PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
EXECUTIVE SUMMARY AND CHAPTER 1
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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 long-
term 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
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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:
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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.
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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 two-
thirds 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.
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BURNING, FOREST PRODUCTS
AGRICULTURALLY/ J\iS
ACTIVITIES
- GENERALLY DESIRABLE VISIBILITY
- SOME UNDESIRABLE CONDITIONS
- FREQUENT UNDESIRABLE CONDITIONS
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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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.
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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.
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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:
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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.
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 862 to light scattering sulfate has been
observed in both Eastern and Western plumes.
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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 NC>2 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.
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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,
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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
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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:
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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 cost-
effective 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.
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Air quality standards and new source performance standards have halted the general
trend toward increased sulfur oxide, paniculate, 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.
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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.
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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." (95* 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 man-
made 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" (95*
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
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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.
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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
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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 of 156 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
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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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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" (NFS, 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
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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
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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
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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.
I A.22. 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
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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,
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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
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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 l-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 NC>2 gas and/or particle
scattering.
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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
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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.
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37
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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.
38
-------
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.
P: Based on photograp
photometry data
H: Based on nephelometry da
*: Based on uncertain extrapolati
visibility frequency distribution
Figure 1-10. Median yearly visual range (miles) and isopleths for suburban /non-
urban 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
39
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summer, with mixed increases and decreases. Visibility increases, however, during the
summer in the Pacific Northwest.
1525
P: Based on ;;hctographir.
pnotometry data
N: Based on nephelometry data
*: Based an uncertain extrapolation of
visibility frequency distribution
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.
40
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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, USD A 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.
41
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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. , RJ. 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., RJ.
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., RJ. Loomis and T .C. Greene (technical
coordinators). Fort Collins, Colorado, U .S. Department of Agriculture, p. 100-105.
Fox, D., RJ. 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, MJ. 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, RJ. and T.C. Green (1979). Air Pollution, Values and Environmental Behavior.
In: Proceedings of the Workshop in Visibility Values, Fox, D., RJ. 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., RJ. 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.
42
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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., RJ. 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., RJ. Loomis and T .C. Greene (technical
coordinators). Fort Collins, Colorado, TJ.S. Department of Agriculture, p. 93-99.
43
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PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
CHAPTER 2
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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
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
-------
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.
CHARACTERISTICS QFOBSiflWR
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Figure 2-1. Vision in the atmosphere.
The physiology of threshold contrast detection is illustrated in Figure 2-2, showing a
bright horizon (I + AI) against which a "hazy" mountain (I) is being detected. Laboratory
experiments indicate that for most daylight viewing intensities, contrasts (AI / I+AI) as
low as .018 to .03 (1.8 to 3 %) are perceptible (Figure 2-3).
-------
I + Al (sky I
pulses per second
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 + AI) (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.
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Figure 2-3. The minimum perceptible (threshold contrast AI/AI 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).
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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 eye-
brain 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
-------
but remains constant (at about 0.3%) for larger targets. The moon and sun occupy about
30 minutes of arc.
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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.
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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).
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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 |im
(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 1'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
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that have the same numerical specifications will appear alike to the standard observer
under standard viewing conditions.
0.1 s-
0.1 0.2 0.3 0.4 0,5 0.6 0,7 0.8
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 AE, which is a function of the
change in light intensity or brightness (AL*) and the change in chromaticity (Ax, Ay), AE
can be considered as a distance between two colors in a color "space" such that equal
distances (AE) between any two colors correspond to equally perceived color changes. It
is possible that a threshold, AEo, can be found to determine whether a given color change
is perceptible. Latimer et al. (1978) have calculated threshold values of AE for visible
plumes, but he applicability of this system for quantifying perceptible atmospheric
discoloration has not yet been experimentally verified.
-------
Factors other than that specified by AE (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).
Y 0.4 -
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:
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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.
-dl = bextldx (2-1)
Where -dl = 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
10
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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:
= bext
jQv(0v)I(v)dQjdx
(2-2)
Where dl = the increase in intensity form added air light
bext = the extinction coefficient
11
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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 £
Qv), and illumination intensity and angle (Iv, 0V) summed over all directions (Q).
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 (dl) is thus:
dl = -dl (extinction) + dl (air light) = - bext [I dx + W JQV (6V) I(v) dQ 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 (C0) 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 = C0 (Bxbextx/Bo) (2-4)
Where C = apparent contrast at observer distance
C0 = 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
12
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<£
CD
LIGHT tNTENSITV OF HORIZON
OBJECT
OBJECT-OBSERVER DISTANCE
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 = (-l)e-bextx
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 ~bext 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
13
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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.
ui
o
u
o
E
UJ
5
0.50
0.40
0.30
0.20
0.10
0,05
0.03
10
20
50 100
VISUAL RANGE, km
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.
14
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"MIXING LAYER" CONTAINING HIGHER POLLUTION
OBSERVER
TARGET (1)
SO km
TARGET (2)
355km
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).
OBSERVER
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).
15
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Detail of
objects
Very coarse
(Form)
Coarse
(Line)
Medium
(Texture)
Fine
(Texture)
Angular size
(minutes)
>30'
17-30'
9-17'
<9'
Characteristics
sizes at 10 km
(m)
> 100
50-100
25-50
<25
Examples for
a hillside at
10km
Hills,
valleys,
ridgelines
Cliffs faces
smaller
valleys
Clumps of
large
vegetation,
clearings on
forested
slopes
Individual
large trees,
clumps of
small
vegetation
Visual range (km)
West
Vr= 100km
79-100
76
62
22
East
Vr = 20 kmb
16-20
15
12
4
Table 2-1. Visual Range of Contrast Detaila. "Based on calculations using MTF
model of eye-brain response and mathematical transformation of scenic features
into a spatial frequency (Henry, 1979). bVR 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 + b
Jap
Where bRgis Rayleigh scattering by air molecules;
bag is absorption by NC>2 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., I/mile. The
16
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most commonly used units are km"1 and (lO'Vf1). 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 um), 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 um, 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
17
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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).
10*
Figure 2-13. Rayleigh scattering by air (bug) is proportional to (wavelength)4
Reduced air density at higher altitudes causes a reduction of bug. The NOi
absorption band peaks at 0.4 |im 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
um), the scattering and absorption of individual particles can be calculated through use of
the "Mie" equations (Mie, 1908).
DIFFRACTION
PHASE SHIFT
Figure 2-14. Light scattering by coarse particles (>2|im) 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
18
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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 |im), 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.
10
1 1 M HIM
~^~r
SCATTERING
.01 .02 ,05 .1 .2 .5124
DIAMETER, um
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 |im (m = 1.5 - 0.051; wavelength: 0.55|im). 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 |im 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 um 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 um 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 um 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
19
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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 um and a coarse mode centered at 5 to 30 um. 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.
6
*
CM
I 4
«
5
o
? 2
oc
LU
5
L>
mm
I I ITTTn
10V
10'1
10°
10
DIAMETER,
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 |im, while the spheres of pure carbon or iron
are most efficient scatterers at 0.2 |im (Faxvog, 1975). Carbon is te most efficient
light absorbing substance, and hence 0.2|im 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
20
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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 um coincides with the peak in observed
aerosol volume (mass), so that the fine particles dominate extinction in most cases.
21
-------
3.0
zo
TT
I I I II I TT
— I
ESTIMATED
1,0
FINt
COMPOSITION
SWLFATSS,
ORGAMICS,
AMMONIUM,
NITRATES, CARBON.
LEAD AND SOME
T RACE CONST ITUEN TS
RCIAIISL MODF
COMPOSITION
CRUSTALMAItHini.
SILICON CUMPULJNDS
IRON ALUMINUM
SEA SALT, PLANT
PARTICLES
ESTIMATED
.001
PARTICLE DIUWETEft, MICRONS
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).
120
10€ —
TJ
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).
22
-------
0.01
0.1 1.0
PARTICLE DIAMETER,)
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 |im. 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 um (Figure 2-20).
0.10 F
E
o
r*
Is
s
0.01
0,001
U—ACCUMULATION
MODE COARSE.
MODE
0.1
1.0
DG
10.0
Figure 2-20. The light scattering per unit volume for various aerosol size
distributions (eg) is the highest in the 0.2 - 1.0 |im 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
23
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Wagman, 1978, Macias et al., 1975, and White and Roberts, 1975). These investigators
measured scattering per unit mass ratios of 0.003 km'Vug/m3 to 0.005 km'Vug/m3 at
several locations. The Mie calculations of Figure 2-19 suggest a ratio of 0.0033 km"
Vug/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 wind-
blown 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'Vug/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 |im to wavelength independent
to "white" scattering for coarse particles > 5 |im. Thus Rayleigh particles (<0.05|im) 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 km"
!), an addition of about 4 |ig/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 |im/ 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).
24
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40
ST. LOUIS AEROSOL
APRIL, 1975
FINE PARTICLE MASS (uQ.'m")
4/17
4/18
4/19 4/20
TIME (days)
4/22
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.
25
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bRg - 0.01 knr1
hext;FINE MASS - 0,004 km '
-------
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 |ig/m3 increment of fine particles.
A similar increment in a relatively polluted area (20 |lg/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 |ig/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 |ig/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
27
-------
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 NC>2 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 30°. 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.
28
-------
\\\\
R fur" i^-twrwrarn "S
1 1 uin tE hlrib kSWIWCi: «R ^ 1C*T Tit BEIhfl LHi rJJUi ITiEI
: T fl»! CUBE V ! H M M P BCT v 1.1
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 30°. 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.
29
-------
Additional experimental data are needed to define the threshold of perceptibility for
plumes and haze layers.
BACKGROUND
LUMINANCE
VIEWING
BACKGROUND
SCATTERED
SKYLIGHT
OBSERVER
Figure 2-25. Appearance of a plume (Charlson et al., 1978).
30
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Plume/source related factors
Particle size distribution
Particle mass concentration
Particle mass distribution (non-uniform
mass distribution)
Plume diameter
Stack height
Stack exit velocity
Particle density
Water vapor content
Particle complex index of refraction (plume
color)
NC>2 concentration in the plume
Observer related factors
Observer position
Observer sensitivity
Environmental Factors
Sun position
Time of day
Day of year
Longitude
Latitude
Cloud cover (sky color)
Other light sources
Ambient temperature
Relative humidity
Wind velocity
Wind direction
Wind turbulence
Terrain
Background
Table 2-2. Factors affecting plume appearance (Charlson et al., 1978).
