DRAFT
ESTIMATED EXPOSURE TO AMBIENT CARBON MONOXIDE CONCENTRATIONS
UNDER ALTERNATIVE AIR QUALITY STANDARDS
Strategies and Air Standards Division
Office of Air Quality Planning and Standards
U.S. Environmental Protection Agency
Research Triangle Park, N.C. 27711
August 1980
DRAFT
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ESTIMATED EXPOSURE TO AMBIENT CARBON MONOXIDE CONCENTRATIONS
UNDER ALTERNATIVE AIR QUALITY STANDARDS
William F. Biller
East Brunswick, New Jersey
Thomas B. Feagans
U.S. Environmental Protection Agency
Ted R. Johnson
PEDCo Environmental, Incorporated
George M. Duggan
U.S. Environmental Protection Agency
James E. Capel
PEDCo Environmental, Incorporated
Strategies and Air Standards Division
Office of Air Quality Planning and Standards
U.S. Environmental Protection Agency
Research Triangle Park, N.C. 27711
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Acknowledgements
Discussions with Dr. Wayne Ott and Dr. Dave Mage of EPA's Office of
Research and Development have contributed significantly to the develop-
ment of the two models described in this report. The work done by
Marc Roddin, Hazel Ellis, Waheed Siddiqee, and Robert Lieberman of SRI
International on human activity pattern data (see referenced reports)
was instrumental to the timely application of these models. Managerial
and substantive assistance was provided by Thomas McCurdy of EPA,
Carl Nelson of PEDCo Environmental, Inc., and Joel Norman of SRI Inter-
national. Irene Griffin of PEDCo Environmental, Inc. assisted in data
collection and data reduction.
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1.0 Introduction
An important element in considering possible alternative air quality
standards is the (uncertain) population exposure to pollutant concentrations
that would result if a given standard were just attained. As part of the
current review of the National Ambient Air Quality Standards for carbon monoxide
(CO), estimates have been made of exposures of the populations of nine U.S.
cities to selected CO levels under existing conditions and assuming attainment
of various alternative standards. These estimates have been made for both hourly
and daily interpretations of statistical standards stated in terms of expected
annual exceedance rates of a given concentration level. Selected estimates
are tabulated in section 4.0. The estimates are also extrapolated to the Urban
U.S. population.
Making use of some ideas that have been developed by other investigators
(see discussion in [1]), two models have been developed for estimating exposures
to ambient carbon monoxide levels. The first model estimates average person-hours
of exposures per year to one-hour average concentrations of CO at or above given
concentration levels. The second model estimates average number of exposures to
eight-hour average concentrations of CO at or above given levels. The two models
are described in section 3.0.
The models attempt to take into account the behavior of both people and
ambient levels of carbon monoxide. Sparsity of information on several of the
needed inputs and the first generation nature of the models make the accuracy of
the estimates uncertain. In a more complete analysis than that reported here
the models would be probabilistic, so that uncertainties in the major variables
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would be represented probabilistically. The resulting outputs would be proba-
bilistic; these outputs would represent the uncertainty about the average
number of exposures in each case. In the present study, bounds were estimated
for the quantities whose uncertainty had the largest impact on the exposure
estimates, and lower bound and upper bound estimates are calculated on this
basis alone. In order that this and other limitations of the models presented
in section 3.0 can be better understood, section 2.0 describes briefly the
complexities that must be dealt with in estimating exposures; an indication is
given of how more refined models, currently under development, will improve on
the models described in section 3.0.
Appendix A presents technical details about the two models described in
more general terms in section 3.0. Appendix B describes in more detail than is
given in section 3.0 how pollutant concentrations at monitoring sites were
estimated. Appendix C explains how the particular matrices were constructed
that are used in the current analysis to derive estimated CO concentrations in
five types of environmental settings from CO concentrations at monitoring sites.
Appendix D documents the computer program used to calculate the exposure estimates.
2.0 Estimating Future Exposures to NAAQS Pollutants
2.1 Complexities in Estimating Exposure
Estimation of future exposures to NAAQS pollutants if various possible air
quality standards were just met is not a simple task. The following list
enumerates some of the complexities and problems that must be dealt with
in general:
1. Uithin a given geographical area pollutant concentrations vary over
space at a given instant in time (this is particularly true of CO;
see [2]).
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2. A determination of compliance or non-compliance with standards is
determined on the basis of data from a network of fixed monitoring
stations.
3. Pollutant concentrations at a given monitoring site vary stochastically
over time, even if there are no general trends in emissions or meteor-
ological variables.
4. There generally are trends in at least pollutant emissions.
5. There are a limited number of years of pollutant concentration
data available for most urban areas.
6. There are missing data in the years for which data are available.
7. Frequently there is measurement error in the available pollutant
concentration data.
8. The time pattern of pollutant concentrations at a given monitoring
site would not be the same were a given standard just met as it is for
situations under which available data were collected.
9. The time pattern of pollutant concentrations at various places
including monitoring sites, would not be the same for all emission
mixes which just achieve a given standard.
10. People move around in space over time in ways that are not totally
predictable, and to the extent that such movements follow predictable
patterns these patterns are a function of several variables.
11. The currently available data on how people move around were not collected
for the purpose of estimating exposure to air pollution [1].
The approach taken at this early stage in dealing with these and other
complexities should, to the extent feasible, be an approach which can be built
on in the future as relevant information grows and exposure models become more
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refined. The basic approach taken in this analysis incorporates some of the
ideas developed by Dr. Wayne Ott, et.al. [3], who will be among those
generating relevant information in the future. The approach is designed to be
easily refined in the direction this research is going, to incorporate new
relevant information easily, and to deal with the constraints inherent in doing
exposure analyses in support of NAAQS's.
2.2 Some Salient Aspects of the Basic Approach
The following is an enumeration of some of the salient features of the basic
approach:
(1) the day is divided into k time intervals of equal length;
(2) the study area (city) is divided into m subareas;
(3) each subarea is divided into (the same) n types of environmental
settings (which exhaust the possibilities);
(4) for each time interval of the day the population of the study area
is apportioned by age/occupation category among the m subareas;
(5) for each time interval of the day the subpopulation apportioned to
the m.th subarea is subapportioned to the n environmental settings
and is assigned one of j exercise levels;
(6) the finite and fixed monitoring network provides the set of base
values from which the pollutant concentration in each environmental
setting is estimated by transformation of the base values;
(7) Since the peak values at the monitoring network determine compliance,
alternative sets of base values are associated with alternative
standards.
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There are many other aspects of any particular application of this
approach which result from the specification of a particular model, such as
the two specified in section 3.0. However, the above list should indicate
the nature of the solution to the following problem: In general a finite and
fixed monitoring network cannot capture inherent spatial variation in pollutant
concentrations, yet a finite and fixed monitoring network is the most practical
means of implementing air quality management programs. The solution to this
problem is to determine compliance based on what happens at the finite number
of monitoring sites, through research learn as much as feasible about how values
in particular kinds of environmental settings relate to values at monitoring
sites, and then incorporate this information into exposure assessments done for
the expressed purpose of informing NAAQS decisions. NAAQS decisions are then based
i
on estimates of actual exposures. (Note, however, that in the present analysis
the contributions of indoor sources of CO are not included.)
2.3 Future Improvements
Future improvements can be classified into two broad categories; refinements
in the exposure models and, conjointly, improvements in data. The future
refinements in the exposure models can be further subclassified; there are
refinements which better model the situation being modeled and refinements
which represent more of the existing uncertainties probabilistically.
Doing sensitivity analyses on significant uncertainties is better than
treating them as certainties, but ideally they would be represented probabil-
istically. Point estimates of future numbers of exposures or average numbers
of exposures above certain levels would be acceptable if statistical confidence
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intervals could accompany such point estimates. But it will be a long time,
if ever, before the overall state of information will be sufficient to support
statistical confidence intervals on the outputs of NAAQS exposure assessments.
Rather, the outputs will most suitably be in probabilistic form. The models
used to generate these probabilistic outputs will most likely be simulation
models which use probabilistic representations of uncertainties as inputs.
Only the pollutant concentration aspects of the two models described in
section 3.0 are handled probabilistically; the models are not designed to
give probabilistic outputs. Failure to represent insignificant uncertainties
probabilistically is not an important limitation, but some of the uncertain
quantities simply estimated in calculating the estimates presented in section
4.0 could be significant. Future sensitivity analyses will make clear which of
these uncertainties have the greatest impact on the exposure estimates. The
approach taken in this report of making upper and lower bound estimates of popu-
lation exposures by using upper and lower bound estimates for the most important
uncertain quantities is a temporary expedient made necessary by time limitations.
There are many possible improvements in the modelling of exposure
situations. The day can be divided into finer time segments than the 24 one
hour intervals used for the present analysis; in the ongoing research mentioned
above the day is divided into 96 fifteen minute intervals [3]. The exhaustive
set of environmental settings can be refined; a refined set has been developed
in the aforementioned research.
Because there are limits to the number of environmental settings it is
practical to use, it would be desirable to have distribution elements rather
than a single linear factor in the matrix used to transform the base pollutant
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7
concentrations into concentration estimates for the environmental settings.
Information on how pollutant concentrations and people distribute through
time within the environmental settings could then be improved. Refinements
such as this could be made for the environmental settings in which the
highest concentrations occur without doing it for the other environmental
settings.
Other possible improvements include generating base concentration values
through spatial interpolation schemes [4] and time series modelling [5], [6];
developing more satisfactory means of adjusting pollutant concentration regimes
from the assumption that one standard is being met to the assumption that
another standard is being met [7]; and making better assignments of subpopula-
tions to particular base concentrations over time by using population centroids
[8] and using transportation data on the movement of people among the various
districts of the study area.
As is indicated in Appendix C, there is a great need for more information
from which the factors used to transform monitor site concentrations to concen-
trations in the various environmental settings can be derived. This type of
information will be increasing and improving through various types of research.
In the case of pollutants, such as CO, for which personal dosimeter technology
is available research with personal dosimeters will make a large contribution.
Both point source and line source dispersion modelling can contribute [9].
It is common practice when introducing new models to discuss plans for
calibrating and/or validating the models [10]. In this instance such a
discussion would lead into a series of complex topics that are beyond the
scope of this report. Suffice it to say here that some future research will
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8
address the analagous questions that apply to models that most appropriately
have probabilistic outputs and that the nature of these analagous questions
will be discussed in other EPA reports [11].
Various output measures other than those calculated in the analysis
reported on here can be developed. Of particular interest for setting a
NAAQS would be exposures of population groups most sensitive to the adverse
health effects contributed to by the given pollutant. The uncertainty about
these exposures and their resultant health effects are both elements in
important health risks associated with alternative ambient air quality standards.
Therefore, outputs of risk models that incorporate both of these uncertainties
are of major interest [11]. The Agency is currently supporting a program in
which such models are being developed.
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3.0 Description of Carbon Monoxide Exposure Models
The one-hour and eight-hour CO exposure models have the same general
form (Figure 1). In both models it fs necessary to know for each hour of
the day where people are and what they are doing. It is assumed that the
large number of possible situations in which people are found at any time
of the day can be approximately represented by a reasonable number of
environmental settings and activity or exercise levels. In the present
case five environmental settings have been assumed: indoors at work or
school, other indoors, inside a transportation vehicle, other transportation
along a road, and outdoors. In each environmental setting exercise levels
are classified into one of three ranges: low, medium and high. The low
level corresponds to lying down, sitting or standing; medium activity
corresponds to walking and other mild exercise; high activity corresponds
to running and other heavy exercising.
In developing the models, studies were undertaken for EPA by SRI
International [12] to estimate for each hour of the day how the population
is distributed among the five environmental settings and three possible
exercise levels within each setting. To take into account variations in the
distribution due to location, the United States was divided into three
climatological regions. Areas within the regions were further classified as
to whether they fell within Standard Metropolitan Statistical Areas (SMSA) or
not. The population was classified into thirteen age/occupation categories.
The week was divided into three categories: weekday (Mon-Fri), Saturday, and
Sunday, and the year into three periods. The information on the distribution
of people by environmental setting and exercise level for each hour of the day
as a function of age/occupation category, day of the week, period of the year,
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Figure 1
CARBON MONOXIDE EXPOSURE MODEL
Human Activity
Data Base
1-Hour
8-Hour
City Descriptor
tegion-
SMSA/nonSMSA
Population
Distribution of
Population by
Occupation/Age
Category and Location
Compute:
Fraction of Population
in each environment
or environment path
and activity level.
Air Quality
Data Base
Concentration
Transformation
Matrix
Compute:
Distribution of CO
by environment or
environment path
and location
Alternative
Standard Levels
1
Exposure
To CO at Alternative
Standard Levels
Compute:
Exposure for
Alternative Standard
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11
SMSA/nonSMSA and region of the U.S. constitutes a human activity data base.
In the one-hour model the data base is combined with CO ambient concentration
data to estimate exposures.
The data base on human acitivities has to be taken another step to be
used in the eight-hour model. In this case it is necessary to take into account
the various environmental settings to which an individual has been exposed over
any consecutive eight hours. As discussed above, it is assumed in any hour an
individual is predominately in one of five representative environmental settings.
Therefore, a listing of the environmental settings occupied over a twenty-four
hour period defines a daily environmental path for an individual. The eight-hour
model assumes that for each age/occupation category there are three representative
daily paths. The specification of the daily path age/occupation subgroup and the
percentage of the corresponding age/occupation group in each subgroup are assumed
to vary with Region, SMSA/nonSMSA designation, type of day, and period of the year.
The study mentioned above was extended to specify the path and the distribution
of the age/occupation groups among their three subgroups. Because of time
constraints the number of age/occupation groups considered was limited to ten,
and effects of region and time of year were not taken into account.
Given the above mentioned data base of daily paths, the subpaths for any
eight-hour period and the distribution of a given population over these subpaths
can be determined.
Given the distribution of a population by environmental setting for each
hour of the day or by environmental path for each of the twenty-four possible
consecutive eight-hour periods that can be associated with a day, it is next
necessary to account for the CO levels that will be experienced each hour by
individuals in the environmental settings or environmental paths. A given
area, depending on its size, may have from one to several sites at which the
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air quality is monitored. The area surrounding each site is considered to be
made up of the five environmental settings. A portion of the total population
is assigned to each site. In the present calculation the population is divided
evenly among the sites and population per site is considered constant over the
day. These assumptions were made necessary by time constraints and lack of
data and will be modified in future refinements of the calculations.
It is well established that CO concentrations vary widely with location at
a given time of day. As a result the concentrations experienced within any of
the five environmental settings associated with a given site can vary markedly
from that indicated at the monitor site. Presently there is insufficient infor-
mation to accurately treat these differences and this deficiency is considered
to be the major source of error in the calculation. It is assumed that the
average concentration for any hour in a given environment is proportional to the
concentration at its associated monitor site. This assumption is an oversimplifi-
cation and will be modified in future work. Because of the large uncertainties
in estimating the relationships between the monitoring sites and their associated
environments, upper and lower bound values were estimated for the proportionality
constants connecting monitoring sites and environmental settings.
The models assume that if emission control programs affect a change in
emissions to comply with a given standard, the ambient concentrations of CO
will be changed by the same factor at all sites, with due allowance for
background levels. That is, proportional rollback of CO levels is assumed
at each monitoring site. The degree of rollback required can be calculated
based on either an hourly or daily interpretation of a statistical standard
based on an allowed expected exceedance rate.
Distribution functions were fit to annual one-hour average CO concentra-
tion data sets for each monitor site for the area under study. Because lognormal
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13
distributions gave reasonably good fits, they were used in all the calculations.
These distributions were used primarily to calculate the parameters of the
annual distribution of one-hour average CO concentrations for, each monitoring
site when a given standard level was just being met at the most critical
monitoring site for the area. However, because the distribution of the population
among the five environmental settings associated with each site changes with each
hour of the day, it was necessary to develop separate distributions for each hour
of the day for each monitoring site. It was found that these distributions could
also be reasonably well represented by lognormal distribution functions. However,
some adjustments were required to bring the individual hour distributions into
agreement with the overall distribution. Given the individual hour distributions
for each site and the above assumptions regarding the associated environmental
settings, the parameters of the distribution functions corresponding to each
environmental setting were then estimated. From these distributions the
average fraction of one-hour CO concentrations above a given concentration could
be calculated at each environmental setting when a given standard was just met
at the critical site for the area. These data were then combined with the data
on the distribution of people by environmental setting for each hour of the day
to calculate the total exposure per year to one-hour concentrations at or above
a given level.
To make full use of the data developed on the distribution of people among
the five environmental settings, separate CO ambient concentration distributions
should be obtained for each of the three types of days and seasons of year.
Data limitations made inclusion of this procedure impractical in the present
calculation.
Calculation of exposure to eight-hour average concentrations above.a given
level is more complicated than for the one-hour exposures because it is
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necessary to account for the movement of people through the various
environmental settings over all possible eight-hour periods in a year. Thus,
it is not sufficient to repeat the above calculation for one-hour CO exposures
using distributions of eight-hour average CO concentrations. Appendix A
shows how approximate parameters for distribution by path rather than by environ-
ment may be derived from one-hour and eight-hour average exposures in a year
at or above a given concentration level for each environmental path associated
with a given level at a given standard level.
The models were applied to data from Los Angeles, Phoenix, San Jose,
Washington, D.C., Philadelphia, Tampa, Steubenville, Ohio, St. Cloud, Minnesota,
and Rock Hill, North Carolina. The last mentioned area was the only rural area
included in the study. Exposure estimates for urban areas of the United States
were made by partitioning the urban areas studied into their respective climato-
logical regions and summing the exposures within each region. These exposures
were then scaled up to correspond to the total population within each region and
added together to give total U.S. exposure.
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4.0 Results
Selected results are presented in three tables. Table 1 presents
1-hour average lower and upper bound expected exposure estimates. Table l(a)
presents the estimates made for the urban population of the United States;
here considered to be the 140,000,000 people who live in Standard Metropolitan
Statistical Areas (SMSA's). Table l(b) presents the estimates made for a sample
one of the nine SMSA's used to make the extrapolation to the whole U.S.; namely,
Washington, D.C. The estimates are of expected person-hours of exposure per year
greater than or equal to three concentrations: 50 ppm, 35 ppm, and 25 ppm. The
estimates are made for eight possible standards and the current situation.
To specify a standard the following must be specified: an averaging time;
a standard level; the number of expected exceedances of the standard level allowed
per year; and whether this expected number of exceedances is to be given an hourly
or a daily interpretation. The eight standards are obtained by combining four
possible standard levels with either an hourly or daily interpretation; a 1-hour
averaging time and one expected exceedance of the standard level are common to
all eight standards considered.
Consider, as an example, the question of how many person-hours of 1-hour
average CO exposures above 25 ppm would occur in urban areas during an upcoming
year if the following standard were just attained: standard level = 0.35 ppm;
1-hour averaging time, one expected exceedance, and daily interpretation. The
lower bound estimate given in Table 1 is 76,400,000 expected person-hours of
exposure, and the upper bound estimate is 1,100,000,000 person-hours of exposure.
