Final Report
ECONOMIC IMPACT OF AIR POLLUTANTS
ON PLANTS IN THE UNITED STATES
Prepared for:
COORDINATING RESEARCH COUNCIL
NEW YORK, NEW YORK
CONTRACT CRC-APRAC CAPA-2-68(1-70)
STANFORD RESEARCH INSTITUTE
Menlo Park, California 94025 • U.S.A.
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Final Report
November 1971
ECONOMIC IMPACT OF AIR POLLUTANTS
ON PLANTS IN THE UNITED STATES
By: H. M. BENEDICT, C. J. MILLER, and R. E. OLSON
Prepared for:
COORDINATING RESEARCH COUNCIL
NEW YORK, NEW YORK
CONTRACT CRC-APRAC CAPA-2-68(1-70)
SRI Project LSD-1056
Approved by:
W. A. SKINNER, Executive Director
Life Sciences Division
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III
CONTENTS
I
INTRODUCTION. .
. . . .
. . . . .
. . . .
. . . . .
II
SUMMARY
. . . . .
. . . . . . . . .
. . . . . . . .
METHODS AND RESULTS
. . . .
. . . . . .
. . . . . .
Pollutants Involved . . . . . . . . . .
Intensity of Pollution and Location of Polluted Areas
Value of Vegetation Occurring in Polluted Areas. . . . .
Commercial Crops. . . . . . . . . . . . . . . . .
Forests and Ornamentals. . . . . . . . . . . . . . . .
Sensitivity of Various Plant Species to the Specific
Pollutants. . . . . . . . . . . . . . . . . . . . .
Formulae for Calculating Dollar Loss. . . . . . . . . . .
Dollar Loss . . . . . . . . . . . . . .
IV
DISCUSSION
. . . . . . .
. . . . . .
. . . . . . . . . . .
REFERENCES. . . . . .
. . . . . .
. . . . . . . .
. . . .
ILLUSTRATIONS
1
Isopleths for the Concentration Rate Factor x!q
Exceeded on 10 Percent of Mornings Annually for
10-km City Sizes. . . . . . . . . . . . . . . .
. . . . .
2
Isopleths of the Number of Days in Periods of
Stagnation of at Least Two Days over a Five-Year Period. .
ii
1
4
9
10
10
24
24
26
38
47
59
67
75
15
16
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TABLES
1
Basic Data for Calculating Relative Air Pollution
Potential in Different SMSAs Based on Emissions and
Weather Factors. . . . . . . . . . . . . . . . . .
. . . .
2
Relative Air Pollution Potential in Different SMSAs Based
on Emission times Concentration Factor times Number of
Stagnation Periods. . . . . . . . . . . . . . . . . . . .
Total Area and Population of Pollution-Threatened Counties
as a Percentage of the Respective Totals in Various
Geographical Regions of the United States. . . . . . . . .
Estimated Acreages, Tonnages and Values of Pasture and Hay
in Counties of States where Possible Fluoride Contamination
Exists. . . . . . . . . . . . . . . . . . . . . . . . . .
3
4
5
Number, Area, and Population of Counties Surveyed in Air
Pollution Study as Percent of Total in States. . . . . . .
Potential Annual Value of Forest Land in Pollution-
Threatened Counties. . . . . . . . . . . . . . . .
6
. . . .
7
Estimated Acreages and Annual Costs to Pollution-Threatened
Counties for Maintenance of Trees and Shrubs in Various
Urband Land Uses - 1964 . . . . . . . . . . . . . . . . . .
Estimated Annual Costs to Pollution-Threatened Counties
for Roadside Landscaping - 1964 . . . . . . . . . . . . . .
8
9
Estimated Acreages and Annual Costs to States and
Pollution-Threatened Counties for Maintenance of Trees
and Shrubs in City, County, State, and National Parks -
1964 . . . . . . . . . . . . . . . . . . . . . . . .
10
Estimated Acreages in and Annual Costs to Pollution-
Threatened Counties for Maintenance of Trees and
Ornamentals around Private Residences. . . . . . . . . . .
Estimates of Resistance and Sensitivity of Various Crops
to Different Pollutants. . . . . . . . . . . . . . . . . .
11
12
Estimated Percentages of Crops Lost in Counties Most
Polluted by Ozone, PAN, and Oxides of Nitrogen; Sulfur
Dioxide; and Hydrogen Fluoride. . . . . . . . . . . . . .
Factors to be Applied to Crop and Ornamental Planting
Values when Plants were Exposed to Different Severity
Classes of Oxidants. . . . . . . . . . . . . . . . .
13
11i
12
17
22
27
28
30
33
35
37
39
40
48
53
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TABLES (Concluded)
14
Factors to be Applied to Production Values of Indicated
Crops to Estimate Losses Due to Sulfur Dioxide in
Different Classes of Pollution Potential. . . . . .
Factors to be Applied to Production Values of Various
Crops to Obtain Estimates of Losses Due to Fluorides
Under Different Classes of Fumigation. . . . . . . .
15
16
Estimated Plant Values and Losses from Air Pollution in
Pennsylvania. . . . . . . . . . . . . . . . . . . . . . .
Estimates of Annual Value of Crops and Ornamentals Grown
in Geographic Regions of the United States and Estimated
Losses Due to Air Pollution. . . . . . . . . . . . . . . .
17
18
Estimated Percentage of Crop and Ornamental Values Lost
in Pollution-Threatened Counties and in the Geographic
Regions as a Whole. . . . . . . . . . . . . . . . . . . .
1v
55
57
60
62
66
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I
INTRODUCTION
Public concern, complaints of the agricultural industry, and the
continuing increase in the number of claimed losses have made it impor-
tant to determine the value of losses to crops and ornamentals caused
by air pollutants. This includes identifying the losses caused by each
major pollutant and the geographical areas in which the losses are oc-
curring.
Some gross estimates have been made of economic losses due to air
pollutants but, for the most part, these have been total estimates, and
no attempt has been made to distribute the aggregate loss among farm
crops, forests, ornamental plantings and home gardens, by pollutant or
by geographical region. Thus the proportions of loss that can be as-
cribed to emissions from manufacturing operations, smelting processes,
automobile exhausts, and other sources are not known.
The Coordination Research Council, a nonprofit organization, en-
tered into a contract with Stanford Research Institute to develop gross
estimates of economic losses resulting from the effects of air pollutants
on plants. Monitoring the program is the Coordinating Research Council's
Air Pollution Research Advisory Committee (APRAC), a group of technical
experts from industry and government. Program funding was made available
by the Automotive Manufacturers Association, the American Petroleum In-
stitute and the Environmental Protection Agency. This report describes
the results of the second year's effort.
The objectives of the first year's study were to provide background
information believed helpful and essential to the problem and, based
on this information, to estimate the dollar loss resulting from the ef-
fect of pollutants on plants. As a result of discussions among members
of a Steering Committee consisting of SRI staff and CRC-APRAC personnel,
plans of work were evolved that were generally followed during the course
of the study. The work plan consisted of the following:
1.
Review of methods used by other agencies to estimate crop
losses caused by factors other than air pollutants, such
as plant diseases, insect pests, and adverse weather con-
ditions.
Continuing literature review concerning the relative sen-
sitivity of some 65 different crop and ornamental plants
to various air pollutants.
2.
1
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3.
Listing of potential sources of industrial and domestic
plant-damaging air pollutants by county, and estimating
the severity of the pollution for each county.
Calculation of the economic value of the individual crops
in these counties.
4.
5.
Derivation of formulae for evaluating the dollar loss to
plants as a result of air pollution effects.
Estimation of dollar loss to agricultural crops for each
county by use of the formulae and background data obtained.
6.
During the first year's stidy, the above work plan was followed
and first-estimate values were obtained on the occurrence by county of
air pollution conditions, dollar value and production of crops in these
counties, and the sensitivity of some 65 major crops to air pollutants.
The following formula was developed for estimating the approximate dol-
lar loss of a particular crop due to a particular pollutant.
c p
C = pPQP(Q Q: Q )
where
C = approximate dollar loss
pP = price per unit produced under polluted conditions
QP = number of units produced under polluted conditions
QC = potential units produced under clean conditions.
Essentially, this states that dollar loss is equal to the value of the
crop times the percentage reduction in yield ascribable to the pollutant.
Application of this formula to the sensitive crops in the counties
where pollution occurred resulted in the following estimates of loss to
commercial crops only:
865,000,000 due to oxidants (ozone, PAN, and nitrogen oxides)
3,500,000 due to sulfur dioxide
3,000,000 due to fluorides.
These estimates did not include losses to ornamentals and home plantings.
It was recognized that these were first estimates and that improve-
ments and additions should be made. Some of the more important defi-
ciencies in the first report were' as follows:
2
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1.
2.
Estimates of severity of pollution in various counties
were based on emission data only, and the effects of
meteorological and other factors in concentrating or di-
luting these emissions were not given proper consideration.
In estimating the loss of individual crops, it was as-
sumed that crops considered sensitive to a given pol-
lutant were equally sensitive and those resistant were
equally resistant.
3.
The omission of the losses to ornamental planting was
not overlooked, but time did not permit the acquisition
of the necessary information.
The second year's study was aimed primarily at revising the esti-
mates to correct the deficiencies described in Items 1 and 2 above and
to include estimates of loss to oranmental plants.
This report describes the studies conducted from September 1, 1970
to August 31, 1971, and presents revised estimates of dollar losses due
to oxidants, sulfur dioxide, and fluorides in the United States.
3
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II
SUMMARY
Following the outline of work described in the Introduction, the
activities and results may be summarized as follows.
1. Counties in the United States where the major air pollutants--
oxidants (ozone, PAN, and oxides of nitrogen), sulfur dioxide, and flu-
orides--were likely to reach plant-damaging concentrations were selected.
The selections were made on the assumption that such concentrations of
oxidants and sulfur dioxide were likely to occur in the most populous
counties, i.e., those in the Standard Metropolitan Statistical Areas
(SMSAs), where fuel consumption was the greatest and hence the emissions
of these compounds or their precursors to the atmosphere would also be
the greatest, and in counties containing large single-source emitters of
sulfur dioxide (such as power plants and copper smelters) or of fluo-
rides (such as aluminum, phosphate and ceramic plants).
2. The relative potential severity of the pollution in each county
was then estimated. The severity of the oxidant pollution was derived
by first estimating, from fuel consumption data, the tons of hydrocarbons
and oxides of nitrogen (the precursors of oxidants) emitted per square
kilometer per day. These emissions values were then multiplied by a
factor related to area of the county or SMSA and by a concentration rate
factor (designated x/q). The product of these multiplications yielded a
value indicative of the relative concentration of oxidant that might be
reached in a single pollution episode. These values were again multi-
plied by the number of days involved in pollution episodes over a five-
year period, which yielded a value indicative of the overall plant-
damaging potential for oxidant pollution in the various counties.
The same procedure was followed for estimating the plant-damaging
potential for sulfur dioxide pollution in the various counties, but the
effect of large single-source emitters in the counties was also taken
into consideration.
For fluorides, the relative plant-damaging potential was based on
the number, type and size of large single-source emitters present.
After arranging the counties in order of severity of potential
plant-damaging pollution, they were then grouped into classes of varying
severity. For oxidants, seven classes were developed, ranging from those
counties where the pollution potential was greatest to those where no
pollution potential seemed to exist. Those counties with sulfur dioxide
plant-damaging potential were split into six classes and those with flu-
oride potential, into four classes.
3. The dollar value of grass hay produced and of pastures (as hay
equivalent) in the potentially polluted counties was calculated. With
these results, the crop value estimates were completed for the counties
where damage to vegetation seemed likely to occur as a result of air pol-
lutants.
4
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4. Estimates of the potential annual value of forests and the an-
nual maintenance costs of ornamental plantings were completed. To com-
plete these estimates, it was necessary to determine the dollar values
for the states (in most instances, the only data available) and then to
prorate this value to the polluted counties on the basis of their pro-
portionate area, population, or combination of area and population of
the state. Separate estimates were made for oxidant-, sulfur dioxide-,
and fluoride-polluted counties. Similarly, these valuations were made
for commercial and noncommercial forests, and for the ornamentals found
on the grounds of educational institutions, industrial parks, golf
courses, roadside landscaping, private residences, and city, county,
state and sectional parks.
5. Tables showing the relative sensitivity of different plant spe-
cies to oxidants, sulfur dioxide and fluorides were prepared and updated
as a result of a continuing literature review. From these relative sen-
sitivities, tables were prepared indicatin~for each pollutant, the per-
centage loss that might be expected to crops and ornamental plantings in
the most severely polluted counties.
6. With this table as background, tables were then prepared show-
ing the percentage loss that might be expected to crops and ornamentals
in counties in the different pollution classes described in Item 2 above.
Obviously, information was not available on all the crops for the three
major pollutants. However, loss factors were compiled for 62 species or
groups of species for oxidant exposures, 63 for sulfur dioxide exposures,
and 36 for fluoride exposures.
7. These factors were then applied to value of the crops, forests,
and ornamentals grown in the polluted counties, and the dollar loss
value for each crop in each county was recorded. These values were added
to obtain the state, regional, and national values.
8. The estimates derived were then compared with similar estimates
made for California and Pennsylvania as a result of on-the-spot surveys
by agricultural experts in the respective states.
5
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The various steps for estimating dollar loss value may be summa-
rized as follows:
Oxidants
Emissions* X Concentrationt X Area* X Episode Days$ = Pollution Potential
Rate Factor (7 classes)
Sulfur Dioxide
Concentration
Emissions X X Area X Episode Days
Rate Factor
+
Emissions from various types and sizes of large
single sources
= Pollution Potential
(6 classes)
Fluorides
Emissions from various types and sizes of large
single sources
=
Pollution Potential
(4 classes)
Oxidants, Sulfur Dioxide and Fluorides
Crop Value X Crop Sensitivity X Pollution Potential = Dollar Loss
Pollution
Ornamental Value X Ornamental Sensitivity X = Dollar Loss
Potential
*
Tons of hydrocarbons or oxides of nitrogen emitted per square
kilometer per day.
tA factor indicative of the tendency of climatic
concentrate pollutants during an air-stagnation
text for further explanation.
conditions to
period. See
*
Square of the radius of the SMSA, assuming the area is circular.
$Number of days occurring in stagnation periods of two or more
successive days.
6
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As a result of the various investigations described above, 551 of
the 3,134 counties in the United states were selected as having poten-
tial plapt-damaging exposure to oxidants, sulfur dioxide and fluorides.
Of these, 327 would be exposed to oxidants, 336 to sulfur dioxide, and
86 to fluorides. (Some counties would be exposed to two or more.) On
the basis of area and population in these counties, it was estimated
that about 9i of the area and 62% of the population occurred in counties
likely to have plant-damaging oxidant pollution. The respective values
were 13i and 54% for sulfur dioxide and 4i and 9i for fluorides. It was
further calculated that 27~ of the dollar value of crops grown in the
United States occurred in the 551 pOllution-threatened counties. The
highest percentages were found in the Middle Atlantic States and the
lowest in the West North Central States.
Based on estimates of losses found to occur to various crops and
ornamentals in the most severely polluted counties, tables were prepared
showing the factors to be applied to values of crops and ornamentals
grown in the different classes of counties. This procedure gave the
estimated loss to a specific crop in the various counties due to oxi-
dants, sulfur dioxide or fluorides.
The values of crops grown in the various counties had been pre-
viously compiled except for grass hay and pastures, which were calcu-
lated during the past year. The estimated values were 5166 million for
pastures and 512 million for grass hay in counties where a fluoride pol-
lution potential existed.
The total potential annual value for commercial forests in the pol-
luted counties was estimated to be about 5130 million, with California
having the highest value and North Dakota the lowest.
The total maintenance values for ornamental plantings in the pol-
luted counties were estimated to be 51,281 million for the United States.
The values for the various categories were: cemeteries, educational in-
stitutions, industrial parks, and golf courses, 5452 million; roadside
landscaping, 531 million; city, county, state and national parks, 5194
million; private residences, 5604 million.
When the loss factors for the various pollution intensities were
applied to the crop and ornamental values, the total annual dollar loss
to crops in the United States was calculated to be about S85.5 million,
of which 578 million was due to oxidants, 53.25 million to sulfur di-
oxide, and S4.25 million to fluorides. The loss to ornamentals was cal-
culated to be about 546 million, of which 543 million was ascribable to
oxidants, 53 million to sulfur dioxide, and 5175 thousand to fluorides.
The SRI estimates of crop loss in California fell between two such
yearly loss estimates developed from on-the-spot estimates by the Cali-
fornia Department of Agriculture. Loss estimates for Pennsylvania for
two years were compiled by the Center for Air Environment Studies of Penn-
sylvania State University from on-the-spot surveys by trained observers.
7
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The SRI loss estimates for Pennsylvania were somewhat higher in one year
and substantially higher in the second year than the estimates made by
the Pennsylvania group. These comparisons seem to indicate that the
loss levels estimated in this report are reasonable; if anything, they
may be high--at least for oxidants.
