Executive Summary
   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

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.

   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
   The location, degree, and the spatial  and temporal extent of visibility impairment must
be addressed in the visibility protection programs.  In areas  such as the Southwest,
anthropogenic air pollution  occurring outside  class I area boundaries can obscure long
distance vistas normally visible from within the class I area. Anthropogenic impairment
may  be frequent, last for long time periods, and be readily apparent to  all observers.
Conversely, anthropogenic visibility impacts may be so infrequent, short in  duration, or
small in  degree that  it is difficult for  the unaided  observer to distinguish them from
existing impairment caused by natural sources.  For the purpose of this report, EPA
adopts the following position on visibility impairment:

1.  Certain vistas  extending  outside class I area boundaries are important to visitor
   experience and are part of the visibility value of the area.  Such views should be
   included in the national goal.
2.  Anthropogenic visibility impairment in the context of the national visibility goal is
   defined as any perceptible**  change in visibility (visual range, contrast, atmospheric
   color,  or other conveniently measured visibility index) from that which would have
   existed under natural conditions.
   Therefore, in  the context of specific control decisions, an increment (or decrement) in
visibility impairment  must as a  minimum be perceptible to  be  significant  or adverse.
Further judgements  with  respect to  the significance  and  adversity  of  perceptible
impairment must be made, at least in part, on a case-by-case basis and must address the
degree and spatial and temporal  extent of the incremental change.  For this  reason, and
because such judgements must involve States, Federal Land Managers, and the public, it
is not possible at this time to specify comprehensive criteria for defining  significant or
adverse impairment.

   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

   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.

                                             - GENERALLY DESIRABLE VISIBILITY
                                             - SOME UNDESIRABLE CONDITIONS
                                             - FREQUENT UNDESIRABLE CONDITIONS
   Figure 2. Preliminary class I area visibility status reposted by Land Managers.

   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
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
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

   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.

   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
   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.

   Relating visibility impairment to its emission sources is a central problem for making
progress towards the national visibility goal.  Some important general understandings
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
3.  Much of the fine particle mass is of secondary origin; that is, most fine particles are
   formed in the atmosphere from their "precursor" gases, sulfur oxides, nitrogen oxides,
   and organics. Hence, the emission rate of secondary particles cannot be measured at
   he  source.  Furthermore, the  gas-to-particle conversion process depends on factors
   such  as solar radiation, the presence of other pollutants, and humidity.   Thus, the
   amount of secondary material formed from a given rate of precursor gases is not
   constant but depends on the environment.

4.  The residence time of fine  particles in the atmosphere is through to be about a week
   or more, and their transport distance can exceed 500 kilometers.

5.  The long-range transport of the fine  particle/precursor chemical complex results in
   the superposition and chemical  interaction of  emissions from  different  types of
   sources (e.g., power plant and urban  plumes). Many of these interactions  currently
   cannot be adequately predicted on a regional scale.

6.  The qualitative evaluation of source receptor relationships will require collection and
   analysis of monitoring data. Properly calibrated mathematical models are necessary
   to predict the impact of controls on existing sources or the impact of new sources in a
   new location.
   Empirical approaches to evaluation source impacts range from simple observation of
visible plumes to sophisticated aircraft sampling and satellite  imagery.  The approaches
discussed in Chapter 4 include: evaluation  of haze  chemical composition, analysis of
historical  trends  of  emissions  and  haziness,  evaluation  of haze/wind-direction
relationships, aircraft plume sampling, and application of diagnostic models.  Important
conclusions from application of these techniques to date include:

1.  Direct measurements and statistical analysis indicate that fine sulfate aerosols account
   for 30 to 60 percent of fine particle related visibility reduction in areas as diverse as
   the Northeast United States, Los Angeles, and the Southwest mountain states.

2.  Other fine  particle constituents are also important and  can  dominate scattering in
   various regions.  IN the Pacific Northwest, for example, carbon-containing aerosols
   from wood or other vegetative burning and motor vehicles appear to be  significant
   components of light scattering aerosols.

3.  Studies of trends in eastern airport visibility indicate that, while wintertime visibilities
   improved in some northeastern locations, overall eastern visibility declined. Summer,
   often the season of best visibility in the early fifties, is  currently the worst season.
   From  1948 to  1974,  summertime  haze (extinction) increased by  more than  100
   percent in the  central  Eastern  States, 50 to 70 percent for the Midwest and Eastern
   Sunbelt  States,  and by 10 to 20 percent for the New England  area. Although the
   results of airport surveys should be viewed with caution, the results are consistent
   from site to site.
   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.

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.

   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
4.   The models are subject to the uncertainties in current understanding of human visual
    perception and the optical characteristics of modeled air pollutants.

5.   An incomplete understanding of large-scale meteorological processes, uncertainties in
    boundary conditions, and lack of adequate inventories of natural and  anthropogenic
    emission sources significantly limit modeling of regional scale transport of pollutants.

6.  Visibility models have generally not been verified through intensive environmental
   monitoring.  Major experimental efforts are under way to confirm the theoretical

   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.

   Vision in the natural "unpolluted" atmosphere is restricted by blue sky scattering, by
curvature of the earth's surface and  by  suspended liquid or solid natural aerosols.  The
important sources of natural aerosols include water (fog, rain, snow),  windblown dust,
forest fires,  volcanoes,  sea spray, vegetative emissions, and  decomposition processes.
These sources must be addressed in estimating base line visibility in class  I areas.  The
extent to which these natural sources control existing visibility levels  in the United States
is not well known.  Nevertheless, it is reasonable to conclude that manmade  sources
contribute significantly to visibility  impairment in most regions of the country  and in
some cases dominate visibility.

   Anthropogenic  emission sources of particulate matter, sulfur oxides, nitrogen oxides,
and volatile organics are of some significance to visibility impairment.  The significance
of volatile organics  (hydrocarbons), however, is not well understood.  Major sources,
projected growth,  and controls are discussed in  Chapter 6.  The  most  important source
categories of visibility-impairing pollutants  include utilities, industrial  fuel combustion,
smelters, pulp mills, urban plumes (the result of point sources, space  heating, mobile and
other urban  sources), fugitive dust from agricultural activities, mining, unpaved roads,

off-road recreational vehicles, and the managed use of fire including prescribed burning
associated with forestry and agricultural burning. The significance of these sources on an
individual and  collective basis varies throughout the country.   Many of them  are not
readily amenable to further control.

   The results of the preliminary Federal Land Manager analysis of visibility in class I
areas provide important implications for control programs.  These include:

1.  Few, if any, of the class I areas are currently free from some anthropogenic influence
   on  visibility.  Given resource limitations  and the lack of adequate information on
   impairment,  however, those areas with current or projected unacceptable visibility
   conditions should receive highest priority in control programs.   If,  as preliminary
   subjective Land  Manager  judgements  suggest,  current   visibility is  generally
   acceptable in two-thirds of the class I areas, there will be little impetus for completely
   eliminating  perceptible man-made impairment.   This appears to be consistent with
   Congressional intent.

2.  Protection of integral views extending outside class I areas is important for a number
   of class I  areas.  A number of managers reported, however, that the haze occurring in
   large urban areas are visible from some vantage points within the class I area.   It is
   not clear  that  Congress intended to remedy these kinds of visibility impairment.
   Case-by-case judgements can address these issues.

