PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

EXECUTIVE SUMMARY AND CHAPTER 1 
Executive Summary 

INTRODUCTION 

This report is prepared in response to the requirements of Section 169A(a) of the 

Clean Air Act. In this section, which was added to the Act in August 1977, Congress 

established as a national goal “the prevention of any future and the remedying of any 

existing impairment of visibility in mandatory class I Federal areas*, which impairment 

results from man-made air pollution.” The Act requires a study and report to Congress 

on methods for meeting the visibility goal, including methods for determining visibility 

impairment, modeling and other methods for evaluating source impacts, methods for 

preventing and remedying pollution-derived visibility impairment, and a discussion of 

pollutants and sources that may impair visibility. In addition to this report, the Act 

requires the following activities: 

1. The Department of the Interior, in consultation with other Federal Land Managers, 

must compile, and the Environmental Protection Agency (EPA) must promulgate, a 

list of mandatory class I Federal areas in which visibility is an important value. The 

list, which includes 156 of the 158 class I areas, was promulgated in November 1979, 

and is included as Appendix A to this report. 

2. EPA must promulgate regulations that (a) provide guidelines to the States on 

appropriate techniques for implementing the national visibility goal through State 

Implementation Plans (SIPs) and (b) require affected States to incorporate into their 

SIPs measures needed to make reasonable progress toward meeting the national 

visibility goal. The regulations and guidelines must require that certain major 

stationary sources, likely to impair visibility, install best available retrofit technology 

(BART). The regulations must also require that the SIPs include a long-term (10-15 

year) strategy for making reasonable progress toward the visibility goal. The longterm strategy may require control of sources not otherwise addressed by the BART 

provision. The Act states that costs, energy and non-air environmental impact, and 

other factors must be considered in determining BART and reasonable progress. 

The language of the national visibility goal and the legislative history of the Act 

indicate that the national goal of Section 169A mandates, where necessary, control of 

both existing and new sources of air pollution. It is apparent, however, that adverse 

visibility impacts from proposed major new or modified sources are to be dealt with 

through the procedure for prevention of significant deterioration (PSD) mandated in 

Section 165(d) of the Clean Air Act. 

In addition to the activities required of EPA and the States, the Clean Air Act requires 

that the Federal Land Managers (the Department of Interior and Department of 

Agriculture, through the National Park Service, the Fish and Wildlife Service, and the 

Forest Service) play an important role in visibility protection. Land Manager 

responsibilities include reviewing the adequacy of the state visibility protection strategies 
and determining whether proposed major air pollution sources have an adverse impact on 

visibility in Class I areas. 

In establishing the national visibility goal, Congress called for explicit recognition of 

the value of visibility in special class I areas. By requiring consideration of “significant” 

impairment in BART decisions, “adverse” effects of proposed new sources, and 

“reasonable progress” in implementing the national goal, Congress has, in effect, 

mandated that judgements be made on the value of visibility in the context of specific 

decisions on control and location requirements for sources of visibility impairing air 

pollution. Preliminary economic studies of the value of visibility and research in 

recreational psychology and human perception support the notion that visibility is an 

important value in class I areas and suggest that several approaches are available for 

estimating the value of an incremental improvement or deterioration in visibility. Such 

work, however, will require a number of years. Currently, the regulatory process 

mandated under the Clean Air Act, involving the Federal Land Managers, the States, 

EPA, and the public, represents the best means for considering visibility benefits in the 

context of associated costs. 

 

DEFINITION OF VISIBILITY IMPAIRMENT 

Although Congressional guidance on the definition of visibility impairment is 

significant, a number of important areas are left open for additional specification, 

interpretation, and judgement. Section 169A indicates that visibility impairment includes 

reduction in visual range and atmospheric discoloration. Visual range, long used as an 

index of visibility in airport observations, is generally defined as the farthest distance 

from which one can see a large black object against the horizon sky. Atmospheric 

discoloration can qualitatively be defined as a pollution-caused change in the color of the 

sky, distant mountains, clouds, or other objects. Conceptually, virtually any type of 

visibility impairment could ultimately be expressed as a reduction in visual range or 

atmospheric discoloration. However, because these effects are often the results of the 

same pollution impact, it is useful to categorize anthropogenic* visibility impairment into 

three general types: (1) widespread regionally homogeneous haze that reduces visibility 

in every direction from an observer, (2) smoke, dust, or colored gas plumes that obscure 

the sky or horizon relatively near sources (this class is also termed “plume blight”), and 

(3) bands or layers of discoloration or veiled haze appearing above the surrounding 

terrain. Examples of these types of impairment are illustrated and discussed in Section 

1.5. 

The location, degree, and the spatial and temporal extent of visibility impairment must 

be addressed in the visibility protection programs. In areas such as the Southwest, 

anthropogenic air pollution occurring outside class I area boundaries can obscure long 

distance vistas normally visible from within the class I area. Anthropogenic impairment 

may be frequent, last for long time periods, and be readily apparent to all observers. 

Conversely, anthropogenic visibility impacts may be so infrequent, short in duration, or 

small in degree that it is difficult for the unaided observer to distinguish them from 

existing impairment caused by natural sources. For the purpose of this report, EPA 

adopts the following position on visibility impairment: 
1. Certain vistas extending outside class I area boundaries are important to visitor 

experience and are part of the visibility value of the area. Such views should be 

included in the national goal. 

2. Anthropogenic visibility impairment in the context of the national visibility goal is 

defined as any perceptible** change in visibility (visual range, contrast, atmospheric 

color, or other conveniently measured visibility index) from that which would have 

existed under natural conditions. 

Therefore, in the context of specific control decisions, an increment (or decrement) in 

visibility impairment must as a minimum be perceptible to be significant or adverse. 

Further judgements with respect to the significance and adversity of perceptible 

impairment must be made, at least in part, on a case-by-case basis and must address the 

degree and spatial and temporal extent of the incremental change. For this reason, and 

because such judgements must involve States, Federal Land Managers, and the public, it 

is not possible at this time to specify comprehensive criteria for defining significant or 

adverse impairment. 

 

CURRENT STATUS OF VISIBILITY IN CLASS I AREA 

Some insight into general visibility condition in class I areas can be obtained by 

examining the regional airport visibility (visual range) data depicted in Figure 1. 

Although some limitations in airport observations exist, the information is indicative of 

regional trends. The best visibility occurs in the mountainous Southwest, where annual 

median visibility exceeds 70 miles (110 km). East of the Mississippi and south of the 

Great Lakes annual median visibilities are less than 15 miles (24 km), and significantly 

lower in the summertime. Figure 1 does not address plume blight or discoloration. 

Ironically, these latter problems can be more severe in “clean” regions. For example, in 

the Southwest, the region of highest visual range, visible plumes can be seen from great 

distances. 
 

Figure 1. Visual range (V) isopleths for suburban non-urban areas, 1974-76 

(Trijonis and Shapland, 1978). 

A preliminary analysis of visibility in class I areas has been provided by the Federal 

Land Managers. The analysis represents observations by individual managers of visual 

impairment and their subjective judgements on the desirability or acceptability of existing 

conditions. Because the level of experience, perception, and criteria for judgement vary 

significantly among these individuals, the results are preliminary and must be confirmed 

by more detailed analysis. The results are summarized in Figure 2. Class I areas are 

grouped into regions of similar status. In regions where a number of areas were reported 

as having undesirable visibility conditions, the major categories reported by the Land 

Managers are listed. 

Approximately one-third of the class I area managers reported undesirable visibility 

conditions and/or the need to evaluate suspected man-made impacts. The remaining twothirds of the areas were reported as having desirable or acceptable conditions at all or 

more of their vistas. On the other hand, it appears that few if any of the class I areas are 

free from at least some potentially observable anthropogenic visibility influence. Over 

90 percent of the class I area managers reported that one of more views from within the 

area looking outside the area may be, to some degree, important. Nearly all of the 

managers indicated the need to prevent existing visibility conditions from deteriorating as 

a result of new source impacts. 

;0 "..ltes IJ

15 miles

25 miles

1\5 miles

v : 25 toiles

1/ _ 45 miles

'oJ _ 70 llI;le~

...... . .. . . . ... .

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Figure 2. Preliminary class I area visibility status reposted by Land Managers. 

VISION IN THE ATMOSPHERE 

The ability to define, monitor, model, and control anthropogenic visibility impairment 

is dependent on available scientific and technical understanding of the factors that affect 

atmospheric visibility. Because visibility involves the human perception of the physical 

environment, evaluation of the effects of air pollution on visibility must include: 

1. Specification of the process of human visual perception and 

2. Quantification of the impacts of air pollution on the optical characteristics of the 

atmosphere. 

Chapter 2 summarizes pertinent information on these areas. 

From a scientific and technical point of view, deterioration of visual air quality is 

probably the best-understood and most easily measured effect of air pollution. However, 

many important uncertainties and limitations exist in available knowledge. Significant 

implications of current understanding of vision in the atmosphere may be summarizes as 

follows: 

1. Visibility impairment is caused by the scattering and absorption of light by suspended 

particles and gases. Fine solid or liquid particles (atmospheric aerosols) and to a 

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_ SOM GENERALLY DESIRABLE E UNDESIRABL VISIBILITY

_ FREQUENT UND E CONDITIONS ESIRABLE CO . _. NDITIONS
lesser extent nitrogen dioxide are the most important anthropogenic causes of 

degraded visual air quality. Air molecules, weather variables, and natural emissions 

also affect visibility. 

2. Light scattering and light absorbing pollutants reduce the amount of light received 

from viewed objects and scatter ambient or “air” light into the line of sight. This 

scattered air light is perceived as haze. Because these effects vary with the 

wavelength of light, discoloration can result. 

3. These effects can be quantified or approximated through use of theoretical 

mathematical treatments and experimentally derived pollutant/optics relationships. 

4. The perceptibility of pollution effect on light depends on human eye-brain responses. 

Studies of the eye-brain response to contrast indicate that typical observers can detect 

a 0.02 (2%) or greater contrast between large dark objects and the horizon sky. 

Preliminary studies suggest that observers may be able to detect a 0.02 to 0.05 change 

in apparent contrast caused by incremental pollution. Roughly, this indicates that a 

reduction in visual range of as little as 5 percent may be perceptible. Additional work 

is needed on human perception of pollution increments. 

5. The perception of color in the atmosphere is less well understood than is contrast. 

For this reason, theoretical calculations of atmospheric discoloration are useful only 

as crude indices and guides for experimental measurements. Studies of atmospheric 

color perception conducted over the next few years should provide an adequate means 

of predicting atmospheric discoloration, even if a comprehensive theoretical treatment 

remains unavailable. 

6. In many Southwestern class I areas, visibility on some days can approach the 

theoretical limit imposed by air molecules (blue sky) scattering (200 miles visual 

range). Visibility in such areas is extremely sensitive to in creased emissions. The 

addition of 1 microgram per cubic meter of fine particles, spread throughout the 

viewing path, to such a clean atmosphere could reduce visual range by about 30 

percent. Addition of the same amount to a dirtier background (20-mile visual range) 

would produce only a 3-percent reduction in visual range. 

7. Since viewing distances in most class I areas do not exceed 50-100 kilometers (60 

miles), a reduction in calculated visual range from, for example, 200 km (120 miles) 

to 150 km (90 miles) would be noticed principally because of the reduction in 

contrast and discoloration of nearby objects and sky (haze). Increased haze causes 

objects to appear "flattened," the horizon sky is whitened, and the aesthetic value of 

the vista can be degraded even though the viewing distances are small relative to the 

visual range. 

8. When particles and light absorbing gases are confined to an elevated haze layer or a 

coherent plume, the main visual impact will be a discoloration of the sky or a white, 

gray, or brown plume. The perceived impact depends on a number of factors such as 

sun angle and condition of background sky. Contrast and brightness effects of 

elevated haze and plumes can be approximated by available techniques. Additional 

work is needed to predict the perceived color impacts. 
MONITORING 

Visibility monitoring is necessary for establishing base line visibility to be used in 

evaluating impacts of proposed sources or controls, assessing the relative impacts of 

man-made air pollution and natural sources, identifying specific sources contributing to 

visibility impairment, and monitoring the effectiveness of visibility protection programs. 

Meeting these objectives requires measurement of optical parameters, meteorological 

variables, pollutant characteristics, and scenic characteristics. 

The most important optical parameters to be measured include the apparent contrast of 

distant objects and the extinction coefficient, a parameter related to the light scattering 

and absorption characteristics of the atmosphere. The basic optical methods include: 

Human Observation  measures perceived air quality, visual range (if targets 

available) 

Photography  documents perceived visual air quality 

Multiwavelength Telephotometer  measures apparent contrast between target and 

horizon or other objects, is useful over long path, up to 50 to 100 kilometers 

Transmissometer  measures transmission and extinction of light over a fixed path, 

10 to 20 kilometers 

Nephelometer  measures light scattering by particles at a single point, estimates 

Extinction coefficient 

Each of these measurement approaches has inherent strengths and limitations, which 

are summarized in Chapter 3. EPA recommends that comprehensive visibility 

monitoring programs in class I areas include: 

1. Baseline monitoring conducted for a year (preferably a meteorologically typical year) 

or more; 

2. Visibility monitoring including color photography, human observation, integrating 

nephelometer, and a multi-wavelength telephotometer; and 

3. Evaluation of anthropogenic and natural source/receptor relationships including a 

two-stage size-segregating particulate sampler or other device compatible with fine 

particulate mass and compositional analysis, meteorological measurements, and when 

necessary, a nitrogen dioxide monitor. 

Such comprehensive monitoring is not needed in all class I areas. The results of 

intensive monitoring in characteristic regions of the country and instrument development 

over the next few years may indicate some smaller set of measurements, which will be 

sufficient. Programs with limited resources should rely on structured human observations, 

photographic documentation, and, where possible, suitable meteorological measurements. 

Other instruments should be chosen with due consideration of their limitations. 
EMPIRICAL METHODS FOR ASSESSING POLLUTION-DERIVED 

IMPAIRMENT 

Relating visibility impairment to its emission sources is a central problem for making 

progress towards the national visibility goal. Some important general understandings 

include: 

1. Light scattering and particle related light absorption are caused principally by fine 

aerosols (those smaller than 2.5 micrometers). Understanding the sources of general 

haze in most areas thus reduced to identification of sources of fine particle mass. 

2. High relative humidity significantly increases light scattering of certain water-soluble 

aerosols. 

3. Much of the fine particle mass is of secondary origin; that is, most fine particles are 

formed in the atmosphere from their "precursor" gases, sulfur oxides, nitrogen oxides, 

and organics. Hence, the emission rate of secondary particles cannot be measured at 

he source. Furthermore, the gas-to-particle conversion process depends on factors 

such as solar radiation, the presence of other pollutants, and humidity. Thus, the 

amount of secondary material formed from a given rate of precursor gases is not 

constant but depends on the environment. 

4. The residence time of fine particles in the atmosphere is through to be about a week 

or more, and their transport distance can exceed 500 kilometers. 

5. The long-range transport of the fine particle/precursor chemical complex results in 

the superposition and chemical interaction of emissions from different types of 

sources (e.g., power plant and urban plumes). Many of these interactions currently 

cannot be adequately predicted on a regional scale. 

6. The qualitative evaluation of source receptor relationships will require collection and 

analysis of monitoring data. Properly calibrated mathematical models are necessary 

to predict the impact of controls on existing sources or the impact of new sources in a 

new location. 

Empirical approaches to evaluation source impacts range from simple observation of 

visible plumes to sophisticated aircraft sampling and satellite imagery. The approaches 

discussed in Chapter 4 include: evaluation of haze chemical composition, analysis of 

historical trends of emissions and haziness, evaluation of haze/wind-direction 

relationships, aircraft plume sampling, and application of diagnostic models. Important 

conclusions from application of these techniques to date include: 
1. Direct measurements and statistical analysis indicate that fine sulfate aerosols account 

for 30 to 60 percent of fine particle related visibility reduction in areas as diverse as 

the Northeast United States, Los Angeles, and the Southwest mountain states. 

2. Other fine particle constituents are also important and can dominate scattering in 

various regions. IN the Pacific Northwest, for example, carbon-containing aerosols 

from wood or other vegetative burning and motor vehicles appear to be significant 

components of light scattering aerosols. 

3. Studies of trends in eastern airport visibility indicate that, while wintertime visibilities 

improved in some northeastern locations, overall eastern visibility declined. Summer, 

often the season of best visibility in the early fifties, is currently the worst season. 

From 1948 to 1974, summertime haze (extinction) increased by more than 100 

percent in the central Eastern States, 50 to 70 percent for the Midwest and Eastern 

Sunbelt States, and by 10 to 20 percent for the New England area. Although the 

results of airport surveys should be viewed with caution, the results are consistent 

from site to site. 

4. Very close parallels have been noted between the geographical/seasonal features of 

airport visibility trends and the geographical/seasonal features of trends in 

atmospheric sulfate concentrations, sulfur oxide emissions, and coal use patterns. 

These parallels provide strong circumstantial evidence that the historical visibility 

changes in the East were caused, at lest in part, by trends in sulfate concentrations and 

sulfur oxide emissions. 

5. Similar analyses of visibility trends in the Rocky Mountain Southwest, a region 

containing numerous class I areas, indicate a gradual decline in visibility with a recent 

improvement, so that current levels are similar to those in the late forties. A strong, 

statistically significant association exists between these visibility trends and regional 

sulfur oxide emissions from copper smelters. The increase in visibility from 1972 to 

1976 paralleled significant decreases in smelter emissions due to pollution controls 

and decreased production. Although the statistical studies do not show causality, the 

results are consistent with theory and experimental results 

6. During a nine-month copper smelter strike, significant increases in Southwestern 

visibility and decreases in sulfate concentrations were noted at great distances from 

the smelters. Notably, sulfates dropped by about 60 percent at the Grand Canyon and 

Mesa Verde, 300 to 450 kilometers from major smelter locations. 

7. Aircraft measurements of the plumes of large power plants, smelters, and major urban 

areas have tracked the visibility impact of these sources to 50 to 200 kilometers 

downwind. The apparent transformation of SO2 to light scattering sulfate has been 

observed in both Eastern and Western plumes. 
8. Episodes of regional scale haziness have been observed in the Eastern United States. 

Examination of airport data, pollution measurements, and satellite photography 

indicate that these hazy air masses move across the Eastern United States in the 

manner of high-pressure systems, causing significant visibility reductions in areas 

with little or no air pollutant emissions. 

PREDICTIVE MODELS 

Although empirical approaches can be used to identify the impact of manmade air 

pollution, predictive models are necessary to evaluate the effects of alternative controls 

on existing sources and the potential impacts of proposed new sources. Visibility models 

adapt the atmospheric dispersion and transformation features of other air pollution 

models for the prediction of fine particles and NO2 concentrations across a sight path. 

The concentration patterns are coupled with optical equations to predict visibility 

impacts. Visibility models deal with essentially two distance and time scales: transport of 

plumes from single sources for short to moderate distances (10 to 100 km) and regional 

scale transport of single and multiple sources over medium to long range distances (100 

to over 500 km). 

Important uncertainties in visibility models include: 

1. Prediction of atmospheric dispersion characteristics becomes less reliable as distance 

from the source increases. Mountainous and hilly (complex) terrain, common near 

class I areas, poses a particularly difficult analytical problem. Nevertheless, because 

concentration across a sight path and not at a single point is the important parameter, 

visibility models can be somewhat less sensitive to dispersion assumptions than are 

conventional air quality models. 

2. The chemical transformation and removal processes for sulfur and nitrogen oxides 

have been experimentally estimated, but are difficult to predict under varying 

environmental conditions. 

3. The models are sensitive to base line visibility conditions. Until monitoring programs 

provide data for class I areas, base line conditions must be derived from rough 

estimates. 

4. The models are subject to the uncertainties in current understanding of human visual 

perception and the optical characteristics of modeled air pollutants. 

5. An incomplete understanding of large-scale meteorological processes, uncertainties in 

boundary conditions, and lack of adequate inventories of natural and anthropogenic 

emission sources significantly limit modeling of regional scale transport of pollutants. 
6. Visibility models have generally not been verified through intensive environmental 

monitoring. Major experimental efforts are under way to confirm the theoretical 

predictions. 

Despite these uncertainties, visibility models can and should, within certain limits, be 

used to evaluate point source impacts. Single source models can estimate the range of 

expected visibility impacts of primary particle emissions at distances of up to 50 to 100 

kilometers from the source. These models can also be used for relatively isolated sources 

located in clean environments to provide rough estimates of the impacts of sulfur and 

nitrogen oxide emissions at similar distances. Thus, the degree of visibility improvement 

resulting from controls on major, obvious sources of plume blight can be predicted, and 

the visibility impacts of proposed major facilities can be addressed. In the case of new 

sources proposing to locate within 100 to 150 kilometers of class I areas, an analysis of 

prevailing meteorological conditions, background visibility, and application of available 

single source plume models can provide an improved basis for siting decisions. 

Models for evaluating the impact of control of existing or proposed sources on a 

regional scale require further refinement and validation before they can be used for 

regulatory applications. Empirical data analyses coupled with mathematical modeling 

exercises are useful for identifying the scales of time and distance upon which visibility 

impact may occur. Roughly, changes in the regional emissions of fine particles and 

sulfur oxides will produce changes in regional visibility levels, although the extent, 

duration, and location of these changes as a function of emissions cannot be adequately 

predicted. As noted above, pristine regions such as the Southwest will be most sensitive 

to the addition of new sources or reductions in regional emissions through control. 

MAJOR SOURCES 

Vision in the natural "unpolluted" atmosphere is restricted by blue sky scattering, by 

curvature of the earth's surface and by suspended liquid or solid natural aerosols. The 

important sources of natural aerosols include water (fog, rain, snow), windblown dust, 

forest fires, volcanoes, sea spray, vegetative emissions, and decomposition processes. 

These sources must be addressed in estimating base line visibility in class I areas. The 

extent to which these natural sources control existing visibility levels in the United States 

is not well known. Nevertheless, it is reasonable to conclude that manmade sources 

contribute significantly to visibility impairment in most regions of the country and in 

some cases dominate visibility. 

Anthropogenic emission sources of particulate matter, sulfur oxides, nitrogen oxides, 

and volatile organics are of some significance to visibility impairment. The significance 

of volatile organics (hydrocarbons), however, is not well understood. Major sources, 

projected growth, and controls are discussed in Chapter 6. The most important source 

categories of visibility-impairing pollutants include utilities, industrial fuel combustion, 

smelters, pulp mills, urban plumes (the result of point sources, space heating, mobile and 

other urban sources), fugitive dust from agricultural activities, mining, unpaved roads, 
off-road recreational vehicles, and the managed use of fire including prescribed burning 

associated with forestry and agricultural burning. The significance of these sources on an 

individual and collective basis varies throughout the country. Many of them are not 

readily amenable to further control. 

CONTROL STRATEGY IMPLICATIONS 

The results of the preliminary Federal Land Manager analysis of visibility in class I 

areas provide important implications for control programs. These include: 

1. Few, if any, of the class I areas are currently free from some anthropogenic influence 

on visibility. Given resource limitations and the lack of adequate information on 

impairment, however, those areas with current or projected unacceptable visibility 

conditions should receive highest priority in control programs. If, as preliminary 

subjective Land Manager judgements suggest, current visibility is generally 

acceptable in two-thirds of the class I areas, there will be little impetus for completely 

eliminating perceptible man-made impairment. This appears to be consistent with 

Congressional intent. 

2. Protection of integral views extending outside class I areas is important for a number 

of class I areas. A number of managers reported, however, that the haze occurring in 

large urban areas are visible from some vantage points within the class I area. It is 

not clear that Congress intended to remedy these kinds of visibility impairment. 

Case-by-case judgements can address these issues. 

3. The kinds of sources that tend to dominate visibility impairment vary greatly 

throughout the country. Visibility control programs must account for the diverse 

nature of sources. Particularly difficult problems include regional haze in the Eastern 

United States, regional emissions in the Southwest, the impact of urban plumes, and 

prescribed burning activities. The Land Managers themselves utilize fire as a means 

for enhancing the production of timber, improving wildlife habitats, and preventing 

catastrophic natural fires. Such activities impair visibility on a temporary basis. 

4. Assessment of existing visibility conditions and projected growth indicate that the 

highest priority for visibility protection programs in class I areas is the evaluation of 

the impacts of new sources of visibility impairment. Many of the class I areas in the 

Western United States are likely to be influenced by increased energy development 

and utilization, population and urban growth, and associated emission increases. 

Once such sources are constructed, it is very difficult to mitigate their impacts. 

Although available models are limited, they should be used to evaluate new source 

impacts. The alternative allowing construction of new sources without such analyses as 

long as prescribed class I increments are met, is not acceptable. Available scientific 
information supports the contention of the House Committee Report that “mandatory 

class I increments do not protect adequately visibility in class I areas” in all cases. 

Programs for the prevention of significant deterioration will address the impact of 

major facilities on class I area visibility. These requirements, however, do not adequately 

deal with the visibility impacts of increases in emissions associated with population 

growth, such as increased urbanization, automotive emissions, and space heating, or with 

activities such as agricultural growth and highway construction. Additional studies are 

needed to quantify the influence of these activities on visibility before adequate guidance 

can be considered. Control of such sources may ultimately prove to be necessary for 

making progress toward the national goal. 

REGULATORY STRATEGIES 

Conceptually, visibility protection under Sections 169A and 165(d) includes the 

following components: 

1. Proposal and promulgation of visibility regulations and guidelines for the States by 

EPA. 

2. Assessment of class I area visibility by the States, Federal Land Managers, EPA, and 

affected industries. 

3. Judgments on significance and adversity of impairment caused by existing and 

proposed new sources and the need to improve existing conditions in class I areas by 

the Federal Land Managers, States, and EPA. 

4. Development of control strategies by the States, assisted by EPA 

5. Monitoring progress toward the national visibility goal. 

NEED FOR PHASED APPROACH 

Because of the lack of base line visibility data in class I areas, the limitations in 

scientific and technical understanding of source/air quality perception relationships, the 

need to consider visibility improvements in the context of control costs, and limitations in 

resources available to States, EPA, and the Federal Land Managers, EPA recommends a 

phased approach to visibility protection. Although regulations and guidelines for the 

States must encompass the full range of Clean Air Requirements, they should, to the 

extent possible: 
1. Permit State control programs to focus initially on the most clearly defined cases of 

existing impairment and on strategies to prevent future impairment and, 

2. Allow for the evolution of guidelines and control strategies made possible with 

expected improvements in scientific understanding of source/impairment 

relationships. 

Although available information is not adequate to develop control strategies that 

demonstrate ultimate attainment of the national goal, enough is known to develop a series 

of corrective and preventive measures. An evolutionary or phased regulatory approach 

would permit these steps to be taken while delaying those actions for which the technical 

basis is less clear. Moreover, such an approach will allow for a more effective use of the 

limited manpower and financial resources available to States, Federal Land Managers, 

and EPA for developing visibility control programs. 

In the initial phases of visibility protection, application of BART is likely to be limited 

to obvious cases of plume blight or single source haze layers. The BART mechanism 

does not appear to apply to important categories such as prescribed burning, regional 

power plant and smelter emissions, and urban plumes. Evaluation of new source impacts 

should focus on major stationary sources, particularly power plants. The visibility 

impacts of growth of smaller area sources and the effect of regional emission increases 

from numerous sources are not adequately addressed by current PSD procedures. 

 

LONG TERM STRATEGIES 

Because of the limitations in BART and PSD, the eventual development and 

implementation of long-term strategies will be central to making progress toward the 

national visibility goal. These strategies should provide for integration of visibility 

objectives into ongoing air management efforts to account for sources not adequately 

covered by other mechanisms and to explore innovative approaches for making costeffective progress toward visibility protection. 

 

A starting point in developing long-term strategies is evaluation of the impact of other 

air pollution control programs; e.g., standards for air quality, new sources, and mobile 

sources. The projected impact of existing programs on some of the more difficult 

visibility impairment problems is outlined below: 

1. The Southwestern copper smelters have made progress toward reducing emissions, 

partially in response to State programs for attaining the National Ambient Air Quality 

Standards. Although final emission reductions may be deferred, the smelters are 

under compliance schedules, which should ultimately provide additional reductions in 

emissions. Preliminary analyses suggest that reductions to date in smelter emissions 

have resulted in improved regional visibility in the Southwest since 1972. 
2. Air quality standards and new source performance standards have halted the general 

trend toward increased sulfur oxide, particulate, and organic emissions in the Eastern 

United States. The recently announced new source standard for power plants 

represents a significant long-term strategy for an ultimate reduction in Eastern sulfur 

oxide emission levels and a limitation on regional increases in the Western United 

States. This approach, however, will not begin to effect significant reductions in 

emissions in the East until after 1995. Accelerated replacement of older uncontrolled 

oil-fired power plants with coal-fired boilers meeting the new source performance 

standard under energy initiatives would accelerate the reduction in sulfur oxide 

emissions. 

3. Progress toward meeting air quality standards in urban areas should limit increased 

impairment and in some cases improve visibility in areas affected by urban plumes. 

 

Once the effect of other regulations on visibility is evaluated, the need for additional 

control approaches for making progress toward the national goal can be evaluated. 

Potential long-term control approaches, which may prove desirable in the 1980’s, include 

an accelerated reduction in regional haze occurring in the East, maintaining regional 

visibility levels in the Southwest and reducing impacts of forest and other burning in the 

Pacific Northwest. Such approaches must be justified on a technical basis and on a 

consensus that the improvements are worth the effort. The States and EPA should 

consider a variety of innovative regulatory strategies for implementing long-term 

visibility improvement strategies. Some of these include a national secondary air-quality 

standard for fine particles and economic control approaches, including marketable 

permits, emission fees, and other economic incentives for improved practices. 

VISIBILITY RESEARCH NEEDS 

Extension and refinement of visibility protection programs are dependent on 

improvement of current knowledge and techniques in a number of areas. The most 

important areas include: 

1. Comprehensive characterization of existing visibility conditions in representative 

regions containing class I areas. 

2. Development of improved and simplified visibility monitoring approaches. 

3. Field studies of selected single and multiple point and area source impacts. 

 

4. Improvements in predictive models for single sources and for regional scale transport. 

5. Studies of human visual perception in clean atmospheres. 
6. Studies of the value of visibility. 

A combination of programs involving government and the private sector is beginning 

to address many of these areas. Significant advances in the next several years should 

enhance our ability to make progress towards the national visibility goal. 
1 INTRODUCTION: ESTABLISHING THE NATIONAL 

VISIBILITY GOAL 

 

1.1 SCOPE OF REPORT 

This report is prepared in response to the requirements of Section 169A(a) of the 

Clean Air Act. In that section, Congress established as a national goal “the prevention of 

any future, and the remedying of any existing impairment of visibility in mandatory class 

I Federal areas which impairment results from man-made air pollution.” (95th Congress, 

1977). The Act requires a study and this report to Congress on available methods for 

implementing the national visibility goal. The report must include “recommendations 

for: 

A. Methods for identifying, characterizing, determining, quantifying and measuring 

visibility impairment in (class I) Federal areas, and 

B. Modeling techniques (or other methods) for determining the extent to which manmade air pollution may reasonably be anticipated to cause or contribute to such 

impairment, and 

C. Methods for preventing and remedying such man-made air pollution and resulting 

visibility impairment. 

Such report shall also identify the classes or categories of sources and the types of air 

pollutants which, alone or in conjunction with other sources or pollutants may reasonably 

be anticipated to cause or contribute significantly to impairment of visibility” (95th

Congress, 1977). 

This chapter will discuss the establishment of the national visibility goal, including the 

requirements of the Clean Air Act, the importance of visibility in class I areas, and the 

definition and nature of visibility impairment. 

Chapter 2 will review fundamental scientific concepts related to human perception of 

light, atmospheric optics, and the means by which man-made air pollutants affect visual 

air quality. The discussion emphasizes those pollutants that are most important in 

causing visibility impairment, fine particulate matter (sulfates, “primary” particles, 

organics, and nitrates) and nitrogen dioxide. 

Chapters 3 through 5 discuss and make preliminary recommendations on methods for 

assessing visibility and relating impairment to sources. Chapter 3 outlines techniques for 

monitoring visibility. The discussion focuses on operating principles and possible 

utilization of human observers, photography, telephotometers, nephelometers, and 

particulate monitoring devices. Existing and planned visibility monitoring networks are 

also outlined. Chapter 4 reviews the application of several approaches for relating 
visibility impacts to man-made sources of air pollution. The methods include chemical 

element balance, statistical studies of air quality, emissions, and visibility trends, 

diagnostic models, and other empirical approaches. Chapter 5 discusses available 

mathematical models for evaluating visibility impacts of major sources and assessing 

alternative controls and siting. 

Natural and anthropogenic sources of visibility impairment are discussed in Chapter 6. 

The general location, impacts, projected growth and possible controls and costs are 

discussed for major anthropogenic source categories. 

Chapter 7 discusses prospects for making progress toward the national goal. A 

preliminary summary of current class I area visibility status as reported by the Federal 

Land Managers is presented, key implications of the preliminary summary are discussed, 

and considerations for developing alternative visibility control strategies are outlined. 

Chapter 8 summarizes ongoing visibility-related research efforts and makes 

recommendations for future research. 

1.2 STATUTORY REQUIREMENTS AND LEGISLATIVE HISTORY 

The Clean Air Act Amendments of 1977 add Section 169A to the Clean Air Act, 

requiring the following activities of the Federal Government: 

1. The Department of Interior, in consultation with other Federal Land Managers, 

must review all mandatory class I Federal areas and identify those where visibility 

is an important value of the area. The EP A Administrator, after consulting with 

Interior, must promulgate a list of mandatory class I Federal areas in which he 

determines visibility is an important value. The list has been promulgated and is " 

included as Appendix A to this report. 

 

2. EPA must prepare this report to Congress on methods for meeting the visibility 

goal, including methods to identify visibility impairment, modeling, and other 

methods for evaluating source impacts, methods for preventing and remedying 

pollution related visibility impairment, and a discussion of pollutants and sources 

that may impair visibility. 

3. EPA must promulgate regulations which will (a) provide guidelines to States on 

appropriate techniques and methods for implementing Section 169 requirements 

through the State Implementation Plans (SIP) where needed, and (b) require SIPs 

for affected States to include emission limits, schedules for compliance, and other 

measures as may be necessary to make reasonable progress toward meeting the 

national visibility goal. 

These regulations must require sources which have been in operation less than 15 

years as of August 1977 and which emit any air pollutant that may reasonably be 

anticipated to impair visibility in the selected class I areas to procure, install, and operate 

the best available retrofit technology (BART) no later than 5 years after SIP approval. 
The regulations must also require that the SIPs include a long-term (10 to 15 years) 

strategy for making reasonable progress toward the visibility goal. The long-term strategy 

may require control of sources older than 15 years or sources not otherwise controlled 

under the BART provisions. BART must be determined for each source by the State (or 

Administrator, in some cases). In the case of a fossil fuel-fired generating power plant 

having a total generating capacity of least 750 MW, the emission limitations (BART) 

must be determined pursuant to EPA guidelines. Guidelines for determining BART must 

take into consideration the costs of compliance, the pollution control technology in use at 

the source, the remaining useful life of the source, and the degree of improvement in 

visibility that may reasonably be anticipated to result from the use of such technology. 

BART can be expressed as an emission limit or operating practice and must be 

incorporated into a revised State Implementation Plan. 

Enactment of the visibility section of the Clean Air Act was stimulated by public 

concern about the deterioration of visibility in scenic areas. Examination of the legislative 

history of the visibility provision indicates that Congress was particularly concerned 

about evidence submitted by the National Parks and Conservation Association, stating, 

"that some areas that in the past had 100-mile (160-km) visibility now have only an 

average of 30-mile (48-km) visibility. Much of this probably can be attributed to 

emissions from power plants, such as the Navaho and Four-Corners plants." (House 

Report, 1977). In addition to the recognized threat of power plants to long-range visibility 

in the western United States, Congress was concerned about reports that "the hazes found 

in high vegetation areas of the southeast are not dominated by natural organic compounds 

but by sulfate particles, probably from the oxidation of SO2 emitted from regionally 

distributed sources. " (House Report, 1977). 

As stated in the Conference Report (1977), "a major concern which prompted the 

House to adopt a visibility protection provision was the need to remedy existing pollution 

in Federal mandatory class I areas from existing sources. Issues with respect to visibility 

as an air quality related value and application to new sources are to be resolved within the 

procedures for prevention of significant deterioration. " This statement is clarified in an 

attachment to technical changes to the 1977 Clean Air Act Amendments by Congressman 

Paul Rogers: " ...it does not state or imply that existing sources were the only 

concern...new sources were also 1-2 of concern. This point is underscored by the 

statutory language of Section 169A(a)(I), retaining as a national goal: the prevention of 

any future impairment. ." (Rogers, 1977). With respect to new-sources, Section 

165(d)(2)(B) of the Clean Air Act makes it clear that the Federal Land Manager 

responsible for the management of class I area(s) "shall have an affirmative responsibility 

to protect the air quality related values (including visibility) of any such lands within a 

class I area and to consider, in consultation with the Administrator, whether a proposed 

major emitting facility will have an adverse impact on such values.” Thus, the national 

goal of Section 169A applies to both existing and new sources; implementation includes 

both 169A(a) and 165(d). 

 Congress noted that the current national ambient air quality standards were not 

adequate to protect visibility in class I areas. Congress also recognized that, as a matter of 
equity, it would be impractical to require the same national ambient air quality standard 

for visibility protection in cities such as New York or Los Angeles as for areas such as 

the Grand Canyon or Yellowstone National Park (House Report, 1977). In requiring an 

analysis of the visibility values in various class I regions before determining whether 

visibility protection would be required, Congress recognized that it might be 

unreasonable to have uniform visibility objectives even for all national parks or other 

class I areas. 

1.3 IDENTIFICATION OF CLASS I AREAS 

Mandatory class I areas are defined by the Clean Air Act as including all international 

parks, national wilderness areas, and national memorial parks exceeding 5,000 acres and 

national parks exceeding 6,000 acres. Such areas that were in existence when that Act 

was passed may not be redesignated. The original 158 class I areas are depicted in Figure 

1-1. The Department of the Interior used an II-step process for applying criteria to 

determine whether visibility is an important value in each of these areas. The areas were 

examined with respect to the following: 

1. Legislation establishing the area and authorizing the boundaries to determine 

whether protection of visibility was intended in designating the area a park or a 

wilderness area; 

2. Importance and character of scenic values; 

3. Degree of visual impairment from known natural sources (e.g., fog, terpene haze). 

The resulting list (see Appendix A) of 156 areas in which visibility is an important 

value was transmitted to EPA by the Secretary of the interior in February 1978 (Andrus, 

1979). EPA reviewed the Department of Interior analysis and, after proposal and public 

comment, promulgated the same list of156 areas in November of 1979 (Blum, 1979, 

Costle, 1979). 

The 156 areas include 36 national parks, one international park, one national memorial 

park, and 118 wilderness areas. The total area protected includes over 29 million acres 

throughout 37 States and territories of the United States. The lands are managed by the 

Departments of Interior and Agriculture through three Federal land managing services; 

the National Park Service (45 class I areas), the Fish and Wildlife Service (23 class I 

areas), and the U.S. Forest Service (88 class I areas). Although the need to preserve 

scenic character for recreational and/or aesthetic reasons is common to all 156 areas, 

there are additional objectives that vary with area and land managing agency. Some of 

these objectives include maintaining and enhancing wildlife habitat, preserving important 

archeological sites and national monuments, and maintaining areas in a wilderness 

condition. 

In addition to listing the areas in which visibility is an important value, the National 

Park Service, the Fish and Wildlife Service, and the Forest Service have each conducted a 
preliminary analysis of the visual values potentially impaired by air pollution. The 

analysis specifies the more important vistas associated with the area, tentatively identifies 

apparent natural and anthropogenic sources of impairment, and provides preliminary 

subjective judgments of the status of visibility in the area. This preliminary analysis is 

summarized in Chapter 7. 
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25

1.4 THE VALUE OF VISIBILITY IN CLASS I AREAS 

1.4.1 Background 

The value of the "wilderness experience” and the importance of preserving our 

natural heritage have long been recognized in the United States (Grasvenor, 1979). For 

example, the National Park Service Act of 1916 created the National Park Service, 

directing it to "conserve the scenery and the natural (objects) and provide for the 

enjoyment of the same in such manner and by such means as will leave them 

unimpaired..." (Andrus, 1978). 

In establishing the national visibility goal, Congress called for explicit recognition of 

the value of visibility in these special (class I) areas. In requiring consideration of 

"significant" impairment, "adverse" effects and "reasonable progress" in implementing 

the goal, Congress has, in effect, mandated judgments on the value of visibility in the 

context of specific decisions on control and location requirements for sources of visibility 

impairing air pollution. The Department of Interior has taken the first step in valuing 

visibility by specifying the 156 class I areas in which visibility is an important value. 

Because of their key role in implementing the national goal, the Federal Land Managers 

have also initiated a number of activities to assist in making visibility value judgments for 

control and siting decisions. The following discussion of the concept of the value of 

visibility and some value measurement techniques is largely based on a workshop 

supported by the Forest Service, National Park Service, and Bureau of Land Management 

held in February 1979 on the subject of the Social Values of Visibility (Fox, Loomis, and 

Greene, 1979). 

1.4.2 Establishment of Visibility Values: Overview 

A major challenge in establishing visibility values is to develop ways to measure 

quantitatively visibility impairment as perceived by the human eye. Recent research on 

environmental quality indices has developed procedures for relating such indices to 

measurable quantities. Craik (1979) outlines the steps required based on soliciting 

opinions from users of “visibility” in class I areas. A successful perceived environmental 

quality index must relate the human perceived experience to a physical setting, and the 

experience should be integral to or typical for that setting. Peterson's (1979) discussion at 

the visibility values conference serves as a prototype for relating visibility to the more 

comprehensive human experience of a class I area. The Park Service in their brochure 

entitled "My Eyes Need a Good Stretching" (NPS, 1978) attempted to summarize this 

relationship between visibility and experience by relating the views of artists, humanists, 

and scientists on the subject of visibility degradation. 

Establishing visibility values must, therefore, involve relating the whole visual 

experience to indices such as visual range, contrast transmittance, and color alteration. 

Such human visual experiences might be protected by different levels of these visibility 

related parameters in different locations. Although the visual experience is a significant 

component of, for example, visits to both the Grand Canyon and Great Smoky National 
26

Parks, protection of that experience might require different magnitudes of visibility 

protection for each area. Both the perception of anthropogenic impairment and visibility 

related values are likely to vary from location to location. 

It is difficult to estimate the number of people who are affected by class I area 

visibility. The numbers of scenic area users are rather high; for example, estimated visitor 

days in 1978 for all Park Service management units are approximately 277 million and 

for Forest Service Wilderness areas 7 .6 million visitor days. The Park Service collected a 

total of approximately $17 million in entrance and use fees in the same year (Fox, 1979). 

Research done in 1966 suggests that approximately $1 per visitor day is an appropriate 

estimate of the economic benefit of recreation. (Beardsley, 1970). This estimate is of 

course, subject to considerable inflation by 1979. These numbers provide an indication 

that direct use of class I areas is high and significant economic impacts are involved. 

Forest Service estimates on various forms of dispersed recreation use suggest a minimum 

of 50 percent and a maximum of 250 percent increase over current use in the next 50 

years (Fox, 1979). Since a prime philosophy in the preservation of wilderness and 

establishment of parks is not the concept of use but rather the concept of preserving the 

existence of unique areas for the benefit of society at large, the value of visibility in class 

I areas is greater than that suggested by current use estimates alone. 

Although the value of visibility may prove to be intangible, it is conjectured that it is 

to some extent quantifiable (can be identified as a discrete point on a scale) and, hence, 

can be generalized for display to the public. Given the lack of consistent units for the 

evaluation of aesthetic qualities such as visibility, values can be categorized according to: 

1) economic criteria, the dollar cost/benefit associated with visibility, 2) psychological 

criteria, the individual need and benefits resulting from visibility and 3) social/political 

criteria, community opinions and attitudes held in common with regard to visibility. 

Preliminary results of past studies in each of these areas and suggestions for future work 

are discussed below. 

1.4.2.1 Economic Criteria - Economists have made some progress toward quantifying the 

values of visibility using dollars as the measure. While in the market place, the market 

value or price reflects marginal value; total value can be estimated from revealed 

consumer preference either in a market or market like simulation. 

The economic value of visibility can be broken into sub-categories, depending on the 

nature of benefits anticipated. These anticipated benefits or values could be classified as 

activity, option, and existence benefits. One may be willing to pay $X to actually visit the 

Grand Canyon without any visibility impairment (an activity value), $Y for keeping the 

Grand Canyon's visibility sufficiently clear so that one might enjoy it in the future (an 

option value) and $Z simply to know that the Grand Canyon will never have degraded 

visibility (an existence value). 

The principal approach to economic evaluation of visibility has been the "iterative 

bidding technique." Brookshire (1979) explains the iterative bidding technique as "a 
27

direct determination of economic values from data which represent responses of 

individuals to contingencies posited to them via a survey instrument. " 

The iterative bidding technique in the current form was first developed and applied by 

Randall et al. (1974 a, b) in the Four Corners region of the Southwest. Three 

contingencies were considered: (a) limited visibility reductions and a view of a power 

plant with limited visible emissions; (b) moderate emissions from the plant, moderate 

visibility reductions and moderate existence of unreclaimed soil bank and transmission 

lines; and (c) extensive emissions, visibility reductions and unreclaimed soil bank and 

transmission lines. Given this selection of scenarios, the results cannot be disaggregated 

into component values for visibility, power plant location, and unreclaimed soil banks 

and transmission lines. Employing a sales tax vehicle, the yearly mean bids were $85 (a 

to c) and $50 (b to c) per household. No bias tests were conducted in this experiment. 

 

The Lake Powell experiment (Brookshire et al., 1976) addressed the potential 

visibility reduction from the proposed Kaiparowits power plant, which would have 

impaired the scenic vistas of the Glenn Canyon National Recreation Area. An estimate 

using the iterative bidding techniques was obtained for the aggregate visitor willingness 

to pay to prevent construction of the proposed Kaiparowits power plant. One of the 

principal motivations for the study in addition to the Kaiparowits power plant issue was 

an attempted replication of a subset of the Randall study results. Three scenarios depicted 

by verbal description and picture sets were employed in the Lake Powell experiment 

where visibility and plant sitting varied from best (a) to worst (c). The study tested for 

strategic bias in the bidding procedure and concluded that the bias was not prevalent in 

this experiment. Using entrance fees as a vehicle, the aggregate marginal willingness to 

prevent one additional power plant near Lake Powell was over $700,000. Employing the 

bids and considering the assumptions and structure of the experiment, an indication of 

worth via the preferences expressed in the study of the canyon lands of southeastern Utah 

can be obtained. Extrapolating to recreation areas within a hundred mile radius, the 

aggregate bid for a similar visibility reduction would be up to $20 million per year 

(Brookshire, 1979). 

The Farmington experiment (Blank, et al., 1978) attempted to value visibility in the 

Four Corners Region of the Southwest. The study had three principal goals which 

represented extensions of the previous experiment: (1) to attempt to link visible range and 

the valuation measures, (2) to develop a theoretical cross check for the iterative bidding 

process and (3) to systematically test for a vehicle, starting point and information bias in 

the iterative bidding process. Starting point and vehicle bias in varying degrees were 

detected in the results. Later Thayer and Schulze (1977), Brookshire and Randall (1978) 

and Brookshire et al. (1978), biases and found none. Various reasons have been 

suggested as to why only the Farmington experiment encountered multiple biases. One 

possibility is the definition of the "good" being valued was poorly specified. 

 The South Coast Air Basin, California (SCAB) experiment (Brookshire et al., 1978) 

was the first urban test of the iterative bidding technique. The SCAB experiment included 

several improvements in the experimental process. The results of the study did not suffer 
28

from vehicle starting point information or strategic bias. The dollar bid per household per 

month was $29 for a 60 percent improvement in air quality. In addition, the

independently conducted property value study produced the same order of magnitude 

valuation results as the iterative bidding portion. Air quality was partitioned into an 

aesthetic effect, including visibility, and acute and chronic health effects. Utilizing the 

aggregate bids for all sample areas, 22 to 55 percent of the total for aesthetic effects. The 

result suggests that, indeed, the aesthetic component of visibility is a of visibility 

valuation. Furthermore, this result is for an urban area where the preliminary reason for 

residence is not vistas as would be the case upon a visit, for example, to the Grand 

Canyon. One might infer that aesthetics, not health effects, would be the principal 

consideration for scenic national vistas. 

These preliminary studies are subject to a number of uncertainties and limitations. The 

preliminary results largely represent activity values for use of class I areas in view of the 

situations where the iterative approach ate. Option and existence values are more 

complex concepts, which have not been studied for visibility. Moreover, to say that 

visibility is worth, for example, $30 to $80 per annum per household does not convey the 

total magnitude of the visibility issue. There is more to the enjoyment of the visibility in 

the natural can be qualified with dollars. Nevertheless, the economic studies support the 

notion that visibility is an important value in class I areas and in urban areas as well. 

1.4.2.2. Psychological Benefits - There are certain psychological benefits, actual or 

perceived, associated with class I areas which would be foregone if visibility were 

degraded. At the visibility values workshop, the area of psychological benefits received 

considerable attention and a number of research formats address the quantification of 

these benefits. Currently, assessment of the benefits is related or can be derived from 

more general studies. For example, for many years scientists have attempted to measure 

the psychological benefits of outdoor recreation, including enjoyment of scenic vistas 

unencumbered with obvious signs of human development. 

Driver et al. (1979) have identified a number of direct and indirect psychological 

benefits and behavior related to visibility in class I areas. The benefits of viewing a scenic 

vista include a variety of user activities. There are also psychological benefits associated 

with options or existence values. For example, many people wish to preserve the option 

for a clear view into the Grand Canyon. Some derive psychological benefits from just 

knowing that pristine areas exist, even though there is no intention of visiting all or any 

of them. 

Several approaches to quality and quantity psychological benefits were suggested at 

the visibility values et al., 1979). These include: 

1. Scenic Beauty Estimation Index (Daniel, 1979), 

 

2. Psychophysiological Measurements (Ulrich, 1979), 

3. Perceived Psychological Benefits (Driver et al., 1979) and 
29

4. Social Value Estimation (Loomis and Green, 1979). 

Application of these and other techniques of valuing visibility for use in visibility 

protection programs represent a considerable challenge, which will require a number of 

years of research. 

1.4.2.3 Social Benefits - Available economic studies suggest mechanisms for developing 

the value of visibility. The discussion of human perception and psychological benefits 

discussions at the Visibility Values Workshop provide research perspectives and a list of 

very general techniques, which could be employed to estimate psychological benefits of 

scenic vistas and of unimpaired visibility. In one sense, social benefits represent the 

aggregate of individual benefits and any associated disbenefits. In order to resolve these 

extremes, there exists a value seeking system which functions well in practice, namely 

the political process. As noted above, the presence of the visibility provisions in the 

Clean Air Act Amendments suggests that the political process has ascribed significant 

value to the protection of class I area vistas. It has also mandated mechanisms for 

considering visibility benefits and associated societal costs. These decision-making 

mechanisms must involve the Federal Land Managers, States, and the general public. 

Additional research is needed in understanding the economic, psychological, and 

social benefits and costs of class I visibility protection. This research must be tied to 

studies of human perception of various forms of visibility impairment. The results of such 

work will significantly enhance the decision making process. 

 

1.5 Definition of Visibility Impairment 

In establishing the national goal, Congress provided the following guidance on the 

definition of visibility impairment: 

1. Visibility impairment "include(s) reduction in visual range and atmospheric 

discoloration"; 

2. The goal applies to impairment from man-made (as opposed to natural) air 

pollution; 

3. The visibility impairment must be observed from a vantage point within a 

mandatory class I area (as opposed to a vantage point outside a class I area); 

4. The ultimate goal is to remedy or prevent "any" man-made impairment; 

5. In the application of controls or restrictions to pollution from man-made sources 

of impairment, consideration must be given to the "significance" of the 

impairment from existing sources and whether a new source visibility impact is 

"adverse." 

This general guidance is significant, but a number of important areas are left open for 

additional specification, interpretation, and judgment. Examples of visibility impairment, 
30

areas requiring further resolution, and preliminary recommendations are illustrated and 

discussed below. 

1.5.1 Categories of Visibility Impairment (Latimer, et al., 1978) 

Although it may be desirable and useful to classify visibility impairment in a number 

of ways (Charlson et al., 1978; Latimer et al., 1978; Malm, 1979a), virtually any type of 

visibility impairment can ultimately be expressed as a reduction in visual range or 

atmospheric discoloration. Visual range is generally defined as the farthest distance at 

which one can see a large, black object against the sky at the horizon. Airport weather 

observers and others often use the term "visibility" synonymously with visual range. One 

can make subjective evaluations of "visibility" every time objects are viewed outdoors. 

Although large black objects are not generally available for observing and evaluating 

visual range, dark objects such as buildings, television towers, hills, or mountains can be 

viewed against the horizon sky. 

Even if no distant objects are within view, subjective judgments about visual range 

can be made by noting the coloration and light intensity of the sky and nearby objects. 

For example, one perceives reduced visual range if a distant mountain that is usually 

visible cannot be seen, if nearby objects look "hazy" or have diminished contrast, or if the 

sky is white, gray, yellow, or brown rather than blue. In this latter case, both reduced 

visual range and atmospheric discoloration are apparent. 

Atmospheric discoloration, "unlike visual range, has not been routinely defined or 

quantified in traditional pollution programs. Qualitatively, atmospheric discoloration is a 

pollution-caused change in color of the sky, distant mountains, clouds, or other objects. 

