United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park NC 27711
EPA-450/4-81-036
August 1981
Air
Existing and Natural
Background Levels
of Visibility
and Fine Particles
in the Rural East
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EPA-450/4-81 -036
August 1981
Existing and Natural
Background Levels of Visibility and
Particles in the Rural East
by
John Trijonis
Santa Fe Research Corporation
228 Griffin Street
Santa Fe, New Mexico 87501
Project Officers: E.L Martinez
J.Bachmann
Prepared for: U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air, Noise and Radiation
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
August 1981
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This report is issued by the U.S. Environmental Protection Agency to
report technical data of interest to a limited number of readers.
Copies are available free of charge to Federal employees, current EPA
contractors and grantees, and nonprofit organizations - in limited
quantities - from the Library Services Office (MD 35), Research
Triangle Park, N.C. 27711; or, for a fee, from the National Technical
Information Service, 5285 Port Royal Road, Springfield, VA 22161.
This report was furnished to the Environmental Protection Agency by
Santa Fe Research Corporation, 228 Griffin St., Santa Fe, N.M. The -
contents of this report are reproduced herein as received from Santa Fe
Research Corporation. The opinions, findings and conclusions expressed
are those of the author and not necessarily those of the Environmental
Protection Agency. Mention of company or product names is not to be
considered an endorsement by the Environmental Protection Agency.
Publication No. EPA-450/4-81-036
ii
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ABSTRACT
An investigation is conducted into existing and natural background
levels of visibility and fine particles in nonurban areas of the Eastern U.S.
An analysis of data for 100 airports nationwide indicates that nonurban areas
of the East experience relatively low visibilities; specifically, rural area-s
east of the Mississippi and south of the Great Lakes generally exhibit an-
nual median visual ranges of 10-15 miles. A review of data from eight moni-
toring programs indicates-that ambient fine (| 2.5 ym) particle concentra-
tions presently average approximately 29 yg/nr in the rural East. The lar-
gest components are water (^ 11 yg/m3), sulfates (^ 9 ug/m3), and organics
(^ 4 yg/m3). The majority of the water is thought to be attached to hygro-
scopic sulfate aerosols. Currently, sulfates and fine particles exhibit a
pronounced maximum in the summer quarter, when visibility shows a pronounced
minimum. This seasonal pattern is a new phenomenon historically; prior to
the 1960s, visibility was distinctly higher during the summer than during the
remainder of the year. An investigation of natural background conditions
suggests that natural fine aerosol concentrations would average 5% * 2% yg/m3
in the East, with the largest components being organics and water. Natural
background visual range for the East is estimated to be 60 * 30 miles. It
is not currently possible to check this estimate of natural background visual
range through an analysis of historical visibility trends from the 1930s to
the 1970s because of limitations in historical emission trend data, uncer-
tainties in airport visibility trend data, and the confounding effects of
meteorology. The best check would be to collect simultaneous measurements
of fine particle mass, fine particle chemical composition, and visibility in
remote continental areas of the Southern Hemisphere.
m
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INTRODUCTION
During the past decade, numerous studies have been conducted of large-
scale regional air quality problems in the Eastern United States. Based on
the results of these studies, it is now generally accepted that the Eastern
U.S. experiences a regional problem with respect to fine aerosols (particles
£ 2.5ym in diameter). Fine aerosol concentrations in rural areas of the East
significantly exceed those in other areas of North America, and visibility
in the rural East is correspondingly low. Because acid sulfate particles
constitute a large fraction of the Eastern aerosol (Pierson et al. 1980;
Stevens et al. 1980; Ferman et al. 1981), the fine aerosol and visibility
problems may be closely linked with the regional acid rain phenomenon."
One major purpose of this paper is to characterize existing levels of
visibility and fine particles in rural areas east of the Mississippi. In
this paper, we document existing visibility patterns by analyzing three years
of visual range data from one hundred airports. We then construct a chemically-
resolved model fine aerosol —annually and spatially averaged for the nonurban
East — by analyzing recent particulate data from eight monitoring programs.
Seasonal variations in visibility and fine particles are also considered.
The second major goal is to estimate natural background conditions, so
that natural versus man-made contributions to existing fine particle concen-
trations can be better understood. A chemically-resolved model fine aerosol
for natural background conditions is determined based on emission calculations,
trace element calculations, and data collected in remote areas. The model
natural aerosol yields an estimate of natural background visibility. We also
investigate the possibility of checking this estimate of natural background
1
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visibility through an analysis of historical visibility trends from the early
1930s to the early 1970s.
EXISTING VISIBILITY LEVELS
In order to characterize existing visibility levels in rural areas of
the East, and in order to compare Eastern visibility to visibility elsewhere
in the nation, we have conducted a comprehensive analysis of daytime visual
range measurements at 100 suburban/nonurban airports nationwide (Trijonis
and Shapland 1979). Daytime visual range measurements at airports are made
by observing distant markers (e.g. mountains or buildings) against the horizon
sky. Before selecting locations for this study, telephone surveys were con-
ducted at each airport to insure that an adequate set of markers was available
for estimating visual range. Specifically, we attempted to select only those
airports that had very distant markers relative to the average visual range
for the surrounding region. In a few cases, however, in order to attain com-
plete geographical coverage, we were forced to use airports with markers at
relatively short distances (e.g. at only 10 to 15 miles).
Our analysis of existing visibility levels is based on median visual
ranges calculated from cumulative frequency distributions of the airport
data. Because the nature of reporting practices at airports leads to an
implicit "greater than or equal to" meaning in the visual range recordings,
special techniques must be applied in determining these cumulative frequency
distributions (Trijonis 1979; Trijonis and Yuan 1978; Trijonis and Shapland
1979; Husar et al. 1979; Latimer et al 1979; Sloane 1980). Specifically,
the cumulative frequency distribution must be given in the form "percent of
time visual range is greater than or equal to X miles", starting with the
-------
most distant marker and proceeding sequentially to the less distant markers.
Furthermore, the points in the cumulative frequency distribution should be
plotted only at the visual ranges that are routinely reported by the airport
observation team; otherwise artificial "kinks" will be produced in the fre-
quency distributions. Application of these special techniques should make
the distributions consistent from site to site, even if the airports have
visibility markers at different distances.