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The estimates are given in terms of lower and upper bounds for reasons
explained in the earlier sections of this document. The lower bound estimate
of 76,400,000 expected person-hours means that the average number of person-
hours of exposure over a long number of years is estimated to be greater than
76,400,000; the upper bound estimate of 1,100,000,000 expected person-hours
means that the average number of person-hours of exposure over a long number
of years is estimated to be less than 1,100,000,000.
Two points should be noted. First, the fact that the average number of
person-hours of exposure over a long number of years is estimated to be between
76,400,000 and 1,100,000,000 does not mean that it is estimated that in any
given year the number of person-hours of exposure would be between 76,400,000
and 1,100,000,000. Second, it is not certain that the average number of person-
hours of exposure over a long number of years would be between 76,400,000 and
1,100,000,000.
Table 2 presents 8-hour exposure estimates. It is similar in form to
Table 1. Table 2(a) presents estimates for the urban U.S. and Table 2(b)
presents estimates for Washington, D.C. The three exposure levels used are
15 ppm, 12 ppm, and 9 ppm. The four standard levels are 15 ppm, 12 ppm, 9 ppm,
and 7 ppm.
Table 3 presents a breakdown of some sample total expected exposure
estimates for the urban U.S. into estimates for each of the three exercise levels:
low, medium, and high. Table 3(a) gives an 1-hour average case and table 3(b)
an 8-hour average case for the urban U.S. These estimates illustrate a point
which holds in general: the number of exposures at the low exercise level are
estimated to be much higher than those at the medium and high exercise levels.
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Table 1. Expected Person-Hours of Exposure Per Year to
1-Hr Average CO Concentrations
(a) Urban United States (Population = 140,000,000)
Standard
:> 50 ppm
> 35 ppm
> 25 ppm
Level; Interpretation Lower Bound
(1 Expected Exceedance) Estimate
Upper Bound
Estimate
Lower Bound
Estimate
Upper Bound
Estimate
Lower Bound
Estimate
Upper Bound
Estimate
40 ppm;
-, 40 ppm;
35 ppm;
35 ppm;
Current
25 ppm;
25 ppm;
20 ppm;
20 ppm;
Daily
Hourly
Daily
Hourly
Situation
Daily
Hourly
Daily
Hourly
' 5,580
4,290
2,890
2,220
1,590
526
400
164
124
,000
,000
,000
,000
,000
,000 •
,000
,000
,000
105,000,000
82,600,000
57,100,000
44,400,000
38,000,000
11,400,000
8,800,000
3,780,000
2,900,000
30,300,000
23,600,000
16,200,000
12,600,000
9,390,000
3,190,000
2,460,000
1,040,000
797,000
498,000,000
398,000
283,000
225,000
187,000
62,800
49,000
21,800
16,900
,000
,000
,000
,000
,000
,000
,000
,000
138,000
109,000
76,400
60,000
45,800
16,200
12,600
5,560
4,300
,000
,000
,000
,000
,000
,000
,000
,000
,000
1,880
1,530
1,100
913
756
283
225
106
83
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,100,000
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Table 1. Expected PersoriTHours of Exposure Per Year to
1-Hr Average CO Concentrations
(b) Washington, D.C. (Population = 3,061,000)
Standard
_> 50 ppm
> 35 ppm
>_ 25 ppm
Level; Interpretation
(1 Expected Exceedance)
Lower Bound
Estimate
Upper Bound
Estimate
Lower Bound
Estimate
Upper Bound
Estimate
Lower Bound
Estimate
Upper Bound
Estimate
40 ppm;
... ' 40 ppm;
35 ppm;
35 ppm;
Current
25 ppm;
25 ppm;
20 ppm;
20 ppm;
Daily
Hourly
Daily
Hourly
Situation
Daily
Hourly
Daily
Hourly
62
49
34
27
19
8
6
3
2
,900
,300
,600
,400
,200
,300
,690
,410
,780
1,550,000
1,220,000
851,000
668,000
460,000
182,000
142,000
64,100
50,300
327,000
255,000
175,000
137,000
94,000
37,900
30,100
14,500
11,600
7,240
5,780
4,110
3,270
2,290
937
737
339
266
,000
,000
,000
,000
,000
,000
,000
,000
,000
1,570
1,230
847
660
450
176
138
63
, 49
,000
,000
,000
,000
,000
,000
,000
,200
,900
28,300
22,900
16,700
13,500
9,640
4,130
• 3,290
1,560
1,240
,000
,000
,000
,000
,000
,000
,000
,000
,000
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Table 2. Expected Number of 8-Hr Average CO Exposures
(a) Urban United States (Population = 140,000,000)
Standard
>^ 15 ppm
> 12 ppm
> 9 ppm
Level; Interpretation Lower Bound
(1 Expected Exceedance) Estimate
Current
15 ppm;
15 ppm;
12 ppm;
12 ppm;
9 ppm;
9 ppm;
7 ppm;
7 ppm;
Situation
Daily
Hourly
Daily
Hourly
Daily
Hourly
Daily
Hourly
255
52
26
19
9
5
2
1
,000
,300
,600
,700
,930
,350
,690
,640
830
,000
,000
,000
,000
,000
,000
,000
,000
,000
Upper Bound Lower bound
Estimate Estimate
5,530,000,000 752,000,000
708,000,000 135,000,000
333,000,000 69,300,000
243,000,000 51,800,000
121,000,000 26,600,000
65,900,000 14,600,000
34,000,000 7,440,000
21,300,000 4,600,000
11,200,000 2,360,000
upper bouna
Estimate
13,700
2,210
1,010
717
341
181
92
57
30
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,600,000
,300,000
Lower Douna
Estimate
3,180
462
235
176
91
51
26
16
8
,000,000
,000,000
,000,000
,000,000
,500,000
,000,000
,700,000
,800,000
,780,000
upper DUUIIU
Estimate
36,800
9,260
4,390
3,150
1,450
736
355
216
111
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
,000,000
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Standard
Table 2. Expected Number of 8-Hr Average CO Exposures
(b) Washington, D. C. (Population = 3,061,000)
j> 15 ppm
>. 12 ppm
j> 9 ppm
Level; Interpretation
(1 Expected Exceedance)
Current Situation
15 Dpm; Daily
15 ppm; Hourly
12 opm; Daily
12 ppm; Hourly
9 ppm; Daily
9 ppm; Hourly
7 ppm; Daily
7 ppm; Hourly
Lower Bound
Estimate
1.670,000
277,000
152,000
117,000
64,500
37,600
20,900
13,600
7,610
Upper Bound
Estimate
30.300,000
4,410,000
2,420,000
1,860,000
1,050,000
622,000
354,000
236,000
136,000
Lower Bound
Estimate
4.270.000
656,000
361,000
277,000
154,000
90,700
50,800
33,500
19,000
Upper Bound
Estimate
85.700.000
11,000,000
5,830,000
4,440,000
2,460,000
1,460,000
833,000
557,000
323,000
Lower Bound
Estimate
ifi.non.nnn
2,070,000
1,110,000
848,000
470,000
278,000
157,000
105,000
59,900
Upper Bound
Estimate
3?i,nnn,nnn...
39,500,000
19,800,000
14,700,000
7,790,000
4,500,000
2,530,000
1,690,000
980,000
-------
Table 3. Breakdown of Total Expected Exposure for Urban U.S. by
Exercise Level
(a) 1-Hr Average CO Exposures Associated with a Standard Level
of 25 ppm (1 Expected Exceedance, Dialy Interpretation)
£. 50 ppm
1 35 ppm
21 25 ppm
Exercise
Level
Lower. Bound
Estimate
Upper. Bound
Estimate
Lower Bound
Estimate
Upper. Bound
Estimate
Lower Bound
Estimate
Upper. Bound
Estimate
Low
Medium
High
Total
Exercise
Level
519,000
6,230
411
526,000
>
Lower Bound
Estimate
11,300,000
116,000
12,200
11,400,000
3,150,000
40,800
2,860
3,190,000
62,000,000
701,000
75,100
62,700,000
16,000,000
223,000
17,200
16,200,000
(b) 8-Hr Average CO Exposures Associated with a Standard
9 ppm (1 Expected Exceedance, Daily Interpretation)
15 ppm > 12 ppm >
Upper Bound Lower Bound Upper Bound Lower Bound
Estimate Estimate Estimate Estimate
279,000,000
3,630,000
400,000
283,000,000
Level of
9 ppm
Upper Bound
Estimate
Low
Medium
High
Total
4,780,000
412,000
151,000
5,350,000
57,500,000
6,100,000
2,230,000
65,900,000
12,900,000
1,210,000
410,000
14,500,000
159,000,000
16,100,000
5,300,000
181,000,000
45,100,000
4,530,000
1,390,000
51,000,000
665,000,000
54,900,000
15,700,000
736,000,000
-------
APPENDIX A
BASIS FOR EXPOSURE MODELS
One-Hour Model
The following assumptions provide the basis for the 1-Hour Carbon
Monoxide Exposure Model.
1. The numerous activities people are found in at any time
may be adequately represented as taking place in a finite and
relatively small (e.g., < 50) number of environments.
2. The continuum of activity or exercise levels people are
engaged in at any time can be adequately represented by a
finite and relatively small number of levels.
3. Each of the ambient air monitoring sites in an area for which
exposure estimates are to be made accounts for the air quality
of the area surrounding the site. These sub-areas account for
all the land and population encompassed by the area. Each sub-
area will contain all the environments referred to in #1. These
environments are not necessarily associated with specific loca-
tions within the sub-area.
4. During each of the 24 one-hour periods of the day: 12 AM to
1 AM, 1 AM to 2 AM 11 PM to 12 AM, any member of the popu-
lation is predominately in one monitoring site/environment at one
exercise level.
-------
A-2
5. All individuals within a monitoring site/environment during a
given hour are exposed to the same ambient levels of carbon monoxide
(CO).
•
6. The population of an area may be divided into a relatively small
number of age/occupation groups.
7» The distribution of any age/occupation group among the monitoring
sites is a function of: the area, the placement of the monitoring
sites, age/occupation group, period of the year, type of day (e.g.,
weekday, Saturday or Sunday) , and hour of the day.
8. The distribution of any age/occupation group among the environ-
ments associated with a given monitoring site is a function of
climatological region of the USA, whether the area is urban or non-
urban (i.e., whether the area is a Standard Metropolitan Statistical
Area (SMSA) or not), period of the year, type of day, and hour of the day.
9. The variation in measured 1-hour average CO concentrations at
a given site can be adequately represented by a 2 parameter distri-
bution function. Furthermore, 2-parmeter distribution functions
of the same functional form can be determined for each of the 24
one-hour periods described in #4, partitioned by type of day and
period of the year.
10. After background is taken into account there is a proportional
relationship between emissions of CO and ambient levels of CO. The
constant of proportionality is the same for all sites in the area.
-------
A-3
11. CO levels in a given environment are directly proportional to
the CO level at the associated monitoring site after taking background
into account. The constant of proportionality is a function of the
site and the location of its associated environment.
Let G(C,y,a) represent the distribution of 1-hour CO concentrations.
G is the fraction of 1-hour average concentrations occuring over an extended
period of time which are greater than or equal to C. y and a are a scale
parameter and shape parameter, respectively. Then by Assumption #9
G(C, y.»CT.) is the distribution for concentrations occuring in the jth hour
J J
of the day. The expected total person hours of exposure to 1 -hour average
concentrations greater than or equal to C in a one year period in a given
geographic area just meeting a standard C~,D is given by:
PEZEEEEE W D A. < -• ,. , . n m
h i J k 1 mn hl h.i.J'k'1»m-n 0)
Where the indicies are:
h = Time of year (season)
i = Type of day (weekday, Saturday, Sunday)
j = Hour of day
k = Age/occupation group
1 = Monitoring site
m = Environment
n = Exercise level
-------
A-4
A = Fraction of the population in environment m, at exercise level n,
in the vicinity of site 1, in age/occupation group k, during
the jth hour of the day, in a day of type i and an annual time
period of type k.
D. = Number of days of type i in a week.
W. = Number of weeks in an annual time period of type h.
P = Total population of the area.
The factors A, D, and W have the following properties:
The day types chosen for the CO exposure analysis are weekdays, Satur-
day and Sunday and therefore D. takes the values 5, 1, 1. The year is
divided into three periods of equal length and, therefore, Wh = 17.38
for h = 1,2,3.
The functions G(C,y,c) have the property:
(3)
E W. = 52.14 (assuming a 365 day year) (4)
h n
J G(C,y,a)dC = 1 (5)
o
-------
A-5
In determining the y and a parameters for a particular standard the
starting point is the set of y and a parameters for the CO concentrations
observed at the monitoring sites. As discussed more fully in Appendix B,
a suitable functional form is chosen for the monitoring site data by fitting
various forms to data sets for each site in an area. A single form is
chosen for the area. In the present case 10 areas were studied and the
lognormal functional used for each.
It is assumed that the form of the ambient air standard is:
CSyg ppm with an expected exceedance rate not greater than
once per year.
This standard may have an hourly or daily interpretation. In the hourly
interpretation the concentration level C<-jD refers to the 8760 one-hour
average concentrations in a 365 day year at a monitoring site. In the daily
interpretation CSTD refers to the 365 daily maximum concentrations at a
monitoring site.
From the statistics of extreme values the concentration which has an
expected exceedance rate of one would be defined as the characteristic
highest value of the distribution of concentrations. For a year of 8760
hourly average concentrations it is the value of C for which G(C,y,a) =
1/8760. For the daily maximum concentrations it is the value of C for
whcich Gd(C,y,a) = 1/365 (where Gd is the distribution of daily maximum
one-hour concentrations). An alternative way to state the above form of
the standard is that the annual characteristic highest concentration should
not exceed
-------
A-6
The characteristic highest value can be obtained from the parameters
of the fitted distribution function. The relationship for the lognormal
distribution is as follows: ....'".
The lognormal distribution is:
If we put the distribution into its standard form by the following trans-
formation:
7 - log C - u
a
Then:
S(C
.u.a) • f -
J v^iro-
«P
The normal integral on the right has been tabulated and appears in most
texts dealing with statistics [13}. if the characteristic highest concen-
tration is designated by Cl, at C = Cl, by definition G = 1/8760.
-------
A-7
The tabulation of the normal form indicates that value of 1 which yields
this value of G is 3,686. We, therefore, have from the definition of Z:
C1 - V = 3.686
or:
Cl = exp (y+ 3.686 a) (6)
It should be noted that the characteristic highest value is in general
not equal to the expected highest value. The quantity Cl can always be
determined directly from the distribution of concentrations whereas in
general the expected highest value must be obtained from the distribution
function of the highest values. The latter distributions is not usually
directly derivalbe from the distribution of concentrations owing to correla-
tion and nonstationarity effects which are normally present with ambient
air pollutant concentrations [6].
To determine whether an area complies with a standard of .the form given
above,the characteristic highest concentration is determined for each moni-
toring site within the area. The highest Cl for the area must be at the
standard or below for compliance. If it is above,the highest Cl is used
as the design value for determing the degree to which emissions within the
area must be reduced in order to achieve compliance. This approach was
followed in the exposure model.
-------
A-8
The monitor with the highest value of Cl will be called the critical
site. Taking background CO concentrations into account, the .fractional
reduction in emissions required to meet the standard at the critical site
is by Assumption #10:
Cl (critical site) - CSTD
Cl (critical site) - CD1/n
DlxIJ
Equation (7) applies to an hourly interpretation of the standard. If
a daily interpretation is used then the standard level CSTD has to be
adjusted slightly by multiplying by a factor of 0.948, This factor was
determined by comparing calculated characteristic highest values for both
hourly and daily maximum concentrations obtained from the same data sets.
It is the average proportionality factor between the two characteristic
high concentrations.
Under Assumption #10 the factor to be applied at each site to maintain
proportionality is:
lC1Site - W1"-' * CBKO
Site
To make a proportional reduction in all concentrations observed at a site
the factor fSl-te is only applied to the scale factor y (in the lognormal
distribution this is u, the mean value of log C),
(7)
f _ ,0,
Site * (8)
-------
A-9
Assumption #11 leads to another set of factors which take into
account the proportionality between a monitoring site and an associated
environment. These factors can be a function of site, environment, time
of year, type of day, and hour'of day and are designated by y.
By fitting distributions of the form G to subsets of the monitoring
data, the y and a values at each-site can'be obtained 'for.individual
hours of the day, day type, and period of the year. It is to the u-values
of these sets of parameters that the f ... and y factors are applied.
51 tc
In the case of the lognormal distribution it can be shown the u, . . , (C<.Tn)
njijjjijiM o I u
appearing in Eq. (1) is given by:
(9)
"h.U.l * 10g (Yh,i,j,l,mfl(CSTD)>
In the calculations discussed in this report it was assumed that there
were no seasonal or day of the week effects for the y, f, and u. In the
case of the y factors it was also assumed there was no effect of hour of
the day. It was also assumed that the population was divided evenly among
the monitoring sites at all times of the day, week and year.
A more accurate but more involved method of applying y and f would fit
the distributions to the concentration data after the backgrounds have
been subtracted. In this case f-j = (1-r).
-------
A-10
Eight-Hour Model
Calculating exposure to 8-hour average concentrations is considerably
more complex than calculating 1-hour exposures because it becomes necessary
to take into account where people have been over any eight hour period. To
do the 8-hour case properly probably requires a simulation employing time
series for the CO concentrations rather than distribution functions.
The following very approximate method involving distribfctions was used
for the present calculation.
The same simple set of assumptions used in the 1-hour model are carried
over to the 8-hour case with the following additional assumptions:
1. The sequences of activities people are engaged in over
any eight hour period can be adequately represented by a rela-
tively small number of paths,
2. In a twenty-four hour period the distribution of people
over monitoring sites remains constant.
3. The distribution of hourly average concentrations of CO can
be represented by a simple time series displaying a diurnal
variation in the scale factor which may be different for differ-
ent day types and times of the year.
It is assumed the distribution of hourly concentrations can be repre-
sented by a simple time series such as:
-------
A-11
log C(t) = w(t) + a(t) (10)
where t = 1,2,3 •«••• and represents successive hours. The term u(t)
is assumed to show a persistent diurnal pattern. That is,
i
u(t) = p(t + 24) (11)
a(t) is a series of normally distributed values with 0 mean and standard
deviation, o\
Equation (10) can be rewritten:
C(t) = exp (u(t) + a(t)) (12)
or
CCt) = mg(t) exp CaCt)) (13)
where
mg = exp
-------
• A-12
A time series of 8-hour running averages would have the form:
|-ZC(t) = g-
C(t) = -an(t) exp(a(t)) (14)
or
c(t) =
9
log C(t) = log mg(t) + a(t) (15)
where:
mg(t) = gEm (t) (16)
a(t) = log E-J exp (aCtll (17)
Thus based on the simple model given in Eq. (10) the 8-hour running averages
would approximately be represented by a lognormal distribution even with a
diurnal variation in y.
