Total Risk Integrated Methodology (TRIM) Air 

Pollutants Exposure Model Documentation 

(TRIM.Expo / APEX, Version 4.3) 

Volume I: User's Guide 

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 

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). 

ii
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. 

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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 

CHAPTER 3. 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 Microenvironment Descriptions File ............................................................................. 69 

4.20.1 Microenvironment Descriptions Section .............................................................. 69 

4.20.2 Parameter Descriptions Section ............................................................................ 70 

4.21 Prevalence File............................................................................................................... 77 

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CHAPTER 5. APEX OUTPUT FILES.................................................................................... 79 

5.1 .......................................................................................................................... 81 Log File

5.2 Hourly File..................................................................................................................... 81 

5.3 Timestep File ................................................................................................................. 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 

Table 4-10. 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 

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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 APEX Run................................................................. 16 

Exhibit 1-3. Screenshot of Successful Completion of an APEX Run ......................................... 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 Microenvironment 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 a Profile 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 

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viii

LIST OF FIGURES 

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

....................................................................................................................................................... 55 
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 (TRIM.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 

1
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 II 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: langstaff.john@epa.gov). 

2
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 I is 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.

3
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. 

4
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 

5
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, 

6
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. 

7
Table 3-1. APEX Input and Output Files 

File 

Pollutant 

Specific? 

Simulation Control 

File Keyword 

Input Files 

Simulation Control File - 

Population Data Files POP 

Employment Probability File EMPLOY 

Commuting Flow File COMMUT 

Population Sector Location File SECTOR 

Air District Location File DISTRICT 

Air Quality Data File YES QUALITY 

Meteorology Zone Location File ZONE 

Meteorology Data File METEOR 

MET Mapping File METSMAP 

MET Distribution File DISTRIB 

Physiological Parameters File PHYSIOL 

Ventilation File VENTIL 

Microenvironment Mapping (MEMap) File MEMAP 

Diary Questionnaire (DiaryQuest) File DIARYQUEST 

Diary Events (Diaryevents) File DIARYEVE 

Diary Statistics (Diarystat) File DIARYSTA 

Profile Functions File FUNCTIONS 

Microenvironment Descriptions File MICROENV 

Prevalence File PREV 

Output Files 

Log File LOG 

Hourly File HOUR 

Daily File DAILY 

Microenvironment Results File YES MICRORES 

Profile Summary (Persons) File PSUM 

Microenvironment Summary File YES MICROSUM 

Output Tables File YES TABLE 

Sites File SITE 

Events File EVENT 

Timestep File TIMESTEP 

8
9

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. 
Table 3-2. APEX Settings and Options 

Impact of Changing Def

SETTING/OPTION 

How Option is Selected 

on Other Input F

GENERAL MODEL SETTINGS AND OPTIONS Simulation start/end dates 

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. 

The indicated start and end dates must be inclin the Air district Location, Meteorology Zon

and Air Quality Data files. These files may cand/or after the start and end dates, but must cbetween the specified start and end dates. 

Adjust for Daylight Saving Time (DST) 

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. 

Changing this setting means that the Air Quatypically is in Standard Time) or that the activTime (the supplied CHAD data are based on setting, the output (hourly exposure and dose) contain exactly 24 hours, and all input activithours. 

Model worker commuting 

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. 

If the user chooses to define sectors as somethCommuting Flow file (in addition to a numbecreated corresponding to the new sectors. 

Air quality rollback adjustment (for estimating exposure in hypothetical control scenarios) 

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). 

If the Rollback keyword is changed to “YES” accompanying APEX, the RBTarget, RBBacmust be set to appropriate values. 

Time resolution (length of APEX timestep) 

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 timestep dictates the required time resoluinput. The time resolution of the Air Quality indicated by TimestepsPerDay.

STUDY AREA LOCATION Center 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 Controlfile. The user must always define the appropriate study area center for an application. 

If the study area is changed, the user must enscontain appropriate data for the new location: (unless the included file is used), Air district LLocation file, Meteorology Data file, and Air 

Radius of study area 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 enscontain appropriate data for the new location: 

10
Impact of Changing Def

SETTING/OPTION 

How Option is Selected 

on Other Input F

define the appropriate study area radius for an application. (unless the included file is used), Air district L

Location file, Meteorology Data file, and Air 

Restrict study area to selected counties 

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 Countykeyword 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. 

None, normally. However, if the user does n

sector location file, they must ensure that the 

file provides the county ID for each sector as appropriate format. 

Restrict study area to selected census tracts 

Specified using the TractList keyword 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. 

Locations of sectors 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. 

Sectors identified in Population sector locatio

identified in Population Data files. If the us

from the 2000 Census, the Population sector APEX will be sufficient. All of the sectors ube included in the Population sector location 

files; if sectors other than 2000 Census tracts Commuting file compatible with these sectorsto restrict the study area to selected counties, 

file must include the county IDs associated wIDs in the proper format (as in the supplied fi

Locations of air districts Specified in the Air district Location file. The user must always define the 

appropriate air districts for an application. 

The locations of the air districts must be selecreasonable estimates of air quality for the secthe analysis. Data for each AQ monitor for emust be provided in the Air Quality Data files 

Radius of air district 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 radius of the air districts must be selected sectors the user would like to include in the a

Type of Air Quality Data 

The keyword ModelAQVar 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). 

The value of ModelAQVar dictates the expec

Data file. See Section 4.5 for details. 

Location of meteorological data stations 

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. 

Data for each meteorological data station speLocation file must be provided in the Meteoro

11
Impact of Changing Def

SETTING/OPTION 

How Option is Selected 

on Other Input F

Radius of meteorological station coverage 

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. 

The radius of the zones must be selected such sectors the user would like to include in the a

POLLUTANTS Number of pollutants The number of different pollutants to be modeled must be specified using the 

#Pollutants keyword 

Pollutant Names 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. 

Must be followed in the Control file by the pooutput table levels. 

Model dose for pollutant 

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. 

If DoDose is set to “YES” and CO is being m

correct values for the Altitude, COHBFact ke

PROFILES Number of profiles 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. 

None. 

Modeled populations 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. 

If the user wishes to model a subpopulation, tPopulation Data files with the appropriate co

Profile function options Specified in the Profile Functions file. The user must develop data relevant 

to a particular application prior to performing an APEX simulation. 

None. 

Employment status 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. 

None. 

Minimum and maximum ages for simulated profiles 

Specified using the AgeMin and AgeMax keywords in the Control file. None. 

Modeled age groups 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. 

None. 

Size of age window 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. 

None. 

Probabilities for selecting diaries with missing characteristics 

Using the MissGender, MissEmpl, and MissAge keywords in the Controlfile, the user can specify the probability that activity diary data with missing gender, employment status, or age will selected. 

None. 

12
13

Impact of Changing Def

SETTING/OPTION 

How Option is Selected 

on Other Input F

Type of diary assembly 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. 

If LongitDiary is YES, then the Diary StatistControl file, and the DiaryD and DiaryAutoC 

Physiological parameters for the simulated population 

Specified in the Physiological Parameters file. The default values in this file are suitable for most APEX applications. 

None. 

Activity-specific energy expenditures for the simulated population 

Specified in the MET Mapping and MET Distribution input files. The default values in these files are suitable for most APEX applications. 

None. 

Modeling of disease prevalence 

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 Ill, and produce 

output tables for the subpopulation of modeled persons with Ill=YES. 

If Disease is given a value (a string of maxim

containing the condition name, spaces allowerequires that a Prevalence file be designated a

MICROENVIRONMENTS Maximum number of microenvironments 

Set to an integer using the #Micro keyword in the Control file; must not 

exceed 127. 

Number of APEX microenvironments in the MMicroenvironment Descriptions files must nothe Control file. 

Microenvironment definitions 

Specified in the Microenvironment Descriptions file. The user must develop 

data relevant to a particular application prior to performing an APEX 

simulation. 

Each location referenced in the activity databmapped to one of the microenvironments speDescriptions file using the Microenvironment choose to define custom microenvironmental depend on conditional variables. If so, these Profile Functions file. 

OUTPUTS Produce hourly outputs 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. 

None. 

Produce daily outputs 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. 

None. 

Produce microenvironmental output 

Specified using the MSumOut 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. 

None. 

Produce event output 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. 
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(10)” file, at which time the user would input the location (path) and name of 

the Control file. APEX calls the Control file “Unit(10)” 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(10)” 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
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). 

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
Exhibit 1-2. Screenshot of the Start of an APEX Run 

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
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
Table 4-1. APEX Input File Descriptions 

Input File Description 

Simulation Control

File 

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). 

Population Data

Files 

Contains information on the population (by age group) in each study sector. 

Each race/gender combination has its own file. 

Employment 

Probability File 

Contains employment probabilities by age group, gender, and study sector. 

Commuting Flow File 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). 

Population Sector 

Location File 

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. 

Air District Location

File 

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. 

Meteorology Zone 

Location File 

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. 

Meteorology Data

File 

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. 

Air Quality Data File 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. 

 MET Mapping File 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. 

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. 

Physiological 

Parameters File 

Contains tables of age- and gender-specific physiological parameters. 

18
Input File Description 

Ventilation File This file contains regression parameters used to estimate total ventilation VE 

from MET. 

Microenvironment 

Mapping File 

Provides the mapping from activity location codes in the Diary Events file (e.g., 

from CHAD) to user-defined microenvironments in the Microenvironment 

Descriptions file. 

Diary Questionnaire 

(DiaryQuest) 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). 

Diary Events File 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., CHAD). 

This file contains the same list of diary IDs as the Diary Questionnaire file, in 

the same order. 

Diary Statistics File Contains the value of the key statistic for all CHAD 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 CHAD. This file is not required if 

longitudinal assembly is not being performed (LongitDiary = NO). 

Profile Functions 

(Distributions) File 

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. 

Microenvironment 

Descriptions File 

Contains the definitions of the microenvironments and the microenvironment 

parameters used to determine the exposure concentrations in 

microenvironments. 

Prevalence File 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
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
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 pollutantspecific, 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 

Chapter 5. 

21
! INPUT FILES 

 Zones file = C:\APEX\APEX\METsites.txt 

 Air Quality file, ozone = C:\APEX\AirQuality_ozone.txt 

 Air Quality file, co = C:\APEX\AirQuality_co.txt 

 Districts file = C:\APEX\AQdistricts.txt 

 Meteorology file = C:\APEX\METdata_h.txt 

 Functions file = C:\APEX\ProfileFunctions.txt 

 Microenvironment file = C:\APEX\MicroDescriptions.txt 

 MEMap file = C:\APEX\ME_Mapping.txt 

 DiaryEvent file = C:\APEX\CHADEvents.txt 

 DiaryQuest file = C:\APEX\CHADQuest.txt 

 METSMap file = C:\APEX\CHADMap.txt 

 METS Distribution file = C:\APEX\MetsDists.txt 

 DiaryStat file = C:\APEX\CHADSTATSoutdoor.txt 

 Physiology file = C:\APEX\Physiology.txt 

 Ventilation file = C:\APEX\Ventilation.txt 

 Prevalence file = C:\APEX\Asthma.txt 

 ! 