Figure 1 presents examples of cumulative frequency distributions for
six rural locations in various parts of the United States. The dots in
Figure 1 represent the routinely reported visual ranges (often these cor-
respond to distinct visibility markers). The lines drawn between the dots
represent linear interpolations of the cumulative frequency distributions.
As is the case with five of the six locations in Figure 1, most of the median
visual ranges are determined by linear interpolations of the cumulative fre-
quency distribution. At some sites (e.g. Madison WI in Figure 1), however,
the frequency distributions require extrapolation beyond the farthest marker
in order to reach the median visual ranges. The forms of these extrapola-
tions, linear or nonlinear, are based on a comparison of the distribution for
the station in question with distributions for other sites located in the
same general geographical area.
Based on the above analytical procedure, we have derived Figure 2, a
map of median mid-day visual ranges for rural areas throughout the United
States. The rather high quality of the data in Figure 2 — at least in terms
of internal consistency ~ is suggested by the monotonic gradients that often
exist in passing from areas of poor visibility to areas of good visibility,
-» •*
and by the agreement of the readings among neighboring stations.
-------
9.0- Grand Junction CO
10-
I
10
III I I I I
20 30 40 50 60 70 80 90 100%
Cumulative Frequency (percent)
Figure 1. Examples of cumulative frequency distributions for
visibility (data for mid-day hour, 1974-1976).
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2515
P: Based on photographic
photometry data
N: Based on nephelometry data
*: Based on uncertain extrapolation of
visibility frequency distribution
Figure 2. Median annual visual range (in miles) at suburban/nonurban
locations in the United States (1974-1976).
-------
Figure 2 demonstrates that the mountainous Southwest experiences the
best visibility in the country. Specifically, median visual range exceeds
70 miles in a region comprised of Utah, Colorado, Nevada, northern Arizona,
northwestern New Mexico, and southwestern Wyoming. Visual range is also
quite good, exceeding 45 miles, to the north and south of this region.
Passing westward or eastward, fairly sharp gradients occur. Median visual
range falls to less than 25 miles in a narrow band along the northern Paci-
fic coast and to less than 15 miles in the Central Valley of California and
the Los Angeles basin. Although some parts of the East (e.g. northern New
England) experience moderate visibility levels (^ 25 miles), median visual
range is generally less than 15 miles in areas east of the Mississippi and
south of the Great Lakes. This Eastern area of low visibility is the focus
of the present paper.
EXISTING FINE PARTICLE CONCENTRATIONS
Table 1 presents average mass concentrations of fine particles (^ 2.5
ym) obtained from several monitoring programs in rural areas of the Eastern
U.S. Data are presented not only for total fine particle mass but also for
fine particle chemical composition. Because some of the monitoring programs
operated only during the summer, Table 1 is divided according to summertime
and annual monitoring programs.
As indicated in the left-hand column and the footnotes of Table 1, we
have made several adjustments in order to establish a consistent basis for
comparing data from the various monitoring programs. For example, we have
reported all the sulfate mass data as ammonium bisulfate (NH^HSO^), because
6
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TABLE 1. SUMMARY OF AVAILABLE DATA ON FINE PARTICLE CONCENTRATIONS IN RURAL AREAS OF THE EASTERN U.S.
ANNUAL MONITORING PROGRAMS
SUMMER!IMt MONITORING PROGRAMS
STUDY
SAMPLING LOCATIONS
*
SAMPLING PERIOD
AVERAGE FINE
AEROSOL MASS
Sul fates
(as NH4HS04)
Organ ics
(as CH20sJ
Elemental
Carbon
Crustal
(as 4 x Si)
Nitrate
(as Nll4N03)
Other
(Water?)
10TAI
EPA Dkliotoinous
Sampler Network
Average of
Will Cnty. IL,
Erie Cnty. NY,
and Durham Cnty.
NC
One year,
10/79 to 9/80
7.7
NA
NA
1.4
1.0
NA
20.3
l)/.uluy (I9ij0)
Iri jonis et .il .
(1980)
Average of
two rural sites
near St. Louis
One year, 1976
8.1
NA
NA
1.4
NA
NA
16.5
UiiUon et .1 1 .
(1981)
Mueller (1981)
Average of
nine nonurban
SURE sites
Six months
of data
8/77-10/78
7.7
NA
NA
NA
NA
NA
,9.0
LPA NASN
Network
Average of
twenty nonurban
Eastern sites
Three years,
1974 to 1976
*
9.2
NA
NA
NA
NA
NA
NA
Daisc.'y i>t ul .
(1979)
Sterl ing Forest,
flew York State
Two years,
1977 to 1978
NA
2.8
NA
NA
NA
NA
MA
jll'VL'llb i-'t d 1 .
(1980)
Great Smokey Mts.
in Tennessee
Six days in
September 1978
13.5
3.3
1.1
0.2
0.3
5.6
24.0
(•eniidii el dl .
' (1981)
Luray, VA
One month in
the summer of
1980
13.3
7.1
1.3
2.0
0.2
0.0
23.9
Pujrsoii
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several investigators have found that the average cation associated with
SO^ in the East corresponds approximately to (NH^H) (Pierson et al. 1980;
Stevens et al. 1980; Ferman et al. 1981). Also, following Duce (1978), Hahn
(1980), and Chu and Macias (1981), we have assumed that the conversion factor
from organic carbon aerosol to total organic aerosol is 1.5 (corresponding
to an average composition of CH90, ).
L- %
The mass concentration and chemical composition of fine particles in
the East exhibits significant variations both seasonally and spatially. For
the purposes of the discussions in this and subsequent sections, we would
like to postulate a single "model" ambient aerosol representing annual mean
concentrations spatially averaged over rural Eastern areas. Table 2 presents
this model ambient aerosol, which is based on the data in Table 1 and the
following considerations: The summertime sulfate averages in Table 1 should
be divided by approximately 1.3 to make them comparable to annual averages;
data for 20 rural EPA NASN sites and 3 rural EPA Dichotomous Network sites
in the East indicate that summertime (3rd quarter) sulfate averages are
generally 1.1 to 1.6 times greater than annual sulfate averages. The sum-
mertime nitrate averages in Table 1 are likely to be low compared to annual
nitrate averages; data from the EPA Dichotomous Network suggest that winter
nitrate levels are nearly an order of magnitude greater than summer nitrate
levels. One might a priori expect (and a cursory examination of Table 1
suggests) that summer organic levels in rural areas are higher than annual
organic levels. However, data collected by Daisey et al. (1979) reveal no
seasonal pattern in organic aerosol concentrations. We have not explicitly
discounted for seasonal variations in using the organic data in Table 1 to
arrive at our organic component in Table 2.