3.  The kinds  of  sources that tend to dominate  visibility impairment vary  greatly
   throughout the country.   Visibility control programs must account for  the  diverse
   nature of sources.  Particularly difficult problems include regional haze in the Eastern
   United States, regional emissions in the Southwest, the impact of urban plumes, and
   prescribed burning  activities.  The Land Managers themselves utilize fire as a means
   for enhancing the production of timber, improving wildlife habitats, and  preventing
   catastrophic natural fires.  Such activities impair visibility on a temporary basis.

4.  Assessment of existing visibility conditions and projected growth indicate that the
   highest priority for visibility protection programs in class  I areas is the evaluation of
   the impacts of new sources of visibility impairment.  Many of the class I areas in the
   Western United States are likely to be influenced by increased energy development
   and utilization,  population and urban  growth,  and associated emission increases.
   Once such sources are constructed, it is very difficult to mitigate their impacts.

   Although available models are limited, they should be used to evaluate new source
impacts.  The alternative allowing construction of new sources without such analyses as
long as prescribed  class I increments are met, is not acceptable.  Available scientific

information supports the contention of the House Committee Report that "mandatory
class I increments do not protect adequately visibility in class I areas" in all cases.

   Programs for the prevention  of significant deterioration will address the impact of
major facilities on class I area visibility.  These requirements, however, do not adequately
deal with the  visibility impacts of increases  in emissions associated with population
growth, such as increased urbanization, automotive emissions, and space heating, or with
activities such as agricultural growth and highway construction.  Additional studies are
needed to quantify the influence of these activities on visibility before adequate guidance
can be considered.  Control of such sources  may ultimately  prove to be necessary for
making progress toward the national goal.
   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
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.

   Because of the lack of base line visibility data in class I areas, the limitations in
scientific and technical understanding of source/air quality perception relationships, the
need to consider visibility improvements in the context of control costs, and limitations in
resources available to States, EPA, and the Federal Land Managers, EPA recommends a
phased approach  to visibility protection.  Although  regulations  and guidelines for the
States  must encompass the full range  of Clean  Air  Requirements,  they should, to the
extent possible:

1.  Permit State control programs to focus initially on the most clearly defined cases of
   existing impairment and on strategies to prevent future impairment and,

2.  Allow for the evolution  of guidelines and  control strategies  made  possible with
   expected   improvements   in   scientific  understanding   of  source/impairment

   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.

   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.

   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
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.

   Extension  and  refinement  of visibility  protection programs  are dependent  on
improvement of current knowledge  and techniques in a number of areas.  The most
important areas include:

1.  Comprehensive characterization  of existing  visibility  conditions in representative
   regions containing class I areas.

2.  Development of improved and simplified visibility monitoring approaches.

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

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

5.  Studies of human visual perception in clean atmospheres.

6.   Studies of the value of visibility.
   A combination of programs involving government and the private sector is beginning
to  address many  of these areas.  Significant advances in the next several years should
enhance our ability to make progress towards the national visibility goal.



  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

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

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.


The  Clean Air Act  Amendments of 1977 add Section 169A to the Clean Air Act,
requiring the following activities of the Federal Government:

   1.  The Department of Interior, in consultation  with other Federal Land Managers,
       must review all mandatory class I Federal areas and identify those where visibility
       is an important value of the area. The EP A  Administrator, after consulting with
       Interior, must promulgate a list of mandatory class  I Federal areas in which he
       determines visibility is an important value. The list has been promulgated and is "
       included as Appendix A to this report.

   2.  EPA must prepare this report to Congress on methods for meeting the visibility
       goal, including methods to identify visibility impairment, modeling,  and other
       methods for evaluating source impacts, methods for preventing and remedying
       pollution related  visibility impairment, and a discussion of pollutants and sources
       that may impair visibility.

   3.  EPA must promulgate regulations which will (a) provide guidelines to States on
       appropriate techniques and methods for implementing Section 169 requirements
       through the State Implementation Plans (SIP) where  needed, and (b) require SIPs
       for affected States to include emission limits, schedules for compliance, and other
       measures as may be necessary to  make reasonable progress  toward meeting the
       national visibility goal.

   These regulations must  require sources which have  been in operation less  than 15
years as of August  1977  and which emit any air pollutant that  may  reasonably be
anticipated to impair visibility in the selected class I areas to procure, install, and operate
the best available retrofit technology (BART) no later than 5 years after SIP approval.

The  regulations must also require that the  SIPs  include a long-term (10 to 15 years)
strategy for making reasonable progress toward the visibility goal. The long-term strategy
may require control of sources older than 15 years or sources not otherwise controlled
under the BART provisions. BART must be determined for each source by the State (or
Administrator, in some cases).  In the case of a fossil fuel-fired generating power plant
having a total generating capacity of least 750 MW, the emission limitations (BART)
must be determined pursuant to EPA guidelines. Guidelines for determining BART must
take into consideration the costs of compliance, the pollution control technology in use at
the source, the remaining useful life of the source, and the degree of improvement in
visibility that may reasonably be anticipated to result from the use of such technology.
BART  can  be  expressed  as an  emission limit  or  operating  practice and must be
incorporated into a revised State Implementation Plan.

   Enactment  of the visibility  section  of the Clean Air Act was  stimulated by public
concern about the deterioration of visibility in scenic areas. Examination of the legislative
history  of the visibility  provision indicates that  Congress was  particularly  concerned
about evidence submitted by the National Parks and Conservation Association, stating,
"that some areas that in the past  had  100-mile (160-km) visibility now have  only an
average  of 30-mile  (48-km) visibility.  Much of this probably can  be attributed  to
emissions from  power plants,  such as the  Navaho and Four-Corners plants." (House
Report,  1977). In addition to the recognized threat of power plants to long-range visibility
in the western United States, Congress was concerned about reports that "the hazes found
in high vegetation areas of the southeast are not dominated by natural organic compounds
but by sulfate particles,  probably  from the oxidation  of SO2 emitted from  regionally
distributed sources. " (House Report, 1977).

   As stated in  the Conference Report (1977), "a major concern which prompted the
House to adopt a visibility protection provision was the need to remedy existing pollution
in Federal mandatory class I areas from existing sources. Issues with respect to visibility
as an air quality related value and application to new sources are to be resolved within the
procedures for prevention of significant deterioration.  " This statement is clarified in an
attachment to technical changes to the 1977 Clean Air Act Amendments by Congressman
Paul Rogers:  "  does not state   or  imply  that  existing sources  were the  only  sources were  also  1-2  of concern. This point is underscored by the
statutory language of Section 169A(a)(I), retaining as a national  goal: the prevention of
any  future  impairment.   ."  (Rogers,  1977).  With respect  to  new-sources,  Section
165(d)(2)(B)  of the Clean Air Act makes it clear  that  the Federal  Land Manager
responsible for the management of class I area(s) "shall have an affirmative responsibility
to protect the  air quality  related values (including visibility) of any such lands within a
class I area and to consider, in  consultation with the Administrator, whether a proposed
major emitting facility will have an adverse impact on such values." Thus, the national
goal of Section 169A applies to both existing and new  sources; implementation includes
both 169A(a) and 165(d).

