sultate e L μ ≥ = 

## [ ] [ ] [ ] [ ] 3
3 

### / 20

, / 20 arg m g Sulfate Total for Sulfate Total

m g Sulfate Total Sulfate e L 

### μ

μ <

× =



## [ ] [ ] [ ] Sulfate e L Sulfate Total Sulfate Small arg

− =Baseline and Natural Background Visibility Conditio ns Page 8

with the small size distribution and the large size distribution sulfate and nitrate compounds and for sea salt ( f S (RH), f

L (RH), and f

SS (RH), respectively).

Figure 3-1. Water growth curves for small and large size distribution sulfate and nitrate, sea salt, and the original IMPROVE algorit hm sulfate and nitrate.

Water Growth Curves

0 1 2 3 4 5 6 7 8 9 10

0 10 20 30 40 50 60 70 80 90 100 Relative Humidity (%)f(RH) fS(RH) fL(RH) Original fSS(RH)

Table 3-1. f(RH) for small and large size distribut ion sulfate and nitrate, and sea salt.

RH (%) f

S (RH) f

L (RH) f

SS (RH) RH (%) f S (RH) f

L (RH) f

SS (RH) RH (%) f S (RH) f

L (RH) f

SS (RH)

0 to 36 1.00 1.00 1.00 56 1.78 1.61 2.58 76 2.60 2.18 3.35

37 1.38 1.31 1.00 57 1.81 1.63 2.59 77 2.67 2.22 3.42

38 1.40 1.32 1.00 58 1.83 1.65 2.62 78 2.75 2.27 3.52

39 1.42 1.34 1.00 59 1.86 1.67 2.66 79 2.84 2.33 3.57

40 1.44 1.35 1.00 60 1.89 1.69 2.69 80 2.93 2.39 3.63

41 1.46 1.36 1.00 61 1.92 1.71 2.73 81 3.03 2.45 3.69

42 1.48 1.38 1.00 62 1.95 1.73 2.78 82 3.15 2.52 3.81

43 1.49 1.39 1.00 63 1.99 1.75 2.83 83 3.27 2.60 3.95

44 1.51 1.41 1.00 64 2.02 1.78 2.83 84 3.42 2.69 4.04

45 1.53 1.42 1.00 65 2.06 1.80 2.86 85 3.58 2.79 4.11

46 1.55 1.44 1.00 66 2.09 1.83 2.89 86 3.76 2.90 4.28

47 1.57 1.45 2.36 67 2.13 1.86 2.91 87 3.98 3.02 4.49

48 1.59 1.47 2.38 68 2.17 1.89 2.95 88 4.23 3.16 4.61

49 1.62 1.49 2.42 69 2.22 1.92 3.01 89 4.53 3.33 4.86

50 1.64 1.50 2.45 70 2.26 1.95 3.05 90 4.90 3.53 5.12

51 1.66 1.52 2.48 71 2.31 1.98 3.13 91 5.35 3.77 5.38

52 1.68 1.54 2.50 72 2.36 2.01 3.17 92 5.93 4.06 5.75

53 1.71 1.55 2.51 73 2.41 2.05 3.21 93 6.71 4.43 6.17

54 1.73 1.57 2.53 74 2.47 2.09 3.25 94 7.78 4.92 6.72

55 1.76 1.59 2.56 75 2.54 2.13 3.27 95 9.34 5.57 7.35Baseline and Natural Background Visibility Conditio ns Page 9

The proposed new algorithm for estimating haze redu ces the biases compared to measurements at the high and low extremes. This is most apparent for the hazier eastern sites. The composition of days selected as best and worst by the current and the new algorithm are very similar, and similar to days sel ected by measurements. Most of the reduction of bias associated with the new algorithm is attributed to the use of the split component extinction efficiency method for sulfate, nitrate, and organic components that permitted variable extinction efficiency depending on the component mass concentration. Although not subject to explicit performance testin g, the proposed new algorithm also contains specific changes from the current algorith m that reflect a better understanding of the atmosphere as reflected in the more recent scie ntific literature (e.g., change to 1.8 from 1.4 for organic compound mass to carbon mass r atio) and a more complete accounting for contributors to haze (e.g., sea salt and NO 2 terms), and use of site specific Rayleigh scattering terms to reduce elevation-relat ed bias. Unlike the default approach, which directly uses th e Trijonis natural species concentration estimates to calculate natural haze l evels, the Alternative Approach uses the baseline data (current species concentrations) with a multiplier applied to each species measurement in order to give the Trijonis estimate for that species. The ratio of the Trijonis estimates for each species divided by the annual mean values for the species is used to transform the entire data set to what is th en assumed to be the natural species concentration levels for that site and year. This p rocess is applied to each of the complete years of data (as defined by the EPA tracking progress guidance) in the baseline period (2000 through 2004). Sites with three complete year s of data are treated as having sufficient data for this assessment. If any of the current annual means for any species is less than the Trijonis estimate for that species, t he unadjusted species data are used. Trijonis estimates did not include sea salt, which is only significant at a few coastal sites. Estimates of current sea salt concentrations determ ined from Cl - ion data (described as part of the new IMPROVE algorithm) are taken to be natural contributors to haze.