31
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REFERENCES FOR CHAPTER 2
Allen, J., R. B. Husar, and E. S. Macias (1978) In: Aerosol Measurement, Lundgren,
D.A. Ed., University of Florida Press, Gainesville, Fla.
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. Thielke, (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.
32
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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-450/3/78-1 lOa.
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.
33
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Niemann, B. L., E. Y. long, M. T. Mills and L. Smith (1979) Characterization of
Regional Episodes of Paniculate 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 Visibility-
Reducing 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.
34
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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.
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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, forward-
scatter 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.
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TABLE 3-1. VISIBILITY MONITORING METHODS"
Method
Parameters Measured
Advantages
Limitations
Preferred Use
Human observer
Integrating nephelometer
Perceived visual quality
Atmospheric Color
Plume blight
Visual range
Scattering Coefficient
at site
Multiwavelength
telephotometer
Sky and/or target
radiance, contrast at
various wavelengths
Transmissotneter
Long path extinction
coefficient (bext)
Flexibility, judgment;
large existing data base
(airport visual range).
Continuous readings;
unaffected by clouds,
night; b^gf directly
relatabte to fine aerosol
concentration at a point;
semi-portable; used Jn a
number Of previous studies;
sensitive models avail-
able; automated.
Measurement over long
view path (up to 100 km)
with suitable illumination
and target, contrast
transmittance, total ex-
tinction, and ehfomati-
city over sight path
can be determined; in-
cludes scattering and
absorption from all
sources; can detect
plume blight;automated.
Measurement over medium
view path (10-25 km);
measures total extinction,
scattering and absorption;
unaffected by clouds,
night.
Labor intensive; variability
in observer perception;
suitable targets for visual
range not generally
available.
Point measurement, requires
assumption of homogeneous
distribution of particles;
neglects extinction from
absorption, coarse particles
>3 to 10 urn; must consider
humidity effects at high RH.
Sensitive to illumination
conditions: useful only
in daylight; relationship to
extinction, aerosol re-
lationship possible only
under cloudless skys; re-
quires large, uniform
targets.
Calibration problems; single
wavelength; equivalent to
point measurement in areas
with long view paths (50-
100 km); limited appli-
cations to date still
under development.
Complement to instru-
mental observations;
areas with frequent
plume blight, discolor-
ation; visual ranges
available target
distances.
Areas experiencing
periodic well mixed
general haze; medium
to short viewing
distances; Email
absorption coefficient
(babs); relating to
point composition
measurements.
Areas experiencing
mixed or in homogeneous
haze, significant
fugitive dust; medium
to long viewing dis-
tances (% of visual
range); areas with
frequent discoloration;
horizontal sight path.
Areas experiencing
periodic mixed general
haze, medium to short
viewing distance areas
with significant
absorption (babs).
ce
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TABU; 3-1. VISIBILITY MONITORING METHODS- (continued)
Photography
Visual quality
Btume blight
Color
Contrast (limited)
Related to perception
of visual quality ;
documentation of vista
conditions.
Sensitive to lighting
conditions; degradation
in storage; contrast
measurement from film
subject to significant
Complement to human
observation, instru-
mental methods; areas
with frequent plume
blight, discoloration .
Particle samplers
Particles
Permit evaluation of
bif impairment.
Not always re I stable
to visual a\r quality;
point measurement.
Complement to visi-
bility measurements.
H»Vof
• ./•'.. -.•
Cascade impactor
Dichotomy* and
fine particle
samplers (several
fundamentally
different types)
TSP
Size segregated
particles
(=> 2 stages)
Fine particles
(<2.5um)
coarse particles
[2.5 to 15 um)
m rial able particles
(0 to 15 um)
Large data base.
amertabte to chemical
anaf^sis; Coarse
p^rt&tejariatysls.
•- th^pj chemical, size
' '•''' 'eva^Stiort. '
.' . ' ""::v" '?':" ..':'.- '
' -''Sfee cut Enhances reso -
lotion, optically im-
portant aerosol analysis.
low artifact potential.
particle bounce; amenable
to automated composi-
tions I' analysis; auto^ :
mated yersfons avaif-
abte; large networks
under development.
Does not separate sizes;
sampling artifacts for
nitrate, sulfate; not
automai^a*.
Particle bounce, wall
losses; labor intensive.
Sorne large^pa rticfe pene-
tration, -24 hour
or longer sample required
in clean areas for mass
measurement; automated
'version relatively un-
tested in remote locations.
Not useful for visi-
bility sites.
Detailed studies of
scattering by particles
< 2 urn.
Complement to visibility
measurement, source
assessment for general
haze, ground levsi plumes.
'
"
a(Oiarlson eta!., 1978;Malm, 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 visibility-
related 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.
-------
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Figute 3-1. Project VIEW — EPA/NPS Southwest visibflity monitorin* network.
3-8
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SEPTEMBER, 1378
Figure 3-2. Ikrget eontraat at Canyonlmds National Park, Utah, for September, 1978 (Maim, 1979b).
-------
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. I, 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
-------
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 |im 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 NC>2 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
-------
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 receptor-
oriented, 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 source-
receptor-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.
-------
4.2.1 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.
r,ow.
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 jim) and coarse (> 2.5 jim) mode
-------
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 size-
chemical 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 |ig/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).
-------
FY>3
PbO OS
OTHER
OTHER
FINE PARTICLES
MASS = 33.4 vg/m3
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).
COARSE PARTICLES
MASS = 27.1
-------
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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.
DOWNTOWN
TOTAL SUSPENDED PARTICULATE, pwewit
(78 ftfl/m'l
VOLATIZABLE CARBON 1.4
PRIMARY INDUSTRIAL 1.7
VEGETATIVE BURN l.B
MARINE 2.2
AUTOMOTIVE EXHAUST 0.8
,H ESI DUAL OIL 0.1
DUIT 19.1
GEOLOGICAL (SOIL, DUST, 17.5
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NONVOLATIZABLE CARBON 0.7-
VEOETATIVE BURN B.7
AUTOMOTIVE EXHAUST 5.9
UNIDENTIFIED £3
PHRMARY INDUSTRIAL 2.9
VOLATIZABLE OAR BOH 1.6
SULFATE l.B
NITRATE 1.5
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FINE FRACTION, pwant
RESIDUAL OIL DL$
PRIMARY INDUSTRIAL l.S
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NONVOLATIZABLE CARBON 1.1
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AUTOMOTIVE EXHAUST 12.3
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VOLATIZABLE CARBON 3.4
SULFATE 3.S
NITRATE 2,5
- NONVOLATIZABLE CARBON 1.7
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.
-------
60 -
TOTAL PARTICULATE
FINE PARTICULATE
SOILS
40 -
20 -
-
"
CARB
-. SULFATE
MARINE 1 AUTO °™*R
_ 1 1 n IONS
•I Jl Jl jn
DM
ACEOUS
O
TH
m
ER
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 Hi-
Volume 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.
COARSE PARTICLES
MASS
f(Ht PARTICLES
MASS - 5.3 (J9/">3
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.
-------
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
Air Molecules
(NH4)2S04a
Si02b
Other
compounds
Coarse Particles
Particle Size
(Mm)
0.1 to 1.0
0.1 to 1.0
0.1 to 1.0
1.0 to 20.0
bsca^km"1)
0.011
0.007
0.004
0.002
0.001
Contribution to
Total bscat
44
28
16
8
4
Contribution to
Extra
Extinction0
50
29
14
7
Table 4-1. Light scattering budget for the Southwest Region, October 9, 1977
(Visual range approximately 160 km) (Macias et al., 1979). "Assumes all fine
particle sulfate exists as ammonium sulfate. bAssumes that all fine particle silicon
exists as SiOi. cExtra 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 = b0 + b! SULFATE + bz NITRATE + b^ (TSP-SULFATE-NITRATE) (4-1)
10
-------
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 (|ig/m3) and NITRATE (|ig/m3) levels are
usually adjusted to account for associated ammonium; TSP-SULFATE-NITRATE
(|lg/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 (l-RH)a 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 a of 1.0; Cass (1976) considered a of .67 to
1.0, while White and Roberts (1977) used other approaches to account for humidity.
Multiple regression analysis selects the coefficients b0 through bs 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-and-
effect. 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, bi/(l-RH)a to b3/(l-RH)a 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"V|lg/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 [km"
V|lg/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 |im)
(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
11
-------
0.0008 [km~V|lg/m3] (Latimer et al., 1978; White and Roberts, 1977; Ursenbach et al.,
1978).
Location
Southwest (Trijonis and
Yuan, 1978a)
Phoenix: County Data
NASNData
Salt Lake City
Los Angeles (White and
Roberts, 1977)
Various Locations'3
(Cass, 1976)
Downtown Los Angeles
(Leaderer and Stolwijk,
1979)
Los Angeles Airport
Northeast (Trijonis and
Yuan, 1978b)
Chicago
Newark
Cleveland
Lexington
Charlotte
Columbus
(Leaderer and Stolwijk,
1979)
New York b
New York
New Haven
St. Louis
Extinction coefficients per unit
Aerosol mass (km^/jig/mS
Sulfates
Nitrates Remainder of
TSP
0.004
0.003
0.004
0.004C
0.007
0.006C
0.017
0.009C
0.016
0.004
0.003C
0.002
0.006C
0.008
0.007C
0.006
0.006C
0.011
0.011C
0.012
0.013C
0.007
0.010
0.016
0.008
0.005
0.003
0.013
0.010C
0.005
0.004C
0.004C
0.005C
0.003
(NPd)
(NPC)
(NP)
(0.000C)
(NP)
(NPC)
(NP)
(0.004C)
(NP)
(NPC)
0.009
0.006
0.005
(0.006)
(NP)
(NP)
0.000
0.000
0.0004
(0.0004C)
0.0015
0.0020C
0.0008
0.0004C
0.0004
(NP)
(NPC)
0.0026
0.0014C
(NP)
(NPC)
(0.0001)
0.0019C
(0.0001)
(0.0000)
(0.0004)
(0.000 19C)
(NP)
(0.0001)
(0.000)
(NP)
Total correlation
Coefficient(R)
associated with the
regression a
0.87
0.68
0.72
0.81
0.60
0.72
0.76
0.76
0.91
0.48
0.52
0.67
0.71
0.70
0.72
0.68
0.72
0.67
0.73
0.81
0.90
0.88
0.76
0.90
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
12
-------
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. 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.