   Congress  noted that  the  current national ambient  air quality  standards were not
adequate to protect visibility in class I areas. Congress also recognized that, as a matter of

equity, it would be impractical to require the same national ambient air quality standard
for visibility protection in cities  such as New York or Los Angeles as  for areas such as
the Grand Canyon or Yellowstone National Park (House Report,  1977). In requiring an
analysis of the visibility values  in various  class I  regions before determining whether
visibility  protection  would be  required, Congress  recognized that  it  might  be
unreasonable to have uniform visibility objectives  even for all national  parks or other
class I areas.


   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

   In  addition to listing  the  areas in which  visibility is an important value, the National
Park Service, the Fish and Wildlife Service,  and the Forest Service have  each conducted a

preliminary analysis  of the visual  values  potentially impaired by air pollution.  The
analysis specifies the more important vistas associated with the area, tentatively identifies
apparent natural  and anthropogenic  sources  of impairment, and provides  preliminary
subjective judgments of the status of visibility in the  area. This preliminary analysis is
summarized in Chapter 7.

JFignre 1-1. Mundatofy      I

l'!«niv  1-2.  lii  :*»at ^I«ijfit«ui-,  wmitiirni  1 tali,  'Ilii-  *iri« iIJii»ir«il»'» tli*' vsilut-- uf iin»mpnin'«l vi«ihilit%  i«  a


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

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. 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

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

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

   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. 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

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

   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

   This general guidance is significant, but a number of important areas are left open for
additional specification, interpretation, and judgment. Examples of visibility impairment,

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

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

   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

   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

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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   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.


   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.

   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

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


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

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.

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.

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.


       CHAPTER 2

   "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.

   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.


2.2.1 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
                   VEHING ATMUSPH ER E	
                   AIR MOLECULES, PARTICLES, WU;
                   -ADD SUN US HT IBLUE, WHITE) TO
                   VIEW PATH
                   -SUBTRACT LIGHT (BLUE, rtHITEl
                   COM)WS FflOhfl VIEWED TARGET
                   -REDUCE CONTRAST, ALTER COLOR
                   OF TARGET
                   -INCREASE HAZE
                                                                  INHEftENTCONTRAST: SPBCTF4L
                                                                  REFLECTANCE (COLOR). SIZE, SHAPE,
                                                                  DISTANCE , PATTE ftN. H on IZON .
   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.

-5 -4 3  2 -1  Q 1

           LOG I
                                                Z  3 4  S
   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).
> 140
5 120
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N = 1000


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                               4.6   3.0
                                    LOG CONTRAST, K
   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.



                           .05 .1      .51      5 10     50
                          SPACIAL FREQUENCY (CYCLES PER DEGREE)

   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.

   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).
                               WAVELENGTH OF LIGHT,

   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
   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

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.
2.3.1 Scattering and Absorption
   Visibility impairment is caused by the following interactions in the atmosphere:

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
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

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
       Where dl = the increase in intensity form added air light
       bext = the extinction coefficient

      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

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,
                      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

                       LIGHT tNTENSITV OF HORIZON
                             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

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.

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.

                           TARGET (1)
                    SO km
                                                             TARGET (2)
   Figure 2-12a. Limitations of Koschmieder relationship. When visual range is
short (1), extinction and illumination through sight path is uniform. When true
visual range is high (2), Koschmieder equation underestimates visual range because
extinction decreases with altitude and illumination (sun angle) at target is different
from that at observer. (Dimensions and earth curvature exaggerated for clarity)
(Malm, 1979a).
   Figure 2-12b.  Similarly, when viewing angel is not horizontal, extinction through
the site path is nonuniform. Koschmieder equation will underestimate visual range
(Malm, 1979a).
   Assumption 5: The visual range for nonblack  objects  depends strongly on initial
contrast,  which in turn depends on amount and angle of illumination,  or  if at night
depends on the power of the light source. As a result of this ambiguity, visual ranges for
nonblack objects or for lights at night cannot be related simply to each other or to optical
air quality.
   Assumption 6:  The effects  of target size,  texture, and  sensitivity of observer are
related to the nature  of human perception.  As discussed in Section 2.1,  in general the
"visual range" for small targets or contrast detail is significantly less than that for large
objects (Table 2-1).


Detail of
Very coarse


Angular size



sizes at 10 km
> 100



Examples for
a hillside at
Cliffs faces
Clumps of
clearings on
large trees,
clumps of
Visual range (km)
Vr= 100km



Vr = 20 kmb



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).
   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
                  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

most  commonly used units are km"1 and (lO'Vf1).   As extinction increases, visibility

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). Light  Scattering and Absorption by Single Particles—Particle size, refractive
index, and shape are the most important parameters in relating particle concentration and

particle derived extinction coefficients, bscat and bap.  If these properties are established,
the light  scattering  and absorption can be  calculated.   Alternatively, the  extinction
coefficient associated with an aerosol can be measured directly (see Chapter 3).
   Figure 2-13.  Rayleigh scattering by air (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).
                                                    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

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.
                                          1   1  M HIM

                       .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

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. 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
                 I   4
                 ?   2
                   I  I  ITTTn
   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

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).  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.

                  I I I  II I   TT
                 —     I
                                   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).
                     10€ —
   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.,

         0.1          1.0

   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

                                         MODE    COARSE.
   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

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. 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).

                                  ST. LOUIS AEROSOL

                                     APRIL, 1975
                                        FINE PARTICLE MASS (uQ.'m")
4/19     4/20

  TIME (days)
   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).
   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-
   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.

                                           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

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.

                         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.

Additional experimental data are needed to define the threshold of perceptibility for
plumes and haze layers.

   Figure 2-25. Appearance of a plume (Charlson et al., 1978).

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
NC>2 concentration in the plume

Observer related factors
Observer position
Observer sensitivity
Environmental Factors
Sun position
Time of day
Day of year
Cloud cover (sky color)
Other light sources
Ambient temperature
Relative humidity
Wind velocity
Wind direction
Wind turbulence
Table 2-2. Factors affecting plume appearance (Charlson et al., 1978).


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,

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,

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.

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,

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.

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,

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,

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.

        CHAPTER 3


   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.

   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.


   Regardless of the specific monitoring application, there are four components useful in
characterizing visibility impairment  and providing information that  may  link  visual
effects to their sources: human observations and measurements of optical, meteorological
and pollutant parameters.

3.2.1 Human Observations

   Since visibility is  an interpretation of what  is perceived by the human eye, it is
essential that any monitoring effort have some relation to human  observations. Human
eye  observation  is  the  sole source  of long-term  visibility  (visual range)  data.
Unfortunately,  human  eye  observations  depend  not  only  on  illumination,  target
characteristics, and air quality, but also include the effects of varying visual perception
and subjective judgment. Nevertheless, with the development of observer-based visibility
indices (Craik, 1979) and an adequate training program, human observations  can provide
useful information about visibility and can complement instrumental measurements.

   The Federal Land  Managers  of parks and wilderness areas represent an important
resource for human observation of visibility  in  class I  areas.  Although the traditional
observation for visibility has been "visual range," i.e., the farthest point that can be seen,
the U.S. Forest  Service has incorporated more  elaborate visual  judgments into their
Landscape  Management System  (USFS, 1973). The visual  elements  of  a  vista are
described in  terms of  "form, line,  color, and  texture.  "  These elements  represent
subjective descriptions of contrast, the basic  optical parameter. Meaningful judgments
made by a trained observer about  the  contrast and  coloration  of a vista and about the
presence of plume blight can be invaluable in assessing visibility impairment.