This statement implies that some natural or “not discolored” of atmospheric colors can be 

defined. Obvious examples of atmospheric discoloration include hazes associated with 

reduced visual range, distinct haze bands or layers, and visible brown, black, gray, or 

white plumes. 

Because visual range reduction and atmospheric discoloration are often the results of 

the same pollution impact, it is useful to categorize anthropogenic visibility impairment 

into three general types: (1) widespread, regionally homogeneous haze that reduces 

visibility in every direction from an observer, (2) visible smoke, dust, or colored gas 

plumes that obscure the sky or horizon relatively near sources (this class is also termed 

"plume blight,” and (3) bands or layers of discoloration or veiled haze appearing well 

above the surrounding terrain. 

Figure 1-3 shows an example of general haze conditions in the Grand Canyon. As seen 

in this photograph, range is detectable because the distant features of the canyon are 

difficult to distinguish. The contrast between the given object (part of the canyon) and the 

background (the horizon or a more distant terrain feature) is reduced by light scattered 

from particles in the intervening atmosphere. Even if terrain features were not 

discernible, the intensity and coloration of the scattered light would degrade the aesthetic 

quality of the atmosphere. In the Western United States, where most of the class I areas 
31

are located, spectacular scenery is enhanced by generally excellent visibility, which 

makes the colorful terrain features stand out with great clarity. Even in flat areas (e.g., the 

big sky country of the Northern Great Plains), however, a slight reduction in visual range 

or a slight atmospheric discoloration can change what originally appeared to be an 

"infinite" horizon to a white, yellow, gray, or brown horizon. 

Figure 1-4 provides a "before and after" comparison of the impact of regional haze. 

Although the visual range is significantly reduced in 1-4b, the distant mountains are 

visible in both pictures. The most noticeable effect is the overall reduction in contrast and 

detail. 

Near-source visibility impairment or plume blight is illustrated in Figure 1-5. The 

spatial extent of visibility impairment is defined by the dimensions of the plume. The 

plume is visible because the light intensity and color of the plume are different from 

those of the clouds and sky in the background. Because of the resultant relatively sharp 

boundary between the plume and the background, the visual impact on the observer is 

dramatic. Light scattering and absorbing particles are responsible for these impacts. 

Figure 1-6 shows a different kind of plume blight: a coherent brown plume. The 

discoloration in this case may be due to light absorption by NO2 gas and/or particle 

scattering. 

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32

Bands of discoloration (Figure 1-7) can result from the transport and mixing of 

plumes. Airplane travelers are familiar with the noticeable boundary between the more 

polluted "mixing layer" and cleaner upper air. In Figure 1-7, the haze layers are clearly 

visible because of the sharp demarcation line between them and the clean air "sandwich." 

Figure 1-8 shows an example of possible discoloration, the source of which is unclear. 

1.5.2 Causes of Visibility Impairment 

It is obviously important to distinguish the causes of visibility impairment and, in 

particular, whether the cause is natural or anthropogenic. Clearly, Congress has been 

concerned only with anthropogenic visibility impairment. Reducations in visual range 

caused by precipitation, fog, clouds, windblown dust, sand, snow, or "natural" aerosols 

are natural occurrences and cannot be controlled by man. Indeed, some forms of natural 

visibility impairment may contribute to the enjoyment of class I areas. Examples of such 

phenomena are the blue haze of forested areas and the fog and hazes along the California 

and Oregon coast. Natural sources are discussed more fully in Chapter 6. 

1.5.3 Location of Impairment 

The location of visibility impairment is extremely important in terms of visibility 

protection because the national goal states that visibility in class I areas is to be restored 

and protected. It is uncertain whether this definition includes impairment caused by 

pollution outside of a class I area. It is reasonable and consistent with traditional (airport) 

usage to assume that visibility in an area includes the view of unobstructed objects 

located inside and outside of the area. Figure 1-9 shows a visible haze layer surrounding 

Navajo Mountain. The mountain, not in a class I area, is usually visible from Bryce 

Canyon. In EPA's view, important views extending outside the boundaries of class I areas 

are part of the visibility value of the area, and are included in the national goal. This issue 

is discussed further in Chapter 7. 

1.5.4 Degree and Extent of Impacts Constituting Impairment 

Each of the three major categories of visibility impacts can be further specified with 

respect to degree as well as to spatial and temporal extent. Judgments are necessary to 

specify where a pollution impact becomes impairment and whether the impairment is 

significant or adverse. 

The degree of impairment can be characterized by the reduction in visual range from 

some reference value, by a reduction in contrast between an object and the horizon sky at 

a known distance from the observer, or by a shift in coloration or light intensity of the sky 

or distant objects, such as clouds or terrain features, compared to what is perceived on a 

"clear" day. In all cases, the magnitude of visibility impairment can be characterized by 

the change in light intensity or coloration of an object (or part of the sky) compared to 

that of some reference object. For example a distant mountain is visible because the 

intensity and coloration of light from the mountain is different from that of the horizon 

sky. Another example is a plume or haze layer seen against the background sky or terrain 
33

features. The pollution is visible (perceptible) only if the light intensity or coloration of 

the plume contrasts with that of the surrounding sky or terrain. 
34

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35

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37

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oll!l4t If III1M" ,·rulu.tl I ... pedfif'(1 M_hn. 197WJoIl.
38

The spatial extent of visibility impairment is important to both the perception and the 

significance of impairment to observers in class I areas. The sensitivity of an observer to 

brightness and color differences between objects depends on the spatial relationship 

between the objects. If each of the objects is uniformly colored and there is a sharp line of 

demarcation between the objects, such as when a mountain is viewed against a horizon 

sky, a smaller change in light intensity or color can be perceived than if the boundary 

between the two objects is vague, as in the case of a plume viewed against the horizon 

sky. If the observer is located in a uniformly colored atmosphere, atmospheric 

discoloration is perceived, not by comparison of two colored fields but by comparison 

with the recollection of a clear atmosphere. 

 The temporal extent (duration, frequency of occurrence, and time of occurrence) is of 

great importance in determining the significance of air pollution levels. Short term or 

infrequent phenomena or both are less likely to be of concern. Visibility impairment 

occurring during times of maximum visitor attendance is of greater significance than the 

same impact during minimum attendance. With sufficient measurements, the frequency 

of occurrence can be characterized as the number of days or hours in a year that the 

degree of visibility impairment is greater than some specified amount. 

Qualitatively, the degree and extent of anthropogenic impairment increases through 

four levels: 1) natural baseline, no anthropogenic pollution; 2) a measurable or 

predictable pollution increment that is so small or short that it is not perceptible by 

human observers; 3) an observed or predicted perceptible impact which, because of 

degree or extent, is generally considered to be insignificant; and 4) an impact that is 

generally considered significant or adverse. 

For the purpose of this report, EPA interprets man-made visibility impairment, in the 

context of the national visibility goal, as any perceptible change in visibility (visual 

range, contrast, atmospheric color or other index) from that which would have existed 

under natural conditions. Judgments with respect to the significance and adversity of 

perceptible impairments should consider the degree and the spatial and temporal aspects 

of impairment in the context of control programs. Such judgments must be made, at least 

in part, on a case-by-case basis. For this reason and because these judgments must 

involve States, Federal Land Managers and the public, it is difficult at this time to specify 

general criteria. As a minimum, however, significant or adverse impairment must be 

perceptible. These issues are discussed further in Chapter 7. 

1.6 OVERVIEW OF CURRENT U.S. VISIBILITY 

Until recently, visibility parameters have not been routinely monitored in any class I 

area. Some insight into general visibility conditions in these locations can, however, be 

obtained by examining available regional airport visibility data throughout the United 

States. The status of visibility in class I areas is discussed further in Chapter 7. 
39

Figure 1-10 presents median yearly visibilities and visibility isopleths (Trijonis and 

Shapland, 1978). The data represent midday, median visual ranges for 1974-1976 from 

100 suburban and non-urban locations. Visibilities at 93 of the locations are determined 

from airport observations. 

The airport data were checked for consistency, quality, and completeness. 

Instrumental visibility measurements from seven sites in the southwest are also included. 

Although some uncertainties arise from the use of airport data*, there is reasonably good 

consistency between airport observations within regions and between airport and in 

instrumental results in the Southwest. 

The best visibility (70+ miles, 110 km) occurs in the mountainous Southwest. 

Visibility is also quite good (45-70 miles) north and south of that region, but sharp 

gradients occur to the east and west. Most of the area east of the Mississippi and south of 

the Great Lakes exhibits median visibilities of less than 15 miles (24 km) annually. 

Figure 1-10. Median yearly visual range (miles) and isopleths for suburban /nonurban Areas, 1974-76 (Trijonis and Shapland, 1978). 

Figure 1-11 represents median summertime (third quarter) visibilities for the same 

data. Comparison of these figures shows that summertime visibility is significantly lower 

than yearly visibility in the East. Most of the Western states show little change in the 

P: Based

Photom~~r~h~tOgraPh; c

N: Based ata •. B on nephelometry d . as~ on au visibili uncertain extr ty frequency d· apo~ation of lstnbution

15
40

summer, with mixed increases and decreases. Visibility increases, however, during the 

summer in the Pacific Northwest. 

Figure 1-11. Median summer visual range (miles) and isopleths for suburban/ 

non-urban areas, 1974-76 (Trijonis and Shapland, 1978). 

Although natural sources of visibility impairment and prevailing meteorological 

conditions are undoubtedly an important factor in producing these geographical and 

seasonal patterns, analysis of visibility trends and other information discussed in later 

sections suggest that man-made air pollution has a significant impact. The regions with 

the best existing visibility levels are most sensitive to additional impairment and most 

responsive to incremental pollution reductions. The reasons for this are discussed in the 

next chapter. 

P: Based

Photom~~r~h~tOgraPhi c

N: Based a ta

*: Based oon nephelometry data

viSibil7 uncerta in extra ly frequency d _ po~ation of lstnbution
41

REFERENCES FOR CHAPTER 1 

Anderson, G. (1979). Personal Communication. Gordon Anderson Photography. 

Colorado Springs, Colorado. 

Andrus, C.D. (February 24, 1978) Identification of Mandatory Class I Federal Areas 

Where Visibility is an Important Value. 43, FR 4310 

Beardsley, W. 1970 Economic Value of Recreation Benefits Determined by Three 

Methods, USDA Forest Service Res. Note Rm-176, Rocky Mtn. 

 

Blank, F., D. Brookshire, T. Crocker, R. d'Arge, R. Horst and R. Rowe (1978) Valuation 

of Aesthetic, Preferences: A Case Study of the Economical Research Institute, Resource 

and Environmental Economic Laboratory, University of Wyoming. 

Blum, B. (1979) National Visibility Goal for Federal Class I Areas. 44 FR 6560 February 

12. 

Brookshire, D., B.S. Iver and W.D. Schultze (1976) The Valuation of Aesthetic 

Preferences. Journal of Environmental Economics and Management, 3 325-246. 

Brookshire, D., R. d'Arge, W. Schultze, and M. Thayer (1978). Experiments in Valuing 

Non-Market Goods: A Case Study of Alternative Benefit Measures of Air Pollution 

Control in the South Coast Air Basin of Southern California. Report prepared for the 

Environmental Protection Agency under Contract No. R 805059010. 

Brookshire, D. and A. Randall (1978) Public Policy Alternatives, Public Goods and 

Contingent Valuation Mechanisms. Paper presented at the Western Economic 

Association Meetings, Honolulu, Hawaii, June 1978. 

Brookshire, D. S. (1979) Issues in Valuing Visibility: An Overview. In: Proceedings of 

the Workshop in Visibility Values, Fox, D., R. J. Loomis and T.C. Green (technical 

coordinators). Fort Collins, Colorado, U.S. Department of Agriculture. p. 130-138. 

Charlson R.J., A. P. Waggoner and Thilke J .F .(1978) Visibility Protection for Class I 

Areas: The Technical Basis. Report to Council of Environmental Quality, Washington, 

D.C. Conference Report (1977) Joint Explanatory Statement of the Committee on 

Conference. House Report No. 95-564, 95th Congress, Congressional Record, August 3. 

95th Congress (1977). The Clean Air Act as Amended August 7, 1977, Committee Print. 

U.S. Government Printing Office, No.99-3020, Washington, D.C. 

Costle, D.C. (1979) Identification of Mandatory Class I Federal Areas Where Visibility is 

an Important Value, 44 FR 69122, November 30. 
42

Craik, K.H. (1979) The Place of Perceived Environmental Quality Indices (PEQIS) in 

Atmospheric Visibility Monitoring and Perservation. In: Proceedings of the Workshop in 

Visibility Values, Fox, D. , R.J. Loomis and T .C. Green (technical coordinators). Fort 

Collins, Colorado, U .S. Department of Agriculture. p. 116-122 , 

Daniel, T .S. (1979) Psychological Perspectives on Air Quality and Visibility in Parks 

and Wilderness Areas. In: Proceedings of the Workshop in Visibility Values, Fox D., R.J. 

Loomis and T.C. Green (technical coordinators). Fort Collins, Colorado, U.S. 

Department of Agriculture. p. 84-92. 

Fox D.G. (1979) What is Visibility Worth? Paper No. 79-26.6, presented at Convention 

of the Air Pollution Control Association. Cincinnati, Ohio, June. 

Driver, B.L., D. Rosenthal and L. Johnson (1979) A Suggested Research Approach for 

Quantifying the Psychological Benefits of Air Visibility. In: Proceedings of the 

Workshop in Visibility Values, Fox, D., R.J. Loomis and T .C. Greene (technical 

coordinators). Fort Collins, Colorado, U .S. Department of Agriculture. p. 100-105. 

Fox, D., R.J. Loomis and T .C. Greene (technical coordinators) (1979) Proceedings of the 

Workshop in Visibility Values, Fort Collins, Colorado. January 28-February 1, 1979. 

U.S. Department of Agriculture, Forest Service, Washington, D.C. p. 153. 

Grasvenor, G.M. (1979), The Best of Our Land, National Geographic 156(1), July. House 

Report, (1977), House Report No.95-294 at 204-207, May, 12 . 

Latimer, D.A., R.W. Bergstrom, S.R. Hayes, M.K. Lui, J.H. Seinfeld, G.Z. Whit ten, 

M.A. Wojcik, M.J. Hillyer, (1978). The Development of Mathematical Models for the 

Prediction of Anthropogenic Visibility Impairment. EPA 450/3-78-110a,b,c. U.S. EPA 

Research Triangle Park, N.C. 

Loomis, R.J. and T.C. Green (1979). Air Pollution, Values and Environmental Behavior. 

In: Proceedings of the Workshop in Visibility Values, Fox, D., R.J. Loomis and T .C. 

Green (technical coordinators). Fort Collins, Colorado, U.S. Department of Agriculture. 

p. 106-115. 

Malm, W. (1979a) Visibility: A Physical Perspective. In: Proceedings of the Workshop in 

Visibility Values, Fox, D., R.J. Loomis and T .C. Greene (technical coordinators). Fort 

Collins, Colorado, U.S. Department of Agriculture. p. 56-68. 

Malm, W. (1979b) Personal Communication, Environmental Protection Agency 

Environmental Monitoring and Support Laboratory, Las Vegas, Nevada. 

National Park Service (1978) My Eyes Need a Good Stretching, Seven Authorities Speak 

out on Visibility, Clean Air, and Unique Natural Areas. Department of Interior, 

Washington, D.C. 
43

Niemann, B.L. (1979) Results of Multiscale Air Quality Impact Assessments for the 

Southwest-Rocky Mountain Northern Great Plains Region. Part I Slide Script. Prepared 

for U.S. EPA, Office of Energy Materials and Industry, Washington, D.C. 

Peterson, G.L. (1979) Atmospheric Visibility Assessment. In: Proceedings of the 

Workshop in Visibility Values, Fox, D., R.J. Loomis and T.C. Greene (technical 

coordinators). Fort Collins, Colorado, U.S. Department of Agriculture p. 8-17. 

Randall, A., B. Iver and E. Eastman (1974a) Bidding Games for Valuation of Aesthetic 

Environmental Improvements. Journal of Environmental Economics and Management. 

pp 132-149. 

Randall, A., B. Iver and E. Eastman (1974b) Benefits of Abating Aesthetic 

Environmental Damage from the Four Corners Power Plant, Farmington, New Mexico. 

Bulletin 618, New Mexico Agricultural Experiment Station, Las Cruces, N .M. 

Rogers, P. (1977) 123 Congressional Record H. 119J8, Nov. 1, 1977. 

Thayer, M. and W. Schulze (1977). Valuing Environmental Quality: A Contingent 

Substitution and Expenditure Approach. Research paper, University of Southern 

California, Los Angeles, California. 

Trijonis, J., and D. Shapland, (1978) Existing Visibility Levels in the U.S., prepared by 

Technology Service Corporation for the U .S. Environmental Protection Agency, Grant 

No.802815, Research Triangle Park. 

Ulrich, R.S. (1979) Psychophysiological Approaches to Visibility. In: Proceedings of the 

Workshop in Visibility Values, Fox, D., R.J. Loomis and T .C. Greene (technical 

coordinators). Fort Collins, Colorado, TJ.S. Department of Agriculture. p. 93-99. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 2 
2

2 FUNDAMENTALS OF ATMOSPHERIC VISIBILITY 

IMPAIRMENT 

“Therefore, O Painter, make your smaller figures merely indicated and not highly 

finished, otherwise you will produce effects opposite to nature, your supreme guide. The 

object is small by reason of the great distance between it and the eye; this great distance 

is filled with air, that mass of air forms a dense body which intervenes and prevents the 

eye from seeing the minute details of the objects.” –Leonardo da Vinci, Six Books on 

Light and Shade. 

2.1 INTRODUCTION: VISION IN THE ATMOSPHERE 

Our ability to define, monitor, model and control anthropogenic visibility impairment 

is dependent on understanding of the scientific and technical factors that affect 

atmospheric visibility. Visibility involves an observer’s perception of the physical 

environment. The fundamental factors that determine visibility are illustrated in Figure 

2-1 and include: 

1. Illumination of the scene by the sun, as mediated by clouds, ground reflection, and 

the atmosphere; 

2. Reflection, absorption, and scattering of incoming light by the target objects and sky 

resulting in inherent contrast and color patterns at the target location; 

3. Scattering and absorption of light from the target and illumination source by the 

atmosphere and its contaminants; 

4. Psychophysical response of the human eye-brain system to the resulting light 

distribution, and 

5. Subjective judgment of the perceived images by the observer. 

Evaluation of the effects of air pollution on visibility thus involves two steps: 1) 

specification of the process of human visual perception and 2) quantification of the 

impacts of air pollution on the optical characteristics of the atmosphere. The 

characteristics of illumination and targets can be important to both steps. 

2.2 HUMAN VISUAL PERCEPTION 

2.2.1 Brightness and Contrast 

The eye receives image-forming radiation from the environment and converts it into 

electrical impulses, which are further interpreted and perceived by the brain. The 

perception of brightness, contrast, and color is not determined simply by the pattern and 
3

intensity of incoming radiation; rather, it is a dynamic searching for the best 

interpretation of the available data (Gregory, 1978). 

A candle in a brightly lit room is scarcely noticeable; but, if the room is dim to start 

with, the candle itself appears bright. Similarly, sunlit treetops may appear dark against 

the horizon sky but bright when viewed against the shadowed forest floor. These 

examples show that the absolute intensity of radiation has little to do with or brightness 

perception of visible objects. The eye normally senses and intensity difference relative to 

the overall intensity level; that is, it detects the contrast. Thus, trees that appear darker 

than background cliffs in bright sunlight will also appear darker than the cliffs in 

moonlight or heavy overcast. 

The detection of contrast between an object and its surroundings is fundamental to 

visibility. Without contrast, as for example in a thick fog, objects cannot be perceived. 

As the contrast between object and background is reduced (for example, by increased 

pollution), the object becomes less distinct. When the contrast becomes very small, the 

object will no longer be visible. This liminal or threshold contrast has been the object of 

considerable study. The threshold contrast is of particular interest for atmospheric 

visibility, since it influences the maximum distances at which various components of a 

scene can be discerned. Of equivalent importance to threshold contrast is the smallest 

perceptible change in contrast of a viewed scene caused by a small increment in pollution 

haze. 

Figure 2-1. Vision in the atmosphere. 

The physiology of threshold contrast detection is illustrated in Figure 2-2, showing a 

bright horizon (I + ∆Ι) against which a “hazy” mountain (I) is being detected. Laboratory 

experiments indicate that for most daylight viewing intensities, contrasts (∆Ι / I+∆Ι) as 

low as .018 to .03 (1.8 to 3 %) are perceptible (Figure 2-3). 

IN~ EflENT CON'T'FlAS" Sf'E(l~"'L

FlE FLEeT"'NCE iCOl.OIlo), Sl2 E, SHAl'E,

DISTANCE. PATTERN. t<DllIZON.

"IlA IGH1l\I ESS."

OPTICAL CHAIlACTEIlISTU~OF

VIDIIED "'1ARGETI:"

CIl'1ICA l CHARAC1E RISTlell 0'

ILLUMINAlIClN SOUJlC_E _

SUN ANG lE, SPEC1R lAIl. IN rl:NSITVAS ALTER ED BY (:LOUD C(}V~ A ANO

ATMOOI'HER E

AlA MOLECULES. PART Ie L~~, r«lz -ADD $UN LIG HT IIlLUE., lI'H ITE) TO

VIEWI'ATH

-SUBTRAC'f L1G~T CEl:~UE, WHITEf - ........----

COMjN" F~DM VIEWED TAAGET

----. -FlE[lUCE CCJoNTRAST. ALTER (:OLOR

OF TARGET

-I NCR EJU~ HAZE

~(:TER~HICS OF OElSEllv~Fl

-PSV(:flOfl~ VSICA l. I~VE·BIloAIM

RESP'ONSE TO INCOMING L1GIoIT:

·'T1tAES~Ol[lS 0 F rERCEl'TION ~OR

OONTIlAIT' CD lOR CHANGE'

-SE~SITIVITV TO SIZE.I'ATTE.F\L\I.

[lISTAIBUTlON OF COLOR.

-SUBJECTI VI: JUDGiIIIENT OF

PE R(:£IVEO IMAG Et. o

-t OPT " .....l CIVIAACTEAIIITICS OF INT£Il.

VEltlNG ATNDSPIoIEll E
4

Figure 2-2. Physiological response of the eye to an increment in light intensity is 

an increase in the number of signals sent to the brain. The detection of threshold 

contrast involves discrimination of the signal field (I) from its brighter background 

(I + )I) (Gregory, 1978). 

Middleton’s measurements of observer threshold contrasts for viewing large, dark 

distant objects in the atmosphere produced similar results, although some variability in 

observer sensitivity was noted (Figure 2-4). This study, however, was conducted in a 

relatively polluted urban area. Similar experiments to evaluate contrast thresholds in 

pristine areas are needed. 

The preceding discussion of thresholds was limited to contrast between objects and 

backgrounds of relatively large apparent size. For “smaller” objects, however, the size of 

the visual image on the retina of the eye also plays an important role in the perception of 

contrast. We all know from experience that, as an object recedes from us and apparently 

becomes smaller, details with low contrast become difficult to perceive. The reason for 

this loss of contrast perception is not only that the relative brightness of adjacent areas 

changes but also that the visual system is less sensitive to contrast when the spacing of 

contrasting areas decreases. If the contrast spacing is regular, a “spatial frequency” can 

be readily determined. The human visual system is much more sensitive to contrast at 

certain spatial frequencies than to contrast of other spatial frequencies. 

1+ c.l (sky)

pulsell per second
5

Figure 2-3. The minimum perceptible (threshold contrast )I/)I is between .018 

and .03 for about four orders of intensity change. Evidently, at low intensities, the 

statistical 'noise' of retinal signals becomes important; at very high intensities, 

blinding deteriorates the contrast sensitivity ((Konig and Brodhum, 1889). 

Figure 2-4. Measured threshold contrast of large, dark targets identified in 1000 

determinations of visual range by 10 observers. Variability is due to both 

differences in observer thresholds and the discrete nature of the marker set 

(Middleton, 1952). 

Figure 2-5 shows the contrast sensitivity (inverse of contrast threshold) of the eyebrain system to a standard test pattern with varying spatial frequency. Although several 

factors affect the location of the curve, the contrast sensitivity is generally highest for 

periodic visual patterns if the spacings are about 0.33 degrees (20 minutes) apart. This 

corresponds to clumps of vegetation viewed at a distance of 10 km. The figure indicates 

that as the visual targets become smaller and their spacing increases, the threshold 

contrast steadily increases. Measurements of the perceived threshold contrast for 

individual circular targets suggest a similar relationship (Taylor, 1964). The threshold 

contrast increases for single targets occupying less than 0.5 degrees (30 minutes) of arc 

0.7

1).6

-- D.S <i

..: 1).4 '"ct

a:: 0.3

z

0

u 0.2

0.1

-4 -3 ·2 -1 0 1 2 3 4 5

LOG I

220

ZOO

180

160

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z

w 120

a 100 w

a::

II.. 80

60

40

20

~OO

I

4.6

N = 1000

-05 -10 ·15 -20

CONTRAST, f

I ! I I

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LOG CONTRAST, K
6

but remains constant (at about 0.3%) for larger targets. The moon and sun occupy about 

30 minutes of arc. 

Figure 2-5. Contrast sensitivity of human subjects for sine-wave grating peaks at 

three cycles per degree corresponding to a contrast threshold of 0.003 or 0.3% 

(Campbell and Maffei, 1974). 

The relationship between perceived contrast threshold and target characteristics (size 

and pattern) is important for visibility, because a scenic vista usually contains a number 

of targets of varying sizes and arrangements. The calculation of the perceptibility of all 

targets would require specification of their angular size distribution. The perception of 

“texture,” consisting of contours of small angular size and high spatial frequency, is 

particularly affected by this loss of threshold sensitivity. Henry (1977, 1979) has 

proposed a system for quantifying this effect through the transformation of the contrast 

details of a scene in conjunction with a specification of the human psychophysical 

contrast response function (Figure 2-5). This approach, termed MTF*, has some 

limitations but theoretically could be used to predict the contrast reduction that would 

cause a just-noticeable (perceptible) difference in the scene. 

Although the MTF approach may ultimately improve the specification of perceptible 

changes invisibility of contrast detail, it has not yet been fully developed or 

experimentally tested for atmospheric vision. Thus, current visibility models and 

assessment tools must rely on evaluation of contrast changes for large dark targets as an 

index of visual degradation. Even for this kid of target, additional experimental 

verification of perceptible contrast changes is needed. For the purpose of this report the 

threshold contrast for large dark targets will be assumed to be 0.02. The minimum 

perceptible contrast change for large targets is less well quantifies and may vary with 

initial conditions.. Based on preliminary, unpublished data, the minimum perceptible 

change may range between 0.01 and 0.05 (Malm, 1979b). 

2.2.2 Color 

The preceding section discussed the response of the eye and brain to the intensity of 

light, ignoring the spectral (wavelength) distribution. Color is the sensation produced by 

the eye-brain system in response to incoming light. 

500

> .005

I-

:;; 100 .01

j::::

C;; 50 .05 lll) Z

w «a: lI) l- I- Z lI)

« 0 10 .1 u a:

Iz 5

0

u

.5

1 1

.05 .1 .5 5 10 50

SPACIAL FREQUENCY (CYCLES PER DEGREE)
7

The eye has three different types of color sensors (cones) which cover the visible 

spectrum in three broad, overlapping curves (Figure 2-6). The system operates so that an 

object that reflects half blue light and half yellow light is identified not as yellow-blue, 

but rather as a new color, white. As in the case with brightness, the perception of color is 

not dependent on the absolute flux of radiant energy reaching the eye. The color of 

objects (e.g. flesh tones) appears similar over a wide range of outdoor and indoor 

illumination. The eye differs in this regard from photographic film, which can take on a 

reddish or bluish cast under differing lighting conditions. Moreover, the color of the 

surrounding scenery can affect the perceived color of a given object. The normalization 

of color and other aspects of color perception are not fully understood. Although recent 

approaches to explaining the mechanism of color perception appear promising (Land, 

1977), no completely adequate theory of color vision exists (Henry, 1979). 

Figure 2-6. The fundamental response curves of the eye (cones). The visible 

spectrum extends from 0.4 (roughly violet or blue) to 0.7 (roughly red) micrometers. 

The weighted peak (photopic) response of the eye occurs at a wavelength of 0.55 μm 

(Gregory, 1978). 

The chromaticity diagram (Figure 2-7) was developed to quantify empirically the 

concept of color. Any three colors, no one of which can be matched by the other two, 

determine an unambiguous system of coordinates for all colors that can be matched by 

mixtures of the three; on has only to specify the proportions in the (unique) match. The 

Commission International de l’Eclairage (CIE) has established two standard schemes, 

based on three imaginary non-physical colors, by which schemes all colors can be 

represented as such matches. The CIE primaries, denoted X, Y, Z, are defined in terms 

of the small field and large field color matching behaviors of a hypothetical “standard 

observer,” whose response to radiation of various wavelengths is near the average of a 

number of actual observers with normal color perception. This system allows for 

complete specification of color through its chromaticity coordinates (x, y) and intensity 

(L*). 

The CIE color metrics enjoy wide use in science and industry as international 

standards. They must not be thought of as methods for describing sensations or a theory 

of vision but only as means of assigning numbers to colors in such a way that two colors 

0.5 0.6 0.7

0.6 r-----,~-__..--"'T"""--_r_--'r'"""-__,

0.5

0.4

0.3

0.2

0.1

-0.10 ...'--";";'_~

--7 """"__""""__--I..._--.I

0.4

WAVELENGTH OF LIGHT, ~m
8

that have the same numerical specifications will appear alike to the standard observer 

under standard viewing conditions. 

Figure 2-7. The small-field (2°) CIE chromaticity diagram. The curved line is 

the locus of the spectral colors; all physically realizable colors lie within the closed 

figure formed by the spectrum locus and the straight line joining its ends. Heavy 

curve in the middle indicates typical chromaticities of daylight. Intensity or 

brightness can be represented by a third dimension, perpendicular to the plane of 

the paper. The corresponding large-field (10°) diagram is similar (adapted from 

Middleton, 1952). 

An attractive feature of the CIE color metrics is that colors that are similar in 

appearance lie close together on the chromaticity diagrams. A great deal of experimental 

work has been done on color discrimination thresholds, which are of critical importance 

to the pain and dye related industries. On the chromaticity diagrams, these thresholds 

take the form of small ellipses of colors just distinguishable from a given color (Figure 2-

8). The differences in colors are specified by a parameter ∆E, which is a function of the 

change in light intensity or brightness (∆L*) and the change in chromaticity (∆x, ∆y), ∆E 

can be considered as a distance between two colors in a color “space” such that equal 

distances (∆E) between any two colors correspond to equally perceived color changes. It 

is possible that a threshold, ∆Eo, can be found to determine whether a given color change 

is perceptible. Latimer et al. (1978) have calculated threshold values of ∆E for visible 

plumes, but he applicability of this system for quantifying perceptible atmospheric 

discoloration has not yet been experimentally verified. 

0.9

0.8

0.7

GREEN

0.6

0.5

Y

0.4

0.3

BLUE /

0.2 PURPLE

0.1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0,8

X
9

Factors other than that specified by ∆E (wavelength, intensity) that are of importance 

to perception include: size of object or area, color of surrounding background, and 

temporal variations. The well-known effect of background color on perceived color is 

called chromatic adaptation. In general, if the eye is adapted to a color, e.g. blue sky, a 

nearby white area may take on the complementary color of the background, in this case a 

light yellow-brown. This effect may be large enough to explain some of the brown color 

of atmospheric haze (Henry, 1979). 

Figure 2-8. Small-field chromaticity diagram showing color-matching ellipses, 

represented 10 times actual scale for clarity. Each ellipse is the locus of standard 

deviation in repeated small-field color matching. The diagram summarizes almost 

25,000 attempted color matches by a single observer (MacAdam, 1942). Insert: 

Variability of large-field color-matching ellipsoids among 12 different observers 

(Brown, 1957). 

Because current understanding of color perception is inadequate, theoretical 

calculations of atmospheric discoloration are useful only as a guide for experimental 

measurements. Empirical measurements of atmospheric color perception and effects of 

pollutants over the next few years should provide an adequate means of handling 

atmospheric discoloration, even without a comprehensive theoretical treatment. 

2.3 OPTIAL EFFECTS OF THE ATMOSPHERE AND ITS CONTAINMENTS 

2.3.1 Scattering and Absorption 

Visibility impairment is caused by the following interactions in the atmosphere: 

x
10

1. Light scattering -by molecules of air 

 -By particles (atmospheric aerosols) 

2. Light absorption-by gases 

 -By particles 

Light scattering by gaseous molecules of air (Rayleigh scattering), which cause the 

blue color of the sky, is dominant when the air is relatively free of aerosols and light 

absorbing gases. Light scattering by particles is the most important cause of degraded 

visual air quality. Fine solid or liquid particles, also known as atmospheric aerosols, 

account for most of atmospheric light scattering. The aerosols with diameters similar to 

the wavelength of light (0.1 to 1.0 micrometers) are the most efficient light scatterers per 

unit mass. Light absorption by gases is particularly important in the discussion of 

anthropogenic visibility impairment because nitrogen dioxide, a major constituent of 

power plant and urban plumes, absorbs light. Nitrogen dioxide appears yellow to reddish 

brown because it strongly absorbs short wavelengths light (blue), leaving longer 

wavelengths (red) to reach the eye. Light absorption by particles is most important when 

black soot (finely divided carbon) or large amounts of windblown dust are present. Most 

atmospheric particles are not, however, generally considered to be efficient light 

absorbers. 

2.3.2 Radiative Transfer 

The effect of the intervening atmosphere on the visual properties of distant objects 

(e.g. the horizon sky, a mountain) theoretically can be determined if the concentration 

and characteristics of air molecules, aerosols, and nitrogen dioxide are known along the 

line of sight. The rigorous treatment of visibility requires a mathematical description of 

the wavelength-dependent interaction of light wit the atmosphere, known as the radiative 

transfer equation. The description presented here is intended to provide a qualitative 

understanding of this process. Detailed and summary treatments are available in a 

number of publications. (Chandraskhar, 1950, Latimer et. al., 1978). 

Figure 2-9 (a) shows the simple case of a beam of light (e.g. the sun or a searchlight) 

transmitted horizontally through the atmosphere. The intensity of the beam in the 

direction of the observer (I(x)) decreases with distance from the source as light is 

absorbed or scattered out of the beam. Over a short interval, this decrease is proportional 

to the length of the interval and the intensity of the beam at that point. 

-dI = bextI dx (2-1) 

Where –dI = decrease in intensity (extinction) 

bext = extinction coefficient 

I = original intensity of beam 

dx = length of short interval 

The coefficient of proportionality, denoted by bext, is called the extinction or 

attenuation coefficient. The extinction coefficient is determined by the scattering and 

absorption of particles and gases and varies with pollutant concentration and wavelength 

of light. 

Consider now an observer looking at a distant target, as shown in Figure 2-9b. Just as 

a beam is attenuated by the atmosphere, the light from the target that reaches the observer 
11

is also diminished by absorption and scattering. The reduced brightness of distant objects 

is, however, not usually the primary factor limiting their visibility; if it were, the stars 

would be visible around the clock, since their light must traverse the same atmosphere 

night and day. In addition to light originating at the target, the observer receives 

extraneous light scattered into the line of sight by the intervening atmosphere. It is this 

air light that forms the diaphanous, visible screen we recognize as haze. 

Figure 2-9. (a) A schematic representation of atmospheric extinction, 

illustrating: (i) transmitted, (ii) scattered, and (iii) absorbed light. (b) A schematic 

representation of daytime visibility, illustrating: (i) residual light from target 

reaching observer, (ii) light from target scattered out of observer's line of sight, (iii) 

airlight from intervening atmosphere, and (iv) airlight constituting horizon sky. 

(For simplicity, "diffuse" illumination from sky and surface is not shown.) The 

extinction of transmitted light attenuates the '"signal" from the target at the same 

time as the scattering of airlight is increasing the background "noise." 

The intensity of the air light scattered into the sight path of the observer in Figure 2-9b 

depends on the distribution of light intensity from all directions, including direct sunlight, 

diffuse sky light or surface reflection, and the light scattering characteristics of the air 

molecule and aerosols. Over a short interval, the air light added is given by: 

(2-2) 

Where dI = the increase in intensity form added air light 

bext = the extinction coefficient 

ext [ QWbdI θ )I( (v)vv Ω ]dxd ∫ =

o ..4 •

i .. .. .~. :

iii

a

,.

. .

. .

· . ·

· .

·

o

·

·.

•· .

·

:.

··

··

··

·l(

. ..

. ii •

.'l + dl'l
12

Bracketed parameters [ ] = the sum of light intensity from all directions scattered 

into the line of sight. This depends on aerosol and air scattering parameters (W Σ

Qv), and illumination intensity and angle (Iv, θv) summed over all directions (Ω). 

dx = length of short interval 

Since both extinction coefficient and other scattering parameters vary with 

wavelength, the added light can produce a color change. 

The overall change in light intensity from an object to an observer is governed by the 

extinction of transmitted light and the addition of air light. The change in intensity for a 

short interval (dI) is thus: 

dI = -dI (extinction) + dI (air light) = - bext [I dx + W ∫Qv (θv) I(v) dΩ dx] (2-3) 

This equation, the radiative transfer equation, forms the basis for determining the effects 

of air pollution on visibility. Its general solution is quite difficult; most visibility models 

(see Chapter 5) incorporate a number of approximations to simplify calculations and data 

requirements. 

2.3.3. Contrast and Visual Range 

The effect of extinction and added air light on the perceived brightness of visual 

targets is shown graphically in Figure 2-10. At increasing distances, both bright and dark 

targets are “washed out” and approach the brightness of the horizon. Thus, the apparent 

contrast of an object relative to the horizon (and other objects) decreases. 

An initial object contrast (Co) can be defined as the ratio of object brightness minus 

horizon brightness divided by horizon brightness. Assuming a relatively uniform 

distribution of pollutants and horizontal viewing distance, the apparent contrast of large 

objects decreases with increasing observer-object distance. As given by Middleton, 

1952: 

C = Co (BT bext x / Bo) (2-4) 

Where C = apparent contrast at observer distance 

Co = initial contrast at object 

BT/Bo = ratio of sky brightness at target object to that at 

observer (usually 1 for distance less than 50-100 km). 

bext = extinction coefficient 

x = observer-object distance 
13

Figure 2-10. Effect of an atmosphere on the perceived brightness of target 

objects. The apparent contrast between object an horizon sky decreases with 

increasing distance from the target. This is true for both bright and dark objects 

(Charlson et al., 1978). 

For a black object, the initial contrast is –1 and: 

C = (-1) e-b

extx

As discussed in the preceding section, the threshold of contrast perception for large 

dark targets varies between .01 and .05; for “standard” observers a .02 threshold is often 

assumed (Malm, 1979). In this case, the distance Vr, at which a large black objet is just 

visible is given by: 

.02 = -e –b

ext

 Vr or Vr = 3.92 / bext (2-5) 

This is the standard formula for calculating visual range, originally formulated by 

Koschmieder in 1924. 

The Koschmieder relationship gives a valid approximation of visual range only under 

a limited set of conditions. Important assumptions and limits are listed and discussed 

below (Charlson, et. al., 1978, Malm, 1979a): 

1. Sky brightness at the observer is similar to the sky brightness at object observed; 

2. Homogeneous distribution of pollutants; 

3. Horizontal viewing distance; 

4. Earth curvatures can be ignored; 

5. Large black objects; and 

6. Threshold contrast of 0.02. 

Assumption 1: The effect on visual range of inhomogeneous illumination, such as that 

under scattered clouds, is difficult to analyze by elementary methods. Limited 

experimental evidence indicates that this effect may not be great for short visual ranges 

(less than 50 km). Visual range has been found to correlate with the reciprocal of the 

LIGHT INTENSITY OF HORIZON

-------~--------------------

OBJECT·OBSERVER DISTANCE ro -
14

scattering coefficient, bscat*, as illustrated in Figure 2-11. The correlation coefficients are 

commonly in the neighborhood of 0.9, with values for bscat times Vr in the range 2 to 4 as 

compared to 3.9 in the Koschmieder equation. The studies were conducted in relatively 

polluted conditions. The effect of scattered clouds or differing sky brightness on visual 

range in clean areas should be further investigated. 

Assumption 2: The Koschmieder equation can be utilized in a non-homogeneous 

atmosphere (e.g., a ground level plume) if the extinction coefficient in and outside the 

plume is known. Otherwise, measurements of bext in areas with strong pollution 

gradients will produce inaccurate visual range estimates. 

Figure 2-11. Inverse proportionality between visual range and light scattering 

coefficient (bscat) measured at the point of observation. The straight line shows the 

Koschmieder formula for non-absorbing (bext =bscat) media, V = 3.9/bscat. The linear 

correlation coefficient for V and bscat is 0.89 (Horvath and Noll, 1969). 

Assumptions 3 & 4: Requirements for horizontal viewing distance and curvature of 

the earth limit the validity of the Koschmieder calculation to cases where visual range is 

less than about 150-200 km (Figure 2-12). Where no proper targets exist and the 

extinction coefficient is measured, however, the calculation of visual range is useful in 

expressing visual air quality in units (miles or kilometers) more readily comprehended by 

the layman. 

0.50

0.40

'7 0.30 E

.:It

u;' 0.20

w

0

u

t.:I 0.10 z

a::

w

.-

.- 0.05

c(

0.03

5 10 20 50 100

VISUAL RANGE, km
15

Figure 2-12a. Limitations of Koschmieder relationship. When visual range is 

short (1), extinction and illumination through sight path is uniform. When true 

visual range is high (2), Koschmieder equation underestimates visual range because 

extinction decreases with altitude and illumination (sun angle) at target is different 

from that at observer. (Dimensions and earth curvature exaggerated for clarity) 

(Malm, 1979a). 

Figure 2-12b. Similarly, when viewing angel is not horizontal, extinction through 

the site path is nonuniform. Koschmieder equation will underestimate visual range 

(Malm, 1979a). 

Assumption 5: The visual range for nonblack objects depends strongly on initial 

contrast, which in turn depends on amount and angle of illumination, or if at night 

depends on the power of the light source. As a result of this ambiguity, visual ranges for 

nonblack objects or for lights at night cannot be related simply to each other or to optical 

air quality. 

Assumption 6: The effects of target size, texture, and sensitivity of observer are 

related to the nature of human perception. As discussed in Section 2.1, in general the 

“visual range” for small targets or contrast detail is significantly less than that for large 

objects (Table 2-1). 

"MIXING LAYER" CONTAINING HIGHER POLLUTION

TARGET (21
16

Visual range (km) 

Detail of 

objects 

Angular size 

(minutes) 

Characteristics 

sizes at 10 km 

(m) 

Examples for 

a hillside at 

10 km 

West 

Vr = 100 km 

East 

Vr = 20 kmb

Very coarse 

(Form) 

> 30' > 100 Hills, 

valleys, 

ridgelines 

79-100 16-20 

Coarse 

(Line) 

17-30' 50-100 Cliffs faces 

smaller 

valleys 

76 15 

Medium 

(Texture) 

9-17' 25-50 Clumps of 

large 

vegetation, 

clearings on 

forested 

slopes 

62 12 

Fine 

(Texture) 

< 9' < 25 Individual 

large trees, 

clumps of 

small 

vegetation 

22 4 

Table 2-1. Visual Range of Contrast Detaila

. aBased on calculations using MTF 

model of eye-brain response and mathematical transformation of scenic features 

into a spatial frequency (Henry, 1979). b

VR sit he assumed background visual 

range (for large black targets). 

2.4 POLLUTANTS THAT IMPAIR VISIBILITY 

As indicated above, the air pollution related alteration of the appearance of distant 

objects (reduction in apparent contrast and visual range) could be estimated if the 

extinction coefficient, bext, is known. To the extent bext varies with the wavelength of 

visible light, this alteration of appearance includes changes in the apparent coloration of 

distant objects. 

The extinction coefficient represents a summation of the air and pollutant scattering 

and absorption interactions outlined in 2.3.1. 

bext = bRg + bag + bscat + bap 

Where bRg is Rayleigh scattering by air molecules; 

bag is absorption by NO2 gas; 

bscat is scattering by particles; 

bap is absorption by particles; 

Each of these quantities has inherently different wavelength or color dependence, as 

will be discussed below. The units of extinction are inverse distance, e.g., 1/mile. The 
17

most commonly used units are km-1 and (10-4

m

-1). As extinction increases, visibility 

decreases. 

2.4.1 Rayleigh Scatter b 

The particle-free molecular atmosphere at sea level has an extinction coefficient of 

about 0.012 inverse kilometers (km-1) for “green” light (wavelength 0.05 μm), limiting 

visual range to about 320 km. bRg decreases with air density and altitude. In some 

western class I areas, the optical extinction of the atmosphere is at times essentially that 

of the particle-free atmosphere (Charlson, 1978). Rayleigh scatter thus amounts to a 

simply definable and measurable background level of extinction against which other 

extinction components (such as those caused by man-made pollutants) can be compared. 

Rayleigh scattering decreases with the fourth power of wavelength (Figure 2-13) and 

contributes a strongly wavelength-dependent component to extinction. When Rayleigh 

scattering dominates, dark objects viewed at distances of over several kilometers appear 

behind a blue haze of scattered light, and bright objects on the horizon (such as snow, 

clouds, or the sun) appear reddened at distances greater than about 30 km. 

2.4.2 Absorption by Nitrogen Dioxide Gas (bag) 

Of all gaseous air pollutants, only nitrogen dioxide (NO2) possesses a significant 

absorption band in the visible part of the spectrum. Nitrogen dioxide and its precursor, 

nitric oxide (NO), are emitted by high temperature processes such as combustion in 

fossil-fuel power plants. Nitrogen dioxide is strongly blue absorbing and can color 

plumes red, brown, or yellow (see Figure 1-6). The hue and intensity of color depend on 

concentration, optical path length, aerosol properties, conditions of illumination, and 

observer parameters. In non-urban settings, the area-wide concentration of NO2 is less 

important than the levels in coherent plumes. In Figure 2-13, the absorption of 0.1 ppm 

NO2, a concentration found in urban areas, is compared to the spectral extinction of pure 

air. At a wavelength of 0.55 μm, the absorption by NO2 is comparable to air scattering. 

The absorption coefficient drops off rapidly with wavelengths, which can give a 

brownish color when viewed against a white background. However, at concentrations 

more typical of class I areas, (less than 0.01 ppm) area-wide impacts of NO2 absorption 

are unimportant. 

2.4.3 Particle Scattering (bscat) and Absorption (bap) 

As the particle concentration increases from very low levels where Rayleigh scatter 

dominates, the particle scattering coefficient bscat increases until eventually bscat > bRg. 

At this point, particle scattering controls the visual quality of air. In understanding the 

degradation of visual quality of air two principal problems have been: 

1. Defining the size range and other physical characteristics of particles most effective 

in causing scatter and 

2. Defining the chemical composition and, thus, identifying the source of particles in 

this optically effective size range (Charlson et al., 1978). 

2.4.3.1 Light Scattering and Absorption by Single Particles—Particle size, refractive 

index, and shape are the most important parameters in relating particle concentration and 
18

particle derived extinction coefficients, bscat and bap. If these properties are established, 

the light scattering and absorption can be calculated. Alternatively, the extinction 

coefficient associated with an aerosol can be measured directly (see Chapter 3). 

Figure 2-13. Rayleigh scattering by air (bRg) is proportional to (wavelength)4

Reduced air density at higher altitudes causes a reduction of bRg. The NO2

absorption band peaks at 0.4 μm but vanishes in the red portion of the spectrum 

(Husar et al., 1979). 

The basic interactions between light and atmospheric particles are illustrated in Figure 

2-14. For spherical particles of sizes similar to the wavelength of visible light (0.1 to 1 

μm), the scattering and absorption of individual particles can be calculated through use of 

the “Mie” equations (Mie, 1908). 

Figure 2-14. Light scattering by coarse particles (>2μm) is the combined effect of 

diffraction and refraction. A) Diffraction is an edge effect whereby the radiation is 

bent to "fill the shadow" behind the particle. B) The speed of a wavefront entering 

a particle with refractive index n >1 (for water n = 1.33) is reduced. This leads to a 

1."

\

\

\

\

,

\ / ~1pp",1II02

\

\

\

\

, RAY _EIGH ,

~,;,,~rIlER~G..-- \

\ PHOTOPIC \

ni" RESPO..SE\ \

..... \

l \ \

, . \ ". \.

11)"3L-_-----'1........,..C-·_ L ----.L.~.""'----'-____'---'

1;1.3 (!.<l V.S O.ll

":"

E

-"

t-"

Z

w

U

i!

...

w

0

.. -~ lI":2 :2

0

i3Ii:

;:

X

w

WAlJllENrHH,~"'"

DIFFRoICflCN PHA.!E SHln
19

reduction of the wavelength within the particle. Consequently a phase shift 

develops between the wave within and outside the particle leading to positive and 

negative interferences. C) Refraction also produces the "lens effect." The angular 

dispersion by bending of incoming rays increases with n. D) For absorbing media, 

the refracted wave intensity decays within the particle. When the particle size si 

comparable to the wavelength of light (0.1 - 1 μm), these interactions (a-d) are 

complex and enhanced. For particles of this size and larger, most of the light is 

scattered in the forward hemisphere, or away form the light source. 

Figure 2-15. Single Particle Scattering and Absorption. For a single particle of 

typical composition the scattering per volume has a strong peak at particle diameter 

of 0.5 μm (m = 1.5 - 0.05I; wavelength: 0.55μm). The absorption per aerosol volume 

however is onlly weakly dependent on particle size. Thus the light extinction by 

particles with diameter less than 0.1 μm is primrily due to absorption (Charlson et 

al. 1978). Scattering for such particles is very low. A black plume of soot from an 

oil burner is a practical example. 

Charlson et al., (1978) used Mie theory to calculate the light scattering and absorption 

efficiency per unit volume of particle for a typical aerosol containing some light 

absorbing soot (Figure 2-15). As illustrated in the figure, particles in the size range of 0.1 

to 1 μm are the most efficient light scatterers. The remarkably high scattering 

efficiencies of these particles are illustrated by the following examples: a given mass of 

aerosol of 0.5 μm diameter scatters about a billion times that of the same mass of air; a 1 

mm thick sheet of transparent material, if dispersed as 0.5 μm particles, is sufficient to 

scatter 99% of the incident light, i.e. to obscure completely vision across such aerosol 

cloud (Husar et. al., 1979). 

Atmospheric particles or aerosols are made up of a number of chemical compounds. 

All of these compounds exhibit a peak scattering efficiency in the same particle size 

range as that calculated for the typical aerosol of Figure 2-15. Because of differences in 

refractive index, however, the values of the peak efficiency and the particle size at which 

it occurs vary considerably among the compounds. 

From Figure 2-16 it is apparent that, for relating light scattering to the aerosol, 

consideration needs to be given to the chemical composition of the scattering and 

absorbing aerosol. In particular, compounds that tend to draw water in the aerosol phase, 

such as sulfates, can be very important. Furthermore, the optical properties of a given 

SCATTERING

5

.05 .1 .2 .5 2 4

0L-_...L---L.-L.J-J...x+-_---I.~"'____\._L...l...J,,..l..LL..l--..L..: ........J

.01 .02

DIAMETER. j,tm
20

mass of aerosol collected over the arid western part of he country may be substantially 

different from those of the same mass of aerosol collected in a humid eastern U.S. air 

mass. 

2.4.3.2 Characteristics of Atmospheric Particles—Investigations of atmospheric aerosols 

over the past several years have revealed some important regular features (Whitby et al., 

1972). A typical atmospheric particle size distribution is shown in Figure 2-17. Most of 

the aerosol volume and mass is distributed in two modes: a fine mode centered at about 

0.3 μm and a coarse mode centered at 5 to 30 μm. The two modes are usually unrelated 

in that they have different compositions, sources, life times, and removal mechanisms. 

Figure 2-18 illustrates a pair of measured particle size distributions showing independent 

variation of fine particle concentration at a single site. 

The source of much of the fine mode particles is atmospheric transformation of 

reactive gases (e.g. sulfur dioxide, volatile organics, and ammonia) into aerosols such as 

sulfates, particulate organics, and ammonium compounds. Such transformed substances 

are called secondary particles. Other important fine mode sources include direct or 

primary particle emissions from combustion (fires, automobiles, etc.) and industrial 

processes. Coarse mode particles usually are derived from mechanical processes such as 

grinding operations or plowing. High winds can suspend large quantities of coarse 

particles. 

Figure 2-16. Single particle light scattering for several substances. Per unit 

mass, water scatters more light than SiO2 or iron. Furthermore, the water 

scattering efficiency peaks at about 1 μm, while the spheres of pure carbon or iron 

are most efficient scatterers at 0.2 μm (Faxvog, 1975). Carbon is te most efficient 

light absorbing substance, and hence 0.2μm carbon particles are the most efficient 

for total extinction (absorption + scatter) (Faxvog and Roessler, 1978). 

From the point of view of aerosol optics, a key question is whether an aerosol particle 

is spherical. For such particles, rigorous Mie theory is applicable and the optical 

properties can be readily calculated from their size and reflective index. Measurements 

10

...... H

.: ..: 20 . . ;\ / \ . . . C I' ,: : . \ !,,~ . I . 1 , . \! "

! ~i02\ If. , '. o I \~', '.l:

/ Fe "4.w~·:-· \....

"'~

DIAMETER, ,LIm
21

in St. Louis by Allen et al(1978) show that in the fine mode less than 5% of aerosol 

population exhibits nonspherical shape. Puschel and Wellman (1978) found that 

spherical particles also dominate fine mode aerosols near Cedar Mountain, Utah. Coarse 

particles are almost exclusively nonspherical and therefore the application of the Mie 

theory to calculate their optical properties is only a crude approximation. Currently there 

is an extensive body of experimental data on the optical properties of the nonspherical 

particles (e.g. Pinnick et al., 1976). 