0,06
A THEORtTlCAUY CM.CUI.AltDVALUES
O EMPIRICAL VALUES
(TRIJOWIS AMD YUAN, 1S7Sn).
A
O
g
PELATIVE HUMIDITY
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 "bi (average SULFATE) /(l-RH)a"
in Equation 4-1 would indicate the average contribution of sulfate aerosols to extinction.
13
-------
The term "b0" is assumed to represent Rayleigh scatter plus contributions to extinction
that are unaccounted for by the regression.
Location
Southwest
(Trijonis and Yuan, 1978a)
Phoenix
Salt Lake City
Los Angeles
(White and Roberts, 1977)
Various Locations b
(Cass, 1976)
Downtown Los Angeles
(Leaderer and Stolwijk,
1979)
Los Angeles Airport
Northeast
(Trijonis and Yuan, 1978b)
Chicago
Newark
Cleveland
Lexington
Charlotte
Columbus
(Leaderer and Stolwijk,
1979)
New York b
New York
New Haven
St. Louis
Average °
Average percent contributions to extra extinction a (%)
Sulfates
53
34
31
46
30
27
42
55
32
59
68
67
74
81
51
53
Nitrates
37
31
27
0
11
0
0
0
0
0
8
14
0
0
0
8
Remainder of TSP
0
35
42
15
0
0
38
0
44
0
0
0
0
0
0
12
Unaccounted for
10
0
0
39
9
73
20
45
24
41
24
19
26
19
49
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
14
-------
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 |im 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.
15
-------
Potential errors in Hi-Vol measurements of sulfate and nitrate are another important
problem. "Artifact" sulfate (formed by 862 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
16
-------
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,
17
-------
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.
Trend Feature
Suburban/no nu
rban areas
Metropolitan
areas
Summer (third
quarter)
Winter (first
quarter)
Best-case
Areas
Worst-case
Area
Parallel between visibility
and sulfate trends
(Early 1950s - early 1970s)
Visibility decreased
substantially at
suburban/no nurban
locations
Visibility changed very
little at metropolitan
locations.
Visibility decreased
dramatically during the
summer. By the early
1970s, the third quarter
became the worst season
for visibility.
Visibility changed little
during the winter.
The only region of the east
exhibiting an improvement
was the Northeast
Megapolis Area
surrounding New York
City.
The greatest decline in
visibility occurred in the
central/eastern states.
(Early/mid 1960's -
early 1970s)
Sulfates increased
substantially at
suburban/nonurban
locations
Sulfates changed
very little at
metropolitan
locations
Sulfates rose
dramatically during
the summer. By
early 1970s, the third
quarter became the
worst season for
sulfates.
Sulfates changed
little during the
winter.
The only region of
the east exhibiting a
decline in sulfates
was the Northeast
Megapolis Area
surrounding New
York City.
The central/eastern
region was one of the
areas showing the
largest increase in
sulfates.
Potential explanation in terms of SOX
emission trends (early 1950s - early
1970s)
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.
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.
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.
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.
The only region showing a significant
decline in SOX emissions was the far
Northeast (the Northeast Megapolis Area
and New England).
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
18
-------
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.
175
150 -
1940
70
YEAR
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
19
-------
to sulfate and nitrate concentrations) increased substantially in the East from 1955-1956
to 1972-1973 (Likens, 1976).
JFMAMJJASOND JFMAMJJASOND
MONTH MONTH
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
20
-------
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.
MONT
IDAHO
WYO
NEV
UTAH
COLO
AN \1
NEWM
ID
1990 tO 70
YSAfl
*0 TO
YEAR
ID 10 BD 1BEQ 6O TO
YtAH YEAH
60 70 6O
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).
21
-------
160
125
uz 75
jcO
P
26
4.0
3.0
2.0
1.6
I I ] J ] i i ] I ] I ] i I ] i i i I i ri ] I ] ] M I i i i ] 11 i i i I i i i i I ri H I.' IJJ '" " J 0.5
1940 SO ' 60 70 80 90 3000
YEAR
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
22
-------
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.
( THE DOTS REPRESENT YEARLY PERCENT OF HWJRS WITH REDUCED VISIBILITY
(MEASURED ON LEFT AXIS). NOTE THAT THE TUCSON OBSERVATION SITE MOVED
IN 155S; ALTHOUGH THIS MCWE DID MOT PROOLJCF a STATISTICALLY siGNlFlOANn
CHANGE IN REPORTED VISIBILITIES, OPEM DOTS ARE USED TO DISTINGUISH DATA
1958.
- THE LINES REPRESENT YEARLY 5U EMISSIONS FROM Aai70WA COPPFB SMELTERS
(MEASURED ON RIQHT AXIS1.
KS 20
us
CL>
0 0
3000 £ a
ll
anno <
1
2000 I
55 BO
70 7S
PS 7D —
S>
L > ao
SI 55 Bo 95
19 75
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).
23
-------
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
Tucson (1950-1975)
Tucson (1959-1975)
Phoenix (1959-1975)
Winslow (1948- 1973)
Prescott (1948- 1975)
Prescott( 1949- 1969)
Correlation
Coefficient
0.91
0.88
0.81
0.68
0.70
0.70
Regression
Coefficient
extinction/emissions
km'V(1000 TPD)
0.0035
0.0038
0.0041
0.0047
0.0031
0.0039
t-Statistic
(t> 1.7 for 95%
confidence)
(t 2.5 for 99%
confidence
11.1
7.2
5.4
4.5
5.0
4.4
Table 4-5. Correlation/regression analysis between airport extinction and copper
smelter SOx emissions (Marians and Trijonis, 1979).
24
-------
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.
O
n
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
25
-------
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.
D
SCALE WILE*)
URBAN AIRMBTS
N ONUS6AN Al RPORTS
- Z50 TONS^OAY BO?
100 200
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.
26
-------
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.
5D
ta
a
2
Uf
u
-------
visibility data and sulfate data implied an extinction/emission coefficient of 0.001 to
0.003 km"V(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"V(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 km"
V(1000 tons per day SOX). AS indicated by the qualified wording, however, these latter
three conclusions are regarded as tenuous.
30
FREQUENCY DISTRIBUTION OF SULFATE
• DURING THE COPTER STRIKE, JULY 1967-MARCH 19B»
(34MiASUHEMENTS AT GRAND CANYON OR MESA VERDE)
LJ
FREQUENCY DISTRIBUTION OF SULFATE
FOR JULY-MARCH SEASON IN FOUR YEARS
SURROUNDING THE COPPER STRIKE
(142 MEASUREMENTS AT GRAND CANYON OR MESA VERDEI
2.8
3.6
6.0
SULFAT6 ((i g/inj>
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 |ig/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
28
-------
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 central-
eastern 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.
OUAHTEFI3
QUARTER 3
3. _
0 lii
d _
194D 1960 1960 1970 1980
CENTRAL/EASTERN STATES
1940 1950 1960 1370 1080
NORTHEAST MEGAPOLIS AREA
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,
29
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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
30
-------
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.
100
X
3°
a*
1
i!
u- <
O -3
40
\/
._ 1949-W56
1967-19*6
— 1967-1976
—0 JULY 1967-MARCH 1968 ICOPPER STRIKE*
• WIND DIRECTIONS ASSOCIATED WITH
SIGNIFICANTLY IMPHW1O VISUAL RANGE
I AT THE 9S PERCENT CONFIDENCE LEVEt)
MfH EN COMPARED WITH THE HEMAINDE R OF
THE OECADE 1967-1978
I
J_
I
I
J_
N NNE NE ENE
E8E SE !SE 3 S5W SW WSW W WWW NVK NNW
WIND DIRECTION
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).
31
-------
Ill
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,
32
-------
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.
33
-------
s
I
I ,
u
*
s
II J 4 6 S 10 IS 11 16 18 20 71 II
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 SOi 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.
34
-------
Figure 4-21. Horizontal profiles of SOi 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).
I
u .04
S
oo«
O LABADIE
• FOUR CORNERS
.8 ° o
o ° d
i
BO 100 150
DISTANCE FROM STACK, km
Figure 4-22. Average plume excess bscat measured during flights through the
Labadie and Four Corners power plant plumes (MRI, 1976; EPRI, 1977).
35
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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 SC>2 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
36
-------
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
San Manuel Smelter
(NH4)2SO4a
Si02b
Other compounds
Coarse particles
Mohave Power Plant
(NH4)2SO4a
Si02b
Other compounds
Coarse particles
Particle Size (|im)
(62 km downwind)
0.1 to 1.0
0.1 to 1.0
0.1 to 1.0
1.0 to 20.0
(32 km downwind)
0.1 to 1.0
0.1 to 1.0
0.1 to 1.0
1.0 to 20.0
bscatc (km"1)
10/4/77
0.041
0.0095
0.0055
0.039
0.095
10/8/77
0.003
0.002
0.001
0.021
0.027
Contribution to total
particle scattering (%)
43
10
6
41
100
11
7
4
78
100
Table 4-6. Plume excess visibility budget. "Assumes that all fine particle sulfate
exists as ammonium sulfate. bAssumes that all fine particle silicon exists as SiOi.
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 paniculate 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.
37
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Source
Labadie Power
Plant3 (St.