 ! POPULATION INPUT FILES 

 Pop file, Female, Asian = C:\APEX\pop_fa.txt 

 Pop file, Female, Black = C:\APEX\pop_fb.txt 

 Pop file, Female, Natam = C:\APEX\pop_fn.txt 

 Pop file, Female, Other = C:\APEX\pop_fo.txt 

 Pop file, Female, White = C:\APEX\pop_fw.txt 

 Pop file, Male, Asian = C:\APEX\pop_ma.txt 

 Pop file, Male, Black = C:\APEX\pop_mb.txt 

 Pop file, Male, NatAm = C:\APEX\pop_mn.txt 

 Pop file, Male, Other = C:\APEX\pop_mo.txt 

 Pop file, Male, White = C:\APEX\pop_mw.txt 

 Sectors file = C:\APEX\pop_geo.txt 

 Employment file = C:\APEX\Employment.txt 

 Commuting file = C:\APEX\Commuting2000.txt

Exhibit 4-1. Input Files Section of Simulation Control File 

! OUTPUT FILES 

 log file = C:\APEX\log.txt 

 hourly file = C:\APEX\hours.txt 

 daily file = C:\APEX\days.txt 

 events file = C:\APEX\events.txt 

 persons file = C:\APEX\psum.txt 

 microsum file = C:\APEX\msum.txt 

 microres file = C:\APEX\mres.txt 

 tables file = C:\APEX\tables.txt 

 site file = 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
#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 Type 

(length) Description

#Pollutants Integer 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 Char(40) 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”. 

InputUnits Char(40) Pollutant concentration units used for the input data for the pollutant (ppm or 

μg/m3

). 

OutputUnits Char(40) Pollutant concentration units used for the output data for the pollutant (ppm or 

μg/m3

). 

#Sources Integer 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. 

PPMFactor Real Units conversion factor, the number of μg/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. 

DoDose Char(1) 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. 

Size Real Aerodynamic diameter (particle size) in micrometers for a particle pollutant. This 

parameter is not required for gaseous pollutants. 

Density Real 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, DM1HExp, DM8HExp, TSExp, DMTSExp, DAvgExp, 

SAvgExp, TimeDose, DM1HDose, DM8HDose, 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
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 

Keyword Data 

Type 

Description

Percentiles PERCENTILES Real 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). 

Exposure Cut 

points 

TIMEEXP Real 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) 

Daily Max 1-

Hour 

Exposure Cut 

points 

DM1HEXP Real This parameter specifies the daily maximum 1-hour exposure cutpoints 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.) 

Daily Max 8-

Hour 

Exposure Cut 

points 

DM8HEXP Real 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 DM1HExp except for the longer averaging time. 

(Note: 8-hour tables are not generated with the APEX timestep is 

greater than one hour.) 

Daily Max 

Timestep 

Exposure Cut 

points 

DMTSEXP Real This parameter specifies daily maximum timestep exposure cut 

points for binning all the person days in the simulation period. It is 

similar to DM1HExp 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 exposure cutpoints for counting multiple 

exceedances of timestep levels over the simulation (Exposure table 

type #9; see discussion of Tables file in Chapter 5) 

Daily Average 

Exposure Cut 

points 

DAVGEXP Real This parameter specifies daily average exposure cut-points for 

binning all the person-days in the simulation period. 

Simulation 

Average 

Exposure Cut 

points 

SAVGEXP Real 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. 

Daily Max 1-

Hour Dose 

Cut points 

DM1HDOSE Real 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
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 DM1HDose 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 

DM1HDose 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 Endof-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 

Cut points 

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 

TIMEDOSE 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. 

Time Step 

Multiple 

Exceedance 

Cutpoints 

TSMULTI Real 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
! 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 

 DM1HExp = 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08 

 DM8HExp = 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 

 DM1HExp = 5, 10, 20, 30, 40, 50, 75 

 DM8HExp = 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 

 DM1HDose = 0.5, 1.0, 1.25, 1.5, 1.75, 2.0, 2.25, 2.5, 2.75, 3.0 

 DM8HDose = 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
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 

Type 

(length) Description 

Simulation Parameters 

#Profiles Integer Number of profiles to simulate. 

RandomSeed Integer 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. 

End_Date Integer Simulation end date in YYYYMMDD format. 

FirstProfile Integer 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. 

Start_Date Integer Simulation start date in YYYYMMDD format (e.g., 19960704 for 

July 4, 1996). 

TimeStepsPerDay Integer 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 Parameters 

Location Char(40) Study area location (for output labeling only; not used internally). 

Latitude Real Latitude in decimal degrees for the center of the study area. Note 

that latitude south of the equator is negative. 

Longitude Real 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
Altitude Real 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. 

DSTadjust Char(1) 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. If DSTadjust 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. 

CityRadius Real 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. 

AirRadius Real 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. 

ModelAQVar Char(1) 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. 

ZoneRadius Real Maximum representative radius (km) of temperature data collected 

at a weather station. 

County Char(5) 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. 

CountyList Char(1) 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). 

Tract String 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. 

TractList Char(1) 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 Char(40) Scenario description (for output labeling only; not used internally). 

Microenvironment 

Parameters 

#Micros Integer Number of microenvironments defined in the Microenvironment 

Mapping file and on the Microenvironment Descriptions file. 

Commuting Parameters 

28
Commuting Char(1) 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. 

KeepLeavers Char(1) 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*Cavg+LeaverAdd. If KeepLeavers = N, then these 

individuals are not modeled. 

LeaverAdd Real Additive concentration term applied when working outside study 

area (only used if KeepLeavers = yes). 

LeaverMult Real Multiplicative factor for city-wide average concentration, applied 

when working outside study area (only used if KeepLeavers = yes) 

Diary Selection Parameters 

Age2Prob Real 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. 

If Age2Probab = 0 then shoulder ages are never selected. 

AgeCutPCT Real 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. 

AgeMax Integer Maximum age for simulated profiles (persons). 

AgeMin Integer Minimum age for simulated profiles (persons). 

MissAge Real 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. 

MissEmpl Real 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
MissGender Real 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. If MissGender=0, then diaries with 

missing gender will never be selected. If MissGender=1, 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. 

Dose Parameters 

COHbFactor Real 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. 

Location Parameters 

#OtherDistricts Integer 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.) 

CustomWork Commadelimited 

list of 

CHAD 

activity 

codes 

List of CHAD activity codes that will be assigned to location = W 

(Work). 

HomeProbab Real 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. 

SampleOtherLocs Char(1) 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 Parameters 

RbBack Real Rollback background concentration. Use same units as InputUnits.

RbMax Real Rollback maximum concentration. Use same units as InputUnits.

RbTarget Real Rollback target concentration. Use same units as InputUnits.

Rollback Char(1) 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. 

Diagnostic Parameters 

DebugLevel Integer A value > 0 results in more information being written to the log file 

than for a value of zero. 

30
Log File Switches 

LogDistrict Char(1) 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(1) 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 

(WorkInside); 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). 

LogProfiles Char(1) 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 (WorkInside); 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(1) 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(1) Y = all the tables that are written to the Tables file are also written to 

the Log file. 

LogZones Char(1) 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 Commaseparated 

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 if EventsOut=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 spaceseparated 

strings 

List of keywords indicating which variables are to be written to the 

Daily output file. See section 5.4 for details. 

31
DailyOut Char(1) Y= the Daily output file containing values of daily parameters 

(exposures, doses, etc.) is created. Otherwise it is not written. 

EventSample Integer Dictates which profiles have their event data written to the Events

file. If EventSample=K, then the data for every Kth profile is 

written. 

EventsOut Char(1) Y = the output file containing the event-level model outputs for each 

simulated individuals is written. Otherwise, the file is not written. 

HourlyList comma 

or spaceseparated 

strings 

List of keywords indicating which variables are to be written to the 

Hourly output file. See section 5.2 for details. 

HourlyOut Char(1) Y= the Hourly output file containing values of hourly parameters 

(exposures, doses, etc.) is created. Otherwise it is not written. 

MResHome Char(1) 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. 

MResList comma 

or spaceseparated 

strings 

List of keywords indicating which variables are to be written to the 

Microenvironmental Results output file. See section 5.6 for details. 

MResMicros commaseparated 

list of 

integers 

A comma-separated list of integers that indicate the 

microenvironments for which data will be written to the 

Microenvironmental Results file. 

MResOut Char(1) Y = the Microenvironmental Results file will be created. Otherwise, 

the file is not written. 

MSumOut Char(1) Y = the Microenvironmental Summary file will be created. 

Otherwise, the file is not written. 

PsumList comma 

or spaceseparated 

strings 

List of keywords indicating which variables are to be written to the 

Profile Summary output file. See section 5.5 for details. 

VaOutput Char(1) Y = the calculated alveolar ventilation rate will be written to the 

events file. Otherwise the values are not output. 

TimeStepOut Char(1) 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. 

TimeStepList comma 

or spaceseparated 

strings 

List of keywords indicating which variables are to be written to the 

Timestep output file. See Section 5.3for details. 

Tables Parameters 

ActivePAI Real 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. 

ChildMax Integer Maximum age for inclusion in the "child" and "active child" 

population subgroups in the output exposure tables. 

32
ChildMin Integer Minimum age for inclusion in the "child" and "active child" 

population subgroups in the output exposure tables. 

HeavyEVR1 Real 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. 

HeavyEVR8 Real 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. 

HeavyEVRTS Real 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. 

ModEVR1 Real 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. 

ModEVR8 Real 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. 

ModEVRTS Real 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. 

Longitudinal Diary 

Selection Parameters 

DiaryAutoC Real Lag-1 autocorrelation statistic for the longitudinal diary assembly 

algorithm. Provides a target for the autocorrelation in the key diary 

statistic. 

DiaryD Real 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. 

LongitDiary Char(1) 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). 

Disease Parameters 

Disease Char(12) 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
! ------- PARAMETER SETTINGS ------- 

! SIMULATION PARAMETERS 

 #Profiles = 40000 

 RandomSeed = 0 

 Start_date = 20040401 

 End_date = 20040930 

! 

! 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 

! 

! MICROENVIRONMENT PARAMETERS 

 #Micros = 12 

! 

! COMMUTING PARAMETERS 

 Commuting = YES 

 KeepLeavers = YES 

 LeaverMult = 0.0 

 LeaverAdd = 0.0 

! 

! 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 

! 

! DOSE PARAMETERS 

 COHbFact = 2.5 

! 

!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 

! 

! LOG FILE SWITCHES 

 LogDistrict = NO 

 LogPopulate = NO 

 LogProfiles = NO 

 LogSectors = NO 

 LogTables = NO 

 LogZones = NO 

 VAOutput = NO 

! 

! 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 

! 

! TABLES PARAMETERS 

 HeavyEVR1 = 30 

 HeavyEVR8 = 99 

 ModEVR1 = 16 

 ModEVR8 = 13 

 ActivePAI = 1.76 

! 

! 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 casesensitive, 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 Latitude Longitude 

01001020100 32.470986 -86.487033 

01001020200 32.466056 -86.472934 

01001020300 32.474035 -86.457764 

01001020400 32.466794 -86.445569 

01001020500 32.454933 -86.425025 

01001020600 32.439950 -86.478442 

01001020700 32.438025 -86.443068 

01001020800 32.502299 -86.495082 

01001020900 32.644428 -86.501249 

...

