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EPA 450/2-81-078
A Screening Procedure for the
Impacts of Air Pollution Sources on
Plants, Soils, and Animals
by
A.E. Smith and J.B. Levenson
Argonne National Laboratory
9700 South Cass Avenue
Argonne, II 60439
Contract No. EPA-IGA-79-D-X0764
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
December 12, 1980
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The guideline series of reports is being issued by the Office of Air Quality
Planning and Standards (OAQPS) to provide information to state and local
air pollution control agencies; for example, to provide guidance on the
acquisition and processing of air quality data and on the planning and
analysis requisite for the maintenance of air quality. Reports published in
this series will be available - as supplies permit - from the Library Services
Office (MD-35), U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina 27711; or, for a nominal fee, from the National
Technical Information Service, 5285 Port Royal Road, Springfield, Virginia
22161.
Publication No. EPA-450/2-81-078
11
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CONTENTS
ACKNOWLEDGMENTS ............................. vi
1 INTRODUCTION ............................. 1
1 . 1 Background ............................ 1
1 . 2 Scope .............................. 1
2 OVERVIEW ............................... 3
3 AIR QUALITY RELATED IMPACT DATA .................... 7
3.1 General ............................. 7
3.2 Natural Vegetation and Crops ................... 8
3.2.1 General .......................... 8
3.2.2 Screening Concentrations for Ambient Exposures ...... 10
3.2.3 Synergisms ........................ 15
3.2.4 Screening Concentrations for Soil and Plant
Tissue Exposures ..................... 16
3.3 Soils .............................. 17
3.4 Fauna .............................. 22
4 TRACE ELEMENT AIR QUALITY DATA .................... 24
5 SCREENING PROCEDURE .......................... 25
5.1 Methodology ........................... 25
5.1.1 Description ........................ 25
5.1.2 Estimating Maximum Concentrations ............. 28
5.1.3 Screening and Deposition ................. 33
5.2 Example Screen and Significant Emission Rates .......... 42
5.2.1 Example Screen ..... . ................ 42
5.2.2 Significant Emission Rates ................ 44
APPENDIX A: ESTIMATES OF MAXIMUM GROUND LEVEL CONCENTRATIONS ...... 49
APPENDIX B: POLLUTANT SENSITIVITIES OF PLANT SPECIES .......... 59
APPENDIX C: TRACE ELEMENT AIR QUALITY DATA ............... 71
APPENDIX D: EFFECTS OF DEPOSITED PARTICULATE MATTER ........... 107
REFERENCES ................................ Ill
111
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TABLES
2.1 Regulated Pollutants .................. ......
2.2 Pollutants Screened .........................
3.1 Screening Concentrations for Exposure to Ambient
Air Concentrations .........................
3.2 Screening Concentrations of Gaseous Pollutants Compared
to Ambient Criteria ......................... ^
3.3 Synergisms of Gaseous Pollutants .................. 6
3.4 Screening Concentrations for Exposure of Vegetation to
Pollutant Concentrations in Soil and Tissue ............. 17
3.5 Range of Endogenous Soil Concentrations of Selected Elements .... 20
3.5 Plant: Soil Concentration Ratios ................... 22
3.6 Dietary Trace-Element Concentrations Toxic to Animals ........ 23
5.1 Steps in Screening Procedure .................... 29
5.2 Pollutants and Averaging Times ................... 31
5.3 Ambient Screening Concentrations .................. 34
5.4 Solubilities of Endogenous Trace Elements .............. 38
5.5 Equivalent Exogenous Soil Screening Concentrations ......... 40
5.6 Significant Emission Rates for Direct Acting Pollutants ....... 46
5.7 Significant Emission Rates for Trace Elements ............ 47
5.8 Summary of Representative Stacks .................. 43
A.I Dispersion Coefficient Parameters and Maximum
Concentration Coefficient ...................... 53
A. 2 Averaging Time Conversion Factors .................. 56
B.I Sulfur Dioxide Sensitivity of Crop Species . ............ 61
B.2 Sulfur Dioxide Sensitivity of Natural Vegetation .......... 62
B.3 Ozcne Sensitivity of Crop Species .................. 65
B.4 Ozone Sensitivity of Natural Vegetation ............... 66
B.5 Nitrogen Dioxide Sensitivity of Crop Species ............ 68
B.6 Nitrogen Dioxide Sensitivity of Natural Vegetation ......... 69
C.I Air Quality Data for Arsenic .................... 73
C.2 Air Quality Data for Cadmium .................... 75
C.3 Air Quality Data for Chromium .................... 80
C.4 Air Quality Data for Fluoride Ion .................. 84
C.5 Air Quality Data for Lead .......... . ....... 85
C.6 Air Quality Data for Manganese ............ at
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TABLES (Cont'd)
C.7 Air Quality Data for Selenium 100
C.8 Air Quality Data for Vanadium 102
C.9 Air Quality Data for Zinc 104
FIGURES
3.1 S02 Dose-Injury Curves for Plant Species 12
3.2 N02 Dose-Injury Curves for Plant Species 13
3.3 Concentrations of Some Trace Elements Toxic to Terrestrial Plants. . 18
3.4 Range of Endogenous Concentrations of Trace Elements 21
5.1 Pollutant Pathways 26
5.2 Flowchart of Screening Procedure 30
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ACKNOWLEDGMENTS
The authors wish to express their appreciation to K. Robeck and
S. Zellmer of the Energy and Environmental Systems Division of Argonne
National Laboratory for their help in assembling the data on which the
screening concentrations were based and for helpful discussions during the
development of the screening procedure.
VI
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1 INTRODUCTION
1.1 BACKGROUND
Section 165 of Che Clean Air Act* requires precons truce ion review of
major emitting facilities to provide for the prevention of significant de-
terioration (PSD) and charges Federal Land Managers (FLMs) with an affirmative
responsibility to protect - the air quality related values of Class I areas.
Regulations? implementing these provisions require:
An analysis of the impairment to visibility, soils, and
vegetation (52.21 (o)) and
A notice from the EPA Administrator to the appropriate FLM
of any permit application from a source whose emissions
would affect a Class I area (52.21 (p)).
For sources more than 10 km from any Class I areas, exemptions provide
that no analysis of impairment need be done if emission increases are below
specified limits.* The analysis should address the impairment due to general
secondary growth associated with the source and need not address the impacts
on vegetation having no significant commercial or recreational value. For
impacts in Class I areas, consultation between EPA and the FLM is required.
1.2 SCOPE
The entire subject of air quality related values and impairment to
these values is currently under investigation. For example, although some
values related to plants, soils, and visibility are "air quality related
values," the term itself remains to be defined in a fashion appropriate to the
review of PSD permit applications and air quality reviews. Much of the data
required to relate ambient concentrations of pollutants to impairment of these
values is currently lacking. However, the requirements of 52.21 (o) and (p)
need to be addressed now while additional investigations are being carried
out.
*The "de minimis" values are given in Sec. 52.21 (b)(23)(i) of the PSD
regulations.2
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The information and screening procedure presented here provide interim
guidance:
To aid in determining whether emissions are significant
or whether there are significant air quality impacts under
Sec. 52.21 (o) and
To aid in flagging sources which should be brought to the
attention of an FLM under Sec. 52.21 (p).
Impacts on vegetation and soils are the principal areas addressed
by the procedure which thus takes a limited view of the possibly broad scope
of air quality related values. A selected review of impacts on fauna has also
been included and the odor potential of regulated pollutants is addressed.
This procedure is intended for use by air quality engineers and is not
a manual for the assessment of impacts on plants, soils, and other air quality
related values such as would be suitable for an ecologist. A handbook provid-
ing for such detailed assessments is being prepared for the FLMs. In keeping
with the screening approach, the procedure provides conservative, not defini-
tive results. However, a source which passes through the screen without being
flagged for detailed analysis cannot necessarily be considered safe. Species
more sensitive to particular pollutants than species considered in this study
probably exist. Further research may indicate that averaging times different
from those used here are controlling. When available, such information
could be easily included in the screening procedure by changing the screening
concentrations presented here.
Based on estimates of typical stack parameters, significant emission
levels have been estimated. These estimates are not intended to replace
source-specific screens, but do indicate what sizes of sources appear most
likely to cause significant impacts on plants and soils.
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2 OVERVIEW
The procedure presented here provides a simple method for assessing
the potential a source has for adversely affecting some air quality related
values. In particular, the potential for impacts on plants, soils, and
animals is assessed. The approach taken is similar to the "de minimis"
approach used by EPA in the PSD regulations.3 in the procedure presented
here, the minimum levels at which adverse effects have been reported in the
literature are used as screening concentrations. These screening concentra-
tions can be concentrations of pollutants in the ambient air, in soils, or in
aerial plant tissues. They have been developed by searching the review
literature; few original sources have been consulted. The analyst applying
this procedure must read the material in Sec. 3 which lists these screening
concentrations and provides background on them in order to apply and interpret-
them appropriately.
Section 5 describes a seven step process for screening a source. The
procedure begins by estimating the maximum ambient concentrations caused' by
the source for the averaging times specified for the screening concentrations.
For some pollutants these maxima are compared directly to the screening
values. For other pollutants (trace elements) estimates of deposition in the
soil and subsequent uptake by plants are made based on an estimate of the
maximum annual concentration. The estimated concentrations of the pollutant
in the soil and aerial plant parts are then compared to appropriate screening
concentrations. Concentrations in excess of any of the screening concentra-
tions would indicate that the source might have adverse impacts on plants,
soils, or animals and that the actions required by 40 CFR 52.21 (o) and (p)
need to be taken. For situations where modeling results are not available for
the source, significant emission levels corresponding to the various screening
concentrations are developed in Sec. 5.2. In these cases, emissions in excess
of the significance levels would trigger the additional actions.
The estimation of potential impacts on plants, animals, and soils is
extremely difficult. The screening concentrations provided here are not
necessarily safe levels nor are they levels above which concentrations will
necessarily cause harm in a particular situation. Effects data for plants,
animals, and soils are under constant revision and reevaluation. There is
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good deal of controversy among experts. In addition, this procedure is based
upon a simplistic view of extremely complex systems in which single value
estimates are not possible and in which the number of variables is extremely
large. Many simplifying assumptions have been involved in developing the
procedure and are discussed in Sec. 3.
Ideally, the screening procedure should address the impacts of all the
pollutants currently regulated under the Clean Air Act, but as shown in
Table 2.1, screening concentrations were found for only half the regulated
pollutants. Ozone and TSP are discussed in Sec. 3.1. Of the remaining sub-
stances for which screening concentrations were not found, methyl mereaptan,
dimethyl sulfide, dimethyl disulfide, carbon disulfide, and carbonyl sulfide
are regulated because of their odor potentials. Odor is an air quality
related value and Sec. 52.21 (b)(23)(i) of the PSD regulations2 gives "de
minimis" emission levels for reduced sulfur (RS) and total reduced sulfur
Table 2.1 Regulated Pollutants
Screening Concentrations
Available Not Available
CO TSPa
N02 Asbestos
S02 Sulfuric Acid Mist
03^ Vinyl chloride
Lead Methyl Mercaptanc
Mercury Dimethyl Sulfide0
Beryllium Dimethyl Disulfidec
Fluoride Carbon Disulfide0
Hydrogen Sulfide Carbonyl Sulfidec
aFraction of TSP present as trace ele-
ments treated through deposition and
uptake by plants.
^Screening concentration available but
no simple procedure for estimating the
ozone impact of a single source is
currently available.
cRegulated indirectly as constituents of
reduced sulfur or total reduced sulfur.
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(TRS) based on odor. RS and TRS include these sulfur compounds. Sources not
emitting more than these "de minimis" levels (10 t/yr for both RS and TRS) are
not expected to have a significant odor impact and hence should not require
any additional review for impacts on air quality related values. If the
10 t/yr "de minimis" level is exceeded, the appropriate FLM might want to
evaluate the potential for an odor problem. Whether or not these sulfur-
containing compounds might adversely affect plants, soils, or animals could
not be determined. Riere was one questionable indication that methyl mer-
captan might be toxic to plants at concentrations near 150,000 ug/m3, far
above likely ambient concentrations.^ Information for asbestos, sulfuric acid
mist, and vinyl chloride was not available in the review literature consulted
for this work.
Pollutants which can be screened by this procedure are listed in
Table 2.2 according to whether they are screened for potential effects on
plants or on animals and according to whether the potential effects are caused
directly by concentrations of the pollutant in the ambient air or whether the
potential effect is exerted indirectly through the soil or the diet. Absence
of a pollutant from a particular column in the table does not necessarily
mean that impacts can not result from the pollutant acting through the
corresponding pathway. Such absence simply means that no data to provide a
suitable screening concentration were found in the review literature consulted.
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Table 2.2. Pollutants Screened
Potential Impacts on
Direct
Ambient
Impact
S02
°3
N02
CO
H2S
Ethyl ene
Fluoride
Plants
Indirect through Direct
Deposition and Ambient
Uptake Impact
Arsenic
Boron Beryllium
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Animals
Indirect through
Plants in
Diet
Arsenic
Cadmium
Cobalt
Copper
Fluoride
Lead
Manganese
Nickel
Selenium
Vanadium
Zinc
aThe other five sulfur-containing compounds are screened for
odor impacts during the "de minimis" determinaion for RS and
TRS.
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3 AIR QUALITY RELATED IMPACT DATA
NOTE: In this chapter and throughout this work, a distinction is made
between parts per million by volume (ppmv) and parts per million by weight
(ppmw). The former, ppmv, is the unit more familiar to air quality analysts
and is used, for example, to express ambient concentrations and standards.
The latter, ppmw, or an equivalent (mg/kg, ug/g)> is frequently used to
express concentrations of elements in soils, plants, and animals. The air
quality analyst should be aware of the difference, because the units are not
equivalent. The unit ppmv is normally used only in expressing concentrations
of components of gaseous mixtures.
3.1 GENERAL
Data to be used in screening impacts on three air quality related
values (vegetation and crops, soils, and fauna) are discussed in this section.
Vegetation and crops receive the greatest amount of attention, reflecting the
availability of data. No direct impacts on soils are defined, such impacts
being screened through the potential impacts on vegetation growing in soils
which have become contaminated by the deposition of air pollutants. Impacts
on fauna are also addressed indirectly with effects being related to the
ingestion of plants containing toxic elements taken up from pollutants
deposited on soils. Thus, the information presented here represents a prelim-
inary definition of air quality related values and impacts.
Perhaps as important as the areas addressed are several areas not
addressed in this procedure. These areas are visibility, acid precipitation,
a screen for TSP, and a screen for ozone. Consideration of visibility as an
air quality related value is required by regulations (40 CFR 52.21 (o) and
(p)). Addressing visibility was beyond the scope of this work. However, EPA
has prepared a report to Congress on visibility** and draft regulations7 have
been published.
No simple procedure is currently available to deal with the impact of
a single source on acid precipitation. Acid precipitation presents a regional
problem involving long-range transport which makes the impact of a single-
source difficult to isolate. Various adverse effects on vegetation have
been noted in areas with low soil buffering capacities and subject to heavy
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annual precipitation. Such areas appear to be most susceptible.8,9,10,
Observed effects include reduced growth, reduced germination of seeds and
pollen, accelerated leaching of nutrients, decrease in soil calcium and other
bases, and reduced microbial activity, particularly that of nitrifiers and
nitrogen-fixers. A major EPA initiative to study acid precipitation is
currently underway. Policy and guidance will be formulated as part of this
initiative.
Total suspended particulates (TSP) are not considered here. No useable
information other than that used to develop the ambient standards (NAAQS) was
found in the review literature. Thus, EPA's current procedure for TSP3 should
suffice for the review of generic TSP- However, the trace metals in TSP may
have greater impacts on vegetation and soils than the total amount of particu-
lates. This section provides information related to specific trace metals.
No simple models are currently available to estimate the impacts on
ozone concentrations of emissions of volatile organic compounds (VOC) from
a single source. EPA is currently developing means other than modeling
to deal with VOC emissions and ozone. It appears likely that an emission
management approach will be taken. When this approach has been completed it
could probably be used to review new sources for impacts on air quality
related values. Meanwhile, the minimum reported concentrations at which
vegetative damage occurs are presented here but no method for their use
is given and no significance levels for VOC emissions have been developed.
3.2 NATURAL VEGETATION AND CROPS
3.2.1 General
Two pathways by which air pollutants can affect vegetation are consid-
ered here. The first is the direct exposure of a plant to a gaseous pollutant
in the ambient air. The second involves indirect exposure to trace elements
through deposition of the pollutant in the soil and later uptake by the plant.
For each pathway certain qualifications and cautions should be kept in mind in
order to avoid interpreting the values presented here either as absolutely
safe levels for all plants or as levels which could never be exceeded without
damaging vegetation. The following discussions are not intended to be exhaus-
tive and details required by specialists are not given. The intent is to
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provide the air quality analyst with a feeling for the difficulty of esti-
mating screening concentrations for plants and the complexity of making
detailed assessments of impacts on vegetation. References 8, 9, 12, and 13
may be consulted for additional details and guidance to primary source
material.
Effects of pollutants can be classified as acute or chronic. Acute
effects result from short-term (e.g., 3-hr) exposures to relatively high
concentrations. Chronic effects result from exposures to lower concentrations
for times of from months to several years. Most of the effects data for
plants comes from experiments conducted under acute conditions of exposure
with some limited information on chronic exposures. Thus, the data may not
adequately reflect impacts which take years or decades to develop.
The values presented here represent the ambient levels at which visible
damage or growth retardation may occur or the observed minimum levels at which
injury and mortality to plants have been reported. These numbers are general-
ly the lowest values consistently reported in the literature on plant response
to controlled exposures of single pollutants. Both field and greenhouse
studies have been used in developing the data. Experiments which demonstrated
only physiological changes (e.g., a change in respiration rate) without
associated visible damage or effects on growth, weight, or yield were not
considered in this compilation.
The majority of the studies were performed on crops and other economic-
ally important species; for lack of sufficient data, it is assumed here that
native plant species are affected at similar concentrations. In addition,
assessment of the data on crops is difficult because of the number of horti-
cultural varieties available for many of the species tested. In the process
of selecting desirable attributes in different varieties, the species'
original sensitivity or resistance to the element being tested may have been
inadvertently altered, making general conclusions about the sensitivity of the
species as a whole difficult.
Effects from simultaneous exposure to two or more pollutants have
been ignored in the majority of the studies. Exposure to a single pollutant
at a time is not the usual situation. Particular combinations and concentra-
tions of pollutants may act either synergistically or antagonistically under
certain conditions. Such situations are seldom clearly predictable with
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10
current information and the screening procedure presented here does not deal
with them. A limited discussion of synergisms is pesented in Sec. 3.2.3.
Each species exhibits a specific range of tolerance which may be
higher, lower, broader, or narrower than another species'. In addition to
the variation in tolerance between species, every individual of a given
population has an intrinsic tolerance to environmental stress. Therefore, the
population exhibits a characteristic range of tolerance so that all members of
the population would not necessarily respond to pollutant levels that would
adversely affect some members.
Species vary in the way they take up, metabolize, eliminate, and
accumulate elements. Species also vary in the way they respond to different
elemental forms. For example, As3+ is generally thought to be more toxic to
plants than As^+. The values presented here do not make such distinctions nor
could they be made based on the review literature.
Finally, the response of species and individuals depends upon a number
of uncontrolled variables. Changes in these variables might alter the
sensitivity of the plant. These variables include: age (stage of develop-
ment), health and vigor, season of year, temperature, light intensity, soil
type, moisture content of soil, pH of soil, humidity, wind speed, and the
presence of other elements.
3.2.2 Screening Concentrations for Ambient Exposures
Table 3.1 presents the suggested screening values for seven gaseous
pollutants. These values represent the minimum concentrations at which
adverse growth effects or tissue injury in exposed vegetation were reported in
the literature. Data for some other gases could not be included because the
critical specification of averaging time was missing. Where information was
available, separate values are given for sensitive, intermediate, and resis-
tant plants. Species belonging to each of these groupings are given in
Appendix B for S02, NC>2, and ozone. Figure 3.1 displays graphically the
variation in experimental determinations of the minimum SC>2 concentration at
which effects occur. Figure 3.2 presents a similar display for N02. For both
pollutants there is reasonable but not perfect agreement between the graphical
data and Che screening concentrations recommended in Table 3.1. The use
of the data from the table rather than interpolation from the curves is
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Table 3.1 Screening Concentrations for Exposure to
Ambient Air Concentrations^1*
Minimum Reported Level (ppmv)
Vegetation Sensitivity
Pollutant
S02
N02
COS
H2S
Ethylene1*
Fluorine
Beryl liumi
LeadJ
Averaging
Time
1 hr
3 hrs
1 yr
1 hr
4 hrs
8 hrs
4 hrs
8 hrs
1 mo
1 yr
1 wk
4 hrs
3-4 hrs
24 hrs
10 days
1 mo
3 mo
Sensitive**
.35(917)
.30(786)
.20(392)
.10(196)
.06(118)
2.0(3760)
2.0(3760)
1000
(1,800,000)
20.0-60.0
(28,000-84,000)
Intermediate
.80(2096)
.35(686)
.15(294)
.15(294)
5.0(9400)
4.0(7520)
Resistant
5.0(13100)
.55(1078)
.35(686)
.30(588)
9.0(16920)
8.0(15040)
10,000
(18,000,000)
400
(560,000)
Reference
14
16
17
18
18
18
19
19
f
20
21
22
24
25
26
27
28
All values except beryllium and lead refer to effects on vegetation.
^Minimum reported levels at which visible damage or growth effects to vegetation may
occur.
*
cValues in parentheses are ug/m3 at 20"C and 1 atm.
''These values should be used in the screening procedure unless it is known that only
intermediate or resistant plants will be affected.
eThe values for 20Z injury are reported here, since they correspond closely with other
values in the literature.
^Based on generalization of results of a number of studies.
8Reversible decreases in photosynthetic rate have been shown to occur at significantly
lower levels but effects on growth have not been demonstrated.
DEthylene " ... is the only hydrocarbon that should have adverse effects on vegetation
at ambient concentration of 1 ppm or less." (Ref. 23).
value to protect public health. Very toxic to humans and presumably to some
animals also.
JNAAQS value to protect public health.