3.2.2. Optical Measurements

   In  order to quantify  scenic contrast as perceived by the  eye, optical measurements
must  be made. The visual air quality  along the  optical  path must also be measured in
order to determine the effect of atmospheric contaminants on the perceived scene.

   A number of optical devices are available or under development that measure some
property of visibility.  The most  obvious optical device is the standard  photographic
camera. Visibility monitoring should always include photography in some  form, at least
for documentation of existing good  visibility conditions or impairment problems. The
two general film formats are: negatives (from  which prints may easily be made) and
reversal film ("slides"). Both slides and negatives produce about equal color rendition.
Prints made from negatives, however, are subject to quality control uncertainty during the
additional laboratory printing process and  are one more generation removed from  the
original image. Slides  are more cumbersome to  use but normally are  more economical
and more visually accurate than prints.

   The chief use of photographs or slides is in preserving a scene in a form  similar to the
view as originally perceived. A secondary  use is photogrammetry, the measurement of
the density of color of individual sections of the picture to determine quantitative contrast
values of different elements of the  scene. The accuracy of this process, however, is
sensitive to variations in film density and exposure and requires a  densitometer closely
matched to the response curve of the particular film being used.

   Photometers measure light intensity and range in complexity from the photographer's
light meter to a television camera. The principle of operation for each instrument is the
same  and is somewhat analogous to the human eye. The heart of a photometer is  the
photodetector, which converts brightness into representative electric signals. By the use
of combinations of lenses and filters, different optical properties, such as color,  may  be

   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

   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 and coarse particles (>2 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).


   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

   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

c.  Relative humidity sensor,

d.  An NO2 detector, if necessary.

                                                              TABLE 3-1. VISIBILITY MONITORING METHODS"
      Parameters Measured
       Preferred Use
          Human observer
          Integrating nephelometer
Perceived visual quality
Atmospheric Color
Plume blight
Visual range
Scattering Coefficient
       at site
Sky and/or target
radiance, contrast at
various wavelengths
                                    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,
                                                                                                             Labor intensive; variability
                                                                                                             in observer perception;
                                                                                                             suitable targets for visual
                                                                                                             range not generally
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
                                                                        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

Areas experiencing
periodic well mixed
general haze; medium
to short viewing
distances; Email
absorption coefficient
(babs); relating to
point composition

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).

                                 TABU; 3-1. VISIBILITY MONITORING METHODS- (continued)
Visual quality
Btume blight
Contrast (limited)
Related to perception
of visual quality ;
documentation of vista
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
Permit evaluation of
     bif impairment.
Not always re I stable
to visual a\r quality;
point measurement.
Complement to visi-
bility measurements.

• ./•'.. -.•
Cascade impactor

Dichotomy* and
fine particle
samplers (several
different types)


Size segregated
(=> 2 stages)
Fine particles
coarse particles
[2.5 to 15 um)
m rial able particles
(0 to 15 um)

Large data base.
amertabte to chemical
anaf^sis; Coarse
•- 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
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.

   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

   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  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.

             I  UTAH    ~* *—•—».-
           /                 L
           /                              H.DU
           '                              T*
                                        tJ MiiA.AA. i in

                                                LU"                       COLORADO


               CANYON  -        *^-5
         /                   CANYONLANDS I                                            1

         1      RRYfF     *V   -__^TN     '                                            I
               — —	    XNAVAJO
       / ARIZONA          "^/*--—.
       I               A                   j  ...  ..             .        ..1-	_

     rx7          *SNCTN                  I                             NEW MEXICO I
      '             \Sx~~*-               I    \CHACOCANYQN                      I

  |       QRANDCANYoi?                   I
I                                      |    / \        \BANDELIER


V                                    .
                                                      WHITE SANDS
                     LEGEND  l*^-*-  T6LEPMOTOMETER VIEWS          X
                                                                      ^       BIG BEND
                                    CIRCLE INDICATES NEPHELOMETER
                       SOUTHWEST VISIBILITY MONITORING NETWORK                  i

          Figute 3-1. Project VIEW — EPA/NPS Southwest visibflity monitorin* network.


             £   -2


             u  .15
                     SOUTHERN US. AIR-MASS
                     BROAD HIGH PRESSURE

                     OVER SOUTHWEST
                           CANADIAN AIR-MASS

                           MOVES IN
                                                                            SOUTHERLY FLOW RETURNING

                                                  I   I  -'-I-1    I   I    I
0      2      4       68      10      12      14     16      18      20     22     24     26     28     30

                                            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:

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,

       CHAPTER 4



   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.,

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

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.


   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.

   The method by which the ambient aerosol chemical composition is sued as a tracer for
origin of the aerosol was formulated and described by Friedlander (1973).  Characteristic
tracer elements  such  as  vanadium (which comes primarily  from fuel  oil) and  lead
(emitted by the automobile)  can be used  as  indicators  of how much  these  sources
contribute to the ambient aerosol.  Application of this approach in various regions has
indicated that the relative amounts of fine particle constituents vary in different regions.
   The first comprehensive study of the size-chemical composition of a haze aerosol was
conducted in the Los Angeles  air basin as part of project ACHEX (Hidy et al., 1975). In
their study of the nature and origins of visibility-reducing aerosols in Los Angeles, White
and Roberts (1977) constructed  a chemical mass balance for the measured aerosol at
seven locations in the basin  (Figure 4-1).   The key contributing  species to the  total
aerosol  mass concentration  were  nitrates,  sulfates,  organics, and other  unidentified
substances.  Based on  a statistical  analysis of  light  scattering  (bscat)  and chemical
composition data, the authors concluded that sulfates are the most efficient scatterers
among the measured chemical species.
   Figure 4-1.  Geographical distribution of (a) particulate mass concentration and
(b) light scattering coefficient in the Los Angeles basin. The pie diagrams show the
relative contributions of nitrates, sulfates, organics, and other compounds.  Sulfates
evidently contribute only about 25 percent of the total mass but cause aobut half of
the light scattering. The estimated contributions of source types (oil, gasoline, and
other) to (c) mass concentrationo and (d) light scattering  coefficient are also shown
(White and Roberts, 1977).
   The chemical mass balance approach is enhanced by use  of size segregating particle
samplers, which distinguish between  fine (<  2.5 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).

                    PbO OS
               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).
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.
                              TOTAL SUSPENDED PARTICULATE, pwewit
                                         (78 ftfl/m'l
                 VOLATIZABLE CARBON 1.4
                 PRIMARY INDUSTRIAL 1.7
                 VEGETATIVE BURN l.B
                 MARINE 2.2
                                                  DUIT 19.1
                 GEOLOGICAL (SOIL, DUST, 17.5

                      NONVOLATIZABLE CARBON 0.7-


          UNIDENTIFIED £3

         SULFATE l.B
         NITRATE 1.5
                                     FINE FRACTION, pwant
                  RESIDUAL OIL DL$
                  PRIMARY INDUSTRIAL l.S
                  AUTOMOTIVE EXHAUST 1,0
                  NONVOLATIZABLE CARBON 1.1
                  MARINE 30
                  DUST £0
                  VOLATIZAILE CARSON 10B
                       UNIDENTIFIED 14.1

          VEGETATIVE BURN 06
                                                     UNIDENTIFIED 8 3
          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 -

                    40 -
                    20 -


_ 1 1 n IONS
•I Jl Jl jn




   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.
            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).
Air Molecules
Coarse Particles
Particle Size

0.1 to 1.0
0.1 to 1.0
0.1 to 1.0
1.0 to 20.0
Contribution to
Total bscat
Contribution to

   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).  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)

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. 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

0.0008  [km~V|lg/m3]  (Latimer et al., 1978; White and Roberts, 1977; Ursenbach et al.,
Southwest (Trijonis and
Yuan, 1978a)
Phoenix: County Data
Salt Lake City

Los Angeles (White and
Roberts, 1977)
Various Locations'3
(Cass, 1976)
Downtown Los Angeles
(Leaderer and Stolwijk,
Los Angeles Airport
Northeast (Trijonis and
Yuan, 1978b)






(Leaderer and Stolwijk,
New York b
New York
New Haven
St. Louis
Extinction coefficients per unit
Aerosol mass (km^/jig/mS
Nitrates Remainder of









(0.000 19C)

Total correlation
associated with the
regression a




   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

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.
                         A THEORtTlCAUY CM.CUI.AltDVALUES
                         O EMPIRICAL VALUES
                           (TRIJOWIS AMD YUAN, 1S7Sn).

