&EPA
               United States
               Environmental Protection
               Agency
                   Office of Mobile Source Air Pollution Control
                   Emission Control Technology Division
                   2565 Plymouth Road
                   Ann Arbor, Michigan 48105
EPA 460/3-84-004
March 1984
              Air
Mobile Source  Exposure
Estimation

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                                       EPA 460/3-84-004
Mobile Source Exposure Estimation
                            by

                        MelvinN. Ingalls

                    Southwest Research Institute
                       6220 Culebra Road
                     San Antonio, Texas 78284

                     Contract No. 68-03-3073

                  EPA Project Officer: Robert J. Garbe



                         Prepared for

               ENVIRONMENTAL PROTECTION AGENCY
               Office of Mobile Source Air Pollution Control
                  Emission Control Technology Division
                      2565 Plymouth Road
                    Ann Arbor,  Michigan 48105
                         March 1984

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 This  report  is  issued  by  the  Environmental  Protection  Agency to  report
 technical  data  of  interest  to a  limited  number of  readers.  Copies are
 available  free  of  charge  to Federal  employees, current contractors and
 grantees,  and nonprofit organizations  -  in  limited quantities -  from
 the Library  Services Office,  Environmental  Protection  Agency, 2565 Plymouth
 Road, Ann  Arbor, Michigan  48105.
This report was furnished to the Environmental Protection Agency by
Southwest Research Institute, 6220 Culebra Road, San Antonio, Texas,
in fulfillment of Work Assignment 6 of Contract No. 68-03-3073.  The
contents of this report are reproduced herein as received from
Southwest Research Institute.  The opinions, findings, and conclusions
expressed are those of the author and not necessarily those of the
Environmental Protection Agency.  Mention of compnay product names is
not to be considered as a endorsement by the Environmental Protection
Agency.

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                                  FOREWORD
     This project was conducted for the U.S. Environmental Protection Agency
by the Department of Emissions Research of Southwest Research Institute.  The
project was begun in June 1982 and completed in May 1983.  The project was
conducted under Work Assignment 6 of Contract 68-03-3073, and was identified
within Southwest Research Institute as Project 05-6619-006.

     Mr. Robert J. Garbe of the Emission Control Technology Division, Office
of Mobile Source Air Pollution Control, Environmental Protection Agency, Ann
Arbor, Michigan, served as EPA Project Officer.  Mr. Charles T. Hare, Manager,
Advanced Technology, Department of Emissions Research, Southwest Research
Institute, served as the Project Manager.  The project was under the super-
vision of Melvin N. Ingalls, Senior Research Engineer, who served as Project
Leader and principal investigator.  The assistance of Mr. Thomas McCurdy and
Mr. George Duggan of the EPA, Office of Air Quality Planning and Standards,
and Mr. Roy Paul of PEDCo, Inc., in running the NAAQS Exposure Model  (NEM)
is gratefully acknowledged.
                                      111

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                                  SUMMARY

     This project was conducted to provide the nationwide annual person
hours of exposure to non-reactive mobile source pollutants.  The first
activity of the project was to determine the suitability of the National
Ambient Air Quality Standards  (NAAQS) Exposure Model  (NEM), as used in a
study of alternative standards for CO to provide the exposure estimate.
It was determined that, by itself, the NEM CO study did not provide a
sufficiently accurate estimate of mobile source exposure for the follow-
ing reasons:

          •  The CO monitor data used were rolled back to meet
             the ambient standard being studied.

             There was only one mobile source microenvironment
             included in the NEM.

          •  Additional nonautomotive CO sources, such as smoking
             and gas stoves were included in the NEM microenviron-
             ments.

     The NEM for CO, with modified inputs, could be used in conjunction
with a mobile source microenvironment exposure model to produce the desired
exposure estimates.  The NEM can be thought of as a "people specific" model,
since it follows groups of people through their daily activities.  The
mobile source microenvironment exposure model developed for this project is
a "place specific" model in that it calculates exposure for a given place
and time, and is not concerned with where the people in the microenvironment
are before or after their stay in the microenvironment.  Exposure in four
separate microenvironments was examined:  parking garages, street canyons,
on-expressways, and roadway tunnels.

     For these microenvironments, measured CO concentrations were used as
the indicator of mobile source pollutant concentrations.  CO concentrations
were obtained from the published literature for parking garages, on express-
ways, and tunnels.  Street canyon CO concentrations were determined by
averaging 23 CO monitors from the EPA SAROAD data base which were identified
as being in street canyons.  The nationwide population in these microenviron-
ments for each hour of the day was obtained from published literature.

     Using the CO concentrations and the hourly population for each micro-
environment, the nationwide annual person hour exposure to CO was calculated
using the mobile source microenvironment model for parking garages, street
canyons and tunnels.  The on-expressway exposure was calculated as part of
the NEM rerun.  The exposure estimates obtained were in the form of person hours
of exposure as a function of CO concentrations.  To convert these exposure
distributions to exposures that could be used for any mobile source pollutant,

                                     v

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the CO concentrations were divided  by an emission  factor appropriate to
the microenvironment.  This produced the exposure distribution that would
be experienced from a 1.0 gram per minute emission  factor.  To obtain exposure
for any pollutant, the 1.0 gram per minute exposure distribution is multiplied
by the emission factor for that pollutant.

     To obtain the exposure everywhere else but in  the three microenvironments,
the NEM for CO was rerun with the following changes from the published NEM CO
study:

        • Air Quality monitor data were used as measured, not
          "rolled back."

        • No indoor sources, such as smoking or gas stoves, were
          used.

        • Additional concentration intervals below 7 ppm CO were
          added to the printout.

     The exposure distributions produced by the rerun of NEM were converted
to exposure distributions for a 1.0 gram per minute emission factor in the
same manner as the microenvironment exposure distributions,using the nation-
wide urban CO emission factor for 1978, which was the median year of the NEM
air quality data base.

     The microenvironment and NEM exposure distributions have not been combined
at this time.  This is because the microenvironment and NEM exposure distri-
butions for 1.0 gram per minute must each be multiplied by a different emission
factor to obtain the nationwide exposure estimate for a given pollutant.  Once
each distribution has been multiplied by the appropriate emission factor, the
distributions can be added together to obtain the nationwide exposure estimate
for that pollutant.
                                    VI

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                         TABLE  OF CONTENTS

                                                                       Page

FOREWORD                                                                 ill

SUMMARY                                                                    v

LIST OF FIGURES                                                           ix

LIST OF TABLES                                                            xi

I.    INTRODUCTION                                                         1

II.   INVESTIGATION OF  METHODOLOGY                                        3

III.  MICROENVIRONMENT  POLLUTANT CONCENTRATIONS
      FROM MOBILE SOURCES                                                  7

IV.   NUMBER OF PERSONS IN MICROENVIRONMENTS                             29

V.    EXPOSURE IN MOBILE SOURCE MICROENVIRONMENTS                        59

VI.   MOBILE SOURCE NEM EXPOSURE ESTIMATE                                73

VII.  NATIONWIDE EXPOSURE  TO MOBILE SOURCE POLLUTANTS                    85

VIII. CONCLUSIONS AND RECOMMENDATIONS                                    89

REFERENCES                                                                91

APPENDICES

      A.  DEVELOPMENT OF LOGNORMAL POLLUTANT DISTRIBUTIONS
          FOR PARKING GARAGES AND ROADWAY TUNNELS

      B.  FORTRAN LISTING OF SAROAD FILE EDITING PROGRAM FOR
          STREET CANYON MONITORS

      C.  FORTRAN LISTING OF MICROENVIRQNMENT EXPOSURE MODEL
          FOR PARKING GARAGES

      D.  FORTRAN LISTING OF MICROENVIRONMENT EXPOSURE MODEL
          FOR STREET  CANYONS

      E.  FORTRAN  LISTING OF MICROENVIRONMENT EXPOSURE MODEL
          FOR TUNNELS

      F.  UNIVAC  1100 RUNSTREAMS FOR NEM  RERUNS
                                   vi i

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                           LIST OF FIGURES

Figure                                                                Page

   1      Parking garage CO concentration distribution,
          25 percent active cars, average wind speed                   11

   2      Wind speed distribution, average of seven U.S. cities        13

   3      Frequency Distribution of CO concentrations outside
          three cars on Los Angeles Freeways                           22

   4      CO concentration as a function of Hourly Percent ADT
          for the Sumner Tunnel (1961)                                 24

   5      CO concentration as a function of Hourly Percent ADT
          for an average Roadway Tunnel                                26

   6      Hourly average cars in motion for weekdays in Parking
          Garages                                                      32

   7      Hourly average cars in motion for Saturdays in Parking
          Garages                                                      33

   8      Hourly average cars in motion for Sundays in Parking
          Garages                                                      34

   9      Number of person trips to CBD per person in urban areas      36

  10      Hourly traffic distribution in the CBD for an average
          weekday                                                      39

  11      Hourly traffic distribution in the CBD for Saturday          42

  12      Hourly traffic distribution in the CBD for Sunday            43

  13      Pedestrians for individual days of the week as a
          percent of total weekly pedestrians                          44

  14      Hourly pedestrian distribution in the CBD for weekdays       46

  15      Hourly pedestrian distribution in the CBD for Saturdays      47

  16      Expressway traffic by day of the week                        48

  17      Hourly expressway traffic for weekdays                       52

  18      Hourly expressway traffic for Sundays                        53

  19      Hourly distribution of people in the NEM "transport
          vehicle" environment in  four cities for Saturdays             54
                                   ix

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                       LIST OF FIGURES (Cont'd)

Figure                                                               Page

  20      Hourly tunnel traffic for weekdays                          56

  21      Hourly tunnel traffic for weekends                          57

  22      Nationwide cumulative exposure distribution in
          parking garages                                             65

  23      Nationwide cumulative person hour exposure
          distribution in street canyons                              68

  24      Nationwide cumulative person hour exposure
          distribution in roadway tunnels                             72
                                   x

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                            LIST OF TABLES

Table                                                                Page

  1       CO Levels Found in Parking Garages                            9

  2       Probability Distribution Parameters for Parking
          Garage Pollutant Distributions                              14

  3       Discrete Pollutant Distributions for Parking Garages        15

  4       SARQAD CO Monitors Used in Street Canyon Analysis           16

  5       Descriptive Statistics for Street Canyon CO Readings        18

  6       Distribution of Hourly Average CO Levels in Street
          Canyons                                                     19

  7       Pollutant Concentration Intervals for Street Canyons        20

  8       Measured CO on Expressways                                  21

  9       CO Levels Found in Roadway Tunnels                           23

 10       Pollutant Concentration Intervals for Roadway Tunnels        27

 11       Distributions of Hourly Average CO Levels in Roadway
          Tunnels                                                      28

 12       Parking Garage Construction in the U.S., 1967-1982           30

 13       Estimated CBD Daily Traffic as a Percent of Weekly Traffic   37

 14       Daily Person Trips and Vehicles in Street Canyons            38

 15       Distribution of People Assigned to the "Transport Vehicle"
          Mode in the NEM CO Report                                    50

 16       Total Person Hours of Exposure, on-Expressway Situation       50

 17       Traffic Distribution by Day of the Week for Several
          Situations                                                   55

 18       Values of Variables Used in Determination of Parking
          Garage Person Hour Exposure Estimate                         ^3

 19       Person Hour Exposure Distribution for Parking Garages        &4

 20       Values of Variables Used in Determination of Street
          Canyon Person Hour Exposure                                  66

                                   xi

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                        LIST OF TABLES (Cont'd)

Table                                                                Page

 21       Person Hour Exposure Distribution for Street Canyons         67

 22       Values of Variables Used in Determination of Roadway
          Tunnel Person Hour Exposure                                  69

 23       Person Hour Exposure Distribution in Roadway Tunnels         71

 24       NEM Input Modifications Required                             74

 25       Person Hours of Exposure to Mobile Source CO for Chicago     75

 26       Person Hours of Exposure to Mobile Source CO for
          Los Angeles                                                  76

 27       Person Hours of Exposure to Mobile Source CO for
          Philadelphia                                                 77

 28       Person Hours of Exposure to Mobile Source CO for St.  Louis    78

 29       1980 Person Hours of Exposure to CO in Four Cities            80

 30       Values of Variables Used to Extrapolate NEM Exposure  in
          Four Cities to Nationwide Exposure                           81

 31       1980 Nationwide Urban Mobile Source CO Exposure  from NEM     82

 32       1980 NEM Nationwide Urban Exposure for Mobile Source
          Pollutants                                                   83

 33       Total Person Hours of Exposure  in Parking Garage, Street
          Canyon and Tunnel Microenvironments                          83

 34       1980 Rural Exposure to Mobile Source Pollutants               86

 35       1980 Total Nationwide (Urban and Rural)  Exposure to
          Mobile Source Pollutants Exclusive of Three Micro-
          en vi ronments                                                 86
                                 XI1

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                              I.   INTRODUCTION
     Internal combustion engines used in motor vehicles produce exhaust
gases that contain a multitude of chemical compounds.  Four of these
pollutants are regulated by standards (hydrocarbons, CO, NOX and particulate
matter).  In devising means to control these four regulated pollutants,
undesirable  chemical compounds may  inadvertently be produced.  Malfunction
of the engine and emission control systems can also change the concentrations
of the various chemical species in the exhaust.  Additionally, alternative
fuels proposed for use in motor vehicles can produce greatly different
compounds and concentrations of compounds than are currently produced by
gasoline and diesel fuels.  The EPA has instituted a program to determine
if any of these unregulated mobile source emissions cause or contribute
to a risk to public health, welfare or safety.

     Previous Work

          The work reported on here is the latest in a series of projects
on the subject of unregulated emissions conducted for the EPA by Southwest
Research Institute.  Previous projects have developed methodologies for
measurement of unregulated pollutants in vehicle exhaust,(1/2,3)* determined
the magnitude of these unregulated emissions in a variety of vehicles,(1/4-8)
evaluated the effects of engine and emission control system malfunctions,(9-12)
and measured unregulated emissions using a. variety of alternative fuels.(13-17)
Thus, the exhaust emission rates, in terms of mass per distance or mass per
time, of many unregulated pollutants are known.

          To determine effects on health and welfare, emission rates of
these unregulated pollutants must be transformed into the ambient pollutant
concentrations to which people are exposed.  Another of  the previous projects
at SwRI examined localized situations in which the dispersal  of mobile
source pollutants is hindered, causing higher than usual concentrations.
Several situations involving small areas, called microscale areas, were
identified.  Mathematical dispersion models of these situations were selected
and validated to allow the prediction of ambient concentrations in these
microscale areas, based on knowledge of vehicle exhaust  emission rates.
These models allowed the identification of areas of high  mobile source pol-
lution and permitted the  evaluation of the health and welfare effects of
short term, high level exposure to these unregulated emissions.(19)

          It was not possible  from that study to ascertain long term effects
due to chronic exposure,  such  as  cancer risk, for unregulated pollutants.
This present project was  conducted to provide annual exposure information
 *Superscript  numbers in parentheses  refer  to  references  at  end of  this  report.

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 resulting  from mobile  source pollutants  which can  then  be  used  to  evaluate
 health  effects from long  term  exposure.   The  exposure is expressed in  terms
 of person  hours.   Person  hours of  exposure  are simply the  number of people
 in a  situation multiplied by exposure  time  in that situation  in hours.   Thus,
 1000  person hours  of exposure  can  be one person exposed for  1000  hours,
 1000  people exposed for one hour, or any  other values of persons and hours
 whose product  is 1000.

      Objective

           The  objective of this project  was to develop  the methodology to
 obtain  the nationwide, annual  person hours  of exposure  to  any mobile source
 pollutant.  Then,  using that methodology, the annual exposure in person
 hours can be determined as a function  of ambient concentration  for  any
 mobile  source  pollutant.

      Approach

          To determine the annual  exposure  in person hours to any mobile
 source  pollutant,  the number of persons  exposed to  the  pollutant in various
 places  must be known as a  function of  time.   The ambient concentration in
 these places must  also be  known as a function of time.  The exposure in
 person  hours can then be  ascertained,  expressed either  as the number of
 person  hours in various concentration  intervals or  as an average concentration
 for the entire population  examined.

          The  ambient concentrations of  most  unregulated pollutants are not
 available from direct measurements.  The  concentrations of these pollutants
 must  be inferred from measurement of some other pollutant.   For this project
 CO was  used as  a surrogate, since urban  CO  is  entirely mobile source related.
 If the CO concentration in an  urban area is known,  then the concentration
 of other mobile source pollutants can  be estimated  by multiplying the CO
 concentration  by the ratio of  the new  pollutant emission rate to the CO
 emission rate:
             ,_  _     J_J_.      __        j_       /Pollutant emission rate\
      Pollutant Concentration =  CO concentration  	—	:	:	)
                                                y   CO emission rate    /

 This  approach  assumes that the  desired pollutant and CO have  equivalent
 dispersion and  reaction characteristics  in  the ambient air.

          At the start of the projeect,  there was no method available to
 combine the concentrations from mobile sources, including the important
microenvironments,  with the person in  the various environments.   The project
 approach was to first determine if methods existed  that could be used either
directly or with modification.   If methods did exist, it was planned to become
 familiar with their use,  then use them to determine exposure.    If no satis-
 factory method existed, a methodology would be developed.   After collecting
the necessary data, the methodology would be  applied to yield the desired
relationship between person hours of exposure and pollutant concentration.

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                      II.  INVESTIGATION OF METHODOLOGY
     Determining person hours of exposure requires that the pollutant con-
centrations for the areas of mobile source exposure be known, and that the
number of people in these areas be known.  There are two basic approaches
to determining person hours of exposure.  One approach is to follow people
through their various activities during the day, determining the amount
of time spent in various locations.  In this report, this approach is
referred to as "people specific."  The second approach is to look at the
places where people encounter mobile source pollutants, then determine the
population in those places for each hour of the day.  This approach is
referred to as "place specific."  If only total person hours of exposure
is desired, and not an individual person's exposure pattern, then the place
specific approach appears to be the easiest and most accurate.

     While all locations in urban environments are exposed to some concen-
tration of pollutants from mobile sources, the highest concentrations occur
in small, confined areas where people and vehicles are in close proximity.
These areas are referred to as microscale areas or microenvironments, and
include such areas as personal garages, parking garages, street caynons,
expressways, and tunnels.  Thus, any method must be able to include these
microenvironments.

     At the start of the project, it was learned that the EPA Office of Air
Quality Planning and Standards  (OAQPS) had developed an exposure model to
evaluate the exposure profile for various levels of pollutant ambient
standards.  A study had just been completed for CO using this model.(33)
If it were possible to use the OAQPS model CO results, the project would
be spared the expense and time of developing a new model for mobile source
exposure.  The OAQPS-developed model had been given the acronym "NEM",
from "NAAQS Exposure Model."

     Evaluation of the NEM CO Report

          The NEM basically traces the movement of people in an individual
city, determining the location of similar groups of people for each hour
of the day, each day for a year.  It is a "people specific" model.  A
pollutant concentration in each location is estimated for each hour of
the year.  As used in the CO study, it determined the hourly exposure of
56 different groups of people moving through six different neighborhood
types.  In any neighborhood, the groups can be  in one of six micro-
environments.

          The groups of people, called  "Activity-Occupation"  (A-O) groups,
had been determined from studies of people's activities.  The number of
people assigned to each group for a given city  was determined from census

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information.  The A-O groups have titles such as:  sales workers, laborers,
housewives, and children under  five.

          The six different neighborhood types provide the basis for the
air quality level.  For each city, one CO monitor was chosen to represent
each neighborhood type.  Thus,  for each hour of the year, there is a
different CO concentration associated with each neighborhood type.

          The actual exposure level takes into account the fact that people
can be exposed to more or less  CO than the monitor level because of their
immediate surroundings—their microenvironment.  Six microenvironments are
used:  indoors (home), indoors  (work), transport vehicle, roadside, outdoors,
and kitchen.  For each microenvironment there is a single multiplication
factor and an additive factor applied to the hourly CO monitor values.

          The NEM produces a person-hour exposure distribution in various
pollutant concentration intervals for a single city.  Currently, NEM CO
results are available for four  cities.  These four city results are then
extrapolated to the entire country.

          The NEM study was reviewed in detail for its applicability to
mobile source exposure estimation.  It was concluded that the CO study, as
published, was not satisfactory for use in determining exposure estimates
from mobile sources for the following reasons:

          1.   Since the purpose of the NEM analysis was to study the
               effect of ambient CO standards, the representative CO
               monitor data was "rolled back," (i.e.,  reduced)  so that
               all areas meet the three different CO standards being
               investigated.   Thus,  the exposure distributions obtained
               did not represent an actual distribution which could be
               used with a calendar year CO mobile source emission factor,
               but rather a distribution that would exist if certain
               ambient CO standards were met.

          2.   The microenvironments considered were only:

                                • indoors (home)
                                • indoors (work)
                                • in a vehicle
                                • roadside
                                • outdoors
                                • kitchen

               A  number of microscale environments with the possibility
               of high ambient  concentrations from mobile sources that
               were identified  under EPA Contract 68-03-2884,  Task
               Specification  1,  were not included in the NEM study.

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          3.    The microenvironments used in the NEM CO study included
               CO sources other than vehicles,  such as smoking and gas
               stoves.   To properly use the CO data to indicate mobile
               source emissions there must be no other known CO sources.

          4.    The use  of multipliers on the CO monitor data to obtain
               microenvironment CO levels is not sufficient in mirco-
               environments that contain large numbers of mobile sources.
               In these cases,  there is probably no relationship between
               the neighborhood monitor CO level and the CO level in the
               microenvironment.  The work done at SwRI under Contract
               68-03-2884 indicates that the number of vehicles and the
               microenvironment ventilation rate are the controlling
               factors for the CO level in the microenvironment.  These
               factors have little effect on outdoor CO monitors, nor are
               they constant from one microenvironment to anohter in the
               same neighborhood.

None of the preceding is intended as criticism of the NEM CO study.  The
remarks are only intended to indicate that the NEM study was not, by itself,
a satisfactory method to meet the objective of the present project.

          While the NEM model does not .adequately cover the microenvironments
of concern in mobile source exposure, it could be satisfactory for the
mesoscale exposure  (e.g., in a suburban housing development), if the monitor
CO values were used "as is," (not rolled back) and the microenvironment
additive factors  (which were used to account for sources such as smoking,
etc.) were set to zero.

     Final Methodology

          Since the NEM could provide an exposure estimate of mesoscale
exposure, which accounts for most of the yearly person hours of exposure,
it was decided that the NEM computer program should be rerun with the
following changes to the input instructions:

          • CO monitor data would be used  "as is"
          • No additive sources, such as smoking, would be used in the
             NEM microenvironments

          To determine the person hours of exposure to those mobile source
microenvironments not accounted  for by the NEM, a new model was developed.
Four microenvironments were investigated:  parking garages, street canyons,
expressways and roadway tunnels.  The NEM appears to satisfactorily cover
the microenvironments where people are exposed to lower levels of mobile
source pollutants,  such as non-street caynon, non-expressway streets, in
the NEM  "outdoor" and  "beside  roadway" microenvironments.  Thus, non-street
canyon,  non-expressway streets are not examined separately, since to  do so
would not make an appreciable  change in the NEM-generated exposure
distribution.

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          The  mobile source microenvironment model is a "place specific"
model.  To obtain annual person hours of exposure in each of the important
mobile source microenvironments, the model uses the population in a micro-
environment for each hour of the day.  Several discrete pollutant concen-
tration  frequency distributions were developed for each microenvironment.
For each hour of the day, the frequency of occurrence of each concentration
interval is multiplied by the microenvironment population for that hour to
obtain person hour exposure distribution for that hour.  The total exposure
is obtained by multiplying the single hour distribution by the number of
days in a year, them summing the distribution from each hour of the day.

          To obtain the range of CO concentrations for the various micro-
environments considered in this project, information from literature searches
done under Contract 68-03-2884, and the EPA SAROAD air quality monitor data
base, was used.  The number of persons nationwide in each microenvironment
for each hour of the day was determined from information in the literature.
The NEM results representing only mobile source emissions can be combined
with person-hour exposure distributions from the four microenvironments
(parking garages, street canyons, expressways, and tunnels) to obtain a
single nationwide person-hour exposure distribution to mobile source
pollutants.

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     III.  MICROENVIRONMENT POLLUTANT CONCENTRATIONS FROM MOBILE SOURCES
     In order to estimate the exposure of persons to mobile source pollu-
tants, information is needed on the ambient concentrations of these pol-
lutants in each microenvironment.   Since it is not possible to know the
pollutant concentration in every occurrence of the microenvironment for all
hours of the year, some method of estimating the distribution of pollutant
concentration values is required.

     From an examination of a number of individual examples of each micro-
environment, an estimate of the average concentration and range of concen-
trations within that microenvironment can be obtained.  If an assumption
is made about the shape of the distribution, then a mathematical description
of the distribution can be obtained.

     Pollutant concentrations within a microenvironment change with the hour
of the day.  The change is, in general, dependent on number of vehicles and
ventilation rate.  Thus, several concentration distributions for each micro-
environment may be necessary, either as a function of time of day, number of
vehicles, or ventilation rate.

     Use of Carbon Monoxide Concentrations

          Nationwide, mobile sources produce approximately 76 percent of
the total carbon monoxide emitted into the atmosphere.(2^)  For the micro-
environments considered in this study, mobile sources are the only signifi-
cant source of CO.  Thus, CO measurements in these microenvironments can
be used to determine the level of any mobile source pollutant.