### 3.1. Application of the Alternative Method Here we present a comparison of the background and natural visibility conditions calculated using the default and the alternative me thods (see Table 3-2 and Table 3-3). Corresponding visibility improvement targets for 20 18 using each approach are also presented (see Table 3-3). Results suggest that the alternative approach leads to very similar uniform rates of progress in New England wi th slightly greater visibility improvement required in the Mid-Atlantic region rel ative to the default approach.Baseline and Natural Background Visibility Conditio ns Page 10

Table 3-2. Comparison of default and alternative ap proaches for estimating the 20 percent worst natural background visibility conditions at M ANE-VU and nearby sites (2000-2004).

MANE-VU Mandatory Federal Class I Area Default Baseline

dv Alternative Baseline

dv Default Natural

dv Alternative Natural

dv

Maine Acadia National Park 22.34 22.89 11.45 12.43

Moosehorn Wilderness 21.18 21.72 11.36 12.01 Roosevelt Campobello International Park, New Brunswick 21.18 21.72 11.37 12.01

New Hampshire Great Gulf Wilderness 22.25 22.82 11.30 11.99 Presidential Range – Dry River Wilderness 22.25 22.82 11.30 11.99

New Jersey Brigantine Wilderness 27.60 29.01 11.28 12.24

Vermont Lye Brook Wilderness 23.70 24.45 11.25 11.73 Nearby Mandatory Federal Class I Areas Virginia James River Face Wilderness 27.72 29.12 11.26 11.13

Shenandoah National Park 27.88 29.31 11.27 11.35 West Virginia Dolly Sods Wilderness 27.64 29.04 11.32 10.39

Otter Creek Wilderness 27.64 29.04 11.32 10.39Baseline and Natural Background Visibility Conditio ns Page 11

Table 3-3. Estimated uniform rates of progress (ROP ) (to be considered for worst 20 percent days) and Best Day Baseline Conditions (not to be d egraded on best 20 percent days) for first implementation period.

MANE-VU Mandatory Federal Class I

Area Default ROP Worst day (dv/14 yrs) Alternative

ROP Worst day (dv/14 yrs) Default

Baseline Visibility Best Day (dv) Alternative

Baseline Visibility Best Day (dv)
Maine Acadia National Park 2.54 2.44 8.06 8.77
Moosehorn Wilderness 2.29 2.27 8.48 9.15 Roosevelt Campobello International Park, New Brunswick 2.29 2.27 8.48 9.15

New Hampshire Great Gulf Wilderness † 2.56 2.53 7.50 7.66 Presidential Range – Dry River Wilderness † 2.56 2.53 7.50 7.66

New Jersey Brigantine Wilderness ‡ 3.81 3.91 13.72 14.33
Vermont Lye Brook Wilderness 2.91 2.97 6.20 6.36 Nearby Mandatory Federal Class I Area Virginia James River Face Wilderness п 3.84 4.20 14.35 14.21
Shenandoah National Park ‡ 3.88 4.19 11.34 10.93 West Virginia Dolly Sods Wilderness 3.81 4.35 12.70 12.28
Otter Creek Wilderness 3.81 4.35 12.70 12.28
Note: The values are presented for the default and alternative approaches at MANE-VU and nearby s ites (2000-2004).Baseline and Natural Background Visibility Conditio ns Page 12

The default estimates provide a sound, nationally c onsistent framework on which to base the regulatory structure of the Haze Rule t hat is justified by the current state of scientific understanding of these issues. However, an alternative approach for the calculation of reconstructed extinction under the R egional Haze Rule has been developed that provides all of the same advantages. EPA recom mendations on potential refinements to the default approach (Pitchford, personal commun ication, 2004) suggest that, if used, any refinements should be broadly accepted by the s cientific community, substantial, practical to implement, and not create arbitrary in consistencies. The alternative approach endorsed by the IMPROVE Steering Committee for base line and natural background conditions meet these requirements.