                                       PELATIVE HUMIDITY
   Figure 4-7.  Light-scattering per unit mass of sulfate aerosol  as  a function of
relative humidity (Latimer et al., 1978). 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.

The term "b0" is assumed to represent Rayleigh scatter plus contributions to extinction
that are unaccounted for by the regression.

(Trijonis and Yuan, 1978a)
Salt Lake City
Los Angeles
(White and Roberts, 1977)
Various Locations b
(Cass, 1976)
Downtown Los Angeles
(Leaderer and Stolwijk,
Los Angeles Airport
(Trijonis and Yuan, 1978b)
(Leaderer and Stolwijk,
New York b
New York
New Haven
St. Louis
Average °
Average percent contributions to extra extinction a (%)












Remainder of TSP






Unaccounted for






   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

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. 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.

   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

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.


   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


   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,

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
Summer (third
Winter (first
Parallel between visibility
and sulfate trends
(Early 1950s - early 1970s)
Visibility decreased
substantially at
suburban/no nurban
Visibility changed very
little at metropolitan
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
The greatest decline in
visibility occurred in the
central/eastern states.

(Early/mid 1960's -
early 1970s)
Sulfates increased
substantially at
Sulfates changed
very little at
Sulfates rose
dramatically during
the summer. By
early 1970s, the third
quarter became the
worst season for
Sulfates changed
little during the
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
Potential explanation in terms of SOX
emission trends (early 1950s - early

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
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

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.
                150 -
   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

to sulfate and nitrate concentrations) increased substantially in the East from 1955-1956
to 1972-1973 (Likens, 1976).
                        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
   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

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.
              AN \1
1990 tO 70

*0  TO

                                    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).

                uz  75

                      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
   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 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

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.  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.
                      (MEASURED ON RIQHT AXIS1.
                KS 20
                          0 0
3000  £ a
anno  <
2000  I
                                 55     BO
                                                    70     7S
                PS 7D —
                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).

   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)

km'V(1000 TPD)

(t> 1.7 for 95%
(t 2.5 for 99%
   Table 4-5.  Correlation/regression analysis between airport extinction and copper
smelter SOx emissions (Marians and Trijonis, 1979).

   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,
   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
   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

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. 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.
         SCALE WILE*)
            URBAN AIRMBTS
           - 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.

   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
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.

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 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.
                       • DURING THE COPTER STRIKE, JULY 1967-MARCH 19B»
                        (34MiASUHEMENTS AT GRAND CANYON OR MESA VERDE)
                                       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

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

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.
                                               QUARTER 3
          3. _
          0 lii
                                                                       d _
           194D    1960    1960    1970    1980

                  CENTRAL/EASTERN STATES
1940   1950    1960    1370   1080

   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,

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.

   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
   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

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
   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.
            u- <
            O -3
._ 1949-W56
— 1967-1976
  THE OECADE 1967-1978
                  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).

   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).


   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,

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
   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.

                I ,
                   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.

   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).
                u  .04
                                              O LABADIE

                                              • FOUR CORNERS
.8   °    o
 o   °           d
                             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).

   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

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.
San Manuel Smelter
Other compounds
Coarse particles

Mohave Power Plant
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)
Contribution to total
particle scattering (%)


   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.

Labadie Power
Plant3 (St.

Four Corners'5
Power Plant
(New Mexico)
San Manuel0

Power Plant,
(+ wind blown



Visibility perpendicular to plume (through plume)
(From experimental data)
Visual Range
due to
(Normalized to "clean"
Visual Range
due to
   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).

                                                           POWER PLANT

   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.
                             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.

                                                3 dr.

                              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

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."

                                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
   Important  questions remain  to be answered about regional  scale episodes of haziness,
including the  following:

1.  Do the hazy air  mass and  the  meteorologically defined anticyclone  completely

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

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.

   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.


   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

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.
Fraction of emitted sulfur deposited locally
Fraction of emitted sulfur transformed
directly to sulfate
Decay rate of sulfur dioxide
Transformation rate of 862 to sulfate
Loss rate of sulfate
Mixing height

   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).

   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


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EPA (1975) Position Paper on Regulation of Atmospheric Sulfates. Publication No. EPA-
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FPC (1976) Form 67. Steam Electric Air and Water Quality Control Data for  Labadie,
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Frank, N.  and N. Posseil  (1976)  Seasonality and Regional Trends in  Atmospheric
Sulfates, Presented  before The  Division  of Environmental  Chemistry,  American
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Friedlander, S.K. (1973) Chemical Element Balances and Identification of Air Pollution
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Galvin,  P.J., PJ. Samson,  E.G.  Peter,  and D.  Romano,  (1978) Transport  of Sulfate to
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Gillani,  N  .V. (1978) Project MISST: Mesoscale  Plume Modeling of the Dispersion,
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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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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.

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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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.

Leaderer, B.P., D.M. Bernstein, J .M. Daisey, M.T. Kleinman, T J. Kneip, E.O. Knutson,
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Summary of the New York Summer Aerosol Study (NYSAS) J. Air Poll. Contr. Assoc
28:  321-327.

Leaderer, B. P., T. R. Holford and J. A. J. Stolwijk (1979). Relationship Between Sulfate
Aerosol and Visibility. J. Air Poll. Cntr. Assoc. 29:154-157.

Lewis, C. W. and E.  S. Macias, (1979)  Composition of Size-fractioned Aerosol in
Charleston, West Virginia, submitted for publication.

Likens, G.E. (1976) Acid Precipitation. Chemical Engineering News 54: 29-44.

Loo, B.W., W.R. French, R.C. Gatti,  F.S. Goulding, J.M. Jaklevic, J. Llacer,  and  A.C.
Thompson,  (1978)  Large-scale  Measurement  of  Air-borne  Parti culate  Sulfur.
Atmospheric Environment 12: 759- 771.

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-
scale Air Pollution Episode. Mon. Weather Rev. 104: 1623-1626.

Macias, E.S., D.L. Blumenthal, J .A. Anderson, B.K. Cantrell (1979) Characterization of
Visibility Reducing Aerosols in the  Southwestern United  States; Interim Report on
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Macias, E.  (1979)  Personal  Communication. California  Institute of  Technology,
Pasadena, CA. July.