Louis)
Four Corners'5
Power Plant
(New Mexico)
San Manuel0
Smelter
(Arizona)
Mohave0
Power Plant,
(+ wind blown
dust)
SOX
emission
(tons/day)
880d
250d
557
66
Down
wind
distance
(km)
40-60
150-
200
50
8
32
60
127
32
60
Plume
width
(km)
20
60
25
16
20
25
54
8
27
Plume
excess
light
scattering
(km'1)
0.030
0.050
0.020
0.283
0.092
0.095
0.050
0.018
0.033
Visibility perpendicular to plume (through plume)
(From experimental data)
Visual Range
With
Plume
(km)
28
23
50
12
45
46
36
104
84
Backgr
ound
(km)
30
30
55
85
85
120
120
110
110
Visual
range
reduction
due to
plume
(%)
7
23
10
86
47
62
70
5
24
(Normalized to "clean"
background)
Visual Range
With
plume
165
56
170
12
103
76
80
191
150
Backgr
ound
195
195
195
195
195
195
195
195
195
Visual
Range
reduction
due to
plume
(%)
15
70
13
94
47
61
69
2
23
Table 4-7. Aircraft measurements of plume visibility impacts. "Typical values
for July 9, 11, 1979; see Figure 4-2 (MRI, 1976). bTypical values for July 10, 1976;
see Figure 4-2 (EPRI, 1976). cExcess 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).
38
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POWER PLANT
REFINERIES
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.
50
150
DISTANCE DOWNWIND (km)
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 (Os), 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.
39
-------
Ihi.
Jhr.
3 dr.
ARFfl
Mf AN TRANSPORT WIND
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 long 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
40
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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 |lg/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."
41
-------
J» '
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:
42
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1. Do the hazy air mass and the meteorologically defined anticyclone completely
coincide?
2. How may the effects of superimposing multiple SC>2 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.
43
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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
NC>2 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
44
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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 developed by Eliassen and Saltbones (1975), Fisher (1978), and Johnson et al.
(1978).
Characteristic
Fraction of emitted sulfur deposited locally
Fraction of emitted sulfur transformed
directly to sulfate
Decay rate of sulfur dioxide
Rain
Dry
Transformation rate of 862 to sulfate
Loss rate of sulfate
Mixing height
Value
00.15
00.05
14.4%/hour
03.6%/hour
01.26%/hour
01.44%/hour
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).
45
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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.
46
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REFERENCES FOR CHAPTER 4
Altshuller, A.P. (1976) Regional Transport and Transformation of Sulfur Dioxide to
Sulfates in the U .S., J. Air Pollut. Control Assoc. 26: 318-324.
Bammel, E. and L. L. Bammel (1978) Leisure Research Program, Division of Forestry,
West Virginia University. Morgantown, West Virginia.
Barone, J.B., T .A. Cahil, R.A. Eldred, R.G. Floccltini, DJ. Shadoan, andT .M. Dietz,
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Bradway, R.M. and F .A. Record (1976) National Assessment of the Urban Particulate
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Brosset, C., K. Andreasson and M. Ferm (1975) The Nature and Possible Origin of Acid
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Cass, G.R. (1976) The Relationship Between Sulfate Air Quality and Visibility at Los
Angeles. Caltech Environmental Quality Laboratory Memorandum No. 18. Pasadena,
California.
Charlson, R.J., A.M. Vanderpol, D.S. Covert, A.P. Waggoner, and N.C. Ahlquist (1974)
M2SO/(NM4) 2SO4 Background Aerosol: Optical Detection in St. Louis Region,
Atmospheric Environment 8: 1257-1267.
Chung, Y .S. (1978) The Distribution of Atmospheric Sulfates in Canada and Its
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1471-1480.
Clark, W .E., D.A. Landis, and A.B. Marker (1976) Measurement of the Photochemical
Production of Aerosols in Ambient Air Near a Freeway for a Range of SO2
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Cooper, J.A., L.A. Currie, and G.A. Klouda, (1979) Application of Carbon 14
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Cooper, J.A. and J.G. Waston, (1979) Portland Aerosol Characterization Study (PACS).
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Dzubay, T .G. (1979) Chemical Element Balance Method Applied to Dichotomous
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47
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Electric Power Research Institute (1977) Oxidant Measurement in Western Power Plant
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Eilassen, A., and J. Saltbones (1975) Decay and Transformation Rates SO2 as Estimated
from Emission Data, Trajectories and Measured Air Concentrations. Atmospheric
Environment 9: 425-429.
EPA (1975) Position Paper on Regulation of Atmospheric Sulfates. Publication No. EPA-
450/2-75-007, U.S. Environmental Protection Agency, Research Triangle Park, N.C.
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,
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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., PJ. Samson, E.G. 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
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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 SC>2 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.
48
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Hidy, G.M., et al. (1975) Characterization of Aerosols in California Report SC 524.25FR
4 California Air Resources Board, Contract 358, Rockwell Science Center, Thousand
Oaks, Calif.
Hidy, G.M., P.K. Mueller, and E.Y. long, (1978) Spatial and Temporal Distributions of
Airborne Sulfate in Parts of the United States. Atmospheric Environment 12: 735- 752.
Holzworth, G.C. (1967) Mixing Depths, Wind Speeds and Air Pollution Potential for
Selected Locations in the United States, J. Appl. Meteorol 6:1039-1044.
Holzworth, G.C. (1972) Mixing Heights. Wind Speeds and Potential for Urban Air
Pollution Throughout Contiguous United States. Environmental Protection Agency,
Office of Air Programs Pub. No. AP-101. Research Triangle Park, N.C.
Husar, R.B., D.E. Patterson, C.C. Paley, and N. V. Gillani, (1976) Ozone in Hazy Air
Masses. Paper presented at the International Conference on Photochemical Oxidant and
its Control, Raleigh, N.C., Sept. 12-17.
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.
Husar, R.B., D.E. Patterson, J.M. Holloway, (1979) Trends of Eastern U.S. Haziness
Since 1948, Presented at the Fourth Symposium on Atmospheric Turbulence, Diffusion
and Air Pollution, Reno, Nevada, January 15-18.
Inhaber, H. (1976) Changes in Canadian National Visibility. Nature 260, March 11.
Isaksen, IS., E. Hesstvedt, and 0. Hov (1978) A Chemical Model for Urban Plumes:
Test for Ozone and Paniculate 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
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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,
M. A. Wojcik and M. J. Hillyer (1978). The Development of Mathematical Models for
the Prediction of Atmospheric Visibility Impairment. EPA 450/3-78-110a,b, c US EPA,
Research Triangle Park, N.C.
49
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Leaderer, B.P., D.M. Bernstein, J .M. Daisey, M.T. Kleinman, T J. Kneip, E.O. Knutson,
M. Lippman, PJ. Lioy, K.A. Rahn, D. Sinclair, R.L. Tanner, G. T. Wolff. (1978)
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Leaderer, B. P., T. R. Holford and J. A. J. Stolwijk (1979). Relationship Between Sulfate
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Lewis, C. W. and E. S. Macias, (1979) Composition of Size-fractioned Aerosol in
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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 Parti culate Sulfur.
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Lyons, C.E., I. Tombach, R.A. Eldred, P.P. Terraglio, and I.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 Synoptic-
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Visibility Reducing Aerosols in the Southwestern United States; Interim Report on
Project VISTTA. MRI Report 78 IR 15-85.
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under Grant 802015, for EPA Office of Air 4-49
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EPA Environmental Sciences Research Laboratory, Research Triangle Park, N. C.
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50
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Munn, R. E. (1973) Secular Increases in Summer Haziness in the Atlantic Provinces
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4-50
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52
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53
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PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
CHAPTER 5
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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
SOURCE (SI
-m~
ATMOSPHERIC
PROCESSES
1
a
t-
L i
>
OROLOG
i
^
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EFPECTS
i >
I
_
t J
ws
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HUM AN VISUAL
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f
ENVIFtONMSNTAL
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Figure 5-1. Grnrral viilhlllry model.
MlXINQ HEIGHT
PLUME fiUQHT
SO,
NO,
PARTI CLJLATE
SOURCE
' "--' ' UP TO
100 km,
MR BASIN TO REGIONAL SCALE
Figure 5-2. Mobility inipflhniem regiraes.
-------
Several Gaussian based mathematical models have been developed that predict the optical effects of a coherent
plume (Latimer et al., 1978; ERT, 1978; Williams et al,, 1979). These visibility models are oriented toward
emissions from individual point sources, auch as smelters and coal-fired power plants, and compute the optical
effects of primary fine particles, sulfate from sulfur dioxide emissions and nitrogen dioxide from nitrogen oxide
emissions.
10,000
(year)
o
H
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c
I
ui
s
o
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o
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, MODELS
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X
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\
\
\
\
\
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\
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\
\
\
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i I
1 10 100 1000 10,000
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Figure 5-3. Scales of time and distance. Approximate dimensions for applicable models.
Figure 5-4 illustrates the major components of visibility models, in this case the model developed for EPA. The
input requirements 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 of sulfur oxides and nitrogen oxides to pollutants that affect visibility. The direction and amount
of light scattered and absorbed by the particles and gases are calculated through approximations of the radiative
transfer equation (Section 2.3). The output of the models is a set of wavelength-dependent light fluxes, which are
then used for computation of more easily understood parameters representing the reduction of visual range and
discoloration of the sky through the plume, contrast of the plume (against the sky), and overall perception of the
plume.
5-3
-------
POLLUTANT CONCENTRATIONS X(ic, y. z, t)
EMISSIONS Q
-------
5.3.1 Display Formats
Two general kinds of formats have been developed for displaying the output of visibility models. The most
commonly used format 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 estimating distances
where maximum visual impacts could occur and for quantifying parameters related to visibility. Figure 5-5 shows
the graphical format used in displaying the EPA model.
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Figure 5-5. Example graphical format of single source-visibility model output (Latimer, et al., 1978),
A more dramatic format for displaying the output of visibility models has been developed by Los Alamos
Scientific Laboratory for the Department of Energy (Williams et al., 1979). This technique creates a computer-
generated simulation of a plume on a color television screen, To accomplish this simulation, a photograph of a
"clean" background vista (Figure 5-6a) is digitized according to color and brightness of different elements in the
picture (Figure 5-6b). 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 jUg/m3 and 26 /iig/m3, respectively, throughout the background
scene. The resulting haze and reductions in visual range and contrast are apparent.
5-5
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The computer simulated plume or haze picture is more readily useful for illustrating impacts than are
graphical outputs. Only one location can be depicted at a tune, however, and the extensive and sophisticated
hardware requirements are presently too costly to allow for routine simulation of many views and conditions.