          Pollutant concentrations are proportional to the exhaust emission
rate  ("emission factor").  For example, the concentration of a pollutant
emitted from vehicles at the rate of 4 g/min will be twice as high as the
concentration of pollutant emitted at 2 g/min in the same situation.  Thus,
CO concentration measurements can be used to determine the concentration
of any unregulated mobile source emission by multiplying the CO concentration
by the ratio of the unregulated emission factor to the CO emission factor.
In this project, the CO concentration is divided by the CO emission factor
in g/min, producing a concentration equivalent to a 1.0 g/min emission
factor.  To obtain the pollutant concentration for any unregulated emission,
the concentration at 1.0 g/min is multiplied by the appropriate unregulated
emission factor expressed in grams per minute.

          The CO emission factors were obtained from the EPA publication
"Compilation of Air Pollutant Emission Factors:  Highway Mobile Sources,"
EPA 460/3-81-005, (21) or directly from the MOBILE 2 computer program which
was used to generate the emission factors in the published compilation.

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 Different  emission  factors were  used  for  the  different  microenvironments
 since  average  vehicle  speed  varies  with the situation.   Also,  the  calendar
 year,  or years, when measured  CO levels were  available  varied  with each
 microenvironment.

     Use of Frequency  Distributions of Pollutant Concentrations

           Any  investigation  of actual pollutant concentrations in  any
 environment reveals a  rather wide range of pollutant  levels.   Thus, persons
 in these environments  at different  times  are  exposed  not just  to one pollu-
 tant concentration, but to a range  of concentrations.   The concentration
 level  depends  mainly on the  number  of vehicles present  and the amount of
 ventilation  (natural or artificial).  The concentrations vary  not  only with
 time at a  single location, but also from  location to  location  at a given
 time.  By  accounting for the occurrence of pollutant  concentration ranges
 for all locations of a microenvironment for a year, a single pollutant con-
 centration frequency distribution can be  developed which takes into account
 the concentration variation  with time and location.

           In most of the microenvionments investigated  in this study,
 insufficient CO measurements were available to define the concentration
 frequency distribution for the measured data.  In those  cases  where measured
 data were not  available, some  assumption  has  to be made  about  the  mathe-
 matical form of the distribution.   The lognormal distribution  has  been
 used for about 15 years to describe the distribution of  ambient pollutant
measurements both with time  and  location.  '22)  Tne lognormal distribution
 gets its name  from the fact  that the logarithms of the  independent variable
 are normally distributed.  Over  the years, a  lively debate has been conducted
 in the literature on whether the lognormal distribution was the best repre-
 sentation of the concentration distribution.  While other distributions,
 such as the Weibull distribution, have been suggested, the lognormal appears
to be the most widely used.  For this study,  the lognormal distribution
has the additional virtue of being  definable  from available concentration
values.  Therefore, the lognormal distribution was chosen as the mathema-
tical form to  use when there were insufficient data to define  the  distri-
bution from measured values.

          The  expression for the two-parameter lognormal  distrubution is:'  '
               dF(x)  = 	 exp
                          \/2T
2CJ2
     (In x - p)'
dx
               where:
                       x = pollutant concentration
                       y = mean
                       02= variance

-------
                                                     2
The distribution can be completely defined if y and a ,  are known.  Appendix
A presents the various relationships between y and a and the mean, median
and mode which were used in this project to define the lognormal distri-
butions for each microenvironment from measured concentration values.

     Parking Garage Pollutant Concentrations

          The first microenvironment for which ambient air concentrations
of pollutants were developed was the parking garage.  While CO concentrations
in parking garages have been a concern for years, few quantitative data
are available.  What is available, is often only as a maximum CO or average
CO concentration.  These values are not sufficient for this project.  A
distribution of concentrations is needed, since using an average concen-
tration would eliminate any high-level exposures.  However, there was not
sufficient information in the literature to determine this distribution.
Table 1 is a list of measured parking garage CO concentrations found in
the literature.  Additionally, the modeling study done under Contract
68-03-2884 calculated a CO concentration of 37 ppm in a "typical"  (mode
average) garage and 374 ppm for a "severe case" parking garage.  These CO
values all indicate that pollutant concentrations are not normally distri-
buted, but rather are skewed, with a long "tail" at the higher concentrations.
                TABLE 1.  CO LEVELS FOUND IN PARKING GARAGES


 	CO Levels	       Reference No.  Study Location  Study Date

 20  ppm to over 100  ppm   (off             27         Detroit           1961
 scale  100).   Several peaks
 appear as though  they would
 exceed 150 ppm

 0-200 ppm Car Park  A (Sat.)               28         England           1976
 0-20 ppm Car Park A (Tues.)
 0-200 ppm Car Park  Bl
 0-30 ppm Car Park B2
 33  ppm @ 200 car/hr Car Park B4
 Max. 110-130 ppm  Car Park Cl
 50  ppm Car Park C2
 105 ppm Car Park  Dl
 Max. 400-450 ppm  Car Park D2
   (mech. vent.)

 30-87 ppm eight hr  avg                    29         Philadelphia     1977

 peaks often above 200 ppm                30         Los Angeles      1975
 max 365 ppm

-------
           Since  adequate  data  to define  the  distribution do  not  exist,  it
was  decided  to choose  a distribution  equation,  then  use  the  CO values for
the  typical  and  severe parking garage from Contract  68-03-2884 to define
the  distribution.   The concentration  distribution  is then in a mathematical
form which could easily be modified if measured data become  available in
the  future.  As  explained earlier, the lognormal distribution  was chosen
to represent the pollutant concentration distributions where there were
insufficient data  to define the distribution experimentally.   As shown  in
Appendix A,  a lognormal distribution  can be  completely defined if the median
and  mode of  the  distribution are known.  For this  project, the typical
garage CO  value  developed under Contract 68-03-2884 (18)  was  used as the
mode.  The median  was  adjusted so that the frequency of  occurrence in the
"severe" concentration range was approximately  equal to  one  garage.
Assuming 10,000  parking garages in the country,  this is  equivalent to a
frequency  of occurrence of 0.01 percent.

           While  ultimately distributions in  yg/m3  based  on an  emission
factor of  1  g/min  are  required,  a distribution  in  ppm CO, using the calcu-
lated typical and  severe  levels  was first computed for a better visuali-
zation of  the distribution and for comparison to the  data in Table 1.  The
mode was taken as  37 ppm^18) and the  median  adjusted  until the frequency of
occurrence in the  300  to  400 ppm interval was approximately 0.01 percent.
This resulted in a median value  of 48.   This distribution is shown in
Figure 1 .  Note  that the  largest  number of occurrences are in  the range
of the CO  values shown in Table  1 .
          This study requires ambient concentrations in yg/m3 based on a
1.0 g/min emission rate.  The typical concentrations obtained from the
modeling work done under Contract 68-03-2884  were actually calculated using
a one gram per minute emission factor.  The typical garage has an ambient
air level of 3900 yg/m3 for 1.0 g/min pollutant emission rate; the severe
garage, a level of 46,100 yg/m3.^8)  For both these situations, the active
cars represented 25 percent of parking capacity.  For this distribution,
the mode was 3900 yg/m3 and the median 5500 yg/m3, giving a y of 8.6125
and a a of 0.58632 (see Appendix A).

          The model used for parking garage ambient concentrations in
Contract 68-03-2884 indicates that after a short period, for instance
10 minutes, the concentrations are essentially proportional to the number
of cars divided by the effective ventilation rate.  Thus, concentrations
will vary with number of active cars.  The active cars vary from 0 to
21.3 percent of parking capacity (see Section IV).  To keep the number of
concentration distributions reasonable, it was decided to develop three
distributions, one each for 3, 9 and 19 percent active cars.  These dis-
tributions were developed by scaling the 25 percent mode and median by
the ratio of active cars to 25 percent active cars, since concentration
varies linearly with number of cars.

          As mentioned above, pollutant concentration varies not only with
number of active cars, but also with effective ventilation rate.  The yg/m3

                                    10

-------
     24
o
•H
X

ff
0)
O

0)
3
O
O
O
C
O
•H
     20
     16
     12
                     50
100
150
  200

CO, ppm
250
300
350
400
                              Figure 1.  Parking garage CO concentration distribution,
                                      25 percent active cars, average wind speed

-------
 pollutant  levels  for  the  typical  garage  were  calculated  assuming  a naturally
 ventilated garage with  an "avergae"  value  for wind speed.   Ninety percent
 of  garages in  the country are naturally ventilated,'   ' with ventilation
 rate depending on wind  speed.   Since the person  hour  exposure  for this
 study  is to be for an entire  year, the ventilation rate  can be expected
 to  vary during the year as wind speed varies.  It  has been  shown  in a
 number of  studies that  wind speed at a given  measuring station varies
 lognormally.(31)

           To obtain an  estimate of how wind speed  varies through  the
 country, the annual wind  speed  distributions  for seven cities were averaged.
 The wind speed distributions for each city were obtained  from the  NOAA
 publication "Airport Climatological Summary."(32)   r^he average of  the seven
 distributions  is  shown  in Figure  2.  Note that approximately 65 percent of
 the time the average  wind speed is between 4  and 10 knots,  25.5 percent of
 the time it is between  11 and  27 knots, and  9.5 percent of the time  it
 is  3 knots  or  less.

           The  pollutant distributions above were calculated using approxi-
 mately a seven knot wind  speed  for the typical (mode) garage.  To account
 for the concentration variation with wind speed, two  other  wind speeds,
 1.5 knots  and  14  knots, were  chosen  to represent ventilation rates lower
 and higher  than the  mode.  Pollutant  concentration  distributions were cal-
 culated using  three wind  speeds by multiplying the mean and mode of each
 of the three distributions calculated at 7 knots by the ratio:  7.0/new
 wind speed, since  pollutant concentration is  inversely proportional to
 ventilation rate.

           These calculations resulted in nine pollutant distributions;
 three distributions depending on  ventilation rate of  each of three levels
 of active cars.   The  mode, median, y and 0 of each of the distributions
 are shown in Table  2.

          The  continuous pollutant distributions generated  must be converted
 into discrete  distributions to obtain the person hour exposure for parking
 garages.   A computer program was  written to evaluate  the expression for the
 lognormal distribution, producing frequences of occurrence  for each pollutant
 interval.    Table  3  shows the relative frequencies for each pollutant inter-
 val in all  nine of the pollutant  frequency distributions.   The pollutant
 intervals were arbitrarily chosen.  The values shown  in Table 3 are one of
the inputs  used to calculate the person hours of exposure in parking garages
as explained in Section V of this report.

     Street Canyon Pollutant Concentrations

          The street canyon exposure calculated in this project is for people
outside on  the sidewalk or in vehicles in the street  canyon.  It does not
include people in buildings adjacent to the street canyon.   Unlike parking
garages,  where there have been few measurements of vehicle pollutant levels,
CO samples  have been taken in downtown street canyons by fixed monitors for

                                    12

-------
u>
0)
Cr>
(0
4-1
C
0)
o
        so r
        40
    i
    -H   30

    M-l
    O
        20
        10
                  9.5
                 0-3
                           29.8
                       m
                                     35.2
                                              21.2
                                                        3.2
                       4-6
 0.7


22-27
                           7-10      11-16    17-21


                         Wind speed,  knots


Figure 2.  wind speed distribution,  average of seven U.S. cities

-------
             TABLE 20   PROBABILITY DISTRIBUTION PARAMETERS  FOR
                  PARKING GARAGE  POLLUTANT  DISTRIBUTIONS
   Percent
   Active
    Cars

     19
 Wind
Speed,
Knots

 1.5

 7

14
  Probability Distribution Parameters,
Mode        Median       y            o
            19500

             4200

             2100
9.8782

8.3428

7.6496
                                                               0.5756

                                                               0.5801

                                                               0.5801
               1.5

               7

              14
               6500

               1400

                700
             9300     9.1378       0.5985

             2000     7.6009       0.5972

             1000     6.9078       0.5972
               1.5

               7

              14
               2200

                470

                235
             3000     8.0064        0.5569

              660     6.4922        0.5827

              330     5.7991        0.5827
a number of years.  The National Air Data Branch of the EPA was contacted
regarding the information that could be retrieved from the data bank of
monitor readings using the SAROAD  (Storage and Retrieval of Aerometrics
Data) system.  From the information received, it appeared that there was
the potential for obtaining a great deal of information regarding CO levels
in street canyons.  However, the data that were easily available were not
sufficient for the needs of the project.  Since the raw data for CO is
stored by hour of the day, it is possible to get summaries of specific
monitors by hour of the day for each month of a year.  These data could
be used to obtain frequency distributions for weekday, Saturday and
Sundays.

          To use the stored monitor data, it was necessary to know which
monitors are in street canyons close to street level.  There are currently
over 4000 active sites, which makes it a time-consuming task to locate CBD
sites manually.  Discussions with personnel in EPA's Office of Air Quality
Planning and Standards led to the EPA group that is charged with inspection
of all monitors that are part of the National Air Monitoring (NAM) network.
This group was able to furnish a list of central city monitors which are
known to be in street canyons.  The list is contained in Table 4.
                                    14

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TABLE  3.   DISCRETE POLLUTANT DISTRIBUTIONS FOR PARKING  GARAGES
Pollutant
Concentration
Interval , yg/m3
0-360
360-463
463-618
618-773
773-1030
1030-1288
1288-1546
1546-1804
1804-2061
2061-2319
2319-2577
2577-3000
3000-4000
4000-5000
5000-6000
6000-8000
8000-10000
10000-15000
15000-20000
20000-25000
25000-30000
30000-40000
40000-50000

Pet. Active cars: 19
Wind Speed, kts: 1.5
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0001
0.0001
0.0004
0.0026
0.0062
0.0113
0.0403
O.D615
0.2008
0.1929
0.1494
0.1060
0.1226
0.0579

19
7
0.0000
0.0001
0.0004
0.0013
0.0062
0.0132
0.0215
0.0299
0.0370
0.0428
0.0466
0.0804
0.1844
0.1513
0.1125
0.1371
0.0666
0.0567
0.0111
0.0029
0.0008
0.0004
0.0001

19
14
0.0034
0.0035
0.0131
0.0248
0.0661
0.0885
0.0981
0.0971
0.0898
0.0840
0.0698
0.0929
0.1370
0.0665
0.0325
0.0255
0.0072
0.0037
0.0003
0.0000
0.0000
0.0000
0.0000
Fraction
9
1.5
0.0000
0.0000
0.0000
0.0000
0.0001
0.0004
0.0009
0.0017
0.0028
0.0043
0.0058
0.0133
0.0401
0.0703
0.0818
0.1678
0.1472
0.2410
0.1132
0.0538
0.0252
0.0206
0.0056
of Time in Interval
9
7
0.0054
0.0052
0.0176
0.0308
0.0760
0.0958
0.1016
0.0975
0.0881
0.0775
0.0663
0.0873
0.1267
0.0610
0.0298
0.0236
0.0068
0.0036
0.0003
0.0001
0.0000
0.0000
0.0000
9
14
0.0435
0.0540
0 . 1096
0.1211
0.1845
0.1433
0.1024
0.0708
0.0490
0.0337
0.0232
0.0242
0.0269
0.0074
0.0024
0.0014
0.0002
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
3
1.5
0.0003
0.0004
0.0020
0.0053
0.0203
0.0368
0.0520
0.0630
0 . 0690
0.0713
0.0701
0.1069
0.1969
0.1235
0.0731
0.0691
0.0243
0.0149
0.0017
0.0003
0.0001
0.0000
0.0000
3
7
0.1481
0.1196
0.1805
0.1497
0.1698
0.0967
0.0535
0.0298
0.0172
0.0100
0.0059
0.0053
0.0046
0.0009
0.0002
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
3
14
0.5656
0.1569
0.1389
0.0684
0.0475
0.0159
0.0058
0.0023
0.0010
0.0004
0.0002
0.0001
0.0001
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000
0.0000

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          TABLE 4.   SAROAD CO MONITORS USED IN STREET CANYON ANALYSIS
          SAROAD No.
        10 1960
        10 2700
        10 4360
        11 0200
        14 1220
        15 2040
        18 2380
        19 2020
        21 0120
        22 0240
        22 2160
        23 1180
        33 4680
        33 4680
        34 0700
        36 1220
        39 7140
        39 7260
        41 0300
        44 2540
        45 1310
        45 4570
        49 1840
        09 0020
        26 4280
085H01
018G01
056G01
04 3F01
040F01
034F01
026G01
017F01
034H02
022F01
007F01
021G01
058F01
062F01
029G01
021G01
045H01
005G01
009F01
021G01
053H01
046F01
077F01
022112
079H01
Hourly Readings
 Available5        State

     7848           FL
     8144           FL
     7782           FL
     6309           GA
     7616           IL
     7912           IN
     7782           KY
     5814           LA
     7768           MD
     6512           MA
     1084           MA
     8030           MI
     8090           NY
     8023           NY
     8002           NC
     7945           OH
     8336           PA
     6716           PA
     7948           RI
     8659           TN
     7899           TX
     2320           TX
     8529           WA
     N.A.b          DC
     N.A.           MO
                                            City
Jacksonville
Miami
Tampa
Atlanta
Chicago
Indianapolis
Louisville
New Orleans
Baltimore
Boston
Springfield
Detroit
New York
New York
Charlotte
Cincinnati
Philadelphia
Pittsburgh
Providence
Nashville
Dallas
San Antonio
Seattle
Washington
St. Louis
        .  8760 hours in one year
          Data from these monitors requested, but not available
          The purpose in obtaining these data was to provide as  large a
measured CO base as possible from which to generate a street canyon
pollutant frequency distribution.  Data from all the cities were merged
in one set of CO readings regardless of city size or other variables.
The time and effort allotted to this project were not sufficient to weight
the individual monitor values by city size, street size, or traffic density,
or to compare individual monitor distributions.  The data, as received,
were formatted to have 12 hours of data from one station on each line.
This means that one day's data from one station required two lines,  if
all 12 hours of data were missing, the whole line was skipped.  Thus, some
days would have two lines of data and some would have only one  line.  The
statistical computer program used to analyze the information  (Statistical
Package for the Social Sciences, SPSS) could not handle this type of
variable format.  The data from the monitoring stations were also not all
                                    16

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in the same units.  Some data were in ppm and some in milligrams per cubic
meter.  The readings themselves consisted of four integers, with the decimal
point location for the data indicated elsewhere on the line.  Additionally,
it was desired to separate out weekdays, Saturdays and Sundays.  This
required checking the date of each line and assigning the CO readings to
the correct category.  With approximately 14,000 lines of data, the editing
process obviously had to be computerized.  A FORTRAN computer program was
written to provide the necessary editing.  Appendix B contains a listing of
the editing program.

          Once edited, the data were processed using the SPSS program to
obtain frequency distributions, the mean, median, and range of the CO data
in ppm for each hour of the day for weekdays, Saturdays and Sundays.  The
minimum, maximum, mean and median for each hour are presented in Table 5.

          Next, the CO distributions for each hour of the day were investi-
gated.  CO distributions were generated using the SPSS computer program
for each hour of the day.  The ppm CO concentrations were divided into 19
intervals.  To reduce the number of distributions to a more manageable
level, the individual hourly distributions were examined and similar dis-
tributions combined.  This resulted in six distributions for each day type.
These CO distributions are shown in Table 6.   These values are presented
in terms of ppm CO, because it is a familiar unit.  For use in the project,
the ambient concentrations should be in yg/m3 for an emission factor of
1.0 g/min.

          From the published "Mobile 2" data, Table G-9 of Reference 21, a
1981 CO emission  factor of 50.51 g/mile was obtained, using a 75°F day.
At 19.6 miles/hr, this emission factor is equivalent to 16.50 g/min.
Using this emission  factor, the CO ppm intervals were converted to  "Vlg/n\3
of pollutant" intervals by multiplying the ppm CO values by the appropriate
conversion factor  (1157/16.50 = 70.12).  The new intervals are shown in
Table 7.  The distributions using the yg/m3 intervals were used to deter-
mine the person hour exposure in street canyons, as explained in Section V.

     On-Expressway Pollutant Concentrations

          The approach to this project was to use the NEM  CO study results
wherever  possible.   Since the NEM contains a  "transport  vehicle" micro-
environment, it was  decided to use this microenvironment for the on-
expressway situation, if at all possible.  The  NEM computer program
attempts  to estimate the CO concentrations in cars by multiplying a CO
monitor reading by a constant.  As part of the  NEM CO study, a literature
review was conducted to determine what  this multiplier  should be.   The
investigation indicated that the  "transport vehicle" microenvironment
multiplier should be between 1.3 and 4.7.  A value of 2.1  was chosen as
the best  estimate.(33)
                                     17

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TABLE 5.  DESCRIPTIVE  STATISTICS FOR STREET CANYON CO READINGS
  Weekdays
Saturdays
Sundays
Hour
Ending
1 am
2
3
4
5
6
7
8
9
10
'-' 11
oo J--L
Noon
1 pm
2
3
4
5
6
7
8
9
10
11
Midnight
Concentration
Range
0-12
0-12.5
0-12.0
0-12.5
0-15.0
0-11.3
0-17.1
0-24.5
0-28.5
0-17.6
0-18.0
0-18.5
0-22.3
0-19.9
0-16.0
0-19.2
0-20.8
0-22.7
0-20.5
0-18.3
0.17.0
0-19.6
0-16.0
9-17.0
Mean
1.63
1.37
1.16
0.99
0.98
1.38
2.57
3.97
4.41
3.96
3.92
3.97
4.06
3.94
3.97
4.32
4.89
4.33
3.07
2.57
2.35
2.32
2.28
2.15
, ppm
Median
1.09
0.99
0.83
0.75
0.79
1.02
2.04
3.47
3.81
3.36
3.37
3.45
3.49
3.41
3.51
3.96
4.42
3.65
2.46
2.02
1.98
1.98
1.96
1.73
Concentration
Range
0-11
0-13
0-12
0-9
0-9.5
0-7.3
0-8.8
0-8.5
0-10.2
0-19.0
0-9.5
0-11.0
0-17.0
0-17.0
0-17.5
0-13.0
0-13.3
0-14.0
0-14.5
0-11.5
0-11.6
0-17.0
0-16.4
0-11.5
Mean
2.26
2.10
1.85
1.42
1.20
1.21
1.49
1.78
1.99
2.12
2.28
2.40
2.45
2.53
2.62
2.62
2.57
2.48
2.30
2.35
2.34
2.45
2.59
2.50
, ppm
Median
1.95
1.49
1.18
1.00
0.96
0.98
1.06
1.49
1.70
1.87
1.99
2.01
2.01
2.02
2.03
2.04
2.02
1.99
1.94
1.97
1.96
1.99
2.04
2.00
Concentration
Range
0-19.4
0-16.0
0.15.3
0-14.3
0-13.6
0-12,. 4
0.11.6
0-10.0
0-10.4
0-12.2
0-10.2
0.9.0
0.10.2
0-9.2
0-11.2
0-11.5
0-11.0
0-11.2
0-12.9
0-11.1
0-13.5
0-10.3
0-10.4
0-10.7
Mean
2.26
2.03
1.78
1.39
1.14
1.04
1.12
1.22
1.21
1.30
1.36
1.46
1.57
1.64
1.80
1.85
1.94
1.99
1.98
1.97
1.94
1.87
1.81
1.65
, ppm
Median
1.72
1.48
1.13
0.99
0.88
0.84
0.96
0.99
1.00
1.02
1.04
1.04
1.16
1.22
1.34
1.39
1.45
1.50
1.53
1.60
1.55
1.48
1.32
1.18

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TABLE 6•  DISTRIBUTION  OF  HOURLY AVERAGE CO LEVELS
                  IN STREET CANYONS
PPM CO
Interval

0.0-0.5
0.6-1.5
1.6-2.5
2.6-3.5
3.6-4.5
4.6-5.5
5.6-6.5
6.6-7.5
7.6-8.5
8.6-9.5
9.6-10.5
10.6-11.5
11.6-12.5
12.6-13.5
13.6-15.5
15.6-18.5
18.6-21.5
21.6-24.5
24.6-29.5


0.0-0.5
0.6-1.5
1.6-2.5
2.6-3.5
3.6-4.5
4.6-5.5
5.6-6.5
6.6-7.5
7.6-8.5
8.6-9.5
9.6-10.5
10.6-11.5
11.6-12.5
12.6-13.5
13.6-15.5
15.6-18.5
18.6-21.5
Percent Frequency for Time Interval Shown

l-6am
33.58
40.51
14.35
6.31
2.71
1.30
0.60
0.34
0.15
0.07
0.04
0.02
0.02
—
<0.01
—
—
—


l-3am
19.87
32.46
19.46
11.62
6.50
3.72
2.61
1.68
1.01
0.50
0.34
0.13
0.07
0.03
--
--
—

7am
6.21
28.58
25.68
17.50
10.00
5.41
3.00
1.39
0.98
0.57
0.35
0.10
0.12
0.04
0.04
0.02
—
—


4-6am
31.37
40.96
16.04
6.18
3.31
1.14
0.57
0.30
0.07
0.07
—
--
—
—
--
—
—

8-9am
1.91
11.37
18.62
18.18
15.05
10.49
8.11
6.03
3.26
2.39
1.63
1.04
0.66
0.35
0.47
0.30
0.07
0.03
0.02

7-8am
16.47
42.22
23.39
10.79
4.57
1.41
0.70
0.30
0.10
0.05
—
—
—
—
—
—
—
Weekdays
10 am- 3pm
2.23
12.92
19.88
18.00
14.27
10.39
7.57
5.49
3.50
2.36
1.42
0.76
0.51
0.32
0.29
0.09
0.01
<0.01

