Connecticut Regional Haze 

State Implementation Plan November 2009 

ATTACHMENT K 

MANE-VU Natural Background Visibility Conditions
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A P P E N D I X X X . 

N AT U R A L BAC KG RO U N D 

V I S I B I L I T Y C O N D I T I O N S 

CONSIDERATIONS AND PROPOSED APPROACH TO THE CALCULATION 

OF NATURAL BACKGROUND VISIBILITY CONDITIONS AT MANE-VU

CLASS I AREAS
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NATURAL BACKGROUND VISIBILITY CONDITIONS 

1. INTRODUCTION 

The long-term visibility conditions that would exist 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 must be considered when setting reasonable progress goals for each mandatory Federal 

Class I area subject to the Regional Haze Rule. Baseline visibility conditions – based on 

monitored visibility during the five year baseline period (2000-2004) – and estimated natural 

background visibility conditions will determine the uniform rate of progress to be considered 

when setting reasonable progress goals for any Class I site. 

The U.S. Environmental Protection Agency (EPA) issued draft methodological 

guidelines for the calculation of natural background and baseline visibility conditions at each 

site as well as methods for tracking progress relative to the uniform rate of progress that 

these values determine. This draft guidance, issued in September 2001 was subsequently 

finalized in September 2003. The final guidance recommends a default method 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 that may be poorly represented by the default 

method. 

This appendix provides a description of the default method for calculation of natural 

background conditions. In addition, the default method is applied to each Class I area in or 

near the MANE-VU region in order to establish default natural background conditions on the 

twenty percent best and worst days. A discussion of potential refinements to the default 

method is presented along with rationale for their consideration. The uncertainty associated 

with each potential refinement is then considered in the context of the overall uncertainty of 

the default estimates. Finally, a recommendation for estimating natural visibility conditions 

to be included in this SIP is provided. 

Based upon these analyses, as well as comments received on the draft MANE-VU 

proposal, it appears that while some aspects of the default calculation method are 

understood well enough that they could be considered as potential refinements, MANE-VU 

does not feel these refinements are warranted in light of the very large uncertainties 

associated with the most basic elements of the default estimates (naturally occurring ambient 

concentrations). The identified refinements would result in substantial differences relative to 

default estimates without significantly improving the accuracy of our estimate relative to the 

default. Rather, MANE-VU advocates a proposed approach that is based on use of the 

default estimates while a program of research is undertaken to refine those elements which 

are most uncertain (natural concentrations) in order to reduce the overall uncertainty as 

better scientific understanding of these issues evolves. Refinements to other aspects of the 

default method (e.g. refinements to the assumed distribution or treatment of Rayleigh 
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APPENDIX XX June 10, 2004 

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extinction, inclusion of sea salt, and improved assumptions about the chemical 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 specific approach and will be 

reconsidered at a later point. 

2. THE DEFAULT METHOD 

The default method is explained in detail in Estimating Natural Background Visibility 

Conditions (U.S.EPA, 2003). Summary information is provided here but the reader should 

consult the original guidance documents for any question as to how this method is applied. 

Estimates of natural visibility impairment due to fine and coarse particles were derived 

using the 1990 National Acid Precipitation Assessment Program reported average ambient 

concentrations of naturally present particles (Trijonis, 1990). Separate concentration values 

were given for the Eastern and Western United States, no finer spatial resolution is available. 

Average natural background light extinction due to particles was then calculated using the 

IMPROVE methodology and site specific ANNUAL f(RH) values. Worst visibility levels are 

derived using the work of Ames and Malm (2001), who estimated the standard deviation of 

visibility in deciviews in the eastern US 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 90th (10th) percentile level which is taken by EPA to be 

representative of the mean of the twenty percent worst (best) conditions. 

Thus in the East, the default method for calculating best and worst natural background 

visibility conditions (in deciviews) for any area in the Eastern U.S. would use the following 

formulae: 

P90 = HI +1.28 sd 

P10 = HI – 1.28 sd 

Where The Haze Index (HI) represents annual average visibility in units of deciview and 

sd is the standard deviation of daily average visibility values throughout a year, defined by 

the guidance as 3.0 for the Eastern U.S. The Haze Index is calculated as shown: 

HI =10 ln (bext/10) 

where the atmospheric extinction, bext, is given by the familiar IMPROVE equation 

(IMPROVE, 2000) in inverse megameters: 
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bext = (3)f(RH)[sulfate] + (3)f(RH)[nitrate] + (4)[OMC] + (10)[LAC] + 

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

Thus with respect to potential refinements to the default method, three primary 

approaches can be considered: refinements to the mass estimates (including spatial and 

temporal allocation as well as addition of other important species), refinement to the relative 

humidity adjustment factors (including averaging times and addition of adjustment factors 

Table 1. Default Parameters Used in Calculating Natural Background Visibility for Sites in 

the Eastern U.S. 