8
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TABLE 2. MODEL AMBIENT FINE AEROSOL, ANNUAL
MEAN FOR RURAL AREAS OF THE EAST.
COMPONENT MASS CONTRIBUTION*(yg/m3)
Sulfate (as NH4HS04) 9 + 2
Organics 4+2
Elemental Carbon I ± h
Crustal Material I ± h
Nitrates (as NH4N03) 1 + h
Non-water Other 2+2
Water 11 + 5
**
TOTAL 29+6
*
Mass of particles less than 2.5 microns in size under
ambient conditions (RH -^ 70-75%).
**
Total error is calculated as the root-mean-square
of the individual errors.
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The most important new consideration in constructing Table 2 involves
the treatment of water. The aerosol samples in Table 1 represent filtered
particulate matter weighed at 40 to 50% relative humidity; these samples likely
contain substantially less water than does the ambient aerosol (Hidy et al.
1974; Tierney and Conner 1967; Demuynck 1975; Pierson et al. 1980). Unfortu-
nately, definitive data are not available regarding mass concentrations of
water in ambient aerosols at Eastern locations. We have calculated the mass
of water associated with the fine rural Eastern aerosol using two methods.
First, thermodynamic calculations (Tang 1981) as well as measurements made
with microwave waterometers, nephelometers, and multi-stage cascade impactors
(Hidy et al. 1974; Ho et al. 1974; Stelson and Seinfeld 1981; Covert et al.
1972, Countess et al. 1981) indicate that, at average Eastern humidities (70-
75%), the mass of water associated with fine aerosols is approximately equal
to, or slightly greater than, the mass of aerosol electrolytes (e.g. sulfates
and nitrates). Noting that our model rural aerosol contains lOyg/m of sul-
fates and nitrates, the above referenced studies suggest that there should be
10 to 15 yg/m of water in the fine aerosol. Second, we have calculated the
water component using recent data taken at Luray VA (Ferman et al. 1981) and
the following assumptions: (1) the mass concentrations of the non-water aerosol
components are as listed in Table 2; (2) on the average, the ambient (wet)
aerosol scatters 1.9 times as much light as the dry aerosol (Ferman et al.
1981); (3) the scattering per unit mass by dry sulfate is 1.5 times the scat-
tering per unit mass by the remainder of the dry aerosol (Ferman 1981; Wolff
et al. 1981); and (4) the scattering per unit mass by water is 1.7 times the
scattering per unit mass by dry sulfate due to density differences (White
1918). A simple algebraic equation based on these data/assumptions can be
10
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3
solved to yield a fine mass concentration for water of 8 yg/m . Considering
3
the results of both methodologies, we have chosen 11 yg/rn as the water com-
ponent in the fine rural Eastern aerosol.
Table 2 contains error bounds for each component in the annual mean,
spatially averaged, model aerosol. These error bounds are based on our sub-
jective evaluation of the uncertainties. For example, the error bounds for
sulfate are relatively low, ± 20%, because the various monitoring programs
all agree rather closely regarding fine sulfate concentrations (once adjust-
ments have been made for seasonality). The error bounds for organics and .
water, on the other hand, are relatively high, ± 50%, because definitive
data are not available for the organic and water components of the fine
rural Eastern aerosol.
According to our model aerosol, the annual/spatial average fine par-
3
tide'concentration in rural areas of the East is 29 yg/m . The two largest
3 3
constituents are water (11 yg/m ) and sulfate (9 yg/m ). Actually, because
we expect that most of the water is attached to hygroscopic sulfate aerosols,
these two constituents might almost be interpreted as a single predominant
component that accounts for more than two-thirds of the fine aerosol mass.
Such an interpretation would be consistent with various statistical studies
indicating that visibility reduction in the East is tied very closely with
high sulfate concentrations (Trijonis and Yuan 1978; Leaderer and Stolwijk
1979; Pierson et al. 1980; Ferman et al. 1981). The only other component
that represents a substantial fraction (e.g. greater than 10%) of fine par-
ticle mass is organic aerosol, which constitutes about 4 yg/m .
11
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SEASONAL PATTERNS IN VISIBILITY AND FINE AEROSOLS
Fine aerosol concentrations and visibility in rural areas of the East
exhibit very strong seasonal variations. Figure 3 illustrates average season-
al patterns in rural Eastern areas for light extinction (proportional to the
reciprocal of visibility), sulfate concentrations, and fine particle con-
centrations. All three parameters demonstrate a strong peak during the sum-
mer quarter.
The summertime maximum in fine particle and extinction levels in the
East manifests Itself not only in averages of data over many sites but also
in data for almost any individual site; that is ~ the summer peak in fine
particles is nearly universal among rural Eastern locations. This phenomenon
is illustrated by a visibility map prepared using 3rd quarter data (see
Figure 4). Comparing Figure 4 to Figure 2, we see that the large area east
of the Mississippi and south of the Great Lakes, which has a 10 to 15 mile
median visual range annually, exhibits a very homogeneous 8 to 10 miles
median visual range during the summer.
ESTIMATE OF NATURAL BACKGROUND CONDITIONS
A reasonable method of investigating natural background visibility and
fine particle concentrations in the East is to estimate the natural and
anthropogenic fractions for each chemical component in our "model" ambient
aerosol (Table 2). We derive these estimates below based on ambient data
collected in remote areas, emission calculations, and trace element calcu-
lations. In the process of making these estimates, we held rather long
12
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30 -
20-
00
00
o:
o_
Ld
CD
£
LU
10 H
-3
TOTAL FINE PARTICLE MASS
FINE SULFATE MASS (as NH4HS04)
Note: Fine particle and fine sulfate mass data are
averages over five rural EPA dichotomous samp-
ler sites (Will Co. IL, Jersey Co. IL, Monroe
Co'. IL, Erie Co. NY, and Durham Co. NC). The
extinction data are averages over eight rural
airports (Trijonis and Yuan 1978).