Saturday
9-noon
8.39
33.20
27.34
15.64
8.29
4.24
1.49
0.78
0.38
0.15
0.03
0.03
0.03
—
—
—
0.03

4 -6pm
1.82
10.05
16 . 16
16.73
14.21
11.33
9.34
6.75
4.70
3.24
2.16
1.28
0.84
0.53
0.50
0.24
0.09
0.01


l-6pm
6.13
29.98
26.22
15.69
9.47
5.48
3.25
1.67
0.98
0.56
0.27
0.10
0.08
0.05
0.02
0.05
—

7-Mid.
9.23
29.54
25.37
15.50
8.85
4.77
2.75
1.66
0.95
0.56
0.26
0.18
0.10
0.09
0.12
0.04
0.02
—


7-mid.
9.92
30.70
23.11
15.72
9.55
4.62
2.38
1.57
1.16
0.62
0.34
0.19
0.05
0.02
0.02
0.05
—
                       19

-------
        TABLE 6 (CONT'D).   DISTRIBUTION OF HOURLY AVERAGE CO LEVELS
                            FOR STREET CANYONS
PPM CO
Interval


 0.0-0.5
 0.6-1.5
 1.6-2.5
 2.6-3.5
 3.6-4.5
 4.6-5.5
 5.6-6.5
 6.6-7.5
 7.6-8.5
 8.6-9.5
 9.6-10.5
10.6-11.5
11.6-12.5
12.6-13.5
13.6-15.5
15.6-18.5
18.6-21.5

Percent
Frequency
for Time Interval Shown
Sunday
l-2am
18.51
31.90
20.31
11.49
7.64
3.08
3.38
1.44
1.08
0.41
0.15
0.21
0.21
—
0.05
0.10
0.05
3-4am
27.18
38.85
16.18
8.30
3.84
1.97
1.66
0.93
0.41
0.31
—
0.16
—
0.10
0.10
—
—
5-10am
28.73
48.47
15.09
4.89
1.43
0.91
0.17
0.12
0.05
0.03
0.03
0.02
0.05

0.02
—
—
11am- 2pm
18.47
46.72
19.76
9.30
2.99
1.67
0.48
0.25
0.20
0.10
0.05
—
—
—
—
—
—
3- llpm
14.84
39.46
21.86
11.60
5.74
2.96
1.54
0.89
0.43
0.28
0.26
0.11
0.01
0.02
—
—
—
Midnight
20.64
40.87
18.15
11.20
4.77
2.49
0.73
0.62
0.10
0.21
0.10
0.10
—
—
—
—
—
      TABLE 7.  POLLUTANT CONCENTRATION INTERVALS FOR STREET CANYONS

                     PPM CO       Rg/m3 at 1. Og/min a

                      0-.5                0-35
                     .6-1.5              36-105
                    1.6-2.5             106-175
                    2.6-3.5             176-245
                    3.6-4.5             246-315
                    4.6-5.5             316-386
                    5.6-6.5             387-456
                    6.6-7.5             457-526
                    7.6-8.5             527-596
                    8.6-9.5             597-666
                    9.6-10.5            667-736
                   10.6-11.5            737-806
                   11.6-12.5            807-876
                   12.6-13.5            877-947
                   13.6-15.5            948-1087
                   15.6-18.5           1088-1297
                   18.6-21.5           1298-1508
                   21.6-24.5           1509-1718
                   24.6-29.5           1719-2069
           aBased on a CO emission factor of 50.51 g/mile  for the
            FTP for 1981.  At 19.6 miles per hour  this  is equivalent
            to 16.50 g/min.  One ppm CO = 1157 yg/m3.
                                  20

-------
          Using the 2.1 multiplier and the maximum one hour CO reading
occurring in each of the four cities used in the NEM study, the highest CO
values used for the NEM transport microenvironment are 52 ppm for Chicago,
66 ppm for Los Angeles, 40 ppm for Philadelphia and 48 ppm for St. Louis.
The maximum geometric means for the transport microenvironment from the
six monitors used in.each city are:  6 ppm, 8 ppm, 5 ppm, and 11 ppm for
Chicago, Los Angeles, Philadelphia, and St. Louis, respectively.(33)

          The work done at SwRI in developing an on-expressway model,
under Contract 68-03-2884, indicates that using a multiplier on a CO value
from a fixed monitor is not the best way to determine CO levels on express-
ways.  Nevertheless, the CO distribution for the transport microenvironment
resulting from the NEM calculations is probably as good as any alternate
distribution that could be developed with reasonable effort.  To check the
reasonableness of the NEM distributions, they were compared to the results
of the only studies of on-expressway CO measurements found in the literature.
(34-48)  A summary of the CO ranges found i/n these studies is presented
in Table 8.  Concentration distributions from Reference 38, for three cars,
are shown in Figure  3.

                    TABLE 8.  MEASURED CO ON EXPRESSWAYS
CO PPM
Cumulative
Frequency %
25
50
75
90
95
1966*
Chicago St.
24
30
46
50
— —

Louis
28
38
44
51
56
est .
Chicago
12
15
22
24
— *~*
1979b
St. Louis
14
19
21
25
27
1982
Car 2
12
20
21
22
30
Los Angelesc
Cars 1 & 3
10
12
15
20
25
 From Reference 34
 Reference 34 values multiplied by ratio of 1979 to 1966
 CO emission factors  (30.57/62.06)
 From Reference 38
 Notes:  Reference 35 gives values of 15-20 ppm CO with only one
         reading  (at 45 ppm) higher than 25 ppm in 1974.
         Reference 36 gives values of 15-45 ppm CO in 1977


          Comparing the maximum NEM transport microenvironment CO concen-
trations with the 95 percent levels in Table 8, the NEM maximums do not
appear unreasonable, considering that maximum values correspond  to the
99.99 percentile of a distribution.  The geometric mean values from the
NEM study appear to be reasonable, considering that the distributions shown
in Figure 3 are one minute averages, while the NEM values are one hour
averages.  Since there are so few measured on-expressway CO data, and the
NEM CO values do not appear to be grossly out of line, the NEM concentration

                                    21

-------
     10
 •P
 o
 EH
 M-i
 O
 -P
 C
 8
Car 3
     10 _
                    10           20          30
                             CD concentrations, ppm
     40
                                                  50
 O
 EH
4-1
C
01
O
M
0)
P4
Car 2
     10  _
10           20           30
        CO  concentrations, ppm
                                                         40
                 50
4J
g
M-4
O
0)
                                                    Car 1
                    10          20           30
                            CO concentrations, ppm
     40
                                                 50
     Figure 3.  Frequency Distribution  of CO concentrations outside
                   three cars on Los Angeles Freeways
                                 22

-------
will be used for the on-expressway microenviixmment.  The NEM program uses
actual hourly CO measurements  (or estimated, if actual value missing) from
the SAROAD data base, so no frequency distribution information is produced
by the NEM.  While frequency distributions could conceivably  be developed
from the hourly measurements, the time and effort allotted to this study
did not permit the development of such distributions.

     Roadway Tunnel Pollutant Concentrations

          The literature on air pollution in tunnels had been extensively
investigated under Contract 68-03-2884.  While CO is monitored in almost
all mechanically ventilated tunnels, there  are few  published CO data.
A list of the information found is presented in Table 9.  The most complete
study found was in Reference  39, which had CO levels for the Sumner Tunnel
in Boston.  From the information presented on the Sumner Tunnel in
Reference 39, plots of both average and maximum CO  levels as functions off
percent of average daily traffic  (ADT) per hour for weekdays were developed.
These plots are shown in Figure 4.
              TABLE 9.  CO LEVELS FOUND IN ROADWAY TUNNELS
           CO Concentrations
Reference
   No.
Study Location
 110 ppm  (7:30-8:00 A.M., No. Tube)     39
 190 ppm  (7:30-8:00 A.M., So. Tube)

 140 ppm  ( 5:00-5:45 P.M., West Tube)   39
  75 ppm  (avg over  3  days)               39
  rarely  exceeded 180 ppm

  12-144  ppm mean                        39
  30-238  ppm peak

  40-200  ppm  (North  tube)              39
  10-60 ppm (Center tube)

  10-100  ppm avg  (West  Tube)            39
  250  max

  40-250  ppm                           39
  42-122  ppm (Brooklyn bound tube)      40
          Squirrel Hill Tunnel
          Pittsburgh, PA

          Liberty Tunnel
          Pittsburgh, PA

          Baltimore Harbor Tunnel
          Baltimore, MD

          Sumner Tunnel
          Boston, MA

          Lincoln Tunnel
          New York, NY

          Fort Pitt Tunnel
          Pittsburgh, PA

          Armstrong Tunnel
          Pittsburgh, PA

          Brooklyn Battery Tunnel
          New York, NY
Study
Date

1969
                         1969
                        ~1971
                         1961
                    est. 1970
                         1971
                        -1971
                        ~1971
                                     23

-------
                                                     D
   220
   200
   180
   160
           Q Maximum

           O Mean
              Max CO  *  a  + b  (%  ADT)
                   a  -  52.896
                   b  =  27.674
                  r2  =  0.7904
                                                a
                                                G
                                                    /

                                               /a
                                               Q
a
a.
o
4-1
c
01
o
0
o
u
   140
   120
100
    80
    GO
    40
                                           Mean CO = a + b (% ADT)
                                                 a = 0.78840
                                                 b = 19.267
                                                r2 = 0.9724
                 1234567
                                   Percent ADT

            Figure 4.  CO concentration as a.  function  of hourly percent ADT
                          for the Sumner Tunnel  (1961)
                              24

-------
          All tunnels have ventilation systems designed for some maximum CO
rate at the maximum expected traffic levels.   This means that for all
tunnels, the CO relationship with percent of average daily traffic (ADT)
should be similar.  The maximum design CO level has generally been in the
200 to 250 ppm CO range.  Maximum hourly traffic is rarely over eight percent
of ADT.  Thus, the Sumner Tunnel data can be used as the basis for develop-
ment of pollutant concentration distributions for roadway tunnels.

          A linear regression was performed on the average CO concentrations
and the percent ADT values shown in Figure 4.  The results of that analysis
are shown on the figure, together with the results of the regression analysis
of the maximum values.  As might be expected, the maximum CO values did not
produce as good a linear fit as the mean CO values.  The mean CO level is
obviously a function of the percent ADT.


          For this study,  a  pollutant distribution representing the con-
centrations over all tunnels, for all days of the year, is required.  Since
the concentrations are a function of percent ADT, seven different distri-
butions were developed, one for each of seven different levels of percent
ADT.  If the pollutant concentration is assumed to be lognormally distri-
buted for a given percent ADT as a result of tunnel^tor;tunnel variability,
fleet composition, weather and traffic flow variability, then, with the
mean concentration taken as the distribution mean  and the maximum concen-
tration as an indication of the range, the distributions could be defined
from the data on hand.  However, from a summary of tunnel ventilation in
Reference 18, the Sumner Tunnel appears to have a worse than average venti-
lation rate in terms of cubic meters per meter of lane, while having
higher than average ADT.  Thus, the Sumner Tunnel is likely to have higher
CO levels than an average tunnel.

          The Sumner Tunnel ventilation rate is approximately 25 percent
less than the average rate.  This can be taken into account by reducing
the mean CO value shown in Figure 4 by 25 percent at a given percent ADT.
The maximum values will not be changed since they are values that are found
in tunnels and must be included in the distribution.  The ADT in the Sumner
Tunnel is approximately 1.6 times higher than the mean ADT for all tunnels.
 (18,39)  To account for this, the percent ADT can be increased 1.6 times
for a given CO concentration.  Again the maximum values are not adjusted.
When these two adjustments are made, the relationships between hourly
percent ADT and CO concentrations for an average tunnel are as shown in
Figure 5.

          Assuming that the CO concentration in tunnels has a lognormal
distribution, the CO distribution can be determined from the mean and
maximum CO values at any percent ADT.  See Appendix A for the method used
to obtain these distributions. CO distributions were determined for roadway
tunnels at one percent ADT intervals starting with 0.5 percent ADT and ending
at 6.5 percent ADT.  The equations obtained  from the calculations in
Appendix A are continuous ppm CO distributions.  This project requires
discrete distributions  in terms of yg/m3 for a 1.0 g/min emission factor.
However, it is also desirable to have the discrete distributions  in terms
of ppm CO for comparison with measured data.

                                     25

-------
   60 -
I  40
8
   20 -
    o S
                                                                           250
                                                                           230
                                                                           210
                                                                           190
                                                                           170
                                                                           150
                                                                                eu
                                                                           130  -
                                                                           110
                                                                           90
                                                                           70
50
                1        23        4         5         6         7
                                  Percent ADT

           Figure 5.   CO concentration as a function  of  Hourly Percent ADT
                         for an average Roadway Tunnel
                                    26

-------
     To convert from ppm CO to yg/m3 at 1.0 g/min, the emission factor
for vehicles in tunnels is required.  The Sumner Tunnel data were taken
in 1961.  Therefore, a 1961 CO emission factor should be used to convert
the data in Figure 5 to a 1.0 g/min emission factor.  A national average
fleet emission factor for 1961 is not available from published EPA emission
factors.  To obtain the 1961 emission factor, Ms. Lois Platte at the EPA
Mobile Source Laboratory in Ann Arbor, MI was contacted.  At her direction,
the EPA emission factor computer program, MOBILE 2, was run to generate a
1961 national fleet CO emission at 35 mph.  The resulting emission factor
was 62.06 g/mile, which converts to 36.2 g/min at 35 mph.  The conversion
factor for ppm CO at 36.2 g/min to yg/m3 at 1.0 g/min is:  31.96=- 1157/36.2.
The concentration intervals are shown in Table 10.  The discrete pollutant
distributions in terms of ppm CO are shown in Table 11 for various levels
of hourly percent ADT.  These distributions, with the yg/m3 interval values
replacing the ppm CO values, were used to determine the person hour exposure
in tunnels, as explained in Section V.
       TABLE 10.  POLLUTANT CONCENTRATION INTERVALS FOR ROADWAY TUNNELS
                    PPM CO           yg/m3 at 1.0 g/mina

                        0                       0
                      6.26                     200
                     12.52                     400
                     18.77                     600
                     21.90                     700
                     25.03                     800
                     28.16                     900
                     31.29                    1000
                     37.55                    1200
                     43.80                    1400
                     50.06                    1600
                     56.32                    1800
                     62.58                    2000
                     68.83                    2200
                     75.09                    2400
                     81.35                    2600
                     93.86                    3000
                    125.15                    4000
                    187.73                    6000
                    250.30                    8000
                Based on a 1961 CO emission factor of 62.06 g/mile
                at 35 mph.  This is equivlaent to 36.20 g/min.
                One ppm CO = 1157 yg/m3 CO.
                                    27

-------
TABLE 11. DISTRIBUTIONS OF HOURLY AVERAGE CO
         LEVELS IN ROADWAY TUNNELS
PPM
CO Interval

0-6.26
2.26-12.52
12.52-18.77
18.77-21.90
21.90-25.03
25.03-28.16
28.16-31.29
31.29-37.55
37.55-43.80
43.80-50.06
50.06-56.32
56.32-62.58
62.58-68.83
68.83-75.09
75.09-81.35
81.35-93.86
93.86-125.15
125.15-187.73
187.73-250.30
Frequency f
0.5

0.777
0.129
0.044
0.011
0.008
0.006
0.004
0.006
0.004
0.003
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
1.5

0.288
0.317
0.169
0.052
0.038
0.029
0.022
0.030
0.019
0.012
0.008
0.005
0.004
0.003
0.002
0.003
0.003
0.001
0.000
2.5

0.067
0.230
0.218
0.086
0.071
0.058
0.047
0.069
0.046
0.032
0.022
0.015
0.011
0.008
0.006
0.007
0.008
0.004
0.001
or Percent
3.5
Weekdays
0.013
0.109
0.175
0.088
0.081
0.073
0.065
0.105
0.077
0.056
0.041
0.030
0.022
0.016
0.012
0.016
0.019
0.009
0.001
ADT Shown
4.5

0.006
0.045
0.105
0.068
0.071
0.071
0.068
0.120
0.099
0.078
0.061
0.047
0.036
0.028
0.021
0.029
0.033
0.019
0.002
5.5

0.001
0.018
0.057
0.045
0.052
0.057
0.059
0.116
0.107
0.092
0.077
0.063
0.051
0.041
0.033
0.047
0.057
0.035
0.005
6.5

0.000
0.007
0.030
0.027
0.035
0.042
0.047
0.100
0.102
0.095
0.085
0.074
0.062
0.052
0.043
0.065
0.085
0.056
0.009
                  28

-------
                 IV.  NUMBER OF PERSONS IN MICROENVIRONMENTS
     This study is concerned with the total, nationwide, annual person hours
of exposure.  As such, it is not necessary to know which particular people
are exposed, or how the microenvironment is related to other exposures.  It
is only necessary to know how many people are in each microenvironment for
each hour of the day.  To determine the microenvironment hourly population,
information on the number of locations, size range, and daily usage of each
microenvironment were required.  The published literature, as well as special
sources, were used to obtain the best possible estimates of these parameters.

     Number of persons in Vehicles

          To obtain the hourly population for all microenvironments, an esti-
mate of the number of persons in each vehicle is required.  There are a vari-
ety of estimates given in the literature.  Early in this project, it was
realized that obtaining an accurate estimate of person hour exposure would
require defining the microenvironment populations on Saturday and Sunday, as
well as during the work week  (called "weekdays" in this report).  Thus, any
differences in vehicle occupancy between weekdays and weekends should be
included in the calculations.  The vehicle occupancies used in this study,
taken from References 41 and 42, are shown below.

                             Weekday       Saturday       Sunday
                                a             a              a
               Cars          1.4           2.3            2.3
                              b             b                b
               Buses        26            23              10.6
                  From Reference 41
                 b
                  From Reference 42

     Population of Parking Garages

          From the literature  search conducted under  Contract  68-03-2884,
Task Specification 1, approximately 70  abstracts on parking garages were
reviewed  for  information on usage and pollutant levels.  Of these, ten had
some useful information.  The  earlier study  of parking garages had obtained
information from several different sources on the  number of parking garages
in the country.  The result was an estimate  that varied from 5300 to  10,000
parking garages in the country.     This  spread in the estimated number of
garages was too large to provide the estimate of the  population in parking
garages needed for this project.

                                     29

-------
          For this project, a  list of parking garage  construction projects
since 1967 was obtained from Data Resources, Inc.  This company provides
construction statistics based  on the F. W. Dodge data bank of construction
projects.  F. W. Dodge is widely recognized as the authoritative source for
statistics on all types of construction projects.  The parking garage con-
struction projects in the U. S. from 1967 to 1982 are listed in Table 12.
The total number of projects from 1967 to 1980 is 8499.  .There were approxi-
mately 1291 public parking garages in existence in 1965.     In Reference 18,
construction data found in the magazine, "Parking," indicated that there
were an average of 330 parking garages built per year between 1971 and 1980.
Apparently, the construction reported was primarily public parking garages.
The F. W. Dodye data is for all construction, and shows approximately 592
garages constructed per year between 1971 and 1980.   The difference between
the two construction estimates is apparently a number of private garages
included in the Dodge statistics.  If the same ratio  of public to private
garages has always existed, then there would be almost twice as many parking
garages in 1965 as the 1291 estimated garages.  Assuming 2500 garages in 1965,
and assuming 600 built in 1966, the number of parking garages in 1980 would
be 11,600.
                   TABLE 12.  PARKING GARAGE CONSTRUCTION
                           IN THE U.S., 1967-1982
                         Year

                         1967
                         1968
                         1969
                         1970
                         1971
                         1972
                         1973
                         1974
                         1975
                         1976
                         1977
                         1978
                         1979
                         1980
                         1981
                         1982
Number of
 Projects

   682
   664
   646
   587
   482
   535
   642
   546
   503
   493
   544
   837
   717
   621
   633
   596
                   Source:   F.W.  Dodge/Data  Resources,  Inc.
                                     30

-------
          The total number of parking spaces in these 11,600 parking garages
was calculated from the information in Reference 18 and from the information
supplied by Data Resources, Inc.  The garages were divided into two groups,
one with 6200 large garages averaging 740 spaces per garage, and the other
with 5400 smaller garages averaging 150 spaces per garage.  The total number
of spaces is then 5,398,000.

          Only three references could be found that had.information on cars
in motion by time of day in a parking garage.    '  '    Since there are
over 10,000 parking garages in the country, this is an extremely small sample.
Nevertheless, this information will be used to represent the nationwide average,
since it is all that is available.  From the three references, a composite of
weekday vehicles in motion as a percent of garage parking capacity was obtained
for each hour of the day.  Similar information for Saturday was derived from
data in Reference 43.  The percent of vehicles in motion by hour for Sunday
was estimated considering the values for weekdays and Saturday together with
the fact that for most garages, Sunday would be a day of greatly reduced activ-
ity.  The average percent of cars in motion by hour for each of the three types
of days is shown in Figures 6, 7, and 80

          Two important points about the fraction of active cars need to be
emphasized.  The curves presented are on a per hour basis.  However, the actual
time any one vehicle is in motion is much less than one hour, generally on the
order of five minutes.  Thus, the vehicles in motion at any instant would equal
the hourly fraction divided by twelve.  For the maximum fraction of active cars
per hour (21.34 percent), this gave 1.78 percent active cars at any instant.
This figure agrees well with an Aerospace Corp. study      which found an
average of 1.5 percent active cars at all times in Los Angeles garages.  The
percent of cars in motion is important  since it will be used to select the
proper pollutant concentration distribution  in the calculation of person hours
of exposure.  The second point is that  the people in the  cars are,  in general,
not exposed to the garage pollution levels for a  full hour.  A fifteen minute
exposure has been used in this study.


          The total nationwide person hours of exposure for any hour of the
day was obtained by multiplying the hourly fraction of cars in motion by the
total number of garage parking spaces available nationwide, then multiplying
by 1.4 persons per car for weekdays or  2.3 persons per car for weekends, then
dividing by 4.0.  This calculation is carried out internally within the mobile
source microenvironment computer program, so there is no  need to calculate
hourly person hours separately.  However, an example may  help in visualizing
the number of people involved in the parking garage microenvironment.  For
the weekday hour ending at 11 a.m., the active cars are 0.213 of the total
spaces, thus the number of people in the parking garage microenvironment
during that hour in 1980 was:

          0.213x(5.398 x 106) x 1.4 = 1,609,684 persons

          Then:  1,609,684/4 = 402,421 person hours of  exposure

                                     31

-------
                              range  of data
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                                       8     10     N      2      4      6

                                            Hour of the Day
                                                                                 8      10     M
               Figure  7.   Hourly  average cars  in motion  for Saturdays  in Parking Garages

-------
     0.30 r

-------
     Number of People in Street Canyons

          Recall that the street canyon exposure in this project is for pedes-
trians and motorists within the canyon; it does not include persons in build-
ings adjacent to the street canyon.  Therefore, the number of people and
exposure times are those outside in the canyon.  Because of sparsity of infor-
mation on street canyon populations on hand, a computerized literature search
was run to assist in locating additional information.  The search generated
a listing of 994 abstracts.  An examination of the abstracts revealed only eight
references with information useful to the project.  In addition, three other
references were located by other means.  Only four references had information
useful in determining the total number of people per day traveling to, from,
or within the central business district  (CBD) in vehicles.

          It was clear from the information obtained that the street canyon
population would have to be obtained in two parts:  vehicular and pedestrian.
After examining the data found in'the references, it appeared that the best
way to arrive at CBD population in vehicles was to use CBD cordon counts,
which were available for the peak traffic hour for a number of cities in Refer-
ence 45.  Table 10-40, in Reference 45, lists the peak hour person cordon
count for the top 20 urbanized areas in the U.S.  Based on these counts, there
were 2,245,000 people passing the CBD cordon limits during the peak traffic
hour in the 20 most populous urban areas.

          Peak hour traffic generally averages about eight percent of total
daily traffic.   '    Using this value, there would be a total of 28,062,500
person trips whose origin and destination are within the CBD.  Approximately  2.5
percent of all trips in an urban area are within the CBD and 27.5 percent of
all trips  (urban and rural) either originate or end in the CBD, with other
than a CBD origin or destination.     Thus, total trips in the CBD are approxi-
mately nine percent higher (2.5/27.5 = 0.09) than measured at the cordon.   To
account for the intra-CBD trips, which are  not measured at the cordon, the
cordon counts were multiplied by 1.09, giving 30,616,188 person trips, into,
out of, or within the CBD.  The total population of these urban areas was
given as 64,920,646.  Using these  figures,  an average of 0.472 CBD trips/person
per day was obtained.


          Two other studies of individual cities (Rochester,  NY, and San
Antonio, TX)  yielded 0.578 and 0.737 CBD trips per person.  (48, 49)   From
Reference 45, the urban population averages 2.43 trips per person per day
for all purposes.  Reference 47 indicates that 24.5 percent of all urban
trips are into, out of,  or within the CBD.  These two figures give 0.60
trips per person per day for the CBD.  The available data on CBD person
trips per day is plotted as a function of urban population in Figure 9.
Some studies have indicated that there is an increasing number of CBD trips
per person as the size of the urban area decreases.  In Figure 9, this trend
appears very weak.   In any case, the 0.60 CBD trips per person appears high.
A more reasonable average, obtained from population weighting the data in
Figure 9, is 0.473 CBD trips per day per person.