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12
3.5
3.0
2.5|-
E
a
a
~ 2.0
O
2
9. 1-5
en
O
« 1.0
0.5
(a) SENSITIVE SPECIES
DAMAGE LIKELY
INJURY OR
DAMAGE
POSSIBLE
INJURY
I I
E
O
O
CM
O
co 2
(b) INTERMEDIATE
SPECIES
DAMAGE LIKELY
INJURY OR DAMAGE
POSSIBLE
NO
INJURY
I I
23456
EXPOSURE (hr)
23458
EXPOSURE (hr)
O
z
o
CM
g
10
9
3
(c) RESISTANT SPECIES
INJURY OR DAMAGE
POSSIBLE
NO
INJURY
J 1 1 I ' '
3458
EXPOSURE (hr)
VALUES
RECOMMENDED
IN THIS
PROCEDURE
Fig. 3.1 S02 Dose-Injury Curves for Plant Species
(From Ref. 8 as adapted from Ref. 29)
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1000 p
^ 100
I
a
ai
o
o
o
N
o
10
0.1
X-SCREENING
CONCENTRATIONS
USED IN THIS WORK
- METABOLIC
AND
GROWTH
EFFECTS
FOLIAR LESIONS
I I I Mill I I I I I 11 ll I t i I I I ll I I | | I | ill i I i | i t\
0.1
10 100
EXPOSURE (hr)
1000 10000
Fig. 3.2 N02 Dose-Injury Curves for Plant Species
(From Ref. 8)
recommended, since Che curves are based on attempts to fit theoretical dose-
response curves to experimental data whereas the tabulated screening concen-
trations are based directly on experimental results.
Several points are worth noting about the chosen screening concentra-
tions. First, the significant variation between the values for the various
sensitivity groupings should be noted. With this large variation it appears
unlikely that use of any values but those for sensitive vegetation could be
justified in a screening procedure, given the large number of species for
which information is. not available.
Second, the tabulated concentrations should be compared to NAAQS, PSD
increments, and likely ambient concentrations. Table 3.2 summarizes these
comparisons for the cases where they can be made. For pollutant/averaging
times not tabulated, either no corresponding NAAQS or PSD increment exists or
it appears that the screening concentration could be exceeded under certain
circumstances. For the criteria pollutants, the NAAQS appear to protect
against vegetative damage except possibly for 3-hr and annual S02 exposures.
For the 3-hr exposure, the screening concentration exceeds the applicable PSD
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14
Table 3.2 Screening Concentrations of Gaseous Pollutants
Compared to Ambient Criteria
Pollutant
S02
03
N02
CO
Averaging
Time
3 hr
1 yr
1 hr
4 hr
8 hr
1 yr
1 wk
Vegetation Sensitivity
Sensitive
< NAAQS3
> PSDb
> NAAQSf
-
c
Intermediate
> NAAQS3
> PSDb
> NAAQS f
c
c
Resistant
c
c
> NAAQSf
c
c
c
aS02 3-hr NAAQS = .SOppmv (1300 ug/m3) .
bS02 3-hr PSD increments (ug/m3) » 25(Class I), 512(Class
II), 700(Class III), 325(Class I variance). These values
do not include background.
cScreening concentration unlikely to be reached under ambient
conditions.
dS02 annual NAAQS .03 ppmv (80 ug/m3).
eS02 annual PSD increments (ug/m3) « 2(Class I), 20(Class
II), 40(Class III), 20(Class I variance). These values do
not include background.
f03 1-hr NAAQS = 0.12 ppmv (235 ug/m3).
8N02 annual NAAQS - O.OSppmv (100 ug/m3).
increments and for the annual exposure, it exceeds the Class I increment.
However, the screening concentration should be compared to the total S02
concentration including background whereas the PSD increment does not include
background. Thus, a source could cause an S02 concentration less than the
increment while the total S02 concentration (source plus background) could
exceed the screening, concentration. With the exception of the following it
appears that possible adverse impacts to vegetation resulting from direct
exposure to ambient concentrations of criteria pollutants are already covered
by existing programs for NAAQS attainment:
S02 exposures at 1 hour, 3 hours, and 1 year,
Ozone exposures at 4 and 8 hours,
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N(>2 exposures of sensitive species at 4 and
8 hours, and
Long-term N(>2 exposures at 1 month and 1 year.
This observation does not preclude doing a review for impacts on plants,
particularly where the minimum values at which effects have been reported
are close to being exceeded. It does, however, indicate that the vegetative
impact review can be done along with the review for NAAQS or PSD increments.
Even in cases where review for NAAQS and PSD increments covers exposures
to plants, there may still be the necessity of dealing with trace metal
exposures through deposition in the soil or through concentration in plant
tissues.
3.2.3 Synergisms
Only a very limited amount of information was available in the review
literature consulted regarding synergisms. Three indications of synergism
were found:
S02 and N02,
S(>2 and 03, and
SC>2, 03, and N02-
Table 3.3 presents values which could be used as screening concentrations
based on the most restrictive values in the references. Where averaging
times allow comparison, the screening concentrations for single pollutants
in Table 3.1 are greater than the screening concentrations for mixed pol-
lutants in Table 3.3. Given the problems with the data discussed in Sees. 3.1
and 3.2.1, this comparison should not be interpreted as clear evidence of
synergism. An additional caution is also in order- Mixtures of gases may act
synergistically on some species and antagonistically on others (see, for
example, Ref. IS). Thus, the tabulated values should be used to indicate
situations where the FLMs should be alerted so that the situation may be
evaluated by them. There may be additional synergisms which are not noted in
Table 3.3 but which could be added to the table and incorporated in the
screening procedure at a later date.
-------
16
Table 3.3 Synergisms of Gaseous Pollutants
(Plants)3
Pollutants
S02
N02
S02b
03
S02b
03
SO 2
03
N02
Cone en tr at ion s
(ppmv)
.05
.05
.30
.10
.05
.05
.14
.05
.10
Exposure
1 hr
1 hr
4 hr
6 hr/day
for 28
days
Reference
30
31
32
33
aThe same criteria were used in selecting these
values from Ref. 15 as were used in developing
Table 3.1.
bAntagonism, as well as synergism, has been
reported for mixutes of SC>2 and 03 (Ref. 18).
3.2.4 Screening Concentrations for Soil and Plant Tissue Exposures
Table 3.4 presents suggested screening concentrations for trace ele-
ments found to adversely affect plants. Two types of data are presented. One
gives a concentration which when present in the soil has been found harmful to
plants. The other gives a concentration found to be present in the tissues
of plants which had been harmed. In considering these values, it should
be remembered that most elements and compounds are not deleterious until they
have been complexed in the soil and become suitable for uptake by plants. In
addition, many soil characteristics such as pH, composition (sand, clay,
loam, organic matter, etc.), moisture content, and cation exchange capacity
affect the amount of trace elements available for uptake. In developing the
tabulated values, only data taken with the plants growing in soil were con-
sidered. Data developed in experiments in which plants were grown in aqueous
nutrient solutions were ignored. Conditions of nutrient solution culture are
likely to be sufficiently different from natural conditions as to render the
results of the experiments misleading for the purposes of this work.
As with the ambient screening concentrations for gases, a great deal of
variation is exhibited by the data as shown in Fig. 3.3. For comparison
-------
Table 3.4 Screening Concentrations for
Exposure of Vegetation to
Pollutant Concentrations in
Soil and Tissue
Minimum Reported Level
Pollutant
Arsenic
Boron
Cadmium
Chromium
Cobalt8
Copper
Fluoride3
Lead3
Manganese
Mercury
Nickel
Selenium3
Vanadium
Zinc
Pollutant Source
Soil Tissue
3 0.25
0.5 11
2.5 3
8.4 1
19
40 0.73
400 310
1000 126
2.5 400
455
500 60
13 100
2.5
300
(ppmw)
Reference
9
9
9
9,35
9
9
9
9
9,36
9
9
9,37
38
9
^Tissue concentrations may affect animals
before affecting plants. Compare to
toxic levels for animals in Table 3.7.
purposes, this figure includes results based on experiments in nutrient
solutions and also shows the values chosen for screening concentrations in
this work.
No standards or PSD increments currently apply to these trace elements
so no comparisons with other review criteria can be made. It should be noted,
however, that the heavy metals listed in Table 3.4 are emitted as particles
and become TSP in the atmosphere. To the extent that they contribute to TSP
levels, the NAAQS and PSD increments would apply to these trace elements. The
connection between such ambient levels and the screening concentrations for
soils and tissues is discussed in Sec. 5.
3.3 SOILS
In contrast to the amount of published information on the effects of
atmospheric pollutants on plants and animals, very little has been reported on
their effects on soils. Research on trace elements in soils, often the same
-------
10000
1000
O
cc
UJ
o
O
o
100
10
0.1
o
8
o
x o
-» Value used In this work
Plants grown in soils
O Plants grown in nutrient solution
x Growth medium unknown
S*Soll Concentration
T = Tissue Concentration
00°
o
o
8
i
0 O
*-
o
o
o
o
o
-**
o
o
*-
ST
As
S T
Be
ST
B
ST
Cd
J 1
ST
Cr
-LI-
ST
Co
.LI-
ST
Cu
JJ_
ST
F
JJ U M II
ST
Pb
ST
Mn
ST
Hg
ST
Mo
-LI-
ST
Nl
JJ LL
J_L
ST
Se
ST
V
ST
Zn
TRACE ELEMENT
oo
Fig. 3.3 Concentrations of Some Trace Elements Toxic to Terrestrial Plants
-------
elements as atmospheric pollutants, has been directed to notable deficiencies
or excesses that limit agricultural crop production. When the amount of an
atmospheric .pollutant entering a soil system is sufficiently small, the
natural ecosystem can adapt to these small changes in much the same way as the
ecosystem adapts to the natural weathering processes that occur in all soils.
Cultural practices (e.g., liming, fertilization, use of insecticides and
herbicides) add elements and modify a soil system more than a small amount of
deposited atmospheric pollutant can. The secondary effects of the pollutant
appear to impact the soil system more adversely than the addition of the
pollut-ant itself to the soil. For instance, damaging or killing vegetative
cover could lead to increased solar radiation, increased soil temperatures,
and moisture stress. Increased runoff and erosion add to the problem. The
indirect action of the pollutant, through changes to the stability of the
system, thus may be more significant than the direct effects on soil inverte-
brates and soil microorganisms. However, the lack of long-term historical
data on both the type and amount of atmospheric pollutants as well as the lack
of baseline data on soils has made difficult the task of determining the
effect of pollutants on soils by monitoring changes associated with exposure
to pollutants. A limited number of studies have been carried out on trace
element contamination of soils.39,40 plant and animal communities appear to
be affected before noticeable accumulations occur in the soils. Thus, the
approach used here in which the soil acts as an intermediary in the transfer
of deposited trace elements to plants appears reasonable as a first attempt at
identifying the air quality related values associated with soils.
When viewing soils in this way it is important to know the endogenous
or background concentrations of elements already in the soil of interest, for
these endogenous levels may be available for plant uptake. There is, however,
a wide variation in the normal concentrations of various trace elements as
shown in Table 3.5.8 if extremes in the concentrations are considered, the
range of endogenous concentrations becomes even larger (see Fig. 3.4) .43. Both
references show relatively good agreement on the normal ranges. The tabulated
values also provide "average concentrations" which can be used when specific
information about the concentrations of trace elements in the region of
interest is not available. One of the difficulties with screening for
impacts on plants and soils becomes apparent when the endogenous concentra-
tions in Table 3.5 are compared with the screening concentrations for soils in
-------
20
Element
Arsenic
Beryllium
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanad ium
Zinc
Average Soil
Range Concentration
(ppmw) (ppmw)
0.1-40
1-40
2-100
0.01-7.0
5-3000
1-40
2-100
30-300
2-100
100-4000
0.01-4.0(7)
10-1000
0.01-80
20-500
10-300
6.0
6.0
10.0
0.06
100
8
20
200
10
850
-
40
0.5
100
50
aBased on Ref. 8.
Table 3.4: the screening values are Table 3.5 Range of Endogenous Soil
exceeded for some part of the listed £f en"a'ion8 °fa
f Selected Elements9
range for nine out of the twelve
elements for which screening concen-
tration are given. Fluorine, lead,
and mercury are the only elements
whose screening values lie above the
corresponding endogenous ranges.
The default average soil concentra-
tion exceeds the screening concen-
tration for boron, manganese,
vanadium, and chromium and, for the
first three of these four, the
entire listed normal range exceeds
the screening value. In inter-
preting this indication, it must be
remembered that the screening
concentration value represents
the lowest value found in the
review literature (see Fig. 3.3) and that not all plant species are as
sensitive as the one upon which the value is based. As outlined in Sec.
3.2.1, there are many additional reasons why there is no inherent conflict
between screening concentrations and endogenous concentrations above these
values. The chief among these are probably the variation in sensitivity
between individuals, the variation in sensitivity between species, and the
fraction of the endogenous concentration really available for uptake by
plants. It should be noted, however, that endogenous concentrations of some
elements can make soils toxic to some species. Thus, certain tolerant plants
can act as indicator species for the element tolerated; they will be among the
species present in soils where the endogenous concentrations of that element
exceed levels toxic to more sensitive species.12
The problem associated with the amount of an element in the soil which
is actually taken up into plant tissues can be handled in an approximate
fashion by using a plant:soil concentration ratio. Table 3.6 provides two
sets of concentration ratios (CR's). One set is recommended for use in this
work; the other is based on nonstandard methods using solution cultures
-------
<-N
a.
a
s^
Z ..-
o 10000
p
£ 1000
Jg
111
o
z too
o
o
_J
5 10
CO
i i
Z 0.1
- !
. 1
mv
1
1 I
i i
1 S
^
i
EXTREMES
R
-"
ti
\
\
j
f
i ;
1 I
T 1
1 1
f
*
^
?
*
?
1
M
pi NORMAL
P RANGE
i
I
3
i
i
t
>
1 i n
* i &
' * -.
< * &
V: ' f
I
0
SEE
5-25
« c -o - o
^B ^^ *
e e * "S
O
a
c
>
.*
o
N
o.
a
o
O
o
OQ
a>
<
0
A
O
O
«
«
CO
ELEMENT
Fig. 3.4 Range of Endogenous Concentrations of Trace Elements
(From Ref. 41)
-------
22
but is given to provide some feeling
for the large uncertainties asso-
ciated with this type of work. The
comparison set of concentration
ratios could be used in the screening
procedure presented here to provide
very conservative estimates of
potential impacts. Some elements
(boron and cadmium) tend to be
concentrated by plants (ratios > 1),
that is, concentrations in plant
tissues exceed those found in the
soil whereas the concentrations of
most of the listed elements tend
to be less in plant tissue than
in the surrounding soil . In any
case, these CR's represent ratios of
averages^ and thus may give results
Table 3.6. Plant: Soil Concentration
Ratios
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Recommended
Value3
0.14
5.3
10.7
0.02
0.11
0.47
0.03
0.45
0.066
0.02-0.5
0.045
1.0
0.01
0.64
Comparat ive
Valueb
4.2
-
222
250
87
1000
2
3000
26
331
4
1
40
a8ased on Ref. 8.
^Based on Ref. 12. Based on non-
standard methods involving solution
cultures. See discussion in text.
quite different from the true ratio
between plant and soil concentrations in a particular case. However, they
appear to be the best means available for estimating .uptakes of various
elements from the soil.
3.4 FAUNA
The screening concentrations presented here are based on data for
terrestrial vertebrates. Data for aquatic species, including fish, were not
examined in the literature reviewed. Also, effects on aquatic and terrestrial
microorganisms are not considered here. Table 3.7 presents the screening
concentration values based on data summarized in Refs. 8 and 9. The tabulated
values represent the lowest dietary concentrations found to be harmful.
Several factors limited the usefulness of the available data. Some harmful
levels were given in terms of average concentrations in the affected animals.
Unfortunately no equivalents of the plant :soil CR's were available to go from
dietary concentrations to concentrations per unit body weight. In addition,
all the data on ambient exposures failed to give averaging times thus ren-
dering it unuseable in this screening procedure. Even for the data upon which
-------
Table 3.7 is based, there were no
indications as to how long the
element needed to be ingested in the
given concentration before causing
the harmful effect. Comparison of
the screening concentrations for
animal effects (Table 3.7) with the
values for plant tissue concentra-
tions (Table 3.4) shows that the
values for animals generally exceed
those for plant tissue concentra-
tions. However, for cobalt, fluor-
ide, lead, and selenium, it appears
that plants could accumulate concen-
trations that would be toxic to
some animals before the plants
themselves were harmed.
Table 3.7- Dietary Trace-Element
Concentrations Toxic
to Animals3
Dietary
Trace Element Concentration (ppmw)
Arsenic''
Cadmium^
Cobalt
Copper''
Fluoride
Lead
Manganese''
Nickelb
Selenium
Vanad ium
Zinc
3
15
1-3
20-30
. 100-300
80-150
500-5000
1000
5-30
10-500
500-1000
aBased on Ref. 8.
^Tissue concentrations in plants may
affect plants before affecting
animals. Compare to plant screening
concentrations in Table 3.4.
For beryllium and lead,
data on ambient air exposures were available in terms of the NESHAP and NAAQS,
respectively (see Table 3.1). These values relate to human exposures. With-
out other indications these same levels have been assumed to be potentially
hazardous to at least some animals as well.
-------
4 TRACE ELEMENT AIR QUALITY DATA
EPA's Storage and Retrieval of Aerometric Data (SAROAD) system was used
as a data base to develop air quality information for trace elements. The
information was intended to serve primarily as an aid in estimating background
concentrations so minimum concentrations were included. A secondary purpose
of the information was to identify locations where high concentrations already
exist. For this purpose, maximum concentrations were included. Compilation
of available data for all the pollutants discussed here with estimates
for all relevant averaging times would not have been feasible so the data
search was limited to trace elements including lead. It was also felt that
more complete data for the gaseous criteria pollutants would be available
locally than could be found in SAROAD. On the other hand, many localities
probably lack estimates of trace element concentrations. Since only annual
averages are used in screening for trace element impacts, the data search
emphasized annual average data. Maximum and minimum short-term observations
have been included in the data compilations for informational purposes.
In order to improve coverage, data for 1975-77 inclusive were used.
Many locations had data for only one of the three years. As expected, all
the data were based on high volume sampler data with 24-hour averaging times.
It was also frequently the case that insufficient data was available to allow
the calculation of a valid annual average. The available data is presented in
Appendix C. No data was found for mercury, boron, cobalt, copper, and nickel.
The data is presented by state and county for each pollutant. As can be seen
from the tables, the spatial coverage is poor. For counties with data, only
the minimum and maximum annual averages from all reporting stations are given.
With multiple stations, it is unlikely that both values come from the same
location.
In order to avoid possible misinterpretation of the data, it should be
kept in mind that SAROAD routinely stores values below the limit of detect-
ability as one-half the minimum detectable limit. In some cases, this will be
the value which is listed as the minimum observation. These situations are
usually fairly obvious, since the same minimum value will be recorded at a
large number of stations.
-------
25
5 SCREENING PROCEDURE
5.1 METHODOLOGY
5.1.1 Description
A simplified view of the pathways between sources and receptors is
presented in Fig. 5.1. This simple view is used here as the basis for
screening a source for potential adverse impacts on plants, soils, and
animals. Emissions from the source are assumed to disperse in the atmosphere
and add to whatever local background concentrations might exist to provide
an estimate of the maximum ambient concentration for the averaging times
of interest. These ambient concentrations may act along four different
pathways. The first two are routes in which the ambient concentrations
affect animals or plants directly without any intervening mechanisms.
In the third, animals can ingest substances deposited on plants before the
substances have been washed off by rain or blown off onto the soil. Such
ingestion is a critical pathway. Appendix D provides a referenced discussion
of the literature related to toxicity resulting from this pathway and the
potential for harm to animals exists whenever heavy metals are deposited on
materials which they ingest. Some start on dealing with this issue was made
here in terms of estimating the amount of deposited material but a complete
methodology was not developed. However, reviewers should be aware of this
potentially critical pathway and the material in Appendix D may be useful
in flagging critical situations. In the fourth, a certain amount of the
dispersed material is deposited on the soil. As noted in Sec. 3, only the
deposition of trace elements is considered here. The deposited trace elements
as well as any endogenous concentration of the element are then available for
uptake by plants in quantities which may be toxic to the plants themselves or
to animals which feed upon the plants.
It is important to realize that this simplified picture leaves out
many potentially important pathways and natural processes. For example,
there is no provision for the uptake and concentration of substances by
plants directly from the air; all such concentration is assumed to be through
the soil with uptake by plant roots. No account is taken of removal of
deposited substances from the soil by runoff, leaching, or erosion and the
-------
Background
Cone.
Source
Direct
Exposure
Deposition
(Trace
Elements)
Endogenous
Cone.
Participate
Deposition
Forage
and
Fodder
Soil
Cone.
Uptake by Roots
Fig. 5.1 Pollutant Pathways
-------
27
subsequent deposition of such substances in bodies of water. Also, no account
is taken of deposition directly from the air into water. Finally, the effects
on animals of ingesting contaminated water have not been addressed.
Screening for a particular source is accomplished in a series of
steps. Steps 1 and 2 apply to airborne pollutants; steps 1 and 3-7 apply for
trace metals where deposition must be taken into account. Step 8 provides an
alternative where modeling results for the source are unavailable.
1. Estimate the maximum ambient concentration for averaging
times appropriate to the screening concentrations for
pollutants emitted by the source and including any
background concentrations.
2. For exposures to airborne pollutants, check the maxima
from Step 1 against the corresponding screening concentra-
tions in Table 3.1 or against the corresponding NAAQS,
NESHAP or PSD increments, whichever applicable standard
is most restrictive. In addition, the possibility of
synergisms should be considered.
3. For trace metals, calculate the concentration deposited
in the soil from the maximum annual average concentra-
tion assuming that all deposited material is soluable
and available for uptake by plants.
4. Compare the increase in concentration in the soil to
the existing endogenous concentration using the average
values in Table 3.5 when local data is unavailable.
(This provides a supportive indicator, not a primary
decision parameter.)
5. Calculate the amount of trace element potentially taken
up by plants using the CR's in Table 3.6.
6. Compare the concentrations from Steps 3 and 5 with the
corresponding screening concentrations in Tables 3.4
and 3.7.
7. Reevaluate the results of the comparisons in Steps 4 and
6 using estimated solubilities of elements in the soil to
provide supportive indications, recognizing that actual
solubilities may vary significantly from the estimated
values.