One of,the minor objectives of this report was to arrive at some
estimate of amounts of loss occurring that might be ascribable to auto
exhausts. This depends on whether oxides of nitrogen or hydrocarbons
are more important in determining the amount of ozone and PAN produced
in the atmosphere. If oxides of nitrogen are the important feature,
then the automobile may be responsible for about 830 million of the crop
loss, or approximately 35%; if hydrocarbons are the important compounds,
they could be responsible for 860 million of the crop loss for the coun-
try as a whole. These ratios would be different in different sections
of the country. For example, the automobile contribution to hydrocarbons
is much lower in the eastern part of the United States than on the West
Coast.
The greatest percentage of loss due to pollutants occurred in
heavily industrialized areas of the Middle Atlantic and East North
tral States. The lowest amount of loss occurred in the West North
tral States, i.e., Missouri, Iowa, Kansas, Nebraska, Minnesota and
Dakotas.
the
Cen-
Cen-
the
The dollar loss as a percentage of the total dollar value of all
commercial crops grown in the United States was about 0.5%. Losses due
to plant diseases and insects have been placed at 10-12% and those due
to weeds, at 6-8%. Estimates of losses due to these pests are not avail-
able for ornamentals.
In conclusion, it must be pointed out
mates presented in this report seem valid,
and, as such, are subject to revision when
formation become available.
that although the loss esti-
they are still only estimates
more reliable sources of in-
8
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III
METHODS AND RESULTS
The same general plan of work was followed in the second year as
in the first, except that no further effort was made to develop methods
of estimating losses based on experience of investigators in other fields.
Previous discussion and studies had indicated that there was no simple
method and that, to be reliable, estimates almost had to be made from
personal observation and experience. The other phases of the work plan
were followed. The data from which the emissions of hydrocarbons and
oxides of nitrogen were calculated are for the year 1963. The crop pro-
duction by county was taken from the 1964 Census of Agriculture. 1 These
were the latest data available at the time these studies were initiated.
The order in which the results are presented has been changed to
that given below:
Pollutants Involved
Nature
Relative intensity of pollution
Regional distribution of pollution
Vegetation Occurring in Polluted Areas
Crops
Types
Yield
Dollar value
Forests
Yield
Dollar value
Ornamental Plantings
Types
Replacement and maintenance costs
Sensitivity of Various Species to the Specific Pollutants
Relative sensitivity
Percentage yield loss under severest condition
Formulae for Calculating Dollar Loss Due to Pollutants
Dollar Loss
By pollutant
By crop
By area
9
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Pollutants Involved
The compounds
vegetation, either
by their effect on
in the atmosphere that cause the greatest damage to
directly by reduced yield and growth or indirectly
the quality of the crop, are:
Ozone
Peroxyacetyl nitrate
Oxides of nitrogen
Sulfur dioxide
Fluorides
(PAN)
Since these pollutants produce well over 90% of the losses to vege-
tation caused by air pollutants, this study has been confined to their
effects. However, two of the pollutants--ozone and PAN--are formed as
a result of photochemical reactions between hydrocarbons and oxides of
nitrogen and are not emitted directly into the atmosphere. Controlled
experiments have not given definitive answers as to whether oxidant con-
centrations developing as a result of the interaction are more readily
related to the hydrocarbons or to the oxides of nitrogen concentration.
However, it has been possible to demonstrate a relationship between the
maximum oxidant level reached in anyone day and the hydrocarbon concen-
tration in the atmosphere between 6:00 and 9:00 a.m.2 Therefore, hydro-
carbons were used in estimating the relative severity of oxidant pollu-
tion. But a review of the ratings based on oxides of nitrogen shows
that there would be only minor changes in the relative ratings assigned,
the most notable changes being a decrease in the estimated relative
severity of pollution in West Coast cities, such as San Jose, Portland
and Seattle, and a slight increase in the large eastern cities.
Intensity of Pollution and Location of Polluted Areas
In the 1970 report, counties were listed where air pollution prob-
lems seemed likely to exist, based primarily on population density
(Standard Metropolitan Statistical Areas) for ozone, PAN, oxides of ni-
trogen and sulfur dioxide, and on industrial operations for sulfur di-
oxide and fluorides. Estimates of emission of hydrocarbons, oxides of
nitrogen, and sulfur dioxide in the SMSAs were calculated from fuel
consumption in those areas. These emission values were expressed simply
as the total number of tons per day by county, not by unit area. Such
forms of expression did not take into account the area over which the
pollutants might be emitted or the effect of meteorological conditions
in either dispersing or concentrating the emissions. Consequently, some
revisions were made in these estimates, as follows.
SRI's hydrocarbon estimates were observed to be lower than other
estimates where such comparisons could be made (Los Angeles County, for
example). It was subsequently determined that these lower values were
due to an improper factor applied to gasoline consumption to provide
figures for hydrocarbon emissions. An appropriate change in this factor
10
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increased the figure for hydrocarbon emissions from auto exhausts by 70%.
The hydrocarbon emissions for SMSAs were therefore recalculated.
Estimates of hydrocarbons, oxides of nitrogen, and sulfur dioxide
have now been expressed in tons per unit area per day rather than as
simple total emissions per day or year. The results, in tons per day
per square kilometer, are shown in Columns 2, 3, and 4 of Table 1.
A recent paper by Ho1zworth3 derives concentration rate factors due
to meteorological conditions. These rate factors, designated as x/q and
expressed as seconds per meter, are a measure of the tendency of mete-
orological conditions to affect the concentration of pollutants emitted
to the atmosphere. Thus,
x/q = time
height
weight
emission =
time X area
time X weight - weight
= concentration
height time X area - volume
The Holzworth paper presents a map showing how these concentration rate
factors vary in different parts of the United States. This map is es-
sentially reproduced in Figure 1. The relative concentration rate fac-
tors for the various SMSAs are given in Column 5 of Table 1. However,
in the table, x/q values of 0-19 are designated as 1, 20-39 as 2, 40-59
as 3, 60-79 as 4, and 80 and over as 5.
Holzworth's paper further indicates that the size of the area over
which the emissions are occurring also affects the ultimate concentration.
The areas of the SMSAs are given in City and County Data Book, 1962,
U.S. Dept. of Commerce.4 It was assumed that these areas were circular,
and the radius of each was calculated. The calculated radii were then
assigned relative values as follows: 5-14 km = 1, 15-24 km = 2, 25-34 km
= 3, etc. These relative radii values are given in Column 6 of Table 1.
The Holzworth paper also presents a map showing the number of days
in a five-year period that were included in atmospheric stagnation periods
of at least two days' duration. These isopleths, which are indicative of
the relative number of days that might be included in pollution episodes
occurring in each SMSA in five years, have been replotted in Figure 2.
These values for each SMSA have also been listed in Column 7 of Table 1.
By multiplying the emission of each pollutant by the relative x/q
values by the radius of the SMSA (Column 2, 3 or 4 by Column 5 by Column
6, Table 1), a value is obtained indicating the relative concentration
that might occur during any pollution episode. When this product is
multiplied by the number of episode days (Column 7, Table 1), a value
representing the overall relative severity of plant-damaging pollution
for each SMSA is obtained. These overall pollution values for hydro-
carbons, oxides of nitrogen, and sulfur dioxide are shown in Table 2.
11
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Table 1
BASIC DATA FOR CAU:ULATING RELATIVE AIR POLLUTION POTENTIAL IN
DIFFERENT SMSAs BASED ON EMISSIONS AND WEATHER FACTORS
Emissions (tons/km2/day) Weather Factors
Hydro- Oxides of Sulfur - -a Radius Episode
x/q
SMSA carbons Nitrogen Dioxide Value Valueb DaysC
(1) (2) (3) (4) ~ (6) (7)
Akron 0.047 0.034 0.132 3 3 50
Albany - Schenectady -
Troy .0205 .024 0.098 4 4 25
Allentown - Bethlehem -
Easton .028 .025 0.146 3 3 25
Atlanta .046 .021 0.061 2 4 50
Baltimore .054 .048 0.257 4 4 50
Birmingham .033 .035 0.081 4 3 75
Boston .142 .217 0.410 2 3 25
Bridgeport .127 .073 0.086 2 1 25
Buffalo .044 .029 0.092 2 4 50
Canton .039 .024 0.068 3 2 50
Chattanooga .0200 .0089 0.029 4 3 75
Chicago .098 .0703 0.309 3 6 50
Cincinnati .029 .029 0.162 3 4 75
Cleveland .078 .052 0.159 2 4 50
Columbus .038 .015 0.025 3 4 50
Dallas .024 .012 O. 00077 2 5 1
Dayton .029 .019 0.078 2 4 25
Denver .017 . 0077 0.028 2 5 100
Detroit .138 .088 0.310 2 4 50
Flint .024 .0093 0.024 3 3 50
Ft. Worth .027 .014 O. 00077 2 4 1
Gary - Hammond -
E. Chicago .044 .058 0.238 3 3 50
Grand Rapids .023 .012 0.043 3 3 25
Greensboro - High Point .026 .0089 0.016 3 2 50
Hartford .068 .031 0.097 2 2 25
12
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Table 1 (continued)
Emissions (tons/km2/day) Weather Factors
Hydro- Oxides of Sulfur -/Q~ Radius Episode
x q
SMSA carbons Nitrogen Dioxide Value Valueb DaysC
(1) (2) (3) (4) ~ (6) (7)
Houston 0.018 0.015 0.000502 2 7 25
Indianapolis .026 .014 0.065 2 5 50
Jersey City .633 .725 3.360 2 1 25
Kansas City .029 .014 0.016 2 5 25
Lancaster .018 .012 0.054 4 3 50
Lawrence - Haverhi11 .163 .073 0.304 2 1 25
Los Angeles - Long
Beach .120 .059 0.024 3 6 300
Louisville .055 .056 0.286 3 3 75
Memphis .017 .020 0.038 4 3 75
Miami .033 .014 0.010 1 4 25
Milwaukee .074 .051 0.278 3 3 50
Minneapolis - St. Paul .051 .027 0.065 4 4 25
Nashville .021 .017 0.097 4 4 50
New Haven .083 .052 0.153 2 1 25
New Orleans .025 .021 0.00058 2 4 100
New York .205 .132 0.539 2 4 25
Newark .149 .095 0.377 2 2 25
Paterson - Clifton -
Passaic .186 .096 0.382 2 2 25
Philadelphia .039 .042 0.215 3 5 50
Pittsburgh .045 .059 0.263 4 5 50
Portland .014 .00502 0.108 4 5 200
Providence .062 .039 0.179 2 2 25
Reading .025 .025 0.198 3 3 50
Richmond .026 .019 0.107 3 3 50
Rochester .017 .0093 0.046 2 4 50
St. Louis .051 .025 0.113 2 6 50
San Diego .015 .069 0.00208 4 6 400
San Francisco -
Oakland .069 .038 0.019 3 5 300
San Jose .039 .012 0.0012 3 3 300
Seattle .017 .0062 0.017 2 6 100
13
-------
Table 1 (concluded)
Emissions (tons/km2/day) Weather Factors
Hydro- Oxides of Sulfur 'X/ija Radius Episode
SMSA carbons Nitrogen Dioxide Value Valueb DaysC
(1) (2) (3) (4) ~ (6) (7)
Springfield 0.046 0.035 0.215 2 2 25
Syracuse .014 .0085 0.041 3 4 50
Toledo .028 .017 0.063 2 4 50
Utica - Rome .00734 .0031 0.014 3 5 50
Washington, D. C. .081 .035 0.128 4 4 50
Wichita .019 .012 0.00506 2 4 25
Wilmington .032 .024 0.094 3 3 50
Worcester .065 .025 0.080 2 2 25
York .013 .014 0.082 4 3 50
Youngstown .031 .029 0.086 3 3 50
a. Holzworth3 presents factors of X/q = seconds per meter of values
21-40, 41-60, 61-80, 81+ for cities with a radius of at least 10
For comparative purposes, these have been designated 1, 2, 3, 4,
respectively.
0-20,
km.
and 5,
b. The distance over which the pollutants pass is related to the total
concentration build-up, so radii of metropolitan areas are designated
as follows: 5-14 km = 1, 15-24 km = 2, 25-34 km = 3, etc.
c. Number of days in a five-year period of limited dispersion.
14
-------
......
C11
re
- -
40
- --
--
20 40
J
-~--- _1
\
\
__h_\ ,.--, J'-'
(7~ -',
f-
\j ,,;p.//
,y
40 r 20
\\
FIGURE 1
ISOPLETHS FOR THE CONCENTRATION RATE FACTOR x/q EXCEEDED ON 10 PERCENT
OF MORNINGS ANNUALLY FOR 10-km CITY SIZES
-------
I-'
0)
I
I
I "
25
''''-..../'--)7
/~ /?
/ ./ t-- --~1
~:: '-/ ~-,
-'--, .-~
- ----j
\.,
'..
.;,'
l, -
,
-,
\
< )
\..--:>'
FIGURE 2
ISOPLETHS OF THE NUMBER OF DAYS IN PERIODS OF STAGNATION OF AT LEAST TWO
DAYS OVER A FIVE-YEAR PERIOD
-------
Table 2
RELATIVE AIR POLLUTION POTENTIAL IN DIFFERENT SMSAs BASED ON EMISSION
TIMES CONCENTRATION FACTOR TIMES NUMBER OF STAGNATION PERIODS
SMSA
Hydrocarbons
Los Angeles -
San Francisco
San Diego
San Jose
Chicago
Long Beach
- Oakland
Washington, D.C.
Portland
Detroit
Jersey City
Pittsburgh
Baltimore
New York
Louisville
Milwaukee
Cleveland
St. Louis
Birmingham
Philadelphia
Cincinnati
Columbus
Boston
Akron
Seattle
Minnesota - St. Paul
New Orleans
Gary - Hammond -
E. Chicago
Relative
Potential
Relative
Potential
SMSA
Hydrocarbons (continued)
648 Paterson - Cli fton -
311 Passaic 19
144 Atlanta 18
105 Chattanooga 18
88 Buffalo 18
65 Denver 17
56 Nashville 17
52 Memphis 15
48 Newark 15
45 Wilmington 14
43 Youngstown 14
41 Indianapolis 13
38 Canton 12
33 Richmond 12
31 Reading 11
31 Toledo 11
30 Flint 11
29 Lancaster 11
26 Syracuse 8
23 Albany - Schenectady -
Troy 8
21
21 Lawrence - Haverhill 8
20 Greensboro - High Point 8
20 York 8
20 Kansas City 7
Hartford 7
20
17
-------
SMSA
Hydrocarbons (concluded)
Rochester
Worcester
Bridgeport
Allentown -
Easton
Houston
Bethlehem -
Providence
Dayton
Utica - Rome
Grand Rapids
Springfield
New Haven
Wichita
Miami
Dallas
Ft. Worth
Oxides of Nitrogen
Los Angeles -
San Francisco
San Diego
Chicago
Pittsburgh
Long Beach
- Oakland
Jersey City
Baltimore
Louisville
Detroit
Boston
San Jose
Philadelphia
Birmingham
Washington, D.C.
New York
Table 2 (continued)
Relative
Poten tial
7
7
6
6
6
6
6
5
5
5
4
4
3
<1
<1
319
171
66
63
59
54
38
37
35
32
32
32
32
28
26
SMSA
Relative
Potential
Oxides of Nitrogen (continued)
Cincinnati
Gary - Hammond -
E. Chicago
Milwaukee
Cleveland
Portland
Memphis
New Orleans
Akron
St. Louis
Nashville
Youngstown
Buffalo
Reading
Minneapolis
Wilmington
- St. Paul
Paterson - Clifton -
Passaic
Albany - Schenectady -
Troy
Newark
Columbus
Richmond
York
Atlanta
Chattanooga
Denver
Seattle
Canton
Lancaster
Indianapolis
Toledo
Allentown - Bethlehem -
Easton
18
26
26
23
21
21
18
17
15
15
14
13
12
11
11
11
10
10
10
9.
9
8
8
8
8
7
7
7
7
7
6
-------
SMSA
Table 2 (continued)
Relative
Potential
Oxides of Nitrogen (concluded)
Houston
Syracuse
Flint
Providence
Dayton
Rochester
Lawrence - Haverhill
Bridgeport
Springfield
Kansas City
Hartford
Grand Rapids
Greensboro -
New Haven
Worcester
High Point
Wichita
Utica - Rome
Miami
Dallas
Ft. Worth
Sulfur Dioxide
Chicago
Pittsburgh
Jersey City
Bal timore
Louisville
Philadelphia
Cincinnati
Los Angeles -
Milwaukee
Detroit
Long Beach
5
5
4
4
4
4
4
4
4
4
3
3
3
3
3
2
2
1
<1
<1
278
263
252
206
193
161
146
130
125
124
SMSA
Relative
Potential
Sulfur Dioxide (continued)
New York
Gary - Hammond
Washington, D.C.