Parameter Value Fractional 

Uncertainty

Reference/Comments 

[SULFATE] 0.23 μg/m3 200% Trijonis, 1990 

[NITRATE] 0.10 μg/m3 200% Trijonis, 1990 

[OC] 1.0 μg/m3 200% Trijonis, 1990 

[LAC] 0.02 μg/m3 250% Trijonis, 1990 

[SOIL] 0.50 μg/m3 200% Trijonis, 1990 

[CM] 3.0 μg/m3 200% Trijonis, 1990 

f(RH) ~3.2 15% Varies by site (see Table 2) 

Organic multiplier 1.4 50% [OCM]=1.4*[OC] 

σS/N 3.0 m2/g 33% Hegg, 1997; IMPROVE, 

2000; Malm, 2000 

σOC 4.0 m2/g 30% Hegg 1997; Trijonis 1990 

σEC 10.0 m2/g 40% Malm, 1996 

σsoil 1.0 m2/g 25% Trijonis, 1990 

σcoarse

0.6 m2/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 

10th, 90th percentile 

adjustment 

1.28 15% Regulation calls for mean of 

top twenty percent, not 90th

percentile 

Parameters used in 

potential refinements 

 

[NaCl] ~0.5 50% Varies by site, IMPROVE 

σNaCl 2.5 m2/s 16% Haywood, 1999 

f(RH)NaCl ~3.2 33% Assumed same as S, N 

Note: the mass estimates presented above are based are on estimates of fine particulate 

concentrations that would exist in absence of any manmade pollution (including Mexican and 

Canadian emissions) consistent with planning requirements 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. 

Table 1. Default Parameters Used in Calculating Natural Background Visibility for Sites in 

the Eastern U.S. 

Parameter Value Fractional 

Uncertainty

Reference/Comments 

[SULFATE] 0.23 μg/m3 200% Trijonis, 1990 

[NITRATE] 0.10 μg/m3 200% Trijonis, 1990 

[OC] 1.0 μg/m3 200% Trijonis, 1990 

[LAC] 0.02 μg/m3 250% Trijonis, 1990 

[SOIL] 0.50 μg/m3 200% Trijonis, 1990 

[CM] 3.0 μg/m3 200% Trijonis, 1990 

f(RH) ~3.2 15% Varies by site (see Table 2) 

Organic multiplier 1.4 50% [OCM]=1.4*[OC] 

σS/N 3.0 m2/g 33% Hegg, 1997; IMPROVE, 

2000; Malm, 2000 

σOC 4.0 m2/g 30% Hegg 1997; Trijonis 1990 

σEC 10.0 m2/g 40% Malm, 1996 

σsoil 1.0 m2/g 25% Trijonis, 1990 

σcoarse

0.6 m2/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 

10th, 90th percentile 

adjustment 

1.28 15% Regulation calls for mean of 

top twenty percent, not 90th

percentile 

Parameters used in 

potential refinements 

 

[NaCl] ~0.5 50% Varies by site, IMPROVE 

σNaCl 2.5 m2/s 16% Haywood, 1999 

f(RH)NaCl ~3.2 33% Assumed same as S, N 

Note: the mass estimates presented above are based are on estimates of fine particulate 

concentrations that would exist in absence of any manmade pollution (including Mexican and 

Canadian emissions) consistent with planning requirements 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. 
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for species assumed to be non-hydroscopic), and refinement to the assumed distribution of 

visibility conditions throughout the year (including the width, amplitude and potentially 

shape of the distribution). Potential refinements are considered in section 4. 

Table 1 below provides the default values to be applied 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 (the average of 11 Northeastern U.S. sites) default estimated 

visibility in the Northeastern U.S. is approximately 3.6 dv on the twenty percent best days 

and 11.3 dv on the twenty percent worst days. 