                                    35

-------
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                                                                     O Most populous  20 urban areas, Ref. 45
                                                                     O Providence,  R.I.,  Ref. 45
                                                                     D San Antonio, Texas,  Ref. 49
                                                                     A Rochester, N.Y., Ref. 48
                                                                                                             O
                                   0
                                                              O
                                          I
                                                  1
                                                            I
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                                   4           6            8          10
                                        Urban Area Population  in  Millions
                                                                               12
                               14
16
                         Figure 9..  Number of person trips  to  CBD per person in urban areas

-------
          Using the MEM CO study value for 1980  urban population of 132,023,885
and 0.473 CBD trips per person, there are approximately 62,500,000 CBD trips
per day in the U.S.  In earlier studies, it was assumed that street canyons
comprised 60 percent of the CBD streets. (18)  If CBD trips are considered
equally distributed over the CBD, then there are 37,500,000 (62,500,000x.600)
person exposures in vehicles to the street canyon environment each day on
weekdays.

          For estimates of number of persons exposed on Saturday and Sunday,
three weekly traffic distributions from two different references were used.
 (46,47)  The average weekly urban traffic distribution obtained from these
references is shown in Table 13.
    TABLE 13.  ESTIMATED CBD DAILY TRAFFIC AS A PERCENT OF WEEKLY TRAFFIC
                                  Nashville
                 Urbana   CBDa      Urbanb     Average    Used

     Sunday       13.2     5.8       10.5         9..9      10
     Monday       14.5    15.5       15.2        15.1      15
     Tuesday      13.7    15.3       14.7        14.6      15
     Wednesday    13.7    15.0       14.7        14.5      15
     Thursday     14.0    14.8       14.7        14.5      15
     Friday       15.0    15.5       15.9        15.5      15
     Saturday     16.2    17.8       14.8        16.3      15
      Reference 47
      Reference 46
In Table 13, the values in the column headed "Used," are the daily traffic
percentages used in this study for street canyons.  The weekday values were
adjusted to give the same percentage for all weekdays, the Sunday value
rounded off to the nearest whole percent, and the Saturday values adjusted
so that the total was 100 percent.

          The total number of person trips and vehicles in street canyons
for each day of the week was calculated starting with the base figure of
37,500,000 persons trips in vehicles on weekdays.  Of the person trips to
and from the CBD, 47.4 percent are by car and 52.6 percent by transit„<45)
Of the transit trips, 74 percent are bus passengers and 26 percent are rail
passengers.  (58)  These facts can be used to determine the total person trips
into the CBD as follows:

          37,500,000= 0.474y +0.74  (0.526y)

          Where y = total number of person trips into the CBD

                                     37

-------
           Solving  this equation  gives  43,441,000  person-trips  in  the  CBD  each
weekday, with  20,590,000  (0.474  times  43,441,000)  person  trips by auto  and
16,903,000 (0.74 times 0.526  times  43,441,000) person  trips by bus.   Using
these values and the values of 1.4  persons per car and 26 persons per bus on
weekdays as shown  earlier, the weekday vehicle trips in the CBD can be  calcu-
lated as shown below:

     Weekday vehicle trips =  20,590,000  +  "16,903,000
                                 1.4            26     = 15,358,000

           The  daily vehicle trips for  Saturday and Sunday can  be  calculated
from the weekday vehicle trips and  the daily vehicle trip relationships in
Table 13.  The Saturday and Sunday  vehicle trips  are 15,358,000 and 10,240,000
respectively.  Using these vehicle  trip values, the persons per vehicle shown
earlier and the weekday ratio between  car person  trips and bus person trips
 (20,590,000/16,903,000 = 1.22) the  Saturday and Sunday person  trips can be
calculated using the following equation:
                                          BV
           person trips = (1.22 + 1)
                                           =: + 1
          Where:  B =  persons per bus

                  C = persons per car

                  V = vehicle trips

The average persons per vehicle can then be obtained by dividing the person
trips by the vehicle trips.  The results of these calculations are presented
in Table 14.


        TABLE 14.  DAILY PERSON TRIPS AND VEHICLES IN STREET CANYONS

                               Weekdays      Saturday       Sunday

       Daily person trips     37,500,000    59,410,000    36,380,000
       Daily vehicle trips    15,358,000    15,358,000    10,240,000
       Persons per vehicle       2.44          3.87          3.55
          The hourly traffic flow as a fraction of daily traffic for weekdays
was obtained from Reference 41.  A population weighed average for the data
from various city sizes was used.  The hourly traffic distribution is shown
in Figure 10.
                                    38

-------
                                                             	  Data from Reference
                                                             - ~-  Computed from SAROAD CO data
0.09
0.08
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—



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Figure 10.  Hourly traffic distribution in the CBD for an average weekday

-------
           Saturday and  Sunday  traffic  distributions  were  not found in  the
 literature for  the CBD.   However,  if the  assumption  that  the CO is almost
 entirely  from mobile  sources is  correct,  then  the  hourly  traffic distribution
 should be able  to  be  deduced from  the  measured hourly CO  distributions for
 street canyons  given  in Section  III.   To  check the assumption that CO  level  is
 related to traffic, the weekday  traffic distribution presented in Figure 10
 was paired with the SAROAD  concentration  data  in Section  III by hour of the
 day.  A linear  regression was  performed using  the  mean hourly CO level and the
 hourly percent  ADT.   The regression analysis produced a coefficient of deter-
 mination,  r2  ,  of  0.9598.   The equation and  its coefficients are:

                   p  =  a +  bx

           Where:   p  =  hourly  percent  ADT

                   x  =  hourly  mean ppm CO

                   a  =  -1.4972

                   b  =  1.9276

           To  see the  physical  meaning  of  this  equation, the  linear form can  be
 rearranged as follows:

                   P  =  b (x -  c)

 In this form, "c"  can be thought of as the background concentration,  (assumed
 constant  for  the entire  day),  and  "b"  as  reciprocal  of the contribution of one
 percent ADT to  the ambient  CO  PPM.
                     Since:

                          P = b  (x - c ) = bx - be

                     then:  a = -be

                     and:   c = - 7—
                                  b

Thus, from the regression analysis, the background concentration is
-  (-1.4972/1.9276) = 0.777 ppm for weekdays, and "b"  (the reciprocal of the
ADT "emission factor")  is 1.9276 percent ADT/PPM.

          The percent ADT for each hour of the day for weekdays was calculated
using the above equation.  These values are also shown in Figure 10 for com-
parison with traffic count data.  As would be expected from the high coefficient
of determination, the two values of ADT agree closely, demonstrating that the
hourly CO pattern can be used to develop an hourly traffic pattern.

                                    40

-------
          Implicit in the equation is some actual value for the weekday ADT.
To apply this equation to Saturday and Sunday, the "b" coefficient must be
adjusted for the traffic count difference between weekdays and Saturdays and
Sundays.  The "b" coefficient was changed by the ratio of weekday vehicles to
Saturday and Sunday vehicles.  The ratio was 1.0 for Saturday and 1.5 for
Sunday.  However, when the weekday equation, adjusted for traffic differences,
was applied to the Saturday and Sunday CO distribution, the calculated hourly
percent ADT values did not total 100 percent.

          After some thought, it was realized that the weekend on-the-road
fleet had a smaller percentage of commercial vehicles  (mostly trucks) than
the weekday fleet.  Since truck CO emissions can be several times car emissions,
this change would reduce the fleet CO emission factor on weekends.  With lower
mobile source CO emissions and reduced industrial activity, the weekend back-
ground will also probably be lower.

          If the emission factor .and background are assumed to be equal on
Saturday and Sunday, but the Sunday traffic is two- thirds of the Saturday
traffic, then two equations can be written for the percent ADT as a function
of PPM with only two unknowns; the background and the  "b" coefficient.  When
these two equations are solved, the resulting background level is 0.589 PPM.
The "b" coefficient for Saturday, which has the same total traffic as weekdays,
is 2.650.  This is equivalent to a 28 percent reduction in the weekday fleet
emission factor.  The "b" coefficient for Sunday is 1.5 times the Saturday
coefficient  (or 3.975) to account for the reduced Sunday traffic.  The percent
of ADT distributions which result from applying these  equations to the hourly
PPM readings in Table 5 of Section III, are shown in Figures 11 and 12 for
Saturday and Sunday, respectively.

          Three references for pedestrian street canyon population were all
that could be found in the literature.  (50, 51, 52)  The total number of
pedestrian trips was calculated from Reference 52 , which indicated that there
were 5.8 weekday pedestrian  trips for each weekday vehicle trip into the
Chicago CBD.  Since no other information could be found, this number was
used for all CBD's in the country.  At  5.8 pedestrian  trips per trip in a
vehicle and  37,500,000 person trips in vehicles  (Table 14), there are
89,076,000 pedestrian trips  in the U. S. each weekday.
           From a  study  of  Seattle  pedestrians,      the daily pedestrians  as
 a percent  of  total  weekly  pedestrians were calculated.  This distribution by
 day  of  the week is  shown in Figure 13.  The average weekday pedestrian trips
 are  16.54  percent of the total weekly trips.   The total weekly trips are  then
 538,552,000.   Saturday  trips are 13.0 percent of the weekly trips,  giving
 70,012,000 pedestrian trips on Saturday in the U. S.  Sunday pedestrian trips
 are  4.3 percent of  the  total weekly trips, or 23,158,000 Sunday pedestrian
 trips.
                                     41

-------
Fraction of total Saturday Traff
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                                                                     M
                         hour  of  the  day
Figure 11.  Hourly traffic distribution in the CBD for Saturday

-------
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10
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               Figure 12.   Hourly traffic distribution in the CBD for Sunday

-------
   20



   18
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               Sun
Mon
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Thu
Fri
Sat
                Figure 13. Pedestrians for individual days of the week as

                          a percent of total weekly pedestrians

-------
          From the three references, hourly distributions of pedestrians in
street canyons for weekdays and Saturdays were developed.  These distributions
are shown in Figures 14 and 15 as percent of total daily pedestrians.  There
were no distribution data available for Sundays.  Therefore, the Saturday
distribution in percentage terms was used for Sunday also.  There were no data
in the literature as to how long people spend for each pedestrian trip.  There-
fore, the exposure period was assumed to be 15 minutes.

     Number of Persons on Expressways

          The total number of people on expressways and their hourly distribu-
tion were determined from traffic count information in the literature.  Since
the NEM has a "transport vehicle," microenvironment, which could be used for
the expressway exposure, the. number of persons and hourly distribution of
people used in the NEM "transport vehicle" microenvironment were also compiled
and compared with the values from traffic counts to determine how well the NEM
values agreed with the expressway literature.

          The total number of persons on expressways can be determined if the
total miles of expressway, the average daily expressway traffic, and the
average trip length are known, as shown below.

          miles of expressway       ,  . ,      persons
          	_	_   x vehicles x  _	  = person trips
     miles of expressway/trip                 vehicles


          From the work done at SwRI under Contract 68-03-2884, it  was deter-
mined that there were 16,910 miles of urban expressway, and that the average
daily traffic was 47,664. (18)  ^ thorough search of the  literature  was con-
ducted to define the expressway trip distance.  Almost no data were found.
Average urban trip distances  (including nonexpressway trips) were found, but
were obviously dominated by short nonexpressway trips, since the mean values
of trips for all purposes were all between 1 and 4 miles.  Three studies were
found that could be used in combination to define expressway trip length.(53,54,55)
Unfortunately, they all dealt with the Los Angeles area.

           From Reference  55,  using  results  from the  1967  "LART"  study,  the
average  time  on  freeways  in  the  L.  A.  area,  for persons  using  the  freeway,
can  be  computed  as  13.3 minutes.   Reference  53  gives  the  average  speed at
peak hour  L.  A.  freeway traffic  as  31.46  mph.   Using  this average  speed  and
13.3 minutes  as  the  average  time,  gives  an  average  of 7.0 miles  of  expressway
travel  per trip.  Los Angeles, however,  is  infamous  for  its  long  commuting
trips.   In older eastern  cities,  the  average  expressway  trip has  the possi-
bility  of  being  much shorter.  Five miles per  expressway trip  nationwide
appears  to be a  reasonable  estimate.

           The average daily  traffic  (ADT) of  47,664  given in Reference 18
is  for  a seven day  week.   Using  the weekly  expressway distribution from
Reference  49, as shown  in Figure 16,  the  weekday ADT  is  50,714,  the Saturday
ADT  is  45,043, and  the  Sunday ADT is  35,033.

                                     45

-------
M
                                                                           Max  of  available data





                                                                           Average




                                                                           Min  of  available data
                                                                       M
   Figure 14.  Hourly pedestrian distribution in the CBD for weekdays

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Figure 15.  Hourly pedestrian distribution in the CBD for Saturdays

-------
00
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          18  -
          16  -
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                             Mon
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                                                                                  Fri
Sat
                               Figure 16.  Expressway traffic by day of  the week

-------
          Computing the total person exposures, using 16,910 miles of urban
expressway, average weekday daily traffic of 50,714, average trip length of
five miles and 1.4 persons per car, gives 240,120,647 person exposures per
weekday.  However, as shown above, trip times are on the order of one quarter
hour.  Using the 240,120,647 weekday person exposures calculated above, at
one quarter hour per exposure gives 60,030,162 person hours of weekday express-
way exposures.  Similar calculations can be made for Saturday and Sunday using
the ADT given above, five miles per expressway trip, and 2.3 persons per vehicle.
The total person trips and person hours of expressway exposure for the three
day types are:

                                      Person trips        Person hours

                    Weekdays           240,120,647          60,030,162

                    Saturday           350,371,480          87,592,870

                    Sunday             272,507,692          68,126,923

          While the NEM has a "transport vehicle" microenvironment as part
of the model, the total number of persons exposed to this situation was not
readily available from the NEM CO report.  It was necessary to tally the
people and hours  from the activity files of the age-occupation  (A-O) groups.
The numbers of persons assigned to the NEM "transport vehicle" category for
weekdays, Saturday and Sunday were calculated using the A-O assignments in
the April 1982 draft of the NEM CO study.  The NEM study was  actually run
for  four cities,  then scaled up to a nationwide estimate.  The "transport
vehicle" population from the four cities must then also be scaled.  Table 15
shows the NEM "transport vehicle" hourly distribution and four city totals,
as well as a  scaled nationwide estimate.  The scaling factor  for the nation-
wide estimate is  the total national urban population given in Chapter  8 of
the April  1982 draft NEM CO report, divided by the total non-farm population
of the  four urban areas studied  (132,023,885 7 15,190,177 = 9.30).  The NEM
CO study uses a one-hour exposure  time  for all environments.  Thus, using the
NEM  study, a  nationwide expressway exposure estimate of  100,075,843 person
hours per weekday was calculated.  The  NEM person hours  in the  "transport
 vehicle"  microenvironment and the person hours derived from traffic counts
 are compared in Table  16.

           As can be seem from Table 16, the  NEM person hours are approximately
 65 to 70  percent higher than the person hours calculated in this study.
 This is not to imply that the NEM "transport vehicle" microenvironment
 figures are incorrect.   The NEM "transport vehicle" category represents
 all vehicular travel,  of which automotive expressway travel is obviously
 just a subset.   It is  reasonable, therefore, that the NEM "transport
 vehicle" category should contain more person hours of exposure.
                                      49

-------
         TABLE 15.  DISTRIBUTION OF PEOPLE ASSIGNED TO THE
          "TRANSPORT VEHICLE" MODE IN THE NEM CO REPORT3

                 Number of People in all Four Cities

     Hour of day       Weekday        Saturday        Sunday

     Mid - 1 am
1
2
3
4
5
6
7
8
9
10
11
noon
1
2
3
4
5
6
7
8
9
10
11
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- noon
- 1 pm
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- mid.
—
30,041
—
—
—
487,539
1,538,501
1,081,739
727,154
884,372
217,109
198,317
497,537
1,436,532
773,521
1,473,064
1,288,102
122,815
—
—
—
—
—
—
—
—
—
—
—
—
—
2,109,330
2,032,865
308,943
614,568
2,332,526
2,383,733
358,224
1,014,843
619,711
13,411
2,221,929
1,227,262
156,333
159,299
—
— —
—
—
—
—
—
—
1,165,518
3,451,698
2,387,678
1,705,864
351,393
579,666
281,118
250,811
807,800
—
237,141
1,120,290
174,942
—
—
—
   4 City Total     10,756,341      15,552,977     12,510,919

National Estimateb 100,075,843     144,703,230    116,400,249
Calculated  from data contained  in the April  1982 draft of  "The NAAQS
Exposure Model  (NEM) Applied to Carbon Monoxide"
Four city total multiplied by 9.30
 TABLE 16.  TOTAL PERSON HOURS OF EXPOSURE ON-EXPRESSWAY SITUATION
                           Person Hours of Exposure
                         Third Studya    NEM CO Study,
           Weekday        60,030,162      100,075,843
           Saturday       87,592,870      144,642,686
           Sunday         68,126,923      116,351,547
           .on-expressway exposure only
            "transport vehicle" microenvironment

                               50

-------
          The hourly distribution of people in the on-expressway microenviron-
ment was also investigated.  The hourly weekday expressway traffic distribution
was obtained from Reference 41 as a percent of daily traffic.  This distribu-
tion is shown in Figure 17.  There are few weekend expressway traffic
distributions in the literature.  A Sunday expressway distribution for an urban
Chicago expressway was found in the "Highway Capacity Manual," Reference 46.
This distribution is shown in Figure 18.  No information was found on Saturday
expressway traffic distribution.

          An examination of the microenvironment assignments in the NEM
activity pattern subgroups shows that an effort was made to distribute people
in the "transport vehicle" microenvironment throughout the day and on weekends.
These assignments were, in general, made on an intuitive basis.^3)  The NEM
weekday hourly distribution presented in Table 15, was also calculated as a
percent of daily traffic.  This distribution is also shown in Figure 17.  While
the two distributions are somewhat similar, in that they peak at the same hours,
the peaks are much higher in the NEM distribution.  In addition, the NEM dis-
tribution has an anomalous peak at 2 to 3 p.m.  Similar calculations were done
for the Saturday and Sunday NEM person hour distributions.

          The Sunday distribution is plotted on Figure 18, together with the
distribution from this study.  The Saturday distribution is  shown on Figure
19.  The Sunday distributions do not compare well at all.  The NEM distribution
has  extremely high  percentages  between  9  and  11  a.m.,  which  are not confirmed
by traffic  count  data.   The  Saturday NEM  distribution  also has  some very  high
percentages for the same hours.  It is apparent from the weekday and Sunday distri-
butions  found in  the  literature,  that hourly  traffic does  not really reach
these  levels.

          From  this analysis,  it is  clear that for  mobile  source exposure,  the
NEM model needs  to  be rerun,  changing the number and distribution of cohorts
 in the transportation vehicle microenvironment to more accurately reflect the
person hour exposure  in the  on-expressway situation.   However,  the effort
 allotted to this  project was not sufficient to permit  the  reprogramming of the
 NEM A-O activity file to change the  number and distribution of people in the
 "transport  vehicle" microenvironment.  Nevertheless,  the "transport vehicle"
 microenvironment was used for the on-expressway exposure because it contained
 reasonable  CO concentrations.  It should be kept in mind that a more accurate
 person hour exposure distribution is possible from the NEM with changes in the
 cohort assignments  to the "transport vehicle" microenvironment.

      Persons in Urban Roadway Tunnels

                                                                           (59)
           From previous studies at SwRI,  the total number of urban tunnelsv  '
 is known,  as well as the average daily traffic for all days of the week
 (52,000).(18)   If the weekly traffic distribution is known, then the weekday
 and Saturday and Sunday average tunnel ADT can be calculated.  Since tunnels
 occur on all types of roadways, expressways, arterials, etc., it was decided
 to average the weekly traffic distribution for several different road types to
 obtain a weekly distribution for urban tunnels.  These distributions and the
 average are shown in Table 17.  It was not possible to weight them by popula-
 tion, traffic,  road type, etc., since these values were not available in the
 references.
                                     51

-------
                                            NEM  "Transport Vehicle"




                                            Expressways
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Figure 17.   Hourly expressway traffic for weekdays

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Figure 19. Hourly Distribution of people in the NEM "transport vehicle" environment
                                in four cities for Saturdays

-------
                TABLE 17.  TRAFFIC DISTRIBUTION BY DAY OF THE
                              WEEK FOR SEVERAL SITUATIONS
                   Daily Traffic as a Percent of Weekly  Traffic
a
Urban
Sunday
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
Reference
b Reference
c Reference
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14.
13.
13.
14.
15.
16.
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46
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Urbanb
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15.
14.


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2
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San Antonio
Expressway
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15.
15.
15.
16.
13.


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Unweighted
Average
10.
15.
14.
14.
14.
15.
15.


1
1
7
6
6
6
6


          From the seven day average ADT of 52,000 and the information in
Table 17, the total traffic for all 59 urban commuter tunnels can be calcu-
lated.  Using 1.4 persons per car on weekdays and 2.3 persons per car on
weekends, the person exposures for each day type can also be calculated.
The results of these calculations are shown below.

          Day Type    Total Vehicles/Day    Person Exposure/Day
          Weekday
          Saturday
          Sunday
3,199,924
3,350,256
2,169,076
4,479,894
7,705,589
4,988,875
          The hourly traffic distribution for two tunnels for weekdays and
weekends was found in the literature. (39,56)  one tunnel was identified as
the Surnner tunnel in Boston, the other tunnel simply as an "urban tunnel."
The hourly traffic distributions for these two tunnels are shown in Figure 20
for weekdays, and Figure 21 for weekends.  For each day type, the distribu-
tions from the two tunnels look very similar.  The data were taken from
different studies conducted during different years, but there is possibility
that the tunnel identified in Reference 56 as an "urban tunnel," is, in fact,
the Sumner tunnel.  It is used nevertheless, since there is so little infor-
mation in the literature.  No data were found on the individual period of
exposure.  Considering that a large number of the exposures occur during
peak traffic periods when traffic is moving at its slowest rate, a five minute
period of exposure was chosen for tunnels.
                                     55

-------
                                                           Sumner Tunnel, ref.  39
                                                      	 Urban Tunnel, ref.  56
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                        Figure 20.  Hourly tunnel traffic for weekdays

-------
                                	  Sumner Tunnel, ref. 39




                                	  "Urban Tunnel, ref. 56
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Figure 21.  Hourly tunnel traffic for weekends

-------
               V.  EXPOSURE IN MOBILE SOURCE MICROENVIRONMENTS
     There are several microenvironments that contribute to mobile source
pollutant exposure.  Of these environments, four are considered the most
significant in terms of total person hours of exposure.  These four are:
parking garages, street canyons, on-expressways, and roadway tunnels.   The
NEM can be used for only one of these four microenvironments:   The on-
expressway microenvironment.  The person hours of exposure from the other
three microenvironments must be determined independently of the NEM using
a model specifically developed for that purpose.

     Microenvironment Exposure Model

          To calculate only person hours of exposure in a specific micro-
environment, no information about the movement of people from place to place
is required.  All that is required is the population and concentration dis-
tributions, nationwide, for each microenvironment.  This approach to calcu-
lating person hours of exposure is referred to as "place specific" as con-
trasted to the NEM which is considered  "people specific" since it follows
a group of people through the day.

          For a place specific model, the number of people in the micro-
environment multiplied by the hours per year each pollutant concentration
interval occurs gives the person hours  of exposure in  the microenvironment
to that concentration interval.  Because pollutant concentration  is a
direct function of the number of vehicles, the most accurate estimates  are
obtained by considering hourly populations, with pollutant concentration
ranges appropriate to that population.  Since hourly populations  are
different for weekdays, Saturdays and Sundays, three sets of hourly popu-
lation figures  are required.  The person hours of exposure are summed for
all hours of  the day  and all day  types for the entire year to give the
annual person hours of exposure.  The mathematical expression  for the model
is:
                 3   24
            P  = Z    I  a.  T..F..
            k   j=l   i=l   3  13
 Where:

           P^   = population exposures to concentration interval "k"
           TJ_-:   = population during hour "i" in the microenvironment on
                  day type "j"
           F^-j, = frequency of occurrence of concentrations in interval
                  "k" during hour "i" of day type "j"
           a-;   = number of type " j" days in a year
                                     59

-------
After calculating the person hours within a given pollutant interval, the
intervals are summed to yield the cumulative frequency distribution.  The
number of weekdays per year was taken as  (52x5) + 1 = 261.  From this was
subtracted 13 holidays, for a total of 248 weekdays.  The holidays were
further divided into 10 "Saturday type" holidays and 3 "Sunday type."
Thus, there were 52 + 10 = 62 "Saturdays," and 52 + 3 = 55 "Sundays."

          The pollutant concentration distributions were generally not
available by hour.  For each microenvironment, the model was modified to
account for the way in which the pollutant concentration distribution was
related to the microenvironment population.  While it would be possible to
develop one computer program to handle all the variations, it was con-
sidered to be more cost effective to use a separate computer program for
each microenvironment.  The computer programs are listed in Appendices C,
D and E for parking garages, street canyons and roadway tunnels, respectively.

          For each of these three mobile source microenvironments, hourly
populations and pollutant concentration distributions were developed and
have been presented in previous sections of this report.   The remainder of
this section covers the results of applying the microscale exposure model
to parking garages, street canyons and tunnels.

     Exposure in Parking Garages

          The actual model algorithm used for the parking garage situation
was somewhat different from the general form shown above.  This change was
necessary since the pollutant concentrations for parking garages given in
Section III of this report were not functions of time of day, but rather,
functions of the number of active cars and wind speed.   Also, the hourly
populations,  as shown in Section IV of this report, were expressed as the
fraction of total parking capacity in motion, not actual people.