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 an example metropolitan area 

! This file contains the locations of 105 air quality districts 

! Created on November 4, 2005 

0000100010 34.371470 -85.461103 20040301 20041031 

0000100009 34.194947 -85.461103 20040301 20041031 

0000100008 34.018423 -85.461103 20040301 20041031 

0000100007 33.841899 -85.461103 20040301 20041031 

0000100006 33.665375 -85.461103 20040301 20041031 

0000100005 33.488851 -85.461103 20040301 20041031 

0000100004 33.312327 -85.461103 20040301 20041031 

0000100003 33.135804 -85.461103 20040301 20041031 

0000200011 34.547994 -85.239577 20040301 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 10/31/04 

! Created on November 4, 2005 

Name = Site0000100003 

0.01553 0.01825 0.02621 0.02989 0.02975 0.02650 0.02310 ... 0.03891 20040301 

0.03822 0.03738 0.03749 0.03754 0.03687 0.03550 0.03240 ... 0.00948 20040302 

0.00577 0.00570 0.00528 0.00477 0.00394 0.00453 0.00430 ... 0.01169 20040303 

0.01456 0.01828 0.01916 0.01810 0.01547 0.00925 0.00591 ... 0.03326 20040304 

0.03354 0.03244 0.02412 0.01705 0.01293 0.01076 0.01066 ... 0.02849 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 II 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 testing 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 0.10 Y 

 20040101 2 Normal 0.01121 .00005 . . 0 0.10 Y 

 20040101 3 Normal 0.01184 .00005 . . 0 0.10 Y 

 20040101 4 Normal 0.01067 .00005 . . 0 0.10 Y 

 20040101 5 Normal 0.01231 .00005 . . 0 0.10 Y 

 20040101 6 Normal 0.01515 .00005 . . 0 0.10 Y 

 20040101 7 Normal 0.01537 .00005 . . 0 0.10 Y 

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 35.4333 -82.5333 20040101 20041231 

03813 32.7000 -83.6500 20040101 20041231 

03816 37.0667 -88.7667 20040101 20041231 

03820 33.3667 -81.9667 20040101 20041231 

03856 34.6500 -86.7667 20040101 20041231 

03870 34.9000 -82.2167 20040101 20041231 

03937 30.1167 -93.2167 20040101 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 II). 

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 

!Date Hr Temp Humidity Prec Windspeed Direction 

name=03812 

20040101 1 64.0000000 30.0000019 RA 12.0000038 180.0000458 

20040101 2 64.0509644 30.1274014 CL 12.2548046 182.5480499 

20040101 3 64.7050323 31.7625809 RA 15.5251617 215.2516174 

20040101 4 65.3338318 33.3345718 CL 18.6691437 246.6914520 

20040101 5 65.9261093 34.8152771 CL 21.6305542 276.3055420 

20040101 6 65.6765747 34.1914406 CL 20.3828812 263.8288269 

... 

name=03813 

20040101 1 66.1480103 30.3700294 CL 12.7400570 187.4005737 

20040101 2 67.6218567 34.0546417 CL 20.1092834 261.0928345 

41
20040101 3 67.6839142 34.2097778 CL 20.4195595 264.1955872 

20040101 4 66.9728241 32.4320602 CL 16.8641205 228.6412048 

20040101 5 66.3958359 30.9895973 CL 13.9791956 199.7919617 

20040101 6 66.9397125 32.3492851 CL 16.6985664 226.9856720 

... 

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 record 2: 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 = Asian or Pacific Islander 

Age group minimum = 0 1 2 3 4 5 6 7 8 9 10 11 12 ... 98 99 

Age group maximum = 0 1 2 3 4 5 6 7 8 9 10 11 12 ... 98 99 

! 

01001020100 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 ... 0 0 

01001020200 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 ... 0 0 

01001020300 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 

01001020400 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 ... 0 0 

01001020500 0 2 0 1 1 0 1 2 1 0 1 0 0 0 0 0 0 0 ... 0 0 

01001020600 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 ... 0 0

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 gender and age group from 2000 census 

! Prepared by ManTech Environmental Technology, Inc. for EPA in April 2003 

Gender= M M M M ... F F 

MinAge= 16 20 22 25 ... 70 75 

MaxAge= 19 21 24 29 ... 74 200 

01001020100 0.39744 1.00000 0.32258 0.83636 ... 0.00000 0.00000 

01001020200 0.45283 0.26415 0.70588 0.79167 ... 0.00000 0.12500 

01001020300 0.55056 0.82857 1.00000 0.95200 ... 0.08475 0.00000 

01001020400 0.34921 0.79310 1.00000 0.91818 ... 0.19192 0.00000 

01001020500 0.57143 0.88889 1.00000 0.96503 ... 0.00000 0.00000 

01001020600 0.64583 1.00000 1.00000 0.87500 ... 0.08621 0.00000 

01001020700 0.38554 0.48571 0.91304 0.90698 ... 0.37500 0.07692 

01001020800 0.29712 0.56757 1.00000 0.79693 ... 0.00000 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 

13600 Obtain car services 

13700 Other repairs 

10100 Work, General 13800 Other services 

10110 Work, general, for organizational 14000 Personal needs and care, general 

45
Activity 

Code Description 

Activity 

Code Description 

 activities 

10111 Work for professional/union organizations 14100 Shower, bathe, personal hygiene 

10112 Work for special interest identity 14110 Shower, bathe 

 organizations 14120 Personal hygiene 

10113 Work for political party and civic 14200 Medical care 

 participation 14300 Help and care 

10114 Work for volunteer/ helping organizations 14400 Eat 

10115 Work of/for religious groups 14500 Sleep or nap 

10116 Work for fraternal organizations 14600 dress, groom 

10117 Work for child / youth / family 

 organizations 

14700 Other personal needs 

10118 Work for other organizations 15000 General education and professional 

 training 

10120 Work, income-related only 15100 Attend full-time school 

10130 Work, secondary (income-related) 15110 Attend day-care 

10200 Unemployment 15120 Attend K-12 

10300 Breaks 15130 Attend college or trade school 

11000 General household activities 15140 Attend adult education and special 

 training 

11100 Prepare food 15200 Attend other classes 

11110 Prepare and clean-up food 15300 Do homework 

11200 Indoor chores 15400 Use library 

11210 Clean-up food 15500 Other education 

11220 Clean house 16000 General entertainment / social activities 

11300 Outdoor chores 16100 Attend sports events 

11310 Clean outdoors 16200 Participate in social, political, or religious 

11400 Care of clothes activities 

11410 Wash clothes 16210 Practice religion 

11500 Build a fire 16300 Watch movie 

11600 Repair, general 16400 Attend theater 

11610 Repair of boat 16500 Visit museums 

11620 Paint home / room 16600 Visit 

11630 Repair / maintain car 16700 Attend a party 

11640 Home repairs 16800 Go to bar / lounge 

11650 Other repairs 16900 Other entertainment / social events 

11700 Care of plants 17000 Leisure, general 

11800 Care for pets/animals 17100 Participate in sports and active leisure 

11900 Other household 17110 Participate in sports 

12000 Child care, general 17111 Hunting, fishing, hiking 

12100 Care of baby 17112 Golf 

12200 Care of child 17113 Bowling / pool / ping pong / pinball 

12300 Help / teach 17114 Yoga 

12400 Talk /read 17120 Participate in outdoor leisure 

12500 Play indoors 17121 Play, unspecified 

12600 Play outdoors 17122 Passive, sitting 

12700 Medical care-child 17130 Exercise 

12800 Other child care 17131 Walk, bike, or jog (not in transit) 

13000 Obtain goods and services, general 17140 Create art, music, participate in hobbies 

13100 Dry clean 17141 Participate in hobbies 

46
Activity 

Code Description 

Activity 

Code Description 

13200 Shop / run errands 17142 Create domestic crafts 

13210 Shop for food 17143 Create art 

13220 Shop for clothes or household goods 17144 Perform music / drama / dance 

13230 Run errands 17150 Play games 

13300 Obtain personal care service 17160 Use of computers 

13400 Obtain medical service 17170 Participate in recess and physical 

 education 

13500 Obtain government / financial services 17180 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 file 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 Age Occ. APEX Dist# Notes 

10000 0 ADMIN 1 Work, general 

10000 0 ADMSUP 1 Work, general 

10000 0 FARM 2 Work, general 

10000 0 HSHLD 3 Work, general 

10000 0 LABOR 4 Work, general 

10000 0 MACH 5 Work, general 

10000 0 PREC 6 Work, general 

10000 0 PROF 7 Work, general 

10000 0 PROTECT 7 Work, general 

10000 0 SALE 7 Work, general 

10000 0 SERV 8 Work, general 

10000 0 TECH 9 Work, general 

10000 0 TRANS 10 Work, general 

10000 0 X 11 Work, general 

10300 0 Any 12 Breaks 

11000 0 Any 13 General household activities 

11100 0 Any 14 Prepare food 

11110 0 Any 15 Prepare and clean-up food 

11200 0 Any 16 Indoor chores 

11210 0 Any 17 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. 

• Par1. 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. 

• UTrunc. 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 II 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 

APEX 

KEYWORD Par1 Par2 Par3 Par4 

LTrunc 

(Optional) 

UTrunc 

(Optional) 

ResampOut 

(Optional) 

Beta BETA Minimum Maximum 

Shape1 

(s1) > 0 

Shape2 

(s2) > 0 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Cauchy CAUCHY Median 

Scale (b) 

> 0 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Discrete DISCRETE 

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.

Exponential EXPONENTIAL 

Decay 

constant, k 

> 0 Shift (a) 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Extreme 

Value EVALUE 

Scale (b) 

> 0 Shift (a) 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Gamma GAMMA 

Shape (s) 

> 0 

Scale (b) 

> 0 Shift (a) 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Logistic LGT Mean 

Scale (b) 

> 0 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Lognormal LOGNORMAL 

Geometric 

mean (gm) 

of unshifted 

dist 

Geometric 

standard 

deviation 

(gsd) > 1 Shift (a) 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Loguniform LUNIFORM 

Minimum 

> 0 

Maximum 

> 0 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Normal NORMAL Mean 

Standard 

deviation 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

OffOn OFFON 

Probability 

of being 0 

(0-1) 

49
Distribution 

APEX 

KEYWORD Par1 Par2 Par3 Par4 

LTrunc 

(Optional) 

UTrunc 

(Optional) 

ResampOut 

(Optional) 

Pareto PARETO 

Shape (s) 

> 0 

Scale (b) 

> 0 Shift (a) 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Point POINT Point Value 

Triangle TRIANGLE Minimum Maximum Peak 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Uniform UNIFORM Minimum Maximum 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

Resample 

outside 

truncation? 