-
i
o
X
-1
1st Quarter
Jan. - Mar.
2nd Quarter
Apr. - Jun.
3rd Quarter
Jul. - Sep.
4th Quarter
Oct. - Dec.
Figure 3. The seasonal patterns in sulfates, fine particle mass,
and extinction for rural areas of the East.
13
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P: Based on photographic
photometry data
N: Based on nephelometry data
*: Based on uncertain extrapolation of
visibility frequency distribution
Figure 4. Median summer visual range at suburban/nonurban locations in the United States (1974-1976)
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conversations with thirty aerosol researchers to solicit data, comments, and
suggestions regarding our calculations. These researchers are listed in the
acknowledgement section of this paper.
Table 3 presents the end result of our investigation — a model ambient
aerosol for Eastern natural background conditions. The error bounds in Table
3 are much larger (in a relative sense) than the error bounds in Table 2, be-
cause estimating natural background conditions is a very precarious undertak-
ing for many of the aerosol components. As a reflection of the uncertainties,
o
we have listed the values in Table 3 as fractions (e.g. % or % yg/m ) rather
than as decimals. Our specific reasonings and calculations for the various
aerosol components are described in the paragraphs that follow.
Two independent approaches suggest that natural background sulfate
concentrations in the East are very low. One approach concerns ambient
measurements made in the Southern Hemisphere which has an order of magnitude
less man-made SO emissions than the Northern Hemisphere (Cullis and Hirschler
A
1980). Most of these measurements have been made in areas that, like the
Eastern U.S., are humid and densely vegetated. Lawson, Winchester, and co-
workers have collected data on fine sulfate concentrations at numerous lo-
cations in the Southern Hemisphere and have recently published an overview
(Lawson and Winchester 1979). Table 4, a summary of that overview, suggests
that natural background fine sulfate concentrations are on the order of 0.1
3
to 0.5 yg/m . Even these very low values could represent overestimates be-
cause anthropogenic influences at remote subtropical Southern Hemisphere
locations may be non-negligible (Lawson 1981).
15
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TABLE 3. MODEL AMBIENT FINE AEROSOL, ANNUAL MEAN FOR
NATURAL BACKGROUND CONDITIONS IN THE EAST.
COMPONENT MASS CONTRIBUTION* ( g/m3)
Sulfate (as NH4HS04) h± h
Organics 2 + 2
Elemental Carbon k - %
Crustal Material h t h
Nitrates (as NH4N03) % t \
Non-water Other ^ - h
Water 1^-1
TOTAL 5h t 2V**
*
Mass of particles less than 2.5 microns in size under
ambient conditions (RH '\> 70-75%).
**
Total error is calculated as the root-mean-square of
the individual errors.
NATURAL BACKGROUND VISUAL RANGE (See Text): 60 t 30 miles.
TABLE 4. SUMMARY OF AVERAGE FINE SULFATE CONCENTRATIONS AT
SOUTHERN HEMISPHERE LOCATIONS (Lawson and Winchester
1979).
AVERAGE FINE SULFATE
CONCENTRATION EXPRESSED
LOCATION AS NH4HS04 (in yg/m3)
Five remote locations in South America 0.04 to 0.16
Four remote locations in South America
possibly under the direct influence of 0.20 to 0.50
sea spray or vegetative burning
One nonurban location in West Africa 0.6
One nonurban location in Samoa 0.2
16
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The second approach involves emissions estimates for sulfur oxides.
Several recent publications have concluded that man-made SO emissions domi-
/\
nate natural SOV emissions in the Eastern United States (Adams et al. 1980;
X
Galloway and Whelpdale 1980; Henry and Hidy 1980; Rice et al. 1981). Based
on measured emission rates, Adams et al. calculated that terrestrial bio-
genie sources contribute only 1 to 2% of the sulfur burden in the Eastern
U.S. Considering both terrestrial and marine influences, Galloway and
Whelpdale calculated a 4% natural sulfur contribution for the Eastern U.S.
Using our model ambient aerosol for rural Eastern areas in Table 3 (includ-
q
ing 9 yg/m of sulfate), a 4% natural contribution represents less than
3
0.4 ug/m of natural background sulfate. This value agrees closely with
the Lawson and Winchester data reported in the previous paragraph.
As our final estimate of natural background sulfate aerosol concen-
3 o
tration in the East, we have chosen h. ug/m . The error bound is ± % ug/m .
Estimating natural background levels for fine organic aerosols in con-
tinental areas is a very uncertain procedure. Some of the uncertainties
are highlighted in recent reviews by Duce (1978) and Hahn (1980). One
major problem is the lack of data for truly remote continental areas
(i.e. in the Southern Hemisphere). There are several data sets for remote
marine areas (Hoffman and Duce 1974, 1977; Ketseridis et al. 1976; Barger
and Ganett 1976; Eichmann et al. 1979; Chesselet et al. 1981). Using ad-
justment factors developed by Duce (1978) and Hahn (1981), (total organic
aerosol ^ twice ether extractable organic aerosol, total organic aerosol £
1.5 times organic carbon, and fine organic aerosol ^ 0.8 times total organic
aerosol), these various data sets yield a very consistent value of 1 ug/m3
17
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for fine organic aerosol concentrations in remote marine areas. This value,
however, may seriously underestimate natural continental organic concentra-
tions, because the organic aerosols from major natural continental sources
(e.g. primary plant wax aerosols, secondary terpenic aerosols, etc.) might
not be adequately represented in remote marine areas. On the other hand,
there could be a slight compensating overestimate due to the presence of
transported anthropogenic organic aerosols into remote marine areas. Be-
cause of these confounding and unknown effects, it does not appear reason-
able to infer natural continental organic aerosols from the measurements
made in remote marine areas.