Additional uncertainty is introduced in this technique because the elements of the original picture must be
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 represen-
tations may be misleading. Nevertheless, this promising display technique should be developed for more
routine use as visibility models are improved and our understanding of color perception increases.
5-6
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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 (NO,,). 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 NO%
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. NO% emissions resulting in NC>2 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 862 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.
-------
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perpendicular to the plume with sun overhead (90° light scatter).
5-8
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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 SO% 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 SO% 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 SC>2 to sulfate and NO% 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 NC>2 formation from different levels of ozone. The effect of
increased NO% 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 862 sulfate, and NC>2. 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 5-1 Od.
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.
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5-10
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5-11
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Western conditions average about 0,5% per hour and range from 0 to 2% per hour (Wilson, 1979),
5-13
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NOr Higher background ozone results in more rapid NO2 conversion and greater discoloration from NOr
In the WeBt levels of 0 to 0.06 ppm ozone are typical.
5-14
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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 fine-
particulate 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.
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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 SC>2 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.
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PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
CHAPTER 6
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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
Acadia
Big Bend (1200m)
Grand Cany on (2 100m)
Bryce Canyon (2500m)
Mt. McKinley (6000m)
Altitude
(m)
Sea Level
1000
2000
3000
4000
Rayleigh
Scatter3 (km'1)
0.012
0.011
0.010
0.009
0.008
Potential
Visual Range
(km)
337
371
410
453
503
Contrast
-0.49
-0.51
-0.54
-0.56
-0.59
Table 6-1. Rayleigh Scattering by clean air. "Rayleigh scattering coefficient for O.SS^im light
(roughly green). Scattering for 0.400^im (blue)) at sea level is 0.042 km"1. Scatttering at longer wave
lengths is much smaller. bApparent 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 particle-
free 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.
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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 visibility-
impairing 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 |lg/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).
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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.
-------
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 (|im) 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 |im. 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 |ig/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 |im
in diameter.
I
o
1.9x10
9.5x10
1.1x10'
55x10
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 nm
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
-------
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.
O PACIFIC CCWSTfmUQH
Q HQCKV HCHJNTAiPU ftESlQf*
a ttOftTH CtMT«Al REGION
-------
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 |im 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).
II"
t£
< LU
-I O
122S 1227 1229
TIME (PST)
0 B
1 I i ,..,_._)
SCALE (km)
(PST)
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
-------
constituting less than one percent of the total number of occurrences consume about two-
thirds 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 (802).
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 |im. 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,
-------
and sun conditions, these vegetative emissions estimates should be considered only as
rough approximations.
GRASSLAND
SCLE ROPH Y L L SCRUB
fleC'OUQUS FOREST
fttOUS FOREST
TEMPEFrAtF RAIN FOREST
DESERT
TUNDRA, ALPIWE FIELDS
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 |im/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 |im). 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.
-------
Biotic Region
Grassland
Total
Schlerophyll
Scrub
Total
Temperate
Rain forest
Total
Deciduous
forest
Total
Coniferous
forest
Total
Desert
Total
Tundra, alpine
field
Total
Vegetation type
Conifers
Oaks
NC-NIb
Nor
LLd
Conifers
Oaks
NC-NI
NO-I
LL
Conifers
Oaks
NC-NI
NO-I
LL
Conifers
Oaks
NC-NI
NO-I
LL
Conifers
Oaks
NC-NI
NO-I
LL
Conifers
Oaks
NC-NI
NO-I
LL
Conifers
Oaks
NC-NI
NO-I
LL
Leaf bio mass,
g/m2
5
2.5
3.75
3.75
250
15
30
210
45
300
990
55
22
22
1100
135
180
90
45
450
559
39
26
26
650
25
25
40
10
100
18
0
9
9
180
Emission factors, |J,g/m2 - hra
Day
44.5
61.75
16.13
38.6
162
322.98
133.5
141
903
463
162
2402.50
8811
1385
94.6
226.6
162
10679.20
1201.5
4446.0
387
463.5
162
6660
4975.10
963.30
111.80
267.80
162
6480.00
222.5
617.5
172.0
103.0
162
1277
160.2
0
38.7
92.7
162
453.6
Night
44.5
11.75
16.13
9.00
162
243.38
133.5
141
903
24.72
162
1364.22
8811
258.50
94.6
226.6
162
9552.70
1201.5
4446.0
387
108
162
2704.5
4975.10
183.30
111.80
62.40
162
5494.60
222.5
117.5
172.0
24
162
698
160.2
0
38.7
21.60
162
384.3
Winter
17.5
0
0
0
0
17.5
52.5
0
0
0
0
52.5
3465
0
0
0
0
3465
473
0
0
0
0
473
1957
0
0
0
0
1957
88
0
0
0
0
88
63
0
0
0
0
63
Table 6-2. Vegetative volatile organic emission activities (Zimmerman, 1978). "Standardized to
30°C; bNC-NI = non-conifer, non-isoprene emitters; CNO-I = non-oak isoprene emitters; dLL = leaf
litter/soil, pasture.
10
-------
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 |im/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.
11
-------
ALL DAYLIGHT OBSERVATIONS
VI SI Bl LI TV > 80 km
IND SPEED
> 1fl m/t
WINDBLOW
DUSTI
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 NC>2 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
12
-------
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).
13
-------
i§-
.:•*•- 0-1 -«6."
>::3i^-^':>i-^i ,**t^*a
e.f-V--
-^- -_ :/.--- i^iSI/-!-^^-*^.'''^-*.*
:
--* :: -^i' ^"
_™^. 1,^^-;.., ,. f^ _-.™i«r--». •j.^S^ti*—.-«Tfc'**»»*H«. j
-------
Source Category
Transportation
Highway vehicles
Non-highway vehicles
Stationary fuel combustion
Electric utilities
Industrial
Residential, commmercial, and
institutional
Industrial processes
Chemicals
Petroleum refining
Metals
Mineral products
Oil and gas production and
marketing
Industrial organic solvent use
Other processes
Solid waste
Miscellaneous
Forest wildfires and managed
burning
Agricultural burning
Coal refuse burning
Structural fires
Mescellaneous organic solvent use
Total
TSP
1.1
0.8
0.3
4.8
3.4
1.2
0.2
5.4
0.2
0.1
1.3
2.7
0
0
1.1
0.4
0.7
0.5
0.1
0
0.1
0
12.4
SOX
0.8
0.4
0.4
22.4
17.6
3.2
1.6
4.2
0.2
0.8
2.4
0.6
0.1
0
0.1
0
0
0
0
0
0
0
27.4
NOX
9.2
6.7
2.5
13.0
7.1
5.0
0.9
0.7
0.2
0.4
0
0.1
0
0
0
0.1
0.1
0.1
0
0
0
0
23.1
voc
11.5
9.9
1.6
1.5
0.1
1.3
0.1
10.1
2.7
1.1
0.1
0.1
3.1
2.7
0.3
0.7
4.5
0.7
0.1
0
0
3.7
28.3
CO
85.7
77.2
8.5
1.2
0.3
0.6
0.3
8.3
2.8
2.4
2.0
0
0
0
1.1
2.6
4.9
4.3
0.5
0
0.1
0
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
15
-------
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 paniculate 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
16
-------
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).
D.01 ,
0.06
01
0.2
O.S
1
2
5
10
zo
30
40
50
60
70
30
90
96
98
99
99.8
99.B
HIGH EFFICIENCY ESP,
FABRIC FILTER NOT SHOWN
99.69
99.9
99.8
95
80
80
TO
60
M
+0
3D
20
2
1
as
0.2
o.i
0-06
0,01
PARTICLE SIZE, tin
Figure 6-14. Comparison of Control Device fractional efficiency (Weast, 1974).
17
-------
Source type
Utility boilersb'°
Copper smelters
Industrial boilersb'e
Coal
Oil
Kraft pulp millf'g
Power boiler6
.p
Recover furnace
Size
250 MW
500 MW
1000MW
73,000-160,000
metric tons/year
150x 106BTU/hr
200 x 106BTU/hr
150x 106BTU/hr
1000 TPD
ADPh
20 MW
Control
Fabric filter
ESP
Fabric filter
ESP
Fabric filter
ESP
Costs (106 dollars) a
Capital
16.1
28.3
51.0
2.7-23.6
0.9
1.19
1.04
1.19
6.1
O&M
0.3
0.6
1.2
NR
0.03
0.03
0.01
0.03
0.25
Annual
3.0
5.0
9.7
0.5-4.6
0.171
0.210
0.160
0.20
1.2
Table 6-4. Summary of participate matter ocntrol costs for selected sources. "Costs do not include
any costs for compliance with state and local regulations. bCosts based on 6,000 hr/yr. 'Capital costs
increased 25 percent to account for retrofit (EPA, 1978c). d(Weisenbery, 1979). e(Roeck et al., 1979).
'Costs (EPA, 1976) updated to 1978 dollars using the Marshall and Swift Plant Index. Operating
costs were updated using the consumer price index. gCosts 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 pre-
existing technology. Usually no attempts are made to reduce white clouds of condensed
water since these normally vaporize relatively near the source.
Device
Electrostatic Precipitator
Fabric Filters
Application
Coal Fired Boiler, High
Sulfur Coal
Coal Fired Boiler, Medium
Sulfur Coal
Coal Fired Boiler, Low
Sulfur Coal
Coal Fired Boiler
Total
99.8
98.3
—
% Efficiencies Fine Particles
(0.1 to 1 mm)
99-99.6
95-98.9
90-99.. 3
94.5-99.7
Table 6-5. Particle collection efficiency of controls (Abbott and Drehmel, 1976).
18
-------
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
Coal fired
utility boiler
Coal fired
industrial boiler
Oil fired
industrial boiler
Size
250 MW
500 MW
1000 MW
200 x 106
BTU/hr
150 xlO6
BTU/hr
150 xlO6
BTU/hr
Control" (%
reduction) a
LEA (11)
SCR (90)
LEA (11)
SCR (90)
LEA (11)
SCR (90)
LEA (11)
SCR (90)
LEA (11)
SCR (90)
LEA (11)
SCR (90)
COST
Capital0'*
3xl06
30 x 106
6xl06
60 x 106
12 x 106
120 x 106
14 x 10"
IxlO6
10.5 x 10"
0.75 x 106
14 x 10"
IxlO6
Annual6 (
-------
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.
