&EPA
United a*s
Environmental PiutecBmi
Agoncy
Total Risk Integrated Methodology (TRIM) Air
Pollutants Exposure Model Documentation
(TRIM.Expo / APEX, Version 4.3)


Volume I:  User's Guide

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                                                      EPA-452/B-08-001a
                                                           October 2008
Total Risk Integrated Methodology (TRIM) Air Pollutants
Exposure Model Documentation (TRIM.Expo / APEX, Version 4.3).
Volume I: User's  Guide
                       U.S. Environmental Protection Agency
                     Office of Air Quality Planning and Standards
                     Health and Environmental Impacts Division
                       Research Triangle Park, North Carolina

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                                   DISCLAIMER
       This document has been prepared by Alion Science and Technology, Inc. (through
Contract No. EP-D-05-065, WAs 21 and 94). Any opinions, findings, conclusions, or
recommendations are those of the authors and do not necessarily reflect the views of the EPA or
Alion Science and Technology, Inc. Mention of trade names or commercial products is not
intended to constitute endorsement or recommendation for use. Comments on this document
should be addressed to John E. Langstaff, U.S. Environmental Protection Agency, C504-06,
Research Triangle Park, North Carolina 27711 (email: langstaff.john@epa.gov).
                                          11

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                             ACKNOWLEDGEMENTS
The primary authors of this document are Graham Glen and Kristin Isaacs, Alion Science and
Technology, Inc.  Contributions have also been made by Melissa Nysewander, Luther Smith,
Casson Stallings (Alion Science and Technology, Inc.), Tom McCurdy, John Langstaff (EPA),
and ICF Consulting.
                                         in

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                                   CONTENTS

CHAPTER 1.   INTRODUCTION	1
  1.1    Overview of the APEX Model	1
  1.2    Scope and Organization of This Guide	3
CHAPTER 2.   INSTALLING APEX	4
CHAPTERS.   SETTING UP AND RUNNING APEX	5
  3.1    Setting Up an APEX Simulation	5
  3.2    Overview of Input and Output Files	6
    3.2.1   Input Files	6
    3.2.2   Output Files	6
  3.3    Overview of Model Settings and Options	9
  3.4    Running APEX in Batch Mode	14
CHAPTER 4.   APEX INPUT FILES	17
  4.1    Input File Formats	17
  4.2    Simulation Control File	19
    4.2.1   Input and Output File List Sections of the Simulation Control File	20
    4.2.2   Pollutant Parameters  Section of the Simulation Control File	22
    4.2.3   Job Parameter Settings Section of the Simulation Control File	26
  4.3    Population Sector Location File	35
  4.4    Air District Location File	36
  4.5    Air Quality Data File	38
    4.5.1   Raw AQ Input Data	38
    4.5.2   AQ Input Defined as Hourly Distributions	39
  4.6    Meteorology Zone Location File	40
  4.7    Meteorology Data File	40
  4.8    Population Data Files	42
  4.9    Commuting Flow File	43
  4.10  Employment Probability File	44
  4.11  MET Mapping File	45
  4.12  MET Distribution File	48
  4.13  Physiological  Parameters File	51
  4.14  Ventilation File	53
  4.15  Profile Functions (Distributions) File	54
    4.15.1    Defining a Profile Function	55
    4.15.2    Functions for Built-in, User-defined, and Regional APEX Variables	57
  4.16  Microenvironment Mapping File	62
  4.17  Diary Questionnaire (DiaryQuest) File	65
  4.18  Diary Events File	67
  4.19  Diary Statistics File	68
  4.20  Mi croenvironment Descriptions File	69
    4.20.1    Microenvironment Descriptions Section	69
    4.20.2    Parameter Descriptions Section	70
  4.21  Prevalence File	77
                                         IV

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CHAPTER 5.   APEX OUTPUT FILES	79
  5.1    Log File	81
  5.2    Hourly File	81
  5.3    TimestepFile	84
  5.4    Daily File	85
  5.5    Profile Summary (Persons) File	88
  5.6    Microenvironmental Results File	92
  5.7    Microenvironmental Summary File	95
  5.8    Output Tables File	96
    5.8.1  Exposure Summary Tables	96
    5.8.2  Dose Summary Tables	102
  5.9    Sites File	104
  5.10  Events File	105
REFERENCES	107

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                                LIST OF TABLES
Table 3-1. APEX Input and Output Files	8
Table 3-2. APEX Settings and Options	10
Table 4-1. APEX Input File Descriptions	18
Table 4-2. Pollutant Job Parameters	23
Table 4-3. Output Parameter Levels in the Output Summary Table	24
Table 4-4. Job Parameters in APEX Simulation Control File	27
Table 4-5. CHAD Activity Codes	45
Table 4-6. Available Probability Distributions in APEX	49
Table 4-7. Parameters in the Physiological Input File	51
Table 4-8. Variables That Can Be Defined in the Profile Functions File	59
Table 4-9. CHAD Location Codes	64
Table4-10. CHAD Occupation Codes	66
Table 4-11. Chad Locations Used in Constructing the Outdoor Time and Vehicle Time Diary
Statistics Files	68
Table 4-12. Microenvironment Parameters For the FACTORS and MASSBAL Methods	70
Table 4-13. Keyword Definitions for the Parameter Descriptions Section of the
Microenvironment Descriptions File	73
Table 5-1. APEX Output Files	80
Table 5-2. APEX Variables Written to the Hourly Output File	81
Table 5-3. APEX Variables Written to the Timestep Output File	84
Table 5-4. APEX Variables Written to the Daily Output File	86
Table 5-5. APEX Variables Written to the Profile Summary File	88
Table 5-6. APEX Variables Written to the Microenvironmental Results File	92
Table 5-7. Format of the APEX Microenvironmental Summary File	95
Table 5-8. Interpretation of the Variables in Exposure Table Type #3 and Other "Person-Days"
Based Tables	99
                                         VI

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                               LIST OF EXHIBITS
Exhibit 4-1.  Starting a Number of APEX Jobs Using a Batch File	15
Exhibit 1-2.  Screenshot of the Start of an APEXRun	16
Exhibit 1-3.  Screenshot of Successful Completion of an APEXRun	16
Exhibit 4-1.  Input Files Section of Simulation Control File	22
Exhibit 4-2.  Output Files Section of Simulation Control File	22
Exhibit 4-3. Pollutant Parameters Section of Simulation Control File	26
Exhibit 4-4.  Job Parameters Sections of the Simulation Control File	35
Exhibit 4-5.  First Part of Population Sector Location File	36
Exhibit 4-6.  First Part of Example Air District Location File	37
Exhibit 4-7.  First Part of Example Air Quality Data File  (Raw Data Type)	39
Exhibit 4-8.  First Portion of an Air Quality Data file (Distribution Type)	39
Exhibit 4-9.  First Part of Example Meteorology Zone Location File	40
Exhibit 4-10. Example Portion of Meteorology Data File	42
Exhibit 4-11. First Part of a Population Data File	43
Exhibit 4-12. First Part of the Commuting Flow File	44
Exhibit 4-13. Excerpt from the Employment Probability  File	45
Exhibit 4-14. Example Portion of the MET  Mapping File	48
Exhibit 4-15. Selected Parts of Activity-Specific MET File	50
Exhibit 4-16. An Example Portion of the Physiological Parameters File	53
Exhibit 4-17. The APEX Ventilation Input File	54
Exhibit 4-18. Examples of Profile Functions	61
Exhibit 4-19. Example Portion of a Microenvironment Mapping File	65
Exhibit 4-20. Example Portion of a Diary Questionnaire  File	66
Exhibit 4-21. Example Portion of Diary Events File	67
Exhibit 4-22. Example Part of a Diary Statistics File	69
Exhibit 4-23. Example Mi croenvironment Descriptions Section of the Microenvironment
Descriptions File	70
Exhibit 4-24. Example Parameter Descriptions in the Microenvironment Description File	77
Exhibit 4-25. Portion of an Example Prevalence File	78
Exhibit 5-1. Example Portion of an APEX Hourly Output File	83
Exhibit 5-2. Example Portion of an APEX Timestep Output File	85
Exhibit 5-3.  Example Portion of a Daily Output File	88
Exhibit 5-4.  Portion of aProfile Summary File	91
Exhibit 5-5.  Portion of an Environmental Results File	95
Exhibit 5-6.  Portion of a Microenvironmental Summary File	96
Exhibit 5-7.  Example of Exposure  Table Type #1 in the Output Tables File	98
Exhibit 5-8.  Example of Exposure  Table Type #3 in the Output Tables File	99
Exhibit 5-9.  Example of Exposure  Table Type #6 in the Output Tables File	101
Exhibit 5-10. Example of Exposure Table Type #11 in the Output Tables File	102
                                          vn

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                               LIST OF FIGURES

Figure 4-1. Relationship between Profile Functions and Microenvironmental Descriptions Files
	55
                                        Vlll

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CHAPTER 1.   INTRODUCTION
1.1  Overview of the APEX Model

The Air Pollutants Exposure model (APEX) is part of EPA's overall Total Risk Integrated
Methodology (TRIM) model framework (EPA, 1999). TRIM is a time series modeling system
with multimedia capabilities for assessing human health and ecological risks from hazardous and
criteria air pollutants; it has been developed to support evaluations with a scientifically sound,
flexible, and user-friendly methodology. The TRIM design includes three modules:

   •   Environmental Fate, Transport, and Ecological Exposure module (TRIM.FaTE);

   •   Human Inhalation-Dietary-Dermal Exposure module (TREVI.Expo); and

   •   Risk Characterization module (TRIM.Risk).

APEX is the inhalation exposure component of TRIM.Expo.  The APEX model is a
multipollutant, population-based, stochastic, microenvironmental model that can be used to
estimate human exposure via inhalation for criteria and air toxics pollutants. APEX is designed
to estimate human exposure to criteria and air toxic pollutants at the local, urban,  and
consolidated metropolitan level.  The current release of the model is Version 4. Human exposure
to a contaminant is defined as "contact at a boundary between a human and the environment at a
specific contaminant concentration for a specific interval of time" (National Research Council,
1991).  For air pollutants, the contact boundaries are nasal and oral openings in the body. Dose
is the amount actually received, or absorbed, in the body, leading to physiological effects.
Pollutant exposures are estimated in a microenvironmental model by treating each individual's
activities as a sequence of events, which are periods with known starting and ending times in
particular microenvironments.  A microenvironment is a defined space with relatively
homogeneous air pollution concentration for a simulated individual. "Indoor kitchen," "outdoor
parking lot," or "in vehicle" are examples of microenvironments. The pollutant concentrations
in the air in each microenvironment are estimated from ambient air pollutant concentrations and
parameters specific to each microenvironment and  each pollutant. A person's inhalation
exposures  for a time interval are the pollutant concentrations in the microenvironment that
person for that interval multiplied by the length of the interval.

The APEX model uses the personal profile approach to generate simulated individuals, for whom
exposure time series are calculated. The profile is a description of the characteristics of an
individual  that may affect their activities, their locations, or the concentrations in  the
microenvironments that they encounter.  Typically, the profile includes demographic variables
such as age, gender, and employment, as well as physiological variables such as height and
weight, and finally some situational variables such as living in a house with a gas stove or air
conditioning. The situational variables are used to  help determine the microenvironmental
concentrations, and the physiological variables are  used in the determination of ventilation rate

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and dose.  The demographic variables are used in the selection of activity diaries from EPA's
Consolidated Human Activity Database (CHAD, McCurdy et al. 2000) to represent the
individual. (Note: CHAD is a comprehensive database of human activity studies, which is
provided with APEX. However, APEX may utilize other human activity data at the discretion of
the user.  Throughout this document "CHAD" will be used to denote the human activity diaries,
although the reader should note that other data could be used).

APEX calculates the exposure and dose time series for a user-specified number of profiles for
any number of pollutants. If modeling the pollutant CO, APEX contains an algorithm for
estimating the blood dose (percent carboxyhemoglobin, %COHb).  APEX also contains an
algorithm  for modeling particulate matter (PM) dose. In the case of PM, dose is defined as the
rate of mass deposition in the respiratory system. If modeling any other pollutant, APEX
calculates dose as Exposure* Ventilation (see Volume //for details of the dose algorithms).
Collectively, these profiles are intended to be a representative random sample of the population
in a given study area.  To this end, demographic data from the decennial  census are used, so
appropriate probabilities for any given geographical area can be derived. In APEX the
demographic geographical units are called sectors. Using the standard input files provided with
the model, each sector is a census tract. Ambient air quality and meteorology data for the study
area are also required by the model; the area represented by an air quality monitor (or air quality
model grid cell) is called an air district, and the area covered by a meteorological monitor (or
meteorological model grid cell) is referred to as a zone. APEX matches up each sector in the
study area with the closest air district and zone to provide the data necessary to  simulate
exposure and dose for an individual.

For each simulated person (profile), the following general steps are performed:

•      Select the profile variables to characterize the person
•      Construct the event sequence by selecting a sequence of appropriate activity diaries for
       the person (using demographic variables)
•      For each pollutant, calculate the concentrations in the microenvironments  (using
       situational variables)
•      For each pollutant, calculate the person's exposure and dose for each event
•      Summarize the results for that  profile

The APEX model reports the results for each profile on various output files (some of which are
pollutant-specific), described in detail later in this guide.  Once all the profiles have been
simulated, the model produces a set of summary tables for each pollutant that indicate the
distributions of exposure and dose across all the profiles.

Model enhancements and other changes are occasionally  made to APEX, and thus users are
encouraged to revisit the download website for notices of these changes.  Comments and
suggestions for improvements to the model or the input data provided with the model should be
addressed to John Langstaff, U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina 27711 (email: langstaffjohn@epa.gov).

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1.2  Scope and Organization of This Guide

The documentation of the APEX model is currently divided into two volumes.  Volume I: User's
Guide (this document) is designed to be a hands-on guide to the model. It focuses on how to run
the APEX computer model, develop the appropriate input files, and understand the model output
files.

Volume II: Technical Support Document describes the scientific basis of the APEX model and
provides scientific background for the model algorithms. It covers the methods implemented in
APEX for calculating microenvironmental concentrations, modeling ventilation, estimating dose,
and assembling activity diaries.

Additional volumes or revisions to these volumes may be developed as APEX is upgraded,
example applications are developed, or other needs arise.

The rest of Volume Us organized into the following chapters:

   •   Chapter 2, Installing APEX—Describes the hardware requirements and provides
       instructions for installing APEX.
   •   Chapter 3, Running APEX—Provides step-by-step instructions on starting single or
       multiple APEX simulations.
   •   Chapter 4, Input Files—Provides a description of the format, data, and options for each
       of the APEX input files.
   •   Chapter 5, Output Files—Provides a description of the format and data associated with
       each of the APEX output files.

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CHAPTER 2.   INSTALLING APEX
APEX is written in Fortran 90 using only standard Fortran 90 routines and conventions to allow
portability to different operating systems and compilers.  APEX has been tested on Windows XP,
2000, NT, and 98 operating systems as well as Linux.

In addition to providing flexibility in modeling options, the APEX code is specifically designed
for fast execution time and reasonable memory requirements.

We recommend running APEX on a computer with at least:

   •   512 MB of RAM;
   •   600 MHz processor; and
   •   1000 MB of available hard drive space.

The input files supplied with APEX will require 320 MB of hard drive space, and the additional
input files created by the user may take up another 1-10 MB of space.

APEX run time on a PC with a 3.6 GHz Pentium 4 CPU and 2 GB of RAM, running Windows
XP, is 6 hours for a one-year single-pollutant simulation of 100,000 individuals in a large
metropolitan area. The combined size of the output files from this simulation is 150 MB, unless
detailed hourly data are requested, in which case the output files can take up more than 5,000
MB.

To install APEX, download the APEX executable and the input database files from
http ://www. epa. gov/ttn/fera. These files can be placed in directories of the user's choice. No
installation procedure is required unless APEX is to be run in the MIMS framework
(http://www.epa.gov/ttn/fera/mims_download.html). At this time APEX Version 4 can not be
run in MIMS.

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CHAPTER 3.  SETTING UP AND RUNNING APEX

This chapter, which describes the steps involved in setting up and running an APEX simulation,
is organized as follows:

Section 3.1   Setting Up an APEX Simulation
Section 3.2   Overview of APEX Input and Output Files
Section 3.3   Overview of Model Settings and Options
Section 3.4   Running APEX in Batch Mode
3.1  Setting Up an APEX Simulation

This section describes the steps involved in performing an APEX simulation.

1.    Select Model Options
After identifying the scope of the analysis, the user must decide which options to select.  To
determine the appropriate options for the application, the user must answer questions such as the
following.

•     How many pollutants do I want to model in a single run?
•     Do I want to model worker commuting?
•     How many profiles (or what percentage of the population) do I want to model?
•     How many microenvironments do I want to model?
•     How should I define my microenvironments?
•     How should I select the activity diaries (i.e. do I randomly select a new diary every day
      for each simulated individual, or do I construct longitudinal diaries based on diary
      properties?)
•     Which model settings should I  select (e.g., model Daylight Savings Time? use air quality
      controls, or "rollbacks"?)
•     What types of outputs do I want from the model?
•     What time resolution do I want to use?

These options and others are described in more detail in Section 3.5.

2.    Prepare Input Files
After deciding which model options to use and how to configure them, the next step in
configuring an APEX simulation is to  set up the input data files with the necessary data.  One of
these files, the Simulation Control file, is used to specify input and output file names and
locations and the  simulation settings.  The remaining files contain the input data necessary to run
APEX. The data  contained in these remaining files varies depending on the configuration of the

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scenario to be modeled and the number of pollutants used. The input files are described in
Chapter 4.

3.    Configure the Simulation Settings
The final step in preparing an APEX simulation is to create the Simulation Control input file for
the desired simulation settings. This file contains four sections:

•      Input file names and locations;
•      Output file names and locations;
•      Pollutant parameters (including output table specifications); and
•      Job parameters.

A detailed description of the data for each of the sections of the Simulation Control file is
provided in Chapter 4.

4.    Running APEX
To perform an APEX simulation the user can run the model via one of the methods described in
Section 3.4.

3.2  Overview of Input and Output Files

This section provides a brief overview of the input and output files associated with APEX.  (For
more detailed descriptions of the input and output files, refer to Chapters 4 and 5, respectively.)
All of the input and output files used by APEX are ASCII text files; they can be read and/or
modified by the user using a text editor or other software. Note, however, that certain files, such
as the commuting input file  and the hourly and events output files, may be very large (over 100
megabytes) and difficult for some text editors to handle.

3.2.1   Input Files

There are 20 types of APEX input data files. Most of these files are required; however, the
Diary Statistics and Prevalence files are optional in some cases. With the exception of the
Population Data and the Air Quality Data files, there is only one file of each type required for a
simulation. The input file paths and names are designated in the Simulation Control file, using a
"keyword" approach.  APEX processes the file and searches for particular keywords followed by
an equal sign and one or more values for the keyword. Table 3-1 lists each file type and the
keyword  that must be used to identify it. (Chapter 4 provides a detailed description of the
approach and its syntax.)

The APEX input files are described  in detail in Chapter 4.
3.2.2   Output Files

There are a total of 9 possible APEX output file types.  These files contain such information as
(1) a summary of the properties of the simulated persons, (2) hourly or event-level exposures,

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doses, and breathing data for the simulated profiles, (3) hourly or daily values of
microenvironmental parameters and pollutant concentrations, (4) dose and exposure summary
tables for the modeled population, and (5) exposure statistics for the modeled
microenvironments. The creation of some of the output files is dependent on settings in the
Simulation Control file, which also contains the path and file name for each output file. Table
3-1 lists each of the output data files and their corresponding keywords. If an output file is
specified with the same name and location as an existing file, the old files are overwritten.
Therefore, if the user wishes to conduct a series of model runs, the output files for each run
should be named differently or the output should be moved elsewhere before the next model run
is submitted.

The APEX output files are covered in detail in Chapter 5.

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Table 3-1.  APEX Input and Output Files
File
Input Files
Simulation Control File
Population Data Files
Employment Probability File
Commuting Flow File
Population Sector Location File
Air District Location File
Air Quality Data File
Meteorology Zone Location File
Meteorology Data File
MET Mapping File
MET Distribution File
Physiological Parameters File
Ventilation File
Microenvironment Mapping (MEMap) File
Diary Questionnaire (DiaryQuest) File
Diary Events (Diaryevents) File
Diary Statistics (Diarystat) File
Profile Functions File
Microenvironment Descriptions File
Prevalence File
Ow/'pwf Fifes
Zog File
Hourly File
Da//y File
Microenvironment Results File
Profile Summary (Persons) File
Microenvironment Summary File
Output Tables File
Stes File
Events File
Timestep File
Pollutant
Specific?







YES

















YES

YES
YES



Simulation Control
File Keyword

_
JW
EMPLOY
COMMUT
SECTOR
DISTRICT
QUALITY
ZONE
METEOR
METSMAP
DISTRIB
PHYSIOL
VENTIL
MEMAP
DIARYQUEST
DIARYEVE
DIARYSTA
FUNCTIONS
MICROENV
PREV

LOG
HOUR
DAILY
MICRORES
PSUM
MICROSUM
TABLE
SITE
EVENT
TIMESTEP

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3.3  Overview of Model Settings and Options

This section briefly describes the primary settings and options available in APEX. These are
specified by the user in the Simulation Control file or other input files. There are five general
categories of settings and options in APEX:

•         General Model Settings and Options;
•         Study Area Location;
•         Pollutants;
•         Profiles;
•         Microenvironments; and
•         Outputs.

Table 3-2 describes the settings and options in each of these categories, how they are selected or
changed, and the impact  of changing a setting or option on the other input files. See Chapter 4
for additional details of input files and their content, how to edit or create them, and how they
interact with other files.

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Table 3-2. APEX Settings and Options
SETTING/OPTION
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
GENERAL MODEL SETTINGS AND OPTIONS
Simulation start/end
dates
Adjust for Daylight
Saving Time (DST)
Model worker
commuting

Air quality rollback
adjustment (for
estimating exposure in
hypothetical control
scenarios)
Time resolution (length
of APEX timestep)
Specified in YYYYMMDD format (e.g., 19960704 is July 4, 1996) using the
Start Date and End Date keywords in the Control file. The user must
define the appropriate start and end dates for an application.
Specified using the DSTAdjust keyword in the Control file. If this parameter
is set to "YES", then the Air Quality Data file will be adjusted for DST in the
summer; if it is set to "NO", no adjustment is made. This keyword should be
set to "YES" if the Air Quality Data file is based on Standard Time yet the
activity data are based on DST.
Specified using the Commuting keyword in the Control file. If this keyword
is set to "YES", commuting to work is allowed and the user must provide a
Commuting Flow file in the appropriate format and employment data must be
specified in the Employment Probabilities file; if it is set to "NO", all workers
are assumed to work at home and the user is not required to provide a
Commuting Flow file. The Commuting Flow file accompanying APEX
contains commuting flows between all census tracts from the 2000 Census.
These commuting data are sufficient for all applications in which the sectors
are defined as census tracts.

Specified using the Rollback keyword in the Control file. If this keyword is
set to "YES", the user must specify appropriate values for the RBTarget,
RBBackgnd, and RBMax keywords in the Control file; if it is set to "NO",
values are not required for these keywords (and any present will be ignored).
Specified using the TimestepsPerDay keyword in the Control file.
The timestep can be either smaller or larger than an hour. However if the
timestep is larger than an hour, it must be an integer multiple of an hour. If it
is smaller than an hour, there must be an integer number of timesteps in an
hour. The default APEX timestep is one hour. If TimestepsPerDay is not set,
then APEX uses the default.
The indicated start and end dates must be included in the date ranges included
in the Air district Location, Meteorology Zone Location, Meteorology Data,
and Air Quality Data files. These files may contain additional data before
and/or after the start and end dates, but must contain data for the entire period
between the specified start and end dates.
Changing this setting means that the Air Quality Data file is based on DST (it
typically is in Standard Time) or that the activity data are based on Standard
Time (the supplied CHAD data are based on DST). Regardless of this
setting, the output (hourly exposure and dose) for all simulated days will
contain exactly 24 hours, and all input activity diaries must contain exactly 24
hours.
If the user chooses to define sectors as something other census tracts, a new
Commuting Flow file (in addition to a number of other input files) must be
created corresponding to the new sectors.

If the Rollback keyword is changed to "YES" in the Control file
accompanying APEX, the RBTarget, RBBackgnd, and RBMax keywords
must be set to appropriate values.
The timestep dictates the required time resolution of the following air quality
input. The time resolution of the Air Quality Data file must match that
indicated by TimestepsPerDay.
STUDY AREA LOCATION
Center of study area
Radius of study area
Specified as the latitude and longitude of the center of the study area in
decimal degrees using the Latitude and Longitude keywords in the Control
file. The user must always define the appropriate study area center for an
application.
Specified as the distance (in km) from the center to the edge of the study area
using the CityRadius keyword in the Control file. The user must always
If the study area is changed, the user must ensure that the following files
contain appropriate data for the new location: Population sector location file
(unless the included file is used), Air district Location file, Meteorology Zone
Location file, Meteorology Data file, and Air Quality Data file.
If the study area is changed, the user must ensure that the following files
contain appropriate data for the new location: Population sector location file
                10

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SETTING/OPTION

Restrict study area to
selected counties
Restrict study area to
selected census tracts
Locations of sectors
Locations of air districts
Radius of air district
Type of Air Quality
Data
Location of
meteorological data
stations
How Option is Selected
define the appropriate study area radius for an application.
Specified using the CountyList keyword in the Control file. If the value of
this keyword is set to "YES", the user must list the FIPS code (or other
relevant portion of the sector ID if the supplied sector files are not used) for
the counties to which the study area will be restricted using the County
keyword in the Control file. The county IDs for all census tracts in the 2000
Census are included in the Population sector location file accompanying
APEX, thus allowing the user to select counties in the Control file without
making changes to the included Population sector location file.
Specified using the TractList key word in the Control file. If the value of this
keyword is set to "YES", the user must list the sector (tract) ID for the tracts
to which the study area will be restricted using the Tract keyword in the
Control file. The sector IDs for all census tracts in the 2000 Census are
included in the Population sector location file accompanying APEX.
Specified as sector IDs and locations (latitude and longitude) in the
Population sector location file. The Population sector location file
accompanying APEX use the census tracts from the 2000 Census as sectors.
This file also specifies the county associated with each sector (via the first
five characters of the sector ID, which are the county FIPS codes in the
supplied data), which allows the user to restrict the study area to selected
counties. In most cases, the user will not need to change this setting as it
provides sectors with the necessary population and commuting data for the
entire United States.
Specified in the Air district Location file. The user must always define the
appropriate air districts for an application.
Using the AirRadius keyword in the Control file, the user can specify the
maximum distance (in km) that a sector can be from the nearest air district to
remain in the study. If all district centers are further than AirRadius from the
sector center, the sector is removed from the study area and is not modeled.
Users must always define an appropriate value for this radius based on their
application.
The key word ModelAQ Var specifies the type of air quality data to be used in
the simulation. The air quality may be entered as raw values for each timestep
in the simulation (the default, ModelAQVar=N) or as distributions for each
hour (ModelAQVar=Y).
Specified as zone IDs and locations (latitude and longitude) in the
Meteorology Zone Location file. The user must always define the locations
of meteorological stations for an application.
Impact of Changing Default Setting
on Other Input Files
(unless the included file is used), Air district Location file, Meteorology Zone
Location file, Meteorology Data file, and Air Quality Data file.
None, normally. However, if the user does not use the included Population
sector location file, they must ensure that the new Population sector location
file provides the county ID for each sector as part of the sector ID in the
appropriate format.

Sectors identified in Population sector location file must match the sectors
identified in Population Data files. If the user wishes to use census tracts
from the 2000 Census, the Population sector location file accompanying
APEX will be sufficient. All of the sectors used in the commuting file must
be included in the Population sector location file and the Population Data
files; if sectors other than 2000 Census tracts are used, the user must provide a
Commuting file compatible with these sectors. In addition, if the user wants
to restrict the study area to selected counties, the Population sector location
file must include the county IDs associated with sector as part of the sector
IDs in the proper format (as in the supplied file).
The locations of the air districts must be selected such that they can provide
reasonable estimates of air quality for the sectors and study period included in
the analysis. Data for each AQ monitor for each pollutant in the simulation
must be provided in the Air Quality Data files (one for each pollutant).
The radius of the air districts must be selected such that they will include the
sectors the user would like to include in the analysis.
The value ofModelAQVar dictates the expected format of the Air Quality
Data file. See Section 4.5 for details.
Data for each meteorological data station specified in the Meteorology Zone
Location file must be provided in the Meteorology Data file.
11

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SETTING/OPTION
Radius of
meteorological station
coverage
How Option is Selected
Using the ZoneRadius keyword in the Control file, the user can specify the
maximum distance (in km) from a sector to the nearest meteorological
station. If all zone centers are further than ZoneRadius from the sector
center, the sector is removed from the study area and is not modeled. Users
must define an appropriate value for this radius based on their application.
Impact of Changing Default Setting
on Other Input Files
The radius of the zones must be selected such that they will include the
sectors the user would like to include in the analysis.
POLLUTANTS
Number of pollutants
Pollutant Names
Model dose for
pollutant
The number of different pollutants to be modeled must be specified using the
#Pollutants keyword
The user must specify each pollutant with the keyword Pollutant. The
pollutant name may contain only alphanumeric characters and the underscore
(" ") character, as it is used to generate filenames.
Specified using the DoDose keyword in the Control file. Pollutant-specific.
If this keyword is set to "YES", APEX will calculate dose for the pollutant; if
it is set to "NO", the dose calculations will be suppressed.