Our estimate of natural fine organic aerosol concentrations in the
3
East, 2 ug/m , is based on two considerations. First, Duce (1978) and Hahn
(1980) interpret available information as suggesting a remote continental
3
background of lh to 2k ug/m of organics. Second, we calculate a value of
3
2 yg/m with a crude "tracer" calculation based on the following assumptions:
3 3
(1) there are 4 ug/m of total organic aerosol and 1 ug/m of elemental car-
bon aerosol in rural areas (see Table 2); (2) the ratio of organic aerosol
to elemental carbon aerosol is 2:1 in urban Eastern areas (Wolff et al. 1980);
and (3) elemental carbon (essentially all man-made) can be used as a tracer
for the contribution of man-made organics according to the 2:1 ratio. The
3
error bounds for our estimate (± 2 ug/m ) are large because emission rate
calculations suggest potentially much greater concentrations of plant waxes
and terpene derivatives (Duce 1978; Went 1960; Rasmussen and Went 1965;
Beauford et al. 1977), whereas certain ambient studies find little or no
direct evidence of significant contributions from natural organic aerosols
(Crittenden 1976; Daisey et al. 1979).
18
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Elemental carbon (soot) constitutes only 1 ug/m of our model rural
ambient aerosol in Table 2. Two approaches suggest that this component is
basically anthropogenic. The first approach involves emission data for
elemental carbon. The only significant natural source of elemental carbon
in the East is wildfires. Comparing wildfire soot emissions to total soot
emissions from prescribed burning, diesels, gasoline vehicles, aircraft,
solid waste incineration, and gas/fuel-oil/coal/wood combustion (EPA 1973,
1976, 1979; Muhlbaier and Williams 1981; Muhlbaier 1981; Cass et al. 1981),
we estimate that wildfires contribute only a small fraction of total elemen-
tal carbon emissions. The second approach is based on a "lead tracer" cal-
culation. Both lead and soot in urban areas are essentially all man-made.
Lead concentrations in rural Eastern areas are also generally assumed to be
man-made. That lead and soot both exhibit approximately the same dilution
factor from urban to nonurban areas of the East -- a factor of about 5-10
(EPA 1972, 1981; Stevens et al. 1980; Wolff et al. 1980) — suggests that
soot concentrations in nonurban areas are also mostly man-made. For our
natural background aerosol in Table 4, we have assumed an elemental carbon
concentration of % t % yg/m . This may be an overestimate, but the errors
are not important because elemental carbon is a very small component of the
aerosol.
3
Crustal material accounts for 1 yg/m of the model fine rural aerosol
in Table 2. This component is composed of fly ash and/or the lower tail of
the soil dust size distribution. Based on a study of the spatial patterns,
meteorological dependencies, and size distributions of the crustal elements
at nonurban sites near St. Louis (Trijonis et al. 1980), we conclude that
this component is predominantly soil dust rather than fly ash. It is
19
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difficult, if not impossible, to calculate how much of the fine soil dust
is natural .wind blown dust versus anthropogenic dust (e.g. dust raised by
traffic, construction, and agriculture or by wind action over surfaces dis-
turbed by man). Arbitrarily assuming that half is related to man-made acti-
vities, our estimate for the natural background concentration of fine
3
crustal particles in the East is h - h yg/m . The error in this assumption
is not critical because fine crustal material is a small component of the
aerosol.
3
Nitrate aerosols also contribute 1 yg/m to the model fine Eastern
aerosol in Table 2. Recent measurements indicate that fine nitrate concen-
trations in remote continental and marine areas of the Northern Hemisphere
3
average approximately .05 to .2 yg/m (Huebert and Lazrus 1980). Adopting
a somewhat conservative approach, we will assume that average natural back-
3
ground nitrate concentrations in the East are % ± % yg/m . Again, the er-
rors in this assumption are not important because nitrate is a small com-
ponent of the fine aerosol.
Natural background concentrations of the "other non-water" component
should be low. In fact, it is hard to imagine significant contributors to
the average fine natural aerosol that are not sulfates, organics, soot,
crustal material, nitrates, or water. The lower tail of the sea-salt size
distribution would be significant in coastal areas but not of great impor-
tance averaged over the East. We will arbitrarily assume that the average
natural background level for the "other non-water" category is % - h yg/m .
Table 2 indicates that the rural Eastern fine aerosol currently con-
tains 11 ± 5 yg/m of water. To estimate the amount of water attached to
the natural background fine aerosol, we consider two alternative hypotheses,
20
-------
First, we assume that all of the water is attached to hygroscopic sulfate
and nitrate aerosols, and that the amount of water in the natural aerosol
should be in proportion to the sulfate and nitrate remaining. This hypo-
thesis yields an estimate of 1 yg/m for "natural" water (with a range of
o
0 to 2 yg/m considering the error bounds in Tables 2 and 3). As an alter-
native, we assume that the water is attached equally to all components of
the non-water aerosol, and that the amount of water in the natural aerosol
should be in proportion to the total fine aerosol mass remaining. This
3 3
second hypothesis yields an answer of 2% yg/m (with a range of 0 to 5 yg/m
considering the error bounds in Tables 2 and 3). The truth should be some-
where between our two alternative hypotheses. The first hypothesis under-
estimates natural aerosol water because at least some small fraction of the
water should be attached to non-sulfate, non-nitrate particles, and because
the natural sulfate aerosol may be more acidic (and therefore more hygro-
scopic) than existing sulfate aerosols (Mueller 1981). The second hypothesis
is not reasonable because much more water should be attached to hygroscopic
aerosol components than to hydrophobic aerosol components. We will assume
3
that the natural fine aerosol contains lh t I yg/m of water.
As an aside, we should comment on a question that we have sometimes
heard raised: "If man-made sulfates were eliminated, wouldn't some of the
water associated with the man-made sulfates have a tendency to become at-
tached to the remainder of the aerosol?" The answer to this question is
"No" because transferring water from the aerosol to the gas phase produces
t
essentially no change in relative humidity. Simple calculations demonstrate
that water in the gas phase is typically orders of magnitude greater than
water in the particulate phase.
21
-------
Table 3 indicates that the model fine aerosol for average natural
3
background conditions in the East adds up to 5% ± 2h yg/m . The two largest
o o
components are organics (2 ± 2 yg/m ) and water (\h - 1 yg/m ). Each of the
other individual components is estimated to contribute h yg/m or less to
the total.