3. APPLICATION OF THE DEFAULT METHOD 

The Class I areas in the MANE-VU region that are subject to the requirements of the 

regional haze rule are: Acadia National Park, Maine; Brigantine Wilderness (within the 

Edwin B. Forsythe National Wildlife Refuge), New Jersey; Great Gulf Wilderness, New 

Hampshire; Lye Brook Wilderness, Vermont; Moosehorn Wilderness (within the 

Moosehorn National Wildlife Refuge), Maine; Presidential Range – Dry River Wilderness, 

New Hampshire; and Roosevelt Campobello International Park, New Brunswick. In 

addition to these Class I areas, we consider several nearby Class I areas where MANE-VU 

states may be contributing to visibility 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 River Face Wilderness in Virginia. MANE-VU understands that it is the 

responsibility of the appropriate VISTAS states to establish estimates of natural visibility 

conditions and reasonable progress goals for these areas. It is anticipated, however that 

subsequent consultations will occur with those MANE-VU states which may be affecting 

visibility in these areas. MANE-VU has therefore calculated estimates of natural background 

visibility conditions at the nearby sites using MANE-VU approved methods in order to 

facilitate future consultations. 

The only factor in the default method that varies by site is the climatological annual mean 

relative humidity adjustment factor. Table 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 using the default method is purely a function of 

differences in climatological annual mean relative humidity, with southern and coastal sites 

being more humid than inland or elevated sites. 
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4. POTENTIAL REFINEMENTS 

According to the guidance (U.S. EPA, 2003), “... the 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.” However, 

the guidance does leave the door open for individual states or RPOs to adopt their own 

methods for calculating natural background if they can demonstrate that the change from 

Table 2. Site Specific Relative Humidity Adjustment Factors, Best and Worst (Default) 

Estimates of Natural Background Visibility 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 11.32 
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the default represents a significant refinement that better characterizes natural visibility 

conditions at a specific Class I site. 

The five Regional Planning Organizations have identified a number of areas for potential 

improvement and have hired a contractor to refine the understanding of natural background 

levels of particulates. The statement of work for this project (managed by the WRAP) 

includes the following text: “There are three broadly different ways to refine the default 

natural aerosol concentrations that are briefly discussed in the guidance document. The 

default annual estimates of species concentrations for the best and worst 20% haze 

conditions can be replaced by better annual estimates, by seasonally varying estimates, or by 

event-specific estimates (e.g. in the case of forest fire and dust storm impacts). Any 

technically defensible combination of these different ways to refine the natural aerosol 

concentration is acceptable. It is likely that refinement will be a multi-step process over a 

period of many years as the information required to justify changes are developed and 

reviewed.” The three methods of refinement noted in this statement of work, mirror those 

listed in the guidance, however, the guidance also states that, “states may identify other[ 

refined approaches] that are more appropriate to their own situations.” 

As noted in section 2, in addition to different ways to adjust ambient concentration 

estimates, the relative humidity adjustment factor and the shape of the distribution would 

also affect the resulting estimates of naturally occurring visibility. The VISTAS RPO has 

commissioned a consultant to investigate potential refinements to natural background 

(Tombach, 2003). In addition, a white paper developed by EPRI on this topic and a recent 

presentation by Bill Malm of CIRA (a principal investigator of the IMPROVE program) all 

serve to inform the multitude of ways that calculations for natural background conditions 

could be refined (Malm, 2004; Kumar, 2004). A synopsis of several potential refinements 

and the rationale for their consideration are presented here. For more detailed discussion of 

the scientific merit of each potential refinement, the original references cited above (or those 

contained in the brief explanations below) should be consulted. 

1. Increase the value of the organic multiplier

The estimates of organic carbon mass that are used in the guidance are derived from 

Trijonis (1990), however his original estimate (1.5) has been adjusted to be consistent 

with the ratio of organic carbon mass/organic carbon that is used in the IMPROVE 

program. This value, 1.4, is uncertain and several review articles and studies (Watson 

2002, Turpin and Lim 2001, Malm 2004) have suggested higher values between 1.8 

and 2.1 are more appropriate values. If a higher value were to be used for the 

organic carbon multiplier, the estimate of natural background organic carbon mass 

would be similarly affected since the original Trijonis estimate was based on organic 

carbon, [OC], and a multiplicative factor which relates [OC] to organic carbon mass, 

[OCM]. 