          The computer program considers each of the day types  (weekday,
Saturday, and Sunday) separately.  For each hour of the day, for each day
type, the program obtains the fraction of active cars in the garage per
hour, then divides by 12 to obtain the fraction of active cars at any
instant.   Using this value, a set of concentration distributions corres-
sponding to that fraction of active cars is chosen for that day type and
hour.  The set of concentration distributions consists of a distribution
for each of three wind speed ranges.  Starting with the fraction of the
total people exposed for each of the selected pollutant concentration
intervals at the lowest wind speed, the total number of person hours in
each interval was obtained by multiplying the total number of active cars
(total spaces times fraction of active cars), the number of people per
car, the  number of days per year of the particulate day type, and the
fraction  of time the wind was in that particular speed range.
                                    60

-------
          The person hours in each concentration interval are summed as each
successive wind speed, hour of the day, and day type is considered.   Expressed
mathematically the program processed the equation:

                3   24   3
          P.=  Z   I   Z  a. (SNC. ,/4) F.   W
           k   .;_-, ;_! __!  D     iJ     km  m
               3=1 1=1 m=l


where:

          P.   = person hours of exposure in concentration interval "k"
          S   = total number of parking garage parking spaces available
                nationwide •
          N   = number of persons per car
          C.. = hourly fraction of  total parking capacity in motion
          F   = frequency of occurrence of concentration interval k.
                A function of concentration "k", fraction of active
                cars at any instant, and wind speed "m".
          a.  = number of type "j"  days per year
          W   = fraction of time wind is within speed range  "m"
           .m    .                                         ^
          i   = hours
          j   = day type
          m   = wind speed interval

People generally  are not exposed to the garage pollutant levels for a  full
hour.  A  fifteen  minute exposure was used in this study.  Thus, for a  given
hour, the computer program divides  the hourly population by  four.  After
the person hours  in each concentration interval were calculated, the inter-
vals were  summed  to give the cumulative frequency distribution.

           Since cars  in motion at  any  instant obtained  from  the garage
population curves are always less  than two percent  of  capacity  (see Section
IV), the  high extremes, such as can be found when a garage is emptying at
the end of an entertainment  event  or workday, would not be considered.
These situations  do occur regularly and should  be included in the study.
There are data which  show that the cars in motion at any instant in these
situations can be as  high as 25 percent of capacity. (!•&)  These situations
normally  last about one-half hour, for either  filling  or emptying.

           For work  related peaks,  it was  estimated  that 25 percent  of  the
garages  experience  this type of use at a  rate  of five  times  per week.   For
entertainment events,  it  was estimated that  25  percent of the  garages  expe-
rience this  type  of usage at a rate of one per week.   To account  for  the
first of the situations,  the 5:00 P.M. calculation  was split into two  parts.
For  75 percent of the population,  the  concentration frequencies were  from
the  distributions for 3 percent active cars.   For 25 percent of  the popu-
 lation,  the  concentration frequencies  were  from the distribution  for  19
percent  active cars (see  Table  3).  The  second situation was accounted for
by modifying the  10:00 P.M.  Saturday  calculation in a  like  manner.

                                    61

-------
          Table 18 contains a  list of the variables that were used in the
parking garage exposure model.  Where it was necessary to estimate a value,
the estimates were made from impressions and inferences gleaned from the
information on parking garages collected under EPA Contract 68-03-2884,
Task Specification 1. d8)

          The nationwide annual person hours of exposure in parking garages
above selected pollutant concentration values calculated from the model
are listed in Table 19 and presented in graphic form in Figure 22.  The
figure indicates that the concentration intervals are sufficiently close
to allow linear interpolation to obtain person hours at concentrations
other than those given in Table 19.

          This information can be used to determine the person hours of
exposure to various levels of any mobile source pollutant.  If the complete
relationship is desired, then the concentrations at a given person hours of
exposure should be multiplied by the parking garage emission factor for the
particular pollutant.  If all that is desired is the person hours of
exposure above some concentration of the pollutant, then the actual
pollutant concentration, in yg/m3 is divided by the emission factor to
obtain a concentration at 1.0 g/min emission factor.  The person hours of
exposure above this level are then obtained by linear interpolation of
Table 19.

          As an example , suppose the person hours of exposure in parking
garages to CO above the one hour NAAQS of 35 ppm are desired.  The 35 ppm
is converted to yg/m3 by multiplying by 1157, then divided by the 1980
parking garage CO emission factor of 5 g/min.  This gives 8099 yg/m3 at
1.0 g/min emission factor.  Interpolating between 8000 and 10,000 yg/m3
in Table 19 gives 26.821x10° annual person hours of exposure above 35 ppm
CO in parking garages.

     Exposure in Street Canyons

          The previous report sections presented the concentration distri-
butions, total persons in vehicles, total pedestrians, and hourly distri-
butions of vehicles and pedestrians in street canyons for weekdays,
Saturdays and Sundays.  The values of these parameters are summarized in
Table 20.  These values were used in the computer model to obtain a nationwide
person hour exposure distribution for street canyons.   The computer program
used was similar to the program used to calculate the parking garage exposure
distribution.  For the street canyon case, the time of an individual exposure
was also taken as 15 minutes.   The concentration distribution used was a
function of time of day and day type.  The computer program processes the
expression:

                 3   24
                                    62

-------
TABLE 18.  VALUES OF VARIABLES USED IN DETERMINATION OF
     PARKING GARAGE PERSON HOUR EXPOSURE ESTIMATE
          Variable
          Value
 1.  Total Spaces


 2.  Persons per car

 3.  Active time per  vehicle

 4.  Exposure time per person

 5.  Percent time in
     wind speed range


 6.  Number of weekdays

 7.  Number of holidays

 8.  Number of Saturdays


 9.  Number of Sundays
 10.   Percent of garages
      experiencing peak
      active cars

 11.   Number of hours of  peak
      activity

 12.   Fraction of active  cars
      per hour (exclusive of
      peak activity)

 13.   Distribution of exposure
      with concentration
5.398 x 10° =
(6200x740) + (5400x150)

1.4 on weekdays,  2.3 on weekends

5 minutes

15 minutes

9.5%, 0 to  3 kts
65.0%, 4  to 10 kts
25.5%, >10 kts

248

13

62
 (52  + 10  holidays)

55
 (52  + 3 holidays)

25%
 310/year
 (248 + 62)

 varies with type of day and
 hour of day.  Minimum = 0,
 maximum = .2134

 lognormal distribution with
 separate distribution for
 ranges of active cars and wind
 speed.  Concentrations vary from
 0 to 50,000 yg/m3
                          63

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TABLE 19. PERSON HOUR EXPOSURE DISTRIBUTION FOR PARKING GARAGES
         Concentration  q
         Exceeded,  Ug/m"

               0
             360
             463
             618
             773
            1030
            1288
            1546
            1804
            2061
            2319
            2577
            3000
            4000
            5000
            6000
            8000
           10000
           15000
           20000
           25000
           30000
           40000
Person Hours
(in millions)

  1520.380
  1182.417
  1016.489
   802.033
   639.181
   461.891
   358.797
   296.807
   254.810
   224.255
   199.532
   178.714
   150.486
   100.445
    68.766
    48.830
    27.293
    17.753
     8.667
     5.375
     3.379
     2.131
     0.683
                              64

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  10000?;
   1000.
(0
8
§
u
id
o
O
a
w

14-1
o
s
en
M
0)

    100
     10

    0.1
                                                         J_
10000               20000            3
       Pollutant Concentration,  yg/m
                                                                    30000

40000
             Figure  22.   Nationwide Cumulative Exposure Distribution in Parking Garages

                                              65

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    TABLE 20.   VALUES  OF VARIABLES  USED  IN DETERMINATION OF  STREET CANYON
                             PERSON HOUR EXPOSURE
              Variable
        Value
Total nationwide persons in vehicles
  in street canyons per day
Total pedestrians in street canyons



Exposure time per person

Number of weekdays

Number of Holidays

Number of Saturdays

Number of Sundays

Fraction of street canyons average
  daily traffic

Fraction of total daily pedestrians
  in street canyons
Distribution of pollutant
  concentrations
37,500,000 on weekdays
59,410,000 on Saturdays
36,380,000 on Sundays

89,076,000 on weekdays
70,012,600 on Saturdays
23,158,000 on Sundays

15 minutes

248

13

62 (52 plus 10 holidays)

55 (52 plus 3 holidays)

Varies by hour of the day and day
type from 0.5 to 8.5 percent ADT

Varies by hour of the day and day
type from 0 to 13 percent of total
daily pedestrians

Determined from street canyon CO
monitors in SAROAD data base.  Con-
centrations vary by hour of the day
and day type from 0 to approximately
2100
                                    66

-------
Where:

          pk   = person hours of exposure in concentration interval "k"
                 per year
          V    = total number of persons in vehicles in street canyons per
                 day for each day type
          P    = total number of pedestrians in streets canyons per day
                 for each day type
          Cv   = hourly fraction of total people in vehicles in street canyons
          C    = hourly fraction of pedestrians in street canyons
               = fraction of time pollutant in concentration interval k.  A
                 function of concentration interval, time of day and day type
          aj   = number of type " j" days per year
          j    = day type:  weekday, Saturday and Sunday
          i    = hour of the day

After calculating the person hours in a given pollutant interval, the intervals
were summed to give the cumulative frequency distribution, as shown in Table 21.
Figure 23 is a plot of this distribution.  The figure indicates that the
concentration intervals are sufficiently close to allow linear interpolation
to obtain person hours at concentrations other than those given in Table  21.


       TABLE 21.  PERSON  HOUR  EXPOSURE DISTRIBUTION FOR STREET CANYONS

                     Concentration
                       Exceeded              Millions  of
                       yg/m3 a	          Person Hours

                            0                 9907.003
                           35                 9324.053
                          105                 7332.058
                          175                 5295.949
                          245                 3691.592
                          315                 2520.097
                          386                 1709.217
                          456                 1124.188
                          526                  713.121
                          596                  451.391
                          666                  275.330
                          736                  165.660
                          806                  103.723
                          876                    63.166
                          947                    38.209
                          1087                    14.141
                          1297                     3.332
                          1508                     0.577
                          1718                     0.164
                   for 1.0 g/min emission factor

                                     67

-------
 10,000
  1,000
O



o
tn
tn


O
    100
s   10
                                       \
                                                 N

                                                         3
                                                           2x
                                                              \
                                                                ^m
                                                                        :._.__ :>_:|.-
                                                                        1^=-Y.T'

                 200    400     600   ~^800    1000    1200     1400    1600    1800   2000


                                         Concentrations
           Figure 23.   Nationwide cumulative person hour exposure distribution

                                   in street canyons

                                         68

-------
          The table can be used to determine the street canyon exposure for
any pollutant in the same manner as for parking garages.  For example, to
obtain the person hours of CO exposure in street canyons above the CO one
hour NAAQS of 35 ppm, first convert the 35 ppm to yg/m3 by multiplying by
1157.  The 40495 yg/m3 obtained is divided by the 1980 street canyon CO
emission factor of 17.9 g/min, to give 2263 yg/m3 at 1.0 g/min emission
factor.  This is above the highest concentration shown in Table 21.  There-
fore all that can be ascertained is that, in street canyons, less than
0.164 million person hours of exposure occur annually at CO levels above
35 ppm.

     Exposure in Roadway Tunnels

          The roadway tunnel person hour exposure distribution can be cal-
culated using the total tunnel traffic and hourly traffic distribution from
Section IV, together with the pollutant concentration distributions from
Section III.  A summary of the exposure model input values is given in
Table  22.  The person hour distribution for roadway tunnels was calculated
          TABLE 22.  VALUES OF VARIABLES USED IN DETERMINATION OF
                     ROADWAY TUNNEL PERSON HOUR EXPOSURE
             Variable
      Total nationwide person
       exposures  in  roadway
       tunnels

      Exposure  time  per person

      Number  of weekdays

      Number  of Saturdays

      Number  of Sundays

      Fraction  of tunnel  average
       daily  traffic
      Distribution of pollutant
       concentrations
Weekdays - 4,479,894
Saturdays - 7,705,589
Sundays - 4,988,875

5 minutes

248

62  (52 plus 10 holidays)

55  (52 plus 3 holidays)

Varies by hour of the day
and day type from 0.5 to
6.9 percent ADT

Lognormal distributions, with
six separate distributions,
one for each of  six different
values of ADT.   Concentrations
vary  from 0 to approximately
8000  yg/m3.
                                     69

-------
 in the  same manner as the street canyon distribution, except that the
 exposure time was taken as 5 minutes and the pollutant concentration was
 a function of ADT rather than time of day.  The computer algorithm for
 roadway tunnels is:

                3    24
          Pu =  £    £  [(V.C . J/12] P
where :

          P]c   = person hours of exposure in concentration interval "k"
                 per year
          V    = total number of persons in vehicles in tunnels per day
                 for each day type
          Cv   = hourly fraction of total people in vehicles in tunnels
               = fraction of time pollutant in concentration interval k.
                 A function of concentration interval, and Cv
          a j   = number of type " j " days per year
          j    = day type :  weekday , Saturday or Sunday
          i    = hour of the day

After calculating the person hours in a given pollutant interval , the inter-
vals were summed to give the cumulative frequency distribution.  The cumu-
lative frequency distribution for person hours of exposure in roadway
tunnels is given in Table 23.  A plot of the distribution is shown in
Figure 24.  The figure indicates that the concentration intervals are
sufficiently close to allow linear interpolation to obtain person hours
at concentrations other than those given in Table 23.

          The table can be used to determine the tunnel exposure for any
pollutant in the same manner as for parking garages and street canyons.
For example, to obtain the person hours of CO exposure in tunnels above the
one hour CO NAAQS of 35 ppm, convert 35 ppm to yg/m3 by multiplying by
1157 to give 40495 yg/m^.  The 1980 tunnel CO emission factor is 26.92
g/mile(21) at 35 mph or 15.7 g/min. (21)  The 40495 yg/m3 concentration is
divided by 15.7 to give 2579 yg/m3 at one gram/min emission factor.  Inter-
polating between 2400 and 2600 yg/m3 in Table 23, gives 22.583xl06 person
hours of exposure in tunnels above 35 ppm CO.
                                    70

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TABLE 23.  PERSON HOUR EXPOSURE DISTRIBUTION IN ROADWAY TUNNELS
              Concentration
                Exceeded             Millions of
                yg/m3(a)             Person Hours

                    0                  148.859
                   200                 144.970
                   400                 138.681
                   600                 128.618
                   700                 122.167
                   800                 115.082
                   900                 107.536
                  1000                  99.815
                  1200                  84.812
                  1400                  70.884
                  1600                  58.722
                  1800                  48.353
                  2000                  39.686
                  2200                  32.598
                  2400                  26.794
                  2600                  22.089
                  3000                  15.171
                  4000                   6.418
                  6000                   0.847
       for  1.0 g/min emission  factor
                              71

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140
120
              1000
2000
                                                              5000
                              3000        4000
                            Concentration, ^g/m3
Figure 24.  Nationwide cumulative person hour exposure distribution
                         in roadway tunnels
                                72
6000

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                  VI.  MOBILE SOURCE NEM EXPOSURE ESTIMATE
     The methodology for this project was to use the NEM computer model to
provide the bulk of the exposure estimate,  then add to that estimate
exposure from several mobile source microenvironments not included in the
NEM.

     As explained in Section II, it was found that the input used in the NEM
CO study was not structured to provide a satisfactory estimate of mobile
source pollutant exposure.  It could be used, however, if rerun with modified
inputs.  As the project progressed, it was also determined that a better
estimate of mobile source exposure could be obtained if, for the NEM "transport
vehicle" microenvironments, the number of people and their hourly distribution
could be modified.  Thus, the NEM computer program was rerun to provide a
more useful estimation of mobile source pollutant exposure.

     New NEM Input

           Several of the input parameters used  in the NEM  CO study required
changes in the input values.  The modifications required are listed  in
Table 24.  After investigating the NEM input files and the structure of the
NEM program, it was found that changes to the activity patterns would require
more effort than was available for this project.  Therefore, the new NEM  run
did not include changes to  the activity patterns(Item 3 in Table 24).

           The NEM computer  program is stored on the UNIVAC computer  at the
EPA's National Computer Center  (NCC)  in Research Triangle  Park,  N.C.   The
EPA Office of Air Quality Planning and Standards  (OAQPS) has used the  NEM
program extensively  for a variety of pollutants over  the past  several  years.
It was learned from  personnel in the OAQPS  that most  of the files required
to modify  the air quality data  and microenvironment factors, while not used
in  the published  NEM CO  study,  did exist.   A search of the input files
stored on  the computer at the NCC  located  the  necessary files.

      New Exposure Distribution  for the Four Cities

           Using  the  modified input files,  the  NEM model was rerun for  CO for
the four cities  used in  the NEM CO report.   For record purposes, the UNIVAC
computer runstreams  for  these computer runs are included in Appendix F.   The
cumulative exposure  distributions  are shown in Tables 25 to 28 for Chicago,
Los Angeles,  Philadelphia and St.  Louis,  respectively.

           It  is  emphasized that the  published CO study was done for the
purposes of regulatory analysis.  The exposure distributions listed in the
 draft versions of that report represent exposures that would occur if certain
 CO standards were met.  The exposure distributions shown  in Tables 25 to 28

                                     73

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                 TABLE 24. NEM INPUT MODIFICATIONS REQUIRED
             Input Area

    Air Quality Data  (CO monitors)
    Microenvironment Factors
       Modification required
EPA study used a variety of rollback
factors.  Rollback factors must be set
equal to 1.0 so that CO data is used
"as is."

The EPA study used multiplicative factors
for all, and additive factors for some,
microenvironments.  All additive factors
must be set to zero.
3.  Activity Patterns
4.   Concentration Levels
EPA CO study has nationwide estimates
for only a portion of the U.S. population.
This study requires using all people
(all ages and both sexes).  The hour by
hour assignment of people to environments
will require extensive modification.
These modifications are necessary to
correctly calculate the expressway
microenvironment and account for people
in microenvironments not considered by
the NEM.

This input defines the CO intervals in
the distribution.  It must be modified
to give more intervals in the lower ppm
range.
                                   74

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                 TABLE 25.  PERSON HOURS OF EXPOSURE TO MOBILE SOURCE CO FOR CHICAGO
                            Total Population, One Hour Averaging Time
Concentrat Ion
Exceeded
(ppm)
60.0
50.0
40.0
35.0
30.0
25.0
20.0
15.0
12.0
9.0
7.0
6.0
5.0
4.0
3.0
2.0
1.5
1.0
0.5
0.0
Max. Concentration
Encounters at Max.
Low Exercise

2,250
164,000
359,000
1,470,000
3,090,000
10,200,000
32,900,000
72,200,000
181,000,000
385,000,000
566,000,000
915,000,000
1,410,000,000
2,460,000,000
5,470,000,000
8,850,000,000
13,100,000,000
17,500,000,000
18,900,000,000
51.1
2,260
Medium Exercise




4,610
25,300
125,000
444,000
1,600,000
5,560,000
16,000,000
29,700,000
60,800,000
118,000,000
260,000,000
586,000,000
867,000,000
1,180,000,000
1,470,000,000
1,560,000,000
32.2
4,620
High Exercise








57,900
344,000
1,360,000
2,570,000
5,930,000
12,900,000
33, 100,000
83,700,000
130,000,000
176,000,000
222,000,000
234,000,000
14.6
15,000
Any Exercise

2,250
164,000
359,000
1,480,000
3,110,000
10,300,000
33,400,000
73,800,000
187,000,000
403,000,000
598,000,000
982,000,000
1,540,000,000
2,760,000,000
6,140,000,000
9,850,000,000
14,500,000,000
19,200,000,000
20,700,000,000
51.1
2,260
tn

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      TABLE 26.   PERSON HOURS OF EXPOSURE TO MOBILE SOURCE CO FOR LOS ANGELES
                     Total Population, One Hour Averaging Time
Concentration
Exceeded
(ppm)
60.0
50.0
40.0
35.0
30.0
25.0
20.0
15.0
12.0
9.0
7.0
6.0
5.0
4.0
3.0
2.0
1.5
1.0
0.5
0.0
Max. Concentration
Encounters at Max.
Low Exercise

297,000
881,000
4,900,000
10,300,000
33,500,000
79,100,000
187,000,000
509,000,000
1,240,000,000
2,940,000,000
4,860,000,000
7,780,000,000
12,200,000,000
19,700,000,000
39,400,000,000
51,200,000,000
54,300,000,000
60, 100,000,000
61,500,000,000
58.8
66,400
Medium Exercise





188,000
1,530,000
9,010,000
29,100,000
104,000,000
243,000,000
357,000,000
629,000,000
1,000,000,000
1,750,000,000
3,290,000,000
4,310,000,000
4,550,000,000
5,020,000,000
5,100,000,000
28.8
107,000
High Exercise






145,000
568,000
2,540,000
13,100,000
32,500,000
57,300,000
109,000,000
180,000,000
330,000,000
597,000,000
866,000,000
875,000,000
1,010,000,000
1,030,000,000
22.8
43,400
Any Exercise

297,000
881,000
4,900,000
10,300,000
33,700,000
80,800,000
197,000,000
540,000,000
1,350,000,000
3,210,000,000
5,270,000,000
8,520,000,000
13,400,000,000
21,800,000,000
43,300,000,000
56,400,000,000
59,700,000,000
66,200,000,000
67,600,000,000
58.8
66,400
•f-
+-

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TABLE 27.  PERSON HOURS OF EXPOSURE TO MOBILE SOURCE CO FOR PHILADELPHIA
               Total Population, One Hour Averaging Time
Concentration
Exceeded
(ppm)
60.0
50.0
40.0
35.0
30.0
25.0
20.0
15.0
12.0
9.0
7.0
6.0
5.0
4.0
3.0
2.0
1.5
1.0
0.5
0.0
Max. Concentration
Encounters at Max.
Low Exercise
35,600
43,300
88,800
283,000
438,000
2,310,000
5, 180,000
10, 100,000
30,000,000
73,900,000
169,000,000
317,000,000
480,000,000
980,000,000
1,660,000,000
4,890,000,000
7,380,000,000
9,470,000,000
16,400,000,000
23,300,000,000
"M.4
35,600
Medium Exercise


10,500
10,500
10,500
64 , 700
70,200
28 1 , 000
1,110,000
5,040,000
11,400,000
17,400,000
34,800,000
75,000,000
160,000,000
445,000,000
715,000,000
917,000,000
1,480,000,000
1,990,000,000
42.0
10,500
High Exercise
*








215,000
854,000
1,750,000
2,180,000
4,570,000
10,200,000
23,100,000
67,700,000
134,000,000
144,000,000
285,000,000
380,000,000
14.3
58,600
Any Exercise
35,600
43,300
99,300
294,000
449,000
2,380,000
5,250,000
10,400,000
31,300,000
79,800,000
182,000,000
336,000,000
520,000,000
1,060,000,000
1,850,000,000
5,410,000,000
8,230,000,000
10,500,000,000
18,200,000,000
25,700,000,000
71.4
35,600

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               TABLE  28.   PERSON  HOURS OF EXPOSURE  TO MOBILE  SOURCE CO FOR ST.  LOUIS




                              Total  Population,  One Hour Averaging  Time
-j
oo
Concentration
Exceeded
(ppw)
60.0
50.0
40.0
35.0
30.0
25.0
20.0
15.0
12.0
9.0
7.0
6.0
5.0
4.0
3.0
2.0
1.5
1.0
0.5
0.0
Max. Concentration
Encounters at Max.
Low Exercise

79,200
135,000
181,000
326,000
631,000
3,280,000
8,340,000
19,400,000
61,000,000
131,000,000
221,000,000
389,000,000
715,000,000
1,570,000,000
3,750,000,000
5,380,000,000
7,390,000,000
9,000,000,000
9,700,000,000
55.9
29,500
Medium Exercise




6,520
6,520
121,000
405,000
987,000
3,550,000
7,970,000
13,700,000
26,200,000
58,300,000
144,000,000
334,000,000
481,000,000
646,000,000
771,000,000
826,000,000
31.4
6.520
High Exercise







17,800
120,000
591.000
1,110,000
1,840,000
3,150,000
7,880,000
25,700,000
61,500,000
90,700,000
123,000,000
145,000,000
158,000,000
19.8
3,260
Any Exercise

79,200
135,000
181,000
332,000
638,000
3,400,000
8,760,000
20,500,000
65,200,000
141,000,000
236,000,000
418,000,000
782,000,000
1,740,000,000
4, 140,000,000
5,950,000,000
8, 160,000,000
9,910,000,000
10,700,000,000
55.9
29, 500

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are estimates of exposures that did occur in the calendar year of the air
quality data used.  Thus, it is not possible to directly compare the exposures
shown in Tables 25 to 28 with those in the draft versions of the NEM CO report.

     Nationwide Exposure Estimate

          The nationwide CO exposure distribution was calculated from the
distribution for the four cities following the procedure used in the April
and December 1982 draft NEM CO reports. (33,57)  Before estimating the nation-
wide exposure, it was necessary to obtain the distribution for each city for
1980.  The calendar year for the air quality data used for each city varied
by city.  The years were:  1979 for Chicago, 1977 for Los Angeles and 1978
for Philadelphia and St. Louis.

          To adjust the distribution from each city, the CO levels were
multiplied by the ratio of the 1980 FTP CO emission factor to the city
base year FTP CO emission factor.


      n n         .^,                    1980 FTP CO g/mile
     1980 ppm = city base year ppm  	—	
                                    city base year FTP CO g/mile

 These  calculations produced different CO intervals for each  city.   Linear
 interpolation between the new CO values was used  to produce  person  hour
 distributions with the original CO  intervals for  each city.   These  person
 hour distributions for all four cities are shown  in Table 29.