Reading
San Fr3ncisco - Oakland
Nashville
Birmingham
St. Louis
Cleveland
Boston
Akron
York
Richmond
Portland
Wilmington
Albany - Schenectady -
Troy
Youngstown
Paterson - Clifton -
Passaic
Newark
Buffalo
Memphis
Allentown - Bethlehem -
Easton
Indianapolis
Lancaster
Denver
Chattanooga
Minneapolis
Toledo
Syracuse
Atlanta
- St. Paul
19
108
107
102
89
86
78
72
68
64
62
59
49
48
44
42
39
39
38
38
37
34
33
33
32
28
27
26
25
25
24
-------
SMSA
Table 2 (concluded)
Relative
Potential
Sulfur Dioxide (concluded)
Springfield
Canton
Seattle
San Diego
Rochester
Providence
Dayton
Lawrence -
Columbus
Flint
Have rhil 1
Utica - Rome
Hartford
Grand Rapids
Worcester
New Haven
Greensboro -
Bridgeport
Kansas City
San Jose
Wichita
High Point
New Orleans
Houston
Miami
Ft. Worth
Dallas
22
20
20
20
18
18
16
15
15
11
11
10
10
8
8
5
4
4
3
1
<1
<1
1
<1
<1
20
-------
Thus calculated, the data indicate that Los Angeles is much above any
other area in terms of potentially high atmospheric concentrations of
hydrocarbons and oxides of nitrogen, and that the West Coast cities show
potential pollution greater than would be expected based on size alone.
In terms of sulfur dioxide emissions, Chicago seems to have the
greatest potential for pollution. In general, the big industrial cities
of the Eastern and Central States (New York, Pittsburgh, Louisville,
Cincinnati, Detroit and Chicago) appear to have a potential for sulfur
dioxide pollution much greater than that for the West Coast cities,
except in some cases for Los Angeles.
Table 2 gives the relative potential pollution intensity for vari-
ous hydrocarbons, oxides of nitrogen, and sulfur dioxide in various
SMSAs throughout the country. As indicated earlier, the hydrocarbons
and oxides of nitrogen react to form ozone and PAN. Oxides of nitrogen
themselves may produce some injury. Since it is difficult to separate
the effects of ozone, PAN, and oxides of nitrogen, they have been lumped
together under the term "oxidants" as a causative agent. The SMSAs in-
clude most counties where injury due to photochemical smog is likely to
occur. However, there are other sources of sulfur dioxide in isolated
areas that emit plant-damaging amounts; these sources, as well as sources
of vegetation-damaging fluorides, were not included in the SMSA data in
Tables I and 2.
In the 1970 Annual Report (Volume I), Table 6 listed, by state and
county, the types of activity that contribute to the five pollutants
under consideration. The table indicated whether or not the county was
in an SMSA and showed the number of iron and steel mills, power plants
with over 100-kw capacity, oil refineries with a capacity over 20,000
barrels per day, copper, lead and zinc smelters, and phosphorus, phos-
phate and aluminum plants, all of which are major emitters of sulfur
dioxide and fluorides. More than 550 counties were tabulated by state,
and their respective areas and populations were calculated as a percent-
age of the state total and United States total. These values (shown in
Table 5) were useful in calculating dollar value of various ornamental
crops, as described later. However, very often several counties were
subjected to all five pollutants or perhaps only one of them. To obtain
a better idea of the regional distribution of the areas in which plant-
damaging pollution seemed likely to occur, the areas (miles2) of the
counties polluted by the different pollutants in the various main geo-
graphic sections of the country were calculated as well as the percent-
age of the total area of the region containing the selected counties.
Similar values were calculated for the number of people residing in
these counties. These data are shown in Table 3. The states included
in the various regions are as follows:
21
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Table 3
TOTAL AREA AND POPULATION OF POLLUTION-THREATENED COUNTIES AS A PERCENTAGE
OF THE RESPECTIVE TOTALS IN VARIOUS GEOGRAPHICAL REGIONS OF THE UNITED STATES
Pollution-Threatened Area
Total Area Thousand Square Mil es Percent of Total Area
Region (000 sq mi) Oxidants" ~ Fluorides Oxidants ~ Fluorides
New England 63.0 13.8 11.0 0.0 21.9 17.5 0.0
Middle Atlantic 100.4 31.3 28.7 2.6 31.2 28.6 2.6
East North Central 244.4 39.7 50.6 7.8 16.2 20.7 3.2
West North Central 507.3 28.4 48.8 4.5 5.6 9.6 0.9
South Atlantic 267.5 34.9 41.9 10.2 13.1 15.6 3.8
East South Central 179.4 14.2 20.0 3.7 7.9 11.1 2.1
West South Central 429.3 37.9 50.9 11.3 8.8 11.9 2.6
Mountain 856.6 50.5 133.3 29.5 5.9 15.6 3.4
Pacific 319.4 81.8 71.1 56.7 25.6 22.3 17.8
Hawaii 6.4 0.6 0.6 0.0 9.4 9.4 0.0
Alaska 566.4 ~ ~ 0.0 0.0 0.0 ~
3,540.1 333.1 456.9 126.3 9.4 12.9 3.6
Population of Pollution-Threatened Counties
Total Percent of
Population Millions Total Population
(millions) Oxidants ~ Fluorides Oxidants ~ Fluorides
New England 10.5 8.6 7.5 0.0 81.9 71.4 0.0
Middle Atlantic 34.2 25.7 23.0 0.7 75.1 67.3 2.0
East North Central 36.2 24.5 21.8 4.0 67.7 60.2 11.0
West North Central 15.4 5.7 5.9 1.7 37.0 38.3 11.0
South Atlantic 26.0 12.8 10.9 2.5 49.2 41.9 9.6
East South Central 12.1 4.8 3.8 0.3 39.7 31.4 2.5
West South Central 17.0 8.6 7.6 2.1 50.6 44.7 12.4
Mountain 6.9 3.3 3.0 0.9 47.8 43.5 13.0
Pacific 20.3 16.2 12.7 4.2 79.8 62.6 20.7
Hawaii 0.6 0.5 0.5 0.0 83.3 83.3 0.0
Alaska 0.2 ~ ~ 0.0 0.0 ~ ~
179.4 110.7 96.7 16.4 61.7 53.9 9.1
a. Os, PAN, and NOx'
22
-------
New England:
Middle Atlantic:
East North Central:
West North Central:
South Atlantic:
East South Central:
West South Central:
Mountain:
Pacific:
Maine, Vermont, New Hampshire, Massachusetts,
Rhode Island, Connecticut
New York, New Jersey, Pennsylvania
Ohio, Indiana, Illinois. Michigan, Wisconsin
Missouri, Iowa, Minnesota, Kansas, Nebraska,
South Dakota, North Dakota
Delaware, Maryland, West Virginia, District
of Columbia, Virginia, North Carolina, South
Carolina, Georgia, Florida
Kentucky; Tennessee, Alabama, Mississippi
Arkansas, Louisiana, Oklahoma, Texas
Montana, wyoming, Colorado, New Mexico, Ari-
zona, Nevada, Utah, Idaho
California, Oregon, Washington, Hawaii
As would be expected, the highest percentages of land in counties
with oxidant or sulfur dioxide pollution sources are found in the heavily
populated, industrialized regions--the Middle Atlantic, New England, East
North Central, and Pacific. The lowest percentage of land involved in
oxidant pollution is in the agricultural areas such as the West North
Central. In general, the areas in counties where S02 sources are present
are larger than those containing oxidant sources. This difference is sur-
prisingly large, however, in the Mountain region. This is due to the
large number of copper, lead, or zinc smelters in that region; these
smelters emit sulfur dioxide but are not main sources of oxidants.
The area exposed to sulfur dioxide fumigations is found in counties
that constitute about 12.9% of the land area of the United States; the
corresponding value for oxidants is 9.4% and for fluorides, 3.6%. Most
of the fluoride-fumigated area is found in the State of Washington be-
cause of the large number of aluminum plants.
Although the land area over which plant-damaging concentrations of
oxidants might be found is only 9.4% of the area of the United States,
62% of the population resides in these counties. This means that although
crop production may be low, the value of ornamental plantings around homes.
parks, etc. will be correspondingly high. This relation between orna-
mental plantings and population was the only reason for presenting these
figures.
Many of the counties involved were both in a metropolitan statistical
area and had sulfur dioxide sources. If only the significant sources of
S02 outside the SMSA are considered, the area is cut about in half (to
6.7%) and the population involved drops from 53.9% to 6.4% on a nation-
wide basis. This method of calculating eliminated most of the power plant
sources, which are so closely tied up with power requirements of large
23
-------
population centers, and left mostly large industrial sources such as
iron and steel plants, nonferrous smelters, and oil refineries.
In general, these data show that the air pollution of concern is
centered in the heavily populated areas. Fluoride is an exception in
that counties with fluoride sources seem to be in less densely popu-
lated areas. This is true because the major fluoride-emitting sources
are constructed where electrical power is plentiful.
Value of Vegetation Occurring in Polluted Areas
Commercial Crops
To estimate dollar loss due to air pollutants, it is necessary to
know the dollar value of the vegetation and the percentage loss that
may be ascribed to the pollutant. The dollar value of commercial crops
growing in the potentially polluted counties was given by county in the
1970 Annual SRI Report (Vol. II), based on data available from the 1964
Census of Agriculture. This value was based on the prices paid the
farmer. No adjustment has been made in prices on any assumed basis of
shift in the effective supply curve due to the smaller supplies being
available to the market as a result of the pollution loss. Such an ad-
justment would be difficult to make with any degree of accuracy-
Air pollution increases production costs in commercial agriculture,
thus affecting both producer and consumer. The effect on the producer
will be greater in a heavily polluted area than in an area where there
is only light pollution, as the production costs per ton of crop har-
vested will be much higher in the heavily polluted area. In the same
way, unit production costs of crops that respond more sharply to a cer-
tain degree or kind of air pollution in an area will be higher than
unit production costs of crops that show little or no response to the
pollution.
The burden of increased costs due to pollution will ordinarily be
shared between producer and consumer. To the extent that the supply
curve for a crop is elastic and the demand curve is inelastic, in a
year when there is a smaller crop than normal, then pollution may force
the consumer to absorb most of the increased costs. If the crop is
larger than normal, then pollution costs may have to be absorbed almost
entirely by the producer, as market prices will not rise higher than
normal. If the demand for a crop is relatively more elastic than the
supply, however; then the producer will have to bear most of the burden
of increased costs in any case.
The 1967 cost at retail of the "farm food market basket" was
81,080; the farm value of the same commodities was 8414.5 ConsequentlYI
the increase in retail value over farm prices amounted to 161%. While
all the discussions of crop values and pollution loss values that fol-
low are based on farm prices, the reader should not forget that the value
24
-------
of crops at the consumer level could also have been used, with equal
validity, and in that case the absolute level of the values would have
been increased very substantially.
It is not necessary to report again the figures given in the 1970
report, but the dollar value of commercial crops in potentially polluted
counties in different regions of the United states, the value in the en-
tire region, and the percentage the polluted value is of the total are
shown below.
Value in Value in
Region Polluted Area Total Area Percent
New England 8 106,000,000 8 326,000,000 33
Middle Atlantic 481,000,000 768,000,000 63
East North Central 1,091,000,000 2,708,000,000 40
West North Central 385,000,000 2,751,000,000 14
South Atlantic 498,000,000 3,449,000,000 14
East South Central 196,000,000 1,127,000,000 17
West South Central 466,000,000 2,353,000,000 20
Mountain 301,000,000 1,011,000,000 30
Pacific 1,125,000,000 3,607,000,000 31
84,649,000,000 818,100,000,000 27
Thus, in the heavily industrialized Middle Atlantic and East North
Central States, the value of crops grown in areas where air pollution is
likely to occur represents 45% of the total value of the crops grown in
those regions. However, in the heavily agricultural areas of the cen-
tral and southern states, the value of crops grown in polluted counties
represents about 15% of the total value of the crops produced, and the
total value in this area represents about 60% of the United States total.
The West Coast area is a highly productive one and, because of meteoro-
logical conditions as well as actual pollution emissions, the value of
the crops subject to pollution is a greater proportion of the total value
than is usual for agricultural areas.
Although values for commercial crops were given in the 1970 report,
values were not obtained for other types of vegetation susceptible to
pollution damage, namely, grass hay and pastures, forests, and orna-
mental plantings. Values for these types of vegetation were derived as
follows.
Grass Hay and Pastures. Although the yield of these forages may
not be affected, fluoride contamination of them may render them useless
as feed because of the effect on the animals consuming them; therefore,
to estimate the losses due to fluorides, it is necessary to know the
value of grass hay and pastures. For this reason, the value of these
crops was determined only for the counties where significant fluoride
sources existed. In the Census of Agriculture, values of grass hay and
25
-------
pastures are not specifically itemized although acreages are reported as
well as hay yields. These values plus those for grass silage were con-
verted to hay equivalents for convenience in making the estimates. The
estimated values are shown in Table 4.
Forests and Ornamentals
Estimates of the value of the various "types" of vegetation in the
potentially polluted counties were based on national or state-wide data.
Such data were often not available by county; hence, the state data had
to be broken down into county estimates through the use of indexes. The
derivation of three such indexes is shown in Table 5; one is based on
population, one on geographic area, and the third on a combination of the
other two. In disucssing each "type" of vegetation, the use of one of
these three indexes will be indicated.
Forests
Commercial forest. "Commercial forest" land is defined as
forested land capable of producing crops of industrial wood and by-
products, in both accessible and inaccessible areas. "Forest products"
include cut timber plus materials produced and sold from the forest that
are not measurable in board feet, such as tanbark, turpentine, seedlings,
Spanish moss, and other products.
The last complete census of the Forest Service was in 1962,
when the commerically forested acreage within national forests totaled
approximately 97 million acres.6 The reported total value of forest
products sold for that year from national forests was approximately
B135 million. If the same national forest acreage is assumed for 1964
and the actual 1964 sale value of forest products (g162 million) is ap-
plied to that acreage, the value per acre would be g1.67. However; the
average value of forest products available for sale annually from all
commercial forest land, both public and private, was estimated to be
B1.34 per acre. It is probable that this figure is too low, both for
public commercial forest in areas of relatively rapid tree growth and
for private commercial forest in many areas of the United States. Al-
though it was impossible to adjust the figures to take such variations
into account in this report, further research will be undertaken to pro-
vide more realistic figures in the future.
Noncommercial forest. Valuation of "noncommerical" forest
(the amount of forest remaining after the commercial forest is sub-
tracted from total forest) is difficult. One approach would be to meas-
ure the increase in land value that could be attributed to the presence
of a noncommercial forest adjacent to property that could be developed
for either commercial or residential purposes. Another approach would
be to measure the intangible values afforded society by a noncommercial
forest, such as benefits of soil and water conservation and of recreation.
Such values, if translated into tourist attractions and spending, appear
26
-------
Table 4
ESTIMATED ACREAGES, TONNAGES AND VALUES OF PASTURE AND HAY IN COUNTIES
OF STATES WHERE POSSIBLE FLUORIDE CONTAMINATION EXISTS
1964
State
Alabama
Arkansas
California
Colorado
Delaware
Florida
Idaho
Illinois
Indiana
Louisiana
Minnesota
Mississippi
Missouri
Montana
New Jersey
North Carolina
Ohio
Oklahoma
Oregon
South Carolina
Tennessee
Texas
Utah
Washington
West Virginia
Total
Pasture (Hay Equivalent)
Acres (000) Tons (000) Value (SOOO)
1,630
2,587
48,564
19,030
35,303
3,214
7,407
2,331
1,952
1,686
2,717
3,008
313
7,873
2,282
1,283
7,176
705
7,561
48,023
6,178
13,880
1,802
226,505
122.8
119.2
1,912.3
233.8
1,135.1
155.8
215.2
100.9
52.1
21.4
23.2
136.7
6.7
63.3
91.3
57.5
279.3
13.5
190.7
654.7
286.6
603.5
41.9
6,517.5
g
3,155.5
2,587.1
46,469.1
6,452.2
35,302.7
3,147.7
5,035.7
2,331.9
1,188.2
488.7
514.8
3,007.3
277.2
2,043.3
2,282.6
1,282.6
7,177.1
434.5
4,986.3
16,105.7
6,178.2
13,880.2
1,420.2
g165,748.8
27
Acres (000)
188
133
3,722
139
932
330
471
136
152
146
275
706
140
63
708
119
187
570
66
567
2,271
90
1,943
107
14,161
Hay
Tons
10,978
6,106
148,462
2,315
29,927
16,062
10,927
o
4,999
2,764
o
30,958
6,411
1,522
9,284
4,763
8,394
22,177
1,629
13,313
68,218
4,163
84,537
2,604
500,543
Value (g)
g
282,135
132,501
3,607,625
63,894
930,731
324,452
255,692
o
113,978
63,019
o
662,501
141,042
62,859
299,873
119,075
187,186
569,949
52,291
350,132
1,678,163
89,920
1,944,351
88,276
812,247,596
-------
Table 5
NUMBER, AREA, AND POPULATION OF COUNTIES SURVEYED IN AIR POLLUTION STUDY
AS PERCENT OF T
-------
to depend on the amount of development that has been achieved in order
to attract tourists, as well as other factors. For instance, expenditures
by tourists in 1968 in two large forested national parks in the state of
Washington, for a limited set of services, were estimated at 80.24 per
acre in one case and 84.08 per acre in the other.i~ For purposes of the
present study, and pending further exploration of possible valuation
methods, the annual value of noncommercial forest was arbitrarily set by
SRI at one-half the value of commercial forest, or 80.67 per acre.