(Y/N) 

Weibull WEIBULL 

Shape (s) 

> 0 

Scale (b) 

> 0 Shift 

Lower 

truncation 

limit 

Upper 

truncation 

limit 

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 

!Dist Shape Par1 Par2 Par3 Par4 LTrunc UTrunc ResampOut General Use 

1 Lognormal 1.7 1.2 0 . 1.4 2.7 Y Work, admin 

2 Lognormal 7 1.5 0 . 3.6 17 Y Work, farm 

3 Lognormal 3.5 1.2 0 . 2.5 6 Y Work, household 

4 Triangle 3.6 13.8 8.1 . . . Y Work, labor 

5 Uniform 4 6.5 . . . . Y Work, mech 

6 Triangle 2.5 4.5 3.3 . . . Y Work, prec 

7 Triangle 1.2 5.6 2.9 . . . Y Work,profess/protect/sales 

8 Triangle 1.6 8.4 5.6 . . . Y Work, service 

9 Triangle 2.5 4.5 2.9 . . . Y Work, tech 

10 Lognormal 3 1.5 0 . 1.3 8.4 Y Work, trans 

11 Triangle 1.2 5.6 1.9 . . . Y Work, missing occup 

12 Uniform 1 2.5 . . . . Y Breaks 

13 Triangle 1.5 8 4.6 . . . Y General household actv 

14 Lognormal 2.5 1.2 0 . 2 4 Y Prepare food 

15 Exponential 1.11 1.9 . . . 4 Y Prepare and clean-up food 

16 Exponential 0.71 2 . . . 5 Y Indoor chores 

17 Uniform 2.3 2.7 . . . . Y Clean-up food 

18 Exponential 0.53 2.2 . . . 5 Y Clean house 

19 Normal 5 1 . . 2 7 Y Outdoor chores 

20 Exponential 0.37 2.6 . . . 6 Y Clean outdoors 

21 Exponential 1.43 1.5 . . . 4 Y Care of clothes 

22 Point 2 . . . . . Y Wash clothes /build fire 

23 Normal 4.5 1.5 . . 2 8 Y Repair, general 

24 Point 4.5 . . . . . Y Repair of boat 

25 Exponential 0.71 3.5 . . . 6 Y Paint home / room 

26 Triangle 3 4.5 3.01 . . . Y 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 Variable Units 

NVO2MAX Normalized maximum oxygen uptake 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) 

BM Body mass kg 

RMRINT Intercept of resting metabolic rate regression MJ/day 

(Note: while the APEX inputs for RMR are in 

MJ/day, APEX outputs RMR in the Profile 

Summary file in kcal/min). 

RMRSLP Slope of resting metabolic rate regression MJ/(day-kg) 

RMRERR Standard deviation for resting metabolic rate 

regression 

MJ/day 

HMG Blood hemoglobin density g/dl 

BSAEXP1 Exponent 1 for calculating body surface area - 

BSAEXP2 Exponent 2 for calculating body surface area - 

MAXOXD Maximum oxygen deficit ml/kg 

BLDFAC1 Blood volume factor 1 ml/lb 

BLDFAC2 Blood volume factor 2 ml/inches3

HEIGHTINT Intercept of height regression inches 

HEIGHTSLP Slope of height regression children under 18:

inches/(year of age) 

adults: 

inches/ln(lbs body weight) 

HEIGHTERR Standard deviation of height regression inches 

ECF Energy conversion factor L-O2/kcal 

RECTIME Time required to recover maximum oxygen 

deficit 

hours 

ENDGN1 Endogenous CO production rate 1 ml/min 

ENDGN2 Endogenous CO production rate 2 (used for 

women in 2nd half of menstrual cycle) 

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
• 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. 

• Par1. 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
! APEX Physiology Data, revised May 4, 2006 

!Variable AgeMin AgeMax Gen Shape Par1 Par2 Par3 Par4 LTrunc UTrunc ResampOut 

!NVO2Max 

NVO2MAX 0 0 M Normal 48.3 1.7 . . 44.3 52.2 N 

NVO2MAX 1 1 M Normal 48.6 2.0 . . 43.8 53.3 N 

NVO2MAX 2 2 M Normal 48.9 2.4 . . 43.4 54.4 N 

NVO2MAX 3 3 M Normal 49.2 2.7 . . 43.0 55.4 N 

NVO2MAX 4 4 M Normal 49.5 3.0 . . 42.5 56.5 N 

NVO2MAX 5 5 M Normal 49.8 3.3 . . 42.1 57.6 N 

NVO2MAX 6 6 M Normal 50.1 3.7 . . 41.6 58.6 N 

NVO2MAX 7 7 M Normal 50.4 4.0 . . 41.2 59.7 N 

NVO2MAX 8 8 M Normal 50.8 4.3 . . 40.8 60.8 N 

NVO2MAX 9 9 M Normal 51.1 4.6 . . 40.3 61.8 N 

. 

. 

.

! Body Mass 

BM 0 0 M Lognormal 7.8 1.301 0 . 3.6 11.8 N 

BM 1 1 M Lognormal 11.4 1.143 0 . 8.2 16.1 N 

BM 2 2 M Lognormal 13.9 1.146 0 . 9.8 20.9 N 

BM 3 3 M Lognormal 16.0 1.154 0 . 11.7 23.7 N 

BM 4 4 M Lognormal 18.5 1.165 0 . 11.1 28.1 N 

BM 5 5 M Lognormal 21.6 1.234 0 . 13.7 42.4 N 

BM 6 6 M Lognormal 23.1 1.213 0 . 16.1 41.1 N 

BM 7 7 M Lognormal 27.1 1.216 0 . 19.3 46.8 N 

BM 8 8 M Lognormal 31.7 1.302 0 . 19.1 66.2 N 

BM 9 9 M Lognormal 34.7 1.265 0 . 24.0 69.9 N 

BM 10 10 M Lognormal 38.3 1.280 0 . 24.3 72.9 N 

BM 11 11 M Lognormal 44.1 1.308 0 . 26.2 83.8 N 

BM 12 12 M Lognormal 48.0 1.315 0 . 27.7 94.8 N 

. 

. 

.

! Intercept for RMR regression 

RMRINT 0 2 M Point -0.127 . . . . . . 

RMRINT 3 9 M Point 2.110 . . . . . . 

RMRINT 10 17 M Point 2.754 . . . . . . 

RMRINT 18 29 M Point 2.896 . . . . . . 

RMRINT 30 70 M Point 3.653 . . . . . . 

RMRINT 71 100 M Point 2.459 . . . . . . 

RMRINT 0 2 F Point -0.130 . . . . . .

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
! APEX4 Ventilation Data File 

! MinAge MaxAge b0 seb0 b1 seb1 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
Built-in profile

functions

User-defined profile

functions

Built-in

and user-defined

conditional

variables

VC

Profile 

Functions

File

Micro parameters, 

MP

Micro 

concentrations

Micro 

Descriptions

File

Input variables

VI

DiaryPools

Built-in profile

functions

User-defined profile

functions

Built-in

and user-defined

conditional

variables

VC

Profile 

Functions

File

Micro parameters, 

MP

Micro 

concentrations

Micro 

Descriptions

File

Input variables

VI

DiaryPools

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 (RegionalConditional1-5), 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
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
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=1 and WindowRes=2 for AC_Home=1, 

57
58

MaxTemp<56, and any AvgTemp value. The last line are the probabilities for WindowRes=1 

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. 
Table 4-8. Variables That Can Be Defined in the Profile Functions File 

Conditional Variable Purpose Input Variables Number of 

Categories 

TempCat Binning hourly temperatures into 

categories 

INPUT1: Temperature on hour of simulation any number 

HumidCat Binning hourly humidities into 

categories 

INPUT1: Humidity on hour of simulation any number 

WindCat Binning hourly wind speeds into 

categories 

INPUT1: Wind speed on hour of simulation any number 

DirCat Binning hourly wind directions into 

categories 

INPUT1: Wind direction on hour of simulation any number 

PrecipCat Assigning precipitation codes to 

categories 

INPUT1: Precipitation code on hour of simulation any number 

(equal to or 

less than the 

number of 

precipitation 

codes in the 

Meteorology 

Data file) 

MaxTempCat Binning daily maximum temperatures 

into categories 

INPUT1: Temperature on hour of simulation any number 

AvgTempCat Binning daily average temperatures 

into categories 

INPUT1: 24-hour average temperature on day of simulation (AvgTemp) 

any number 

Diary Pools (Required)

Assigning diary pools INPUT1: Maximum temperature on simulated day (MaxTemp) 

INPUT2: Average temperature on simulated day (AvgTemp) INPUT3: Day of the week 

any number 

HasGasStove Probability of having a gas stove INPUT1: Probabilities for the 2 results 2 (Y/N) HasGasPilot Probability of having a pilot light, 

conditional on HasGasStove 

INPUT1: Has Gas Stove (Y/N)? (HasGasStove) INPUT2: Conditional Probabilities for the result categories for both HasGasStove=Y and HasGasStove=N 

2 (Y/N) 

AC_Home Probability of having different types of 

home air conditioning or ventilation 

INPUT1: Fixed probabilities for the types of air conditioning / 

ventilation (the number of types is user-defined) 

any number 

AC_Car Probability of having A/C in car INPUT1: Probabilities for the 2 results 2 (Y/N) WindowRes Probability of residence windows 

being open or closed, conditional on AC_Home, MaxTempCat, and AvgTempCat 

INPUT1: Type of home A/C (AC_Home) INPUT2: Max. temperature on day of simulation (MaxTemp) INPUT3: Average temperature on day of simulation (AvgTemp)

INPUT4: Conditional probabilities for the result categories for every combination of input1-input3 categories 

2 (Y/N) 

WindowCar Probability of car windows being open INPUT1: Has car A/C (AC_Car) 2 (Y/N) 

59
60

Conditional Variable Purpose Input Variables Number of 

Categories 

or closed, conditional on AC_Car, MaxTempCat, and AvgTempCat 

INPUT2: Max. temperature on day of simulation (MaxTemp) INPUT3: Average temperature on day of simulation (AvgTemp)INPUT4: Conditional probabilities for the result categories for every combination of input1-input3 categories 

SpeedCat Probability of average speed categories 

for vehicles 

INPUT1: Fixed probabilities for the result categories any number 

DailyConditional1 Generic daily conditional variable #1 INPUT1: Fixed probabilities for the result categories any number DailyConditional2 Generic daily conditional variable #2 INPUT1: Fixed probabilities for the result categories any number DailyConditional3 Generic daily conditional variable #3 INPUT1: Fixed probabilities for the result categories any number ProfileConditional1 Generic profile conditional variable #1 INPUT1: Fixed probabilities for the result categories any number ProfileConditional2 Generic profile conditional variable #2 INPUT1: Fixed probabilities for the result categories any number ProfileConditiona3 Generic profile conditional variable #3 INPUT1: Fixed probabilities for the result categories any number ProfileConditional4 Generic profile conditional variable #4 INPUT1: Fixed probabilities for the result categories any number ProfileConditional5 Generic profile conditional variable #5 INPUT1: Fixed probabilities for the result categories any number RegionalConditional1 Generic regional conditional variable 

#1 

INPUT1: Fixed probabilities for the result categories, defined for 

each region (sector or county) modeled 

any number 

RegionalConditional2 Generic regional conditional variable 

#2 

INPUT1: Fixed probabilities for the result categories, defined for 

each region (sector or county) modeled 

any number 

RegionalConditional3 Generic regional conditional variable 

#3 

INPUT1: Fixed probabilities for the result categories, defined for 

each region (sector or county) modeled 

any number 

RegionalConditional4 Generic regional conditional variable 

#4 

INPUT1: Fixed probabilities for the result categories, defined for 

each region (sector or county) modeled 

any number 

RegionalConditional5 Generic regional conditional variable 

#5 

INPUT1: Fixed probabilities for the result categories, defined for 

each region (sector or county) modeled 

any number 
AvgTempCat 

! Temperature ranges (categories) in Fahrenheit 

INPUT1 INTRANGE 3 "AvgTemp" 

50 78 

RESULT INTEGER 3 "TempCatA" 

1 2 3 

# 

WindowRes 

! Home windows open(1) 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 

1 2 3 4 

# 

RegionalConditional1 

! 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 DailyConditional3. 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
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 

RegionalConditional1. 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 RegionalConditional1-5 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,1=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" 

INPUT3 INTINDEX 7 "DayOfWeek" 

RESULT INTEGER 7 "Pool number" 

1 1 1 1 1 1 1 

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
“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 

II 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 ‘U’ and ‘X’). 