8. If modeling results are unavailable, the significance
levels for emissions developed in Sec. 5,2 may be used
to screen the source.
The discussion in Sec. 5.2 also provides an example of the application of
the screening procedure. This example develops the significant emission
levels for one of the trace elements from an estimate of a source's maximum
-------
annual average concentration. Table 5.1 summarizes these steps and indexes
them to the relevant sections, tables, and equations in the text. Figure 5.2
provides a flowchart of the screening procedure showing the more commonly
used tables and equations.
5.1.2 Estimating Maximum Concentrations (Step 1)
To estimate the maximum concentration, the maximum air quality impact
of the new source must be estimated and added to an appropriate background
c one entrat ion.
5.1.2.1 Air Quality Modeling
The first step in the screening procedure for air quality related
values is to estimate the maximum ambient concentrations of pollutants
emitted from the new source for appropriate averaging times. Table 5.2 gives
the correspondence between pollutants and the averaging times to be considered
for each. Two cases need to be considered. The first arises when the
required source-specific concentration estimates are available and the second
arises when they are not.
Concentration Estimates Available. When source-specific estimates
made by an approved model are available they should be used directly in
making the calculations and comparisons called for in Steps 2-7 of Table 5.1.
Such a situation would be ideal but such estimates may frequently be unavail-
able, particularly during early discussions of a permit application.
Concentration Estimates Unavailable. When source-specific estimates
of concentrations are unavailable or when they are lacking for some critical
averaging times, there are two courses of action:
Use of a screening technique for air quality impacts
if the emission rates and stack parameters are
available or
Use of the significance levels for emissions presented
in Sec. 5.2.
If stack parameters are available, some simple techniques of dispersion
modeling can be used to screen the source for its air quality impact, remem-
bering that only a screen and not a definitive demonstration is required.
Reference 42 provides such techniques developed by EPA for use in new source
-------
Table 5.1 Steps in Screening Procedure
Step
1
2
3
4
5
6
7
8
Description
Estimate ambient maxima
Modeling
Background
Screen for direct exposure
Calculate deposited concentration
of trace elements8
Calculate percentage increases
over endogenous concentrations^
Calculate tissue concentrations
in plants
Screen for potential adverse
impacts of trace elements
Consider effects of trace element
solubility''
Apply significance emission levels0
Applicable
Text
Section Tables Equation
5.1.2
5.1.2, Appendix C C
5.1.3 3.1
5.1.3
5.1.3
5.1.3
5.1.3 3.4
5.1.3 3.4
5.2 5
.1-C.10
,3.3,5.3
5.1
3.5 5.4
3.6 5.5
,3.7,5.5
,3.7,5.4 5.7,5.8
.6,5.7
aReviewers may want to review the information in Appendix D to assess the potential for
harm to animals from directly ingesting deposited materials.
bSupportive indication only, not primary decision parameter.
cUsed only when source-specific modeling results are not available.
ro
vo
-------
Uiln Flw
TIMMH InrinrnllM
ili In B»» Rifw »
3t»l In PraeMurt-Sii TtiU S. I.
Fig. 5.2 Flowchart of Screening Procedure
-------
Table 5.2 Pollutants and Averaging Times
Pollutant
S02
N02
CO
H2S
Ethylene
Fluoride
Be
Pb
Trace Elements'*
Required Averaging Times
1 hr 3 hr 4 hr 8 hr 24 hr 1 wk 10 days 1 mo 3 mo 1 yr
X X Xa Xb
XX X Xb
Xa Xa X
Xa X
X X
Xa X
xa
xb xc
xe
aFor comparison with criteria not necessarily related to impacts on plants, animals,
or soils (NAAQS, NESHAP's, PSD increments).
bApplies to both impacts on plants, animals, soils and other criteria.
cAlso included in trace element analysis.
dTrace elements: As, B, Cd, Cr, Co, Cu, F (as fluoride), Pb, Mn, Hg, Ni, Se, V, Zn.
eRequired for use in estimating amount of deposition.
-------
review. These methods were used to develop EPA's significance levels for
emissions42 published as part of the proposed PSD regulations.^3,44
As an alternative, the procedure used in Ref. 45 to estimate air
quality impacts can be used as presented in Appendix A. Some expansion
of the original procedure was required to cover the range of averaging
times needed for this screening procedure. The equations presented in
Appendix A are suitable for hand calculation or the development of a simple
computer code. The significance levels presented in Sec. 5.2 are based on
this procedure.
5.1.2.2 Background Concentrations
The estimation of background concentrations is one of the perennially
difficult problems of air quality analysis. Development of new approaches
was beyond the scope of this work. The analyst should consult Ref. 46 for
guidance on this subject. No attempt was made here to develop information for
the gaseous criteria pollutants. For these gases, it was felt that local
records would be likely to provide more timely and complete information. In
addition, the sheer volume of data available precluded its inclusion in this
procedure. No attempt was made to develop background estimates for other than
annual averaging times.
For the 14 trace elements (including lead), EPA's SAROAD files were
searched as described in Sec. 4. No information was found for mercury, boron,
cobalt, copper, and nickel. The tables in Appendix C summarize the informa-
tion found by state and county. To estimate a background value, the concen-
trations in the county of interest or nearby counties should be used and
the minimum geometric mean picked. This minimum can then be added to the
estimated «q?«imi^i» annual concentration from the source being screened. Values
of the minimum geometric mean from other areas should be compared with the
value chosen. It is possible that some of the tabulated minima may be too
high to represent background levels because the monitor providing the data is
impacted by a large source and thus is not representative of general back-
g round c ond i t ion s.
It will not be possible to estimate background levels by this method
for many locations. In such a situation, the minimum geometric mean may
-------
33
be selected from among those tabulated in Appendix C and used in a sensitivity
analysis to determine if the addition of a background level is likely to
raise the predicted concentration above the screening concentration. If
it does, then a determination of background will be necessary to allow a
clear determination of the source's potential to cause adverse impacts due
to trace element deposition.
5.1.3 Screening and Deposition (Steps 2-7)
Screening for Direct Impacts (Step 2). This screen applies to the
pollutants listed in Table 3.1 for which data was available on direct impacts
of airborne concentrations on plants and animals: SC>2, N02, CO, t^S, ethyl-
ene, flourides, Be, and Fb. After the maximum concentrations both with and
without background have been calculated, screening is simple. The appropriate
maxima are compared to the values given in Table 5.3. Values in excess of
the screening concentrations indicate that additional detailed review is
required and that the appropriate FLM should be notified. The possibility of
synergisms should also be checked at this point. Consideration should be
given to the synergisms listed in Table 3.3 but no screen on the values listed
there is recommended here. Rather, the information could be used to alert the
appropriate FLM to the possibility of a problem arising from synergisms.
Also included in Table 5.3 are the values used in reviewing new sources
under other criteria. The value expected to be controlling for each pollutant
has been circled in the table under the following assumptions:
No background,
Long averaging times result in lower concentrations
than short averaging times, and
For short averaging times, the concentration is
proportional to averaging time raised to the power
-0.17.
This observation is made only to give some feeling for what might be expected.
It is possible, for example, for a new S02 source in a Class III area to
be controlled by the 700 ug/m3 PSD increment and still need to do a review
for plant, soil, and animal impacts if 3-hour background levels are high
enough to make the predicted ambient concentration likely to exceed 786 ug/m3.
Completion of Step 2 would complete the screening for direct impacts from
airborne pollutants.
-------
Table 5.3 Ambient Screening Concentrations
Aabient Concentration
Pollutant and Averaging Ti«e*
Screening ^? M°2 CO H2S Ethylene fluoride Beryl1in* Lead
Criterion 1324A48MA1 8 W 4 3 24 240 M 3M
AQRV
Screening
Concentration11 917 786 - 18 3.760* 3760b 564 C^fi) - - l.SOO.OOO1* 28,000* 47(772) Qj^) CfiD CLi-
NAAQSc.d - 1.300 365 80 (loo)40,000
PSD Increment
ie.f _ 25 C_O 2-----
II*. f -512 91 20-----
Ilie.f - 700 182 40 -----
Variance6.8 -325 91 20-----
NESHAPf>h --_____._
Note: Circled value* expected to be controlling; «ee text.
aNumeral8: hour*
W: 1 week
M: 1 Month
A: Annual
'Ambient concentration* thi* high are unlikely.
C40 CFR 50.
dBaaed on maxiaua impact of aource plu* background.
eRef. 1.
fBased on oaxinua impact of source alone.
^Includes the aource together with all other source*.
h40 CFR 61.
-------
35
Calculating Deposited Soil Concentrations (Step 3). Deposition of trace
elements is a long-term process extending over the lifetime of the source.
The simple procedure used here depends upon an estimate of the maximum annual
average concentration from the source as corrected by the addition of a
background concentration if known. Reviewers may also want to review Appendix
D at this point to assess the potential for harm to animals from direct
ingestion of deposited heavy metals (see Sec 5.1.1). The following equation
can be used to estimate the maximum concentration in the soil:
DC(ppmw) = 21.5 (N/d)X (5.1)
where:
DC = deposited concentration (ppmw),
N = expected lifetime of source (yr),
d = depth of soil through which deposited material
is distributed (cm), and
X =» maximum annual average ambient concentration from
the source (ug/m^).
The value generally recommended for d is 3 cm.8,9,12 Some work*-3 has assumed
20 cm for d, but the more conservative value of 3 should be adopted for use
in this screening procedure unless site-specific data indicate that greater
penetrations of deposited substances are more representative of local condi-
tions. It should also be noted that an estimate of the source's lifetime must
be made in order to use Eq. 5.1. In the absence of contrary indications, a
value of N s 40 years should provide a reasonable and generally conservative
estimate of source lifetimes based on lifetimes equal to twice the time
allowed by the Internal Revenue Service for equipment depreciation.^, 47
If the source is tied to a resource, the estimated resource lifetime might be
used instead of 40 years. For example, a mine-mouth power plant might have a
lifetime of N = 100 years based on the life expectancy of the mine or a gas
plant might have a lifetime N = 15 years, the expected useful life of the gas
field.
Equation 5.1 is simply derived. Consider a volume of soil 1 m2 in
area and d cm deep at the location of the source's annual maximum. The weight
of material deposited on this area of 1 m2 can be calculated as:
-------
/Weight \ /Ambient \ /Deposition^ ,. 2^ IT- \ t* «\
^Deposited) " (concentration) * ^Velocity J * (1 m } X (Tme)' (5'2)
The weight of the soil in the volume of interest is
/Weight \ m /Volume
\of soil/ ^of soil
/Weight \ m /Volume \ /Bulk Density\
l/ \ of soil j
(5.3)
Then the ratio of the weight deposited to the weight of the soil can be
used to find the concentration of the deposited material by weight in the
soil. Soil densities range from 1-2 gm/cm3 and a value of 1.47 g/cm3 is
assumed here as a good average value. 12 if an average value of 1 cm/sec is
assumed for the deposition velocity, Eqs. 5.2 and 5.3 can be combined to
give
DC - (Weight deposited) /(Weight of soil)
1 m
- 21.5 (N/d) X |
21.5 (N/d) X(ppmw)
where conversion factors have been used as appropriate to give consistent
units. This result is simply Eq. 5.1. The principal assumptions in this
derivation are:
Deposition velocity of 1 cm/sec,
Average bulk density of soil » 1.47 gm/cm3,
Uniform distribution of deposited material throughout
the soil volume, and
All deposited material is retained by the soil, that
is, no leaching, surface runoff, or erosion.
Calculate Increase over Endogenous Soil Concentration (Step 4). The
purpose of this simple calculation is to provide a supportive indication
-------
37
for the primary screen for deposition to be carried out in Step 6. As sug-
gested in Ref. 13, an increase over the endogenous concentration of more than
10% over the lifetime of the source could be taken as a possible cause for
concern. The percentage increase is simply calculated from
(% Increase) - [DC(ppmw) x 100)]/[Endogenous
Concentration (ppmw)] (5.4)
where the deposited concentration (DC) was calculated in Step 3. The average
endogenous concentrations from Table 3.5 can be used but data for the area
of interest is preferable given the wide range in natural concentrations.
It is not recommended at this time that a source be flagged for
further actions based solely on the results of this calculation. The results
of the screens in Step 6 are appropriate for that purpose. However, an
indicated increase of more than 10% in this step would increase the assurance
with which a finding that additional action was necessary could be made.
Calculate Potential Concentrations in Plant Tissue (Step 5). Once
the deposited concentration in the soil has been calculated using Eq. 5.1,
straightforward application of the plant:soil concentration, ratios in Table
3.6 can be used to estimate the concentration in aerial plant parts (tissue
concentration)
[Tissue concentration (ppmw)] *
[Deposited concentration (ppmw)] x [Concentration ratio]
or
TC (ppmw) » DC (ppmw) x CR (5.5)
using TC for tissue concentration and other symbols introduced earlier.
Equation 5.5 requires an additional conservative assumption:
All the deposited material is soluable and
available for uptake by plants.
This assumption is almost always violated in practice. Table 5.4 gives
the solubilities of some trace elements based on extraction of these elements
from endogenous concentrations in the soil.13 of course, the solubilities of
exogenous deposited elements could differ markedly from these values as could
the solubilities of endogenous concentrations in different soils. The solu-
bility of a trace element in the soil depends upon many factors. Among these
-------
Table 5.4 Solubilities of Endogenous
Trace Elements*>b
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Solubility
«)c
9
40
0.004
0.4
0.1
37
0.8
0.1
21
8
Emission Rate
Increase Factor^
11
2.5
25,000
250
1,000
2.7
120
1,000
4.8
12
aBased on Ref. 13.
bUsed in Step 7.
C0nly soluable fraction would be available
for uptake by plants.
dUsed when Step 8 is required.
are chemical form, temperature, presence of other elements, selective uptake
by plants, soil pH, and soil moisture content. The composition of the soil is
also an important determinant of solubility, especially the presence of
organic matter and clays which can bind trace elements. The point is that a
significant portion of the exogenous concentration may be unavailable for
uptake by plants, making Eq. 5.5 a conservative estimator.
Screen for Potential Adverse Impacts from Trace Elements (Step 6).
At this point the screen for adverse impacts from the deposition of trace
elements is straightforward. The process is similar to that used in Step 2,
that is, the comparison of calculated concentrations to tabulated screening
concentrations. In this step, however, three comparisons need to be made:
-------
39
1. The deposited concentration (DC) is compared to
the soil screening concentration in Table 3.4,
2. The tissue concentration (TC) is compared to the
tissue screening concentration in Table 3.4, and
3. The tissue concentration (TC) is compared to the
dietary screening concentration for animals in
Table 3.7.
A calculated concentration in excess of any one of the three screening concen-
trations is an indication that a more detailed evaluation may be required for
the new source and/or that the FIM should be notified, since there are indica-
tions of potential adverse impacts to plant, soils, or animals. In making
these three comparisons, the following additional assumptions have been
made:
All deposited forms of an element have the same toxicity,
The feeding or grazing range of animals is limited to the
area exposed to the estimated maximum annual concentration,
and
Most importantly, it is the exogenous incremental burden
which should be compared with the screening concentration
values, not the burden which would result from both the
exogenous and endogenous concentrations.
This last assumption is critical and follows the procedure used in Refs. 12
and 13. The assumption is implicit in Eq. 5.5 where only the deposited
concentration (DC) is used to calculate the tissue concentration (TC) and in
the three screens as defined above.
The three screens can be compared to see which is the most restrictive.
The screening value for concentrations in aerial plant tissues and for concen-
trations toxic to animals can be converted into equivalent soil concentration
values by use of the plantrsoil concentration ratios. The dietary concen-
tration potentially toxic to animals can be thought of as the concentration in
aerial plant parts that may be toxic to animals. Thus, Eq. 5.5 can be re-
arranged to give the equivalent deposited concentration (EDC) corresponding
to a particular screening tissue concentration (STC):
EDC (ppmw) = STC (ppmw)/CR (5.6)
where the STC is either the plant tissue screening concentration from Table
3.4 or the animal screening concentration from Table 3.7. in fact, Eq. 5.6
provides an alternative approach to the screening procedure that is equivalent
-------
to the one presented here. Table 5.5 gives the equivalent deposited concen-
trations (EDCs) for the trace elements. Based on the CR's and assumptions
used here, animals appear to be the critical receptor for cobalt, lead, and
«
selenium while tissue concentrations in plants appear to be critical for
arsenic, cadmium, copper, and zinc. For the remaining seven elements, the
soil concentration appears to be critical. As long as the screening concen-
trations and concentration ratios given here are used, Table 5.5 can be used
to reduce the number of comparisons required for a screen. For example,
cadmium sources need only be screened against the single screening value for
plant tissue concentrations, since this screening concentration is shown to be
controlling in the table.
Table 5.5 Equivalent Exogenous Soil
Screening Concentrations
Trace
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Equivalent
Soil*
3
0.5*
2.5
8.4d
-
40
400d
1000
2.5d
455d
SOQd
13
2.5d
-
Deposited Concentration (ppmw)
Plant
Tissue^
1.8d
2.1
0.28d
50
170
1.6d
10,300
280
6,100
-
1,300
100
-
470d
Animals0
21
-
1.4
-
9.1d
43
3,300
180d
7,600
-
22,000
5d
1,000
780
aSame as soil value in Table 3.4.
bEDC * (STC for plants from Table 3.4)/CR.
CEDC « (STC for animals from Table 3.7)/CR.
dContro11ing value.
-------
41
Since acute fluoride poisoning in various species of cattle has been
well documated,48 it is surprising that animals do not appear to be critical
for fluorides. This may be due to the omission of the critical pollutant
pathway involving ingestion by animals of materials deposited on plants
prior to these materials being washed off or blown off the plants and carried
into the soil. The same indication could be given of course, if the screening
concentration value for the effects of soil fluorides on plants were based
upon a very sensitive species. Further detailed investigation and more data
would be required to determine whether the latter explanation is true or
whether there is a deficiency in the procedure outlined here. In either case,
the fluoride example serves to illustrate the potential problems involved
in screening for impacts on air quality related values.
Consider Effects of Solubilities (Step 7). The assumption that all
deposited material is soluable and available for uptake by plants is unlikely
ever to be met in practice. If a screen indicates that a further action
is needed on a source because its emissions will cause a trace element screen-
ing concentration to be exceeded, an attempt may be made to look at the
possible effect of reduced solubility on that indication by considering the
solubility of the deposited material. This additional consideration should
only be used as a supportive indicator; it can only increase confidence in
the decision to take further action; it can never reverse such a decision
based on the screens in Step 6. That is, the conservative assumption of
100% solubility should be used in making the decision for further action on
the source.
If the solubility of a particular trace element is SZ, the amount
actually available for uptake (AA) by plants is
/Amount \
I available )=» DC x (S/100)
\for uptake/
or
AA = DC x (S/100). (5<7)
This value for AA should be compared with the soil screening concentrations
in Table 3.4. An equation similar to Eq. 5.5 can now be written reflecting
-------
the assumption that only the fraction AA of the deposited concentration is
available for uptake.
TCcorr. - AA x CR - DC x (S/100) x CR - TC x (S/100) (5.8)
where TCcorr> stands for the tissue concentration corrected for the solubility
of the deposited material. The new values of TCcorr% could be compared with
the screening concentrations for plant tissues and animals given in Tables 3.4
and 3.7, respectively.
5.2 EXAMPLE SCREEN AND SIGNIFICANT EMISSION RATES
Section 5.2.1 illustrates the use of Steps 1-7 of the screening
procedure through application to a source of nitrogen dioxide and arsenic.
Whenever source-specific estimates of maximum concentrations are available
or can be generated. Steps 1-7 should be used. Step 8 provides an alternative
screening procedure based on the concept of significant emission rates
(SER). Section 5.2.2 illustrates the derivation of the SER for arsenic from
the results for the example source and describes the use of the SER's for
screening. Use of the SER's precludes any consideration of the emission
characteristics cf the source other than emission rate. Local conditions
including background also cannot be taken into account. Application of Steps
1-7 is the preferred procedure.
5.2.1 Example Screen
The example source is assumed to have a plume release height of 30 m
(physical stack plus plurae rise). It is assumed that the source is subject
to PSD review and Chat it is desired to screen the source for arsenic and
nitrogen dioxide among other pollutants. An emission rate of 1 T/yr of
arsenic is assumed for this example and estimates of maximum concentrations
of N02 are available for 4-hour and 8-hour averaging times. Following Table
5.1 or Fig. 5.2, the first step in the procedure is to estimate maximum
concentrations for the times listed in Table 5.2. For arsenic, these esti-
mates need to be made. Using the simple modeling procedure outlined in
Appendix A, the maximufa annual average ground level concentration is found to
be X = 0.1051 ug/m^. Other appropriate models or techniques could also be
used. If an insignificant background is assumed for the example, this
result completes Step 1 of the screening procedure for arsenic. For N02, the
-------
43
available results show maximum ground level concentrations (including back-
ground) of X^. = 51 ug/m3 and Xg » 45 ug/m for averaging times of 4 and 8
hours, respectively. (A little foresight will show that estimates need not be
made for 1 mo and 1 yr.) These results complete Step 1.
Then in Step 2 of the screening procedure, these maximum concentrations
for N(>2 would be compared to the appropriate screening concentrations in
Table 3.1 or Table 5.3. For N02, the screening concentration at both 4 and 8
hours is 3760 ug/m3. The estimated maxima are for below this value. No
calculation need be done for the one month and annual averaging times, since
the modeled 4- and 8-hour maxima are already below the corresponding screening
concentrations. There would thus be no indication that a more detailed review
would be required for NC>2 impacts on plants, soils, and animals.
Since the screen also involves a trace element, the next step is
Step 3. If a 10-year lifetime (N="10) is assumed and the recommended value of
3 cm is used for the depth of soil throughout which the deposited arsenic is
mixed, Eq. 5.1 gives
DC - 21.5 (N/d)X
* 21.5 (10/3) x (.1051) 3 7.53 ppmw as the concentration
of arsenic in the soil.
Following with Step 4 and Eq. 5.4,
[% Increase] = 7.53 x 100/6 - 126%
where 6.0 ppmw has been used as the average endogenous soil concentration
of arsenic from Table 3.5. Thus, there is a supportive indication that the
source should receive further review if Step 6 shows the potential for adverse
impacts because the source may increase concentrations of arsenic in the soil
by more than 10%. In Step 5, the plant tissue concentration would be calcu-
lated from Eq. 5.5:
TC - DC x CR - 7.53 x 0.14 - 1.05 ppmw.