-------
A-13
Now if the path traveled by a given fraction of the population over
any eight hour period is known and it is assumed as in #2 that there is
no movement between sites, the only effect,of the path is to multiply the
m (t) for any hour by the factor y corresponding to the environment on a
given path for that hour* Thus, the nT(t) for the path is:
jjT(t) = lz y(t)m (t) (18)
y y
-------
APPENDIX B
DEVELOPMENT OF POLLUTANT CONCENTRATION DISTRIBUTIONS
For each monitoring site in each study area, "lognonnaT distributions :
were fit to data sets collected over a one year period on 1-hour average
concentrations and 8-hour running average concentrations. Fits were made
using the least squares technique on a linearized form of the distribution.
These yielded a mean and standard deviation (u and a) for the logarithm
of the concentration. The 1-hour and 8-hour data sets were segregated by
hour of the day and the y's and a's for each hour were obtained by the
least squares method.
The lognormal distribution fits 1-hour CO data well but is somewhat
less suited to the 8-hour data. There is further degredation in goodness
of fit when fitting the data to individual hours of the day. It is likely
that had the data been further segregated into type of day and season there
would have been further' degrading of the fit. In general the lognormal
distribution tended to over predict the frequency of occurrence of the
highest concentration observed over a one year period.
In applying the overall and individual hour y's and a's to the 1-hour
model it is important that the overall and individual hour parameters
be mutually consistent. A simple test is available to test for this
consistency. The following situation should hold:
24
.-.o) = G(C,u,0)
-------
B-2
Where the y.» and o\ are the parameters for the individual hours of the
day and the y and a are the overall parameters. Tests with actual data
sets were made for concentrations that when substituted on the right hand
side of the equation gave G values of .90, .75,.50, .1, .01, 10/8760,
2/8760, and 1/8760. Thus the overall distribution was tested over its
whole range. In most cases there was reasonable agreement but not to the
accuracy needed.
It was assumed that the overall parameters were more reliable than
those for the individual hours. Basically what was desired in the
individual hour parameters was that they reasonably reflect the diurnal
nonstationarity of the CO data, and when taken as a group give results in
close agreement with the overall parameters, Consequently for each site
the individual hours y's and a's were adjusted with a multiplier to bring
them into close agreement with the overall u and a through Eq. (1). A
single multiplier was used for the y's and a single multiplier for the a's
of a given site. Generally the needed correction was a number fairly
close to 1. However, in* some case initial agreement was poor and could
not be improved except through large corrections. In these cases the sites
were discarded. In most cities this step was not necessary. However, for
St. Louis the agreement was generally poor and the city was dropped from
the study.
In the 8-hour model » obtaining agreement by adjustment through Eq. (1)
was somewhat less satisfactory but still practical. It was found more
effective, however, to use an additive correction to the y rather than a
multiplicative correction. (In the 1-hour case, either could have been
used with equal success.) The situation came about because u may be either
-------
B-3
positive or negative. If there are about the same number of positive
and negative values in a 24 hour set, a multiplicative factor will have
little effect. The geometric mean which is exp (y) can only be positive
and a multiplicative correction to it is in effect an additive correction
to y. Thus the additive correction is basically more appropriate.
The 8-hour model, uses the individual hour y's for the 1-hour set,
and the individual hour a's from the 8-hour set. It also uses the overall
8-hour y's and a's. It, therefore, requires consistency between the 8-hour
and 1-hour data sets. This was not obtained, largely because of an incon-
sistency between the procedures used in fitting the 1-hour and 8-hour
sets. As a consequence the 8-hour y's were used in the model instead of
the 1-hour y's in the present calculation. This substitution has the
effect of partially meeting the diurnal nonstationarity in the CO data.
-------
APPENDIX C
MONITOR TO ENVIRONMENTAL SETTING CO CONCENTRATION TRANSFORMATION MATRICES
As is indicated in section 4.0, an abstraction from reality embodied in
the two exposure analyses models described there is the assumption that CO
concentrations within a given environmental setting are a constant function
over time and space of its associated monitor site concentration. Thus,
transformation matrices which have the study area monitor sites as one dimension,
the five environmental settings as the other dimension, and numerical constants
as entries can formally represent the transformation of monitor site setting
concentrations.
Although such a matrix is a big step in the right direction from assuming
that monitored concentrations straightforwardly reflect actual exposure levels,
the degree of abstraction from reality is still significant. Also, many matrix
entries are mainly judgmental estimates at this time. Hence, rather than
estimating single transformation matricies, an upper bound matrix and a lower
bound matrix are estimated for each city.
For the present purpose urban areas are divided into the following five
(exhaustive) environmental settings:
1. Indoor at Work
2. Other Indoor
3. Inside Transportation Vehicle
4. Other Transport Along Roads
5. Other Outdoors.
Table l(a) gives the upper bound exposure matrix for Washington, D.C. and
Table l(b) gives the lower bound matrix. Similar upper and lower bound
-------
Table 1. CO Concentration Transformation Matrices; Washington, D.C.
(a) Upper Bound
Site 1
Site 2
Site 3
Site 4
Site 5
Site 6
Site 7
Site 8
Site 9
Site 10
Site 11
Site 1
Site 2
Site 3
Site 4
Site 5
Site 6
Site 7
Site 8
Site. 9
Site 10
Site 11
uEl
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
yEl
.42
.50
.50
.42
.50
.59
.61
.59
.59
.61
.50
yE2
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
yE2
.49
.54
.54
.49
.54
.62
.62
.62
.62
.62
.62
yE3
2.5
2.3
2.3
2.5
2.3
2.0
2.0
2.0
2.0
2.0
2.0
(b) Lower
yE3
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
yE4
1.7
1.7
1.6
1.7
1.6
1.5
1.5
1.5
1.5
1.5
1.5
Bound
yE4
.85
.80
.80
.85
.80
.75
.75
.75
.75
.75
.75
yE5
0.95
0.93
0.93
0.95
0.93
0^90
0.90
0.90
0.90
0.90
0.90
yE5
.50
.40
.40
.50
.40
.33
.33
.33
.33
.33
.33
-------
C-3
exposure matrices were developed for the eight other cities and towns included
in the analysis. Environmental setting n is represented by fyEn).
The first environmental setting is "Indoor at Work." Ordinarily CO levels
are lower indoors than outdoors, particularly on higher floors of a building.
(Recall that the present analysis does not include indoor sources such as
cigarette smoke.) Hence, 1.0 is taken to be the upper bound factor for all sites,
For the lower bound factor a calculation was made based on: (a) estimates
of the percentages of buildings with various numbers of floors in the area
associated with a given monitoring site, and (b) some data on the decrease in CO
levels as a function of how high in the building the measurement is made [14].
Table 2 gives estimates of the percentages of buildings with various numbers of
floors for the eleven Washington, D.C. sites. Basements were not included in
the calculation. Table 3 gives a lower bound estimate of the multiplicative
factor associated with each floor.
Now, consider site 1 in table 2. From the estimates for site 1 in table 2
and the multiplicative factors in table 3 we can calculate a weighted lower bound
multiplicative factor for site 1 in which the weights are determined by the
relative number of floors. An important point in this calculation is that every
building has a first floor, all buildings at least two stories tall have a second
floor, all buildings at least three stories tall have a third floor, and so on.
The calculation is as follows:
100 x .9 = 90
(100 - 20 =) 80 x .4 = 32
(80-25 =) 55 x .25 = 13.75
(55-15 =) 40 x .18 = 7.2
(40-10 =) 30 x .14 = 4.2
-------
Table 2. Estimated Distribution of Building Heights (Percentages):
Indoor at Work; Washington, D.C.
Site 1
Site 2
Site 3
Site 4
Site 5
Site 6
Site 7
Site 8
Site 9
Site 10
Site 11
Factor
1
20
30
30
20
30
40
40
40
40
40
40
1
.9
2
25
35
35
25
35
40
40
40
40
40
40
Table
2
.4
3
15
10
10
15
10
10
10
10
10
10
10
3.
3
25
4
10
9
9
10
9
3
5
3
3
5
3
Lower
4
.18
Floor
5
8
6
6
8
6
3
2
3
3
2
3
6
7
3
3
7
3
1
2
1
1
2
1
Bound Multiplicative
Floor
5
.14
6
.11
7
5
2
2
5
2
1
2
1
1
1
1
8
3
2
2
3
2
1
-
1
1
-
1
9
2
1
1
2
1
-
-
-
-
1
1 10
5
2
2
5
2
1
-
1
1
-
1
Factors
7
10
8
.10
9
.10
10
.10
-------
C-5
( 30 - 8 =) 22 x .11 = 2.4
( 22 - 7 =) 15 x .10 = 1.5
( 15 - 5 =) 10 x .10 = 1.0
( 10 - 3 =) 7 x .10 = 0.7
(7-2 fj 5_x .10 = 0.5
Sf=364 E6..=153.25
E6_. 153.25
ULB Sf = 364 = .42
This weighted factor is the entry in Table l(b) for site 1. The above
calculation is a sample of the type of calculation used to get the entries
for the first environmental setting, Indoor at Work, in Table l(b).
The second environmental setting is "Other Indoor." The same reasoning is
used to obtain both the upper bound and lower bound multiplicative factors for
environmental setting 2 as for environmental setting 1. Table 4 gives estimates
of the percentages of buildings with various numbers of floors that contain
people who are in environmental setting 2.
Environmental setting 3 is "Inside Transportation Vehicles." Studies have
shown that monitor readings tend to underestimate average CO exposure inside
transportation vehicles, so 1.0 is taken to be the lower bound factor for all
sites. One study in Boston, a city approximately the same size as Washington,
D.C., found the average exposure to be 2.1 times monitor readings [15], So 2.5
was chosen as the upper bound factor for downtown sites, 2.3 for sites between
downtown and suburban, and 2.0 for suburban sites.
Environmental setting 4 is "Other Transport Along Roads." The results of
three studies, [16], [17], and [18], are factored into the determination of the
upper bound and the lower bound factors for this environmental setting.
-------
Table 4. Estimated Distribution of Building Heights (Percentages):
Other Indoor; Washington, D.C.
Site 1
Site 2
Site 3
Site 4
Site 5
Site 6
Site 7
Site 8
Site 9
Site 10
Site 11
1
20
35
35
20
35
40
40
40
40
40
40
2
40
40
40
40
40
45
45
45
45
45
45
3
15
10
10
15
10
8
8
8
8
8
8
4
10
4
4
10
4
3
3
3
3
3
3
Floor
5
6
3
3
6
3
1
1
1
1
1
1
6
2
2
2
2
2
1
1
1
1
1
1
7
2
2
2
2
2
1
1
1
1
1
1
8
2
2
2
2
2
-
-
-
-
-
_
9
1
1
1
1
1
-
-
-
-
-
_
± 10
2
1
1
2
1
1
1
1
1
1
1
-------
C-7
Environmental setting 5 is "Other Outdoors." Both the upper bound
factors and the lower bound factors are judgments based on line source
dispersion models [19] and scattered measurements [20]. Indications are
that CO concentrations are definitely lower in outdoor settings away from
roadways, so even the upper bound factors are made less than 1.0.
-------
APPENDIX D
COMPUTER PROGRAMS FOR CO EXPOSURE MODELS
-------
PL/1 Program for 1-Hour CO Exposures
-------
*** PL1ABS OF CXPO-2 *»*
DATE 101179
PAGE
8PL1.HETRS X«,EXPO-2
PL1 7R1A SL74R1 10/11/79 18:22:34 C->0)
JSOURCE.EXPO-2 . ADO THE PROGRAM
:EOURE OPTIONS (MAIN) ;
(FLOAT !8 BINARY 8 " CONSTANT)
HUMBER_OF_PONITO RATIO FOR HICRO-ENVI RONHENT 1
VALUE = 2 r> RATIO FOR HICRC-ENV IRQNMENT 2
VALUE = 3 => RATIO FOR MICRO-ENVIRONMENT 3
VALUE r 4 -> RATIO FOR K1CR0-ENV IRQNMENT 4
VALUF - 5 -> RATIO FOR MICRO-ENVIRONHENT 5
VALUE = t, -> FRACTION OF TOTAL POPULATION AT THIS SHE
VALUF - T => REDUCTION F*CTCR AT SITE TO MEET STAMDAKO
VALUE = ft => CHARACTERISTIC VALUE FOR THE SITE
SITES(20)
STANDARD
STANOARO_N».1E
CHARACTERISTIC_VALUE
PACKGROUMD
TOTAL.POPULATION
FRACTIO:N_EXCEEDING
RPDUCTIO'N_NEEOEO
CONCENTRATIONS(20)
NUMBER_OF_CONCENT RAT IONS
ACTIVITY.LEVELS(5f3)
CAYS_IN_INTERVAL(3)
UEIfiULL_CELTA
GEOMETRIC.MEAN
(Ft T. X)
TERMS IN THE LOG - NORMAL INTEGRATION
CHARd2). STATIC;
FLOAT BINARY STATIC;
CHAR(6) STATIC INIT ( «
FLOAT BINARY STATIC;
AS IS*)i
FLOAT
FLOAT
FLOAT
FLOAT
FLOAT
FIXED
FLOAT
FLOAT
5.t 1.
FLOAT
FLOAT
FLOAT
BINARY
BINARY
BINARY
BINARY
BINARY
BINARY
BINARY
BINARY
B INARY
BINARY
BINARY
STATIC;
STATIC;
STATIC;
STATIC;
STATIC;
•
STATIC;
STATIC
STATIC;
STATIC;
STATIC:
INIT (
n I 1 H o r r.r
-------
*** PL1ABS OF EXPO-2 ***
DATE 101179
PAGE
52.
53.
50.
55.
56.
57.
58.
59.
60.
61.
62.
63.
60.
65.
66.
67.
68.
69.
70.
71 .
72.
73.
75.
76.
77.
78-
79.
80.
81.
82.
33.
80.
85.
86.
87.
88.
89.
90.
91.
92.
93.
90 .
95.
96.
97.
98.
99.
100.
101.
102.
103.
105.
106.
107-
108.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
33 /*
*/
30
35 /«
*/
36
37
38
39
00
01
02
03
00 /*
*/
05
06
07
08
09
50
51
52
DECLARE
THE
DECLARE
DECLARE
AIR
DECLARE
CECLARE
DECLARE
DECLARE
DECLARE
OECL *RE
DECLARE
DECLARE
DECLARE
EXP
DECLARE
DECLARE
DECLARE
DECLARE
CECLARE
CECLARE
CECLARE
DECLARE
CECLARE
FLOAT BINARY STATIC IHITC
<0.31938153.
-0.356563782.
<1 .781077937.
-1.821255978 »
il .33027'I029);
THE EXPANSION COEFFICIENTS FOR THE INTEGRATION
SATIWE.X SITU) STATIC;
DECLARE AIR_QUALITY(20.25.2) FLOAT BINARY STATIC:
AIR.CUALITY (MONITOR. HOUR* VALUE)
HOUR ~ 25 => OVERALL VALUES
VALUF = 1 => GEOMETRIC DEVIATION
VALUE = 2 => GEOMETRIC RCAN
HOUR.25
CORRECTION.! (201
CORRECTION_2(20)
CITY.NAKE
CITY_NUM8ER(0)
SIT£_NU«BER(0)
CARD.NUKBER(0)
HOUR.TYPE(0)
fXPOSURES(?0.3)
FIXED BINARY STATIC INIT
FLOAT BI»*ARY STATIC;
FLOAT BINARY STATIC;
CHAfidi) STATIC;
FIXEO BINARY STATIC;
FIXED BINARY STATIC;
FIXED BIMRY STATIC;
FIXED BINARY STATIC;
FLOAT E^ARY STATIC:
EXPOSURES (CONCENTRATION. ACTIVITY LEVELJ
FLOAT BINARY STATIC;
BUILTIN;
su i L T i tt;
BUILTIN;
FILE OUTPUT STREAM PRINT
ENV (CONSECUTIVE APRINT RECSIZE (132)
TOPKARGIM6) BOT.-ARGIN (0) PAGSIZE (66»:
FILE INPUT STREAP
ENV (CONSECUTIVE AREAO RECSIZE (80)):
FILE INPUT STREAK
ENV (CONSECUTIVE AREADA RECSIZE I132))J
FILE OUTPUT STREAM PRINT
TNV (CONSECUTIVE APRNTA RECSIZE (132)
TOPHARGIN(6) BOTHARGIN (0) PAGSIZE (66)):
FILE OUTPUT STRE«K PRINT
ENV (CONSECUTIVE APRNTA RECSIZE (80)
TOPHARGIN(O) BOTHARGIN (0) PAGSIZE (66)):
-------
*** PL1ABS OF £XPO-2 »*»
DATE 101179
PAGE
109.
1 10,
111.
112.
113.
53
5;
B1T(36I STATIC EXTERNAL;
BIT(i) STATIC EXTERNAL:
end) STATIC;
*PAGE;
-------
**« PL1ABS OF EXPO-2 »*»
DATE 101179
PAGE
1 14.
115.
1 16.
117.
118.
119.
1?0.
121. 1
122. 1
123.
125. 1
126.
127.
128. 1
129.
130. 1
131.
1^2. 1
133.
134. 1
135. 1 1
136.
137. 1 1
138. 1
139.
140. 1
141.
142. 1
143. 1 1
144.
145.
146.
147.
148.
149.
150.
151.
152.
153.
154.
155.
156.
157.
156.
159. 1 1
160.
161. 1 1
162.
163.
164. 1 1
165. 1
166. 1 1
167.
166.
169.
170. 1 1
58
59
60
62
63
64
66
67
69
71
72
73
74
75
• 76
78
80
81
82
84
86
87
88
69
CAL:L EROPKOPTIONS) :
T_OPT = SUBSTR(OPTIONS.33.1 >!
OPEN FILE (SYSPRINT);
IF (T_OPT» THEN
OPEN FILE (OUKP<) :
OPEN FILE (SYSIN)i
ON ENOFILE (SYSIN) GO TO FINISHED;
ON UNDERFLOW BEGIN; ENC;
RET fOIT (NUH8ER_OF_MONITORS. BACKGROUND.
TOTAL_POPULATION. STANCARD.TYPE)
(COL(l). F(2)» X(l), F(5)t F(10)t Fll»;
IF (T_OPT) THEN
PUT FILE (DUMP) DATA (NUKBER.OF.PONITORS • BACKGROUND.