Must be followed in the Control file by the pollutant-specific parameters and
output table levels.
If DoDose is set to "YES" and CO is being modeled the user must specify the
correct values for the Altitude, COHBFact keywords in the Control file.
PROFILES
Number of profiles
Modeled populations
Profile function options
Employment status
Minimum and
maximum ages for
simulated profiles
Modeled age groups
Size of age window
Probabilities for
selecting diaries with
missing characteristics
Set to an integer using the ^Profiles keyword in the Control file. Users must
define an appropriate value for this keyword based on their application.
Specified in the Control file following the specification of the file names.
The user must provide a population file for each population to be modeled
and indicate the gender and race associated with the file. All gender/race
combinations without specified population files are assumed to have zero
populations. Users can select from the sets of available Population Data files
accompanying APEX (i.e., the national population files or the files specific to
the Houston example applications), or generate their own.
Specified in the Profile Functions file. The user must develop data relevant
to a particular application prior to performing an APEX simulation.
Specified in the Employment Probability file for implementation of
commuting. The file accompanying APEX should be sufficient for all
applications where sectors are defined as census tracts.
Specified using HheAgeMin andAgeMax keywords in the Control file.
Specified in the Population Data files. The files that accompany APEX
define the age groups as single years up to 99, and are sufficient for all
applications where sectors are defined as census tracts.
The AgeCutPct and Age2Probab keywords in the Control file are used to
specify the window around the assigned age of a profile from which activity
data can be selected.
Using the MissGender, MissEmpl, and MissAge keywords in the Control
file, the user can specify the probability that activity diary data with missing
gender, employment status, or age will selected.
None.
If the user wishes to model a subpopulation, the user must supply alternative
Population Data files with the appropriate counts.
None.
None.
None.
None.
None.
None.
12

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SETTING/OPTION
Type of diary assembly
Physiological
parameters for the
simulated population
Activity-specific energy
expenditures for the
simulated population
Modeling of disease
prevalence
How Option is Selected
Determined by the LongitDiary keyword. If YES, longitudinal dairy
assembly will be performed based on the statistic in the Diary Statistics file.
If NO, APEX will randomly select a new activity diary for each day in the
simulation.
Specified in the Physiological Parameters file. The default values in this file
are suitable for most APEX applications.
Specified in the MET Mapping and MET Distribution input files. The default
values in these files are suitable for most APEX applications.
Determined by the Disease keyword. If Disease is given a value (a string of
maximum length 12 characters containing the condition name, spaces
allowed) in the input file, APEX will then use data in the Prevalence file to
assign a YES/NO value to the physiological profile variable HI, and produce
output tables for the subpopulation of modeled persons with 111= YES.
Impact of Changing Default Setting
on Other Input Files
If LongitDiary is YES, then the Diary Statistics file must be designated in the
Control file, and the DiaryD and DiaryAutoC keywords must be set.
None.
None.
If Disease is given a value (a string of maximum length 12 characters
containing the condition name, spaces allowed) in the input file, then APEX
requires that a Prevalence file be designated as well.
MICROENVIRONMENTS
Maximum number of
microenvironments
Microenvironment
definitions
Set to an integer using the #Micro keyword in the Control file; must not
exceed 127.
Specified in the Microenvironment Descriptions file. The user must develop
data relevant to a particular application prior to performing an APEX
simulation.
Number of APEX microenvironments in the Microenvironment Mapping and
Microenvironment Descriptions files must not exceed the specified value in
the Control file.
Each location referenced in the activity database (e.g., CHAD) must be
mapped to one of the microenvironments specified in the Microenvironment
Descriptions file using the Microenvironment Mapping file. The user may
choose to define custom microenvironmental parameter definitions that
depend on conditional variables. If so, these variables must be defined on the
Profile Functions file.
OUTPUTS
Produce hourly outputs
Produce daily outputs
Produce
microenvironmental
output
Produce event output
Specified using the HourlyOut keyword in the Control file. If this keyword
is set to "YES", the hourly output file is created; if it is set to "NO", the file is
not created. The variables to be written are listed using the keyword
HOURLYLIST.
Specified using the DailyOut keyword in the Control file. If this keyword is
set to "YES", the hourly output file is created; if it is set to "NO", the file is
not created. The variables to be written are listed using the keyword
DAILYLIST.
Specified using the MSutnOut and MResOut keywords in the Control file. If
these keywords are set to "YES", the Microenvironmental Summary and/or
Microenvironmental Results output files are created; if they set to "NO",
these files are not created.
Specified using the EventsOut keyword in the Control file. If this keyword is
set to "YES", the events output file is created; if it is set to "NO", this file is
not created.
None.
None.
None.
None.
13

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3.4  Running APEX in Batch Mode

The compiled code of the APEX model is stored as an executable file. In general, running the
model requires calling this executable and specifying a valid APEX Simulation Control file. The
Simulation Control file (which we also refer to as the Control file) is a text file that acts as a
"master" APEX input file. It contains the locations of all the required APEX input and output
files, as well as the model settings, and is described in detail in the next Chapter.

There are several methods of invoking the APEX program.  These include:

•      Typing the path and file name of the APEX executable at the prompt in a DOS window,
      followed by the path and name of the Control file. For example:

       C:\APEX4\apex4.exe C :\APEX4\Input\SimControl.txt

       If the Control file name is omitted from this command, APEX will prompt the user for
       the "Unit(lO)" file, at which time the user would input the location (path) and name of
       the Control file.  APEX calls the Control file "Unit(lO)" internally, which is the
       indication given at the prompt. If any other unit number is requested, then that means
       that one of the other input files (which are designated in the Control file) cannot be found
       (see Table 3-1 to identify which file), and the user should consult the instructions on
       input files in Chapter 4 of this guide.

•      Double-clicking on the APEX executable in Explorer. APEX will prompt the user for the
       "Unit(lO)"  file, at which time the user would input the location and name of the Control
       file.

•      Selecting "Run" from the  Windows  "Start" menu and entering the path and filename for
       the .exe file and  the Control file. Once again, if the Control file name is omitted from
       this command, APEX will prompt the user.

•      Batch mode, described below.

The preferred way to run APEX is in batch mode, meaning that the model's executable (.exe)
and Control files are specified in a single user-created text file (referred to as a "batch" file) that
is submitted to the operating system for job  execution. With this method, multiple APEX runs
may be performed  at once. To run APEX in batch mode, the user must complete the following
steps.

1.      Create the APEX batch file

To create an APEX batch file, open a new file in a text editor. On each line of this file, enter the
file path and name of the APEX executable  followed by  a space and the file path and name of a
unique Control file. An example  is given in Exhibit 4-1.  The commands shown in Exhibit 4-1
perform five APEX runs in series. In this manner, multiple runs using different model settings
                                          14

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can be started by running the batch file. Note that each of the Control files used should contain
unique names for the model output files to avoid overwriting the output from the previous run.
See Chapter 4 for information on designating output file names in the Control file.  After
entering the information, save the file. The file can be named anything, provided it ends with the
extension ".bat" (e.g., APEXbatch.bat).
             APEXbatch.bat - Notepad
            File Edit Format View Help
Ji
             :\APEX\APEX4.exe c:\APEX\input\Parametersl.txt
             :\APEX\APEX4.exe c:\APEX\-input\Parameters2.txt
             :\APEX\APEX4.exe c:\APEX\input\Parameters3.txt
             :\APEX\APEX4. exe e:\APEX\input\Parameters4.txt
             :\APEX\APEX4.exe C:\APEX\1nput\Parameters5.txt
           UJ
             Exhibit 4-1. Starting a Number of APEX Jobs Using a Batch File


2.      Run the APEX batch file

APEX can be run using the batch file in any of the following ways.

•      Opening a DOS window and typing the batch file name (and path, if necessary)
•      Double-clicking on the batch file in Explorer
•      Selecting "Run" from the Windows Start menu and entering the file path and name of the
       batch file
•      Creating a shortcut to the batch file on the desktop by selecting the batch file in Explorer,
       right-clicking the mouse, and selecting "Create Shortcut" from the menu. A shortcut file
       will be created and this file can be dragged onto the desktop and optionally  renamed. To
       run APEX, double-click on this shortcut.

Except for the first method (a DOS window is already open), when APEX runs, a DOS window
appears. As the model run starts and then progresses, normal status messages will be printed to
the screen (see Exhibit 1-2),  in addition to any error or warning messages that may  arise from
incomplete or incorrect model  set-ups.

After the initialization of the run, APEX will begin progressing through the simulated profiles.
When the model run ends, APEX will stop, as shown in Exhibit 1-3.
                                            15

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 Simulation  start date =    19950101
 Simulation  end date   =    19951231
 Finished  ReadPopulation
 F in is he d  Re adEnplo yme n t
 Finished  GenerateProfiles
 Finished  GeneratePhysio logy
 Reading activity diary tt        1000
 Reading activity diary tt        2000
 Reading activity diary tt        3000
 Reading activity diary tt        4000
 Reading activity diary tt        5000
 Reading activity diary It        6000
 Reading activity diary tt        7000
 Reading activity diary tt        8000
 Reading activity diary tt        9000
 Reading activity diary tt       10000
 Reading activity diary tt       11000
 Reading activity diary tt       12000
 Reading activity diary tt       13000
 Reading activity diary tt       14000
 Reading activity diary tt       15000
 Reading activity diary tt       16000
 Diaries Discarded=        6793
 Pool sizes=       16175
 Finished  output for profile tt
  728294
  728658
     36141
     74638
    113892
    159710
    207746
    254202
    296423
    331133
    365358
    399993
    435016
    470612
    505427
    540340
    575812
    614773
 1   of
                 Exhibit 1-2. Screenshot of the Start of an APEX Run
  Finished output for  profile tt
  Finished output for  profile tt
  Finished output for  profile tt
  Finished output for  profile It
  Finished output for  profile tt
 Finished flPEX model run
 Press any key to continue_
 96  of
 97  of
 98  of
 99  of
100  of
           Exhibit 1-3. Screenshot of Successful Completion of an APEX Run
Even if an APEX simulation runs to completion (i.e., as shown in Exhibit 1-3), the user should
examine the APEX Log output file to confirm that the model behaved as expected. The Log file
contains information on the model settings, input parameter values, and input and output file
names. The file also contains a great deal of detailed information about the model run, including
(but not limited to) summaries of (1) the modeled profiles, (2) the final study area (including the
final sectors, air quality districts, and meteorology zones), (3) the simulated microenvironments.
The Log-file (which is discussed in Section 5.1) will also contain listing of any warning or error
messages that resulted from the run.
                                         16

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CHAPTER 4.   APEX INPUT FILES

This chapter provides the details necessary for creating and modifying the APEX input files.
The first section describes the general format and properties that pertain to all of the APEX input
files, while the remaining sections cover each input file in detail.

4.1  Input File Formats

The APEX input files and their descriptions are given in Table 4-1.  Some of the input files are
not required if certain features of the model are turned off.  For example, the Diary Statistics file
is not needed if longitudinal diary assembly is not being used, and the Commuting Flow file not
needed if commuting is not considered. These are noted in Table 4-1. All input files are ASCII
text files that can be edited using a text editor. Each input line of these files is categorized into
one of four types:

1.  Keyword (or variable or parameter) line: Keywords are used in the Simulation Control file to
   indicate to APEX where the input files are located and what values  should be assigned to
   certain variables. A keyword line always contains an "=" sign. The part of the line to the left
   of "=" is called the "keyword" and the part to the right is called the "value."  The keyword
   must start with a letter and must match the spelling sought by the program code, after which
   the keyword may contain other letters, blanks, or commas.  APEX uses the keyword to locate
   and set the input values.  The values may be character, logical, or numeric values, or file
   names.
2.  Numeric line: Any line beginning with a digit (0-9) is recognized as a numerical data line by
   APEX.  Non-digits may  appear later in a numeric line.
3.  Character line: A line that begins with a character but does not contain an "=" sign is
   recognized as a character data line.
4.  Comment line: Any blank lines and any lines beginning with "!" generally are regarded as
   comment lines by APEX and used only by the user to help document the input file data.
   However, comment lines should not be inserted in the middle of a block of data.  That is, if
   the computer code is expecting to read a long series of numbers without a break, then
   comments may break the flow.
The keywords and input values are not case sensitive, except as noted.  Also, each line on an
input file is processed independently by APEX. Continuation of data values across multiple
lines is not permitted unless specifically noted for a particular file. APEX uses "list" (or "free")
format for all input values. This means that the values or data do not have to be fixed in specific
positions on an input line. Multiple items on an input line can be separated by either a blank or
comma. The various site names and similar inputs should not contain internal blanks, as these
will be interpreted as delimiters between input fields. This does not apply to keyword lines, as
those lines have only two fields (separated by the "=" sign), so either or both sides may contain
internal blanks.
                                          17

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Table 4-1. APEX Input File Descriptions
Input File
Simulation Control
File
Population Data
Files
Employment
Probability File
Commuting Flow File
Population Sector
Location File
Air District Location
File
Meteorology Zone
Location File
Meteorology Data
File
Air Quality Data File
MET Mapping File
MET Distribution
File
Physiological
Parameters File
Description
Specifies the overall settings (or parameters) for an APEX simulation (i.e., input
file names, population data file names, output file names, job parameter settings,
and output table levels).
Contains information on the population (by age group) in each study sector.
Each race/gender combination has its own file.
Contains employment probabilities by age group, gender, and study sector.
Provides probabilities of a worker commuting to various destination census
tracts from any given home tract. This file is only required when worker
commuting is modeled (Commuting =Y).
Provides the IDs and locations (in degrees latitude and longitude) of sectors
(e.g., census tracts). The file is used along with the user-defined CityRadius
and other data to select the sectors within the modeled area.
Provides the site IDs and locations (degrees latitude and longitude) of air quality
monitoring or modeling locations. The file is used along with the user-defined
AirRadius to define the geographical area covered by the air quality data. The
air quality data from a monitoring or modeling location are used for the sectors
(e.g., census tracts) within its covered area. Start and end dates indicate the
dates during which the data for a particular location are valid.
Provides the site IDs and locations (degrees latitude and longitude) of the
meteorological stations. The file is used along with the user-defined
ZoneRadius to determine the area covered by the meteorological data. Start
and end dates indicate the dates during which the data for a particular location
are valid.
May contain temperature, wind, humidity, and precipitation data for the
meteorological stations and dates indicated in the Meteorology Zone Location
file. These data can be used to determine window positions, group activity
pattern pools, and microenvironmental parameters in APEX.
Provides the air quality data for the modeled pollutants for each air
monitoring/modeling location listed in the Air District Location file. The
required time resolution of the air quality data for each day depends on the
Control file setting TimestepsPerDay. Each file is pollutant specific, so there is
the same number of input files as pollutants in the simulation. An optional type
of air quality data may be used that includes distributions for hourly air quality
values, see Section 4.5 for details.
Maps each activity codes present in the Diary Events file to an APEX MET
distribution. (A MET value is a dimensionless ratio of the activity-dependent
energy expenditure rate to the basal or resting metabolic rate). The MET
distributions are defined by number in the MET Distribution File.
Provides distribution types and parameters for calculating the metabolic (MET)
value for each distribution number in the MET Mapping file. A MET value is a
dimensionless ratio of the activity-dependent energy expenditure rate to the
basal or resting energy expenditure (metabolic) rate.
Contains tables of age- and gender-specific physiological parameters.
                  18

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Input File
Ventilation File
Microenvironment
Mapping File
Diary Questionnaire
(DiaryQuest) File
Diary Events File
Diary Statistics File
Profile Functions
(Distributions) File
Microenvironment
Descriptions File
Prevalence File
Description
This file contains regression parameters used to estimate total ventilation VE
from MET.
Provides the mapping from activity location codes in the Diary Events file (e.g.,
from CF£AD) to user-defined microenvironments in the Microenvironment
Descriptions file.
Provides personal and other information (e.g., day type, gender, age, race,
occupation) relating to each 24 hour activity record from the original activity
database (e.g., CHAD).
Provides the 24 hour event descriptions (i.e., start time, duration, activity, and
location) for all the diary days in the original activity database (e.g., CF£AD).
This file contains the same list of diary IDs as the Diary Questionnaire file, in
the same order.
Contains the value of the key statistic for all CF£AD activity diaries. These data
are used in the longitudinal diary assembly algorithm. Statistics files are
included with APEX for outdoor time and time spent in vehicles. Users could
construct other statistics files from CF£AD. This file is not required if
longitudinal assembly is not being performed (LongitDiary = NO).
Contains user-defined functions for several model variables, which in turn can
be used by the model for a variety of purposes, including calculating
microenvironmental concentrations .
Contains the definitions of the microenvironments and the microenvironment
parameters used to determine the exposure concentrations in
microenvironments .
Contains prevalence rates (probabilities) for disease (or any other condition) for
different age/gender cohorts. This file is not required if the Control file variable
Disease is not set.
The following sections discuss the details of APEX input files and provide several examples.
Note that these example files in this and the next chapter are provided for illustration only.
These are provided for the purpose of highlighting various aspects and options of APEX. While
some of these examples are from the input files provided with the APEX Version 4 release, some
of them have been changed to demonstrate specific aspects and options of APEX. In addition,
most of these  examples are only portions of the necessary input files.  Thus, these example files
will not work as an actual set of input files. Users are encouraged to view the example input files
(which can be downloaded separately) for a complete set of input files.

4.2  Simulation Control File

The Simulation Control file (which we also refer to as the Control file) is APEX's master
simulation file. The Simulation Control file names input and output files, sets model parameters,
and controls formats of output files.  APEX only processes keyword lines in this file. Any other
types of input lines are ignored. However, the very first line of the file (even if it is a comment
beginning with !) is saved to be used as part of the header that is written to each output file for
audit trail purposes.  Therefore, it is helpful for this line to include information that describes or
identifies the simulation.
                                          19

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When creating the Control file, the following rules should be used:

•      The very first line of the file should identify the specific simulation (up to 224 characters
       in length);
•      Keywords (or parameter or variable names) are placed to the left of the equal sign in a
       keyword line;
•      Parameter values are to the right of the equal sign;
•      Lines may appear in any order after the first line, with the following exceptions:
       o  Lines using the County keyword, which must immediately follow the line with the
          CountyList keyword;
       o  Lines using the Tract keyword, which must immediately follow the line with the
          TractList keyword;
       o   Lines using pollutant-specific parameters or table levels, which must immediately
          follow the line with their corresponding Pollutant keyword.
•      Lines may be omitted if defaults are allowed and are acceptable;
•      Only one equal sign is allowed per keyword line;
•      Anything after an exclamation mark in a line is treated as a comment and ignored; and
•      Any unexpected line without an equal sign treated as a comment and is ignored.

It is useful to keep a copy of the Control file associated with each simulation to provide a record
of the input and output files and model settings associated with the simulation and to make it
easier to run the model again based on different input data.

We describe the control file in terms of four sections of the file:  input files, output files,
pollutant parameters (including output table levels), and job parameters. Organizing the Control
file in this manner is not required.  The details of each section are discussed below.

4.2.1   Input and Output File List Sections of the Simulation Control File

In the Input Files section of the Control file (Exhibit 4-1), the user needs to specify the names
and path names of all of the input files. The details on the content and format of these input files
are provided in the subsequent sections of this chapter.

The keywords for these files were  given in Table 3-1.  (The keyword may be longer than those
listed, as long as the listed keyword is contained within the text).  The keyword FILE must
appear (with a blank space before it) right after each of the file keywords and before the "=". If
any of these files are not found at the specified locations, then APEX will print an error listing
the file that is missing.

The Air Quality Data files are the  only input files that are pollutant-specific,  and thus there is one
file for each pollutant modeled. Each Air Quality file keyword must be followed by a comma
and the name of its corresponding  pollutant (the pollutant names must match the names given by
the Pollutant keyword in the simulation control file; see Section 4.2.2).  Exhibit 4-1 provides an
example of designating Air Quality Data files for a two-pollutant scenario (CO and ozone).
                                           20

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The example in Exhibit 4-1 has 10 population data files. The number of population files could
change, depending on how the user classifies the population. For example, the user could
provide two population files, for all females and all males.

For the population input files, the keywords Pop and File must appear at the beginning of the
keyword part of the keyword input line in the Control File, followed by a comma and Gender
and another comma and Race. Gender must be either male or female and it can be shortened to
M or F. If the population files provided with APEX are to be used, the Race must be White,
Black, Asian, NatAm, or Other.. If the user provides the population files, Race could be
different, however, the race name must have 5 or more  characters, with the first 5 characters of
each race being unique. For example, if one file each is given for all males and all females, Race
could be specified as AllRaces. It is necessary for Race to match the designation in the header of
the population files, or an error will result. Further information on population files is given in
Section 4.8.

It is not necessary to specify all genders and race combinations for APEX to run. However, the
model assumes that any missing gender/race combinations have zero population. A warning
message is returned if one gender for a race is present but the other is missing.

In the Output File section of the Control file (Exhibit 4-2), the user needs to specify the
keywords  (Table 3-1), names,  and paths for the output files.  If the user turns off the hourly file
creation, event file creation, or microenvironmental summary file creation, the corresponding
output files will not be generated, and file names do not need to be specified. The
Microenvironmental Summary, Microenvironmental Results, and Tables files are pollutant-
specific, and one of each of these files will be created for each pollutant. However, only one
filename for each type has to be defined in the Control file - output filenames for each pollutant
are constructed by appending the pollutant name (as defined using the Control file Pollutant
keyword) to the end of the filename base.  The details of the output files are further explained in
Chapters.
                                          21

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!  INPUT FILES
 Zones file
 Air Quality file,  ozone
 Air Quality file,  co
 Districts file
 Meteorology file
 Functions file
 Microenvironment  file
 MEMap file
 DiaryEvent file
 DiaryQuest file
 METSMap  file
 METS Distribution file
 DiaryStat file
 Physiology file
 Ventilation file
 Prevalence file
 i
 !  POPULATION INPUT FILES
 Pop file, Female,  Asian
 Pop file, Female,  Black
 Pop file, Female,  Natam
 Pop file, Female,  Other
 Pop file, Female,  White
 Pop file, Male,    Asian
 Pop file, Male,    Black
 Pop file, Male,    NatAm
 Pop file, Male,    Other
 Pop file, Male,    White
 Sectors file
 Employment file
 Commuting file	
C:\APEX\APEX\METsites.txt
C:\APEX\AirQuality_ozone.txt
C:\APEX\AirQuality_co.txt
C:\APEX\AQdistricts.txt
C:\APEX\METdata_h.txt
C:\APEX\ProfileFunctions.txt
C:\APEX\MicroDescriptions.txt
C:\APEX\ME_Mapping.txt
C:\APEX\CHADEvents.txt
C:\APEX\CHADQuest.txt
C:\APEX\CHADMap.txt
C:\APEX\MetsDists.txt
C:\APEX\CHADSTATSoutdoor.txt
C:\APEX\Physiology.txt
C:\APEX\Ventilation.txt
C:\APEX\Asthma.txt
C:\APEX\pop_fa.txt
C:\APEX\pop_fb.txt
C:\APEX\pop_fn.txt
C:\APEX\pop_fo.txt
C:\APEX\pop_fw.txt
C:\APEX\pop_ma.txt
C:\APEX\pop_mb.txt
C:\APEX\pop_mn.txt
C:\APEX\pop_mo.txt
C:\APEX\pop_mw.txt
C:\APEX\pop_geo.txt
C:\APEX\Employment.txt
C:\APEX\Commuting2000.txt
              Exhibit 4-1.  Input Files Section of Simulation Control File
!  OUTPUT FILES
  log file
  hourly file
  daily file
  events file
  persons file
  microsum file
  microres file
  tables file
  site file
C:\APEX\log.txt
C:\APEX\hours.txt
C:\APEX\days.txt
C:\APEX\events.txt
C:\APEX\psum.txt
C:\APEX\msum.txt
C:\APEX\mres.txt
C:\APEX\tables.txt
C:\APEX\sites.txt
              Exhibit 4-2. Output Files Section of Simulation Control File
4.2.2  Pollutant Parameters Section of the Simulation Control File

The Control file variables (keywords) Pollutant, DoDose, InputUnits, OutputUnits,
PPMFactor,  and #Sources, are pollutant-specific.  These parameters are described in Table 4-2.
                                       22

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^Pollutants must be equal to the number of different pollutants being modeled. It must precede
any Pollutant keywords. The Pollutant  keyword is used to 1) assign a name to each pollutant
being modeled and 2) designate the start of the definition of the pollutant-specific variables.
Thus, the Pollutant keyword must immediately precede the definition of the variables for a given
pollutant. The pollutant name may be up to 40 alphanumeric characters long, and may also
contain an underscore ("_") character. When modeling PM, each discrete size of PM must be
modeled as a separate pollutant. All PM pollutants must start with the characters "PM." The Size
and Density parameters must be defined for these pollutants.