Next the screening comparisons are made in Step 6. The DC ("7.53 ppmw)
exceeds the soil screening concentration of 3 ppmw for arsenic given in
Table 3.4. Similarly, the TC (1.05 ppmw) exceeds the tissue screening concen-
tration of 0.25 ppmw given in Table 3.4. The TC does not exceed the animal-
related screening concentration of 3 ppmw given in Table 3.7. There are thus
-------
two indications that this source might adversely affect plants and that
further actions need to be taken.
To look at the possible effect of arsenic solubility on these indica-
tions, the calculations in Step 7 can be done. For arsenic, Table 5.4 gives a
solubility of 9Z to account for the limited solubility of arsenic compounds.
Equations 5.7 and 5.8 give AA - 7.53 x .09 0.68 ppmw and TCcorr * 1-05 x .09
0.0945 ppmw. AA does not exceed the soil screening concentration of 3 ppmw
and TCcOrr does not exceed the tissue screening concentrations for plants and
animals, 0.25 ppmw and 3 ppmw, respectively. Thus, no supportive indication
has been found but the original indication that additional detailed work is
required on the source is not altered and it is known that solubility effects
might be important.
5.2.2 Significant Emission Rates
Basic Levels. This subsection discusses the development of a signifi-
cant emission rate (SER) for arsenic based on the generic source discussed*in
Sec. 5.2.1 with a release height of 30 m and an expected lifetime of 10 years.
An SER is defined as the minimum emission rate which would cause the source's
impact to just equal the screening concentration. That is,
/Sign ificantX
I emission I * [(Screening concentrationVCConcentration from source)]
\rate /
x (Source's emission rate).
For arsenic in soils and the example source,
SER(Soils) - [3/7.53] x (1 T/yr) - 0.40 T/yr.
Arsenic emissions from this source in excess of 0.40 T/yr might be expected
to cause a soil concentration in excess of the screening concentration.
Similarly, significant emission rates based on plant tissues (TC » 1.05 ppmw)
and animal ingest ion (TC * 3 ppmw) can also be calculated:
SER(Tissue) » [0.25/1.05] x (1 T/yr) - 0.24 T/yr and
SER(Animals) - [3/1.05] x (1 T/yr) =2.8 T/yr-
Such significant emission rates were calculated assuming a 30 m release height
as in Ref. 43, a 10-year source lifetime, and the air quality model presented
-------
45
in Appendix A. For pollutants acting along the direct pathways, Table 5.6
presents the significant emission rates. Table 5.7 presents such rates for
trace elements. When no modeling results or stack parameters such as are
required by simple air quality screening procedures are available, the
source's emission rates can be compared directly with those given in these
two tables. As already noted in the discussion of Table 5.3, other criteria
may be controlling particularly when background is considered. Still, the
significant emission rates presented in Table 5.6 can.be used to screen for
potential adverse impacts to plants, animals, and soils. Other criteria may
apply to different stages of the new source review process. When applying the
significant emission rates in Table 5.7, only the smallest value need be
considered for each pollutant. The values based on exceeding ten percent of
the average endogenous soil concentration should again only be used as suppor-
tive indicators; the primary decision is based upon exceeding the values based
on the criteria for soils, plant tissues, and animals.
The values tabulated in Table 5.7 assume a source lifetime of 10
years. Significant emission rates for other lifetimes for trace elements
acting through the deposition pathway are easily calculated:
/Significant^ .
/emission \ /Tabulated \
Irate for I = I significant I x (10/N). (5.9)
\ N year / Remission rate/
\lifetime /
Thus, for example, if the lifetime of the arsenic source in the above example
had been 40 years instead of 10 years, the associated significant emission
rate based on the plant tissue screening concentration would have been
changed from 0.24 T/yr to
(0.24) x (10/40) = 0.06 T/yr.
Solubility. As in Step 7, additional supportive indications can be
sought by considering the effects of solubility. A corrected significant
emission rate can be found from
/Significant \
/emission \ /Significant \ /Emission rate \
I rate corrected/ = (emission rate 1 x I increase factor) (5.10)
\for solubility/ \frora Table 5.7/ \from Table 5.4/
-------
Table 5.6 Significant Emission Rates for Direct Acting Pollutants8
Significant Eviction Rate (T/yr)
Screening
Criterion
AQRV
Screening
Concentration
NAAQS
PSD Increment I
II
III
Variance
NESHAP
S02
1 3
160 170
290
5.3
110
150
69
-
24
_
110
1.5
28
55
28
-
Pollutant and Averaging Ti
NO] 00
A 4 8 M A 1 8 W
171 840 950 3,200 950 - - 760,000
760 - 950 7.000 2,500
19 _ - - _ -
190
380
190
______
M-
H2> Bthylene Fluoride Beryl HUB Lead
4 3 24 240 M 3M
6,400 10.0 0.36 0.23 0.057 11
- - - - - 11
_ _ _ _ _ _
_
_ _ _ _ _ _
_
- - - - 0.057
Based on 30 o release height and no background.
"Nuoerals: hours
W: 1 week
M: I month
A: Annual
-------
47
Table 5.7 Significant Emission Rates for Trace Elements3
Significant
Emission
Rate (T/yr)
Criterion
Trace
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanad ium
Zinc
Soils
.40
.067
.33
1.1
-
5.3
53C
130d
.33
6 ic
67C
1.7
.33
-
Plant
Tissue
.24
.28
.037
6.7
23C
.21
1400C
37d
810C
-
17 Oc
13C
-
63C
Animals
2.8
-
.19
-
1.2
5.7
440C
24d
1000C
-
3000C
.67
130C
100C
10% of
Endogenous Soil
Concentration*9
.08
.13
.00080
1.3
.11
.27
2.7
.13
llc
-
.53
.0067
1.3
.67
aBased on a 30 m release height, no background, and a
source lifetime of 10 years. For a lifetime of N years,
divide the tabulated values by (N/10).
bFor use as a supportive indicator only; based on a 10%
increase over the average values in Table 3.5.
cExceeds the significant emission level for TSP of 10
T/yr established for PSD (Ref. 3).
^Exceeds the significant emission level for lead of 1
T/yr established for PSD (Ref. 3).
These emission rate increase factors are simply (100/S), the reciprocals of
the solubilities in percent.
Other Stacks. Even though the stack parameters may not be known
exactly, it may be known that the stack is hot or cold. Table 5.8 gives
stack parameters for four stacks which might be useful if they are closer
to the source's expected stack parameters than the 30 m release height assumed
-------
Table 5.8. Summary of Representative Stacks
Stack Parameters
Stack
30 m release
10 m cold
10 m hot
30 m cold
30 m hot
Height
(m)
30
10
10
30
30
Temperature
CK)
293
350
550
350
550
Flow
(m3/sec)
0
4
4
4
4
Emission Rate
Increase Factor
1.00
0.96
4.07
3.43
8.93
in Tables 5.6 and 5.7. The volume flow rate of 4 m3/sec is felt to be
conservative for major sources unless a large number of stacks are used. Also
given in the table are emission rate increase factors for each model stack. A
particular factor would be used to adjust the tabulated significant emission
rates in Tables 5.6 and 5.7 to correspond more closely to concentrations
expected from the proposed source:
/Significant \ /Significant \
I emission rate) [ emission rate! /Qnission rate \
I corrected I "(from Tables I x I increase factor] (5.11)
\for stack / \5.6 or 5.7 / \from Table 5.8/
-------
APPENDIX A
Estimates of Maximum
Ground Level Concentrations
-------
APPENDIX A
ESTIMATES OF MAXIMUM GROUND-LEVEL CONCENTRATIONS
This appendix develops the procedure used to estimate maximum ground-
level concentrations (mglc's) from a single source for averaging times ranging
from one hour to one year. The developments presented here follow the presen-
tation in Ref. 45 which can be consulted for additional details. The procedure
is useful for screening because the calculations can be done by hand or
implemented in a simple computer program. The procedure accounts for stack
parameters, plume rise, and meteorological conditions.
A.I SHORT-TERM ESTIMATES
The familiar Gaussian plume model is the basis for estimating short-
term ground level concentrations.49 According to this model the plume center-
line concentration is given by
\2
*<*>
-1/2
(A.I)
where:
x * Downwind distance from source (m),
X(x) » Ground-level centerline concentration at x
Q - Source emission rate (g/sec),
u " Wind speed (m/sec),
cjy(x) - Horizontal dispersion coefficient (m)
oz(x) - Vertical dispersion coefficient (m), and
H * Effective stack height (m) ha * Ah «
(Physical stack height) + (Plume rise).
To derive an analytic expression for the mglc, the following commonly
used representatives of the two dispersion coefficients are used:
oy(s) - ax" (A.2)
and
crz(x) ex
.d (A.3)
-------
52
The parameters a, b, c, and d depend upon atmospheric stability class
and, for oz, the downwind distance x. The following expressions for the esti-
mated mglc (Xm) and the corresponding downwind distance x^ may be derived.
AQ x 106 1
Xm X Til (A.4)
n
and
»
/ O\ 1 /OJ
^. (|i)l_ 1/2d (A.5)
where:
a - (b+d)/(2d) (A.6)
and
2a-l
A = £-£ (2a)a exp (-a) (A.7)
Values for a, b, c, d, and A are presented in Table A.I.
Both Xm and 3% depend on stability class and wind speed. To estimate
these quantities, the plume rise must be estimated because both depend upon
the effective stack height H. Plume rise can be estimated using the formulas
of Briggs .52,53
Se tt ing
F - sf^-^V (A.8)
where:
g = Acceleration of gravity (9.8 m/sec^).
T » Exit gas temperature (°K),
Ta = Ambient temperature (°K), and
V = Exist gas flow rate at temperature T (m^/sec),
it can be shown that
Ah(n/u) = C/u for neutral/unstable conditions (A.9)
and
Ah(s) = D/ul'3 for stable conditions. (A.10)
-------
Table A.I Dispersion Coefficient Parameters and Maximum Concentration Coefficient
Atmospheric
Stability
Corresponding
Pasquill-Gifford
Stability Class
a*
b*
c**,+
At
Moderately Unstable
B
0.351
0.867
0.139, 0.0494, 0.0494
0.947, 1.114, 1.114
0.335, 0.188, 0.188
Neutral
D
0.150
0.889
0.0856, 0.259, 0.737
0.865, 0.687, 0.564
0.396, 0.955, 3.85
Moderately Stable
E-F (intermediate)
0.0853
0.894
0.0682, 0.227, 1.437
0.814, 0.618, 0.401
0.468, 1.21, 34.7
^Estimated from Fig. 3.2, Ref. 49.
**Taken from Table 5, Ref. 51.
*The first numbers given for each stability are appropriate at distances between 100 and 500 m, the
second numbers at distances between 500 and 5000 m, and the third numbers at distances greater than
5000 m.
-------
54
Assuming an ambient temperature of 293*K (20*C) and an ambient potential
temperature lapse rate (36/3z) of 0.5"K/100 m, representative of moderately
stable conditions,
C = 21.4F0-75 m2/sec for F<55 m4/sec3, (A.12)
C = 38.7F0-6 m2/sec for F>55 mVsec3, and (A.13)
D = 47.2F1/3 m*/3 sec'1^. (A.14)
A wind speed corresponding to the mglc can now be found. For neutral
and unstable conditions,
, . , b C /» i e\
Uworstln/uJ * -T r, VA.uy
d hs
with a corresponding mglc
AQ x 1Q6 . __ 1 . (b/d)b/d
Ch
Xworst(n/u) = ^T-^ ' ^r ' ' (A'16)
For stable conditions
, . AQ x 1Q6 . q(b-2d)/3d
v _(s) « ^ ryr . .,. (A.17)
*worst IT ,1/3. _Nl+b/d
(u h + D;
S
Equation A.17 has no maximum unless b/d is greater than 2. Operationally,
this difficulty is solved by setting u = 2 m/sec for the stable case in which
case Eqs. A.10 and A.17 become
Ah(s) - 0.794 D ' (A.18)
and
, N AQ x 106 . 2/3d
w^'-h a.26VD)^/d- <*»>
Equations A.15, A.16, and A.19 are the basic equations used to cal-
culate the short-term mglc. The calculations need to be done separately for
unstable, neutral, and stable conditions and the maximum value selected for
the mglc. In addition, for each stability class, the calculations need to be
done for three ranges of downwind distance because of the dependence of c, d,
and A on x (see Table A.I). The value chosen for each stability class is the
-------
maximum self-consistent value, that is, the maximum of the values for which
the calculated x^ falls within the range of downwind distances over which the
particular c, d, and A values apply.
In implementing this procedure, high worst-case wind speeds are
occasionally found which are unlikely to persist for periods of time on the
order of hours to one day. On the other hand, low worst-case wind speeds are
found which are small enough to render the Gaussian plume formulation inap-
plicable. To avoid both extremes and still retain a conservative estimate of
the mglc, limits are placed on the worst-case wind speed for neutral/unstable
conditions such that 0.8 jC u,, £ 30 m/sec.
Estimates made in this way are appropriate for averaging times of one
hour. For averaging times out to about 24 hours, the one-hour estimates can
be multiplied by an appropriate conversion factor from Table A.2. These
factors represent a power law dependence of concentration on averaging time
with an exponent of -0.17:
X(t) - X(l)t-0.17. (A.20)
For averaging times between 24 hours and about one month, a recognized
simple procedure for estimating the concentration from a. single source at one
averaging time given the concentration at another averaging time appears to
be lacking. Larsen54 has developed a method which can be used in multi-source
applications. For averaging times less than one month, he finds that for a
year's data
r(t) - X-.-U hr)t4 (A.21)
where q depends upon the geometric standard deviation of the concentration
values. The form of Eq. A.21 with q - -0.17 is exactly the same as that of
Eq. A.20. On the basis of this equivalence of mathematical form, the use of
Eq. A.20 was extended beyond 24 hours to estimate conversion factors for 4 and
10 days as shown in Table A.2.
A.2 LONG-TERM ESTIMATES
Expected monthly and annual mglc's from a single source are based
upon the "sector-averaged" form of Eq. A.l:49>55
-------
56
Table A.2 Averaging Time Conversion Factors
Averaging
Time (hrs)
1
3
4
8
24
96 (4 da)
240 (10 da)
aBased on Ref. 49.
bSee discussion in text.
x(l) -/2N1/2 fQ x 106 /
v/ u]
where:
n » the number of sectors into which the entire 360"
range of wind directions is divided and
f » the fraction of the time during which the wind
direction lies in the sector of interest.
Using the same parameterization as above (Eq. A.3),
=, BfQ x 1Q6
rt_- « Q
Tq ^ n
uh
where:
8 - (l-i-d)/2d
and
B - =
_
2ir
c28'1 (2B)6 exp (-6).
(A. 22)
(A.23)
(A. 24)
(A.25)
To estimate Che expected long-term mglc, values of c and d for neutral atmo-
spheric stability and distances between 500 and 5000 m are used and the plume
rise is calculated using Eq. A.9. With these assumptions,
-------
B - 0.256 and
B - 1.23.
Examination of annual wind roses in Ref. 56 indicated that the maximum ex-
pected wind direction in a single 22.5* sector (n-16) is about 27% (f-0.27).
For monthly wind roses, this maximum persistence is about 45Z (f"0.45).
The wind speed u used for both the annual and monthly calculations is u 4.4
m/sec, corresponding to the nationwide annual mean wind speed based upon the
speeds listed with the annual wind roses. For these conditions Eq. A.23
gives
, v 0.0157 Q x 1Q6 , . . , ,.
v (yr) . ... for annual mglc s CA.
H
and
v (mo) » "-"*»* Q » 1()6 for monthly mglc's. (A.27)
^DL Z 4O
-------
58
-------
APPENDIX B
Pollutant Sensitivities of Plant Species
-------
60
-------
Table B.I. Sulfur Dioxide Sensitivity of Crop Species3
Sensitivity
Sensitive
Intermediate
Resistant
Alfalfa
Apple
Barley
Bean, field
, lima
Beet, sugar
, table
Blackberry
Blueberry
Broccoli
Brussels Sprouts
Cabbage
Carrot
Celery
Chard, Swiss
Cherry, sour
, sweet
Clover
Clover, sweet
Cucumber
Currant, red
Eggplant
Endive
Gooseberry
Grapes
Kale
Leek
Lettuce
Oats
Okra
Onion
Parsley
Parsnip
Pea
Peach
Pear
Pepper
Plum, prune
Potato, Irish
Potato, sweet
Pumpkin
Radish
Raspberry
Rye
Safflower
Soybean
Spinach
Squash
Tobacco
Turnip
Wheat
Cotton
Corn
Sorghum
Cantaloupe
Citrus spp.
Compiled from data in Ref. 16.
-------
62
Table B.2. Sulfur Dioxide Sensitivity of
Natural Vegetation3
Common Name
Scientific Name
Sensitive
Alder, mountain
Aspen, large-toothed
, trembling
Ash, red (green)
, white
Birch, gray
, western paper
, white (paper)
, yellow
Blueberry, lowbush
Cherry, bitter
Fir, subalpine
Grasses-bentgrass
-bluegrass
-desert grass
-Ky. bluegrass
-orchard grass
-red fescue
Hazel, beaked
, California
Hemlock, mountain
Larch, western
Maple, Manitoba
, Rocky Mt.
Mulberry, Texas
Pine, eastern white
, jack
, red
, Virginia
Rockspirea, creambush
Serviceberry. low
, Saskatoon
, Utah
Sumac, staghorn
Tulip tree
Willow, black
Alnua tenuifolia
Populua grandidentata
Populus tremit aides
Fraxinua pennsylvanica
Fraxinua amerioana
Betula populifolia
Betula papyrifera commitata
Betula papyrifera
Betula alleghenienaia
Vacoinium anguatifolium
Prunua emarginata
Abies laaiooarpa
Agrostis paluatria
Poo. ormua
Orysopsia hymenoidea
Poo, pratenaia
Doctylia glomerata
Featuoa rubra
Corylue aornuta
Corylua aornuta oalifornioa
Tauga mertenaia
Larix oooidentalia
Acer negundo interiua
Acer globrwn
Morua miarophylla
Pinue strobile
Pinue bankeiana
Pinua reainoaa
Pinua virginiona
Holodiscus discolor
Amelanohier stolonifera
Amelanohier alnifolia
Amelanohier utaheneia
Shua typhina
Liriodendron tulipifera
Salix nigra
-------
Table B.2. (Cont'd)
Common Name
Scientific Name
Intermediate
Basswood
Birch, water
Boxelder
Chokecherry
Cottonwood, black
, eastern
, narrowleaf
Dogwood, red osier
Elm, American
Fir, bias an
, Douglas
, grand
Grape, wild
Hemlock, western
Mahogany, mountain
Maple, Douglas
, red
Mountain-ash, western
Oak, white
Pine, lodgepole
, ponderosa
, shortleaf
, western white
Poplar, balsam
Sagebrush, big
Snowberry, mountain
, Columbia
Sprue e, EngeImann
, white
Witch hazel
Tilia amerioana
Betula occidental-is
Acer negundo
Prunua virginiona
Populua triohooarpa
Populua delta-idea
Populua onguatifolia
Cornus stolonifera
Ulmue americana
Abies baleamea
Paeudoteuga menziesii
Ab-iea grondis
Vitia rn.po.ria
Teuga heterophylla
CercocarpUB montanua
Acer gldbrum douglasii
Acer rubrum
Sorbue acopulina
Quercua alba
Pinua cantorta
PinuB ponderosa
Pinua echinota
Pinua monticola
Populua balaomifera
Artemisia tridentata
Symphoricarpoe oreophilus
Symphoriaarpoe rivularie
Pieea engelmamii
Picea, glauca
Hamamelis virginiana
Resistant
Black gum
Buck-brush
Buffalo-berry
Ceanothus, reds tern
Cedar, western red
, white(arborvitae)
Dogwood, flowering
Fir, silver
, white
Hawthorn, black
Nyssa sylvatica
Ceanothus velutinue
Shepherdia canadensis
CeanothuB sanguineua
Thuja plicata
Thuja occidentalis
CornuB florida
Abies oanabiliB
Abies consolor
Crataegus douglasii
-------
64
Table B.2. (Cont'd)
Common Name
Scientific Name
Resistant (cont'd)
Grape, Oregon
Grasses-blue grama
-needle grass
-western wheatgrass
Juniper, common
, Rocky Mt.
, Utah
, Western
Kinnikinnick
Locust, black
Mahogany, curl-leaf mt.
Maple, mountain
, silver
, sugar
Oak, gambel
, live
, northern red
, pin
Pine, limber
, pinyon
Poplar, Carolina
Sourwood
Spruce, blue
Squawbush
Sumac, smooth
Sycamore, American
Willow, shrubby
Yew, Pacific
Odostemon aquifolium
Bouteloua gracilis
Stipa sonata
Agrapyron smithii
Juniperus communis
Juniperus saopulorum
JuniperuB osteosperma
Juniperus occidental-is
Arctostaphyloe uva-ursi
Robinia pseudoacacia
Cercoaarpus ledifolius
Acer apicatian
Acer saccharinum
Acer eaccharwn
Quercus gambelii,
Queraus Virginians,
Quercus rubra
Queraus palustris
Pinus flexilis
Pinus edulis
PopuluB canadeneis
Oxydendron arboreum
Picea pungens
Shus trilobata
Ehus glabra
Platanus ocoidentalis
Salix trietis
Taxus brevifolia
aCompiled from lists in Refs. 9 and 16.
-------
Table B.3. Ozone Sensitivity of Crop Species3
Sensitivity
Sensitive
Alfalfab
bean, pinto
, White
Broccoli
Clove rb
Corn, sweet
Oatsb
Radishc
Saffloverc
Soybean5
Spinachb
Tobacco
Tomatob
Intermediate
Bean, bush
, lima
Beet, table
Cabbage
Chard, swissd
Clover, white sweet
Corn, field
Cucumber d
Potato, Irish
Sorghum
Squash, summer
Resistant
Cotton
Lettuce
Onion
Compiled from data in Ref. 18.
bSome cultivars intermediate or resistant.
cSome cultivars intermediate.
dSome cultivars resistant.