TOTAL_POPUL*TION) J
IF •(STANCARO.TYPE = 1) T>EK
DAILY_STANOARO = M'SJ
FLSE
DAILY_STANDARO = «0*8J
CET EDIT (NUMEER.OF.CONCENTRAT^S)
(COL(1 ) . F(2) );
00 CONCEMTRATIO'N.SUB = 1 TO NUHBF R_CF_COKCE UTR AT IONS;
GET EDIT (CONCEMTRAT10NS(COH;CENTRATICN_SUB) )
(COLd )» F(10) );
END:
IF (T_OPT) THEN
PUT FILE (DUKP) SKIP(2>i
IF (T.OPT) THEN
PUT FILE (DUMP) DATA { NUHBF.R_OF_CONCENTRA T 10 NS. CONCENTRATIONS)
CO PONITCR r 1 -TO NUKBER.OF.MON ITORS i
GET EDIT (CITY_NAHE.
CITY_NUKBER(1)t SITE_NUH3ER(1).
(AIR.QUALIT'Y JHONlTORt KOURt 2).
DO HOUR - I TO 6)t
CITY.NUMBER(2)» SITE_NUHBER(2).
(AIR.QUALITY (MONITORt HOUR. 2)»
DO HOUR = 7 TO 13).
CITY.NUHREKm . S IT E.HUHB ER I 3 ) .
( AIR_QUALITY(f10NITOR. HOUR. 2).
DO HOUR = IH TO 20)«
CITY.NUMBERdt). SITE.NUMBER(tt).
(AIR.QUALITY (MOMTOR. HOUR. 2).
00 HOUR = 21 TO 2H, 25).
CORRrCTION.HMOiMITOR) . COSREC T ION.2 (H CNI TOR ) )
•CCLfl). A(ll). F(2). F(3). F(2). F(2). 12(F(5)).
3 (COL (II. F(i3). F(3). F(2). F(2I.
IF (T.OPT) THEN
PUT FILE (DUMP) PAGE!
IF (T.OPT) THEN
PUT FILE (DUMP) DATA (CITY.HAME.
CARO.MUMBER. HOUR_TYPE)J
END; /* END
CO MONITOR : 1 TO NUMBER.0F.MOW I TORSi
GET EDIT ( (MONITORS(MONITOR.HICRO_ENVIROtJHENT )
CO HICRO.ENVIRONfEMT : 1 T0 6). /* 6 IS THE FRACTION POP »/
SITES(MONITOR I)
(COL(21). SF(5.2). F(6.1)> COL(5S). A(12)>:
PUT PARE EDIT ('SITE '. S ITES (MON'I TOR) .
HOUR_TYPE(1). CARC_NUMBEk(l).
AIR.CUALITY(PONITOR. HOUh. 1)
HOUR_TYFE(2). CARD_^UHBEK(2).
AIR_CUALITY(KONITOR. HOUHi. 1)
HOUfi_TYFE(3). CARD.MUKBfh(3).
AIR_OUALITY(«ONITOR. HOUrt. 1)
HOUR_TYPE(U). CARO.NUM3EftC»).
AIR.CUALITY(fCNITOR. HOUk. 1)
) ) ))
CITY.rUHBER. SITE.NUHBLR.
CF READIhG AIR_CUALIIY DATA */
-------
*«* PLIABS OF F.XPO-2 •*» DATE 101179 PAGE
171. X- - I N P U T - -> <- - CCRRECTEC - ->••
172. • STANDARD GEOMETRIC't 'HOUR 't
173. 'DEVIATION KEAN •»
171. 'OEVIATI-ON MEAN *t
175. 'DEVIATION KE*Nf)
176. (COL(l)t At At LINE(3)t At At LINE(I). At A, A, A);
177. 1 1 90 PUT SKIP(2)i
178. 1 1 91 DO HOUR = 1 TO 24S
179. 12 92 PUT EDI-T (HOURt A IR_QUAL ITY (KON1 TORt HOURt lit
ISO. AIR_OUALITY(HONITORt HOURt 2))
181. (COL(l)i F(3)t F(10t3)» F(12t3)>:
182. 1 2 93 MR_CUALITY (HOMTORt HCURt 1) =
183. . AIR_OUALITYtMONITOR. HOURt 1) » CORRECTION_l(HONJTOR)i
184. 1 2 91 *TR_OUALITY (MONITOR. H0l"»t 2) =
185. AIR_OU«LI TYdONITORt HOURt 2) * CORRECTION.2(MONITOR)!
136. 1 2 95 PUT EDIT ( AIR_QI)A|_I T Y( HON ITOR t HOURt lit
187. AIR_OUALITY (KONITORt HOUR> 2))
188. (F(15t3)> FU2.3I);
189. 12 96 «IR_QUALITY(MONITOR. POURt 2) =
190. TXP (AIR_OUALITY(MOMTORt HOUR» 2))f
191. 12 97 PUT EDIT ;
198. 1 1 100 '*IR_OUALITY F(6t3)t F(12t3»;
203. 1 1 102 PUT SKIPC3) EDIT (
2fl<*. 'CORRECTION TO ThE STANDARD DEVIATIONS WAS ',
2C5. CORRECriON.l(MONITOR)t
206. « CORRECTION TO THE MEANS WAS «t
2C7. CORRECriON_2«MONlTOR))
208. (COL(30)t At F(6.3). COL(30)t At F(6t3>>:
2T9. 1 t 103 nONITORSCWONITORt 8) = EXP ( LOG (AI3_QUALITY(MONITORt 25t 21)
210. * 3.666 * AIR.OUALITY (MOMTCRf 25. 1)»J
211. 1 1 101 CHARACTERISTIC_VALUE = MAX(CHARACTERISTIC_VALUEt
212. MONITORS(MOKITORt 8))r
213. 1 1 105 /« END OF GETTING CHARACTERISTIC VALUES */
211. KONITORSIMOMITOR. 7) = 1.0; /* SET FOR AS IS EXPOSURE »/
215. 1 1 106 EN'C;
216- 1 107 IF (T_OPT) THEN
217. PUT FILE (ourp) PAGE;
216. I 109 IF (T_OPT) THEN
219. PUT FILE (DUMP) DATA (A IP_OUAL IT Y ) ',
2?0. 1 111 GO TO OPrN_ACTIVITY_LEVELS;
221. 1 112 NEXT_ST«ND«RO:
222. GET EDIT t ST AiMD'ARD) (COLI1). F(5>>:
223. 1 113 PUT STRUG (S.T ANCAR C _HA KE) EDIT (STANDARD) (F(6t2>>;
2?1. 1 111 IF (OAILY.STANOARO) THEN
225. REDUCTION_MEEDEO = (CHARACTERISTIC_VALUE * 0.918 - STANDARD) /
226. (CHARACTERISTIC_VALUE * 0.918 - BACKGROUND);
227. 1 116 . ELSE
-------
«** PL1A8S OF EXPO-2 *** DATE 101179 PAGE
228. REDUCTIOfl.WEEDEO = (CHtRACTERISTIC_VALUE - STANDARD) /
229. (CHARACTERISTIC.VALUE - BACKGROUND);
230. 1 117 00 MONITOR = 1 -TO NUHBER_OF_HON ITORS !
231. 1 1 118 MONITORSCKONITOR. 7) =
-------
•*» PL1ABS OF EXPO-2 ***
DATE 10117S
PAGE
10
239.
.210.
21 1.
242.
243.
244.
245.
246.
247.
248.
249.
250.
251.
252.
253.
254.
255.
256.
257.
258.
259.
260.
261.
262.
263.
264.
265.
246.
267.
266.
269.
270.
271.
272.
273.
274.
275.
276.
277.
278.
279.
230.
281.
282.
283.
284.
285.
286.
287.
288.
289.
290.
291.
292.
293.
294 .
295.
1
1
1
1
1
1
1
1
1
1
I
1
1
1
1
1
1
1
1
1
1
1
1
1
I
1
2
2
•»
3
3
3
3
3
3
3
.7
3
3
3
3
3
3
3
3
2
3
4
4
125
126
127
128
129
131
133
134
136
137
139
140
142
144
145
146
148
149
150
151
152
153
154
155
156
157
159
160
162
164
165
166
OPEN_ACTiV.TTY_LE'Vf LS:
CPEN FILE (EXPO'» i
ON ENOFILE (EXPO) GO TO URI TE.REP ORT ;
EXPOSURES = o;
GET.ACTIVITY.LEVELS:
GET FILE (EXPO) EDIT (REGION. METEOROLOGY. SEASON. OAY. TYPE.
HOl/R. ((ACTIVITY_LEVELS(ACTIVITY, LEVEL)
DO LEVEL =1 TO 3)
DO ACTIVITY = 1 TO 5>>
(COL(l)t 2FM). X(2). 3F(1), F(2). X(l), 15F(5.D):
ACriVITY.LEVELS = O.CI » ACT IVITY_LEVELS;
IF (T.OPT) THEN1
PUT FILE (DUMP) PAGE;
IF (T.OPT) THEM
PUT FILE (DUMP) DATA (REGION. METEOROLOGY. SEASON. DAY. TYPE.
HOUR. »CTIVITY_LEVELS):
DO CONCENTRATION.SU8 = 1 TO NUM3ER_OF_CONCENTRATIONS:
IF (T.OPT) THEN
PUT FILE (DUMP) DATA (CONCENTRAT ION.SUB);
DO PONITCR = 1 -TO NUKBER.OF.HON ITORS;
IF (T.OPT) THEN
(MONITOR)i
: 1 TO 5;
IF
IF
(MICRO.ENVIRONMENT);
PUT FILE (DUMP) DATA
CO «IC"?0_ENVIROIVKENT
(T.CPT) THEN
PUT FILE (DUMP) DATA
(T.OPT) THEN
PUT FILE (DUMP) SKIP?
JOISTSIBUTION:
PEOKETRIC.P EAfJ : HON ITORS < KON IT OR. 7)
* HONITORS(?10NITOR. M ICRO.ENV IRONMENT )
* AIR_OUALITY(KCNITOR. HOUR. 2>:
X = (LOG(CONCENTrUTIONS(CONCENTSATION_SU8) )
- LOG(GEOfE-TRIC.KEAN)) /A IR.CUALIT V ( f.ON ITOR . HOUR. 1)1
TF (X < 0) THEN 005
NEGATIVE.X r "t'B:
X - - X;
END:
ELSE DO:
MEC-ATIVE.X = 'O'B:
END:
T : 1.0 / (1.0 « O.<316119 * X)J
F - 0.3989423 * EXP(-(X * X / 2.0))5
FRACTION.EXCEEDING =
((((B(5) * -T + B(4)) » T + 6(3)) * T * E(2)) * T * B(l)> * T » F;
IF (NEG^IVE.X) THEN
FRACTIQN.EXCEEDING - I. - FR«CT ION_EXCEEDI KG :
GO TO FRACTIOM.EXCEEOING.FOUNO:
FRACTIOM.rxCEEOING.FOUNO:
IF (T.CPT) THEN
PUT FILE (DUMP) SKIP;
IF (T.OPT) THEN
PUT FILE (DUMP) DATA (FRACTION.EXCEEOING)S
00 L'EVFL = 1 TO 3:
EXPCSURES(CONCENTRATION_SUB. LEVEL) = EXPOSURES(CONCENTRATION.SUC. LEVEL)
+ FRACTION.8XCEEDING * ACT IV ITY.LEVELS(HICRO.ENVIRONMENT• LEVEL)
* CAYS_IN_i:i\ITERVAL(n«Y) * MOM TORS (KCNI TOR. 6)i
END; /* END OF LEVEL */
-------
*** PL1ABS OF EXPO-2 ***
DATE 101179
PAGE
1 1
296.
297.
298.
299.
300.
301.
302.
303.
304.
1
1
1
1
1
1
1
3
2
1
167
168
169
170
172
17t
175
IF
IF
XPAGE;
END;
END:
END;
(T.CPT) THEN
PUT FILE (DUMP)
THEN
PUT FILE (DUMP)
/*
/»
/»
END OF MICRO.ENVIRONHENT */
EN'D OF HCNITCR */
END OF CONCENTRATION.SUB */
SKIPC 2>J
DATA (EXPOSURES):
GO TO GET_ACTIVITY.LEVELS;
-------
*** PL1ABS OF EXPO-2 ***
DATE 101179
PAGE
12
305.
306.
3P7.
308.
309.
310.
311.
312.
313.
311.
315.
316.
317.
318.
319.
320.
321.
322.
323.
321.
325.
326.
327.
328.
329.
330.
331.
332.
333.
331.
336.
337.
338.
339.
310.
311.
312.
313.
311.
315.
316.
317.
318.
319.
350.
351.
352.
353.
351.
355.
.356.
357.
358.
359.
360.
1
1
1
1
1
1 1
1 1
1 2
1 2
1 2
1 1
1 I
1 1
1
1
1
1
]
1
1
1
1
176
177
178
179
180
181
182
183
181
185
186
187
188
189
190
191
192
193
191
195
196
197
199
200
201
WITH BACKGROUND OF '
E S - >'t
».
CUTSID't
URITE.RFPORT:
PUT PAGE EDIT ('STANDARD OF 't STANDARD,
RACKeROUNOt CITY.NAHft
• < - G A H H A VALU
• INDOORS OTJ-ER TRA^S TRANS
• FRACTION REDUCTION CHARACTERIST1C•t
•SITE U'ORK INDCORS VEHICLE OTHER
•E POPULATION FACTOR HIGH •)
(LIKE(5>» COL(3S)t At At At F(6t2)t LINE(7)t COL(50)t At
LINE(10)t At LTME(12)t A, At LINE(13)t At A>;
PUT SK IP( 2):
TO MONITOR : 1 -TO NUMBER. OF.MON I TORS;
PUT SKIP EDIT tSlTES(MONITOf?> t < HONIT ORS (MONI TOR t J) DO J = 1 TO 8))
(COL(l)r A(12)t FIB.3). 1(F(10t3))t F(12t1)t FdltDt F(13t3)>:
END:
PUT PAGE;
PUT EOT.T ('PERSON HOURS OF EXPOSURE FOR A STANDARD OF «t
STANCARO.NAMEt ' WITH BACKGROUND OF 't BACKGROUNDi CITY_NA«Et
•CONCENTRATION LOW MEDIUM
• EXCEEDED TOTAL ACTIVITY ACTIVITY
J
(LINf(5)t COL(B)t At At At F(6t2)t
LINT (7) t COL (30) , At
LINE: m , At LINE (io>» A>;
PUT SKIP(2)t
no CONCENTRATION.SUB : 1 TO NUMBER_OF_COMCEhTRAT IONS I
, TOTAL_EXPOSURE = 0.0:
00 LEVEL = 1- TO 3!
EXPOSURESICCNCENTRATION.SUBt LEVEL) =
EXPOSURES(CONCENTRATION_SUBt LEVEL)
* 17.1 * TOTAL.POPULATION:
TOTAL.EXPOSURE = TOTAL.EXPOSURE
* EXPOSURESICONCENTRATION.SUBt LEVEL);
END; /* END OF SUHHUG EXPOSURE »/
PUT EDIT (CONCENTRATIONS(CONCENTRATION_SUB)t
TOTHL.EXFOS'UREt
EXPOSURES(CONCENTRATION_SUBt l)t
EXPOSURES(CONCENTRATIOrj_SUBt 2)t
FXPOSURIES(CCNCF.NTRATIOH_SUB t 3) )
(COL(l)t F(9)t X(5)t E(15t3)t X(5). 3E(15t3)i:
PUT SKIP(2>;
END: /» END CONCENTRATION.SUB */
CLOSE FILE (EXPO);
PUT FILE (SUMS) FOIT (STANDARD.ISAflE t
BACKGROUNOt CONCENTRATIONSt CITY.NAMEt EXPOSURES)
(COL(l)t A(6)t F(]0t3)t COL (1) t20(F ( 10t 3)) t f.OL(l), A(ll),
COL ( 1) t 60(:E (20.8) ) ) ;
00 TO NEXT.STANDARC;
FINISHEP:
CLOSE FILE (SYSPRINT);
CLOSE FILE (SUMS);
IF (T_OPT) THEN
CLOSE FILE (OUMP>;
CLOSE FILE (SYSI-N):
RETURN:
END: /* END PROGRAM */
HIGH't
ACTIVITY'
-------
*** PL1A6S OF EXPO-2 *«* DATE 10117V PAGE 13
CROSS REFERENCE LISTING
ACTIVITY DECLARED*10) ALLOC<*(2I) 000007 BIT 1, 36 BITS) BIN*RY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 127
4CTIVITY.LFVELS DECLAREIH27) ALLOC(S(2) 000677 BIT 1, 12 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL
OIHEfJSIONdlSt 1:3) ALIGNED
SET 127 128
USED 128 132 165
AIR.OUALITY DECL4RECH34) ALLOC{$(2) 000770 BIT It 72 BITS) 8INARYC60) FLOAT REAL STATIC VARIABLE INTERNAL
OICEr.'SIONCi:20ii:25t 1 Z2) ALIENED
SET 81 81 81 ftl 81 81 81 81 93 94 96 100
USED 92 92 93 9<» 95 95 96 97 97 99 99 100 101 101 103 103 110 144
115
B DErLAREO<32) ALLOC<$<2> 000755 BIT 1, 72 BITS) BINARYUO) FLOAT REAL STATIC VARIABLE INTERNAL OIHENSION<1:5)
ALIGNED INITIAL
SET 32
USED 156 156 156 156 156
R»CKGROUNP OEfLAREC(21) ALLOCtJ(2l) 000617 BIT It 72 BITS) BIN*RY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 66
USED 68 115 116 118 118 175 161 193
CASP.NUMBER OECLAREOC41 ) M-LOC($(2) 005044 BIT 1, 36 BITS) eiNARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL DIMENSION (1: 4)
ALIGNED
SET 81 81 81 81
USEO 85
CHARACTFRISTIC.VALUE CECLARED(20> ALLOC($(2) C0061S BIT It 72 BITS) BINARYC60) FLOAT fitAL STATIC VARIABLE INTERNAL ALIGNED
SET 104
USED 10* 115 115 116 116 123
CITY.NAHE DECLAREC(38) ALLOC(S(2I) 005031 BIT It 9« BITS) NONVARYING CHAR ACT Efi (1 1 ) STATIC VARIABLE INTERNAL UNALIGNED
SET 81
USED 85 175 181 193
CTTY.NUPRFR DECLARED(39) «LLOC($(2) 00503H BIT It 36 BITS) BINARY(35tO) FIXED R£AL STATIC VARIABLE INTERNAL 0IMENSION<1 :4)
ALIGNED
SET si ai ai ai
USED 85
CONCENTRATIONS OECLAREC<25> ALLOC(S(2<) 000627 PIT It 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL 01 HENS I ON(1:20)
ALIGNED
SET 74
USED 79 1115 189 193
CONCENTRATION.SUB DECLAREC(I) ALLOCU<2) 000001 BIT It 36 BITS) BINARY(35tO) FIXED RE*L STATIC VARIABLE INTERNAL ALIGNED
SET 73 133 183
USED 74 135 145 165 165 186 186 187 1B9 189 189 189
CORRECTTON.l DECLARFO(36) ALLOC(*(21- 004711 BIT It 72 BITS) .BINARY(60 ) FLOAT REAL STATIC VARIABLE INTERNAL DIMENSION I 1:20)
ALIGNED
SET 81
USEO 93 102
CORRECTION.? OECLAPEC«37) ALLOC($(2I) 004761 BIT It 72 BITS) BINARYUO) FLOAT REAL STATIC VARIABLE INTERNAL DIHE NSI ON (1 120)
ALIGNED
SET 81
USED 94 102
nAILY.STANOARD OECLAREO(56) ALL OCI'S ( 21 005246 HIT It 1 BIT) NONVARYING IUT(1) STATIC VARIABLE INTERNAL UNALIGNED
SET 70 71
USEO 114
PAY OrCLAREO(12) ALLOC($(2!) OOC011 BIT 1» 36 BITS) BINARY(35tO) FIXED RLAL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 132 165
DAYS.TN.INTfRVAL OfCL ARED (2>8*> ALLO'C'<*(2) 000735 BIT It 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL 0IMENS ION ( 1 : 3 )
-------
*** PL1ABS OF fXPO-2 *»*
DATE 101179
PAGE
14
ALIGNED I
SET 28
USED 165
PAY_OF_UFFK DECLAREC(7) ALLOC($(2) 00000i» BIT 1» 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
NOT REF
PUMP OECLAREC(51> *LLOC(t(12> OG0004 ) FILE STATIC CONSTANT EXTERNAL EHV1RONMENT (? ) STREAK OUTPUT PRINT
USED 61 68 77 79 83 85 108 110 121 123 130 13? 135 138 1 4 1 113 161 163
171 173 198
ERO°T DFCLARED153) ENTRY CONSTANT EXTERNAL
SET 57
NOT USED
FXP DECLARED«I5> RUILTIN
NOT SET
USED 96 100 I 103 1!55
FXPO OECLAREOI50) ALLOC(S(11> 000004 » FILE STATIC CONSTANT EXTERNAL ENVIRONMENTS) STREAM INPUT
USED 124 125 127 1912
FXPOSURFS OECLAREn(43J ALLOC($<2') 005051 BIT 1, 72 BITS) 8IN*RY<60) FLOAT REAL STATIC VARIABLE INTERNAL
DIHENSIONtl:20t113) ALIGNED
SET 126 165 186 v
USED 165 173 186 187 189 189 189 193
EXP0.2 DECLARED(l) «LLOC(t(l) 004714 ) ENTRY CONSTANT EXTERNAL
NOT REF
F DEHLAREOOl) ALLOC(f<2') 000747 PIT It 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 155
USED 156
FTNISHEO DECLAREOU95) »LLOC($(1) 004631 ) LABEL CONSTANT INTERNAL
USEtl 63
FR4CTION_£XCEEOING DECLAREO(23) 4LLOC($(21 000623 BIT 1, 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 156 158
USED 158 163 165
FRArTION_.':XCEEDTNG_FOUNC D FCL APED < 160) ALLOC(Kl) G03624 ) LABEL CONSTANT INTERNAL
L'SEO 159
GEO«ETRTr_HF*N CECIAREPC30) ALLOC<$<2) 000745 BIT It 72 BITS) BIN*RY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 144
USED 145
GET_ACTIVITY_LEVELS OECL AR ED (127) />LLOC<$:<1> C02633 ) LABEL CONSTANT INTERNAL
USED 174
HOUR OECLAREDtS) ALLCC($(2) 000002 BIT If 36 BITS) BINARY(35»0) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 81 81 31 81 91 127
USED 81 81 81 81 61 81 81 81 92 92 92 93 93 94 94 95 95 96
96 97 97 99 101 132 144 145
HOUR.25 DECL*REC(35) ALLOC<*(2» 004710 BIT 1, 36 BITS) BIN«RY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
INITIAL
SET 35
NOT USED
HOUR_TYPE DFCLAREIH42) ALLOC($(2'J 005050 BIT 1, 36 BITS) BIN«RY«35tO> FIXED REAL STATIC VARIABLE INTERNAL 01 HENS I ON(1 14)
ALIGNED
SET 81 81 81 i81
USED 85
J IMPLICIT ALLOC(C00021 BIT It 36 BITS) BINARY<35tO) FIXED REAL AUTOMATIC VARIABLE INTERNAL ALIGNED
SET 178
USED 178
LEVfL DEfLAREC(ll) ALLOC($(21) 000010 BIT 1, 36 BITS) BIN«RY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED.