2.4.3.3 Light Scattering by Typical Particle Distributions—Measured particle size 

distributions can be used in conjunction with Mie theory calculations for single particles 

as shown in Figures 2-15 and 2-16, to determine the contribution of different size classes 

to extinction. The result of this kind of calculation is shown in Figure 2-19. The peak in 

single particle scattering per unit volume at 0.3 μm coincides with the peak in observed 

aerosol volume (mass), so that the fine particles dominate extinction in most cases. 
22

Figure 2-17. Number, Surface, and Volume (Mass) distributions for typical 

aerosols in the lower atmosphere. They typical chemical consitutents of each mode 

are also given. The area under each curve segment is proportional to the fraction of 

the property (number, N; surface, S; volume, V) that is contained within a given size 

range (Whitby et al., 1972). 

Figure 2-18. Variation in Fine and Coarse Particle Modes. In the California 

ACHEX study, the measured areosol distributions have shown that the fine and 

coarse particle modes are essentially independent. In Rubidoux, for example, the 

size distribution has been observed to change from a fine particle-free distribution 

at 16:50 (Sept. 25, 1973) to the usual bimodal distribution at 17:20 (Hidy et al., 

1975). 

a.o

~. Nl)M~Hl

I

2.0 ....., I COAnSl MQDF

f I COMPOS InON I I;RUSTAL MAHHIAI. I FIN\, MOI)~

~llICON CUMPUUN"S J3 COtdPOSITION

S1JLfATl:S, IRON, ALUMINUM

SE .... SALT, PLI\NT ORGANICS, PARTICLES

,-- AM'"

~ITflATES.

aN IU \II,

CI\R!ON, , ... LEAD AND SOME

\ r- T~ACE CON:iTITUENTS

1.0 \

{

0

.001 , \ 10

MFlTlCLE DIA"ETEA, MICR(li'.~

120

-T-'r",

a 16:50 PST

(bscat =0.025 km"l

M 100 E

u o 17:20 PST M- Cbscat =0.369 km"l e 80 :L

a.

c 60 l:Il

.!:

c 40 ;;

'0

20

.01 .03 .06 0.' 0.3 0.61.0 3.06.010 30
23

Figure 2-19. Light scattering for a typical aerosol volume (mass) distribution. 

The calculated light scattering coefficient is contributed almost entirely by the size 

range 0.1 - 1.0 μm. The total bscat and total aerosol volume are proportional to the 

area under the respective curves (Charlson et al., 1978). 

Because the peak and shape of the bimodal particle mass distribution curve can 

vary, the light scattering characteristics of a given particle mass might also be expected to 

vary. As noted by Charlson (1978), however for the observed range of atmospheric 

particle distributions, the calculated scattering coefficient per unit mass is relatively 

uniform. Latimer et al. (1978) have determined the scattering efficiency per unit mass for 

several aerosol distributions. The calculated coefficient changes by no more than 40 

percent in the size range of 0.2 to 1.0 μm (Figure 2-20). 

Figure 2-20. The light scattering per unit volume for various aerosol size 

distributions (σg) is the highest in the 0.2 - 1.0 μm range, and does not vary greatly 

(Latimer et al., 1978). 

The relative consistency of calculated light scattering per unit mass over a range 

of particle distributions and the dominant influence of fine particles suggest that 

reasonably good approximations of light scattering coefficients can be obtained by 

measurements of fine particle mass. Simultaneous monitoring of the two parameters at a 

number of sites has been conducted by several investigators (Weiss, 1978, Patterson and 

....I

<:(

> '"e",II:

.,!!1-

....12 0-

>~

III - ....I Q 1.)<:(

i= II:

a:t'

<0

tI. ....I

VOLUME

0.01 0.1 1.0 10

PARTICLE DIAMETER, jJm

1.0 10.0

I

I

I

I

r

I

I

I

----.,.----------- : /7g=3

l-ACCUMULATION

I MODE I

I COARSE~

I MODE I

I I

I I I ,

0.001 '--_-'--L-L-LLJ...L.JU-_-L---L.....1....L..J...u...L.l..-_...J

0.1

0.10

M

rs ME

-'"

":" 0.01 E

orCl

:::

>

1;

SJ'i.

DG
24

Wagman, 1978, Macias et al., 1975, and White and Roberts, 1975). These investigators 

measured scattering per unit mass ratios of 0.003 km-1/μg/m3

 to 0.005 km-1/μg/m3 at 

several locations. The Mie calculations of Figure 2-19 suggest a ratio of 0.0033 km1

/μg/m3. Moreover, at these locations, correlations between fine particle mass and bscat

were consistently 0.95 or better. Figure 2-21 shows the relationship for St. Louis. The 

high correlations indicate that at the sites studied, fine particle mass dominates particle 

scattering. The relationship between several chemical components of fine particles and 

light scattering is discussed in Chapter 4. 

Coarse particles are a less significant cause of visibility degradation. Notable 

exceptions include wind-blown dust, fog, fly ash, and certain plumes. In case of windblown dust, for example, Gillette et al. (1978) have reported light scattering to mass 

ratios more than an order of magnitude lower than the ratios noted above, since coarse 

dust particles are much less efficient scatterers per unit mass (Figure 2-15). In clean 

areas where fine particle levels are low, however, coarse mode particle may contribute a 

non-negligible portion of light scattering. Secondly, it should be noted that a given bscat

to mass ratio is only applicable if the refractive indexes of the light scattering particles 

are the same. It is conceivable that, in the dry and arid western states, the aerosol 

refractive index and relative amounts of coarse and fine mode particles are sufficiently 

different that the scattering mass ratios quoted above would not be applicable. 

Preliminary results from project VISTTA, however (Macias, et al., 1979) suggest 

bscat/fine mass ratios in the southwest are 0.003 km-1/μg/m3

, or about the same as 

measured elsewhere. 

The wavelength dependence of light scattering ranges from the very strong blue 

scattering of air molecules and very small particles <0.05 μm to wavelength independent 

to “white” scattering for coarse particles > 5 μm. Thus Rayleigh particles (<0.05μm) in 

the exhaust of a poorly tuned automobile appear blue against a dark background while a 

fog of coarse water droplets appears white. A typical aerosol size distribution at 

moderate concentrations tends to scatter more blue light than red, but the wavelength 

dependence is not as strong as for Rayleigh particles. It has generally been observed that 

the wavelength dependence of light scattering diminishes as the total light scattering and 

humidity increases (Husar et al., 1979). 

In pristine class I areas on days when Rayleigh scattering dominates (bRg = 0.012 km1

), an addition of about 4 μg/m3 of fine particles (bscat = 0.013 km-1) would cause 

substantial “whitening” of the natural blue Rayleigh haze and the horizon sky (Charlson 

et al., 1978). At a fine particle level of 30 μm/ m3 (0.1 km-1), the wavelength dependent 

scatter would be controlled by the aerosol itself. 

2.4.3.4 Light Absorption by Typical Particle Distributions—Particle absorption (bap) 

appears to be on the order of 10 percent of particle scattering (bscat) in clean background 

areas (Bryce Canyon, Utah) and up to 50 percent of composition and particle size 

distribution (Waggoner, 1973, Bergstrom, 1973). The most important contributor to this 

absorption (in cities) appears to be graphitic carbon in the form of soot (Novakov et al., 

1978). The source of this highly absorbing submicrometer soot appears to be the 

combustion of liquid fuels, particularly in diesel engines; coal combustion may not be a 

major contributor (Charlson et al., 1978). 
25

Figure 2-21. Light scattering vs. fine particle mass. Simultaneous monitoring of 

bscat and fine particle mass in St. Louis showed a high correlation coefficient of 

0.96, indicating that bscat depends primarliy on the fine particle mass concentration 

(Macias et al., 1975). 

2.5 POLLUTANT/IMPAIRMENT RELATIONSHIPS 

The scattering and absorption from an aerosol cloud depend on the wavelength of 

incident light, the angle of observation, and the concentration and size distribution of the 

light scattering and absorbing aerosol and gases. The role of these parameters will be 

examined briefly as applied to the three major types of visibility impairment: general 

haze, plume blight, and atmospheric discoloration. 

2.5.1 General Haze—Visual Range, Contrast, Color 

Visibility in the atmosphere of pristine class I areas is extremely sensitive to 

incremental additions of fine aerosol. The sensitivity of clean atmospheres to change is 

illustrated in the graph of visual range versus extinction (fine particle mass) in Figure 2-

22. 

However, in many class I areas, where viewing distances are 50 to 100 km, a 

reduction in calculated visual range (for example, from 350 km to 250 km) will not be the 

most noticeable impact of incremental pollution. The reduction in apparent contrast and 

discoloration of nearby objects and sky are the main effects perceived in such areas. 

40

20

1.0

ST. LOUIS AEROSOL

APRll,1975

4/17 4/18 4/19 4/20 4/21 4/22

TIME (days)
26

Figure 2-22. Effects of fine particle increments on calculated visual range. 

Addition of 1 μg/m3

 to a clean atmosphere reduces visual range by 30 percent. 

Addition of the same amount when bckground visual range is 35 km (20 miles) 

produces a 3 percent reduction. 

Figure 2-23. Effect of fine particle increments (calculated) on apparent contrast 

(measured) between sky and target (mountain) (Malm, 1979b). 

400

300

bRg • (I.(lll<m- 1

b• .,IFINE MASS: 0.(1(14 km- 1l"g!m3

HUMIDITY < 60%

100

ARROWS INDICATE

ADDITION OF 11'g/m3

)""",",m

(1.0 10 20 30 40

FINE PARTICLE CONCENTRATlON.l'glm-3

50

'E lICTINCnOH (!rIa...•I).

(QVIV_LENT f!lPoiE P~'IlCLi: Co.\CI!NHUITION 1Jig(m3)

I.

01 rMtuunCOtli".&.$T

OFTA"l;;l;Tka) -C.72

OlIILTANCE l'OTAAGITb)- t;;(Il.._

.'---'---'--....I..----'--'---'-....:::::r

001 0 OZ 0.03 0.04 Out 1).01

1S ....,..J
27

Figure 2-23 shows that apparent contrast between an object and sky also decreases 

rapidly with increasing extinction in clean atmospheres. The graph also indicates the 

calculated concentration of fine particles spread throughout the viewing distance 

associated with the listed extinction coefficient. The accompanying photographs show 

the dramatic changes in contrast detail of even a 3 to 5 μg/m3

 increment of fine particles. 

A similar increment in a relatively polluted area (20 μg/m3

 of fine particles) might not be 

perceptible. Calculation of contrast changes (for large targets) accompanying 

incremental particle levels indicate that the maximum decrease in contrast will occur for 

objects located at distances of about one-fourth of the visual range from the observer 

(Malm, 1979a). Thus, in an initially clean atmosphere, a fine particle increment produces 

maximum contrast reduction for large objects 50 to 100 km away. A reduction in visual 

range of 5 percent would result in a reduction in contrast of 0.02 for those objects. As 

discussed in Section 2.2.1, such a change may be just perceptible. The contrast detail 

(texture, small objects) and coloration of closer objects in contrast may, however, be 

affected to a greater degree (Henry, 1979, Malm, 1979a). 

The perceived color of objects and sky is also changed by the addition of aerosols. 

Because of the difficulties and uncertainties in specifying perceived color, only a 

qualitative description is possible. In general, the apparent color of any target fades 

toward that of the horizon sky with increasing distances from the observer. Without 

particles, scattered air light is blue, and dark objects appear increasingly blue with 

distance. The addition of small amounts (1 to 5 μg/m3) of fine particles throughout the 

viewing distance tends to whiten the horizon sky making distant dark objects and 

intervening air light (haze) appears grayer. According to Charlson et al., (1978), even 

though the visual range may be decreased only slightly from the limit imposed by 

Rayleigh scattering the change from blue to gray is an easily perceived discoloration. 

The apparent color of white objects is less sensitive to incremental aerosol loadings. As 

for contrast, incremental aerosol additions produce a much greater color shift in cleaner 

atmospheres (Malm, 1979a). 

Aerosol haze can also degrade the view of the night sky. Light scattering and 

absorption diminish star brightness. Perception of stars is also reduced by an increase in 

the brightness of the night sky caused by scattering of available light. In or near urban 

areas, particle scattering of artificial light significantly increases night sky brightness. 

The combination of extinction of starlight and increased sky brightness markedly 

decreases the number of stars visible in the night sky at fine particle concentrations of 10 

to 30 μg/m3

 (Leonard et al., 1977). 

Thus, the overall impact of aerosol haze is to reduce visual range and contrast, and 

change color. Visually the objects are “flattened” and the aesthetic value of the vista is 

degraded even though the distances are small relative to the visual range. Much of the 

scenic value of a vista can be lost when the visual range is reduced to a distance that is 

several times greatest line-of-sight range in the scene. 

 

2.5.2 Discolored Layers 

Layers of colored haze can be caused by particles and nitrogen dioxide. The visual 

impact depends greatly on a number of factors such as sun angle, surrounding scenery, 

sky cover, viewing angle, perception parameters, and pollutant loading. Quantitative 
28

theoretical treatments of these effects, combining radiative transfer and human 

perception, are not fully developed. The following general observations can, however, be 

made (Charlson et al., 1978): 

1. The relative importance of aerosol or NO2 in determining the color and appearance of 

a plume or haze layer can be addressed, in part, in terms of the relative extinction as a 

function of wavelength. 

2. Suspended particles generally scatter much more in the forward direction than in 

other directions. This fact means a plume or haze layer can appear bright in forward 

scatter (sun in front of observer) and dark in back scatter (sun in back of observer) 

because of the angular variation in scattered air light (Figure 2-24). This effect can 

vary with background sky and objects. 

3. The added air light (see 2.3.1) is both angle and wavelength (color) dependent and the 

wavelength dependence can vary with illumination angle. Extinction is wavelength 

dependent but not angle dependent. 

4. A visible aerosol layer will be brighter than an adjacent particle-free layer for sun 

angles (in front of observer) less than 30o

. At larger angles, the aerosols will usually 

be darker. 

5. Aerosol optical effects alone are theoretically capable of imparting a reddish-brown 

color to a haze layer when viewed in backward scatter. NO2 would increase the 

degree of coloration in such a situation. Specific circumstances of brown layers must 

be examined on a case-by-case basis. 
29

Figure 2-24. Effect of sun angle on visibility. 

2.5.3 Plume Blight 

The description of discolored layers in the previous section applies to plume blight. 

The significant factors affecting plume visibility are listed in Table 2-2 and Figure 2-25. 

The plume will have a brightness and color that is different from its background, and this 

difference can be approximated by simplifications to the radiative transfer operation for 

optically “thin” plumes; that is, plumes that transmit a large fraction of incident light 

(Latimer et al., 1978, Williams et al., 1979). 

The plume air light is a strong function of scattering sun angle. A plume viewed in 

forward scatter will appear bright against the sky or background targets. The same plume 

can appear dark against the sky and bright against dark targets at scattering angles greater 

than 30o

. Detailed calculation for models requires particle concentration and size 

information for the plume and similar information or extinction measurements for the 

surrounding atmosphere. Increases in extinction resulting from plume absorption, from 

soot or NO2, for example, will make the plume darker at all sun angles. 

Because the line of demarcation between the plume and sky is “fuzzy,” it has been 

argued (Latimer et al., 1978) that the threshold contrast for perception may be greater 

than that for dark targets with sharp boundaries (about 2 percent). Contrast 

enhancement* by the eye-brain system may, however, compensate for lost sharpness. 

- ....

L..OOIiI ... 'TtRl'A~ ,.,.., '"UIJ. IliP :1--= :.-1ttnl.1

'll'r....., Iiii~ ':o('a.-TTF! r........ I:<--......'r... r3rn "'-.oI.-lT ..-=--.,... 11.

,I

,ei } (

,oJ' ,/ ./ / ( I I

J f I i

/ .~ / j / / ) .'

",/ )' ./ ./ i ,/ (' )

,

J' .r , I I

--- ... l J

__i -i -) ~_

,.~~.

~- - -

.'1 !l.IlItI bE .. lroIC:I CJUoERIJ'EF: U"&lI • • Ii!-.'I~IY;:

~"':I""P.~ le,TTU_ 8EI~~ L!!j ......,. ",."(~~ j~~TTn ro!~ ~:Ta'HUIEY! .'l !"!cTn.,
30

Additional experimental data are needed to define the threshold of perceptibility for 

plumes and haze layers. 

Figure 2-25. Appearance of a plume (Charlson et al., 1978). 

SCATTERED

SUNLIGHT

TRANSMITTED

LIGHT

OBSERVER

VIEWING

BACKGROUND

BACl<<lROUND

LUMINANCE
31

Plume/source related factors Environmental Factors

Particle size distribution Sun position 

Particle mass concentration Time of day 

Particle mass distribution (non-uniform 

mass distribution) 

 Day of year 

Plume diameter Longitude 

Stack height Latitude 

Stack exit velocity Cloud cover (sky color) 

Particle density Other light sources 

Water vapor content Ambient temperature 

Particle complex index of refraction (plume 

color) 

Relative humidity 

NO2 concentration in the plume Wind velocity 

 Wind direction 

Observer related factors Wind turbulence 

Observer position Terrain 

Observer sensitivity Background 

Table 2-2. Factors affecting plume appearance (Charlson et al., 1978). 
32

REFERENCES FOR CHAPTER 2 

Allen, J., R. B. Husar, and E. S. Macias (1978) In: Aerosol Measurement, Lundgren, 

D.A. Ed., University of F1orida Press, Gainesville, F1a. 

Bergstrom, R. W. (1973) Extinction and Absorption Coefficients of the Atmospheric 

Aerosol as a Function of Particle Size. Beitr A. Phys. Atm., 46: 223. Beitr A. Phys. Atm., 

46: 223. 

Blackwell, H. R. (1946) Contrast Thresholds of the Human Eye. J. Opt. Soc. Amer. 36: 

642-643. Brown, W. R. S. (1957) Color Discrimination of Twelve Observers. J. Opt. Soc. 

Amer. 47: 142. 

Campbell, F. W., and L. Maffei (1974) Contrast and Spatial frequency. Scientific 

American 231: 106-112. Chandrasekhar, S. (1950) Radiative Transfer, Clarendon, 

Oxford. 

Charlson, R. J., A. P. Waggoner, and J. F. ThieIke, (1978) Visibility Protection for Class 

I Areas. The Technical Basis. Report to Council of Environmental Quality. Washington, 

D.C. 

Faxvog, F. R. (1975) Optical Scattering per Unit Mass of Single Particles. Applied Opt. 

14: 269-270. Faxvog, F. R. , and Roessler (1978) Carbon Aerosol Visibility versus 

Particle Size Distribution. Applied Opt. 17: 261-262. 

Gillette, D. A., R. N. Clayton, T. K. Mayeda, M. L. Jackson, K. Sridhar, (1978) 

Tropospheric Aerosols From Some Major Dust Storms of the Southwestern U.S. Journal 

of Applied Meteorology 17: 832-845. 

Gregory, R. L. (1978) Eye and Brain: the Psychology of Seeing. McGraw-Hill Book Co., 

New York. 

Henry, R. C. (1977) The Application of the Linear System Theory of Visual Acuity to 

Visibility Reduction by Aerosols. Atmospheric Environment 11: 697-701. 

Henry (1979) Psychophysics and Visibility Values. In: Proceedings of the Workshop on 

Visibility Values, Fox, D. , R. J. Loomis and T. C. Greene (Technical Coordinators). Fort 

Collins, Colorado. U .S. Department of Agriculture. 

Hidy, G. M. et al. (1975) Characterization of Aerosols in California. Report SC 534.25 

FR 4. California Air Resources Board, Contract 358, Rockwell Science Center, Thousand 

Oaks, California. 

Horvath, H. (1971) On the Applicability of the Koschmieder Visibility Formula. 

Atmospheric Environment 5: 177-184. 
33

Horvath, H., and K. E. Noll, (1969) The Relationship Between Atmospheric Light 

Scattering Coefficient and Visibility. Atmospheric Environment 3: 543-550. 

Husar, R., W. H. White, D. E. Patterson, and J. Trijonis (1979) Visibility Impairment in 

the Atmosphere, Draft report prepared for U.S. Environmental Protection Agency under 

Contract Number 68022515, Task Order No.28. 

Konig, A., and E. Brodhum (1889) Experimentelle Untersuchungen ueber die 

physchaphysische Fundamen- talformel in Bezug auf den Gesichtssinn. 

Land, E. H. (1977) The Retinex Theory of Color Vision, Scientific American, 108-128, 

December. 

Latimer, D. A., R. W. Bergstrom, S. R. Hayes, M. K. Liu, J. H. Seinfeld, G. Z. Whitten, 

M. A. Wojcik, M. J . Hillyer, (1978) The Development of Mathematical Models for the 

Prediction of Anthropogenic Visibility Impair- ment, EPA-450/3/78-110a. 

Leonard, E. M., M. D. Williams, and J. P. Mutschlecner, (1977) The Visibility Issue in 

the Rocky Mountain West, Prepared by Los Alamos Scientific Laboratory for the 

Department of Energy , preliminary draft report, September 30. 

MacAdam, D. D. (1942) Visual Sensitivities to Color Differences in Daylight. J. Opt. 

Soc. Amer. 32: 247-273. 

Macias, E. S., R. B. Husar, J. D. Husar, (1975) Monitoring of Atmospheric Aerosol Mass 

and Sulfur Concentration. International Conference on Environ. Sensing and Assessment. 

Las Vegas, Nevada, September. 

Macias, E. S., D. C. Blumenthal, J. A. Anderson, B. K. Cantrell, (1979) Characterization 

of Visibility, Reducing Aerosols in the Southwestern United States; Interim Report on 

Project VISTT A MRI Report 78 IR 15-85. 

Malm W. (1979a) Visibility: A Physical Perspective. In: Proceedings of the Workshop in 

Visibility Values, Fox, D., R. J. Loomis and T. C. Greene (technical Coordinators). Fort 

Collins, Colorado, U.S. Dept. of Agriculture. p. 56-68 

Malm, W. (1979b) Personal Communication, Environmental Protection Agency, 

Environmental Monitoring and Support Laboratory, Las Vegas, Nevada. 

Middleton, W. E. K. (1952) Vision through the Atmosphere, University of Toronto Press, 

Toronto, Canada. 

Mie. G. (1908), Beitrage zur optic truber Medien, speciell kolloidaler Metallosungen. 

Ann. Phy. 25: 377. 
34

Niemann, B. L., E. Y. Tong, M. T. Mills and L. Smith (1979) Characterization of 

Regional Episodes of Particulate Sulfates and Ozone over the Eastern United States and 

Canada. Paper to be presented at Symposium on Long-Range Transport, World 

Meteorological Organization, Sofia, Bulgaria, October, 1979. 

Novakov, R., et al. (1977) Report, LBL-6819, Lawrence-Berekley Laboratory, Berkeley, 

California. 

Patterson, D. K. and J. Wagman, (1977) Mass and Composition of an Urban Aerosol as a 

Function of Size for Several Visibility Levels. J. Aerosol Sci. 8: 262-279. 

Pinnick, R. G., D. E. Carroll, and D. J. Hofmann, (1976) Polarized light scattered from 

Monodispersal Randomly Oriented Non-spherial Aerosol particle measurements Appl. 

Optics 15: 384. 

Pueschel, R. F., and D. L. Wellman (1978) On the Nature of the Atmospheric 

Background Aerosol. Atmospheric Physics and Chemistry Laboratory, National Oceanic 

and Atmospheric Administration, Boulder, Colorado. 

Taylor, J. H. (1964) Practice Effects in a Simple Visual Detection Task. Nature, 201: 691. 

Waggoner, A.P., et al. (1973) Optical Absorption by Atmosphere Aerosols. Applied 

Optics 12:896. Weiss, R. (1978) P.hD. Dissertation, University of Washington, Seattle, 

Washington. 

Whitby, K. T., R. B. Lusar, and Lui, B.Y.H. (1972) The Aerosol Size Distribution, J. 

Colloid Interface Sci., 39: 177-204. 

White, W. H., and P. T. Roberts, (1975) On the Nature and Origins of VisibilityReducing Aerosols in the Los Angeles Air Basin, W. M. Keck Laboratories, California 

Institute of Technology. 

Williams, M. D., E. Treiman, M. Weeksung (1979) Utilization of a Simulated 

Photograph Technique as a Tool for the Study of Visibility Impairment LA-UR-79-1741, 

Los Alamos Scientific Laboratory, Los Alamos, N.M. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 3 
3 METHODS FOR MEASURING ATMOSPHERIC VISIBILITY 

IMPAIRMENT 

 Measurements of visibility-related parameters in class I areas will be an important 

component of programs for making progress toward the national goal. Specifically, 

monitoring is necessary for: 

1. Establishing a base line range of visibilities for a given area to be used in 

evaluating potential impacts of proposed sources; 

2. Determining the extent to which man-made air pollution and natural sources 

cause or contribute to visibility impairment; 

3. Identifying specific sources of air pollution that cause or contribute to 

visibility impairment; and 

4. Monitoring the effectiveness of visibility protection programs over time. 

 Meeting these objectives will require measurement of optical parameters, pollutant 

levels, meteorological variables, and scenic characteristics. This chapter discusses the 

applicability of various visibility monitoring approaches and outlines current efforts to 

establish class I area visibility monitoring networks. 

3.1 VISIBILITY-RELATED PARAMETERS 

 Because visibility involves human perception of the environment, no instrument truly 

measures visibility (Malm, 1979a). Thus it is essential to select appropriate measurable 

parameters, which can be related to both air quality of the environment and human visual 

perception. Important optical indices of visibility discussed in Chapter 2 include visual 

range, apparent contrast, extinction coefficient, and the variation of these parameters with 

wavelength (color) .The major categories of impairment (Chapter 1) to be dealt with 

include plume blight, general haze, and elevated layers of discoloration. 

 The most important indices for visibility measurements are apparent contrast and 

atmospheric extinction coefficient. In practice, the scattering component of the extinction 

coefficient, b scat, is usually reported. Preliminary measurements in non-urban areas 

suggest that the scattering coefficient is 90 percent of the extinction coefficient 

(Charlson, 1979). Extinction coefficient is directly related to the visual air quality and 

represents the optical characteristics of the pollutants along an optical path that contribute 

to visibility impairment. The extinction coefficient, plus the optical effects of the target 

and illumination, determines the apparent contrast (visibility) of a target (such as plume 

or mountain) against a background (sky or other surroundings). Thus, extinction 

coefficient is the optical parameter related to air quality, and contrast is the optical 

parameter that describes visibility. Both extinction coefficient and apparent contrast are 

measurable at several wavelengths. 
 Contrast and light scattering measurements are directly applicable to visibility 

impairment caused by general haze. Plume blight and layers of discoloration might be 

assessed by employing contrast measurements and aircraft mounted extinction 

measurements. Direct observation of these kinds of impairment may, however, be the 

most practical approach for recording such conditions. 

 Measurement of aerosol parameters is a useful adjunct to optical measurements. 

Fine-particle concentrations, detailed size distributions, and chemical composition can be 

used to calculate extinction coefficient. More importantly, such data, when coupled with 

meteorological information, permit assessment of the contribution of anthropogenic and 

natural sources to visibility impairment. 

3.2 MEASUREMENT METHODS 

Regardless of the specific monitoring application, there are four components useful in 

characterizing visibility impairment and providing information that may link visual 

effects to their sources: human observations and measurements of optical, meteorological 

and pollutant parameters. 

3.2.1 Human Observations 

Since visibility is an interpretation of what is perceived by the human eye, it is 

essential that any monitoring effort have some relation to human observations. Human 

eye observation is the sole source of long-term visibility (visual range) data. 

Unfortunately, human eye observations depend not only on illumination, target 

characteristics, and air quality, but also include the effects of varying visual perception 

and subjective judgment. Nevertheless, with the development of observer-based visibility 

indices (Craik, 1979) and an adequate training program, human observations can provide 

useful information about visibility and can complement instrumental measurements. 

The Federal Land Managers of parks and wilderness areas represent an important 

resource for human observation of visibility in class I areas. Although the traditional 

observation for visibility has been "visual range," i.e., the farthest point that can be seen, 

the U.S. Forest Service has incorporated more elaborate visual judgments into their 

Landscape Management System (USFS, 1973). The visual elements of a vista are 

described in terms of "form, line, color, and texture. " These elements represent 

subjective descriptions of contrast, the basic optical parameter. Meaningful judgments 

made by a trained observer about the contrast and coloration of a vista and about the 

presence of plume blight can be invaluable in assessing visibility impairment. 

3.2.2. Optical Measurements 

In order to quantify scenic contrast as perceived by the eye, optical measurements 

must be made. The visual air quality along the optical path must also be measured in 

order to determine the effect of atmospheric contaminants on the perceived scene. 
A number of optical devices are available or under development that measure some 

property of visibility. The most obvious optical device is the standard photographic 

camera. Visibility monitoring should always include photography in some form, at least 

for documentation of existing good visibility conditions or impairment problems. The 

two general film formats are: negatives (from which prints may easily be made) and 

reversal film ("slides"). Both slides and negatives produce about equal color rendition. 

Prints made from negatives, however, are subject to quality control uncertainty during the 

additional laboratory printing process and are one more generation removed from the 

original image. Slides are more cumbersome to use but normally are more economical 

and more visually accurate than prints. 

The chief use of photographs or slides is in preserving a scene in a form similar to the 

view as originally perceived. A secondary use is photogrammetry, the measurement of 

the density of color of individual sections of the picture to determine quantitative contrast 

values of different elements of the scene. The accuracy of this process, however, is 

sensitive to variations in film density and exposure and requires a densitometer closely 

matched to the response curve of the particular film being used. 

Photometers measure light intensity and range in complexity from the photographer's 

light meter to a television camera. The principle of operation for each instrument is the 

same and is somewhat analogous to the human eye. The heart of a photometer is the 

photodetector, which converts brightness into representative electric signals. By the use 

of combinations of lenses and filters, different optical properties, such as color, may be 

determined. 

Photometers designed specifically to measure properties of atmospheric visibility over 

an optical path to a target are telephotometers, so named because they resolve visual 

detail at a distance. Telephotometersprovide an output proportional to the absolute 

brightness of a target within the optical field of view. The human sensation of seeing, is 

however, produced not by absolute brightness levels of light, but by contrast in 

brightness or color between two objects. Therefore, the most practical application of a 

telephotometer is as a contrast measuring device-comparing the brightness of color of an 

object to a background. The visibility of a target can be quantified in terms of its contrast 

at a given distance from the observer and is dependent upon the inherent contrast of the 

target, uniformity of the atmosphere along the sight path, angle of observation, and 

illumination of the sight path. A disadvantage of using telephotometers is that it is 

difficult to separate the different effects from each other. This disadvantage is important 

if the goal is to isolate the contribution of anthropogenic air quality on visibility. 

A transmissometer may be used to measure the optical characteristics over a given 

path. This instrument is comparable to an application of a telephotometer in which a 

known light source becomes the target. Transmission instruments measure the amount of 

light transmitted from a specified source to a receiver, allowing the direct calculation of 

the average extinction coefficient of the air along the instrument path. The light lost along 

the path is either scattered out of the path or absorbed by gas molecules and aerosol in the 

path. The path for transmission instruments is long compared to the small volume 
measured by scattering instruments and short compared with the 20 to 100 km paths used 

by telephotometers. 

Transmissometers use artificial light sources; either the receiver or reflectors must be 

placed at one end of a base line and the transmitter at the other end. This fixed base line 

does not allow flexibility to measure visibility-related variables in different directions. 

When transmissometers are used in very clean atmospheres, such as class I areas in the 

Southwest, their critical sensitivity to atmospheric turbulence can introduce error. 

Additionally, these instruments are usually limited to a single wavelength and not very 

portable. 

Scattering instruments are used to measure a basic optical property of the air sample: 

the volume scattering function. The measurement is independent of target properties, 

natural illumination of the atmosphere, and distance between the observer and the target. 

Scattering instruments include integrating nephelometers, back-scatter meters, forwardscatter meters, and polar nephelometers. 

Integrating nephelometers perform a point measurement of the light scattered over a 

range of angles and permit determination of the scattering component of extinction, bscat. 

Since the contribution of air itself to bscat is known, the bscat measurement permits 

determination of light scattering by particles. In clean areas where light scattering 

dominates extinction, bscat approximates the extinction coefficient, bext. Because bscat is 

measured at a point, it can be directly related to simultaneous point measurements of 

aerosol properties. The air sampled by the integrating nephelometer is enclosed and 

illuminated indirectly by an artificial light source, allowing automated continuous day 

and night operation. Enclosed instruments also allow control of ambient air conditions; 

such control permits study of the influence of relative humidity. Nephelometers have 

been used in a variety of applications, including to a limited extent, applications in class I 

areas (Charlson et al., 1978). Models differing in wavelength response and sensitivity are 

available. Since nephelometers involve point measurements, care must be taken to 

minimize the influence from local sources, such as automobiles or cigarette smoke. 

Unless nephelometers are physically moved through a plume, inhomogeneous 

impairment, such as plume blight, cannot be detected. Nephelometers cannot be used to 

measure absorption and cannot detect discoloration caused by NO2. 

3.2.3. Meteorological Variables 

Meteorological conditions largely determine the extent and speed with which 

pollutants disperse, and thus have a major effect on visibility. Four specific 

meteorological parameters that strongly influence visibility include: wind speed and 

direction, mixing height, and relative humidity. Solar illumination and cloud cover affect 

atmospheric stability and are also important. Instrumentation for meteorology is 

standardized and will not be discussed here 

3.2.4. Pollutant Measurements 

 

A number of methods and instruments can be used to measure the size distribution, 

mass concentration or number concentration of the airborne particles that usually 
dominate the scattering of light. Nitrogen dioxide gas can also be measured. The Mie 

theory of light scattering allows measurement of the aerosol size distribution to be used to 

compute the scattering of light. These relationships allow a calculation of contrast, visual 

range and color change, but not as precisely as by more direct measurements. The most 

important advantage of measuring aerosol mass, size, and chemical properties is that 

when combined with meteorological data, such measurements aid in the identification of 

natural and anthropogenic aerosol sources in order to determine which are most important 

in affecting visibility. 

 

The most useful particle monitoring instruments for visibility studies include those 

that permit analysis of chemical composition and particle size. Although multistage 

cascade impactors can be useful for detailed studies, samplers that permit separation of 

optically important fine (<2 .5.um) and coarse particles (>2 .5.um) are acceptable. These 

latter samplers, which are termed dichotomous samplers, have several arrangements for 

size separation, including direct and "virtual" impaction. (Stevens et al, 1978). 

3.3 COMPARISONS AND RECOMMENDATIONS 

Each of the visibility-related methods described above has inherent strengths and 

weaknesses, which limit its optimal application and utility. The characteristics and 

applicability of important methods are compared in Table 3-1. No single instrument or 

approach can provide sufficient information for meeting class I area visibility monitoring 

objectives. A significant limitation for most of the methods is securing locations in class I 

areas that are reasonably accessible and can accommodate instrument power 

requirements. 

Recently, EPA sponsored a workshop on visibility monitoring to discuss alternate 

monitoring methods and make recommendations for further work (Malm, 1978). A 

number of technical experts and managers from industry, Federal and State agencies, and 

contractors participated in these discussions. As interim guidance for developing 

visibility monitoring programs in class I areas, this report adopts the recommendations of 

the workshop participants. Specifically: 

1. Base line monitoring should be conducted for at least I year, preferably a 

meteorologically typical year; 

2. Visibility measurements should include: 

a. Color photographs or slides and human observations of selected vistas, 

b. Multiwavelength telephotometer measurements of sky and target contrast 

of the selected vistas, 

c. Integrating nephelometer measurements of aerosol scattering; 

3. Evaluation of source-receptor relationship requires: 
a. A two-stage size-segregating particulate sampler compatible with gravimetric 

and chemical analyses techniques, 

b. Sensors of wind speed and direction, representative of meteorological 

transport, 

c. Relative humidity sensor, 

d. An NO2 detector, if necessary. 
TABLE 3-1. VISIBILITY MONITORING METHODS"

Method

Human observer

Integrating riephelometer

Multiwavelength

telephotometer

Transmissometer

Parameters Measured

Perceived visual quality

Atmospheric Color

Plume blight

Visual range

Scattering Coefficient

(bscat) at site"

Sky apd/or target

radiance, COntrast at

various wavelengths

Long path extinction

coefficient (bextI

Advantages

Flexibility. jUdgment;

large existing data base"

{airpOrt visual rangel.

Continuous readings;

unaffected by clouds,

night; bscat directly

relatablno fine

conCerftTation at a poirit;

semi-ponable; used lna

number of "previous stutlies;

sensitiw models available; 4Utl;)mated.

Measurement over long

view path (up to 100 kml

with suitable illumination

and target, contrast

transmittance, total extinction, and chromati·

city over sight path

can be determined; includes scattering and

absorPtion from all

sources; can detect

plume blight; automated.

Measurement over medium

"view path kml;

measures totel extinction,

scattering and absorption;

unaffected by clouds,

night.

Limitations

Labor intensive; variability

"In observer perception;

suitabte targets for visual

range not generally

available.

Point measurement, requires

assumption of homogeneous

distribution of particles;"

neglects extinction from"

"absorption, eoane particles

;:. 3 to 10 um; must consider

humidity effects at high RH.

sensitive to illumination

conditiOns: useful only

in daylight; relationship to

extinction, aerosol relationship possible only

under doudless skY1; requires .farge, uniform

targets.

Calibration problems: single

wavelenqth; equivalent to

"point measurement in areas

with long view paths (50-

100 km); limited applications to date still

under development.
. . '.' . . . .

TABLE 3-}.

"" Photographv

"

.:: . '.'

Hi Vol "

Dieliotori'\QU!8nd

"

"samplers (several "

,fun¢tmentaUv

different types)

.....

ViSual

Btumeblight

Color"

Contrail (limited)

Particles

TSP

Size

particles

(>2 stages)

Fine partides"

« 2.5 um)

coarse particles

"" (2.5 to 15 um)

inhaJable particles

(0 to 15

'.. . .

to

"" ofVisual

documentation of vista

""" ""

. . .'. .

of

.

'.' ." .

,

"

lutiQn, optically im- Porttirit aerosol "

loW

particle bC>UOce;

to"8I.lt.Qri'lated composi-

""" anaIYsis;irUto,."

"r:nated

abte:

underdeVelOpment.

Sens.itive to lighting

conditions; degradation

"in storage: contrast

measurement from film

subject to si9nificant

errors..

NotalwaysrelatBIJle "to visual air quaiitY;

POi!'rt measurement."

OOtlS not 5epatate "sizes;

sampling anifacts for

nitrate, sulfate; oot avtOrr1ated. "

Particle boUnCe, wall

losses; labOt: inU!'nSiiie.

'.'.

sOmetaige.:particfe 'Penetration; 24 lwui"

or longef' s.i!mPle required

"in clean areas for mass

";:n;easurement; automated

reiati\'eIV unteSted" in remote iocatioos.

8iCtlarison et aI., 1978; Maim, 1978b, 1978c;Tombach, 1978)."
Comprehensive monitoring of this kind will not be needed in all class I areas. Over the 

next several years, visibility monitoring in various regions of the country may indicate a 

smaller set of measurements, which can be used for most monitoring goals. In the 

interim, in programs with limited resources, the limitations and strengths outlined in 

Table 3-1 should be considered when choosing monitoring sites and methods. EPA is 

preparing detailed guidance on visibility monitoring. 

3.4 VISIBILITY MONITORING PROGRAMS 

The only substantial visibility monitoring program to date has been the National 

Weather Service hourly visual range observations. These observations have proven useful 

in identifying trends at particular locations but more accurate optical measurements and 

additional air quality parameters will be necessary for visibility modeling and source 

identification. Various optical qualities of the atmosphere have been studied in a number 

of short-term programs, generally with the use of turbidity and/or nephelometer 

measurements. 

One of the first major instrumental monitoring programs designed to study visibility, 

air quality, and meteorological variables near class I areas was the Cedar Mountain, Utah 

visibility program which was begun in 1976 by NOAA and EPA (Allee, 1978). The site 

is north of several major class I areas in southeast Utah. Many measurements were taken 

with different instruments and much of the data is still being analyzed. The general 

conclusion thus far is that northerly air masses bring in substantially cleaner air than from 

other directions, causing base line visibility to vary dramatically. In addition, some 

information about the limitation of visibility monitors and spatial homogeneity of the 

surrounding atmosphere has been gathered. 

The Cedar Mountain Study has been incorporated into EPA 's project VIEW 

(Visibility Investigative Experiment in the West), which is now is operation in the 

Southwest with 14 additional monitoring sites (Figure 3-1). The VIEW program is a 

prototype visibility-monitoring network that may be suitable for monitoring visibility in 

and near class I areas in the Southwest. At each site, a telephotometer records apparent 

contrast of different targets in different directions (denoted by the arrows at each location 

on the map in Figure 3.1). Where practical, sites are outfitted with additional visibilityrelated devices, such as nephelometers, particle samplers, photographic cameras, and 

meteorological instruments. Most of the sites are operated by personnel of the National 

Park Service, who also record visual observations. 

Data from the VIEW network are currently being processed. Preliminary results 

appear similar to those reported at Cedar Mountain. The most obvious result so far is the 

strong correlation between observed visibility and air mass movement. Figure 3-2 is a 

sample plot of target contrast at Canyonlands National Park for September, 1978. 

Passages of weather systems from the Pacific Northwest, which generally bring in 

cleaner air, correlate closely with better visibility, measured as increasing target contrast. 

Further analysis of pollutant composition is needed to identify the causes of reduced 

visibility. 
Visibility monitoring is also planned by the Electric Power Research Institute, the 

National Park Service, the Tennessee Valley Authority, and other groups. Most of these 

projects are now in the planning or initiation stage. 
':'"

SOUTHWEST VISIBILITY MONITORING NETWORK

!:TA~--l

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REFERENCES FOR CHAPTER 3 

Allee, P., R. F. Pueschel, C. C. Van Valin and W. F. Roberts (1978) Air Quality Studies 

in Carbon and Emory Counties, Utah. Draft. NOAA Environmental Research 

Laboratories, Atmospheric Physics and Chemistry Laboratory, Boulder, Colo. 

 

Charlson, R. J., A. P. Waggoner, And J. F. Thielke (1978). Visibility Protection in Class I 

Areas: The Technical Basis. Report to the Council of Environmental Quality, 

Washington, D.C. 

Charlson, R. J. (1979) Personal Communication. University of Washington, Seattle, 

Washington, August. 

Craik, K. H. (1979) The Place of Perceived Environmental Quality Indices (PEQIS) in 

Atmospheric Visibility Monitoring and Preservation. In: Proceedings of the Workshop in 

Visibility Values, Fox, D., R. J. Loomis and T. C. Green (technical coordinators). Fort 

Collins, Colorado, U.S. Department of Agriculture. P. 116-122. 

Malm, W. (1978). Summary of Visibility Monitoring Workshop, July 12-13,1978. 

Environmental Protection Agency, Environmental Monitoring Support Laboratory, Las 

Vegas, Nevada. 

Malm, W. (1979a) Visibility A Physical Perspective. In: Proceedings of the Workshop in 

Visibility Values, Fox D., R. J. Loomis and T. C. Greene (technical coordinators). Fort 

Collins, Colorado, U.S. Department of Agriculture. p. 56-68. 

Malm, W. (1979b) Personal Communication, Environmental Protection Agency. 

Environmental Monitoring and Support Laboratory, Las Vegas, Nevada, June. 

Stevens, R. K., Dzubay, J. G., Russwurm, G. and D. Rickel, (1978) Sampling and 

Analysis of Atmospheric Sulfates and Related Species. Atmospheric Environment. 12: 

55-68. 

Tombach, I. (1978) A Critical Review of Methods for Defining Visual Range in Pristine 

and Near Pristine Areas. Paper presented at meeting of Air Pollution Control Association. 

Houston, Texas, June 25-30, 1978. 

U.S. Forest Service (1973) National Forest Landscape Management, Vol. I, USFS, U.S. 

Dept of Agricultural Handbook No.434, U.S. Department of Agriculture, Washington, 

D.C. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 4 
2

4 EMPIRICAL METHODS FOR ASSESSING POLLUTION 

DERIVED IMPAIRMENT 

4.1 INTRODUCTION 

Relating visibility impairment to emission sources is a central problem for developing 

visibility protection programs. Before discussing various approaches, it is worthwhile to 

summarize some important generalities regarding the current understanding of the 

relationship between anthropogenic air pollution and visibility impairment (Husar, et al., 

1979): 

1. The size distribution of atmospheric aerosol mass is generally bimodal. The 

distribution of fine particle or accumulation mode particles can vary, but most mass is 

concentrated in the 0.1 to 1 μm range. 

2. Light scattering and particle related light absorption are usually dominated by fine 

mode aerosols. 

3. The degree of haze is, thus, directly proportional to the aerosol mass (or volume) 

concentration in the fine particle mode. The identification and quantification of 

sources of haze in most areas reduced to the identification of the sources of fine 

particle mass. 

4. Fine particle chemical composition can be used as a powerful tool for the 

identification of the source of the haze. 

5. In some instances, particularly in combustion source plumes, atmospheric brown 

coloration may be caused by NO2 absorption. 

6. The relative humidity of ambient air influences the source/impairment relationship, 

and empirical humidity correction schemes have been developed. 

7. Much of the fine particle mass is of secondary origin; fine particles are formed in the 

atmosphere from their precursor gases, sulfur dioxide, nitrogen oxides, and organics, 

and hence, their emission rate cannot be measured at the source. Furthermore, the 

gas-to-particle conversion process depends on factors such as solar radiation, the 

presence of other pollutants, and humidity. Thus, the amount of secondary material 

formed from a given emission rate of precursor gas is not constant but depends on the 

environment. 

8. The residence time of fine particles in the atmosphere is estimated to be on the order 

of a week, and the transport distance can exceed 500 km. Within that distance, the 

contributions of many sources can be superimposed. 

 

9. The long-range transport of the fine particle-precursor chemical complex results in 

the superposition and chemical interaction of different types of sources (e.g., power 
3

plant and urban plumes). Many of these interactions currently cannot be predicted; 

hence, the quantitative evaluation of a source-receptor relationship requires collection 

and analysis of pollutant and visibility data. Properly calibrated theoretical models 

are necessary to predict the impact of controls on existing sources or the impact of 

new sources in a new physico-chemical environment. 

10. Assessment of the nature of visibility impairment requires the monitoring of the 

pertinent aerosol parameters (e.g., size distribution, fine particle mass, chemical 

composition, optical parameters, (e.g., contrast, extinction coefficient)) and 

meteorological variables. 

When a visible plume causes visibility impairment, the source can be identified by 

direct observation. Direct observation is an elementary example of an empirical 

approach to assessing the causes of impairment. Empirical approaches involve the 

collection and analysis of real-world data, ranging in complexity from simple observation 

to sophisticated aircraft sampling and satellite imagery. Identification and resolution of 

the sources of general haze or layers of discoloration is considerably more difficult than 

the case of a visible plume. Because of the complexity of the haze/source relationship, a 

number of markedly different approaches are currently being pursued. 

 

In this chapter, applications of several empirical approaches to identifying sources and 

assessing their impacts are discussed. The first three approaches, which are receptororiented, utilize existing information on haze at various receptor sites in conjunction with 

other relevant data as clues for the probable origin of the haze. The relevant data include 

the haze chemical composition (Section 4.2), historical trends of emissions and haziness 

(4.3) or the direction from which the haze is coming (4.4). In the other methods 

discussed, the source is the starting point, and the pollutant transmission processes 

through the atmosphere to the impact at a receptor are examined. This can be done 

through field observations (4.5), and “diagnostic” modeling, i.e. simultaneous use of 

source data, ambient concentration data, and a model to decipher what is happening in 

between (4.6). Theoretical predictive modeling approaches are discussed in Chapter 5. 

Several of these methods can only provide circumstantial evidence for the sourcereceptor-effect relationships. Other approaches may provide direct evidence but impose 

heavy demands on environmental data that are currently sparse or non-existent. Hence, it 

is evident that assessing the impact of manmade pollution on visibility in various class I 

areas will require prudent use of all these available source resolution techniques, as well 

as new ones as they are developed. 

4.2 CHEMICAL COMPOSITION OF LIGHT SCATTERING AEROSOLS 

The knowledge of the chemical composition of light scattering aerosols is essential to 

understanding the cause of visibility impairment. The chemical composition of the 

aerosol can affect its optical properties (Barone, et al., 1978); more importantly, the 

chemical composition serves as a tracer of the probable origin of the light scattering 

aerosol. In fact, for atmospheric haze in general, the chemical composition is the most 

important available clue regarding its probable origin. 
4

4.2.1 CHEMICAL-MASS BALANCE METHOD 

The method by which the ambient aerosol chemical composition is sued as a tracer for 

origin of the aerosol was formulated and described by Friedlander (1973). Characteristic 

tracer elements such as vanadium (which comes primarily from fuel oil) and lead 

(emitted by the automobile) can be used as indicators of how much these sources 

contribute to the ambient aerosol. Application of this approach in various regions has 

indicated that the relative amounts of fine particle constituents vary in different regions. 

The first comprehensive study of the size-chemical composition of a haze aerosol was 

conducted in the Los Angeles air basin as part of project ACHEX (Hidy et al., 1975). In 

their study of the nature and origins of visibility-reducing aerosols in Los Angeles, White 

and Roberts (1977) constructed a chemical mass balance for the measured aerosol at 

seven locations in the basin (Figure 4-1). The key contributing species to the total 

aerosol mass concentration were nitrates, sulfates, organics, and other unidentified 

substances. Based on a statistical analysis of light scattering (bscat) and chemical 

composition data, the authors concluded that sulfates are the most efficient scatterers 

among the measured chemical species. 

Figure 4-1. Geographical distribution of (a) particulate mass concentration and 

(b) light scattering coefficient in the Los Angeles basin. The pie diagrams show the 

relative contributions of nitrates, sulfates, organics, and other compounds. Sulfates 

evidently contribute only about 25 percent of the total mass but cause aobut half of 

the light scattering. The estimated contributions of source types (oil, gasoline, and 

other) to (c) mass concentrationo and (d) light scattering coefficient are also shown 

(White and Roberts, 1977). 

The chemical mass balance approach is enhanced by use of size segregating particle 

samplers, which distinguish between fine (< 2.5 μm) and coarse (> 2.5 μm) mode 
5

particles. The composition of fine particles is important because this fraction contains the 

most efficient light-scattering aerosols by mass. The results for several locations are 

summarized in Figures 4-2 through 4-5. Urban data are presented to show the spectrum 

of applications and because urban sources can impact upon nearby class I areas. These 

and other data indicate that sulfur compounds constitute the most significant chemical 

component of fine particulate mass over the Eastern United States, including class I areas 

like the Smoky Mountains (Figure 4-3). As noted above, sulfates are also significant in 

Los Angeles. Pacific Northwest data (Figures 4-4, 4-5) suggest that various forms of 

vegetative burning (forest and field burning, space heating) are important sources of light 

scattering aerosols. In the Portland Aerosol Characterization Study (PACS), (Cooper 

and Watson, 1979) the chemical balance for organics was supplemented by use of carbon 

isotope analysis (Cooper et al., 1979). Because the distribution of the forms of carbon 

(C14, C12) varies for fossil fuels and modern vegetation, the origin of organic aerosols 

can be better specified. IN the Willamette Valley, Oregon study, a preliminary 

association between field burning and the presence of potassium in fine particles was 

used to “finger print” vegetative burning (Lyons et al., 1979). 

Much of the current concern for visibility pertains to the origin of the haze in pristine 

areas of the Western and Southwestern U.S. where many of the class I areas are located. 

Reporting the results of the EPA VISTTA Program*, Macias et al. (1979) presented sizechemical composition data for size segregated aerosol collected in the Four Corners area 

of the Southwest during aircraft flights (Figure 4-61, b). The size distribution followed 

the typical bimodal p pattern (Figure 2-17). As anticipated, the coarse particle fraction 

could be accounted for by the crustal element contributions. In the fine particle mass 

balance, about 40 percent of the 5.3 μg/m3 consisted of sulfate, another 10 percent of 

trace constituents, and 22 percent of other species such as ammonium and metal oxides. 

The have also reported a 29 percent contribution of silicon dioxide to the fine particle 

mass. This contribution is unusual because the crustal elements normally accompanying 

silicon were not present in the fine particle samples. Macias et al. argued, therefore, that 

the fine particle silicon may possibly be due to direct emissions from high temperature 

sources. However, the possibility of contamination of the sample (Macias, 1979) and 

limited data from other Western monitoring (Winchester et al., 1979) preclude definitive 

conclusions on the significance and source of fine silicon. Preliminary results from ore 

recent VISTTA regional flights suggest similar levels of fine mass, sulfate and silicon but 

also provide carbon and nitrate data. Carbon contributed roughly 10 percent of fine mass 

and nitrate only 2 percent (Wilson, 1979). 
6

Figure 4-2. Chemical-mass balance for fine and coarse particles collected in 

Charleston, WV. The composition of the two modes is distinctly different. 

Ammonium sulfate accounts for about 40 percent of fine mass. A portion of the 

undetermined mass includes water associated with sulfates and other particles 

(Lewis and Macias, 1979). 

FINE PARTICLES

MASS = 33.4 fJ.9/m3

VALUES IN PERCENT

COARSE PARTICLES

MASS =27.1 1J.9/m3
7

Figure 4-3. Source resolution of St. Louis aerosol compared with showrt term 

results from the Smoky Mountains in Tennessee. Rural sites near St. Louis (122, 

124) and the Smoky Mountain site have similar sulfate levels, but significantly lower 

primary motor vehicle derived particles (<10 percent) than do urban sites in St. 