-------
66
Table B.4. Ozone Sensitivity of Natural Vegetation3
Common Name Scientific Name
Sensitive
Aspen, trembling Populus tremuloides
Ash, red(green) Fraxinus pennsylvaniaa
, white Fraxinus ameriaana
Cottonwood, black Populue triohocarpa
Grasses-bent grass Agrostis palustris
-blue grass Poa armua
-brome grass Bromus teetonun
Oak, gambel Queroue gambelii
, white Queraus alba
Pine Coulter Pinus aoulteri
eastern white Pinus etrobus
jack Pinus banksiana
Jeffrey Pinus jeffreyi
loblolly Pinus taeda
Monterey Pinus radiata
ponderosa Pinus ponderosa
Virginia Pinus virginiana
Serviceberry, Saskatoon Amelanchier alnifolia
Sycamore, American Platanus oaoidentalis
Tulip tree ' Liriodendron tulipifera
Intermediate
Boxelder Acer negundo
Cedar, incense Libooedrus deourrens
Grasses-Ky. bluegrass Poa pratensis
-perennial rye Lolium perenne
-red fescue Festuoa rubsa
Oak, black Querous velutina
. pin Quercus palustris
, scarlet Onerous coecinea
Pine lodgepole Pinus aontorta
pitch Pinus rigida
shortleaf Pinus echinata
slash Pinus elliottii
sugar Pinus Icanbertiana
Torrey Pinus torreyana
Cerais aanadensis
Sweetgum Liquidambar styraaiflua
-------
Table B.4. (Cont'd)
Common Name
Scientific Name
Resistant
Basswood
Birch, white (papet)
Black gum
Cedar, white (arboxvitae)
Dogwood, f1owe r ing
Fir, balsalm
, Douglas
, white
Grasses-orchard grass
Hemlock
Juniper, western
Locust, black
Maple, red
, sugar
Oak, mossy-cup
, northern red
, shingle
Pine, digger,
, red
Redwood
Sequoia
Spruce, black
, blue
, white
Walnut, black
Tilia americana
Betula papyrifera
Nyssa sylvatica
Thuja occidentalis
Cornus florida
Abies balsamea
Pseudotsuga mensiesii
Abies concolor
Dactylis glomerata
Tsuga eanadensis
Juniperus occidental-is
Robinia pseudoaoaeia
Acer rub-man
Acer saccharum
Quercus macrocarpa
Quercus rubra
Quercus imbricaria
Pinus sabiniana
Pinus resinosa
Sequoia sempervirens
Sequoiadendron giganteum
Picea mariana
Picea pungens
Picea glaucaa
Juglans nigra
aCompiled from lists in Refs. 18 and 57.
-------
68
Table B.5. Nitrogen Dioxide Sensitivity of
Crop Species3
Sensitivity
Sens it ive
Alfalfa
Barley
Bean, pinto
Broccoli
Carrot
Clover, crimson
, red
Leek
Lettuce
Luc erne
Mustard, white
Oats
Parsley
Peas
Radish
Rhubarb
Tobacco''
Intermediate
Bean, bush
Celery
Citrus spp.
Corn, sweet
Cotton
Endive
Potato, Irish
Rye
Strawberry, pine
Tomato
Wheat
Resistant
Asparagus
Cabbage,
>
red
white
Corn, field
Cucumber
Kale
Kohlrabi
Onion
Sorghum
acompiled from lists in Refs. 19, 20, and 58.
bSome cultivars intermediate or resistant.
-------
Table B.6. Nitrogen Dioxide Sensitivity of
Natural Vegetation3
Common Name Scientific Name
Sensitive
Grasses-Viper's grass Seorzonera hiepaniaa
Intermediate
Fir, common silver Abies pectinate
, white Abies alba
Grasses-bluegrass Poa arauia
Spruce, blue Pieea pungene
, white Picea glauea
Resistant
Grasses-Ky. bluegrass Poa prateneie
Compiled from tables in Refs. 20 and 58.
-------
70
-------
APPENDIX C
Trace Element Air Quality Data
-------
72
-------
TABLE C-1. AIR QUALITY DATA FOR ARSENIC
HINIHUH IUS/H3I
STATE
HO
TX
COUNTY
BUCHANAN
CLAY
JEFFERSON
BEE
BEXAR
BOUIE
BRA20RIA
BRAZOS
BR0184
CALIIOUN
CAIIEROtl
CHAMBERS
DALLAS
DEMTOH
ECTOR
ELLIS
EL PASO
6ALVESTON
GRAY
GRAYSON
HALE
HARRIS
HAYS
HIDALGO
HOUARD
JEFF DAVIS
JEFFERSON
LUDDOCK
HCLEIUIAM
HCMULLEH
NATAGORDA
MAVERICK
NIOLAIID
HOJIT601IERY
HOORE
IIACOGDOCHES
HUECES
ORANGE
POTTER
SAN PATRICIO
SCURRY
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
DBS
0100
0100
0100
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
ARITH
HE AM
6EO
MEAN
MAXIMUM IU6/M3I
DBS
ARITH
MEAN
GEO
MEAN
o.oioo
0.0100
0.0200
0.0200
0.0200A
0.0300A
0.0200
0.0300A
0.0300A 0.0200
0.0300A 0.1100
0.0300 0.0500
0.0300 A 0.0700
0.0200A
0.0300A
0.0300
0.0300A
0.0300A
0.0300A
0.0300
0.0300A
fl.OSOfl
0.0200
0.0200
...
0.0200
...
0.0200A
...
0.0200
0.0200A
...
...
...
0.0200
...
0.0200
0.0200A
...
0.0200
0.0300 0.3000
...
0.0300
...
0.0300 A
...
0.0200
0.0300A
...
...
0.0300
...
0.0300
0.0300A
...
0.0300
.0200
.0600
.0500
.0600
.1000
.6600
.4000
.0200
.0600
.0200
.1300
.0700
.1000
.0200
.0200
.0500
0.0300
--_
0.0200
_._
0.0200A
...
0.0700
0.0200A
-..
...
0.0300
--_
0.0300
0.0200A
0.0200
0.0700
0.0300
0.0300
0.0300A
0.0500
0.0300A
...
---
0.0300
0.0300
0.0300 A
0.0300
0.0200
0.0200
...
0.0200A
0.0200A
I
1.0200
0.0300A 0.0200
0.0300A 0.0300
0.0200
0.0200A
0.0200A
...
0.0300A
0.0300A
0.0200
0.0200
0.0200
0.0200A
0.0300 0.2000
0.0300A 0.0200
0.0300
0.0200A
0.0200
0.0300
0.0300A
0.0200
0.0200
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-1. AIR QUALITY DATA FOR ARSENIC
MINIMUM (UG/M3)
STATE COUNTY
SHITH
T ARRANT
TAYLOR
TITUS
TOM GREEN
TRAVIS
VAL VERDE
VICTORIA
WALKER
MEBB
IUCMITA
WISE
OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
ARITH
MEAN
0.0300A
...
0.0300A
0.0200A
0.0200
...
...
GEO
MEAN
0.0300 A
_
0.0300 A
0.0300A
...
0.0300
...
...
...
...
...
MAXIMUM (UG/M3)
OBS
0.0700
0.1200
O.OSOO
0.0500
0.0500
0.0700
0.0200
0.0500
0.0200
0.0200
0.0200
0.0600
ARITH
MEAN
0.0300A
0.0300A
0.0200A
0.0300
.
...
GEO
MEAN
0.0300A
0.0300A
0.0300A
0.0300
...
-------
TABLE C-2. AIR QUALITY DATA FOR CADMIUM
MINIMUM (U6/M3)
STATE
A2
CO
ID
IN
m
COUNTY
APACHE
COCOIIINO
HARICOPA
HOIIAVE
HAVAJO
PIMA
LA PLATA
HONTEZUHA
SHOSHONE
ALLEN
BARTHOLOHEH
CLARK
DUCOIS
ELKMART
GRANT
HOWARD
JASPER
JEFFERSON
KMOX
LAKE
LA PORTE
MARION
HOKUOE
ST. JOSEPH
STEUDEN
TIPPECANOE
VAHDERBURGH
VIGO
HAYNE
BELTRAtll
BIG STOIIE
BLUE EARTH
CARLTON
CLAY
CROH UIN6
DAKOTA
600DHUE
HENNEPIN
OBS
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0100
0.0009
0.0002
0.0010
0.0009
0.0006
0.0010
0.0012
0.0001
0.0003
0.0019
0.0002
0.0012
0.0012
0.0009
0.0004
0.0006
0.0010
0.0005
0.002?
0.0005
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
ARITH
HE AN
0.0001
0.0001
0.0003
0.0001
0.0002A
0.0006
0.0001A
0.0001 A
0.0095
...
...
...
...
___
...
...
.._
...
...
...
...
-
...
...
-
...
...
...
...
...
___
CEO
MEAN
0.0001
0.0001
0.0001
0.0001
0.0001A
0.0001
0.0001A
0.0001 A
0.0054
...
...
...
.__
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
-_.
...
...
...
...
HAXIIKJM IU6/N3)
OBS
0.0100
0.0100
0.0700
0.0001
0.0100
3.0000
0.0100
0.0001
3.6800
0.0360
0.0016
0.0083
0.0024
O.OC42
0.0095
0.0143
0.0007
0.0011
0.0162
0.0031
0.0207
0.0217
0.0050
0.0019
0.0048
0.0012
0.0056
0.0075
0.0057
0.0020
0.0010
0.0020
0.0020
0.0020
0.0020
0.0090
0.0060
0.0090
ARITH
MEAN
0.0002
0.0003
0.0040
0.0001
0.0002A
0.0037
0.0002A
O.OG01A
0.4592
...
...
...
---
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
6EO
MEAN
0.0001
0.0001
0.0004
0.0001
0.0001A
0.0002
0.0001 A
0.0001 A
1.5670
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-2. AIR QUALITY DATA FOR CADMIUM
STATE
HO
MT
NH
COUNTY
ITASCA
KAHDIVOHI
KOOCIIICHING
LYON
MCLEOD
MILLE LACS
MOIIER
NOBLES
OLMSTED
OTTERTAIL
POLK
ST. LOUIS
SCOTT
STEARNS
WASHINGTON
HIIIOHA
ADAIR
AUDRAIN
BOONE
BUCHANAN
BUTLER
CALLAItAY
CAHOEN
CAPE GIRARDEAU
CLAY
COLE
JASPER
> JEFFERSON
LIVINGSTON
MARION
HEN MADRID
NODAIIAY
PETTIS
PIIELPS
PLATTE
ST. CHARLES
STE. GENEVIEVE
SCOTT
VERNON
DEER LODGE
RIO ARRIBA
DBS
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0016
0.0007
0.0016
0.0003
0.0012
0.0003
0.0020
0.0016
0.0012
0.0024
0.0027
0.0010
0.0012
0.0003
0.0010
o.oooa
0.0011
0.0010
o.ooso
0.0031
0.0010
0.0015
0.0100
0.0001
MINIMUM IU6/M3)
ARITH GEO
KEAII MEAN
. ...
...
... ...
... ...
- ...
... ...
... ...
... _
...
...
... ...
... ___
... ...
- ...
... ...
_ _
... _
...
...
. ...
... ...
... ...
...
--- ...
- ...
... ...
...
...
... ...
... ...
... ...
... ...
- ...
...
... ...
... ...
...
0.0001 0.0001
MAXIMUM (UG/H3I
CDS
0.0010
0.0020
0.0110
0.0040
0.0010
0.0010
0.0020
0.0020
0.0450
0.0020
0.0050
0.0030
O.OG20
0.01SO
0.0040
0.0020
0.0042
O.OOS3
0.0140
0.0440
0.0062
0.0055
0.0046
0.0050
0.0150
0.0066
0.0079
1.4350
0.0052
0.0050
0.0045
0.0052
0.0125
0.0053
0.0109
O.OOSO
0.0030
0.0074
0.0041
0.0500
0.0100
ARITH
HE AN
.
...
...
...
...
...
...
...
0.0002
GEO
MEAN
...
...
...
...
...
...
...
...
-__
...
...
...
...
...
...
.
.
.
...
...
...
...
0.0001
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-2. AIR QUALITY DATA FOR CADMIUM
STATE
OK
SC
TN
TX
COUNTY
SAN JUAN
OKLAHOMA
CHARLESTON
ANDERSON
BEDFORD
BLOUIT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
6REEME
HAMQLEN
HENRY
HUMPHREYS
LINCOLN
MCIIIKII
MADISON
MARION
HAU8Y
MONTGOMERY
OBION
POLK
> PUTNAM
ROAHE
ROBERTSON
RUTHERFORD
SULLIVAN
SUMMER
HARREH
WASHINGTON
WILLIAMSON
WILSON
BEE
BEXAR
BOS1IE
BRAZORIE
OBS
0.0001
0.0001
0.0020
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
.0010
.0010
.0010
.0010
.0040
.0010
.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0300
0.0300
0.0300
0.0300
MINIMUM IUG/M3)
ARITH
MEAN
0.0002 0
0.0008 0
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
_
...
---
...
...
...
...
...
...
...
0.0300A 0
0.0300A 0
0.0300 0
MAXIMUM IUS/H3)
6EO
MEAN
.0001
.0006
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
-
...
...
.
...
...
...
.0300A
.0300A
.0300
OBS
0.2000
5.0000
0.0020
0.0030
0.0010
0.0040
0.0010
0.0040
0.0010
0.0050
0.0020
0.0030
0.0070
0.0010
0.0090
0.0030
0.0040
0.0010
0.0040
0.0030
0.0030
0.0030
0.0100
0.0030
0.0370
0.0010
0.0090
0.0050
0.0010
O.OOjO
0.0020
0.0010
0.0010
0.0010-
0.0010
0.0300
0.0300
0.0300
0.0300
ARITH
MEAN
0.0002
0.2739
...
...
...
...
...
...
...
...
...
...
...
...
...
...
.
...
...
...
...
...
...
...
...
...
...
...
...
...
«M
0.0300A
0.0300A
0.0300
6EO
MEAN
0.0001
0.0012
...
...
...
...
...
...
...
...
...
.
...
...
_-_
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
0.0300A
0.0300A
0.0300
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-2. AIR QUALITY DATA FOR CADHIUft
MINIMUM IU6/H3I
STATE COUITY
BRAZOS
BROHN
CALHOUH
CAIIEROII
CHAIIBERS
DALLAS
OENTOH
ECTOS
ELLIS
EL PASO
6ALVESTON
GRAY
6RAYSON
HALE
HARRIS
HAYS
HIDALGO
IIOIIARD
JEFF DAVIS
JEFFERSON
LU6BOCK
MCLEMIAH
HCIIULLEN
MATAGOROA
HAVERICK
MIDLAND
MONTGOMERY
MOORE
. NACOGDOCHES
KUEHCES
ORAM6E
POTTER
SAN PATRICIO
SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TOM GREEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
DBS
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0001
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
ARITII
MEAN
0.0300A
.._
_..
0.0300
._.
0.0300
...
0.0300A
0.0300
0.0300A
-
0.0300
0.0300
0.0300A
0.0300A
.._
0.0300A
0.0300A
...
...
0.0300
0.0300A
...
0.0300A
__.
0.0300A
0.0300A
0.0300
...
GEO
MEAN
0.0300A
...
0.0300
...
0.0300
...
0.0300A
0.0300
0.0300A
...
...
0.0300
...
0.0300
0.0300 A
...
0.0300A
...
...
0.0300A
0.0300A
.._
___
0.0300
0.0300A
...
0.0300 A
...
0.0300A
0.0300A
___
0.0300
MAXIMUM (UG/lll)
OBS
0.0300
0.0300
0.0300
0.0300
0.0300
0.1000
0.0300
0.0300
0.0300
0.1000
0.1000
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.2000
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
ARITH
MEAN
0.0300A
0.0300
...
0.0300
0.0300A
0.0300
0.0300A
...
0.0300
0.0300
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300A
...
...
...
0.0300A
0.0300A
0.0300 A
0.0300
GEO
MEAN
0.0300A
0.0300
...
0.0300
0.0300A
0.0300
0.0300A
0.0300
0.0300
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300A
.
0.0300A
0.0300A
0.0300 A
0.0300
-_-
00
A INDICATES ONLY ONE STATION REPORTIM6
-------
TAOLE C-2. AIR QUALITY DATA FOR CADMIUM
MINIMUM IUG/M3) MAXIMUM (UG/M3)
STATE
UT
COUNTY
MEBB
WICHITA
WISE
EMERY
6ARFIELO
KAHE
SAN JUAN
WASHINGTON
DBS
a. 0300
0.0300
0.0300
0.0001
0.0001
0.0001
0.0001
0.0001
ARITII
MEAN
...
_._
__
0.0001
0.0002A
0.0001
0.0001
6EO
MEAN
...
...
...
...
0.0001
0.0001A
0.0001
0.0001
003
0.0300
0.0300
0.0300
0.0001
0.0200
0.0100
0.0100
0.0100
ARITH
MEAN
...
...
...
...
0.0003
0.0002A
0.0020
0.0002
6EO
MEAN
...
...
...
0.0001
0.0001A
0.0001
0.0001
VO
-------
TABLE C-3. AIR QUALITY DATA FOR CHROMIUM
MINIMUM (U6/H3»
STATE
AZ
CO
HO
IN
NM
COUNTY
APACHE
COCOMINO
IIARICOPA
MOIIAVE
NAVAJO
LA PLATA
KOMTEZUHA
ADAIR
AUDRAIN
BOOIIE
BUCHANAN
BUTLER
CALLAUAY
CAMDEH
CAPE 6IRARDEAU
CLAY
COLE
JASPER
JEFFERSON
LIVINGSTON
MARION
NEII MADRID
MODAIIAY
PETTIS
PHELPS
PLATTE
ST. CHARLES
STE. GENEVIEVE
SCOTT
VERHOII
ALLEN
BARTHOLOMEW
ELKHART
LAKE
MOttROE
VANOERBURGH
RIO ARRIBA
SAN JUAN
OB3
0.0010
0.0010
0.0010
o.ooto
0.0010
0.0010
0.0010
0.0060
0.0060
0.0040
0.0060
0.0050
0.0050
0.0040
0.0060
0.0070
0.0060
0.0070
0.0030
0.0040
0.0060
0.0050
0.0060
0.0070
0.0050
0.0050
0.0050
0.0090
0.0050
0.0070
0.0050
0.0010
0.0020
0.0060
0.0050
0.0040
0.0010
0.0010
AIUTII
MEAN
0.0020
0.0020
0.0010
0.0030A
0.0020 A
0.0030A
...
...
...
...
...
...
-_.
...
_
...
...
...
...
...
...
...
...
...
0.0020 A
0.0020
GEO
MEAN
0.0010
0.0010
0.0010
0.0010A
0.0010A
0.0010A
...
...
--_
...
...
_-_
...
...
...
...
...
...
...
...
...
...
...
_..
.__
...
...
...
...
...
...
0.0010A
0.0010
MAXIMUM (UG/M3)
DBS
0.0500
0.0700
0.0010
0.0300
0.0500
0.0500
0.0400
0.09SO
0.0920
0.0170
0.0860
0.0130
0.0670
0.0310
0.0180
0.0600
0.0640
0.0150
0.0640
0.0£80
0.0670
0.2370
0.0610
0.0110
0.0840
0.0620
0.0080
0.0090
0.0760
0.0130
0.0270
0.0140
0.0090
0.0160
0.0110
0.0100
0.0500
0.0500
ARITH
MEAN
0.0030
0.0050
0.0040
0.0030A
0.00'iOA
0.0030A
...
...
_
...
«...
-«
...
....
- .
...
0.0030A
0.0030
GEO
MEAN
0.0010
0.0020
0.0020
0.0010A
0.0020A
0.0010A
-
-_..
..
...
...
--.
-.-
...
..
...
_._
...
-_-
-
...
...
...
...
___
.>_<
0.0010A
0.0010
oo
o
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-3. AIR QUALITY DATA FOR CHROMIUM
MINIMUM (U6/M3)
STATE
SC
TH
TX
COUNTY
CHARLESTON
ANDERSON
BEDFORD
BLOUHT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUCERLAND
DYER
GIBSON
GREENE
HAHBLEN
HENRY
HUMPHREYS
LINCOLN
NCHINN
MADISON
MARION
HAURY
MONTGOMERY
OBION
POLK
PUTNAM
ROANE
ROBERTSON
- RUTHERFORD
SULLIVAN
SUKIIER
MARREH
MASHItlGTOH
WILLIAMSON
HILSOH
BEE
BEXAR
BOMIE
BRAZORIA
BRAZOS
BROtiH
CALHOUH
ARITII
ODS MEAN
0.1530
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0050
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
6EO
MEAN
...
...
...
...
...
...
-
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
.
...
...
...
...
...
...
...
MAXIMUM (US/113)
ODS
0.1530
99.0000
.0050
.0050
.0050
.0050
.0010
.0050
0.0090
0.0050
0.0050
0.0010
0.0050
0.0050
0.0050
0.0010
0.0050
0.0050
0.0050
0.0050
0.0090
0.0050
0.0050
0.0020
0.0050
0.0050
0.0050
0.0050
0.0050
0.0050
0.0010
0.0010
0.0050
0.0200
0.0900
0.0900
0.0300
0.0200
0.0200
0.0200
ARITH
MEAN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
....
...
...
...
...
...
...
6EO
HEAH
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
_
_
...
...
...
...
...
...
...
...
...
...
...
...
...
.
. .
...
03
A irUICATES DULY 0>IE STATION REPORTINS
-------
TABLE C-3. AIR QUALITY DATA FOR CHROMIUM
STATE COUNTY
CAMERON
CHAMBERS
DALLAS
DENTON
ECTOR
ELLIS
EL PASO
GALVESTON
GRAY
6RAYSQM
HALE
HARRIS
HAYS
HIDALGO
HOWARD
JEFF DAVIS
JEFFERSON
LUCBOCK
MCLEKNAN
KCHULLEN
HATAGORDA
MAVERICK
MIOLAIID
MONTGOMERY
MOORE
NAGOOOCHES
NUEIICES
ORANGE
POTTER
SAN PATRICIO
SCURRY
SMITH
T ARRANT
TAYLOR
TAYLOR
TON GREEN
TRAVIS
VAL VERDE
VICTORIA
WALKER
tIEDQ
WICHITA
WISE
MINIMUM (U3/M3I
ARITII GEO
DBS MEAN MEAN
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
023
0.2400
0.0200
O.CBOO
0.0200
0.0500
0.0200
0.1'iOO
0.1000
0.0200
0.0200
0.0200
0.5600
0.0200
0.0200
0.0500
0.0500
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0230
0.0200
0.3100
0.0200
o.oaoo
0.0700
0.0200
0.0700
0.0700
0.0700
0.0200
0.0200
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
MAXIMUM (UG/M3)
ARITH GEO
MEAM MEAN
... ...