63
Table 4-9. CHAD Location Codes 

Location 

Code Description 

Location 

Code Description 

X No data 31210 Walk 

U Uncertain of correct code 31230 In stroller or carried by adult 

30000 Residence- general 31300 Waiting for travel 

30010 Your residence 31310 ... bus or train stop 

30020 Other residence 31320 ... indoors 

30100 Residence- indoor 31900 Travel- other 

30120 Your residence- indoor 31910 ... other vehicle 

30121 ... kitchen 32000 Non-residence indoor- general 

30122 ... living room or family room 32100 Office building/ bank/ post office 

30123 ... dining room 32200 Industrial/ factory/ warehouse 

30124 ... bathroom 32300 Grocery store/ convenience store 

30125 ... bedroom 32400 Shopping mall/ non-grocery store 

30126 ... study or office 32500 Bar/ night club/ bowling alley 

30127 ... basement 32510 Bar or night club 

30128 ... utility or laundry room 32520 Bowling alley 

30129 ... other indoor 32600 Repair shop 

30130 Other residence- indoor 32610 Auto repair shop/ gas station 

30131 ... kitchen 32620 Other repair shop 

30132 ... living room or family room 32700 Indoor gym /health club 

30133 ... dining room 32800 Childcare facility 

30134 ... bathroom 32810 ... house 

30135 ... bedroom 32820 ... commercial 

30136 ... study or office 32900 Large public building 

30137 ... basement 32910 Auditorium/ arena/ concert hall 

30138 ... utility or laundry room 32920 Library/ courtroom/ museum/ theater 

30139 ... other indoor 33100 Laundromat 

30200 Residence- outdoor 33200 Hospital/ medical care facility 

30210 Your residence- outdoor 33300 Barber/ hair dresser/ beauty parlor 

30211 ... pool or spa 33400 Indoors- moving among locations 

30219 ... other outdoor 33500 School 

30220 Other residence- outdoor 33600 Restaurant 

30221 ... pool or spa 33700 Church 

30229 ... other outdoor 33800 Hotel/ motel 

30300 Residential garage or carport 33900 Dry cleaners 

30310 ... indoor 34100 Indoor parking garage 

30320 ... outdoor 34200 Laboratory 

30330 Your garage or carport 34300 Indoor- none of the above 

30331 ... indoor 35000 Non-residence outdoor- general 

30332 ... outdoor 35100 Sidewalk- street 

30340 Other residential garage or carport 35110 Within 10 yards of street 

30341 ... indoor 35200 Outdoor public parking lot /garage 

30342 ... outdoor 35210 ... public garage 

30400 Residence- none of the above 35220 ... parking lot 

31000 Travel- general 35300 Service station/ gas station 

31100 Motorized travel 35400 Construction site 

31110 Car 35500 Amusement park 

31120 Truck 35600 Playground 

64
Location 

Code Description 

Location 

Code Description 

31121 Truck (pickup or van) 35610 ... school grounds 

31122 Truck (not pickup or van) 35620 ... public or park 

31130 Motorcycle or moped 35700 Stadium or amphitheater 

31140 Bus 35800 Park/ golf course 

31150 Train or subway 35810 Park 

31160 Airplane 35820 Golf course 

31170 Boat 35900 Pool/ river/ lake 

31171 Boat- motorized 36100 Outdoor restaurant/ picnic 

31172 Boat- other 36200 Farm 

31200 Non-motorized travel 36300 Outdoor- none of the above 

! APEX4 Microenvironment Mapping File 

! Mapping of CHAD activity locations to APEX microenvironments 

!CHAD Loc. Description Micro # Location Notes 

--------- ------------------------------------------------------------------------------- 

U Uncertain of correct code = -1 U Unknown 

X No data = -1 U Unknown 

30000 Residence, general = 1 H Home 

30010 Your residence = 1 H Home 

30020 Other residence = 1 H Home 

30100 Residence, indoor = 1 H Home 

30120 Your residence, indoor = 1 H Home 

30121 ..., kitchen = 1 H Home 

30122 ..., living room or family room = 1 H Home 

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, TUE, ..., 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
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. 

BAL97001A,TUE,F,W,N, 77, 43,X , 45, 29

BAL97001B,WED,F,W,N, 77, 51,X , 135, 28

BAL97001C,THU,F,W,N, 77, 57,X , 15, 30

BAL97001D,FRI,F,W,N, 77, 45,X , 0, 28

BAL97001E,TUE,F,W,N, 77, 47,X , 0, 27

BAL97001F,WED,F,W,N, 77, 36,X , 0, 28

BAL97001G,THU,F,W,N, 77, 38,X , 0, 26

BAL97001H,FRI,F,W,N, 77, 43,X , 0, 28

BAL97001I,TUE,F,W,N, 77, 41,X , 15, 28

BAL97001J,WED,F,W,N, 77, 54,X , 15, 28

BAL97001K,THU,F,W,N, 77, 48,X , 0, 30

BAL97001L,FRI,F,W,N, 77, 42,X , 30, 30

BAL97006A,WED,M,W,N, 80, 51,X , 0, 31

BAL97006B,THU,M,W,N, 80, 57,X , 60, 36

BAL97006C,FRI,M,W,N, 80, 45,X , 75, 31

BAL97006D,TUE,M,W,N, 80, 47,X , 15, 33

BAL97006E,WED,M,W,N, 80, 36,X , 30, 31

BAL97006F,THU,M,W,N, 80, 38,X , 210, 34

BAL97006G,FRI,M,W,N, 80, 43,X , 165, 30

BAL97006H,TUE,M,W,N, 80, 41,X , 45, 31

BAL97006I,WED,M,W,N, 80, 54,X , 60, 34

BAL97006J,THU,M,W,N, 80, 48,X , 15, 31

BAL97008A,TUE,F,W,N, 88, 43,X , 0, 31

BAL97008B,WED,F,W,N, 88, 51,X , 60, 27

BAL97008C,THU,F,W,N, 88, 57,X , 345, 33

BAL97008D,FRI,F,W,N, 88, 45,X , 90, 28

BAL97008E,TUE,F,W,N, 88, 47,X , 30, 29

BAL97008F,WED,F,W,N, 88, 36,X , 90, 26

BAL97001A,TUE,F,W,N, 77, 43,X , 45, 29

BAL97001B,WED,F,W,N, 77, 51,X , 135, 28

BAL97001C,THU,F,W,N, 77, 57,X , 15, 30

BAL97001D,FRI,F,W,N, 77, 45,X , 0, 28

BAL97001E,TUE,F,W,N, 77, 47,X , 0, 27

BAL97001F,WED,F,W,N, 77, 36,X , 0, 28

BAL97001G,THU,F,W,N, 77, 38,X , 0, 26

BAL97001H,FRI,F,W,N, 77, 43,X , 0, 28

BAL97001I,TUE,F,W,N, 77, 41,X , 15, 28

BAL97001J,WED,F,W,N, 77, 54,X , 15, 28

BAL97001K,THU,F,W,N, 77, 48,X , 0, 30

BAL97001L,FRI,F,W,N, 77, 42,X , 30, 30

BAL97006A,WED,M,W,N, 80, 51,X , 0, 31

BAL97006B,THU,M,W,N, 80, 57,X , 60, 36

BAL97006C,FRI,M,W,N, 80, 45,X , 75, 31

BAL97006D,TUE,M,W,N, 80, 47,X , 15, 33

BAL97006E,WED,M,W,N, 80, 36,X , 30, 31

BAL97006F,THU,M,W,N, 80, 38,X , 210, 34

BAL97006G,FRI,M,W,N, 80, 43,X , 165, 30

BAL97006H,TUE,M,W,N, 80, 41,X , 45, 31

BAL97006I,WED,M,W,N, 80, 54,X , 60, 34

BAL97006J,THU,M,W,N, 80, 48,X , 15, 31

BAL97008A,TUE,F,W,N, 88, 43,X , 0, 31

BAL97008B,WED,F,W,N, 88, 51,X , 60, 27

BAL97008C,THU,F,W,N, 88, 57,X , 345, 33

BAL97008D,FRI,F,W,N, 88, 45,X , 90, 28

BAL97008E,TUE,F,W,N, 88, 47,X , 30, 29

BAL97008F,WED,F,W,N, 88, 36,X , 90, 26

Exhibit 4-20. Example Portion of a Diary Questionnaire File 

Table 4-10. CHAD Occupation Codes 

Code Description 

ADMIN Executive, administrative, and managerial 

PROF Professional 

TECH Technicians 

SALE Sales 

ADMSUP Administrative support 

HSHLD Private household 

PROTECT Protective services 

SERV Service 

FARM Farming, forestry, and fishing 

PREC Precision production, craft, and repair 

66
Code Description 

MACH Machine operators, assemblers, and inspectors 

TRANS Transportation and material moving 

LABOR Handling, equipment cleaners, helpers, and laborers 

X 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 (DiaryQuest) 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,0000,60,14500,30125,

BAL97001A,0100,60,14500,30125,

BAL97001A,0200,60,14500,30125,

BAL97001A,0300,60,14500,30125,

BAL97001A,0400,60,14500,30125,

BAL97001A,0500,60,14500,30125,

BAL97001A,0600,60,14500,30125,

BAL97001A,0700,30,14500,30125,

BAL97001A,0730,30,14400,30121,

BAL97001A,0800,60,16000,30122,

BAL97001A,0900,60,14500,30125,

BAL97001A,1000,30,14500,30125,

BAL97001A,1030,30,X ,X ,

BAL97001A,1100,45,14500,30125,

BAL97001A,1145,15,X ,X ,

BAL97001A,1200,60,14500,30125,

BAL97001A,1300,60,14500,30125,

BAL97001A,1400,60,14500,30125,

BAL97001A,1500,60,16000,30122,

BAL97001A,1600,60,14600,30125,

BAL97001A,1700,15,14600,30125,

BAL97001A,1715,45,14400,30123,

BAL97001A,1800,45,14400,30123,

BAL97001A,0000,60,14500,30125,

BAL97001A,0100,60,14500,30125,

BAL97001A,0200,60,14500,30125,

BAL97001A,0300,60,14500,30125,

BAL97001A,0400,60,14500,30125,

BAL97001A,0500,60,14500,30125,

BAL97001A,0600,60,14500,30125,

BAL97001A,0700,30,14500,30125,

BAL97001A,0730,30,14400,30121,

BAL97001A,0800,60,16000,30122,

BAL97001A,0900,60,14500,30125,

BAL97001A,1000,30,14500,30125,

BAL97001A,1030,30,X ,X ,

BAL97001A,1100,45,14500,30125,

BAL97001A,1145,15,X ,X ,

BAL97001A,1200,60,14500,30125,

BAL97001A,1300,60,14500,30125,

BAL97001A,1400,60,14500,30125,

BAL97001A,1500,60,16000,30122,

BAL97001A,1600,60,14600,30125,

BAL97001A,1700,15,14600,30125,

BAL97001A,1715,45,14400,30123,

BAL97001A,1800,45,14400,30123,

Exhibit 4-21. Example Portion of Diary Events File 

67
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 CHAD Location IDs Considered 

“Outdoors” “In Vehicle” 

30332, 30342, 30320, 30200, 31310, 

35000-36300 

31000-31172 

68
! CHAD Longitudinal Activity Statistics File for Time Outdoors 

! (CHAD locations 30332,30342,30320,30200,31310,35000-36300) 

! Prepared by Alion Science & Technology, Inc. for EPA 

! Created 6/24/05 

! CHAD ID, time spent outdoors (minutes) 

BAL97001A, 45 

BAL97001B, 180 

BAL97001C, 0 

BAL97006A, 75 

BAL97006B, 270 

BAL97006C, 135 

BAL97006D, 75 

BAL97006E, 30 

BAL97006F, 270 

BAL97006G, 135 

BAL97006H, 150 

BAL97006I, 90 

BAL97006J, 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 pollutantspecific). 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 MASSBAL or FACTORS. In the MASSBAL 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 MASSBAL and 

FACTORS methods. 