Macracken, M.  C.  (1978) MAP3S: An Investigation of Atmospheric, Energy Related
Pollutants in the Northeastern United States. Atmospheric Environment 12: 649-659.

Marians, M.  and J.  Trijonis (1979)  Empirical Studies  of  the  Relationship  Between
Emissions and Visibility in the Southwest. Prepared at Technology Service Corporation,
under Grant 802015, for EPA Office of Air 4-49

Quality  Planning and Standards, and Atmospheric Chemistry and  Physics Division of
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Munn, R. E.  (1973)  Secular Increases in Summer Haziness in the Atlantic Provinces
Atmosphere 11: No.4.

Niemann, B.  L., E.  Y.  long, M.  T. Mills and  L.  Smith (1979) Characterization  of
Regional Episodes of Particulate Sulfates and Ozone Over the Eastern United States and
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Samson,  P.  J.   (1978) Ensemble  Trajectory  Analysis  of  Summertime  Sulfate
Concentrations on New York. Atmospheric Environment 12: 1889-1893.

Samson, P. J.  and K. W.  Ragland (1977) Ozone and Visibility Reduction in the Midwest:
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Tong, E. Y.,  G. M.  Hidy, T. F.  Lavery,  and F.  Berlandi, (1976) Regional  and Local
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Protection Agency, Research Triangle Park, N.C.

White, W. H., and R. B. Husar (1976) A Lagrangian Model of the Los Angeles  Smog
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White, W. H., J. A. Anderson, D. L. Blumenthl, R. B. Husar, N. V.  Gillani, J. D. Husar,
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Vukovich, F. M., W. D. Bach, Jr.,  B.  W.  Crissman, and W. J. King, (1977) On the
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White, W. H., J. A. Anderson, D. L. Blumenthol, R. B. Husar, N. V. Gillani, J. D. Husar,
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Aerosols in the Los Angeles Air Basin. Atmospheric Environment II: 803-812.

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Atmospheric Environment II: 797-802.

        CHAPTER 5



   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.


   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.


   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.





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                          Figure 5-1. Grnrral viilhlllry model.
                                                    MlXINQ HEIGHT
                  PLUME fiUQHT
                         ' "--' '  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

? -,
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                                 ,  CLIMATIC
   GRID     V
     N   AIR
                                    > QUALITY
                                    „	\
                                                                             i I
                             1          10          100        1000         10,000
                                LOCAL  AIR BASIN  REGIONAL  GLOBAL
                                             DISTANCE, km.

        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

                          POLLUTANT CONCENTRATIONS X(ic, y. z, t)
 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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                                 INCREASED HAZINESS OR REDUCED VISUAL RANGE
                                  PLUMES BLUER THAN BACKGROUND SKY
                                  (OR LESS YELLOW-BROWN)
                                  PlUMiS MORE RED (OR YELLOW BROWN)
                                  THAN BACKGROUND SKY
                                  PLUMES BRIGHTER THAN BACKGROUND SKY
                                  PLUMES DARKER
                                               THAN BACKGROUND SKY
                              1    11
                                  INCREASING PLUME (OR HAZE! PERCEPTIBILITY
                       1      2      4   6    10     20     40  60   100    200

                                 LOCATION OF OBSERVER DOWNWIND OF POWER PLANT (km)
  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.

    a.  Orijciiliil slid*-, "Vlcaii**
       visual raiifjr 2 SO kin.
                                  digitized lhruU)Kll
   c.  Simulated pollution: I !}i i  I n: Kflrcl nf uildition of
                   lift ;JK/IH'' of niillaU* Ni (In. \IXIKI| rangf 2O km.
iiit. and ^ii
                                                                         « AVitli:im» «•! al..
  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.

5.3.2 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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                             (1) NORMAL NOX EMISSIONS; 0.5 PERCENT/HR SULFATE FORMATION
                             (2) NORMAL NQX EMISSIONS; NO SULFATE FORMATION
                             (3) NO NOX EMISSIONS; 0.5 PERCENT/HR SULFATE FORMATION
                             (4) NO NOX EMISSIONS; NO SULFATE FORMATION
                                                                    .1 AND3
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                                           3 AND 4 (NO NO,
                                               AND 2 (NORMAL NOX)
                                       10      20       40   80
                                       DOWNWIND DISTANCE (KM)
Figure 5-7. Visual effects predicted for a 2250 MW hypothetical power plant with stability D. Mew
perpendicular to the plume with sun overhead (90° light scatter).

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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                           (1) EASTERN U.S. (BACKGROUND VISIBILITY = 15 KM)

                           (2) WESTERN U.S. (BACKGROUND VISIBILITY = 130 KM)
                                                      ~' '  'i
                                                          I   ill
           f «
        o  S.O
                              4    6     10      20       40   60   100      200
                                       DOWNWIND DISTANCE (KM)
                         HYPOTHETICAL 2250-Mwa COAL-FIRED POWER PLANT;

Figure 5-8. Comparison of predicted phime visibility in the eastern and western United States. Higher

background particulate loadings mask NO2 related discoloration.

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      £ 10.0

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                                    6      10        20       40    60
                                       DOWNWIND DISTANCE (KM)
                      SCATTERING ANGLE OF 45°
Figure 5-9. Comparison of predicted visibility impairment for stabilities C, D, and E (slightly unstable,

neutral, slightly stable). A single stability would rarely occur over the entire transport time and distance.

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                                                    _J	I   I  1  ]  I 1
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                                  6     10       20       40   60    100
                                      DOWNWIND DISTANCE (KM)
                         HYPOTHETICAL 2250-Mwe COAL-FIRED POWER PLANT; BEST
                         NOX EMISSIONS AT NSPS.
Figure 5-11. Comparison of effects of different eulfate formation rates. A marked increase in predicted
haze occurs at rapid aulfate formation rates (5% per hour). Based on limited plume studies, overall
Western conditions average about 0,5% per hour and range from 0 to 2% per hour (Wilson, 1979),


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                      NOX, SOX AT MAXIMUM NSPS LEVELS.
 Figure 5-12. Comparison of effect of available ambient ozone on predicted visibility impairment from

 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.


   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

         "•,,^7^rijc„ "Hi"-
                                                                                        >"i~-ii-"f'-"'- -
. Thf
.   ;Ht«t i» r\(rrnM-l\  ilidiruft  In Itmtli'l,
                                                                       tti of l

   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.


   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

   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

   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.


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.

       CHAPTER 6

  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
Big Bend (1200m)
Grand Cany on (2 100m)
Bryce Canyon (2500m)
Mt. McKinley (6000m)
Sea Level
Scatter3 (km'1)
Visual Range
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.

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).

   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.
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

   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).
  < LU
  -I O
       122S           1227           1229
                      TIME (PST)
                                    0        B
                                    1  I i ,..,_._)
                                     SCALE (km)
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.

                  SCLE ROPH Y L L SCRUB

                  fleC'OUQUS FOREST

                    fttOUS FOREST


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


Rain forest




Tundra, alpine

Vegetation type







Leaf bio mass,







Emission factors, |J,g/m2 - hra
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.

   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)
   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.

   VI SI Bl LI TV > 80 km
                       IND SPEED
                       > 1fl m/t
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)

   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

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).

                                     .:•*•-	0-1             -«6."