SET 127 164 185
USED 127 165 165 1165 186 186 187
LOG CECLAREOU6) BUTLTIN
WOT SET
-------
**» PL1ABS OF EXPO-2 ••* DATE 101179 PAGE 15
USED 103 145 145
LOO.NORMAL.DISTRIBUTION DECL ARE 0 C 14 4) ALLOC(S<1) 003364 » LABEL CONSTANT INTERNAL
NOT REF
MAX DECLASECM47) BUILTIN
NOT SET
USED 10H
METEOROLOGY DECLARECO4) ALLOf(S(2l> OP0013 BIT It 36 BITS) eiN«RY<35.0> FIXED RtAL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 132
HICRO.ENVIRONr'ENT DECLARED?) ALLOC($(2) COOC06 BIT 1» 36 BITS) B IN A RY < 3 5 »0 ) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 88 139
USED 68 101 144 165
MONITOR OECLAREDC8) ALLOC($(2) 000005 BIT 1, 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 80 87 117 136 177
USED 81 81 Bl ;81 81 61 81 81 81 81 88 88 89 92 92 93 93 93
91 94 9* 915 95 96 96 97 97 99 99 100 100 101 101 102 102 103
103 103 104 1C5 118 118 118 138 141 144 144 145 165 178 178
MONITORS OECLAREOU6) ALLOC<$(2) 000015 HIT 1, 72 BITS) 8INARYI60) FLOAT REAL STATIC VARIABLE INTERNAL
OIKENSIONC K20t i:;8) tLIGNEC
SET 88 103 105 118
USED 1C4 118 118 1'23 144 144 165 176
NEGATTVf.X OECLAREOI33) ALLOC($(2t 000767 BIT If t BIT) NONVARYING BIT(l) STATIC VARIABLE INTERNAL UNALIGNfEO
SET 148 152
USED 157
NEXT_ST*Nr«RD DEfL»REOC112) AlLOCtlM) 002326 ) LABEL CONSTANT INTERNAL
USED 194
NUHPER.CF.CON'CCNTRATIOIVS OECLAREP(26) ALLOC(000017 BIT It 36 BITS) BIIURYC35tO) FIXED HEAL AUTOMATIC VARIABLE INTERNAL ALIGNED
SET 72
USED 73 79 133 183
NUM"ER_OF_MONITORS 0£CLARED(3) 4LLOC(S(2) 000000 BIT It 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 66
USED 68 80 87 117 136 177
OPEN.ACTIVITY.LFVELS OECL A RED (124) ALLOC(Kl) 002541 ) LAGEL CONSTANT INTERNAL
USED 111
OPTIONS DECLAREOC54) ALLOC($(1«) 000000 BIT It 36 BITS) NO.MVARYING BIT<36) STATIC VARIABLE EXTERNAL UNALIGNED
K'OT SET .
USED 58 57
REDUCTION_NCEDEO DECLAREDC24) ALLOC<$(2) OOC625 BIT It 12 BITS) EINARYUO) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 115 116
USED 118 123
RESIGN DECLAREOU3) ALLOCIK2) 000012 BIT It 36 BITS) BINARY(35tO> FIXED R£AL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 132
SFASON DECLARECC6) ALLCCUI2) OOOC03 BIT It 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 132
SITES OECL AREOU7) ALLOC(J(2) 000515 BIT 1, 108 BITS) NONVARYING CH AR ACTES (12) STATIC VARIABLE INTERNAL
PI PENS ION ( K20) UNALIGNED
SET 88
USED 89 178
SITr_NUM8FR OrrLAREO(40) ALLOC($(2) 005940 BIT It 36 BITS) EINARY(35tO) FIXED RLAL STATIC VARIABLE INTERNAL DIMENSION*1:4)
ALIGNED
SET 81 81 81 81
USED 85
STANDARD DErLAREDIlS) ALLOC($(2) 000611 BIT It 72 BITS) BINARY<60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 1)2
USED 113 115 116
-------
*** PL1ABS OF EXPO-2 *** DATE 101179 PAGE 16
STAMDARD.NAME nECLAREOO9) ALLOCC$t2> 000613 BIT It 51 BITS) NONVARYING CHARACTER(6) STATIC VARIABLE INTERNAL UN»LIGNEO
IN ITIAL
SET 19 113
USED 175 181 193
STANOARn.TYPE IMPLICIT ALLOCT000020 BIT It 36 BITS) BI NARY(35t 0 ) FIXED REAL AUTOMATIC VARIABLE INTERNAL ALIGNED
SET 66
USED 69
SURSTR CONTEXTUAL RUILTIN
NOT SET
USED 58
SUMS DECLAREn<52) ALLOC($(13) 00000* ) FILE STATIC CONSTANT EXTERNAL ENVIRONMENT (?l STREAM OUTPUT PRINT
USED 193 1S6
SYSIN OFrLAREO<49) ALLOC($(10> 000004 ) FILE STATIC CONSTANT EXTERNAL ENV1RONHENT(?> STREAM INPUT
USED 62 67 66 72 74 81 88 112 199
SYSPRTNT DECLARECC48) ALLOC(${9) 000004 ) FILE STATIC CONSTANT EXTERNAL ENV IRONKENT (?1 STREAH OUTPUT PRIN'T
USED 59 89 90 .92 95 97 99 101 102 175 176 178 160 181 182 189 190 195
T DECLAREO(3l> ALLOC($(2) 003751 BIT It 72 BITS) 8INARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 154
USED 156 156 156 - 156 156
TOT«L. EXPOSURE DE CL AREC (44) ALLOC($<2) 005244 HIT 1» 72 BITS) BINARY(60J FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 184 187
USED 187 189
TOT»L_POPUL«TTON OFCLftREO(22) ALLOC<«(21 000621 BIT 1, 72 BITS) 8INARY(60> FLOAT RF.AL STATIC VARIABLE INTERNAL ALIGNED
SET 66
USED 68 136
TYPF DECLARETdS) ALLOC($(2I) OOC01« BIT If 36 BITS) 8IN*RY<35fO) FIXED RLAL STATIC VARIABLE INTERNAL ALIGNED
SET 127
USED 132
T_OPT OECLAREO(55) ALLOC($(15) OOOOOC BIT If 1 BIT) NONVARYItG BIT(l) STATIC VARIABLE EXTERNAL UMALIGHED
SET 58
USED 60 67 76 >78 82 84 107 109 120 122 129 131 134 137 140 142 160 162
170 172 197
UFI^ULL.OELTA DECLAREDC29) ALLOC{$(21 000743 BIT It 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
NOT REF
URITE.RFPORT DECL AREfl 1175) ALLOCdd) 004043 ) LA3EL CONSTANT INTERNAL
USED 125
X DECLARED(31) ALLOC($(2I) 000753 BIT 1, 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 145 149
USED 146 149 154 155 155
*•*• MO ERRORS OR WARNINGS IN ABOVE PROGRAM
END PL1 3033 IB/»NK 3402 DBAKK
18:23:?! PL1
PRUK 00:00:05.129 DISC 00:00:00.792 TAPE oo:oc:oo.H4 i/o oo:oo:06.036
CCFR 00:00:07.167 CAU 00:00:04.588 MEflY 00 :00 :0 3.094-0025K
-------
*** PL1ABS OF EXPO-2 «»*
DATE 101179
PACE:
17
SPLT.L *1AP.EXPO-2
CLT007 SL73R1 10/11/79 18:23:31 <17t)
000001 013 IN EXPO-2
LIST THE HAP INSTRUCTIONS
END TLT.
18:23:31 ELT
DRUM 00:00:OP.029 DISC 00:CO:C0.261 TAPE 00:00:00.COC I/O 00:00:00.250
CC.r.R 00:00:00.501 CAU 00:00:00.000 MEMY 00 : 00 : 00. 0 39-0007K
-------
PL/I Program for 8-Hour CO Exposures
-------
»** PL1ABS OF EXPO-8 •*»
DATE 11027S
PAGE
aPLltOETRS XSiEXPO-8
PL1 7R1A SL74R1 11/02/79 08:52:18, (->0>
11.
2.
3.
4.
5.
6.
7.
8.
9.
10.
1 1.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
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31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
13.
44.
45.
46.
47 .
48.
49.
50.
51.
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
JSOURCE.EXPO-8 . ADD THE PROGRAM
EXPO_8_HR: PROCEDURE OPTIONS (MAIN):
DEFAULT (FLOAT IS BINARY 8 " CONSTANT) PRECI SI ON(60) ;
DECLARE NUMBER_OF_MONITORS FIXED BINARY STATIC:
DECLARE DISTRIBUTION FIXED BIKARY STATIC:
DISTRIBUTION = 1 => UICBULL
DISTRIBUTION = 2 => LOG - NORMAL
*/
*/
DECLARE: WIEBULL
DECLARE LOn.NORHAL
DECLARE CONCENTRATICN.SUB
DECLARE HOUR
DECLARE DAY_OF_'WEEK
DECLARE MONITOR
DECLARE !«ICRO_ENVIRONMENT
DECLARE LEVEL
DECLARE lONITORSC20t8>
MONITORS
= >
RATIO FOR MICRO-ENVIRONMENT
RATIO FOR KICRO-ENVTROKKENT
RATIO FOR MICRO-ENVIRONMENT
RATIO FOR MICRO-ENVIRONMENT
RATIO FOR K1CRC-ENV JROHMENT
FRACTION OF TOTAL POPULATION
REDUCTION FACTOR AT SITE TO
CHARACTERISTIC VALUE FOR THE
1
2
3
5
AT THIS SITE
MEET STANDARD
SITE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
SITES(20)
STANDARD
STANOARD.NAME
CHARACTERISTIC.VALUE
BACKGROUND.
TOTAL_POPULATION
POPULATIONU2)
FR«CTION_EXCEEDING
REDUCTION.NEEDED
CONCENTRATIONS120)
NUMBER_OF_CONCENTRATIONS
GEOrETR'IC.MEAN
«Ff T» X)
2) STATIC;
FLOAT BIKARY STATIC!
CHAR(6) STATIC INIT l
FLOAT BINARY STATIC;
FLOAT BIKARY STATIC;
FLOAT BINARY STATIC;
FLOAT BIKARY STATIC;
FLOAT BINARY STATIC;
FLOAT BIK'ARY STATIC:
FLOAT BINARY STATIC;
FIXED BINARY STATIC:
AS IS«);
FLOAT
FLOAT
BIKARY
BINARY
STATIC;
STATIC;
TERM? IN THE LOC - NORMAL IKTEGRATIOK
-------
*** PL1ABS OF EXPO-B •**
DATE 110279
PAGE
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
36.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
96.
99.
100.
101.
102.
103.
104.
105.
106.
137.
108.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
CEHLARf E(5)
*/
/*
FLOAT BINARY STATIC If,'IT(
*0.31938153.
-0.356563782.
+1.781477937.
-1 .82125597E,
+ 1.33027442V) ;
THE EXPANSION COEFFICIENTS FOR THE INTEGRATICN
DECLARE NEGATIVE_X BIT(l) STATIC:
HE CLARE AIR.QUALITY (NUKBER.OF.MOMTCRS.-t:169.5)
FLOAT BINARY CONTROLLED!
AIR.CUALITY (MONITOR. HOUR. VALUE)
HOUR = 169 => OVERALL VALUES
VALUE
VALUE
VALUE
VALUE
= 4
1 => GEOMETRIC DEVIATION (1 HR DATA)
2 => GEOMETRIC MEAN OR LCG THERE OF (1
3 => REDUCED 1 HR MEAN
= •> GEOMETRIC DEVIATION (8 HR DATA)
HR DATA!
VALUE : 5 => GEOMETRIC KEAN OR LOG THERE OF (8 HR DATA)
CECLARE
DECLARE
DECLARE
DECLARE.
DECLARE
CECLARE
DECLARE
DECLARE
DECLARE
DECLARE
DECLARE
CORRECTION_l(20)
CORRECTION_2(20)
CORRECriON_4(20)
CORRECTION_5(20)
CITY.NAKE
CITY.NUHEER(4)
SITE_NUH3ER(4)
CARO.N'UKBER(4)
HOUR_TYPE(4)
EXPOSURES(20.3)
FIXED BIN'ARY STATIC INIT
FLOAT BINARY STATIC.'
FLOAT BINARY STATIC;
FLOAT BINARY STATIC;
FLOAT BINARY STATIC!
CHAR(ii) STATIC:
FIXED BINARY STATIC!
FIXED BINARY STATIC;
FIXED BINARY STATIC;
FIXED BINARY STATIC;
FLOAT BINARY STATIC:
(16V) :
EXPOSURES (CONCENTRATION. ACTIVITY LEVEL)
DECLARE TOTAL.EXPOSURE
DECLARE EXP
DECLARE LOG
CECLARE PAX
DECLARE SUBSTR
CECLARE SYSPRIN-T
CECLARE SYSIN
CECLARE EXPO
FLOAT BINARY STATIC:
BUILTIN';
BUILTIN;
EUILTIN;
BUILTIN:
FILE OUTPUT STREAM PRINT
ENV (CONSECUTIVE APRINT RECSIZE (132)
TOPHARGINU) BOTHARGIN (0) PAGSIZE (66)):
FILE INPUT STREAK
ENV (CONSECUTIVE AREAD RECSIiE (80))}
FILE INPUT STREAM
-------
*** PL1ABS OF EXPO-8 *•*
DATE 110279
PAGE
109.
110.
111.
112.
113.
114.
1 16.
117.
1 IB.
119.
120.
121.
122.
123.
124.
125.
126.
127.
128.
129.
130.
131.
132.
133.
134.
135.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
19
50
DECLARE DUMP
DECLARE SUffS
51 DECLARE EROPT
52 DECLARE OPTIONS
53 CECLARE T_OPT
54 DECLARE 0_OPT
55 DECLARE ACTIVITY_IN(24)
56 DECLARE LEVEL_IN(24)
57 DECLARE ACTIVITYS(-6:168)
58 DECLARE LEVELS(-6:i68)
59 DECLARE
60 DECLARE LEVEL.NAME(3)
61 DECLARE PERCENT_IN_GROUP_IN
62 DECLARE PERCENT_IN.CROUP(168)
63 DECLARE J
64 DECLARE OCCUPATION
65 DECLARE SMSA
66 CECLARE SUfi_GROUP
67 DECLARE STANDARO.TYPE
68 CECLARE DAILY.STANDARD
69 tPAGE;
ENV (CONSECUTIVE AREAQA RECS1ZE (132)>:
FILE OUTPUT STREAM PRINT
ENV (CONSECUTIVE APRfJTA RECSIZE (132)
TOPMARGIN(6) BOTMARGIN (0) PAGSIZE (66»;
FILE OUTPUT STREAM PRINT
ENV (CONSECUTIVE APRNTA RECSIZE 180)
TOPKARGINU ) BOTPARGIN (0) PAGSIZE (66));
ENTRY (BIT(36)>;
BIT(36> STATIC EXTERNAL;
FiT(i) STATIC EXTERNAL:
BiT(i) STATIC EXTERNAL;
CHAR<2) STATIC:
cH»R(i) STATIC;
FIXED BINARY STATIC;
FIXED BINARY STATIC:
CHAFM2) INIT (
•lu ••»oi*r *TV« t «CT•t »OD*) STATIC;
CHAR(D INIT (-L*f 'N't »H« ) STATIC;
FLOAT BINARY STATIC;
FLOAT BIIVARY STATIC;
FIXED BINARY STATIC;
FIXED BINARY STATIC;
FIXED BIPJARY STATIC;
FIXED BINARY STATIC;
FIXED BINARY STATIC;
EiT(i) STATIC;
-------
**« PL1A5S OF EXPO-8 *** DATE 110279 PAGE
136. CALL EROFT(OPTIONS);
137. 1 70 T_OPT = SUBSTR(OPTIONS,30,1 > !