Potential annual value of forest land. Table 6 shows the po-
tential annual value of forest lands in pOllution-threatened counties.
Acreages, by states,of (1) federally owned or managed commercial forest
land, (2) state, county, and municipal commercial forest land, and (3)
private forest land were first estimated. These figures were totaled,
giving the estimated commercial forest acreage, and then subtracted from
total forest land7 to give the estimated noncommercial forest acreage
for each state. By multiplying the commercial acreage by 81.34 and the
noncommercial acreage by 80.67, a "potential sales" value was obtained.
This is defined (for commercial acreage) as the annual sales value of
forest products that could have been obtained if each acre had been ex-
ploited at its average capacity. For many acres, for various reasons,
the forest was allowed to increase in value rather than to have enough
forest products sold to equal the average sales value; in fact, this
erratic harvesting is typical of the management of any specific plot of
actual forest.
The next step was to calculate the acreage in the pollution-
threatened counties as a percentage of the acreage in each state and to
apply that percentage to both the state commercial and noncommercial
acreages, as well as to the annual values, to obtain a first approxima-
tion of the value of forest products in those counties. The final step
was to subtract from these gross figures the actual sales of forest prod-
ucts reported by the 1964 Census of Agriculture for the pollution-
threatened counties (to avoid double-counting) to obtain the net potential
value of sales.
*
Adapted from William B. Beyers, "An Economic Impact Study of Mt. Ranier
and Olympic National Parks," 1970. The values given are for Olympic
and Mt. Rainier, respectively, and include only rentals (primarily boat),
horseback rides, and guide and tour service.
29
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Table 6
P
-------
Ornamental Plantings
Ornamentals were classified as to plantings:
.
In various urban use areas (cemeteries, colleges,
primary and secondary schools, industrial parks,
and golf courses)
On highway roadsides
.
.
In parks
.
Around private residences.
Calculation of the value of each category
ties where potential damage to vegetation
involved the following principal steps:
of ornamental planting in coun-
by air pollutants could occur
1.
Obtaining a basic estimate of the total acre-
age involved for the whole United states and
for individual states.
2.
Placing a dollar value on those acreages that
indicated a total state-wide value as mainte-
nance or replacement cost of such plantings.
Estimating the percentages of such dollar val-
ues represented by the counties in each state
in which pollution damage was likely to occur.
3.
It is difficult to find an acceptable value for ornamentals in
public and private areas that do not have a market value based on an an-
nual harvest. As a minimum estimate of the value placed on such orna-
mentals, SRI has placed the value of the annualized cost of establishing
and maintaining such plantings on a permanent basis, or, alternatively,
the cost of replacement of such ornamentals if they were to be eliminated.
It is argued that society (in the case of publicly owned property) or
the individual (in the case of privately owned property) expends the
price of establishing, maintaining, or replacing the ornamentals and thus
values them by at least the amount spent. Such a method of evaluation
also has the merit that certain types of data are available with which to
make the estimate and that researchers can usually agree on the methods
used in such evaluations.
The dollar value of each category of ornamental plantings for
each state was obtained by the methods described below for each category.
Ornamentals on various urban lands. The ornamental plantings
considered here are those found in cemeteries, industrial parks, col-
leges, primary and secondary schools, and golf courses. Although these
land uses vary greatly, it was possible to use similar methodologies in
many cases to make the necessary estimates. The estimates for the various
31
-------
uses defined above are shown in Table 7. state acreages and costs were
allocated to pollution-threatened counties according to population.
Cemeteries. Published information on cemeteries is very frag-
mentary. Limited statistics from turf grass surveys* were supplemented
by telephone interviews with selected cemetery associations, state and
local government officials, and cemetery directors. Over 200,000 acres
were estimated by SRI to be in cemeteries in the United States, and an
estimated twenty percentt of this acreage was placed in trees and orna-
mentals. The acreage was allocated according to population.
Colleges. An SRI survey estimated somewhat over 200,000 acres
in cOllege campuses, with 50%t of this acreage being devoted to grass
and shrubbery and 10% being planted in trees and ornamentals.* The acre-
age was allocated according to population.
Secondary schools. An SRI survey was used to supplement pub-
lished data; over 180,000 acres were estimated to be devoted to grass
and shrubberY,and 20% of this was the estimate for trees and orna-
mentals.t This acreage was allocated according to population.
Primary schools. Sources of published data for schools were
supplemented by a telephone interview with school architects. It was
estimated that 230,000 acres were devoted to grass and shrubbery, and 20%
of this was the estimate for trees and ornamentals.t This acreage was
allocated according to population.
Industrial parks. Published information was supplemented by
an SRI survey.$ Of an estimated 280,000 acres in such parks, 30 percent
was estimated to be in grass and shrubbery and 6 percent in trees and
ornamentals.t
Golf courses. An SRI survey was utilized, which included in-
formation from the National Golf Foundation. Of an estimated 835,000
acres in golf courses, 10 percent was estimated to be planted in trees
and shrubbery.t This acreage was allocated according to population.
i~ ". f 1967 "
Such as the Wash1ngton Tur grass Survey, , done by the State of
Washington. Total area in grass and ornamentals in cemeteries in the
state was found to be 4400 acres.
tThese estimates are subject to correction if improved data show them to
be incorrect.
:t:
See also articles on campus planning in Urban Land for December 1966.
--
.see also: "Site Selection Issue" in Industrial Development and Manage-
ment Record, June 1969.
32
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Table 7
ESTIMATED ACREAGES AND ANNUAL COSTS TO POLLUTION-THREATENED COUNTIES
FOR MAINTENANCE OF TREES AND SHRUBS IN VARIOUS URBAN LAND USES
1964
Pollution-
Threatened
Counties
State (thousands of acres) Cost of
Secondary Primary Industrial Golf Acres Maintenance-
State Cemeteries Colleges School s 'School s Parks ~ Total (000) ($000)
Alabama 0.7 0.4 0.7 0.8 0.3 1.5 4.4 1.5 $ 6,592
Alaska
Arizona 0.3 0.2 0.3 0.4 0.1 0.7 2.0 1.2 5,392
Arkansas 0.4 0.2 0.4 0.5 0.2 0.8 2.5 0.4 1,794
CaU:(omia 3.8 2.1 3.5 4.3 1.6 7.9 23.2 13.7 61,583
Colorado 0.4 0.2 0.4 0.5 0.2 0.8 2.5 1.1 5,109
Connecticut 0.6 0.3 0.5 0.6 0.2 1.2 3.4 2.1 9,249
Delaware 0.1 0.1 0.1 0.1 b 0.3 0.7 0.4 1,789
District of Columbia
Florida 1.2 0.7 1.1 1.4 0.5 2.5 7.4 3.9 17,648
Georgia 0.9 0.5 0.8 1.0 0.4 1.8 5.4 1.0 4,581
Hawaii 0.2 0.1 0.2 0.2 0.1 0.3 1.1 0.5 2,689
Idaho 0.1 1,574
1111nois 2.2 1.2 2.0 2.5 0.9 4.6 13.4 7.4 32,598
Indiana 1.0 0.6 0.9 1.2 0.4 2.1 6.2 2.4 10,826
Iowa 0.6 0.3 0.5 0.6 0.2 1.2 3.4 0.7 3,000
Kansas 0.5 0.2 0.4 0.6 0.2 1.0 2.9 0.9 3,733
Kentucky 0.7 0.4 0.6 0.8 0.3 1.4 4.2 1.1 4,711
Louisiana 0.7 0.4 0.7 0.8 0.3 1.5 4.4 1.6 7,517
Maine 0.2 900
Maryland 0.7 0.4 0.7 0.8 0.3 1.5 4.4 2.4 10,981
Massachusetts 1.1 0.6 1.0 1.3 0.5 2.3 6.8 4.4 19,488
Michigan 1.7 1.0 1.6 2.0 0.7 3.6 10.6 4.5 20,233
Minnesota 0.7 0.4 0.7 0.8 0.3 1.5 4.4 1.8 8,062
Mississippi 0.5 0.2 0.4 0.6 0.2 1.0 2.9 0.4 1,931
Missouri 0.9 0.5 0.8 1.1 0.4 1.9 5.6 1.6 7,412
Montana 0.2 0.1 0.2 0.2 0.1 0.3 1.1 0.2 879
Nebraska 0.3 0.2 0.3 0.4 0.1 0.7 2.0 0.5 2,412
Nevada 0.1 b 0.1 0.1 b 0.2 0.5 0.3 1,169
New Hampshire 0.1 0.1 0.1 0.1 b 0.3 0.7 0.1 605
New Jersey 1.4 0.8 1.3 1.6 0.6 2.9 8.6 4.7 21,049
New Mexico 0.2 0.1 0.2 0.2 0.1 0.4 1.2 0.4 1,976
New York 3.8 2.1 3.5 4.3 1.6 7.9 23.2 6.5 26,914
North Carolina 1.0 0.6 0.9 1.2 0.4 2.1 6.2 1.3 5,827
North Dakota
Ohio 2.1 1.2 1.9 2.4 0.9 4.4 12.9 6.7 29,720
Okl ahoma 0.5 0.3 0.5 0.6 0.2 1.1 3.2 1.0 4,753
Oregon 0.4 0.2 0.4 0.5 0.2 0.8 2.5 0.9 3,751
Pennsylvania 2.4 1.2 2.2 2.7 1.0 5.0 14.5 8.0 35,590
Rhode I sl and 0.2 0.1 0.2 0.2 0.1 0.4 1.2 0.7 3,154
South Carolina 0.5 0.3 0.5 0.6 0.2 1.1 3.2 0.7 3,362
South Dakota
Tennessee 0.8 0.4 0.7 0.9 0.3 1.7 4.8 1.7 7,602
Texas 2.2 1.2 2.0 2.5 0.9 4.5 13.3 5.9 26,143
Utah 0.2 0.1 0.2 0.2 0.1 0.4 1.2 0.5 2,361
Vermont
Virginia 0.9 0.5 0.8 1.0 0.4 1.9 5.5 1.3 5,790
Washington 0.6 0.4 0.6 0.7 0.3 1.3 3.9 2.0 8,885
West Virginia 0.4 0.2 0.4 0.5 0.2 0.8 2.5 1.2 3,125
Wisconsin 0.8 0.5 0.8 1.0 0.4 1.8 5.3 1.8 8,112
Wyoming 0.1 b 0.1 0.1 b 0.2 0.5 ~
Total 101.7 $451,671
a. Estimated, based on figures obtained in survey for omsmentals planted along highways and in roadside parks.
b. Less than 500 acres.
33
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Highway roadsides. Estimated roadside landscaping acreage and
costs are given in Table 8. The general basis for the assumptions used
in estimating these acreages and costs was derived from a series of tele-
phone interviews conducted with landscape architects and highway horti-
culturalists in various parts of the United States.i~ The basic highway
mileage data was provided in "Highway Statistics, 1964" published by the
U.S. Bureau of Public Roads. Acreage of highway ornamental landscaping
was allocated to counties according to the "combined area-population"
index. Valuation of highway ornamental acreage was based on a number of
cost factors, including routine operation and maintenance costs as well
as a proportion of shrubbery replacement costs, and varied from a very
nominal figure up to 3750 per acre per annum.t The series of assumptions
developed by SRI to estimate roadside acreages of shrubs and trees are
given below. Simplifying averages had to be used, in spite of the fact
that variations exist for each factor.
1.
State differentiation. Assume state differentiations due to
"dry" and "humid" weather. "Dry" states include Arizona,
California, Nevada, New Mexico, Texas, Idaho, and Utah. In
these states, assume that there is little effort to maintain
turf grass on rural roadsides and that rural road landscaping
is primarily composed of shrubs and trees. Assume that all
urban road landscaping includes permanent irrigation equipment.
States that are part humid and part dry, such as Washington and
Oregon, or part mountain and part plains, such as Colorado,
were assigned simplifying assumptions that apply state-wide.
Rest areas. Assume that rest areas exist only in rural areas
and are located one-half hour's driving time apart (35 miles).
Rest areas now exist on interstate highways and to varying ex-
tents on other primary highways.
2.
3.
Interchanges: urban. Assume that urban interchanges are an
average five miles apart and are located only on streets with
access control.
*
Names in the selected states were obtained from two source books:
American Association of State Highway Officials, Reference Book of
Member Department Personnel and Committees, 1970; (2) American-Road
Builders' Association, Highway Officials and Engineers, "Directory of
Personnel," June 1968. -
tA very brief listing of reports and articles found useful in providing
background includes: (1) Automotive Safety Foundation, Development and
Management of Mississippi's State Highways: 1960-1980; (2) Michigan---
Highway Department, Michigan's Highways: 1960-1980; (3) U.S. Bureau of
Public Roads Highways and Economic and Social Changes, 1964; (4) SRI,
, - -
Impact of Improved Highways on the Economy of the United States, pre-
pared for the U.S. Bureau of-PUblic Roads, 1955:-
(1 )
34
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Table 8
ESTIMATED ANNUAL COSTS TO POLLUTION-THREATENED COUNTIES FOR ROADSIDE LANDSCAPINGa
1964
County Costs (thousands of dollars)
Rural Urban Urban-Rural
State Primary ~ Secondary
Alabama $ 111 $ 128 $ 187
Alaska
Arizona 414 214
Arkansas 23 31 143
California 1,503 7,183
Colorado 112 154 35
Connecticut 112 218 22
Delaware 24 45 26
District of Columbia
Florida 19 176 173
Georgia 74 132 79
Hawaii 12 13 6
Idaho
Illinois 364 634 176
Indiana 147 110 174
Iowa 100 113 148
Kansas 103 129 136
Kentucky 58 76 82
Louisiana 62 94 73
Maine
Maryland 80 213 99
Massachusetts 134 341 41
Michigan 218 246 237
Minnesota 163 337 266
Mississippi 52 86 59
Missouri 147 195 147
Montana 67 19 29
Nebraska 63 43 82
Nevada 338 18
New Hampshire 99 25 9
New Jersey 257 247 32
New Mexico 221 138
New York 252 689 171
North Carolina 77 84 171
North Dakota
Ohio 263 422 247
Oklahoma 134 189 89
Oregon 73 51 50
Pennsylvania 288 590 180
Rhode Island 23 26 10
South Carolina 88 62 127
South Dakota
Tennessee 127 77 89
Texas 1,137 4,579
Utah 141 194
Vermont
Virginia 79 81 96
Washington 137 153 140
West Virginia 62 81 117
Wisconsin 128 110 145
Wyoming 17 2 4
Total $8,103 $18,748 $4,097
a. Trees and shrubs only.
35
Total
$ 426
628
197
8,686
301
352
95
368
285
31
1,174
431
361
368
216
229
392
516
701
766
197
489
115
188
356
133
536
359
1,112
332
932
412
174
1,058
59
277
293
5,716
335
256
430
260
383
23
$30,948
-------
4.
Interchanges: rural. Assume that rural interchanges are an
average ten miles apart on all highways with access control
and on half the highway mileage of other four-lane and divided
highways.
Landscaping. Assume landscaping on highway mileage in a range
from 0 percent to 100 percent, depending on type of highway*
and location of state. For each mile of landscaped highway,
assume one to five acres of trees and shrubs, depending on lo-
cation and type of highway. For eligible highway interchanges,
assume 2.5 to 12.5 acres of trees and shrubs, depending on
whether the interchange is urban or rural and its location
within the United States. For rest areas, assume 3 to 7.5 acres
of trees and shrubs.
City, county, state, and national parks. The data given in
Table 9 were obtained from several official sources.8 The park acreage
devoted to trees and shrubs was estimated at 50%.t Estimated annual costs
of repair, upkeep and maintenance were obtained from the same published
sources; reported costs of personnel salaries and wages were added to
costs for current operating expenditures. Acreages and costs were al-
located based on area.
As with forests, it is difficult to estimate the value of parks
to the U.S. public in any meaningful quantitative terms.* When a park
area is acquired or established, considerable capital investment is re-
quired to prepare it for use by the public--the building of new roads,
buildings, camping and housing facilities, etc. Once this capital in-
vestment is made, annual expenditures can shift to a maintenance basis
(although in practice, capital improvements in a park may continue for
many years). Much of the annual cost of park maintenance can be directly
related to upkeep of its trees and shrubs--watering, fertilizing, weeding,
trimming and removing, planting, spraying, fire control, and numerous
other tasks. A major part of this cost is the cost of personnel required
for these tasks. Consequently, even though other types of personnel and
their associated costs$ are included in the totals reported, it was decided
*
Urban or rural; full, limited, or free access; divided, 4-lane, or
2-lane primary; secondary.
tThiS would vary, depending on the location of the park and other fac-
tors. Modification of this estimate will be attempted in further re-
search.
*A publication of the National Park Service, "The Economics of Public
Recreation: An Economic Study of the Monetary Evaluation of Recreation
in the National Parks," concludes: "...it was impQssible to measure the
economic benefits of the National Park system in dollars and cents on
any basis other than judgment," (Washington, D.C., 1949)
$Office personnel and park rangers, road repair and building maintenance,
etc.