           To extrapolate the four cities to a nationwide exposure estimate,
 the NEM CO study  divided the 105 urban areas in the country  with  a  population
 of 200,000 or more  (1970 census) into four categories.   Each category
 corresponded to one  of the four cities investigated in the NEM CO study.
 The relative CO distribution obtained for the study city was assumed to
 represent all urban  areas in that category.  The  urban areas were assigned
 to one of the four cities based on  such  considerations as proximity to
 the base area,  average wind speed,  observed peak  CO concentration,  climate,
 and general character of the area.^57'   The nationwide CO  exposure  estimate
 for 1980 was calculated using  the following relationships.

            , ,_ Total Population 1980      Total  Urban Population in 1970
            (C)~ Total Population 1970  X  Total Population >200,000 in 1970   *
                  E   e. (c)  f .
                      i      i

 where:

           E(c)     total nationwide CO exposure distribution
           ei(c)  = CO exposure distribution for city "i"
                   Total population in city "i" type areas
           fi    ~         Population of city "i"

                                     79

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        TABLE 29.  1980 PERSON HOURS OF EXPOSURE TO CO IN FOUR CITIES
Concentration
  Exceeded
                            Person Hours (Millions)
60.0
50.0
40.0
35.0
30.0
25.0
20.0
15.0
12.0
  .0
   0
   0
   0
  .0
  .0
 2.0
 1.5
 1.0
 0.5
 0
     9.
     7.
     6.
     5.
     4
     3.
Chicago
0.000
0.000
0.118
0.262
1.000
2.530
8.270
28.500
62.400
163.000
350.000
515.000
846.000
1,368.000
2,501.000
5,662.000
9.064.000
13,843.000
18,868.000
20,700.000
Los Angeles
0.000
0.000
0.389
0.742
3.840
10.000
41.100
124.000
251.000
837.000
1,830.000
2,960.000
5,720.000
9.284,000
16,500.000
34,200.000
48,100.000
53,300.000
64,800.000
67,600.000
Philadelphia
0.036
0.038
0.068
0.103
0.319
1.030
3.640
8.240
19.600
59.300
132.000
207.000
391.000
759.000
1,520.000
4,400.000
7,050.000
9,870.000
17,100.000
25,700.000
St. Louis
0.000
0.000
0.104
0.136
0.205
0.424
1.850
6.510
13.900
46.300
104.000
156.000
290.000
579.000
1,340.000
3,460.000
5,190.000
7,550.000
9,670.000
10,700.000
          The value used for each of the variables is shown in Table 30.
When all the various factors are multiplied together, for each of the
values of CO in Table 29, the equation becomes:

          National Person Hours =21.051 (Chicago person hours)!

                                  +4.368 (Los Angeles person hours)
                                   r                                 1
                                  +J9.963 (Philadelphia person hours)
                                   »-                                 J
                                  +;18.211 (St. Louis person hours)

          The nationwide Urban CO exposure distribution resulting from these
calculations is presented in Table 31.  Again, since the NEM CO study was
conducted to study the effects of various levels of ambient CO standards,
there is no table in the published NEM CO study comparable to Table  31.
                                    80

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    TABLE 30.  VALUES OF VARIABLES USED TO EXTRAPOLATE NEM
        EXPOSURE IN FOUR CITIES TO NATIONWIDE EXPOSURE

       	  Variable                             Value
    From  References  33  and  57
Total urban population >200,000 (1970)             103,137,849

Total urban population in 1970                     118,447,000

Total population 1970                              203,212,000

Total population 1980                              226,505,000

Total population of Chicago (1970)                   2,364,970

Total population of Chicago-like urban
  areas >200,000 (1970)                              38,894,365

Total population of Los Angeles (1970)               7,719,108

Total population of Los Angeles-like
  urban areas >200,000  (1970)                         26,339,249

Total population of Philadelphia  (1970)              2,935,244

Total population of Philadelphia-like
  urban areas >200,000  (1970)                        20,553,523

Total population of St. Louis  (1970)                 1,219,561

Total population of St. Louis-like
  urban areas >200,000  (1970)                        17,350,712
                                81

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         TABLE 31.  1980 NATIONWIDE URBAN MOBILE SOURCE CO EXPOSURE FROM NEM
                   One Hour Average
                    Concentration
                      Exceeded
                      (CO PPM)	      Person Hours (Millions)

                        60.0                         0.323
                        50.0                         0.341
                        40.0                         6.687
                        35.0                        12.160
                        30.0                        44.420
                        25.0                       113.900
                        20.0                       419.900
                        15.0                     1,334.000
                        12.0                     2,839.000
                         9.0                     8,462.000
                         7.0                    18,440.000
                         6.0                    28,470.000
                         5.0                    51,580.000
                         4.0                    86,700.000
                         3.0                   162,700.000
                         2.0                   371,000.000
                         1.5                   558,600.000
                         1.0                   772,000.000
                         0.5                 1,010,000.000
                         0.0                 1,156,000.000
     NEM Exposure Estimate for Mobile Sources

          For the evaluation of unregulated pollutants, the person hour
exposure distribution is needed in terms of JJg/m3 at a 1.0 g/min emission
factor rather than in ppm CO.  To convert Table 31 to the required distri-
bution, the CO values are converted to yg/m^ by multiplying by 1157, then
adjusted to one gram/min by dividing by the 1980 FTP CO emission factor
of 17.9 g/min (54.65 g/mile at 19.6 mph).(18)  The nationwide person hour
exposure distribution in yg/m3 for a 1.0 g/min emission factor is presented
in Table 32.

          To properly combine the NEM results with the results from the
parking garage, street canyons, and roadway tunnel, the total person hours
represented by these three microenvironments must be subtracted from the
NEM distribution.

          Table 33 lists the person hours of exposure for each of the three
microenvironments together with the total annual person hours of exposure
for all three situations.  Ideally,  these person hours would be subtracted,  in

                                    82

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               TABLE 32.   1980 NEM NATIONWIDE URBAN  EXPOSURE
                        FOR MOBILE SOURCE POLLUTANTS
     Mobile Source
       Pollutant     .
Concentrations/ yg/m3
            0
           32
           65
           97
          129
          194
          259
          323
          387
          452
          582
          776
          970
         1293
         1616
         1939
         2262
         2585
         3232
         3878
Person Hours
  from NEM
 (Millions)

1,156,000.000
1,010,000.000
  772,000.000
  558,600.000
  371,000.000
  162,700.000
   86,700.000
   51,580.000
   28,470.000
   18,440.000
    8,462.000
    2,839.000
    1,334.000
      419.900
      113.900
       44.420
       12.160
        6.681
        0.341
        0.323
      NEM Person  Hours
   Minus  Microenvironment
  Person  Hours  (Millions)

       1,144,424.000
          999,886.000
          764,269.000
          553,006.000
          367,285.000
          161,071.000
          85,832.000
          51,063.000
          28,184.000
          18,255.000
            8,377.300
            2,810.600
            1,320.600
              415.700
              112.760
              43.975
              12.038
                6.614
                0.338
                0.320
 For a 1.0 g/min emission factor
        TABLE  33.  TOTAL PERSON HOURS OF EXPOSURE IN PARKING GARAGE,
                 STREET CANYON AND TUNNEL MICROENVIRONMENTS
                 Microenvironment

                  Parking Garage

                  Street Canyons

                  Tunnels

                  Total
Yearly person hours
    of exposure
	(millions)	

    1,520.380

    9,970.003

      148.859
   11,576.240
                                     83

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the form of numbers of people, from the NEM A-O groups in the central city that
would logically be in these microenvironments.  The A-O groups would include:
students over 18, professional and administrative, sales workers, and clerical
workers.  One method would be to have,the NEM exposure concentrations set at zero
for the number of persons involved in the three microenvironments.  The total
person hours could then be subtracted from 0 ppm in the NEM person hour
distribution in Table 32.  To do this the NEM "kitchen" microenvironment
multiplicative factor would be set equal to zero, then, each hour, the
number of people equal to those exposed  to the three microenvironments
would be assigned to the kitchen microenvironment.  Since the ambient
pollutant level would then be multiplied by zero, these people would be
put in the interval containing zero ppm for that hour.  Any persons pre-
sently assigned to the kitchen microenvironments would be reassigned to
the "indoor-home" microenvironment, which has the same multiplicative
factor as the kitchen has currently.
                                            ,  *

          Unfortunately, the time and effort allotted to this study did not
permit this adjustment to the A-O group population and activity patterns.
A less exact, but more expeditious method of subtracting the required person
hours from the NEM is to proportionally remove them from each of the NEM
concentration intervals.  If 20 percent of the total NEM person hours are
in the interval between 65 and 97 Mg/m3, then 20 percent of the person hours
to be subtracted would be taken from this interval.  Using the total person
hours in the three microenvironments as 11,576,240, the NEM exposure distri-
bution was adjusted to give the exposure without the microenvironments.
This adjusted exposure is also shown in Table 32.
                                    84

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            VII.  NATIONWIDE EXPOSURE TO MOBILE SOURCE POLLUTANTS
     To obtain the total urban person hour exposure to mobile source pol-
lutants, the microscale exposure distribution from Section V (Tables 19,
21 and 23) must be combined with NEM exposure distribution from Section
VI  (Table 32).  It should again be emphasized that the exposure estimates
for mobile sources in this report are based on CO.  The use of these CO
based exposures as surrogates for other mobile source pollutants must be
approached with reasoned caution.  While CO is probably the best surrogate
to use on a national basis for a mobile source surrogate, especially for
the NEM model, other mobile source pollutants may not have the same ends-:
sion rates under the same vehicle operating conditions or chemical reactivity
as CO  (e.g., the spatial and temporal distributions may be different).
Adjustments or corrections to these exposure estimates may be appropriate
if the mobile source pollutant under study has characteristics which differ
markedly from CO.. However, in most intended uses of this methodology, a
rough assessment of exposures to a mobile source pollutant which has not
been adequately monitored in the ambient air is desired, and these estimates
may be entirely adequate.  Both the microscale exposures and the NEM exposure
are for urban situations.  The total nationwide exposure should contain
rural exposure as well.  Therefore, an estimate of rural mobile source
exposure is required before a total nationwide exposure estimate can be made.

     Rural Exposure

          The urban exposure represented by the NEM and microscale models
accounts for the exposure of approximately 132 million of the  226.5 million
people  in the country  (1980 census).(33)  The remaining 94.5 million people
live in rural areas.   In general, persons living  in rural areas do not
experience high concentrations of mobile  source pollutants.  To estimate
the magnitude of  rural exposure, CO was again used as the indication of
mobile  source emissions.   Background  levels of CO range from 0.03 to  0.22
ppm.(20)  However, air masses that  have recently  traversed  urban areas
show levels as high  as 1.0 ppm  in rural areas.^^'

          A detailed examination of rural exposure to mobile source pollutants
was not part  of the  scope  of  this study.  However, from the data presented
above,  it is  estimated that all rural exposure to CO is below  2 ppm.   Using
the 1980  mobile source FTP emission factor  for CO of 17.9  g/min,  this 2 ppm
CO converts to a  mobile source  exposure upper limit  of  129  yg/m3  at 1.0 g/min
emission  factor.   For purposes  of this study,  it was assumed that 50  percent
of the person hour exposure was between 0 and 32 yg/m3, 30 percent  between
 32 and 65 yg/m3,  15  percent between 65 and  97 yg/m3,  and  5 percent  between
 97 and 129  yg/m3.  For the 94.5 million people in rural areas, the  person
 hour  exposure distribution is then  as shown in Table 34.
                                     85

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           TABLE 34,   1980 RURAL EXPOSURE TO MOBILE SOURCE POLLUTANTS
                   FOR ONE GRAM PER MINUTE EMISSION FACTOR

                   Concentration
                      Exceeded             Person Hours
                        yg/m                (Millions)

                           0                 827,820.000
                          32                 413,910.000
                          65                 165,564.000
                          97                  41,391.000
                        129                      0.000
     Total National Exposure

          Since the rural exposure estimate and the NEM urban exposure
estimate should always use the same mobile source emission factor, the two
distributions can be combined as shown in Table 35.  This table gives the
         TABLE 35.   1980  TOTAL NATIONWIDE (URBAN AND RURAL)  EXPOSURE TO
         MOBILE SOURCE POLLUTANTS  EXCLUSIVE OF THREE MICROENVIRONMENTS
                   FOR ONE GRAM PER MINUTE EMISSION FACTOR

                   Concentration
                     Exceeded                   Person Hours
                     yg/n\3(a)                     (Millions)

                           0                    1,972,244.000
                          32                    1,413,796.000
                          65                      929,833.000
                          97                      594,397.000
                         129                      367,285.000
                         194                      161,071.000
                         259                       85,832.000
                         323                       51,063.000
                         387                       28,184.000
                         452                       18,255.000
                         582                        8,377.300
                         776                        2,810.600
                         970                        1,320.600
                       1293                          415.700
                       1616                          112.760
                       1939                           43.975
                       2262                           12.038
                       2585                            6.614
                       3232                            0.338
                       3878                            0.320

                                    86

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nationwide (urban and rural)  mobile source exposure distribution exclusive
of the three mobile source microenvironments,  for a one gram per minute
emission factor.  While it is possible to combine this distribution with
the microenvironment distributions to produce  a single exposure distribution
for a 1.0 g/min emission factor, such a distribution would have little use.
This is because the pollutant emission factors for each individual environ-
ment are different.  Therefore, each individual exposure distribution must
be multiplied by a different emission factor to obtain the exposure in
that environment for a given pollutant.

          Two different uses are examined for the exposure distributions
developed from this project.  The first use is to determine the person
hours of exposure above a specified concentration of a specific pollutant.
The  second use is to develop new sets of exposure distribution tables for
a specific pollutant.  Ideally, a computer program should be written for
both of these problems.  However, the time and effort available for this
project did not permit the development of the necessary computer program.
The paragraphs that follow explain how to  manually calculate the solutions
to these problems.

     Person Hours of Exposure above a Specific Concentration

          The total nationwide  annual person hours of exposure  above a
specified mobile source pollutant concentration  can be calculated using
Tables 19, 21,  23, and 35.   The steps are as follows:

          1.    Divide the  specified pollutant concentration, expressed
                in  yg/m3, by  the 1980 FTP  emission factor  converted  to
                grams/min  for the pollutant being studied.   This gives
                the concentration at  a  1.0 g/min  emission  factor.

          2.    Enter  Table 35,  the urban  and  rural exposure, with the
                new concentration  from Step  1.  Read the person hours
                of  exposure exceeding the  concentration from the table;
                linearly  interpolating between concentration values,
                if  required.

           3.    For each of the three microenvironments,  divide the
                specified pollutant concentration by the 1980 emission
                factor.   The emission factor will probably be different
                for each different microenvironment.

           4.    Enter the appropriate Table for each of the microenviron-
                ments with the new pollutant concentration for each one
                of the microenvironments.   Table  19 is used for parking
                garages, Table 21 for street canyons, and Table 23 for
                tunnels.  From each of the tables obtain a value for
                person hours of exposure above the concentration.   Inter-
                polate, if necessary.


                                     87

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          5.   Add the four values of person hours of exposure together
               to obtain the nationwide number of person hours exposure
               to the pollutant above the specified concentration.

     Tables of Exposure for a Specific Pollutant

          Exposure tables showing person hours of exposure above given
concentrations of a pollutant can be constructed for any mobile source
pollutant for which emission factors are known, using Tables 19, 21, 23
and 35.  In fact, for a given pollutant, a single exposure table can be
constructed combining the urban plus rural exposure and the microenvironment
exposures.  The procedure is as follows:

          1.   For Tables 19, 21, 23, and 35, multiply each concentration
               reading in each table by the emission factor appropriate
               to the environment for  which the individual table was
               constructed.  This will produce four tables with four
               different sets of concentration values in terms of yg/m3.

          2.   If units other than yg/m3 are desired (for instance,  ppm)
               multiply each concentration in the tables by the appro-
               priate conversion factor at this time.

          3.   Choose a convenient set of concentration intervals that can
               be used for all tables.  For each table, interpolate  to
               find the person hours of exposure at the chosen concentra-
               tion values.  This will produce four tables with the  same
               concentration values.

          4.   For each concentration value, add the person hours of
               exposure for each table to obtain a single table showing
               the nationwide person hours of exposure for the given
               pollutant.
                                    88

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                   VIII.  CONCLUSIONS AND RECOMMENDATIONS
     The goal of this project was to obtain nationwide annual person hours
of exposure to any mobile source pollutant.  This goal was accomplished
within the appropriate limitations and caveats mentioned previously, including
the caution which should be used when assessing pollutants with emissions
distributions markedly different from CO.  This goal was accomplished.
Tables 19, 21, 23, and 35 should be used for this purpose, following the
steps shown in Section VII.  Additionally, as the result of the work done
for this project, several important facts concerning the estimation of
exposure to mobile source pollutants were revealed, prompting the conclu-
sions and recommendations below.

     Conclusions

          Conclusions from this study are:

          1.   The results of NAAQS Exposure Model  (NEM) study of CO
               exposure do not provide a  sufficient estimation of
               mobile source pollutant exposure.

          2.   The NEM, with inputs modified from the published CO
               study inputs, and a mobile  source microenvironment
               exposure model used together were able to provide a
               reasonable  estimate of exposure to any mobile  source
               pollutant.

           3.   The place  specific approach used  in  the  mobile source
               microscale  exposure model developed  for  this  project
               is an  efficient  and accurate method  for  exposure deter-
               mination when  only person hours of  exposure is desired.

           4.    In mobile  source microscale situations,  CO concentra-
                tions  are  an excellent indicator  of  the  number of
                vehicles  present.

           5.    Neighborhood monitor concentrations will not  adequately
                predict mobile source pollutant concentrations within
                microenvironments with a large number of mobile sources.

      Recommendations

           During the course of this study, a number of data deficiencies,
 methodology improvements, and needed additional work were identified.
 From these, a number of recommendations for future action have been
 developed.


                                     89

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1.   To make the results of this study easier to use, a
     computer program should be written to provide a single,
     nationwide exposure distribution for any pollutant.

2.   To improve the exposure estimates for the on-expressway
     situation, the number of people in the NEM A-O groups
     needs to be adjusted, as do the activity patterns of
     the groups.

3.   On a longer range basis, the NEM computer program should
     be rewritten for nationwide mobile source exposure esti-
     mates.  It should be structured to utilize a nationwide
     data base of CO monitor data for the mesoenvironments,
     as well as national populations.  The time frame would be
     reduced to one quarter hour.  Activity patterns would be
     adjusted to account for the various mobile source micro-
     environments.  The exposure within the microenvironments
     themselves could possibly be part of the program.

4.   Additional mobile source microenvironments need to be
     included in the exposure estimate.  The two most significant
     areas needed are the personal garage and area sources,
     such as parking lots and trucking terminals.

5.   The best estimate of on-expressway exposure would be
     obtained by removing this microenvironment from the NEM.
     It should be possible to identify some of the SAROAD
     data base monitors as beside expressway monitors.  These
     monitors could be used to better estimate expressway
     exposure.  The on-expressway situation could then be
     treated as any other microenvironment.

6.   Additional measured CO data should be collected for parking
     garages and tunnels.

7.   Additional data are needed on the range and average time of
     individual exposure periods for each of the microenvironments.
                          90

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                                 REFERENCES
1.   Springer,  K.  J.,  and Ingalls,  M.N.,  "Measurement of Sulfate and Sulfur
     Dioxide in Automobile Exhaust."  Prepared for the Environmental Pro-
     tection Agency under Contract No. 68-03-2118, EPA 460/3-76-015.
     August 1976.

2.   Dietzmann, H. E., Smith, L. R., Parness, M. A., and Fanick, E. R.,
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     February 1979.

3.   Smith L. R.,  Parness, M. A., Fanick, E. R., and Dietzmann, H. E.,
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     EPA 600/2-80-068, April 1980.

4.   Springer, K. J., "Investigation of Diesel-Powered Vehicle  Emissions
     VII."  Final Report to the Environmental Protection Agency under
     Contract 68-03-2116, EPA 460/3-76-034, February  1977.

 5.   Springer, K. J., "Characterization of  Sulfates,  Odor,  Smoke,  POM, and
     Particulates from Light and Heavy Duty Engines - Part  IX." Final Report
     to the Environmental Protection  Agency under Contract  No.  68-03-2417,
     EPA 460/3-79-007, June  1979.

 6.   Hare, C. T.,  "Characterization of Gaseous  and  Particulate  Emissions from
     Light-Duty Diesels  Operated on Various Fuels."  Final  Report to the
     Environmental  Protection Agency  under  Contract 68-03-2440, EPA 460/3-79-008,
     July  1979.

 7.    Smith,  L.  R.,  "Characterization  of  Exhaust Emissions  from High Mileage
      Catalyst-Equipped Automobiles."   Final Report  to Environmental Protection
      Agency under Contract 68-03-2884, Task Specifications 7 and 10,
      EPA 460/3-81-024,  September 1981.

 8.    Smith,  L.  R.,  "Unregulated Emissions for Vehicles Operated under Low
      Speed Conditions."   Final Report to the Environmental Protection Agency
      under Contract 68-03-3073, Work  Assignment 4, EPA 460/3-83-006,
      May 1983.

 9.   Urban, C. M., "Regulated and Unregulated Exhaust Emission from Malfunctioning
      Non-Catalyst and Oxidation Catalyst Gasoline Automobiles."  Final Report
      to the Environmental Protection Agency under Contract No. 68-03-2499.
      Report No. EPA 460/3-80-003, January 1980.
                                     91

-------
                             REFERENCES  (Cont'd).


10.  Urban, C. M., "Regulated and Unregulated Exhaust Emissions from Malfunc-
     tioning Three-way Catalyst Gaseoline Automobiles."  Final Report to the
     Environmental Protection Agency under Contract 68-03-2588, Report No.
     EPA 460/3-80-004, January 1980.

11.  Urban, C. M., "Regulated and Unregulated Exhaust Emissions from A Malfunc-
     tioning Three-Way Catalyst Gasoline Automobile."  Final Report to the
     Environmental Protection Agency under Contract 68-03-2692.  Report No.
     EPA 460/3-80-005, January 1980.

12.  Urban, C. M., "Unregulated Exhaust Emissions from Non-Catalyst Baseline
     Cars Under Malfunction Conditions."  Final Report to Environmental
     Protection Agency under Contract 68-03-2884, Task Specifications 4 and 5.
     Report No. EPA 460/3-81-020, May 1981.

13.  Hare, C. T., "Characterization of Gaseous and Particulate Emissions from
     Light-Duty Diesels Operated on Various Fuels."  Final Report to the
     Environmental Protection Agency under Contract 68-03-2440, EPA 460/3-79-008
     July 1979.                                                                 '

14.  Ullman, T. L., and Hare, C. T., "Emission Characterization of an Alcohol/
     Diesel-Pilot Fueled Compression-Ignition Engine and Its Heavy-Duty
     Diesel Counterpart."  Final Report to Environmental Protection Agency
     under Contract 68-03-2884, Task Specification 6. Report No. EPA 460/3-81-023,
     August 1981.

15.  Bykowski, B. B., "Characterization of Diesel Emissions from Operation of
     a Light-Duty Diesel Vehicle on Alternate Source Diesel Fuels."  Final
     Report to the Environmental Protection Agency under Contract 68-03-2884,
     Task Specification 3, Report No. EPA 460/3-82-002, November 1981.

16.  Ullman, T. L., and Hare, C. T., "Emission Characterization of a Spark-
     Ignited, Heavy-Duty, Direct-Injected Methanol Engine." Final Report to
     the Enviornmental Protection Agency under Contract 68-03-3073, Work
     Assignment 2,  Report No. EPA 460/3-83-003, November 1982.

17.  Smith, L. R.,  Urban. C. R., and Baines, T. M., "Characterization of
     Exhuast Emissions from Methanol- and Gasoline-Fueled Automobiles."
     Final Report to Environmental Protection Agency under Contracts 68-03-2884
     and 68-03-3073,  Task Specifications 11 and 12, and Work Assignments 1 and
     3, Report EPA 460/3-82-004, August 1982.

18.  Ingalls, M. N.,  "Estimating Mobile Source Pollutants in Microscale
     Exposure Situation."  Final Report to Environmental Protection Agency
     under Contract 68-03-2884, Task Specification 1.  Report No. EPA 460/
     3-81-021, July 1981.


                                    92

-------
                          REFERENCES  (Cont'd).


19.  Harvey/  C.  A.,  et al "A Study of the Potential  Impact  of  Some  Unregulated
     Motor Vehicle Emissions."   SAE Paper 830937  to  be  presented  at the  1983
     SAE Passenger Car Meeting,  Dearborn, Michigan,  June 1983.

20.  "Carbon Monoxide", National Research Council, Committee on Medical  and
     Biologic Effect of Environmental Pollutants, National  Academy  of Sciences,
     Washington, D.C., 1977.

21.  "Compilation of Air Pollutant Emission Factors:  Highway  Mobile Sources"
     EPA 460/3-81-005, dated March 1981, U.S.,  EPA,  Office  of  Mobile Source
     Air Pollution Control, Emission Control Technology Division, Ann Arbor,
     Michigan.

22.  Larsen, R. I., "A New Mathematical Model of Air Pollutant Concentration
     Averaging Time and Frequency."  Journal of the Air Pollution Control
     Association, Vol. 19, No.  1, January 1969.

23.  Larsen, R. I., "A Mathematical Model for Relating Air Quality Measurements
     to Air Quality Standards," AP-89, Environmental Protection Agency,
     Research Triangle Park, N.C., November 1971.