Source type
Utility
Boiler"
Industrial
boilers
Coald
Non-ferrous
smelters e>f
Copper
Size
250 MW
500 MW
1000 MW
200 x 106
BTU/hr
150 xlO6
BTU/hr
73,000-
160,000
metric
tons/yr.
Control
Lime
FGD
Lime
FGD
Double
contact acid
plant + MgO
FGD system
S02
removed
1-5 lb/106
BTU
90%
removal
3. 5% sulfur
coal
95
Costs (106 1978 dollars) a'b
Capital
38.4-40.8
66.5-71.3
115.2-124.6
1.9
1.75
14.4-99.1
O&M
3.6-4.6
5.04-7.56
7.06-12.42
0.77
0.65
NRg
Annual
12.7-14.2
20.8-24.4
34.1-41.6
1.21
1.05
5.36-38.43
Table 6-7. Summary of SOX control costs for selected sources. "Costs based on 6,000. bCosts do not
include any costs for compliance with state and local regulations. cCosts from (EPA, 1979b) adjusted
for size. Capital costs were increased by 25 percent to account for retrofit. dCosts from (Dickerman
20
-------
et al., 1979). Costs were increased by 25 percent to account for retrofit. 'Costs from (Weisenbery,
1979). '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.
CURRENT POWER PLfW GENERflTING COPQCITY
Figure 6-15. Current power plant generating capacity (EPA, 1979c).
i 100 km from Class I Area
I 100 - 200 km from Class I Area
Figure 6-16. Areas within approximately 100 km (60 miles) of class I areas.
21
-------
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.
22
-------
U'l 1WO 1(M »19
TIMC
Tin 1595 159* MIC
TWE
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.
23
-------
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).
24
-------
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.
I960
96 2000
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).
25
-------
• ZINC SMELTERS
* LEAD SMELTERS
• ALUMINUM SMELTERS
0 PROPOSED ALUMINUM SMELTERS
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).
26
-------
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).
27
-------
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
28
-------
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, space-
heating 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.
29
-------
Figure 6-28. Population distribution, 1970.
-J 70%
'\ 1-07
V
t
V 17% '
X^v
-
; 32%
. 1.64
.V«'
r$*r-
$6% * , *'
3-98 J* I
""--.^ / i
X ' * i
I -> '
, t «H
, • 3.80 |
' **•' !
...«•__
;' * . A i
14% 1
1.34 ;
^ ' • ' !
-. ^i- v - — :
1 I---- "• •/ 8% '. 589' 11-HS y S
v ^v 12.24 ; ' •,_ r-^ r "J
'•• ,„ X. '• /"' ""''(l.»1''
9% ; 6?*4 ; ^.,.,- i« ,,,-^' '
i s r:»y---,-^\'"Ci»7
' ''"'"-: j 13% i 11% ''-. J3,'! /
1 2.08 ' 4.07 i S'" /
36* M»* / '. ...^ tv\
I «•_
! 4.% °^
i '-30 O
1740
60%
19-48V
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.
30
-------
VEHICLES,
UNPAVED ROAOS,
OFF ROAD VEHICLES
AGRICULTURAL TILLING
RESUSPENSION,
PAVED ROADS
AGGREGATE STORAGE
PERCENTAGES OF ALL PARTICLES ( BY WEIGHT )
LESS THAN STATED SIZE
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 tolOO 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).
31
-------
Figure 6-31. Fugitive dust emissions from strip mining.
Source
Overburden
removal
Drilling/Blasting
Shovels/Truck
ore loading
Haul road truck
transport
Truck dumping
Crushing
Transfer/
Conveying
Control
Applicate control method/comments
Watering/rarely practiced
Watering, cyclones, or fabric filters
for drilling/Employment of control
equipment increasing; Mats for
blasting/very rarely employed
Watering/rarely practiced
Watering/by far the most widely
practiced of all mining fugitive dust
control methods
Surface treatment with penetration
chemicals/employment of this method
increasing
Paving/Limited practice
Watering/rarely practiced
Ventilated enclosure to control
device/Rarely employed
Adding water or dust suppressants to
material to be crushed and venting to
baghouse/Fairly commonly practiced
Enclosed conveyors/Commonly
employed
Estimate
d
efficienc
y
50% a
No data
50% a
50% b
50% b
90-95% a
50% a
85-90% a
95% a
90-99% a
Control Cost
Unit cost per
application, $
No data
No data
No data
No data
600-1800 ' (1000-
3000)
2390-6860 J'k
(2220-6370)
No data
No data
100-360 ''m (90-
330)
Units
Kilometer
(mile)
1,000 m2
(10,000 ft2)
Mg/hr
capacity
(ton/hr
capacity)
32
-------
Cleaning
Storage
Waste
disposal/Tailing
piles
Enclosure and exhausting of transfer
points to fabric filter/Limited
employment
Very little control needed since
basically a wet process
Continuous spray of chemical on
material going to storage piles/Rarely
practiced
Watering (sprinklers or trucks)/Rarely
practiced
Chemical stabilization/Limited
practice
Vegetation/Commonly practiced
Combined chemical-vegetative
stabilization/Rarely employed
Slag cover/Limited practice
85-99%
(depends
on
control
devices)
90% c
50% a
80% d
65% e
90% a
90-99% a
0.5-1.50 '(.10-
3.25)
No data
40-100 (160-400)
g; 65-150 (250-
600)
50-115(200-450)
h (hydroseeding)
25-40 (100-160) '
90-115(350-450)
g
Kilogram
of chemical
(pound)
1000 m2
(acre)
1000 m2
1000 m2
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.
6.2.43.1 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.
33
-------
Figure 6-32. U.S. Forest Service regions.
1975 - 1977
Number of Burns
per Hundred Square Miles
I I None EU 7.5 • 9.9
LJ o.i -2.4 mn io.o-14.9
5.0 - 7.4
20.0 •
Acres Burned
per Hundred Square Miles
None mi 300-399
1 - 99 UK 400 • 499
100-199 H 500 -599
200 - 299 H 600
1975 - 1977
Estimated Tons of FuBl Burned
per Hundred Square Miles
None
1 • 2,499
2.500-4.999
5,000 - 7,499
7,500 9,999
10,000- 14,999
15,000 19,999
20,000
Figure 6-33. Geographic distributions 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
34
-------
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)
1
2
3
4
5
6
8
9
10
Total
Burns of Timber
Harvesting and Land
Clearing Residues
(slash) (million tons/yr)
9.81
0.65
2.28
0.84
3.13
9.64
1.19
0.04
0.05
27.60 (69%)
Burns of Naturally
Occurring Forest
Residues (million
tons/yr)
—
0.02
0.03
—
0.05
—
12.59
0.01
12.70(31%)
Total Material
Burned (million
tons/yr)
9.81
0.67
2.31
0.84
3.18
9.64
13.78
0.05
0.05
40.33 (100%)
Table 6-9. National Prescribed Burning Statistics (Pierovitch, 1979).
35
-------
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.
36
-------
Table 6-10. Major alternatives to prescribed burning.
37
-------
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.
38
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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. EPAPB-223. U.S. Environmental Protection Agency, Washington, D.C.
39
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Geomet, Inc. (1978) Impact of Forestry Burning Upon Air Quality, A State-of-the-
Knowledge 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
40
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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
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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: Paniculate 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.
41
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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.
42
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PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
CHAPTER 7
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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:
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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 (NFS, 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.
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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.
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NEW ENGLAND
PACIFIC
NORTHERN ROCKIES/
~ '
/ »*<*°t|uji» I
^-
COAST Vvrr-r
SOUTH COAST
s. ARIZONA
NON-CONTIGUOUS
Figure 7-1. Class I area reguns.
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V -. 10 miles
10 miles • V - 15 miles
15 ml les •' V - 25 mi 1 es
2!> miles • V - 45 miles
'I
. 4b mi les • V - 70 mi 1es
1
i A) miles V
Figure 7-2. \isual Range bopletha—Summer 1974-76 (TKjonis and Shapland, 1978).
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TABLE 7-1. STATUS OF CLASS I AREA VISIBILITY IMPAIRMENT9
Number of
class!
Region («e map) areas
Reported
Status'
Observed
visibility*
phenDrriena
Potential sources8
Man-made
Natural
Potential for
future frnpairmeritS"*
We«t gf lOty1 Meridian
Pacific Nortnwest 33
California [excluding North):
West Coatt Central Valley 7
East Mountain 2 North
Gensrrtl y desirable visibility,
intermittent undesirable
conditions
Generally impaired outside areat.
some impairment in area}
Impairment outside areas,
1 r>Mrmi ItSn I in Steal
1.
2.
1,
2.
3
1,
2.
Smoke, haze
Visible pJurmt
Haze
Smoke
Dust
Haze
Smoke
1,2. Agricultural
burning;
Mash burning;
fore&t products industry ;
pulp, paper mills;
taw mlllsr
Al, Cu smeJtera.;
u rban piurnas;
prescribed burning
1,2,3, Agricultural
activity, burning;
u rben pi umes;
prescribed burning
1, LakeTaho*, urban
plume
2. Prescribed burning
1^. Wildfires;
foj
1,2. WiWfires
3. Windblown
du»t
Smell .increase in
utitity, indus-
trial coal u»;b'c
populaticn growth4
Small increase in
jliiity, industrial
coal useprfi
Sorns improvemtnt,
with progress toward
meeting air quality
South Coast
7 Soutti Gansrally desirable visibility, 1, Haze
some impalrrntnt-out in ar««c 2. Smoto
6 General ly impaired 1, Haze,$mag
1, Aaricultural activity,
San Joquin Valley
2. Wildfire*
unban plume jntrusiona;
torn* pnHCribcd burning
Norther-rt Rockl«6/PlainE 12
Generally de£irabl6 visibility
Some Impairment outskte AHHK
2. Visible plumes
^I2, Slash, agrtcultural
burning; prEjcritjed
burning
1,2. Wildfires
3. Winctblngvn
dust; fog
IrwrsMed utltity coal
ujt;" increased in-
dustrial ctjal uEajC pos-
sible decreast in smalttr
amissioris in attalorng
air oualjtv itandfirda;6
Colorado
"Golden Circle"
1 1
Generally dasi rabls- visibi 1 i ty
Soir* impairment ;nend
to sttesj noted
1, Smoke
1 , Haze (intermittent!