36
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Tabl e 9
ESTIMATED ACREAGES AND ANNUAL COSTS TO STATES AND POLLUTION-THREATENED COUNTIES
FOR MAINTENANCE OF TREES AND SHRUBS IN CITY, COUNTY, STATE, AND NATIONAL PARKS
1964
State Pollution-Threatened Counties
State Acres (000) ,Cost (11'000) Acres (000) Cost (11'000)
Alabama 196 $ 3,512 41 $ 741
Alaska
Arizona 1,521 9,892 774 5,035
Arkansas 47 534 5 62
California 2,613 111,135 1,259 53,567
Colorado 318 5,852 54 992
Connecticut 84 8,736 52 5,399
Delaware 9 1,278 6 893
District of Columbia
Florida 1,958 21,918 730 8,175
Georgia 130 5,442 9 392
Hawaii 743 4,595 69 427
Idaho
Illinois 90 52,112 28 16,248
Indiana 117 9,112 31 2,433
Iowa 63 6,018 7 626
Kansas 40 3,666 3 284
Kentucky 106 6,306 12 738
Louisiana 6,784 3,396 1,250 626
Maine
Maryland 104 11,127 37 3,961
Massachusetts 170 10,020 110 6,480
Michigan 2,293 31,890 362 5,023
Minnesota 904 10,426 155 1,793
Mississippi 137 1,679 12 145
Missouri 167 13,438 14 1,032
Montana 885 2,246 77 195
Nebraska 40 3,703 1 115
Nevada 490 2,484 103 522
New Hampshire 38 2,187 7 394
New Jersey 142 15,510 77 8,406
New Mexico 268 2,282 42 354
New York 1,742 77,895 610 27,263
North Carolina 295 7,102 63 1,509
North Dakota
Ohio 256 23,880 108 10,101
Oklahoma 234 4,488 34 660
Oregon 587 8,416 26 370
Pennsylvania 1,509 27,145 675 12,137
Rhode Island 13 1,590 12 1,417
South Carolina 75 2,498 19 617
South Dakota
Tennessee 479 8,756 84 1,528
Texas 525 19,676 91 3,443
Utah 824 3,881 118 555
Vermont
Virginia 218 8,026 21 779
Washington 2,628 9,348 825 2,935
West Virginia 132 2,532 31 602
Wisconsin 331 23,258 72 5,005
Wyoming 1,218 ~ 105 351
Total 31,277 $593,070 8,221 $194,330
37
-------
to use the current personnel and operating costs as a first approximation
of the costs of maintaining park shrubbery in its present condition, and
to accept this cost, now borne by the public, as a public evaluation of
the worth of trees and ornamentals grown in parks. It was also decided
that any new plantings placed in parks would usually be acquired outside
the normal commercial channels.
Land occupied by private residences. SRI held a number of
telephone interviews with various city planning departments, in addition
to obtaining information from published sources.* In the pollution-
threatened counties, the number of residences was calculated based on
population. Residence location was designated as "central city," "urban,"
or "rural." Different proportions of single-family, 2- to 4-family, and
multiple-family residences were assumed in each of the three levels of
urbanization. In each case, 20 percent of the open space around the
residence was assumed to be devoted to trees and ornamentals. In only
one type of housing situation--the multiple-family dwelling in the central
city--was it assumed that there was virtually no landscaping. The 1960
and 1964 censuses of population and housing were used to estimate size
of family and the percentage distribution of the different types of
housing. Estimated acreage planted to trees and ornamentals was multi-
plied by an annual maintenance cost of $750 per acre to obtain annual
cost figures.t The results of the various calculations are shown in
Table 10. Allocation of acreage and costs to pollution-threatened coun-
ties was made on the basis of population.
Sensitivity of Various Plant Species to the Specific Pollutants
To arrive at a more realistic method of assigning losses to crops
and ornamentals based on their differing sensitivities to various pol-
lutants, the literature has been continuously reviewed and a table was
prepared indicating the relative sensitivity of the plants on which such
information was available. The results of this survey are shown in Table
11, in which some 200 different species are listed by the type of crop.
*
A brief list of useful reports and articles would include: (1) Urban
Land Institute bulletins No. 42 and 420, 1961; (2) articles in Urban
Land for July-Aug. 1955, May 1960, Oct. 1961, Oct. 1963, Oct. 1964,
April and Oct. 1967; (3) San Francisco Housing stock Census, 1970; (4)
HUD Federal Housing Administration, Minimum Standards ~ Low ~
Housing.
tThis figure for an acre of trees and ornamentals would be divided among
a number of families, so that the figure per family per residence would
be much lower than $750.
38
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Table 10
ESTIMATED ACREAGES IN AND ANNUAL COSTS TO POLLUTION-THREATENED COUNTIES
FOR MAINTENANCE OF TREES AND ORNAMENTALS AROUND PRIVATE RESIDENCES
Acres (000) Costs ($000)
State Central City Other Urban Ru ral Total
Alabama 1.3 ' 3.3 21.3 25.9 $ 19,381
Alaska
Arizona 0.7 1.4 6.1 8.2 6,067
Arkansas 0.2 0.5 5.3 6.0 4,501
California 7.5 31.1 24.7 63.3 47,412
Colorado 0.3 3.7 1.6 5.6 4,163
Connecticut 0.6 4.3 8.7 13.6 10,263
Delaware 1.3 2.4 3.7 2,772
District of Columbia
Florida 0.5 13.5 20.7 34.7 26,044
Georgia 3.1 5.3 8.4 6,192
Hawaii 0.2 1.0 1.0 2.2 1,650
Idaho 0.1 0.8 1.3 2.2a 1,574
Illinois 2.8 24.5 22.6 49.9 37,636
Indiana 0.6 7.6 17.2 25.4 18,896
Iowa 0.1 2.5 5.0 7.6 5,566
Kansas 0.3 2.3 4.0 6.6 4,817
Kentucky 0.3 3.2 6.8 10.3 4,303
Louisiana 0.5 4.5 8.5 13.5 10,329
Maine 0.1 1.0 1.5 2.6a 1,976
Maryland 1.0 11.3 14.0 26.3 19,530
Massachusetts 1.7 13.1 11.8 26.6 19,892
Michigan 1.7 13.2 15.0 29.9 22,420
Minnesota 0.7 5.5 6.0 12.2 9,039
Mississippi 0.1 1.1 3.4 4.6 3,550
Missouri 1.0 8.2 4.8 14.0 10,336
Montana 2.1 4.3 6.4 1,559
Nebraska 0.3 1.2 1.3 2.8 2,101
Nevada 0.9 0.7 1.6 1,203
New Hampshire 0.4 2.5 2.9 2,175
New Jersey 1.5 16.2 8.1 25.8 19,332
New Mexico 0.1 1.1 2.4 3.6 2,469
New York 1.2 22.0 33.0 56.2 41,998
North Carolina 0.1 2.5 19.4 22.0 16,583
North Dakota 0.3 0.4 0.7a 543
Ohio 2.2 20.0 35.0 57.2 43,163
Oklahoma 0.6 3.1 4.5 8.2 6,111
Oregon 0.3 2.5 1.7 4.5 3,389
Pennsylvania 2.0 27.2 49.8 79.0 59,415
Rhode Island 0.2 2.2 1.8 4.2 3,195
South Carolina b 1.4 11.8 13.2 9,879
South Dakota
Tennessee 4.2 10.7 14.9 11 , 511
Texas 2.0 17.1 19.3 38.4 28,901
Utah 0.1 1.6 1.4 3.1 2,360
Vermont
Virginia 0.6 6.1 14.0 20.7 15,594
Washington 0.5 5.9 13.2 19.6 14,779
West Virginia b 3.2 16.6 19.8 8,805
Wisconsin 0.6 5.5 8.0 14.1 10,549
Wyoming b ~ 0.4 300
Total 34.6 308.7 479.3 822.6 $604,223
a. Urban/rural distribution for these counties based on total distribution.
b. Less than 100 acres.
39
-------
Table 11
ESTIMATES OF RESISTANCE AND SENSITIVITY OF
VARIOUS CROPS TO DIFFERENT POLLUTANTS
S = Susceptible, I = Intermediate, R = Resistant
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
Field crops
Alfalfa S I S S R
Barley S I S I
Beans (field) S S S S S R
Buckwheat S S
Clover (hay) S S S R
Corn (field) R R I
Cotton S R
Isspedeza
Oats S S S S I
Peanuts S
Potatoes (Irish) S R R
Rye S I S
Safflower S
Sorghum R I
Soybean I S R
Sugar beets I S I R
Sunflower S S I
Tobacco S S I S R
Wheat S I S R
Seed crops
Alfalfa S I S S R
Clover S I S S R
Alsike S
Crimson S
Ladino S
Red S
Isspedeza
Mustard S I
40
-------
Table 11 (continued)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
-
Citrus S R I
Grapefruit I
Kumquats
Lemons I
Limes
Oranges I
Valencia
Navel
Temple
Mandarins
Tangerines I
Tangelos
Fruits and nuts
Almonds
Apples S
Apricots I S
Avocados
Blackberries
Blueberries S
Cherries R
Sour R
Sweet
Grapes S S I S
Peaches I
Clingstone
Freestone S
Pears S R
Pecans
Plums I S
Prunes S
Strawberries R
Walnuts I
Raspberry I
Figs I
41
-------
Table 11 (continued)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
-
Vegetables
Asparagus R R R
Beans, snap S S S R
Beans, lima S R S I
Beets (table) S I S S R
Broccoli R S
Brussel sprouts R S
Cabbage I
Carrots I S
Cauliflower I
Celery I R R
Corn (sweet) S R R S
Cucumber R R
Endive and escarole S S
Eggplant l
Is t tuce (head) S S R
Muskmelon S S R
Okra S
Onion S R R
Parsley I
Parsnip I
Peas I
Peppers I
Potato (sweet) S
Pumpkin S
Radish S R I
Romaine S S
Spinach S I S S
Squash S
Swiss chard S S
Tomatoes S S S I R
Turnip S
42
-------
Table 11 (continued)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
-
FlOWering plants
Aster I I
Azalea S R
Bachelor's button S
Begonia R I
Canna R
Carissa R
Carnation S
Chrysanthemum S R R
Cosmos S
Croton R
Dahlia R
Four o'clock R
Geranium I
Gladiolus R S
Goldenrod I
Heath R
Hibiscus S R
Hollyhock I
Honeysuckle R
Hydrangea I
Iris I
Ixora R
Lilac S I
Marigold I
Morning glory S
Narcissus I
Nasturtium I
Peony I
Periwinkle R
Petunia S S S
Privet S
Pyrocantha R
43
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Table 11 (continued)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
-
Flowering plants (cont.)
Rhododendron I
Rose R I
Snowball R
Snowberry S
Spired S R
Sunflower S I I
Sweet pea S
Sweet william I
Touch-me-not R
Tulip S
Verbena S
Violet S S I
Virginia creeper R R
Wisteria R
Zinnia S
Trees and native shrubs
Alder S
Arbor-vitae R I
Ash (green) I
Aspen (quaking) S I
Birch S-I R
Box elder S R S
Brittlewood S
Catalpa S S-I
Douglas fir S
Elderberry R
Elm (American) S-I R
Honeylocust S
Juniper (most species) R R
Larch S S
Linden, American I R
Linden, European I
44
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Table 11 (continued)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
Trees and native shrubs ( cont . )
Maple
S11 ver S R I
Sugar R
Hedge I
Mock orange R
Mulberry S
Oak, ~ambel S
Oak, live R
Oregon grape S
Pine
Eastern, white S S S S
Lodgepole S
Mugho S
Scotch S
Western, yellow S S S S
Poplar, Carolina I
Poplar, Lombardy S-I I
Service berry I
Spruce, blue S
Spruce, white I
Sumac I
Sycamore S R
Tobacco tree S
Tree of Heaven' R
Walnut, black I
Walnut, English I
Willow, weeping S R
Yew S I
45
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Table 11 (concluded)
Pollutant and Sensitivity
Nitrogen General Sulfur Hydrogen
Ozone Dioxide PAN Oxidant Dioxide Fluoride
Weeds and grasses
Bindweed S
Careless weed S
Cheeseweed I I S S R
Chickweed I S R I
Cocklebur I
Dock sour S
Fleabane S
Goosefoot nettle (leafed) R I R S
Grasses
Annual blue S S R R
Bent S
Brome S
Crab S
June S
Kentucky blue R R R
Orchard S I R
Rye S
Salt R
Lambsquarters I I I
Milkweed R
Mustard, black S I
Mustard, yellow
Nettle (little leaf) S
Nightshade I
Pigweed R
Plantain S
Purslane R
Ragweed S
Shepherd's purse R
Smartweed I
Sweet clover I
46
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The data for Table 11 were assembled from many sources, but pri-
marily the following:
1.
Recognition of Air Pollution Injury to Vegetation: A
Pictorial Atlas. Informative Report No.1. TR7 Com-
mittee, Air Pollution Control Association, Pittsburgh,
Pa., 1970. Edited by J. S. Jacobson and A. Clyde Hill.
Farbtafelatlas uber Schwefeldioxid-Werkungen an Pflangen.
H. Van Hout and H. Stratmann. W. Gerardet, Essen, 1970.
2.
3.
Air Pollution Injury to Vegetation. I. W. Hindawi.
National Air Pollution Control Office Publication No. AP-
71. Raleigh, North Carolina, 1970.
As mentioned in the Introduction, the dollar loss estimates given
in the first annual report were calculated by assuming that all the sen-
sitive species suffered equally as a result of an air pollution episode
(a recognized fallacy). During this report period, an attempt was made
to develop relative damage percentages for various crops as a result of
a pollution episode of a specific concentration.
Every year the California State Department of Agriculture, through
its Los Angeles office, publishes estimates of percentage loss as well
as total dollar loss to crops as a result of smog. Since 1969, the Cen-
ter for Air Environment Studies of Pennsylvania State University has been
estimating dollar losses to air pollutants in various counties in Penn-
sylvania. From these pUblications 9-13 and published and unpublished
data from other sources, percentage losses to various crops that could
occur in counties suffering from the most severe pollution were obtained.
Using this information, plus the data in Table 11 showing comparable sen-
sitivity of various crops to the various pollutants, Table 12 was prepared
showing estimated percentages of crop losses that might occur in counties
with the heaviest pollution. There are still many crops on which infor-
mation as to sensitivity is not available.
Formulae for Calculating Dollar Loss
In the previous year, the following formula was developed to ex-
press the dollar loss of a particular crop due to a particular pollutant:
C = pPQP(Qc - QP)
QC
where
C = approximate dollar loss
pP = price per unit produced under polluted conditions
QP = number of units produced under polluted conditions
QC = potential units produced under clear air conditions.
47
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Table 12
ESTIMATED PERCENTAGES OF CROPS LOST IN COUNTIES MOST POLLUTED BY
OZONE, PAN, AND OXIDES OF NITROGEN; SULFUR DIOXIDE; AND HYDROGEN FLUORIDE
(Species Are Grouped According to Listing in Table 11)
Percentage of Crop Lost
Ozone, PAN, Sulfur Hydrogen
Crop Oxides of Nitrogen Dioxide Fluoride
Field crops
Alfalfa 30 10 10
Barley 5 5
Beans 5 5
Buckwheat 10
Clover 30 10 10
Corn field 5 10
Cotton 2 5
Lespedeza 10
Oats 5 5
Peanuts 5
Potatoes, Irish
Rye 5 5
Safflower 5
Sorghum 2
Soybean 5 5
Sugar beet 10 2
Sunflower 5 5
Tobacco 10
Wheat 5 5
Seed crops
Alfalfa 10 10
Clover 10
Alsike 10
Crimson 10
Ladino 10
Red 10
Lespedeza
Mustard 10 5
48
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Table 12 (continued)
Percentage of Crop Lost
Ozone, PAN, Sulfur Hydrogen
Crop Oxides of Nitrogen Dioxide Fluoride
Citrus 30 1 5
Grapefruit 5
Lemons 30 5
Oranges 5
Fruits and nuts
Almonds
Apples 5
Apricots 2 5
Avocados 5
Blueberries 5
Cherries 1 1
Figs 10
Grapes 20 2 5
Peaches 2 3
Pears 5 1
Pecans 1
Plums 2 5
Prunes 5
Strawberries 1
Walnuts 1 2
Raspberries 2
Vegetables
Asparagus 1 1 1
Beans, snap 10 5 1
Beans, lima 5 5 1
Beets 10 5 1
Broccoli 5 5
Brussel sprouts 1 5
Cabbage 5 1
Carrots 2 5
Cauliflower 5 2
Celery 10 1 1
Corn, sweet 2 1 5
CUcumber 5 2
Endive 10 5
Eggplant 2
49
-------
Table 12 (concluded)
Percentage of Crop Lost
Ozone, PAN, Sulfur Hydrogen
Crop Oxides of Nitrogen Dioxide Fluoride
Vegetables ( cont . )
~ttuce (leaf) 10
~ttuce (head) 2 5 1
Muskmelon 5 1
Okra 5
Onion 2 1
Parsley 5 2
Parsnip 2
Peas 2
Peppers 5 2
Potato, sweet 5
Pumpkin 5 5
Radish 5 2
Romaine 10 1
Spinach 10 1
Squash 5
Swiss chard 5 5
Tomatoes 2 2
Turnips 5 5
Nursery stocka
General 5 2 1
Trees and native shrubsa
General 2 2 1
Weeds and grassesa
Lawn grasses 2
Generalb
a.