## 4. RECOMMENDATIONS This document reviews EPA guidelines and an IMPROVE Steering Committeeendorsed alternative for calculating baseline and n atural background visibility conditions under the Regional Haze Rule. It also explores how adoption of the alternative approach would affect calculated rates of progress and other regulatory drivers under the Haze Rule. The alternative approach attempts to incorporate be tter science for several components of the equation to calculate reconstruct ed extinction that reflects the latest scientific research. MANE-VU recognizes the time an d effort that has been invested in the development of this alternative. We also recogn ize the high likelihood that other RPOs will adopt and use the alternative approach an d consider it desirable to use a similar approach to other RPOs with which MANE-VU w ill consult on visibility goals. Given the large uncertainties that remain in our ab ility to estimate the concentrations of organic carbon and other species that would be pres ent in the absence of anthropogenic influences, we are not certain that the alternative approach significantly improves the overall accuracy of the estimated natural backgroun d conditions, but it certainly does not diminish the accuracy and is likely to improve our estimates of baseline conditions. Finally, MANE-VU has considered the fact that the u niform rate of progress that results from these calculations is a relatively arb itrary baseline against which progress is measured. This Haze Rule requires states to consid er this uniform rate, but control decisions are to be based on a four-factor analysis that is independent of the uniform rate of progress. The relatively small differences in th e uniform rate that are introduced as a result of using the alternative approach further di minish the significance of this decision. Based on all of the considerations above, MANE-VU r ecommends adoption of the alternative approach for use in 2008 MANE-VU SIP su bmittals, active participation in further research efforts on this topic, and future reconsideration of natural background visibility conditions as evolving scientific unders tanding warrants.Baseline and Natural Background Visibility Conditio ns Page 13



## References

Ames, R. B., and Malm, W. C., Recommendations for N atural Condition Deciview Variability: An Examination of IMPROVE Data Frequen cy Distributions. Proceedings (CDROM) of A&WMA/AGU Specialty Conference on Region al Haze and Global Radiation Balance -- Aerosol Measurements and Model s: Closure, Reconciliation and Evaluation , Bend, Oregon, 2-5 October, 2001.

Hand, J.L. and W.C. Malm, Review of the IMPROVE Equation for Estimating Ambie nt Light Extinction Coefficients , on the IMPROVE web site at http://vista.cira.colostate.edu/improve/Publication s/GrayLit/gray_literature.htm , 2005.

Haywood, Ramaswamy, and Soden, Tropospheric aeroso l climate forcing in Clear-Sky Satellite Observations over the oceans, Science , V 283 , pg. 1299-1303, 26 February, 1999.

Hegg, Livingston, Hobbs, Novakov and Russell, Chem ical Apportionment of aerosol column optical depth off the Mid-Atlantic coast of the United States, Journal of Geophysical Research , vol. 102, No. D21, pg. 25,293-25,303, 1997.

IMPROVE, Malm, W. C., Principal Author, Spatial and Seasonal Patterns and Temporal Variability of Haze and Its Constituents in the Uni ted States: Report III , Cooperative Institute for Research in the Atmosphere, Colorado State University, Ft. Collins, CO, May, 2000.

Kumar, N. Recommendations for Natural Background Co nditions and Potential Refinements, Proceedings (CDROM) of MANE-VU/MARAMA Science Meeti ng on Regional Haze – Organic Aerosols and Natural Backgr ound Conditions , MARAMA Baltimore, MD, 27-29 January, 2004.

Lowenthal, D. H., and Kumar, N. PM2.5 Mass and Ligh t Extinction Reconstruction in IMPROVE. Journal of the Air and Waste Management Association , Vol. 53, pp. 1109- 1120, 2003.

Malm, Molenar, Eldred and Sisler, Examining the rel ationship among atmospheric aerosols and light scattering and extinction in the Grand Canyon area, Journal of Geophysical Research , vol. 101 , No. D14, pg. 19,251-19,265, 1996.

Malm, Day, Kreidenweis, Light Scattering Characteri stics of Aerosols as a function of Relative Humidity: Part 1- A comparison of Measured Scattering and Aerosol Concentrations Using the Theoretical Models, Journal of the Air and Waste Management Association , Vol. 50 , pg. 686-700, May 2000.

U.S. EPA, Guidance for Estimating Natural Visibility Conditio ns under the Regional Haze Rule , EPA-454/B-03-005, September, 2003a.Baseline and Natural Background Visibility Conditio ns Page 14

U.S. EPA, Guidance for Tracking Progress under the Regional H aze Rule , EPA-454/B03-004, September, 2003b.

Ryan, P.A., Lowenthal, D., and Kumar, N., Improved light extinction reconstruction in Interagency Monitoring of Protected Visual Environm ents, J. Air & Waste Manage. Assoc. 55 , 1751-1759, 2005.

Trijonis, J. C., Characterization of Natural Backgr ound Aerosol Concentrations, Appendix A in Acidic Deposition: State of Science and Technology. Report 24. Visibility: Existing and Historical Conditions -- Causes and Ef fects, J. C. Trijonis, lead author, National Acid Precipitation Assessment Program, Was hington, DC, 1990.