2. Vitibta plumes
3. Discoloration
(brovm, yellow band)}
1. Aprrcultural
burning; saw mills;
prescribed burning
2, Urban plumes
1 , Ppwer plants;
smaltlfni: urban plumes
2, Power p-ianti;
mijcellartecHjj small
sources
1. Wildfire*
2, Windblown
du«t
3, Fog
1 , Natural haza
2. Wildfires
: rmorrig ertaroy
prediction activities;'
auocratedL population
growth.6-*1
Significant copulation
growth in COt UT;d
aaociat«d urban, &thar
devil opment.
Possible decreate in
smaltBr impact) from .
air quality standard
attainment8
Southern Arizona
11
Gantrally impaired
1 , Regional haze
2, Dust
3, Smoke
A,
1, Smelter*; urban
piumst |Phd«nix,
Tucson I
2, AgricultuTal
activities; burning
3, Prestrkxid burning
1, Natural haze
1, Windblown
dust
PottlbJe Further de-
crease in arrveltBrs
tmtetiortt to attai n a ir
CJUaM«if *%B« M*aiu*,~ .
major popuiation growth,1^
development
New
10
Cenarally desirable visibility
aSS*88 not«d
1, Haze-
2, Dust
3, Smoke
1, Smelters
2, Agricultural
activrties
3, Prescribed burning
t. Natural haze
2. Windblown
dj&t
Postal* deereas* in
smelter impacts,*
increased gan«ral
dtvelopment*
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TABLE 7-1. (continued} STATUS OF CLASS I AREA VISJBUJTY IMPAIRMENT3
Number of
class 1
Region (see map) aratt
Reported
visibility
status*
Qb*ery«|
pnenomena
Fotsiitial tourcei*
Man-rndda
Natural
Potential for
future n gromrfh41
Planrwd Canadian
power plant? increased
regional utility goal USB">€
Significant increase In
utility, industrial coal
use, §QX emi&sionaV^
Noncontiguous U.-S
Alaska/Hawaii 7
Gan*rally dotirabl* viability
2, S-mDkH
2. Agricultural
burning3
1 Fog
2. Volcanic
Piamed power plant
^Federal Land Manager Workbook} IMPS, 1279;USFS, I979a; USFWS, 1979),
bUt<(itV emission Projections (ICF, 1979P; sae Figure 6-18.
clndustriel Coel USE Project ions (DOE, 19791; n«a Figure £-19.
rijfjtjii^iii^f i i tunrtjUS-nn i.uvi'sjj. i&t f f, xsv ri^uriw tF"£-.ji
eSmelter Emission Projections (TfijOnis, 1979P; s8« Figure 6-22,
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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 169 A 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
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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
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CONTINUED
RESEARCH,
NEW DATA
IEPA. FUPSTATES
DOE, INDUSTRY)
CLEAN AIR ACT AMENDMENTS
NATIONAL GOAL
SECTIONS 169A, 165
VISIBILITY REGULATIONS
AND GUIDE LINES
ASSESS AREA VISIBILITY
(STATES. FLM, EPA, INDUSTRY}
1. REVIEW AVAILABLE DATA
Z. MONITOR IMPAIRMENT
3, IDENTIFY SOURCES
4, MODEL IMPACTS
6, ESTIMATE NATURAL
BASE LINE
ESTABLISH CRITERIA (OBJECTIVES)
I FLM, STATES, EPA)
1. CLASS OF IMPAIRMENT
*| GENERAL HAZE
b) PLUME BLIGHT
cJ LAYERS OF DISCOLORATION
2, DEGREE AND EXTENT
B) QUANTITATIVE INDEX
b) FREQUENCY, DURATION,
TIME OF OCCURRENCE
3.
a) NATIONAL, REGIONAL,
AREA SPECIFIC
J») SOURCE CATEGORY
<•) EXISTING/NEW
DEVELOP CONTROL STRATEGIES [*
(STATE S|
1. BART ANALYSIS FOR
EXISTING SOURCES
(MAJOR < 15 YR)
2. PSD REQUIREMENTS FOR
NEW MAJOR SO URGES
3, LONG-TERM STRATEGIES
ak ANALYZE EFFECT OF
OTHER REGULATORY
EFFORTS
h) EVALUATE IMPACT OF
EXISTING AND NEW
SOURCES NOT ADDRESSED
BY BART, PSD
c! ALTERNATIVES
1, TRADITIONAL EMISSION
LIMITATIONS AND
SCHEDULES
2. SECONDARY AIR
QUALITY STANDARD
FOR FINE PARTICLES
3, ECONOMIC INCENTIVE
APPROACHES
MONITOR PR OGRESS TOWARDS
NATIONAL GOAL
Figure 7-3. Conceptual framework for visibility protection
7-W
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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 cost-
effective 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 zjig/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 area-
specific 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 power-
plant configurations suggests that potential problems in this region include plume bright
from NO2 and sulfate-derived haze. As discussed in Chapter 5, brown NC>2 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
power-plant growth
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7-2. TOTENTIAL APPLICABILITY Of
TO BY FLW
Source category
Agricultural activities
Burnt np
Fugitive dust
Forest product development
burning
Pulp and mills
mills
Miscellaneous point sources
Prescription fires
Power
Single identifiable
emissions
Sm-ailtn
Copper
Aluminum
Urban pollution
activities
Mo I Of vt hides
Space heating
BART applicability
Not
Varies with age, controls.
Not applicable
Varies with controls, impairment
Not applicable
Viriis with *ff, controls, impairment
Probably not applicable (evaluation of
improvement not
Not applicable to most {too old)
Varies with controls, impairment
Varies with
(probably fimittdj
Not
-------
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 visibility-
impairment 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.
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TABLE 7-3. EKAWPLES OF POTENTIAL L0NG-T1RM
ViiibBity problem Major sources Desirattt ieeteic»I control approach
Redue* rogsonal hats in Regional sulfur wide Bedoce rep iof»l juSluf Oxide
Eist Iraor* »"«k»y Shan 9 plants, Braissionf/emphwis an te-
NSPS approach) oth«f fottil fu»t eajnbustton ductiort during tumrriir
montbi of peik tuifate itrwti
Maintain n&siona! Regional suiftir oxide Maintain or riduee currant
v<$
-------
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.
NFS (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.
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PROTECTING VISIBILITY
AN EPA REPORT TO CONGRESS
CHAPTER 8
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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 VISIT A, 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 ~ SO% 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 NC>2 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. I, 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. Lpomis 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
-------
D- IDENTIFICATION OF MANDATORY CLASS I
FEDEBAL AREAS WHERE VISIBILITY IS AN IMPORTANT VALUE
81,400 Scope.
Subpart I), Section 81.401 through 81.437 lists those mandatory Federal Class I areas, established tinder the
Clean Air Aet Amendments of 1977, where ihe Administrator, in consultation with the Secretary of line
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 interna-
tional 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 (NFS), and Fish and Wild Life Service (FWS); and the Department of Agriculture (USDA).
Forest Service (FS).
State
381,401 Alabama.
S8t, 402 Alaska.
S81 ,403 Arizona
S81 .404 Arkansas.
Area Name
Sipsey Wild
Bering S«a Wild
Mount McKinley NP
Simeonof Wild
Tuxedni Wild
Chiricahua National
Monument Wild
Chiricahua Wild
Galiuro Wild
Grand Canyon NP
Mazatzai Wild
Mount Baldy Wild
Petrified Forest NP
Pine Mountain Wild
Saguaro Wild
Sierra Ancha Wild
Superstition Wild
Sycamore Canyon Wild
Caney Croek Wild
Upper Buffalo Wild
Acreage
1 2,646
41,113
1 ,949,493
25.141
6,402
9,440
18,000
52,71?
1,176,913
205,137
6,975
93,493
20,061
71,400
20,850
124,117
47,757
14,344
9,912
Public Law
Establishing
93-622
91 -622
64-353
94-55?
91-504
94-567
88-577
88-577
65-277
88-577
91 -504
85-358
92-230
94-567
88-57?
88-577
92-241
93-622
93-622
Federal Land
Manager
USDA-FS
USD I -FWS
USD I -NFS
USDl-FWS
USDI-FWS
USOI-NPS
USDA-FS
USDA-FS
USQI-WS
USDA-FS
USDA-FS
USDI-NPS
USDA-FS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
A-a
-------
State
S81. 405 California
881,406 Colorado,
S81.407 Florida.
S81 .408 Georgia,
S81. 409 Hawaii,
S8 1.410 Idaho.
! HellsCanyon Wilderm
Area Name
Aqua Tibia Wild
Caribou Wild
Cucamonga Wild
Desolation Wild
Dome Land Wild
Emigrant Wild
Hoover Wild
John MuirWild
Joshua Tree Wild
Kaiser Wild
Kings Canyon NP
Lassen Volcanic NP
Lava Beds Wild
Marble Mountain Wild
Minarets Wild
Mokelumme Wild
Pinnacles Wild
Point Reyes Wild
Redwood NP
San Gabriel Wild
San Gorgonio
San Jaeinto Wild
San Rafael Wild
Sequoia IMP
South Warner Wild
Thousand Lakes Wild
Ventana Wild
Yolla-Ball¥-Middte-Eel Wild
Yosemlte NP
Black Canyon of the
Gynniton Wild
Eagles Nest Wild
Flat Tops Wild
Great Sand Dunes Wild
La Qarita Wild
Maroon Bells - Snowmass
Wild
Mesa Verde NP
Mount Zirkel Wild
Rawah Wild
Rocky Mountain NP
Weminuehe Wild
West Elk Wild
Chassahowitika Wild
Everglades NP
St. Marks Wild
Cohotta Wild
Gkefenoke* Wild
Wolf Island Wild
Haleakala NP
Hawaii Volcanoes
Craters of the Moon Wild
Hells Canyon Wild
Sawtooth Wild .