... ...
...
.__ -__
...
...
...
.__
...
...
...
._. ...
... ...
...
-._
...
... ...
...
___
...
...
...
...
.
. ._.
... .
. __.
.
.
.__
. .._
CD
ro
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-3. AIR QUALITY DATA FOR CHROMIUM
MINIHUH (UO/H3I HAXII1UH IU6/H3I
ARITII 6EO ARITH 6EO
STATE COUNTY DBS HEAII HEAH DBS MEAN HEAH
UT EMERY 0.0010 0.0300
6ARFIELD 0.0016 0.0020 1.0010 0.0500 0.0040 0.0010
KANE 0.0010 0.0030A 0.0010A 0.0300 0.0030A 0.0010A
SAM JUAN 0.0010 0.0010 0.0010 0.0400 0.0040 6.0020
WASHINGTON 0.0010 0.0020 0.0010 O.O'iOO 0.0030 0.0010
00
-------
TABLE C-4. AIR QUALITY DATA FOR FLUORIDE ION
MINIMUM (UG/M3)
STATE COUNTY
AZ HARICOPA
NO BARNES
BILLINGS
BOI1IIAN
BURLEIGH
CASS
DUNN
GRAND FORKS
GRANT
HETTINGER
HCKEHZIE
MCLEAN
MERCER
MORTON
MOUNTRAIL
OLIVER
RAMSEY
RICIILANO
SHERIDAN
STARK
STUTSHAM
HARD
UILLIAHS
DBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
ARITH
MEAN
0.0300
0.0200A
0.0200A
0.0200A
0.0300A
0.0200
0.0200
0.0200
0.0300A
0.0200
0.0200A
0.0200A
0.0200
0.0200
0.0200
0.0200
0.0200A
0.0200
0.0200
0.0200
0.0200
0.0200 A
0.0200
GEO
MEAN
0.0300
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300
0.0300
0.0300A
0.0300
0.0300 A
0.0300A
0.0300
0.0300
0.0300
0.0300
0.0300A
0.0300
0.0300
0.0300
0.0300
0.0300 A
0.0300
MAXIMUM IUG/M3I
DBS
0.3700
0.0500
O.OSOO
0.0200
0.3500
0.0300
0.0200
0.1900
0.1200
0.0200
0.0200
0.1600
0.3000
0.0600
0.0200
0.1100
0.0200
0.0200
0.0200
0.0200
0.1400
0.0200
0.0200
ARITH
MEAN
0.0500
0.0200A
0.0300A
0.0200A
0.0400A
0.0300
0.0200
0.0300
0.0300A
0.0200
0.0200A
0.0200A
0.0600
0.0300
0.0200
0.0300
0.0200A
0.0200
0.0200
0.0200
0.0300
0.0200 A
0.0200
GEO
MEAN
0.0400
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300
0.0300
0.0300 A
0.0300
0.0300A
0.0300A
0.0400
0.0300
0.0300
0.0300
0.0300 A
0.0300
0.0300
0.0300
0.0300
0.0300 A
0.0300
co
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
MINIMUM (UG/M3)
STATE
AL
AZ
AR
CA
COUNTY
OBS
ETOHAII 0.1700
JEFFERSON
MADISON
MOBILE
MONTGOMERY
APACHE
COCHISE
COCOHUiO
GILA
GRAHAM
GREEHLEE
MARICOPA
HOIIAVE
NAVAJO
PIMA
PINAL
YAVAPAI
YUMA
CRITTENOEN
MILLER
MONTGOMERY
.2000
.2200
.3500
.2300
.0010
.0010
.0010
.0010
.1000
.0010
.0010
.0010
.0010
.0010
.1000
.0010
.1000
.3800
.2300
.0500
PULASKI 0.3000
ALAMEDA 1.4900
FRESNO 0.2900
> KERN 0.1960
LOS ANGELES 0.5200
MADERA 0.2150
MERCED 0.2110
MODOC 0.1860
MONTEREY 0.0450
NAPA 0.0600
ORANGE 0.4400
RIVERSIDE 0.0900
SACRAIIEMTO 0.2600
SAN BERNARDINO 0.4100
SAN DIE60 0.2500
SAN FRANCISCO 0.3400
SAN JOAQUIN 0.2830
SAN MATED 0.0100
ARITH
MEAN
0.5300A
0.9400A
0.6500A
...
...
0.0140
0.0190A
0.0120
...
...
...
0.5530
0.0130
0.0150
0.3600
...
...
...
...
...
0.9100A
0.7210
1.5100A
1.431QA
1.9100
...
...
-__
0.5020A
0.7290A
1.8000A
0.6120
0.6310
1.5600
0.9680
0.9000A
...
0.6580 A
CEO
MEAN
0.4400A
0.8400A
0.5500A
...
...
0.0010
0.0090A
0.0060
...
...
...
0.0220
0.0050
0.0070
0.3210
...
...
...
...
...
0.8390A
0.6110
1.1200A
1.0960A
1.6100
...
___
-__
0.4160A
0.5460A
1.4200A
0.5310
0.7900
1.4000
0.9900
0.8000A
«.
0.46 10A
MAXIMUM IU6/H3)
OBS
2.0600
4.2300
1.9600
2.9400
3.0900
0.2000
0.9300
0.6200
0.4000
0.4000
0.4000
9.3670
0.3000
0.3000
2. 1870
0.5000
0.2000
0.4000
2.8700
1.0500
0.1500
1.6300
6.1100
5.1300
5.5320
8.9400
2.0610
O.C700
0.1260
1.5120
4.0500
6.4900
4. 5 '.90
8.5000
4.5500
6.2600
6.9100
0.4630
4.2600
ARITH
MEAN
0.5300A
0.9400A
0.6500A
...
...
0.0320
0.0190A
0.0260
...
...
...
2.3240
0.0180
0.0150
1.0010
...
...
...
...
...
...
0.9100A
1.2150
1.5100A
1.4310A
2.5900
._.
___
0.5020A
0.7290A
.6000 A
.8390
.1000
.6550
.5930
.0290A
0.6560A
6EO
MEAN
0.4400A
0.8400A
0.5500A
...
0.0160
0.0090A
0.0130
...
...
... '
1.7560
0.0070
0.0070
0.8470
...
...
.--
0.8390A
0.8800
1.1200A
1.0960A
2.6500
...
...
.4 160 A
.5460A
.4200A
.6740
.5150
.4820
.1040
.8890A
0.4610A
00
in
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
HIIIIHUH IUG/H3)
STATE
CO
CT
OE
DC
FL
GA
ID
IL
COUNTY
SANTA BARBARA
SANTA CLARA
SISKIYOU
SOLA! 10
SONOMA
TEHAHA
VENTURA
DENVER
LA PLATA
HONTEZUMA
FAIRFIELD
HARTFORD
NEH HAVEN
KENT
NEM CASTLE
HASHINGTON
DADE
OUVAL
HARDEE
HIGHLANDS
HILLSBOROUGH
PINELLAS
CHATHAM
FULTON
HUSCOGEE
ADA
BAIINOCK
BUTTE
IIEZ PERCE
SIIOSIIOUE
COOK
LAKE
PEORIA
ROCK ISLAND
ST. CLAIR
OBS
0.0870
0.3100
0.0620
0.0300
0.0800
0.0670
0.1920
0.4000
0.0010
0.0
C.6300
0.5400
0.4600
0.0500
0.0700
0.4600
0.1000
0.3000
0.0400
0.0
0.1500
0.1100
0.1000
0.4100
0.1900
0.2SOO
0.1200
0.0
0.2000
0.0200
0.1500
0.1500
0.2800
0.1600
0.0300
ARITH
MEAN
1.1050A
1.6200
0.2600 A
0.4840
0.0170
0.0250 A
1.3020 A
I.0650A
1.1220
0.1600A
0.5300
0.3460
0.8900A
0.5590A
1.2000A
0.6100A
0.7800 A
0.5170
GEO
HEAN
0.7940A
0.8460
0.2050 A
0.3480
0.0060
0.0120A
1.2060A
0.9890A
1.0100
0.1300A
0.3900
0.2590
0.8000A
0.4600A
1.0700A
0.5500A
0.7000A
0.4390
MAXIMUM (UG/M3)
OBS
5.2470
8.5000
0.8430
1.3000
2.0000
0.3460
1.9370
3.6400
0.1700
0.1100
2.4600
2.2500
4.1900
0.5200
3.0700
3. 1800
6.9000
2.7200
0.5200
0.1100
2.5200
1.3100
1.3700
3.2800
2.9400
2.6200
1.0500
0.1300
1 .8300
82.0900
4.3SOO
1.9200
3.9000
1.9900
1.4400
ARITH
MEAN
1.1050A
1.4280
0.2600A
0.4840
0.0220
0.0250A
1.3020A
1.0650A
1.9160
0.1600 A
1.5000
2.0270
0.0390A
0.5590A
1.2000A
0.6140A
0.7800 A
15.7250
GEO
HEAN
0.7940A
1.11CO
0.2050 A
0.3480
0.0100
0.0 120 A
1.2060A
0.9S90A
1.7340
0.1300A
1.4200
1.7460
0.8000A
0.4600A
1.0700 A
0.4870 A
0.7000A
11.7850
00
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-S. AIR QUALITY DATA FOR LEAD
STATE
IN
IA
KS
KY
COUNTY
SANGAHON
MILL
MINNEBA60
ALLEN
BARTHOLOHEH
CLARK
DELAWARE
DUBOIS
ELKIIART
FLOYD
6RAIIT
HaiARD
JASPER
JEFFERSON
KNOX
LAKE
MINIMUM IU6/H3I
ARITH 6EO
OBS MEAN MEAN
. 1800
.3100
.2000
.2940
.1290
.3550
.3300
.1630
.2560
.4600
.1940
.1400
.0310
.1300
.2060
.1080
LA PORTE 0.2380
MARION 0.0560
MONROE 0.0400
PARKE
ST. JOSEPH
STEUDEN
TIPPECAHOE
VANOERBURGH
VI60
HAYNE
BLACKHAIK
DELAIIARE
DUBUQUE
LEE
LIUM
POLK
POTTAHATAMIE
SCOTT
SEDGUICK
SHAIMEE
HYAIIOOTTE
.0600
.2350
.0440
.6810A
.4300A
.3370A
...
.4870A
.5080A
...
.4850A
.5150A
.1210A
.3770 A
.4990A
.5910
.4400A
.8300A
.7280A
...
.6000A
.1780A
.2220 0.5300A
.1720 0.5250A
.1930 0.5120A
.1960 0.5280
.6130A
.3660A
.1770A
...
.4440A
.4770A
.4420A
.45SOA
. 1070A
.3380A
.4620A
.4910
MAXIMUM IU6/M3I
OBS
.8300
.2100
.0500
.8200
.0460
.4040
.2900
.0780
.1020
.0600
.9970
.5120
.2720
.0410
.2810
.8700
.4160A 0.7700
.7070A 5.2550
.6360A
(
.5190A
1.8610
1.2800
1.3500
.1640A 0.3760
.4930A
.4670A 1
.4420A
.4600
1.0500
1.3620
1.5340
1.6340
.1700 0.4300A- 0.3900A 2.0100
ARITH
MEAN
...
...
...
0.6810A
0.4300A
1.3370A
0.4870A
0.5080A
...
0.4850A
0.5150A
0.1210A
0.3770A
0.4990A
0.7320
0.4400A
0.8300A
0.7230 A
...
0.6000A
0.1780A
0.5300A
0.5250A
0.5120A
0.6270
0.5S40A
GEO
MEAN
...
...
...
0.6130A
0.3660A
1.1770A
...
0.4440A
0.4770A
...
0.4420A
0.4580A
0.1070A
0.33SOA
0.4620A
0.6440
0.4160A
0.7070A
0.6360A
0.5190A
0.1640A
0.4930A
0.4670A
0.4420A
0.5840
0.5090A
.0520 0.2800
.0200 99.0000
.1100 0.3200
.1500 0.5400A 0.4500A 1
1.8300
.3400 1.0070A 0.9030A 2.7500
0.5180A
1.0070A
0.4680A
0.9030A
.4500 0.6500
.3000 2.6700
.2000 1
.1600 1
1.1400
1.6400
.0900 0.5100 0.4600 3.0200
...
...
0.4280
...
...
0.3840
BOYD 0.1300 3.8900
FAYETTE 0.2900 3.5600
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
HINIHUH IUB/H3)
STATE
LA
HE
HO
HA
HI
mi
,
COUNTY
JEFFERSON
KENTON
HARREH
CADOO PARRISH
EAST BATON ROUGE PARRISH
IBERVILLE PARRISH
ORLEANS PARRISH
CUII3ERLAI10
HANCOCK
BALTIIIORE (CITY)
CALVERT
CENTRAL HA. APCO
METROPOLITAN BOSTOtl APCO
PIONEER VALLEY APCO
SOUTHEASTERN HA. APCO
GENESEE
IIIGIIAH
KENT
SAGINAH
HAYHE
BELTRAHI
BIG STONE
BLUE EARTH
CARLTOM
CLAY
CROW MING
DAKOTA
GOODHUE
HEHilEPIN
ITASCA
KAtiDIYOHI
KOOCHICIIIHG
LYOU
HCLEOD
HILLE LACS
HOMER
NOBLES
OBS
0.2700
0.3200
0.1900
0.2000
0.2SOO
0.0300
0.3900
0.1000
0.0
0.4400
0.0300
0.3000
0.4000
0.6500
0.1900
0.3800
0.2100
0.2700
0.1400
0.1800
0.0860
0.0060
0.2690
0.0530
0.0530
0.0130
0.0550
0.3130
0.1800
0.0220
0.1120
0.0320
0.1730
0.1130
0.3330
0.2190
0.0520
ARITII
HEAH
0.9760A
0.7100A
0.4800A
0.6720A
1.1500A
0.1300A
0.8000
0.4500 A
0.0600A
1.0700 A
0.1700A
0.8400A
...
...
...
_._
.--
0.4000 A
_._
-
___
...
...
.-,
1.2700A
.-_
._.
...
...
...
...
...
GEO
MEAN
0.9400A
0.6300A
0.4100A
0.6100A
0.9000A
0.1100A
0.7700
0.4000A
0.0400 A
0.9SOOA
0.1400A
0.7400A
.__
...
...
...
0.3700A
...
...
._.
...
...
...
_
0.9400A
...
...
...
...
.
MAXIMUM IUG/113)
ODS
3.JSOO
1.2200
1.1500
1.4400
4.2600
0.3300
1.6400
1.4700
0.3900
2.5000
0.3900
1.8600
1.3900
2.9000
1.1700
1.3400
1.7100
2.2500
0.9100
2.7100
0.1560
0.1130
0.75SO
0.2230
0.1150
0.2790
0.4750
1.2540
8.8100
0.1190
0.2040
0.4450
0.3670
0.3200
1.2220
0.3910
0.1720
ARITH
HEAH
1.1800 A
0.7100A
0.4&OOA
0.6720A
1.1500A
0.1300A
1.0300
0.4500A
0.0600A
1.0700 A
0.1700A
0.8400A
...
0.4 000 A
*-.
...
* .
---
«._
---
_.--
1.2700A
__
_--
«.-
_ .
__
-»
GEO
HEAH
0.8910A
0.6800A
0.4100A
0.6100A
0.9000A
0.1 100 A
0.9330
0.4000A
0.0400A
0.9800A
0.1400A
0.7400A
...
»«
...
...
0.3700A
...
»
_*-
._
...
...
....
...
0.9400A
...
...
...
...
...
00
CO
A INDICATES OIILY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
MIMIHUH IUG/M3)
STATE
H3
KO
NT
COUNTY
OLMSTEO
OTTERTAIL
POLK
RAMSEY
ST. LOUIS
SCOTT
STEARHS
WASHINGTON
HINOHA
HINDS
JACKSON
ST. LOUIS (CITYI
ADAIR
AUDRAIN
BQOIIE
BUCHANAN
BUTLER
CALLAIIAY
CAHOEN
CAPE 6IRARDEAU
CLAY
COLE
JACKSON
JASPER
JEFFERSON
LIVINGSTON
> IIARION
MEN MADRID
NODASIAY
PETTIS
PIIELPS
PLATTE
ST. CHARLES
STE GENEVIEVE
SCOTT
SHANNON
VERNON
6LACIER
JEFFERSON
LEIUS AW CLARK
ODS
0.2150
0.0840
0.0530
0.0720
0.0010
0.0320
0.0100
0.2180
0.1110
0. 1400
0.0020
0.2900
0.1200
0.1100
0.1100
0.0500
0.0190
0.1150
0.0100
0.0680
0.0010
0.0900
0.3500
0.1600
0.2340
0.0900
0.1700
0.1000
0.0460
0.1970
0.0690
0.0900
0.2400
0.1400
0.1400
0.0300
0.1490
0.0
0.0600
0.3300
ARITH
MEAN
...
_..
...
...
...
...
...
...
0.7500A
0.8900A
...
...
_..
...
...
...
...
...
...
...
...
...
...
.
...
___
...
...
0.0790A
...
...
GEO
MEAN
...
...
...
...
...
...
...
...
...
0.6700A
0.8100A
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
.
0.0710A
...
...
MAXIMUM (UG/M3)
DOS
2.3930
0.3140
0.1320
3.8600
2.3100
0.3430
1.1350
0.5610
0.5770
2.7600
0.4200
2.9200
0.5540
4.2300
2.9400
2.8100
4.0600
0.3920
0.7280
0.3100
2.1790
0.7300
1.3900
0.9600
37.5300
0.6120
1.0800
0.6360
0.3150
0.3500
0.2300
1.1420
0.6510
0.3700
2.1900
0.1900
0.3130
0.0600
10.9700
24.6200
ARITH
MEAN
...
...
...
...
...
...
...
...
0.7500A
0.8900A
...
...
...
...
_
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
0.0790A
6EO
MEAN
w..
...
...
...
...
...
...
...
0.6700A
0.8100A
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
-
0.0710A
...
00
VO
A IIDICATES ONLY OtIE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
MINIMUM (UG/M3)
STATE
MB
NV
NH
NJ
NH
NY
i
NC
COUNTY
POWDER RIVER
ROSEDUD
DOUGLAS
LANCASTER
THOMAS
CLARK
HASHOE
WHITE PINE
CODS
MERRIHACK
CAMDEN
ESSEX
GLOUCESTER
HUDSON
MERCER
MIDDLESEX
PASSAIC
UNION
BERNALILLO
RIO ARRIBA
SAN JUAN
ALBANY
ERIE
JEFFERSON
MOHROE
HEM YORK
NIAGARA
OMEIDA
OHOUDAGA
WESTCIIESTER
DARE
DURHAM
FORSYTH
GUILFORD
MECKLENBURG
OBS
0.0
0.0
0.2400
0.1200
0.0020
0.5300
0.3100
0.0
0.0020
0.2000
0.3100
0.2200
0.1300
0.2600
0.4000
0.4800
0.6100
0.6500
0.4800
0.0010
0.0010
0.1700
0.4300
0.0100
0.5700
0.2700
0.2300
0.4600
0.2700
0.4100
0.0200
0.3600
0.2900
0.3300
0.2300
ARITH
MEAN
...
...
...
0.3800A
...
.
...
...
...
...
...
...
...
1.2700A
0.0130A
0.0130
...
...
...
...
...
...
...
...
0.8000
0.6900
GEO
MEAN
...
...
0.3400A
...
...
...
...
...
...
...
...
...
1.0600A
0.0040A
0.0060
...
--_
...
...
...
...
...
...
...
0.7400
0.5900
MAXIMUM IUG/M3)
OBS
0.0400
0.0300
1.9900
0.9500
0.0500
6.5200
5.2200
0.0400
0.1600
1.5300
2.5200
2.1100
1.1200
2.4900
4.4200
1.4400
3.0500
4.8600
4.3200
0.1600
0.1100
1.2700
1.3SOO
0.2600
1.2700
2.3700
0.7500
1.9000
2.7000
2.1400
0.2500
4.0300
2.2200
3.0600
3.8100
ARITH
MEAN
...
...
0.3800A
...
...
...
...
...
...
...
-
...
.
1.2700A
0.0140A
0.0230
...
...
...
._.
...
...
...
...
...
0.9230
0.7550
GEO
MEAN
...
...
0.3400A
...
...
...
...
...
...
...
...
...
1.0600A
0.0070A
0.0120
...
...
...
...
...
...
...
...
...
0.8300
0.6270
MD
o
MD BURLEIGII 0.3500
A INDICATES ONLY ONE STATION REPORTING
0.5700
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
HINIHUH (U6/H3I
STATE
OH
OK
OR
PA
RI
COUNTY
CUYAHOBA
FRAIKLIN
HAMILTON
JEFFERSON
LUCAS
HAIIOIUNu
MONTGOMERY
SCIOTO
SUMtT
CHEROKEE
OKLMIOHA
TULSA
CURRY
HULTNOHAH
ALLEGHENY
BEAVER
BERKS
BLAIR
BUCKS
CAIIBRIA
CHESTER
CLARION
DAUPHIN
ERIE
< INDIANA
LACKAllANNA
LANCASTER
LEHIGH
LUZERNE
LYCONING
NERCER
MONTGOMERY
NORTIIAHPTON
NORTHUMBERLAND
PHILADELPHIA
WESTMORELAND
YORK
PROVIDENCE
OBS
0.4300
0.2700
0.3600
0.1300
0.2600
0.2500
0.4300
0.1300
0.2800
0.0500
0.0100
0.0005
0.0020
0.0020
9.5200
0.5S60
0.2900
0.0010
0.1600
0.0020
0.1600
0.0300
0.2400
0.0200
0.1600
0.6500
0.1170
0.0700
0.2800
0.3230
0.2340
0.2530
0.16SO
0.2400
0.4600
0.1670
0.2900
0.3800
ARITH
MEAN
0.7900A
O.B200A
...
«_
0.6100
0.9800
0.4100
0.5700A
...
0.1810
0.5300A
0.0300A
0.8300A
...
...
0.8IOOA
-_.
...
_._
0.5100
...
1.0400
0.6000A
--..
2.0500A
.._
0.7900A
0.7900
...
...
...
...
0.6600A
1.2480
...
0.7200A
6EO
HE AN
0.7100A
0.7500A
...
...