Louis. Significantly, about 60 percent of the fine mass in the Smokies is from sulfur 

oxide sources. The unknown fraction probably contains water, organics, and 

nitrates. Almost all of coarse particle mass at all sites is accounted for by dust from 

the earth's crust (Dzubay, 1979). 

Macias et al. (1979) combined the results of the chemical elements balance with 

concomitant light scattering measurements to determine a visibility “budget” for the 

southwest aerosol. The measured scattering coefficient (bscat) was within about 10 

percent of that predicted from the size distribution. Visual range calculated from bscat 

(160 km or 96 miles) was consistent with observations and within the range of values 

typically reported for the Southwest. The estimated contribution of the aerosol 

components to light scattering (extinction) is shown in Table 4-1. On this typically clean 

~I> nNE. rRACTl(:fll

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8

day, Rayleigh (air) scattering contributes a significant amount, with fine particles 

contributing about 52 percent of the total extinction. Sulfates account for half of the 

scattering caused by particles. 

Figure 4-4. Source resolution of Portland, Oregon, aerosol indicates 

contributions of background air (shaded) and local sources. Carbonaceous 

(organics and elemental carbon) material from fireplaces and wood stoves, forest 

and field burning, automobiles, and other sources account for about 37 percent of 

the fine mass. Simultaneous light scattering measurements showed a 0.97 

correlaton with fine particle mass (Cooper and Wilson, 1979). 

In summary, the chemical composition of the light scattering aerosols provides a 

valuable, if not the most important, clue we currently have regarding their probable 

sources. Future applications of these techniques, combined with visibility measurements 

in class I areas, will add significantly to an understanding of the extent of manmade vs. 

natural visibility impairment. The approaches are, however, usually too coarse to provide 

resolution of specific source contributions or to enable prediction of the impact of control 

of single source emissions. 

DOWNTOWN

TOTAL SUsP~NDEO PARTiCULATE, perclIIlt

(76~fm31

naHATIYE BURN 1.7

'-'lIDENTIFIED 8.3

VEll ETATIVE IIL1RN 9.6

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ET<:.I
9

Figure 4-5. Relative Composition of Willamette Valley, Oregon, aerosol (June - 

Novemnber, 1978) from 11 rurual and urban sites. Carbonaceous material, partly 

from field and slash burning is the major fraction of fine particle mass. Burning 

impacts were dominant for ays on which burning occurred (Lyons et al., 1979). 

4.2.2 Statistical Analysis of Visibility/Aerosol Relationships 

As discussed above, detailed measurements of particle size distribution and chemical 

composition are useful in identifying the important components of urban and regional 

hazes. When large data sets are collected, statistical analysis can provide additional 

insights. The contribution o f certain components of total suspended particulate matter 

(TSP) to haze has been investigated through s statistical analyses relating routine HiVolume measurements to light-scattering (nephelometry data) or total extinction as 

determined from airport visual range data. This section describes these statistical studies 

and discusses conclusions and limitations. 

Figure 4-6a. Chemical-mass balance for fine and coarse particles collected 

during flights in the Four Corners region. The total aerosol mass was estimated 

from in situ size distribution measurements. In this data set SiO2 accounted for an 

estimated 29 percent of the fine particle mass (Macias et al., 1979). Preliminary 

results from more recent measurements suggest carbon contributes roughly 10 

percent of fine mass and nitrates about 2 percent. 

-'Z0 3' CIO. F.20 3

'"

fiNE PARTICLES

MASS - 5.3 p.glm3

COARSE PARTICLES

MASS =4.0 p.vlm3

•TOTAL PARTICULATE

60 [] FINE PARTICULATE

SOILS

CIl 40 CAR BON ACEOUS

::E

...

0

IZ OTHER w

CJ

II:

w 20 "-

SULFATE

MARINE ilO OTHER

11 IONS

0 • .n
10

Figure 4-6b. Flight path of VISTTA regional flights on October 5 and 9, 1977. 

The entire flight path is about 1080 km (Macias et al., 1979). 

Component Particle Size 

(μm) 

bscat(km-1) Contribution to 

Total bscat

Contribution to 

Extra 

Extinctionc

Air Molecules 0.011 44 

(NH4)2SO4

a

 0.1 to 1.0 0.007 28 50 

SiO2

b

 0.1 to 1.0 0.004 16 29 

Other 

compounds 

0.1 to 1.0 0.002 8 14 

Coarse Particles 1.0 to 20.0 0.001 4 7 

Table 4-1. Light scattering budget for the Southwest Region, October 9, 1977 

(Visual range approximately 160 km) (Macias et al., 1979). a

Assumes all fine 

particle sulfate exists as ammonium sulfate. b

Assumes that all fine particle silicon 

exists as SiO2. c

Extra Extinction is that fraction not including blue sky (Rayleigh) 

scattering. In this case, extra extinction is assumed to equal particle scattering 

(bscat). 

4.2.2.1 Multiple Regression Analysis—Several investigators have used multiple 

regression analysis to relate sulfates, nitrates, other particulate matter, and relative 

humidity to light-extinction, (Trijonis and Yuan, 1978a,b; Cass, 1976; Leaderer et al., 

1979) or light–scattering (White and Roberts, 1977; Leaderer et al., 1978). The initial 

statistical analysis is often based on an equation such as the following: 

B = bo + b1 SULFATE + b2 NITRATE + b3 (TSP-SULFATE-NITRATE) (4-1) 

(1-RH) α

".

N"

I

,,,.

, ..

+-i

j.

...

_.~.

I'r

.....• ~-

".

...
11

where B(km-1) represents either the extinction coefficient (bext) (estimated from airport 

visibility data using the Koschmieder relationship) or light-scattering (bscat) (based on 

nephelometry data); measured SULFATE (μg/m3

) and NITRATE (μg/m3) levels are 

usually adjusted to account for associated ammonium; TSP-SULFATE-NITRATE 

(μg/m3

) represents the non-sulfate, non-nitrate fraction of TSP (including coarse and fine 

particles) and RH (no units) is relative humidity. The database usually consists of daily 

measurements for each parameter. Humidity is sometimes included in the regression 

equation as a separate linear term (RH) (Trijonis and Yuan, 1978a, b; Cass, 1976). The 

non-linear term (1-RH)α

 accounts for the increase in light scattering per unit mass 

observed for hygroscopic (water absorbing) aerosols like sulfates at higher humidities. 

Trijonis and Yuan (1978a, b) assumed an α of 1.0; Cass (1976) considered α of .67 to 

1.0, while White and Roberts (1977) used other approaches to account for humidity. 

Multiple regression analysis selects the coefficients bo through b3 in the Equation 4-1 that 

produce the best straight line (linear) relationship between the “dependent” variable (B) 

and the “independent” variables (SULFATE, NITRATE, etc.). 

Multivariate linear regression is an appropriate statistical tool for relating extinction to 

various aerosol components. Theoretically, extinction produced by various aerosols is 

additive, and the total extinction from a given aerosol component should be directly 

proportional to its mass concentration (assuming particle size is constant). Thus a linear

relationship makes sense theoretically. Barone et al. (1978), however, report useful 

information from nonlinear regression approaches. Multivariate regression is designed to 

separate out the individual impact of each independent variable, accounting for the 

simultaneous effects of other independent variables. It is, therefore, preferable to 

analyses based on simple one-on-one relationships, because multivariate analyses have a 

better potential for avoiding some of the spurious relationships caused by 

intercorrelations among the independent variables. 

4.2.2.2 Extinction Coefficients Per Unit Mass—Regression analysis is a purely statistical 

technique, and there is no guarantee that the observed relationships represent cause-andeffect. However, if, as in the above analysis, the regression is structured to reflect 

fundamental principles, the results may strongly suggest certain physical interpretations. 

In particular, the regression coefficients, b1/(1-RH)α

 to b3/(1-RH)α in Equation 4-1, are 

readily interpretable as extinction (or scattering) coefficients per unit mass for sulfates, 

nitrates, and other particles, respectively. 

Table 4-2 lists extinction coefficients per unit mass for sulfates, nitrates, and the 

remainder of TSP obtained in various regression studies. There is general agreement that 

sulfates and, to a lesser extent, nitrates exhibit extinction coefficients per unit mass on the 

order of 0.004 to 0.011 [km-1/μg/m3

], and that the extinction coefficient per unit mass for 

the remainder of TSP tends to be much lower. These results are quite consistent with 

Mie theory and experimentally derived fine-particle scattering efficiencies discussed in 

Section 2.4.3. Mie theory calculations indicate that fine particles like sulfates and nitrates 

should exhibit extinction coefficients per unit mass on the order of 0.003 to 0.009 [km1

/μg/m3], (Latimer et al., 1978; White and Roberts, 1977; Ursenbach et al., 1978). The 

remainder of TSP mass is usually dominated by the coarse particles (Diameter > 2.5 μm) 

(Bradway and Record, 1976; Whitby and Sverdrup, 1978). The coarse particle mode 

should exhibit an average extinction coefficient per unit mass on the order of 0.0002 to 
12

0.0008 [km-1/μg/m3] (Latimer et al., 1978; White and Roberts, 1977; Ursenbach et al., 

1978). 

Extinction coefficients per unit 

Aerosol mass (km-1)/μg/m3 

Location 

Sulfates Nitrates Remainder of 

TSP 

Total correlation 

Coefficient(R) 

associated with the 

regression a

Southwest (Trijonis and 

Yuan, 1978a) 

 

 Phoenix: County Data 0.004 0.005 0.000 0.87 

 NASN Data 0.003 0.003 0.000 0.68 

 Salt Lake City 0.004 0.013 0.0004 0.72 

 0.004c 0.010c (0.0004c) 0.81 

 Los Angeles (White and 

Roberts, 1977) 

0.007 0.005 0.0015 0.60 

 Various Locationsb 0.006c 0.004c 0.0020c 0.72 

(Cass, 1976) 

 Downtown Los Angeles 0.017 0.004c 0.0008 0.76 

(Leaderer and Stolwijk, 

1979) 

0.009c 0.005c 0.0004c 0.76 

 Los Angeles Airport 0.016 0.003 0.0004 0.91 

 Northeast (Trijonis and 

Yuan, 1978b) 

 

 Chicago 0.004 (NPd) (NP) 0.48 

 0.003c (NPc) (NPc) 0.52 

 Newark 0.002 (NP) 0.0026 0.67 

 0.006c (0.000c) 0.0014c 0.71 

 Cleveland 0.008 (NP) (NP) 0.70 

 0.007c (NPc) (NPc) 0.72 

 Lexington 0.006 (NP) (0.0001) 0.68 

 0.006c (0.004c) 0.0019c 0.72 

 Charlotte 0.011 (NP) (0.0001) 0.67 

 0.011c (NPc) (0.0000) 0.73 

 Columbus 0.012 0.009 (0.0004) 0.81 

 0.013c 0.006 (0.00019c) 0.90 

(Leaderer and Stolwijk, 

1979) 

 

 New York b 0.007 0.005 (NP) 0.88 

 New York 0.010 (0.006) (0.0001) 0.76 

 New Haven 0.016 (NP) (0.000) 0.90 

 St. Louis 0.008 (NP) (NP) 0.83 

Table 4-2. Extinction Coefficients per unit mass. ( ) Not significant at 95 percent 

confidence level. a

 Only those variables that are statistically significant at the 95 

percent confidence level are included in determining the total correlation ( R ). Note 

that the square of the correlation coefficient represents the percent of variance 
13

explained by the regression; thus, a correlation of 1.0 indicates a perfect statistical 

fit. b

 Based on light-scattering (nephelometry data) rather that total extinction 

(airport visibility data). C

 Based on nonlinear RH regression model, with insertion 

of average RH. d NP Not positive. 

As shown in Figure 4-7, Latimer et al., (1978) found that the regression analysis by 

Trijonis and Yuan (1978a) for the Southwest also tends to be consistent with theoretical 

calculations in regard to the relative humidity dependence of light scattering by sulfates. 

The regression results obtained by Trijonis and Yuan (1978b) for three locations in the 

Northwest (Newark, Cleveland, and Lexington) are in equal agreement with the 

theoretical predictions in Figure 4-7. The empirical extinction coefficients at two other 

Northeast sites (Charlotte and Columbus) are, however, nearly twice the theoretical 

values, while the empirical extinction coefficient at another site (Chicago) is almost half 

the theoretical value. 

Figure 4-7. Light-scattering per unit mass of sulfate aerosol as a function of 

relative humidity (Latimer et al., 1978). 

4.2.2.3 Extinction Budgets—By entering average values for each of the variables in the 

regression equations, the average fraction of extinction attributable to each aerosol 

component can be estimated. For example, the term “b1 (average SULFATE) /(1-RH)α” 

in Equation 4-1 would indicate the average contribution of sulfate aerosols to extinction. 

O.H r---------------~----~!<-

h. T}1E()~nll:A'_l.Y CALClJlAHD VALUES

O.IZ - 0 .MPIRICA~ VALUES

(TRIJONIS ANI) YUAN, 1978.1. o

0.40 0.60 n.So 1.0

0.10

6 <"'Ie

.. 0.08 0

;=."

E

1

il

m 0,06 8

0.D4 2

2 9

flElA liVE HUMlDlTV
14

The term “bo” is assumed to represent Rayleigh scatter plus contributions to extinction 

that are unaccounted for by the regression. 

Average percent contributions to extra extinction a

 (%) 

Location Sulfates Nitrates Remainder of TSP Unaccounted for 

Southwest 

(Trijonis and Yuan, 1978a) 

 Phoenix 53 37 0 10 

 Salt Lake City 34 31 35 0 

Los Angeles 

(White and Roberts, 1977) 

 Various Locations b 31 27 42 0 

(Cass, 1976) 

 Downtown Los Angeles 46 0 15 39 

(Leaderer and Stolwijk, 

1979) 

 

 Los Angeles Airport 30 11 0 9 

Northeast 

(Trijonis and Yuan, 1978b) 

 Chicago 27 0 0 73 

 Newark 42 0 38 20 

 Cleveland 55 0 0 45 

 Lexington 32 0 44 24 

 Charlotte 59 0 0 41 

 Columbus 68 8 0 24 

(Leaderer and Stolwijk, 

1979) 

 

 New York b 67 14 0 19 

 New York 74 0 0 26 

 New Haven 81 0 0 19 

 St. Louis 51 0 0 49 

Average c 53 8 12 27 

Table 4-3. Extinction Budgets based on the regression studies. a Extra extinction 

is defined to be the fraction of extinction above-and-beyond the contribution from 

Rayleigh scatter. For each location, the extinction budget is based on the regression 

equation that achieved the best statistical fit (see Table 4-2 for correlation 

coefficients). Variables are included only if they are statistically significant at 95-

percent confidence level. b Budget for light-scattering rather than for extinction. c

The average is only for the sites presented and is not intended to represent an 

average of national conditions. 

Table 4-3 presents extinction budgets for the various study locations. The budgets are 

given for extra extinction; the portion of extinction above-and-beyond the contributions 

from Rayleigh scatter by air molecules. The regression studies indicate that, in each of 

the three areas studied, sulfates tend to be the most important single component of the 
15

aerosol with respect to visibility degradation. The contribution of sulfates to extra 

extinction ranges from approximately 30 to 80 percent and averages 53 percent among 

the study locations. The contribution of sulfates in the Southwest agrees well with 

preliminary VISTTA visibility budget (Table 4-1), in which sulfates contribute 50 

percent of extra extinction. The special importance of sulfates to visibility in California 

cities has also been suggested by strong statistical relationships observed in other recent 

studies (Barone et al., 1978; Grosjean et al., 1976). Barone et al., included detailed size 

and composition data in four California cities (Los Angeles, Los Alimitos, Bakersfield, 

Oakland). They found visibility reduction to be dependent on elemental content as well 

as particle size and that each area exhibited some site-specific (local) variables that 

affected visibility. Sulfur (compounds) in the 0.65 to 3.6 μm size range was the only 

variable significantly related to visibility at all sites. 

The estimated contributions of nitrates and remainder of TSP to extra extinction in 

Table 4-3 vary greatly among locations and are often zero. The estimates of zero 

contribution imply only that a statistically significant relationship was not observed and 

do not necessarily mean that the actual contributions are really zero. Problems in 

estimating the effects of nitrates and remainder TSP are included in the discussion of 

limitations below. 

4.2.2.4 Limitations of the Regression Studies—There are several limitations in the above 

regression studies. One limitation involves random errors in the data base produced by 

imprecision in the measurement techniques (for airport visibility, light-scattering, or 

aerosol concentrations) and, in the case of studies using airport visibility data, by the fact 

that the airport and Hi-Vol site are often located several miles apart. Random errors in 

the data tend to weaken the statistical relationships, leading to lower correlation 

coefficients and lower regression coefficients. This results in an underestimate of the 

extinction coefficients per unit mass and an underestimate of the contribution of the 

aerosol species to the total extinction budget. The overall effect of random errors in the 

database should not be excessive, however, because good correlations (typically 0.7 to 

0.8, as may be seen in Table 4-2) are usually obtained in the analysis. 

For the studies using airport visibility data (as opposed to nephelometry data), at least 

two types of systematic bias are possible. The aerosol concentrations measured at the 

downtown Hi-Vol locations may be systematically higher than the aerosol concentrations 

averaged over the visual range surrounding the airport. The bias caused by relatively 

high aerosol measurements would result in an underestimate of extinction coefficients per 

unit mass for the aerosol species. A reverse type of bias (e.g. an overestimate of 

extinction coefficients per unit mass) would result if daytime aerosol levels 

(corresponding to the time period of the visibility measurements) were higher than the 

24-hour average aerosol levels measured by the Hi-Vol. Although these systematic 

errors could bias the extinction coefficients per unit mass (Table 4-2), they should not 

bias the extinction budgets, which are based on a multiplication of extinction coefficients 

per unit mass times the measured mass of the aerosol (Table 4-3). 

Another limitation is that the regression analysis may overstate the importance of the 

aerosol variables if these variables are correlated with other visibility-related pollutants 

omitted from the analysis. In particular, sulfates and nitrates may act, in part, as 

surrogates for related pollutants, such as total fine particle mass, organic and primary 

carbon aerosols, and nitrogen dioxide, not measured or included in the regression. 
16

Potential errors in Hi-Vol measurements of sulfate and nitrate are another important 

problem. “Artifact” sulfate (formed by SO2 conversion on the measurement filter) may 

cause a slight underestimation in the extinction coefficient per unit mass for sulfates. The 

greatest measurement concern, however, involves nitrates (Spicer and Schumacher, 

1977). Nitrate data may represent gaseous compounds (NO2 and especially nitric acid), 

as well as nitrate aerosols. Also, high sulfate concentrations may negatively interfere 

with nitrate measurements (Harker et al., 1977). Because of potentially severe 

measurement errors, the visibility/nitrate relationships are especially uncertain. 

Figure 4-8. Seasonal and spatial distribution of long-term trends in average 

airport visiblities for the eastern United States. Note marked decline in 

summertime (third quarter) visual range throughout the East (Husar et al., 1979). 

A final difficulty in the regression analysis is the problem of colinearity; i.e. the 

intercorrelation among the “independent” variables (sulfates, nitrates, remainder of TSP, 

and relative humidity). Although the intercorrelation among these variables is not 

extremely high, they usually are significant (correlations on the order of 0.2 to 0.6). 

Multiple regression is designed to estimate the individual effect of each variable, 

discounting for the simultaneous effects of other variables, but he colinearity problem can 

still lead to distortions in the results. In particular, the effect of nitrates and the remainder 

eo-ec

.. .. t-, Mid 110-41'11-1)

V~ fM~L~n

3.G-~.8

IIJI-B

2.4.:uJ

1.10

1.lJ.2,4

1[)-1:1.3

70-7•

<,1.8

':>1:1.3
17

of TSP may be lost in the analysis because these variables are colinear with sulfate, 

which tends to be the predominant aerosol variable related to extinction. 

Although the regression models are subject to several limitations, the conclusions 

resulting from these models have proven to be very reasonable. The extinction 

coefficients per unit mass estimated for sulfates, nitrates, and the remainder of TSP are 

consistent with the Mie theory of light scattering by aerosols, and the extinction budgets 

agree (at least qualitatively) with the conclusions of special field studies conducted in 

corresponding areas of the country. 

4.3 ANALYSES OF HISTORICAL VISIBILITY/POLLUTANT TRENDS 

Several investigators have used historical airport visibility data (observer-determined 

visual range) to examine long-term changes in haze. These studies have generally 

focused either on the Northeast, where the lowest rural visibilities in the United States 

occur, or on the Southwest, where the highest rural visibilities in the United States occur 

(Figure 1-10). Some of the studies have also examined the relationship of visibility 

trends to emission and ambient aerosol trends. Although these historical trend analyses 

basically provide only circumstantial evidence concerning the relationship between 

visibility and man-made emissions, the results are nevertheless very consistent with the 

conclusion of other studies. This section discusses these studies in some detail because 

of the relevance of the results and usefulness of the analytical approaches. Until adequate 

visibility monitoring data for class I areas in these and other regions are available, 

analysis of airport visibility data can provide useful information for preliminary 

assessments. 

4.3.1 VISIBILITY/POLLUTANT TRENDS IN THE EAST 

In comparison studies, Husar et al. (1979) and Trijonis and Yuan (1978b) investigated 

historical trends in airport visibility data for the East and Northeast, respectively. Husar 

et al. took a large-scale regional view by preparing visibility maps based on 70 locations 

(representing varied degrees of urbanization, from rural to metropolitan), partially 

accounted for meteorological variations by eliminating days with precipitation, and 

converted the visibility data to extinction by using the Koschmieder relationship. Their 

study examined the period 1948 to 1974. 

The findings of Husar et al. with respect to the spatial and seasonal aspects of 

historical extinction trends from 1948-1952 to 1970-1974 are summarized in Figure 4-8. 

During the winter (first) quarter, the northern half of the East underwent little change (or 

a slight decrease) in haziness from 1948-1952 to 1970-1974, while the southern half 

experienced a moderate rise (~20%) in extinction. A slight to moderate increase in 

extinction (averaging about 18%) occurred throughout the East during the fall quarter 

with a moderate to strong increase (averaging about 35%) during the spring quarter. A 

dramatic growth in haze occurred during the summer quarter. This growth was 

distributed through the region as follows: a more than 100 percent increase in extinction 

for the central/eastern states (Kentucky, Tennessee, West Virginia, Virginia, and North 

Carolina); an increase on the order of 50-70 percent for the Midwest (Missouri, Illinois, 

Indiana, Michigan, and Ohio) and for the Eastern Sunbelt (Arkansas, Louisiana, 
18

Mississippi, Alabama, Georgia, and South Carolina); and an increase on the order of 10-

20 percent for the far Northeast (the Northeast Megalopolis area and New England). The 

summer quarter, which had been nearly the best season for visibility in the East during 

the early 1950s, became the worst season by the early 1970s. 

 Parallel between visibility 

and sulfate trends 

Potential explanation in terms of SOX

emission trends (early 1950s - early 

1970s) 

Trend Feature (Early 1950s - early 1970s) (Early/mid 1960's - 

early 1970s) 

Suburban/nonu

rban areas 

Visibility decreased 

substantially at 

suburban/nonurban 

locations 

Sulfates increased 

substantially at 

suburban/nonurban 

locations 

An increase in total SOX emissions 

occurred in the Northeast; in particular, 

there was a very great rise in SOX

emissions from nonurban, tallstack 

sources (power plants). This may have 

increased large-scale background levels 

of sulfates. 

Metropolitan 

areas 

Visibility changed very 

little at metropolitan 

locations. 

Sulfates changed 

very little at 

metropolitan 

locations 

SOX emissions were reduced within 

metropolitan areas by control of 

residential, commercial, and some 

industrial sources. This may have locally 

offset the increase in large-scale 

background levels of sulfates. 

Summer (third 

quarter) 

Visibility decreased 

dramatically during the 

summer. By the early 

1970s, the third quarter 

became the worst season 

for visibility. 

Sulfates rose 

dramatically during 

the summer. By 

early 1970s, the third 

quarter became the 

worst season for 

sulfates. 

The summer exhibited the greatest 

increase in total SOX emissions because 

of rapid growth of power plant emissions 

was offset only by small summertime 

reductions in emissions from other 

sulfates. 

Winter (first 

quarter) 

Visibility changed little 

during the winter. 

Sulfates changed 

little during the 

winter. 

Total SOX emissions changed little during 

the winter because a large increase in 

power plant emissions was offset by a 

nearly as large decrease in wintertime 

emissions from other sources. 

Best-case 

Areas 

The only region of the east 

exhibiting an improvement 

was the Northeast 

Megapolis Area 

surrounding New York 

City. 

The only region of 

the east exhibiting a 

decline in sulfates 

was the Northeast 

Megapolis Area 

surrounding New 

York City. 

The only region showing a significant 

decline in SOX emissions was the far 

Northeast (the Northeast Megapolis Area 

and New England). 

Worst-case 

Area 

The greatest decline in 

visibility occurred in the 

central/eastern states. 

The central/eastern 

region was one of the 

areas showing the 

largest increase in 

sulfates. 

The largest rise in SOX emissions 

occurred in the central/eastern states 

(particularly Kentucky, Tennessee, West 

Virginia, and North Carolina.) 

Table 4-4. Parallels among historical trends for visibility, ambient sulfates, and 

SOX emissions in the Northeast. 

Trijonis and Yuan (1978b) examined differences in airport visibility trends between 

large metropolitan areas (New York, Chicago, Cleveland, and Washington, D.C.) and 

suburban/rural areas of the Northeast. They found that, from the middle 1950s to the 
19

early 1970s, visibility did not change much in large metropolitan areas. Outside the large 

metropolitan centers, however, visibility decreased on the order of 10 to 40 percent over 

the same period with the largest declines occurring in the central/eastern region (at 

Lexington, KY, and Charlotte, NC). The 10-40 percent decrease in visibility at 

suburban/rural locations corresponded to an increase in extra extinction (extinction 

above-and-beyond Rayleigh scatter) of 10 to 80 percent. Seasonally, the constant yearly 

visibility trends at metropolitan locations were actually composed of moderate (~20%) 

declines in summertime visibility, which cancelled moderate increases in wintertime 

visibility. The 10-40 percent decrease in yearly visibility at non-urban locations was 

composed of strong (~25-60%) declines during the summer and moderate declines during 

the spring and fall, with little change during the winter. 

Figure 4-9a. Seasonal trends in U.S. coal consumption. A. In 1974, the U.S. 

winter coal consumption was well below, while the summer consumption was above, 

the 1943 peak. Since 1960, the average growth rate of summer consumption was 5.8 

percent per year while the winter consumption increased only at 2,8 percent per 

year (Data from the U.S. Bureau of Mines, Minerals Yearbooks 1933-1974) (Husar 

et al, 1979). 

The above conclusions concerning visibility trends in the Northeast are supported by 

the results of several other trend studies. Miller et al. (1972) reported substantial declines 

in airport visibilities during the 1960s for the summer season at three nonurban airports in 

Ohio, Kentucky, and Tennessee. From the middle 1950s to the early 1970s, airport 

observations of haze increased significantly in eastern Canada, especially during the 

summer at nonurban locations (Munn, 1973; Inhaber, 1976). Sun-photometry data from 

the middle 1960s to the middle 1970s indicate that turbidity increased at nonurban 

locations in the East, especially during the summer, and that turbidity at urban locations 

decreased (Peterson and Flowers, 1977). Also, the acidity of rainfall (presumably related 

175

150

125 ..::z:

IZ

0

:Ii'

...

..

z

e

g 75

0.

§.

1940 50 80 70 1940

YEAR

1i0 611 70
20

to sulfate and nitrate concentrations) increased substantially in the East from 1955-1956 

to 1972-1973 (Likens, 1976). 

Figure 4-9b. In the 1950s, the seasonal U.S. coal consumption peaked int the 

winter primarily because of the incresed residential and railroad use. By 1974, the 

seasoal pattern of coal usage was determined by winter and summer peak of utility 

coal usage. The shift away from a winter peak toward a summer peak of coal 

consumption is consistent with the shift in haziness from a winter peak to a summer 

peak at Dayton, Ohio for 1948-52 and 1970-74. (Data form U.S. Bureau of Mines, 

Minerals Yearbooks 1933-1974) (Husar et al., 1979). 

Because several studies have indicated that sulfates are the single most important 

component of the visibility-reducing aerosol in the Northeast (Trijonis and Yuan, 1978b; 

Leaderer et al., 1978, 1979; Weiss et al., 1977; Charlson et al., 1974), it is of interest to 

compare historical visibility trends in the Northeast with corresponding trends in ambient 

sulfate concentrations and sulfur oxide (SOx) emissions. Ambient sulfate concentration 

and sulfur oxides emission trends from the early/middle 1960s to the early 1970s have 

been analyzed by Altshuller (1976), Frank and Posseil (1976), Trijonis (1975), and EPA 

(1975). Trijonis and Yuan (1978b) and Husar et al. (1979) noted very close parallels 

between the spatial/seasonal features of visibility trends and the spatial/seasonal features 

of ambient sulfate and SOx emission trends. These parallels, summarized in Table 4-4, 

provide strong circumstantial evidence that the historical visibility changes in the 

Northeast were caused, at least in part, by trends in sulfate concentrations and SOx

emissions. 

Trends in coal usage, the dominant factor affecting sulfur oxide emission trends, have 

been documented from the early 1950s to the early 1970s and have been related to airport 

visibility trends by Husar et al. (1979). Shifts in seasonal patterns for coal usage and 

visibility are shown in Figure 4-9a and 4-9b. Consistency of long-term or seasonal trends 

of coal consumption and haziness can hint at, but not substantiate, a cause and effect 

70 7

60 bex! 1951 bex! 1974 6

0

i:

:r: 58 5 0 ...

z z·

0 0

:Ii ... .....

(I) 40 4 >

'II( Z Q 0

... '7

§ 30 3 E

"Il'

§: b

... 20 2 ;.

x

OJ .a

10

J F M A M J J A SON D J F M A M J J A S o N 0

MONTH MONTH
21

relationship. It is instructive, however, to examine the state-by-state spatial trend of 

yearly coal consumption data (Figure 4-10) available since 1957. 

The comparison of the Eastern U.S. summer coal consumption and summer average 

extinction over the entire Eastern United States is shown in Figure 4-11. While a high 

statistical correlation could be established between the trends in coal consumption and 

haze, a cause-effect relationship cannot be established from trends analysis alone. Trends 

in other fuel use and in emissions of various pollutants from a number of source 

categories must also be examined. 

Figure 4-10. Regional trends of coal consumption in the continental United 

States. Dark shading is electric utility coal. The greatest increases in haziness 

occurred in the east central United States (Kentucky, West Virginia, North and 

South Carolina, and Tennessee). Sulfur oxides emissions in these regions are not 

completely dependent on coal use because of toher SOX sources (oil in the east, 

smelter in west, oil and gas in the south) and differences in coal sulfur content 

(lower in the west) (Husar et al., 1979). 

70 10 7CI ""r I I

II: MOl\IT II: MINN 60 IN

I~f « 60 ::.l ~O '" IDAHO IOWA > '" II: WYO ~ho WrS ... SCI

'" NEV ... .. . .. .. ,. : ...

"" 40 UTAH z COLO ,. : . .. , c ..... ,0)....

... AIHl z 3CI c NEWill

:;

..,j zo :ii 10

10

'"

« $0 w

>-

" \ 50 SO

'"

...

" 40 40

t- 3(J 30

..,j

20 - ..,j

...j ...J

i !i! 10

ImiC 60 70

""JIll YEA" Y~AFl YEAI' 'rEAR y~A!'I
22

Figure 4-11. Summer trends of U.S. coal consumption (dashed line) and Eastern 

U.S. average extinction coefficient, or haziness (solid line). Adapted from Husar et 

al., 1979. 

4.3.2 Visibility/Pollutant Trends in the Southwest 

4.3.2.1 Visibility Trends—Recent studies have investigated airport visibility data for the 

Rocky Mountain Southwest, a region containing numerous class I areas, for the period 

1948 to 1976. Trijonis and co-workers (Trijonis and Yuan, 1978a; Trijonis, 1979; 

Marians and Trijonis, 1979) examined historical visibility trends at 12 locations: 4 urban 

airports and 8 suburban/nonurban airports. After reviewing data quality with individual 

airport observers, the investigators restricted their analysis to daytime visibility data, to 

locations with farthest markers at distances exceeding 40 miles (typically at 60 to 90 

miles), and to time periods with constant observation location, inexcessive turnover of 

personnel, and consistent reporting practices. 

Visibility data were expressed as percentiles, such as median. Visibility trends in the 

Southwest were summarized according to three time periods within the 1948 to 1976 

time span. From the late 1940s to the early/mid 1950s, visibility trends were mixed, with 

some sites showing a slight improvement and a lesser number of sites showing a slight 

deterioration. From the early/mid 1950s (1953-1955) to the early 1970s (1970-1972), 11 

of the 12 trend sites indicated a drop in visibility of approximately 10 to 30 percent. 

From the early 1970s (1970-1972) to the middle 1970s (1974-1976), visibility generally 

tended to increase by about 5-10 percent, especially at those sites in or near Arizona. 

Latimer et al. (1978) examined visibility trends from 19448 to 1976 at 16 airports; 14 

sites in the Rocky Mountain Southwest, and 2 sites in the Northern Great Plains. They 

175 4.0

It;O 3.5

125 3.0

Z

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1940 50 60 10 60 9lJ 2000

YEAR
23

reported visibility trends in terms of the percent of time visibility exceeded various 

thresholds on days without fog or precipitation. Although Latimer et al. included several 

more locations, used a different type of visibility trend index, and subdivided the 1948-

1976 time period differently than Trijonis and co-workers, the conclusions reached by 

both groups were qualitatively consistent. Latimer et al. found a tendency toward 

declining visibility from 1948 to 1970; they concluded that, during this period, visibility 

decreased at seven sites, remained relatively constant at eight sites, and improved at one 

site. From 1970 to 1976, Latimer et al. found that visibility improved at 12 sites, 

remained relatively constant at 3 sites, and declined at one site. 

4.3.2.2 Historical Emission Trends—In order to help explain visibility trends in the 

Southwest, Marians and Trijonis (1979) documented historical emission trends for 

precursors of secondary aerosols: sulfur oxides (SOx), nitrogen oxides (NOx), and 

organics (non-methane carbons, NMHC). Primary (directly emitted) fine particle 

emissions data were not available. Emissions for the 10 dominant source categories were 

determined on a year-by-year basis from 1948 to 1975. The emission trends were 

compiled individually for four states (Arizona, Colorado, Nevada, and Utah) and for 

certain air basins within those states. 

Figure 4-12. Historical trends in hours of reduced visibility at Pheonix and 

Tucson compared to trends in SOX emissions from Arizona copper smelters 

(Marians and Trijonis, 1979). 

_ TlIF. DOTS R~PRESENT YEARLY PERCENT OF IiQ<JRS WITH REDUCED VISIBILITY

IM£ASUnEOON LEFT AXISL !>JOTE THAT TH" TUCS(]N O!i$E~VATION S!Tl MOVED IN 195$; ALTHOUGH THIS MOVE DID NOT PROOlJr,F A STAT'~'CALLY 5WN1F'CIINl cHIINGE I!>J REPOflT£D V'S'''' L1T1Es, UPEIIl DOTS ARE USED TO DISTlNGlllSH DATA PRIOR TO 1958.

--THE LINES REPRFSENT YEARLY 50 EMISSIONS FP.OM A:t170NA COPPFR "Mf.LTEllS

(MEASLIHED DN RIGHT AI'I.), •

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24

The historical emission trends agreed qualitatively with the overall visibility trends 

noted in the previous section. Specifically, the slight and varied visibility trends from the 

late 1940s to the early/mid 1950s occurred while the principal emission changes were as 

follows: moderate decreases in Utah smelter SOx and in region-wide railroad SOx, 

moderate increases in Nevada smelter SOx and in region-wide sources of NOx and 

NMHC, and constant levels of Arizona smelter SOx (the single predominant source, on a 

tonnage basis, of aerosol precursor emissions in the Southwest). The 10 to 30 percent 

decrease in visibility (20 to 70 percent increase in extra extinction) form the early/mid 

1950s to the early 1970s was accompanied by a 70 percent increase in regional SOx

emissions (almost all due to a doubling of SOx from Arizona copper smelters), a three 

and one-half fold increase in regional NOx (almost all due to power plants and motor 

vehicles and a doubling of regional NMHC emissions (almost all due to gasoline 

vehicles)). The 5-10 percent improvement in visibility from the early to middle 1970s 

occurred as regional SOx emissions dropped 25 percent, regional NOx emissions 

increased 25 percent, and regional NMHC emissions decreased 5 percent. 

Marians and Trijonis used multiple regression techniques to derive quantitative 

relationships between yearly extinction levels (for six Arizona airport visibility data sets) 

and yearly Arizona emissions of smelter SOx, non-smelter SOx, NOx, and NMHC. The 

multiple regressions selected Arizona smelter SOx as, by far, the most significant 

variable for each of the data sets and as the only significant variable for five of the data 

sets. The particularly close relationships between Arizona smelter SOx and visibility at 

Tucson and Phoenix are illustrated in Figure 4-12. 

The significant relationship between extinction in Arizona and copper smelter 

SOx emissions is not surprising in light of the extremely large emissions arising from the 

smelters. For example, during the late 1960s and early 1970s, Arizona NMHC and NOx

emissions constituted about 3⁄4 percent of the nationwide total NHMC and NOx, but 

Arizona SOx emissions (96 percent of which cam from the smelters) constituted over 6 

percent of the nationwide total SOx. Also, the Arizona smelters emitted over ten times as 

much SOx as the Los Angeles basin and over four times as much SOx as the state of 

California (Marians and Trijonis, 1979). 

Data Set Correlation 

Coefficient 

Regression 

Coefficient 

extinction/emissions 

km-1/(1000 TPD) 

t-Statistic 

(t > 1.7 for 95% 

confidence) 

(t 2.5 for 99% 

confidence 

Tucson (1950-1975) 0.91 0.0035 11.1 

Tucson (1959-1975) 0.88 0.0038 7.2 

Phoenix (1959-1975) 0.81 0.0041 5.4 

Winslow (1948-1973) 0.68 0.0047 4.5 

Prescott (1948-1975) 0.70 0.0031 5.0 

Prescott (1949-1969) 0.70 0.0039 4.4 

Table 4-5. Correlation/regression analysis between airport extinction and copper 

smelter SOX emissions (Marians and Trijonis, 1979). 
25

Table 4-5 summarizes the results of the correlation/regression analysis between yearly 

airport extinction (visibility) data and Arizona smelter SOx emissions. The correlation 

coefficients and t-statistics indicate significant statistical relationships at high confidence 

levels. The regression (extinction/emission) coefficients are remarkably consistent from 

site to site and represent the change in yearly median extinction associated with a given 

change in SOx emissions; i.e., adding 1000 tons/day of SOx tended to increase yearly 

median extinction by approximately 0.004 km-1. Considering the placement of the 

airports and smelters, these extinction/emission estimates might pertain to distances of 

approximately 50 to 200 miles (80 to 320 km) from the source (Marians and Trijonis, 

1979). 

Because of the limited number of data points (at most 28 yearly values) and because of 

problems introduced by intercorrelations among the emission variables, Marians and 

Trijonis could not isolate the effects of NOx and NMHC emissions on extinction trends in 

Arizona. They found several indications, however, that the effects of NOx and NMHC 

were probably significant, although secondary to the effects of the large SOx emissions in 

Arizona. Moreover, estimates of the extinction/emission coefficient for SOx could be 

inflated because of concurrent changes in NOx, NMHC, and primary particulate 

emissions. 

Figure 4-13. Seasonally adjusted changes in sulfate during the copper strike of 

1967-68 compared to the geographical distribution of smelter SOX emissions 

(Trijonis and Yuan, 1978a). 

Regression studies relating extinction trends to historical emissions were also 

performed for four other sites: Salt Lake City, Denver, Grand Junction (Colorado), and 

Ely (Nevada). Possibly because of the lack of a predominating emission type (such as 

SOx in Arizona), the regressions tended to have lower statistical significance than in 

ollR6#-N Sl~~

o1'I0l'lUAil"'" SITE

1'10 200

L ' SCALE ..J \"'11..~$1
26

Arizona, and the extinction/emission coefficients lacked consistency from site to site. 

Although the results were somewhat uncertain, the analysis did suggest that growth in 

urban emissions of photochemical precursors (NOx and NMHC) was the key factor 

related to visibility changes in Salt Lake City and Denver, and that a measurable impact 

for the Arizona smelters may have extended well north of Arizona. 

4.3.2.3 The 1967-1968 Copper Strike—In the late 1960s, copper smelters accounted for 

approximately 90 percent of the sulfur oxide emissions in the Rocky Mountain Southwest 

(Marians and Trijonis). The nine month industry-wide shutdown of the smelters during a 

labor strike (July 1967-March 1968) provided a unique opportunity to investigate the 

relationship between SOx emissions and regional visual air quality. 

Trijonis and co-workers examined regional changes in sulfate concentrations and 

visibility during the strike. As shown in Figure 4-13, substantial decreases in sulfate 

occurred at five locations (Tucson, Phoenix, Maricopa County, White Pine, and Salt Lake 

City) that are within 12 to 70 miles of copper smelters. More notably, sulfates evidently 

dropped by about 60 percent at Grand Canyon and Mesa Verde; these class I areas are 

located 200-300 miles from the main smelter area in Southeast Arizona. 

Figure 4-14. Seasonally adjsted percent changes in visibility during the copper 

strike compared to the geographcal distribution of smelter SOX emissions (Trijonis 

and Yuan, 1978a). 

As shown in Figure 4-14, Trijonis and co-workers found that visibility improved at 

almost all locations during the strike, with the largest improvements occurring near and 

downwind (north) of the copper smelters in southeast Arizona and near the copper 

smelters in Nevada and Utah. The nine locations showing statistically significant 

improvements are all within 150 miles of a copper smelter. 

o URBAN IlolflP()l\T5

o NOl'lU"l>Al'I P.IRPQRTS

YlI"SLOW

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.

....
27

Many of the sulfate and visibility changes during the copper strike are statistically 

significant at extremely high confidence levels (Trijonis, 1979). The statistical 

significance of the changes is also illustrated by step functions in the time series data 

(Figure 4-15) and by major differences in frequency distributions (Figure 4-16). 

Preliminary analyses of meteorological data indicated that unusual weather did not 

contribute significantly to the observed air quality changes during the strike (Trijonis and 

Yuan, 1978a). 

The reductions in sulfate and extinction during the copper strike tend to confirm the 

results of the multiple regression models for Phoenix and Salt Lake City (See 4.2.2.2). 

For example, the regression model for Phoenix indicated that sulfates account for 53 

percent of extra extinction. Since sulfates decreased by 62 percent in Phoenix during the 

strike, one would predict that extra extinction should decrease by 33 Percent (0.53x62%). 

The actual decrease in extra extinction, computed from the visibility increase, was 29 

percent, quite good agreement. Similar agreement was found in Salt Lake City. 

There is one paradox concerning the air quality changes during the copper strike. The 

spatial scale of the visibility impact during the strike (apparently on the order of 150 

miles from the smelters) seems to differ from the spatial scale of the sulfate changes 

(apparently on the order of 300 miles away from the smelters). In particular, as shown in 

Figures 4-13 and 4-14, significant improvements in visibility did not occur in 

Farmington, NM, and Las Vegas, NV, although these sites experiences pronounced drops 

in sulfates. Several potential explanations for this discrepancy are discussed in Trijonis 

and Yuan (1978a), but the basic cause of the discrepancy remains unresolved. Latimer et 

al. (1978), however, found statistically significant improvements in visibility at 

Farmington (as well as other locations) during the strike by stratifying the data according 

to wind direction and/or relative humidity. 

Figure 4-15. Changes in number of hazy days at Tucson during the 1967-68 

copper strike. The number of hazy days before the strike (aobut 50%) fell to about 

20 percent during the strike and rose to about 80 percent during the following year 

when copper production expnded substtantially (Hartmann, 1972). 

Marians and Trijonis (1979) used the air quality changes during the copper strike to 

estimate regional extinction/emission coefficients for SOx. They found that both the 

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28

visibility data and sulfate data implied an extinction/emission coefficient of 0.001 to 

0.003 km-1/(1000 tons per day SOx) for the mesoscale region (50 to 200 miles from the 

source). This estimate for the mesoscale extinction/emission coefficient is somewhat 

lower than the one derived by the historical regression analysis (See 4.3.2.2). Marians 

and Trijonis also found some evidence of the following: (1) average regional extinction 

produced by an SOx emission source in the Southwest may tend to be inversely 

proportional to distance from the source; (2) at distances of 250-375 miles from the 

source, the extinction/emission coefficient may be approximately 0.001 km-1/(1000 tons 

per day SOx); and (3) at distances within 10 to 15 miles from the source (within the air 

basin scale), the extinction/emission coefficient may be as high as 0.01 to 0.025 km1

/(1000 tons per day SOx). AS indicated by the qualified wording, however, these latter 

three conclusions are regarded as tenuous. 

Figure 4-16. Frequency distribution of sulfate concentrations during te copper 

strike compared to seasonal average distriution for Grand Canyon and Mesa Verde 

data combined. Most sulfate measurements fell below 1.2 μg/m3

 during the strike 

(Trijonis and Yuan, 1978a). 

4.3.3 Limitations of the Historical Trend Studies 

The greatest drawback in the visibility trend analysis is the possibility that the trends 

may be distorted by changes in visibility observation procedures or that airport visibility 

does not adequately represent regional conditions. Of particular concern are relocations 

of the observation sites, excessive turnover of personnel on the observation teams, and 

changes in reporting practices (i.e., the set of visual ranges that are routinely reported). 

Husar et al. (1979) attempted to minimize the overall effect of such changes by using data 

from a large number of airports (70 locations in the East). Trijonis and co-workers 

FREQUENCY DISTRIBUTION OF SULfATE

FOR JULY-MARCH SEASON IN fOUR YEARS

SURROUNDING THE COPl'ER STRIKE

1142 MEASUREMENTS AT GRAND CANYON OR MESA VERDEI

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I I 134 MEASUREMENTS AT GRAND CANYON OR MESA VERDE)

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29

performed data quality checks and restricted their analysis to sites and time periods of 

constant observation location, stable personnel, and consistent reporting practices. 

Because changes in visibility observation procedures—even very subtle changes—can 

distort visibility trends at individual airports, it is important to examine trends at 

numerous locations to see if a consistent pattern emerges. Su h consistency has been 

found both in the Northeast and in the Southwest. For example, Figure 4-17 

superimposes third quarter extinction trends for about 15 stations, each in the centraleastern states and the Northeast Megapolis Area. 

Several other factors add confidence to the conclusions reached concerning East and 

Southwest visibility trends: 

1. The visibility trend pattern for the East is supported by very similar patterns in trend 

data for SOx emissions, ambient sulfates, photometric turbidity, and acid rain (see 

4.3.1). 

2. One of the most significant features of the Northeast trends, the deterioration in 

summer visibility relative to winter visibility, is independent of changes in visibility 

reporting procedures. 

3. In the Southwest, qualitative agreement (and in some cases very high quantitative 

correlation) exists between visibility trends and emission trends. 

 

4. These factors and the site-to-site consistencies significantly lessen the uncertainty 

associated with the trends. Confidence in the conclusions should be especially high for 

the Northeast where there is a multitude of visibility stations and where independent data 

sets (e.g., for sulfates and turbidity) confirm the results. 

Figure 4-17. Third-quarter extinction trends at various locations in the 

central/eastern States and the Northeast Megapolis area (Husar et al., 1979). 

For studies that have related visibility trends to historical changes in emissions, a basic 

limitation is the intercorrelation among trends in various types of emissions (e.g., SOx, 

1960 1960 1970 1980

QUARTER 3

19541 1960 1910 1980 1940

3,

5. l'TTITT"r"rrrrTTT1nnTTT'1r'TTTTTT'f

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CENTRAL/EASTERN STATES NORTHEAST MEGAPOllS AREA
30

NOx, NMHC, and primary particles). This drawback may be less severe in cases such as 

central/southern Arizona, where emissions of a single pollutant (e.g., SOx) appear 

dominant. In many other cases, however, the effect of intercorrelated emission variables 

may be important. For example, although the patterns of sulfate increases and visibility 

decreases in the Northeast seem to be consistent with the patterns in SOx emission 

changes, one cannot rule out significant contributions from NOx and/or NMHC emissions 

in the production of the observed air quality changes. Disentangling the individual 

impact of each emission variable cannot be accomplished by historical trend analysis 

alone. Moreover, potentially important emissions of primary particles (dust storms, fires, 

and stack emissions) were not included in the analysis. 

Another problem of emission-visibility trend analysis is that of choosing the proper 

spatial scale in a region such as the Eastern United States. If the scale of trend analysis is 

chosen to be, say a 700-km sized region, then long-range transport from neighboring 

sources may obscure the cause-effect relationship. If on the other hand, the scale is too 

large, say the entire Eastern United States, then the trends within interdivided sub-regions 

(e.g., states) are masked by the overall averages. 

4.4 WIND DIRECTION ANALYSES 

The estimation of source-receptor relationships via “pollution roses” has been used 

successfully for decades in the case of primary pollutants, such as sulfur dioxide. In its 

simplest form, the method consists of classifying each pollutant measurement according 

to the corresponding wind direction and computing the average pollutant concentration 

for each wind direction class. The plot of average concentration versus wind direction is 

referred to as a pollutant rose; with careful selection of the wind direction classes, it is 

possible to infer the individual effect of local sources. The major assumption required in 

such analysis is that the plume must arrive at the receptor from the same direction in 

which the source lies. 

A similar technique has been applied by Latimer et al. (1978) to historical visibility 

data from Farmington, NM (Figure 4-18). The percentage of daylight observations for 

which RH < 60 percent and visual range > 121 km was chosen rather than the mean. The 

visual range was significantly improved for the South-Southeast (SSE) to West (W) wind 

direction classes during the shutdown of copper smelters, lying in the same directions at 

distances of more than 400 km. Thus it might be inferred, for example, that the smelters 

cause a major portion of the reduction of visual range below 121 km associated with SSE 

winds. 

Most cases of general haze/source location are not as clear as the smelter strike. 

During long-range transport, the plume may meander and arrive at the receptor from 

almost any direction. In these situations, the traditional pollution rose may be inadequate 

for determining the sources of regional haze. 

The utility of wind directional analysis determining the source-receptor relationship 

may be improved by the more sophisticated approach of trajectory sector analysis. 

Backward air-parcel trajectories are performed to determine the source region that 

contributes most strongly to the measured concentration. The direction from the receptor 

to the source may then be used in place of the local wind direction in construction of the 

pollution rose (Figure 4-19). Samson (1978) and Niemann et al. (1978) have used this 

approach to establish the importance of Ohio River Valley sources of sulfate 
31

concentrations at non-urban sites Pennsylvania and NY State. Chung (1978) used 

trajectory analysis to implicate the same region as an important source of sulfate in 

southwestern Canada. Rodhe et al. (1972), Brosset et al. (1975), and others established 

the importance of continental European sources via this technique. The Organization for 

Economic Cooperation and Development (OECD) Program on the Long-Range 

Transport of Air Pollutants (LRTAP) included trajectory sector analysis of sites across 

Europe. 

The more elaborate trajectory analysis techniques are easily adapted to include simple 

gas-particle conversion and removal kinetics along the trajectory. Such models are used 

to extract the regional average rate constants from source emissions and measured 

concentrations, as in the OECD project. Such empirical approaches to data analysis, 

which are known diagnostic models, are discussed further in (4.6). 

In summary, observed measurements of aerosols wand visibility parameters such as 

contrast (bscat) or visual range can be attributed to sources or source regions when the 

meteorological transport between source and receptor is known. For conditions where 

long-range transport and unsteady winds are significant, the utility of pollution roses may 

be increased by receptor-back-to-source trajectory computations. 

 

Figure 4-18. Percentage of daylight observations with RH < 60% for which 

visual range was > 121 km as a function of wind direction at Farmingotn, NM. The 

period of the copper strike sows significant improvement of visual range from the 

direction of copper smelters, SSE to W implicating the contribution of these SOX

sources (Latimer et al., 1978). 

100 r-___,r---r-~---,..-..,__-:r_-r____,-__r-..,- ....- ....- ....

fOliE So. iSE SSW SW VlSW W WNW NW NM't

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WM EN COMPARED WITIf THE REMAINDE R OF

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OL----I_-L_..J-_......-JL----l._-L_.l-_L...----'_-L._..J-_-'---''----1

N

80

\"fIND DI RECnON
32

Figure 4-19. Hypothetical backward trajectory illustrating the curved transport 

path of a plume arriving at receptor point A. If the emissions originated at source 

D, the direction of the source-receptor sector is defined by the line from D to A and 

not the local wind direction (Samson, 1978). 

4.5 DIRECT OBSERVATIONS OF SOURCE IMPACTS: PLUMES AND 

REGIONAL HAZES 

In the previous three sections, the source-receptor relationships were examined from 

the point of view of the receptor; i.e., what source types contribute how much to the total 

burden at that site. An alternative approach, discussed in this section, is that of starting at 

the source and following the transmission of the air pollutants through the atmosphere 

until they are ultimately removed. Studies of this kind permit identification of the 

specific roles of transport, transformation and removal processes, which facilitates 

consideration of these transmission processes in the appropriate control strategies. 