                         Table 4-2. Pollutant Job Parameters
Keyword
^Pollutants
Pollutant
InputUnits
OutputUnits
#Sources
PPMFactor
DoDose
Size
Density
Type
(length)
Integer
Char(40)
Char(40)
Char(40)
Integer
Real
Char(l)
Real
Real
Description
The number of pollutants in the simulation. Any number of pollutants may be
modeled - the maximum is limited only by the available system memory.
Pollutant name. There must be one Pollutant statement for each pollutant modeled,
which must be immediately followed by the other pollutant-specific job parameters
and table levels. If the pollutant is a particle, then the pollutant name must start with
the characters "PM".
Pollutant concentration units used for the input data for the pollutant (ppm or
ug/m3).
Pollutant concentration units used for the output data for the pollutant (ppm or
ug/m3).
Largest number of sources in any one microenvironment for the pollutant Any
number of sources may be modeled - the maximum is limited only by the available
system memory.
Units conversion factor, the number of ug/m3 that equate to 1 ppm. For CO,
ppmfact = 1,145 (i.e., 1 ppm = 1,145 ug/m3). It is used when source strengths are
expressed in micrograms per hour, but concentrations are in parts per million
(ppm), and when InUnits and OutUnits are in different units.
Y = perform dose calculations, N = don't perform calculations. If this flag is NO,
the dose calculations will be turned off. This saves some job execution time if the
user does not need dose calculation.
Aerodynamic diameter (particle size) in micrometers for a particle pollutant. This
parameter is not required for gaseous pollutants.
Density (in g/cm3) of a particle pollutant
In the Pollutant Parameters section, the user also specifies the levels of each of the parameters
used in the creation of the output summary tables for each pollutant. These specification
parameters are Percentiles, TimeExp, DMIHExp, DMSHExp, TSExp, DMTSExp, DAvgExp,
SAvgExp, TimeDose, DMIHDose, DMSHDose, TSDose, DMTSDose, DAvgDose, and
SAvgDose. The table specifications for each pollutant must come after the corresponding
Pollutant keyword.  Each parameter is identified by a single keyword, and the values are a list of
numbers ordered from smallest to largest and  separated by commas. All the values are read as
real numbers, although the decimal points are optional if the values happen to be integers. Items
                                          23

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in each list must be separated by commas. Except for the Percentiles, all of these parameters are
used to bin exposures or doses into categories in order to create output tables.  Note that there is
always one more bin than there are number of values in the list, since the first bin is less than the
first value in the list and the last bin is greater than or equal to the last number in the list.  The
specific meanings of the parameters are explained in Table 4-3. Note that these parameters, with
the  exception of Percentiles, are optional; if they are omitted, then the corresponding table is
simply not written in the output file.  See Chapter 5 for more information on the APEX output
tables.
           Table 4-3. Output Parameter Levels in the Output Summary Table
Table
Parameter
Percentiles
Exposure Cut
points
Daily Max 1-
Hour
Exposure Cut
points
Daily Max 8-
Hour
Exposure Cut
points
Daily Max
Timestep
Exposure Cut
points
Timestep
Exposure Cut
points
Daily Average
Exposure Cut
points
Simulation
Average
Exposure Cut
points
Daily Max 1-
Hour Dose
Cut points
Keyword
PERCENTILES
TIMEEXP
DM1HEXP
DM8HEXP
DMTSEXP
TSEXP
DAVGEXP
SAVGEXP
DM1HDOSE
Data
Type
Real
Real
Real
Real
Real
Real
Real
Real
Real
Description
This parameter specifies the levels of percentiles of the exposed
population for exposure or dose in APEX output files. Values can
include up to one digit beyond the decimal point (e.g. the 99.5 or
99.9 percentile).
This parameter specifies the exposure cut points for summing time
spent at various exposure levels. The time is expressed in minutes
and is summed across all profiles. TimeExp is used in two tables.
(Exposure Tables Type 1 and 2; see discussion of Tables file in
Chapter 5)
This parameter specifies the daily maximum 1-hour exposure cut-
points for binning all the person-days in the simulation period.
(Note: 1-hour tables are not generated with the APEX timestep is
greater than one hour.)
This parameter specifies daily maximum 8-hour average exposure
cut-points for binning all the person days in the simulation period.
It is similar to DMIHExp except for the longer averaging time.
(Note: 8-hour tables are not generated with the APEX timestep is
greater than one hour.)
This parameter specifies daily maximum timestep exposure cut
points for binning all the person days in the simulation period. It is
similar to DMIHExp except that that the time period considered is
a timestep rather than an hour. (Note: If using the default timestep
of one hour, then only the hour tables are generated - the timestep
tables are not.)
This parameter timestep exposure cutpoints for counting multiple
exceedances of timestep levels over the simulation (Exposure table
type #9; see discussion of Tables file in Chapter 5)
This parameter specifies daily average exposure cut-points for
binning all the person-days in the simulation period.
This parameter specifies cut-points for average exposure over the
simulation period. The cut points are used to bin all simulated
persons created in a run.
This parameter specifies cut points in %COHb for Daily Maximum
1-Hour Dose. The cut points were used to bin all the person-days
in the simulation period.
                                           24

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 Table
 Parameter
   Keyword
 Data
 Type
                        Description
 Daily Max 8-
 Hour Dose
 Cut points
DM8HDOSE
Real
This parameter specifies cut points in %COHb for Daily Maximum
8-Hour Dose. The cut points were used to bin all the person-days
in the simulation period..	
 Daily Max
 Timestep
 Exposure Cut
 points
DMTSEXP
Real
This parameter specifies daily maximum timestep dose cut points
for binning all the person days in the simulation period. It is
similar to DMIHDose except that that the time period considered is
a timestep rather than an hour. (Note:  If using the default timestep
of one hour, then only the hour tables are generated - the timestep
tables are not.)	
 Timestep
 Exposure Cut
 points	
TSEXP
Real
This parameter timestep dose cutpoints for counting multiple
exceedances of timestep levels over the simulation (Dose table type
#5; see discussion of Tables file in Chapter 5)	
 Daily Max
 End-of-hour
 Dose Cut
 points
DMEHDOSE
Real
This parameter specifies cut points in %COHb for Daily Maximum
End-of-Hour Dose. The cut-points are used to bin all the
person/days in the simulation period. Note that DMEHDose uses
the instantaneous level at the end of each hour, whereas
DMIHDose uses the time-averaged level over each hour.  For CO,
These two statistics usually track each other fairly closely.  For
other pollutants, the end-of-hour dose is just the dose on the last
event of the hour.
 Hourly End-
 of-hour Dose
H EHDOSE
Real
Similar to DMEHDose, except that instead of using just the highest
single end-of-hour dose on each day, it collects results for all 24
end-of-hour doses on each day. As with the other keywords, the
values specified here refer to the cut points used for tabulating the
dose results.
 Daily Average
 Dose Cut
 points	
DAVGDOSE
Real
This parameter specifies cut points in dose for the Daily Average
Dose. The cut-points are used to bin all the person/days in the
simulation period.	
 Simulation
 Average Dose
 Cutpoints
SAVGDOSE
Real
This parameter specifies cut points in dose for the Average Dose
over the entire simulation. The cut-points are used to bin all the
persons (or profiles) created in the APEX run.	
 Dose Cut
 points

 Time Step
 Multiple
 Exceedance
 Cutpoints
TIMEDOSE
TSMULTI
Real
Real
This parameter specifies cut-points in dose for summing time spent
at various dose levels. Apart from the statistic, the tables resemble
the Time Exp tables.
This parameter lists the number of exceedances to use as cutpoints
in Exposure table type #9 and Dose table type #5 (multiple
exposure or dose exceedances of timestep values of the simulation;
see discussion of Tables file in Chapter 5). For example, if the user
may want to track the number of persons that have 1, 10, 50, and
100 exceedances of the levels indicated by TSExp and TSDose over
the course of the simulation.
The following example Control file excerpt shows an example pollutant parameters section for a
simulation of two pollutants: ozone and CO:
                                                 25

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!  POLLUTANT  PARAMETERS
 #Pollutants = 2

 Pollutant    = Ozone
 DoDose       = NO
 InputUnits   = ppm
 OutputUnits = ppm
 PPMFactor    = 1.
 #Sources     = 0
 Percentiles  = 10, 25,  50,  75,  90, 95, 99
 Percentiles  = 10, 25,  50,  75,  90, 95, 99
 TimeExp       = 0.01, 0.02,  0.03,  0.04, 0.05,  0.06,  0.07, 0.08
 DMIHExp       = 0.01, 0.02,  0.03,  0.04, 0.05,  0.06,  0.07, 0.08
 DMSHExp       = 0.01, 0.02,  0.03,  0.04, 0.05,  0.06,  0.07, 0.08
 DAvgExp       = 0.01, 0.02,  0.03,  0.04, 0.05,  0.06,  0.07, 0.08
 SAvgExp       = 0.01, 0.02,  0.03,  0.04, 0.05,  0.06,  0.07, 0.08
 AlertThresh  =0.16

 Pollutant    = CO
 DoDose       = YES
 InputUnits   = ppm
 OutputUnits = ppm
 PPMFactor    = 1145.0
 #Sources     = 1
 Percentiles  = 10, 25,  50,  75,  90, 95, 99
 TimeExp       = 2, 4, 6,  8,  10,  15, 20, 25,  30,  35,  40, 45,  50  ,  60
 DMIHExp       = 5, 10, 20,  30,  40,  50, 75
 DMSHExp       = 3, 6, 7,  8,  9,  10,  11, 12,  13,  14,  15, 18, 20,  25
 DAvgExp       = 2, 4, 5,  6,  7,  8,  9, 10, 11,  12,  14,  16, 18,  20
 SAvgExp       = 0.5, 1,  1.25,  1.5,  1.75, 2,  2.5,  3,  4, 5, 6,  8,  10
 DMIHDose      = 0.5, 1.0,  1.25,  1.5, 1.75,  2.0,  2.25,  2.5, 2.75,  3.0
 DMSHDose      = 0.5, 1.0,  1.25,  1.5, 1.75,  2.0,  2.25,  2.5, 2.75,  3.0
 DMEHDose      = 0.5, 1.0,  1.25,  1.5, 1.75,  2.0,  2.25,  2.5, 2.75,  3.0
 H_EHDose      = 0.5, 1.0,  1.25,  1.5, 1.75,  2.0,  2.25,  2.5, 2.75,  3.0
 DAvgDose      = 0.5, 0.75,  1.0,  1.25, 1.5,  1.75,  2.0,  2.25,  2.5,  2.75
 SAvgDose      = 0.4, 0.5,  0.6,  0.7, 0.8, 0.9,  1.0,  1.2, 1.4,  1.6,  1.8
 AlertThresh  = 100.
          Exhibit 4-3. Pollutant Parameters Section of Simulation Control File
4.2.3  Job Parameter Settings Section of the Simulation Control File

In the Job Parameter Settings section of the Control file, the user can specify a number of
different job parameters for APEX runs. Table 4-4 provides a description of the keyword, data
type, and uses of these job parameters.  As with Input and Output Files, the keyword is the part
of the Parameters input line that is necessary to allow APEX to identify the parameter.  Data
type is either integer, real, or character. Each character variable has a specified length:  input
values longer than allowed will be truncated to this length, and values shorter than allowed are
simply padded with blanks. In all cases in this section except County or Tract, if the same
keyword appears more than once, the last occurrence overwrites the others.  Exhibit 4-4 shows
an example of this section of the Control file.
                                        26

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When APEX runs, the values of all the job settings (including the default settings for parameters
not explicitly set) will be printed to the Log file.
               Table 4-4. Job Parameters in APEX Simulation Control File
Keyword
Simulation Parameters
{{Profiles
RandomSeed
End_Date
FirstProfile
Start_Date
TimeStepsPerDay
Study Area Parameters
Location
Latitude
Longitude
Type
(length)

Integer
Integer
Integer
Integer
Integer
Integer

Char(40)
Real
Real
Description

Number of profiles to simulate.
Seed>0 is user preset, Seed=0 gets seed from clock. If RandomSeed
is changed between runs (using 0 for both runs or using two different
non-zero numbers), two separate model runs of 100 profiles each
time will be equivalent to one model run of 200 profiles. If
RandomSeed is the same, the same 100 profiles will be generated
over again. Control of the random number seeds is an important part
of using APEX for sensitivity analysis. For example, when
performing multiple runs with slightly different inputs, it may be
convenient to sample the same set of profiles, activity diaries, and
microenvironmental concentrations, in order to prevent stochastic
differences between the runs from obscuring the differences due to
the changed input.
Simulation end date in YYYYMMDD format.
First profile number to simulate. For example, this can be used for
skipping to a particular person's profile when performing repeated
runs using RandomSeed.
Simulation start date in YYYYMMDD format (e.g., 19960704 for
July 4, 1996).
Number of timesteps in a day. This settings dictates the required time
resolution of the air quality input data, as well at the resolution of calculated
exposures and doses.
The timestep can be either smaller or larger than an hour. However if the
timestep is larger than an hour, it must be an integer multiple of an hour. If
it is smaller than an hour, there must be an integer number of timesteps in an
hour. Therefore, the following are allowable APEX timesteps: 1 hour, 2
hours, 6 hours, 5 minutes, 15 minutes. Examples of unacceptable timesteps
are 14 minutes, 1.25 hours, etc. The size of the timestep is controlled by a
new control file variable TimeStepsPerDay. Thus, to use an APEX
timestep of 5 minutes, use
TimeStepsPerDay = 288
This parameter is optional. The default APEX timestep is one hour. If
TimeStepsPerDay is not set, then APEX uses the default.

Study area location (for output labeling only; not used internally).
Latitude in decimal degrees for the center of the study area. Note
that latitude south of the equator is negative.
Longitude in decimal degrees for the center of study area. Note that
longitude west of the prime meridian is negative (e.g., in the United
States).
                                           27

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Altitude
DSTadjmt
CityRadius
Air Radius
ModelAQVar
ZoneRadius
County
CountyList
Tract
TractList
Scenario
Microenvironment
Parameters
#Micros
Commuting Parameters
Real
Char(l)
Real
Real
Char(l)
Real
Char(5)
Char(l)
String
Char(l)
Char(40)

Integer

Altitude of study area in feet. The altitude in feet is assumed
constant for the study area. It is used in the Coburn-Forster-Kane
(CFK) equation for determining blood COHb concentration. Only
necessary for when simulating CO dose.
Y = use Daylight Saving Time (DST) in summer, N = don't use
DST. In areas that use DST, one day per year (in April) is only 23
hours long and another (in October) is 25 hours long. However,
most air quality data sets are reported in Standard Time throughout
the year. HDSTadjust is set to Y, the first and last days of summer
time (using different rules before 1986) are determined, and the
concentration from 2-3 a.m. on the short day is duplicated, while the
concentration from 2-3 a.m. on the long day is deleted. Regardless
of this setting, the output (hourly exposure and dose) for all
simulated days will contain exactly 24 hours, and all input activity
diaries must contain exactly 24 hours.
Radius of study area in km. The population sectors (e.g., census
tracts) with centers (or representative locations) within this radius
will be automatically selected for modeling.
Maximum representative radius (km) of air quality data collected at
an air monitoring station or modeled at that location. Air quality
data can be applied to the sectors within this radius.
Dictates the expected format of the Air Quality Data file. N
(Default) = APEX expects raw AQ data for each timestep.
Y=APEX expects AQ distributions for each hour of the simulation.
Maximum representative radius (km) of temperature data collected
at a weather station.
FIPS code for listed county (or other relevant portion of the sector
ID if the supplied sector files are not used). County is used only if
Countylist=Y . Repeat this line for each additional county code.
Y = the study area is composed of sectors in the listed counties (next
variable) and within CityRadius; N = the study area is restricted to
sectors within the specified CityRadius only or defined with the
TractList. The default value is N. (May be used in conjunction with
TractList, final study area is union of tracts and counties listed).
Sector ID for a listed sector (usually census tract). Tract is used
only if Tractlist=Y. Repeat this line for each additional sector to be
used.
Y = the study area is composed of the sectors (usually census tracts)
listed using the Tract keyword which are within CityRadius; N = the
study area is restricted to sectors within the specified CityRadius
only or defined with the CountyList. The default value is N. (May
be used in conjunction with CountyList, final study area is union of
tracts and counties listed).
Scenario description (for output labeling only; not used internally).

Number of microenvironments defined in the Microenvironment
Mapping file and on the Microenvironment Descriptions file.

28

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Commuting
KeepLeavers
LeaverAdd
LeaverMult
Diary Selection Parameters
Age2Prob
AgeCutPCT
AgeMax
AgeMin
MissAge
MissEmpl
Char(l)
Char(l)
Real
Real

Real
Real
Integer
Integer
Real
Real
Y = allow a simulated profile (or person) to commute to a work
sector (or census tract), N = No commuting. If Y, a work sector
(e.g., census tract) is randomly selected for each simulated profile
based on the probabilities of work sectors a person may travel to
from a home sector. If N, then workers are assumed to work in their
home sector.
Y = the persons who commute outside of the study area will be
modeled. While a commuter is at a workplace outside the study
area, then the ambient concentration cannot be determined from any
air district. Instead, it is assumed to be related to the average
concentration overall air districts at the same point in time. Calling
this average Cavg, the ambient concentration C for the person is:
C=LeaverMult*Cwg+LeaverAdd. If KeepLeavers = N, then these
individuals are not modeled.
Additive concentration term applied when working outside study
area (only used if KeepLeavers = yes).
Multiplicative factor for city -wide average concentration, applied
when working outside study area (only used if KeepLeavers = yes)

Diary probability factor for "shoulder" ages. This parameter allows
an optional shoulder window of ages outside the primary age
window. The shoulders have the same width in years as the main
age window, so in the example under AgeCutPCT the shoulders are
ages 20-29 and 51-60. The Age2Probab parameter operates like
MissAge, by suppressing the selection probability in the shoulders.
lfAge2Probab = 0 then shoulder ages are never selected.
Width of main age window (%). Each simulated profile (person) is
assigned a specific year of age. A window is created around this
target age, of size equal to AgeCutPCT percent of the target age. If
the target age is 40 and AgeCutPCT = 25, then the age window is
ten years wide (25% of 40) and diaries for persons from 30 to 50
years of age inclusive are permitted to be selected. The age window
is always at least 1 year wide.
Maximum age for simulated profiles (persons).
Minimum age for simulated profiles (persons).
Diary probability factor for missing age. Some of the supplied
CHAD diaries are for persons of unknown age. This factor operates
just like MissGender and MissEmpl to lower the selection
probability for such diaries.
Diary probability factor for missing employment. Some of the
supplied CHAD diaries are for persons of unknown employment
status. Like MissGender, this factor lowers the selection probability
for such diaries. If MissEmpl = 0, then such diaries will never be
selected.
29

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MissGender
Dose Parameters
COHbFactor
Location Parameters
#OtherDistricts
CustomWork
HomeProbab
SampleOth erLocs
Rollback Parameters
RbBack
RbMax
Rb Tar get
Rollback
Diagnostic Parameters
DebugLevel
Real

Real

Integer
Comma-
delimited
list of
CHAD
activity
codes
Real
Char(l)

Real
Real
Real
Char(l)

Integer
Diary probability factor for missing gender. Some of the supplied
CHAD diaries are for persons of unknown gender. All profiles are
assigned gender, however, and the CHAD diaries are selected from
those of the same gender or from the unknowns. MissGender is
used as a multiplicative factor to reduce the probability of selecting
diaries of unknown gender. lfMissGender=Q, then diaries with
missing gender will never be selected. lfMissGender=\, then such
diaries are equally likely to be selected as diaries of the correct
gender. MissGender can also be set to values between zero and one.
By setting MissGender to a non-zero value, you are essentially
telling APEX it is OK to use a diary with missing gender for
whatever profile you are generating. Allowing a small but nonzero
value for MissGender expands the pool size without permitting very
much chance of selecting a diary with missing gender.

Convergence parameter for COHb algorithm. This is a safety factor
that limits the permitted error in determining the solution to the CFK
equation. Larger factors mean greater accuracy but slower
evaluation. Numerical tests indicate that factors in the range of 2 - 3
are optimal for most purposes. Only necessary when simulating CO
dose.

Number of other districts to use in calculating the air quality for
diary events with location=O ("Other") when SampleOtherLocs is
used. (The probability of the person's home district being one of
these districts is given by HomeProbab)
List of CHAD activity codes that will be assigned to location = W
(Work).
Probability (0-1) of a person's home district being one of the
districts used to calculate the air quality for diary events with
location=O ("Other") when SampleOtherLocs is used.
If = Y, a random list of air districts will be selected for each person
for calculating the air quality for diary events with location=O
("Other"). The number of districts selected for each person is given
by #OtherDistricts, and the probability of the person's home district
being the list is given by HomeProbab.

Rollback background concentration. Use same units as InputUnits.
Rollback maximum concentration. Use same units as InputUnits.
Rollback target concentration. Use same units as InputUnits.
Y = use air quality rollback adjustments, N = don't use adjustments.
Rollback adjusts the ambient air quality data before the exposure
calculations occur. The purpose is to determine exposure in
hypothetical scenarios where the ambient concentrations have been
reduced by various controls.

A value > 0 results in more information being written to the log file
than for a value of zero.
30

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      Log File Switches
LogDistrict
Char(l)
Y = the name and location of each of the air districts will be written
to the Log file. Both a preliminary list (all the air districts in the Air
districts Locations file that are within the study area and have data
for the entire simulation period) and a final list (those required to
simulate the final list of study sectors) are printed.	
LogPopulation
Char(l)
Y = the following population information will be written to the Log
file for each study area sector: The total population of the sector
(TotalPop); the base population for the study (StudyPop), which will
be smaller than TotalPop if only certain age ranges are being
considered; the total population of workers in the sector (Workers);
the sector population of workers who work inside the study area
(Worklnside); and the final population (FinalPop) for the simulation,
which may be smaller than StudyPop if the workers who leave the
sector are excluded (if KeepLeavers=NO).	
LogProftles
Char(l)
Y = the following population information will be written to the Log
file for each study area sector: The total population of the sector
(TotalPop); the base population for the study (StudyPop), which will
be smaller than TotalPop if only certain age ranges are modeled; the
total number of workers in the modeled age range who live in the
sector (Workers); the population of these workers who work inside
the study area (Worklnside); and the final study population of the
sector (FinalPop), which may be smaller than StudyPop if the
commuters who leave the study area are not modeled (if
KeepLeavers=NO).	
LogSectors
Char(l)
Y = the name and location of each study sector will be written to the
Log file.  Both a preliminary list (all the sectors geographically
within the study area) and a final list (those sectors within the study
area having available air quality and temperature data) are printed.
LogTables
Char(l)
Y = all the tables that are written to the Tables file are also written to
the Log file.	
LogZones
Char(l)
Y = the name and location of each of the temperature zones will be
written to the Log file. Both a preliminary list (all the air districts in
the Temperature Zone Locations file that are within the study area
and have data for the entire simulation period) and a final list (those
required to simulate the final list of study sectors) are printed.	
  Output File Switches and
 	Keywords	
CustomSample
Comma-
separated
list of
integers
The profiles designated by CustomSample are written in addition to
the profiles specified by the EventSample variable. If both
EventsSample and CustomSample are set, then all the
EventsSample events are written as before and any additional
CustomSample events are written in the appropriate place in the
numerical profile order. Writing of CustomSample events is
dictated by  the value of the EventsOut variable, so no events will be
written ifEventsOut=~N, even if a CustomSample is specified. If
neither CustomSample nor EventSample is set, then events are
written as dictated by the default EventSample value (if EventsOut
= Y). If the user wishes to write only the CustomSample events,
then EventSample should be set to 0.	
DailyList
comma
or space-
separated
strings
List of keywords indicating which variables are to be written to the
Daily output file. See section 5.4 for details.

-------
DailyOut
EventSample
EventsOut
HourlyList
HourlyOut
MResHome
MResList
MResMicros
MResOut
MSumOut
PsumList
VaOutput
TimeStepOut
TimeStepList
Tables Parameters
ActivePAI
ChildMax
Char(l)
Integer
Char(l)
comma
or space-
separated
strings
Char(l)
Char(l)
comma
or space-
separated
strings
comma-
separated
list of
integers
Char(l)
Char(l)
comma
or space-
separated
strings
Char(l)
Char(l)
comma
or space-
separated
strings

Real
Integer
Y= the Daily output file containing values of daily parameters
(exposures, doses, etc.) is created. Otherwise it is not written.
Dictates which profiles have their event data written to the Events
file. If EventSample=K, then the data for every Kth profile is
written.
Y = the output file containing the event-level model outputs for each
simulated individuals is written. Otherwise, the file is not written.
List of keywords indicating which variables are to be written to the
Hourly output file. See section 5.2 for details.
Y= the Hourly output file containing values of hourly parameters
(exposures, doses, etc.) is created. Otherwise it is not written.
If =Y, then only values associated with "home" locations will be
written to the Microenvironmental Results file. Otherwise, values
will be written for "home", "work", and 'other" locations.
List of keywords indicating which variables are to be written to the
Microenvironmental Results output file. See section 5.6 for details.
A comma-separated list of integers that indicate the
microenvironments for which data will be written to the
Microenvironmental Results file.
Y = the Microenvironmental Results file will be created. Otherwise,
the file is not written.
Y = the Microenvironmental Summary file will be created.
Otherwise, the file is not written.
List of keywords indicating which variables are to be written to the
Profile Summary output file. See section 5.5 for details.
Y = the calculated alveolar ventilation rate will be written to the
events file. Otherwise the values are not output.
Y= the Timestep file will be created. Otherwise, the file is not
written. If the default timestep (1 hour) is used, then this file will
not be written because it will be identical to the Hourly file.
List of keywords indicating which variables are to be written to the
Timestep output file. See Section 5.3for details.

Threshold median daily PAI (MET) value for defining active
persons. Simulated individuals having median PAI equal to or
greater than this value over the simulation period will be included in
the "active persons" population subgroup in the output exposure
tables.
Maximum age for inclusion in the "child" and "active child"
population subgroups in the output exposure tables.
32

-------
ChildMin
HeavyEVRl
HeavyEVRS
HeavyEVRTS
ModEVRl
ModEVRS
ModEVRTS
Longitudinal Diary
Selection Parameters
DiaryAutoC
DiaryD
LongitDiary
Disease Parameters
Disease
Integer
Real
Real
Real
Real
Real
Real

Real
Real
Char(l)

Char(12)
Minimum age for inclusion in the "child" and "active child"
population subgroups in the output exposure tables.
This parameter sets the threshold for equivalent ventilation rate
defining one-hour heavy exertion. It is used in generating the APEX
output tables for one-hour exposures under heavy exertion.
This parameter sets the threshold for equivalent ventilation rate
defining eight-hour heavy exertion. It is used in generating the
APEX output tables for eight-hour exposures under heavy exertion.
This parameter sets the threshold for equivalent ventilation rate
defining timestep-level heavy exertion. It is used in generating the
APEX output tables for timestep exposures under heavy exertion.
Thus, this value should be dependent on the length of timestep used.
This parameter sets the threshold for equivalent ventilation rate
defining one-hour moderate exertion. It is used in generating the
APEX output tables for one-hour exposures under moderate
exertion.
This parameter sets the threshold for equivalent ventilation rate
defining eight-hour moderate exertion. It is used in generating the
APEX output tables for eight-hour exposures under moderate
exertion.
This parameter sets the threshold for equivalent ventilation rate
defining timestep-level moderate exertion. It is used in generating
the APEX output tables for timestep exposures under moderate
exertion. Thus, this value should be dependent on the length of
timestep used.

Lag-1 autocorrelation statistic for the longitudinal diary assembly
algorithm. Provides a target for the autocorrelation in the key diary
statistic.
Provides a target D statistic for the longitudinal diary assembly
algorithm. The D statistic reflects the relative importance of within
person variance and between person variance in the key diary
statistic.
Y = APEX will use the longitudinal diary assembly algorithm to
construct the activity diaries for the simulated persons, based on the
statistics in the DiaryStat file. In this case, DiaryAutoC, DiaryD,
and the name of the diary statistics file must all be designated in the
Control file. If LongitDiary = N, then a new diary will be randomly
selected each day (the default setting).

Provides the name of a condition or disease. If set, then APEX
expects the Prevalence file to be defined as well, and a
subpopulation of persons with the condition will be modeled,
resulting in exposure summary tables corresponding to the
subpopulation. The tables will be labeled using this variable; spaces
are allowed.
33

-------
i  	  PARAMETER SETTINGS 	
!  SIMULATION PARAMETERS
  #Profiles    = 40000
  RandomSeed  = 0
  Start_date  = 20040401
  End_date    = 20040930
i
!  STUDY AREA PARAMETERS
  Location    = Description of Location of the Study Area
  Latitude    =  33.7629
  Longitude    = -84.4004
  Altitude    = 150.
  DSTadjust    = YES
  CityRadius  = 100.
  AirRadius    =  25.
  ZoneRadius  = 100.
  CountyList  = YES
  County      = 01017
  County      = 13013
  County      = 13015
i
!  MICROENVIRONMENT PARAMETERS
  #Micros      = 12
i
!  COMMUTING  PARAMETERS
  Commuting    = YES
  KeepLeavers = YES
  LeaverMult  =0.0
  LeaverAdd    =0.0
i
!  DIARY SELECTION  PARAMETERS
  AgeMin      =  0
  AgeMax      =99
  ChildMin    =  5
  ChildMax    =18
  MissGender  =  0.0
  MissEmpl    =  0.0
  MissAge      =  0.0
  AgeCutPct    =20.0
  Age2Probab  =  0.05
i
!  DOSE  PARAMETERS
  COHbFact    =2.5
i
!LOCATION  PARAMETERS
 CustomWork    =
 SampleOtherLocs = YES
 #OtherDistricts = 2
 HomeProbab    = 0

!  ROLLBACK PARAMETERS
  Rollback    = NO
  RBtarget    =  5.0
  RBbackgnd    =  0.0
  RBmax       = 10.0
                                      34

-------
!  DIAGNOSTICS PARAMETERS
  DebugLevel  = 0
i
!  LOG FILE  SWITCHES
  LogDistrict = NO
  LogPopulate = NO
  LogProfiles = NO
  LogSectors  = NO
  LogTables   = NO
  LogZones     = NO
  VAOutput     = NO
i
!  OUTPUT  FILE SWITCHES AND  KEYWORDS
 EventsOut     = YES
 EventSample = 2
 CustomSample = 3092
 MResOut       = NO
 MSumOut       = NO
 HourlyOut     = NO
 DailyOut     = YES
 PSumList     = AVGEXP,MAXEXP,AVGEXP,MAXEXP
 HourlyList   = CONC1, AMB,  EXP,  EVR, VE,  VA,  EE, METS, EF
 DailyList     = MAX1DOSE  MAX8DOSE  MAX1FDOSE   AVGDOSE
 MResList     = VOL, AER, RR,  PRX, PEN,  CSUM,  AMB
 MResHome     = YES
 MResMicros   = 1,2,8,12
i
!  TABLES  PARAMETERS
  HeavyEVRl    =30
  HeavyEVRS    = 99
  ModEVRl      = 16
  ModEVRS      =13
  ActivePAI    = 1.76
i
!  LONGITUDINAL DIARY PARAMETERS
  LongitDiary  = YES
  DiaryAutoC   =0.19
  DiaryD	= 0.22	

          Exhibit 4-4. Job Parameters Sections of the Simulation Control File
4.3  Population Sector Location File

The Population Sector Location file provides the latitude and longitude of a representative
location such as the geographic center of all the sectors (e.g., census tracts) to be included in the
population data files.  Each line includes a Sector ID, Latitude, and Longitude. The sector ID
may be any string, numeric or character, and is stored as a character string (up to length 40). The
string may contain any characters except! or embedded spaces. The sector ID must match the
sector IDs in the Commuting Flow file (if worker commuting is being modeled). The ID is case-
sensitive, so the values in the two files must match exactly.
                                        35

-------
The population sector location file is used along with the user-specified CityRadius to
automatically select population sectors within the study area (after also addressing an optional
county test and ensuring suitable air district and meteorology zone data). APEX calculates the
distance between the location of a sector and the center of the study area and then compares it
with the CityRadius  Sectors with a distance from the study area center greater than the city
radius will not be included in the exposure assessment.

The tract-level population sector location file supplied with APEX contains the 11-digit ID and
latitudes and longitudes of the year 2000 U.S. Census tracts. APEX expects that the left-most
five characters of a sector ID will be the state and county FIPS code or the county-level code
used in the County list (if the study area will be limited in that way).