The fine aerosol concentrations in Table 3 can be used to estimate
natural background visibility levels in the East. Noting that median visual
range averaged over the East is currently about 13 miles (see the first sec-
tion of this paper as well as Allard and Tombach 1980), assuming that dry
sulfate has a mass scattering efficiency 1.5 times greater than other dry
aerosol components and that water has a mass scattering efficiency 1.7
times greater than dry sulfate (see earlier discussion and references),
taking into account absorption by elemental carbon (Ferman et al. 1981;
Groblicki et al. 1981), and taking into account Rayleigh (blue-sky) scatter
by air molecules, we calculate that median visual range would be 60 ± 30
miles under average natural background conditions in the East.
We conceived a crude method of checking this estimate of natural back-
ground Eastern visibility based on an inter-site regression analysis. Spe-
cifically, we regressed annual median visibility levels at various rural
Eastern sites (from Figure 2) against annual mean sulfate levels (from NASN
data) and annual mean relative humidity (from NOAA 1977). Following the
physical principles discussed by Cass (1979) and Trijonis and Yuan (1978),
the regression equations used extinction coefficient (3.9 ^ visual range)
as the dependent variable and "sulfate/(l-RH)M as the independent variable.
By plugging estimated natural background sulfates (h yg/m ) and average
22
-------
Eastern relative humidity (70%) into this regression equation, we might ob-
tain a crude approximation of natural background visual range. This ap-
proach should underestimate natural background visual range because non-
sulfate anthropogenic aerosols are not explicitly discounted for; however,
this difficulty should be mitigated by the fact that anthropogenic sulfates
are colinear (correlated) with other anthropogenic aerosols.
The spatial regression method yielded a natural visibility estimate
of 30-40 miles, not bad agreement with our previous value of 60 ± 30 miles.
There were indications, however, that the spatial regression analysis was
too crude to be accepted as reliable. There was a great amount of scatter
in the data points, the regression coefficients were unstable, and the re-
sults depended significantly on which sites were included (e.g. on whether
only nonurban or both nonurban and suburban sites were included, or on
which' geographical areas were included).
Although the spatial regression analysis was not a reliable method of
checking our estimate of natural background visibility, it did provide in-
sights regarding an important concept — the geographical distribution of
natural visibility levels in the East. Our estimates of natural background
levels for fine particles and visibility are intended to be spatial averages
for the entire East. It is important to recognize, however, that natural
background levels of fine particles and visibility might exhibit substantial
spatial variations over the East. For example, one might expect organic
aerosol concentrations to be greater in the south than in the north.
This possibility is, in fact, strongly suggested by our inter-site regression
analysis which indicates lower natural background visibility for the south
23
-------
than for the north if the data are divided geographically. Also, one would
expect natural background visibility to be lower for coastal areas than for
inland areas because of higher relative humidity (NOAA 1977) and greater sea
salt concentrations in the coastal areas. Insufficient data are available
to quantify the geographical variations of natural background fine particle/
visibility levels in the East; it is nevertheless important to acknowledge
that spatial variations would exist under natural conditions.
LONG-TERM VISIBILITY TRENDS .
As part of this investigation, we also considered the possibility of
checking our estimate of natural background Eastern visibility (60 ± 30
miles) by comparing long-term visibility trends with historical trends in
anthropogenic emissions. This comparison might suggest a relationship be-
tween visibility and emissions that could be extrapolated back to zero man-
made emissions. Sulfur oxides would be the most appropriate emission vari-
able for the comparison because sulfates and associated water constitute
the predominant visibility reducing component of the Eastern aerosol (see
discussion and references in the previous section, "Existing Fine Particle
Concentrations"). Gschwandtner et al. (1981) have recently compiled sulfur
oxide emission trends for the Eastern U.S. for the period 1950 to 1978.
Also of relevance, estimates of national coal consumption are available
from the early 1800s to 1970 (Bureau of Census 1975; Husar and Holloway 1980)
For the long-term visibility trend data, we selected eight suburban/
rural Eastern airports that have adequate visibility marker systems, have
24
-------
data back to the early 1930s, and have not undergone major relocations.
These airports are Evansville IN, Louisville KY, Albany NY, Charlotte NC,
Dayton OH, Allentown PA, Nashville TN, and Burlington VT (see Figure 5).
Actually, in a survey of all suburban/rural airports in the East, we found
that few, if any, airports besides these eight met all our criteria regard-
ing marker systems, long-term data availability, and site relocations. Even
these eight airports are not ideal because nearly all of them have undergone
at least some (minor) relocations.
In the long-term trend analysis, we compiled airport visibility data
for three-year periods corresponding to the second to fourth year of each
decade (e.g. 1932-1934, 1942-1944, etc.). We did not consider every year of
each decade because we lacked sufficient resources for the effort of compil-
ing hard-copy visibility data (for the 1930s and 1940s, we had to manually
transcribe hard-copy records from the National Climatic Center archives
in Asheville NC). The second to fourth year of each decade seemed to be a
logical choice for two reasons: (1) the visibility records at most airports
started around 1932, and (2) the historical cycle in coal usage exhibits
maxima and minima during these years (e.g. a Great Depression minimum in
1932-1934, a war-time maximum in 1942-1944, and clean-fuel switch minima in
the early 1950s and early 1960s) (Husar and Holloway 1980).
From the early 1940s to the early 1970s, the visibility trends at
seven of the airports agree qualitatively with one another and with histori-
cal SO emission trends. As shown in Figure 6, visibility increased at
J\
these seven airports from the 1940s to the 1950s in agreement with the sub-
stantial post-war decrease of national coal consumption (Husar and Holloway
1980). Visibility at the seven airports decreased from the 1950s to the
25
-------
Dayton
Burlingtonu
Albany
Allentown
Evansville*
Louisville
Nashville
•Charlotte
Figure 5. Airports used to analyze long-term visibility trends,
26
-------
30 —
00
20 —
CtL
00
I
1943-44
I
1952-54
I
1962-64
Burlington
Allentown
Charlotte
Nashville
Evansville
Dayton
Louisville
I
1973-74
YEARS
Figure 6. Visibility trends at seven Eastern airports from the early
1940s to the early 1970s.
27
-------
1970s in agreement with the increases in estimated Eastern SO emissions
A
(Gschwandtner et al.- 1981) and national coal consumption (Husar and Holloway
1980) during that period.
We caution the reader, however, that the above agreement should be
regarded with some skepticism. For one, the available emissions trend
data are questionable. For example, although the Eastern SO emission esti-
A
mates (Gschwandtner et al. 1981) and national coal consumption estimates
(Husar and Holloway 1980) both show some increase from the early 1950s to
the early 1970s, the former indicates a much larger increase than the latter.