2. Adjust the factor used to translate average visibility conditions into twenty 

percent worst or best conditions 

The guidance recommendation for calculating the twenty percent worst and best 

visibility conditions by multiplying the average by 1.28 times the standard deviation 
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of 3.0 assumes a normal distribution and is designed to return the 90th percentile 

value in that distribution. The Regional Haze Rule requires improvement on the 

average of the twenty percent worst days. This value is not equivalent to the 90th

percentile of a normal distribution. The 92nd percentile is closer to the simple 

average of the top twenty percent of values, if you assume a normal distribution 

(Lowenthal et al., 2003). In this case, a factor of 1.40 is more appropriate for 

calculation of the 92nd percentile, or the mean of the top twenty percent of values. 

However, it is clear that the distributions of visibility conditions at most Class I sites 

are not perfectly normal. In fact, the 90th percentile may be closer to the average of 

the top twenty percent of visibility conditions at sites that do not experience as many 

extreme visibility conditions as a normal distribution would predict (Malm, 2004). 

3. Account for visibility impairment due to sea salt at coastal sites 

Many Class I sites are located along the coast and are significantly affected by coarse 

mode sea salt particles. The tail of the coarse mode sea salt particle size distribution 

is within the sub-2.5 micron size fraction and should properly be included the 

IMPROVE equation. This would be a straightforward refinement if we assume that 

all sea salt is in the form of sodium chloride (NaCl). However, significant evidence 

suggests that a substantial portion of the sodium along the Gulf Coast is associated 

with sodium nitrate (NaNO3

) (Malm, 2004). As sea salt particles age, atmospheric 

chemical processes appear to replace chloride with other ions, altering both the 

chemical composition and the scattering efficiency.

4. Account for hygroscopicity of sea salt 

Research to date reflects a substantial degree of uncertainty regarding the appropriate 

scattering efficiency and hygroscopic growth of sea salt particles. Refined estimates 

hold the potential to significantly change natural background estimates depending on 

assumed composition and concentrations. 

5. Account for organic PM of oceanic origin 

Observational evidence exists to support the hypothesis that significant levels of 

organic precursor gases are emitted over the open ocean which could potentially 

increase the natural background levels of organics, particularly at coastal sites. 

6. Review soil concentrations 

Tombach (2003) suggests that fine soil contributions in the Southeast U.S. are 

underpredicted by the Trijonis estimate of 0.5 ug/m3. He bases this on the 

estimated impact of Saharan dust and Asian dust that are subject to inter-continental 

transport. The contribution of these sources to Northeast and Mid-Atlantic sites is 

estimated to be significantly less than for Southeast and Western U.S. 

7. Account for episodic inter-continental dust contributions 
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In addition to contributing on an annual average basis, the Saharan and Asian dust 

impacts are likely to be highly variable in time and should not necessarily be applied 

on an annual average basis. Given the extreme uncertainty in predicting the 

frequency of occurrence at any specific site, there is no reliable means of estimating 

the temporal frequency for these effects. 

8. Review organic and sulfur emissions from forests 

Observational evidence exists for the tropics (mostly the Amazon River Basin) to 

suggest that the estimated natural background concentrations of organics and sulfur 

compounds may be significantly higher than the Trijonis values in those areas. 

Application of these data to U.S. areas remains highly uncertain and requires further 

research. 

9. Improve estimates of organic and elemental carbon released by natural 

fires 

Global modeling studies have produced estimates for organic and elemental carbon 

released by natural fires that are consistent with the Trijonis estimates used by EPA. 

Nonetheless, these studies as well as the Trijonis estimates remain uncertain and 

could be refined through further research efforts. 

10. Account for inter-continental sulfate and nitrate contributions 

Techniques to account for the fraction of light scattering and absorbing PM that 

results from extra-jurisdictional anthropogenic emissions (i.e. Canada, Mexico, Asia) 

could be developed with the same rough level of uncertainty that is used in the 

current default method for calculating natural visibility conditions. This is less a 

refinement of natural background, however and more of a policy decision as to how 

natural background conditions are defined and what is an appropriate planning goal. 

The definition in statute and planning goal supported by the courts should remain as 

described in EPA guidance. MANE-VU feels that international contributions to 

Class I fine particulate burdens should be considered in setting reasonable progress 

goals, not natural condition estimates. 