4.5.1 Power Plant and Smelter Plume Studies 

Since the late 1960s and increasing fraction of the national sulfur oxide emissions to 

the atmosphere have been released from tall stacks, of 150-300 meters height. The 

visible impact of these emissions begins in the near stack region, where primary particles 

can make the plume itself visible against the background sky and where fumigation can 

occur. The impact of such stacks may extend large distances downwind, where the 

secondary products (sulfates and NO2) can cause layers of discoloration and general haze. 

The atmospheric transmission of tall stack effluent has been studied extensively during 

the past decade, by EPA, DOE, the Electric Power Research Institute (EPRI), and others. 

In these studies, the transport, chemical transformations, removal, and the interaction of 

these processes in determining the sulfur budget of large plumes have been assessed. 

One set of results and conclusions of these studies is given in Figure 4-20. 

Instrumented aircraft have been used to track and characterize plumes from large 

sources. A number of these studies have included visibility (light scattering) 

measurements. EPA’s MISTTT* project tracked the plume from the Labadie power 

plant near St. Louis. Figure 4-21 illustrates the plume geometry and the measured sulfur 

dioxide concentrations attributed to the Labadie plume for two long-range sampling days, 

D

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33

July 9 and July 18, 1976. On both days, the plumes were tracked to about 300 km from 

the source. 

The average light scattering coefficient imposed on the background by the Labadie 

power plant plume is shown in Figure 4-22. Near the source, over the first 50 km, the 

excess light-scattering coefficient was quite variable (between 0.01 to 0.10 km-1). At 

distances of between 50 and 200 km, however, the MISTT data indicate a rather uniform 

light-scattering coefficient of 0.05 km-1 plume excess bscat, averaged over the plume 

width. This observation indicates that the horizontal and vertical dispersion of the plume 

material is generally balanced by the formation of secondary aerosols. Neglecting 

background, at that bscat level, the visual range would be approximately 60 km, which is 

typically the width of the plume at 100 or 200 km from the source when dispersed by 

daytime convection. 

Light scattering measurements for the Four Corners power plant in New Mexico have 

been reported by EPRI. These measurements, extending to 50 km from the source are 

compared to the Labadie plant in Figure 4-22. Plume excess bscat near the Four Corners 

plant (less than 20 km) is higher or equal to comparable measurements at Labadie. 

Where, however, excess bscat for Labadie tends to remain constant at greater distances, 

the Four Corners generally show a decrease with distance. In this regard it should be 

noted that annual SOx emissions from Four Corners are roughly 1/3 that of Labadie but 

primary particulate emissions from Four Corners are as much as ten time higher (FPC, 

1976). Primary particulate impacts are greater near the source (See Figure 1-5) and tend 

to decrease with distance. Secondary particulate sulfates (related to SOx emissions) that 

form during transport are probably responsible for maintaining bscat levels in the Labadie 

plume. 

Figure 4-20. Results of plume studies (Husar et al., 1979). 

Figure 4-20a. Diurnal pattern of plume dispersion. The vertical plume 

dispersion is limited at night by the stability of the planetary boudary layer, 

resulting in narrow ribbon-like plumes at night and in the early morning. Daytime 

dispersion increases as the "mixing" layer height increses to about 1 km, diluting 

the plume and decreasing near source visual impact. Late afternoon atmospheric 

instability and plume buoyancy results in elevation of tall stack plumes to 1-2 km 

heights. Such a plume may appear as a visible, elevated ribbon. 

1100

'JIIXI~(t t-4fl\iMr r- :I

1000

c

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5 10 11 I. U

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T1MI OF DAV
34

Figure 4-20b. Diurnal sulfate formation rate. The daytime conversion rate of 

SO2 to light scattering sulfates in the MISTT study was quite variable, between 1 to 

4%/hr, whereas nightime values were consistently below 0.5%/hr. Either 

photochemical conversion or liquid-phase oxidatio in daytime cumulus clouds are 

consistent with the daytime peak of conversion rate. 

Figure 4-20c. Diurnal frction of SO2 conversion to aerosol. The amount of 

particulate sulfur formed increases when the plume is removed from the surface by 

dilution or by decoupling from the surface layer. Hency daytime emissions into 

deeply mixed layers or elevated stable layers are expected to produce more sulfate 

than nighttime emissions. 

Gr---~r----r----T'""~~-""'---""""'~--'"

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35

Figure 4-21. Horizontal profiles of SO2 during selected constant altitude aircraft 

flights on July 9 and July 18, 1976. July 9 traverses are at about 450 m above 

ground, and July 18 traverses are at about 750 m. The Labadie plume sections are 

shaded. Also shown are backward trajectories for the Labadie plume. The plume 

was tracked to distances of over 300 km from the plant (Gillani, 1978). 

Figure 4-22. Average plume excess bscat measured during flights through the 

Labadie and Four Corners power plant plumes (MRI, 1976; EPRI, 1977). 

SCAlE

o 20 4{)

KilOMETERS -

.12 I I I

0

.10 Io lABADIE

• FOUR CORNERS -

";'

] .OB - 0 -

• 0 .. .06 - ~O 0 0

'" 0 w - <.l ~O. 0 0

X 0 0 w 0 08 w .04 ..0 00 0

:l: 0 0

:l 0 0 .... 00. 0

"-

.02 - <i 8~·": -

0·. · · 0 ,... I I

0 50 100 150

DISTANCE FROM STACK, km
36

Figure 4-23. San Manuel smelter plume viewed from VISTTA aircraft. View is 

approximately eight km downwind of the smelter. 

In the VISTTA program, plume visibility parameters have been measured in the San 

Manual Smelter (Figure 4-23) (Arizona) and the Mohave Power Plant (California) 

(Macias, et al., 1979). An indication of sulfate formation at distances greater than 30 km 

was reported. The SO2 transformation rate in the smelter plume was estimated to be 

0.7%/hr, or comparable to rates measured for Labadie and other sources. An excess 

plume visibility budget for these sources is presented in Table 4-6. Sulfates account for 

43 percent of plume light scattering in the smelter plume (at 60 km), the balance being 

made up of primary coarse and fine particles. These results suggest that the statistically 

derived smelter extinction/SOx emissions estimates reported in Section 4.3 may be 

somewhat high. The Mohave data are not representative of a typical power plant plume 

because wind blown dust from agricultural activities were mixed into the plume during 

the sampling period. 

The visibility impacts of the plume measurements discussed above are compared in 

Table 4-7. Visual range (Vr) is calculated for an observer standing at the edge of the 

plume, viewing a hypothetical black target. Visual range and plume impacts for the 

measured background conditions during the studies are given. To enhance the 

comparison among sources, the impacts of the plumes on visual range for relatively clean 

background conditions (Vr = 195 km) are given in the last column. The plume impacts 

are marked and in some cases are dramatic. Visually, the plumes would cause the 

whitening of the horizon sky and reduction in general contrast associated with haze. If 

the plumes were elevated from the surface, they could appear as definable haze layers. 

4.5.2 Urban Plumes 

Urban plumes constitute an aggregate plume from various sources originating within a 

metropolitan area. The best-studied urban plume is that of the metropolitan St. Louis 

area, a major industrial center, encompassing coal-fired power plant with a combined 

capacity of 4600 MW, oil refineries with a combined capacity of 4.4 x 105

 barrels per 
37

day, various other industries and a population of about 2 million (White et al., 1976). 

Because St. Louis is remote from other major metropolitan areas, its impact on the 

surrounding ambient air quality is relatively easy to identify; air that has been modified 

by the aggregate emissions of the metropolitan area form an “urban plume” downwind. 

The Fate of Atmospheric Pollutants Study (FAPS) (e.g. Hagenson and Morris, 1974) has 

shown that this plume is often identifiable at distances of 80 to 120 km from the city. 

Component Particle Size (μm) bscatc

 (km-1) Contribution to total 

particle scattering (%) 

San Manuel Smelter (62 km downwind) 10/4/77 

(NH4)2SO4

a

 0.1 to 1.0 0.041 43 

SiO2

b 0.1 to 1.0 0.0095 10 

Other compounds 0.1 to 1.0 0.0055 6 

Coarse particles 1.0 to 20.0 0.039 41 

 0.095 100 

Mohave Power Plant (32 km downwind) 10/8/77 

(NH4)2SO4

a

 0.1 to 1.0 0.003 11 

SiO2

b 0.1 to 1.0 0.002 7 

Other compounds 0.1 to 1.0 0.001 4 

Coarse particles 1.0 to 20.0 0.021 78 

 0.027 100 

Table 4-6. Plume excess visibility budget. aAssumes that all fine particle sulfate 

exists as ammonium sulfate. bAssumes that all fine particle silicon exists as SiO2. c

Determined from bscat (total) – bscat (fine particles). 

As a part of project MISTT (Wilson, 1978), the three-dimensional flow of aerosols 

and trace gases in the St. Louis urban plume was studied. The plume was successfully 

tracked up to 240 km, and it was mapped quantitatively up to 160 km (Figure 4-24). At 

these distances, the plume was still well defined and on the order of 50 km wide. 

An increased concentration of light-scattering aerosols was a key characteristic of the 

St. Louis urban plume. The primary contribution of project MISTT was to quantify the 

flow of material at increasing downwind distances so as to study the transformations that 

pollutants undergo in the atmosphere. 

The flow rate of ozone light scattering (bscat) and particulate sulfur (Sp) all increased 

with distance downwind of St. Louis on July 18, 1975, reflecting the secondary origin of 

ozone and most of the light scattering aerosols (White et al., 1976). Most of the increase 

in the bscat flow rate was observed downwind of the major increase in ozone flow rate; 

this is consistent with the finding of laboratory studies that aerosol production lags 

behind ozone production in a photochemical system (Wilson et al., 1973). The ratio of 

the flow rate of bscat to the flow rate of particulate sulfur (Sp) indicates that sulfate 

compounds accounted for most of the newly formed light scattering aerosol in the urban 

plume. This case study illustrates that emissions from a metropolitan area such as St. 

Louis can cause reduced visibility and elevated ozone concentration in urban plumes, 

long after their primary gas phase precursors have been diluted to low concentrations. 
38

Visibility perpendicular to plume (through plume) 

(From experimental data) (Normalized to “clean” 

background) 

Visual Range Visual Range 

Source SOX

emission 

(tons/day) 

Down 

wind 

distance 

(km) 

Plume 

width 

(km) 

Plume 

excess 

light 

scattering 

(km-1) 

With 

Plume 

(km) 

Backgr

ound 

(km) 

Visual 

range 

reduction 

due to 

plume 

(%) 

With 

plume 

Backgr

ound 

Visual 

Range 

reduction 

due to 

plume 

(%) 

Labadie Power 

Planta

 (St. 

Louis) 

880d

 40-60 20 0.030 28 30 7 165 195 15 

 150-

200 

60 0.050 23 30 23 56 195 70 

Four Cornersb

Power Plant 

(New Mexico) 

250d

 50 25 0.020 50 55 10 170 195 13 

San Manuelc

Smelter 

(Arizona) 

557 8 16 0.283 12 85 86 12 195 94 

 32 20 0.092 45 85 47 103 195 47 

 60 25 0.095 46 120 62 76 195 61 

 127 54 0.050 36 120 70 80 195 69 

 66 32 8 0.018 104 110 5 191 195 2 

Mohavec

Power Plant, 

(+ wind blown 

dust) 

 60 27 0.033 84 110 24 150 195 23 

Table 4-7. Aircraft measurements of plume visibility impacts. aTypical values 

for July 9, 11, 1979; see Figure 4-2 (MRI, 1976). bTypical values for July 10, 1976; 

see Figure 4-2 (EPRI, 1976). c

Excess bscat from Table 9; Plume width, Table 10 

(Macias et al., 1979). dBased on annual (1976) emissions (FPC, 1976). 

The visibility reduction in the St. Louis urban plume was also studied as part of 

project METROMEX. Komp and Auer (1978) have reported actual observations of 

visual range from aircraft downwind of St. Louis and presented those as contour maps, 

Figure 4-25. Their observations show that, within about two hours of aging in the urban 

plumes, the visual range was reduced by a factor of two. 

 

4.5.3 Regional Scale Episodes of Haziness 

Episodes of regional-scale haziness have been observed in the Eastern United States. 

While the class I areas east of the Mississippi account only for about 20 percent of the 

class I area acreage, their proximity to population centers results in high visitor 

attendance. For example, the Shenandoah National Park in Virginia has been among the 

most frequently visited class I areas in the United States (Bammel and Bammel, 1978). 
39

Figure 4-24a. Ozone and light scattering (bscat) measurements downwind of St. 

Louis on 18 july, 1975. Data are taken from horizontal traverses by instrumented 

aircraft, at altitudes indicated in figure 4-24b. Graph base lines show sampling 

paths; base-line concentrations are not zero. 

Figure 4-24b. Traverse altitudes and pollutant flow rates in the St. Louis urban 

plume on 18 July, 1975. Data are plotted against distance downwind of the St. Louis 

Gateway Arch. Closed circles correspond to traverse shown in 4-24a. Mixing 

heights were determined from aircraft surroundings. Approximate time (C.D.T.) of 

sampling is shown at the bottom. 

Figure 4-24c. Flow rates (in excess of background) of ozone (O3), bscat, and 

particulate sulfur (Sp). The total loading across the plume for all these increases, 

indicating that these pollutants are being produced in the plume. 

>

A

I

MISSOURI

_.__ I,UUI'4lt:

0_.-.-.-. bw:..t

~os

SOktn. 1- ..J1

A POWER PLANT

• REFIIIIERIES

w

0- ::>...J

I- Cil

I--~• ...JE

«-

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o

::t

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Z

o

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Q.

CIl

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0.5

8 E'G~1..---------- . __ -,\"G __ -- 0 0_

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0915 1230 1400 1645 1815

o

50 100 150

DISTANCE DCM'NW!I'I:> (kml
40

Figure 4-25. Visual range contours (statute miles) downwind of St. Louis for 9 

August, 1976 between 1400-1800 CDT. Outline of city limits and surrounding 

communities is represented by short-dashed lines and the metropolitan area by 

long-dashed lines. 

Large-scale episodes of reduced visibility in the West have not yet been documented. 

The meteorological conditions, which lead to regional episodes also occur in the West, 

but, because of the low density of air pollution sources, Western episodes would be much 

less intense than in the East. Efforts to detail Western haze episodes are now under way 

(Niemann, 1979). 

One of the earliest case studies of transport of large-scale hazy air masses was that of 

Hall et al. (1973). Since about 1975, the evolution and transport of regional-scale hazy 

air masses have received increasing attention by numerous research groups. Detailed 

case studies of such episodes have been reported by Tong et al. (1976), Husar et al. 

(1976), Lyons and Husar (1976), Wolff et al. (1977), Samson and Ragland (1977), 

Vukovich et al. (1977), Galvin et al. (1978), and Hidy et al. (1978), among others. A 

common finding among recent studies is that formation of regional-scale haziness is 

~",'JG 19111

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I h•. .--+ .. _2-r-lw_. :l~h,.

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B

MfAN TRANSPORT l'iIND..
41

usually associated with the presence of slow moving high-pressure systems. Since 

precipitation is relatively infrequent in anticyclonic systems, the residence time of fine 

aerosol may be increased to a week or more. 

An example of one such episode over a two-week period I June-July, 1975, is 

presented in Figure 4-26 (Husar et al., 1976). The sequence of contour maps reveals that 

multistate regions are covered by a haze layer in which noon visibility is less than 10 km 

(bext = 0.4 km–1, outer contours). 

Figure 4-26. Sequential contour maps of noon isibility for June 25-July 5, 1975 

illustrate the evolution and transport of a large-scale hazy airmass. Contours 

correspond to visual range 6.5-10 km (light shade), 5-6.5 km (medium shade), and 

<5 km (black) (Husar et al., 1976). 

The regions of haziness in these and other such episodes are clearly visible in satellite 

photography (Figure 4-27) (Lyons and Husar, 1976). Sequential photographs confirm the 

motion of the haze. Figure 4-28 shows the impacts of regional haze at ground level. 

Two passages of the June-July, 1975, hazy air mass over St. Louis resulted I sharp 

increases of bscat over the entire metropolitan region. Sulfate concentration also 

increased during the haze episode, from about 9 to 33 μg/m3

. Figure 4-29 indicates 

substantial correspondence of the regions of highest sulfate and lowest visibility for two 

days during the episode period. During this period, the visual air quality was beyond the 

control of any local jurisdiction. The Alabama Air Pollution Control Commission 

reported the following (Bulletin of the AAPCC, 1975): 

“During the weekend of July 5, 1975, a heavy haze layer enveloped the State of 

Alabama and much of the Southeastern United States. At that time, the AAPCC 

technical staff received may comments from the public concerning the origin and 

composition of the haze. The National Weather Service in Birmingham did issue an air 

stagnation advisory (ASA) for Alabama for this same time period; however, the 

traditional pollutant measurements made by the AAPCC and local programs did not show 

excessive levels. In fact, the measured local levels were lower than had been measured 

under previous ASAs, making the dramatic decrease in visibility more intriguing.” 

KI'II

==- o 1000
42

Figure 4-27. Satellite photograph of hazy air transport. Haze appears over parts 

of Ohio, West Virginia, Eastern seaboard states and stretches several hundred miles 

into the Atlantic (Lyons, 1979). 

Figure 4-28. Eastern Regional Haze, (a) clear vista in White Mountains, New 

Hampshire (b) Effect of episodic haze intrusion. 

Husar et al. (1976) reported that in June-August 1975, there were at least six episodes 

similar to that discussed above. Other investigators confirm that episodes of regional 

scale hazy air masses are not rare in the Eastern United States. Yet, at present, only the 

qualitative features of such episodes are understood; the observed effect on visibility, the 

composition in terms of secondary sulfate and ozone, and the apparent motion of the 

haze. 

Important questions remain to be answered about regional scale episodes of haziness, 

including the following: 
43

1. Do the hazy air mass and the meteorologically defined anticyclone completely 

coincide? 

2. How may the effects of superimposing multiple SO2 plumes and urban reactive 

plumes be quantified? 

3. What are the effects of high pollutant concentration on rainfall, temperature, and 

cloudiness? 

4. What is the actual residence time of fine particulates in the atmosphere during such 

episodes; it may be, for example, that lack of precipitation leads to extremely long 

sulfate lifetime. 

Figure 4-29. Comparison of noon extinction coefficient and daiy mean sulfate 

concentration on June 23 and July 5, 1975. The regions of ighest sulfate 

concentratios coincide with area of lowest visibility (Husar et al., 1976). 

The current Sulfate Regional Experiment (SURE) program, sponsored by the Electric 

Power Research Institute, is yielding valuable information about sulfur transmission in 

the eastern United States. The Environmental Protection Agency’s Transformation and 

Transport in the Environment (STATE) program is directed toward expanded knowledge 

of the complicated source receptor relationship. The upcoming Prolonged Elevated 

Pollution Episode (PEPE) project of STATE is specifically designed to sample such 

regional scale episodes of haziness from their inception throughout their residence over 

the eastern United States. 

The East has experienced the most severe episodes of manmade haziness to date, 

because the sources of precursor gases are concentrated in that area. As noted in 4.3, 

empirical evidence indicates that anthropogenic sulfates are important factors in the 

visual air quality of the West and Southwest as well. Figure 4-30 from Holzworth (1972) 

reveals that the meteorological potential for air pollution/haziness in the West may be as 

high or higher than the Eastern U.S. potential. 

A

b,ut

I'EII 4 '.6

SloB _ :>8

SULFA.TE CONe. 1~;I",3,

.. :> 30

Em 20t.30

!Z::l 10,.20

c::l < 10

B

SULFATE eOfl/{:. (~gim31 _ :> 30

20'030

W 10t<>20

c:::J < 10
44

Figure 4-30. Isoleths of total number of forecast-days of high meteorological 

potential for air pollution in a 5-year period (Holzworth, 1972). Evidently the 

potential for regional scale anthropogenic haziness is at least as high in the West as 

in the East. 

4.6 DIAGNOSTIC MODELS 

When adequate information is available about both the source distribution and the 

total impact at a receptor, knowledge of the transmission from source to receptor 

completes the picture and permits quantification of the source-receptor relationship. The 

transmission of the most important pollutants that cause deterioration of visual air quality 

is more complex than simple dilution of the emissions by meteorological action; both 

NO2 and atmospheric aerosols undergo the additional processes of formation and removal 

during transport. These key processes are currently the least well-documented aspects of 

the visibility problem; particularly, for the secondary fine particulate species (e.g. sulfate, 

nitrate, and organics), these processes entirely determine the impact of a source. 

Since atmospheric kinetics cannot be measured directly, available emissions, 

trajectories, and resulting concentrations must be filtered through some mathematical 

formulation of the key processes to extract the rates of creation and depletion within the 

atmosphere. The mathematical formulation used for this purpose is referred to as a 

diagnostic model. 

One of the best-known applications of a diagnostic model was for the analysis of the 

OECD monitoring data (OECD, 1977). An emission inventory and transport conditions 

for the European region were input to the model. The rates of gas to particle conversion 

and removal were then extracted by tuning these parameters until the best fit between 

calculated and observed concentrations was achieved. The resulting parameters for sulfur 

transmission from the OECD study are listed in Table 4-8. 

The year-round average conversion rate of 1-2 percent per hour and the overall 

average dry removal rate of 3-4 percent per hour were major new results. Studies being 
45

conducted in the United States, with similar scope and objectives as the OECD study 

include the Multistate Atmospheric Power Production Pollutant Study (MAP3S) of the 

Department of Energy and EPA (MacCracken, 1978), and the aforementioned EPRI 

SURE program (Perhac, 1978), and the STATE project of EPA. Similar models have 

been deve4loped by Eliassen and Saltbones (1975), Fisher (1978), and Johnson et al. 

(1978). 

 

Characteristic Value 

Fraction of emitted sulfur deposited locally 00.15 

Fraction of emitted sulfur transformed 

directly to sulfate 

00.05 

Decay rate of sulfur dioxide 

Rain 14.4%/hour 

Dry 03.6%/hour 

Transformation rate of SO2 to sulfate 01.26%/hour 

Loss rate of sulfate 01.44%/hour 

Mixing height 1000m 

Table 4-8. Empirically derived atmospheric conversion and removal paramters 

for European region (OECD, 1977). 

The main utility of the regional approach is that the obtained rate constants are 

inherently averaged over all sources and spatial-temporal scales of interest. The suitably 

tuned model may then be used to separate the impact of an individual source. 

On a smaller scale, White and Husar (1976) estimated the aerosol size distribution 

dynamics contributing to visibility reductions at Pasadena, CA. Their study used 

emission grids of gases and particulates, solar radiation intensity, an initial marine 

background aerosol size distribution, and backwards trajectories at 1-hour intervals as 

inputs to the diagnostic model. The conversion rate was tuned to match the observed 

daily mean fine mass; thus, the output included hourly estimates of total fine mass and 

aerosol size distribution, as shown in Figure 4-31. Diagnostic models have also been 

developed for the urban plume of St. Louis (Isakson et al., 1978) and Power Plant Plumes 

(Gillani, 1978). 
46

Figure 4-31. (a) Calculated air trajectories arriving in Pasadena on 3 September 

1969; (b) Development of the calculated aerosol volume distribution (White and 

Husar, 1976). 

In summary, the determination of the source-effect relationship of secondary fine 

particulates on a regional scale requires the filtering of measurable data (emissions, 

transport path, and concentrations) through a diagnostic model. The impact of major 

source regions can be roughly estimated once the model is properly tuned. Also, with 

care, the tuned diagnostic model may be used to investigate the effect of altering source 

characteristics. 

hi

300

Ibl - CALCULATED

o MEASURED 250

M

E 200

M

E,.,

a. 0 150

i ..

!2

"D

;;

"D 100

I 0

50

0 0

8 0 8 00 0

ER?d I 0

5 0 5 0.1 1,0

,.. Dp ,lIm
47

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Sulfates in the U .S., J. Air Pollut. Control Assoc. 26: 318-324. 

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Barone, J.B., T .A. Cahil, R.A. Eldred, R.G. Floccltini, D.J. Shadoan, andT .M. Dietz, 

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Charlson, R.J., A.M. Vanderpol, D.S. Covert, A.P. Waggoner, and N.C. Ahlquist (1974) 

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Eilassen, A., and J. Saltbones (1975) Decay and Transformation Rates SO2 as Estimated 

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Fisher, B.E.A. (1978) The Calculation of Long Term Sulfur Deposition in Europe. 

Atmospheric Environment 12: 489-501. 

FPC (1976) Form 67. Steam Electric Air and Water Quality Control Data for Labadie, 

Four Corners Power Plants. Report to Department of Energy. 

Frank, N. and N. Posseil (1976) Seasonality and Regional Trends in Atmospheric 

Sulfates, Presented before The Division of Environmental Chemistry, American 

Chemical Society, San Francisco, California, September. 

Friedlander, S.K. (1973) Chemical Element Balances and Identification of Air Pollution 

Sources. Environ. Sci. Tech. 7: 235-240. 

Galvin, P.J., P.J. Samson, E.C. Peter, and D. Romano, (1978) Transport of Sulfate to 

New York State. Atmospheric Environment 9: 643-659. 

Gillani, N .V. (1978) Project MISST: Mesoscale Plume Modeling of the Dispersion, 

Transformation and Ground Removal of SO2. Atmospheric Environment 12: 569-588. 

Grosjean, D. et al. (1976) The Concentration, Size Distribution and Modes of Formation 

of Particulate Nitrate, Sulfate and Ammonium Compounds in the Eastern Part of the Los 

Angeles Basin. Presented at the 69th Annual Meeting of the Air Pollution Control 

Association, Portland, Oregon, June 27-July I. 

Haagenson, P.L. and A.L. Morris (1974). Forecasting the Behavior of the St Louis, Mo., 

Pollutant Plume. J . Appl. Meteorol. 13:901-909. 

Hall, F.P., Jr., C.E. Duchon, L.G. Lee, and R.R. Hagan, (1973) Long-range Transport of 

Air Pollution: A Case Study, August 1970. Mon. Weather Rev. 101: 404-411. 

Marker, A.B., et al. (1977) The Effect of Atmospheric SO2 Photochemistry upon 

Observed Nitrate Concentrations in Aerosols. Atmospheric Environment II: 87-91. 

Hartmann, W.K. (1972) Pollution: Patterns of Visibility Reduction in Tucsan. Journal of 

the Arizona Academy of Science 7: 101-109. 
49

Hidy, G.M., et al. (1975) Characterization of Aerosols in California Report SC 524.25FR 

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Hidy, G.M., P.K. Mueller, and E.Y. Tong, (1978) Spatial and Temporal Distributions of 

Airborne Sulfate in Parts of the United States. Atmospheric Environment 12: 735- 752. 

 

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Husar, R.B., W.H. White, D.E. Patterson, and J. Trijonis (1979) Visibility Impairment in 

the Atmosphere. Draft report prepared for U .S. Environmental Protection Agency under 

Contract No.68-02-2515 Task Order No.28. 

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Since 1948, Presented at the Fourth Symposium on Atmospheric Turbulence, Diffusion 

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Inhaber, H. (1976) Changes in Canadian National Visibility. Nature 260, March 11. 

Isaksen, I.S., E. Hesstvedt, and 0. Hov (1978) A Chemical Model for Urban Plumes: 

Test for Ozone and Particulate Sulfur Formation in St. Louis Urban Plume. Atmospheric 

Environment 12: 599-604. 

Johnson, W.B., D.E. Wolf, R.L. Mancuso (1978) Long-term Regional Patterns and 

Transfrontier Exchanges of Airborne Sulfur Pollution in Europe. Atmospheric 

Environment 12: 511-527. 

Komp, M. J., and A.H. Aver J r (1978). Visibility Reduction and Accompanying Aerosol 

Evaluation Downwind of St. Louis. J. Appl. Meteorol. 17:1357-1367). 

Korshover, J. (1967) Climatology of Stagnating Anticyclones East of the Rocky 

Mountains, 1936-1965, NAPCA . 

Latimer, D. A., R. W. Bergstrom, S. R. Hayes, M. T. Liu, J. H. Seinfeld, G. F. Whitten, 

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50

Leaderer, B.P., D.M. Bernstein, J .M. Daisey, M.T. Kleinman, T .J. Kneip, E.O. Knutson, 

M. Lippman, P.J. Lioy, K.A. Rahn, D. Sinclair, R.L. Tanner, G. T. Wolff. (1978) 

Summary of the New York Summer Aerosol Study (NYSAS) J. Air Poll. Contr. Assoc 

28: 321-327. 

Leaderer, B. P., T. R. Holford and J. A. J. Stolwijk (1979). Relationship Between Sulfate 

Aerosol and Visibility. J. Air Poll. Cntr. Assoc. 29:154-157. 

Lewis, C. W. and E. S. Macias, (1979) Composition of Size-fractioned Aerosol in 

Charleston, West Virginia, submitted for publication. 

Likens, G.E. (1976) Acid Precipitation. Chemical Engineering News 54: 29-44. 

Loo, B.W., W.R. French, R.C. Gatti, F.S. Goulding, J.M. Jaklevic, J. Llacer, and A.C. 

Thompson, (1978) Large-scale Measurement of Air-borne Particulate Sulfur. 

Atmospheric Environment 12: 759- 771. 

Lyons, C.E., I. Tombach, R.A. Eldred, F.P. Terraglio, and J.E. Core (1979). Relating 

Particulate Matter Sources and Impacts in the Willamette Valley during Field and Slash 

Burning, Paper No. 79-46.3, Annual Meeting of the Air Pollution Control Association, 

Cincinnati, Ohio, June, 1979. 

Lyons, W.A., and R.B. Husar, (1976) SMS/GOES Visible Images Detect a Synopticscale Air Pollution Episode. Mon. Weather Rev. 104: 1623-1626. 

Macias, E.S., D.L. Blumenthal, J .A. Anderson, B.K. Cantrell (1979) Characterization of 

Visibility Reducing Aerosols in the Southwestern United States; Interim Report on 

Project VISTTA. MRI Report 78 IR 15-85. 

Macias, E. (1979) Personal Communication. California Institute of Technology, 

Pasadena, CA. July. 

Macracken, M. C. (1978) MAP3S: An Investigation of Atmospheric, Energy Related 

Pollutants in the Northeastern United States. Atmospheric Environment 12: 649-659. 

Marians, M. and J. Trijonis (1979) Empirical Studies of the Relationship Between 

Emissions and Visibility in the Southwest. Prepared at Technology Service Corporation, 

under Grant 802015, for EPA Office of Air 4-49 

 

Quality Planning and Standards, and Atmospheric Chemistry and Physics Division of 

EPA Environmental Sciences Research Laboratory, Research Triangle Park, N. C. 

Miller, M. E., et al. (1972) Visibility Changes in Ohio, Kentucky, and Tennessee from 

1962-1969. Monthly Weather Review 100: 67-71. 

MRI (1976) Data volume for Project MISTT. St. Louis, Mo., July-August 1976. 
51

Munn, R. E. (1973) Secular Increases in Summer Haziness in the Atlantic Provinces 

Atmosphere 11: No.4. 

Niemann, B. L., E. Y. Tong, M. T. Mills and L. Smith (1979) Characterization of 

Regional Episodes of Particulate Sulfates and Ozone Over the Eastern United States and 

Canada. Paper to be presented at Symposium on Long-Range Transport, World 

Meteorological Organization, Sofia, Bulgaria, October 1979. 

Niemann, B. L. (1979). Personal Communication. Teknekron, Inc. Berkeley, CA. April. 

OECD (1977): The OECD Program on Long-range Transport of Air PollutantsMeasurements and Findings. Organization for Economic Cooperation and Development, 

Paris. 

Patterson, R. K. and J. Wagman (1977) Mass and Composition of an Urban Aerosol as A 

Function of Particle Size for Several Visibility Levels, J. Aerosol Sci. 8: 269-279. 

Perhac, R. M. (1978) Sulfate Regional Experiment in Northwestern United States. 

Atmospheric Environment 12: 641-647. 

Peterson, J. T., and E. C. Flowers, (1977) Interactions Between Air Pollution and Solar 

Radiation. Solar Energy 19. 

Rodhe, H., C. Persson, and 0. Akesson (1972) An Investigation into Regional Transport 

of Soot and Sulfate Aerosols. Atmospheric Environment 6: 675-693. 

Samson, P. J. (1978) Ensemble Trajectory Analysis of Summertime Sulfate 

Concentrations on New York. Atmospheric Environment 12: 1889-1893. 

Samson, P. J. and K. W. Ragland (1977) Ozone and Visibility Reduction in the Midwest: 

Evidence for Large-Scale Transport. J. Appl. Meterol. 16: 1101-1106. 

 

Spicer, C. W., and P. M. Schumacher, (1977) Interferences in Sampling Atmospheric 

Particulate Nitrate, Atmospheric Environment 11: 873-876. 

Tong, E. Y., G. M. Hidy, T. F. Lavery, and F. Berlandi, (1976) Regional and Local 

aspects of Atmospheric Sulfates in the Northeast Quadrant of the U. S. Proceedings, 

Third Symposium of Turbulence, Diffusion and Air Quality, American Meteorological 

Society. 

Trijonis, J. (1975) The Relationship of Sulfur Oxide Emissions to Sulfur Dioxide and 

Sulfate Air Quality. Air Quality and Stationary Source Emission Control, National 

Academy of Sciences. Prepared for Committee on Public Works, United States Senate, 

Washington, D.C. 

Trijonis, J. (1979) Visibility in the Southwest: An Exploration of the Historical Data 

Base. Accepted for publication in Atmospheric Environment. 
52

Trijonis, J., and K. Yuan (1978a) Visibility in the Southwest: An Exploration of the 

Historical Data Base, EPA-600-3-78- 039, U.S. Environmental Protection Agency, 

Research Triangle Park, N.C. 

4-50 

Trijonis, J. and K. Yuan, (1978b) Visibility in the Northeast: Long-term Visibility Trends 

and Visibility/Pollutant Relationships, EPA-600/3-78-975, U.S. Environmental 

Protection Agency, Research Triangle Park, N.C. 

White, W. H., and R. B. Husar (1976) A Lagrangian Model of the Los Angeles Smog 

Aerosol J. Air Poll. Contr. Assoc.26: 32-35. 

 

White, W. H., J. A. Anderson, D. L. Blumenthl, R. B. Husar, N. V. Gillani, J. D. Husar, 

and W. E. Wilson, (1976) Formation and Transport of Secondary Air Pollutants: Ozone 

and Aerosols in the St. Louis Urban Plume. Science 194: 187-189. 

Ursenbach, W. 0., et al. (1978) Visibility Models for the Arid and Semi-Arid Western 

United States, Paper No. 78-43.6 Presented at the 71st Annual Meeting of the Air 

Pollution Control Association, Houston, Texas. 

Vukovich, F. M., W. D. Bach, Jr., B. W. Crissman, and W. J. King, (1977) On the 

Relationship Between High Ozone in the Rural Surface Layer and High Pressure 

Systems. Atmospheric Environment II: 967-983. 

Weiss, R. E., A. P. Waggonner, R. J. Charlson, and N. C. Ahlquist, (1977) Sulfate 

Aerosol: Its Geographical Extent in the Midwestern and Southern United States. Science 

197: 977-981. 

Whitby, K. T. and G. M. Sverdrup (1978) California Aerosols: Their Physical and 

Chemical Characteristics. To be published in the ACHEX Memorial Volume. Particle 

Technology Laboratory Publications No.347, University of Minnesota, Minneapolis, 

Minnesota. 

White, W. H., and R. B. Husarn (1976) A Lagrangian Model of the Los Angeles Smog 

Aerosol J. Air Poll. Centr. Assoc. 26:32-35. 

White, W. H., J. A. Anderson, D. L. Blumenthol, R. B. Husar, N. V. Gillani, J. D. Husar, 

and W. E. Wilson, (1976) Formation and Transport of Secondary Air Pollutants: Ozone 

one Aerosols in the St. Louis Urban Plume. Science 194: 187-189. 

White, W. H. and P. T. Roberts, (1977) On the Nature and Origins of Visibility Reducing 

Aerosols in the Los Angeles Air Basin. Atmospheric Environment II: 803-812. 

Wilson, W. E., Jr. (1978) Sulfates in the Atmosphere: A progress report on Project 

MISTT. Atmospheric Environment 12: 537-547. 
53

Wilson, W. E. Jr. (1979) Personal Communication. Environmental Protection Agency. 

Environmental Sciences Research Laboratory. Research Triangle Park, N .C .August. 

Wilson, W. E., Jr., D. F. Miller, A. Levy, and R. K. Stone, (1973) J. Air. Pollut. Control 

Assoc. 23: 949. 

Winchester, J. W., R. J. Ferek, D. R. Lawson, J. 0. Pilotte, M. H. Thiemens, L. E. Wagon, 

(1979) Comparison of Aerosol Sulfur and Crustal Element Concentrations in Particle 

Size Fractions from Continental U.S. Locations. Submitted for publication. 

Wolff, G. T., P. J. Lioy, R. E. Meyers, and R. T. Cederwall, (1977) An Investigation of 

Long-range Transport of Ozone Across the Midwestern and Eastern United States. 

Atmospheric Environment II: 797-802. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 5
5 MODELING VISIBILITY IMPAIRMENT 

5.1 INTRODUCTION 

While the empirical approaches of Chapter 4 are useful for identification or 

confirmation of source impacts on visibility, "prognostic " mathematical approaches are 

needed to predict the visibility improvement associated with retrofit controls or the 

incremental effect of proposed new sources. Thus, visibility models predict, for a given 

set of environmental conditions, the visual effects resulting from air pollution loadings of 

the atmosphere. The general flow of a visibility model is shown in Figure 5-1. Visibility 

models adapt the atmospheric dispersion and transformation features of other air 

pollution models to predict fine particle and nitrogen dioxide concentrations across a 

sight path. The modeling procedure must relate changes in light scattering and 

absorption, resulting from those atmospheric constituents, to changes in contrast, which 

will be perceived as changes in visibility. 

Visibility models require information about the dispersion, transport, transformation, 

and removal of the pollutants, as well as the optical characteristics of the pollutants, the 

background air, and the environment (illumination, target properties). These factors must 

be further related to human visual perception to evaluate possible visibility impairment. 

Although there are uncertainties in all of these areas, ongoing research should result in 

significant refinements over the next several years. 

5.2 REGIMES OF VISIBILITY IMPAIRMENT 

Visibility models must address the major categories of impairment: "plume blight,” 

layers of discoloration, and general haze. As a preface for constructing predictive models, 

it is helpful to consider the processes that lead to these types of impairment. To simplify 

discussion, they are considered here as two separate regimes, depicted in Figure 5-2. 

Plume blight may be defined as a coherent, identifiable plume, which can be seen as 

an optical entity against the background sky or distant object. Implicit in this definition is 

the assumption that a single source produces light-affecting pollutants that are not widely 

dispersed. Thus, plume blight is considered "local" and can be treated with traditional 

Gaussian dispersion modeling. 

As the plume travels downwind, it diffuses throughout the mixing layer and becomes 

identified less as a "plume, " but more as a general haze, which obscures the view of 

distant objects. Not only are targets on the horizon masked, but also the contrast of 

nearby objects is reduced. In some cases, the haze may be elevated and appear as layers 

of discoloration. Multiple sources may combine over many days to produce haze, which 

may be regional in scale. The summertime haze in the Eastern United States is a 

prominent example of a very large-scale haze. Because of these different visual 

impairment regimes, separate modeling approaches must be used: short-term dispersion 

from a single source to model plume blight, and regional transport and climatic models to 

accommodate single or multiple sources on a larger meteorological scale. Scales of time 

and distance, which provide the dimensional framework for modeling, are graphically 
depicted in Figure 5-3. It is logical first to consider local short-term dispersion, which 

results in plume blight and haze layers from single sources. 

5.3 SINGLE-SOURCE GAUSSIAN MODELS 

Gaussian dispersion modeling, long used for estimating single-source pollution 

concentrations, is a reasonable concept for developing a local, single-source visibility 

model. With appropriate geometry, chemistry, and optical considerations, the visual 

effect of a plume against the background sky may be characterized.

EMISSION

SOURCEISI

ATMOIP~eftIC opnCAl

PROCUS'S - EH.CTS

, J~

vi

'" ,. Ii: OJ 0;;: ... 2 g 1:;2 ... ::J <!;; '"

z ;( 0 0(

~~ < 0: 0: ::>

&: 0 :tlE '"

z .. ... a: u" :;j ..

W..l ... !

;; "'- 0:

;:!:

ENVlftONM.NTAL

CHAftACTii ft ISTICS

HUMAN VI SUAL

PERCEPTION

VISIBILITY

IIlDlJNG HEIGHT

SO.

NO.

PARTICULATE

SOURCE

PLUME 8LIGHT

LOCAL AI II 8ASIN TO REG IONA L SCAlE

Figure 5-2. "\isibility impllirrnenl rep"".
Several Gaussian based mathematical models have been developed that predict the optical effects of a coherent

plume (Latimer et aI., 1978; ERT, 1978; Williams et al., 1979). These visibility models are oriented toward

emissions from individual point sources, such as smelters and coal.fired power plant8, and compute the optical

effects of primary fme particles, sulfate from sulfur dioxide emissions and nitrogen dioxide from nitrogen oxide

emissions.

"

,

'\.

"

\

\

\

\

\

\

\

........ EMPIRICAL " APPROACHES,

DIAGNOSTIC

CLIMATIC

"'

GAUSSIAN

DISPERSION

MODELS

......

" ...... GRID "-

............. MODELS

" LIMITED '\.

'AIR '\

"QUALITY \

'DATA

\ \

\ \

\ \

\ \

- 10,000

lyear)

u

i=

<{

!!

.J

u 1000

u

c .. 0 .. III

"0

.r. UJ 100

w' .J lweekl ::!i <l:

-u

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Cl

0

.oJ

0 10 a: (day) 0

w

Iw

::!i

10 100 1000 10,000

LOCAL AIR BASIN REGIONAL GLOBAL

DISTANCE, km.

F~ 5·3. Scales of tiDle and distance. Approximate dimensions for applieable models.

Figure 5-4 illustrates the major components of visibility models, in this case the model developed for EPA. The

input requirement8 for these models include standard stack emission and meteorological data, plus additional

data for computation of the optical effects of the particles and nitrogen dioxide gas. The models use Gaussian

diffusion parameters for dispersion and empirical estimates or chemical reaction simulations to compute the

transformation ofsulfur oxides and nitrogen oxides to pollutants that affect visibility. The direction and amount

oflight scattered and absorbed by the particles and gases are calculated through approximations ofthe radill.tive

transfer equation (Section 2.3). Tbe output ofthe models ia a set ofwavelength-dependent light fluxes, which are

then used for computation ofmore easily understood parameters representing the reduction of visual range and

discoloration ofthe sky through the plume, contrast ofthe phune (against the sky), and overall perception ofthe

plume.

5·3
POLLUTANT CONCENTRATIONS xt". y, Z, tI

SCATTERING AND ABSORPTION

bleo'- bobsl\ ". V. z.,)

I

TIME·OEPENDENT

PARTICLE SIZE DISTRIBUTION

,-,. ...,..____ ...

r PRECURSORS SECONDARY POLLUTANTS

I ISO". NO". SOi. N03) PRIMARY PARTICULATEI

I I

1 r

I I

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I 

I I I 

I I SOLAR FLUX SCA

POLLUTION r I I A

CONTROL UPPER AIR 

I EQUIPMENT Fsli\1 

I WiNDS AND STABILITIES r ATMOSPHERIC CHEMISTRY I 

AND SITING I I 1 1 I 1 I 2NO + Oz - 2N02 I 

I r I LIGHT ABSORPTIONU 

- N02 +02 ATMOSPHERIC OPT

I I I babslM 

EMISSIONS

I r+ No'! + hV - NO + 0 I .!fiLN. pl}.ElI b (i\lF I

ATMOSPHERIC 

dr rr scat s 

PRIMARY f-.1.. TRANSPQRT, r PARTICLE GROWTH l LIGHT 

PARTICULATES DIFFUSION, lLIGHT SCATTERE

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502 - sOi I - [b""at1i\1 + bob,1M

NO"

r HYGROSCOPIC NO" - N03" GROWTH (LIGHT REMOVED 

SCATTERING LINE OF SIGHTI 

DISTRIBUTION

SURFACE

r

OEPOSITION 

VELOCITIES 

IlACKGROUND

[OH) • [H02 ), INTENSITY GEO

LIQUID WATER HIGH IE.G., BLUE OBS

[03J. [NH3l, (CLOUDS. WET RH SKY, WHITE AND 

OTHERS? PLUMES, FOG) CLOUD,

MOUNTAIN)

Hgllre 5-4. flow of single'l!Otmle Gawllian Villibility Model (Latimer, et aI., 1978).
5.3.1 Display Formats

Two general kinds of fonnats have been developed for displaying the output of visibility models. The most

commonly used fonnat is a graphical plot of an optical parameter (such as discoloration) versus downwind

distance for a set of given atmospheric and emission conditions. This format is useful for estimatiug distances

. where maximum visual impacts could occur and for quantifying parameters related to visibility. Figure 5-5 shows '

the graphical fonnat used in diBplaying the EPA model.

2 4 6 10 20 40 60 100 200

'.

-

- l'RCR'ASED HAZINESS OR REOU". VISUAl RAR"

, " I I I ,

t PLUMES 8LUER THAN BACKGROUND SKY

(OR LESS YELLOW-BROWN)

! , ._..

. PLUMeS MORE RED (OR YELLOW-BROWN)

THANBACKGROUNOSKY

8

7

1

t PLUMES BRIGHTER THAN BACKGRDUND SKY

0

PLUMES DARKER THAN BACKGROUND SKY

1 i

i

i

!

i

3

0

,

1

:

, ,

INCREASING PLUME (OR HAZE) PERCEPTIBILITY

0

0,0

260.0

=

fi 58.0

=

~40.0

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10.0 w

D. 0.0

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l-

...

... ' Cl 5.

·0.

15.

t;

·0.

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:3 -D. w

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O.

gl.1

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=... "'a; :3 ..,0.9 ",:::>

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LOCATION OF 08SERVER DOWNWIND OF POWER PLANT (km)

Figure 5-5. Example graphical fonnat of single source-visibility model output (Latimer, et al., 1978).

A more dramatic fonnat for displaying the output of visibility models has been developed by Los Alamos

Scientific Labot'atory for the Department of Energy (Wdliams et a1., 1979). This technique creates a compntergenet'ated simulation of a plume on a color television screen. To accomplish this simulation, a photograph of a

"clean" backgroWld vista (Figure 5-6a) is digitized according" to color and brightness of different elements in the

picture (Figure 5-61). Then, the effects of the plume. as predicted by the visibility model, are introduced into the

clean picture by a digital computer, and the result is displayed on a color TV screen. Figures 5-6c and d show the

model prediction for fine particle additions of 5 p.,g/m3 and 26 p.,Wm3, respectively, throughout the backgroWld

scene. The resulting haze and reductions in visual range and contrast are apparent.

5-5
fl. b. "'CJellll ut f+

d "f 11 Jl Lili. til of

flllllt:e 2

:- ·6. Gt>1ll1. d' , .-Ill. and imulotc·d lUl2t' pbut,,-'-rapk I aI.• ]979 .

The computer simulated plume or haze picture is more readily useful for illustrating impacts than are

graphical outputs. Only one location can he depicted at a time, however, and the extensive and sophisticated

hardware requirements are presently too costly to allow for routine slllUlation ofmany views and conditions.

Additional uncertainty is introduced in this technique because the elements of the original picture must he

digitized, modified according to the model, and converted back into a color television representation.

Moreover, no visibility model can currently predict human color perception. As such, photographic representations may be misleading. Nevertheless, this promising display technique should he developed for more

routine use as visibility models are iinproved and our understanding of color perception increases.

5-6
5.3.2 Applications of Single Source Visibility Models 

The single-source Gaussian plume visibility models developed for EPA and DOE 

(LASL) have been applied to a variety of conditions for different sizes and emission 

levels of hypothetical coal-fired power plants. The complete description of the EPA 

model, the assumptions under which it is run, and output scenarios are described in detail 

elsewhere (Latimer et al., 1978). The LASL model scenarios are also detailed elsewhere 

(Williams et al., 1979). 

The sample applications assume flat terrain, constant dispersion conditions and fixed 

transformation ratios. At sulfur oxide emission levels comparable to the ceiling for the 

recently promulgated new source performance standard (NSPS) for power plants, the 

model predicts relatively little sulfate haze at distances up to 100 km from a single 2000-

MW facility. Limited mixing conditions, longer downwind transport, and multiple 

sources-even widely separated-could intensify the impact significantly, however, since 

fine- particulate sulfates have long-residence times in the atmosphere and may 

accumulate under such conditions. The Gaussian models do not adequately address 

cumulative pollution intensification from separated emission sources. 

 

The potential for discoloration from nitrogen dioxide (NO2) may be significant at 

distances up to 80 km even for a plant meeting the NSPS for nitrogen oxides (NOχ). The 

models also show that primary particles, controlled at NSPS levels, contribute little to 

visibility impairment. Therefore, discoloration from NO2 might be the most troublesome

cause of local plume blight for new power plants. 

Figure 5-7 is an example of the EPA model's output for a 2250-MW coal-fired power 

plant under neutral (D) atmospheric statibility. In this example, SO2 emissions are the 

maximum ceiling allowed by the current NSPS (1.2 Ib/106Btu). Four optical parameters 

are computed and plotted as a function of downwind distance from the source. Visual 

range reduction (top graph) results mostly from the sulfate formed from SO2. The second 

graph shows discoloration effects plotted as blue red ratio. Under the indicated 

conditions, the plume would appear the most discolored-a reddish brown-about 25 km 

downwind. This predicted effect is almost entirely due to NO2 formed from NOχ

emissions. Plume contrast (third graph) is an indication of the brightness of the plume 

relative to the background sky. The negative number indicates that, for these viewing and 

sun angles, the plume would appear darker than the sky. The same plume could appear 

brighter than the background under different illumination conditions. Delta E (bottom 

graph) is a parameter synthesized from color and brightness contrasts between sky and 

plume and represents a relative plume "perceptibility" term (see Section 2.2). According 

to the model, the plume would be most perceptible about 25 km downwind, owing mostly 

to NO2 discoloration. Similar visual effects are indicated from the Gaussian model 

developed by LASL for DOE (Williams et al., 1979). 

These models suggest two visibility impacts: 

 
1. NOχ emissions resulting in NO2 formation may cause perceptible discoloration of 

a plume up to 80 km downwind, particularly during atmospheric conditions of 

poor dispersion. The perceptibility of the predicted impacts, however, must be 

empirically verified. 

2. Sulfate formed from SO2 emitted from poorly controlled large sources could 

cause perceptible haze for very long downwind distances. The effect from an 

individual well-controlled plant is small, but the cumulative effect of many 

sources may be large. These predictions agree qualitatively with aircraft plume 

studies summarized in Section 4.5. 

It must be emphasized that no visibility model has yet been fully tested and validated. 
(1) NORMAL NOx EMISSIONS; 0.5 PERCENT/HR SULFATE FO~MATION

(2) NORMAL NO EMISSIONS; NO SULFATE FORMATION

(3) NO NOx EMI~1nDNS; 0.5 PERCENT/HR SULFATE FORMATION

(4) NO NOxEMiSSIONS; NO SULFATE FORMATION'" .

,

.,

1

!

..

z 60.0r------------~----------------__t

Q

t 50.0

ffi=40.0

Ill:

30.0

>

=: 20.0 w

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D. O.O!======~====~~~~~E

, :

200

p:± j

1 AND :Z(NORMAL NOx)

'.

.

i

i

!

i

1 AND 2 (NORMAL NOxl

!

i

j

3AND 4 (NO N0X)K

:

.

10 20 4D 80 100

DOWNWIND DISTANCE (KM)

4 6

CI 1.1

j::::

c

g;: ..... ~_......,_....'Ott"t't'tt'.,.,tt1t'

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a::

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::::J

....

a:I

0.7

0.1 ...

Ill: 0.0 _..........._---_. ...

z

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Figure 5·7. 'Visual effect. predicted for a 2250 MW hypothetical power plant With !liability D. View is

perpendicular to the plume with !lWl overhead (90" light scatter).

5-8
5.3.3 Sensitivity Analysis for Single-Source Models 

Sensitivity analyses provide insights into the potential uncertainties that may limit 

model application; that is, what input information needs to be known to what precision. 

Sensitivity analyses also can aid in identifying which variables may be the most 

important in controlling visibility impairment. 

For a 2000-MW or smaller power plant operating at or below the current NSPS, single 

source visibility models are more sensitive to background pollutants and meteorological 

conditions than to SOχ and particulate emission rates at distances up to 100 km from the 

source. The principle implication that could be drawn is that, for a well-controlled 

emission source, siting may be the key factor in protecting visibility in a class I area. 

Even if a validated single-source visibility model existed, there would likely remain 

enough inherent modeling uncertainty to preclude meaningful analysis of the incremental 

visibility improvement from particulate and SOχ controls beyond those required for new 

source performance standards. 

Visibility models are very sensitive to: 

1. Background visibility input to the model, which is used as the base line. The 

aerosol loading of the background atmosphere is especially important because it 

determines the coloration of the background sky. In Figure 5-8, atmospheric 

discoloration from pollution in clean Western air is predicted to m significant 

while, under Eastern conditions, the effect should be masked. 

2. Atmospheric conditions. Atmospheric stability can inhibit or promote dispersion 

of pollutants. Figure 5-9 and 5-10 a,b show the effect of atmospheric stability on 

visual effects. Dispersion decreases as stability goes from "C" to "F". Under 

stable conditions (such as E or F), mixing is limited and plume concentrations 

are greater with corresponding increased visual effects. As the mixing height 

increases, pollutants become more dilute and visibility effects are smaller. 