69
Micro Name Method 

1 Residence MASSBAL 

2 Car MASSBAL 

3 InsideOther FACTORS 

4 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 (CSource and ESource) which permit multiple 

sources in the same microenvironment. 

Table 4-12. Microenvironment Parameters For the FACTORS and MASSBAL Methods 

Calculation 

method 

Parameter 

type 

Code Units Default value 

Proximity PR None 1 

Penetration PE None 1 

FACTORS 

Csource CS ppm or μg/m3

 (depends 

on InputUnits) 

0 

Proximity PR None 1 

Penetration PE None 1 

Decay Rate DE 1/hr 0 

Air Exchange 

Rate 

AE 1/hr none 

Volume VO m3 none 

MeanR MR 1/hr AirExRate+DecayRate

Csource CS ppm or μg/m3

 (depends 

on InputUnits) 

0 

MASSBAL 

ESource ES μg/hr 0 

70
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 II 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
• 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, 

DailyConditional1-DailyConditional3, ProfileConditional1-ProfileConditional5, 

RegionalConditional1-RegionalConditional5), 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
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 #1. 

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
Keyword Description 

Condition # 1 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. 

Condition # 2 Choice for the second conditional variable. 

Condition # 3 Choice for the third conditional variable. 

ResampHours 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. 

ResampDays 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. 

ResampWork 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. 

RandomSeed 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 

• C1 — 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
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, DailyConditional1-DailyConditional3, ProfileConditional1-ProfileConditional5, 

or RegionalConditional1-RegionalConditional5 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=1). 

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 II 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 

• Par1. 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. 

• UTrunc. 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
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
Micro number = 1 

Parameter Type = AE 

Condition # 1 = AvgTempCat 

Condition # 2 = ACHome 

ResampHours = NO 

ResampDays = NO 

ResampWork = YES 

Block DType Season Area C1 C2 C3 Shape Par1 Par2 Par3 Par4 LTrunc UTrunc ResampOut 

1 1 1 1 1 1 1 Lognormal 0.95 1.7 0 . 0.111 10.0 Y 

1 1 1 1 2 1 1 Lognormal 0.65 1.7 0 . 0.111 10.0 Y 

1 1 1 1 3 1 1 Lognormal 0.35 1.7 0 . 0.111 10.0 Y 

1 1 1 1 4 1 1 Lognormal 0.33 1.9 0 . 0.111 10.0 Y 

1 1 1 1 5 1 1 Lognormal 0.33 1.9 0 . 0.111 10.0 Y 

1 1 1 1 1 2 1 Lognormal 0.50 2.0 0 . 0.111 10.0 Y 

1 1 1 1 2 2 1 Lognormal 0.50 2.0 0 . 0.111 10.0 Y 

1 1 1 1 3 2 1 Lognormal 0.60 2.0 0 . 0.111 10.0 Y 

1 1 1 1 4 2 1 Lognormal 0.80 2.0 0 . 0.111 10.0 Y 

1 1 1 1 5 2 1 Lognormal 1.00 2.0 0 . 0.111 10.0 Y 

Micro number = 12 

Pollutant = 3 

Parameter Type = PE 

Hours - Block = 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 

Weekday-DayType = 1 2 2 2 2 2 1 

Month-Season = 1 1 2 2 2 3 3 3 4 4 4 1 

Block DType Season Area C1 C2 C3 Shape Par1 Par2 Par3 Par4 LTrunc UTrunc ResampOut 

1 1 1 1 1 1 1 Point 1.0 . . . . . . 

2 1 1 1 1 1 1 Point 0.5 . . . . . . 

1 2 1 1 1 1 1 Point 0.9 . . . . . . 

2 2 1 1 1 1 1 Point 0.4 . . . . . . 

1 1 2 1 1 1 1 Point 0.8 . . . . . . 

2 1 2 1 1 1 1 Point 0.3 . . . . . . 

1 2 2 1 1 1 1 Point 1.0 . . . . . . 

2 2 2 1 1 1 1 Point 0.9 . . . . . . 

1 1 3 1 1 1 1 Point 0.8 . . . . . . 

2 1 3 1 1 1 1 Point 0.7 . . . . . . 

1 2 3 1 1 1 1 Point 0.6 . . . . . . 

2 2 3 1 1 1 1 Point 0.5 . . . . . . 

1 1 4 1 1 1 1 Point 0.5 . . . . . . 

2 1 4 1 1 1 1 Point 0.3 . . . . . . 

1 2 4 1 1 1 1 Point 0.2 . . . . . . 

2 2 4 1 1 1 1 Point 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, Ill, and to produce output exposure summary tables for persons 

with Ill=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
! Asthma Prevalence Rates

!Age Male Female 

 0 0.041 0.034 

 1 0.070 0.052 

 2 0.102 0.071 

 3 0.129 0.088 

 4 0.144 0.099 

 5 0.164 0.119 

Exhibit 4-25. Portion of an Example Prevalence File 

78
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 N Lines: 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
Table 5-1. APEX Output Files. 

Output file Description 

Log File 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. 

Hourly File The Hourly file provides an hour-by-hour time series of exposures, doses, 

and other variables for each modeled profile. 

Daily File The Daily file provides a day-by-day time series of exposures, doses, and 

other variables for each modeled profile. 

Profile Summary

File 

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. 

Microenvironment 

Summary File 

The Microenvironment Summary file provides a summary of the time and 

exposure by microenvironment for each profile modeled in the simulation. 

Output Tables File 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. 

Sites File The Sites file lists the sectors, air districts, and zones in the study area, and 

identifies the mapping between them. 

Events File 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. 

Microenvironment 

Results File 

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
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, LogProfiles, 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 

Description Control File 

Keyword Optional

Person Simulated profile number - N 

Hour Hour # of the simulation - N 

Ve Ventilation VE Y 

Va Alveolar ventilation VA Y 

81
Variable 

Description Control File 

Keyword Optional

EVR 

Equivalent ventilation rate, Ve 

divided by body surface area 

EVR 

Y 

MET 

Metabolic equivalents. Timeaveraged multiple of basal 

energy expenditure for the 

hour. 

METS 

Y 

EE Energy expenditure, EE Y 

Micro Time 

Time spent in 

microenvironment N (minutes) 

TIME1 - 

TIMEN Y 

Micro Exposure 

Exposure in microenvironment 

N 

EXP1 – EXPN 

Y 

Ambient Concentration 

Ambient pollutant 

concentration, time averaged 

over events 

AMB 

Y 

Exposure 

Time-averaged exposure for 

the hour 

EXP 

Y 

Dose 

Time-averaged dose for the 

hour. Units of dose depend on 

pollutant, see Volume II.

DOSE 

Y 

Intake Dose 

PM pollutants only. Average 

mass inhaled per minute 

(includes mass not deposited) 

during the hour (ug/min) 

INTAKEDOSE 

Y 

Deposited Dose 

PM pollutants only. Total 

mass deposited in the 

respiratory system during the 

hour (ug). 

DEPDOSE 

Y 

Exposure Factor 

The ratio of the hourly 

exposure to the hourly ambient 

concentration EF 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 = 60

∑ConcN * Duration

, for events in the hour in microenvironment N 

82
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 (Pol1 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 = Pol1 Pol2 

 Air Quality = ! Hourly Pol1 air quality data for an example metropolitan area 

 Air Quality = ! Hourly Pol2 air quality data for an example metropolitan area 

 P Hour Time_4 Time_12 Amb-Pol1 Exp-Pol1 EF-Pol1 Amb-Pol2 Exp-Pol2 EF-Pol2 

 1 1 60 0 1.039E-02 5.842E-03 0.562 1.132E-02 6.351E-03 0.561 

 1 2 60 0 9.000E-03 3.295E-03 0.366 9.000E-03 3.351E-03 0.372 

 1 3 60 0 7.000E-03 2.710E-03 0.387 7.000E-03 2.756E-03 0.394 

 1 4 60 0 2.000E-03 9.189E-04 0.459 2.000E-03 9.379E-04 0.469 

 1 5 25 0 7.000E-03 2.297E-03 0.328 7.000E-03 2.333E-03 0.333 

 1 6 26 0 2.300E-02 8.118E-03 0.353 2.300E-02 8.241E-03 0.358 

 1 7 60 0 2.100E-02 7.262E-03 0.346 2.100E-02 7.392E-03 0.352 

 1 8 60 0 1.800E-02 6.180E-03 0.343 1.800E-02 6.291E-03 0.349 

 1 9 30 0 1.800E-02 7.378E-03 0.410 1.800E-02 7.491E-03 0.416 

 1 10 12 30 1.900E-02 6.683E-03 0.352 1.900E-02 6.799E-03 0.358 

 1 11 60 0 2.026E-02 8.227E-03 0.406 2.044E-02 8.427E-03 0.412 

 1 12 4 15 2.400E-02 8.700E-03 0.363 2.400E-02 8.846E-03 0.369 

 1 13 60 0 2.271E-02 1.138E-02 0.501 2.334E-02 1.183E-02 0.507 

 1 14 60 0 3.000E-02 1.170E-02 0.390 3.000E-02 1.189E-02 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 HourlyOut parameter to NO in the Control

file. 

83
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 

Description Control File 

Keyword Optional

Person Simulated profile number - N 

Hour Hour # of the simulation - N 

Timestep Timestep # of the simulation - N 

Ve Ventilation VE Y 

Va Alveolar ventilation VA Y 

EVR 

Equivalent ventilation rate, Ve 

divided by body surface area 

EVR 

Y 

MET 

Metabolic equivalents. Timeaveraged multiple of basal 

energy expenditure for the 

timestep. 

METS 

Y 

EE Energy expenditure, EE Y 

Ambient Concentration 

Ambient pollutant 

concentration, time-averaged 

over events in the timestep 

AMB 

Y 

Exposure

Exposure, time-averaged over 

events in the timestep 

EXP 

Y 

Dose 

Time-averaged dose for the 

hour. Units of dose depend on 

pollutant, see Volume II.