11. Use global chemical transport models to refine estimates of natural 

ambient concentrations 

The use of global models will certainly prove to be a useful tool for future research 

into the topic of natural background conditions, but MANE-VU does not feel that 

these tools provide a consistent framework to serve as the basis for a national 

program. The uncertainties within the model structure mirror the uncertainties in 

observational evidence for deducing ambient emission levels of specific PM 

components. 

12. Refine temporal resolution of relative humidity adjustment 

factors/consider observed relative humidity data instead of climatological 

average data. 
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The use of different averaging periods and different relative humidity data certainly 

does affect the resulting estimates of visibility conditions. Climatologically average 

data serves to remove inter-annual variability of humidity from the process of 

tracking progress. This ensures that measured progress is based on changes in 

pollution, rather than meteorological variability. Further research into the most 

appropriate averaging period is still warranted. 

In addition to the many potential refinements listed above, NESCAUM has considered 

one other possible refinement to the default method; the use of a higher Rayleigh scattering 

estimates for coastal sites (12Mm-1 are approximate Rayleigh conditions at sea level; 10 Mm-1

is used for all sites in the IMPROVE equation). 

Of the multitude of ways that natural background visibility conditions could be refined, 

MANE-VU believes that very few can be justified as significantly improving the accuracy on 

the basis of current scientific understanding. That is not to say that MANE-VU feels that 

the default estimates of natural conditions are truly representative of natural conditions at 

each site or that each of the potential refinements listed above does not bear further 

investigation, but rather that alternative methods or values for use in calculating more 

precise values for most of the refinements listed above are not readily available at this time. 

Research into many of the potential refinements above should be continued and MANEVU intends to continue research on many of these questions. However, MANE-VU feels 

that only a very few of these potential refinements can justifiably be considered at this time. 

These include an alternative value for the carbon multiplier, the calculation of the 92nd

percentile of a normal distribution to represent the mean of the top twenty percent worst 

visibility conditions, and the inclusion of sea salt at coastal locations and refined estimates of 

Rayleigh scattering. Calculations were performed to evaluate the effect of these potential 

refinements to better understand the effect of such changes on resulting rates of progress 

and are shown in Tables 3 and 4. 
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Table 3. Default and Refined Estimates of the Twenty Percent Worst Natural Background Visibility 

Conditions at MANE-VU and Nearby Sites. Default values are provided for comparison, estimates 

labeled “[OMC]=[OC]*1.8” are calculated using 1.8 as the organic multiplier, “P90=HI+1.40*sd” values 

are calculated using the 92nd percentile instead of the 90th percentile of the visibility distribution, 

“w/seasalt” values show the effect of adding the measured value of sea salt mass at coastal sites, and

“Rayleigh 12Mm-1” values show the effect of using alternate Rayleigh scattering at coastal sites. 

Assumption tested at MANE-VU 

Mandatory Federal Class I Area 

Default 

Visibility

dv 

[OMC]= 

[OC]*1.8

dv 

P90=HI 

+1.40*sd

dv 

w/ 

sea salt 

dv 

Rayleigh 

12 Mm-1

dv 

Maine 

Acadia National Park 11.45 12.17 11.81 12.87 12.34 

Moosehorn Wilderness 11.36 12.09 11.72 12.88 12.26 

Roosevelt Campobello International 

Park, New Brunswick 

11.37 12.09 11.73 12.88 12.27 

New Hampshire 

Great Gulf Wilderness 11.30 12.03 11.66 

Presidential Range – Dry River 

Wilderness 

11.30 12.03 11.66 

New Jersey 

Brigantine Wilderness 11.28 12.01 11.64 13.40 12.19 

Vermont 

Lye Brook Wilderness 11.25 11.99 11.61 

Nearby Mandatory Federal Class I 

Areas 

 

Virginia 

James River Face Wilderness 11.26 11.99 11.62 

Shenandoah National Park 11.27 12.00 11.63 

West Virginia 

Dolly Sods Wilderness 11.32 12.05 11.68 

Otter Creek Wilderness 11.32 12.05 11.68 
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Table 4. Estimated baseline visibility conditions,† Uniform Rates of Progress (ROP) to be considered 

for first implementation period, and Effect of Natural Background Refinements on ROP at MANE-VU 

and Nearby Sites. “1.8*OC” values are the percent change in uniform progress (relative to the default

ROP) resulting from the substitution of the 1.8 carbon multiplier, “1.4*sd” values are the percent 

change in uniform progress when the 92nd percentiles are used to represent the average of the worst 

twenty percent visibility conditions, “sea salt” values are the percent change in uniform progress when 

extinction due to measured sea salt at coastal sites is included and “Rayleigh” values are the percent

change in uniform progress when 12Mm-1 of Rayleigh extinction is used at sea-level sites.