24.  Mage, D. T., and Ott, W. E.,  "Refinements of the Lognormal Probability
     Model for Analysis of Aerometric Data," APCA Journal Vol. 28, No. 8,
     August 1978.

25.  Johnson, T.,  "A Comparison of the Two-Parameter Weibull and Lognormal
     Distributions Fitted to Ambient Ozone Data."   Proc. of Specialty
     Conference on Quality Assurance in  Air Pollution Measurement, Air Pollution
     Control Association,  1979.

26.  Aitchison, J., and  Brown,  J.A.C., The Lognormal Distribution, Cambridge
     University Press, New Youk,  1957.

27.  Kama,  G.  M.,  et  al,  "Air Flow Requirement for  Underground Parking  Garages,"
     American  Industrial Hygiene Journal, December  1961, pp 462-470.

 28.  Barker,  I. W.,  and Fox, M. F.,  "Vehicular Pollution in Car  Parks," Royal
     Society of Health Hournal, Vol.  96.

 29.  Glazer,  N.,  "The Regulation and Control of  Carbon Monoxide  in Enclosed
     Parking Garages."  APCA Paper 78-4.6,   presented at the  71st  Annual
     Meeting of APCA, June 1978.

 30.   Ayres & Hayakawa, Consulting Engineers, "Project Program Plan and Statement
      of Probable Costs.  Music Center and Mall Garages.  Phase I and III."
      Submitted to County and Los Angeles for Capitol Projects No.  7085.09,
      7065.21 amd 7065.22, May 1975.

                                     93

-------
                             REFERENCES  (Cont'd).
31.  Mage, D. T., "Frequency Distributions of Hourly Wind Speed Measurements,"
     Atmospheric Environment, Vol. 14, pp 367-374, 1980.

32.  "Airport Climatological Summary."  Climatography of United States No. 90,
     for various airports.  National Climatic Center, National Oceanic and
     Atmospheric Administration, Asheville, N.C.

33.  Johnson, T., and Paul, R. A., "The NAAQS Exposure Model (NEM)  Applied to
     Carbon Monoxide."  Draft Final Report by PEDCo Environmental,  Inc. for
     EPA, Contract 68-02-3390, Work Assignments 13 and 16, April 12, 1982.

34.  Brice, R. M., and Roesler, J. F., "The Exposure to Carbon Monoxide of
     Occupants of Vehicles Moving in Heavy Traffic."  JAPCA  Vol. 16,
     No. 11,.November 1966.

35.  Peterson, G. A., and Sabersky, "Measurement of Pollutants Inside an
     Automobile", JAPCA, Vol025, No. 10, October 1975.

36.  Chaney, L. W., "Carbon Monoxide Automobile Emissions Measured from the
     Interior of a Traveling Automobile." Science, Vol. 199, 17 March 1978.

37.  Colwill, D. M., and Hickman, A. J., "Exposure of Drivers to Carbon Monoxide "
     JAPCA, Vol. 30, No. 12, December 1980.                                     '

38.  Peterson, W. B., and Allen, R., "Carbon Monoxide Exposures to Los Angeles
     Area Commuters," JAPCA, Vol. 32, No. 8, August 1982.

39.  Rodgers, S. J., et al, "Tunnel Ventilation and Air Pollution Treatment,"
     Prepared for FHWA, Office of Research by Mine Safety Appliance Research
     Crop. Report FHWA-RD-72-15, NTIS No. PB210-360, June 30, 1970.

40.  "Study of Air Pollution Aspects of Various Roadway Configurations,"  Final
     Report to the New York City Department of Air Resources under Contract
   •  209624 by the General Electric Company, 3198 Chestnut Street,  Philadepphia,
     PA., dated September 1, 1971.

41.  Sosslau, A. B., and Hassom, A. B., "Quick-Repsonse Urban Travel Estimation
     Techniques and Transferrable Parameters,',1 National Cooperative Highway
     Research Program Report 187.  Transportation Research Board, National
     Research Council, Washington, D.C., 1978.

42.  "Short-Range Urban Transit Study, San Antonio, Texas," prepared for the
     San Antonio Transit System and City of San Antonio by Wilbur Smith and
     Associates, Houston, Texas, 1972.
                                    94

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                             REFERENCES (Cont'd).


43.  Thayer, S. D.,  "Vehicle Behavior In and Around Complex Sources and
     Related Complex Sources Characteristics, Vol  IV—Parking Facilities,"
     Final Report prepared by Geomet, Inc.,  Rockville, MD,  under Contract
     No. 68-02-1094 Task Orders to the U.S.  Environmental Protection Agency,
     Research Triangle Park, N.C., Publication No. EPA-460/3-74-003d,
     October 1973.

44.  Forrest, L. "Assessment of Environmental Impacts of Light Duty Vehicle
     Dieselization," Aerospace Report No. ATR-79(7740)-!. Draft Final Report
     by Aerospace Corporation under Contract DOT-TSC-1530, March 1979.

45.  Homburger, W. S., editor, Transportation and Traffic Engineering Handbook,
     second edition, Prentice Hall, Inc. Englewood Cliffs, N.J.

46.  "Highway Capacity Manual," Highway Research Board Special Report 87.
     Highway Research Board, National Research Council, Washington, D.C. 1965.

47.  Matson, T. M., Smith,  W. S., and Kurd,  F. W., Traffic Engineering,
     McGraw-Hill  Book Company, Inc., New York, N.Y.,  1955.

48.  Curtin, J. F.,  "Traffic-Transit-Parking in Downtown Rochester:   How to
     1975." Contained in Highway  Research Board Bulletin  293,  Highway
     Research  Board, National Research Council, 1961.

49.  "San Antonio-Bexar  County Urban Transportation Study  Report 6A and  6B -
     Origin-Destination Survey 1968,"   Texas Highway Department, Austin, Texas.

 50.  Pushkarev,  B.  and  Zupan,  J.  "Pedestrian Travel Demand;" Highway Research
     Record No.  355,  Highway Research Board, National Academy of Sciences,
     Washington,  D.C.,1971.

 51.  Cameron,  R.  M., "Mechanical Measurements of Pedestrian Volumes." Trans-
     portation Research Record No. 498.  Transportation Research Board,
     National Academy of Sciences, Washington, D.C., 1974.

 52.   Rutherford, G. S., and Schofer, J. L., "Analysis of Some Characteristics
      of Pedestrian Travel," Transportation Research Record No. 605. Transpor-
      tation Research Board, National Academy of Sciences, Washington, D.C., 1976.

 53.  Teague, D. M., "Los Angeles Traffic Pattern Survey" SAE  Paper 171 pub-
      lished in "Vehicle Emissions, Part I",  SAE Progress  in Technology
      Series, Vol.  6, Society of  Automotive  Engineers, Inc. pp 17-38,  1964.

 54.  Kruse, R. E., and  Huls, L.  A.,  "Development of the Federal Urban Driving
      Schedule," SAE Paper  730553  presented  at Detroit, MI,  Society of Automotive
      Engineer, Warrensdale, PA,  May 1973.
                                      95

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                             REFERENCES (Cont'd).


55.  Papette, B. and Horowitz, J. "Stochastic Model of Worst Case Exposures
     to Sulfuric Acid from Catalyst-Equipped Vehicles."  U.S. Enviornmental
     Protection Agency in-house (unpublished) report, November 1975.

56.  Schlaug, R. N., and Carlin, T. J., "Aerodynamics and Air Quality Management
     of Highway Tunnels." Final Report for Contract DOT-FH-11-8538 to Science
     Applications, Inc.  Report FHWA-RD-78-185, January 1980.

57.  Johnson, T., and Paul, R. A., "The NAAQS Model (NEM)  Applied to Carbon
     Monoxide."  Draft Final Report by PEDCo Environmental, Inc. for EPA
     Contract 68-02-3390, Work Assignments 13 and 16, December 1982.

58.  Meyer, J.R., Kain,  J.F., and Wohl, M., The Urban Transportation Problem.
     Harvard University Press, Cambridge,  MA., 1965.
                                    96

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                              APPENDIX A
Development of Lognormal Pollutant Distributions for Parking Garages
                         and Roadway Tunnels

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                        The  Lognormal Distribution

     The  lognormal distribution has historically been used to describe
ambient air concentration distributions.  For areas where the pollutant
concentration distribution is not  completely defined by measured-values,
but values such as the mean, median, mode or range are known, the properties
of the lognormal distribution can  be used to define the complete pollutant
distribution.
     The lognormal distribution is defined as:
               df  (x) =
exp
                                              2 a
2
(in x -  y)
                                                                     dx
Obviously, if a and y are known, the distribution can be defined  for any
value of X.

Additionally for a lognormal distribution:

               Mean, X = e  (y + 1/2 a2)

                Median = e^1
                Mode   = eM~a

The coefficient of variation n, defined as the  standard deviation divided
by the mean is:
     For the parking garage, the concentration distributions were developed
by using a CO concentration value known to be typical of parking garages
as the distribution mode, then adjusting the median so that the frequency
of occurence in the 300 to 400 ppm CO range was 0.01 percent.  If the median
and mode are known, then y and a are solved for  as follows:

               In  (median)= In  (e^)
               y = In  (median)

               In  (mode) = In  (ey~a'')
               y - a2 = In  (mode)

               a =  yln  (mode) - y

With y and a defined, the entire lognormal distirbution can be defined.

     For roadway tunnels a slightly different approach was used.  The
measured data on concentrations in roadway tunnels produced a mean value
and a maximum value of CO concentration as a function of average daily
traffic  (ADT).
                                    A-2

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     Using the proper CO emission factor, these CO levels were converted to
pollutant concentrations for a 1.0 g/minute emission factor (see text).
The CO concentrations and pollutant concentrations at 1.0 g/minute for
several ADT values are shown in the table below.

                                      Pollutant  Concentration
                                      yq/m3 at 1.0 g/min(a)
         ADT      Mean       Max.        Mean        Max.

         0.5       5.2        66.7       166.2      2131.8
         1.5      14.3        94.4       457.0      3017.2
         2.5      23.4       122.1       747.9      3902.5
         3.5      32.5       149.8      1038.7      4787.8
         4.5      41.6       177.4      1329.6      5669.9
         5.5      50.7       205.1      1620.4      6555.3
         6.5      59.9       232.8      1914.5      7440.6
            based on a CO emission factor of 62.06 g/mile  at  35 mph

      Assuming  that  the pollutant concentration  is  lognormally distributed,
 the  problem is to define the distribution for each value of ADT,  given only
 the  mean  and maximum concentrations.  Note  that if the  minimum concentration
 is assumed to  be 0  then the range  (maximum  - minimum)  is also known.   The
 expression for the  mean of a lognormal  distribution  is  shown  above.   It can
 also be shown  that  the standard deviation,  S, can  be approximated by  the
 following relationship, assuming that the range available  is  the  result of
 a large number of observations(2)

                           S =

 Thus the  standard deviation  for  the  tunnel  distribution can be estimated
 from the  range.  If the  standard deviation  and  mean are known the coeffi-
 cient of  variation  is  known  and  a can be obtained as follows:
                         n2 =   e°2 - 1
                        e°2 =   n2 + 1

                         a2 =   In  (n2 + 1)
                            =  Vln(n2
a =  Vln (n" + 1)
                                      A-3

-------
               Once a is known, y can be obtained from the equation for the
               mean:
                         X =  e
                                (y + 1/2
                       M + 1/2 a2 = In X

                         y = in x - 1/2 a2

     With both y and O known the distribution is fully defined.  The
table below shows the y and a for the tunnel pollutant concentration dis-
tributions at seven different values of ADT.
APT
0.5
1.5
2.5
3.5
4.5
5.5
6.5

range
(max-min)
2131.8
2017.2
3902.5
4787.8
5660.0
6555.3
7440.6
std. dev.
range
S = 6.5
327.97
464.18
600.38
736.58
872.29
1008.51
1144.71

mean
= X
166.2
457.0
747.0
1038.7
1329.6
1620.4
1914.5
n
= S
X
1.97
1.02
0.80
0.71
0.66
0.62
0.60


a
1.26
0.84
0.71
0.64
0.60
0.57
0.55


y
4.32
5.77
6.37
6.74
7.01
7.23
7.40
References:
   1. Aitchison, J. and Brown, J.A.C., The Lognormal Distribution,
      Cambridge University Press, New York, 1957.

   2. Sokal, R. and Rohof, T.J., Biometry, W. H. Freeman and Co., 1981,
                                    A-4

-------
                      APPENDIX B
Fortran Listing of SAROAD File Editing Program for
                Street Canyon Monitors
               (written for CDC Cyber 173)

-------
       GO TO 75
    190 PRINT 2040, I STACK),IMON(K),IDAY(K)
    200 60 TO 75
    220 PRINT 2050, ISTA(1),IMON(1),IDAY(1),IMON(2),IOAY(2),ISTA(2)
       CALL DUMREC( OUM,IDUML,IDUM4.K)
       K=1
       WRITE(2, 3000)   NARI(K), ISTA(K),NAR2(K),NAR3(K),IMON(K), |OAY(K),
       1         IDUML,IDUM4,ITYPE(K),IUNT(K),IDEC(K),(DUM(M),M=1,12)
        NAR1(1)=NAR1(2)
       NAR2O)=NAR2(2)
       NAR3(1)=NAR3(2)
       NAR4(1)»NAR4(2)
       IMON(1)=IMON(2)
       IDAY(1)=IDAY(2)
       ITYPE(1)=ITYPE(2)
       ISTA(1)*ISTA(2)
       IUNT(1)=IUNT(2)
       IDEC(1)=IDEC(2)
       ILINEd ) = l LINE(2)
       00 225 M-1,12
    225 RDG(M,1)=RDG(M,2)
       I =IMON(K)
       J»IDAY(K)
       GO TO  70
   1000 FORMAT(I 3,I 7,A3,I 3,I 2,I 2,I 1,16,I 2,I 2,I1,12F4.0)
   2000 FORMAT(1X,«FOR STATION ",17," SOMETHING  IS  WRONG  AT  »,I2,M/»,I2,
i       1       "LINE 2")
f°  2010 FORMAT(IX,"FOR STATION ",I7,« DATA IS MISSING FOR MONTH »,I2,
       1       ".  NEXT MONTH  WITH DATA  IS  MONTH  ",12)
   2020 FORMAT(IX,"FOR STATION ",17," DATA IS MISSING FOR MONTH »,I2,
       1        "  DAY ",12,".   NEXT  DAY  WITH  DATA  IS DAY " 12)
   2030 FORMAT(1X,«FOR STATION ",17," THERE  IS NO FIRST LINE OF DATA FOR  "
       1        ,I2,"/",I2)
   2040 FORMAT(1X,«FOR STATION ",17," SOMETHING  IS  WRONG  AT  ",I2,"/",I2,
       1        "LINE  1")
   2050 FORMAT(IX,"FOR STATION ",17," THERE  IS NO SECOND  LINE OF DATA  FOR»
       1        1X,I2,"/"I2,".  NEXT DATA IS ",I 2,"/",I 2," STATION  ",17)
   3000 FORMAT(I3,I7,A3,I 3,I 2,I 2,I 1,16,I 2,I 2,I1,12F4.1)
    999 STOP
       END
        SUBROUTINE DAYWEK(IMON,(DAY,ITYPE)
       COMMON/SATOA /ISAT(52)/SUNDA /ISUN(52)
        IDATE  «(IMON    »100)  + IDAY
        ITYPE    " 1
       00 100 L  - 1,52
        IFdDATE.EQ.ISAT(L))  ITYPE   * 2
        IF(IDATE.EQ.ISUN(L))  ITYPE   = 3
    100 CONTINUE
       RETURN
       END
        SUBROUTINE DUMREC( DUM,IDUML,IDUM4.K)
       DIMENSION  DUH(12)
       DO 200 I» 1,12
         DUM(I)  * 99.9
    200 CONTINUE
        IFCK.EQ.1) IDUML  - 0

-------
        PROGRAM  EOTEPA( INPUT. OUTPUT, EDDAT,TAPE2»EDDAT,TAPE60=I NPUT )
        DIMENSION   IMON(2),IOAY(2),ILINE(2),ITYPE(2), RDG( 12,2) , I UNT<2)
        DIMENSION   NAR1(2),NAR2(2),NAR3(2),NAR4(2), I STA(2),DUM( 12) . IDEC(2)
        ISTA(2)  =    1960085
     50 READ 1000,NAR1(K), I STA(K),NAR2(K),NAR3(K), IMON(K), IDAY(K) ,
       II LINE (K),  NAR4
-------
 IF(K.EQ.I) IDUM4 » 042101
 IF(K.EQ.2) IDUML « 1
 IF(K.EQ.2) IDUM4 « 242101
 RETURN
 END
 SLOCK DATA  SATDATE
 COMMON/SATDA/1 SAT(52)
 DATA (ISAT(I),l»1,52)/
1        0103,0110,0117.0124,0131,0207,0214,
2        0221,0228,0307,0314,0321,0328,0404,
3        0411,0418,0425,0502,0509,0516,0523,
4        0530,0606,0613,0620,0627,0704,0711,
5        0718,0725,0801,0808,0815,0822,0829,
6        0905,0912,0919,0926,1003,1010,1017,
7        1024,1031,1107,1114,1121,1128,1205,
8        1212,1219,1226/
 END
 BLOCK DATA SUNOATE
 COMMON/SUNDA/1 SUN(52)
 DATA (ISUNO ),l*1,52)/
 1        0104,0111,0118,0125,0201,0208,0215,
2        0222,0301,0308,0315,0322,0329,0405,
3        0412,0419,0426,0503,0510,0517,0524,
4        0531,0607,0614,0621,0628,0705,0712,
 5        0719,0726,0802,0809,0816,0823,0830,
 6        0906,0913,0920,0927,1004,1011,1018,
 7         1025,1101,1108,1115,1122,1129,1206,
 8         1213.1220.1227/
 END

-------
                 APPENDIX C
Fortran Listing of Microenvironment Exposure
          Model for Parking Garages
         (written for CDC Cyber 173)

-------
           PROGRAM PHD 1ST     73/74   OPT»1                           FTN 4.8+552        83/05/21. 16.57.26       PAGE


        1                PROGRAM PHD I ST( INPUT, OUTPUT)
                         REAL NPC
                        COMMON/POP/  P(24,5) /CONC / FRAC(23.9)
                        DIMENSION  R(2),FTT(3),SUM(23), ICON 1 (23) , ICON2C23) , ITI TLE (8) ,X<23)
        5                DATA  ICON1 /O, 361 ,464, 61 9, 774, 1031 , 1289, 1 547, 1805, 2062. 2320,2578,
                        1             3001,4001,5001,6001,8001,10001,15001,20001,25001,
                        2             3000 1,4000 1/
                        DATA  ICON2 /360, 463, 618, 773, 1030, 1288, 1 546, 1804, 206 1 , 231 9,2577,
                        1             3000,4000,5000,6000,8000,10000,15000,20000,25000,
       10                2             30000, 40000, 50000/
                  C**»* READ  INPUT VALUES
                        READ  1000,  ITITLE
                        READ  *  , TOTCAR
       15                 DO  50  1-1,23
                         SUM (I )*0.0
                      50  CONTINUE
                         DO  900 JDAY - 1,5
                         GO  TO  (  100,120,140,145,150)  JDAY
       20           C*«*  JDAY*1 IS WEEKDAYS
                     100  H»248
                         NPC-1.4
                         GO  TO  160
                   C**»  JDAY-2 IS SAT. + SOME HOLIDAYS
       25             120  H=62
                         NPC-2.3
                         GO  TO  160
O                  C*    JDAY=3 IS SUN. + 3 HOLIDAYS
'                     140  H=55
       30                 NPC=2.3
                         GO  TO  160
                   C**«»  JDAYS= 4 IS FOR WORKER RELATED PEAK HOUR
                     145  H*  248.
                         NPC-1.4
       35                TOTCAR«.25»TOTCAR
                         GO  TO 160
                   C**»*  JDAYS= 5 IS FOR ENTERTAINMENT RELATED PEAK
                     150  H=»  62
                         NPC«2 3
       40            160 CONTINUE
                         DO  800 IHR=  1,24
                         PTC- 1.0
                         IFUDAY.EQ. 1.AND.IHR.E0.17) PTC=0.75
                         IF(JDAY.EQ.3.AND.IHR.Ep.22) PTC=0.75
       45                IF(JDAY.GT.3.AND.IHR.GT.1) GO TO 800
                     170 IFUDAY.LE.3) GO TO  180
                         N-7
                         GO TO 240
                     180 IF«P(|HR,JDAY)/12.).GT.6) GO TO 200
       50                N-1
                         GO  TO 240
                     200  IF((P(IHR,JDAY)/12.).GT.14) GO TO 220
                         N-4
                         GO  TO 240
       55            220  N-7
                     240  CONTINUE
                         M-N+2

-------
     PROGRAM PHDIST     73/74   OPT-1                           FTN 4.8+552        83/05/21.  16.57.26       PAGE


                  DO 700 LWS = N,M
                  IF(LMS.EQ.N)   WF-0.095
 60                IF(LWS.EQ.N-H) WF-0.65
                  IFUWS.EQ.N+2) WF=0.255
                  DO 600 KCON =1,23
                  SUM(KCON) = SUM(KCON) +  (FRAC(KCON,LWS) *PTC* TOTCAR»(P(IHR,JDAY)
                  1          /4.)   *NPC *  H * WF)
 65            600 CONTINUE
              700 CONTINUE
              800 CONTINUE
              900 CONTINUE
                  PRINT 2000 , ITITLE
 70                DO  940   I* 1,23
              940 PRINT 2010 ,ICON 1(I),ICON2(I),SUM(I)
                  X(23)=SUM(23)/1E6
                  DO 960 1=2,23
                  J = l-1
75                XC24-I )=X(24-J)-KSUM(24-I )/1E6)
              960 CONTINUE
                  PRINT 2020,ITITLE
                    PRINT 2040,ICON1(1),X(1)
                  DO 980 1=2,23
80            980 PRINT 2040,ICON2(I-1),X(I)
             2020 FORMAT(1H1,//,26X,8A10,////,17X,"CONCENTRATION EXCEEDED*,
                 I       5X,*PERSON HOURS*,/)
             2040 FORMAT(20X,6X,I5,5X,10X,F9.3)
             1000 FORMAT (8A10)
85           2000 FORMAT (1H1,//,26X,8A10,////,17X,"CONCENTRATION INTERVAL*,
                 1            5X,*PERSON HOURS*,/)
             2010 FORMAT (20X,I5,*  TO  *,I 5,10X,F11.0)
              999 STOP
                  END

-------
       BLOCK DATA CONCEN     73/74   OPT=1                           FTN 4.8+552        83/05/21. 16.57.26       PAGE


       1                BLOCK DATA CONCEN
                       COMMON/CONC/P6FRAC(23,9)
                 C»*»  ORDER OF DATA  IS  3 PCT,FOR 1.5,7,14 KTS WIND,THEN 9+19 PCT.
                       DATA((PSFRAC(I
      10
      15
      20
      25
n
i
A
B
C
D
E
F
6
H
1
J
K
.000,
.000,
.002,
.005,
.020,
.037,
.052,
.063,
.069,
.071,
.070,
.148,
.120,
.180,
.150,
.170,
.097,
.053,
.030,
.017,
.010,
.006,
DATA((P6FRAC(I,
L
M
N
0
P
0
R
S
T
U
V
w

.107,
.197,
.123,
.073,
.069,
.024,
.015,
.001,
.000,
.000,
.000,
.000,
END
.005,
.005,
.001,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,

.566,
.157,
.138,
.068,
.047,
.016,
.005,
.002,
.000,
.000,
.000,
J),J=1,9)
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,

.000,
.000,
.000,
.000,
.000,
.000,
.001,
.002,
.003,
.004,
.006,
,1=12,
.013,
.040,
.070,
.081,
.168,
.147,
.241,
.113,
.054,
.025,
.021,
.006,

.005,
.005,
.018,
.031,
.076,
.096,
.102,
.097,
.088,
.077,
.066,
23)/
.087,
.127,
.061,
.030,
.024,
.007,
.003,
.000,
.000,
.000,
.000,
.000,

.044,
.054,
.110,
.121,
.185,
.143,
.102,
.071,
.049,
.034,
.023,

.024,
.027,
.007,
.002,
.001,
.000,
.000,
.000,
.000,
.000,
.000,
.000,

.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,

.000,
.003,
.006,
.011,
.040,
.061,
.201,
.193,
.149,
.106,
.123,
.058,

.000,
.000,
.000,
.001,
.006,
.013,
.022,
.030,
.037,
.043,
.047,

.080,
.184,
.151,
.112,
.137,
.067,
.057,
.011,
.003,
.000,
.000,
.000,

.003,
.004,
.013,
.025,
.066,
.089,
.098,
.097,
.090,
.084,
.070/

.093,
.137,
.067,
.033,
.026,
.007,
.004,
.000,
.000,
.000,
.000,
.OOO/


-------
         BLOCK DATA POPPG
73/74   OPT=1
FTN 4.8+552
83/05/21. 16.57.26
PAGE
n
i
Ul
       10
       15
       20
       25
       30
                         BLO K DATA POPPG
                         COMMON/POP/PGP(24,5)
                   C««»  DATA ORDER IS  WEEKDAY,
                         DATA ((P6P(I,J),J=1,5),
                  SAT., SUN
A
B
C
D
E
F
G
H
1
J
K
L
DATA
M
N
0
P
0
R
S
T
U
V
w
X
END
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0099,
.0693,
.1284,
.1943,
.2134,
.1750,
( (PGPd.J)
.1729,
.1819,
.1678,
.1902,
.1960,
.1836,
.1033,
.0829,
.0723,
.0409,
.0449,
.0251,