136. 1 71 O.OPT ; SUESTR(OPTICNS.25.1):
139. 1 72 OPEN FILE (SYSPRINT);
110- 1 73 OPEN FILE (SUMS)!
111. 1 7<» IF (T_OPT • O.OPT) THEN
1H2. OPFN FILE (DUMP)!
113. 1 76 OPEN FILE (SYSINIS
l>:
Iit9. 1 81 *LLCCATE AIR.CUALITY;
150. 1 82 IF (T.OPT) THEN
151. PUT FILE (DUfP) DATA (NU PB ER_OF .PONITORS . DISTRIBUTION. BACKGROUND.
152- TOTAL_POPUL/mON. STANOARD.TYPE) i
153. 1 81 IF (STANnARO_TYP£ - 1) THEN
151. DAILY.STANDARO = 'I'SJ
155. 1 86 ELSE
156. OAILY.STANDARO = *0'B;
157. 1 87 GET EDIT (POPULATION) (l?;
168. 1 96 IF (T.OPT) THFN
169. PUT FILE (DUMP) DATA (NUMBER_OF_CONCENTRATIONS. CONCENTRATIONS);
170. 1 98 CO MONITOR = 1 TO NUHBER.OF.HON I TORS:
171. 1 1 99 fiET EDIT (CITY.NAHE.
172. CITY.NUMRERdl). SITE_NUHBER(1 ) . HOUR.TYPE<1). CARO.NUMBEK(1),
173. (AIR_OUALIT'Y(MONITOR. POUR. 2). A I R_CU AL IT Y ( FON ITOR . HOUh. 1)
174. ' DO HOUR = 1 TO 6) .
175. CITY.NUMPERTm . S ITE .NUMB ER (2 > . HOUR.T YPE ( 2 ) . C ARO.NUMBEK (2 ) .
176. I AIR.OUALIT'Y (MONITOR. HOUR. 2). AI R_ CU» L I TY « MONITOR . HOUR. 1)
177. DO HOUR r 7 TO 13).
178. C1TY.NUKBER'(3) , S IT E.NUFIR ER (3 ) . HOUR.T YFE ( 3 ). C 4RD.NUHBEK ( 3 ) .
179. (AIR.OUALITYIHONITOR. HOUR. 2). AIR_QUALITYCHONITOR. HOUh. 1)
180. 00 HOUR r 1« TO 20).
181. CITY.NUMBER (H) , S IT E.NUHB ER ( fl ) . HOUR.T Y FE (<«). C ARD.KUMB ER <«!) .
182. (ATR_OUALITY(HONITOR, HOUR, 2). AIR.QUALITY(HONITOR, HOUK. 1)
183. CO HOUR : 21 TO 2t» 169),
18. F(2), F(3). F(2). F(2), 12(F(5»,
186. 3(COL(1). F(3). F(3>. F(2). F(2). 14(F(5»)>:
187. 1 1 100 IF (T.OPT) THEN
188. PUT FILE (DUMP) PAGE:
189. 1 1 102 IF (T_OPT) THEN
190. PUT FILE (DUMP) DATA (CITY_NAHEt CITY.NUMBER. SITE_NUH8tR.
191. CARO.NU'HBER. HOUR_TYPE);
192. 1 1 10<» 00 HOUR = 1 TO 21 ;
-------
193. I 2 105 AIR_OUALITY(MONITOR. HOURt 1) = AIR_QUALITY(MONITOR, HOUR. 1)
191. * CCRRECTION.l(MONITOR);
195. 1 2 106 AIR_QUALITY(!HONITOR , HOUR. 2) = AIR_QUA|_ I TV (NONI TOR. HOUS, 2>
196. * CORRECTION_2(HONITOR>:
197. 1 2 107 DO J = 74, IB. 72. 96. 120. 144;
198. 1 3 108 AIR_QUALITY(MONITOR. HOUR * J. 1) =
199. AIR_OUALITY (MONITOR. HOUR. 1)?
200. 1 3 109 ftlR.OUALITY (KONITOR. HOUR •• J. 2) =
201. AIR_QUALITY;
2t2. i 3 110 END;
203. i 2 in END;
204. 1 1 112 ENO;
205. 1 113 DO MONITOR = 1 TO NUMflER_OF_MONITORS;
206. 1 I 111 GET EDIT (CITV_:N«HE.
207. CITY.NUMBER'd ). SITE_NUMBER(I>. HOUR.TYPE(1)• CARD.NUKBEK(1>,
208. (AIR.OUAL1T'Y(MOMTOR. HOUR. 5). AIR_CUALITY(HONITOR. HOUh, 4)
209. DO HOUR = 1 TQ 6).
210. CITY_NIIM8F. S(!2). SI TE_NUMBER(2)• HOUR_TYP E ( 2) . CARD.NUMBEk(2)»
211. (AIR_aUALIT'Y(MOMTOR» HOUR. 5)» AI R_CU ALITY (f.ON IT OR. HOUR. 4)
212. 00 HOUR = 7 TO 13).
213. CITY_NIJMBER(-3) . S I TE_NUMBER( 3 ) . HOUR.TYP E < 3) . C4RO_NUMBEK ( 3 ) .
211. ( AIR_QUALIT'Y(HONITOR. HOUR, 5). AI R_CU ALIT Y C HON IT OR . HOUR. HI
215. 00 HOUR = If TO 20),
216. CITY_NUM6ER. Ft2)» F(2). 11(F(5)))>:
222. 1 1 1-115 IF (T_OPT) THEN
223. RUT FILE (DUMP) PAGE!
221. 1 1 117 IF (T_OPT) THEN
225. PUT FILE (DUMP) DATA ( C IT Y_N AIHE» CITY.NUHBER. SITE_NUM6ER.
226. CARD_NUMBER. HOUR_TYPE);
227. 1 1 119 AIR.GUALITY (MONITOR. 149. 5) = AIR.OUALITYtKCNITOR. 169. 5) - 0.13i;
228. 1 1 120 DO HOUR r 1 T0~2«;
229. i 2 121 AIR_OUALTTY:(HOMTOR . HOUR, 4> - AIR_CUALITY(KONITOR. Hour,, t»
230. * CORRECTION_'»(f10NUOR);
231. 1 2 122 AIR_QU«LITY(HONITOR, HOUR. 5) = AIR.QUALITY(MOW I TOR. HOUS. 5)
232. + CORRECTION.5IKONITOR) - 0.134;
233. 1 "i 123 DO J ~ 24, H 8. 72. 96. 120, 144;
234. 1 3 124 AIR_QUALITY(HONITOR. HOUR » J, 4) -
235. AIR_QUALITY (MONITOR, HOUR. 4);
236. 1 3 125 AIR_QUALITY(MONITOR. HOUR * J. 5) =
237. «IR_OUALITY(HONITOR. HOUR, 5)J
238. i 3 126 FND;
239, i ? 127 END;
210. i i 128 END; /* END OF READIHG AIR_CUALITY DATA */
241, 1 129 DO HOUR = -6 TO 0!
2«2. 1 1 130 DO KGNITOR = 1 TO NUKB ER_OF_C,ON ITORS;
2«3. 1 2 131 «IR_OUA:LITY(KON1TOR. HOUR. 2) =
244. AIR_OUALITY(HONITOR. HOUR » 168. 2)1
2«5. i 2 132 CND:
246. 1 1 133 ENO:
2«7. I 134 TO HOUR = -6 TO 169!
248. 1 1 135 00 MONITOR = 1 TO NUMBCR.OF.HONI TORS•
2«9. 1 2 136 MR.OUALITY (MONITOR. HOUR. 2) =
*»*'PLIABS OF Expo-fl •*« DATE' 110279" PAGE
-------
*** PL1ABS OF EXPO-8 *** DATE 110279 PAGE
250. EXP (ATR.OUALITY(MONITOR. HOUR. 2>»!
251. 1 2 137 AIR_OUALITY(HONITOR, HOUR. 5) =
252. EXP (AIR.OUALITY (MOMTOR, HOUR. 5) ) ;
253. i 2 138 END;
254. i i 139 END;
255. 1 140 CHARACTERISTIC.VALUE = 0.0;
256. 1 141 CO MONITOR = 1 -TO NUMBE R.OF.HON I TORS:
257. 1 1 142 GET EDIT ((MONI TORS(HONI TOR,MICRO_ENVIRQNMENT )
258. CO MICRO.ENVIRONMENT = 1 TO 6), /* t IS THE FRACTION POP »/
259. SITES(HONITOR))
260. (COL(21>. 5F(5,2>. F(6»l)» COL<55). A<12» :
261. 1 1 143 MONITORS(HOI\II TOR , 8) - EXP ( LOG (AIR_OU ALITY«HONI TOR, Io9« 5))
262. + 3.686 * A IR_OUAL ITY (KOM T OR. 169. 4»:
263. 1 1 144 CHARACTERISTIC.VALUE = HAX(CHAR4CTERISTIC_VALUE.
264. HONITORMMONITOS. 81)5
265. 1 1 145 /* END OF GETTING CHARACTERISTIC VALUES */
266. MONIT03S(«ONIT03» 7) = 1.0! /* SET FOR AS IS EXPOSURE */
267. 1 1 146 DO HCUR = -6 TO 168;
268. 1 2 147 AIR.QUALITY(MONITOR. HOUR. 3) =
269. (10NI-TORS(NONITOR. 7) * A IR_QU ALI T Y(HON ITOR. HOUR, 2>;
270. i 2 i4a END;
271. i i 149 END;
272. 1 150 CO MONITOR = 1 -TO NUMBER.OF.MON1TORS;
273. 1 1 151 PUT PAGE EDIT ('SITE •• SITES(MCNITOR). »1 - HOUR DATA'.
274. •< MON > ',
275. •< TUiE > •,
276. ' •< WED > •»
277. '< THU > '.
278. •< FRI > •,
279. •< SAT > •,
280. •< SUN > *•
281. - 'STAND GEO •.
282. 'STAND GEO '.
283. 'STAN'D GEO •»
284. 'STAND GEO •,
285. 'STAND GEO ',
286. 'STAND GEO ',
287. . 'STAND GEO ',
288. 'HOUR ',
289. • OEV MEAN ».
290. • OEV MEAN '.
291. ' DEV MEAN '.
292. ' OEV MEAN '. .
293. • DEV MEAN •,
294. • OEV MEAN • .
295. • DEV MEAN •)
296. (LINE(3>. A, A. COL(40)f A.
297. IINEC5). COL(IO). 7A.
298. LINE 16).: COL (10). 7A.
299. LINE(7)'» COL<1>» 8A>;
300. 1 1 152 PUT SKIP<2>:.
3fH. 1 1 153 00 HCUR = 1 TO 24;
302. 1 2 154 PUT SKIP EDIT .
304. AIR_QUALITY(MONITOR. HOUR » 0. 2>.
305. AIR_QUALITY(HOMTOR. HOUR •» 24. 1).
306. AIR.QUALITY(HONITOR. HOUR + 24. 2>.
-------
*** PL1ARS OF EXPO-8 **•
DATE 110279
PAGE
10
307.
308.
309.
310.
11 1.
312.
313-
314.
315.
316.
317.
318. 1 2 155
319. 1 1 156
3?0.
321.
322.
323.
324. 1 1 157
325.
326.
327.
328.
329.
330. 1 1 158
331.
332.
333.
334.
335.
336.
337.
338.
339.
340.
341.
342.
343.
344.
345.
346.
347.
348.
349.
350.
351.
352.
353.
354.
355.
356.
357. 1 1 159
358. 1 1 160
359. 1 2 161
360.
361.
362-
363.
PUT
PUT
PUT
HOUR
HOUR
HOUR
HOUR
HOUR
HOUR
HOUR
HOUR
HOUR
HOUR
* 48.
« 48.
» 72.
* 72.
* 96.
+ 96.
* 1 20
« 120
+ 144
* 144
1 )
2)
1)
2)
1)
2)
. 1)
. 2)
. 1 )
. 2)
AIR_OU*LITY(MONITOR.
AIR.OUALITY (KONITOR*
AIR_OUALI TYCMONITOP..
AIR_GUALITY(00NITOR.
AIR_QUALlTY(f10fJITOR.
AIR .QUALITY (ROM TOR.
AIR.OUALI TYU10NI TOR.
AIR_QUALITY(MONITOR*
AIR.QUALITY(MONITOR.
AIR_QUALITY(HONITOR.
(F03). 7(F(8.3>. F(7.3)1):
FNO;
SKIP(4) EDIT COVERALL STANDARD CEVIATIOI\ = •.
AIR_QUALITY(KOMITOR. 169. 1).
• OVERALL GEOMETRIC MEAN = ',
AIR_OUALITY(KONITOR» 169. 2))
( COLC30) . 2( A, F(7f 3» >:
SKIP(3) EDIT (
•CORRECTION TO THE STANDARD DEVIATIONS WAS '.
CORRECTION.1(MOW ITCR).
« CORRECTION TO THE MEANS WAS '.
CORRECTION.2(MONIT OR)1
, A. FI8.5). COL(30)> A. F(8.5»:
PAGE EDI-T ('SITE '. SI TES (MONI TOR ) . '8 - HOUR DATA'.
•< MON > •»
•< TUE > ',
•< WED > •»
•< THU > '.
•< FRI > *.
•< SAT > • .
.< SUN > ',
•STAND GEO •,
•STAND 6EP '.
• STAND
•STAND
•STAND
•STAND
• STAND
•HOUR
• OEV
• DEV
• DEV
• DEV
• DEV
• DEV
• DEV
GEO
GEO
GEO
GEO
GEO
MEAN •,
KEAN '»
MEAN «,
MEAN '»
MEAN '•
KEAN •»
MEAN ')
(LINE (3) . A. A. COL(40).
L INE(5) .' COL( 10) . 7A.
LIf.'E (6)'. COL (10) . 7A.
L INE(7) . COL(I). 8A);
PUT SKIP (2)5
00 HOUR r 1 TO 24:
PUT *;KIP EOIT (HOUR.
AIR.OUALITY(MONITOR.
AIR.OUALITYIHONITOR.
A IR_QUALITY(MONITOR.
AIR_QUALITY(HONITOR.
A .
HOUR
HOUR
HOUR
HOUR
Ot
0.
24.
24.
4) .
5).
4) .
5).
-------
*•* PL1ABS OF EXPO-8 ***
DATE 110279
PAGE
1 1
364.
365.
366.
367.
368.
369.
370.
371.
372.
373.
374.
375.
376.
377.
378.
379.
3RD.
381.
382.
383.
384.
385.
386.
387-
388.
389.
390.
391.
392.
393.
394.
395.
396.
397.
398.
399.
400.
401.
4C2.
403.
404.
405.
406.
407.
408.
409.
410.
41 1.
412.
413.
414.
415.
416.
1 2
1 1
1 1
1 1
1
1
1
1
1
1
1 1
I t
1
1
1
2
2
1
1
1
162
163
164
165
166
167
168
169
171
172
173
174
175
177
179
180
181
182
183
184
186
188
NEXT_S
IF
IF
IF
IF
*PAGE;
HOUR *
HOUR ••
HOUR »
HOUR *
HOUR •»
HOUR +
HOUR «
HOUR »
HOUR *
HOUR *
48.
48.
72.
72.
96.
96.
120.
1 20.
1 44.
144 .
4)
5)
4)
5)
4)
5)
4 )
5)
4)
5)
AIR_QUALITY(HOMITOR.
AIR_GU*LITY(CONITOR.
AIR_QUALI TYCOON I TOR.
AIR.GUALI TY(MONITOR.
A1R_OU».LJTY (MONITOR.
AIR_QUALI TYC10NITOR.
AIR.CUALITY (fOMTOR.
AIR.QUALITYIMONITOR.
AIR_OUAl_ITY(HONITORi
* IR_ QUALITY (MONITOR.
(F t3> . 7(F(8.3) • F(7»3)) ) ;
END;
PUT SKIP(4) EDIT COVERALL STANDARD DEVIATION = '.
AIR_OUAL'I TYCKONITOR » 169. 4).
• OVERALL GEOKETRIC KEAN = '.
A IR_OUALI TY(MONITOR. 169. 5>>
(COL(30I) » 2(A, F (7,3) » J
PUT SKIP(3) EDIT (
'CORRECTION TO THE STANDARD DEVIATIONS UAS ••
CORRECriON_4(HOMTOR) .
' CORRECTION TO THE MEANS WAS '.
rORRECT:ION_5(HONITOR) )
(CCLC30). A, F(8.5). COL<30). A. F(8.5)>; '
END. .
GO TO OPEN_ACTIVITY_LEVELS;
r ANDARD:
GET EDIT (STANDA1RO) f COL ( 1) i F(5>)!
PUT STRIf.G tSTANDARC.NAHE) EDIT ISTANOARC) (F(6t2»:
IF (DAILY_STAND:ARD) THEN
REDUCTION.NEEOED = ( CHAR ACTER 1ST IC.VALUE * 0.852 - STANDARD) /
(CHARACTERISTIC.VALUE * C.852 - QACKGROUKD);
ELSE
REDUCTION_NEEDED = 1 CHAR ACTER ISTTC_VALU£ - STANDARD) /
(CHARACTER1STIC.VALUE - 6ACKGROUHD):
DO MONITOR : 1 TO NUM BER_OF_MONITORS ;
MONITORStHOWITOR. 7) = ( (MONI TORS (MOM ITO R . 8) - BACKGROUND)
» (1.0 - RECUCT ION.NEEDED) « BACKGROUND) / POM TORS (HON I TOR t 8)
END; /* .END OF SITE REDUCTIONS «/
(T.CPT) THEN
PUT FILE (DUMP) PAGE;
(T_OPT) THEM
PUT FILE (DUMP) DATA (MONITORS. REOUCT I ON_NEEDE D . CHAR ACTER 1ST IC.VALUE
DO HOUR = -6 TO 169;
CO r-ONITOR = 1 TO NUPBER_OF_PONITORS;
AIR.OUALITY (MONITOR. HOUR.