80 many species are involved in this category and so little is known about
the sensitivity and resistance of individual species that a general value
has been given for the groups as a whole based on average estimates of
Los Angeles County for ozone, PAN, and oxides of nitrogen, and general
observations and experience for sulfur dioxide and hydrogen fluoride.
Effect on weeds may be an ecological loss but not an economic one.
b.
50
-------
This essentially says that the current value of a crop under smog con-
ditions times the fractional yield reduction is a fair approximation of
the crop loss in dollars due to the particular air pollutant.
The difficulty in applying the above formula is, of course, in es-
timating the yield reduction ascribable to air pollutants. As indicated
in Table 12, no quantitative data are available on the effects of air
pollutants on yield or growth for some crops. Crops vary greatly in their
response to pollutants, depending on species and environmental conditions.
Not only do crops vary in their response to different pollutants, but
(as indicated in Table 2) the relative severity of the pollution varies
from county to county, depending on the emissions, meteorological con-
ditions, and topography. In spite of all these difficulties, a system-
atic formula was applied to each county for each pollutant and for each
crop, forest, and ornamental planting as follows.
First, the counties in which plant-damaging pollution was likely to
occur were placed in classes of different relative pollution intensities
for each pollutant, i.e., oxidants (ozone, PAN, and oxides of nitrogen),
sulfur dioxide, and fluorides. According to the 1962 City and County
Data Book,4 there were 3,134 counties in the United states (as of De-
cember 1965, this number had declined to 3,109). The classes in which
the counties were placed are given below in increasing order of severity
of pollution.
The classes for oxidant pollution, along with the number of counties
in each class, are:
Class 0:
Class 1:
Class 2:
Class 3:
Class 4:
Class 5:
Class 6:
The 2,807 counties not included in the Standard Metro-
politan Statistical Areas.
The 141 counties in an SMSA but not in the 65 SMSAs for
which relative pollution intensities were calculated, as
shown in Table 2.
The 31 counties included in the last 13 SMSAs listed under
"Hydrocarbons" in Table 2, i.e., Bridgeport to Fort Worth.
The 24 counties included in the SMSAs in Table 2 from
Reading to Worcester, inclusive.
The 42 counties included in the SMSAs in Table 2 from
Patterson-Clifton-Passaic to Richmond, inclusive.
The 52 counties in the SMSAs in Table 2 from Louisville
to Gary-Hammond-East Chicago, inclusive.
The 37 counties in the first 12 SMSAs listed in Table 2,
i.e., Los Angeles to New York, inclusive.
To classify the counties as to severity of sulfur dioxide pollution,
it was necessary to consider the number and nature of the sulfur dioxide
sources, i.e., the relative sulfur dioxide emissions in counties in the
51
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65 SMSAs shown in Table 2, and the number of significant individual sta-
tionary sources present. This included the number of iron and steel mills,
power plants with over 100 kw capacity, oil refineries with a capacity of
over 20,000 barrels per day, and copper; lead and zinc smelters. Based
on this information, the counties were placed in the following classes
for sulfur dioxide pollution.
Class 0:
Class 1:
Class 2:
Class 3:
Class 4:
Class 5:
All counties with no significant sulfur dioxide sources.
There were 2,798 such counties.
The 73 counties in the upper half of the SMSAs listed in
Table 2 under sulfur dioxide.
209 counties with 1-2 sources of sulfur dioxide.
14 counties with 3-6 sources of sulfur dioxide.
13 counties with 7 or more sources of sulfur dioxide.
27 counties with copper, lead or zinc smelters.
The main sources of fluoride emissions known to adversely affect
vegetation are ceramic plants, steel plants (especially in the Western
United States), phosphorus and phosphate plants, and aluminum reduction
plants. On this basis, the counties were classed as follows for fluoride
pollution.
Class 0:
Class 1:
Class 2:
Class 3:
3,048 counties with no significant fluoride sources.
38 counties with large ceramic plants or a phosphorus or
phosphate plant.
23 counties with 2 phosphorus or phosphate plants.
25 counties with aluminum reduction plants or a steel
plant if west of the Rocky Mountains.
With the establishment of various classes of pollutant intensity
for the three main types of pollutants, the next step was to estimate
the losses that would occur to the various crops growing in counties in
the different pollution classes. Table 12 shows estimates of the per-
centage losses to various crops that are likely to occur under the se-
verest of conditions for each pollutant, i.e., Class 6 for oxidants,
Class 5 for sulfur dioxide, and Class 3 for fluorides. With this as a
basis, estimates were then made of percentage losses to various crops
that would occur in the different classes. These are shown in Table 13
for oxidants, Table 14 for sulfur dioxide, and Table 15 for fluorides.
Some of these classes and the percentages involved require a little
discussion. Class 1 for oxidants, including counties in the smaller
SMSAs,was established because the literature indicates that low concen-
trations of oxides of nitrogen may cause reduced growth and yield without
visibly affecting the plant. Therefore, a small reduction in yield was
estimated for these counties. Recent work by Thompson et al.14 indicates
that ambient levels of N02 that occur in the Los Angeles basin are probably
52
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Table 13
FACTORS TO BE APPLIED TO CROP AND ORNAMENTAL PLANTING VALUES
WHEN PLANTS WERE EXPOSED TO DIFFERENT SEVERITY CLASSES OF OXIDANTS
C 1 as s
Vegetation Types 0 1 2 3 4 5 6
Field Crops
Alfalfa 0 .010 .020 .040 .060 .070 .100
Barley 0 .005 .010 .020 .030 .040 .050
Beans 0 .010 .020 .040 .060 .080 .100
Buckwheat 0 .005 .020 .040 .060 .080 .100
Clover 0 .005 .020 .040 .060 .080 .100
Corn 0 0 0 .005 .010 .015 .020
Cotton 0 0 0 0 0 .005 .010
Oats 0 .005 .010 .020 .030 .040 .050
Peanuts 0 .005 .010 .020 .030 .040 .050
Rye 0 .005 .010 .020 .030 .040 .050
Sorghum 0 0 0 .005 .010 .015 .020
Soybeans 0 .005 .010 .020 .030 .040 .050
Sugar beets 0 .010 .020 .040 .060 .080 .100
Sunflower 0 .005 .010 .020 .030 .040 .050
Tobacco (cigar wrap) 0 .010 .020 .040 .060 .080 .100
Wheat 0 .005 .010 .020 .030 .040 .050
Seed Crops
Alfalfa 0 .010 .020 .040 .060 .080 .100
Clover 0 .010 .020 .040 .060 .080 .100
Mustard 0 .010 .020 .040 .060 .080 .100
Citrus -
Grapefruit 0 .010 .060 .120 .180 .240 .300
Lemons 0 .010 .060 .120 .180 .240 .300
Oranges 0 .010 .060 .120 .180 .240 .300
Fruits and Nuts
Apples 0 .005 .010 .020 .030 .040 .050
Avocados 0 .005 .010 .020 .030 .040 .050
Cherries 0 .001 .020 .040 .060 .080 .100
Figs 0 .001 .020 .040 .060 .080 .100
Grapes 0 .010 .020 .160 .240 .320 .400
53
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Table 13 (Concluded)
Class
Vegetation Types 0 1 2 3 4 5 6
Vegetables
Asparagus 0 0 0 0 0 .005 .010
Beans (snap) 0 .010 .020 .040 .060 .080 .100
Beans (Lima) 0 .005 .010 .020 .030 .040 .050
Beets 0 .010 .020 .040 .060 .080 .100
Broccoli 0 .005 .010 .020 .030 .040 .050
Brussels sprouts 0 0 0 0 .005 .005 .010
Cabbage 0 .005 .010 .020 .030 .040 .050
Carrots 0 0 0 .005 .010 .015 .020
Cauliflower 0 0 .010 .020 .030 .040 .050
Celery 0 .010 .020 .040 .060 .080 .100
Corn (sweet) 0 0 0 .005 .010 .015 .020
Cucumber 0 .005 .010 .020 .030 .040 .050
Endive 0 .010 .040 .080 .120 .160 .200
Lettuce (leaf) 0 .010 .020 .040 .060 .080 .100
Lettuce (head) 0 0 0 .005 .010 .015 .020
Muskmelon 0 .005 .010 .020 .031 .040 .050
Onion 0 0 0 .005 .010 .015 .020
Parsley 0 .005 .010 .020 .030 .040 .050
Potatoes (Irish) 0 .010 .020 .040 .060 .080 .100
Potatoes (sweet) 0 .005 .010 .020 .030 .040 .050
Pumpkin 0 .005 .010 .020 .030 .040 .050
Radish 0 .005 .010 .020 .030 .040 .050
Romaine 0 .010 .020 .040 .060 .080 .100
Spinach 0 .010 .020 .040 .060 .080 .100
Swiss chard 0 .005 .010 .020 .030 .040 .050
Tomatoes 0 0 0 .005 .010 .015 .020
Turnips 0 .005 .010 .020 .030 .040 .050
Nursery Crop 0 .005 .010 .020 .030 .040 .050
Floral Crops 0 .010 .020 .040 .060 .080 .100
Forests 0 .005 .010 .020 .030 .040 .050
Christmas trees 0 .010 .010 .040 .060 .080 .100
Parks 0 .003 .020 .040 .060 .080 .100
Highway plantings 0 .003 .020 .040 .060 .080 .100
Urban uses 0 .003 .020 .040 .060 .080 .100
Residential plantings 0 .003 .020 .040 .060 .080 .100
54
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Table 14
FACTORS TO BE APPLIED TO PRODUCTION VALUES OF INDICATED CROPS
TO ESTIMATE LOSSES DUE TO SULFUR DIOXIDE
IN DIFFERENT CLASSES OF POLLUTION POTENTIAL
Class
Vegetation Types 0 1 2 3 4 5
Field Crops
Alfalfa 0 .001 .001 .005 .020 .100
Barley 0 0 0 .002 .010 .050
Beans 0 0 0 .002 .010 .050
Buckwheat 0 .001 .001 .005 .020 .100
Clover 0 .001 .001 .005 .020 .100
Cotton 0 0 0 .001 .005 .050
Oats 0 0 0 .002 .010 .050
Rye 0 0 0 .002 .010 .050
Safflower 0 0 0 .002 .010 .050
Soybeans 0 0 0 .002 .010 .050
Sugar beets 0 0 0 0 .005 .020
Sunflower 0 0 0 .002 .010 .050
Wheat 0 0 0 .002 .010 .050
Seed Crops
Alfalfa 0 .001 .001 .005 .020 .100
Clover 0 .001 .001 .005 .020 .100
Mustard 0 0 0 .002 .010 .050
Citrus
Grapefruit 0 0 0 0 0 .010
Lemons 0 0 0 0 0 .010
Oranges 0 0 0 0 0 .010
Fruits and Nuts
Almonds 0 0 0 .002 .010 .050
Apricots 0 0 0 0 .005 .020
Cherries 0 0 0 0 .003 .010
Grapes 0 0 0 0 .005 .020
Peaches 0 0 0 0 .005 .020
Pears 0 0 0 .002 .010 .050
Plums 0 0 0 0 .005 .020
Walnuts 0 0 0 0 .003 .010
55
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Table 14 (Concluded)
Class
Vegetation Types 0 1 2 3 4 5
Vegetables
Asparagus 0 0 0 0 .003 .010
Beans (snap) 0 0 0 .002 .010 .050
Beans (Lima) 0 0 0 .002 .010 .050
Beets 0 0 0 .002 .010 .050
Broccoli 0 0 0 .002 .010 .050
Brussels sprouts 0 0 0 .002 .010 .050
Cabbage 0 0 0 0 .003 .010
Carrots 0 0 0 .002 .010 .050
Cauliflower 0 0 0 0 .005 .020
Celery 0 0 0 0 .003 .010
Corn (sweet) 0 0 0 0 .003 .010
Cucumber 0 0 0 0 .005
Endive 0 0 0 .002 .010 .050
Eggplant 0 0 0 0 .005 .020
Lettuce (head) 0 0 0 0 .005 .020
Muskmelon 0 0 0 0 .003 .010
Okra 0 0 0 .002 .010 .050
Onion 0 0 0 0 .005 .020
Parsley 0 0 0 0 .005 .020
Parsnip 0 0 0 0 .005 .020
Peas 0 0 0 0 .005 .020
Peppers 0 0 0 0 .005 .020
Potatoes (sweet) 0 0 0 .002 .010 .050
Pumpkin 0 0 0 .002 .010 .050
Radish 0 0 0 0 .005 .020
Romaine 0 0 0 0 .003 .010
Spinach 0 0 0 0 .003 .010
Squash 0 0 0 .002 .010 .050
Swiss chard 0 0 0 .002 .010 .050
Tomatoes 0 0 0 0 .005 .020
Turnips 0 0 0 .002 .010 .050
Forest products 0 .001 .001 .002 .005 .010
Parks 0 0 0 .002 .020 .100
Highway p1antings 0 0 0 .002 .020 .100
Urban uses 0 0 0 .002 .020 .100
Residential p1antings 0 0 0 .002 .020 .100
56
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Table 15
FACTORS TO BE APPLIED TO PRODUCTION VALUES OF VARIOUS CROPS
TO OBTAIN ESTIMATES OF LOSSES DUE TO FLUORIDES
UNDER DIFFERENT CLASSES OF FUMIGATION
Class
Vegetation Types 0 1 2 3
Field Crops
Alfalfa 0 .002 .020 .100
Clover 0 .002 .020 .100
Corn (field) silage 0 .002 .020 .100
Lespedeza 0 .002 .020 .100
Grass Hay 0 .002 .020 .100
Pasture 0 .00002 .0003 .001
Citrus
Grapefruit 0 0 .001 .005
Lemons 0 0 .001 .005
Oranges 0 0 .001 .005
Fruits and Nuts
Apricots 0 .002 .020 .100
Blueberries 0 0 .010 .050
Cherries 0 0 0 .010
Grapes 0 0 .010 .050
Peaches 0 0 0 .030
Pears 0 0 0 .010
Pecans 0 0 0 .010
Plums 0 0 .010 .050
Prunes 0 0 .010 .050
Raspberries 0 0 0 .020
Strawberries 0 0 0 .020
Walnuts 0 0 0 .020
Vegetables
Asparagus 0 0 0 .010
Beans (snap) 0 0 0 .010
Beans (Lima) 0 0 0 .010
Beets 0 0 0 .010
Celery 0 0 0 .010
Corn (sweet) 0 0 .010 .050
Lettuce (head) 0 0 0 .010
Forest products 0 0 .010 .050
Nursery crop 0 0 .010 .050
Floral crop 0 0 0 .010
Parks 0 0 .004 .025
Highway plantings 0 0 .002 .010
Urban uses 0 0 .002 .020
Residential plantings 0 0 .010 .050
57
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without effect on citrus. Since the concentrations
Angeles basin are much greater than in the counties
ascribed in Class 1 may not be warranted. However,
needed before this class can be eliminated.
of N02 in the Los
in Class 1, losses
more studies are
There is room for argument about the oxidant pollution classes in
which the SMSAs were placed, especially the first 12 in Table 2 (Class 6).
Thus, the range of pollution potential is from 41 to 648, but placing
them in the same class implies that plant damage is equal in all of them.
It may have been better to have placed Los Angeles-Long Beach in one
class, San Francisco-Oakland in a second class, San Diego and San Jose
in a ,third, Chicago in a fourth, and the remainder of those now in Class
6 into another class--in other words, split the present Class 6 into five
classes. However, this would have resulted in extremely complicated cal-
culations. The ranges of relative pollution potentials in the remainder
of the classes were not so great and seemed reasonable. The effect of
the present groupings has no doubt been to raise the dollar loss esti-
mate somewhat.
Many plant responses are logarithmic in nature. If logarithmic
values are assigned to the relative pollution potential for hydrocarbons
shown in Table 2, the relative levels--in terms of their effect on vege-
tation--are:
Class
Relative Potential Range
As Calculated Log10 as Calculated
6
5
4
3
2
41-648
20-38
12-19
7-11
1-6
1.65
1.30
1.08
0.84
0.03
- 2.81
- 1.58
- 1.27
- 1.04
- 0.78
On the logarithm basis, the division into the five classes does not ap-
pear too inappropriate. However, even the logarithmic values for Los
Angeles and San Francisco are high compared to the others; in future
estimates, these two SMSAs may be put in a class by themselves.
Class 1 for sulfur dioxide includes about a third of the SMSAs--
those with the greatest potential for S02 pollution. Although Los
Angeles County ranks eighth in this group, very little injury to vegeta-
tion due to S02 is reported in Los Angeles County these days and there
may not be significant dollar loss. In fac~ in 1970 only two reports of
plant damage to crops by S02 were recorded (both to azaleas), and there
were no reports of damage to alfalfa, which is more sensitive than a-
zaleas.12 Thus this class may result in some overestimate of losses due
to sulfur dioxide. However, the potential is there and the class has
been included.