The latitude and longitude should be in  decimal degrees. At least three significant digits should
be provided after the decimal point to prevent significant rounding error. Note that the longitude
west of the prime meridian (e.g., United States locations) should be negative. Exhibit 4-5
provides an example of the first few records of this input file.
! Population census tract locations
! Tract ID
01001020100
01001020200
01001020300
01001020400
01001020500
01001020600
01001020700
01001020800
01001020900
Latitude
32
32
32
32
32
32
32
32
32
.470986
.466056
.474035
.466794
.454933
.439950
.438025
.502299
.644428
Longitude
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
-86.
487033
472934
457764
445569
425025
478442
443068
495082
501249
                Exhibit 4-5. First Part of Population Sector Location File
4.4   Air District Location File

The Air District Location file provides the Site ID, Latitude, Longitude, air data Start Date, and
air data End Date for all air quality (modeling or monitoring) sites included in the Air Quality
Data file (Section 4.5). The site ID may be any string, numeric or character, and is stored as a
character string (up to length 40), but must not contain an ! character or embedded spaces.
Latitude and longitude are in decimal degrees. The start and end dates are in YYYYMMDD
format (for example, 19951231 is December 31, 1995).  The IDs and order of the listed sites
must match those in the Air Quality Data file exactly (IDs are case-sensitive).  It is good practice
to insert a comment on the first line of the file to indicate the source or type of data used for air
quality. See Exhibit 4-6 for an example of the first few records of an Air District Location file.
                                           36

-------
! Hourly ozone air quality districts for
! This file contains the
! Created
0000100010
0000100009
0000100008
0000100007
0000100006
0000100005
0000100004
0000100003
0000200011
on
34
34
34
33
33
33
33
33
34
November
.371470 -
.194947 -
.018423 -
.841899 -
.665375 -
.488851 -
.312327 -
.135804 -
.547994 -
4,
85
85
85
85
85
85
85
85
85
an example metropolitan area
locations of 105 air quality districts
2005
.461103
.461103
.461103
.461103
.461103
.461103
.461103
.461103
.239577

20040301
20040301
20040301
20040301
20040301
20040301
20040301
20040301
20040301

20041031
20041031
20041031
20041031
20041031
20041031
20041031
20041031
20041031
               Exhibit 4-6. First Part of Example Air District Location File
APEX uses the Air District Location file to determine the "air district" or geographical area
represented by the ambient air quality data for a specified location. All pollutants use the same
air districts and thus there is only one file of this type. APEX first compares the start and end
dates for each air quality site with the start and end dates for the APEX exposure simulation.
Only the sites with air quality data covering the entire simulation period are accepted. If a site is
encountered with incomplete data, APEX prints a warning to the log file and stops execution.
Air quality data in the file before or after the simulation period are simply ignored.

APEX then calculates the distance of an air district location from the study area center and
compares it with the sum of CityRadius and AirRadius.  This allows air quality data to be used
from a nearby (and the nearest) air district even if the air district's location is outside the study
area. Only the sites with a distance less than this sum are retained for further calculations.

APEX then calculates the distances of a site from the locations of sectors (e.g., census tracts).
Sectors with distances less than AirRadius will be mapped to an air site. Based on this mapping,
APEX will use each set of air quality data in the Air Quality file only for the sectors within its
AirRadius. APEX assigns the sector to the nearest air district. Each sector is assigned to only
one air district. Sectors within the study area that lack a matching air district are not included in
the simulation.

Not all air districts on the air quality input file need sectors assigned to them.  Such air districts
are simply not included in the modeling. This feature allows the user to prepare an input file in
the simplest manner, perhaps containing more air districts than are necessary. For example, a
single input file could be prepared for all air districts in a given state.  This same input file could
then be run on several study areas in the state without having to alter the air quality input file.

Internally, APEX refers to air quality districts by a sequential index (district #1, #2, etc.) that is
assigned when the district-sector mapping is established. The Log file for the model run reports
the names and locations for each air quality district number.  Note that district #1 for a particular
study area might not always mean the same location on the ground for all model runs. For
example, if a series of runs for different years in Denver were performed, different monitors
might be online during different years, in which case district #1 might change meaning from year
to year. This can be avoided by preparing an Air Quality Data input file (see next Section) that
                                            37

-------
has complete data for all air quality districts for all years being modeled, in which case the
mappings should remain the same from year to year.

4.5  Air Quality Data File

This file provides air concentration data for air sites listed in the Air District Location file for a
given pollutant; there is one file of this type for each pollutant in the simulation. Only keyword
or numeric input lines are processed and other types of input lines are ignored in this file, with
the exception of the first line which (even if it is a comment) is always echoed to the header in
each output file.  Therefore, the first line should contain information describing the simulation
and pollutant.

There are two different types of AQ data files that may be used in APEX.  The first type of file
simple contains values of the air quality data for each air district for each timestep (for example,
hour) in the simulation. The second type of AQ data file contains distributions that allow for
person-to-person variability in the AQ data for each hour of the simulation. This type of file may
only be used when the APEX timestep is  1 hour.  APEX accepts raw AQ data (type 1) by
default, if a type 2 file is to be used the user must set the Control file flag ModelAQData =YES.

The formats of two types of files are described in detail below.

4.5.1   Raw AQ Input Data

This type of AQ file is the APEX default, and will be adequate in most cases.  Within this file the
data for each site begins with a header section containing the site ID or Name (see Exhibit 4-7).
Recall that these site IDs must match those in the Air District Location file exactly; the IDs are
case sensitive and must not contain an ! or embedded spaces.  The sites can be in any order in
this file.  APEX locates the air data set by matching a site  name in the Air district Location file
with the site name in this file.  There can be no missing data within the simulation period.

Each of the subsequent numeric records includes a list of Timestep Average Air Concentrations
followed by a Date  The date should be in YYYYMMDD format (e.g., 20010507 is May 7,
2001).  Air quality data should be in the units specified in  the Control file for the pollutant. The
data values can be either comma or space delimited. Note that the length of each data line in an
air quality file  should not exceed 5000 characters. Foe example, if the APEX timestep is one
hour, each numeric record will  list 24 hourly average concentration values, followed by a date.
If the APEX timestep is 5 minutes, then each line have 288 5-minute averages followed by the
date. An example of the beginning portion of this type of file is given in Exhibit 4-7.
                                           38

-------
! Ozone air quality data for an example metropolitan area
! For 105 air quality districts, for the period 03/01/04 to
! Created on November 4, 2005
Name = SiteOOOOlOOOOS
0.
0.
0.
0.
0.
01553
03822
00577
01456
03354
0.
0.
0.
0.
0.
01825
03738
00570
01828
03244
0.
0.
0.
0.
0.
02621
03749
00528
01916
02412
0.
0.
0.
0.
0.
02989
03754
00477
01810
01705
0.
0.
0.
0.
0.
02975
03687
00394
01547
01293
0.
0.
0.
0.
0.
02650
03550
00453
00925
01076
0.
0.
0.
0.
0.
02310 . . .
03240 ...
00430 . . .
00591 . . .
01066 . . .
10/31/04
0.
0.
0.
0.
0.
03891
00948
01169
03326
02849
20040301
20040302
20040303
20040304
20040305
        Exhibit 4-7. First Part of Example Air Quality Data File (Raw Data Type)
4.5.2   AQ Input Defined as Hourly Distributions

This type of AQ input data can be used to model person-to-person variability within an hour
within an AQ district. This type of data can only be used if the APEX timestep is equal to 1 hour
(TimestepsPerDay=24, the APEX default).

Within this file the data for each site begins with a header section containing the site ID or Name
(see Exhibit 4-7). Recall that these site IDs must match those in the Air District Location file
exactly; the IDs are case sensitive and must not contain an ! or embedded spaces. The sites can
be in any order in this file. APEX locates the air data set by matching a site name in the Air
district Location file with the site name in this file.  There can be no missing data within the
simulation period.

 In this type of AQ file, each numerical record begins with a date and an hour number, followed
by any APEX distribution definitions. See Table 3-1  and  Volume //for a discussion of available
probability distributions in APEX.  If this type of input is to be used, the Control file flag
ModelAQVar must be set to Y, otherwise an APEX error will result. An example of the first
part of an AQ Data file (distribution type) is shown below in Exhibit 4-8. In this example, the
AQ value for each hour is defined by a normal distribution. The ambient AQ value for the hour
for will be sampled from this distribution for each person in the Air Quality district.
!  Hourly ozone air quality distributions  for an example metropolitan area
!  This  file contains data for  127 air quality districts, for the  period 01/01/04 to 12/30/04
!  Created on February 26, 2008  for testinq new APEX code. KKI.
!  Format is Date  Hour DistributionDef
!  Where DistributionDef is any standard APEX distribution definition
Name =0000200006
!  Date    Hr Distribution
 20040101  1 Normal  0.01066    .00005  .   .  0
          2 Normal  0.01121    .00005  .   .  0
          3 Normal
          4 Normal
          5 Normal
          6 Normal
          7 Normal
         Exhibit 4-8. First Portion of an Air Quality Data file (Distribution Type).
                                            39

-------
4.6   Meteorology Zone Location File

The format and use of the Meteorology Zone Location file is analogous to the Air District
Location file. Each record represents one site, and contains five values: Site ID, Latitude,
Longitude, Start Date, and End Date.  Again, the Site ID may be any string up to 40 characters
long;  it cannot contain an ! or embedded spaces.  The IDs must match those in the Meteorology
Data  file exactly; the IDs are case sensitive.  The site selection process is also analogous to that
described above for the Air District Location file. The file is used to map the set of meteorology
data collected at a weather station to  sectors within its zone radius for exposure calculations.  An
example file is provided in Exhibit 4-9. Similar to air districts, zones within the sum of
CityRadius and ZoneRadius are used.  Study area sectors for which no meteorology data are
available are not included in the simulation.

APEX makes an internal list of meteorological zones that have sectors assigned to them and
assigns them sequential numbers for  convenience. This mapping is reported in the Log file,
which is output from each model run.
! Example APEX4 Meteorological Station Locations (Zones) File
! Created 11/4/05
03812
03813
03816
03820
03856
03870
03937
35.
32.
37.
33.
34.
34.
30.
4333
7000
0667
3667
6500
9000
1167
-82.
-83.
-88.
-81.
-86.
-82.
-93.
5333
6500
7667
9667
7667
2167
2167
20040101
20040101
20040101
20040101
20040101
20040101
20040101
20041231
20041231
20041231
20041231
20041231
20041231
20041231
            Exhibit 4-9. First Part of Example Meteorology Zone Location File
4.7   Meteorology Data File

This file provides hourly temperature and meteorological data for the sites listed in the
Meteorology Zone Location file. Only numeric input lines or lines containing the keyword
"name" followed by an equal sign are processed.  All other types of input lines are ignored.
The meteorology sites may be in any order in this file.  The section of data for each site must
begin with the "name" keyword input line. An example is shown in Exhibit 4-10. The site
names (site IDs) must match those in the Meteorology Zone Location file exactly; the IDs are
case sensitive and must not contain an ! or embedded spaces.

APEX matches a site name in the Meteorology Zone Location file with the data set site name to
locate its data in this file.  If desired, the user could add more comment lines in the header
section of a data set.

Temperatures can be used to assign activity diaries to days (via the profile function DiaryPools,
see Section 4.15), and any meteorological variable present in the file may be used as conditional
variables for microenvironment parameters  (see Section 4.15.2 and Volume IT).
                                           40

-------
The "site name" input line is followed by the meteorological data. Each data line may contain the
following data:
       Date (YYYYMMDD)
       Hour (1-24)
       Temperature (degrees Fahrenheit)
       Relative Humidity (percent)
       Precipitation (character code, see below)
       Wind speed (km per hour)
       Wind Direction (degrees from north)
The data do not have to be in fixed columns and may be separated by whitespace only.

The numerical data may be integer or real (decimal) - they are translated to integers when the
file is read.

The precipitation code may be any character string, up to 12 characters in length (no spaces),
although it is assumed that this code will be no more than 2 letters under normal circumstances.
(The codes used for precipitation must match those used in the Profile Functions file,  see Section
4.15).

Not all variables need to be defined in the file; only temperature is required. If a variable is to be
included, though, all variables before it on the data line must be defined. For example, if the user
wishes to include wind speed, then precipitation must exist in the file in order for it to be read
correctly. Note that this does not imply that the user must use precipitation in the model run (for
example, to set microparameter distributions, see Section 4.15). Therefore, a dummy  code could
be entered for precipitation in this case.

Each data set should cover the exposure simulation period.  A data set can include more days
than the exposure simulation period; APEX only uses the data within the simulation period.
Thus, the user may prepare a file with a full year or many years of data for each site and then use
the same meteorology file for a series of different simulation periods. There can be no missing
data within the simulation period.
! Hourly Meteorological Data
IDate Hr Temp Humidity
name=03812
20040101
20040101
20040101
20040101
20040101
20040101
name=03813
20040101
20040101

1
2
3
4
5
6

1
2

64.
64.
64.
65.
65.
65.

66.
67.

0000000
0509644
7050323
3338318
9261093
6765747

1480103
6218567

30
30
31
33
34
34

30
34

.0000019
.1274014
.7625809
.3345718
.8152771
.1914406

.3700294
.0546417
Free

RA
CL
RA
CL
CL
CL

CL
CL
Windspeed

12
12
15
18
21
20

12
20

.0000038
.2548046
.5251617
.6691437
.6305542
.3828812

.7400570
.1092834
Direction

180.
182.
215.
246.
276.
263.

187.
261.

0000458
5480499
2516174
6914520
3055420
8288269

4005737
0928345
                                           41

-------
20040101
20040101
20040101
20040101
3
4
5
6
67.
66.
66.
66.
6839142
9728241
3958359
9397125
34
32
30
32
.2097778
.4320602
.9895973
.3492851
CL
CL
CL
CL
20.
16.
13.
16.
4195595
8641205
9791956
6985664
264.
228.
199.
226.
1955872
6412048
7919617
9856720
                 Exhibit 4-10. Example Portion of Meteorology Data File
4.8   Population Data Files

Each Population Data file contains sector-level data for a single gender/race combination.  Ten
gender/race specific population data files for all year 2000 Census tracts have been prepared and
provided with the APEX release. However, user-defined population data files may be
constructed, if the format given below is followed.

The population files contain the  population counts for each sector contained in the Sector
Location file. In general, each population file is for a single race/gender combination, although
composite files containing more than one gender or race can be used.  The population counts are
given by age group. The age groups are designated in the first part of the file (the descriptor
records).

Four descriptor records must appear in each population file. These records must appear
immediately after any header comment records (which start with "!") and before the population
data records (i.e., the actual population counts). The data on these four records are read starting
to the right of the '=' sign, if present.  Text descriptors to the left of the '=' signs are optional.
The contents of these four records must be as follows:

       Descriptor record 1:  Gender, Race (5 characters), Number of population groups
       Descriptor record2:  Race  description (may contain blanks, up to 200 characters)
       Descriptor record 3:  Minimum age for each group
       Descriptor record 4:  Maximum age for each group

The fields in descriptor records 1, 3 and 4 are space-delimited.  Gender must be  "Female"
"Male" or "All".  The 5-character label for race also appears as a column header on the Profile
Summary output file. If the population files provided with APEX are to be used, the Race must
be White, Black, Asian, NatAm, or Other, which may be shortened to W, B, A, N, or O. If the
user provides the population files, Race could be different. For example, if one  file each is given
for all males and all females, Race could be specified as All. However, it is necessary for Race
to match the designation in the Control file, or a Fatal error will  result.

The race description is not used, but is echoed in the log file for the benefit of the user. Only the
shorter 5-character race label that is given on the first line is written to the other output files, to
save space.

The next two records specify the minimum and maximum ages for the age groups. The ages
must be delimited by a  single space. Note that all the population data files must contain the same
                                           42

-------
number of population groups, and furthermore, all the group age limits (minima and maxima)
must match as well, or APEX will exit with a Fatal error.  The population files provided with
APEX contain single-year age groups.

The actual population data follows the descriptors records. Each population record has the
Sector ID, (which must match the IDs in the Sector Locations file exactly, and thus can be any
alphanumeric string of 40 or fewer characters without embedded spaces or an !) followed by a
Count for each population age group (youngest first). The counts are the number of people in a
given age group living in the sector; they must be delimited by a single space. Each Population
Data file used in a model run must have a record for each sector listed in the  population Sector
Location file or a Fatal error will result.  The sectors do not necessarily have  to be in the same
order in every population file in order for APEX to run, however, a warning message will result
if APEX finds that the order of the sectors in any population file differs from the order of the
sector list. A single error message will be written for each population file having out-of-order
sectors, no matter how many differences are found. APEX will exit with a Fatal error message if
a sector in the final list of study area sectors cannot be found in a population  file.

Exhibit 4-11 provides an example of a portion of a Population Data file.
! Population file by census tract, extracted from 2000 census
! File prepared by ManTech Environmental Technology, Inc., Apr 2003
Gender, Race, #Ages = Female, Asian, 100
Race description
Age group minimum
Age group maximum
i
01001020100 000
01001020200 000
01001020300 000
01001020400 000
01001020500 020
01001020600 000
= Asian
=
=

0
0
0
0
1
0
0
0

0
0
0
0
1
0
1
1

0
0
0
0
0
0
2
2

0
0
0
0
1
0
or Pacific Islander
3
3

0
0
0
0
2
0
4
4

0
0
0
0
1
0
5
5

0
0
0
0
0
0
6
6

1
0
0
0
1
0
7
7

0
0
0
0
0
0
8
8

0
0
0
0
0
1
9
9

1
0
0
1
0
0
10 11
10 11

000
100
000
010
000
010
12
12

0 .
0 .
0 .
0 .
0 .
0 .
c
c

. . 0
. . 0
. . 0
. . 0
. . 0
. . 0
)8
)8

0
0
0
0
0
0
99
99







                    Exhibit 4-11.  First Part of a Population Data File
4.9   Commuting Flow File

This file provides cumulative fractions of the population in a home sector that commute to
different work sectors. An example portion of this file is provided in Exhibit 4-12.  Each section
of commuting data in the file contains a Home Sector and each of the corresponding Work
Sectors for the home sector. All sector IDs in this file must be exactly identical to those
contained in the Sector Location file (i.e., they are case sensitive and must not contain an ! or
embedded spaces). The first record of each section lists the Home Sector ID followed by a -1.
This -1 has no meaning; it is simply used by  APEX to recognize the beginning of a new data
section (i.e., a new home sector).  After the home sector record, each of the work sectors for that
home sector is listed. Each work sector record contains the Work Sector ID, a Cumulative
Fraction of the home sector population commuting to this work sector, and the Distance (km)
between the home sector and the work sector. (The distance is not used by the current release of
                                           43

-------
APEX and thus may be omitted if desired.)  The cumulative fraction for the last work sector in
each group should always be equal to 1.  APEX uses this file to determine which work sector a
simulated individual may commute to by using the cumulative fractions as commuting
probabilities.

The user can create their own commuting databases using the format given above, recalling that
the sectors in the commuting file must correspond to those in the Sector Location file.  For
example, if a user creates a Sector Location file that contains sectors corresponding to spatial
units smaller than census tracts, a corresponding Commuting Data file would have to be
constructed as well in order to model commuting.

If the sectors used in the simulation are year 2000 Census tracts, the commuting flow file
provided with APEX can be used.  This database contains all the year 2000 Census tracts and
their associated work tracts.  The mean number of associated work tracts per home tract is 79,
with a minimum of 1 and a maximum of 413.

!  APEX  U.S.  Tract-Level Commuting File from  2000 Census
!  Prepared  by Alion  Science  and Technology,  January  2005
!  ID  cumFrac km
01001020100 -1.00000  -1.0
01001020700 0.10412  5.5
01101000100 0.20097  19.6
01001020600 0.28814  3.5
01001020500 0.36804  6.1
01001020200 0.44068  1.4
01001020300 0.49153  2.8
01001020400 0.53632  3.9	

                  Exhibit 4-12. First Part of the Commuting Flow File
4.10 Employment Probability File

A nationwide employment probability file has been prepared for ages 16 and above, covering all
the tracts from the 2000 census.  Each record (tract) contains 26 probabilities (13 age groups
each for males and females).  The age groups in the provided file are for ages 16-19, 20-21, 22-
24, 25-29, 30-34, 35-44, 45-54, 55-59, 60-61, 62-64, 65-69, 70-74, and 75 and older.

The employment probability age groups do not have to match the population file age groups,
providing increased flexibility in the demographic inputs to APEX. Users may create their own
employment files, as long as the file format is followed.  The ages in the employment file may
extend beyond those in the population files, but be  aware that APEX will never generate a profile
outside of the ages in the Population Data files.

An example portion of the Employment Probability file is given in Exhibit 4-13.  The file
contains optional header lines, followed by three required lines. The first required line reports
the gender for each column of data, the second line reports the age group minimum, and the third
line reports  the age group maximum. Below that, each line starts with the  sector ID, followed by
a vector of decimal probabilities (one per column).  The first item on each  line below the header
                                         44

-------
lines is the sector ID, followed by the eight employment probabilities for that sector. Each
probability in the national file is calculated by dividing the number of employed persons by the
total sector population for the specified age range and gender.  Whenever the total sector
population for a particular age range and gender is zero, then obviously the employed persons
must also be zero.  These data are reported as zero probabilities in the file. It should not matter
what values are assigned, since no simulated persons of that type should ever be generated by the
model. Note that a custom employment probability file must be created if custom Population
Data files are used. That is, the sectors in the employment probability file must match those  in
the population files.

Note that any ages not covered by one of the employment age groups will automatically have an
employment probability of zero.  In the example below this would apply to persons younger than
age 16.
! Employment probability fractions by
! Prepared by
Gender=
MinAge=
MaxAge=
01001020100
01001020200
01001020300
01001020400
01001020500
01001020600
01001020700
01001020800
M
16
19
0.
0.
0.
0.
0.
0.
0.
0.
gender and age group from 2000 census
ManTech Environmental Technology, Inc.



39744
45283
55056
34921
57143
64583
38554
29712
M
20
21
1.
0.
0.
0.
0.
1.
0.
0.



00000
26415
82857
79310
88889
00000
48571
56757
M
22
24
0.
0.
1.
1.
1.
1.
0.
1.



32258
70588
00000
00000
00000
00000
91304
00000
M
25
29
0.
0.
0.
0.
0.
0.
0.
0.
. . .

. . .
83636 . . .
79167
95200 ...
91818
96503 . . .
87500 . . .
90698
79693 ...
for EPA
F
70
74
0.
0.
0.
0.
0.
0.
0.
0.



00000
00000
08475
19192
00000
08621
37500
00000
in April 2003
F
75
200
0.00000
0.12500
0.00000
0.00000
0.00000
0.00000
0.07692
0.03191
               Exhibit 4-13.  Excerpt from the Employment Probability File
4.11 MET Mapping File

This file maps each CHAD (or other database) activity code to an internal APEX distribution
number, for calculating the energy expended by a simulated person for each diary event. Energy
expenditures are used for estimating activity level and ventilation for each simulated person.
These quantities are used for used in creating tables of exposures at different exertion levels and
for estimating pollutant dose.  A MET value is a dimensionless ratio of the activity-dependent
energy expenditure rate to the basal or resting energy expenditure (metabolic) rate, and the
CHAD activity code is an identifier associated with each diary event that indicates the type of
activity being performed.  The current CHAD activity codes are  given in Table 4-5.
                            Table 4-5. CHAD Activity Codes
 Activity
 Code	Description
Activity
Code
Description
 10000   Work and other income producing
         activities, general

 10100   Work, General
 10110   Work, general, for organizational
13600   Obtain car services

13700   Other repairs
13800   Other services
14000   Personal needs and care, general
                                            45

-------
Activity
Code
Description
Activity
Code	Description
          activities
10111     Work for professional/union organizations
10112     Work for special interest identity
          organizations
10113     Work for political party and civic
          participation
10114     Work for volunteer/ helping organizations
10115     Work of/for religious groups
10116     Work for fraternal organizations
10117     Work for child/youth/family
          organizations
10118     Work for other organizations

10120     Work, income-related only
10130     Work, secondary (income-related)
10200     Unemployment
10300     Breaks
11000     General household activities

11100     Prepare food
11110     Prepare and clean-up food
11200     Indoor chores
11210     Clean-up food
11220     Clean house
11300     Outdoor chores
11310     Clean outdoors
11400     Care of clothes
11410     Wash clothes
11500     Build a fire
11600     Repair, general
11610     Repair of boat
11620     Paint home / room
11630     Repair / maintain car
11640     Home repairs
11650     Other repairs
11700     Care of plants
11800     Care for pets/animals
11900     Other household
12000     Child care, general
12100     Care of baby
12200     Care of child
12300     Help/teach
12400     Talk/read
12500     Play indoors
12600     Play outdoors
12700     Medical care-child
12800     Other child care
13000     Obtain goods and services, general
13100     Dry clean
                                            14100    Shower, bathe, personal hygiene
                                            14110    Shower, bathe
                                            14120    Personal hygiene
                                            14200    Medical care
                                            14300    Help and care
                                            14400    Eat
                                            14500    Sleep or nap
                                            14600    dress, groom
                                            14700    Other personal needs

                                            15000    General education and professional
                                                     training
                                            15100    Attend full-time school
                                            15110    Attend day-care
                                            15120    Attend K-12
                                            15130    Attend college or trade school
                                            15140    Attend adult education and special
                                                     training
                                            15200    Attend other classes
                                            15300    Do homework
                                            15400    Use library
                                            15500    Other education
                                            16000    General entertainment / social activities
                                            16100    Attend sports events
                                            16200    Participate in social, political, or religious
                                                     activities
                                            16210    Practice religion
                                            16300    Watch  movie
                                            16400    Attend theater
                                            16500    Visit museums
                                            16600    Visit
                                            16700    Attend a party
                                            16800    Go to bar/lounge
                                            16900    Other entertainment / social events
                                            17000    Leisure, general
                                            17100    Participate in sports and active leisure
                                            17110    Participate in sports
                                            17111    Hunting, fishing, hiking
                                            17112    Golf
                                            17113    Bowling / pool / ping pong / pinball
                                            17114    Yoga
                                            17120    Participate in outdoor leisure
                                            17121    Play, unspecified
                                            17122    Passive, sitting
                                            17130    Exercise
                                            17131    Walk, bike, or jog (not in transit)
                                            17140    Create  art, music, participate in hobbies
                                            17141    Participate in hobbies
                                                 46

-------
Activity
Code
13200
13210
13220
13230
13300
13400

13500
Description
Shop / ran errands
Shop for food
Shop for clothes or household goods
Run errands
Obtain personal care service
Obtain medical service

Obtain government / financial services
Activity
Code
17142
17143
17144
17150
17160
17170

17180
Description
Create domestic crafts
Create art
Perform music / drama / dance
Play games
Use of computers
Participate in recess and physical
education
Other sports and active leisure
Each of the CHAD codes is mapped to an internal APEX distribution number; activities that
have identical energy expenditure associated with them map to the same distribution. The
distributions themselves are defined by number in the MET'Distribution File (section 4.12).
Each line of the MET Mapping ?\\Q contains a

•     Activity Code. This activity code maps the CHAD activity to the internal APEX
      distribution number.
•     Age Category.  Some MET distributions are differ for persons of different ages. This
      variable maps the age groups to the correct distribution number. The age category given
      in this file is a label representing the age group. APEX will assign distributions as
      follows:
             -Age is "0": APEX will use for persons of all ages
             -Age is "20": APEX will use for persons age 0 to 25
             -Age is "30": APEX will use for persons age 26 to 39
             -Age is "40": APEX will use for persons age 40 and older
•     Occupation.  The MET distributions for the "Work"  CHAD activity differ based on the
      occupation of the profile. This variable maps the different occupations to the correct
      distribution number.
•     MET Distribution Number. This is an internal index used by APEX to access the
      distribution. These values range from 1 to 166. They may be expanded to distribution
      number 256 if necessary.
•     Notes. Description of the activity being modeled by the MET distribution. This is for the
      convenience of the user and is not used internally by  APEX.

An example portion of the MET Mapping File is given in Exhibit  4-14.
                                          47

-------
! METS Distribution Mapping file
! Created 12-12-2006
Activity
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10300
11000
11100
11110
11200
11210
Age
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Occ. APEX
ADMIN
ADMSUP
FARM
HSHLD
LABOR
MACH
PREC
PROF
PROTECT
SALE
SERV
TECH
TRANS
X
Any
Any
Any
Any
Any
Any
Dist#
1
1
2
3
4
5
6
7
7
7
8
9
10
11
12
13
14
15
16
17
Notes
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Work, general
Breaks
General household activities
Prepare food
Prepare and clean-up food
Indoor chores
Clean-up food
                 Exhibit 4-14. Example Portion of the MET Mapping File.

The user should not change this file unless the user has developed her own activity codes.


4.12  MET Distribution File

This file provides the actual distributions for calculating the MET value for each diary event
(activity). The distributions are defined by APEX distribution number as given in the MET
Mapping file. A MET value is a dimensionless ratio of the activity-dependent energy
expenditure rate to the basal or resting energy expenditure (metabolic) rate, and the CHAD
activity code is an identifier associated with each diary event that indicates the type of activity
being performed.  In general, the user should not change  the distributions in this file, as these
data were developed from extensive experimental data on human energy expenditures.