Selway-Bitterroot Wild
Yellowstone NP
Acreage
16,934
19,080
9,022
63,469
82,206
104,311
47,916
484,673
429,890
22,500
459,994
105,800
28,640
213,743
108,484
60,400
12,952
25,370
27,792
36,137
34,644
20,564
142,722
386,642
68,507
15,695
95,152
109,091
759,172
11,180
133,910
235,230
33,460
48,486
71,060
51 ,488
72,472
28,674
263,138
400,907
61,412
23,360
1 ,397,429
17,745
33,776
343,850
8,126
27,208
217,029
43,243
83,800
216,383
988,770
31,488
sss, 192,700 acres overall , of which 1 08,900 acres are in Oregon and 83,800 acres ar<
Selway Bitterroot Wilderness, 1 ,240,700 acres overall, of which 688
Yellowstone National
are in Idaho.
,700 acres are in Idaho and 2S1 530 t
Public Law
Establishing
93-632
88-577
88-57?
81-82
88-577
93-632
88-577
88-577
94-667
94-577
76-424
64-184
92-493
88-677
88-677
88-577
94,567
94-544,94-567
90-545
90-318
88-677
88-677
90-271
26 Stat. 478
!51stCong.)
88-877
88-577
91-88
88-677
68-49
94-567
94-352
94-146
94-567
88-877
88-677
69-363
88-577
88-577
63-238
93-632
88-577
94-557
73-26?
93-632
93-622
93-429
93<32
87-744
64-171
91-604
94-199
92400
88-577
1 7 Stst, 32
(42nd Cong.)
a in Idaho.
icres are in Montana
Park, 2,219,737 acres overall, of which 2,020,628 acres are in Wyoming, 167,624 acres are in Montana
Federal Land
Manager
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDA-FS
USDI-NPS
USDI-NPS
USDI-NPS
USDA-FS
USOA-FS
USDA-FS
USOA-NPS
USDI-NPS
USOI-NSP
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDI-NPS
USDA-FS
USDA-FS
USOI-NPS
USOA-FS
USDA-FS
USOI-NPS
USOA-FS
USOA-FS
USDI-NPS
USDA-FS
USOA-FS
USDI-FWS
USOI-NPS
USDI-FWS
USDA-FS
USDI-FWS
USDI-FWS
USDI-NPS
USDI-NPS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
i.
, and 31,488 acres
-------
State
S81 .41 1 Kentucky,
881,41 2 Louisiana,
381,413 Maine.
S81. 414 Michigan.
881, 41 6 Minnesota.
581,416 Missouri.
581,417 Montana.
Area Name
Mammoth Caw NP
Breton Wild
Aeadia NP
Moosehorn Wild
{Edmunds Unitl
Waring Unit)
Isle Royale NP
Seney Wild
Boundary Waters Canoe Area
Wild
Voyafeurs NP
Hercules-Glades Wild
Mingo Wild
Anaconda-Pintlar Wild
Bob Marshal I Wild
Cabinet Mountains Wild
Gates of the Mtn Wild
Glacier NP
Medicine Lake Wild
Mission Mountain Wild
Red Rock Lakes Wild
Scapegoat Wild
Selway-Bitterroot Wild
U, L, Bend Wildh
Yellowstone NP°
Acreage
51,303
5,000+
37,603
7,601
(2,782)
(4,7191
542,428
28,150
747,840
114,964
12,316
8,000
157,803
950,000
94,272
28,562
1,012,599
11,366
73,877
32,350
239,295
251,930
20,890
167,624
Public Law
Establishing
69-283
93-632
65-278
91-504
S3-632
71-836
91-504
99-577
99-261
94-557
94-557
88-577
88-577
88-577
88-677
61-171
94-557
93-632
94-557
92-395
88-577
94-557
17 Star. 32
(42nd Cong.)
Federal Land
Manager
USOI-NPS
USDI-FWS
USDI-NPS
USDI-FWS
USDI-NPS
USDI-FWS
USOA-FS
USDI-NPS
USDA-FS
USDI-FWS
USOA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDI-FWS
USDA-FS
USDI-FWS
USDA-FS
USDA-FS
USDI-FWS
USDI-NPS
.Selway-Bitterroot Wilderness, 1,240,700 acres overall, of which 988,770 acres are in Idaho and 231,930 acres are in Montana.
Yellowstone National Park, 2,219,73? 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,
$81,419 New Hampshire,
S81 .420 Nsw Jersey,
S81.421 New Mexico,
581,422 North Carolina.
Jarbridge Wild
Great Gulf Wild
Presidential Range-Dry
River Wild
Brigantine Wild
Bandelier Wild
Bosque del Apache Wild
Carlsbad Caverns NP
G, Is Wild
Pecos Wild
Salt Creek Wild
San Pedro Parks Wild
Whealer Peak Wild
White Mountain Wild
Great Smoky Mountains NF*?
Joyce Kilmer-Si ickrock Wild
Linville Gorge Wild
Shining Rock Wild
SwanQuarter Wild
64,667
5,552
20,000
6,603
23,267
80,850
48,435
433,690
167,416
8,500
41,132
6,027
31,171
273,551
10,201
7,575
13,350
9.000
88-577
88-577
93-622
93-632
94-567
93-632
71-216
88-577
88-577
91-504
88-577
88-577
88-577
69-268
93*22
88-577
88-577
94-557
USDA-FS
USDA-FS
USDA-FS
USDI-FWS
USDI-NPS
USDI-FWS
USDI-NPS
USDA-FS
USDA-FS
USDI-FWS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDI-FWS
Great Smoky Mountains National Park, 514,758 acres overall, of which 273,551 acres are in North Carolina, and 241,20? acres are in
, Tennessee,
Joye® Ktimer-SiickfDEk Wiktoroet*, 14,033 acres overall, of which 10,201 acres are m North Carolina and 3,832 acres are irt Tennessee.
-------
State
S81 .423 North Dakota.
S81 .424 Oklahoma.
S81. 425 Oregon.
Area Name
Lostwood Wild
Theodore Roosevelt, NMP
Wichita Mountains Wild
Crater Lake NP
Diamond Peak Wild
Eagle Cap Wild
Gearhart Mountain Wild
Hells Canyon Wild"
Kalmiopsis Wild
Mountain Lakes Wild
Mount Hood Wild
Mount Jefferson Wild
Mount Washington Wild
Strawberry Mountain Wild
Three Sisters Wild
Acreage
5,657
69,676
8,800
160,290
36,637
293,476
18,709
108,900
76,900
23,071
14,160
100,208
46,116
33,003
199,902
8 Hells Canyon Wilderness, 192,700 acres overall, of which 108,900 acres are in Oregon
S81 .426 Soyth Carolina
S81 .427 Soyth Dakota.
S81.428 Tennessee.
a Great Smoky Mountains Ni
Cape Remain Wild
Badlands Wild
Wind Cave NP
Great Smoky Mountains NP .
Joyce Kilrner-Slickrock Wild
ttional Park, 514,758 acres overall,
28,000
64,250
28,060
241,207
3,832
Public Law Federal Land
Establishing
93-632
80-38
91-504
57-121
88-577
88-577
88-577
94-199
88*77
88-577
88-577
90-548
88-577
88-577
88-577
, and 83,800 acres are in Idaho.
93-632
94-567
57-16
69-268
93-622
Manager
USDI-FWS
USDI-NPS
USDI-FWS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-FWS
USDI-NPS
USOI-NPS
USD! -NFS
USDA-FS
of which 273,551 acres are in North Carolina, and 241 ,207 acres are in
b Joyce Kilmer-Slickroek Wilderness, 14,033 acres overall, of which 10,201 acres are in
S81 .429 Texas.
S8 1.430 Utah.
S81.431 Vermont.
S81. 432 Virgin Islands
S8 1.433 Virginia.
S81 .434 Washington.
Big Bend NP
Guadalupe Mountains NP
Arches NP
Bryce Canyon NP
Canyonlands NP
Capitol Reef NP
Zion NP
Lye Brook Wild
Virgin Islands NP
James River Face Wild
Shenandoan NP
Alpine Lakes Wild
Glacier Peak Wild
Goat Hocks Wild
Mount Adams Wild
Mount Rainier NP
North Cascades NP
Olympic NP
Pasayten Wild
708,118
76.292
65,098
35,832
337,570
221 ,896
142,462
12,430
12,295
8,703
190,535
303,508
464,258
82,680
32,356
235,239
503.277
892,578
505,824
North Carolina and 3,832 acres in
74-1 57
89-667
92-155
68-277
88-590
92-507
68-83
93-622
84-925
93-622
69-268
94-357
88-577
88-577
88-577
30 Stat. 993
(55th Cong.)
90-554
75-778
90-544
t in Tennessee.
USDI-NPS
USDI-NPS
USDI-NPS
USDI-NPS
USDI-NPS
USDI-NPS
USDI-NPS
USDA-FS
USDI-NPS
USDA-FS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USDA-FS
USDI-NPS
USDI-NPS
USDI-NPS
USDA-FS
-------
Stats Area Name
S81
S81
,435 West Virginia, Doily Sods Wild
Otter Creek Wild
.438 Wyoming. Bridger Wild
Fttzpatriek Wild
Grand Teton NP
North Absaroka Wild
Teton Wild
Washakie Wild
Yellowstone NP
8 Yellowstone National Park, 2,219,737 acres
31 ,488 acres are in Idaho.
Acreage
10,215
20,000
382,160
191,103
305,504
351,104
567,311
686,584
2,020,826
overall, of which 2,020,625 acres are in Wyoming,
Public Law
Establishing
93-622
93-622
88-577
94-567
81 -787
88-577
88-577
92-476
17 Slat. 32
(42nd lonsl
167,624 acres are
Federal Land
Manager
USDA-FS
(JSOA-FS
USDA-FS
USDA-FS
USDI-NPS
USDA-FS
USDA-FS
USDA-FS
USOI-NPS
in Montana, and
S81.437 Maw Brunswick, Reoseygtl CampobeHo
Canada, International Park
88-363
t applicable
------- |