.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0040,
. 0060 ,
.0340,
.0600,
.0820,
.1060,
,J=1,5)
.1340,
.1610,
.1800,
.1930,
.1980,
.2000,
.2000,
.1980,
.1750,
.1200,
.0540,
.0000,

.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0125,
.0375,
.0500,
.0500,
.0500,
0.750,
0.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
0.750,
0.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.ooo/
,l=12,24)/
.0500,
.0500,
.0500,
.0500,
.0375,
.0125,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,

.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,

.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.000,
.ooo/

                                                                                            M TO
                                                               TO
                                                               TO
                                                               TO
                                                               TO
                                                               TO
                                                               TO
                     1
                     2
                     3
                     4
                     5
                     6
                     7 TO 8
                     8 TO 9
                     9 TO 10
                    10 TO 11
                    11 TO 12
                                                            12 TO
                                                            13 TO
                                                               TO
                    14
                    15 TO
                    16 TO
                    17 TO
                    18 TO
                    19 TO
                    20 TO
                    21 TO 22
                    22 TO 23
                    23 TO 24
       13
       14
       15
       16
       17
       18
       19
       20
       21

-------
                    APPENDIX D
Fortran Listing of Microenvironment Exposure Model
                 for Street Canyons
            (written for CDC Cyber 173)

-------
      PROGRAM SCOIST(INPUT,OUTPUT)
      COMMON/SPOP/  P(24.6)  /SCONC / FRACd9,6,3)
      DIMENSION  TOTP(3),TOTPD(3),SUM(19),ICONK19>,ICON2M9),mTLE<8),
     1           X(19)
      DATA ICON1 /O,36,106,176,246,3 16,387,457,527,597,667,737,807,877,
     1            948,1088,1298,1509,1719/
      DATA ICON2 /35,105,175,245,315,386,456,526,596,666,736,806,876,
     1      947,  1087,1297,1508,1718,20697
C«*»« READ INPUT VALUES
      READ 1000, ITITLE
      READ » ,(TOTP(I ), 1=1,3), (TOTPDd ), 1=1,3)
C*»»»
      DO 50 1=1,19
      SUM(I)=0.0
   50 CONTINUE
      DO 900 JDAY =1,3
      60 TO ( 100,120,140) JDAY
C*«»  JDAY=1 IS WEEKDAYS
  100 H=248
      GO TO 160
C**»  JDAY=2 IS SAT. + SOME HOLIDAYS
  120 H»62
      GO TO 160
C»    JDAY=3 IS SUN. + 3 HOLIDAYS
  140 H=55
      GO TO 160
  160 CONTINUE
      00 800 IHR= 1,24
       GO TO (200,220,240) JDAY
  200 IF(IHR.LE.6)  L-1
      IFdHR.EQ.7)  L-2
      IF(IHR.GE.8.AND.IHR.LE.9) L-3
      IF(IHR.GE.10.AND.IHR.LE.15)  L=4
      IF(IHR.GE.16.AND.IHR.LE.18)  L-5
      IFdHR.6E.19)  L«6
      GO TO 280
  220 IFdHR.LE.3)  L-1
      IFdHR.GE.4.AND.IHR.LE.6) L-2
      IF(IHR.GE.7.AND.IHR.LE.8) L-3
      IFdHR.GE.9.AND. IHR.LE. 12)  L-4
      IFdHR.GE.13.AND.IHR.LE.18)  L=5
      IFdHR.GE.19)  L-6
      GO TO 280
  240 IFdHR.LE.2)  L-1
      IFdHR.GE.3.AND. IHR.LE.4) L*2
      IFdHR.GE.5.AND.IHR.LE.10)  L-3
      IFdHR.GE.11.AND.IHR.LE.14)  L«4
      IFdHR.GE.15.AND.IHR.LE.23)  L=5
      IFdHR.GE.24) L«6
  280 CONTINUE
      DO 600 KCON =1,19
      SUM(KCON)  » SUM(KCON)  + (FRAC(KCON,L,JDAY) »(((TOTP(JDAY)*P(IHR,
      1   JDAY))   +(TOTPD(JDAY)*P(IHR,JDAY+3)))/4)  *  H)
  600 CONTINUE
  800 CONTINUE
  900 CONTINUE

-------
                        •1,3),  (TOTPD(I),I-1.3)
       PRINT  2000  ,  ITITLE
       PRINT  2005,  (TOTP(I).I
       PRINT  2007
       DO  940  1-1,19
   940 PRINT  2010  ,I CON 1(I),ICON2(I>,SUM(I )
       X(19)»SUM(19)/1E6
       00 960 1-2,19
       J = l-1
       X(20-l )-X(20-J)-HSUM(20-l )/1E6)
   960 CONTINUE
       PRINT  2000,I TITLE
       PRINT  2005,  (TOTP(I),1-1.3),  (TOTPDCI),I-1,3)
       PRINT  2020
         PRINT 2040,ICON1(1),X(1)
       DO 980  1=2.19
   980 PRINT  2040,ICON2(I-1),X(I)
  2020 FORMAT(17X,"CONCENTRATION EXCEEDED",
      1        5X,"PERSON HOURS",/)
  2040 FORMAT(20X,6X,I5,5X,10X.F9.3)
  1000 FORMAT  (8A10)
  2000 FORMAT  (1H1.//.26X.8A10,////)
  2005 FORMATOOX.6F12.0,///)
  2007 FORMAT(17X,"CONCENTRATION INTERVAL",5X,"PERSON  HOURS*,/)
  2010 FORMAT  (20X.I5,* TO  *,I 5,10X,F11.0)
  999 STOP
       END
      BLOCK DATA  SCCONC
      COMMON/SCONC/SCFRAC(19,6,3)
C""»  ORDER OF DATA  IS WEEKDAYS BY  HOUR  GROUP  THEN  SAT.  AND  SUN.
DATAC
A
B
C
0
E
f
G
H
1
J
K
L
M
N
0
P
Q
R
S
(SCFRACd.J,
.3358,
.4051,
.1435,
.0631.
.0271,
.0130,
.0060,
.0034.
.0015,
.0007,
.0004,
.0002,
.0002,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
D.J-1.
.0621,
.2858,
.2568,
.1750,
.1000,
.0541,
.0300,
.0139,
.0098,
.0057,
.0035,
.0010,
.0012,
.0004,
.0004.
.0002,
.0000,
.0000,
.0000,
6), 1-1, 19)/
.0191,
.1137,
.1862,
.1818,
.1505,
.1049,
.0811,
.0603,
.0326,
.0239,
.0163,
.0104,
.0066,
.0035,
.0045,
.0030,
.0007,
.0003,
.0002,
.0223,
.1292,
.1988,
.1800,
.1427,
.1039,
.0757,
.0549,
.0350,
.0236,
.0142,
.0076,
.0051,
.0032,
.0029,
.0009,
.0001,
.0000,
.0000,
.0182,
.1005,
.1616,
.1673,
.1421,
.1133,
.0934,
.0675,
.0470,
.0324,
.0216,
.0128,
.0084,
.0053,
.0050,
.0024,
.0009,
.0001,
.0000,
.0923,
.2954,
.2537,
.1550,
.0885,
.0477,
.0275,
.0166,
.0095,
.0056,
.0026,
.0018.
.0010,
.0009,
.0012,
.0004,
.0002,
.0000,
.oooo/
 DATA((SCFRAC(I,J,2),J-1,6), 1-1
A
B
C
D
E
F
.1987,
.3246,
.1946,
.1162,
.0650,
.0372.
.3137,
.4096,
.1604,
.0618,
.0331,
.0114,
.1647,
.4222,
.2339,
.1079,
.0457,
.0141,
.0839,
.3320,
.2734,
.1564,
.0829,
.0424,
.0613.
.2998,
.2622,
.1569,
.0947,
.0548,
.0992,
.3070,
.2311,
.1572,
.0955,
.0462,
                                                                             WKD
                                                                             NKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD
                                                                             WKD

                                                                             SAT
                                                                             SAT
                                                                             SAT
                                                                             SAT
                                                                             SAT
                                                                             SAT

-------
G
H
1
J
K
L
M
N
0
P
P
R
S
DATA(
A
B
C
D
E
F
G
H
1
J
K
D L
l M
*" N
0
P
Q
R
S
END
BLOCK
.0261,
.0168,
.0101,
.0050,
.0034,
.0013,
.0007,
.0003,
.0000,
.0000,
.0000,
.0000,
.0000,
(SCFRAC(I,J,
.1851,
.3190,
.2031,
.1149,
.0764,
.0308,
.0338,
.0144,
.0108,
.0041,
.0015,
.0021,
.0021,
.0000,
.0005,
.0010,
.0005,
.0000,
.0000,

DATA POPSC
.0057,
.0030,
.0007,
.0007,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
. 0000 ,
.0000,
.0000,













3),J=1,6>
.2718,
.3885,
.1618,
.0830,
.0384,
.0197,
.0166,
.0093,
.0041,
. 003 1 ,
.0000,
.0016,
.0000,
.0010,
.0010,
.0000,
.0000,
.0000,
.0000,























.0070,
.0030,
.0010,
.0005,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
.0000,
,1=1,19
.2873,
.4847,
.1509,
.0489,
.0143,
.0091,
.0017,
.0012,
.0005,
.0003,
.0003,
.0002,
.0005,
.0000,
.0002,
.0000,
.0000,
.0000,
.0000,


.0149,
.0078,
.0038,
.0015,
.0003,
.0003,
.0003,
.0000,
.0000,
.0000,
.0003,
.0000,
.0000,
)/
.1847,
.4672,
.1976,
.0930,
.0299,
.0167,
.0048,
.0025,
.0020,
.0010,
.0005,
.0000,
.0000,
.0000,
.0000,
.0325,
.0167,
.0098,
.0056,
.0027,
.0010,
.0008,
.0005,
.0002,
.0005,
.0000,
.0000,
.0000,

.1484,
.3946,
.2186,
.1160,
.0574,
.0296,
.0154,
.0089,
.0043,
.0028,
.0026,
.0011,
.0001,
.0002,
.0000,
.0238,
.0157,
.0116,
.0062,
.0034,
.0019,
.0005,
.0002,
.0002,
.0005,
.0000,
.0000,
.00007

.2064,
.4087,
.1815,
.1120,
.0477,
.0249,
.0073,
.0062,
.0010,
.0021,
.0010,
.0010,
.0000,
.0000,
.0000,
.0000, .0000, .0000,
.0000, .0000, .0000,
.0000,
.0000, .0000,
.0000, .0000, .00007






COMMON/SPOP/PSC(24.6)
C«*» DATA
DATA
A
B
C
0
E
F
G
H
1
J
K
L
DATA
M
N
0
P
0
ORDER 1 S WEEKDAY,
((PSC(I,J),J
.0117
.0079
.0050
.0050
.0067
.0158
.0388
.0765
.0650
.0565
.0571
.0598
«PSC(I,J),
.0580
.0580
.0601
.0674
•1,6), 1
.0444
.0399
.0334
.0222
.0161
.0165
.0238
.0315
.0370
.0407
.0447
.0479
•1,6). 1
.0492
.0513
.0538
.0538
.0840 , .0524
SAT., SUN
•
t
t
9
»
t
9
9
9
t
9
9
9

9
9
9
9
9
1 , 12)/
.0663
.0572
.0472
.0319
.0219
.0179
.0211
.0249
.0247
.0281
.0305
.0345
12, 24)/
.0390
.0419
.0481
.0501
.0536

.004
.002
.001
.001
.001
.003
.008
.030
.059
.054
.058
.075

.126
.115
.090
.075
.085

.0046
.0023
.0012
.0000
.0000
.0012
.0023
.0046
.0185
.0323
.0611
.0934

.1130
.1280
.1349
.1153
.1038

.0046
.0023
.0012
.0000
.0000
.0012
.0023
.0046
.0185
.0323
.0611
.0934 /

.1 130 ,
.1280 ,
.1349 ,
.1153 ,
.1038 ,
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT
SAT

SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
SUN
M
1
2
3
4
5
&
7
8
9
10
1 1
12
13
14
15
16
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

-------
      R
      S
      T
      U
      V
      w
      X
       END
0675
0472
0417
0338
0317
0246
0190
.0500
.0455
.0466
.0463
.0494
.0530
.0506
.0555
.0554
.0550
.0538
.0509
.0484
.0422
.090
.044
.026
.018
.014
.010
.008
.0669
.0369
.0219
.0185
.0150
.0150
.0092
.0669
.0369
.0219
.0185
.0150
.0150
.0092 /
17 TO  18
18 TO  19
19 TO 20
20 TO 21
21 TO 22
22 TO 23
23 TO 24
o
I
Ln

-------
                   APPENDIX E
Fortran Listing of Microenvironment Exposure Model
                   for Tunnels
           (written for CDC Cyber 173)

-------
      PROGRAM TUDIST(INPUT,OUTPUT)
      COMMON/TPOP/  P(24,3) /TCONC / FRAC(19,7)
      DIMENSION  TOTP(3),AP(24,3),SUM(19),ICON1(19),ICON2(19),ITlTLE(8),
     1           X(19)
      DATA ICON1 70,201,401,601,701,801,901,1001,1201, 1401,
     1            1601,1801,2001,220t,2401,2601,3001,4001,60017
      DATA ICON2 7200,300,600,700,800,900,1000,1200,1400,1600,1800,
     1      2000,2200,2400,2600,3000,4000,6000,80007
C»**» READ INPUT VALUES
      READ 1000, ITITLE
      READ * ,(TOTP(I),I=1,3)
C**»»
      DO 50 1=1,19
      SUM(I)=0.0
    50 CONTINUE
      DO 900 JDAY =1,3
      GO TO (  100,120,140) JDAY
C«*»  JDAY=1 IS WEEKDAYS
   100 H=248
      GO TO  160
C*»«  JDAY=2 IS SAT. + SOME HOLIDAYS
   120 H=62
      GO TO  160
C*   JDAY=3 IS SUN. + 3  HOLIDAYS
   140 H=55
w    GO TO  160
 I  160 CONTINUE
10    DO 800  IHR*  1,24
       IF(JDAY.EQ.I)  AP(IHR.I)  = P(IHR,1)
       IFUDAY.EQ.2)  AP(IHR,2)  = P(IHR,2)*(TOTP(2)/TOTP(1))
       IFUDAY.EQ.3)  AP(IHR,3)  = P( I HR,3)»(TOTP(3)/TOTP( 1 ) )
       IF(AP(IHR,JDAY).LE.0.01) L=1
       IF(AP(IHR,JDAY).GT.0.01.AND.AP(IHR,JDAY).LE.0.02)  L=2
       IF(AP(IHR,JDAY).GT.0.02.AND.AP(IHR,JDAY).LE.0.03)  L=3
       IF(AP
-------
   980 PRINT 2040,ICON2(I-1),X
-------
     R
     S
     T
     U
     V
     w
     X
      END
.0634
.0599
.0576
.0461
.0417
.0375
.0299
.0560
.0583
.0635
.0562
.0497
.0456
.0424
.0560
.0583
.0635
.0562
.0497
.0456
.0424 /
17 TO 18
18 TO 19
19 TO 20
20 TO 21
21 TO 22
22 TO 23
23 TO 24
M

-------
              APPENDIX F




UNIVAC 1100 Runstreams for NEM Reruns

-------
          Runstream to Produce the NEM Air Quality Input
                          File for Chicaco
«RUN,R/R AIRDAT/80,l«iMMiM,EXES/MMSAP, 120,9999
«DELETE,C EXES*PRTAg.
|DELETE,C EXES«AQCHIC.
ICOND
ICAT.P PRTAQ.,F33///140
«US*ER.BK1,A PRTAQ.
IASG.CP EXES*AQCHIC.
fASG.T AQFILE.
fASG.A SASO*CO-TRACK.
|COPY,A SASD*EXP-ABS.TRACK-11
|SETC,0
fX(JT SASD*EXP-ABS.TRACK-H
 7  1.31 11                         SASD*CO-TRACK.CHICAGO
•COPY AQFILE.,EXES«AQCHIC.
«SETC,X
fUS»ER.BK2,N
           Runstream to  Produce the  NEM Air Quality Input
                      File for Los Angeles
0RUN,R/R AQDAT2/80,•••••*!•••,EXES/MMSAP,120,9999
IDELETE,C EXES»PRTAQLA.
iDELETE.C EXES»AQLA.
ICOND
«CAT,P PRTA(JLA.,F33///140
fUS*ER.BKI,A PRTAQLA.
«ASG,CP EXESMQLA.
|ASG,T AQFILE.
fASG.A SASO*CO-TRACK.
iCOPY.A SASD*EXP-ABS.TRACK-11
«SETC.O
«XQT SASD*EXP-ABS.TRACK-11
 7 1.75 II                         SASO*CO-TRACK.LOS-ANGELES
fCOPY AQFILE.,EXES*AQLA.
iSETC.X
fUS»ER.BK2,N
                                    F-2

-------
          Runstream to Produce the  NEM Air Quality Input
                       File for Philadelphia
0RUN.R/R AQDAT3/80,Mt*IMim,EXES/MMSAP. 120, 9999
«OELETE,C EXES»PRTAQPHIL.
§DELETE,C EXES»AQPHIL.
8CONO
ICAT,P PRTAOPHIL.,F33///140
iUS»ER.8KI,A PRTAQPHIL.
«ASG,CP £XES»AQPHIL.
«ASG,T AQFILE.
tASG.A SASD*CO-TRACK.
ICOPY.A SASO«EXP-ABS.TRACK-11
«SETC,0
«XQT SASO*EXP-ABS.TRACK-11
  7 0.96 11                         SASD»CO-TRACK.PHILADELPHIA
iCOPY AQFILE.,EXES»AQPHIL.
«SETC,X
SUS*ER.BK2,N
EOF:16
           Runstream to Produce  the NEM Air Quality Input
                           File  for St.  Louis
 IRUN.R/R A
-------
                       NEM  Runstream  for Chicago
IRUN.R/R NEMRN2/80,ilfi|iim,EXES/MMSAP,30,50
IDELETE.C EXES*PRTNEM1.
ICO NO
«CAT,P PRTNEM1..F33///150
fUS*ER.BK],A PRTNEM1.
IASG.T SUMFILE.
IASG.A EXES»AQCHIC.
IUSE AQFILE.,EXES»AQCHIC.
ICOPY.A SASD*EXP-ABS.NEM
IXQT NEM
1
iADD SASD*TRACK-DATA.YEAR-START/MONDAY
CHICAGO          8             CHIC,ALL PERS, B.E.MICRCXNO SOURCESJAS IS AQ
IADD SASD"CO-TRACK.BE/BASE
IADD EXES*MOBILE-DATA.CONCS/20
IAOO SASD*CO-TRACK.CONCS-COHB/U
8ADD SASD*CO-TRACK.CONSTANTS/M
IADD SASD*TRACK-DATA.CHICAGO/NT-6
IEOF
IUS»ER.BK2,N
                       NEM  Runstream  for Los Angeles
    , R/R NEMRN3/80, ••«»••••, EXES/MMSAP, 30, 50
IDELETE.C EXES»PRTNEMLA.
ICOND
ICAT.P PRTNEMLA..F33///150
«US*ER.BKJ,A PRTNEMLA.
|ASG,T SUMFILE.
IASG.A EXES»AOLA.
IUSE A9FILE.,EXES»AQLA.
ICOPY,A SASD*EXP-ABS.NEM
IXQT NEM
1
IADD SASD*TRACK-OATA.YEAR-START/SATUROAY
LOS-ANGELES      8             ALL PERSONS,  B.E. MICRO(NO SOURCES),AS IS AQ
IADD SASO»CO-TRACK.BE/BASE
IADD EXES»MOBILE-DATA.CONCS/20
IADD SASD*CO-TRACK.CONCS-COHB/14
IAOD SASD*CO-TRACK.CONSTANTS/M
IADO SASD*TRACK-DATA.LOS-ANGELES/NT-6
IEOF
IUS»ER.BK2,N
                                    F-4

-------
                       NEM Runstream for Philadelphia
iRUN,R/R NEMRN4/80,M«lMt*M,EXES/MMSAP,30,50
iDELETE,C EXES«PRTNEMPHIL.
fCOND
iCAT.P PRTNEMPHIL..F33///150
iUS*ER.BK1,A PRTNEMPHIL.
iASG,T SUMFILE.
iASG.A EXES*AQPHIL.
IUSE A
-------
                                  TECHNICAL REPORT DATA
                           (Please read Instructions on the reverse before completing)
 REPORT NO.
   EPA 460/3-84-004
                             2.
                                                           3. RECIPIENT'S ACCESSION-NO.
 TITLE AND SUBTITLE

   Mobile Source Exposure Estimation
                                                           5. REPORT DATE
                          March  1984
             6. PERFORMING ORGANIZATION CODE
 AUTHORIS)

   Melvin N.  Ingalls
                                                           8. PERFORMING ORGANIZATION REPORT NO.
 PERFORMING ORGANIZATION NAME AND ADDRESS
   Southwest Research Institute
   6220 Culebra
   San Antonio,  Texas 78284
                                                           10. PROGRAM ELEMENT NO.
             11. CONTRACT/GRANT NO.

                  68-03-3073
2. SPONSORING AGENCY NAME AND ADDRESS
   Environmental Protection Agency
   2565 Plymouth Road
   Ann Arbor,  Michigan 48105
             13. TYPE OF REPORT AND PERIOD COVERED
             Final  (.Tung  \ Qft?  -  May 1
             14. SPONSORING AGENCY CODE
S. SUPPLEMENTARY NOTES
   This  project was conducted to provide a national exposure,  in terms of person
   hours, to non-reactive mobile source pollutants.  The basis  for the estimate was
   the EPA "NAAQS Exposure Model"  (NEM)  as applied to carbon monoxide, supplemented
   by four mobile source microenvironments:  parking garages,  street canyons, on-
   expressways, and roadway tunnels.   From previous studies, both published and
   unpublished, CO concentration distributions and national  population estimates,
   by hour of the day, for each of  these mobile source microenvironments were
   developed.  That information was combined to determine national exposure in the
   microenvironments.  By using the mobile source CO emission factor, exposure to
   mobile source pollutants based on a pollutant  emission rate of one gram per
   minute was determined for each of the microenvironments  and the environments
   covered by the NEM.  The methodology for using this information to determine
   exposure to any mobile source pollutant, regulated or unregulated was explained.
                                KEY WORDS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS
                                                                          c. COSATI Field/Group
    Air Pollution
    Exhaust Emissions
    Motor Vehicles
   Exposure  Estimates
   Parking Garages
   Tunnels
   Street Canyons
   Expressways
13. DISTRIBUTION STATEMENT
    Unlimited
19. SECURITY CLASS (ThisReport)
20. SECURITY CLASS (This page)
   Unclassified
                                                                          21. NO. OF PAGES

                                                                                 131
                                                                          22. PRICE
EPA Form 2220-1 (9-73)

-------
                                                         INSTRUCTIONS

     1.   REPORT NUMBER
         Insert the EPA report number as it appears on the cover of the publication.

     2.   LEAVE BLANK

     3.   RECIPIENTS ACCESSION NUMBER
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         type or otherwise subordinate it to main title. When a report is prepared in more than one volume, repeat the primary title, add volume
         number and include subtitle for the specific title.

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         approvcl, date of preparation, etc.).

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     8.   PERFORMING ORGANIZATION REPORT NUMBER
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         Give name, street, city, state, and ZIP code. List no more than two levels of an organizational hireaichy.

     10.  PROGRAM ELEMENT  NUMBER
         Use the program element number under which the report was prepared.  Subordinate numbers may be included in parentheses.

     11.  CONTRACT/GRANT NUMBER
         Insert contract or grant number under which report was prepared.

     12.  SPONSORING AGENCY NAME AND ADDRESS
         Include ZIP code.

     13.  TYPE OF REPORT AND PERIOD COVERED
         Indicate interim final, etc., and if applicable, dates covered.

     14.  SPONSORING AGENCY CODE
         Leave blank.

     15.  SUPPLEMENTARY NOTES
         Enter information not included elsewhere but useful,  such as: Prepared in cooperation with, Translation of, Presented at conference of,
         To be published in. Supersedes, Supplements, etc.

     16.  ABSTRACT
         Include a brief (200 words or less) factual summary of the most significant information contained in the report. If the report contains a
         significant bibliography or literature survey, mention it here.

     17.  KEY WORDS AND DOCUMENT ANALYSIS
         (a) DESCRIPTORS - Select from the Thesaurus of Engineering and Scientific Terms the proper authorized terms that identify the major
         concept of the research and are sufficiently specific and precise to be used as index entries for cataloging.

        (b) IDENTIFIERS AND OPEN-ENDED TERMS - Use identifiers for project names, code names, equipment designators, etc. Use open-
        ended terms written in descriptor form for those subjects for which no descriptor exists.

         (c) COSATI FIELD GROUP - Field and group assignments are to be taken from the 196S COSATI Subject Category List. Since the ma-
        jority of documents are multidisciplinary in nature, the Primary Field/Group assignment(s) will be specific discipline, area of human
        endeavor, or type of physical object.  The application(s) will be cross-referenced with secondary Field/Group assignments that will follow
        the primary posting(s).

    18. DISTRIBUTION STATEMENT
        Denote releasability to the public or limitation for reasons other than security for example "Release Unlimited."  Cite any availability to
        the public, with address and price.

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        Insert the total number of pages, including this one and unnumbered pages, but exclude distribution list, if any.

    22. PRICE
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EPA Form 2220-1 (9-73) (Reversal

-------