Part of this discrepancy is probably due to inaccuracies in the Eastern SO
/\
emission estimates; Gschwandtner (1981) has stated that the data he used to
compile emission trends are less than adequate prior to 1960, and that cer-
tain corrections must be made to his 1950s values. Part of the discrepancy
may a-lso reflect the facts that the coal consumption data do not necessarily
track SO emissions (due to changes in sulfur content, processes, etc.), and
/\
that the coal consumption data represent national rather than Eastern figures.
In any case, because of this discrepancy, we also feel less confident in
using the post-war decrease of national coal consumption as a measure of
post-war decreases in Eastern SO emissions.
X
As a second caution, we note that meteorology may have played a sig-
nificant role in determining visibility trends. Although visibility trends
stratified by meteorological parameters tend to be similar to the overall
visibility trends presented in Figure 6 (Trijonis and Yuan 1978), we cannot
rule out the possibility that the qualitative agreement between Figure 6 and
historical S0¥ emission trends is a fortuitous one produced by meteorological
/\
28
-------
fluctuations. The potentially confounding effect of meteorology seems all
the more important when one considers that SO emissions over the past five
/x
decades have fluctuated only about ± 30% compared to the 50-year average
(Husar and Holloway 1980).
The third caution concerns the tenuous nature of historical trend
studies based on airport visibility data. It has been found that airport
data are of generally good quality for studying geographical/seasonal/
meteorological patterns in visibility but are of questionable quality with
respect to historical trend analysis (Trijonis 1981). The major problem is
that, in historical trend analysis, one is usually dealing with long-term
visibility changes on the order of 30% or less. Changes in median visibi-
lity of 10 to 20% can also be produced artificially by modifications in
visibility reporting practices. One way of circumventing this problem is to
examine data from numerous airports and to verify that the trends are con-
sistent among the airports. In this regard, we can be somewhat encouraged
that seven of our eight airports are in qualitative agreement.
In addition to the general uncertainties in airport visibility data
discussed in the previous paragraph, we must note three specific problems
in our particular airport data sets. First, the visibility trends at Albany
NY do not agree with the trends at the other seven locations. In fact,
Albany shows exactly the opposite pattern — decreasing visibility from the
1940s to the 1950s and increasing visibility from the 1950s to the 1970s.
Increasing visibility from the 1950s to the 1970s in New York State has been
previously^noted by Husar et al. (1979); they attributed this atypical pat-
tern to the fact that New York, unlike most other Eastern areas, underwent
decreases in coal usage and SOV emissions from the 1950s to the 1970s.
29
-------
Despite ah apparent explanation for the atypical visibility trends at Albany,
the contradiction represented by the Albany trends remains an important
caveat to our analysis. This caveat is strengthened even further by the re-
sults of Sloane (1980), v/ho found that some rural sites in the Appalachian area
did not show the visibility decreases exhibited by most other rural Eastern
sites from 1948 to 1978. .Second, we believe that the large increase in
visibility (decrease in extinction) at Allentown from the 1940s to the 1950s
is more of a data quality artifact than a real effect associated with de-
creased post-war emission's. The visibility reporting system at Allentown
during the 1940s was extremely unusual and therefore highly questionable.
Third, the visibility trends at the various airports from the 1930s to the
1940s are a hodgepodge. Half of the airports show.improving visibility (of
widely varying degrees) from the 1930s to the 1940s, while half show deteri-
orating visibility (of widely varying degrees). We think that this reflects
problems with the quality of the 1930s airport visibility data. Personnel
at the National Climatic Center stressed to us that visibility reporting
practices were at an infancy stage during the early 1930s and that good
consistency was not attained until the 1940s. In fact, we found some re-
porting codes (involving both letters and numbers) for visual range during
the 1930s that none of our contacts at NCC could interpret. Although the
lack of consistent visibility trends from the 1930s to the 1940s probably
reflects data quality problems, it could also be interpreted as a contra-
diction to the correspondence between historical visibility trends and SO
/>
emission trends. Specifically, national coal consumption data suggest that
the 1932-1934 period had significantly less SO emissions than the 1942-1944
30
-------
period; on the other hand, the available (albeit poor) airport data for that
period show no clear deteriorating trend in visibility from the 1930s to the
1940s.
Because of the uncertainties in the visibility and emission data, it
is not presently worthwhile to attempt a quantitative comparison of visibi-
lity trends and SO emission trends for the purpose of estimating natural
/\
background visibility. Such a quantitative analysis may become feasible in
the future as some of the uncertainties are resolved. The most immediate
problem to be solved is the accurate estimation of SO emission trends prior
}\
to 1960. Even if this problem is solved, however, a good quantitative
analysis may be precluded by the uncertainties in visibility trend data and
by the fact that SO emissions have changed only moderately (± 30%) over the
X
past five decades.
SEASONAL PATTERN OF HISTORICAL VISIBILITY TRENDS
In a previous section, we showed that sulfates and total fine particle
concentrations currently exhibit pronounced maxima and that visibility cur-
rently exhibits a pronounced minimum during the summer season (3rd calendar
quarter) in the East. It is of interest to examine this seasonal pattern
historically. Fortunately, the data quality problems associated with his-
torical trend analysis of airport visibility data are essentially eliminated
when one considers relative visibility levels among seasons. Artificial
trends produced by site relocations and by changes in reporting practices
should affect all seasons equally and should cancel out if one just compares
*
relative visual range among seasons.
31
-------
Figure 7 illustrates historical trends in the ratio of median third
quarter visibility to median visibility for the other three calendar
quarters. Trends are presented for all eight study sites from the early
1930s to the early 1970s. Figure 7 shows that, during the 1930s, 1940s,
and 1950s, summertime visibility exceeded visibility for the remainder of
the year by a factor of 1.0 to 1.5. From the early 1950s to the early 1970s,
however, summertime visibility declined precipitously relative to visibility
for the remainder of the year so that, by the early 1970s, summer had become
a season of distinctly poor visibility.
Many other researchers have noted a strong decline in summertime visi-
bility (Miller et al. 1972; Trijonis and Yuan 1978; NRC 1979; Husar et al.