                                     >::3i^-^':>i-^i         ,**t^*a

                                     -^-	-_ :/.--- i^iSI/-!-^^-*^.'''^-*.*

                                    --* :: -^i' ^"
                                    _™^.	1,^^-;..,	 ,. f^ _-.™i«r--». •j.^S^ti*—.-«Tfc'**»»*H«. j
Source Category
Highway vehicles
Non-highway vehicles
Stationary fuel combustion
Electric utilities
Residential, commmercial, and
Industrial processes
Petroleum refining
Mineral products
Oil and gas production and
Industrial organic solvent use
Other processes
Solid waste
Forest wildfires and managed
Agricultural burning
Coal refuse burning
Structural fires
Mescellaneous organic solvent use
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

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). 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

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 ,




                         PARTICLE SIZE, tin
Figure 6-14. Comparison of Control Device fractional efficiency (Weast, 1974).

Source type

Utility boilersb'°

Copper smelters
Industrial boilersb'e

Kraft pulp millf'g

Power boiler6
Recover furnace

250 MW
500 MW
metric tons/year

150x 106BTU/hr
200 x 106BTU/hr
150x 106BTU/hr
1000 TPD
20 MW


Fabric filter


Fabric filter


Fabric filter
Costs (106 dollars) a






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.
Electrostatic Precipitator

Fabric Filters
Coal Fired Boiler, High
Sulfur Coal
Coal Fired Boiler, Medium
Sulfur Coal
Coal Fired Boiler, Low
Sulfur Coal
Coal Fired Boiler

% Efficiencies Fine Particles
(0.1 to 1 mm)
90-99.. 3
Table 6-5. Particle collection efficiency of controls (Abbott and Drehmel, 1976).

------- 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
   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

250 MW

500 MW

1000 MW

200 x 106

150 xlO6

150 xlO6

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)
30 x 106
60 x 106
12 x 106
120 x 106
14 x 10"
10.5 x 10"
0.75 x 106
14 x 10"
Annual6 (
------- 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


smelters e>f
250 MW
500 MW
1000 MW
200 x 106

150 xlO6



contact acid
plant + MgO
FGD system

1-5 lb/106

3. 5% sulfur

Costs (106 1978 dollars) a'b






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

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.

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.

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.

      U'l 1WO 1(M »19
Tin 1595 159* MIC

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.

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).

------- 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.
                                         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).

                 • ZINC SMELTERS
                 * LEAD SMELTERS
                 • 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. 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,
Figure 6-24. Existing pulp mills (Post, 1975).

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.  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).

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
   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
   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

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.

Figure 6-28. Population distribution, 1970.
-J 70%
'\ 1-07
V 17% '


; 32%
. 1.64
$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
Figure 6-29. Projected population growth by State, 1978-2000 (DOC, 1977b). 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.

                           UNPAVED ROAOS,
                           OFF ROAD VEHICLES
                                               AGRICULTURAL TILLING
                                                  PAVED ROADS
                                                 AGGREGATE STORAGE
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).

Figure 6-31. Fugitive dust emissions from strip mining.
ore loading
Haul road truck

Truck dumping

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
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
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-
2390-6860 J'k
No data
No data

100-360 ''m (90-

1,000 m2
(10,000 ft2)





Enclosure and exhausting of transfer
points to fabric filter/Limited
Very little control needed since
basically a wet process
Continuous spray of chemical on
material going to storage piles/Rarely
Watering (sprinklers or trucks)/Rarely
Chemical stabilization/Limited
Vegetation/Commonly practiced
Combined chemical-vegetative
stabilization/Rarely employed
Slag cover/Limited practice

90% c
50% a
80% d
65% e
90% a
90-99% a

0.5-1.50 '(.10-
No data
40-100 (160-400)
g; 65-150 (250-
h (hydroseeding)
25-40 (100-160) '

of chemical

1000 m2
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. 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. 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.

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
   1 • 2,499
5,000 - 7,499
 7,500  9,999
10,000- 14,999
15,000 19,999
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

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,
   Although a number of means for reducing impacts of prescription fires on class I areas
visibility exist, they will be difficult to implement.  The least costly method is to restrict
burning to periods of minimum impact on class I areas or limit such impacts to times of
low visitor utilization. In the  Oregon/Washington area this  approach may conflict with
existing health protection goals or at best significantly reduce the frequency of allowable
burning conditions.  Reduction of burns might have adverse impacts on the silvicultural
and hazard reduction objectives  of forestry practices.  Smoke from burning can also be
reduced  by  improved  burning practices and  technology.   A  number of possible
alternatives to forestry burning are listed in Table 6-10. The feasibility, effectiveness and
environmental impacts of these approaches vary  with site.   Most of these  alternative
methods are useful  for  disposal of accumulated  slash material.  However,  practical
alternatives to the use of fire for improving wildlife habitat and reducing fire hazard in
non-harvested areas have not been documented.
Forest Service
Region (See
Figure 6.32)
Burns of Timber
Harvesting and Land
Clearing Residues
(slash) (million tons/yr)
27.60 (69%)
Burns of Naturally
Occurring Forest
Residues (million

Total Material
Burned (million
40.33 (100%)
Table 6-9. National Prescribed Burning Statistics (Pierovitch, 1979).

Figure 6-34. Prescription fire in forested area (Pierovitch, 1979). 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
Figure 6-35. Agricultural (grass seed production) burning in Willamette Valley, Oregon.

Table 6-10.  Major alternatives to prescribed burning.


Abbott, J. H., and D. C. Drehmel (1976) Control of Fine Particulate Emissions. CEp, pp.

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,

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
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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
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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.

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:
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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,
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EPA (1977b)  Technical Guidance for Control of Industrial Fugitive Particulate Emissions
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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
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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
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Forest Service, 1975 Wildlife Statistics  (1976) Cooperative Fire Protection Staff Group,
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Pollutants. EPAPB-223. U.S. Environmental Protection Agency, Washington, D.C.

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Environmental Protection Agency, Seattle, Washington.

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Husar, R. B., W. H. White, D. E. Patterson, and J. Trijonis (1979) Visibility Impairment
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ICF (1979) The Final Set of Analyses of Alternative New Source Performance Standards
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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,
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Marians, M. and J. Trijonis (1979) Empirical Studies of the Relationship Between
Emissions and Visibility in the Southwest. Prepared at Technology Service Corporation,
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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.

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Southwest-Rocky Mountain Northern Great Plains Region. Part I Slide Script. Prepared

for U.S. Environmental Protection Agency, Office of Energy Materials and Industry,
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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):

Patterson, E. M., D. A. Gillette and G. W. Grams (1976) The Relation Between Visibility
and The Size-Number Distribution of Airborne Soil Particles. J. Appl. Mgt. 15:470-478.
Pierovich J. (1979) Personal Communication. U.S. Forest Service, Southern Forest Fire
Laboratory, Macon, Georgia

Post's 1975 Pulp and Paper Directory (1975) Miller Freeman Publications, Inc., San
Francisco, Calif. 612 pp.

Radke, L. F.,  J. L. Stith, D. A.  Hegg, and P. V. Hobbs (1978) Airborne Studies of
Particles and Gases from Forest Fires. J. Air Pollut. Contr. Assoc. 28:30-34.

Richard, G. (1977) An Implementation Plan for Suspended Particulate Matter in the
Phoenix Area, Volume IV: Control Strategy Formulation. EPA-450/3-77-021d, U.S.
Environmental Protection Agency, Research Triangle Park, N.C.

Roeck, D. R.  and R. Denum (1979) Technology Assessment Report for Industrial Boiler
Applications: 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.