MANE-VU Mandatory Federal Class I 

Area 

Baseline 

Visibility

dv 

Default 

ROP 

dv/14 yrs

1.8*[OC] 

%change

1.40*sd 

%change

sea salt 

%change

Rayleigh 

%change

Maine 

Acadia National Park 22.86 2.66 -3.9% -3.2% -6.7% -6.0% 

Moosehorn Wilderness 21.53 2.37 -3.8% -3.5% -8.9% -6.5% 

Roosevelt Campobello International 

Park, New Brunswick 

21.53 2.37 -3.8% -3.5% -8.9% -6.5% 

New Hampshire 

Great Gulf Wilderness† 

Presidential Range – Dry River 

Wilderness†

 

New Jersey 

Brigantine Wilderness‡ 27.92 3.88 -2.5% -2.2% -10.5% -4.7% 

Vermont 

Lye Brook Wilderness 24.24 3.03 -4.1% -2.8% 

Nearby Mandatory Federal Class I Area 

Virginia 

James River Face Wildernessп 28.41 4.00 -2.4% -2.1% 

Shenandoah National Park‡ 27.55 3.80 -2.8% -2.2% 

West Virginia 

Dolly Sods Wilderness 27.72 3.83 -3.1% -2.2% 

Otter Creek Wilderness 27.72 3.83 -3.1% -2.2% 

†

 Note that EPA guidance requires at least 3 complete years out of 5 to calculate baseline conditions. Routine year-round monitoring did 

not begin at Camp Dodge (IMPROVE site for Great Gulf/Presidential Range) until June 2000 so estimates of baseline conditions (and 

thus a uniform rate of progress) will not be possible for these sites until data are available through June 2003. 

‡

 Only 4 years of data was used in the calculation of estimated baseline conditions and uniform rates of progress at these sites since 1998 

did not meet completeness criteria at these sites. 

п Only 3 years of data was used in the calculation of estimated baseline conditions and uniform rates of progress at this site since 1998 
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APPENDIX XX June 10, 2004 

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The uniform rate of progress as determined by baseline and natural background 

conditions is most sensitive to absolute changes in natural background estimates (as opposed 

to baseline conditions), given the logarithmic structure of the haze index. For example, using 

data from Brigantine Wilderness Area 1999-2002 (a four year period that overlaps, but does 

not correspond to the baseline period as described by EPA guidance) the default estimate 

for baseline visibility conditions is 27.92 dv. If sea salt is included in the reconstructed 

extinction calculation, the baseline estimate increases by 0.24 dv to 28.16 dv. Changes in 

natural background resulting from the addition to sea salt at Brigantine are from 11.28 to 

13.40 dv, a difference of 2.12 dv. The end result is a decrease of approximately 10.5 percent 

in the required rate of progress slope during the initial period. Although the annual rate 

decreases by less than 0.03 dv/year, the change over the course of 14 years is 4 tenths of a 

deciview which is a substantial difference. The estimated impact of adding sea salt to 

Brigantine has the largest effect of any of the refinements considered here, thus all 

refinements considered (on an individual basis) have less than 10.5 percent impact on the 1st

period progress goal. 

While the changes in the rate of progress resulting from these refinements are 

substantial, the decision to refine baseline conditions must be based on whether the 

refinements are statistically significant. In order to meet that test, a potential refinement must 

alter the rate of progress to the point that the refined value lies outside the range of 

uncertainty of the default value. To implement refinements that do not meet this test would 

result in new values that are substantially different, but not significantly more accurate. 

Very large uncertainties are associated with most of the parameters that go into the 

default natural background calculation and many of the potential refinements. For example, 

In the case of a change to the organic multiplier, different values ranging from 1.4 to 2.1 or 

higher have been proposed, however the uncertainty bounds of these estimates are large 

and overlapping (i.e. most estimates are within the uncertainty bounds of the others and thus 

are not statistically different). 

In the case of sea salt, it certainly represents an improvement in accuracy to include a 

term for sea salt scattering when we know it to exist. Given the potential for complex 

chemical interaction of sodium and chlorine with other components of particulate matter, 

estimates of uncertainty are difficult to quantify and large (on the order of 50 percent). 