0.5500
0.8600
0.3600
O.S500A
...
0.0650
0.4700A
0.0100A
G.6600A
_«»
._-
0.7400A
...
...
...
0.4700
...
0.9000
0.3000A
...
1.8500A
0.7100A
0.7200
...
...
...
...
0.6100A
1.1790
...
0.6600A
...
HAXINUH (UG/H3)
OSS
1.8700
2.3100
1.8000
1.4200
1.7200
1.4700
2.7500
1.0400
1.2000
0.2100
30.0000
1.4200
0.0700
4.2300
3.1100
2.8i)20
6.43SO
2.8250
2.2600
3.2430
1.3SOO
0.4400
2.6000
2.1630
0.9600
6.6100
2.7500
2.6600
2.6200
1.7820
1.5640
2.1700
1.4550
0.3300
2.7200
2.5S90
2.2630
2.0300
ARITH
HE AN
...
0.7900A
0.8200A
...
...
0.6100
0.9800
0.4100
0.5700A
..»
1.9120
0.5300A
0.0300A
0.8300A
...
._.
0.8100A
...
...
0.5670
-
1.0400
0.6000A
...
2.0500A
_..
0.7900A
0.8270
...
...
_»
0.6600A
1.3200
0.7200A
...
GEO
MEAN
0.7100A
0.7500A
.
...
0.5500
0.8600
0.3600
0.5500A
...
1.5170
0.4700A
0.0100A
0.6600A
...
...
0.7400A
...
...
...
0.4860
...
0.9000
0.3000A
...
1.8500 A
0.7100A
0.7820
.._"*
...
...
0.6100A
1.2100
0.6600A
...
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
STATE
SC
SD
TN
COUNTY
WASHINGTON
CHARLESTON
GREENVILLE
RICHLAIID
CUSTER
HINHEHAHA
ANDERSON
BEDFORD
BLOUIIT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DAVIDSON
DYER
GIBSON
GREEN
HAI1BLEH
HENRY
HUMPHREYS
KNOX
LIMCOLN
HCMIIitt
MADISON
> MARION
HAURY
MONTGOMERY
OBIOH
POLK
PUTNAH
ROANE
ROBERTSON
RUTHERFORD
SHELBY
SULLIVAN
SUMMER
HARKEH
UASHIN6TON
HILLIAM30N
CBS
0.0300
0.8450
0.3500
0.0500
0.0
0.0200
0.5800
0.2800
0.6500
0.2000
0.4500
0.5300
0.1600
0.0100
0.2500
0.1600
0.1400
0.4300
0.1300
0.0200
0.0300
0.3700
0.2300
0.1SOO
0.1300
0.1500
0.4000
0.2300
0.2400
0.3700
0.1700
0.3300
0.2300
0.2400
0.2500
0.2300
0.2100
0.2200
0.6300
0.2700
MINIMUM (UG/H3)
ARITII
MEAN
...
1.0500 0
...
...
...
...
...
...
0.0900A 0
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
GEO
MEAN
...
.8600
...
...
.
...
---
...
._-
.0200 A
...
...
...
...
.
.-t
...
...
...
...
...
...
...
___
...
...
...
...
OBS
0.6900
0.8450
3.4500
4.1500
0.0500
1.6200
1.3100
0.6400
1.5000
0.4900
0.8100
0.5300
1.6200
0.5000
2.4600
0.7700
0.4500
0.6500
2.7400
0.7100
0.2100
3.9000
0.2300
0.1200
2.3300
0.2200
2.4700
0.9200
0.5700
1.4200
0.7200
1.9000
0.4500
0.8200
5.5700
2.2900
0.4900
0.4200
0.6300
0.2700
MAXIMUM (UG/H3I
ARITH
MEAN
1.1320 0
...
...
...
...
0.0900A 0
_-_
...
...
...
...
...
...
...
...
...
GEO
MEAN
...
.9380
...
...
--.
.OSOOA
.__
...
--.
.
...
...
...
.
to
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
HINIHUH (UG/H3)
STATE COUNTY
NILSON
TX BEE
BEXAR
BOHIE
BRAZORIA
BRAZOS
BROCN
CALHOUM
CAMERON
CHAMBERS
DALLAS
OENTON
ECTOR
ELLIS
EL PASO
6ALVESTON
6RAY
GRAYSON
HALE
HARRIS
HAYS
HIDAL60
H01IARO
JEFF DAVIS
JEFFERSON
LUDDOCK
HCLEMIIAM
> HCHULLEH
HATAGORDA
MAVERICK
MIDLAND
HONTGOOERY
MOORE
NACOGOOCHES
NUECES
ORANGE
POTTER
SAN PATRICIO
SCURRY
SMITH
T ARRANT
TAYLOR
OBS
0.2500
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
.0200
.0200
.0200
.0200
.0200
.0200
. 0.0200
o.oo to
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.1000
0.0200
0.0200
0.0200
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0600
0.0010
0.0200
ARITH
MEAN
...
0.4400A
0.4200A
0.1400
0.3700A
...
...
0.0500
...
0.2300
...
0.4400A
~.
0.0900
0.4500A
-._
.__
0.1500
~.
0.0300
0.0700
...
0.1300
...
...
...
...
0.4900A
0.1200A
-
...
...
0.3600
0.1100A
...
...
_
0.5000A
0.6910A
0.1700A
GEO
MEAN
0.2800A
0.3300A
0.0900
0.3000A
...
...
0.0300
...
0.1700
...
0.3900A
...
0.0500
0.3800 A
...
...
...
0.0900
...
0.0300
0.0500
...
0.0600
...
...
...
0.3900A
0.0900A
...
...
0.2400
0.0700 A
...
...
...
0.3900 A
0.5340A
0.1300A
MAXIMUM IUG/N3I
ODS
0.2900
0.1300
4.3300
1.9500
0.7400
0.8700
1.8100
0.1300
1.2300
0.2000
8.0200
0.7200
1.0700
1.5000
4.0900
1.2000
0.1200
1.9900
0.1300
3.9100
1.2300
1.2500
0.0200
0.0200
0.9600
1.9600
0.7900
0.3300
0.2100
1.9000
0.6000
0.7000
0.1400
0.5600
17.3000
0.7200
1.4800
0.1100
0.2700
1.4000
3.8000
0.7400
ARITH
MEAN
...
0.4400A
0.4200A
0.1900
0.3700A
...
0.1700
...
2.9280
...
0.4400A
...
1.1100
0.4500A
...
...
...
0.8500
...
0.2800
0.0700
0.5200
...
...
...
0.4900A
0.1200A
....
.*.
0.6100
0.1100A
...
-p
0.5000A
0.8650A
0.1700A
GEO
MEAN
...
0.2800A
0.3300A
0.1200
0.3000A
...
...
0.1000
...
2.6310
0.3900A
...
1.0200
0.3800A
...
...
0.6700
...
0.2100
0.0500
0.5000
...
...
...
0.3900A
0.0900A
...
..»
0.5300
0.0700A
««
...
0.3900A
0.8060A
0.1300A
VO
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-5. AIR QUALITY DATA FOR LEAD
MINIHUH (UG/M3I
STATE
UT
VT
VA
HA
UV
HI
COUNTY
TITUS
TOH GREEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
UEBB
WICHITA
HISE
EMERY
6ARFIELO
KANE
SALT LAKE
SAN JUAN
WASHINGTON
WEBER
CHITTENDEN
ORANGE
0000
FAIRFAX
PAGE
PITTSYLVANIA
HYTHE
KING
PIERCE
SPOKANE
CABELL
KAHAIIHA
DANE
DOOR
DOUGLAS
EAU CLAIRE
KENOSIIA
MILWAUKEE
RACINE
OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0010
0.0010
0.3500
0.0010
0.0010
0.2300
0.0020
0.0500
0.1300
0.2100
0.0300
0.1800
0.0200
0.0700
0.1600
0.1800
0.2200
0.1200
0.1400
0.0
0.0300
0.1500
0.0800
0.3200
0.1300
ARITH
MEAN
0.1100 A
0.1000A
0.0400
_
...
...
...
0.4600A
0.0150
0.0170A
0.0110
0.0190
0.6860
0.5200
.__
0.2400A
0.5700A
0.0900
1.4600 A
0.9500A
...
0.5200
0.6000A
..-
0.2300A
...
...
0.4200A
6EO
MEAN
0.0700A
0.0700A
0.0300
...
...
.-_
...
0.4000A
...
...
0.0070
o.ooaoA
0.0050
0.0070
0.4710
...
0.4400
...
0.1900A
0.4800 A
0.0300
1.3100A
0.8200 A
.
0.4400
0.5200 A
...
0.1900A
...
...
...
0.3500A
MAXIMUM IUS/H3)
DCS
0.5SOO
0.6500
2.6000
0.6000
0.8300
0.3300
0.7100
1.2100
0.6500
0.1600
0.1700
0.0900
4.9100
0.1400
0.2400
3.5500
1.2600
1.1800
3.7500
2.1100
0.8100
1.9300
0.1900
4.4800
2.1900
1.2900
2.2900
2.6900
1.3000
' 0.5500
1.0700
0.9800
1.0300
1.6100
1.4700
ARITH
HE AN
0.1100A
0.1000A
0.7300
-r-
...
.._
0.4600A
...
0.0170
0.0170A
...
0.0200
0.0300
0.7900
0.9700
...
0.2400A
0.5700 A
0.0900
1.4600A
0.9500A
...
0.6240
0.6000A
_._
0.2300A
...
...
...
0.4200A
GEO
MEAN
0.0700A
0.0700A
0.6400
...
...
...
0.4000A
...
0.0080
0.0030 A
0.0080
0.0160
0.7600
0.8600
___
0.1900A
0.4800 A
0.0800
1.3100A
0.8200A
...
0.7200
0.5200A
0.1900A
...
.
0.3500A
HY
LARAIIIE
0.1100
0.6600
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-S. AIR WJAUTV DATA FOR LEAD
MINIMUM (UG/H3I MAXIMUM (U6/M3I
ARITH 6EO ARITH GEO
STATE COUNTY OBS HEAN HEAN DOS MEAN IIEAH
NATROHA H.OaOO O.V.OO
PARK 0.0 0.0300
\o
-------
TABLE C-6. AIR QUALITY DATA FOR MANGANESE
MINIMUM (U6/II3)
STATE
AZ
CO
IN
HO
COUNTY
APACHE
COCOHIHO
MARICOPA
HOIIAVE
NAVAJO
LA PLATA
HONTEZUHA '
ALLEN
BARTHOLOMEW
CLARK
OUBOIS
ELKIIART
GRANT
HOVIARO
JASPER
JEFFERSON
KHOX
LAKE
LA PORTE
MARION
MONROE
ST. JOSEPH
STEUBEN
TIPPECANOE
VAHDERBURGH
. VI60
UAYHE
AOAIR
AUDRAIN
BOOilE
BUCHANAN
BUTLER
CALLAIIAY
CAIIOEN
CAPE GIRARDEAU
CLAY
COLE
JASPER
JEFFERSON
OBS
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0170
0.0060
0.0230
0.0130
0.0120
0.0150
0.0250
0.0060
0.0070
O.OOSO
0.0060
0.0180
0.0040
0.0090
0.0150
0.0030
0.0130
0.0110
0.0160
0.0190
0.0260
0.0290
0.0210
0.0040
0.0190
0.0190
0.0130
0.0160
0.0300
0.0210
0.0330
0.0 1
-------
TABLE C-6. AIR QUALITY DATA FOR MANGANESE
MINIMUM IUG/H3I
STATE
NH
SC
TH
COUNTY
LIVINGSTON
MARION
NEU MADRID
HODAHAY
PETTIS
PHELPS
PLATTE
ST. CHARLES
STE. GEHEVIEVE
SCOTT
VERNON
RIO ARRIBA
CHARLESTON
ANDERSON
BEDFORD
BLOUNT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
GREENE
HAMBLEN
< HENRY
HUMPREYS
LINCOLN
MCIIIIUI
MADISON
MARION
HAURY
MONTGOMERY
OBIOH
POLK
PUTNAM
ROAHE
ROBERTSON
RUTHERFORD
SULLIVAN
0
0
OBS
0310
.0190
.0190
ARITH
MEAN
6EO
MEAN
MAXIMUM IUG/M3)
ARITH
OBS MEAN
6EO
liEAN
0.8280
0.0690
0.2720
.0200
.0310
0.0710
0.0610
.0110 (
.0230
.0230
.0610
.0020
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0340
.0
.0170
.0320
.0160
.0310
.0100
.0200
.0200
.0030
.0040
.0060
.0060
.0280
.0160
.0060
.0120
.0360
.0190
.0160
.0270
.0310
.0080
.0160
.0370
.0060
.0610
.2500
.0100
.0060
1.0730
.
.
0.0960
0.1120
0.0610
0.3640
0.0820
0.0040A
0.0010A 0.0400 0.0040A
0.00 IDA
0.0170
...
...
...
...
...
...
...
...
...
...
...
...
_
...
...
(
(
(
1
1
I
t
(
.« |
1
(
<
(
(
(
(
1.0420
1.0240
1.0450
1.1290
1.0340
1.0200
1.0330
1.0250
1.1260
1.0300
1.0340
1.0700
1.0260
).6960
1.0360
1.0190
_
-
-
-
_
-
.
_
_
_
_
.
.
_
_
_
_
_
_
_
_
_
..
_
.
_
_
_
_
--
«
..
--
_-
__
..
__
_.
--
--
w_
_«
^
__
0.0350
0.0290
(
1.0810
^
_
w
6 i 0410
0.1030
1
>.0«fl
_
_^
oioifio
0.9720
0.0270
0.0240
O!l670
vo
A INDICATES OltLY ONE STATION REPORTING
-------
TADLE 06. AIR QUALITY DATA FOR MANGANESE
STATE COUNTY
SUtUIER
UARREN
UASHIN6TON
UILLIAHSON '
HILSON
TX BEE
BEXAR
BOS1IE
BRAZORIA
BRAZOS
BR013I
CALHOUI
CAMERON
CHAMBERS
DALLAS
DEHTOtt
ECTOR
ELLIS
EL PASO
GALVESTON
GRAY
GRAYSON
HALE
HALE
HAYS
HIDALGO
HOUARO
> JEFF DAVIS
JEFFESON
LUBBOCK
HCLEtlllAN
HCCULLEN
MATAGOROA
HAVERICK
MIDLAND
MONTGOMERY
MOORE
NACOGDOCHES
IAJECES
ORANGE
POTTER
SAN PATRICIO
MINIMUH (U6/H3)
ARITII GEO
DBS MEAN MEAN
0.0180
0.0070
0.4350
0.0370
0.0100
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.0200
.0200
.0200
.0200 -
. .0200
.0200
.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
DBS
0.0250
0.0250
0.0350
0.0370
0.0230
0.0900
0.1400
0.1000
0.1600
0.0900
0.0700
0.0900
0.3100
0.1000
0.1900
0.0700
0.3100
O.OSOO
0.2000
0.1300
0.1500
0.0700
O.OSOO
1.1500
0.1100
0.1500
0.0900
0.1400
0.1400
0.1000
O.OSOO
0.0300
0.0200
0.0700
0.3700
0.1000
0.1600
0.0200
2.6600
0.2200-
0.1600
0.0200
MAXIMUM (UG/M3)
ARITH
MEAN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
.
...
-
.
...
...
GEO
MEAN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
.
...
.
...
...
.
.
...
...
.
.
...
...
...
00
A INDICATES ONLY ONE STATION REPORTING
-------
TABLE C-6. AIR QUALITY DATA FOR MANGANESE
MINIMUM (UO/M3I
STATE COUNTY
SCURRY
SMITH
TARRAMT
TAYLOR
TITUS
TCH 6REEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
HEEB
WICHITA
WISE
UT EHERY
6ARFIELD
KANE
SAN JUAN
WASHINGTON
OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.0
0.0
0.0
0.0
ARITH
MEAN
...
.--
...
...
...
...
...
...
...
...
...
...
...
...
0.0070
0.0050A
0.0040
0.0070
6EO
MEAN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
0.0020
0.00 IDA
0.0010
0.0030
MAXIMUM IUG/M3)
033
0.0600
0.0900
0.1000
0.0500
0.0700
0.1700
0.1000
0.0200
0.0700
0.0600
0.0600
0.0200
0.0600
0.0400
0.0500
0.0400
0.0300
0.0800
ARITH
MEAN
...
...
...
...
...
.._
...
...
...
___
___
...
...
0.0140
0.0050A
0.0100
0.0070
6EO
HE All
...
...
...
...
...
...
_
...
...
...
...
___
...
0.0071
0.0010A
0.0030
0.0030
NO
VO
-------
TABLE C-7. AIR QUALITY DATA FOR SELEHIUII
MINIMUM (UG/M3I
STATE COUNTY
TX BEE
BEXAR
BOHIE
BRAZORIA
BRAZOS
EROUM
CALHOUH
CAMERON
CHAMBERS
DALLAS
OENTOil
ECTOR
ELLIS
EL PASO
6ALVESTOH
GRAY
6RAYSOII
HALE
HARRIS
HAYS
HIDALGO
HOIIARD
JEFF DAVIS
JEFFERSOH
LUBBOCK
HCLEHHAN
MCHULLEII
HATAGORDA
HAVERICK
MIOLAHF
MONTGOMERY
MOORE
NACOGOOCHES
MUECES
ORANGE
POTTER
SAII PATRICIO
SCURRY
SHITH
TARRAHT
TAYLOR
TITUS
OBS
0.0100
0.0100
0.1000
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
ARITH
MEAN
0.0100A
0.0100A
0.0100
0.0100A
_
0.0100
0.0100
0.0100A*
0.0100
...
0.0100
...
0.0100
0.0100A
--_
0.0100A
_-_
«_
0.0100A
0.0 100 A
...
0.0100
0.0100A
.-.
.._
0.0100A
9.0000
0.0100A
0.0 100 A
GEO
MEAN
0.0200 A
0.0200A
0.0200
0.0200 A
.--
_--
0.0200
.
0.0200
.--
0.0200A
.»
0.0200
0.0200
0.0200
0.0200 A
_--
0.0200 A
_--
...
.-.
0.0200A
0.0200 A
.--
...
.-_
0.0200
0.0200A
---
-.-_
_._
0.0200A
99.0000
0.2000A
0.0200A
MAXIMUM (UG/M3I
OBS
0.0100
0.0400
0.0300
0.0100
0.0100
0.0300
0.0100
0.0100
0.0300
0.0100
0.0600
0.0100
0.0400
0.0100
0.1300
0.0100
0.0300
0.0100
0.0300
0.0300
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0400
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0300
0.0100
0.0100
0.0100
0.0100
0.0300
0.0300
0.0100
0.0100
ARITH
MEAN
0.0100A
0.0100A
0.0100
0.0100A
»_
0.0100
0.0100
0.0100A
99.0000
--.-
-_-
0.0100
0.0100
0.0100A
0.0100A
0.0100A
0.0100A
-_-
0.0100
0.0100A
0.0100A
99.0000
0.0 100 A
0.0100A
GEO
MEAN
...
0.0200A
0.0200A
0.0200
0.0200 A
---
0.0200
---
0.0200
0.0200A
99.0000
_.-
_
0.0200
_._
0.0200
0.0200A
__-
0.0200 A
0.0200A
0.0200A
0.0200
0.0200A
___
...
_
0.0200A
99.0000
0.2000A
0.0200 A
o
o
A INDICATES DULY OHE STATION REPORTING
-------
TABLE C-7. AIR WMUTY DATA FOR SELENIUM
HIMUUH IU6/HJ) MAXIMUM IUG/II3)
STATE
COUNTY
TON 6REEN (
TRAVIS 1
VAL VEROE (
VICTORIA
UALKER
IIEBB
MICHITA
WISE
DBS
1.0100
1.0100
1.0100
.0100
.0100
.0100
.0100
.0100
ARITII
MEAN
0.0100
6EO
MEAN
0.0200
DBS
0.0100
0.0500
0.0100
0.0400
0.0100
0.0100
0.0300
0.0100
ARITH
HE AH
0.0200
6EO
ME AH
0.0200
-------
TABLE C-8. AIR QUALITY DATA FOR VANADIUM
STATE
TN
TX
COUNTY
ANDERSON
BEDFORD
BLOUNT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
GREENE
HAHBLEH
HENRY
HUMPREYS
LINCOLN
HCMINN
MADISON
MARION
HAURY
MONTGOMERY
OBION
POLK
PUTNAM
ROANE
ROBERTSON
RUTHERFORD
SULLIVAN
SUI1KER
HAKREN
IIASIIItiGTOH
HILL I AIISOII
UILAON
BEE
BEXAR
BOIIIE
BRAZORIA
BRAZOS
BROUN
CALHOUI
CAMERON
CHAtiOERS
MINIMUM (UG/M3I
ARITH 6EO
OBS MEAN MEAN
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200 -/--
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
n.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0020
0.0010
0.0010
0.0020
0.0030
0.0040
0.0010
0.0020
0.0010
MAXIMUM (UG/lttl
ARITH GEO
MEAN MEAN
...
...
...
... ...
...
... ...
...
___
...
...
...
-__
...
...
_
... ...
... ...
...
... ...
...
...
... ...
. -._
...
...
...
o
10
A INDICATES 0>1LY ONE STATION REPORTING
-------
TABLE C-ft. AIR SUAUITY DATA FOR VANADIUM
HIHINUH IUO/H3)
STATE COUNTY
DALLAS
DEHTOM
ECTOR
ELLIS
EL PASO
6ALVESTOH
GRAY
6RAYSOH
HALE
HARRIS
HAYS
HIDALGO
HOI1ARD
JEFF DAVIS
JEFFERSON
LUCBOCK
MCLENNAN
HHULLEN
HATAGORDA
MAVERICK
HIOLAHO
MONTGOMERY
WORE
NAC06DOCHES
NUECES
03AUGE
POTTER
SAN PATRICK
SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TON GREENE
TRAVIS
VAL VERDE
VICTORIA
MALKER
HEEB
WICHITA
HISE
OBS
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
ARITH
MEAN
...
...
.--
_..
...
...
...
...
...
...
...
...
_
...
...
...
...
...
...
_-.
...
...
...
...
...
...
...
...
...
...
...
...
_--
.-.
...
6EO
HE AN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
_
...
...
...
...
...
-__
...
...
...
...
...
...
...
...
...
...
...
...