The distribution definitions make use of the standard APEX distribution format (a distribution
shape, followed by 4 distribution parameters, upper and lower truncation bounds, and a
resampling flag).  The 4 parameters used are dependent on the shape of the distribution. Each
data line in this file provides the following information in list format:

•      APEX Distribution Number.  This is an internal index used by APEX to access the
       distribution. These values range from 1 to 166. They may be expanded to distribution
       number 256 if necessary. This matches the distribution numbers used in the MET
       Mapping file.
•      Distribution Shape. This variable gives the type of the MET distribution.
•      Parl.  Parameter 1 of the MET distribution.
                                           48

-------
•      Par2.  Parameter 2 of the MET distribution.
•      Par3.  Parameter 3 of the MET distribution.
•      Par4.  Parameter 4 of the MET distribution.
•      LTrunc. Lower truncation point of the MET distribution.
•      VTrunc Upper truncation point of the MET distribution.
•      ResampOut. Distribution resampling flag.
•      General Use. Text description of the general use of the particular distribution in APEX.
       Optional - not used by the model code.

Volume //provides complete details for defining probability distributions in APEX; a summary
of the available distributions is given in Table 4-6.
                 Table 4-6. Available Probability Distributions in APEX.
Distribution
Beta
Cauchy
Discrete
Exponential
Extreme
Value
Gamma
Logistic
Lognormal
Loguniform
Normal
OffOn
APEX
KEYWORD
BETA
CAUCHY
DISCRETE
EXPONENTIAL
EVALUE
GAMMA
LOT
LOGNORMAL
LUNIFORM
NORMAL
OFFON
Parl
Minimum
Median
Par2
Maximum
Scale (b)
>0
Par3
Shape 1
(sl)>0

Par4
Shape2
(s2) > 0

LTrunc
(Optional)
Lower
truncation
limit
Lower
truncation
limit
UTrunc
(Optional)
Upper
truncation
limit
Upper
truncation
limit
ResampOut
(Optional)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
This type of distribution has no parameters, rather the keyword is simply followed by a list
of up to 100 discrete values. The distribution returns each of these values with equal
probability.
Decay
constant, k
>0
Scale (b)
>0
Shape (s)
>0
Mean
Geometric
mean (gm)
of unshifted
dist
Minimum
>0
Mean
Probability
of being 0
(0-1)
Shift (a)
Shift (a)
Scale (b)
>0
Scale (b)
>0
Geometric
standard
deviation
(gsd) > 1
Maximum
>0
Standard
deviation



Shift (a)

Shift (a)











Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit

Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit

Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)

                                          49

-------
Distribution
Pareto
Point
Triangle
Uniform
Weibull
APEX
KEYWORD
PARETO
POINT
TRIANGLE
UNIFORM
WEIBULL
Parl
Shape (s)
>0
Point Value
Minimum
Minimum
Shape (s)
>0
Par2
Scale (b)
>0

Maximum
Maximum
Scale (b)
>0
Par3
Shift (a)

Peak

Shift
Par4





LTrunc
(Optional)
Lower
truncation
limit

Lower
truncation
limit
Lower
truncation
limit
Lower
truncation
limit
UTrunc
(Optional)
Upper
truncation
limit

Upper
truncation
limit
Upper
truncation
limit
Upper
truncation
limit
ResampOut
(Optional)
Resample
outside
truncation?
(Y/N)

Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Resample
outside
truncation?
(Y/N)
Periods (".") must be used as placeholders in the file if a parameter is not needed for a particular
distribution.

See Volume II: Technical Support Document for further information about the use of MET
probability distributions in APEX.  A portion of this file is shown in Exhibit 4-15.
!  APEX METS Distribution File
IDist Shape
1     Lognormal
2     Lognormal
3     Lognormal
4     Triangle
5     Uniform
6     Triangle
7     Triangle
8     Triangle     1.6    8.
9     Triangle     2.5    4.
10   Lognormal    3      1.
11   Triangle     1.2    5.
12   Uniform     1      2.
13   Triangle     1.5
14   Lognormal    2.5
15   Exponential  1.11
16   Exponential  0.71
17   Uniform     2.3
18   Exponential  0.53   2.2
19   Normal      5      1
20   Exponential  0.37   2.6
21   Exponential  1.43   1.5
22   Point       2
23   Normal      4.5    1.5
24   Point       4.5
25   Exponential  0.71   3.5
26   Triangle     3      4.5
Par4
                        esampOut General  Use
                                 Work,  admin
                                 Work,  farm
                                 Work,  household
                                 Work,  labor
                                 Work,  mech
                                 Work,
                                       prec
                                 Work,profess/protect/sales
                                 Work,  service
                                 Work,  tech
                                 Work,  trans
                                 Work,  missing  occup
                                 Breaks
                                 General  household actv
                                 Prepare  food
                                 Prepare  and clean-up food
                                 Indoor chores
                                 Clean-up food
                                 Clean house
                                 Outdoor  chores
                                 Clean outdoors
                                 Care of  clothes
                                 Wash clothes /build fire
                                 Repair,  general
                                 Repair of boat
                                 Paint home / room
                                 Repair / maintain car
                 Exhibit 4-15.  Selected Parts of Activity-Specific MET File
                                              50

-------
4.13 Physiological Parameters File

This file provides age and gender specific distributions for a number of physiological
parameters (see Exhibit 4-16).  The parameters are listed in Table 4-7.  See Volume II: Technical
Support Document for details of these parameters and the equations in which they are used in
APEX.
                  Table 4-7. Parameters in the Physiological Input File
Keyword
NVO2MAX
BM
RMRINT
RMRSLP
RMRERR
HMG
BSAEXP1
BSAEXP2
MAXOXD
BLDFAC1
BLDFAC2
HEIGHTINT
HEIGHTSLP
HEIGHTERR
ECF
RECTIME
ENDGN1
ENDGN2
Variable
Normalized maximum oxygen uptake
Body mass
Intercept of resting metabolic rate regression
Slope of resting metabolic rate regression
Standard deviation for resting metabolic rate
regression
Blood hemoglobin density
Exponent 1 for calculating body surface area
Exponent 2 for calculating body surface area
Maximum oxygen deficit
Blood volume factor 1
Blood volume factor 2
Intercept of height regression
Slope of height regression
Standard deviation of height regression
Energy conversion factor
Time required to recover maximum oxygen
deficit
Endogenous CO production rate 1
Endogenous CO production rate 2 (used for
women in 2nd half of menstrual cycle)
Units
ml-O2/(min-kg)
(Note: while the APEX inputs for NVO2MAX
are in ml-O2/(min-kg), APEX outputs VO2Max
in the Profile Summary file in L-O2/min)
kg
MJ/day
(Note: while the APEX inputs for RMR are in
MJ/day, APEX outputs RMR in the Profile
Summary file in kcal/min).
MJ/(day-kg)
MJ/day
g/dl
-
-
ml/kg
ml/lb
ml/inches
inches
children under 18:
inches/(year of age)
adults:
inches/ln(lbs body weight)
inches
L-O2/kcal
hours
ml/min
ml/min
Distributions for the above parameters are assigned to persons of every age and gender
combination in the Physiology file. The distributions are defined in the APEX distribution
format (a distribution shape, followed by 4 distribution parameters, upper and lower truncation
bounds, and a resampling flag -  see Volume II). Thus, each data line contains the following
information:
                                          51

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             Parameter keyword.
             Minimum age for the current parameter distribution definition.
             Maximum age for the current parameter distribution definition.
             Gender for the current parameter distribution.
             Distribution Shape. This variable gives the type of the distribution.
             Parl.  Parameter 1 of the distribution. Depends on shape.
             Par2  Parameter 2 of the distribution. Depends on shape.
             Par3.  Parameter 3 of the distribution. Depends on shape.
             Par4.  Parameter 4 of the distribution. Depends on shape.
             LTrunc. Lower truncation point of the distribution.
             UTrunc Upper truncation point of the distribution.
             ResampOut. Distribution resampling flag.
Thus, each line of the physiology file can define the distribution for a range of ages, but only a
single gender.  The physiological parameters must be defined for both genders for all ages 0-100
years, with the exception of ENGN2, which need only be defined for females. An APEX fatal
error will result if not all data are provided. In general, the distributions in this file should not be
changed from their default values, as they were derived from available physiological data.

See Table 4-6 for the available distribution shapes and required parameters. Periods (".") must
be used as placeholders if a parameter is not needed for a particular distribution.
                                           52

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!  APEX  Physiology Data,  revised May 4, 2006
!Variable
!NVO2Max
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
NVO2MAX
AgeMin AgeMax
                                          Parl
                                  Normal
                                           51.1
Par3  Par4  LTrunc  UTrunc ResampOut
BM
BM
BM
BM
BM
BM
BM
BM
BM
BM
BM
BM
BM
                            Drmal 7.8
                            urinal 11.4
                                   9
!  Intercept for  RMR regression
                   17
                        Point
                        Point
                        Point
                        Point
                        Point
                        Point
                        Point
          Exhibit 4-16. An Example Portion of the Physiological Parameters File
4.14 Ventilation File

This file contains a set of regression parameters used by APEX to estimate ventilation from the
event MET. This is a small file of five lines, containing the parameters for each of five age
groups (Exhibit 4-17). This file should not be edited except by advanced users who understand
the APEX ventilation algorithm.

For more information on the ventilation algorithm and the derivation of the values in this file, see
Volume II:  Technical Support Document and Graham and McCurdy (2005).
                                           53

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! APEX4 Ventilation Data File
! MinAge MaxAge  bO  sebO   bl   sebl   b2    seb2   b3   seb3  eb   ew   R2
  0   19   4.4329 0.0579  1.0864  0.0097 -0.2829  0.0124  0.0513 0.0045 0.0955 0.1117  0.925
 20   33   3.5718 0.0792 1.1702 0.0067  0.1138  0.0243  0.045 0.0031 0.1217 0.1296  0.8927
 34   60   3.1876 0.1271 1.1224 0.012   0.1762  0.0335  0.0415 0.0095 0.126 0.1152 0.8922
 61   100  2.4487 0.3646 1.0437 0.0195  0.2681  0.0834 -0.0298 0.01  0.1064 0.0676  0.8932

                     Exhibit 4-17. The APEX Ventilation Input File
4.15 Profile Functions (Distributions) File

The Profile Functions input file defines functions for variables associated with each simulated
profile.  There are two types of functions that can be defined. They are:

   •   Functions for built-in APEX variables. These are variables that are predefined in
       APEX, and whose values under different circumstances can be customized by the
       functions defined in this file.  Most of these variables are also "conditional variables"
       because microenvironmental parameters can depend on their values.

   •   Functions for creating user-defined APEX conditional variables. These are generic
       variables that the user may define and then use in calculating microenvironmental
       parameters. These names of these variables have no set intrinsic meaning in APEX; they
       can be used to represent whatever the user wishes. Up to eight of these variables may be
       defined in APEX.

   •   Functions for creating user-defined APEX conditional variables that vary by region.
       These are generic variables that the user can define and then use for calculating
       microenvironmental parameters. These variables can vary by region (either county or
       sector) and thus may be evaluated differently for individuals who reside in these different
       regions. Up to five of these functions may be defined.
The relationships among the different functions that can be defined in the Profile Functions file
and the microenvironmental descriptions are shown in Figure 4-1. The built-in and user-defined
functions are used to define a set of conditional variables Vc, which are functions of input APEX
variables (Vi). These conditional variables are used in determining microenvironmental
parameters.  Microenvironment parameters are quantities that appear in the equations for the
microenvironmental concentrations.  The relationship between the conditional variables and the
microenvironment parameters are described in the Microenvironmental Descriptions file (see
Section 4.19).
                                           54

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                                   Input variables

                                        V,
                       Built-in profile
                         functions
          User-defined profile
               functions
 Profile
Functions
   File
                                     Built-in
                                 and user-defined
                                   conditional
                                    variables
                                       Vc
Micro parameters,
       MP
                                                                Micro
                                                             Descriptions
                                                                 File
                                     Micro
                                 concentrations
 Figure 4-1.  Relationship between Profile Functions and Microenvironmental Descriptions
                                           Files
4.15.1 Defining a Profile Function

The general procedure for defining a profile function is as follows:

1.  A function definition begins with its name on the first input line.

2.  The user may add as many comment lines as necessary to describe the profile function or
units of the involved parameters.

3.  If the function is of type regional (RegionalConditionall-5), then a statement is required to
define how the regions are defined, either by county or sector, and how many different regions
are being modeled.
                                            55

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4.  The number of subsequent input lines varies with the number of input variables required to
define the function. At least one (and usually two) input lines are needed for each input variable
of the function. In addition, at least two lines are also needed for the function result. For each
input variable (table dimension), the first line starts with the keyword INPUT., followed by the
indexing number of the variable in the function, the Type of Input Variable, and the Number of
Values (Nvals) allowed for the input variable. At the end of this input line, the user may add
comments in double quotes to explain input variables. The lines directly following define the
input variable data - specifically, they  define how the input variable is grouped into integer
categories for indexing the table of results. The Type of Input Variable must be one of the
following:

•      probability,
•      realrange,
•      intrange,
•      intvalue,
•      intindex, or
•      conditional

Probability means fixed probabilities for each outcome (result). The input variable data for
probability is a list of the Nvals fixed probabilities.  The sum of the probabilities must equal 1.
Realrange means a set of discrete categories, each consisting of a range of real numbers.  In this
case, the categories are defined by Nvals-1 cut points. (If the input variable falls on a cut point,
it falls into the higher bin.) Intrange is similar, except each category consists of a range of
integers. Intvalue means that each possible value that the input variable may take on is listed on
the data line. Intindex means that the  input variable is integer and is to be used to index the
table of results directly (e.g., a value of 3 means use the third cell a table dimension).  Thus, this
type of input variable does not require  a second line. Conditional refers to conditional
probabilities that depend on the values of other input variables.  A conditional input variable
comes last in a function specification.  A table of probabilities follows.  The number of entries in
the probability table must be equal to the product of the number of category combinations for the
other inputs and the number of possible function results.

See the examples in the sections that follow for illustration of the appropriate use of these input
variable types.

5.  After all the input variables are specified, the next line must contain the keyword RESULT,
followed by a type (integer, real, or histogram) and the number of possible results (Nresults).

6.  The table results are then listed in order in subsequent lines.  If the result type is designated as
integer,  the results must be a list of integers of length Nresults.  If the type is real, then the list of
results must contain Nresults real numbers.  If the result type is histogram, the results are a
series of Nresults+1 cut points that define Nresults bins.

7.  The profile function ends with a new line that has a # sign.
                                           56

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The types of profile functions are discussed in detail below, with examples. Note that when
preparing or editing a profile functions file, be careful not to use Tab to separate the items on a
line.  APEX explicitly searches for blanks (spaces) as delimiters, and does not recognize Tabs as
such.

4.15.2  Functions for Built-in, User-defined, and Regional APEX Variables

The built-in APEX variables for which functions can be assigned are given in Table 4-8. All of
these variables are conditional variables which can be used to define microenvironment
parameters, with the exception of the variable DiaryPools. (Note that a few other APEX
variables, such as gender, can be used as conditional variables, see Section 4.19.2). DiaryPools
is the only function that APEX requires be defined, as it is used in the selection of appropriate
CHAD diaries for different days in the simulation.  The input variables required for each of these
functions are hard coded; the required inputs for each variable are listed in the table. Also note
that some conditional variables defined in this file must be used to define other conditional
variables.

Three user-defined conditional variables are listed in the table as well. These functions take a
single input variable, which must be defined by fixed probabilities for each of the function
results (categories).

Each of the functions in the table returns an integer category for each combination of input
parameters.  For the conditional  variables, these category numbers can be used in defining the
microenvironment parameters in the Microenvironment Description File (see Section 4.19.2).

Three examples are shown in Exhibit 4-18. The first is the definition for a function for
AvgTempCat.  It returns an integer category number for the average temperature, which will be
used in the definition of one or more microenvironment parameters. Recall that the input
parameters for this function are fixed, and that the text in quotes is not used by APEX. The first
and only  input variable defines the integer ranges (via intrange) for the three categories of
average temperature.  In this case, the ranges are < 50 degrees, 50-77 degrees, and > 78 degrees.
The function essentially reads the daily average temperature and determines which category it
falls in.  The resulting categories are 1, 2 and 3. If the average temperature were 69 degrees,
then the AvgTempCat function would return "2".

The second example  is a definition for WindowRes.  The first input variable is AC_Home, and
the categories for it are defined by its two possible integer values (via intvalue), as 1 or 2.  The
second input variable is the maximum daily temperature; the categories for it are defined via
intrange in a manner similar to that demonstrated in the first example. The third input variable,
the average daily temperature, is also defined as intrange, but in this case there is only 1
category, which all temperatures fall into.  (This is the correct way to ignore the influence of a
required input variable).  In this  case, no cut points are required to be listed.  The fourth and final
input variable is the conditional probability for the two function results categories, 1 and 2. The
probabilities for the results must be defined at all combinations of the categories for the first
three input variables.  The table of conditional probabilities  loops first over the possible results,
and then  over the input variables, in order.  So the first row of the table can be interpreted as
containing the probabilities for WindowRes=l and WindowRes=2 for AC_Home=l,
                                           57

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MaxTemp<56, and any AvgTemp value. The last line are the probabilities for WindowRes=l
and WindowRes=2 for AC_Home=2, MaxTemp>78, and any AvgTemp value. As expected,
the probabilities for the two results sum to 1 for each combination of input variable categories.
                                        58

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Table 4-8. Variables That Can Be Defined in the Profile Functions File
Conditional Variable
TempCat
HumidCat
WlndCat
DirCat
PrecipCat
MaxTempCat
AvgTempCat
Diary Pools
(Required)
HasGasStove
HasGasPilot
AC Home
AC Car
WindowRes
WindowCar
Purpose
Binning hourly temperatures into
categories
Binning hourly humidities into
categories
Binning hourly wind speeds into
categories
Binning hourly wind directions into
categories
Assigning precipitation codes to
categories
Binning daily maximum temperatures
into categories
Binning daily average temperatures
into categories
Assigning diary pools
Probability of having a gas stove
Probability of having a pilot light,
conditional on HasGasStove
Probability of having different types of
home air conditioning or ventilation
Probability of having A/C in car
Probability of residence windows
being open or closed, conditional on
AC Home, MaxTempCat, and
AvgTempCat
Probability of car windows being open
Input Variables
INPUT1 : Temperature on hour of simulation
INPUT 1 : Humidity on hour of simulation
INPUT1 : Wind speed on hour of simulation
INPUT 1 : Wind direction on hour of simulation
INPUT 1 : Precipitation code on hour of simulation
INPUT1 : Temperature on hour of simulation
INPUT1 : 24-hour average temperature on day of simulation
(AvgTemp)
INPUT 1 : Maximum temperature on simulated day (MaxTemp)
INPUT2: Average temperature on simulated day (AvgTemp)
INPUTS: Day of the week
INPUT 1: Probabilities for the 2 results
INPUT 1: Has Gas Stove (Y/N)? (HasGasStove)
INPUT2: Conditional Probabilities for the result categories for
both HasGasStove=Y and HasGasStove=N
INPUT1 : Fixed probabilities for the types of air conditioning /
ventilation (the number of types is user-defined)
INPUT 1: Probabilities for the 2 results
INPUT 1: Type of home A/C (AC_Home)
INPUT2: Max. temperature on day of simulation (MaxTemp)
INPUTS: Average temperature on day of simulation (AvgTemp)
INPUT4: Conditional probabilities for the result categories for
every combination of inputl -inputs categories
INPUT 1: Has car A/C (AC_Car)
Number of
Categories
any number
any number
any number
any number
any number
(equal to or
less than the
number of
precipitation
codes in the
Meteorology
Data file)
any number
any number
any number
2 (Y/N)
2 (Y/N)
any number
2 (Y/N)
2 (Y/N)
2 (Y/N)
Function
Reevaluated
hourly
hourly
hourly
hourly
hourly
daily
daily
daily
once per profile
once per profile
once per profile
once per profile
daily
daily
                               59

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Conditional Variable

SpeedCat
DailyConditionall
DailyConditional2
DaifyConditional3
ProftleConditionall
ProfileConditional2
ProJUeConditionaS
ProfileConditional4
ProfUeConditionalS
RegionalConditionall
RegionalConditional2
RegionalConditionalS
RegionalConditionaU
RegionalConditionalS
Purpose
or closed, conditional on AC Car,
MaxTempCat, and AvgTempCat
Probability of average speed categories
for vehicles
Generic daily conditional variable # 1
Generic daily conditional variable #2
Generic daily conditional variable #3
Generic profile conditional variable #1
Generic profile conditional variable #2
Generic profile conditional variable #3
Generic profile conditional variable #4
Generic profile conditional variable #5
Generic regional conditional variable
#1
Generic regional conditional variable
#2
Generic regional conditional variable
#3
Generic regional conditional variable
#4
Generic regional conditional variable
#5
Input Variables
INPUT2: Max. temperature on day of simulation (MaxTemp)
INPUTS: Average temperature on day of simulation (AvgTemp)
INPUT4: Conditional probabilities for the result categories for
every combination of inputl -inputs categories
INPUT1 : Fixed probabilities for the result categories
INPUT 1: Fixed probabilities for the result categories
INPUT 1: Fixed probabilities for the result categories
INPUT 1: Fixed probabilities for the result categories
INPUT 1 : Fixed probabilities for the result categories
INPUT 1 : Fixed probabilities for the result categories
INPUT 1 : Fixed probabilities for the result categories
INPUT 1 : Fixed probabilities for the result categories
INPUT 1 : Fixed probabilities for the result categories
INPUT1 : Fixed probabilities for the result categories, defined for
each region (sector or county) modeled
INPUT1 : Fixed probabilities for the result categories, defined for
each region (sector or county) modeled
INPUT1 : Fixed probabilities for the result categories, defined for
each region (sector or county) modeled
INPUT1 : Fixed probabilities for the result categories, defined for
each region (sector or county) modeled
INPUT1 : Fixed probabilities for the result categories, defined for
each region (sector or county) modeled
Number of
Categories

any number
any number
any number
any number
any number
any number
any number
any number
any number
any number
any number
any number
any number
any number
Function
Reevaluated

daily
daily
daily
daily
once per profile
once per profile
once per profile
once per profile
once per profile
once per profile,
based on profile's
home sector
once per profile,
based on profile's
home sector
once per profile,
based on profile's
home sector
once per profile,
based on profile's
home sector
once once per
profile, based on
pro file's home
sector profile
60

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AvgTempCat
!  Temperature  ranges (categories)  in Fahrenheit
INPUT1  INTRANGE 3        "AvgTemp"
50 78
RESULT  INTEGER 3         "TempCatA"
123
#
WindowRes
!  Home  windows open(l)  or closed
INPUT1  INTVALUE 2        "AC_Home"
1 2
INPUT2  INTRANGE 3        "MaxTemp"
56 80
INPUT4  CONDITIONAL 12
0.2 0.8
0.2 0.8
0.5 0.5
0.7 0.3
0.1 0.9
0.9 0.1
RESULT  INTEGER 2
1 2
#
DailyConditional3
!  DailyConditional3 - Penetration  values for vehicle  micro
INPUT1  PROBABILITY 4
0.2 0.5  0.2  0.1
RESULT  INTEGER 4
1234
#
RegionalConditiona11
!  Has attached garage
BY Sector  14
INPUT1  PROBABILITY 2
01017953800  0.05  0.95
01017953900  0.05  0.95
01017954000  0.05  0.95
01017954200  0.05  0.95
01017954300  0.05  0.95
01017954400  0.05  0.95
01017954500  0.05  0.95
13013180101  0.8   0.2
13013180102  0.8   0.2
13013180201  0.8   0.2
13013180202  0.8   0.2
13013180300  0.8   0.2
13013180400  0.8   0.2
13013180500  0.8   0.2
RESULT  INTEGER 2
1 2
#
                     Exhibit 4-18. Examples of Profile Functions
The third example is a definition for a user-defined conditional variable DailyConditionalS.  In
this case, the user wanted to define four categories of a variable (penetration) for a given
microenvironment, and assign each category a probability of being selected on a given day.  All
user-defined conditional variables are designated in an analogous manner. The only valid input
type for the user-defined conditional variables is PROBABILITY.  Note the probabilities for the
                                        61

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four categories in the example sum to one.  The resulting category number is saved to the profile
on each day, and can be used to determine the microenvironment parameters (Section 4.19.2).

The final example is a function definition for a regional conditional variable
RegionalConditionall. In this example, it is being used to describe difference in housing
conditions (presence of an attached garage) in different sectors of the study area. The BY
statement indicates how the prevalence vary regionally, either by county or by sector (in this
case, sector).  This line must additionally contain the number of regions (ie. counties or sectors)
that will be used (in this case, 14).  After this BY line, the probability input for each sector or
county is listed. APEX matches these regions to the appropriate study area sector (or sectors, in
the case of a county), and uses them when assigning the value of RegionalConditionall-5 to each
profile.  Counties may only be used when modeling census tracts, as the first 5 characters of the
census tract is the FIPS code for the county. An APEX warning will result if a listed region does
not match up with any study area sector, and APEX will fail if there exists a study area sector for
which there is no corresponding region. The result of this function is that profiles in each sector
will be assigned an attached garage (the RESULT,l=yes, 2=no) based on their sector's listed
probabilities.

The minimum number of categories for all the variables defined  in the Profile Functions file is
one, in which case all profiles will have the same value for the variable. However,
microenvironment parameters cannot depend on the values of variables having only one category
(it wouldn't make sense because everyone is the same). In the case of all functions EXCEPT
DairyPools, having one category is the default case and can be implemented by simply omitting
the function definition from the Profile Functions file. DiaryPools, however, is required to be
defined in the file.  Therefore, if one wishes to define only a single diary pool, this must be done
explicitly, by setting all the RESULT values for the function equal to one. For example,

DiaryPools
!  Group activity diaries  into pools
TABLE
INPUT1 INTRANGE 1        "MaxTemp"
INPUT2 INTRANGE 1        "AvgTemp"
INPUTS INTINDEX 7        "DayOfWeek"
RESULT INTEGER  7         "Pool number"
1111111

There is no explicit upper limit on the number of categories, and in practice it is only limited by
what is convenient.
4.16 Microenvironment Mapping File

This file provides the mapping of the Location Codes (e.g., for CHAD) to Microenvironments
defined in APEX. The current CHAD location codes are given in Table 4-9, and an example
portion of a Microenvironment Mapping file is provided in Exhibit 4-19. This file only allows
comment lines and keyword input lines, except for the first two header lines. Each keyword
input line begins with a location code followed by a short description, an "=", an integer that
designates a microenvironment defined in the Microenvironment Description file, and a
character variable that assigns the location code as belonging to a "Home", "Work", "Other", or

                                          62

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"Unknown" location (H/W/O/U).  These designations are used to assign a set of
microenvironment concentrations to each event; as three sets of concentrations are calculated in
APEX based on air concentrations for the "home", "work", and "other" locations. (See Volume
//for details).

The supplied file contains microenvironment assignments for the 115 CHAD location codes.
The user must assign each location code to microenvironments defined in the Microenvironment
Description file by  specifying the microenvironment number in the APEX Microenvironment
column. The file must contain assignments for all CHAD location codes, or APEX will exit with
a Fatal error.