MONMORS(MONITOR. 7) *
END;
END;
tT_OPT) THEN
PUT FILE (DUMP) PAGE;
(T.OPT) THEN
PUT FILE (DUMP) DATA ( »I3_OUAL I TY ) ;
3) =
A IR_OU ALI T Y «HON I TOR . HOUR. 2);
-------
*** PL1A8S OF EXPO-8 *»*
DATE 110279
PAGE
12
1 17.
416.
H 19.
420.
421.
422.
133.
424.
425.
426.
427.
428.
429.
430.
431.
4?2.
433.
4 34.
435.
436.
437.
438.
439.
440.
401.
442.
483.
444.
445.
446.
447.
448.
449.
450.
451.
452.
453.
454.
455.
456.
457.
458.
459.
460.
461.
462.
463-
464.
465.
466.
467.
466.
469.
470.
471.
472.
47?.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
>
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
1
2
2
2
2
2
2
2
2
1
1
1
1
2
2
2
1
2
2
2
2
1
189
190
191
192
194
195
196
197
198
199
201
202
203
204
205
206
207
208
210
211
212
213
214
215
216
217
218
21 9
221
222
223
224
225
226
228
229
230
231
233
234
235
?36
GC TO UR 1TE.RE FORT :
OP EN.ACTIVITY.LEVELS:
OPEN FILE (EXPO):
ON ENOFILE (EXPO)
EXPOSURES = 0;
GET.ACTIVITY.LEVELS:
GET FILE (EXPO) EDIT (OCCUPATION. SMSA. OAY.OF.UEEK.
PERCENT.IN.GROUP.IN. SUB.GROUP. (ACT IVITY.IN(HOUR). LEVEL.IN(HOUR)
CO HCUR = 1 TO 24))
(COL(l). F(2). F(l). F(l)> F(2)t X(l), A<1). 24(A(2). AU))):
IF (T.OPT • 0_0!PT> THEN
PUT FILE (DUMP) SKIP DATA (OCCUPATION. CAY.CF.WEEK.
PERCENT.IN.GROUP.IN. POPULAT I ON(0CCUPATI ON )) :
HO HOUR : 1 TO '120;
PERCENT.IN.GROUP(HOUR) = 0.5217857
ENR;
CO HOUR : 1 TO 24:
DO HICRO.ENVIRONMENT = 1
IF (ACTIVITY.IN (KOtlR) = AC T IVI T Y.N A CE ( P. ICRO.E NV IROKKLNT » THEN DC
ACTI-VITYS(HOUR »
ACriVITYS(HOUR «
ACTIVITYS(HOUR «•
ACTIVITYS(HOUR «
ACTIVIT YSUiOUR * 96) = MICRC.EKVIR0NKENT;
END;
EDO!
no LEVEL = 1 TO 3:
IF (LEVFL.IMHOUR)
LEVELS(KOUR + 0)
* PER CENT. IN.GROUP.IN ;
TO 5;
: ACTIVITY_NACE(P. ICRO_ENVIROKKLNT»
0)
24)
48)
72)
HICRO.ENVIRONMENT;
HICRO.ENVIRONMENT;
LEVEL.KAKE (LEVEL))
LEVEL;
THEN DO.
LEVELS (HOUR *
LEVELS(t-OUR +
LEVELS(HOUR »
LEVELS(hOUR +
END;
24> = LEVEL;
48) = LEVEL;
72> = LEVEL;
96) = LEVEL;
END;
END;
GET FILE (EXPO) EDIT (OCCUPATION. SMSA. OAY.OF.UEEK.
PERCENT.IN.GROUP.IN. SUB.GROUP. (ACTIVITY.IN(HOUR), LEVEL.IN(HOUR 1
DO HCUR = 1 TO 24))
(COL(l). F(2). F(l>. F(l). F(2). X(l>. Ad). 24{A(2). Ati)));
IF (T.OPT f O.CIPT) THEN
PUT FILE (DUMP) SKIP DATA (OCCUPATION* CAY.CF.WEEK,
PERCENT.IN.GROUP.IN. POPULATION(0CCUPATI ON)) ;
CO HOUR : 121 TO 144;
PERCFNT.IN.GROUPtHOUR) ~ 0.5217857 * PERCENT.IN.GROUP.IN;
END;
CO HOUR : 1 TO 24;
no MICRO.ENVIRONMENT = 1 TO 5 ;•
IF (ACTIVITY_IN
-------
»** PL1ABS OF EXPO-8 ***
DATE 110279
PAGE
13
474.
475.
476.
177.
178.
479.
480.
481.
482.
483.
484.
485.
486.
487.
488.
489.
190.
491.
492.
493.
494.
495.
496.
497.
498.
499.
500.
501.
502.
503.
504.
505.
506.
507.
508.
509.
510.
51 1.
512.
513.
514.
515.
516-
517.
518.
519.
520.
521.
522.
523.
524.
525.
526.
527.
528.
529.
530.
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
1
2
2"
2
2
1
1 .
1
1
1
2
2
3
3
4
4
3
3
3
3
3
3
3
1
3
3
3
3
237
238
240
241
242
243
245
246
247
249
250
251
252
254
255
256
257
258
259
260
261-
262
264
265
266
268
269
270
271
272
273
274
275
277
278
279
280
281
282
283
284
285
GET FILE (EXPO) EDIT (OCCUPATION? SNSA. D AY.OF.UEEKt
PERCENT_TN_. 24(A(2>.
IF
DO
IF
00
HOUR = 1 TO 24) )
(COL(l)t F(?>. F(l).
(T.OPT • n_OPT) THEN
PUT FILE (DUMP) SKIP
PER CENT. I N_ CROUP _IN.
HOUR - 145 TO 168;
PERCENT_IN_GROUP(HOUR) = 0.5217857 « PE RCE NT. I N. GROUP. IN i
END;
(T_OPT) THEN
PUT FILE (D-UKP) PAGE DATA ( PERCENT_I IV_G ROUP ) :
HOUR - 1 TO 24;
00 MICRC.ENVIRO.MMENT - 1 TO 5!
IF (ACT7VITY.IN thOUR) = AC T I VITY.fc A PE ( H I CRO.ENV I RONMiNT ) )
ACTIVITYS(HOUR » 144) = H ICRO.EN V IRONHEN T ;
END:
END:
t£VEL = 1 TO 3;
IF (LEVlEL_IN(HOUR) = LE VEL.KAME ( LE V EL ) ) THEH DO:
LEVELS(HOUR » 1441 = LEVEL;
DATA (OCCUPATION! OAY_OF_UEEKt
POPUL A T ION t CCCUPAT I CM ) !
TKEN CO
00
END;
END; .
00 HOUR = -6 TO Q;
LEVELS(HOURI) = LEVELS(HOUR * 168);
ACTIVITYS(HOUR) = ACTJ V I T YS( HOUR » 168);
END;
IF (T_OPT) THEN
PUT FILE (D-UHP) PAGE DATA (LEVEL_INi LEVELSt ACT IV I TY_ IlVf
ACTIVITYS);
CALCULATE. EXPO SURFS:
00 MONITOR = 1 TO NUHBER_OF_HONITOHS J
HO CONCENTR«TION_SUB = 1 TO N UMBER_OF_CONCENTR AT IONS :
IF (T_OPT) THEN
PUT FILE (DUMP) PAfiE DATA (KONITORt CONCENTRAT ION.SU8 ) ;
HO HOUR : 1 TO -168;
GEOME TRIC.HEAN = 0;
DO J = HOUR - 7 TO HOUR;
GEOHETRIC_ME«N : GEOHETR 1C _KE AN *
AIR_OUALITY(HO.NITORf Jf 3) «
MONITORS (MONITORf AC TI V ITYS { J) ) ;
END;
GEOHETRIC.KEIAN = GEOHETRIC_HE AN / 8.;
X = (LOG(CONCENTRAT10NS ( CONCE NTR*T I CN_SUR ) )
- LOG(GEOHETRIC_HEAN> ) /A IR_0 UAL I TY (H ONI TOR . HOUR. 4);
IF (X < C) THEN DO;
NEGATIVE.X : «1'B;
X = - XS
END;
ELSE oo;
NEGATIVE.X = 'O'B;
END;
T = 1.0 / (1.0 *. 0.2316419 * X);
F : 0.3969423 * EXP(-(X » X / 2.0));
FRACTION_EXCEEOING =
{(((E(5) * T « B(4)) * T + B(3>) » T + E(2)) * T + 8(1))
T * ft
-------
«*» PL1ABS OF F.XPO-8 *** DATE 110279 PAGE
531. 1 3 286 IF (NEGATIVE.X) THEN
532. FRACTION_EXCEEOING - 1. - FRACTION_EXCEEDINGJ
533. 1 3 288 GO TO FR*CTION_EXCEEOING.FOUNDJ
531. 1 3 289 FRACTION_rXCEE01NG_FOU:NO:
535. IF (T_OPT) THEN
536. PUT FILE (DUMP) SKIP;
5}7. 1 3 291 IF (T_OPT) THEN
538. PUT FILE (DUMP) DATA (HOURt FRACTION_EXCEEDING):
539. 1 3 293 DO LEVF.L = LEVELS (HOUR >;
510. 1 3 291 EXPOSURES(CONCE:NTR*TION_SUB» LEVEL) = EX FOS URES (CONCENTR AT ICM.SUEt LEVEL)
5«1. + FRACTION_F.XCEF.OING * POPULA T ION (OCCUP A TION ) *
512. PERCFNT.INJCROUP (HOUR) * MONITORS(MOMTORi 6)S
513. i 3 295 END; /* END OF LEVEL */
54i. i 3 296 END: /* END OF HOUR */
515. i 2 297 END: /* END OF MONITOR */
516. i i 298 END; /* END OF CONCENTRATION_SUB »/
517. 1 299 IF (T_OPT) THEN
548. PUT FILE (DUMP) SKIP(2)i
5«9. 1 301 IF (T_OPT • 0_OPT) THEN
550. PUT FILE (DUMP) DATA (EXPOSURES);
551. 1 303 GO TO GET_ACTIV 1TY_LEVELS;
552. i 304 *PAGE;
-------
«** PL1ABS OF EXPO-3 *** DATE 110279 PAGE 15
553.
554.
555.
556.
557.
558.
559.
560.
561.
562.
563.
564.
565.
566.
567.
568.
569.
570.
571.
572.
573.
574.
575.
576.
577.
578.
579.
580.
591.
582.
583.
584.
5fl5.
586.
587.
588.
589.
590.
591.
592.
593.
594.
5 "5.
596.
597.
598.
599.
600.
601.
602.
603.
6C4 .
605.
1
1
1 1
1 1
1
I
1
1
1 1
I 1
1 2
1 2
1 1
1 1
1 1
1
1
1
1
1
1
1
1
1
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
327
328
329
URITE.REPORT:
PUT PAGE EDIT ('STANDARD OF 't ST AND ARO.N AHE t ' WITH BACKGROUND OF 't
BACKGROUND! CITY.NAKEt
' <-GAMMA VALUES->'t
• INDOORS OTHER TRAHS TRANS 't
' FRACTION REDUCTION CHARACTER I ST I C • t
• S I T iE WORK INDOORS VEHICLE OTHER CuTSID't
•E POPULA-TION FACTOR VALUE ')
fLINE(5>> COIL(35)t At At At F(6t2)t LIN£<7>> COL(50)t At
LINE ( 10) t A't LINE(12)t At At LINE (13 It At A);
PUT SKIP<2>.
00 MONITOR = 1 TO NUHBER_OF_MONIT ORS :
PUT SKIP EDIT (SITES(KONITOR)? (MON I TORS ( MO MTOR t J) DO J = 1 TO 8)1
(COL(l)t: A(12)t F(8t3)t 4(F(10t3)>t F(12t4)t F(14.«)t F(13t3)>t
END;
PUT PAGE;
PUT EDIT ('PERSON HOURS OF EXPOSURE FOR A STANDARD OF 't
STANOARD.NAKEt • WITH BACKGROUND OF '» BACKeROUIkDt CITY.hAHEt
'CONCENTRATION LOU MEDIUM HIGH'.
' EXCEEDED TOTAL ACTIVITY ACTIVITY ACTIVITY1
)
(LINE(5>« COL (8). At At At F(6t2)t 1
LINE(7)t COL(30)t At
LINE( 9) t At LINE( 10) t A) ;
PUT SKIPC 2) :
DO CONCENTRATIOIN.SUB = 1 TO NUMB ER_OF_CO^E ATR AT I ONS .'
TOTAL.EXPOSURE = 0.0;
DO LEVEL = -1 TO 3;
TOTAL.EXPOSURE = TOT AL_EX POSURE
+ EXPOSURES (CONCFNTRATIOr.SUBt LEVEL);
END; /» END OF SUMMING EXPOSURE »/
PUT EDIT (CONCENTRATIONS(CONCENTRATICN.SUB) t
TOTAL_EXPOSUSEt
E XPO SUR ES ( CONCENTRATION. SUB t 1) t
EXPOSURES (CCNCF.NTR ATI ON.SUB. 2) t
EXPOSURE S(rONCENTRATION_SUB. 3) )
(COL(l)-t F(9)t X(5)t E(15t3)t X(5>» 3E(15t3)>:
PUT SKIP(2)J.
END; /* END CONCENTRATICM.SUB */
CLOSE FILE (EXPO) t
PUT FILE (SUKS) EDIT ( S T ANnARD.N «ME t
BACKGROUND. CONCEN TR A TI ONS t CITY_NA«Et EXPOSURES)
(COL(l). A(i6)t F(10.3)t COL (1) t 20(F ( 10. 3) ) f COL(l). 1(11).
COL(l). 600E (20.8) ) ) :
GO TO NEXT_STANDARD;
FIMSHEC:
CLOSE FILE (SYSPR INT) ;
CLOSE FILE (SUKSi;
IF (T.OPT) THEN
CLOSE FILE (DUMP);
CLOSE FILE (SYSI.M):
RETURN;
END; /« END PROGRAM «/
-------
»** PL1*RS OF EXPO-8 *»»
CROSS REFERENCE
DATE 110279
PAGE
16
LISTING
ACT1VITY_IN
»CTIVITY_NAME
»IR_OUALITY
ACTTVITYS OECLARECM57) ALLOCIK2J 001151 BIT It 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTE'NAL
DIMFNSIONC-6:i68) ALIGNED
SET 200 2C1 202 2.C 3 201 227 218 260
USED 260 263 271
CECLAREC<55> ALLOC<$(2!) 001127 BIT 1, 16 BITS) NONVARYUG CHARACTERS) STATIC VARIABLE INTERNAL 01 MEMS ION(1 : 21>
UNALIGNED
SET 191 2'18 237
USED 199 226 217 2!6 3
OECLAREO<59> ALLOC($(2) 002207 BIT It 18 BITS) NONVARYING CHARACTERS) STATIC VARIABLE INTERNAL DIMENSION(1:5)
UNJL1GNED INITIAL
SET 59
USED 199 226 217
DECL»RED<29) BINARY(60I> FLOAT REAL CONTROLLED VARIABLE INTERNAL DIKLNSION<1 INUMBER_OF_HCNI TORSt-6:16911:5 )
ALIGNED
SET 99 <59 99 99 99 99 99 99 105 106 108 109 111 111 111 111 111 111
111 111 119 121 122 121 125 131 136 137 117 181
USED 81 105 106 1.C8 109 119 121 122 121 125 131 136 137 113 113 117 151 151
151 151 151 151 151 151 151 151 151 151 151 151 156 156 161 161 161 161
161 161 161 161 161 161 161 161 161 161 163 163 181 187 271 271
8 DECLAREDI27) *LLOC<$(2) 000735 BIT 1. 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL DIHENSIONI 1:5)
ALIGNEP INITIAL
SET 27
USED 285 285 285 2»5 285
BACKGROUND OECLAREC<18) ALLOC($(2> OOC611 BIT It 72 BITS) BIN*RY<60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 80
USED 83 170 171 1173 173 301 310 321
CALTULATE.EXPPSURES DECLARfD (261) *LLCC($:<1) C12011 > LABEL CONSTANT INTERNAL
NOT REF
CSRO.NUKEER DECL«REC<38> ALLOC«$(2I) 001225 BIT It 36 BITS) 61N«RY«3510 ) FIXED KE.AL STATIC VARIABLE INTERNAL 01 KENS ION(1 :1 )
ALIGNED
SET 99 99 99 .99 111 J11 111 111
USED 103 118
CHARACTFRISTIC_VALUE DFCLARED(17) ALLOC<$(2) 000612 BIT 1, 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 110 111 I
USED 111 170 170 171 171 178
CITY_NAME DECLARED<35> ALLOC($(2I) 001212 BIT It 9S BITS) NONVARYING CHAR ACTE fi {11 ) STATIC VARIABLE INTERNAL UNALIGNED
SET 99 111
USED 103 118 301 310 321
CITY.NUMBtR OECLAREDM6) ALLOC($<2) 001215 BIT It 36 BITS) BINARYl35tO) FIXED RLAL STATIC VARIABLE INTERNAL DIMENSION I 1:1)
ALIGNED
SET 99 99 99 99 111 111 (1 11 111
USED 103 118
CONCENTRATIONS DECL*REO(23) ALLOC($(2D 000651 BIT 1. 72 BITS) BINARY«60) FLOAT REAL STATIC VARIABLE INTERNAL 01 MENSI ON<1:20)
ALIGNED
SET 92
USED 97 271 317 3?1
CONCEN'TRATION.SUR OECLARED(7) ALLOC($(2) 000001 BIT If 36 BITS) BIKAfiY(35.0) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 91 ?65 312
USED 92 267 271 29.1 291 315 317 317 317 317
CORRECTION.! DECLAREC(31) ALLOCtlCa) OOC752 BIT It 72 BITS) B1NARY<60) FLOAT REAL STATIC VARIABLE INTERNAL DIKENSI ON(1:20)
ALIGNER
SET 99
USED 105 157
CORRECTTON.2 OECLAREP(32) ALLOC(«(2) 001022 HIT It 72 BITS) BIN«RY(60) FLOAT REAL STATIC VARIABLE INTERNAL 01 HE MS I ON(1:20)
ALIGNED
-------
*** PL1AES OF CXPO-6 *** DATE 110279 PAGE 17
SET 99
USED 106 157
CORRECTION."* OECLAREOC33) ALLOC(t<2> 001072 BIT It 72 BITS) 8INARYUO) FLOAT REAL STATIC VARIARLE INTERNAL 0 I MENSION<1:20 )
ALIGNED
SET llil
USED 121 161
CORRECTION.? DECLARED<34) ALLOC($<21> 001112 BIT It 72 BITS) BINARYC60) FLOAT REAL STATIC VARIABLE INTERNAL 01 KENS ICN(1:20)
ALIGNED
SET 111
USED 122 164
DATLY.STANDARO OECLAREO(68) ALLOC(Sm 002742 BIT It 1 BIT) NONVARYING BIT(l) STATIC VARIABLE INTERNAL UNALIGNEO
SET 85 86
USED 169
DAY_OF_UEEK OECLARECCJ) ALLCC($t2) COOOC6 BIT It 36 BITS) 6INARY(35tO) FIXED fiE«L STATIC VARIABLE INTERNAL ALIGNtO
SET 191 218 237
USED 193 220 239
DISTRIBUTION OECLAREOU) ALLOC($(2) 000001 BIT It 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 80
USED 83
DUMP DECLAREOJ49) ALLOCC$«12) 000004 ) FILE STATIC CONSTANT EXTERNAL ENV1RONMENT(?) STREAM OUTPUT PRINT
USED 75 83 89 .95 97 101 103 116 118 176 176 185 187 193 220 239 244' 263
267 290 292 300 302 326
EROPT DECLAREC(Sl) ENTRY CONSTANT EXTERNAL
SET 69
NOT USED
EXP DECLAREC(42) BUILTIN
NOT 'SET
USED 136 137 143 2:84
EXPO DECLAREDC48) ALLOCtS(ll) 000004 > FILE STATIC CONSTANT EXTERNAL ENV IRONHENT (?) STREAM INPUT
USED 188 189 191 2>18 237 320
EXPOSURFS DECLAREOUO) ALLOc 001235 BIT i, 72 BITS) aiNARY<60> FLOAT REAL STATIC VARIABLE INTERNAL
DIMENSION? i:20» 1H31 ALIGNED
SET 190 294
USED 294 302 315 31'7 317 317 321
EXPO_8_HR DECLARECU) ALLCC($(1) 013460 ) ENTRY CONSTANT EXTERNAL
MOT REF
F DECLAREC<26> ALLOC($(2I) 000727 BIT It 12 BITS) BIN«RY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 234
USED 285
FINISHED DECLAREDI323) ALLOCft(l) 013375 ) LABEL CONSTANT INTERNAL
USED 77
FRACTION.EXCEFDING DECLARED(21) ALLOC($(2I) 000650 BIT It 72 BITS) 8INARYC60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 285 287
USED 287 292 294
FRACTION.EXCEEOING.FOUfOD DE CL AREO( 2 89) ALLOCCSIl) 012447 ) LABEL CONSTANT INTERNAL
USED 288
GEOHETRTC.Hr AN DECLAREOC25) ALLOC($(2) 000725 BIT It 72 BITS) BINARYUO) FLOAT REAi. STATIC VARIABLE INTERNAL ALIGNED
SET 269 271 273
USED 271 273 274
GFT_ACTIVTTY_LEVELS DECLAREOC191) ALLOC«$(U 010255 ) LABEL CONSTANT INTERNAL
USED 303
HOUR DECLAREPtB) ALLCC(S<2> 000005 BIT It 36 BITS) BINA RY (35 tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 99 99 99 99 104 114 114 111 114 120 129 134 146 153 160 179 191 194
197 218 221 224 237 240 245 258 268
USED 99 99 99 99 99 99 99 99 105 105 106 106 108 108 109 109 114 114
114 114 114 114 114 114 121 121 122 122 124 124 125 125 131 131 136 136
137 137 147 147 154 154 154 154 154 154 154 154 154 154 154 154 154 154
-------
*** PH»BS OF EXPO-8 *•*
DATE 110279
PAGE
16
HOUR.169
1
HOUR.TYPE
J
LFVEL
LEVELS
SET
NOT USED
SET
USED
SET
USED
SET
USED
154 161
191 191
226 227
292 293
DECLAREOI30)
INITIAL
30
DECLAREDO9)
ALIGNED
99 99
103 118
OECLARED(63)
107 123
108 109
OECl ARECI12)
207 230
208 210
OECLARECU58)
161 16-1 161
195 199 200
231 2>33 237
294
ALLOC(S!2I> 000751
--••
ALLOC<$(21 001231
99 99 114
ALLOCISI2? 002735
270 3.07
124 125 271
ALLOC It (2!) OOC011
251 291 314
211 2-12 213
»LLOC($(2) 001730
161
201
237
BIT It
—
BIT 1.