DOSE 

Y 

Intake Dose 

PM pollutants only. Average 

mass inhaled per minute 

(includes mass not deposited) 

during the timestep (ug/min) 

INTAKEDOSE 

Y 

Deposited Dose 

PM pollutants only. Total 

mass deposited in the 

respiratory system during the 

timestep (ug). 

DEPDOSE 

Y 

Exposure Factor 

The ratio of the timestep 

exposure to the timestep 

ambient concentration EF 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
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 (Pol1 and 

Pol2) is shown in Exhibit 5-2. 

 

 APEX Timestep File 

 APEX Version 4.0 (dated February 21, 2008) Run Date = 20080227 Time = 111351 

 Location = Description of Location of the Study Area 

 Scenario = APEX4 Sensitivity Simulation 

 Simulation = ! APEX4 Sensitivity Simulation 

 Pollutant = ozone 

 Air Quality = Name =0000200006 

 

 P Hour Timestep Ve Amb-ozone Exp-ozone 

 1 1 1 4858. 3.760E-03 3.760E-03 

 1 1 2 5951. 1.027E-02 1.027E-02 

 1 1 3 4156. 3.570E-03 3.570E-03 

 1 1 4 4949. 8.480E-03 8.480E-03 

 1 1 5 5060. 3.680E-03 3.680E-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
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 

Description Control File 

Keyword Optional 

Person Simulated profile number - N 

Day Day number of the simulation - N 

Diary ID 

ID of CHAD diary selected for the 

current day for the profile 

CHADID 

Y 

Diary Age 

Age associated with the selected CHAD 

diary (may be different from the age of 

the simulated profile) 

CHADAGE 

Y 

Diary Employment 

Employment status associated with the 

selected CHAD diary 

CHADEMP 

Y 

Diary pool 

Index of the APEX diary pool for the 

current day (as determined by profile 

functions file) 

DIARYPOOL 

Y 

PAI 

Physical activity index, the timeaveraged MET over the day for the 

simulated person 

PAI 

Y 

Key Diary Variable 

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) 

KEYVAR 

Y 

WindowRes 

Conditional variable value indicating 

whether residence windows are open or 

closed (as determined by profile 

functions file) 

WINDOWRES Y 

WindowCar 

Conditional variable value indicating 

whether car windows are open or closed 

(as determined by profile functions file) 

WINDOWCAR Y 

SpeedCat 

Conditional variable value indicating the 

speed at which a vehicle is traveling (as 

determined by profile functions file) 

SPEEDCAT Y 

DailyCond1 

Value of daily conditional variable 1 (as 

determined by profile functions file) 

DCOND1 Y 

DailyCond2 

Value of daily conditional variable 2 (as 

determined by profile functions file) 

DCOND2 

Y 

DailyCond3 

Value of daily conditional variable 3 (as 

determined by profile functions file) 

DCOND3 Y 

MaxTempCat 

Conditional variable giving the category 

for the maximum temperature for the day 

(as determined by profile functions file) 

MAXTEMPCAT Y 

86
Variable 

Description Control File 

Keyword Optional 

AvgTempCat 

Conditional variable giving the category 

for the average temperature for the day 

(as determined by profile functions file) 

AVGTEMPCAT Y 

Maximum 

Temperature 

Maximum hourly temperature for the 

current day 

MAXTEMP Y 

Average 

Temperature 

Average of the hourly temperatures for 

the current day 

AVGTEMP Y 

Average Exposure 

Time-averaged pollutant exposure for the 

day. 

AVGEXP Y 

Max 1 Hour 

Exposure 

Maximum 1 hour exposure on the given 

day; each hourly exposure time-averaged 

over events. 

MAX1EXP Y 

Max 8 Hour 

Exposure 

Maximum 8 hour exposure on the given 

day; each 8-hour exposure time-averaged 

over events. 

MAX8EXP Y 

Average Dose 

Time-averaged pollutant dose for the 

day. Units of dose depend on pollutant, 

see Volume II.

AVGDOSE 

Y 

Intake Dose 

PM pollutants only. Average mass 

inhaled per minute (includes mass not 

deposited) during the day (ug/min) 

INTAKEDOSE 

Y 

Deposited Dose 

PM pollutants only. Total mass 

deposited in the respiratory system 

during the day (ug). 

DEPDOSE 

Y 

Max 1 Hour Dose 

Maximum 1 hour dose on the given day; 

each hourly dose time-averaged over 

events 

MAX1DOSE 

Y 

Max 8 hour Dose 

Maximum 8 hour dose on the given day; 

each 8-hour dose time-averaged over 

events. 

MAX8DOSE 

Y 

Max End-of-Hour 

Dose 

Maximum dose as calculated at the end 

of each hour of the day. 

MAX1FDOSE 

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
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 (Pol1 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 = Pol1 Pol2 

 Air Quality = ! Hourly Pol1 air quality data for an example metropolitan area 

 Air Quality = ! Hourly Pol2 air quality data for an example metropolitan area 

P Day CHADID CHADAge CHADEmp DiaryPool PAI KeyVar WindowRes WindowCar AvgExp-Pol1 AvgExp-Pol2 

 1 1 NHW19167A 24 Works 2 2.20 540.00 0 0 7.833E-03 1.436E-02 

 1 2 CIN02759A 21 Works 2 2.41 49.00 0 0 7.748E-03 5.456E-02 

 1 3 NHW10859A 20 Works 5 2.60 490.00 0 0 9.537E-03 7.764E-02 

 1 4 NHA16047A 27 Works 5 1.95 0.00 0 0 8.256E-03 8.379E-02 

 1 5 NHW13255A 24 Works 1 2.43 525.00 0 0 4.343E-03 5.747E-02 

 1 6 NHW15968A 21 Works 1 1.58 475.00 0 0 6.938E-03 7.345E-02 

 1 7 NHW12055A 20 Works 1 1.82 600.00 0 0 6.196E-03 3.253E-02 

 1 8 WAS96832A 25 Works 1 2.24 15.00 0 0 4.372E-03 6.744E-02 

 1 9 DEN34716B 22 Works 1 3.63 11.00 0 0 6.306E-03 9.222E-02 

 1 10 CIN80040B 21 Works 4 2.70 390.00 0 0 5.712E-03 2.543E-02 

 1 11 CIN00339B 24 Works 4 2.46 457.00 0 0 6.089E-03 4.334E-02 

 1 12 WAS63046A 24 Works 1 2.14 0.00 0 0 6.366E-03 6.435E-02 

 1 13 CIN61737C 26 Works 2 2.95 91.00 0 0 4.539E-03 6.765E-02 

 1 14 CAA06251A 21 Works 2 2.37 230.00 0 0 2.629E-03 6.279E-02 

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 

Description Control File 

Keyword Optional 

Person 

Sequential index number for 

simulated individual - N 

Home Sector 

Sector in which the person lives 

(home) 

- 

N 

88
Variable 

Description Control File 

Keyword Optional 

Work Sector 

Sector in which the person works 

(=home sector for non-workers) 

- 

N 

Home District Air district for the home sector - N 

Work District Air district for the work sector - N 

Zone 

Meteorology zone for the home 

sector 

- 

N 

Age 

Age of the simulated profile 

(years) 

- 

N 

Gender Male or female - N 

Race 

Such as White, Black, Asian, 

Native American (NatAm), Other 

(depending on pop. files) 

- 

N 

Employment 

Indicates employment outside the 

home 

- 

N 

Height Person height (inches) - N 

Weight Body mass (pounds) - N 

Car AC type 

Type of air conditioning in the 

car (depends of Profile Functions

file) ACCAR Y 

Home AC type 

Type of air conditioning in the 

residence (depends of Profile 

Functions file) ACHOM Y 

Disease status 

Whether or not a profile is ill 

(depends on Prevalence file) DISEASE Y 

Gas Pilot 

Indicates the presence of a gas 

pilot light in the home (depends 

of Profile Functions file) PILOT Y 

Gas Stove 

Indicates the presence of a gas 

stove in the home (depends of 

Profile Functions file) STOVE Y 

ProfileConditional1 

Value of profile conditional 

variable # 1 for the person PCOND1 Y 

ProfileConditional2 

Value of profile conditional 

variable # 2 for the person PCOND2 Y 

ProfileConditional3 

Value of profile conditional 

variable # 3 for the person PCOND3 Y 

ProfileConditional4 

Value of profile conditional 

variable # 4 for the person PCOND4 Y 

ProfileConditional5 

Value of profile conditional 

variable # 5 for the person PCOND5 Y 

RegionalConditional1 

Value of regional conditional 

variable # 1 for the person RCOND1 Y 

RegionalConditional2 

Value of regional conditional 

variable # 2 for the person RCOND2 Y 

89
Variable 

Description Control File 

Keyword Optional 

RegionalConditional3 

Value of regional conditional 

variable # 3 for the person RCOND3 Y 

RegionalConditional4 

Value of regional conditional 

variable # 4 for the person RCOND4 Y 

RegionalConditional5 

Value of regional conditional 

variable # 5 for the person RCOND5 Y 

Number of Events 

Number of diary events covering 

the simulation period for the 

person EVENTS Y 

Blood Vol 

The volume of blood in the body 

(ml) BLOODVOL Y 

BSA Body surface area (m2

) BSA Y 

Energy Conversion Factor 

Energy conversion factor for 

person (L-O2/kcal) ECF Y 

Lung Diffusivity 

A lung diffusivity parameter 

used in the COHb (CO dose) 

calculation (ml/min/torr) DIFFUS Y 

Endogenous CO production 1 

Endogenous CO production rate; 

only used for calculating CO 

dose (ml/min) ENDGN1 Y 

Endogenous CO production 2 

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) ENDGN2 Y 

Hemoglobin 

The amount of hemoglobin in the 

blood (g/ml) HEMOGLOB Y 

METmax 

Maximum obtainable MET level 

for the person. (MET) METSMAX Y 

Maximum Oxygen Uptake VO2MAX Y 

Maximum obtainable oxygen 

uptake rate for person (LO2/min) 

Maximum Oxygen Debt 

ygen 

MOXD Y 

Maximum obtainable ox

debt for person (ml/kg) 

Physical Activity Index 

s 

ET on each 

PAI Y 

Median of the daily PAI value

(time-averaged M

simulated day) 

Recovery Time 

Time required to recover the 

maximum oxygen debt (hours) RECTIME Y 

Resting Metabolic Rate Resting metabolic rate (kcal/min) RMR Y 

VE Intercept VEINTER Y 

Regression parameter for the 

ventilation routine 

VE Slope VERESID Y 

Regression parameter for the 

ventilation routine 

90
Variable 

Description Control File 

Keyword Optional 

VE Residual VESLOPE Y 

Regression parameter for the 

ventilation routine 

Average Exposure 

the simulation (ppm or 

l

AVGEXP Y 

Mean exposure concentration 

over 

μg/m3, as specified in Contro

file) 

Maximum Exposure 

 over the simulation 

MAXEXP Y 

Maximum 1-hour exposure 

concentration

(ppm or μg/m3

, as specified in 

Control file) 

Average Dose AVGDOSE Y 

Mean dose over the simulation. 

Units of dose depend on 

pollutant, see Volume II.