While estimated values that would be appropriate for MANE-VU coastal Class I sites are 

statistically different from zero, the resulting improvement in the overall accuracy of the final 

natural visibility estimates relative to the default estimates must be calculated using standard 

error propagation techniques. 

Following standard error propagation techniques (Taylor, 1982), estimates of the 

contribution of each parameter (see table 1) to the overall accuracy of natural extinction 

estimates have been derived. The fractional contribution of each parameter to total 

extinction is presented in Figure 1 for coastal and inland sites in the MANE-VU region. As 

this figure demonstrates, the overwhelming, dominant contributor to the accuracy of the 

estimate of total extinction is the uncertainty in organic carbon mass. 
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Because of the logarithmic relationship between extinction and deciview, the standard 

error propagation techniques do not apply simply to the resulting estimate of natural 

background deciview. The high and low error bounds for the extinction estimate do not 

translate into an equivalent fractional uncertainty of the resulting deciview estimate. To 

account for this, Figure 2 presents a range of contributions to the final natural background 

visibility in units of deciview. The two estimates of fractional contribution are based on 

estimates of extinction that correspond to the high and low error estimates of the extinction 

calculation. Following standard error propagation techniques again, (Taylor, 1982) these two 

distinct estimates of uncertainty associated with the extinction calculation are then compared 

to the uncertainty in assumptions regarding the shape of the distribution of natural visibility 

conditions in units of deciview. Figure 2 presents the relative contribution of each 

component for both the high and low estimates of extinction. A reasonable estimate for the 

contribution of each component would, therefore, lie somewhere between these two 

estimates, but we have no reliable way to determine exactly where. Due to the nature of the 

logarithmic relationship, the lower estimate is more sensitive to small changes than the upper 

range of uncertainty, so the true contribution is probably closer to the “high” estimate than 

the “low” estimate, but cannot be quantitatively determined in an easy way. 

Figure 1. Relative contribution to overall uncertainty of natural background visibility extinction at

MANE-VU Class I Areas. Several potential refinements that have been proposed are highlighted in red 

in the legend. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Coastal Inland

EC dry extinction

soil dry extinction

f(RH)

EC mass

NaCl dry extinction

coarse dry extinction

S/N dry extinction

soil mass

NaCl f(RH)

OC dry extinction

NaCl Mass

Rayleigh

N mass

OCM factor

coarse mass

S mass

OC Mass
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Based on this general review of uncertainties associated with the refinements and the 

potentially substantial effect on rate of progress slopes that could result from implementing 

such changes, it is appropriate to accept the default natural background visibility estimates as 

provided in U.S. EPA guidance. The default estimates provide a sound, nationally consistent 

framework on which to base the regulatory structure of the haze rule that is justified based 

upon the current state of scientific understanding of these issues. 

Further, EPA recommendations on potential refinements (Pitchford, personal 

communication, 2004) suggest that such refinements be broadly accepted by the scientific 

community, substantial, practical to implement and not create arbitrary inconsistencies. In 

addition, these recommendations request that state efforts to refine the default estimates 

should not side-track technical efforts on other aspects of the regional haze program. 

Hence, it is appropriate to adopt the default natural background conditions at present time 

until broad consensus on refined estimates of the individual species concentrations (in 

particular, organic carbon) is established. 

Figure 2. Range of relative contribution to overall uncertainty in natural background deciview estimates 

(high and low extremes derived using extreme values of extinction range) 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

high extreme low extreme

Standard deviation

92nd vs 90th percentile

Uncertainty in extinction
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5. RECOMMENDATION 

This document reviews potential refinements to EPA guidelines for calculating natural 

background visibility conditions and explores how such refinements are likely to affect 

calculated rates of progress. Based on the currently available literature on naturally 

occurring fine particulate matter over the coastal and continental U.S. and a detailed analysis 

of the error propagation of such refinements on the resulting estimates of natural visibility 

conditions, changes to the default methods for calculating these conditions will not be 

undertaken by MANE-VU at this time. 

MANE-VU recognizes the simplicity of the default approach and supports future 

adjustments which better reflect true natural background visibility levels as the science 

surrounding this issue evolves and more accurate information is available to support such 

changes. In particular, efforts to reduce the uncertainties associated with estimates of organic 

carbon, sulfate and coarse mass are most important to pursue through future research 

activities aimed at improving estimates of natural visibility conditions. Potential refinements 

investigated in this document including the addition of sea salt, revision of the organic 

carbon multiplier and improved understanding of the distribution of naturally occurring 

visibility conditions rank as a second tier set of priorities to be addressed through future 

research. 