A zero in the APEX Microenvironment column will result in no exposure in that CHAD
microenvironment location.  A value of -1 means that APEX will use whichever
microenvironment was previously in use in the composite diary time series for an individual
(typically used for CHAD locations  'IT and 'X').
                                          63

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                             Table 4-9. CHAD Location Codes
Location
Code
Description
Location
Code
Description
X      No data                                31210
U      Uncertain of correct code                 31230
30000   Residence-general                      31300
30010   Your residence                          31310
30020   Other residence                         31320
30100   Residence-indoor                       31900
30120   Your residence-indoor                   31910
30121    ...kitchen                             32000
30122    ... living room or family room            32100
30123    ...dining room                         32200
30124    ...bathroom                           32300
30125    ...bedroom                            32400
30126    ...study or office                       32500
30127    ...basement                           32510
30128    ... utility or laundry room                32520
30129    ...other indoor                         32600
30130   Other residence-indoor                  32610
30131    ...kitchen                             32620
30132    ... living room or family room            32700
30133    ...dining room                         32800
30134    ...bathroom                           32810
30135    ...bedroom                            32820
30136    ...study or office                       32900
30137    ...basement                           32910
30138    ... utility or laundry room                32920
30139    ...other indoor                         33100
30200   Residence- outdoor                      33200
30210   Your residence-outdoor                 33300
30211    ...pool or spa                          33400
30219    ...other outdoor                        33500
30220   Other residence-outdoor                 33600
30221    ...pool or spa                          33700
30229    ...other outdoor                        33800
30300   Residential garage or carport              33900
30310      ...indoor                            34100
30320      ... outdoor                           34200
30330   Your garage or carport                   34300
30331    ...indoor                              35000
30332    ...outdoor                            35100
30340   Other residential garage or carport         35110
30341    ... indoor                              35200
30342    ... outdoor                            35210
30400   Residence-none of the above             35220
31000   Travel-general                          35300
31100   Motorized travel                        35400
31110   Car                                    35500
31120   Truck                                  35600
                                             Walk
                                             In stroller or carried by adult
                                             Waiting for travel
                                                ... bus or train stop
                                                ... indoors
                                             Travel- other
                                                ... other vehicle
                                             Non-residence indoor- general
                                             Office building/ bank/ post office
                                             Industrial/ factory/ warehouse
                                             Grocery store/ convenience store
                                             Shopping mall/ non-grocery store
                                             Bar/ night club/ bowling alley
                                             Bar or night club
                                             Bowling alley
                                             Repair shop
                                             Auto repair shop/ gas station
                                             Other repair shop
                                             Indoor gym /health club
                                             Childcare facility
                                                ... house
                                                ... commercial
                                             Large public building
                                             Auditorium/ arena/ concert hall
                                             Library/ courtroom/ museum/ theater
                                             Laundromat
                                             Hospital/ medical care facility
                                             Barber/ hair dresser/ beauty parlor
                                             Indoors- moving among locations
                                             School
                                             Restaurant
                                             Church
                                             Hotel/ motel
                                             Dry cleaners
                                             Indoor parking garage
                                             Laboratory
                                             Indoor- none of the above
                                             Non-residence outdoor- general
                                             Sidewalk- street
                                             Within 10 yards of street
                                             Outdoor public parking lot /garage
                                                ... public garage
                                                ... parking lot
                                             Service station/ gas station
                                             Construction site
                                             Amusement park
                                             Playground
                                               64

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  Location
  Code
Description
Location
Code
Description
   31121   Truck (pickup or van)
   31122   Truck (not pickup or van)
   31130   Motorcycle or moped
   31140   Bus
   31150   Train or subway
   31160   Airplane
   31170   Boat
   31171   Boat- motorized
   31172   Boat- other
   31200   Non-motorized travel
                                 35610      ... school grounds
                                 3 5620      ... public or park
                                 3 5700   Stadium or amphitheater
                                 35800   Park/golf course
                                 35810   Park
                                 35820   Golf course
                                 35900   Pool/river/lake
                                 36100   Outdoor restaurant/ picnic
                                 36200   Farm
                                 36300   Outdoor- none of the above
             Uncertain of correct code
             No data
             Residence, general
             Your residence
             Other residence
             Residence, indoor
             Your residence, indoor
             ..., kitchen
             ..., living room or family room
           Exhibit 4-19.  Example Portion of a Microenvironment Mapping File
4.17 Diary Questionnaire (DiaryQuest) File

This file provides the personal information component of each 24-hour activity diary (Exhibit
4-20).  Each record contains values for the following variables:

•      CHAD ID
•      Day type (MON, THE, ..., SUN, Missing (X))
•      Gender (Male (M), Female (F), Missing (X))
•      Race (White (W), Black (B), Asian (A), Hispanic (H), Other (O), not available (X))
•      Employment status (Yes (Y), No (N), Missing  (X))
•      Maximum hourly temperature for this diary day (degrees F)
•      Daily mean temperature for this diary day (degrees F)
•      Age (Years)
•      Occupation code (see Table 4-10)
•      Missing time (the total number of minutes associated with events in the Diary Events file
       for which the activity and/or location codes are missing for this diary day)
•      Record count (the number of records in the CHAD Diary Events file corresponding to
       this diary day)
                                            65

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The user should not change this input file unless the CHAD database has changed or other
activity data are to be used instead. If the latter, the input file format restrictions must be met,
the CHAD coding conventions used, and the other CHAD files modified to be consistent with
this file. Note that this file has one record per CHAD ID, whereas the CHAD Diary Events file
has Record Count of records per CHAD ID.
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
     BAL97
001A,
001B,
001C,
001D,
001E,
001F,
001G,
001H,
0011,
001J,
001K,
001L,
006A,
006B,
006C,
006D,
006E,
006F,
006G,
006H,
0061,
006J,
008A,
008B,
008C,
008D,
008E,
008F,
TUE,F,W,
WED,F,W,
THU,F,W,
FRI,F,W,
TUE,F,W,
WED,F,W,
THU,F,W,
FRI, F,W,
TUE,F,W,
WED, F,W,
THU,F,W,
FRI,F,W,
WED,M,W,
THU,M,W,
FRI,M,W,
TUE,M,W,
WED,M,W,
THU,M,W,
FRI,M,W,
TUE,M,W,
WED,M,W,
THU,M,W,
TUE,F,W,
WED, F,W,
THU,F,W,
FRI,F,W,
TUE,F,W,
WED, F,W,
               Exhibit 4-20. Example Portion of a Diary Questionnaire File
                           Table 4-10. CHAD Occupation Codes
Code
ADMIN
PROF
TECH
SALE
ADMSUP
HSHLD
PROTECT
SERV
FARM
PREC
Description
Executive, administrative, and
managerial
Professional
Technicians
Sales
Administrative support
Private household
Protective services
Service
Farming, forestry, and fishing
Precision production, craft, and repair
                                             66

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Code
MACH
TRANS
LABOR
X
Description
Machine operators, assemblers, and inspectors
Transportation and material moving
Handling, equipment cleaners, helpers, and laborers
Missing
4.18 Diary Events File

This file provides descriptions of events in each day for all the diary days in the CHAD database.
Events may last from one minute to one hour in duration.  Each record includes the following
variables:

•      CHAD ID,
•      Event Start Time (the time the event began; HHMM, with 0000 representing midnight);
•      Event Duration (the duration of the event, in minutes);
•      Activity Code (see Table 4-5); and
•      Location Code (see Table 4-9).

This file should be generated from the CHAD database at the same time as the Diary
Questionnaire (DiaryQuesi) file to ensure that the CHAD IDs are in the same order. Each diary
day begins and ends at midnight  and there should be exactly twenty-four hours of data per diary.
See Exhibit 4-21 for an example  of a portion of this file.  See the previous section on the Diary
Questionnaire file if user-supplied data are to  be provided.
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
     BAL97001A,
0000,60
0100,60
0200,60
0300,60
0400,60
0500,60
0600,60
0700,30
0730,30
0800,60
0900,60
1000,30
1030,30
1100,45
1145,15
1200,60
1300,60
1400,60
1500,60
1600,60
1700,15
1715,45
1800,45
                   Exhibit 4-21. Example Portion of Diary Events File
                                            67

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4.19 Diary Statistics File

This file contains a diary statistic for each diary in the CHAD database. This file is used in
constructing multi-day (longitudinal) diaries in APEX from the CHAD one-day diaries. Refer to
Volume II for information on how to construct this file.

APEX has two options for assembling simulation-length diaries.  The first method is to randomly
pick a new day-long diary from CHAD for each day in the simulation. However, APEX also
contains a longitudinal diary assembly algorithm for selecting diaries based on some key statistic
of each CHAD diary. Details of this longitudinal diary algorithm are provided in Volume II:
Technical Support Document.  In short, the algorithm requires the selection of a diary based on
some key diary statistic relevant to the pollutant being studied. For example, the statistic may be
time spent outdoors or time spent in a vehicle.

The Diary Statistics file must contain the CHAD ID for each diary and the value of this statistic
(ID and statistic separated by a comma or a space, one diary per row).  The order of the CHAD
IDs in this file must be the same as on the Diary Questionnaire (DiaryQuest) file, or an error will
result.

Two Diary Statistics files have been generated from CHAD and are included in the APEX
Version 4 release. These files are for time spent outdoors and time spent in vehicles.  The files
were constructed by summing the time spent in locations considered "outdoors" or "in vehicle"
in each CHAD diary.  Table 4-11 gives the CHAD location codes that were used to generate
these files. Users may construct other files from the CHAD database.  An example portion of a
diary statistic file is shown in Exhibit 4-22.

The use of the longitudinal algorithm is invoked by setting the Simulation Control file keyword
LongitDiary = YES.  If LongitDiary=NO, the Diary Statistics file is not needed, and need not
be specified in the Control file.
  Table 4-11. Chad Locations Used in Constructing the Outdoor Time and Vehicle Time
                                  Diary Statistics Files
CHAD Location IDs Considered
"Outdoors"
30332, 30342, 30320, 30200, 31310,
35000-36300
CHAD Location IDs Considered
"In Vehicle"
31000-31172
                                          68

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! CHAD Longitudinal Activity Statistics File for Time Outdoors
! (CHAD locations 30332,30342,30320,30200,31310,35000-36300)
! Prepared
! Created
! CHAD ID,
BAL97001A,
BAL97001B,
BAL97001C,
BAL97006A,
BAL97006B,
BAL97006C,
BAL97006D,
BAL97006E,
BAL97006F,
BAL97006G,
BAL97006H,
BAL97006I,
BAL97006J,
by Alion Science & Technology, Inc. for EPA
6/24/05
time spent outdoors (minutes)
45
180
0
75
270
135
75
30
270
135
150
90
90
                  Exhibit 4-22. Example Part of a Diary Statistics File
4.20 Microenvironment Descriptions File

The Microenvironment Descriptions input file serves two purposes.  Firstly, it defines the
methods by which pollutant concentrations are calculated in each microenvironment.  Secondly,
it tells APEX how to define the parameters that are required to calculate these concentrations.
The parameters are defined for each microenvironment for each pollutant (with the exception of
the parameters air exchange rate and microenvironment volume, which are not pollutant-
specific). Thus, the Microenvironment Descriptions file has two sections following the general
header records: Microenvironment Descriptions and Parameter Descriptions. An example of
the Microenvironment Description section is shown in Exhibit 4-23 while an example Parameter
Description section is shown in Exhibit 4-24. The examples shown in these figures will be
discussed in detail below.

4.20.1 Microenvironment Descriptions Section

In the Microenvironment Descriptions section of the Microenvironment Descriptions file, the
user specifies a Microenvironment Number, a Name,  and a Calculation Method for each
microenvironment, as shown in Exhibit 4-23. The microenvironment number cannot exceed the
number of microenvironments specified in the Control file, nor can it exceed 127. It also has to
correspond with each of the microenvironment numbers in the Microenvironment Mapping file.
A microenvironment name may be a word up to 40 characters. The calculation method could be
either MAS SEAL or FACTORS. In the MAS SEAL method, the concentration in a
microenvironment is calculated using a mass balance approach, while in the FACTORS method
the microenvironment concentration is assumed to be a linear function of ambient concentration.
See Volume II: Technical Support Document for further description of the MASSE AL and
FACTORS  methods.
                                         69

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       Micro
       1
       2
       3
       4
Name            Method
      Residence       MASSBAL
      Car             MASSBAL
      InsideOther     FACTORS
      Outside         FACTORS
 Exhibit 4-23. Example Microenvironment Descriptions Section of the Microenvironment
                                   Descriptions File
4.20.2  Parameter Descriptions Section

The Parameter Descriptions section of'the Microenvironment Descriptions file consists of the
specification of probability distributions for the microenvironmental parameters that are required
for calculating pollutant concentrations in the microenvironments.  See Volume II: Technical
Support Document for further information on the microenvironmental parameters required for
the MASSBAL and FACTORS concentration calculation methods. Three microenvironmental
parameters can be defined for the FACTORS method and eight microenvironmental parameters
can be defined for the MASSBAL method.  In each method, some of the microenvironmental
parameters can take on default values, and thus need not be explicitly defined. The parameters
and their default values (if present) are given in Table 4-12.  Air exchange rate and volume are
not pollutant-specific, so they are only defined once.  Otherwise, there must be one definition for
each microenvironmental parameter for each pollutant for each microenvironment, with the
exception of the two pollutant source types (C Source and ESource) which permit multiple
sources in the same microenvironment.
 Table 4-12.  Microenvironment Parameters For the FACTORS and MASSBAL Methods
Calculation
method
FACTORS
MASSBAL
Parameter
type
Proximity
Penetration
Csource
Proximity
Penetration
Decay Rate
Air Exchange
Rate
Volume
MeanR
Csource
ESource
Code
PR
PE
CS
PR
PE
DE
AE
VO
MR
CS
ES
Units
None
None
ppm or ng/m3 (depends
on InputUnits)
None
None
1/hr
1/hr
m3
1/hr
ppm or |J,g/m3 (depends
on InputUnits)
Hg/hr
Default value
1
1
0
1
1
0
none
none
AirExRate+DecayRate
0
0
                                         70

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As mentioned above, not all of the parameters must be explicitly defined for each
microenvironment. If the default values in Table 4-12 are acceptable for a microenvironment,
then a given parameter definition may be omitted from the input file. For FACTORS, default
values exist for all the parameters. If no parameters are defined for microenvironments using the
FACTORS method, then the microenvironment concentration is always equal to the current
ambient concentration.  For a MASSBAL microenvironment, the air exchange rate parameter
must always be defined as it has no default value. The volume parameter does not have a default
either, but it is only used if ESource terms exist for that microenvironment and may be omitted
otherwise.  All other parameters are optional. The proximity and penetration factors are used to
model the ambient pollutant concentrations immediately outside and inside a microenvironment.
The air exchange rate and volume variables define the air flow rate in and out of the
microenvironment and the microenvironment air volume. The decay rate defines the rate of
removal of pollutant from the microenvironment via various means. The parameter MeanR is a
factor that describes the removal of pollutant by both air flow and decay.  The CSource and
Esource terms are concentration and emission pollutant sources, respectively.  See Volume //for
a detailed description of these parameters and the microenvironmental concentration equations.

As part of the estimation of microenvironment concentrations, each microenvironmental
parameter for each pollutant is given a value for each hour of the simulation, for each profile
generated.  This value may or may not be different from the values at other hours, depending on
choices in the microenvironmental parameters definition. Some microenvironmental parameters,
such as house volume, typically remain constant throughout the simulation, while others may
change seasonally, daily, or hourly. Values may recur in patterns,  such as the same set of 24
hourly values for some parameter may recur each Saturday in the Winter season. These patterns
are determined from the four mapping options and the three resampling options specified in each
microenvironmental parameter definition.

The definitions for the microenvironment parameters may appear in any order in the
Microenvironment Descriptions file. Therefore, the user (for example) may choose to group
definitions by microenvironment or by pollutant. Each definition should be separated from the
next either by blank lines or by comment lines (starting with an exclamation point) to aid in
clarity. A parameter description consists of keywords and distribution definitions, described in
the following sections.

Keywords

The first part of a microenvironment parameter description is a list of settings, each described by
a keyword. The different keywords have a number of purposes, including specifying:

•     Which microenvironment is being considered
•     Which pollutant is being considered (not needed for air exchange rate or volume)
•     Which parameter is being defined for that microenvironment (the parameter Code)
•     The source number for the current parameter (if it is ESource or CSource)
•     How that parameter varies over hours in the day, days of the week, or months of the year
•     Whether the parameter depends on any conditional variables
                                          71

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•      Whether the parameter is correlated with any other parameter (by being sampled using
       the same random numbers)
•      A random number seed for generating the parameter values
•      Whether or not a new value of parameter is generated for each hour, for each day, and for
       the workplace

The keywords and their descriptions are provided in Table 4-13.

The conditional variable keywords must be either one of the conditional variables listed in Table
4-8 (TempCat, HumidCat, WindCat, DirCat, PrecipCat, MaxTempCat, AvgTempCat,
HasGasStove, HasGasPilot, AC_Home, AC_Car, WindowRes, WindowCar, SpeedCat,
DailyConditionall-DailyConditionalS, ProfileConditionall-ProfileConditionalS,
RegionalConditionall-RegionalConditionalS), or Gender, Employed, or PopCat. All
variables, with the exception of the last three, must be defined in the Profile Functions file in
order to be used as a conditional variable in a microenvironmental parameter description.
PopCat is the "population category," or gender/race combination (for example, "white males" is
a population category). Therefore, Gender and PopCat should not both be used as conditional
variables for the same microenvironmental parameter.

In APEX the user has the option of correlating samples for microenvironmental parameters.
Such correlation would make sense, for example, when the value of the parameter is assumed to
be mainly a function of the properties of a simulated individual's home and the pollutants have
similar properties (for example, are all particles).  In addition, in some  cases it may be that the
same parameters may be correlated in different microenvironments.  APEX uses a simple
method of correlation microparameters - by sampling them using the same random numbers.
This results in values being selected for correlated parameters at the same percentile from the
appropriate distributions. The percentiles will correspond each hour as long as the 2 (or more)
parameters use the same conditional variables, time and area mappings, and resampling rates
and thus have the same number of required distributions and samples.  Otherwise the samples get
out of phase and any correlation is lost.  APEX checks that the conditionals,  mappings, and
resampling are the same when correlating parameters, and writes a warning if they are not.
APEX will still run, but the user should be aware that the correlation is lost.

Correlation is handled by an optional keyword in the microparameter definition, CORRNUM.
Each subset of microparameters that the user desires be  correlated (sampled at the same
percentile each hour) are assigned a unique integer 1-N, where N is the total  number of
correlated subsets.

All the keywords for the microenvironmental parameter come at the beginning of the
microenvironmental  parameter definition. After the definition of all the keywords, the next line
should be the header line for the data section (that is, the section that contains the actual
distribution definitions for the microenvironmental parameter).  The header line must begin with
the word Block, as APEX recognizes this word as  indicating the end of the keyword section.
(See Exhibit 4-24 for an example of an appropriate header.)
                                          72

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     Table 4-13. Keyword Definitions for the Parameter Descriptions Section of the
    	Microenvironment Descriptions File	
     Keyword
                              Description
Microenvironment
Number
These numbers must match the microenvironment numbers in the
Microenvironment Descriptions section.
Pollutant
Integer corresponding to the pollutant being considered. (Number corresponds
to the order of the pollutant definition in the Control file). Not needed for
AER and Volume definitions (ignored if defined).
Parameter Type
A parameter code such as PR (Proximity) and PE (Penetration) provided in
Table 5-8 should be used to specify a parameter type.
Correlation
Number
Integer number corresponding to correlation subset. Each subset of
microparameters that the user desires be correlated (sampled at the same
percentile each hour) are assigned a unique integer 1-N, where N is the
total number of correlated subsets.
Source Number
Numbers multiple sources in the same microenvironment. Not needed if there
is only one source present.
Hours - Block
This variable is used to map hours of a day to different time blocks. A "time
block" is a group of hours for which the same microenvironmental parameter
distribution(s) will be used. The input line always contains a list of 24 integers,
representing 24 hours a day. The first hour is midnight to 1 a.m. and the 24th
is 11 p.m. to midnight. The position of an integer in the input line represents
the hour in a day. The integer represents the number of a time block that an
hour belongs to. The hours in a time block do not need to be consecutive, nor
does a time block have to have the same number of hours. If this line is
missing, the default value is that all 24 hours are in a single time block - block
#1.
Weekday - Daytype
This variable is used to map days in a week to different day types. A "day
type" is a set of days for which the same microenvironmental parameter
distribution(s) will be used. Seven integers must be given in this input line.
The position of an integer in the input line represents a day, beginning on
Sunday and ending on Saturday.  The integer represents the day type a day
belongs to. If this variable is not defined, all days of a week will belong to day
type#l.
Month - Season
This variable is used to map months of a year to different seasons. A "season'
is a set of months for which the same microenvironmental parameter
distribution(s) will be used. Twelve integers must be given in this input line.
The position of an integer represents a month of a year, beginning in January
and ending in December. The integer represents the season that a month
belongs to. If this line is missing, all 12 months belong to season #1.
District - Area
This variable is used to map air districts to larger areas.  The number of
integers in this line must match the number of air districts in the study area.
This variable is a holdover from APEX2 and should not be used unless really
necessary. The user could delete this line or place the same number of 1 in this
line as the number of air districts.
                                            73

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Keyword
Condition # 1
Condition # 2
Condition # 3
ResampHours
ResampDays
ResampWork
RandomSeed
Description
Choice for the first conditional variable. A conditional variable is a variable
whose value affects the choice of microenvironmental parameter
distribution(s). If not used, this line may either be omitted or the value set to
zero.
Choice for the second conditional variable.
Choice for the third conditional variable.
Either YES or NO. If YES, a random value is selected from distribution for a
parameter in each hour within a time block. If NO, a random value is selected
for a parameter for a time block and used for every hour within the time block.
The default value is NO.
Either YES or NO. If YES, a random value is selected from a distribution for
a parameter for each day within a day type. If NO, a random value is selected
for a day type and used for every day within the same day type. The default is
NO.
Either YES or NO. If YES, a separate set of random values is selected from a
distribution for the workplace. If NO, the same set of random values are used
(for the same day and hour) both for home and at work. The default is YES.
Either zero or a positive integer up to about 2.1 billion. If zero, the random
number seed for a parameter is determined from the internal clock, and the
results will differ from one run to another. If not zero, then Seed =
(RandomSeed x 232) + RandomSeed. Multiple model runs with the same seed
will generate the same sequence of random numbers for the parameters (as
long as the microenvironmental parameter definition is unchanged). The
default value is zero.
Distribution Definitions

The last part of a microenvironmental parameter definition lists the probability distributions for
the microenvironment parameter at different times or under different circumstances during the
simulation. Sets of distribution data may exist for all possible combinations of the user-specified
cases of the following seven indexing variables:

•  Block — time block (as described by the Hours -Block mapping in the keyword section)
•  Daytype — day type (as described by the Weekday - Daytype mapping in the keyword
   section)
•  Season — season of the year (as described by the Month - Season mapping in the keyword
   section)
•  Area — air quality area (as described by the District - Area mapping in the keyword section
•  Cl — conditional variable # 1
•  C2 — conditional variable # 2
•  C3 — conditional variable # 3

These variables are listed in the header line for the data section. The indices for each of the
above variables should be noted under their appropriate columns in the header.  Then the
parameter distributions must be listed one per  line, looping over the variables in the order of the
                                          74

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above list. Note that the cases of each indexing parameter must be represented by integers
ranging from 1 to the maximum number of cases for an indexing variable.

The number of cases for the indexing variables Block, Daytype, and Season are specified by
mappings in the keyword section. For example, the number of time  blocks would be the highest
integer indicated in the Time-Block mapping. For the conditional variables MaxTempCat,
AvgTempCat, HasGasStove, HasGasPilot, AC_Home, AC_Car,  WindowRes, WindowCar,
SpeedCat, DailyConditionall-DailyConditionalS, ProfileConditionall-ProfileConditionalS,
or RegionalConditionall-RegionalConditionalS the number of cases is determined by the
number of Results indicated on the Profile Functions file (Section 4.15). For Gender, there are
always 2 cases. For PopCat, the number of cases is indicated by the number of population
groups (population files) defined on the Control file (Section 4.2), and the groups  are indexed in
the order they appear in the file (for example, if the population file for white females happened to
be defined first in the Control file, then that group would correspond to the case PopCat=l).

The user specifies the microparameter distribution using the standard APEX distribution format
(a distribution shape, followed by 4 distribution parameters, upper and lower truncation bounds,
and a resampling flag). The 4 parameters used are dependent on the shape of the distribution.
See Volume //for a complete discussion of the use of probability distributions in APEX. Thus
the following data must be present in each specification:

   •         Distribution Shape. This variable gives the type of the distribution
   •         Parl.  Parameter 1 of the microparameter distribution. Depends on shape.
   •         Par2.  Parameter 2 of the microparameter distribution. Depends on shape.
   •         Par3.  Parameter 3 of the microparameter distribution. Depends on shape.
   •         Par4.  Parameter 4 of the microparameter distribution. Depends on shape.
   •         LTrunc. Lower truncation point of the distribution.
   •         VTrunc  Upper truncation point of the distribution.
   •         ResampOut. Distribution resampling flag.
See Table 4-6 for the available distribution shapes and required parameters.  The parameters that
are not used for specifying a distribution should be marked with a period (".").

Example Parameter Descriptions

Two examples of parameter descriptions are shown in Exhibit 4-24. These examples should
provide the user with a good idea of how the keywords and distribution definitions work.

In the first example, the microenvironment parameter Air Exchange Rate (AE) is defined for
Microenvironment #1. In this case, the parameter distribution is only a function of two
conditional variables, AvgTempCat, and AC_Home.  The parameter is not resampled from the
distribution every hour (ResampHours=NO) nor each day (ResampDays=NO), although the
parameter is resampled if the simulated person moves between home and work
(ResampWork=YES). In this case the conditional variable AvgTempCat has five possible
values (1-5) and AC_Home has two possible values (1-2); these variables and their values were
defined in the Profile Functions file.  Thus, probability distributions for AE must be defined at

                                         75

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all 10 combinations of the two conditional variables. The ten distributions are lognormal in
shape (although they have different parameters), and are listed in order - first looping over the
values of AvgTempCat and then AC_Home.

In the second example, Penetration Factor (PE) is defined for Microenvironment #12.  Here, the
distributions are not a function of any conditional variable, but rather different time blocks, day
types, and seasons. Distributions for PE must be defined for all possible combinations of these
time variables. The Hour-Block keyword line indicates a mapping of the hours of the day into
two different time blocks (1 and 2) roughly defining night and day. Thus a different parameter
distribution for PE will  be used for these two time blocks. Similarly, the Weekday-Daytype
mapping keyword line defines two different day types, "1" for Saturday and Sunday, and "2" for
the rest of the days of the week.  Finally, the Month-Season mapping keyword line defines four
seasons, labeled 1-4, corresponding to winter, spring, summer, and autumn.  The distributions
follow (again looping first over block, then day type, then season), and in this example the
parameter is defined as  a single point value in all cases.

It is clear that these methods allow the user a great deal of flexibility in defining different
distributions for the microenvironmental parameters. In most cases, many of the features of
these descriptions will not be used, but in some cases the user may wish to define a large number
of distributions for a single parameter. There is no limit in APEX on the number of distributions
that can be defined for a microenvironment parameter.
                                           76

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Micro number
Parameter Type
Condition # 1
Condition # 2
ResampHours
ResampDays
ResampWork
Block DType Season
ill
ill
ill
ill
ill
ill
ill
ill
ill
ill
Micro number
Pollutant = 3
Parameter Type
Hours - Block
Weekday-DayType
Month-Season = 1
Block DType Season
111
211
121
221
112
212
122
222
113
213
123
223
114
214
124
224
= 1
= AE








= AvgTempCat
= ACHome
= NO
= NO
= YES
Area Cl
1 1
1 2
1 3
1 4
1 5
1 1
1 2
1 3
1 4
1 5
= 12

= PE
= 1111
= 1222
1222
Area Cl
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1




C2
1
1
1
1
1
2
2
2
2
2



1 1
3 3
C2
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1




C3
1
1
1
1
1
1
1
1
1
1




1
344
C3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1




Shape
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal
Lognormal





4 1
Shape
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point
Point




Parl Par2 Par3 Par4 LTrunc UTrunc ResampOut
0.95 1.7 0 . 0.111 10.0 Y
0. 65 1.7 0 . 0. Ill 10.0 Y
0.35 1.7 0 . 0.111 10.0 Y
0.33 1.9 0 . 0.111 10.0 Y
0.33 1.9 0 . 0.111 10.0 Y
0.50 2.0 0 . 0. Ill 10.0 Y
0.50 2.0 0 . 0.111 10.0 Y
0.60 2.0 0 . 0.111 10.0 Y
0.80 2.0 0 . 0.111 10.0 Y
1.00 2.0 0 . 0.111 10.0 Y



222211111


Parl Par2 Par3 Par4 LTrunc UTrunc ResampOut
1.0 . . .
0.5 . . .
0.9 . . .
0.4 . . .
0.8 . . .
0.3 ....
1.0 . . .
0.9 . . .
0.8 . . .
0.7 . . .
0.6 . . .
0.5 ....
0.5 ....
0.3 ....
0.2 . . .
0.1 . . .
 Exhibit 4-24. Example Parameter Descriptions in the Microenvironment Description File
4.21 Prevalence File

The Prevalence file is an optional APEX input file for modeling a subpopulation of persons with
a particular disease or condition. The Prevalence file is only required when the setting Disease is
set in the Control file. APEX uses the prevalence rates to assign a YES/NO value to a
physiological profile variable, 111, and to produce output exposure summary tables for persons
with I11=YES. If Disease is not set in the control file, then the Prevalence file is not required and
no summary tables for ill persons will be printed.

The prevalence file must contain prevalence rates (probabilities) for all age and gender cohorts
from ages 0-100. Each line of the prevalence file contains an age, followed by the values for
males, then females.  The values in the prevalence file may be separated by one or more spaces.
The age value in the file is not actually used (although it must be present); it is assumed that the
values are given in age order in 1-year increments from 0 to 100.  A portion of an example
Prevalence file is shown in Exhibit 4-25.
                                          77

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! Asthma Prevalence Rates
!Age
0
1
2
3
4
5
Male
0
0
0
0
0
0
041
070
102
129
144
164
Female
0
0
0
0
0
0
034
052
071
088
099
119
Exhibit 4-25. Portion of an Example Prevalence File
                       78

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CHAPTER 5.   APEX OUTPUT FILES

APEX produces the following output files:

•      Log File
•      Hourly File
•      Daily File
•      Profile Summary (Persons) File
•      Microenvironmental Summary File
•      Microenvironmental Results File
•      Output Tables File
•      Sites File
•      Events File

These are all ASCII files which can be opened and reviewed using a text editor or other software
(e.g., spreadsheet, database, statistical analysis, and graphics).  A brief summary of these files is
given in Table 5-1. Details of each file are provided in Sections 5.1 to 5.12 below.