As stated previously, to obtain a reasonable estimate of dollar loss
due to a pollutant, it is necessary to know the value of a crop or vegetation
58
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type under polluted conditions and the percentage of reduction in yield
caused by the pollutant. The data obtained in 1970 on commercial crops
and those presented in previous sections on grass hays, forests, and
ornamentals provide the necessary information on the dollar value of the
vegetation types. The data presented in Tables 13, 14, and 15 give the
percentage loss that would be expected to occur to each crop or vegeta-
tion type under different degrees of pollution. To derive estimates of
crop loss, when data by county were available (i.e., on commercial crops)
the percentage loss factors were applied to each crop in each county for
each pollutant, and the county values were added to provide state totals.
Where only state values were available (i.e., for forests and orna-
mental plants), the loss factors for the counties involved were averaged,
and this value was applied to the value of the vegetation type to give
an average state loss value for each type.
Dollar Loss
The estimates of losses in each county were assessed based on crop
values and estimates of pollution potential for the counties totaled into
state values. Table 16 shows the totaled values for Pennsylvania and is
included to indicate the general detail of the information that was as-
sembled. However, because in many instances only one significant source
was present in an area and to preserve some anonymity, the data were in-
tegrated into crop types and standard geographical regions of the United
states (described on page 23).
The value of the crops grown in the counties where plant-damaging
pollution was likely to occur and the estimated dollar losses to the
main types of crops ascribable to the different pollutants are shown in
Table 17 for the different regions. The last section of the table sums
the values for the different regions into the values for the entire coun-
try.
The estimate of losses to crops totals about 885.5 million, of which
~78 million is due to oxidants, the remainder (87.5 million) to sulfur
dioxide and fluorides.
The losses estimated for citrus are greater than for any other type
of crop, accounting for 33% of the total crop loss estimates. This is,
of course, related to the fact that the production of citrus occurs in
the most severely polluted areas. Field crops rank second to citrus.
accounting for 28% of the crop losses. This is partly related to the
importance of alfalfa as a field crop and its sensitivity to all the pol-
lutants being considered.
Ornamental loss estimates as shown here include several types of
plantings, as indicated in Tables 6 through 10. The total loss for this
category is about 846.5 million, of which 843.5 million is due to oxi-
dants, 83 million to sulfur dioxide, and 8127 thousand to fluorides.
59
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Table 16
ESTIMATED PLANT VALUES AND LOSSES FROM AIR POLLUTION
IN PENNSYLVANIA
Value in
Polluted Losses (21000) Due To
Counties Sulfur
Plant ( gooo ) Oxidants Dioxide Fluorides Total
Field Crops
Alfalfa hay g 37,312.4 g 343.2 g148.3 gO.O 21 491.5
Barley 4,194.8 15.4 4.5 .0 19.9
Buckwheat 105.6 1.3 0.0 .0 1.3
Clover hay 17,775.4 118.8 76.4 .0 195.2
Corn for grain 44,384.1 19.5 0.0 .0 19.5
Corn for silage 19,670.0 3.4 0.0 .0 3.4
Grass hay 417.3 0.0 0.0 .0 0.0
Oats 7,318.7 42.4 18.6 .0 61.0
Pasture 2,756.7 0.0 0.0 .0 0.0
Soybeans 569.6 1.0 0.2 .0 1.2
Tobacco 10,652.7 0.6 0.0 .0 0.6
Wheat 12,370.6 67.4 8.5 .0 75.9
Total 157,527.8 613.0 256.5 0.0 869.5
Seed Crops
Red clover 145.2 5.1 0.3 0.0 5.4
Lespedeza 53.5 0.0 0.0 .0 0.0
Mustard 21.3 0.4 0.0 .0 0.4
Total 220.0 5.5 0.3 0.0 5.8
Citrus 0.0 0.0 0.0 0.0 0.0
Total 0.0 0.0 0.0 0.0 0.0
Fruits and Nuts
Apples 4,259.6 162.9 0.0 0.0 162.9
Sour cherries 599.8 16.7 0.9 .0 17.6
Sweet cherries 347.3 11.1 0.5 .0 11.6
Grapes 4,742.9 98.4 0.1 .0 98.5
Peaches 2,891.5 388.1 0.3 .0 388.4
Plums and prunes 178.0 11.1 0.0 .0 11.1
Total 13,018.9 688.3 1.8 0.0 690.1
60
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Table 16 (Concluded)
Value in
Polluted Losses (8000) Due To
Counties Sulfur
Plant (8000) Oxidants Dioxide Fluorides Total
Vegetable Crops
Snap beans B 39.0 8 0.8 8 0.0 80.0 8 0.8
Table beets 3.2 0.4 0.0 .0 0.4
Broccoli 2.6 0.5 0.0 .0 0.5
Carrots 1.1 0.2 0.0 .0 0.2
Sweet corn 46.6 0.2 0.0 .0 0.2
Cucumbers 22.7 0.2 0.0 .0 0.2
Lettuce 5.0 0.0 0.0 .0 0.0
Sweet peppers 15.6 0.1 0.0 .0 0.1
Potatoes 16,296.7 687.6 0.0 .0 687.6
Sweet potatoes 26.3 1.7 0.0 .0 1.7
Spinach 1.7 0.0 0.0 .0 0.0
Squash 2.3 0.0 0.0 .0 0.0
Tomatoes 174.4 0.1 0.1 .0 0.2
Turnips 14.1 0.1 0.0 .0 0.1
Total 16,651.2 691.9 0.1 0.0 692.0
Nursery/Forest Crops
Nursery products 9,074.0 256.0 6.7 0.0 264.7
Floral products 22,443.8 1,442.3 40.6 .0 1,482.9
Forest products 911.3 16.0 1.0 .0 17.0
Total 32,429.1 1,714.3 50.3 0.0 1,764.6
Crop Total 219,847.0 3,713.4 309.0 0.0 4,022.4
Ornamentals
Forests 7,650.0 342.1 9.9 0.0 352.0
Highway plantings 1,088.0 9.4 0.7 .0 10.1
Parks 6,130.0 74.3 7.4 .0 81.7
Residences 59,415.0 2,080.5 175.1 .0 2,255.6
Urban uses 35,590.0 104.5 49.8 .0 154.3
Total 109,873.0 2,610.8 242.9 0.0 2,853.7
Total All Plants g329,720.0 86,324.2 8551.9 80.0 g6,876.1
61
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Table 17
ESTIMATES OF ANNUAL VALUE OF CROPS AND ORNAMENTALS GROWN IN GEOGRAPHIC REGIONS
OF THE UNITED STATES AND ESTIMATED LOSSES DUE TO AIR POLLUTION
Value in
Polluted Losses (8000) Due To
Areas Sulfur
Region and Plant ( 8000 ) Oxidants Dioxide Fluorides Total
New England
Field crops 8 52,558.9 8 1,365.7 8 6.6 8 0.0 8 1,372.3
Seed crops 31.8 0.3 0.0 0.0 0.3
Fruit and nuts 8,904.3 482.8 0.2 0.0 483.0
Vegetables 10,496.9 510.2 0.0 0.0 510.2
Nursery and forest 33,673.9 1,246.2 0.1 0.0 1,246.3
Citrus 0.0 0.0 0.0 0.0 0.0
Crop Total 105,665.8 3,605.2 6.9 0.0 3,612.1
Ornamentals 168,332.0 1,941.5 0.0 0.0 1,941.5
Total All Plants 273,997.8 5,546.7 6.9 0.0 5,553.6
Middle Atlantic
Field crops 301,535.9 1,155.9 351.4 951.5 2.458.8
Seed crops 322.2 8.9 0.6 0.1 9.6
Fruits and nuts 60,234.8 4,747.4 8.8 0.0 4,756.2
Vegetables 36,628.7 1,278.2 2.3 0.1 1,280.6
Nursery and forest 82,137.7 4,379.7 54.8 15.1 4,449.6
Citrus 36.8 0.4 0.0 0.0 0.4
Crop Total 480,896.1 11,570.5 417.9 966.8 12,955.2
Ornamentals 243,141. 7 4,392.9 335.1 0.0 4,728.0
Total All Plants 724,037.8 15,963.4 753.0 966.8 17,683.2
East North Central
Field crops 980,263.0 5,925.8 270.5 187.1 6,383.4
Seed crops 1,769.0 52.4 1.4 1.8 55.6
Fruits and nuts 17,018.0 550.8 1.5 0.9 553.2
Vegetables 19,244.1 682.3 2.5 0.0 684.8
Nursery and forest 73,072.1 3,675.5 0.9 10.0 3,686.4
Citrus 0.0 0.0 0.0 0.0 0.0
Crop Total 1,091,366.2 10,886.8 276.8 199.8 11,363.4
Ornamentals 272.385.0 13,854.1 1,593.7 0.0 15,447.8
Total All Plants 1,363,751.2 24,740.9 1,870.5 199.8 26,811.2
West North Central
Field crops 362,290.3 1,112.6 26.4 7.7 1,146.7
Seed crops 1,083.4 18.3 0.1 0.0 18.4
Fruits and nuts 1,245.1 66.9 0.0 0.0 66.9
Vegetables 4,099.1 294.4 0.0 0.0 294.4
Nursery and forest 16,574.0 614.6 0.2 0.0 614.8
Citrus 0.0 0.0 0.0 0.0 0.0
Crop Total 385,291.9 2,106.8 26.7 7.7 2,141.2
Ornamentals 66,943.0 1,393.5 0.0 0.0 1,393.5
Total All Plants 452,234.9 3,500.3 26.7 7.7 3,534.7
62
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Table 17 (Continued)
Value in
Polluted Losses (8000) Due To
Areas Sulfur
Region and Plant (8000) Oxidants Dioxide Fluorides Total
South Atlantic
Field crops 8 257,623.5 8 3,240.9 8 49.9 8 93.0 8 3.383.8
Seed crops 480.3 0.8 0.0 0.0 0.8
Fruits and nuts 5,568.4 30.1 0.1 26.6 56.8
Vegetables 8,610.0 160.7 0.0 0.7 161.4
Nursery and forest 61.137.8 889.6 0.9 186.9 1,077.4
Citrus 164.867.9 5,655.9 0.0 338.0 5,993.9
Crop Total 498,287.9 9,978.0 50.9 645.2 10,674.1
Ornamentals 139,292.0 4,633.5 364.8 0.0 4,998.3
Total All Plants 637,579.9 14,611.5 415.7 645.2 15,672.4
East South Central
Field crops 171,352.8 495.6 10.6 202.2 708.4
Seed crops 162.4 1.4 0.0 0.2 1.6
Fruits and nuts 3,106.0 79.6 0.0 0.4 80.0
Vegetables 8,599.2 108.6 0.0 0.0 108.6
Nursery and forest 12,714.3 323.6 10.9 8.9 343.4
Citrus 0.0 0.0 0.0 0.0 0.0
Crop Total 195,934.7 1,008.8 21.5 211.7 1,242.0
Ornamentals 74,036.0 1,568.7 48.1 0.0 1,616.8
Total All Plants 269,970.7 2,577.5 69.6 211. 7 2,858.8
West South Central
Field crops 445,197.9 1,077.6 874.2 52.1 2,003.9
Seed crops 275.2 3.0 0.6 16.0 19.6
Fruits and nuts 1,362.2 9.4 0.0 3.3 12.7
Vegetables 1,478.1 16.2 0.2 0.1 16.5
Nursery and forest 16,239.3 216.8 29.6 11.6 258.0
Citrus 1,231.1 12.5 0.0 0.0 12.5
Crop Total 465,783.8 1,335.5 904.6 83.1 2,323.2
Ornamentals 109,974.0 1,806.3 253.8 0.0 2,060.1
Total All Plants 575,757.8 3,141.8 1,158.4 83.1 4.383.3
Mountain
Field crops 247,950.8 603.6 1,354.8 198.3 2.156.7
Seed crops 114.1 0.9 0.1 0.0 1.0
Fruits and nuts 2,504.1 43.7 5.1 0.0 48.8
Vegetables 9,123.5 134.2 0.2 0.0 134.4
Nursery and forest 17,453.8 505.7 14.7 5.3 525.7
Citrus 24,089.8 843.1 3.4 0.0 846.5
Crop Total 301,236.1 2,131.2 1,378.3 203.6 3,713.1
Ornamentals 48,259.0 485.3 231.8 76.9 794.0
Total All Plants 349,495.1 2,616.5 1,610.1 280.5 4,507.1
63
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Region and Plant
Pacific
Field crops
Seed crops
Fruits and nuts
Vegetables
Nursery and forest
Citrus
Crop Total
Ornamentals
Total All Plants
Total United States
Field crops
Seed crops
Fruits and nuts
Vegetables
Forest and nursery
Citrus
Crop T';Jtal
Ornamentals
Total All Plants
Table 17 (Concluded)
Value in
Polluted Losses (~OOO) Due To
Areas Sulfur
(I~ooo ) Oxidants Dioxide Fluorides Total
g 537,722.2 g 3,006.5 g 109.7 81,278.4 8 4,394.6
11,644.7 113.7 7.2 0.0 120.9
234,048.6 4,530.3 1.0 233.3 4,764.6
71,366.8 155.9 0.0 1.0 156.9
112,409.4 6,642.3 22.2 327.9 6,992.4
157,833.3 20,917.2 1.9 50.1 20,969.2
1,125,025.0 35,365.9 142.0 1,890.7 37,398.6
223,744.0 13,331.3 151.9 50.0 13,533.2
1,348,769.0 48,697.2 293.9 1,940.7 50,931.8
3,357,000 17,984 3,044 2,970 24,008
16,000 200 10 18 228
334,000 10,541 17 265 10,822
170,000 3,341 5 2 3,348
425,000 18,494 134 566 19,194
348,000 27,429 5 388 27,823
4,650,000 77,989 3,225 4,209 85,423
1,346,000 43,407 2,979 127 46,513
g5,996,000 8121,396 86,204 84,336 8131,936
64
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The losses to ornamentals due to sulfur dioxide and fluorides are mostly
for forest losses as contrasted to Christmas tree losses, which are in-
cluded under forestry and nursery crops. The total loss estimate for
crops and ornamentals is about 8132 million.
The area of greatest loss is associated with the industrialized and
heavily populated areas. Thus, if citrus is ignored, about 56% of the
crop loss and almost 50% of the ornamental losses occur in the New Eng-
land, Middle Atlantic, and East North Central states. The loss to orna-
mentals in the Pacific region is almost entirely due to losses in the
Los Angeles basin.
Another approach to evaluation of the data is to consider the esti-
mated losses as a percentage of the value of the crops produced. This
can be done in two ways: (a) as a percentage of the value in the pol-
luted counties and (b) as a percentage of the total crop production in
both polluted and unpolluted areas. Such percentages for total crops
and total ornamentals are given in Table 18 for the various geographic
regions. The percentages were obtained by simply dividing the loss esti-
mate by the crop value in the respective areas. In reviewing the table~
it is immediately apparent that estimated losses to ornamentals represent
a higher proportion of the total value than do the estimated losses to
crops.* This, of course, is because most of the ornamental plantings are
in heavily populated counties close to sources of pollution, whereas crops
are generally grown away from such sources. Furthermore, the percentage
losses for ornamentals are not much higher in polluted areas than in the
entire region, i.e., polluted plus nonpolluted areas. Again, this indi-
cates that most of the ornamental plantings are in the polluted counties.
The percentage losses to ornamentals when the entire region is considered
are generally highest in the so-called agricultural or "bread-basket" re-
gions of the country, i.e., the central and mountain regions. On the
other hand, the crop loss percentages are low in these regions and higher
on either coast. The percentages for crop loss in the East North Central,
West North Central, East South Central, West South Central and Mountain
regions average 0.21 percent of the total value of crops produced. The
overall crop loss in the United States is 0.46 percent. Higher percent-
age crop losses occur in the Pacific and South Atlantic States because
most of the citrus is grown in those regions. The estimated loss of
citrus in California represents about 13 percent of the value of the crop
in the polluted counties, in Florida about 3.5 percent. This does not
mean that Florida citrus is more resistant, but only that it is grown
under less severe pollution conditions than in California.
*The New England and Middle Atlantic regions are exceptions.
65
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Table 18
ESTIMATED PERCENTAGE OF CROP AND ORNAMENTAL VALUES LOST
IN POLLUTION-THREATENED COUNTIES AND IN THE
GEOGRAPHIC REGIONS AS A WHOLE
Region and Percentage Value Lost
Vegetation Type Polluted Counties Entire Region
New England
Crops 3.41 1.10
Ornamentals 1.15 1.00
Middle Atlantic
Crops 2.70 1.68
Ornamentals 1.85 1.32
East North Central
Crops 1.04 0.42
Ornamentals 5.29 3.70
West North Central
Crops 0.54 0.08
Ornamentals 2.09 1.36
South Atlantic
Crops 2.15 0.31
Ornamentals 3.42 1.93
East South Central
Crops 0.60 0.11
Ornamentals 2.16 1.70
West South Central
Crops 0.49 0.10
Ornamentals 1.73 1.40
Mountain
Crops 1.22 0.37
Ornamentals 1.24 0.68
Pacific
Crops 3.32 1.13
Ornamentals 5.99 4.37
United States
Crops 1.84 0.46
Ornamentals 3.29 2.37
66
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IV
DISCUSSION
The values for economic losses of plants due to air pollutants are
based on fuel consumption data for 1963 and agricultural crop value data
for 1964, the most recent years for which the complete or detailed data
needed were available. However, a method of evaluating these data has
been developed and can be applied to new data on pollution and vegetation
values on a county-by-county basis as they become available.