Based on this review, MANE-VU proposes to adopt the default estimates at this time, to 

actively participate in further research efforts on this topic, and to reconsider our position 

with respect to natural background visibility conditions as future scientific understanding 

warrants. 

References 

Ames, R. B., and Malm, W. C. (2001). Recommendations for Natural Condition Deciview 

Variability: An Examination of IMPROVE Data Frequency Distributions. Proceedings 

(CDROM) of A&WMA/AGU Specialty Conference on Regional Haze and Global 

Radiation Balance -- Aerosol Measurements and Models: Closure, Reconciliation and 

Evaluation, Bend, Oregon, 2-5 October. 

Day, Malm, Kreidenweis Aerosol Light Scattering Measurements as a Function of Relative 

Humidity JAWMA 50: 710-716 May 2000 

Eldred, Feeney, Wakabayashi The Major Components of PM2.5 at Remote Sites across the 

United States V1 of AWMA Proceedings of an International Specialty Conference Jan 1998 

Long Beach CA pp13-26 

Haywood Ramaswamy and Soden SCIENCE V283 26Feb99 1299-1303 Tropospheric 

aerosol climate forcing in Clear-Sky Satellite Observations over the oceans. 

Hegg, Livingston, Hobbs, Novakov and Russell JGR vol. 102 D21 P25293-303 1997 

Chemical Apportionment of aerosol column optical depth off the Mid-Atlantic coast of the 
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United States 

IMPROVE, (2000), Malm, W. C., Principal Author, Spatial and Seasonal Patterns and 

Temporal Variability of Haze and Its Constituents in the United States: Report III. 

Cooperative Institute for Research in the Atmosphere, Colorado State university, Ft. Collins, 

CO. May. 

Kumar, N. (2004). Recommendations for Natural Background Conditions and Potential 

Refinements. Proceedings (CDROM) of MANE-VU/MARAMA Science Meeting on 

Regional Haze – Organic Aerosols and Natural Background Conditions, Baltimore, MD, 27-

29 January. 

Lowenthal, D. H., and Kumar, N. (2003). PM2.5 Mass and Light Extinction Reconstruction 

in IMPROVE. Journal of the Air and Waste Management Association, Vol. 53, pp. 1109-1120. 

Malm, Molenar, Eldred and Sisler Examining the relationship among atmospheric aerosols 

and light scattering and extinction in the Grand Canyon area JGR V101 D14 pg19251-65 

1996 

Malm, Day, Kreidenweis, Light Scattering Characteristics of Aerosols as a function of 

Relative Humidity: Part 1- A comparison of Measured Scattering and Aerosol 

Concentrations Using the Theoretical Models. JAWMA 50:686-700 May 2000 

Malm, W. C. (2004). Recommendations for Natural Background Conditions and Potential 

Refinements. Proceedings (CDROM) of MANE-VU/MARAMA Science Meeting on 

Regional Haze – Organic Aerosols and Natural Background Conditions, Baltimore, MD, 27-

29 January. 

U.S. EPA (2003). Guidance for Estimating Natural Visibility Conditions under the Regional 

Haze Rule. EPA-454/B-03-005. September. 

Taylor, J. R. (1982). An Introduction to Error Analysis, University Science Books, Oxford 

University Press, Mill Valley, CA. 

Tombach, I., 2003. On Refining Estimates of Natural Background Light Extinction in the 

VISTAS Region, A report prepared for VISTAS, December 04. 

Trijonis, J. C. (1990). Characterization of Natural Background Aerosol Concentrations. 

Appendix A in Acidic Deposition: State of Science and Technology. Report 24. Visibility: 

Existing and Historical Conditions -- Causes and Effects. J. C. Trijonis, lead author. National 

Acid Precipitation Assessment Program, Washington, DC. 

Turpin, B. J., and Lim, H-J. (2001). Species Contributions to PM2.5 Mass Concentrations: 

Revisiting Common Assumptions for Estimating Organic Mass. Aerosol Science and Technology, 

Vol. 35, pp. 602-610. 

 
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Watson, J.G. (2002). Visibility: Science and Regulation. J. Air Waste Manag. Assoc., 52, 628-

713.