All output files contain the same set of header records, allowing files generated from the same
run to be identified, and for audit trail requirements. This header section consists of six lines
followed by a blank line. The contents are:

       Line 1:       Type of output file
       Line 2:       APEX version,  date and time of start of run
       Line 3:       Location description (from Control file)
       Line 4:       Scenario description (from Control file)
       Line 5:       Echoes first line of Control file
       Line 6:       List  of the Pollutants (as given in Control file)
       Next NLines:  Echo the first line of the each of the Air Quality Data files for the N
                    pollutants in the simulation. If the output file is pollutant-specific, then
                    only the line from its corresponding Air Quality file is echoed.

The Location, Pollutant, and Scenario descriptions echo what the user provided for those
keywords in the Simulation Control file. In the first line of the Control file the user typically
gives general identifying information for the  simulation.  Similarly, the first lines of the Air
District Data files can identify the contents of the files.
                                           79

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Table 5-1. APEX Output Files.
Output file
Log File
Hourly File
Daily File
Profile Summary
File
Microenvironment
Summary File
Output Tables File
Sites File
Events File
Microenvironment
Results File
Description
The Log file contains the record of the APEX model simulation as it
progresses. If the simulation completes successfully, the log file indicates
the input files and parameter settings used for the simulation and reports
on a number of different factors. If the simulation ends prematurely, the
log file contains error messages describing the critical errors that caused
the simulation to end.
The Hourly file provides an hour-by-hour time series of exposures, doses,
and other variables for each modeled profile.
The Daily file provides a day -by-day time series of exposures, doses, and
other variables for each modeled profile.
The Profile Summary file provides a summary of each profile modeled in
the simulation. Each line lists the person's age, gender and race, in
addition to a number of other personal profile variables that the model uses
to simulate exposure.
The Microenvironment Summary file provides a summary of the time and
exposure by microenvironment for each profile modeled in the simulation.
The Output Tables file contains a series of tables summarizing the
exposure (and dose, if calculated) results of the simulation for a pollutant.
The percentiles and exposure/dose cut-off points used in these tables are
defined in the Control file. A Tables file is generated for each pollutant.
The Sites file lists the sectors, air districts, and zones in the study area, and
identifies the mapping between them.
The Events file contains event-level information (including MET,
exposure, ventilation, and dose) for individuals in the simulation. Settings
in the Control file allow the user to write this information for all persons,
every Nth person, or for a set of specified profile IDs.
The Microenvironment Results file provides an hour-by-hour time series of
microenvironment concentrations and parameters for a pollutant for each
modeled profile for each location ("Home", "Work", and "Other"). A
Microenvironment Results file is generated for each pollutant.
            80

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5.1  Log File

The Log file records the following information as a model run progresses:
       Input files used;
       Model parameters used;
       Number of diaries available to match each simulated person (or profile);
       Model execution time;
       Sectors in the study area;
       Air districts in the study area;
       Meteorology zones in the study area:
       Mappings of sectors to air districts and meteorology zones;
       Statistical summaries of each simulated person (profile); and
       Output summary tables.
If a model run stops abnormally, an error message will be written to the log file. The user should
review the Log file after a model run to ensure that the simulation executed and terminated
normally and that the output results are valid. Note that output summary tables in this file are
exactly the same as the tables in the Output Table file. The level  of detail of the information
written to the Log file is controlled by the Control file setting DebugLevel.  DebugLevel can
have a value of 1, 2, or 3; the higher the level, the more information is written to the log.  The
Control file settings LogDistrict, LogPopulation, LogPrqftles, LogSectors, LogTables, and
LogZones also control the writing of information to the Log file.  See Table 4-4 for more
information on these settings.

5.2   Hourly File

The Hourly file contains hourly time series of a number of APEX variables, including
concentrations and doses, for each simulated person or profile.  Note: if the APEX timestep is
greater than 1 hour (TimeStepsPerDay<24), the Hourly file will not be written. In this case
the Timestep file (see next section) provides the best summary of the exposure and dose time
series. The user can control which variables are written to the Hourly file via  a list of keywords
using the Control file keyword HourlyList.  The variables and their corresponding keywords are
given in Table 5-2.
              Table 5-2. APEX Variables Written to the Hourly Output File
Variable
Person
Hour
Ve
Va
Description
Simulated profile number
Hour # of the simulation
Ventilation
Alveolar ventilation
Control File
Keyword
-
-
VE
VA
Optional
N
N
Y
Y
                                          81

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Variable
EVR
MET
EE
Micro Time
Micro Exposure
Ambient Concentration
Exposure
Dose
Intake Dose
Deposited Dose
Exposure Factor
Description
Equivalent ventilation rate, Ve
divided by body surface area
Metabolic equivalents. Time-
averaged multiple of basal
energy expenditure for the
hour.
Energy expenditure,
Time spent in
microenvironment N (minutes)
Exposure in microenvironment
N
Ambient pollutant
concentration, time averaged
over events
Time-averaged exposure for
the hour
Time-averaged dose for the
hour. Units of dose depend on
pollutant, see Volume II.
PM pollutants only. Average
mass inhaled per minute
(includes mass not deposited)
during the hour (ug/min)
PM pollutants only Total
mass deposited in the
respiratory system during the
hour (ug).
The ratio of the hourly
exposure to the hourly ambient
concentration
Control File
Keyword
EVR
METS
EE
TIME1 -
TIMEN
EXP1-EXPN
AMB
EXP
DOSE
INTAKEDOSE
DEPDOSE
EF
Optional
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
See Volume II: Technical Support Document for a description of the APEX ventilation
algorithms and further information on Ve, Va, EVR, and EE.  Ve, Va, EVR, MET, EE,
Exposure, dose, and ambient concentration are the time-weighted averages of the event values
for these variables.  The ambient concentration is time-averaged over the events because the
simulated individual may move between home/work/other locations (and thus possibly between
air districts) in the course of an hour. Thus, the hourly ambient concentration may not be equal to
the home district AQ data for that hour.

The hourly exposure in microenvironment N is the portion of the total exposure for the hour
occurring in microenvironment N, equal to:
ExpN =
^ ConcN * Duration
        60
                            -, for events in the hour in microenvironment N
                                          82

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where ConcN is the concentration in microenvironment N for the event and Duration is the event
duration in minutes.  A weighted average is used because it is possible for concentrations in a
given microenvironment to vary as the person moves between home/work/other locations during
the hour.  The sum of all ExpN for the hour will be identical to the total hourly exposure. Hourly
exposure factor EF is just the ratio of the hourly exposure to the hourly ambient value.

The variables may be listed in any order in the control file using the keyword HourlyList, but
they are printed in the output file in the order they appear in the table.  The list should be on a
single line and may be comma or space-delimited. The EXP, DOSE, EXPN, AMB, and EF
keywords control the writing of that variable for all pollutants in the simulation; the file headers
for these variables will contain the pollutant name. However, the dose variables will not be
written for a pollutant if it has DoDose=NO in the Control file, even if a dose keyword is
included in the HourlyList.

An example use of the HourlyList keyword would be:

HourlyList      =  TIME4, TIME12  EXP,  EF, AMB

An example portion of the resulting Hourly file for an example two-pollutant run (Poll and Pol2)
is shown  in Exhibit 5-1.
APEX Hourly File
APEX Version 4.0 (dated February 19, 2007) Run Date = 20070321 Time = 101001
Location = Description of Location of the Study Area
Scenario = APEX4 Sensitivity Simulation
Simulation = ! APEX4 Sensitivity Simulation
Pollutant = Poll Pol2
Air Quality = ! Hourly Poll air quality data for an example metropolitan area
Air Quality = ! Hourly Pol2 air quality data for an example metropolitan area
P
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Hour Time 4 Time 12
1
2
3
4
5
6
7
8
9
10
11
12
13
14
60
60
60
60
25
26
60
60
30
12
60
4
60
60
0
0
0
0
0
0
0
0
0
30
0
15
0
0
Amb-Poll
1
9
7
2
7
2
2
1
1
1
2
2
2
3
039E-02
OOOE-03
OOOE-03
OOOE-03
OOOE-03
300E-02
100E-02
800E-02
800E-02
900E-02
026E-02
400E-02
271E-02
OOOE-02
Exp-Poll
5
3
2
9
2
8
7
6
7
6
8
8
1
1
842E-
295E-
710E-
189E-
297E-
118E-
262E-
180E-
378E-
683E-
227E-
700E-
138E-
170E-
03
03
03
04
03
03
03
03
03
03
03
03
02
02
EF-Poll
0.562
0.366
0.387
0.459
0.328
0.353
0.346
0.343
0.410
0.352
0.406
0.363
0.501
0.390
Amb-Pol2
1
9
7
2
7
2
2
1
1
1
2
2
2
3
132E-02
OOOE-03
OOOE-03
OOOE-03
OOOE-03
300E-02
100E-02
800E-02
800E-02
900E-02
044E-02
400E-02
334E-02
OOOE-02
Exp-Pol2
6
3
2
9
2
8
7
6
7
6
8
8
1
1
351E-
351E-
756E-
379E-
333E-
241E-
392E-
291E-
491E-
799E-
427E-
846E-
183E-
189E-
03
03
03
04
03
03
03
03
03
03
03
03
02
02
EF-P012
0.561
0.372
0.394
0.469
0.333
0.358
0.352
0.349
0.416
0.358
0.412
0.369
0.507
0.396
              Exhibit 5-1. Example Portion of an APEX Hourly Output File

Note that the hourly file could be very large if a large number of profiles are simulated. The user
may block generation of the hourly file by setting the Hourly Out parameter to NO in the Control
file.
                                          83

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5.3  Timestep File

The Timestep file contains the timestep-level time series of a number of APEX variables,
including exposure and doses, for each simulated person or profile. The user can control which
variables are written to the Timestep file via a list of keywords using the Control file keyword
TimeStepList.  The variables and their corresponding keywords are given in Table 5-3.


             Table 5-3. APEX Variables Written to the Timestep Output File
Variable
Person
Hour
Timestep
Ve
Va
EVR
MET
EE
Ambient Concentration
Exposure
Dose
Intake Dose
Deposited Dose
Exposure Factor
Description
Simulated profile number
Hour # of the simulation
Timestep # of the simulation
Ventilation
Alveolar ventilation
Equivalent ventilation rate, Ve
divided by body surface area
Metabolic equivalents. Time-
averaged multiple of basal
energy expenditure for the
timestep.
Energy expenditure,
Ambient pollutant
concentration, time-averaged
over events in the timestep
Exposure, time-averaged over
events in the timestep
Time-averaged dose for the
hour. Units of dose depend on
pollutant, see Volume II.
PM pollutants only. Average
mass inhaled per minute
(includes mass not deposited)
during the timestep (ug/min)
PM pollutants only Total
mass deposited in the
respiratory system during the
timestep (ug).
The ratio of the timestep
exposure to the timestep
ambient concentration
Control File
Keyword
-
-
-
VE
VA
EVR
METS
EE
AMB
EXP
DOSE
INTAKEDOSE
DEPDOSE
EF
Optional
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
See Volume II: Technical Support Document for a description of the APEX ventilation
algorithms and further information on Ve, Va, EVR, and EE.  Ve, Va, EVR, MET, EE,
Exposure, dose, and ambient concentration are the time-weighted averages of the event values
                                          84

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for these variables. The ambient concentration is time-averaged over the events because the
simulated individual may move between home/work/other locations (and thus possibly between
air districts) in the course of an timestep. Thus, the timestep ambient concentration may not be
equal to the home district AQ data for that timestep.

The variables may be listed in any order in the control file using the keyword TimestepList, but
they are printed in the output file in the order they appear in the table.  The list should be on a
single line and may be comma or space-delimited. The EXP, DOSE, AMB, and EF keywords
control the writing of that variable for all pollutants in the simulation; the file headers for these
variables will contain the pollutant name. However, the dose variables will not be written for a
pollutant if it has DoDose=NO in the Control file, even if a dose keyword is included in the
TimestepList.

An example use of the TimestepList keyword would be:

TimestepList      = VE AMB EXP

An example portion of the resulting Timestep file for an example one-pollutant  run (Poll and
Pol2) is shown in Exhibit 5-2.
APEX Timestep File
APEX Version 4.0 (dated February 21, 2008)
Location = Description of Location of the
Scenario = APEX4 Sensitivity Simulation
Simulation = ! APEX4 Sensitivity Simulation
Pollutant = ozone
Air Quality = Name =0000200006
P Hour Timestep Ve Amb-ozone
111 4858. 3.760E-03 3
112 5951. 1.027E-02 1
113 4156. 3.570E-03 3
114 4949. 8.480E-03 8
115 5060. 3.680E-03 3

Run Date = 20080227 Time = 111351
Study Area




Exp-ozone
.760E-03
.027E-02
.570E-03
.480E-03
.680E-03
             Exhibit 5-2. Example Portion of an APEX Timestep Output File

Note that the timestep file could be very large if a large number of profiles are simulated or if the
APEX timestep is very small. The user may block generation of the Timestep file by setting the
TimestepOut parameter to NO in the Control file. Also note that if the APEX timestep is equal
to the default (1 hour, or TimestepsPerDay=24), then the Timestep file in general would contain
the same information as the Hourly file, and thus in this case it is not written.
5.4  Daily File

The Daily Exposure file contains a daily time series of a large number of APEX variables for
each simulated person or profile. Writing of the file is controlled by the Control file variable
DailyOut. The user can control which variables are written to the file via a list of keywords
                                          85

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using the Control file keyword DailyList. The variables and their corresponding keywords are
given in Table 5-4.
               Table 5-4. APEX Variables Written to the Daily Output File
Variable
Person
Day
Diary ID
Diary Age
Diary Employment
Diary pool
PAI
Key Diary Variable
WindowRes
WindowCar
SpeedCat
DailyCondl
Daily Cond2
DailyCondS
MaxTempCat
Description
Simulated profile number
Day number of the simulation
ID of CHAD diary selected for the
current day for the profile
Age associated with the selected CHAD
diary (may be different from the age of
the simulated profile)
Employment status associated with the
selected CHAD diary
Index of the APEX diary pool for the
current day (as determined by profile
functions file)
Physical activity index, the time-
averaged MET over the day for the
simulated person
Daily value of the key diary variable
(statistic) used for longitudinal diary
assembly for the simulated day for the
profile (such as time spent outdoor or in
vehicles)
Conditional variable value indicating
whether residence windows are open or
closed (as determined by profile
functions file)
Conditional variable value indicating
whether car windows are open or closed
(as determined by profile functions file)
Conditional variable value indicating the
speed at which a vehicle is traveling (as
determined by profile functions file)
Value of daily conditional variable 1 (as
determined by profile functions file)
Value of daily conditional variable 2 (as
determined by profile functions file)
Value of daily conditional variable 3 (as
determined by profile functions file)
Conditional variable giving the category
for the maximum temperature for the day
(as determined by profile functions file)
Control File
Keyword
-
-
CHADID
CHADAGE
CHADEMP
DIARYPOOL
PAI
KEYVAR
WINDOWRES
WINDOWCAR
SPEEDCAT
DCOND1
DCOND2
DCOND3
MAXTEMPCAT
Optional
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
                                         86

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Variable
AvgTempCat
Maximum
Temperature
Average
Temperature
Average Exposure
Max 1 Hour
Exposure
Max 8 Hour
Exposure
Average Dose
Intake Dose
Deposited Dose
Max 1 Hour Dose
Max 8 hour Dose
Max End-of-Hour
Dose
Description
Conditional variable giving the category
for the average temperature for the day
(as determined by profile functions file)
Maximum hourly temperature for the
current day
Average of the hourly temperatures for
the current day
Time-averaged pollutant exposure for the
day.
Maximum 1 hour exposure on the given
day; each hourly exposure time-averaged
over events.
Maximum 8 hour exposure on the given
day; each 8-hour exposure time-averaged
over events.
Time-averaged pollutant dose for the
day. Units of dose depend on pollutant,
see Volume II.
PM pollutants only. Average mass
inhaled per minute (includes mass not
deposited) during the day (ug/min)
PM pollutants only. Total mass
deposited in the respiratory system
during the day (ug).
Maximum 1 hour dose on the given day;
each hourly dose time-averaged over
events
Maximum 8 hour dose on the given day;
each 8-hour dose time-averaged over
events.
Maximum dose as calculated at the end
of each hour of the day.
Control File
Keyword
AVGTEMPCAT
MAXTEMP
AVGTEMP
AVGEXP
MAX1EXP
MAX8EXP
AVGDOSE
INTAKEDOSE
DEPDOSE
MAX1DOSE
MAX8DOSE
MAX1FDOSE
Optional
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
See Volume II: Technical Support Document for further information on the diary selection
variables, and conditional variables on this list.  The exposure and dose keywords will control
printing for all pollutants in the simulation; the file headers for these variables will contain the
pollutant name.

Note that the Daily file could be very large if a large number of profiles or pollutants are
simulated.  The user may block generation of the daily file by setting the DailyOut parameter to
NO in the Control file.

The keywords may be separated by either spaces or commas. An example DailyList would be:
                                           87

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DailyList  = CHADID CHADAGE CHADEMP  DIARYPOOL PAI  KEYVAR WINDOWRES WINDOWCAR
AVGEXP

An example portion of a Daily file created with the DailyList example above for an example
two-pollutant run (Poll  and Pol2) is shown in Exhibit 5-3. Note that in the daily file the values
may not fall directly under the corresponding label in the file header (in order to minimize file
size).
 APEX Daily File
 APEX Version 4.0 (dated February 19, 2007)   Run Date = 20070321  Time = 101001
 Location    = Description of Location of the Study Area
 Scenario    = APEX4  Sensitivity Simulation
 Simulation  = !  APEX4 Sensitivity Simulation
 Pollutant   = Poll  Pol2
 Air Quality = !  Hourly Poll air quality data for an example metropolitan area
 Air Quality = !  Hourly Pol2 air quality data for an example metropolitan area

P Day CHADID CHADAqe  CHADEmp DiaryPool PAI KeyVar WindowRes WindowCar AvqExp-Poll AvqExp-Pol2
         1 NHW19167A
         2 CIN02759A
         3 NHW10859A
         4 NHA16047A
         5 NHW13255A
         6 NHW15968A
         7 NHW12055A
         8 WAS96832A
         9 DEN34716B
        10 CIN80040B
        11 CIN00339B
        12 WAS63046A
        13 CIN61737C
        14 CAA06251A
                   Exhibit 5-3. Example Portion of a Daily Output File
5.5   Profile Summary (Persons) File

This file provides a summary of profile characteristics and exposure/dose for each simulated
person. Each record contains values for a number of variables for each simulated individual.  A
small set of variables are written by default to the file, and additional variables are only written if
designated by the user in the Control file.  The variables are defined using the PSumList
keyword, followed by an equals sign and a list of variable-specific keywords.  The available
variables and their corresponding keywords are given in Table 5-5.
             Table 5-5. APEX Variables Written to the Profile Summary File
Variable
Person
Home Sector
Description
Sequential index number for
simulated individual
Sector in which the person lives
(home)
Control File
Keyword

-
Optional
N
N
                                            88

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Variable
Work Sector
Home District
Work District
Zone
Age
Gender
Race
Employment
Height
Weight
Car AC type
Home AC type
Disease status
Gas Pilot
Gas Stove
ProfileConditionall
ProfileConditional2
ProfileConditionalS
ProfileConditional4
ProfileConditionalS
RegionalConditionall
RegionalConditional2
Description
Sector in which the person works
(=home sector for non-workers)
Air district for the home sector
Air district for the work sector
Meteorology zone for the home
sector
Age of the simulated profile
(years)
Male or female
Such as White, Black, Asian,
Native American (Nat Am), Other
(depending on pop. files)
Indicates employment outside the
home
Person height (inches)
Body mass (pounds)
Type of air conditioning in the
car (depends of Profile Functions
file)
Type of air conditioning in the
residence (depends of Profile
Functions file)
Whether or not a profile is ill
(depends on Prevalence file)
Indicates the presence of a gas
pilot light in the home (depends
of Profile Functions file)
Indicates the presence of a gas
stove in the home (depends of
Profile Functions file)
Value of profile conditional
variable # 1 for the person
Value of profile conditional
variable # 2 for the person
Value of profile conditional
variable # 3 for the person
Value of profile conditional
variable # 4 for the person
Value of profile conditional
variable # 5 for the person
Value of regional conditional
variable # 1 for the person
Value of regional conditional
variable # 2 for the person
Control File
Keyword
-
-
-
-
-
-

-
-
-
ACCAR
ACHOM
DISEASE
PILOT
STOVE
PCOND1
PCOND2
PCOND3
PCOND4
PCOND5
RCOND1
RCOND2
Optional
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
89

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Variable
RegionalConditionalS
RegionalConditional4
RegionalConditionalS
Number of Events
Blood Vol
BSA
Energy Conversion Factor
Lung Diffusivity
Endogenous CO production 1
Endogenous CO production 2
Hemoglobin
METmax
Maximum Oxygen Uptake
Maximum Oxygen Debt
Physical Activity Index
Recovery Time
Resting Metabolic Rate
VE Intercept
VE Slope
Description
Value of regional conditional
variable # 3 for the person
Value of regional conditional
variable # 4 for the person
Value of regional conditional
variable # 5 for the person
Number of diary events covering
the simulation period for the
person
The volume of blood in the body
(ml)
Body surface area (m2)
Energy conversion factor for
person (L-C>2/kcal)
A lung diffusivity parameter
used in the COHb (CO dose)
calculation (ml/min/torr)
Endogenous CO production rate;
only used for calculating CO
dose (ml/min)
Endogenous CO production rate
for women between ages of 12
and 50 for half the menstrual
cycle; only used for calculating
CO dose (ml/min)
The amount of hemoglobin in the
blood (g/ml)
Maximum obtainable MET level
for the person. (MET)
Maximum obtainable oxygen
uptake rate for person (L-
O2/min)
Maximum obtainable oxygen
debt for person (ml/kg)
Median of the daily PAI values
(time-averaged MET on each
simulated day)
Time required to recover the
maximum oxygen debt (hours)
Resting metabolic rate (kcal/min)
Regression parameter for the
ventilation routine
Regression parameter for the
ventilation routine
Control File
Keyword
RCOND3
RCOND4
RCOND5
EVENTS
BLOODVOL
BSA
ECF
DIFFUS
ENDGN1
ENDGN2
HEMOGLOB
METSMAX
VO2MAX
MOXD
PAI
RECTIME
RMR
VEINTER
VERESID
Optional
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
90

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Variable
VE Residual
Average Exposure
Maximum Exposure
Average Dose
Maximum Dose
Description
Regression parameter for the
ventilation routine
Mean exposure concentration
over the simulation (ppm or
|J,g/m3, as specified in Control
file)
Maximum 1 -hour exposure
concentration over the simulation
(ppm or |J,g/m3, as specified in
Control file)
Mean dose over the simulation.
Units of dose depend on
pollutant, see Volume II.
Maximum 1-hour average dose
over the simulation. Units of
dose depend on pollutant, see
Volume II.
Control File
Keyword
VESLOPE
AVGEXP
MAXEXP
AVGDOSE
MAXDOSE
Optional
Y
Y
Y
Y
Y
The exposure and dose variables listed are written for all pollutants in a multiple-pollutant run.
An example portion of a Profile Summary file for an example 2-pollutant (Poll and Pol2)
scenario is given in Exhibit 5-4. This file was created using the Control file command:

PSumList      =  PAI,  AVGEXP

Note that each record in the file could be much longer, as many more variables could be printed.
APEX Diary Questionnaire File
APEX Version 4.0 (dated February 19, 2007) Run Date = 20070321 Time = 133813
Location = Description of Location of the Study Area
Scenario = APEX4 Sensitivity Simulation
Simulation = ! APEX4 Sensitivity Simulation
Pollutant = Poll Pol2
Air Quality = ! Hourly Poll air quality data for an example metropolitan area
Air Quality = ! Hourly Pol2 air quality data for an example metropolitan area
P HSect WSect
1
2
3
4
5
6
7
8
9
10
513
64
359
222
177
287
688
661
280
793
513
64
359
222
177
287
688
661
280
793
HDis
27
14
42
39
39
49
28
23
55
17
WDis
27
14
42
39
39
49
28
23
55
17
Zone Age Gender Race
2
2
2
2
2
2
2
2
2
2
22
19
22
15
20
32
48
50
39
32
Male
Male
Female
Male
Female
Male
Female
Female
Male
Female
White
Black
Other
Black
Other
White
Black
White
Black
White
Empl
Works
NoWrk
Works
NoWrk
NoWrk
Works
Works
Works
NoWrk
NoWrk
Height
71
67
61
68
65
65
66
60
69
65
908
179
018
519
608
658
264
355
081
700
Weight
228
138
173
182
160
155
183
106
209
172
339
067
609
139
464
154
261
818
165
692
PAI
2
1
1
1
1
2
1
1
1
1
09
74
92
74
65
04
97
93
76
87
AvgExp-Poll
9
9
9
9
8
9
8
8
9
1
956E-
238E-
749E-
100E-
906E-
978E-
873E-
765E-
120E-
020E-
03
03
03
03
03
03
03
03
03
02
AvgExp-Pol2
1
9
9
9
9
1
9
8
9
1
005E-
413E-
415E-
131E-
377E-
059E-
257E-
625E-
331E-
041E-
02
03
03
03
03
02
03
03
03
02
                     Exhibit 5-4. Portion of a Profile Summary File
                                           91

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5.6  Microenvironmental Results File

The Microenvironmental Results file contains hourly values for a number of microenvironment
parameters and variables for all microenvironments, for all persons in a simulation. The file is
pollutant-specific, so one file will be created for each pollutant in the simulation. The variable
values are written for the "home," "work," and "other" locations; there is a set of
microenvironment concentrations associated with each location for each profile. This file may be
useful in examining/testing the effects of conditional values on microenvironment
concentrations.

 The creation of the file for all pollutants is controlled by the Control file variable MResOut.
The files are written if MResOut =YES. The default is NO, as these files are very large, and
writing them greatly affects the speed of the simulation.  The printing of the optional
variables is dictated by the Control file keyword MResList via a comma- or space-separated list
of variable keywords. The MResList will control the writing of the Microenvironment Results
file for all  of the simulation  pollutants.  The variables that may be written to the file and their
corresponding keywords are given in Table 5-6.
       Table 5-6. APEX Variables Written to the Microenvironmental Results File
Variable
Person
Hour#
Micro #
Location
Proximity
Penetration
CSum
Ambient
Concentration
Description
The number of the simulated profile
Hour of the simulation. Hour ranges
from -23 to 24 times the number of
days in the simulation. The hours -23
to 0 are included because APEX
extends the calculation of the
microenvironment concentrations to
include the 24 hours prior to the
beginning of the simulation
Microenvironment number (See
Section 4. 16).
Apex calculates concentrations for
each microenvironment for home (1),
work (2), and other (3) locations (see
Volume II). All are listed in the file.
Proximity factor: microenvironment
parameter, greater than 0.
Penetration factor: microenvironment
parameter, ranging from 0 to 1 .
Sum of concentration sources
(CSource) terms
Pollutant concentration associated
with the location sector and hour (as
determined from the Air Quality Data
file).
Control File Keyword
-

-

PRX
PEN
CSUM
AMB
Optional
N
N
N
N
Y
Y
Y
Y
                                           92

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Variable
Micro
Concentration
ESum
Source Strength
Micro Volume
Air Exchange
Rate (AER)
Removal (Decay)
Rate
WindowRes
WindowCar
MaxTempCat
AvgTempCat
SpeedCat
Daily Conditionall
Daily Conditional
Daily Conditionals
Temp Cat
HumidCat
PrecipCat
Description
Pollutant concentration in the
microenvironment
Sum of Emission Sources (ESource)
terms (ng/hr).
Combined source strength for
emission and concentration sources
in |j,g/m3/hr.
Volume of the microenvironment in
m3.
Rate of air exchange in
microenvironment (1/hr).
Total removal rate of pollutant from
microenvironment (1/hr).
Conditional variable value indicating
whether residence windows are open
or closed (as determined by profile
functions file)
Conditional variable value indicating
whether car windows are open or
closed (as determined by profile
functions file)
Daily maximum temperature
category conditional variable - will
be same for all hours in a day. (as
determined by profile functions file)
Daily average temperature category
conditional variable - will be same
for all hours in a day. (as determined
by profile functions file)
Conditional variable value indicating
the speed at which a vehicle is
traveling (as determined by profile
functions file)
Value of daily conditional variable 1
for the hour
Value of daily conditional variable 2
for the hour
Value of daily conditional variable 3
for the hour
Hourly temperature category
conditional variable
Hourly humidity category conditional
variable
Hourly precipitation category
conditional variable
Control File Keyword
CONC
ESUM
SOURCE
VOL
AER
RR
WINDOWRES
WINDOWCAR
MAXTEMPCAT
AVGTEMPCAT
SPEEDCAT
DCOND1
DCOND2
DCOND3
TEMPCAT
HUMIDCAT
PRECIPCAT
Optional
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
93

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Variable
WindCat
DirCat
Day
Month
Air District
Day Week
Description
Hourly wind speed category
conditional variable
Hourly wind direction category
conditional variable
Day of the simulation
Month of the year
Air district person is in (i.e., the
district corresponding to the
home/work/other location)
Day of the week
Control File Keyword
WINDCAT
DIRCAT
DAY
MONTH
DISTRICT
DAYWEEK
Optional
Y
Y
Y
Y
Y
Y
See Volume III: Programmer's Guide for details on the microenvironment parameters,
microenvironment concentration equations, and conditional variables.