114
BIT It
271
BIT It
214
SIT It
161
202
241
36 BITS
161 161
203 204
247 248
) BIN'RY(35
36 BITS) BINARYC35
1 14
114
161 161 161 161 161
208 210 211 212 213
252 254 259 259 260
tO) FIXED RLAL STATIC VARIABLE
tO) FIXED REAL STATIC VARIABLE
36 BITS) BINARY<35tO) FIXED RtAL STATIC VARIABLE
307
36 BITS) BINARY!35rO) FIXED RtAL STATIC VARIABLE
?31
V
233 252
36 BITS) BINARY<35
254 294 294 315
tO) FIXED RtAL STATIC VARIABLE
161
214
260
161
218
270
isi lai
218 222
270 274
INTERNAL ALIGNED
INTERNAL DIMENSION* 1 14 )
INTERNAL
INTERNAL
ALIGNED
ALIGNED
INTERNAL
Dir>.ENSION<-6:i68) ALIGNED
LEVEL.IN
SET
USED
210 211
259 263
DECLAPECI56)
212 21-3 . 214
293
ALLOCI$!2I) 001443
233
BIT It
254
9 BITS)
259
NCNVARYIMG
CHARACTER!!) STATIC VARIABLE
INTERNAL DIHENS ION 1 1 :24 )
UNALIGNEO
LEVfL_NAMF
SET
USED
191 218
208 231
DECLARED(60)
237
252 263
ALLOC(*!2) 002212
BIT It
9 BITS)
NONVARYING
CHARACTER!!) STATIC VARIABLE
INTERNAL DIMENSION! 1 :3>
UN ALIGNED INITIAL
LOG
LOG.NORML
fMX
SET
USED
NOT SET
USED
SET
NOT USED
MOT SET
USED
PICRO.ENVIRONfENT
HONT TOR
MONI TORS
SET
USED
SET
USED
60
208 231
OECLAREIH43)
143 274
DECLAREDC6)
6
DECLAREOI44)
144
DECLARED! 11)
142 198
142 199
OECLAREOI10)
98 113
99 99
109 109
122 122
145 147
154 156
161 161
307
OECLAREOU3)
252
BUILTIN
274
ALLOC(i(2) C00003
BUILTIN
ALLOCISC2) 000010
225 246
200 2.01 202
ALLOCISI2) 000007
130 135 . 141
99 9,9 99
114 M 4 114
124 124 125
147 147 151
156 1157 157
163 163 164
ALLOC(1(2) 000012
BIT It
BIT It
203
BIT 1,
150
99
114
125
154
158
164
BIT It
36 BUS)
/
_.-•
/'
••''
BINAfiY!35tO) FIXED REAL STATIC VARIABLE
•V
* *"
*..'
36 BITS) 6IN«RY(35tO> FIXED RLAL STATIC VARIABLE
204
226 227
36 BITS) BINARY(35
172
99
114
131
154
161
173
180 264
99 99
114 114
131 136
154 154
161 161
173 173
72 BITS) BINARYI60
247 248
tO) FIXED R£AL STATIC VARIABLE
306
99 105 105 105 106
114 114 114 119 119
136 137 137 142 142
154 154 154 154 154
161 161 161 161 161
181 181 181 267 271
INTERNAL ALIGNED INITIAL
INTERNAL
INTERNAL
106
121
143
154
161
271
106
121
ALIGNED
ALIGNED
' 143
154
161
274
108 ioa
121 122
143 144
154 154
161 161
294 307
) FLOAT REAL STATIC VARIABLE INTERNAL
DIMENSION (1:20, i: 8) ALIGNEC
NFG»TIVr_X
SET
USED
SET
142 143
144 147
DECLAREPC28)
277 281
145 173
173 173 178
ALLOC!$(2!> 000747
181
BIT 1,
271
1 6IT>
294 307
NONVARYING
BITil) STATIC VARIABLE INTERNAL UNALIGNEO
-------
»** PL1A6S OF EXPO-6 *** DATE 110279 PAGE 19
USED 286
NEXT_STANDAfiD DECLARED (167) ALLOC(Sd) 007413 ) LABEL CONSTANT INTERNAL
USED 322
NUM6ER_OF_CONCENTRATIONS DECLARED(2H ) ALLOCJK2) OC0724 BIT It 36 BITS) BINARYC35tO> FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 90
USED 91 97 265 312
NUMPER.OF.MONTTORS DECLAREOO) ALLOC(S(2> OOOGOO BIT It 36 PITS) BINARYI35.0) FIXEO REAL STATIC VARIABLE INTERNAL ALIGNED
SET 80
USED 83 98 113 H30 135 141 150 172 180 264 306 29
orcUPATTON DECLAREO<64) ALLOC(S(21 002736 BIT It 36 BITS) BINARYI35tO) FIXED RtAL STATIC VARIABLE INTERNAL ALIGNED
SET 191 218 237
USED 193 193 220 2210 239 239 294
OPEN.ACTIVITY.LEVELS DECLARED<188) ALLOC{$(1) 010163 ) LABEL CONSTANT INTERNAL
USED 166
OPTIONS DECLAREOI52) ALLOC(S(14) 000000 BIT It 36 BITS) NONVARYING RITI36) STATIC VARIABLE EXTERNAL UNALIGNEO
NOT SET
USED 70 71 69
O.OPT DECLAREOC54) ALLOC($(1!6) 000000 BIT It 1 BIT) NCNVARYING BITC1J STATIC VARIABLE EXTERNAL UNALIGNEO
SET 71
USED 74 88 192 2-19 238 301
PERTENT.IN.GROUP OECLAREOC62) ALLOC(S(2I) 002215 BIT It 72 BITS) BINARY160) FLOAT REAL STATIC VARIABLE INTERNAL 0IMENSION 41 1168)
ALIGNED
SET 195 222 241
USED 244 294
PERCENT_IM_GROUP_IN DECLARED(61> AILOCCSC2> 002213 BIT It 72 BITS) BINARY<60> FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 191 218 237
USED 193 195 220 222 239 241
POPULATION OECLARED(20) ALIOCC*<2> OOC620 BIT It 12 BITS) BINARY (60) FLOAT REAL STATIC VARIABLE INTERNAL 0IHE N'S I ON < 1 : 12 >
ALIGNED
SET 67
USED >> 89 193 220 239 294
REDUCTICN.NEEPED DECLARED(22> ALLOC(t(2!) 000652 BIT It 72 BITS) EINARY(60> FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 170 171
USED 173 178
SITES DECLAREDC14) ALLOC($(21 000512 BIT It 108 BITS) NONVARY ING CHARACTER(12) STATIC VARIABLE INTERNAL
DIHENSION(i:20) UNALIGNED
SET 142
USED 151 156 307
SITF.NUHRTR DECLAREO(37) ALLOC(t(2) 001221 BIT It 36 BITS) 8INARY(35tO> FIXED R£AL STATIC VARIABLE INTERNAL 0IHENSIONf1:4)
ALIGNED
SET 99 99 99 99 114 114, 114 114
USED 103 118
SMSA OECLAREOC65) M.LOCC$C2> 002737 BIT It 36 BITS) BINARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED
SET 191 218 237
HOT USED
STANDARD OECLAREDU5) ALLOC(f(2> 000606 BIT It 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 167
USED 16fl 170 171
STANDARO.NAME OECLAREOU6) ALLOC($<2) 000610 BIT It 54 BITS) NONVARYING CHARACTERS) STATIC VARIABLE INTERNAL UNALIGNED
INITIAL
SET 16 168 "" ,
USED 304 310 321
STANDARP.TYPE DECLAREDI67) ALLOC($(2) 002741 BIT It 36 BITS) OINARY(35tO) FIXED fiLAL STATIC VARIABLE INTERNAL ALIGNED
SET 80
USED 83 84
SUBSTR DECLARED(45) BUILTIN
fJOT SET
-------
••* PL1ABS OF EXPO-8 *•» DATE 110279 PAGE 20
USED 70 71
SU9_GROUP DECLARED(66> ALLOC(»(2) 002740 BIT It 36 BITS) BINARY«35tO> FIXED RcAL STATIC VARIABLE INTERNAL ALIGNED
SET 191 218 237
NOT USED
SUMS DECLAREO(5C) ALLOCC$ (13) 000001 ) FILE STATIC CONSTANT EXTERNAL ENVIRONMENT (?) STREAM OUTPUT PRINT
USED 73 321 321
SYS]N OECLAREE<17) ALLOCC$(10> OC0001 ) FILE STATIC CONSTANT EXTERNAL ENVIRONMENT (?) STREAM IKPUT
USED 76 77 80 .87 90- 92 99 111 1*2 167 327
SYSPRINT DECLAREtldi) ALLOC<*(9) 000001 ) FILE STATIC CONSTANT EXTERNAL ENVIKONMENTt?) STREAM OUTPUT PRINT
USED 72 151 152 151 156 157 158 159 161 163 161 301 305 307 309 310 311 317
318 323
T OECLARECI26) ALLOC (t(2l> 000731 BIT It 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 233
USED 285 285 285 285 285
TOTAL_FXPOSURE DECLAREO(ll) ALLOCISm 001125 BIT 1. 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 313 315
USED 315 317
TOTSL.POPULATTON DECLAREOI19) »LLOC(*(2> 000616 BIT I. 72 BITS) BINARY(60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 80
USED 83
T.OPT OECLAREQ<53) ALLOC(«(15) 000000 BIT It 1 BIT) NONVARYING BIT(l) STATIC VARIABLE EXTERNAL UNALIGNED
SET 70
USED 71 82 38 91 96 100 102 115 117 175 177 181 136 192 219 238 213 262
266 289 291 299 301 325
WIEPULL OECLARED(5> ALLOC(*(2> 000002 BIT It 36 BITS) B!NARY(35tO) FIXED REAL STATIC VARIABLE INTERNAL ALIGNED INITIAL
SET 5
WOT USED
URITE_REPORT OECLAREO{301) ALLOC(*(10 012651 ) LABEL CONSTANT INTERNAL
USED 189
V DECLARED(26) ALLOC(*(2t> 000733 BIT It 72 BITS) 8INARYI60) FLOAT REAL STATIC VARIABLE INTERNAL ALIGNED
SET 271 278 /
USED 275 278 283 2*1 261
**** NO ERRORS OR WARNINGS IN ABOVE PROGRAM
END PL1 6612 IBANK 2708 OBANK •'
08:51:17 PL 1
PRUH C0:00:i0.393 DISC 00:00:C1.18B TAPE .OOIOCrOO.OOC I/O OCKOOrit.5£1
CCER 00:00:09.706 CAU 00:00:09.116 MEHY 00:00:05.811-0025K
-------
«*• PL1ABS OF EXPO-8 ***
DATE 110279
PAGE
3ELT.L JPAP. EXPO-8
ELT007 SL73R1 1 1 /02/79 08: 5» M7
000001 010 IN EXPO-8
LIST THE KAP INSTRUCTIONS
(Hit)
EN1 ELT.
08:54:17 ELT
DRUM 00:00:00.029 DISC 00:00:00.261 TAPE 00:00:00.000 i/o oo:oo:oo.290
CCFR oc:oo:oo.soo CAU oo:co:oo.ooo HEMY _oo:oc:oo.c39-oco7K
-------
REFERENCES
1. James L. Repace, Wayne R. Ott and Lance A. Wallace, "Total Human Exposure
to Air Pollution," Proceedings of the 73rd Annual Meeting of the Air
Pollution Control Association, Pages 80-61.6, June 1980.
2. Wayne R. Ott, "An Urban Survey Technique for Measuring the Spatial Variation
of Carbon Monoxide Concentrations in Cities," Ph.D. Dissertation, Depart-
ment of Civil Engineering, Stanford University, 1971.
3. Wayne R. Ott, "Development of Activity Pattern Models for Human Exposure
Monitoring," EPA Office of Research and Development, Washington, D.C.
Innovative Research Program Proposal, Approved July, 1 179.
4. Yuji Horie and Jack Morrison, "Technical Memorandum on Spatial Inter-
polation of Air Quality Monitoring," Technology Services Corporation,
Santa Monica, California, December 21, 1977.
5. Modore S. Phadke, Michael R. Grupe and George C. Tiao, "Statistical Evaluation
of Trends in Ambient Concentrations of Nitric Oxide in Los Angeles,"
Environmental Science and Technology, Vol. 12, No. 4, pp. 430-435, April,
1978.
6. Joel Horowitz and Somir Barakat, "Statistical Analysis of the Maximum
Concentration and Non-stationarity," Atmospheric Environment, Vol. 13,
No. 6, pp. 811-818, (1979).
7. Yuji Horie and J. Trijonis, "Population Exposure to Oxidants and Nitrogen
Dioxide in Los Angeles, Vol. VI: Analysis and Interpretation of Trends,"
Technology Service Corporation Report for U.S. EPA, EPA-450/3-77/004d,
June, 1977.
8. Edwards C. Reifenstein, III, Rd drt J. Horn, III, Michael J. Keefee,
"The Hackensack Meadowlands Air Pollution Study - Task 5 Report: The
AQUIP Software System User's Manual," Environmental Research and Technology,
Inc. ERT Document No. P-244-5, June, 1974.
9. "OAQPS Guidline Series - Guidline on Air Quality Models." U.S. EPA, EPA-450/
2-78-027 and OAQPS No. 1.2-080, April, 1978.
10. S.R. Hayes," Performance Measures and Standards for Air Quality Models,"
U.S. EPA, EPA-450/4-79-032, October, 1979.
11. Thomas B. Feagans and William F. Biller, "A Method of Assessing the Health
Risks Associated with Alternative Air Quality Standards," Office of Air
Quality Planning and Standards, U.S. EPA, Research Triangle Park, NC
27711, (In preparation).
-------
References (continued)
12. Marc F. Roddin, Hazel T. Ellis and Waheed M. Siddiqee, "Background Data
for Human Activity Patterns," Vols. 1 and 2. Draft final report
prepared for Strategies and Air Standards Division, Office of Air
Quality Planning and Standards, U.S. EPA, Research Tri'angle Park, NC
27711, August, 1979.
13. Robert L. Winkler and William L. Hayes: Statistics, 2nd Edition, Holt,
Rinehart and Winston, New York, 1975.
14. K.B. Schnelle, F.G. Ziegler and P.A. Krenkel, "A Study of the Vertical
Distribution of Carbon Monoxide and Temperature Above an Urban Inter-
section," Proceedings of the 62nd Annual Air Pollution Control
Association Meeting, Paper No. 69-152, 1969.
15. Anthony D. Cortese, "Ability of Fixed Monitoring Stations to Represent
Personal Carbon Monoxide Exposure," Ph.D. Dissertation, Harvard School
of Public Health, April, 1976.
16. Wayne R. Ott and R. Eliasson, "A Survey Technique for Determining the
Representation of Urban Air Monitoring Stations with Respect to
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