 

3. Chemical conversion of SO2 to sulfate and NOχ to NO2 and particulate nitrate. 

Figures 5-11 and 5-12 show the effects on visual range on varying the rate of 

sulfate formation from 0 to 5 percent per hour, and the effect on discoloration 

resulting from NO2 formation from different levels of ozone. The effect of 

increased NOχ emissions is shown in Figure 5-10c. The impacts of particulate 

nitrate formation (if any) cannot yet be estimated because of a lack of empirical 

data. The initial and ultimate particle size of secondary (and primary) particles is 

also important. Particles may be below, in, or above the optimal size range for 

light scattering during the course of transport and transformation. 

4. Removal processes for SO2 sulfate, and NO2. Deposition mechanisms must be 

incorporated into visibility models to account for removal of pollutants from the 

atmosphere. Deposition on ground surfaces is increased by good mixing, lower 

stack heights, and certain surface characteristics of the terrain. The conversion-
removal processes determine the amount of secondary pollutants available for 

transport and dispersion. 

 

5. Viewing angles relative to the sun and plume. These angles are important in 

determining the optical effect of the plume. Different viewing geometries result 

in different optical effects, e.g. Figure 5-10d. 

5.3.4 Uncertainties and Limitations of Single Source Models 

There are substantial uncertainties common to all visibility models that, unfortunately, 

affect the most sensitive input parameters described above. While different models use 

different algorithms in their dispersion and optical calculations, they are all sensitive to 

the same factors and share similar uncertainties. Limitations of visibility modeling can be 

categorized as follows. 

 

1. Uncertainties inherent in dispersion modeling. Since the mathematical visibility 

model relies on some type of dispersion model, many of the uncertainties of air 

quality modeling will be inherent in visibility modeling. These uncertainties in 

modeling over flat terrain (such as assumed by EPA's and LASL's visibility 

models) are compounded greatly in complex terrain. Figure 5-13 is a 

physiographic diagram, which illustrates the mountainous terrain in the West. 

This terrain can channel pollution and create "corridors of pollution" which are 

very difficult to model. Visibility modeling is, however, primarily concerned with 

visual effects of a pollutant integrated through an entire plume. Questions of 

ground level concentrations at a point and horizontal dispersion are not as 

important as is the case for conventional air pollution modeling. 

2. Optical and chemical characteristics of the pollutant. Research is underway to 

develop more information about the physical properties of pollutants which 

impair visibility and their formation mechanisms. Reasonable assumptions, 

however, may be made on the basis of empirical data. 

3. Base-line visibility. There are very limited data available on base-line visibility. 

Airport visual range observations are of some use in determining historical trends 

but are often inadequate for modeling purposes. Because the determination of 

visual impact rests on base-line visibility, this is an important limitation. 

4. Human visual perception. As discussed in Section 2.2, perception of color and 

contrast is based on psychophysical mechanisms, which are not completely 

understood. There are little data available to define threshold values of color 

perceptibility under actual atmospheric conditions.
l'.

(1) EASTERN U.S. (BACKGROUND VISIBILITY =15 KM)

(Z) WESTERNU.S. (BACKGROUND VISIBILITY';" 130 KM)

z 60.0r-----~-------:------------:-------_.,

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DOWNWIND DISTANCE (KM)

HYPOTHETICAL 2250·Mwl COAl·FIRED POWER PLANT;

TYPIC.AL VISIBILITY WITH PAsaUILL STABILITY D

Figure 5-8. Comparison of prediclted plume vUibility in the eutem and westen! United States. Higher

bac~undpartkulate loadings mask N02 related di8coloration.

5·10
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Ll.l 10.0-

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HVPOTHETICAl2250·Mwe COAL-FIRED POWER PLANT WITH LIGHT

SCATTERING ANGLE OF 45°

Figure 5·9. Comparison of predicted visibility impairment for stabilities C, D, and E (Illightly UD.l!table,

neutral, slightly stable). A single stability would rarely oceur over the entire transport time and distance.

5-Il
11.

rru (9 ')

5.12
SULFATE FORMATION RATE

(115.0 PERCENT/HOUR· TYPICAL URBAN

(2) 0.5 PERCENTfHOUR· TYPICAL RURAL

(3) 0.0 PERCENT/HOUR· NEVER·NEVER LAND

I- : .

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HYPOTHETICAL 225D-Mwe COAL·FIRED POWER PLANT; BEST

WESTERN AMBIENT CONDITIONS WITH PASOI,JILL STABILITY 0

NOx EMISSIONS AT NSPS.

Figure 5·11. Comparieon of effects of dift'erent sulfate formation rates. A marked increue in predicted

haze OCCU1'8 at rapid sulfate {orination rates (5% per hour). Based on limited phone studies, overall

Western condilioD8 average about 0.5% per hour and rimge from 0 to 2% per hour (Wilson, 1979).

5-13
OZONE CONCENTRATION

(1) 0.12 PPM

(1) 0.04 PPM

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DOWNWIND DiStANCE (KMI

HYPOTHHICAl2250·Mwe COAl·FIRED POWER PLANT; TYPICAL

WESTERN AMBIENT CONDlnONS WITH PAsaUlU STABILITY D

NOx•SOx AT MAXtMUM NSPS lEVElS.

Figure 5-12. Compari80n of effect of avaDable ambient ozone on predicted visibility impairment from

N02• Higher background ozone re8uIt8 in more rapid NO2 conversion a,nd greater discoloration from NO2'

In the Weet levels of 0 to 0.06 ppm ozone are typical.

5-14
5.4 REGIONAL MODELING 

As a plume travels downwind and becomes uniformly vertically mixed (as illustrated 

in Figure 5-2), it may combine with pollution from other sources, both natural and 

anthropogenic. The resulting haze cannot readily be linked to a specific source, or 

perhaps not even to an area. The fate of this haze is now a function of meteorological 

processes that occur concurrently on larger scales of time and distance. Visibility 

modeling can be no more accurate than regional-scale transport models. Until the 

meteorological processes are better under- stood, regional visibility modeling, like other 

regional dispersion modeling, will be subject to significant uncertainties. 

In Figure 5-3, the dotted lines separate the time and distance scales into different 

regimes for modeling applicability. Local short-term dispersion is handled through 

Gaussian modeling. As the time and distance increase, Gaussian modeling becomes less 

and less reliable and numerical grid schemes must be used. Most of the unknowns of 

Gaussian modeling remain, however, as well as a number of additional uncertainties, 

which arise because most of the simplifications, assumptions, and boundary conditions 

used in Gaussian modeling are no longer valid. Data are limited and computer numerical 

computations must be iterated many times over very large databases. 

There is a certain balance between time steps and distance points, which is required in 

order to maintain computational stability in a numerical model. As time and distance 

dimensions increase, a point is eventually reached where numerical modeling is no longer 

practical. Diagnostic and other approaches based on empirical and statistical relationships 

(see Chapter 4) may then be used to suggest large-scale effects. 

5.4.1 Applications of Regional Models 

Various numerical regional models have been developed which attempt to predict the 

fate of pollutants over a wide area (Nuber et al., 1977; Lui and Durran, 1977). Generally 

speaking, on a regional scale, the transport of pollutants is controlled by air mass 

movement, which is dependent upon the wind field. Thus, most regional air quality 

models rely on some type of scheme to compute the changing wind field, which varies 

with time and in both horizontal and vertical dimensions and which transports the 

pollutant of concern. 

To date, the application of these models to visibility consists mostly of computing 

isopleths of sulfate from SO2 sources via chemical transformation, and then calculating 

increases in general extinction coefficient resulting from light scattering by fineparticulate sulfate. Obviously, many simplifying assumptions must be made, including 

assumptions regarding meteorology, transformations, and removal processes. Variations 

in terrain are reflected only in the changing wind field as it moves around and over 

mountains. 
t 5·u. 1 ) 1"""10100.. .\l.I.....' ...IS,....... Th.........·.. n I..........r,.... " ...,.....

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At this time, no validated regional air quality models are available for assessing the 

visibility impacts of many sources on a large scale. Latimer et al. (1978), however, have 

used regional models to estimate the potential spatial impact of multiple sources on 

regional visibility during short-term episodes. Qualitatively, the results of such 

preliminary predictions agree with empirical studies. 

5.4.2 Sensitivity and Uncertainties of Regional Models 

Regional visibility models are extremely sensitive to the rate of conversion of SO2 to 

sulfate and to the wind field, both of which are uncertain and must be assumed or 

interpolated from limited data. 

Among the additional limitations of regional models are: 

1. Lack of adequate inventory of emission sources and base-line visibility. The 

visual impact of any source at any location is a function of existing visibility. Any 

model must be able to handle multiple sources. Urban areas in particular are 

difficult to characterize. 

2. Incomplete knowledge of large-scale meteorological processes and uncertainties 

about boundary conditions. Chemical transformations apparently vary greatly and 

are largely unknown on regional scales. 

3. The existing visibility database is insufficient for input to a model and too 

imprecise for validation of output. 

4. Statistical and empirical methods such as those discussed in the previous chapter 

do not necessarily specify source and effect relationships and do not permit 

strategy analysis because of the independent variables. 

5.5 SUMMARY AND RECOMMENDATIONS 

 

Development of visibility models is just beginning. No model has been validated at 

this time, although the optical principles used are sound and theoretical concepts have 

been established. The primary modeling questions concern optical and chemical 

properties of the integrated cross section of the plume and not individual concentrations 

at specific points. The sensitivities of the models can be used to advantage in identifying 

critical variables in consideration of visibility impairment, given visibility model input 

parameters. 

Despite the inherent uncertainties, visibility models can and should, within certain 

limits, be used to evaluate source impacts. Single-source models can estimate the 

expected visual effects of primary particle emissions at distances of up to 50 to 100 km 

from the source. These models can also be used to provide rough estimates of the impacts 

of sulfur and nitrogen oxide emissions at similar distances for relatively isolated sources 

located in clean environments. Thus, the degree of visibility improvement resulting from 

controls on major, obvious sources of plume blight can be predicted, and potential 
visibility impairment by proposed major facilities can be addressed. In the case of new 

sources proposed to be located within 100 to 150 km of class I areas, an analysis of 

prevailing meteorological conditions, background visibility, and application of available 

single-source plume models can provide an improved basis for siting decisions. 

Preliminary model applications suggest that, with careful siting, power plants meeting the 

recently promulgated NSPS can be constructed without serious impairment in class I 

areas. 

Models for evaluating the effectiveness of controls on existing or proposed new 

sources on a regional scale require further refinement and validation before they can be 

used in regulatory applications. Empirical data analyses, coupled with mathematical 

modeling exercises, are a useful tool in identifying at least the scales of time and distance 

upon which visibility impairment may occur. On the basis of empirical evidence and 

modeling exercises, it is reasonable to expect that changes in the regional emissions of 

fine particles and sulfur oxides will produce changes in regional visibility levels, 

although the extent, duration, and location of these changes as a function of emissions 

can not be adequately predicted at this time. 
REFERENCES FOR CHAPTER 5 

Environmental Research and Technology, Inc. (1979) Draft. Phase I Report: Analysis of 

Clear Air Act Provisions to Protect Visibility. ERT Contract EE-77-C-01-6036. Prepared 

for U.S. Department of Energy, Washington, D. C. 

Latimer, D. A., R. W. Bergstrom, S. R. Hayes, M. K. Lui, J. H. Seinfeld, G. Z. Whitten, 

M. A. Wojcik, and M. J. Hillyer (1978) The Development of Mathematical Models for 

the Prediction of Anthropogenic Visibility Impairment. EPA/450/4-78-110a,b,c. U.S. 

Environmental Protection Agency, Research Triangle Park, N.C. 

Lui and Durran (1977), The Development of a Regional Air Pollution Model and its 

Application to the Northern Great Plains, EPA 9081-77-001. U.S. Environmental 

Protection Agency, Research Triangle Park, N.C. 

Nuber, J. A., A. Bassm, M. T. Mills, C. S. Norris (1977), A Review of Regional Scale 

Air Quality Models for Long Distance Dispersion Modeling in the Four Corners Area. 

EPA 600/7-78066. U.S. Environmental Protection Agency, Research Triangle Park, N.C. 

Williams, M. D., E. Treiman, M. Wecksung (1979) Utilization of a Simulated 

Photograph Technique as a Tool for the Study of Visibility Impairment. LA-UR-79-1741, 

Los Alamos Scientific Laboratory, Los Alamos, N. Mex. 

Wilson, W. (1979) Personal Communication. Environmental Protection Agency, 

Environmental Sciences Research Laboratory, Research Triangle Park, N. C. March. 
1

PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 6 
2

6 SIGNIFICANT SOURCES OF VISIBILITY IMPAIRMENT 

6.1 NATURAL SOURCES 

Vision in the natural, unpolluted atmosphere is restricted by blue-sky scattering (Air 

molecule light scattering is often termed Rayleigh scattering), by curvature of the earth’s 

surface, and by suspended liquid or solid natural aerosols. Important sources of natural 

aerosols include water (fog, rain, snow), wind-blown dust, forest fires, volcanoes, sea 

spray, vegetative emissions, and decomposition processes. Although these sources are 

not generally amenable to control, they contribute to the natural “baseline” visibility in 

class I areas. As such, their impacts must be considered in evaluating anthropogenic 

visibility impairment. 

6.1.1 Visibility Effects of Particle-Free Air 

The particle-free atmosphere scatters light and limits visual range to about 200 miles 

at sea level. Although no class I area enjoys such perfectly clean air all year, Charlson et 

al. (1978) and Malm (1979) have measured light scattering coefficients within a few 

percent of the particle-free limit on a number of occasions in Southwestern class I areas. 

Since light scattering by air molecules is proportional to the air density, it decreases with 

altitude as shown in Table 6-1. 

Class I Area Altitude 

(m) 

Rayleigh 

Scattera (km-1) 

Potential 

Visual Range 

(km) 

Contrastb

Acadia Sea Level 0.012 337 -0.49 

Big Bend (1200m) 1000 0.011 371 -0.51 

Grand Canyon (2100m) 2000 0.010 410 -0.54 

Bryce Canyon (2500m) 3000 0.009 453 -0.56 

Mt. McKinley (6000m) 4000 0.008 503 -0.59 

Table 6-1. Rayleigh Scattering by clean air. aRayleigh scattering coefficient for 0.55μm light 

(roughly green). Scattering for 0.400μm (blue)) at sea level is 0.042 km-1. Scatttering at longer wave 

lengths is much smaller. b

Apparent contrast between the sky and a dark tree covered mountain 50 

km away. Initial contrast is –0.87. 

Dark objects, such as distant mountains, when viewed in daytime through a particlefree atmosphere, appear bluish because blue light is scattered preferentially into the line 

of sight. Bright snow-covered mountain tops or clouds on the horizon can appear yellow 

to pink because the atmosphere scatters more of the blue light from bright “targets” out of 

the line of sight, leaving the longer wavelength colors. 

The actual visual range in the particle-free atmosphere is also limited by the earth’s 

curvature. Few class I areas have any vistas in excess of 200 km (120 miles). Thus, 

Rayleigh scattering is seldom the limiting factor in the detection of the most distant 

objects, i.e. the visual range. Rayleigh scattering is, however, important in reduction of 

visual texture and in bluish coloration of distant dark visual targets. Moreover, air 

scattering is solely responsible for the blue color of the non-horizon sky. 
3

6.1.2 Visual Impairment by Condensed Water 

Atmospheric water vapor is transparent for visible radiation. Deposition of water 

vapor onto condensation droplets (producing fog, clouds, or snow) or absorption of the 

vapor by suspended particles can drastically change the optical properties of water. 

White convective cumulus clouds may appear “from out of the blue” simply by a change 

of phase from transparent gas to light-scattering droplets. Such natural visibilityimpairing water condensates include clouds, rain, hail, snow, and fog. 

Relative humidity is a measure of the amount of water vapor in the atmosphere and as 

such, is an index of the potential for condensation of water onto small particles from 

natural or manmade sources. At relative humidities greater than 70 percent, the 

condensation of water vapor onto hygroscopic particles (e.g., sulfates) significantly 

increases light scattering and visibility reduction (Charlson, et al., 1978). Figure 6-1 

illustrates average U.S. humidity levels. Humidities higher than 70 percent are common 

in the East and in the Pacific Northwest. 

Figure 6-1. Annual mean relative humidity (5) (NOAA, 1978). 

Fog is a naturally occurring phenomenon, which can reduce the visual range to nearly 

zero. It is characterized by high liquid water content, typically over 1000 μg/m3

, 

dispersed in droplets with a mean diameter of several micrometers or more. In “natural” 

fogs all colors are scattered and absorbed about equally, so the atmosphere appears white 

(Husar, et al., 1979). 

," ·'I" ••f1_ ......
4

The historical frequency of occurrences of fogs in the continental United States 

reveals considerable geographic variability (Figure 6-2). Coastal areas experience the 

highest frequency. Most inland portions of the United States west of the Appalachians 

can expect fewer than 20 days of fog per year, with less than five days of fog annually in 

the arid west. 

Figure 6-2. Average annual number of days with occurrence of dense fog (Conway, 1963). Coastal 

and mountainous regions are most susceptible to fog. 

With the exception of coastal and mountainous regions, fogs are rare during the 

summer months. Fogs tend to be localized events of, at most, a few hours duration, 

commonly during the early morning hours. On an hourly basis, fogs exist less than one 

percent of the time (Conway, 1963). Thus, the overall contribution of fog to the 

degradation of visual air quality is small, and it is an insignificant cause of reduced 

visibility during the daylight hours. 

Thunderstorms and other rainfall can also reduce visibility. East of Nevada, most of 

the U.S. experiences from 30-50 days each year with thunderstorm activity. Such storms 

are most common on summer afternoons. Since thunderstorms are usually intense but 

brief, they also contribute to visibility reduction less than one percent of the time on an 

annual basis. 

Snow is another major natural cause of degradation of visual air quality. It is an 

important factor in many regions of the North and in some mountainous areas, where 

blowing snow occurs from 1 to 12 percent of winter hours (Conway, 1963). During the 

winter months, snowstorms may account for most of the hours of reduced visibility, and 

certainly may dominate the episodes of extremely low visibility in winter months. 

"'~'\10 ~. "

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5

The natural contribution of fog, thunderstorms, snow, and other forms of precipitation 

can thus cause severe degradation of visual air quality. With few exceptions, however, 

these intense but infrequent events do not dominate the average visual range within the 

continental U.S.; typically only a small percentage of the hours involve storms or fog. 

Such effects are currently beyond human control and are seldom viewed as an aesthetic 

degradation of visual air quality. It is also worth noting that the removal of manmade 

aerosols by precipitation often leads to a relatively clearer atmosphere. 

6.1.3 Visual Impairment by Wind-blown Dust 

In the arid West, where many class I areas are located; the contribution of wind-blown 

dust to degradation of visual air quality is an important problem. Because human 

activities that disturb natural soil surfaces add significantly to wind-blown dust, dust 

storms are only partially natural (see Section 6.2.4). Quantification of these effects is 

important for visibility protection programs. 

Cohesiveness of the particles to the underlying material, the force of the surface wind, 

and the topography of the surface layer determine the suspension of particles from the 

surface. The ideal situation leading to suspension of surface material is a dry, crumpling, 

or disturbed crust in flat terrain without vegetation. Agitation of such surfaces by strong 

winds and turbulence can transform a pristine arid atmosphere into a dust storm with 

severely reduced visibility. 

Suspended crustal material in a dust storm usually consists of coarse solid particles with 

volume mean diameters of tens of micrometers (μm) or more. Figure 6-3 displays 

measured particle volume size distributions in a major Texas dust storm. Most of the 

particulate mass is of diameter much greater than 2 μm. As discussed in Chapter 2, the 

light scattering efficiency per unit mass of coarse particles is very low relative to that for 

fine particles; however, the mass of coarse particles in a severe dust storm is on the order 

of several thousand μg/m3

, so that total light extinction is pronounced. Pattterson et al. 

(1976) found that the optically important fugitive dust particles include those up to 40 μm 

in diameter. 

Figure 6-3. Aerosol volume size distributions of dust collectedin a major dust storm in NW Texas on 

18 April 1975 (Gillette et al., 1978). The optically important dust mode peaks at about 20 μm 

diameter. 

Orgill and Sehmel (1976) have analyzed the frequency of occurrence of dust storms in 

the continental United States in great detail, based on National Weather Service 

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observations of wind-blown dust and sand associated with visibility of seven miles or 

less. The peak hours for dust are noon to eight p.m., during the period of maximum 

thermal turbulence. Forested, coastal, and mountainous regions have few, if any, 

episodes. The Pacific coast has high (>0.1%) incidence of dust only in the San Joaquin 

Valley and the Los Angeles Basin. Western desert areas in Eastern Washington, Western 

Nevada, Utah, New Mexico, and Arizona are also prone to dust. The highest dust 

frequency is in the Southern Great Plains, where wind-blown dust is a serious problem up 

to 3% of the time (Figure 6-4). 

Figure 6-4. Annual percent frequency of occurrence of wind-blown dust when prevailing visibility 

was 7 miles or less, 1940-1970 (adapted from Orgill and Sehmel, 1976). Dust is a visibility problem in 

the Souther Great Plains and Western desert regions. 

The monthly dust frequencies for seven regions covering the contiguous United States 

show a consistent summer maximum (Figure 6-5). The spring and fall peaks are partially 

due to agricultural activity in most sections of the country. 

• >3%

II 2-3% 1 1-2% .5-1% II .1-.5%

'.00' L.L.J......l_......i-.L...L..-l_L..L....1......L......JL.....J

JAN' eeMl\1'I 1I1'1~ "'I>,'" JUN JL.L. AU!:!:E} Ol::t t-IO," DEC J6101

MONTH
7

Figure 6-5 (a) Seven defined dust regions; (b) Monthly regional average frequencies for seven regions 

of the U.S. (Orgill and Sehmel, 1976). Dust is most common in the South Central region, and least 

common in the industrialized Northeast. 

Visual Impairment by Forest Fires 

Since many class I areas are located in or near forested areas, wildfires can be a 

significant source of natural visibility impairment. Controlled burning of forested areas 

by human intervention is, however, increasingly replacing the natural process of 

uncontrolled wildfires. Such managed burning is discussed in Section 6.2.4. 

Forest fires impair visibility by producing massive visible smoke plumes and by 

causing general haze and reduced visibility over broad regions. Studies of the burning 

process (Sandberg and Martin, 1975) and measurements made in forest fire plumes 

(Radke et al., 1978) indicate that approximately 80 percent of the mass of smoke particles 

is less that 1 μm in diameter. Figure 6.6a shows light scattering coefficients measured in 

the plume of a managed burning of logging debris. The width of the visible plume is 

sketched in Figure 6.6b. Similar measurements made in other fires indicate that visual 

range in smoke plumes can be reduced to one mile or less (Eccleston et al., 1971; 

Packham and Vines, 1978). 

Figure 6-6. (a) Measurements of light scattering coefficient for forest burning plume. Thepeak in 

scattering occurred when the plume was intercepted. The broken segment was due to instrument 

adjustment. (b) Flight path of the aircraft. The broken line indicates theThke plume centerline. 

Thke first pass was made at an altitude of 520 m, and the second pass was made at an altitude of 580 

m (Radke et al., 1978). 

Wildfires burn approximately 1.8 million acres per year in the United States and emit 

an estimated 2 million tons per year of particulate matter. The regional breakdown of 

wildfires for 1975 is presented in Figure 6-7 (U.S. Forest Service, 1976). Although a 

large number of fires are reported, most of these are extremely small. Large fires 

;

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1226 ,

1227

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8

constituting less than one percent of the total number of occurrences consume about twothirds of the total acreage burned. 

Figure 6-7. National wildfire statistics, 1975 (USFS, 1976). 

6.1.5 Visual Impairment by Natural Sources of Secondary Aerosols 

Secondary aerosols are those formed by atmospheric reaction of gaseous “precursor” 

emissions. Important natural sources of secondary aerosols include biogenic emissions of 

hydrocarbons and various sulfur species and volcanic emissions of sulfur dioxide (SO2). 

These emissions can, under varying conditions, be transformed into fine particles and 

impair visibility. 

Plants release a number of volatile organic substances comprised primarily of 

ethylene, isoprene, and a variety of terpenes. Although all of these substances are 

photochemically reactive, the terpenes can be transformed from the vapor state into 

particulate matter. Smog chamber studies demonstrated that terpenes from pine needles 

react rapidly with ozone to produce a blue haze (Rasmussen and Went, 1965; Jeffries and 

White, 1967). The blue color indicates that the gaseous terpenes react to form particles 

with the diameter of less than 0.1 μm. Particles of this very fine size preferentially 

scatter blue light (Chapter 2). Similar bluish hazes have long been noted in heavily 

forested areas. The Blue Ridge Mountains and the Great Smokies may owe their names 

to terpene-derived particles. 

An initial attempt at a natural hydrocarbon emissions inventory for vegetation has 

been reported by Zimmerman (1978). Figure 6-8 indicates the major biotic regions of the 

United States. Table 6-2 lists regional vegetative emission factors derived from direct 

measurements of emissions from trees and forest litter and estimates of the distribution of 

species in the major regions. It should be noted that oak emissions consist primarily of 

isoprene, which does not form particles, while conifer emissions are principally terpenes, 

which do. Terpene emissions tend to be greatest at higher temperatures, at lower 

elevations, and in the spring of the year. Due to uncertainties in sampling procedures, 

biomass estimates, and insufficient data for various times of year, latitude, temperature, 

-.'.-•• . ·v..",.·

• 0 PACI F'e GROUP

'" "f~

t"

V
9

and sun conditions, these vegetative emissions estimates should be considered only as 

rough approximations. 

Figure 6-8. Major biotic regions of the United States (Zimmerman, 1978). 

Because adequate measurements of ambient concentrations of terpene derived 

particulate matter in rural areas are not available, it is difficult to estimate the extent of 

their visual impacts. Based on the emissions estimates in Table 6-2, the temperate rain 

and conifer forest regions of the Pacific Northwest should have among the highest natural 

terpene emission densities. Since visual ranges reported in the region (25 to 35 miles) are 

three to four times higher than those of the Southeast, factor other than terpene emissions 

must dominate haze in Southeastern class I areas. This is supported by limited air 

sampling in the Smoky Mountains (Dzubay, 1978). Non-sulfated particles amount to 

about one-third of fine particulate mass in the Smokies (less than 8 μm/m3

). Only a 

portion of this non-sulfate fraction could have been derived form terpenes. Because 

terpene particles cause blue haze, their size is probably less than the optimal light 

scattering range (0.1 to 1 μm). This reduces their potential effect on contrast and visual 

range. Eventually, however, such particles may undergo further transformation and 

growth into the optimal scattering range. Additional information is needed on the 

impacts of terpenes in specific class I areas. 

.mGRASSLAND

SCLIEFlOPHYLLS-CRU8

~{:I(:C'OUOUSFOI"IEST lIIIIIIDI r.oNIF~ROU5 FOREST

II TeMPERA'T~ RAI"" FOREST

DESERT

TUNDRA, ALPIf*~ F"IELDS

50'
10

Emission factors, μg/m2

 – hra Biotic Region Vegetation type Leaf biomass, 

g/m2 Day Night Winter 

Grassland Conifers 5 44.5 44.5 17.5 

 Oaks 2.5 61.75 11.75 0 

 NC-NIb 3.75 16.13 16.13 0 

 NO-Ic 3.75 38.6 9.00 0 

 LLd 162 162 0 

Total 250 322.98 243.38 17.5 

Schlerophyll 

Scrub 

Conifers 15 133.5 133.5 52.5 

 Oaks 30 141 141 0 

 NC-NI 210 903 903 0 

 NO-I 45 463 24.72 0 

 LL 162 162 0 

Total 300 2402.50 1364.22 52.5 

Temperate 

Rain forest 

Conifers 990 8811 8811 3465 

 Oaks 55 1385 258.50 0 

 NC-NI 22 94.6 94.6 0 

 NO-I 22 226.6 226.6 0 

 LL 162 162 0 

Total 1100 10679.20 9552.70 3465 

Deciduous 

forest 

Conifers 135 1201.5 1201.5 473 

 Oaks 180 4446.0 4446.0 0 

 NC-NI 90 387 387 0 

 NO-I 45 463.5 108 0 

 LL 162 162 0 

Total 450 6660 2704.5 473 

Coniferous 

forest 

Conifers 559 4975.10 4975.10 1957 

 Oaks 39 963.30 183.30 0 

 NC-NI 26 111.80 111.80 0 

 NO-I 26 267.80 62.40 0 

 LL 162 162 0 

Total 650 6480.00 5494.60 1957 

Desert Conifers 25 222.5 222.5 88 

 Oaks 25 617.5 117.5 0 

 NC-NI 40 172.0 172.0 0 

 NO-I 10 103.0 24 0 

 LL 162 162 0 

Total 100 1277 698 88 

Tundra, alpine 

field 

Conifers 18 160.2 160.2 63 

 Oaks 0 0 0 0 

 NC-NI 9 38.7 38.7 0 

 NO-I 9 92.7 21.60 0 

 LL 162 162 0 

Total 180 453.6 384.3 63 

Table 6-2. Vegetative volatile organic emission activities (Zimmerman, 1978). aStandardized to 

30o

C; bNC-NI = non-conifer, non-isoprene emitters; cNO-I = non-oak isoprene emitters; dLL = leaf 

litter/soil, pasture. 
11

Natural sulfur sources include sea spray, volcanic activity, decay of animal and plant 

tissue, green algae, microbiological activity along shores of lakes, rivers, marshes, and 

oceans, and inland soil processes. Sea spray generally consists of large particles and 

effects on visibility are limited to the near shore area. Volcanic emissions are of 

significance on a global scale, but the small number of volcanoes located in or near class 

I areas are often considered part of the visual resource, such as in Hawaii Volcano Park. 

The natural source of sulfur nearest most class I areas is therefore biological (biogenic) 

processes. 

Various attempts at deriving a global sulfur budget suggest significant quantities of 

biogenic sulfur emissions. However, all available estimates are subject to considerable 

uncertainty and controversy (McClenny et al. 1979). Recent measurements of natural 

sulfur emissions from various soil types suggest that swamp and marsh regions produce 

the largest emissions. Measurements of emissions from inland soils in Indiana, Ohio and 

Arkansas suggest an emission rate of 0.002 to 0.02 grams of sulfur per square meter per 

year (Adams et al., 1979). Emissions from marsh areas indicate average rates of 0.02 

grams of sulfur per square meter per year (McClenny et al., 1979). One apparently 

unique marsh site emitted over 100 grams per square meter per year. 

Further work must be undertaken before more reliable natural sulfur emissions 

estimates are possible. However, assuming an inland soil emission rate of 0.02 grams of 

sulfur per square meter per year, natural sources in the entire Eastern United States 

(approximately 3 million km2

), emit an SO2 equivalent of 120,000 metric tons per year, 

or about as much as a single 800 megawatt power plant burning 2 percent sulfur coal. 

Emissions form marsh area alone might be equivalent to the inland soil contribution. 

These relatively small emissions estimates together with measurements made in remote 

locations suggest that biogenic contributions to secondary sulfate levels should be less 

than 1 μm/m3

 in most class I areas. 

6.1.6 Example of Natural Effects in the Southwest 

The association between visibility and some natural phenomena in the arid 

Southwestern United States is illustrated in Figure 6-9 (Latimer et al., 1978). In this 

"Venn" diagram the outer box represents the fraction of the time (about 20%) when 

visibility was below 80 km. Similarly, the area of the right-most circle represents 

frequency of occurrence of sky cover greater than 90 percent. 

Overlapping areas of two or more circles represent the fraction of the time when each 

phenomenon occurs simultaneously. Visibility below 80 km always occurs when fog is 

present, and reduced visibility usually accompanies precipitation. The coincident 

occurrence of reduced visibility wit sky cover greater than 90 percent; relative humidity 

grater than 90 percent and wind speed greater than 10 meters per second is also more 

frequent than would be expected by chance. With the exception of fog, however, none of 

the natural parameters is necessarily a cause of reduced visibility greater than 80 km. 

The diagonally shaded portion of the visibility less than 80-km circle represents the 

fraction of the time when reduced visibility cannot be attributed to the natural phenomena 

shown. This suggest that over half of the occasions of reduced visibility may be due to 

other causes, such as other natural sources and anthropogenic aerosols. 
12

Figure 6-9. Venn diagram of the association of some naturla phenomena with visibility in the 

Southwestern U.S. Over half of the hours of daylight visibility below 800 km remain unexplained by 

these natural phenomena (Latimer et al., 1978) 

6.2 ANTHROPOGENIC SOURCES AND CONTROL TECHNOLOGY 

This section discusses anthropogenic sources of air pollution, which may potentially 

impair visibility. An overview of national emission densities and major source categories 

is presented, followed by summary information on the characteristics, location, growth 

potential, and applicability of control to several important source categories that may 

impair visibility in class I areas. This information is intended to provide some idea of the 

spatial distribution of current and future emission sources in relation to class I areas, the 

general effectiveness of the available control technology and a rough estimate of the 

economic costs of installing such technology on certain source categories. No attempt is 

made to provide a definition of "best available retrofit control technology" for specific 

source categories or to provide and economic impact analysis. A regulatory impact 

analysis is, however, being prepared in support of the forthcoming EPA proposal of 

visibility regulations and guidance to the States. 

6.2.1 Overview

The principal air pollutants that directly impair visibility are fine particles (aerosols) 

and NO2. Sulfur oxides emissions contribute to visibility impairment because they are 

transformed into sulfates, which, in some areas, can dominate the fine particulate mass 

loading. Volatile organic compounds (VOC) can contribute to visibility impairment by 

increasing photochemical formation of sulfates, nitrates, and NO2 and by conversion into 

organic aerosols. Nitrogen oxides also participate in photochemical reactions. Therefore, 

the emissions of particulate matter sulfur oxides, nitrogen oxides, and volatile organics 

are of significance to visibility impairment. 

Table 6-3 summarizes national emission estimates for these pollutants by major source 

category for 1977 (EPA, 1978a). These rough estimates were based on published data on 

fuel use and industrial production and on other EPA data describing emission factors and 

It' ALL DAYLIGHT OBSERVATIONS

VISIBILITY> 80 km
13

the extent of air pollution controls employed. Figures 6-10 through 6-13 are shaded maps 

that display emission density estimates by county for these same pollutants. These maps 

are derived from data obtained from the National Emissions Data System and represent 

1975 data. As might be expected, emission densities are usually low in counties, which 

contain class I areas. In general, emission density increases with higher population 

density for each of the four pollutants, with highly urbanized areas having high emission 

densities. This relationship is strongest for nitrogen oxide and hydrocarbons, the 

principal pollutants generated by automobiles. 

Figure 6-10. Total suspended particulate emission density by county (EPA, 1978a). 

Figure 6-11. Sulfur oxide emission density by county (EPA, 1978a). 

."

I

_ ..."u-<,N" AN" t<"f'u.. ,~ "f'!;>.NCH

OFr.~i~j~1fi~a~~\~lit~iwt;:t!iJ:~~D~ AES=ARCHTllIAHClEFARK.N.C,27111

B.Ali'COUNVAT",t'JiCMNJ,TIOIlAL (MISSION

f)AU.. G-VE<TE.... •••...v ...,,,,

PR~I'AR"08Y

MONlTOIUNG AND RIEPOHfS IIRAHCH

MONITORING ANl)DATA AHAlV$IS DIVISION

OFF't~.(:tN~:~~~~~~v,.,r'tA~~'~g,.ttNO;l~g:r- I'IEs.EARCHTRIANGL(PAIU:;.N.c.~nll

8ASEOON DATA FI10M NATIONAll';MISSION

DATA SVl;TW. MAY 1!178.
14

Figure 6-12. Nitrogen oxide emission density by county (EPA, 1978a). 

Figure 6-13. Hydrocarbonemission density by county (EPA, 1978a). 
15

Source Category TSP SOX NOX VOC CO 

Transportation 1.1 0.8 9.2 11.5 85.7 

Highway vehicles 0.8 0.4 6.7 9.9 77.2 

Non-highway vehicles 0.3 0.4 2.5 1.6 8.5 

Stationary fuel combustion 4.8 22.4 13.0 1.5 1.2 

Electric utilities 3.4 17.6 7.1 0.1 0.3 

Industrial 1.2 3.2 5.0 1.3 0.6 

Residential, commmercial, and 

institutional 

0.2 1.6 0.9 0.1 0.3 

Industrial processes 5.4 4.2 0.7 10.1 8.3 

Chemicals 0.2 0.2 0.2 2.7 2.8 

Petroleum refining 0.1 0.8 0.4 1.1 2.4 

Metals 1.3 2.4 0 0.1 2.0 

Mineral products 2.7 0.6 0.1 0.1 0 

Oil and gas production and 

marketing 

0 0.1 0 3.1 0 

Industrial organic solvent use 0 0 0 2.7 0 

Other processes 1.1 0.1 0 0.3 1.1 

Solid waste 0.4 0 0.1 0.7 2.6 

Miscellaneous 0.7 0 0.1 4.5 4.9 

Forest wildfires and managed 

burning 

0.5 0 0.1 0.7 4.3 

Agricultural burning 0.1 0 0 0.1 0.5 

Coal refuse burning 0 0 0 0 0 

Structural fires 0.1 0 0 0 0.1 

Mescellaneous organic solvent use 0 0 0 3.7 0 

Total 12.4 27.4 23.1 28.3 102.7 

Table 6-3. Nationwide emission estimates, 1977 (EPA, 1978a) (106 metric tons/year). Note: A zero 

indicatres emissions of less than 50,000 metric tons per year. 

These maps are only imperfect indicators of potential impairment. For example, TSP 

emissions are not a uniformly good surrogate for primary fine particle emissions. 

Furthermore, in areas of apparently low emission density, single point sources located in 

close proximity to class I area may produce significant local plume impacts. Regions 

containing several counties of high TSP emission densities are, however, at least 

indicative of regional primary fine particulate impacts. High sulfur oxide emission 
16

densities indicate potential regional sulfate impacts. As noted in Chapter 4, strong 

geographical similarities exist between high sulfur oxide emission density and low 

regional median visibility levels. The nitrogen oxide map is a less useful visibility 

indicator. Discoloration of visibility in class I areas by nitrogen oxide emissions is 

probably only significant near (within 80 km of) large power plants in clean areas and for 

class I areas immediately adjacent to urban areas of the highest nitrogen oxides emission 

density. The significance of VOC (hydrocarbon) emission density for visibility 

impairment is not well understood. However, the VOC emission density map is a good 

surrogate for population centers and possible impacts of general urban development. 

6.2.2 Control Technology for Potentially Important Point Sources

This section discusses general kinds of control technologies and the effectiveness of 

each as applied to major point sources of particulate matter, sulfur oxides, and nitrogen 

oxides. Significant variations in the application, effectiveness, and cost of these 

technologies will occur among source categories and between sources of the same 

category. In particular, control technologies for point sources are generally more 

effective and less expensive when applied to new sources than when applied to existing 

sources. Detailed information on control technology can be obtained form a number of 

sources listed as references. A comprehensive control techniques document for nitrogen 

oxides has been published (EPA 1978b), and similar documents will be available for 

sulfur oxides and particulate matter in Spring, 1980. In addition, detailed information on 

available control technology for specific source categories has been published as support 

documents for the new source performance standard for utility boilers, kraft pulp mills, 

aluminum smelters, and other sources categories. (EPA, 1979a; EPA, 1976; EPA, 1974). 

6.2.2.1 Particulate Matter -- Although primary fine particulate emissions from point 

sources can contribute to region-wide haze conditions, the principle concern with these 

emissions over the next several years is likely to be intrusion of perceptible plumes or 

haze layers into important vistas. As noted in Chapter 4, such plumes have been 

observed in the Southwest to extend for over 50 km from large, inadequately controlled 

sources. Visible primary particle plumes from smaller industrial or well-controlled larger 

sources are normally limited to the near source environment, at distances of less than 20 

km from the facility. Historically, the public has complained about the presence of 

visible plumes even in urban settings; therefore, reduction in visible plumes has long 

been a concern of air pollution regulations. Traditionally, agencies have enforced such 

regulations by setting limits on plume opacity, or optical "thickness." Many state 

regulations call for restriction of opacity to no more than 20 percent. This level is 

generally achievable by most sources of particulate matter. Some localities have adopted 

regulations calling for no visible emissions. Such restrictions are more difficult to meet 

on a continuous basis, but, using available control technologies, many source types can 

meet a no visible emission standards most of the time. 

The effectiveness of any control device in reducing near source particulate plume 

blight is limited by the control efficiency for fine particles. Although fine particulate 

removal efficiency is known form many control technologies, the lack of adequate 

emissions estimates and particle size distributions will limit the accuracy of visibility 

models in assessing control alternatives for some source categories. Previous experience 
17

and experimentation in reducing opacity can, however, enable sources or control agencies 

to assess the effectiveness of possible retrofit controls on opacity. Although 

correspondence between opacity and plume perceptibility depends on a number of factor, 

opacity is, at least, a useful index for control assessments. 

Table 6-4 provides a general estimate of applicability of particulate control 

technologies to a number of major point sources. Estimates of the range of costs are also 

listed. Figure 6-14 and Table 6-5 illustrates the effectiveness of these and other 

technologies as a function of particle size. Many of these controls, currently in wide use, 

are relatively inefficient at removing fine particles in the light scattering range. Both a 

modern electrostatic precipitator and fabric filter system can, however, efficiently remove 

such particles (Table 6-5). 

Figure 6-14. Comparison of Control Device fractional efficiency (Weast, 1974). 

0.01 99.99

O.ll!i

0.1 99.9 0.2 99.8 0.5

1 99

2 98

5 !IS

l: 10 !Ill

ZO 80 I

!. 30 70 >-' 40 eo 2 u 50 tl Z &fl ... 60 g 40 70 30 lII: II. l- ll. 80 III oJ 20 ;;:

.. 90 10 "-

95 5

98 IlIGH EFFICIENCV ESP. - 2

99 FABRIC FilTER NOT SHOWrt 1

0.5 99.8 0.2 98.9 0.1

(1.05

99.99 0.01

0.01 0.1 1.D 10

PARTICLE SIZE. ...
18

Source type Size Control Costs (106 dollars) a 

Capital O & M Annual 

Utility boilersb,c 250 MW Fabric filter 16.1 0.3 3.0 

 500 MW 28.3 0.6 5.0 

 1000 MW 51.0 1.2 9.7 

Copper smelters 73,000-160,000 

metric tons/year 

ESP 2.7-23.6 NR 0.5-4.6 

Industrial boilersb,e 

Coal 150 x 106 BTU/hr Fabric filter 0.9 0.03 0.171 

200 x 106 BTU/hr 1.19 0.03 0.210 

Oil 150 x 106 BTU/hr ESP 1.04 0.01 0.160 

Kraft pulp millf,g 1000 TPD 

 ADPh 

Power boilere 20 MW Fabric filter 1.19 0.03 0.20 

Recover furnacef ESP 6.1 0.25 1.2 

Table 6-4. Summary of particulate matter ocntrol costs for selected sources. aCosts do not include 

any costs for compliance with state and local regulations. b

Costs based on 6,000 hr/yr. cCapital costs 

increased 25 percent to account for retrofit (EPA, 1978c). d

(Weisenbery, 1979). e(Roeck et al., 1979). f

Costs (EPA, 1976) updated to 1978 dollars using the Marshall and Swift Plant Index. Operating 

costs were updated using the consumer price index. g

Costs based on 8,000 hr/yr of operation. hADP 

= Air Dried Pulp. 

Most control technologies are not particularly efficient at removing certain substances, 

which are emitted in a gaseous state at stack temperatures and then condense to form fine 

particles upon cooling in the ambient air. This effect is particularly notable for certain 

condensable organic materials, sulfur trioxide and sulfuric acid, and water vapor. The 

potential for control of these condensable pollutants varies with source category and preexisting technology. Usually no attempts are made to reduce white clouds of condensed 

water since these normally vaporize relatively near the source. 

Device Application Total % Efficiencies Fine Particles 

(0.1 to 1 mm) 

Electrostatic Precipitator Coal Fired Boiler, High 

Sulfur Coal 

99.8 99-99.6 

Coal Fired Boiler, Medium 

Sulfur Coal 

 95-98.9 

Coal Fired Boiler, Low 

Sulfur Coal 

98.3 90-99..3 

Fabric Filters Coal Fired Boiler  94.5-99.7 

Table 6-5. Particle collection efficiency of controls (Abbott and Drehmel, 1976). 
19

6.2.2.2 Nitrogen Oxides -- As discussed in Chapter 5, nitrogen oxide emissions from 

certain major combustion sources produce a yellowish-brown plume, which, in some 

cases, has been observed at significant distances from the source (Williams, 1979). 

Emission controls to reduce these impacts are of limited efficiency. The only 

demonstrated technology in the United States involves modifications of combustion 

processes. These controls can reduce NOx emissions by 30 to 50 percent when applied to 

existing sources (EPA, 1978b). New source controls for large power plants can provide 

efficiencies of up to 80 percent. Based on preliminary modeling results, such controls 

can reduce, but not entirely eliminate, perceptible plumes from large coal combustion 

sources. 

EPA and others are developing more efficient NOx reduction technologies. The most 

promising techniques are: (a) additional improvements of combustion techniques (b) 

various types of NOx removal processes which can reduce NOx emissions by 90 percent 

form incoming levels (EPA, 1978b). These techniques are not considered generally 

available to most sources of nitrogen oxides. Ongoing research and development 

programs should provide significant information leading to potential improvements in 

NOx removal capability from power plants over the next several years. Estimated 

efficiencies, capacity, and capital and operating costs for NOx control for major 

combustion sources are illustrated in Table 6-6. 

Source Type COST Size Controlb (% 

reduction) a

Capitalc,d Annuale

 (¢ 106

BTU) (without 

fuel cost) 

Annual (¢ 106

BTU) (with 

fuel cost) 

Coal fired 

utility boiler 

250 MW LEA (11) 3 x 106 0.2 -0.35 

SCR (90) 30 x 106 26.0 36.4 

500 MW LEA (11) 6 x 106 0.2 -0.35 

SCR (90) 60 x 106 26.0 36.4 

1000 MW LEA (11) 12 x 106 0.2 -0.35 

SCR (90) 120 x 106 26.0 36.4 

Coal fired 

industrial boiler 

200 x 106

BTU/hr 

LEA (11) 14 x 103 0.3 -1.8 

SCR (90) 1 x 106 23.0 32.6 

150 x 106

BTU/hr 

LEA (11) 10.5 x 103 0.3 -1.8 

SCR (90) 0.75 x 106 23.0 32.6 

Oil fired 

industrial boiler 

150 x 106

BTU/hr 

LEA (11) 14 x 103 0.26 -1.67 

SCR (90) 1 x 106 23.0 35.0 

Table 6-6. Summary of NOX control costs for selected sources. aPercent reduction over uncotrolled 

emission rate given in NOX Control Technique Document (EPA, 1978b). b

LEA = Low Excess Air. 

SCR = Selective Catalytic Reduction. c

Capital cost is 1978 estimated retrofit cost (EPA, 1978b). 

Includes equipment installation . d

Costs do not include any costs fro compliance with state and local 

regulations. e

Annual costs include O & M and annual capital recovery factor based on 6,000 hr/yr. 
20

6.2.2.3 Sulfur Oxides -- Essentially two approaches exist for reducing sulfur oxide 

emissions form fossil fuel combustion: (a) reduce sulfur in the fuel through treatment or 

selection of low sulfur fuels or (b) remove sulfur oxides during or after the combustion 

process through stack gas cleaning. Because most coal used in the Western United States 

is low in sulfur, the potential for reducing emission from existing sources through the 

first approach is limited principally to eastern areas. Although significant emission 

reductions by existing plants might be possible through use of low sulfur fuels, 

implementation of this approach on a regional scale is limited by the availability of low 

sulfur fuel and associated costs, energy and employment impacts. 

The applicability, efficiency and cost of flue gas desulfurization (FGD) are illustrated 

in Table 6-7. FGD systems and/or coal cleaning are mandated for all new utilities by the 

recently promulgated new source performance standard (Costle, 1979). Emissions 

reductions of up to 90 percent are required. Applicability of FGD systems to existing 

sources can be constrained by a number of factors including remaining useful life, cost, 

available space for the controls, and degree of improvement expected. A number of 

improvements in FGD control systems are expected to be demonstrated over the next 

several years which will improve sulfur removal capabilities and in some cases achieve 

emission reductions at lower costs. 

Visibility improvements associated with controlling SOx emissions from isolated, 

major point sources can be estimated by use of the visibility models discussed in Chapter 

5. The limitations of available models, discussed in the chapter, should be noted. It is 

currently not possible to estimate the scale and degree of visibility improvements 

associated with control of any single SOx source in a region of high SOx emissions. 

Historical trends and other empirical and analysis provide strong support for a 

proportional relationship between regional SOx emissions and sulfate/visibility impacts, 

but additional validation work is needed before more quantitative estimates are possible. 

 Costs (106 1978 dollars) a,b Source type Size Control 

SO2

removed 

Capital O & M Annual 

Utility 

Boilerc 250 MW Lime 1-5 lb/106BTU 

38.4-40.8 3.6-4.6 12.7-14.2 

 500 MW FGD 66.5-71.3 5.04-7.56 20.8-24.4 

 1000 MW 115.2-124.6 7.06-12.42 34.1-41.6 

Industrial 

boilers 

200 x 106

BTU/hr 

Lime 90% 

removal 

1.9 0.77 1.21 

Coald FGD 3.5% sulfur 

coal 

 

150 x 106

BTU/hr 

 1.75 0.65 1.05 

Non-ferrous 

smelters e,f

 

Copper 73,000-

160,000 

metric 

tons/yr. 

Double 

contact acid 

plant + MgO 

FGD system 

95 14.4-99.1 NRg

 5.36-38.43 

Table 6-7. Summary of SOX control costs for selected sources. aCosts based on 6,000. bCosts do not 

include any costs for compliance with state and local regulations. c

Costs from (EPA, 1979b) adjusted 

for size. Capital costs were increased by 25 percent to account for retrofit. d

Costs from (Dickerman 
21

et al., 1979). Costs were increased by 25 percent to account for retrofit. e

Costs from (Weisenbery, 

1979). f

Costs based on 8,000 hours per year of operation. gNR = not reported. 

6.2.3 Potentially Important Point Sources 

Utilities -- The geographical locations of existing coal and oil fired power plant boilers 

are presented in Figure 6-15. The circles are proportional to generating capacity in 

megawatts. For purposes of comparison, regions within 100 km of class I areas are 

shown in Figure 6-16. Although single source visibility impacts may occur at these and 

perhaps larger distances, the range of influence will vary with emission strength, 

meteorology, terrain and other factors. Planned utility sites through 1990 are shown in 

Figure 6-17. 

Figure 6-15. Current power plant generating capacity (EPA, 1979c). 

Figure 6-16. Areas within approximately 100 km (60 miles) of class I areas. 

CURRENT POWER PLR~T GENERRTING CRPQCITY

O~ It iA

~E'(;~l.llfl

f;11PFlt..Tt

.,

",I]::'

o ""

L 100 km from Cfan: I Area

(11100 - 200 km from Clan I Area 200 400 600 800 , , I ,

SCALE.
22

Figure 6-17. Future power plant generating capacity (EPA, 1979c). 

Potential future regional visibility impacts of utilities can be estimated form projected 

regional sulfur oxide emissions trends. Comprehensive projections have already been 

made as part of the analysis accompanying the recently announced new source 

performance standards for power plants. Projected regional sulfur oxide emissions 

through 2010 are presented in Figure 6-18. The underlying assumptions, uncertainties 

and models used in these projections are detailed elsewhere (ICF, 1979). This timing and 

extent of projected emissions reductions after 1995 are very sensitive to assumptions 

concerning the rate of retirement of existing, less well controlled plants, growth n nuclear 

capacity, and energy conservation actions. These projections must therefore be viewed 

with caution. As shown in the figure, significant decreases in utility sulfur oxide 

emissions are expected after 1995 in regions of current high utility emission density. 

Although modest increases in emissions are expected in the West, utilities are not 

currently the dominant source of regional sulfur oxide in this region. 

.:V"....,

". , .\

--c'I\7J

,~./ \I';'~ ',-"'"- _J..}

M~U:~

"[Iil:.M~T·

l~I'FlC r~

"

'0' r". .aDa oJ
23

Figure 6-18. Projected utility sulfur oxide emissions by geographic region (ICF, 1979). Note added 

in proof: Continuing analysis of potential utility emissions growth using differing assumptions on 

plant retirement, existing control requirements, and energy mix suggest that the timing and extent of 

emissions reductions shown here may be optimistic. 

Industrial Fuel Consumption -- Industrial boilers are dispersed throughout the country. 

Because they are generally concentrated in industrialized urban areas, these sources can 

contribute to visibility impairment associated with urban plumes. Figure 6-19 shows 

counties containing industrial boilers. Most growth in industrial coal use is expected to 

occur in these same counties (DOE, 1979). Current and projected sulfur oxide emissions 

form industrial facilities by region are shown in Figure 6-20. The basis for the 

projections are detailed elsewhere (DOE, 1979). The projections assume installation of 

emission controls on major industrial fuel users and also assume that growth in coal use 

will follow the national energy plan. According to DOE these assumptions may tend to 

overstate projected industrial emissions growth. 

111'1 1910 1111 ~G

TIME

I.

II.U.I"'I

NC;W ..........SHIPI!.

...~R"~T

MEWVOAK

M.-.s5ACMUSn T~

<::~NEClICUT

Pl:I10DEI!lLANO

I'ffw JfASE'f

P'l!!:NN5YLYAN 1,11,

DELAWAf1E

",A"VlAiI.,/O

TWllE TIME

f '

f

f · a

!

€

NORTH tJ,4IJ"CJTA

'9OU1H {J"tc.lJ'fA

IilEBRA&4CA.

tcA~.slld

MI~BSOTA

"""" MlsaQUR.