1979; Sloane 1980) and a corresponding increase in summertime sulfate con-
centrations (Trijonis 1975; EPA 1975; Altshuller 1976; Frank and Possiel
1976;- NRC 1979) in rural Eastern areas from the 1950s to the 1970s. This
phenomenon has been attributed to the rapid grov/th of summertime SOV emissions
X
from coal-fired power plants due to air conditioning demands (Holland et al.
1977; Husar et al. 1979; Sloane 1980). Also, summertime visibility should
be particularly sensitive to SO emissions because photochemical processes
/\
are important in the conversion of sulfur dioxide emissions to sulfate
aerosols, and because solar radiation is most intense in the summer.
SUMMARY AND CONCLUSIONS
Existing visibility in rural areas of the Eastern U.S. is rather low.
For example, in contrast to the 70-85 mile median visual range in the
32
-------
o •<
LU LU
s: >-
O LU
LU
a: u_
z o
1.5 _
<
oo
Q
1.0 —
o;
o
LU
ii 0.5 —
00 «=C
U_
O _l
O ID
-------
mountainous Southwest, annual median visual range is only 10-15 miles over
most of the area south of the Great Lakes and east of the Mississippi. Some
parts of the East, however, such as New England and the eastern slope of the
Appalachians, experience more moderate visibility levels (on the order of 15-
35 miles).
Visibility in the East is essentially controlled by ambient fine par-
ticle concentrations. Based on data from eight monitoring programs and on
information concerning water content of aerosols, we conclude that -- annually
and spatially averaged — there is about 29 ug/m of ambient fine aerosol
in rural Eastern areas. The components are water (11 ug/m ), sulfates
o o o o
(9 ug/m ), ornanics (4 ug/m3), soot (1 uq/nr), crustal material (1 ug/m ),
3 3
nitrates (1 ug/m ), and other (2 u9/m )• Because most of the water is prob-
ably attached to hygroscopic sulfate aerosols, sulfates and associated water
might-be interpreted as a single predominant component of the fine aerosol.
This would explain the high statistical correlations that have been observed
between sulfate concentrations and visibility reduction.
Fine parti'cle concentrations and visibility in the East currently ex-
hibit strong seasonal patterns. Specifically, sulfates and total fine par-
ticles reach a pronounced maximum in the summer (third) quarter, when visi-
bility reaches a pronounced minimum. This seasonal pattern is apparently a
rather recent phenomenon historically; data from the 1950s and prior decades
indicate that summer used to have significantly higher visibility than the
remainder of the year.
Under natural background conditions, we estimate that rural Eastern
3
areas would have an average fine aerosol concentration of 5% ±2% ug/m . The
34
-------
3 3
largest components would be organics (2 ± 2 yg/m ) and water (\h - 1 yg/m )•
Sulfates would contribute only about % yg/m under natural conditions. This
natural ambient fine aerosol would produce an average visual range of 60 ±
30 miles.
It is not currently possible to derive natural background visual range
from long-term visibility trend data because of limitations in historical
emission estimates, uncertainties in airport visibility trend data, and the
confounding influences of meteorology. Even if some of these uncertainties
are resolved, quantitative analyses of long-term visibility trends will be
hindered by the fact that SOV emissions have varied only ± 30% over the past
/\
five decades. The most promising method of checking our estimates of natur-
al background conditions would be to conduct field studies in remote contin-
ental areas of the Southern Hemisphere. Such field studies should include
simultaneous measurements of fine particle mass, fine particle chemical
composition, and atmospheric optical parameters (visibility).
ACKNOWLEDGEMENTS
The work reported in this paper was partly supported by EPA Purchase
Order #1D3559NASX. The project officers at EPA, E.L. Martinez and John
Bachmann, deserve credit for their suggestions and for their help in
acquiring some of the data. We owe a great debt to Ms. Janet Holloway of
Washington University in St. Louis for providing the visibility trend data
for the 1950s, 1960s, and 1970s. Also, we acknowledge the following aerosol
35
-------
researchers who offered data, comments, and/or suggestions: Paul Altshuller,
Glen Cass, Peter Coffey, Alden Crittenden, Dagmar Cronn, Joan Daisey, Robert
Duce, Thomas Dzubay, Peter Groblicki, Charles Hakkarinen, James Huntzicker,
Douglas Latimer, Douglas Lawson, Paul Lioy, Edward Macias, Peter McMurry,
Peter Mueller, Thompson Pace, William Pierson, Kenneth Rahn, Hal Rosen,
Robert Stevens, Roger Tanner, Alan Waggoner, Warren White, William Wilson,
John Winchester, and George Wolff.
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40
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42
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-450/4-81-036
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
Existing and Natural Background Levels of Visibility
and Fine Particles in the Rural East
5. REPORT DATE
August 1981
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO
John Trijonis
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Santa Fe Research Corporation
228 Griffin Street
Santa Fe, NM 87501
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
Monitoring and Data Analysis Division
Office of Air Quality Planning and Standards
US Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
EPA Project Officers: E. L. Martinez and J. Bachmann
16. ABSTRACT
Existing and natural background levels of visibility and fine particles
are investigated for nonurban areas of the Eastern U.S. Analysis of data for
100 airports nationwide indicates that nonurban areas of the East experience
relatively low visibilities. Eastern rural areas generally show annual median
visual ranges of 10-15 miles. Data from eight monitoring programs indicate
that ambient fine ( <2.5 ym) particle concentrations presently average approxi-
mately 29 yg/m3 in the rural East. Main components are water, sulfates and organics.
Currently seasonal sulfate and fine particle levels peak in summer, when visibility
is lowest. Prior to the 1960's, visibility was distinctly higher in summer than
the rest of the year. An investigation of natural background conditions suggests
that natural fine particle concentrations would average 5% + 2% yg/m in the East,
mostly composed of organics and water. Natural background visual range for the
East is estimated to be 60 + 30 miles.
17.
KEY WORDS AND DOCUMENT ANALYSIS
a.
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
18. DISTRIBUTION STATEMENT
19. SECURITY CLASS (This Report)
20. SECURITY CLASS (Thispage)
21. NO. OF PAGES
.Afi
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
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EPA Form 2220-1 (Rev. 4-77) (Reverse)
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