MAXIMUM IUS/H3I
OBS
0.0020
.0010
.0010
.0010
.0020'
.0070
.0010
.0020
.0010
.0030
.0010
0.0010
0.0020
0.0010
0.0230
0.0020
0.0020
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0020
.0010
.0010
.0010
.0030
.0100
.0010
.0010
0.0010
0.0030
0.0010
0.0010
0.0010
0.0010
0.0010
0.0020
ARITH
HE AN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
___
...
...
...
...
...
...
...
...
...
...
....
...
...
...
GEO
MEAN
...
...
...
...
...
...
...
--_
...
...
...
...
...
...
...
...
___
...
_
...
_._
...
_
...
...
...
...
...
...
...
...
...
...
...
...
o
LO
-------
TABLE C-9. AIR QUALITY DATA FOR ZINC
STATE
AZ
10
IN
SC
TX
COUNTY
APACHE
COCOHIHO
6ILA
GRAIIAII
GREEtlLEE
HARICOPA
MOIIAVE
HAVAJO
PIIIA
FINAL
SANTA CRUZ
YAVAPAI
YUIA
SIIOSHOHE
ALLEH
BARTHOLOMEH
CLARK
OUBOIS
ELKHART
6RANT
HOItARD
JASPER
JEFFERSON
KNOX
LAKE
> LA PORTE
MARIOti
KOtlROE
ST. JOSEPH
STEUBEN
TIPPECANOE
VAUDERBURGH
VI60
MAYHE
CHARLESTON
BEE
BEXAR
BOUIE
MINIMUM (UG/H3)
ARITII 6EO
DBS HEAH HEAH
0.0100
0.0200
0.0100
0.0200
0.0300
0.0001
0.0001
0.0100
0.0001
0.0300
0.1100
a. 0100
0.0200
0.0100
0.0550
0.04SO
0.0924
0.0478
0.0590
0.0772
0.2010
0.0543
0.0215
0.0410
0.0410
0.0634
0.1000
0.0430
0.0645
0.0602
0.0637
0.0520
0.1391
0.0736
0.3500
0.0
0.0 0.0200A 0.0100A
0.0 0.0500 A 0.0300A
DBS
0.2300
0.1500
0.1900
0.0900
0.2300
O.C410
0.1700
0.1400
0.3000
0.2200
0.1100
o.wao
0.1000
ft. 9000
0.1590
0.1140
0.6551
0.2774
O.Q7CO
0.2225
1.4440
0.136S
0.0976
0.0851
0.3990
0.1971
0.4960
0.0960
0.406S
0.2373
0.0995
0.1720
0.4640
0.3921
0.3500
0.0300
0.2100
0.7400
MAXIMUM (U6/M3I
ARITII GEO
MEAN IIEAH
...
...
... ...
...
...
...
...
_
... ...
... ...
...
...
...
- ...
0.0200 A 0.0100A
Q.0500A 0.0300 A
A INDICATES OtILY ONE STATION REPORTING
-------
HIHItlUH IU6/H3I
MAXIMUM (UG/M3I
STATE COUNTY
BRAZORIA
BRAZOS
BROUN
CALIIQUN
CAMERON
CHAMBERS
DALLAS
DENTON
ECTOR
ELLIS
EL PASO
6ALVESTON
6RAY
6RAYSON
HALE
HARRIS
HAYS
HIDALGO
HOIIARD
JEFF OAVIS
JEFFERSON
LU8BOCK
MCLEMMAN
HCIKJLLEII
HATA6CRDA
MAVERICK
HIDLAltD
MONTGOMERY
MOORE
NACOGOOCHES
NUECES
ORANGE
POTTER
, SAN PATRICIO
SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TON 6REEN
TRAVIS
VAL VERDE 1
VICTORIA
DOS
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0100
.0
.0100
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0200
.0
.0300
.0
.
9.
1.
1.
1.
I.
1.0
1.0
1.0
1.0
1.0
ARITH
MEAN
0.0300
0.0400A
...
...
0.0100
...
0.0200
...
0.0600A
__.
0.0500
o.oaooA
...
...
---
0.0400
...
0.0100
0.0200A
...
0.0400A
...
...
~-
...
0.0500A
0.0400A
...
...
...
0.0300
0.0400A
...
...
...
0.0400A
...
0.0300
0.0400A
...
0.0100
...
6EO
MEAN
0.0200
0.0300A
...
...
0.0100
...
0.0100
...
0.0400A
_
0.0200
0.0700A
...
...
...
0.0200
...
0.0100
0.0100A
...
0.0200A
...
...
...
...
0.0300A
0.0200A
...
...
...
0.0200
0.0300A
...
0.0300A
...
0.0200
0.0200A
.__
0.0100
-._
DBS
0.5500
0.0900
0.4500
0.0600
0.4200
0.7400
0.2400
0.1000
0.1600
0.1400
2.3400
6.7000
0.0500
0.1600
0.0300
Z.OoOO
0.1000
0.2200
0.1700
0.1000
0.4300
0.3100
0.1200
0.1COO
0.0600
0.3600
0.1300
0.1000
0.0900
0.1000
28.6100
0.4700
0.1800
0.0400
0.1200
0.1700
1.5000
0. 1600
0.3SOO
1.1400
1.E300
0.0900
0.0700
ARITH
MEAN
0.0400
0.0400A
...
...
0.0400
...
0.0200
...
0.0600A
...
0.1500
0.0800A
_-.
...
0.1300
...
0.0200
0.0200A
_._
0.0400A
...
...
...
0.0500A
0.0400A
._.
...
2.5200
0.0400A
___
0.0400A
...
0.0300
0.0400A
~_
0.0500
...
GEO
MEAN
0.0300
0.0300A
...
0.0200
0.0200
...
0.0400A
...
0.0700
0.0700A
...
0.0800
...
0.0100
0.0 100 A
...
0.0200A
...
___
0.0300A
0.0200A
-__
1.1500
0.0300A
...
__.
0.0300A
0.0200
0.0200A
...
0.0400
...
A INDICATES OilLY ONE STATION REPORTING
-------
106
-------
APPENDIX D
Effects of Deposited Particulate Matter
-------
108
-------
APPENDIX D
EFFECTS OF DEPOSITED PARTICULARS MATTER
Most evidence for particulate toxicity is derived from studies of
domestic animals. It is often not clear if the symptoms of toxicity are the
result of ingestion, inhalation, or both. Only those studies which clearly
indicated ingestion of dust-covered vegetation are summarized here. There
appears to be a definite relationship between deposition of fine particles of
arsenic, fluoride, lead, and copper on vegetation; their ingestion by animals;
and chronic or acute injury to animals.59,60 other metals which may also be
implicated are zinc and cadmium. The surfaces of vegetation, especially those
covered with fine hairs (stems, leaf petioles, and blades), provide a major
filtration and reaction surface for metal-laden particles of 1-5 um and
less.61
Fluorides are reported to cause more damage to domestic animals than
any other air pollutant.62 Dietary fluoride is generally accepted as the
major source of fluorosis in animals.' Fluorosis has been noted in most
domestic livestock, presumably resulting from particulate fluoride deposited
on vegetation and ingested by animals.63,64 por cattle, the most susceptible
domestic animal,26,65,66 diets containing concentrations exceeding 40 ppmw
fluoride may have severe toxic effects.67 The safe range for soluble and
insoluble fluorides has been specified at 30-50 ppmw and 60-100 ppmw, respec-
tively, for cattle.68 Sheep and swine (70-100 ppmw), chickens (150-300 ppmw),
and turkeys (300-400 ppmw) are less sensitive to dietary fluoride levels.68
Arsenic deposited on vegetation from smelting operations has been known
to kill livestock if enough was ingested .62,69-72 ingestion of arsenic-
contaminated dust/soil on forage presents the greatest dangers to grazing
animals.73 However, a wide range of toxicity for arsenic compounds exists and
is correlated to animal excretion rates.9 The reported biological half-life
of arsenic compounds ranges from 30-60 hours.?4,75 Those compounds excreted
most rapidly tend to be least toxic.
Lead poisoning of cattle, horses, and other grazing animals as a result
of ingestion of contaminated forage has been reported often.76-80 Fodder
contaminated by lead and zinc by atmospheric deposition from a foundry was
responsible for the death and slaughter of 140 cows.8* Ingestion of surface
-------
110
deposits of airborne lead on forage, especially adjacent to heavily traveled
highways,82 an
-------
XXX
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1. Clean Air Act (42 U.S.C. 1857 et seq.).
2. 40 CFR 52.21 (o), (p), 45 FR 52675 (Aug. 7, 1980).
3. 40 CFR 51 and 52, 45 FR 52676 (Aug. 7, 1980).
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Control, Vol. 1: Air Pollution, The Chemical Rubber Co., Cleveland, Ohio
(1972) (as cited in Ref. 5).
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Environmental Assessment, Vols, I and n, U.S. EPA Report No. EPA-600/7-
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EPA 450/5-79-008, Research Triangle Park, N.C. (Oct. 1979).
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(May 22, 1980).
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L.F. Soholt, and W.S. Vinikour, A Biologist's Manual for the Evaluation
of Impacts of Coal-Fir'ed Power Plants on Fish, Wildlife, and Their Habi-
tats, U.S. Fish and Wildlife Service Publication No. FWS/OBS-78/75, Ann
Arbor, Mich. (Aug, 1978).
9. Dvorak, A.J., B.G. Lewis, et al, Impacts of Coal-Fired Power Plants on
Fish, Wildlike, and Their Habitats, U.S. Fish and Wildlife Service Report
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cultural Research Council, London (1967).
11. Katy, M., Sulfur Dioxide in the Atmosphre and Its Relation to Plant
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12. Dvorak, A.J. et al., The Environmental Effects of Using Coal for Gene-
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NUREG-0252, Washington, D.C. (June 1977).
13. Vaughan, B.E., K.H. Abei, D.A. Cataldo, J.M. Hales, C.E. Haue, L.A.
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the Environment as a Result of Coal Utilization, Unnumbered Batelle
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(Aug. 1975).
14. White, K.L., A.C. Hill, and J.H. Bennett, Synergistic Inhibition of
Apparent Photosynthesis Rate of Alfalfa by Combinations of Sulfur Dioxide
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in Ref. 15).
-------
112
15. Zaragoza, Larry, U.S. Environmental Protection Agency, personal communi-
cation of tables attached to Environmental Impact Statement for Montana,
Ambient Air Quality Standards Study (Aug. 1980).
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the Potential for SO^-Induced Vegetation Damage in the Evaluation
of Energy Policy Scenarios, Changing Energy Futures, Proceedings of
the Second International Conference on Energy Use Management, R.A. Fazz-
olare and C.B. Smith, eds., Pergamon Press, New York (1979).
17. Materna, J., Criteria for Characterisation of Pollution Damages in
Forests, Proc. Int. Clean Air Congr. 3rd, Dusseldorf, West Germany (1973)
(as cited in Ref. 15).
18. National Research Council, Ozone and Other Photochemical Oxidants,
National Academy of Sciences, Washington, D.C. (1977).
19. Heck, W.W., and D.T. Tingey, Nitrogen Dioxide: Time-Concentration Model
to Predict Acute foliar Injury, U.S. EPA Report No. EPA 600/3-79-057,
Research Triangle Park, N.C. (1979).
20. Taylor, O.C. et aL, Oxides of Nitrogen, in J.B. Mudd and T.T. Kozlowski,
Responses of Plants to Air Pollutants, Academic Press, New York (1975).
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Washington, D.C. (1977).
22. Thompson, C.R., and G. Katz, Effects of Continuous ffgS Fumigation on Crop
and Forest Plants, Envt. Science and Tech. 12:550-553 (May 1978).
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Hydrocarbons, U.S. Department of Commerce, Springfield, Va. PB 190-489
(1970).
24. Stahl, Q.R., Preliminary Air Pollution Survey of Ethylene, U.S. EPA
Report No. APTD 69-35, Research Triangle Park, N.C. (1969) (as sited in
Ref. 5).
25. Jacobson, J.S., and A.C. Hill (eds.), Recognition of Air Pollution Injury
to Vegetation: A Pictorial Atlas, Air Pollution Control Administration,
Agricultural Committee Informative Report No. 1, TR-70, Pittsburgh, Pa.
(1970).
26. National Research Council, Fluorides: Medical and Biological Effects
of Environmental Pollutants, Committee on Biological Effects of At-
mospheric Pollutants, National Academy of Sciences, Washington, D.C.
(1971).
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for Lead, 43 FR 46245 (Oct 5, 1978).
-------
3£fec*a °f Sulfur Oxides in the Atmosphere on Vegetation: Revised
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30. Bull, J.N., and T.A. Mansfield, Photosynthesis in Leaves Exposed to S02
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33. Kress, L.W., and J.M. Skelly, The Interaction of 03, S02, and N02 and
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36. National Research Council, Manganese: Medical and Biological Effects of
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38. Preliminary Investigation of Effects of Boron, Indium, Nickel, Selenium,
Tin, Vanadium, and Their Compounds, Vol. VI, Vanadium, U.S. EPA Report
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39. Costeque, L.M., and T.C. Hutchinson, The Ecological Consequences of
Soil Pollution by Metallic Rust from the Sudbury Smelters , Proc.
Inst. Environ. Sci., 18th Annual Technical Meeting, New York (1972).
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41. Sillampaa, M., Trace Elements in Soils and Agriculture, United National
Food and Agricultural Organization Report, Rome (1976).
42. Budney, Lawrence J., Guidelines for Air Quality Maintenance Planning
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Quality Impact of New Stationary Sources, U.S. EPA Report No. EPA-
450/4-77-001, Research Triangle Park, N.C. (Oct. 1977).
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114
43. General Guidelines Used in Determining "de minimis" Air Quality Impacts
for the Prevention of Significant Deterioration Regulations, Unnumbered
U.S. EPA document, Research Triangle Park, N.C. (Aug. 27, 1979).
44. 40 CFR 51 and 52 in 44 FR 51,924 (Sept. 5, 1979).
45. Monarch, M.R., R.R. Cirillo, B.H. Cho, G.A. Concaildi, A.E. Smith,
E.P. Levine, and K.L. Brubaker, Priorities for New Source Performance
Standards under the Clean Air Act Amendments of 1977, U.S. EPA Report
No. EPA-450/3-78-019, Research Triangle Park, N.C. (April 1978).
46. Guideline on Air Quality Models, U.S. EPA Report No. EPA-450/2-78-027,
Office of Air Quality Planning and Standards Guideline No. 1.2-080,
Research Triangle Park, N.C. (April 1978).
47. Depreciation, Guidelines and Rules, Revenue Procedure 62-21, U.S.
Treasury Department, Internal Revenue Service Publication No. 456,
Washington, D.C. (Revised Aug. 1964).
48. Coffin, D.L. and H.E. Stokinger; Biological Effects of Air Pollutants,
Air Pollution VII, A.C. Stern, ed., Academic Press, New York (1977).
49. Turner, D.B., Workbook of Atmospheric Dispersion Estimates, U.S.
EPA Report No. 999-AP-26, Research Triangle Park, N.C. (May 1970).
50. Ragland, K.W., Worst-Case Ambient Concentrations from Point Sources
Using the Gaussian Plume Model, Atmos. Env., 10:371-374 (1976).
51. Busse, A.D., and J.R. Zimmerman, User's Guide for the Climatological
Dispersion Model, Publication No. EPA-RA-73-024 (NTIS PB 227346), U.S.
EPA, Research Triangle Park, N.C. (1973).
52. Briggs, G.A., Chimney Plumes in Neutral and Stable Surroundings, Atmos.
Env=, 0:507-510 (1972).
53. Briggs, G.A., Plume Rise Predictions, Lectures on Air Pollution and
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can Meteorological Society. Boston, pp. 59-111 (1975).
54. Larsen, R.I., A Mathematical Model for Relating Air Quality Standards,
U.S. EPA Report No. AP-89, Research Triangle Park, N.C. (Nov. 1971).
55. Slade, D.H., Meteorology and Atomic Energy, U.S. Atomic Energy Commis-
sion, Office of Information Services (NTIS TID 24190), Oak Ridge,
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56. U.S. Department of Commerce, Climatic Atlas of the United States, U.S.
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57. Davis, D.D. and H.D. Gerhold, Selection of Trees for Tolerance of Air
Pollutants, Better Trees for Metropolitan Landscapes: Symposium Pro-
ceedings, USDA Forest Service, General Technical Report No. NE-22 (1976),
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58. National Research Council, Nitrogen Oxides, National Academy of Sciences,
Washington, D.C. (1977).
59. Daesler, H.G., Vegetationschaeden ala Falge der Luftwer schutsing, Wiss.
Z. Tech. Univ., Dresden, 20:1171-1173 (1971).
60. Manning, W.J., Bio-environmental Impact of Fine Paniculate Pollutants:
A Summary Document and Critical Review, prepared for U.S. EPA, National
Environmental Research Center, Corvallis, Ore. (Jan. 1975).
61. Glass, N.R., Environmental Effects of Increased Coal Utilisation:
Ecological Effects of Gaseous Emissions from Coal Combustion, U.S. EPA
Report No. EPA 600/7-78-108, Washington, D.C. (June 1978).
62. Li1lie, R.J., Air Pollutants Affecting the Performance of Domestic
Animals - A Literature Review, USDA Agriculture Handbook No. 380,
Washington, D.C. (1970).
63. Phillips, P.H., D.A. Greenwood, C.S. Hobbs, and C.F. Huffman, The
Fluorosis Problem in Livestock Production, NAS-NCR Publ. 381, National
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64. Shupe, J.L., M.L. Miner, L.E. Harris, and D.A. Greenwood, Relative
Effects of Feeding Bay Atmospherically Contaminated by Fluoride
Residue, Normal Say Plus Calcium Fluoride and Normal Hay Plus Sodium .
Fluoride to Dairy Heifers, American Journal of Veterinary Research,
23:777-797 (1962).
65. Allaway, W.H., Agronomic Controls over the Environmental Cycling of Trace
Elements, Advances in Agronomy, 2(7:235-274 (1968).
66. Suttie, J.W., J.R. Carlson, and C.C. Faltin, Effects of Alternating
Periods of High- and Lou-Fluoride Ingestion in Dairy Cattle, J. of
Dairy Science, 55:790-804 (1972).
67. National Academy of Sciences, Effects of Fluorides in Animals,
Washington, D.C. (1974).
68. Phillips, P.H., et al., The Fluorosis Problem in Livestock Production,
a Report of the Committee on Animal Nutrition, NAS-NRC Publ. No. 824
(1960) (as cited in Ref. 9).
69. Formad, R.J., The Effect of Smelter Fumes upon the Livestock Industry
in the Northwest, USDA Pathological Division, Bureau of Animal
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70. Swain, R.E., and W.D. Harkins, Papers on Smelter Smoke: Arsenic in
Vegetation Exposed to Smelter Smoke, J. American Chemical Society,
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71. Bischoff, 0., Poisioning of Domestic Animals through Copper and Arsenic
Containing Fly Dust, Dent. Tierarztl. Wochschr-, 47:442-447 (1939).
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72. Phillips, P.H., The Effects of Air Pollutants on Farm Animals, Air
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74. Frost, D.V., Arsenioals in Biology - Retrospect and Prospect, Federal
Proceedings, 20:194-208 (1967).
75. Sullivan, R.J., Air Pollution Aspects of Arsenic and Its Compounds,
Litton Systems, Inc., Bethesda, Md. (1969).
76. Allcroft, R., Lead as a nutritional Hazard to Farm Livestock IV,
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Various Lead Compounds, J. Comp. Pathol. Exp. Ther., 0(7:190 (1950).
77. Allcroft, F., Lead Poisoning in Cattle and Sheep, Vet. Rec., 05:583-590
(1951).
78. California Air Resources Board, A Joint Study of Pb Contamination
Relative to Horse Deaths in the Area of Southern Solano County (Dec.
1971) (as cited in Ref. 9).
79. Hammond, P.B., and A.L. Aronson, Lead Poisoning in Cattle and Horses
in the Vicinity of a Smelter, Annals of New York Academy of Science,
111:595-611 (1964).
80. Schmitt, N., G. Brown, E.L. Devlin, A.A. Larsen, E.D. McCausland, and
J.M. Saville, Lead Poisoning in Horses, an Environmental Health Hazard,
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81. Vetter, H., Loads and Damage by Heavy Metals in the Vicinity of a Lead
and Zinc Foundry in Lower Saxony, Staub Reinhaltung der Luft (English
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82. Lagerweiff, J.V., Lead, Mercury and Cadmium as 'Environmental Contami-
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85. Bazell, R.J., Lead Poisoning: Zoo Animals May be the First Victims,
Science, 273(3992):130-131 (1971).
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86. Scientific and Technical Assessment Report an Vanadium, U.S. EPA Report
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90. Newman, J.R., Effects of Industrial Air Pollution on Wildlife,
Biological Conservation, 25:181-190 (1979).
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/» TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
EPA*450/1-81-078
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
A Screening Procedure for the Impacts of A1r
Pollution Sources on Plants, Soils, and Animals
'ATE
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
A. E. Smith and J. B. Levenson
B. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
EPA-I6A-79-D-X0764
12. SPONSORING AGENCY NAME AND ADDRESS . _ . .
Office of A1r Quality Planning and Standards
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
JRT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Section 165 of the Clean A1r Act requires preconstructlon review of major
emitting facilities to provide for the prevention of significant deterioration (PSD)
and charges Federal Land Managers (FLMs) with an affirmative responsibility to
protect the air quality-related values of Class I areas. Regulations implementing
these provisions require an analysis of the impairment to visibility, soils, and
vegetation (52.21(o)).
The information and screening procedure presented here provide interim
guidance: (1) to aid in determining whether emissions are significant or
whether there are significant air quality Impacts under Section 52.21(o), and
(2) to aid in flagging sources which should be brought to the attention of
an FLM under Section 52.21(p).
Impacts on vegetation and soils are the principal areas addressed by the
procedure which thus takes a limited view of the possibly broad scope of air
quality-related values. A selected review of impacts on fauna has also been
included and the odor potential of regulated pollutants is addressed. This
procedure is Intended for use by air quality engineers and is not a manual for the
nf Imacts on lants, soils, and other air quality-related values such
17. as would be suitable for an
DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
6F
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report)
None
21. NO. OF PAGES
117
20. SECURITY CLASS (Thispage)
22. PRICE
ERA Form 2220-1 (Rev. 4-77) PREV.OUS ED.T.ON ,.
OBSOLETE
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