~!lHI"",.-rON

OIII'lON

C-.UFO.-NIA
24

Figure 6-19. Counties containing industrial coal boilers. Most growth in industrial coal use is 

expected ino r near these same counties (DOE, 1979). 

Figure 6-20. Projected regional sulfur oxide emissions from industrial coal use (DOE, 1979). 

ALASK ... MONTANA NEBRASKA WISCONSIN NEWVQRIl;

{ WASHINGTON WVOlIAING

t ICANSAS i IL.LlNOIS NEWJERSEV OREGON 13 UTAH 'OW' INOIANA

1 VIRGIN ISLANOS IDAHO COLORAOQ MISSOURI OHIO ~UERTO AICO jj, N.OAKOTA S' g, MICHIGAN S' MAINE

.~ g S,OAICOTA

.~ .i M'J .~ VERMONT

MASSACHLJSETTIi ! i AriOO,;;, ISLAND E NEW H"'~~SHIAE oi .,; ~-1 oi oi CONNECTICUT

~2 ii' ii' ii' l! i:j i;j i;j iii

. . g, 2, £-, fj,", g,

1975

CALIFORNIA NEWMEKICO KENTUCK'I" PENNSYLVANIA

NEVADA TEXAS TENNESSEE WEST VIRGINIA

{ ARIZONA i OIl;LAHOMA { M1SSISS1f!'PI { VIRGINIA

HAWAII AAKANSAS ALABAMA MARVLANO

S, GUAM S' LOUISiANA 23 GEORGIA !, DELAWARE

nORIOA

.~ < s.CAROLlNA .~ i ,g N.CAAOllNA

E i oi .; .; .;

ii ' ii' ii' ii' fl iii iii

ill / fj," . 'i:, , g,

1975 "., "'" 197~

"'" '990

TIME TIME
25

6.2.3.3 Smelters -- Studies summarized in Chapter 4 have implicated copper smelter 

particulate and sulfur oxide emissions (Figure 6-21) as one of the principal causes of 

reduced visibility in the Western United States. Historical and projected emissions are 

illustrated in Figure 6-22. During the past ten years, significant reductions in sulfur oxide 

emissions have been made in copper smelters (Marians and Trijonis, 1979). As noted 

previously, these reductions may have already produced improvement in southwestern 

visibility. These reductions have resulted from smelter retirement, decreased copper 

production, and improved emission controls. Further improvements in emissions are 

anticipated as smelters comply with air quality standards. Although some growth in 

copper production is contemplated, no additional smelter sites are currently planned. 

Figure 6-21. Existing primary copper smelters. 

Figure 6-22. Historical and projected trends in Western copper smelter emissions (Mariano and 

Trijonis, 1979). On a regional basis, the reductions from 1978 to 19900 could offset projected utility 

increases (see Figure 6-18). 

.....-.j \. _ i \

.I ", f-._._,J ( I >";'1'-'-" ,. --, I' "\ '__ I' l'-'-\', . I ........ -....-1 ,._._.-..( ~-'. -\ \ ._.

,. I t-,-._.L \.J I \ /~ . -,' - I ~-._.~.~ \ .\)'~ / \ . • I'. J' .'-- .- . . 1 I ."r -/'-:7'-' \ f-._. . I ):..r-'./'

\[ 1-'-'~"~'-'1-'-'lf_I'-\~"'''' ! _. . I.... '. .'

- ':: _ I ·-·..-'r·-\ i 1 !II ') /_. . .->-'~'

3.0

c

"Q; 2.0 «

w

>-

a:

w

'"'"Z

o

"'"Z 1.0

!:!

i

1950 55 60 65 70 75 8tl 85 90 95 2000 2010
26

Figure 6-23. Aluminum, lead, and zinc smelters. 

Figure 6-23 gives the location of existing aluminum, lead, and zinc, smelters. These 

sources emit particles and sulfur oxides. As a class, these sources are most likely to 

effect class I area visibility through visible plumes or other near source impacts. Many of 

these smelters have already or are expected to install particulate and sulfur oxide controls. 

Only a few new smelters are expected over the next 15 years. 

6.2.3.4 Kraft Pulp Mills -- Pulp and paper manufacturing operations are often located 

near forest production sites and wilderness areas, including some class I areas (Figure 6-

24). Visible particulate plumes form these sources may, in some cases, impair visibility 

in some class I areas. Kraft pulp mills account for about 85 percent of total pulp 

production. Most existing mills have already installed particulate control devices of 

varying effectiveness at removing fine particles (Goldberg, 1975), while new kraft pulp 

mill emissions are regulated under a new source performance standard (EPA, 1976). 

Pulp production is expected to increase by about 3 percent annually through 1985 (DOC, 

1977a). 

Figure 6-24. Existing pulp mills (Post, 1975). 

• ZINC SMELTERS

• LEAD SMELTE RS

• ALUMINUM SMEL TERS

o PROPOSED ALUMINUM SMELTERS
27

6.2.4 Area Sources 

Area sources include groupings of smaller point sources, e.g. home heating and 

automobiles, and large-scale emission sources such as field burning. The impact of these 

sources on visibility can in some cases equal or exceed that of major point sources. 

Because of their number and/or spatial characteristics, however, area sources are that of 

major point sources. Because of their number and/or spatial characteristics, however, 

area sources are generally difficult to control. The best control approach may be to limit 

the growth of area sources that significantly impair visibility in the vicinity of class I 

areas and to limit certain intermittent area source operations to prescribed times of the 

year or day. This section discusses three major categories of area sources which have 

been observed to impair visibility in class I areas; urban plumes, fugitive dust, and fire. 

6.2.4.1 Urban Plumes -- Urban plumes result from the combination of the many point 

and area emissions sources located in urban areas. The combined grouping can be 

considered as an area source. Visual impacts of urban plumes have been tracked at 

distances of over 100 km from their origin (Chapter 4). These plumes may blanket a 

class I area or be visible as a distinct haze layer or area of discoloration. The Los 

Angeles urban plume (Figure 6-25) frequently extends into the southern California desert 

area, a region which contains several class I areas. The Los Angeles plume may also be 

transported into the southwestern states. The Phoenix urban plume (Figure 6-26) 

combines with smelter emissions and can affect class I areas in southern Arizona. The 

Denver brown plume (Figure 6-27) is visible from the Rockies. 

Figure 6-25. The Los Angeles urban plume appears as a visible smog font as it moves into the 

southern California desert near Victorville (Niemann, 1979). 
28

Figure 6-26. Phoenix urban plume derived from smelters and area sources (Niemann, 1979). 

Figure 6-27. Denver brown cloud (Niemann, 1979). Particles and NO2 contribute to this 

discoloration. 

The visibility impact of urban plumes varies with source composition, meteorology, 

location, and season. The principal sources of primary and secondary fine aerosols in 

urban plumes include 1) major stationary source emissions of sulfur oxides, organics, and 

primary particulate matter, 2) mobile source emissions, and 3) space heating. Many of 

these sources also emit nitrogen oxides. Each of these categories is briefly discussed 

below. 

Point Source Emissions -- In areas with significant sulfur oxide emissions such as St. 

Louis, southern Arizona, and Los Angeles, secondarily formed sulfates are a major 
29

component of light scattering in the urban plume. Primary emissions of unburned 

carbonaceous material and metallic oxides form major fuel combustion and industrial 

process point sources are usually of lesser importance in the downwind plume. Control 

of these point source categories is discussed in Section 6.2.2 In addition, large and small 

point source emissions of volatile organic chemicals and nitrogen oxides can accelerate 

the formation of both organic and inorganic secondary aerosols. 

Mobile Sources—The principle primary particulate emissions from mobile sources 

have been associated with lead. These emissions can account for ten to twenty percent of 

fine particulate mass within urban areas. Although automotive lead emissions are 

expected to decrease with increased use of catalytic converters, the replacement of 

conventional gasoline engines with diesels suggests a possible increase in fine particulate 

replacement of conventional gasoline engines with diesels suggest a possible increase in 

fine particulate mass emissions from mobile sources. Studies in Denver suggest that light 

absorption by carbonaceous particulates, such as those emitted by diesels, account for up 

to 30 percent of the fine particulate visibility reduction in the city (Waggoner, 1979). 

Mobile source emissions of nitrogen oxides and unburned hydrocarbons also contribute 

to photochemical smog formation and are themselves transformed into secondary 

particulates (organics, nitrates) and nitrogen dioxide. 

Space Heating—Homes, apartment houses, commercial dwellings, and the like are 

often heated by combustion of oil, gas or wood fuels. These sources emit primary 

particulate matter, nitrogen oxides, and sulfur oxides in varying amounts. Space heating 

was one of the largest components of fine particulate matter in the Portland study 

summarized in Section 4.2. A substantial contribution was made by wood burning in 

stoves and fireplaces (Cooper et al., 1979). Since wood stoves emit 20 to 50 times the 

particulate matter as oil and gas per unit of heat output, the general trend toward 

increasing use of wood as a space heating fuel may be of concern. However, spaceheating impacts are limited to the colder months, a time of minimum visitor attendance at 

most class I areas. 

Population is a useful index of the potential for urban plume impacts on class I areas. 

For example, is has been estimated that approximately one pound of secondary 

particulate matter per person is formed in the St. Louis urban plume, and overall 

emissions rate of 1000 tones of fine particles per day. This per-capita emissions rate will 

of course vary greatly with time and city. The distribution of major United States 

population centers, their relationship to call I areas and anticipated state population 

growth rates are shown in Figures 6-28 and 6-29. A number of states containing class I 

areas are expected to grow rapidly over the next twenty years. The observed effects of 

populated areas on surrounding rural visibility suggest that care must be taken to prevent 

aggravation of existing impacts or creation of new urban plume visibility problems, 

particularly in regions sensitive to small emission changes. 
30

Figure 6-28. Population distribution, 1970. 

Figure 6-29. Projected population growth by State, 1978-2000 (DOC, 1977b). 

6.2.4.2 Fugitive Dust—Recent studies indicate that while some fugitive dust emissions 

result from the natural phenomena discussed in Section 6.1, most frequently fugitive dust 

sources result directly form previous or ongoing human activity (EPA, 1977a). Direct 

man-caused fugitive dust sources include unpaved roads, agricultural tilling, construction 

or mining activity, off road motor vehicles and inactive tailing piles. These and other 

processes that generally disturb natural soil surfaces can also make large areas more 

susceptible to dust emissions form wind erosion. Figure 6-30 presents typical particle 

size characteristics of fugitive dust sources. 

.. -

.

",'

'-"'" ...-,

...;~- .~-

orr"-

':. ..',- .• '. .:-. '".t ,.,

.. .

.. ,:-:

.. ":-t.

. ""

.. ," ..~.

. - ..,-

...:-. ,,,,."

- :~-

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'. ;'. .<..

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·f '.:

,'/' ... ".'

"

['-;0- - --J I ""_ I 46% t1~ i 1.30 \) I __._ - - - •

,,.._."
31

Figure 6-30. Particle size distribution for fugitive dust emissions (EPA, 1977a). 

Fugitive dust sources are not normally a major component of visibility reduction in 

urban plumes, but when such sources are located relatively near class I areas, they may 

adversely affect visibility. Control approaches include: Paving or use of chemical 

stabilizers on unpaved roads; increasing overall vegetative cover, modified tilling 

operations, irrigation, and stabilizers on agricultural fields; physical controls (covering), 

application of water, and vegetative cover for construction and storage piles. 

The effectiveness and cost of controlling these sources vary widely. In many cases 

significant reduction of fugitive emissions may impose unreasonable demands. For 

example, paving roads may reduce fugitive dust emissions by up to100 percent but cost 

$100,000 per mile. More detailed information on these control approaches, their 

efficiencies, and costs is available (EPA, 1977a,b; Richard et al., 1977). The impacts of 

mining emissions (Figure 6-31) on visibility in class I areas are likely to increase because 

of the increasing need to develop the major energy resources located in pristine Western 

areas. Table 6-8 presents a summary of control efficiencies and costs for major sources 

of fugitive particulates form mining operations (EPA, 1977b). 

Given the difficulty of controlling existing sources of fugitive dust, it is important to 

consider the growth of activities which produce fugitive dust emissions near class I areas. 

Particularly important are those activities, which can disturb large areas of soil, 

increasing the potential for wind derived dust emissions. Even activities which 

themselves generate dust for only a short time period for example, agricultural tilling and 

recreational vehicles, can cause changes in soils leading to increased emissions over 

much longer time periods (EPA, 1977a). 

VEHICLES.

UNPAVED ROADS.

OFF ROAD VEHICLES

100

90

80

a:

w

!-

'" 70

0

a:

u 60 i

ti.

w

... 50 w

<I:

is 40 w

...

U

j::

0: 30

<I:

"'-

20

10

0 10 20 30 40 50 60 70 80 90 laO

AGRICULTURAL TILLING

RESUSPENSION.

PAVED ROADS

AGGREGATE STORAGE

PERCENTAGES OF ALL PARTICLES I BY WeiGHT I

LESS THAN STATED SIZE
32

Figure 6-31. Fugitive dust emissions from strip mining. 

Control Control Cost Source 

Applicate control method/comments Estimate

d 

efficienc

y 

Unit cost per 

application, $ 

Units 

Overburden 

removal 

Watering/rarely practiced 50% a No data 

Drilling/Blasting Watering, cyclones, or fabric filters 

for drilling/Employment of control 

equipment increasing; Mats for 

blasting/very rarely employed 

No data No data 

Shovels/Truck 

ore loading 

Watering/rarely practiced 50% a No data 

Haul road truck 

transport 

Watering/by far the most widely 

practiced of all mining fugitive dust 

control methods 

50% b No data 

Surface treatment with penetration 

chemicals/employment of this method 

increasing 

50% b

 600-1800 f (1000-

3000) 

Kilometer 

(mile) 

 Paving/Limited practice 90-95% a 2390-6860 j,k

(2220-6370) 

1,000 m2

(10,000 ft2) 

Truck dumping Watering/rarely practiced 50% a No data 

Ventilated enclosure to control 

device/Rarely employed 

85-90% a No data 

Crushing Adding water or dust suppressants to 

material to be crushed and venting to 

baghouse/Fairly commonly practiced 

95% a

 

Transfer/ 

Conveying 

Enclosed conveyors/Commonly 

employed 

90-99% a 100-360 l,m (90-

330) 

Mg/hr 

capacity 

(ton/hr 

capacity) 
33

Enclosure and exhausting of transfer 

points to fabric filter/Limited 

employment 

85-99% 

(depends 

on 

control 

devices) 

 

Cleaning Very little control needed since 

basically a wet process 

 

Storage Continuous spray of chemical on 

material going to storage piles/Rarely 

practiced 

90% c

 0.5-1.50 f (.10-

3.25) 

Kilogram 

of chemical 

(pound) 

Watering (sprinklers or trucks)/Rarely 

practiced 

50% a No data 

Waste 

disposal/Tailing 

piles 

Chemical stabilization/Limited 

practice 

80% d 40-100 (160-400) g

; 65-150 (250-

600) 

1000 m2

(acre) 

 Vegetation/Commonly practiced 65% e 50-115 (200-450) h

 (hydroseeding) 

1000 m2

 Combined chemical-vegetative 

stabilization/Rarely employed 

90% a 25-40 (100-160) i 1000 m2

Slag cover/Limited practice 90-99% a 90-115 (350-450) g

1000 m2

Table 6-8. Summary of control efficiencies and costs for mininng fugitive particulate emission 

sources (EPA, 1977b). a-m References in EPA, 1977b. 

6.2.4.3 Managed Fires—The three major sources of large-scale fires that can impair 

class I area visibilities include: (1) wildfires, (2) prescription fires in natural areas and (3) 

agricultural burning. The nature of visibility impairment caused by the dense smoke 

accompanying wild fires is discussed in section 6-1. The latter tow categories can 

produce impacts similar in character to wildfires. Because the burning process is 

manageable in space and time, the impacts are usually lower on a unit basis than form 

wildfires. 

6.2.4.3.1 Prescription Fires—Prescription Fires, also know as prescribed burning, are 

those fires that are burning under predetermined conditions of weather, fuel moisture, soil 

moisture and other factors that will produce the intensity of heat and rate-of-spread 

required to accomplish certain planned benefits to one or more land management 

objectives such as silviculture, wildlife management, grazing and hazard reduction. 

These fires may result form either planned or unplanned ignitions. Private, State and 

Federal land managers throughout the United States use prescription fires. The amount 

of use attributable to each varies by State. Prescription fire is most widely used in timber 

producing areas under supervision of the U.S. Forest Service. Figure 6-32 lists national 

prescription fire statistics by category. Federal land managers use prescription fires in 

class I areas primarily to maintain natural ecosystems. This practice is increasing in the 

National Parks and Fish and Wildlife Service and National Forest Wilderness. A primary 

difference between these fires and those outside the class I areas is the method of 

ignition. Within wilderness, natural sources of ignition (primarily lightning) are relied 

upon while outside these areas people ignite the prescription fire. If a fire is naturally 

ignited within a wilderness or park under conditions outside the prescription, the fire is 

suppressed. Outside these areas, fires are not ignited unless prescribed conditions exist. 
34

Figure 6-32. U.S. Forest Service regions. 

Figure 6-33. Geographic dsistributions off prescribed burns in Washinton and Oregon, 19975-77 

(Geomet, 1978). 

In the Pacific-Northwest, prescription fires for silviculture and hazard reduction 

purposes have been the source of political controversy where prescription fires apparently 

affect urban as well as class I area air quality (Cooper et al., 1979). In Washington and 

Oregon, particulate emissions from these fires are estimated at 50-200,000 tons per year 

(Figure 6-33). Currently, the principal means for reducing the air quality impact of these 

emissions is through use of smoke management programs designed to keep the smoke out 

of designated populated areas. The programs have been effective in minimizing smoke in 

designated areas, but because of the geographic and meteorological relationships between 

" , ...........

1975·1977 1975 - 1977 1975 - 1977

Number of Burns Acres Bumed Estimaled Tons of Fue' 81.1med

per Hundred Squ..... Mile' per Hundred Square Miles per Hundred Square Miles

0 None IIIlIIIII 7,5·9,9 D None I11III 300- 399 D None m 7.500· 9.999

U 0.1·2.4 IIlB 10.0- 14.9 §l 1 - 99 IIIIII 400·499 1·2,499 • 10.000· 14,999

!lIIlI 2.5- 4.9 • 15.0·19.9 lllIB 100·199 • 500· 599 IIIII!l 2.500 . 4.999 • 15.000 - 19,999

5.0· 7.4 • 20.0· 200·299 • 600· 5,000 - 7,499 • 20,000 -
35

populated regions and class I areas, the programs tend at times to encourage burning 

during periods when winds carry the smoke toward class I areas. A general view of the 

impact of forestry burning on air quality in Washington and Oregon is available (Geomet, 

1978). 

Although a number of means for reducing impacts of prescription fires on class I areas 

visibility exist, they will be difficult to implement. The least costly method is to restrict 

burning to periods of minimum impact on class I areas or limit such impacts to times of 

low visitor utilization. In the Oregon/Washington area this approach may conflict with 

existing health protection goals or at best significantly reduce the frequency of allowable 

burning conditions. Reduction of burns might have adverse impacts on the silvicultural 

and hazard reduction objectives of forestry practices. Smoke from burning can also be 

reduced by improved burning practices and technology. A number of possible 

alternatives to forestry burning are listed in Table 6-10. The feasibility, effectiveness and 

environmental impacts of these approaches vary with site. Most of these alternative 

methods are useful for disposal of accumulated slash material. However, practical 

alternatives to the use of fire for improving wildlife habitat and reducing fire hazard in 

non-harvested areas have not been documented. 

Forest Service 

Region (See 

Figure 6.32) 

Burns of Timber 

Harvesting and Land 

Clearing Residues 

(slash) (million tons/yr) 

Burns of Naturally 

Occurring Forest 

Residues (million 

tons/yr) 

Total Material 

Burned (million 

tons/yr) 

1 9.81 -- 9.81 

2 0.65 0.02 0.67 

3 2.28 0.03 2.31 

4 0.84 -- 0.84 

5 3.13 0.05 3.18 

6 9.64 -- 9.64 

8 1.19 12.59 13.78 

9 0.04 0.01 0.05 

10 0.05 0.05 

Total 27.60 (69%) 12.70 (31%) 40.33 (100%) 

Table 6-9. National Prescribed Burning Statistics (Pierovitch, 1979). 
36

Figure 6-34. Prescription fire in forested area (Pierovitch, 1979). 

6.2.4.3.2 Agricultural Burning--Managed fire is used in agriculture to dispose of 

unwanted vegetative residue to reduce the possibility of disease and to prepare fields for 

future planting. Agricultural burning can be an important source of particulate matter in 

a number of the Western states. Although emissions and visibility impacts are probably 

less than those from forestry burning, significant impacts can occur where such burning 

takes place near class I areas. 

Field burning is particularly important in the Pacific Northwest. In the Willamette 

Valley of Northwestern Oregon, approximately 140,000 acres of grass seed stubble were 

burned in 1978 during the months of July through October including 51,000 acres on a 

single day (Figure 6-35)(Lyons et al., 1979). In the Northwest, agricultural burning is 

controlled under a smoke management plan similar to the plan discussed above for 

prescribed burning in forests. The state of Oregon is encouraging the development of 

reasonable and economically feasible alternatives to the practice of open field burning. 

These alternatives are generally similar to those outlined for control of forestry debris 

disposal. 

Figure 6-35. Agricultural (grass seed production) burning in Willamette Valley, Oregon. 
37

Table 6-10. Major alternatives to prescribed burning. 

Mechanical

Tn!ltlbi'l9nt Chemica' T,&Slmeot lmp,,,,,ed

Ha,.o,ling Sy'llOm$ Utilization NQ T",atment

Optimal)

Timb9't

con",,:"

WhO~-.;~ V·V

OPlim~ Matllri.l 1

Ih""liV

>
38

REFERENCES FOR CHAPTER 6 

Abbott, J. H., and D. C. Drehmel (1976) Control of Fine Particulate Emissions. CEp, pp. 

47-51. 

Adams, D. F., S. 0. Farwell, M. R. Park, and W. L. Bamesberger (1979) Preliminary 

Measurements of Biogenic Sulfur-Containing Gas Emissions from Soils. J. Air Pollut. 

Contr. Assoc. 29(4), 380-382. 

Charlson R. J., A. P. Waggoner, and J. F. Thielke, (1978) Visibility Protection for Class I 

Areas: The Technical Basis. Report to Council of Environmental Quality, Washington, 

D.C. 

Conway, H. M. Ed. (1963) The Weather Handbook. Conway Publications. 

Cooper, J. A. and J. G. Watson (1979) Portland Aerosol Characterization Study (PACS). 

Final report summary, Prepared for Portland Air Quality Maintenance Area Advisory 

Committee and Oregon Department of Environment Quality, April. 

Costle, D. (1979) New Stationary Sources Performance Standards; Electric Utility Steam 

Generating Units, FR 335844 (113) June 11. 

Dickerman, J. C. and K. L. Johnson (1979) Technology Assessment Report for Industrial 

Boiler Applications: Flue Gas Desulfurization. Draft report prepared by Radian 

Corporation for U.S. Environmental Protection Agency, Office of Research and 

Development, Washington, D.C. EPA Contract Number 68-02-2608, Task 47. 

July. 1979. 

DOE (1979) An Assessment of National Consequences of Increased Coal Utilization, 

Executive Summary. TID-29425 (Vol. 2). Dist. Category UC-90. Argonne National 

Laboratory, Brookhaven National Laboratory, Lawrence Berkeley Laboratory, Los 

Alamos Scientific Laboratory, Oak Ridge National Laboratory, Pacific Northwest 

Laboratory for U.S. Department of Energy, Washington, D.C., February. 

Dzubay, T. G. (1979) Chemical Element Balance Method Applied to Dichotomous 

Sampler Data. Proc. Symp. on Aerosols: Anthropogenic and Natural Sources and 

Transport. Annals of the New York Acad. of Sci. New York. 

DOC U.S. (1977a) U.S. Industrial Outlook, Department of Commerce Washington, D.C. 

DOC (1977b) Population, Personal Income, and Earnings by State: Projections to 2000 

Bureau of Economic Analysis, Department of Commerce, Washington, D.C., October. 

 

Eccleston, A. J., N. K. King and D. R. Packham (1974) The Scattering Coefficient in 

Mass Concentration of Smoke from Some Off Strand Forest Fires. J. Air Pollut. Contr. 

Assoc. 24(11): 1047-50. 
39

EPA (1974) Background Information for Standards of Performance: Primary Aluminum 

Industry EPA 450/2- 74-020a, Office of Air Quality Planning and Standards, Research 

Triangle Park, N.C. 

EPA (1976) Standards Support and Environmental Impact Statement, Volume 2: 

Promulgated Standards of Performance for Kraft Pulp Mills. EPA-450/2- 76-014b, Office 

of Air Quality Planning and Standards, Research Triangle Park, N.C. 

EPA (1977a) Guideline for Development of Control Strategies in Areas with Fugitive 

Dust Problems. EPA- 450/2-77-029, Office of Air Quality Planning and Standards, 

Research Triangle Park, N.C. 

EPA (1977b) Technical Guidance for Control of Industrial Fugitive Particulate Emissions 

EPA-450.3- 77-010 Office of Air Quality Planning and Standards, Research Triangle 

Park, N.C. 

EPA (1978a) National Air Quality and Emissions Trends Report, 1977. EPA-450/1-77-

022, U.S. Environmental Protection Agency, Research Triangle Park, N.C. 

EPA (1978b) Control Techniques for Nitrogen Oxides Emissions from Stationary 

Sources, Second Edition. EPA-450/1- 78-001, Office of Air Quality Planning and 

Standards, Research Triangle Park, N. C. 

EPA (1978c) Electric Utility Steam Generating Units-Background Information for 

Proposed Particulate Matter Emission Standards, Office of Air Noise and Radiation, 

Office of Air Quality Planning and Standards, Research Triangle Park, N. C. 

EPA (1979a) Electric Utility Steam Generating Units-Background Information for 

Promulgated Emission Standards EPA-450/3- 79-021, Office of Air, Noise and 

Radiation, Office of Air Quality Planning and Standards, Research Triangle Park, N.C. 

EPA (1979b) Cost Analysis of Lime Based Flue Gas Desulfurization Systems for NSW 

500 MW Utility Boilers EPA-450/5- 79;003 Office of Air Quality Planning and 

Standards, Research Triangle Park, N. C. 

EPA (1979c) Data Sources: Generating Unit Reference File, Federal Energy Regulatory 

Commission. Prepared by Energy Strategies Branch, Office of Air Quality Planning and 

Standards, Research Triangle Park, N.C., June. : 

Forest Service, 1975 Wildlife Statistics (1976) Cooperative Fire Protection Staff Group, 

State and Private Forestry. Washington, D.C. October. 

Goldberg, A. J. (1975). A Survey of Emissions and Controls for Hazardous and Other 

Pollutants. EPA PB-223. U.S. Environmental Protection Agency, Washington, D.C. 
40

Geomet, Inc. (1978) Impact of Forestry Burning Upon Air Quality, A State-of-theKnowledge Characterization in Washington and Oregon. EPA-910/9-78-052, U.S. 

Environmental Protection Agency, Seattle, Washington. 

Gillette, D. A., R. N. Clayton, T. K. Mayeda, M. L. Jackson, K. Sridhar (1978) 

Tropospheric Aerosols from Some Major Dust Storms of the Southwestern U.S. Journal 

of Applied Meteorology, 17; 832-845. 

Husar, R. B., W. H. White, D. E. Patterson, and J. Trijonis {1979) Visibility Impairment 

in the Atmosphere. Draft report prepared for U.S. Environmental Protection Agency 

under Contract Number 68-02-2515. 

ICF (1979) The Final Set of Analyses of Alternative New Source Performance Standards 

for New Coal-Fired Power Plants, Draft report prepared for the Environmental Protection 

Agency and the Department of Energy. June. 

Jeffries, H. E., and 0. White, Jr. (1967) a-Pinene and Ozone: Some Atmospheric and 

Biospheric Implications. Dept. of Environ. Sci. and Engineering. University of North 

Carolina, Chapel Hill, N.C. 

Latimer D. A., R. W. Bergs Iron, S. R. Hayes, M. K. Liw, J. H. Seinfeld, G. Z. Whitten, 

M. A. Wojcik, and M. J. Hillyar (1978) The Development of Mathematical Models for 

the Prediction of Anthropogenic Visibility, Impairment. EPA-450/3/78-110a. U.S. 

Environmental Protection Agency, Research Triangle Park, N.C. I 

Lyons, C. E., I. Tombach, R. A., Eldred, F. P. Terraglio, and J. E. Core (1979) Relating 

Particulate Matter Sources and Impacts in the Willamette Valley during Field and Slash 

Burning. Paper No. 79-46.3, Annual Meeting of the Air Pollution Control Association, 

Cincinnati, Ohio, June. 

Malm, W. (1979) Personal Communication. Environmental Monitoring and Support 

Laboratory, Environmental Protection Agency, Las Vegas, Nevada, June. 

Marians, M. and J. Trijonis (1979) Empirical Studies of the Relationship Between 

Emissions and Visibility in the Southwest. Prepared at Technology Service Corporation, 

under Grant 802015, for EPA Office of Air Quality Planning and Standards and 

Atmospheric Chemistry and Physics Division of EPA Environmental Sciences Research 

Laboratory, Research Triangle Park, N.C. 

McClenny, W. A., R. W. Shaw, R. E. Baumgardner, R. Paur and L. Coleman, 

Environmental Protection Agency, and R. S. Braman and J. M. Ammons, University of 

South Florida (1979) Evaluation of Techniques for Measuring Biogenic Airborne Sulfur 

Compounds, Cedar Island Field Study 1977. EPA-600/2- 79-004. Environmental 

Protection Agency, Research Triangle Park, N.C. 

Niemann, B. L. (1979) Results of Multiscale Air Quality Impact Assessments for the 

Southwest-Rocky Mountain Northern Great Plains Region. Part I Slide Script. Prepared 
41

for U.S. Environmental Protection Agency, Office of Energy Materials and Industry, 

Washington, D.C. 

NOAA (1974) Climatic Atlas of the United States. U.S. Department of Commerce, 

Washington, D.C. 

 

Orgill, M. M., and G. A. Sehmel (1976) Frequency and Diurnal Variation of Dust Storms 

in the Contiguous U.S.A. Atmospheric Environment 10:813-825. 

Packham, D. R., and R. G. Vines. (1978) Properties of Bushfire Smoke. The Reduction in 

Visibility Resulting from Prescribed Fires in Forests. J. Air Pollut. Contr. Assoc. 28 (8): 

790- 795. 

Patterson, E. M., D. A. Gillette and G. W. Grams (1976) The Relation Between Visibility 

and The Size- Number Distribution of Airborne Soil Particles. J. Appl. Mgt. 15:470-478. 

Pierovich J. (1979) Personal Communication. U .S. Forest Service, Southern Forest Fire 

Laboratory, Macon, Georgia 

Post's 1975 Pulp and Paper Directory (1975) Miller Freeman Publications, Inc., San 

Francisco, Calif. 612 pp. 

Radke, L. F., J. L. Stith, D. A. Hegg, and P. V. Hobbs (1978) Airborne Studies of 

Particles and Gases from Forest Fires. J. Air Pollut. Contr. Assoc. 28:30-34. 

Richard, G. (1977) An Implementation Plan for Suspended Particulate Matter in the 

Phoenix Area, Volume IV: Control Strategy Formulation. EPA-450/3-77-021d, U.S. 

Environmental Protection Agency, Research Triangle Park, N.C. 

Roeck, D. R. and R. Denum (1979) Technology Assessment Report for Industrial Boiler 

Applications: Particulate Control. Draft report prepared by GCA/Technology Division for 

U.S. Environmental Protection Agency, Office of Research and Development, 

Washington, D.C. June. 

Sandberg D. M. and D. Martin (1975) Particle Sizes in Slash Fire Smoke. U. S. 

Department of Agriculture, Forest Service. Pacific Northwest Forest and Range 

Experiment Station Research Paper PENW-99. 

Trijonis, J. (1979) Prepared for U.S. Environmental Protection Agency, Office of Air 

Quality Planning and Standards, Research Triangle Park, N.C. Contract Number 68-02-

2515, Task No.28. 

Waggoner, A. P. (1979) Personal Communication, University of Washington, Seattle, 

Washington, June. 
42

Weast, T. E., L. J. Shannon, P. G. Forman, and C. M. Guenther (1974) Fine Particulate 

Emission Inventory and Control Survey. Prepared by Midwest Research Institute, Kansas 

City, Missouri for U.S. Environmental Protection Agency, Research Triangle Park, N.C. 

Weisenbery, I. J. (1979) Cost Estimate prepared by Pacific Environmental Services, Inc., 

U.S. Environmental Protection Agency Under EPA Contract Number 68-02-3060. 

Williams, M. D. (1979) Implications of Visibility Regulations The Environmentalist's 

Perspective, Paper Number 79-26.2. Presented at the Air Pollution Control Association 

Meeting, Cincinnati, Ohio, June 24-29. 

 

Rasmussen, R. A., and F. W. Went (1965) Volatile Organic Material of Plant Origin in 

the Atmosphere. In: Proc. Nat. Acad. Sci. U.S.A. 53:215-220. 

Zimmerman, P. R. (1978) Testing of Hydrocarbon Emissions from Vegetation and 

Development of a Methodology for Estimating Emission Rates from Foliage. Draft Final 

Report. Prepared by Washington State Univ. for U.S. Environmental Protection Agency, 

Research Triangle Park, N.C. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 7 
7 PROGRESS TOWARDS THE NATIONAL VISIBILITY GOAL: 

CONTROL STRATEGIES PERSPECTIVES 

Drawing from information and discussion in previous Chapters of this report, and 

from a preliminary analysis of class I area visibility conducted by the Federal Land 

Managers, this chapter provides some initial perspectives on technological and regulatory 

control strategies for making progress toward the national visibility goal. The chapter 

summarizes the preliminary class I area visibility assessment, discusses important 

implications of the assessment, and outlines key components of visibility protection 

programs, together with alternative control approaches. 

7.1 PRELIMINARY ASSESSMENT OF VISIBILITY IN CLASS I AREAS 

 7.1.1 Nature of the Preliminary Analysis 

A fundamental process in conducting programs for protecting class I areas visibility is 

to evaluate existing visibility, to identify sources of perceptible impairment, and to 

establish visibility management objectives on a national, regional, or area specific basis. 

(Such objectives could take the form of criteria for incorporating visibility value 

judgments in case-by-case control decisions. See 7.2.3) A comprehensive evaluation 

might involve a year or more of monitoring, source identification and modeling, and 

judgments on the nature, frequency, and extent of significant or adverse visibility 

impacts. Clearly, it will be some time before complete assessments are available for the 

156 class I areas. 

Therefore, in order to develop guidance in the interim for control programs, EPA 

requested that the Federal Land Managers (National Park Service, Fish and Wildlife 

Service, Forest Service) perform a preliminary national assessment of visibility values in 

their respective class I areas. In conducting their assessments, the Land Managers relied 

on the collective expertise of individual park managers and field and regional office 

personnel. Visibility analysis "workbooks " were developed and distributed for 

completion by managers representing each of the 156 areas. Although the format 

developed by the three land management agencies differed in specifics, each requested 

the same basic information. An example of one of the workbooks is included as 

Appendix B. 

The workbooks generally called for the following kinds of information: 

1. General information on the current status of visibility, including: 

a) Man-made sources of air pollution which may significantly affect visibility, 

b) Sources and significance of natural visibility degradation (e.g., fog, dust), 

c) Impact of area management practices which may significantly affect visibility 

(e.g., prescribed burning, campfires, traffic), 

2. An assessment of the individual scenic resources in the area, including: 
a) Identification of the important vistas in the area, 

b) An assessment of current visibility conditions specifying degree and extent of 

impairment, 

c) A judgment as to whether or not the view at each vista represents desirable or 

undesirable visibility; 

 3. Formulation of visibility management objectives for each area, considering 

both the national visibility goal and the management responsibilities assigned 

to the Federal land managing agencies by enabling legislation; 

 4. Photographic documentation; to supplement the written analysis and to provide a 

baseline for further assessments, each of the land managing agencies instituted a 

program to photograph the most critical vistas and document desirable visibility 

conditions for important vistas. 

The visibility workbooks were completed by field personnel for 150 of the 156 areas 

during the summer and fall of 1978 and transmitted to their respective headquarters for 

summary and analysis (NPS, 1979; USFS, 1979; FWS, 1979). The information contained 

in these workbooks is, in effect, as assessment of visibility in class I areas based on 

human observations made over a period of one to many years. Evaluation of the sources 

of impairment, the desirability of current conditions, and articulation of visibility 

management objectives represent the subjective judgment of the individual Land 

Managers. Because factors such as the time of service, understanding of 

pollutant/visibility relationships, and criteria for specifying "desirable " visibility all may 

be expected to vary among these managers, the results of the preliminary analysis for any 

individual class I area must be evaluated with caution. Nevertheless, as long as these 

limitations are understood, the personal observations, experiences, and judgments of the 

individuals managing the class I areas in question can be extremely valuable. 

All 150 workbooks have been reviewed and summarized for this report. When viewed 

in the context of information available from other sources on regional visibility patterns 

(Chapters 1,4) and location of existing and projected major sources of visibility-impairing 

pollutants (Chapter 6), the Land Managers' assessments provide important perspectives 

for developing visibility control strategies. A preliminary synthesis of the workbook 

summary with this additional information is presented in Figure 7-1 and Table 7-1. For 

convenience, the airport visibility isopleth map for the summer months is reproduced as 

Figure 7-2. To avoid placing undue significance on the results of any single workbook, 

the class I areas are grouped into regions according to similarities in both the nature of 

visibility impairment reported and regional visual range patterns. For each region, Table 

7-1, summarizes 1) subjective judgments on the status of visibility impairment as 

reported in the workbooks, 2) observed phenomena affecting visibility, 3) a listing of 

potential manmade and natural sources reported in the workbooks and, in some cases 

from other studies, and 4) an indication of the potential for future impairment within each 

general region. 
7.1.2 Implications of the Preliminary Analysis 

The preliminary analysis suggests a number of implications for developing control 

strategies and for approaching some of the major issues, which have arisen in structuring 

visibility regulations. Some of these implications are summarized below. 

7.1.2.1 Definition of Visibility Impairment - Approximately one-third of the individual 

class I area managers reported "undesirable" visibility conditions and/or the need to 

evaluate suspected anthropogenic impacts. The remaining two-thirds of the areas were 

reported as having "desirable " or "acceptable " visibility conditions for all or most of 

their vista. Although more detailed analyses and later judgments by Land Managers and 

other interested parties might alter this estimate, the preliminary results suggest that, for a 

fair percentage of the class I areas, anthropogenic pollution is not currently causing 

frequent significant or adverse influences on visitor enjoyment of the area. On the other 

hand the analysis suggests that virtually none of the class I areas are free from at least 

some measurable or potentially observable anthropogenic visibility influence. 

These findings indicate that, if impairment is defined as any perceptible difference 

from natural visibility conditions, it appears likely that few, if any, of the class I areas 

will be able to achieve the national goal in the foreseeable future. Moreover, little 

impetus may exist for improving current visibility in areas that have "desirable " 

visibility, but perceptible impairment. 
CENTRAL VALLEY

~!isI

__-_~.

,0

';•.~: ~, NON-CONTIGUOUS

--"

\

\.

MIDWEST

~~:3 :

-~""'''V'"-'v-~''~

1-- -

I

l.-

1

I

I

,

\ --..--

..

GREAT LAKES

F.gure 7·1. ClaM I area regions.
v " 10 miles

10 !II; 1es V:' 15

15 lIli 1es V'.;. 25 III; 1es

.

-

.

--2'> m; leo, . V 45 Ill; les

•

-

•

--I.

... 'I • :\5 Ill; 1e<; V - 70 1es

ill It r ,

I .0., ••---'

-----------....--.."......-... • • •

• • •

• • •

• •

•

•

• • •

• •

•••

• •

•••

FJgUre 7-2. \isual Range Isopleth8-Swnmer 1974-76 (1Hjonis and Shapland, 1978).
TABLE 1-1. STATUS Of CLASS I AREA VISIBILITY tMPAIRMENr

Number of Reported

class I .... fJibiII t\lil 

Region mal>} afut; 

'West of 100" Mllridien

Pacfhc Northwel;l 39 G8r)8rallVdesirllble , ,. Smoke, hilZl!I 12. AgfiwIturilll 1,2. Wi Idfir8'

il'lterm I""rat urKIll!l.irable 2, V Isible plumu buming; for, 

condition9 bu rning; 

products ; 

pulp. paper mills;

saw mills;

AI, Cl,J

u rban

pl'8serl bufn in(l

C3lifomi.a Northl:

Coast Cel1tra V 7 Gener.U,;, i red 00 Uide afe8li. 1, Hau 12,:3., t ,2. Wildl'irB

some impairmE!'l1t in 2, Smoke aetl\lIW. 3. Wi ndblcw

3. Dust u rbl;ln pi um!!1; du!}t 

pr8l;crlbOd burnifl'lJ

Moufltaln 2 North Impairmetlt cuuidB areas, 1, I1l;1za 1. Ll;lke TshQe, Yf'bl;ln 2. Wildfires 

i U!ln t In 2. Smoke 

. buming 

7 Souttl GenB!"al 'y d&sirable visi bility. 1. H.ze 1. sctr..ity, :2. Wildfires

sornft imp!lrmsl'lt Ollt in illreas 2. Smoiut Siln OQuin. ValleV

1;C)(Jrcu

Sooth COO6t (WI I) GenBrally 1. HoIJZe, 1. l-l;ll other

urban plUI11B i ntnJ5imu;

1;ome prac:ribed bCHning

Northftrn ROcl< iilt/Plains 12 GilnBI"iIIIIV desirablil visibility 1. Sll'oke SI!IISh, rl;ll 1,2. 

Some Impltlrment outside ;!N'8,u 2. V isibh!1 p1Un'l86 burfllr)g; pres.cribed 3. Windblow

:), Duft bumfnll dust; 

Colorado 11 G!lnE'rBlly dBsirabla visibi Iity 1. Smoke 1. A,grie\.llwral 1, Wildfires

mills; 2, Wlndblow

PI'lIllerl bufnil"l9 d\Jllt 

:2. Urb\lra umt:$ 3, Fog 

"Golde... Circle" 9 $emil impairm4mt; need 1. HI;IZII {jnterminend 1. Power plant!}; 1, NlIwral ha

aaeu noted :2. \li&lbUi pi urnM lin'Il!Ilt8l"s; urbar1 plumlls :2. WildfirB!> 

:3. Discolor.don 2, F'ower pints; 

IbrOWl1, yellow blilndd miscellaneO\ls 

&.OurcBliO

SoutMm ArizOlla 11 Gllnflrally 1, RClgional 1. urb8lll 1. Nlltl.lrall1

2, Dun IflhOilnill, 2. WindblolM

3, Smoke UClonl dust 

4, 2, AgriC1,JltI,lfljll 

acti"itill5; burnir111 

3, bl,un 11I!l 

NiIW 10 ... deo9irabIB visibillty " 1, smelters 'T. Natl.lf8t hl

Neild to ilSYU noted 2. Du!}t 2. rtural 2. 

3. Srnakft acU\lP1lllS dust 

J. Prescribed burn Ing 
TABLE 7-'. STATUS OF C·LASS I AREA VISJBtLfTY IMPA.RMENr

Er1gland

Mid·At1sntlC

Souttl IE}

Greet Laka!l.

MidWast

NoncorltillUOU6 U-S.

Allsl(a/l-llwaii

Number of

class I

areas

6

15

4

5

7

Reporter;l

vi,ibility

status'i

GlmerallV de-sirllble v1sibilit'l/

SOrT\8 impairment, need to

llsten visibility rloted

Ganerallv deslnlble iIity

. Genlraltv d,"iratM8 ",it;ibility

GenenlUy visibility

Obterved l'ot!lntial \/is,jbilitrt 

pnenomeft1l Man-made Natura

1. .EQhod ie re- t. Regional su Ifur 1. Fog; Natur

hpe oxide; fine pllf"1ii;;la Mza 

. Vislbl-e p.I urnas emiSlllion!" 

6id. f;Om8 arees 2. Pulp mills; Opef1 

dump 

1. R"ion.1 h.lle, 1, Regional sulfur 1. Fog; 

mere nlel1se In .oxidt ; fine particle hazs 

2. Vi,itllEJ emiliiQrI1; u rbIln WilClfir& 

3. 0 iscolofatIon 

lli2e. brown ,3. Misc:ella'leolJ¥ 

p urneil Industrial $Oun:ll1;; 

prs".;ribl!d 

1. Regional haze, 1. Regionel!W Ifur 1. f Qg; natur

morEJ irltam:i\llll IfI OJ( ide; fine panide- haze 

sUn'lmer amist;iOOS 2. 

Pre9t;rjbed bu

1, ·Fj)(j 2. Pulp mills 1, 

2. Smoke, visi!;lla 11 areal 2. Wi dfine; 

Pf8'Cribed bu

1. Smoke. 1. CharcOiII kil" l. f>,escribed 

'

.. 11 areal bI.lrning;

• 01J$t 2. Fulliti'l/ll du

1. Fog 2. Ajlfioo IlL,ua I 1. 

2. Smcka 2, Vo canic

emi$lijOflS

;'JFederal La1ld Man8gli!r HIlPS, 1978;lJSFS, 1979a; IJSFWS,1979l.

b Util ity tminion ProjectiOrl' lief:. 19791; sse F 6-18-

clnchJstrieJ Coal PrcjaettCn5 IDOE. figure 6·19.

dPQplJletion {DOC, 19111; !IBe Fi\)Jre &-29,

eSmelter Emiggjon ftroJectionG (Tfijoo 19791: G!HI Figu re 6-22.
As a practical matter, it may not make much difference whether impairment is defined 

as a measurable, perceptible, or undesirable visibility impact. Given competing demands 

on available resources and lack of adequate information on impairment in most areas, the 

areas with current or projected undesirable visibility impacts should, in any case, receive 

highest priority in control programs. Section 169A of the Clean Air Act provides for 

consideration of the degree or significance of visibility improvement, costs, energy, and 

other factors in applying retrofit controls to major sources and in making "reasonable " 

progress toward the national goal. These provisions indicate that some flexibility can be 

allowed in implementing control programs for remedying existing impairment and that 

priorities can be established. Similarly, under Section 165 (PSD), the Federal Land 

Manager must determine whether construction of a major new source would result in "no 

adverse impact on the air quality related values (including visibility)" of an impacted 

class I area (emphasis added). This provision suggests that in making progress towards 

the national goal, priority is to be given to situations where impairment by a new source 

is projected to be perceptible and undesirable or adverse. Defining visibility impairment 

in the literal sense, (as a perceptible impact) and permitting flexibility in implementation 

appears to be consistent with Congressional intent. 

7.1.2.2 Need for Protecting Vistas Extending Out of Class I Areas -The preliminary 

analysis confirms the notion that it is important to consider the impact of air pollution on 

visibility for vistas that extend beyond class I boundaries. Land Managers in over 90 

percent of the class I areas, who provided detailed information on vistas, reported that 

one or more views from within the area looking outside the area may be, to some extent, 

important. Moreover, in some areas, these external views appear to be an integral part of 

the visibility experience in the area. For example, the view from Mesa Verde of Shiprock 

(New Mexico), a unique natural feature, is reportedly impaired regularly by power plant 

plumes. To exclude consideration of visibility impairment of this kind of vista appears 

contrary to the national goal. 

Nevertheless, it may not be practical or necessary to require protection for all vistas 

extending outside of class I areas. A number of class I area managers reported that large 

urban areas are visible from some vantage points within the areas. In some cases, 

visibility impairment and discoloration within the urban or developed areas were 

reported. It is not clear that Congress intended to remedy this kind of visibility 

impairment. It is, therefore, important to develop criteria for determining which views 

outside class I areas constitute an integral part of the class I area experience. 

7.1.2.3 Variety of Sources and Control Approaches Needed - The preliminary analysis 

indicates that the mix of sources that tend to dominate visibility impairment varies greatly 

throughout the country. The most frequent sources of impairment named by the Land 

Managers include (in alphabetical order): 

1. Agricultural activities-burning, fugitive dust 

2. Forest product development-prescription fires, pulp and paper mills, saw mills 

3. Miscellaneous point sources-usually in connection with visible plumes 
4. Natural sources-fog, natural haze, wind-blown dust, smoke from vegetation burning 

 (wildfires) 

5. Power plants-as single point sources and contributions through regional emissions 

6. Prescription fires-supervised by Land Managers for hazard reduction, ecosystem 

 management, etc 

7. Smelters-copper and, to a lesser extent, aluminum 

8. Urban pollution-mix of industrial activities, motor vehicles, space heating 

The feasibility and effectiveness of remedying existing impairment from these sources 

vary with both the source category and the regional setting in which they are located. For 

example, the empirical evidence discussed in 7-7 previous chapters suggests that power 

plants make a significant contribution to the general regional haze, which impairs 

visibility throughout much of the Eastern United States. Because of the large number of 

power plants and the presence of significant contributions from other manmade and 

natural sources, however, it appears unlikely that control of any single power plant in the 

East will perceptibly improve visibility. On the other hand, in the Golden Circle region of 

the West, the Land Managers reported that the impacts of single power plants are quite 

noticeable; hence, control in this region could conceivably provide substantial 

improvements. 

A totally different control approach will be needed in the Pacific Northwest and much 

of California to deal with the intermittent impairment caused by prescription fires and 

agricultural activities. Such sources are clearly not amenable to control through 

mechanisms requiring best available retrofit technology. Technically and economically 

feasible controls for these sources may, at least for the time being, be confined to 

attempts to minimize impacts during peak visitor periods or on days when meteorology 

ensures visibility impacts will be minimal. As noted in Chapter 6, prescription fires are 

often used in or near class I areas to protect natural ecosystems from eventual 

catastrophic natural wildfires. 

Guidelines for the states in developing visibility regulations must recognize and take 

into account the diverse nature of the sources of visibility impairment. 

7.1.2.4 Relative Importance of Enhancement and Protection - As discussed above, 

approximately one-third of the areas reported undesirable visibility conditions and/or a 

need to assess current visibility to determine the impact of anthropogenic pollution. 

Pinpointing the causes of these conditions and effecting improvements where possible are 

clearly important needs. Nevertheless, nearly all of the class I areas indicated the need to 

prevent existing conditions from deteriorating as a result of new source impacts. As Table 

7 -1 indicates, many of the class I areas are likely to be influenced by increased energy 

development and utilization, population, and urban growth, and associated emissions 

increases. Once such sources are constructed, it is very difficult to mitigate their impacts. 

It, thus, appears that a high priority for visibility protection programs is to incorporate 

visibility objectives in prevention of significant deterioration (PSD) programs and to 
develop long-term strategies in the state implementation plans for ensuring that increased 

development does not adversely affect visibility in class I areas. 

EPA is developing guidance for dealing with the impacts on visibility of major 

emitting facilities and associated development through the preconstruction review 

procedures required under PSD. The PSD requirements, however, do not adequately 

address increases in emissions associated with population growth, such as increased 

urbanization, automotive emissions, and space heating. PSD also may not adequately 

cover the impact of activities such as agricultural growth and highway construction. 

Additional studies to quantify the influence of such activities on visibility are needed 

before adequate guidance for states can be developed. 

 

7.2 COMPONENTS OF VISIBILITY PROTECTION STRATEGIES 

A number of important activities are involved in developing programs for making 

progress towards the national visibility goal. A conceptual framework for this process is 

outlined in Figure 7-3. The remainder of this chapter focuses on the most important 

components illustrated in this figure and highlights significant considerations and 

alternative regulatory approaches for these components. 

7.2.1 Regulation and Guidance 

 

As indicated earlier, EPA must promulgate visibility regulations and guidelines under 

Section 169A and 165 of the Clean Air Act. These regulations will establish minimum 

requirements for States to follow in ensuring reasonable progress towards the national 

goal. In order to ensure effectiveness and coordination of regulations, the Clean Air Act 

requirements for State implementation plan (SIP) guidance and preconstruction review of 

new sources under PSD will be integrated. The regulations must also specify the roles 

and responsibilities of the Federal Land Managers in this process. 

In promulgating these regulations, EPA must consider the issues outlined in the 

previous section and acknowledge the limitations in current scientific and technical 

knowledge. For this reason, EPA recommends a phased approach to visibility programs. 

Although regulations and guidelines for the State must encompass the full range of Clean 

Air Act requirements, they should, to the extent possible: 1) permit State control 

programs to focus initially on the most clearly defined cases of existing impairment and 

on strategies to prevent future impairment and 2) allow for the evolution of guidelines 

and control strategies with expected improvements in scientific understanding of 

source/visibility/observer relationships. 

Available technical information does not permit the development of control strategies 

for ultimate attainment of the national goal, but enough is known to develop a series of 

corrective and preventive actions. An evolutionary or phased regulatory approach permits 

these steps to be taken while delaying actions for which the technical basis is less clear. 

Moreover, such an approach will allow for more effective use of the limited resources 

available to States, Federal Land Managers, and EPA for developing visibility control 
programs. In the discussion of the remaining components of Figure 7-3, the need and 

potential for phasing of activities are identified. 

7.2.2 Assessment of Class I Area Visibility 

An essential initial step in developing visibility control strategies is an assessment of 

existing visibility conditions in class I areas and the identification of sources of 

perceptible impairment. Preliminary assessments such as Federal Land Manager 

workbook analyses summarized in Section 7.1 can identify significant sources of 

impairment, indicate the sensitivity of the area to future impairment, and form the basis 

for establishing priorities for control strategy development and conducting detailed 

visibility assessments. These detailed assessments will be necessary to provide an 

improved basis for control strategy decisions, especially where the impact of existing or 

proposed man-made sources is less obvious. 