The method itself requires some additional discussion, although some
details have been considered in the section describing the methods. The
value estimates are for the counties in which the source is located. In
many instances, because of wind direction and topography, it is possible
for a source to be in one county and affect vegetation in the next county.
This possibility is, of course, recognized. It was believed that when
this occurred, the values calculated would be more or less equalized
since the source county would actually suffer no loss but a loss would
be shown, while no loss would be shown for the adjacent county. The agri-
culture and types of p1antings are not likely to change greatly across
county lines. There are some exceptions, of course, a few of which have
been considered here, but these exceptions may also tend to equalize
each other. This difficulty is greater with single large sources than
with the general urban sources since the SMSAs include several counties
around large metropolitan areas. The Chicago SMSA, for example, includes
five counties whose total area is about the same as that of Los Angeles
County (some 4,000 square miles), and there are areas in Los Angeles
County relatively free of air pollutants.
With establishment of the relative pollution level in various coun-
ties, it was then necessary to estimate the percentage of loss that would
occur to crops and ornamentals as a result of the various pollutants in
each county. The procedures followed in arriving at these loss factors
were briefly described under Methods, but a more detailed discussion seems
warranted. There have been many publications dealing with effects of
air pollutants on vegetation, as indicated by various review articles:
Jacobson and Hi11,15 Heggestad,16 Brandt and Heck, 17 Thomas, 18 Wein-
stein, 19 Tay10r,2o. A relatively few of these have dealt with actual
yield losses. Most of them have been concerned with markings produced
on leaves or with effects on dry weights and other growth indicators
during relatively long or short growth periods. For this reason, rather
heavy reliance has been placed on the few published and, in some cases,
private communications that give data on yields.
In estimating yield losses under various conditions, each pollutant
has its own special considerations. Oxidants kill portions of the leaves;
where this occurs, quantitative estimates of reduction in photosynthetic
area may be extrapolated to indicate yield loss. Oxidants may also pro-
duce a general reduction in growth and yield that would not be apparent
67
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unless comparisons with nearby unfumigated plants were possible. Further-
more, although reduction in growth may be a disadvantage or loss to a
commercial crop, it may be a gain in an ornamental planting because less
maintenance is required, i.e., pruning or mowing.
Sulfur dioxide affects vegetation through killing of leaf
with a resultant reduction in photosynthetic area. The growth
of vegetation does not appear to be affected by sulfur dioxide
leaf tissue is killed.18
tissue,
and yield
unless
Fluorides affect vegetation by marking the leaves. In some in-
stances, crop and ornamental losses have resulted from such markings.
However, on the ~hole, the greatest economic loss to vegetation as a re-
sult of fluoride is the rendering of forage crops unfit for animal con-
sumption.19
The loss factors ascribed to oxidants were based primarily on the
percentage loss estimates that were made for Los Angeles County during
1967, 1968, and 1970 by the California State Department of Agriculture.9,10,12
These were on-the-scene estimates by individuals trained in effects of air
pollutants. These percentages of loss estimates cover a wide range of
crops, including fruits and vegetables, field crops, cut flowers, and nur-
sery crops. They include more crops than for any other area. Since Los
Angeles Basin counties have the severest oxidant pOllution potential,
loss factors in other areas were assigned based on their pollution class
relative to that in the Los Angeles area.
However, there are additional studies and reports on the effects of
oxidants on plants, and these were also considered in arriving at loss
factors. The studies by LaCasse13 during the last two years are as com-
prehensive for Pennsylvania as the ones for California; thus, the re-
sults reported for Pennsylvania influenced the assigning of loss factors
since a different area of the country is involved. Other studies con-
sidered included the following: Thompson and Taylor21 on citrus; Thomp-
son22 on grapes; Heggestad23 on potatoes in Maryland; Heck24 on soybeans
in North Carolina; Feder and Campbel125 on carnations in Massachusetts;
Miller26 on forest trees in California; Dochinger27 on forest trees in
Ohio.
Class No.1 for oxidant effects was established to include "hidden
injury" effects due to these pollutants. Based on the results obtained
by Taylor and Eaton,28 it was believed that nitrogen dioxide was impor-
tant in this connection. Recent studies, including those by Thompson et
al.}4 indicate that no such effects are occurring to citrus in Los Angeles
County. Since Los Angeles County is one of the heaviest N02-polluted
counties, the postulated effects of N02 may have to be revised.
The estimated loss factors due to sulfur dioxide were based primarily
on publications of Thomas18 and Brisley and coworkers~29,3o They actually
68
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studied yields of crops under various field fumigation conditions in the
vicinity of smelters where heaviest losses due to S02 occur, and developed
formulae for calculating yield reduction. The above work was carried out
in the western United states. Of equal importance is the work by Drei-
singer31 and Linzon32 in eastern Canada. The results reported by these
investigators, plus the data on relative sensitivity, have provided the
basis for estimating vegetation losses due to sulfur dioxide.
There have been very few studies on the effects of fluorides on
yield. The scarcity of such information is brought out by Weinstein. 19
Some studies that were utilized in arriving at loss factors due to fluo-
rides are as follows: Brewer et al.33 and Thompson et al.21 on citrus;
Adams et al.34 on ponderosa pine; Hitchcock et al.35,36 on sorghum and
gladiolus.
As indicated above, the greatest economic impact of fluorides on
vegetation is the rendering of forage crops unusable as a result of flu-
oride accumulation, even ,though the growth of the plant is not affected.
Loss factors due to this cause have been mostly derived from unpublished
reports of fluoride content of forage crops in the vicinity of aluminum,
steel, and phosphorus or phosphate plants, to which we had access.
It will be noticed that there are many blank spaces in the table in-
dicating sensitivity of species to various air pollutants. Information
on these species is not available. It may develop that some of these
are very sensitive to certain pollutants and, although in this report no
loss has been said to occur to them, later research may show that loss
is indeed occurring. However, most of the major crops have been investi-
gated or at least closely observed, and it does not seem likely that
large increases in dollar loss will later be assessed because of sensi-
tivities not now known. Also, it is possible that some of the indicated
dollar losses may be too large. In this report, factors for loss to
grapes and citrus ascribable to oxidants have been based on experiments
in which plants were grown essentially under greenhouse conditions (the
only method presently available), and these growth conditions may have
increased their sensitivity; thus, the losses may not be as high under
actual field conditions.
Systematic application of factors to crop and ornamental plant val-
ues, based on pollution conditions, is a straightforward procedure for
estimating crop losses and eliminating hunches, etc., but it does pre-
vent the consideration of interfering factors or special cases. The
weather fleck on tobacco in the Connecticut Valley is a case in point.
Higher losses occur there than would be expected based on pollution
levels and tobacco sensitivity because of the special nature and require-
ment of the cured crop. In this instance, since the authors were aware
of this and actually visited the area, special allowances were made.
On the other hand, climatic conditions before and after a severe pollu-
twn episode may cause the plant damage to be much less or greater than
69
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would be expected. Thus, the episode of heavy pollution that occurred
in New Jersey, New York and Pennsylvania at the end of July in 1970 had
surprisingly little effect on sensitive species.
In evaluating ornamental plantings, no attempt has been made to as-
sign esthetic values. Instead, emphasis has been placed on the cost of
establishment and maintenance. This does not mean that esthetic values
are not real, but only that no satisfactory method is available for as-
cribing dollar values to them.
In some instances in years past, air pollutants have completely de-
nuded certain areas or rendered productive land nonproductive. In other
instances, air pollutants have made it impossible to grow certain crops
in a particular area. In some cases, air pollutants have reduced or even
eliminated the value of recreation areas through the killing of vegeta-
tion. Such losses in land value have not been included.
Because of the various sources of error and other factors mentioned
above, it should be emphasized that the loss values presented in this
report are estimates and, as such, are subject to error and open to re-
vision. In fact, it is expected that suggested revisions will be forth-
coming from many sources.
However, it is also believed that the loss estimates derived are
reasonable and are not too far from the true values. There are several
reasons for believing this.
Each year, the U.S. Department of Agriculture provides estimates of
the losses to crops due to plant diseases, insects, weeds, and other pests.
At the start of this study, individuals responsible for such estimates
were consulted in the hope that we could obtain help in developing quick
and accurate methods for estimating crop losses due to air pollutants.
Their experience has been that reliable estimates can be obtained only
by detailed on-the-spot observation on almost a field-by-field basis.
Two states, California and Pennsylvania, have been conducting such sur-
veys, and it is interesting to compare the estimates derived in this re-
port with those obtained by these two states. The values given below are
for commercial crops only.
70
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California:
Los Angeles
1967
1968
1970
County
8 4,048,0009
2,536,00010
2,855,00012
SRI
8 6,500,000
Entire State
1969 844,500,00011
1970 25,691,00012
Pennsylvania13:
1969-1970
1970-1971
835,230,000
8 6,000,000
437,200
8 7,391,000
(Pennsylvania, in considering losses, estimated only the cost of produc-
tion and not what the grower might receive; therefore, the Pennsylvania
estimates were doubled to arrive at the values given above and to make
them comparable with the others.)
One possible reason for SRI estimates being so much higher than
those of Pennsylvania is that where oxidants are the pollutants, the SRI
loss factors include what might be called "hidden injury damage." Thus,
in the Los Angeles area, any number of studies on many crops have shown
reduced yields and growth without obvious symptoms developing on the vege-
tation. For the purpose of this report, such losses have been judged to
occur throughout the United States. This mayor may not be true, and
only additional research can provide the answer. Inclusion of this
"hidden injury" loss may mean that the SRI estimates of losses due to ox-
idants are higher than the actual losses.
The above data for California and Pennsylvania show how crop losses
due to air pollutants can vary from year to year--depending on climatic,
edaphic, and biotic factors. Other factors are also involved. The SRI
values are based on 1963 crop production and values. In Los Angeles
Count~ a great many citrus orchards were converted to housing develop-
ments between 1963 and 1967. Thus, the higher SRI values for Los Angeles
County could reflect this shift in land use.
It is also of interest to compare individual crop loss estimates in
California as compiled the State of California11,12 and by SRI.
California
1969 1970
SRI
1963
Field crops
Citrus
Fruits and
Vegetables
8 1,579,000
33,565,000
1,165,000
1,651,000
8 2,653,000
19,553,000
720,000
264,000
8 3,189,000
20,969,000
4,695,000
111,000
nuts
71
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There are some differences in the estimates. For instance, SRI es-
timates of fruits and nuts losses are much greater than California's.
This is related primarily to the values of the crops and the area in-
cluded. In 1963, the value of the grape crop in Los Angeles, Riverside,
San Bernardino, and Ventura Counties was about 310,000,000. Applying
the loss factor of 0.4 (California used 0.5), a loss value of 34,000,000
is obtained. Of course, in SRI estimates, the value of the crop in the
whole county is considered as being affected. In 1970, the value of
grapes being affected in these counties was about 31,600,000. SRI's es-
timate of vegetable losses was much less than California's. This seems
to be related to the base value being considered. The State of Cali-
fornia gives the harvest value of vegetable crops in 1970 as 337,171,000.
The harvest value on which SRI estimates are based was 35,000,000.
Thus, on the basis of detailed estimates in California and Penn-
sylvania, two states greatly different in climate and agriculture, the
loss estimates presented in this report are in general agreement with
those obtained by detailed surveys, which are as accurate as can be de-
rived.
To obtain a quick estimate of crop losses, an assumption was made
that all of the crops in counties threatened with oxidant pollution were
injured as much as in Los Angeles County. Such a procedure gave a loss
value of about 3130 million. This was obviously too high, and the esti-
mate of 378 million derived in this report would appear to be reasonable.
In an early effort to arrive at an estimate of losses to ornamental
plantings, it was assumed that all the nursery business conducted in
counties threatened by oxidant pollution consisted of replacements of
plants lost due to air pollution. Such an assumption gave a loss value
of about 3150 million. The estimated loss to ornamentals of about 343.5
million (due to oxidants) also appears reasonable since it is less than
one-third of the total nursery business.
For all of the above reasons, it is believed that the crop and orna-
mental loss estimates ascribed to ozone, PAN, and oxides of nitrogen are
close to the actual losses that would occur in an average year, particu-
larly since the pollution intensities were calculated.
Comparison data for estimates of loss due to sulfur dioxide and
hydrogen fluoride are not readily available. Pennsylvania indicated a
loss of 314,000 due to sulfur dioxide and none due to fluorides; the SRI
estimates for Pennsylvania in this report are 3552,000 and none, respec-
tively. Although the State of California report indicated that visible
injury ascribable to these two pollutants was observed, the amount of
crop loss was not given. The SRI procedure for estimating results in
loss values of g90,000 for sulfur dioxide and 3732,000 for fluorides in
California. These values are largely the potential loss to alfalfa near
large sulfur dioxide sources and potential loss of forage crops as a re-
sult of fluoride accumulation, rendering them unfit for feed. On the
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basis of general experience, I believe that these estimates are not too
far off. They could be low by as much as 100% in anyone year. Most of
the crop and ornamental losses occur in the vicinity of large single
sources, and adverse weather conditions can result in severe plant-
damaging fumigations. Thus, each fumigation source might be considered
a special case. To properly evaluate loss to crops and ornamentals in
the vicinity of these sources requires on-the-scene evaluations over a
period of years. In a subjective approach, the author has had such ex-
perience with large emitters of sulfur dioxide and fluoride for many
years, and these estimates are based on that experience. As indicated
above, where direct comparisons are available, the estimates presented
here are somewhat higher than those from other sources.
Considering the way in which sulfur dioxide sources are being con-
centrated in local areas and the erection of tall stacks as a compen-
sating factor, I can envision a case in which a single sulfur dioxide
incident might cause more damage than the 36.2 million loss estimate
given in this report.
This again emphasizes the fact that the estimates presented here
are for an average year over the United States.
Earlier, it was pointed out that the total crop loss ascribable to
air pollutants amounted to 0.46 percent of the total value of all crops
produced in the United States. It is interesting to compare this loss
estimate with those ascribable to other crop pests such as plant dis-
eases, weeds, and insects. Data taken from Loss in Agriculture, U.S.
Department of Agriculture Handbook *291, 196~ndicate that the average
annual loss to crops due to plant diseases is 33,068 million, to insects is
32,965 million, and to weeds is 31,828 million. These figures represent
about 12, 12, and 8 percent, respectively, of the value of the total po-
tential production. The Handbook gives 3325 million as the annual crop
loss due to air pollutants, which would represent about 1.2 percent of
the total crop value and is almost four times the dollar loss estimated
in this report. In any event, the above data indicate that as a crop
pest, air pollution is at present nowhere near the economic threat that
weeds, insects, and diseases are.
However, there are certain factors that contribute in part to this
difference. By the nature of man's activities, pollution-emitting sources
and crop production activities almost cannot occur in the same location
and both be economical, for reasons other than pollution. Furthermore,
pollution sources cannot fly around the country at their whim as insects
might, nor be carried as far by air currents and retain their plant-
damaging potential as spores and seeds can. But in the few instances
where crop production and heavy pollution do occur in the same general
vicinity, there can be very high crop losses. Thus, grape yields are
reduced by 40-50% in Los Angeles County, citrus by 2010, etc. In areas
close to a single sulfur dioxide source, one fumigation episode may re-
sult in a loss of 50-60% to one cutting of alfalfa.
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One objective of these investigations was to arrive at some evalu-
ation of the crop loss that might be ascribed to automobile emissions.
Since automobiles emit no fluorides, they cannot be held responsible for
fluoride losses. Sulfur dioxide emissions from automobiles average less
than 1% of the total emissions from all sources, and there may be some
doubt as to whether auto exhaust emissions of sulfur dioxide would ever,
by themselves, result in crop or vegetation losses. The data calculated
here indicate that autos emit 67% to 85% of the hydrocarbons and 38% of
the oxides of nitrogen into the atmosphere. If these values are applied
directly to the estimated loss values given in this report, crop losses
from automobiles could amount to about 360 million on a hydrocarbon basis,
or 330 million on an oxides-of-nitrogen basis. Which of these two emis-
sions is the limiting factor in the formation of ozone and PAN is not
known. However, Schuck et al.37 have shown a correlation between the
hydrocarbon content of the atmosphere in the early morning (6-9 a.m.) and
the maximum oxidant content later in the day (0.3 ppm of nonmethane hydro-
carbon produces a maximum hourly concentration of oxidantsaf up to 0.1
ppm) .
As indicated earlier, these values are estimates and, as such, sub-
ject to revision. There will be many exceptions taken to the estimates
presented. The authors expect that where the effects of air pollutants
are evaluated through state surveys, such as those conducted by Cali-
fornia and Pennsylvania, recently initiated by New Jersey, and proposed
by other states, revisions of loss estimates will occur.
It is my general feeling that losses ascribed to oxidants may be too
high and those to the other pollutants a little low, but we have no way
of substantiating these feelings at this time.
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