A number of the parameters in the file are undefined for a FACTORS microenvironment (See
Section 4.20.1). These parameters will be padded with 0 in that case.

An example use of MResList in the Control file is:

MResList   =   AER,  PRX, PEN, AMB,  CONG, MAXTEMPCAT, AVGTEMPCAT,  WINDOWRES

The resulting exampleMicroenvironmentalResults file for an example pollutant (Poll) is given
in Exhibit 5-5.  Note that in the file the variable values may not fall directly under the
corresponding label in the file header (in order to minimize file size).
                                          94

-------
 APEX Microenvironmental Results File
 APEX Version 4.0 (dated February 19, 2007)  Run Date = 20070321
 Location    = Description of Location of the Study Area
 Scenario    = APEX4  Sensitivity Simulation
 Simulation  = !  APEX4  Sensitivity Simulation
 Pollutant   = Poll
 Air Quality = !  Hourly Poll air quality data for an example metropolitan area
 Simulation Start Date  = 20040101
 Person Micro
      111
      1
      1
      1
      1
      1
      1
      1
      1
      1
      1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
         1 1
     -o
     -5
     -4
     -3
     -2
     -1
      0
      1
Hour Prx
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
1.0000  1
  0000
  0000
  0000
  0000
  0000
  0000
                 1.0000
0000
0000
0000
0000
0000
0000
0000
 Cone AER
OOOE-03  4
OOOE-03  6
OOOE-03  7
OOOE-03  2
OOOE-03  1
300E-02  1
100E-02  1
800E-02  1
800E-02  1
900E-02  1
100E-02  1
400E-02  3
800E-02  3
OOOE-02  3
200E-02  2
OOOE-02  1
800E-02  1
600E-02  1
200E-02  1
300E-02  1
300E-02
300E-02
200E-02
600E-02 2
                         0000 8.OOOE-03 6
WindowRes
.227E-04
.518E-04
.044E-04
.335E-04
.645E-04
.712E-03
. 922E-03
.398E-03
.207E-03
.192E-03
. 496E-03
.147E-03
.395E-03
.091E-03
.390E-03
.132E-03
.395E-03
.487E-03
.440E-03
.960E-03
.610E-03
.683E-03
.279E-03
.226E-03
.081E-04
empCat AvgTempCat  TempCat
40111
20111
20111
00111
10111
20111
30111
10111
00111
30111
30111
70111
30111
30111
00111
50111
90111
30111
30111
20111
50111
50111
70111
30111
40111
                   Exhibit 5-5. Portion of an Environmental Results File

5.7   Microenvironmental Summary File

This file provides the amount of time spent, mean exposure concentration, and maximum
exposure concentration in each microenvironment during the period of simulation, for each
simulated person.  The Microenvironmental Summary file is pollutant-specific, and thus one is
created for each pollutant in the simulation.  After the six header records and one blank record,
there is one record labeling the columns of the subsequent records in the file.  These labels and
descriptions of the values in the corresponding columns are given in Table 5-7. The first part of
an example Microenvironmental Summary File is shown in Exhibit 5-6.
            Table 5-7.  Format of the APEX Microenvironmental Summary File
Column
1
2
Label
Person
Micro
Type
Num
Num
Description
Profile number - Sequential index number for the simulated
individual
Microenvironment number - Sequential index number for
each microenvironment (as designated in the
Microenvironment Mapping file)
                                            95

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3
4
5
6
Name
Minutes
MeanConc
MaxConc
Char
Num
Num
Num
Microenvironment name (as designated in the
Microenvironment Mapping file) (maximum of 40
characters)
Total time spent in the microenvironment by this individual
(minutes)
Average concentration during the time spent in the
microenvironment by this individual (ppm or |J,g/m3, as
specified in the Control file)
Maximum concentration during the time spent in the
microenvironment by this individual (ppm or |J,g/m3, as
specified in the Control file)
APEX Microenvironmental Summary File
APEX Version 3.4 August 30, 2005 Run Date = 20051104 Time = 180331.421
Location = Location of the Study Area
Pollutant = Ozone
Scenario = Example APEX4 Simulation
Parameters = APEX version 4 Simulation Control File
Person Micro
1
1
1
1
1
1
1
1
1
1
2
0
1
2
3
4
5
6
7
8
9
0
Name
Zero Expo sure
Indoors -residence
Indoors-bars and restaurants
Indoors -schools
Indoors-day care centers
Indoors -other
Outdoors-near road
Outdoors -other
In
In
ZeroExposure
Minutes
0
1338
60
0
0
2
0
10
30
0
0
MeanConc
0
0
0
0
0
0
0
0
0
0
0
0000
0028
0076
0000
0000
0004
0000
0089
0043
0000
0000
MaxConc
0
0
0
0
0
0
0
0
0
0
0
0000
0070
0080
0000
0000
0004
0000
0089
0056
0000
0000
              Exhibit 5-6.  Portion of a Microenvironmental Summary File
5.8  Output Tables File

This file provides up to 242 summary tables, depending on the table specifications in the
Simulation Control file. The first 130 are exposure summary tables, while the last 112 are dose
summary tables.  The Tables file is pollutant-specific, and thus one is created for each pollutant
in the simulation.

5.8.1   Exposure Summary Tables

APEX writes out up to 130 different exposure summary tables.  There are eleven different types
of exposure tables:

1.      Minutes in each exposure interval by microenvironment
2.      Minutes at or above each exposure level by microenvironment
3.      Person-days at or above each daily maximum 1-hour exposure level
                                          96

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4.     Person-days at or above each daily maximum 8-hour exposure level
5.     Person-days at or above each daily maximum timestep exposure level
6.     Number of simulated persons with multiple exposures at or above each daily maximum
       1-hour exposure level
7.     Number of simulated persons with multiple exposures at or above each daily maximum
       8-hour exposure level
8.     Number of simulated persons with multiple exposures at or above each daily maximum
       timestep exposure level.
9.     Number of simulated persons with multiple exceedances (in the simulation) of the
       threshold timestep exposure levels.
10.    Person-days at or above each daily average exposure level
11.    Number of persons at or above each overall average exposure level

Table types 1,2, 10, and 11 are generated only once, for the  entire population. Table types 3 to 9
are generated for six population subgroups, under three exertion levels. The six population
subgroups are as follows:

1. All Persons.  The table statistics are based on the entire population.
2. Children. The table statistics are based on the  population of children, as defined by the age
range given by the Control file settings ChildMin  and ChildMax.
3. Active Persons.  The table statistics are based on the population of people having a median
Physical Activity Index (PAI, mean MET) over the whole simulation period that exceeds the
value designated by the Control file setting ActivePAI.
4. Active Children. The table statistics are based  on the population of active children, as
determined by the Control file settings ChildMin,  ChildMax, and ActivePAI.
5. Ill Persons.  The table statistics are based on the population of ill people. The population is
determined by the probabilities given in the Prevalence file.  This population is only considered
if the input variable Disease is set in the Control file.
6. Ill Children. The table statistics are based on the population of ill people. The population is
determined by the probabilities given in the Prevalence file and the Control file settings
ChildMin and ChildMax. This population is only considered if the input setting Disease is set
in the Control file.

The three exertion levels are:

1. All Exertion Conditions. The table statistics are based on exposures experienced by the
population subgroup under any ventilatory conditions.
2. Moderate Exertion.  The table statistics are based on exposures experienced by the
population subgroup only during periods in which  their average equivalent ventilation rate
(EVR) is in the "moderate" range.  The period of time during which EVR is averaged is either 1
hour or 8 hours, based on the table being generated. The "moderate" EVR ranges are defined by
the Control file settings ModEVRl andHeavyEVRl (for 1-hour  exposures) andModEVRS and
HeavyEVRS (for 8-hour exposures). An individual's EVR is in the moderate range if it is
                                           97

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greater than or equal to the ModEVR# setting and less than the HeavyEVR# setting for the
exposure period.
3. Heavy Exertion. The table statistics are based on exposures experienced by the population
subgroup only during periods in which their average equivalent ventilation rate (EVR) is in the
"heavy" range. The period of time during which EVR is averaged is either 1 hour or 8 hours,
based on the table being generated. The "heavy" EVR ranges are defined by the Control file
settings HeavyEVRl (for 1-hour exposures) and HeavyEVRS (for 8-hour exposures). An
individual's EVR is in the heavy range if it is greater than or equal to the HeavyEVRtt setting for
the exposure period.
For each table that is generated, APEX prints out a label that identifies the table uniquely. For
example, a table of type #1, for all people under all exertion conditions, has the identifier TIME,
WITHIN, ALL, ALL.  Users can reference these identifier labels in custom programs that read
in and process the APEX Tables file.

Exposure Table Type #1: Minutes in each Exposure Interval by Microenvironment
This table lists the total minutes spent by all simulated persons in each microenvironment when
exposure concentration is within various ranges. The bounds of a range are specified at the top of
each column and the top of the next column to the right (Exhibit 5-7).  For each
microenvironment, the table provides three rows of data for the following three variables:

•      Minutes—The number of person-minutes summed over all the simulated persons that are
       spent in the specified microenvironment and that fall within the exposure concentration
       range bounded by the values indicated at the top of the column and the top of the next
       column to the right;
•      Row_%—The percent of the minutes spent in the specified microenvironment that fall
       within the exposure concentration range; and
•      Tot_%—the percent of the total minutes that are spent in the microenvironment and that
       fall within the exposure concentration range.
        Exhibit 5-7. Example of Exposure Table Type #1 in the Output Tables File
Exposure Table Type #2:  Minutes in each Exposure Interval by Microenvironment

                                          98

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This table is similar to Table #1, except that it reports the cumulative person-minutes that are
spent in a microenvironment with an exposure concentration that equals or exceeds the value
indicated at the top of the column.

Exposure Table Type #3:  Person-Days at or above each Daily Maximum 1-Hour Exposure
Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum 1-hour (hourly) average
exposure concentration that equals or exceeds the value indicated at the top of the column
(Exhibit 5-8). The interpretations of the variables in Table Type #3 (and other "person-days"
tables) are provided in Table 5-8.
                                    0 . 755E + 05 0.
    Min
    Max
                       188.
                       214.
                      0.239E+06
        Exhibit 5-8. Example of Exposure Table Type #3 in the Output Tables File
 Table 5-8. Interpretation of the Variables in Exposure Table Type #3 and Other "Person-
                                 Days" Based Tables.
Table entry
Counts (Pop)
#Meet (Pop)
%Meet (Pop)
Mean
Interpretation
Total number of person-days at or above the level specified at the top of each column
for the population [of the subgroup] in the study area [while at this exertion].
Number of persons [in the subgroup] in the study area population who have at least
one exposure at or above the level specified at the top of each column [while at this
exertion]. NOTE: For exertion level tables, the 0.0 level count will not necessarily be
equal to the population of the subgroup, since some persons may have no events at the
exertion level.
Percentage of people [in the subgroup] in the population who have at least one
exposure at or above the level specified at the top of each column [while at this
exertion]. NOTE: For exertion level tables this may not be 100% at the 0.0 level,
since some persons may have no events at the exertion level.
Mean number of days per person [in the subgroup] during which an exposure at or
above the level specified at the top of each column is experienced [while at this
exertion].
                                          99

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Std. Dev.
CV
Minimum
Percentiles
Maximum
Mean (%)
Min (%)
Max (%)
Counts (Sim)
#Meet (Sim)
Standard deviation across persons [in the subgroup] in the number of days during
which an exposure at or above the level specified at the top of each column is
experienced [while at this exertion].
Coefficient of variation across persons [in the subgroup] in the number of days during
which an exposure at or above the level specified at the top of each column is
experienced [while at this exertion].
The lowest total number of days across persons [in the subgroup] during which an
exposure at or above the level specified at the top of each column is experienced [while
at this exertion].
The Nth percentile of number of days across persons [in the subgroup] during which an
exposure at or above the level specified at the top of each column is experienced [while
at this exertion].
The highest total number of days across persons [in the subgroup] during which an
exposure at or above the level specified at the top of each column is experienced [while
at this exertion] .
Mean number of days per person [in the subgroup] during which an exposure at or
above the level specified at the top of each column [while at this exertion] is
experienced, as percentage of possible days.
The lowest total number of days across persons [in the subgroup] during which an
exposure at or above the level specified at the top of each column is experienced [while
at this exertion], as percentage of possible days.
The highest total number of days across persons [in the subgroup] during which an
exposure at or above the level specified at the top of each column is experienced [while
at this exertion], as percentage of possible days.
Total number of simulated person-days [in the subgroup] during which an exposure at
or above the level specified at the top of each column is experienced [while at this
exertion]. NOTE: At the 0.0 level in the exertion-dependent tables, Counts(Sim)
might not necessarily be equal to #Meet(Sim)*NumDays, since some persons may
have no events at the exertion level.
The total number of simulated persons [in the subgroup] who experience at least one
exposure at or above the level specified at the top of each column [while at this
exertion].
Exposure Table Type #4:  Person-Days at or above each Daily Maximum 8-Hour Exposure
Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum 8-hour average exposure
concentration that equals or exceeds specified levels. The table and its interpretation are the
same as Table #3 (Exhibit 5-8) except that the exposure metric is the daily max 8-hour average
exposure concentration.

Exposure Table Type #5:  Person-Days at or above each Daily Maximum Timestep
Exposure Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum timestep average exposure
concentration that equals or exceeds specified levels. The table and its interpretation are the
same as Table #3 (Exhibit 5-8) except that the exposure metric is the daily max timestep average
exposure concentration. This table is not written if the timestep is equal to one hour.
                                         100

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Exposure Table Type #6: Number of Simulated Persons with Multiple Exposures at or
above each Daily Maximum 1-Hour Exposure Level
This table simply provides a count of the number of simulated persons who have at least 1 (2, 3,
4, 5, 6) days in the simulation during which they have experienced an exposure above each of the
daily maximum 1-hour exposure levels. An example is shown in Exhibit 5-9.
MULTIPLE,
DM1H,ALL,ALL
Exposure: Number of Simulated Persons with Multiple Exposures at or above each Daily
Maximum 1-Hour Exposure Level (ppm) , f or N = 1000 Profiles.
Group: All People

Le\
0
5
10
20
30
40
50
75
At
7~ -i
/ e j. —
000
000
000
000
000
000
000
000
least 1
Exposure
1000
1000
1000
16
2
0
0
0
At least 2
Exposures
1000
1000
1000
3
0
0
0
0
At least 3
Exposures
1000
1000
1000
0
0
0
0
0
At least 4
Exposures
1000
1000
1000
0
0
0
0
0
At least 5
Exposures
1000
1000
1000
0
0
0
0
0
At least 6
Exposures
1000
1000
1000
0
0
0
0
0

       Exhibit 5-9. Example of Exposure Table Type #6 in the Output Tables File.
Exposure Table Type #7: Number of Simulated Persons with Multiple Exposures at or
above each Daily Maximum 8-Hour Exposure Level
This table simply provides a count of the number of simulated persons who have at least 1 (2, 3,
4, 5, 6) days in the simulation during which they have experienced an exposure above each of the
daily maximum 8-hour exposure levels. The table is the same as Table #6 (Exhibit 5-9) except
that the exposure metric is the daily max 8-hour average exposure concentration.
                                        101

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Exposure Table Type #8:Number of simulated persons with multiple exposures at or above
each daily maximum timestep exposure level.
This table provides a count of the number of simulated persons who have at least 1 (or 2, 3, 6,
etc) days in the simulation during which they have experienced an exposure above each of the
daily maximum timestep exposure levels. The table is the same as Table #6 (Exhibit 5-9) except
that the exposure metric is the daily max  timestep average exposure concentration. This table is
not written if the timestep is equal to one hour.

Exposure Table Type #9: Number of simulated persons with multiple exposures at or
above some threshold timestep exposure level.
This table provides a count of the number of simulated persons who have at least 1 (or 2, 30, or
300, for example) timesteps in the entire  simulation during which they have experienced an
exceedance of each timestep threshold exposure level. The different number of exceedances to
include in the table are listed in the Control file using the keyword TSMultiLevels. The
threshold exposures are listed using the keyword TSExp. This table is not written if the timestep
is equal to one hour.

Exposure Table Type #10:  Person-Days at or above each Daily Average Exposure Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily average exposure concentration that
equals or exceeds specified levels. The table and its interpretation are the same as Table Type #3
(Exhibit 5-8) except that the exposure metric is the daily average exposure concentration.

Exposure Table Type #11:  Persons at  or above each Overall Average Exposure Level
This table provides a statistical summary of cumulative numbers of both simulated persons and
people in the study area whose overall average exposure concentrations equal or exceed
specified levels. The overall average exposure concentration is the average of hourly exposure
concentrations over the whole period of simulation.  An example of this table is provided in
Exhibit 5-10.
PERSONDAYS , SAVG , AI
Exposure: Persons
Area Population =
Level :
Counts (Pop) :
#Meet (Pop) :
%Meet (Pop) :
Counts (Sim) :
#Meet (Sim) :

jL,ALL
at or above
3976069
0.000
0.398E+07
3976069
100.000
0.100E+04
1000


each Overall

0.500
0.398E+07
3976069
100.000
0.100E+04
1000


Average ExpoE

1.000
0.392E+07
3916428
98.500
0.985E+03
985


sure Level

2.000
0.386E+06
385679
9.700
0.970E+02
97


( ppm ) ,

3 .000
O.OOOE+00
0
0.000
O.OOOE+00
0


for N =

4.000
O.OOOE+00
0
0.000
O.OOOE+00
0


1000 Profiles.

5.000
O.OOOE+00
0
0.000
O.OOOE+00
0

      Exhibit 5-10.  Example of Exposure Table Type #11 in the Output Tables File.
5.8.2   Dose Summary Tables

APEX writes out up to 112 different exposure summary tables.  There are 10 different types of
dose summary tables. The contents of each table type are described in detail below. Table types
7-10 are generated only once, for the entire population.  Table types 1-6 are each generated for
six population subgroups, under three exertion levels. See the previous section on Exposure

                                         102

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tables for the definition of population subgroups and exertion levels.  For the pollutant CO, dose
is blood dose (%COHb), and for any PM pollutant the dose is the rate of mass deposited in the
respiratory system in ug/min (See Volume II). For all other pollutants dose is simply
exposure*ventilation.

Dose Table Type #1— Person-Days at or above each Daily Max End-of-Hour Dose Level
This table provides a statistical summary of the cumulative person-days for both simulated
persons and the population in the study area, for which the daily maximum end-of-hour dose is
equal to or exceeds specified levels. The format of the table is the same as Exposure Table #3
(Exhibit 5-8).

Dose Table Type #2— Person-Days at or above each Daily Max 1-Hour Dose Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily maximum 1-hour average dose
is equal to or exceeds specified levels. The format of the table is the same as Exposure Table #3
(Exhibit 5-8). The definitions of the variables in this table can be found in Table 5-8.

Dose Table Type #3—Person-Days at or above each Daily Max 8-Hour Dose Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily maximum 8-hour average dose
is equal to or exceeds specified levels. The format of the table is the same as Exposure Table #3
(Exhibit 5-8). The definitions of the variables in this table can be found in Table 5-8.

Dose Table Type #4:  Person-Days at or above each Daily Maximum Timestep Dose Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum timestep average dose that
equals or exceeds specified levels.  The table and its interpretation are the same as Exposure
Table #3 (Exhibit 5-8) except that the exposure metric is the daily max timestep average
exposure concentration. This table is not written if the timestep is equal to one hour. The
definitions of the variables in this table can be found in Table 5-8.

Dose Table Type #5: Number of Simulated Persons with Multiple Timestep Doses at or
above some Threshold Timestep Dose Level.
This table provides a count of the number of simulated persons who have  at least 1 (or 2, 30, or
300, for example) timesteps in the entire simulation during which they have experienced an
exceedance of each timestep threshold dose level. The different number of exceedances to
include in the table are listed in the Control file using the keyword TSMultiLevels. The
threshold exposures are listed using the keyword TSDose. This table is not written if the timestep
is equal to one hour.

Dose Table #6— Person-Days at or above each Daily Average Dose Level
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily average dose is equal to or
exceeds specified levels.  The format of the table is the same as Exposure  Table #3 (Exhibit 5-8).
The definitions of the variables in this table can be found in Table 5-8.

Dose Table #7— Persons at or above each Overall Average Dose Level


                                          103

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This table provides a statistical summary of cumulative numbers of both simulated persons and
the people in the study area whose overall average doses are equal to or exceed a specified level.
The overall average dose is the average of hourly dose levels over the whole period of
simulation.

Dose Table #8—Person-hours at or above each End-of-Hour Dose Level
This table provides a statistical summary of the number of person-hours, for both simulated
persons and the population in the study area, for which each end-of-hour dose level is equal to or
exceeds specified levels.  The format of the table is the same as Exposure Table #3 (Exhibit
5-8), except that the time units are hours rather than days. The definitions of the variables in this
table can be found in Table 5-8.

Dose Table #9— Minutes in each Dose Interval
This table provides a statistical summary of cumulative person-minutes, for both simulated
persons and the population in the study area, for which the dose (for example, blood %COHb
level) is within a specified range.  The bounds of the dose range are specified by the levels at the
top of each column and the top of the next column to the right.  The definitions of the variables in
this table are similar to those found in Table 5-8, except that the time units are in minutes rather
than days.

Dose Table #10— Minutes at or above each Dose Level
This table provides a statistical summary of cumulative person-minutes spent by both simulated
persons and the population in the study area, for which the dose (for example, blood %COHb
level) is equal to or exceeds specified levels.  The definitions of the variables in this table are
similar to those found in Table 5-8, except that the time units are in minutes rather than days.

5.9   Sites File

The Sites output file lists the sectors, air districts, and zones in the study area, and identifies the
mapping between them. Thus, each record contains the following:

•      Sector#—Sector ID
•      Latitude—Sector latitude (decimal degrees)
•      Longitude—Sector longitude (decimal degrees)
•      Sectorname—Sector name
•      Air#—Air district ID
•      Airdistance—Distance from air district to sector (km)
•      Airlatitude—Air district latitude (decimal degrees)
•      Airlongitude—Air district longitude (decimal degrees)
•      Airname—Air district name
•      Tem#—Meteorology zone ID
•      Temdistance—Distance from zone to sector (km)
•      Temlatitude—Zone latitude (decimal degrees)
•      Temlongitude—Zone longitude (decimal degrees)
•      Temname—Zone name
                                          104

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5.10 Events File

The Events file contains a summary of the activity diary with accompanying exposure and dose,
at the diary event level.  The variables printed in this file include:

•      Person - the profile number of the simulated individual
•      Seq - the event number for the profile
•      Day - the day number of the simulation, incremented from Day 1 of simulation
•      Year - the year of the event (4-digit)
•      Mn - the month of the event (1 to 12)
•      Dy - the day of the week the event (1 to 7)
•      Hr - the hour of the event (1 to 24)
•      Dur - the duration of the event (integer minutes)
•      Act - the MET distribution code for the event activity
•      Mic - the microenvironment code for the event
•      HW - l=event in home sector, 2=event in work sector, 3=elsewhere
•      Exposure - Exposure level during the event (ppm or |J,g/m3)

Optionally, the user can ask APEX to include the variables:

•      METS - MET level for the event (units)
•      UMET - Unmodified MET level for the event (units)
•      VA - Alveolar ventilation during the event (ml/min)
•      VE - Ventilation during the event (ml/min)
•      EVR - Equivalent Ventilation rate
•      DEFICIT - Oxygen debt, percent of nominal

by including the keyword EVENTSLIST, and listing the variable names to be included. If
DoDose = Yes in the Control file, then two variables related to dose will be printed for all cases,
and an additional two will be printed for PM exposure:

•      Dose - Dose over the event
•      FDose - Final dose for the event
•      DepDose - Deposited mass dose for PM events
•      IntakeDose - Intake dose rate for the PM event

An example  of the EVENTSLIST keyword would be:

EventsList    =    UMET VA VE EVR METS  DEFICIT
                                         105

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 APEX Events File
 APEX version 4.3 (dated June 13,  2008)  Run Date = 20081014  Time = 161345
 Location   = NYC
 scenario   = NYCPM,  Randomseed =0, N = 50
 simulation  = APEX NYC simulation - Benchmark  Test #1
 pollutant   = pml pm2 pm3 pm4
 Air Quality = !  PM25  Air Quality Data for the  2003 AMI NYC Exposure study Area (ug/m3)
 Air Quality = !  PM25  Air Quality Data for the  2003 AMI NYC Exposure Study Area (ug/m3)
 Air Quality = !  PM25  Air Quality Data for the  2003 AMI NYC Exposure Study Area (ug/m3)
 Air Quality = !  PM25  Air Quality Data for the  2003 AMI NYC Exposure Study Area (ug/m3)
Person Seq Day Year Mn Dy Hr Dur Act Mic HW UMET METS VA
Depoose-pml Exp-pm2 Dose-pm2 lntakeDose-pm2 Depoose-pm2
Dose-pm4

2.

2.

2.

2.

2.

2.
1
, 6Q4E-Q3
1
, 344E-03
1
, 064E-03
1
, 569E-03
1
. 713E-03
1
, 219E-Q3
VE
Exp-pm3
EVR E>
Dose-pm3 ir
lntakeDose-pm4 DepDose-pm4

1.

1.

9.

1.

1.

1.
1 1
, 51QE-Q2
2 1
.195E-Q2
3 1
, 613E-03
4 1
.423E-02
5 1
. 573E-02
6 1
, Q99E-Q2
2003 2 1
1. 562E-Q1 2.
2003 2 1
1.406E-01 2.
2003 2 1
1.239E-01 2.
2003 2 1
1. 541E-01 1.
2003 2 1
1.628E-01 1.
2003 2 1
1.332E-01 2.
1 60 50
, QQ6E-Q1 2.
2 60 50
, 050E-01 1.
3 60 50
, 033E-01 9.
4 60 50
, 984E-01 1.
5 60 50
. 967E-01 2.
6 60 50
, 017E-01 1.
1 1
, Q75E-Q3
1 1
, 388E-03
1 1
, 688E-04
1 1
, 873E-03
1 1
. 238E-03
1 1
, 214E-03
3.
6.
2.
5.
2.
4.
3.
6.
3.
6.
3.
4.
,521 3.529 21405.
, 7QQE-Q3 1.245E-Q1 2.
,767 2.777 16847.
,337E-03 8.327E-02 2.
,861 2.862 17358.
, 275E-03 5.813E-02 2.
,398 3.398 20614.
, 284E-03 1.124E-01 1.
.477 3.477 21091.
. 943E-03 1.343E-01 1.
,207 3.207 19452.
, 893E-03 7.282E-02 2.
33406.
, QQ6E-Q1
26039.
, 050E-01
21035.
, 033E-01
31667.
, 984E-01
35301.
. 967E-01
24262.
, 017E-01

6.

' 5.

3.

'e.

6.

4.
15.154 4. 522E-
, 577E-Q3 6.689E
11.812 4. 591E-
.112E-03 5.328E
9. 542 4. 570E-
, 958E-03 4.268E
14.365 4.494E-
.143E-03 6.2731
16.014 4.457E-
. 839E-03 6.930E
11.006 4. 528E-
, 640E-03 4.884E
                           Exhibit 5-1.  Portion of an Events File.


A portion of an example Events file is shown in Figure 5-11 above. This file can become very
large, averaging about 1.4 MB per person-year. For this reason, the user is given the option of
writing the events for only a fraction of the simulated persons.  This is controlled by the Control
file settings EventSample and CustomSample.  See Section 4.2.3 for more information on these
keywords.
                                              106

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REFERENCES

Graham S.E. and T. McCurdy (2005). Revised ventilation rate (V.&) equations for use in
inhalation-oriented exposure models.  EPA/600/X-05/008.

McCurdy, T., G. Glen, L. Smith, and Y. Lakkadi (2000). The National Exposure Research
Laboratory's Consolidated Human Activity Database, Journal of Exposure Analysis and
Environmental Epidemiology 10: 566-578 (2000).

National Research Council (1991).  Human exposure assessment for airborne pollutants:
advances and opportunities. Washington, DC: National Academy of Sciences.

U.S. Environmental Protection Agency (1999).  Total Risk Integrated Methodology. Website:
http://www.epa.gov/ttn/fera/trim fate.html#1999historical
                                         107

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United States                             Office of Air Quality Planning and Standards            Publication No. EPA-452/B-08-001 a
Environmental Protection                  Health and Environmental Impacts Division                                  October 2008
Agency                                          Research Triangle Park, NC

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