Figure 7-3 lists the essential components of an assessment of class I area visibility: 

1. Review of Available Data-Airport data, preliminary Land Manager analysis, and 

other information should be obtained to support preliminary analyses and 

establish priorities. 

2. Monitoring - As discussed in Chapter 3, determining the current or "baseline" 

visibility characteristics in a class I area will require a minimum of a year of 

monitoring involving human observations and several types of visibility pollutant 

and meteorological monitoring devices. 

3. Source Identification - Sources that might impair visibility can be identified by 

direct observation of impacts of a visible source (empirical evidence), review of 

existing data bases containing emission source information, and analysis of the 

nature of the air pollutants detected in the monitoring program. 

4. Evaluation of Source Impacts - The relative impacts of man-made and natural 

sources on visibility can be estimated by empirical analyses of available visibility, 

pollutant, meteorological monitoring data, and mathematical modeling of the 

impacts of various man-made sources that have been identified. Empirical 

assessments of visibility impairment can range from simple observations of plume 

blight from visible sources to the more complex data analyses summarized in 

Chapter 4. The resolution of empirical techniques is, however, often inadequate 

for evaluating the effect of control strategies. The contribution of individual major 

point sources can also be estimated through the use of mathematical models such 

as those described in Chapter 5. Such models can, within certain limits, be used to 

evaluate the effectiveness of controls. At the current stage of development, it is 

important, where possible, to supplement the results of mathematical models with 

empirical evidence. 

5. Estimation of Natural Baseline - Ideally, a comprehensive assessment of visibility 

in a class I area would permit estimation of the distribution of visual parameters 

expected over the course of a meteorologically typical year in the absence of any 

anthropogenic air pollution impacts. Although this
CONTINUED

RESEARCH.

NEW DATA

tEPA. FlM. STATES

DOE,INDUSTRVI

CLEAN AIR ACTAMENDMENls

NATIONAL GOAL

SECTIONS 16!1A. 16:$

t-- VIS'BI LITV REGULATIONS .... _

AND GUIDE LINES (EPA~

i

ASSESS AREA VISIB'LlTV

--.llSTATES. FlM. EPA, INDUSTRY}

1. REVIEW AVAILABLE DATA

2. MONITOR IMPAIRMENT

J. IDENflfY SOU RCeS

4. MODEL IMPACTS

6. ESTIMATE NATURAL

BASE L~NE

ESTABLISH CRITERIA (OBJECTiVESl

IFLM.STA1ES, EPAI

1. CLASS. OF IMPAIRMENT

;i~ GENERA.L HAZE

bl PUJM[ BLIGHT

c~ LAVERSOF OlSCOlORAT10N

2. OEGREE AND EXTENT

.}" QUANTITATIVEtNDEX ""

bl FREQUENCY, DURATION,

TIME OF OCCURRENCE

3. SCOP'::::

""al NATIONAL, REGIONAL.

AREA SPECifiC

""b} SOURCr CATEGORY

" ci) EXISTING/NEW

--. DEVELOP CONTROL STHATEGIES ~-....."

(STATESl

1. BART ANALVSIS FOR

EXISTING SOURces

\MAJOR < 15 YRI ""

2. PSD REOUIREMENTS FOR

N~W MAJOfl SOURCES

3. L,ONG·'1"ERM STRATEGI ES

81 ANALYZE EFFECT OF

Onu:;R REGULATORY

EfFOF\TS

bl EVALUAT£ IMPACT OF

eX'$TING AND New

SOURCES NOT ADDRESSED

BV BART, PSD

(:~ ALTERNATIVES

1. TRADITIONAL EMI8810N

LIMlTATIOl\lS AND

SCHEDULES

2. SfCON DARY AIR

QUAL1TY STANDARD

Fon FINE PAAT'ClES

3. ECONOMIC INCENl1VE

AP?ROACHES· "

"" ·1

IMONITOR PROGRESS TOWARDSl '----......---......1 NAnONAL GOAL I

Ilfr;ure 7-3. Co~frRll1eWork tol' visibility pnrteelion programlt.
objective is a desirable one, even with years of monitoring, the precision of 

available visibility assessment tools and the variability of natural impacts will 

probably preclude anything more than a very rough approximation of natural 

visibility conditions. 

The principal purpose of assessing visibility in class I areas is to assist the States and 

Federal Land Managers in implementing Clean Air Act requirements. Therefore, the 

primary responsibility for assuring that these assessments are conducted must lie with the 

States and Land Managers. As indicated above, however, these assessments can be costly 

and time-consuming. Since visibility protection represents a major new regulatory 

program, it is unlikely that the States and Federal Land Managers possess sufficient 

funding, manpower, or expertise to conduct the full range of activities needed for 

comprehensive assessments. Although the Land Managers and EPA are acquiring 

additional funding for support of such assessments, it would be neither wise nor costeffective to attempt detailed assessments and analyses of visibility in all 156 class I areas 

at once. Federal and State programs should attempt to establish priorities for conducting 

assessments in areas already reporting significant anthropogenic visibility impairment or 

in those areas where construction of new sources poses the greatest threat to future 

visibility. Where available resources are inadequate, EPA or the states might require 

proposed sources to conduct visibility assessments in class I areas as part of the 

preconstruction review process. 

7.2.3 Establishing Visibility Objectives 

Development of control strategies for meeting the national goal will require a number 

of judgments concerning priorities for assessments and controls, the meaning of 

"perceptible," "adverse," and "significant" impairment, and criteria for measuring 

"reasonable" progress. Such judgments will involve coordination among the Federal 

Land Managing, Agencies, States, EPA, and the public. Although many such judgments 

must be made on a case-by-base basis, it is desirable to establish, where possible, a 

consensus among interested parties in advance of control strategy decisions. For this 

purpose, it may be useful to establish series of visibility objectives as general guidelines 

for control strategy development. The term "objective," is used here to distinguish 

desirable/acceptable visibility conditions or control strategies, which may vary for class I 

areas, from the national goal, which is, in principle, the same for all class I areas where 

visibility is an important value. These objectives would represent the visibility 

characteristics and values, which are to be restored and protected, or, in some cases, 

tolerated on a temporary basis. Although ultimate visibility objectives must be consistent 

with the national goal, interim or preliminary objectives reflecting the range of judgments 

noted above will be useful in making reasonable progress towards the goal. 

Visibility objectives should, where possible, be articulated in such a form as to permit 

eventual measurement or estimation by models. The objectives also must take into 

account the various kinds of visibility impairment and incorporate the results of studies of 

human perception and visibility values. Significant aspects to be considered are outlined 

in Figure 7-3. The objectives should express qualitative judgments concerning desired 

visibility in quantifiable terms, which can be related to source emissions. For example, 
the general objective "maintain good visibility" might be expressed in several ways: a) 

maintain a median visual range ofx kilometers, b) ensure no new source emissions result 

in a change of contrast of greater than y percent on any day at the most sensitive viewing 

distance, or c) limit total anthropogenic fine particulate concentration at any point in the 

area to zμg/m3 annual average. 

 

There has been some debate over what single indicator might best be used to 

characterize visibility objectives. Prominent examples include extinction coefficient, 

contrast (between sky and target plume and background), visual range, fine particulate 

concentration, and chromaticity. As discussed in Chapter 3, the basic visibility indices are 

contrast and extinction. With the exception of chromaticity, however, all of these indices 

of visibility can be directly monitored or estimated from monitoring data, although 

simplifying assumptions and approximations are often necessary. No single indicator will 

be clearly useful for characterizing general haze, plume blight, and discoloration in all 

areas. It is, however, advisable to tie visibility objectives to indices that are directly 

measured in class I areas. 

Frequency, duration, and time of occurrence should be taken into account in 

establishing visibility objectives. These factors are important because meteorological 

conditions can cause natural and anthropogenic visibility impacts to vary widely 

throughout the course of a year. Moreover, all else being equal, impairment from 

anthropogenic sources is considerably more objectionable during times of the year with 

greatest visitor attendance (e.g., summer). Visibility objectives might, therefore, be stated 

in terms of acceptable frequency distributions of visibility (e.g., contrast) over the course 

of a year. A comprehensive visibility assessment would be necessary before such an 

objective could be articulated. Frequency might also be considered by expressing the 

visibility objective as an allowable increment (e.g., an x percent increase in contrast) over 

an estimated or assumed baseline for any day in the year. 

Conceptually, the scope of visibility objectives might be national, regional, or areaspecific and might distinguish among source categories and existing and new sources. 

National objectives must be articulated in such a way as to account for prevailing 

differences in regional visibility. A national visual range objective would have no 

meaning. A hypothetical visual range within x percent of natural background might, 

however, be a useful long-term objective. Several qualitative examples of interim 

visibility objectives include: 

1. National or regional objectives regarding the seasonality, frequency, and intensity 

of prescribed burning activities. 

 

2. A national objective with respect to visible coherent plumes. 

3. Area-specific objectives with respect to vistas extending outside class I areas. 

4. National or regional objectives concerning allowable increments from new 

sources. 
5. Regional or area-specific objectives calling for maintenance of current visibility 

or improvement to specific levels. 

Providing a mechanism for the development and articulation of visibility objectives is 

a key problem. The process must include affected States and Land Managers and 

opportunity must be provided for direct public comment. EPA could call for formal 

procedures in guidelines for implementing Section 169A or allow individual states and 

Land Managers to develop ad hoc mechanisms. The Forest Service has recently proposed 

regulations that incorporate air quality considerations (including visibility) in their overall 

land management planning process (USFS, 1979b). 

7.2.4 Development of Control Strategies 

The development of control strategies is guided and limited by the regulations, 

assessments, and judgments discussed above. The essential control programs required by 

the Clean Air Act are outlined in Figure 7-3. Each of these components is discussed 

below. 

7.2.4.1 Best Available Retrofit Technology (BART) Analysis -State visibility strategies 

must require that certain major stationary sources install and operate BART. These 

requirements apply to major stationary sources that (a) may reasonably be anticipated to 

impair visibility in a class I area, (b) began operation during the period from August 1962 

to August 1977, (c) are not exempted from BART requirements by the Administrator of 

EPA. The Administrator can exempt on a case-by-case basis major sources that do not by 

themselves, or in combination with other sources, cause or contribute to significant 

impairment of visibility in a class I area. Furthermore, in determining BART, the State 

must evaluate the degree of improvement in visibility, economics, energy, and other 

factors, as well as availability of controls. 

In essence then, application of BART will be restricted to those major sources a) for 

which the preliminary or detailed visibility assessment provide reasonably good evidence 

for noticeable visibility impacts, b) which meet the age requirements and c) the control of 

which can be expected to result in a perceptible improvement in visibility. The 

applicability of BART to those 28 source categories named in Section 169 will depend 

upon such factors as the type and amount of emissions and the location of each individual 

source. The potential applicability of the BART mechanism to man-made visibility 

impairment identified by the Land Managers, workbooks is summarized in Table 7-2. 

It appears likely that in the early stages of visibility protection programs, application 

of BART will be quite limited. Improvements in understanding source/visibility 

relationships and developments in control technology could expand, to some extent, the 

application of BART. 

The preliminary Land Manager analysis indicates that a number of significant sources 

of visibility impairment identified in the preliminary analysis will not be covered under 

BART requirements. However, states must ultimately consider such sources in 
developing long-term strategies for making progress toward the national goal. This 

requirement is discussed in 7.3. 

7.2.4.2 Prevention of Significant Deterioration - Issues in making progress towards the 

national visibility goal with respect to new major emitting facilities must be resolved 

within the procedures established for the prevention of significant deterioration (PSD). 

Therefore, the preconstruction review procedures established by the state under PSD 

must incorporate mechanisms for a) evaluating visibility impacts, and b) involving 

Federal Land Managers in judgments as to whether permitting construction of a proposed 

new source would adversely affect current visibility or be inconsistent with long-term 

programs for making reasonable progress toward the national goal. As discussed in the 

previous section, one mechanism for formalizing such value judgments is the 

establishment of regional or area-specific visibility objectives to guide the 

implementation of procedures for granting new source permits. 

A visibility analysis for a proposed new source must consider whether the new source 

impact is consistent with applicable visibility objectives with respect to general haze 

conditions, perceptible plumes, and atmospheric discoloration. The analysis must rely 

heavily on predictive models as supported by empirical data. As discussed in previous 

chapters, there are a number of uncertainties, which must be recognized in applying these 

procedures. Areas of important uncertainty include the difficulty in predicting the 

formation of secondary aerosols (sulfates) under varying meteorological conditions, 

estimation of transport and dispersion parameters in areas of complex terrain, predictions 

of the impact of single or multiple sources on a regional (200 to 500 kilometer) scale, and 

theoretical limitations in predicting whether incremental changes in contrast or color will 

be perceptible. Although major efforts to reduce these uncertainties are of high priority, 

the available tools can, and must, be used in evaluating new source impacts. The 

alternative, allowing construction of new sources as long as prescribed class I increments 

are met, is not acceptable. Analyses of available scientific information by Charlson et al. 

(1978), Latimer et al. (1978), and others support the contention of the House Commerce 

Committee that "mandatory class I increments do not protect adequately visibility in class 

I areas" in all cases. 

These preliminary analyses also suggest that the areas most sensitive to these effects 

lie in or near the "Golden Circle " region of the Southwest, the region with the best visual 

range and a number of heavily visited class I areas. Initial modeling of alternative powerplant configurations suggests that potential problems in this region include plume bright 

from NO2 and sulfate-derived haze. As discussed in Chapter 5, brown NO2 plumes might 

occur at distances of up to 80 km from the source and be perceptible for plants larger than 

a capacity of 500 megawatts. Under most meteorological conditions, maximum impacts 

of sulfate haze derived from SO2 emissions would be expected at distances from 100 to 

200 km from the source. Preliminary analyses suggest these impacts will likely not be 

significant for single well-controlled plants of less than 2000 MW capacity, although the 

cumulative effect of several sources may be of concern. 
If preconstruction analysis for a proposed new source suggests an unacceptable 

visibility effect, the available options for the sources include reduced emissions through 

improved controls or "downscaling" of the project and alternative siting in locations 

where meteorology and/or the terrain reduce or eliminate the expected impacts. 

Specification of visibility objectives and detailed analyses of visual air quality will be 

needed to determine the extent to which such alternative sites can accommodate regional 

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in the Southwest. Initial analyses, however, suggest that, with proper siting, application 

of NSPS controls, and expected reductions in smelter emissions, planned growth in 

Southwestern utility generation through the year 2000 should not be unduly constrained 

by visibility requirements (Latimer, 1979). 

The analysis of the impact of proposed new sources also encompasses the impacts of 

other growth associated with the proposed facility. The Federal Land Managers' 

workbooks underscore a need for evaluating the impacts of general urban development, 

since these impacts are often reported to be substantial. As noted earlier, PSD 

mechanisms do not provide for an explicit analysis of visibility impacts for growth in 

smaller or urban scale source emissions not associated with a major facility. Moreover, 

PSD guidance to date does not provide for assessing the cumulative impact of issuing 

permits for a large number of new sources on a regional scale. Again, such issues must 

eventually be considered by the States in developing long-term strategies. 

7.3 LONG-TERM STRATEGIES 

 

As indicated in the previous discussion, development and implementation of long-term 

strategies are central to making progress towards the national visibility goal. These 

strategies should provide for integration of visibility objectives into ongoing air 

management efforts, to take into account sources not adequately covered by other 

mechanisms and to explore innovative approaches for making cost-effective progress 

toward visibility protection. Important considerations and alternatives are outlined below. 

7.3.1 Analysis of the Effect of Other Regulatory Efforts 

An essential starting point in developing long-range strategies for visibility protection 

is to assess the impact of other air pollution related control programs. These control 

programs include: 1) State implementation plan emission limits and compliance 

schedules for attainment and maintenance of the ambient air quality standards, 2) new 

source performance emission standards for power plants, industrial boilers, and other 

major sources of visibility impairing pollutants, 3) motor vehicle emission standards, and 

4) PSD increments for class II, as well as class I areas. These regulatory programs can be 

expected to provide significant benefits in meeting interim objectives and making 

progress toward the national visibility goal. 

The potential impact of existing programs on some of the more difficult visibilityimpairment problems identified in the workbook analysis is outlined below. 

1. Southwestern regional impairment from smelters -The Southwestern smelters 

have significantly reduced emissions in response to state programs for attaining 

the national ambient air quality standards and because of reduced production. The 

smelters are under compliance schedules that should provide further significant 

reductions in emissions by 1990 (see Figure 6-22). Preliminary analyses (Marians 

and Trijonis, 1979; Latimer et al., 1978), suggest that the reductions in smelter 

emissions to date have resulted in improved regional visibility in the Southwest 
since 1972. Therefore, the exemption of most smelters from BART requirements 

(due to their age) will not materially affect progress toward the visibility goal. 

2. Regional visibility impairment in the East - As discussed in Chapters 4 and 5, 

regional trends in visibility are strongly associated with regional sulfur oxide 

emissions, especially from power plants. Additional contributions come from 

direct fine particulate emissions and photochemically produced organic particles. 

Strategies for attaining the air quality standards for particulate matter, sulfur 

oxides, and ozone in the East have already stopped the general trend toward 

increased emissions of these pollutants. In addition, the recently announced new 

source performance standard for power plants represents an important long-term 

strategy that will ultimately reduce Eastern sulfur oxides emission levels, because 

the eventual replacement of older, poorly controlled power plants will be with 

cleaner new plants. This strategy however, will not begin to significantly reduce 

emissions until after 1995 (see Figure 6-18). 

3. Impairment from urban plumes -A number of the class I areas are impaired by 

urban plumes from cities where one or more of the current ambient air quality 

standards are not met; for example, the South Coast Air Basin of California. Such 

urban areas are already moving as rapidly as practical towards meeting the air 

quality standards. 

These efforts should, at least, limit any increased impairment and in some cases 

improve visibility conditions. 

Once the impact of other regulatory programs is evaluated, the need for additional 

control approaches for meeting the national goal can be assessed. For example, in the 

cases of impairment caused by smelters or the South Coast Air Basin urban plume, it 

does not appear reasonable or necessary to develop major new strategies for visibility 

improvement at this time. Such strategies would not significantly affect the rate, or 

extent, of control application. Long-term strategies must focus on those situations and 

source categories that can not meet interim visibility objectives or make reasonable 

progress toward the national goal. 

7.3.2 Analysis of Existing Sources not Covered by BART 

As discussed above, long-term strategies must consider the problem of existing 

sources of visibility impairment that are not covered by BART requirements and that are 

inadequately handled by other programs. Significant examples are sources that began 

operations after August 1977 or before August 1962, certain non-major point source 

categories, such as agricultural and other prescribed burning, and area wide emissions 

from populated areas. In many cases, the age of the source and existing controls may 

preclude any action for major stationary sources. Control of many categories of area 

sources for visibility protection will be difficult to justify and defend. However, the 

preliminary workbook results indicate a significant need to consider the impact of 

prescription fires in a manner that minimizes visibility impacts. This task will not be an 

easy one. In the area with the most significant problem (the Pacific Northwest), current 
fire management practices are designed to avoid effects on populated areas. Because of 

geography, this practice often results in increased burning impacts on class I areas. 

Clearly, in such situations public health protection must be paramount. However, it is 

likely that current programs have not attempted to deal with the question of minimizing 

visibility impacts. 

 

7.3.3 Growth of Sources not Adequately Considered by PSD 

As indicated above, general urban development and increased dispersion of smaller 

population centers in the vicinity of class I areas pose a significant threat to visibility in 

these areas. Long-term strategies must give some consideration to the impact on class I 

areas of new population growth, residential development, and increased agricultural 

activities. Historically, efforts to control the impact of generalized small sources have 

been controversial. Nevertheless, without some consideration of these sources, 

generalized growth could thwart attempts at preserving and attaining pristine conditions 

in class I areas. 

7.3.4 Innovative or Supplemental Long-Term Strategies 

Over the next several years, State visibility control programs will focus on controlling 

existing sources that have a demonstrable impact on visibility, evaluating visibility 

impacts of major new point sources located within about 150 kilometers of class I areas, 

and assessing the impact of other regulatory programs on improving and maintaining 

visibility in class I areas. Continued study of the various aspects of the visibility problem 

will permit evaluation of the effectiveness and necessity of additional control approaches 

for making progress toward the national goal. Examples of visibility problems that must 

ultimately be faced when improved technical information is available are given in Table 

7-3. Potentially desirable technical control approaches are also listed. Although 

traditional emission limitations and control strategies may be useful, implementation of 

these and other necessary long-term technical control approaches may also require the 

use of innovative or supplemental regulatory strategies. Technical control approaches 

include applying control technology, conservation or other actions, which reduce 

emissions. Regulatory strategies include means of implementing desirable technical 

controls. 
Several alternative regulatory approaches that may prove useful are outlined below, 

with some discussed in greater detail elsewhere (Fiorino, 1979). Because of the regional 

character of the visibility problems and the nature of the approaches, some of the 

alternatives discussed below are beyond the capability of individual States without 

further guidance from EPA and, in some cases, are not without additional legislative 

mandates. Considerable analysis of the feasibility, effectiveness, and desirability of these 

and other approaches is needed before they can be seriously considered. 

7.3.4.1 Secondary Air Quality Standard for Fine Particles - Current understanding of the 

regional visibility problem in the Eastern United States suggests that any attempt to make 

improvements significantly faster than projected under current new source performance 

standards and air quality standard implementation would be extremely costly. There is 

some question as to whether possible enhancement of visibility in the 35 Eastern Class I 

areas provides sufficient justification for an accelerated cleanup effort. A general 

reduction in sulfur oxide emissions would, however, probably improve visibility 

throughout the East. Depending on the extent to which the public views this objective as 

a desirable one, sufficient reason may exist for establishment of a secondary ambient air 

quality standard for fine particles. Besides mandating regional visibility improvements, a 

standard that reduces regional sulfur oxide emissions could provide other benefits, such 

as a reduction in acid rain. 

No national ambient air quality standard could be established which would protect 

visibility in all class I areas and at the same time be attainable throughout the nation. This 

is true because of generally higher natural and man-made concentrations of fine particles 

in the East. Nevertheless, such a standard would accelerate progress toward improved 

visibility throughout the Eastern United States and might also increase the efforts for 

visibility improvements in major urban areas of the Western United States. Thus, a 

secondary air quality standard for fine particles could effectively complement visibility 

protection programs in class I areas. 

 

Recently initiated research efforts in monitoring of fine-particles, transformation and 

transport studies, and progress in evaluating visibility values could provide support for a 

TABLIE 1-1 IEXAMf'LE$OF POTIENTIAL LONG-TIERM STRATIEGIES

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decision on the desirability of such an air quality standard by 1982 or 1983. 

Implementation is required under the Act within "a reasonable time". The consequences 

of such a standard for State programs are, however, far-reaching, and significant 

additional resources at the Federal and state level may be necessary to handle the 

additional load and to deal with multi-state emission control strategies. 

7.3.4.2 Economic Incentives for Cost - Efficient Implementation -The problem of 

reducing existing impairment caused by regional haze, such as that found in the East and 

in the Los Angeles Basin, may well be more economically solved by means other than 

traditional air pollution control programs. Unlike plume blight, where the source of the 

plume can be identified by direct observation, pollutants that cause haze come from a 

multitude of sources and are so well mixed together that even the most sophisticated 

tracer studies are not reliable for identifying individual sources. Consequently, it may be 

necessary to consider polluting sources as a group rather than individually. 

Macro-scale approaches such as marketable permits and fees may be suitable 

instruments for implementing a long-term strategy that must deal with such a group of 

sources. Such strategies define ways of allocating control burdens among sources that 

impair visibility; they differ from ambient standards that traditionally prescribe the total 

level of pollutants desired rather than the distribution of control requirements. Economic 

incentives distribute control requirements in a way that is different from and potentially 

more cost-effective than traditional air pollution control regulations. 

 

1. Controlled Trading (Marketable Permits) 

Under a controlled trading approach, EPA or the States would allocate pollution 

privileges among sources in a defined area and establish conditions for future exchanges 

of these privileges. The process would be implemented in several stages: 

1. Draw boundaries around groups of sources that contribute to a common visibility 

problem; this action defines each "market" for allocating and exchanging 

pollution privileges. 

2. Establish maximum loadings for each pollutant (or precursor) that impairs 

visibility in each area, or market, on the basis of the definition of visibility goals, 

air quality modeling data, and economic and energy considerations. 

3. Allocate or auction off pollution privileges to sources in each market, to the point 

where total allocations equal the maximum loading of each pollutant consistent 

with visibility goals. The number of permits each source has would determine its 

allowable emissions. 

4. Establish conditions for the purchase and sale of pollution privileges among 

sources that are part of the same market. 

The advantage of a marketable permit system is that it produces the desired level of 

visibility protection at the lowest achievable cost by giving incentives to the sources with 

the lowest abatement costs to reduce emissions the most. Those sources with low 
abatement costs would find it more economical to install controls than to buy permits, 

and those sources with high abatement costs would find it more economical to buy 

permits than to install controls. As the permits are traded among sources, the total 

cleanup cost lessens while the burden of paying for it remains spread among all sources 

responsible for visibility impairment. 

A disadvantage of this system is that the equilibrium price of the permits is unknown 

until the auction has stabilized. This price factor is crucial to businesses making 

investment decisions, and its uncertainty might lead to less than optimal decisions on the 

part of the regulated industries. Coordinating the system on a multi-state basis presents 

additional difficulties. 

2. Emission Fees 

Under a fees approach, firms face a fixed charge for each unit of waste emitted (e.g. 

$X/lb sulfur). To control visibility, charges would be levied on sulfur oxides, nitrogen 

oxides, and all other constituents that can be shown to impair visibility. If the fees are set 

high enough, it will be cheaper for sources to reduce emissions than pay the charge. 

Ideally, sources would minimize their pollution control costs by abating their wastes up 

to the point where the incremental cleanup cost equals the level of the fee. The next 

increment of pollution reduction would cost more than the fees. The proper fee should be 

set so that the sum of residual discharges from all sources does not exceed the maximum 

amount of each pollutant that is consistent with the visibility goal. In theory, the amount 

of waste reduction from each firm will vary as a function of the firm's marginal 

abatement cost. 

Unlike a marketable permits approach, a fees approach results in a known price for 

pollutants emitted but an unknown level of pollutant loading and, therefore, an unknown 

level of visibility protection. Consequently, several iterations of fee levels would be 

necessary before an optimal level is reached. 

3. Supplemental Economic Approaches 

Government cost-sharing, through tax incentives or direct subsidies, can be used along 

with visibility control strategies. Accelerated depreciation allowances, direct grants, 

interest-free loans, and guaranteed financing might be used selectively. Such cost-sharing 

schemes have proven to be most desirable in promoting control technology development. 

Incentives may be particularly useful in encouraging alternative means of disposing of 

forest debris, which is currently burned on site. 

Noncompliance penalties, provided for in the Clean Air Act, can be imposed for 

violations of BART requirements. Such penalties remove the incentive to avoid 

compliance by assessing firms an amount equal to the economic benefits they receive 

from noncompliance. 
REFERENCES FOR CHAPTER 7 

Charlson R. J., A. P. Waggoner, and J. F. Thielke, (1978) Visibility Protection for Class I 

Areas: The Technical Basis Report to the Council of Environmental Quality. 

Washington, D.C. 

DOE (1977) Population, Personal Income, and Earnings by State: Projections to 2000. 

Bureau of Economic Analysis, Department of Commerce, Washington, D.C. 

DOE (1979) An Assessment of National Consequences of Increased Coal Utilization, 

Executive Summary. TID-29425 (Vol. 2). Dist. Category UC-90. Argonne National 

Laboratory, Brookhaven National Laboratory, Lawrence Berkeley Laboratory, Los 

Alamos Scientific Laboratory, Oak Ridge National Laboratory, Pacific Northwest 

Laboratory for U.S. Department of Energy, Washington, D.C., February. 

Fiorino, D. (1979) Alternative Regulatory Strategies for Visibility Protection. Draft 

Report, Office of Planning and Evaluation, U.S. Environmental Protection Agency, 

Washington, D.C. 

ICF (1979) The Final Set of Analyses of Alternative New Source Performance Standards 

for New Coal-Fired Power Plants, Draft report prepared for the Environmental Protection 

Agency and the Department of Energy, June. 

Latimer, D. A., R. W. Bergstrom, S. R. Hayes, M. K. Lui, J. H. Seinfeld, G. Z. Whittem, 

M. A. Wojcik, M. J. Hillyer (1978) The Development of Mathematical Models for the 

Prediction of Anthropogenic Visibility Impairment. EPA 450/3-78-110a,b, c. U.S. 

Environmental Protection Agency, Research Triangle Park, N.C. 

Latimer, D. (1979) Power Plant Impacts on Air Quality and Visibility: Siting and 

Emissions Control Implication Prepared for Office of Planning and Evaluation, U.S. 

Environmental Protection Agency, Washington, D.C. 

NPS (1979) Visibility Workbooks for National Park Service Class I Areas. Preliminary 

Analysis, Washington, D.C. 

Trijonis, J. (1978) Prepared under Contract Number 68-02-2515, Task No.28 for U .S. 

Environmental Protection Agency, Office of Air Quality Planning and Standards, 

Research Triangle Park, N.C. 

Trijonis, J., and D. Shapland, (1978) Existing Visibility Levels in the U.S., prepared by 

Technology Service Corporation for the U.S. Environmental Protection Agency under 

Grant No.802815, Research Triangle Park, N.C. 

USFS (1979a) Visibility Workbooks for Forest Service Class I Areas. Preliminary 

Analysis, Washington, D.C. 

USFS (1979b) National Forest System Land and Resource Management Planning. FR. 

26643.44(88). May 4. 

USFWS (1979) Visibility Workbooks for Fish and Wildlife Service Class I Areas. 

Preliminary Analysis, Washington, D.C. 
PROTECTING VISIBILITY 

AN EPA REPORT TO CONGRESS 

CHAPTER 8 
8 RECOMMENDATIONS FOR VISIBILITY RESEARCH 

The preceding chapters have identified a number of important information gaps and 

uncertainties in our current understanding of atmospheric visibility impairment. The 

extension and refinement of visibility protection programs will depend on improvement 

in available knowledge and techniques in several fundamental areas. These areas include 

monitoring, source identification, predictive modeling, atmospheric chemistry and 

transport, human perception, control techniques, implementation strategies, and value 

judgments. Increased communication among the various regulatory, scientific and 

technical disciplines represented by each of these areas is vital to the development of 

comprehensive research approaches to improve methods for making progress toward the 

national visibility goal. 

EPA is currently developing an expanded visibility research program to be carried out 

over the next several years. In developing and implementing this program, EPA will 

continue coordination with major visibility studies conducted by the Federal Land 

Managers, Department of Energy, other governmental agencies, and industry groups. 

Important areas that should be addressed by these programs are summarized below. 

8.1 CHARACTERIZATION OF EXISTING REGIONAL VISIBILITY 

CONDITIONS 

Assessment of existing visibility in class I areas is an important need. Class I areas can 

be grouped into regions of similar climatology, scenery, prevailing visibility, and sources 

of impairment (such as those illustrated in Figure 7-1). Long-term comprehensive 

characterization of visibility-related parameters should be conducted in at least one class I 

area in each of these representative regions. Minimum requirements for such a program 

would include operation of a 10-to-20-station monitoring network for a period of 5 years. 

Priority should be given to pristine areas with significant emissions growth (or reduction) 

potential and areas with existing impairment problems. Approximately 3 to 5 Eastern 

sites (Northeast, mid-Atlantic, South Coast, Great Lakes) and 7 to 15 Western sites 

("Golden Circle", Colorado, Pacific Northwest, California, Northern Plains, Southern 

Arizona, New Mexico-Texas) would give sufficient coverage. Each location should 

provide for comprehensive monitoring of optical, meteorological, and pollutant 

parameters. In addition to the human observation and instrumentation recommended in 

Chapter 3, instrumentation for monitoring light absorption by particles should be 

included. All identifiable major components of fine particulate mass should be 

monitored, and the contribution of coarse-mode particles to extinction estimated. The 

sampling strategy should be designed with data reduction and analysis methods in mind. 

Attempts should be made to separate natural and anthropogenic contributions and to 

characterize various air-mass influences. Supplemental regional aircraft sampling and 

auxiliary site "intensive " monitoring would be a useful adjunct to the base network. 

The results of this comprehensive monitoring would include an improved 

understanding of natural and anthropogenic base-line contributions to visibility 

impairment, an indication of which parameters are necessary or most useful in 
characterizing visibility, better monitoring instruments and operating procedures, and 

more precise approaches to assessment of visibility impairment. The network would also 

serve as a focal point for other visibility-related studies. 

8.2 IMPROVED VISIBIDY MONITORING APPROACHES 

Additional work is needed to develop simplified and improved visibility measurement 

approaches. An initial priority is development of a standardized guideline for "context 

pertinent" human observations by trained personnel. A consistent index should be 

developed for the three classes of impairment (plume blight, haze layers and general 

haze) and a generalized daily observation form should be made available. Development 

on standardized human observer methods should be coordinated with studies of human 

perception (Section 8.5) and visibility values (Section 8.6). 

Improvements are needed in optical instruments. If possible, a single instrument, 

useful in a variety of applications, should be developed and tested. A portable, low-power 

consumption device for use in remote wilderness areas is particularly needed. Instruments 

for routine measurements of scattering and absorption by particles would be most useful. 

More sophisticated monitoring techniques for research applications are also needed. 

Instruments for measuring aerosol mass and chemical composition over shorter time 

intervals (1 to 2 hours) in clean areas would be a useful adjunct to current optical 

instrumentation. More accurate sampling and analysis approaches are needed for 

particulate organics and nitrates. 

 

8.3 FIELD STUDIES OF POINT AND AREA SOURCE IMPACTS 

Plume flights conducted in the VISTTA, MISTT, MAP3S, SURE and other research 

programs have provided significant information on the visibility impacts of major point 

source and large urban plumes. Such programs should be continued. Additional field 

studies are needed to examine the visibility impacts of source/environment combinations 

not yet studied. Briefly, these combinations include: 

1. Plumes from power plants equipped with wet and dry ~ SOχ scrubbers. 

 

2. Secondary sulfate, NO2, and nitrate formation rates in plumes from Western 

power plants. 

3. Emissions from new energy technologies. 

4. Impacts of Los Angeles, Phoenix, and Tucson urban plumes on Southwest 

regional visibility. 

5. Impacts of medium to small urban areas on nearby (50 to 100 km) Class I areas in 

the Southwest. 

6. Fugitive dust emissions from mining, agriculture, and unpaved roads. 
7. Impact of prescribed burning in the Pacific Northwest. 

8.4 IMPROVEMENT IN PREDICTIVE VISIBILITY MODELS 

 

8.4.1 Single Point Source Models 

Validation and improvement of existing visibility models are extremely important. It 

is particularly necessary to determine whether the predicted significant NO2 impacts at 

distances of 20 to 80 kilometers from well-controlled plants are observable. Analysis of 

validation studies (plume flights and ground measurements of relevant optical, 

dispersion, and chemical parameters), conducted by the VISTTA program for 1978-1979, 

should be accelerated to the extent possible, and plans for additional studies made. 

Current models should be improved to deal more effectively with complex terrain, 

channeling effects, and variable meteorological conditions over the course of a day and 

through seasonal cycles. Models should be extended to permit impact analyses of area 

sources, mining operations, and new energy technologies. The results of empirical studies 

of atmospheric visual perception (Section 8.5) should be incorporated into improved 

models. The LASL color display technique should be further developed and adapted for 

routine use on less sophisticated computers. 

8.4.2 Regional Scale Models 

As a starting point in developing regional-scale visibility models, the available airport 

visibility/pollutant satellite database in the Western states should be examined to 

determine if any evidence of hazy air mass episodes exists. Planned field studies in the 

East (PEPE and SURE) to evaluate chemistry, transport, and removal processes in a 

variety of conditions will be of significant value. Additional studies of Western hazy air 

masses should be initiated. 

Studies of regional dispersion in the complex terrain of the West are needed. Basic 

Western meteorological data, such as transport winds through the mixing layer (up to 3 

km), should be gathered as input for regional models. Regional models should be capable 

of dealing with spatial/temporal variations in plume trajectories, diurnal patterns in 

mixing heights, turbulence, stagnation, recirculation, channeling by terrain, and moderate 

to large scale meteorological patterns. 

8.5 STUDIES OF ATMOSPHERIC HUMAN VISUAL PERCEPTION IN CLEAN 

AREAS 

Both visibility modeling and monitoring require improved specification of the 

response of the eye/brain to atmospheric visual stimuli. Tests of the relationship between 

visual range of large dark objects and extinction (Koschmeider) are needed in "clean" 

areas. Validation of the applicability of the MTF approach for predicting the visual range 

of contrast detail and perceptibility of small pollution increments in scenic vistas is also 

needed. Most importantly, a study of thresholds of perception for discoloration caused by 

NO2 and haze layers in the atmosphere should be conducted. Such studies should be 

linked and compared to the predicted outputs of visibility models. Many of these 
perception studies could be conducted by use of panels of observers at or near 

comprehensive monitoring sites, discussed in Section 8.1. Initial studies by the American 

Petroleum Institute and the National Park Service will provide important insights for 

further work. 

8.6 STUDIES OF THE VALUE OF VISIBILITY 

Improved specification of the value of visibility, whether in economic, psychological, 

or social terms can assist in specific control/permitting decisions and in establishing 

interim objectives for making progress toward the national goal. A coordinated visibility 

values research program, tied to decision-making needs of the Land Managers and States, 

should be developed. The 1979 Visibility Values workshop represented a first step in this 

process (Fox et al., 1979). Values studies might be connected with studies of human 

perception and monitoring programs. Photography or field studies using observer panels 

could be conducted to define "significant" or "adverse " impairment better. Economic and 

psychological studies of activity, options, and existence values of class I area visibility 

might also prove useful. An analysis should be conducted of the benefits and desirability 

of improving visibility in Eastern class I areas, and hence, improving general visibility 

throughout the East. Such analyses may form the basis for deciding on long-term 

strategies for remedying existing impairment, as well as protecting general public 

welfare. 
REFERENCES FOR CHAPTER 8 

Charlson R. J., Waggoner A. P. and Thilke J. F. (1978) Visibility Protection for Class I 

Areas: The Technical Basis. Report to Council of Environmental Quality, Washington, 

D.C. 

Environmental Research and Technology, Inc. (1979) Draft. Phase I Report: Analysis of 

Clean Act Provisions to Protect Visibility. ERT Contract EE- 77-C-01-6036. Prepared for 

U. S. Department of Energy, Washington, D.C. 

Latimer, D. A., R. W. Bergstrom, S. R Hayes, M. K. Lui, J. H. Seinfeld, G. Z. Whittem, 

M. A. Wojci, M. J. Hillyer (1978) The Development of Mathematical Models for the 

Prediction of Anthropogenic Visibility Impairment EPA 450/3- 78-110a,b,c. U.S. 

Environmental Protection Agency, Research Triangle Park, N. C. 

Fox, D., R. J. Loomis and T. C. Greene (technical coordinators) Proceedings of the 

Workshop in Visibility Values, Fort Collins, Colorado. January 28-February 1, 1979. 

U.S. Department of Agriculture, Forest Service, Washington, D. C. 

Malm, W. (1978). Summary of Visibility Monitoring Workshop, July 12-13,1978. 

Environmental Protection Agency, Environmental Monitoring Support Laboratory, Las 

Vegas, Nevada. 
APPENDIX A: 

CLASS I AREAS WHERE VISIBILITY IS AN IMPORTANT VALUE 
SUBPART D. IDENfIFlCATION OF MANDATORY ClASS I

FEDERAL AREAS WHERE VISIBILllY IS AN IMPORTANf VALUE

81,400 Scope,

Subpart D, Section 81.401 through 81.437 lists those mandatory Federal Class I areas, established under the

Clean Air Act Amendments of 1977, where the Administrator, in consultation wi"th the Secretary of the

Interior, has determined visibility to be an important value.

The following listing of areas where visibility is an important value represents an evalation of all international parks (IP), national wilderness areas (Wild) exceeding 5,000 acres, national memorial parks (NMP)

exceeding 5,000 acres, and national parks (NP) exceeding 6,000 areas, in existence on August 7, 1977.

Consultation by EPA with the Federal Land Managers involved: the Department of Interior (USDI), National

Park Service (NPS), and Fish and Wild Life Service (FWS); and the Department of Agriculture (USDA),

Forest Service (FS),

Public Law Federal Land

State Area Name Acreage Establishing Manager

S81.401 Alabama. Sipsey Wild 12,646 93-622 USDA-FS

S81.402 Alaska. Bering Sea Wild 41,113 91-622 USDI-FWS

Mount McKinley NP 1,949,493 64-353 USDI-NPS

Simeonof Wild 25,141 94-557 USDI-FWS

Tuxedni Wild 6,402 91-504 USDI-FWS

S81 .403 Arizona Chiricahua National

Monument Wild 9,440 94-567 USDI-NPS

Chiricahua Wild 18,000 88-577 USDA-FS

Galiuro Wild 52,717 88-577 USDA-FS

Grand Canyon NP 1,176,913 65-277 USDI-NPS

Mazatzal Wild 205,137 88-577 USDA-FS Mount Baldy Wild 6,975 91-504 USDA-FS

Petrified Forest NP 93,493 85,358 USDI-NPS

Pine Mountain Wild 20,061 92-230 USDA-FS

Saguaro Wild 71,400 94-567 USDI-NPS

Sierra Ancha Wild 20,850 88-577 USDA-FS

Superstition Wild 124,117 88,577 USDA-FS Sycamore Canyon Wild 47,757 92-241 USDA-FS

S81.404 Arkansas. Caney Creek Wild 14,344 93-622 USDA-FS

Upper Buffalo Wild 9,912 93-622 USDA-FS

A-2
State

S81.405 California

S81.406 Colorado.

S81.407 Florida.

S81.408 Georgia.

S81.409 Hawaii.

S81.410 Idaho.

Public Law Federal Land

Area Name Acreage Establishing Manager

Aqua Tibia Wild 15,934 93-632 USDA-FS Caribou Wild 19,080 88-577 USDA-FS

Cucamonga Wild 9,022 88-577 USDA-FS Desolation Wild 63,469 91-82 USDA-FS Dome Land Wild 62,206 88-577 USDA-FS

Emigrant Wild 104,311 93-632 USDA-FS Hoover Wild 47,916 88-577 USDA-FS John Muir Wild 484,673 88-577 USDA-FS Joshua Tree Wild 429,690 94-567 USDI-NPS Kaiser Wild 22,500 94-577 USDA-FS

Kings Canyon NP 459,994 76424 USDI·NPS Lassen Volcanic NP 105,800 64-184 USDI-NPS Lava Beds Wild 28,640 92-493 USDI-NPS Marble Mountain Wild 213,743 88-577 USDA-FS Minarets Wild 109,484 88-577 USDA-FS Mokelumme Wild 50,400 88-577 USDA-FS Pinnacles Wild 12,952 94,567 USDA-NPS Point Reyes Wild 25,370 94-544,94-567 USDI-NPS Redwood NP 27,792 90-545 USDI-NSP San Gabriel Wild 36,137 90-318 USDA-FS San Gorgonio 34,644 88-577 USDA-FS San Jacinto Wild 20,564 88-577 USDA-FS San Rafael Wild 142,722 90-271 USDA-FS Sequoia NP 386,642 26 Stat. 478 USDI-NPS

(51st Cong.!

South Warner Wild 68,507 88-577 USDA-FS Thousand Lakes Wild 15,695 88-577 USDA-FS Ventana Wild 95,152 91-58 USDA-FS

Yolla-Bolly-Middle-Eel Wild 109,091 88-577 USDA-FS Yosemite NP 759,172 58-49 USDI-NPS

Black Canyon of the 11,180 94-567 USDI-NPS Gunnison Wild

Eagles Nest Wild 133,910 94-352 USDA-FS Flat Tops Wild 235,230 94-146 USDA-FS Great Sand Dunes Wild 33,450 94-567 USDI-NPS La Garita Wild 48,486 88-577 USDA-FS Maroon Bells - Snowmass 71,060 88-577 USDA-FS Wild

Mesa Verde NP 51,488 59-353 USDI·NPS Mount Zirkel Wild 72,472 88-577 USDA-FS Rawah Wild 26,674 88-577 USDA-FS Rocky Mountain NP 263,138 63-238 USDI-NPS Weminuche Wild 400,907 93-632 USDA-FS West Elk Wild 61,412 88-577 USDA-FS

Chassahowitzka Wild 23,360 94-557 USDI-FWS Everglades NP 1,397,429 73-267 USDI-NPS St. Marks Wild 17,745 93-632 USDI-FWS

Cohotta Wild 33,776 93-622 USDA-FS Okefenokee Wild 343,850 93-429 USDI-FWS Wolf Island Wild 5,126 93;632 USDI-FWS

Haleakala NP 27,208 87-744 USDI-NPS

Hawaii Volcanoes 217,029 64-171 USDI-NPS

Craters of the Moo.{l Wild 43,243 91-504 USDI-NPS Hells Canyon Wild 83,800 94-199 USDA-FS

Sawtooth Wild . b 216,383 92400 USDA-FS

~~17oa~;~~~:r~~cttWIld 988,770 88-577 USDA-FS

31,488 17 Stat. 32 USDI-NPS

(42nd Cong.)

a HelisCanyon Wilderness, 192,700 acres overall, of which 108,900 acres are in Oregon and 83,800 acres are in Idaho.

b Selway Bitterroot Wilderness, 1,240,700 acres overall, of which 988,700 acres are in Idaho and 251,930 acres are in Montana.

c Yellowstone National Park, 2,219,737 acres overall, of which 2,020,625 acres are in Wyoming, 167,624 acres are in Montana, and 31,488 acres

are in Idaho.
Public Law Federal Land

State Area Name Acreage Establishing Manager

581 .411 Kentucky. Mammoth Cave NP 51,303 69-283 USDI-NPS

581.412 Louisiana. Breton Wild 5,000+ 93-632 USDI-FWS

581.413 Maine. Acadia NP 37,503 65-278 USDI-NPS Moosehorn Wild 7,501 USDI-FWS

{Edmunds Unitl 12,7821 91-504 (Baring Unit) 14,7191 93-632

581.414 Michigan. Isle Royale NP 542,428 71-835 USDI-NPS Seney Wild 25,150 91-504 USDI-FWS

581.415 Minnesota. Boundary Waters Canoe Area 747,840 99-577 USDA-FS Wild

Voyageurs NP 114,964 99-261 USDI-NPS

581.416 Missouri. Hercules-Glades Wild 12,315 94-557 USDA-FS Mingo Wild 8,000 94-557 USDI-FWS

581.417 Montana. Anaconda·Pintlar Wild 157,803 88-577 USDA-FS Bob Marshall Wild 950,000 88-577 USDA-FS Cabinet Mountains Wild 94,272 88-577 USDA-FS Gates of the Mtn Wild 28,562 88-577 USDA-FS Glacier NP 1,012,599 61-171 USDI-NPS Medicine Lake Wild 11,366 94-557 USDI-FWS Mission Mountain Wild 73,877 93-632 USDA-FS Red Rock Lakes Wild 32,350 94-557 USDI·FWS Scapegoat Wild 239,295 92-395 USDA·FS Selway-Bitterroot Wilda 251,930 88-577 USDA·FS U. L. Bend Wildb 20,890 94-557 USDI·FWS Yellowstone NP 167,624 17 Stat. 32 USDI·NPS

(42nd Cong.)

a Selway-Bitterroot Wilderness, 1,240,700 acres overall, of which 988,770 acres are in Idaho and 251,930 acres are in Montana.

b Yellowstone National Park, 2,219,737 acres overall, of which 2,020,625 acres are in Wyoming, 167,624 acres are in Montana, and

31,488 acres are in Idaho.

581.418 Nevada. Jarbridge Wild 64,667 88-577 USDA-FS

581.419 New Hampshire. Great Gulf Wild 5,552 88-577 USDA·FS

Presidential Range-Ory 20,000 93-622 USDA·FS

River Wild

581.420 New Jersey. Brigantine Wild 6,603 93-632 USDI·FWS

581.421 New Mexico. Bandelier Wild 23,267 94-567 USDI·NPS

Bosque del Apache Wild 80,850 93-632 USDI·FWS

Carlsbad Caverns NP 46,435 71-216 USDI·NPS

Gila Wild 433,690 88-577 USDA·FS

Pecos Wild 167,416 88-577 USDA·FS

Salt Creek Wild 8,500 91-504 USDI·FWS

San Pedro Parks Wild 41,132 88-577 USDA·FS

Wheeler Peak Wild 6,027 88-577 USDA·FS

White Mountain Wild 31,171 88-577 USDA·FS

581.422 North Carolina_ Great Smoky Mountains NP~ 273,551 69-268 USDI·NPS

Joyce Kilmer-Slickrock Wild 10,201 93-622 USDA·FS

Linville Gorge Wild 7,575 88-577 USDA-FS

Shining Rock Wild 13,350 88-577 USDA·FS

Swanquarter Wild 9,000 94-557 USDI·FWS

a Great Smoky Mountains National Park, 514,758 acres overall, of which 273,551 acres are in North Carolina, and 241,207 acres are in

b Tennessee.

Joyce Kilmer-Slickrock Wilderness, 14,033 acres overall, of which 10,201 acres are in North Carolina and 3,832 acres are in Tennessee.
State Area Name Acreage Public Law Federal Land

Establishing Manager

S81.423 North Dakota. Lostwood Wild 5,557 93-632 USDI·FWS

Theodore Roosevelt, NMP 69,675 80-38 USDI-NPS

581.424 Oklahoma. Wichita Mountains Wild 8,900 91·504 USDI-FWS

S81.425 Oregon. Crater Lake NP 160,290 57-121 USDI-NPS

Diamond Peak Wild 36,637 88-577 USDA-FS

Eagle Cap Wild 293,476 88-577 USDA-FS

Gearhart Mountai~Wild 18,709 88-577 USDA-FS

Hells Canyon Wild 108,900 94·199 USDA-FS

Kalmiopsis Wild 76,900 88·577 USDA-FS

Mountain Lakes Wild 23,071 88-577 USDA-FS

Mount Hood Wild 14,160 88-577 USDA-FS

Mount Jefferson Wild 100,208 90·548 USDA-FS

Mount Washington Wild 46,116 88·577 USDA-FS

Strawberry Mountain Wild 33,003 88·577 USDA-FS

Three Sisters Wild 199,902 88-577 USDA-FS

a Hells Canyon Wilderness, 192,700 acres overall, of which 108,900 acres are in Oregon, and 83.800 acres are in Idaho.

S81.426 South Carolina Cape Romain Wild 28,000 93-632 USDI·FWS

581.427 South Dakota. Badlands Wild 64,250 94-567 USDI·NPS

Wind Cave NP 28,060 57-16 USDI-NPS

581.428 Tennessee. Great Smoky Mountains Npa

b 241,207 69-268 USDI-NPS

Joyce Kilmer-Slickrock Wild 3,832 93-622 USDA·FS

a Great Smoky Mountains National Park, 514,758 acres overall, of which 273,551 acres are in North Carolina. and 241,207 acres are in

Tennessee.

b Joyce Kilmer-Sltckrock Wilderness, 14,033 acres overall, of which 10,201 acres are in North Carolina and 3.832 acres are in Tennessee.

SBl.429 Texas. Big Bend NP 708,118 74·157 USDI·NPS

Guadalupe Mountains NP 76,292 89-667 USDI-NPS

S81.430 Utah. Arches NP 65,098 92-155 USDI-NPS

Bryce Cc>nyon NP 35,832 68-277 USDI·NPS

Canyonlands NP 337,570 88-590 USDI·NPS

Capitol Reef NP 221,896 92-507 USDI-NPS

Zion NP 142,462 68-83 USDI-NPS

581.431 Vermont. Lye Brook Wild 12,430 93-622 USDA-FS

581.432 Virgin Islands Virgin Islands NP 12,295 84-925 USDI-NPS

5al .433 Virginia. James River Face Wild 8,703 93-622 USDA-FS

5henandoan NP 190,535 69-268 USDI-NPS

581.434 Washington. Alpine Lakes Wild 303,508 94-357 USDA·FS

Glacier Peak Wild 464,258 88-577 USDA-FS

Goat Rocks Wild 82,680 88-577 USDA-FS

Mount Adams Wild 32,356 88·577 USDA-FS

Mount Rainier NP 235,239 30 Stat. 993 USDI-NPS

(55th CongJ

North Cascades NP 503,277 90·554 USDI-NPS

Olympic NP 892,578 75·778 USDI-NPS

Pasayten Wild 505,524 90·544 USDA-FS
Public Law federal Land

State Area Name Acreage Establishing Manager

581.435 West Virginia. Dolly Sods Wild 10,215 93-622 USDA-FS

Otter Creek Wild 20,000 93-622 USDA-FS

$81.436 Wyoming. Bridger Wild 392,160 88-577 USDA-FS

Fitzpatrick Wild 191,103 94-567 USDA-FS

Grand Teton NP 305,504 81-787 USDI-NPS

North Absaroka Wild 351,104 88-577 USDA-FS

Teton Wild 557,311 88-577 USDA-FS

'¢':~~~~:o~~I~pa 686,584 92-476 USDA-FS 2,020,625 17 Stat. 32 USDI-NPS

(42nd long)

a Yellowstone National Park, 2,219,737 acres overall, of which 2,020,625 acres are in Wyoming, 167,624 acres are in Montana, and

31,488 acres are in Idaho.

581.437 New Brunswick, Roosevelt Campobello

Canada. International Park

2,721 88-363 Not applicable