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.

        CHAPTER 7


   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.


 7.1.1 Nature of the Preliminary Analysis

   A fundamental process in conducting programs for protecting class I areas visibility is
to evaluate existing visibility, to identify sources of perceptible impairment, and to
establish visibility management objectives on a national, regional, or area specific basis.
(Such objectives could take the form of criteria for incorporating visibility value
judgments in case-by-case control decisions. See 7.2.3) A comprehensive evaluation
might involve a year or more of monitoring, source identification and modeling, and
judgments on the nature, frequency, and extent of significant or adverse visibility
impacts.  Clearly, it will be some time before complete assessments are available for the
156 class I areas.

   Therefore, in order to develop guidance in the interim for control programs, EPA
requested that the Federal Land Managers (National Park Service, Fish and Wildlife
Service, Forest Service) perform a preliminary national assessment of visibility values in
their respective class I areas. In conducting their assessments, the Land Managers  relied
on the collective expertise of individual park managers and field and regional office
personnel. Visibility analysis "workbooks " were developed and distributed for
completion by managers representing each of the 156 areas. Although the format
developed by the three land management agencies  differed in specifics, each requested
the same basic information. An example of one of the workbooks is included as
Appendix B.

   The workbooks generally called for the following kinds of information:

   1. General information on the current status of visibility, including:

       a) Man-made sources of air pollution which may significantly affect visibility,

       b)  Sources and significance of natural visibility degradation (e.g., fog, dust),

       c) Impact of area management practices which may significantly affect visibility
          (e.g., prescribed burning, campfires, traffic),

    2. An assessment of the individual scenic resources in the area, including:

       a)  Identification of the important vistas in the area,

       b)  An assessment of current visibility conditions specifying degree and extent of

       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.

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. 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.

                                                                                                                        NEW ENGLAND
                                      NORTHERN ROCKIES/
                                                                 ~    '
/  »*<*°t|uji»   I
COAST  Vvrr-r

                 s. ARIZONA
                                                       Figure 7-1. Class I area reguns.

 V -. 10 miles

 10 miles • V - 15 miles

 15 ml les •' V - 25 mi 1 es

 2!> miles • V - 45 miles
. 4b mi les • V - 70 mi 1es
i A) miles  V
                        Figure 7-2. \isual Range bopletha—Summer 1974-76 (TKjonis and Shapland, 1978).

                                               TABLE 7-1. STATUS OF CLASS I AREA VISIBILITY IMPAIRMENT9
Number of
Region («e map) areas

Potential sources8
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
Generally impaired outside areat.
some impairment in area}
Impairment outside areas,
1 r>Mrmi ItSn I in Steal
Smoke, haze
Visible pJurmt
1,2. Agricultural
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
2. Prescribed burning
1^. Wildfires;
1,2. WiWfires
3. Windblown
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
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
"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
1. Wildfire*
2, Windblown
3, Fog
1 , Natural haza
2. Wildfires
        : rmorrig ertaroy
prediction activities;'
auocratedL population

Significant copulation
growth in COt UT;d
aaociat«d urban, &thar
devil opment.
Possible decreate in
smaltBr impact) from .
air quality standard
Southern Arizona
Gantrally impaired
                                                                             1 ,  Regional haze
                                                                             2,  Dust
                                                                             3,  Smoke
                                                                       1, Smelter*; urban
                                                                       piumst |Phd«nix,
                                                                       Tucson I
                                                                       2, AgricultuTal
                                                                       activities; burning
                                                                       3, Prestrkxid burning
                           1,  Natural haze
                           1,  Windblown
                   PottlbJe Further de-
                   crease in arrveltBrs
                   tmtetiortt to attai n a ir
                                                                                                                                                 CJUaM«if *%B« M*aiu*,~       .
                                                                                                                                                 major popuiation growth,1^
             Cenarally desirable visibility
                     aSS*88 not«d
                                  1, Haze-
                                  2, Dust
                                  3, Smoke
1, Smelters
2, Agricultural
3, Prescribed burning
t. Natural haze
2. Windblown
Postal* deereas* in
smelter impacts,*
increased gan«ral

                                     TABLE 7-1. (continued} STATUS OF CLASS I AREA VISJBUJTY IMPAIRMENT3
Number of
class 1
Region (see map) aratt
Fotsiitial tourcei*
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
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,

   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. 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. Variety of Sources  and Control Approaches Needed - The preliminary analysis
indicates that the mix of sources that tend  to dominate visibility impairment varies greatly
throughout the country. The most frequent sources of impairment named by the Land
Managers include (in alphabetical order):

   1. Agricultural activities-burning, fugitive dust

   2. Forest product development-prescription fires, pulp and paper mills, saw mills

   3. Miscellaneous point sources-usually in connection with visible plumes

   4. Natural sources-fog, natural haze, wind-blown dust, smoke from vegetation burning

   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

   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. 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.


   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

        NEW DATA
        DOE, INDUSTRY)
                            CLEAN AIR ACT AMENDMENTS
                                 NATIONAL GOAL
                                SECTIONS 169A, 165
                (STATES. FLM, EPA, INDUSTRY}
                1. REVIEW AVAILABLE DATA
                Z. MONITOR IMPAIRMENT
                3, IDENTIFY SOURCES
                4, MODEL IMPACTS
                6, ESTIMATE NATURAL
                  BASE LINE
                    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
                                                   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
                                  h) EVALUATE IMPACT OF
                                    EXISTING AND NEW
                                    SOURCES NOT ADDRESSED
                                    BY BART, PSD
                                  c! ALTERNATIVES
                                    1, TRADITIONAL EMISSION
                                      LIMITATIONS AND
                                    2. SECONDARY AIR
                                      QUALITY STANDARD
                                      FOR FINE PARTICLES
                                    3, ECONOMIC INCENTIVE
                                 MONITOR PR OGRESS TOWARDS
                                      NATIONAL GOAL
              Figure 7-3. Conceptual framework for visibility protection

       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

   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. 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. 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

                    7-2. TOTENTIAL APPLICABILITY Of
                 TO                                           BY FLW
         Source category
Agricultural activities
        Burnt np
        Fugitive dust
Forest product development
        Pulp and      mills
Miscellaneous point sources
Prescription fires
        Single identifiable

Urban pollution

        Mo I Of vt hides
        Space heating
        BART applicability
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


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.


   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

    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
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. 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.


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.

       CHAPTER 8


   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.


   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.


   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.


   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.


8.4.1 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.


   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.


   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


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,

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:


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).
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
1 2,646
1 ,949,493

Public Law
91 -622

91 -504
Federal Land



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
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




51 ,488
1 ,397,429

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
26 Stat. 478


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




, and 31,488 acres

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
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°


Public Law
17 Star. 32
(42nd Cong.)
Federal Land


.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



  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.


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

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,
Public Law Federal Land
, and 83,800 acres are in Idaho.

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
221 ,896

North Carolina and 3,832 acres in
74-1 57
30 Stat. 993
(55th Cong.)
t in Tennessee.


Stats Area Name

,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.

overall, of which 2,020,625 acres are in Wyoming,
Public Law
81 -787
17 Slat. 32
(42nd lonsl
167,624 acres are
Federal Land

in Montana, and
S81.437 Maw Brunswick,   Reoseygtl CampobeHo
        Canada,           International Park
                          t applicable