Maximum 1-hour average dose

over the sim

Maximum Dose Volume II. MAXDOSE Y 

ulation. Units of 

dose depend on pollutant, see 

The exposure and dose variables listed are written for all pollutants in a multiple-pollutant run. 

n example portion of a Profile Summary file for an example 2-pollutant (Pol1 and Pol2) 

is file was created using the Control file command: 

n Date = 20070321 Time = 133813 

8 661 661 23 23 2 50 Female White Works 60.355 106.818 1.93 8.765E-03 8.625E-03 

9 280 280 55 55 2 39 Male Black NoWrk 69.081 209.165 1.76 9.120E-03 9.331E-03 

10 793 793 17 17 2 32 Female White NoWrk 65.700 172.692 1.87 1.020E-02 1.041E-02 

A

scenario is given in Exhibit 5-4. Th

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) Ru

Location = Description of Location of the Study Area 

Scenario = APEX4 Sensitivity Simulation 

Simulation = ! APEX4 Sensitivity Simulation 

Pollutant = Pol1 Pol2 

Air Quality = ! Hourly Pol1 air quality data for an example metropolitan area 

Air Quality = ! Hourly Pol2 air quality data for an example metropolitan area 

P HSect WSect HDis WDis Zone Age Gender Race Empl Height Weight PAI AvgExp-Pol1 AvgExp-Pol2 

1 513 513 27 27 2 22 Male White Works 71.908 228.339 2.09 9.956E-03 1.005E-02 

2 64 64 14 14 2 19 Male Black NoWrk 67.179 138.067 1.74 9.238E-03 9.413E-03 

3 359 359 42 42 2 22 Female Other Works 61.018 173.609 1.92 9.749E-03 9.415E-03 

4 222 222 39 39 2 15 Male Black NoWrk 68.519 182.139 1.74 9.100E-03 9.131E-03 

5 177 177 39 39 2 20 Female Other NoWrk 65.608 160.464 1.65 8.906E-03 9.377E-03 

6 287 287 49 49 2 32 Male White Works 65.658 155.154 2.04 9.978E-03 1.059E-02 

7 688 688 28 28 2 48 Female Black Works 66.264 183.261 1.97 8.873E-03 9.257E-03 

Exhibit 5-4. Portion of a Profile Summary File 

91
5.6 Microenvironmental Results File 

The Microenvironmental Results file contains hourly values for a number of microe

parameters and v

nvironment 

ariables for all microenvironments, for all persons in a simulation. The file is 

ollutant-specific, so one file will be created for each pollutant in the simulation. The variable 

e 

ault is NO, as these files are very large, and 

riting them greatly affects the speed of the simulation. The printing of the optional 

variable d list 

f varia sults 

f the simu ts. The variables that may

c ng keywo

Table 5-6. A roenvironmental Results File 

Variable Control File Keyword Optional

p

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 b

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 def

w

s is dictated by the Control file keyword MResList via a comma- or space-separate

o ble keywords. The MResList will control the writing of the Microenvironment Re

file for all o

di

lation pollutan be written to the file and their 

orrespon rds are given in Table 5-6. 

PEX Variables Written to the Mic

Description 

Person The number of the simulated profile - N 

Hour # 

of 

urs -23 

lation of the 

- 

N 

Hour of the simulation. Hour ranges 

from -23 to 24 times the number 

days in the simulation. The ho

to 0 are included because APEX 

extends the calcu

microenvironment concentrations to

include the 24 hours prior to the 

beginning of the simulation 

Micro # 

Microenvironment number (See 

Section 4.16). 

- 

N 

Location 

 home (1), 

ile. 

N 

Apex calculates concentrations for 

each microenvironment for

work (2), and other (3) locations (see 

Volume II). All are listed in the f

- 

Proximity 

microenvironment PRX 

Y 

Proximity factor: 

parameter, greater than 0. 

Penetration 

PEN 

Y 

Penetration factor: microenvironment

parameter, ranging from 0 to 1. 

CSum 

Sum of concentration sources CSUM 

(CSource) terms Y 

Ambient 

Concentration 

ion associated 

 the Air Quality Data

file). 

AMB 

Y 

Pollutant concentrat

with the location sector and hour (as 

determined from

92
Variable Description Control File Keyword Optional

Micro 

Concentration Y 

Pollutant concentration in the 

microenvironment 

CONC 

ESum 

Sum of Emission Sources (ESource) ESUM 

terms (μg/hr). Y 

Source Strength 

bined source strength for 

on sources 

SOURCE 

Y 

Com

emission and concentrati

in μg/m3

/hr. 

Micro Volume 

Volume of the microenvironment in 

m3

. 

VOL Y 

Air Exchange 

Rate (AER) 

Rate of air exchange in 

microenvironment (1/hr). 

AER Y 

Removal (Decay) 

ent (1/hr). 

RR Y 

Rate 

Total removal rate of pollutant from

microenvironm

WindowRes 

Conditional variable value indicating 

whether residence windows are op

or closed (as determined by profil

functions file) 

en 

e 

WINDOWRES Y 

WindowCar 

Conditional variable value ind

whether car windows are open or 

closed (as determined by profile 

functions file) 

icating WINDOWCAR Y 

MaxTempCat 

Daily maximum temperature 

category conditional variable - will 

be same for all hours in a day. (as 

determined by profile functions file) 

MAXTEMPCAT Y 

AvgTempCat 

me 

ions file) 

Daily average temperature category AT Y 

conditional variable - will be sa

for all hours in a day. (as determined

by profile funct

AVGTEMPC

SpeedCat 

Conditional variable value indicating 

the speed at which a vehicle is 

) 

T 

traveling (as determined by profile 

functions file

SPEEDCA Y 

DailyConditional1 

Value of daily conditional variable 1 

for the hour 

DCOND1 Y 

DailyConditional2 

Value of daily conditional variable 2 

for the hour 

DCOND2 Y 

DailyConditional3 ur 

Value of daily conditional variable 3 

for the ho

DCOND3 Y 

TempCat 

Hourly temperature category 

conditional variable 

TEMPCAT Y 

HumidCat 

Hourly humidity category conditional 

variable 

HUMIDCAT Y 

PrecipCat 

Hourly precipitation category T 

conditional variable 

PRECIPCA Y 

93
Variable Description Control File Keyword Optional

WindCat

Hourly wind speed category CAT Y 

conditional variable

WIND

DirCat 

Hourly wind direction category 

conditional variable 

DIRCAT Y 

Day Day of the simulation DAY Y 

Month Month of the year MONTH Y 

Air District 

Air district person is in (i.e., the 

district corresponding to the 

home/work/other location) 

DISTRICT Y 

DayWeek Day of the week DAYWEEK Y 

See Volume III: Programmer’s Guide for details on the microenvironment parameters, 

al variables. 

EMPCAT, WINDOWRES

file for an example pollutant (Pol1) is given 

r the 

le size). 

microenvironment concentration equations, and condition

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, CONC, MAXTEMPCAT, AVGT

The resulting example Microenvironmental Results 

in Exhibit 5-5. Note that in the file the variable values may not fall directly unde

corresponding label in the file header (in order to minimize fi

94
 APEX Microenvironmental Results File 

 APEX Version 4.0 (dated February 19, 2007) Run Date = 20070321 Time = 152320 

 Location = Descr

 Scenario = APEX4

 example metropolitan area 

 Simulation Start Date = 20040101 

 1 1 1 -14 1.0000 1.0000 1.900E-02 1.192E-03 0.4138 0 1 1 1 

 1 1 

1 .0000 3.00 3 0.6968 0 1 1 1 

1 .0000 3.20 3 0.4730 0 1 1 1 

 1 1 .0000 3.00

 1 1 .0000 2.80

 1 1 1 -6 1.0000 1.0000 2.600E-02 1.487E-03 0.3753 0 1 1 1 

 1 1 1 -5 1.0000 1.0000 2.200E-02 1.440E-03 0.4299 0 1 1 1 

 1 1 .0000 2.30

 1 1 .0000 2.60

 1 1 1 -2 1.0000 1.0000 2.30

 1 1 1 -1 1.0000 1.0000 2.30

 1 1 1 0 1.0000 1.0000 2.20

 1 1 1 1 1.0000 1.0000 8.000E-03 6.081E-04 0.4104 0 1 1 1

iption of Location of the Study Area 

 Sensitivity Simulation 

 Simulation = ! APEX4 Sensitivity Simulation 

 Pollutant = Pol1 

 Air Quality = ! Hourly Pol1 air quality data for an

 

 Person Micro Loc Hour Prx Pen Amb Conc AER WindowRes MaxTempCat AvgTempCat TempCat 

 1 1 1 -23 1.0000 1.0000 8.000E-03 4.227E-04 0.4104 0 1 1 1 

 1 1 1 -22 1.0000 1.0000 9.000E-03 6.518E-04 0.5042 0 1 1 1 

 1 1 1 -21 1.0000 1.0000 7.000E-03 7.044E-04 0.6962 0 1 1 1 

 1 1 1 -20 1.0000 1.0000 2.000E-03 2.335E-04 0.5010 0 1 1 1 

 1 1 1 -19 1.0000 1.0000 7.000E-03 1.645E-04 0.1511 0 1 1 1 

 1 1 1 -18 1.0000 1.0000 2.300E-02 1.712E-03 0.5822 0 1 1 1 

 1 1 1 -17 1.0000 1.0000 2.100E-02 1.922E-03 0.6193 0 1 1 1 

 1 1 1 -16 1.0000 1.0000 1.800E-02 1.398E-03 0.4841 0 1 1 1 

 1 1 1 -15 1.0000 1.0000 1.800E-02 1.207E-03 0.4370 0 1 1 1 

 

 1 1 1 -13 1.0000 1.0000 2.100E-02 1.496E-03 0.4923 0 1 1 1 

1 -12 1.0000 1.0000 2.400E-02 3.147E-03 1.0217 0 1 1 1 

 1 1 1 -11 1.0000 1.0000 2.800E-02 3.395E-03 0.8523 0 1 1 1 

 1 

 1 

 1 -10 1

 1 -9 1

 1.0000 

 1.0000 

0E-02 3.091E-0

0E-02 2.390E-0

 

 

 1 -8 1

 1 -7 1

 1.0000

 1.0000

0E-02 1.132E-03 0.1955 0 1 1 1 

0E-02 1.395E-03 0.3449 0 1 1 1 

 

 

 1 -4 1

 1 -3 1

 1.0000

 1.0000

0E-02 1.960E-03 0.6052 0 1 1 1 

0E-02 2.610E-03 0.7176 0 1 1 1 

0E-02 1.683E-03 0.4316 0 1 1 1 

0E-02 1.279E-03 0.3517 0 1 1 1 

0E-02 1.226E-03 0.3640 0 1 1 1 

xh . P

5.7 Mic m l Su

This file provides the amount of tim

exposure concentration in each mic od of simulation, for each 

sim ted M viro ne is 

created for each pollutant in the sim d, 

there is one record labeling the columns of the subsequent records in the file. These labels and 

escriptions of the values in the corresponding columns are given in Table 5-7. The first part of 

n example Microenvironmental Summary File is shown in Exhibit 5-6. 

Table 5-7. Format of the APEX Microenvironmental Summary File 

Column Label Type Description 

E ibit 5-5 ortion of an Environmental Results File 

roenviron enta mmary File 

e spent, mean exposure concentration, and maximum 

roenvironment during the peri

ula person. The icroen nmental Summary file is pollutant-specific, and thus o

ulation. After the six header records and one blank recor

d

a

1 Person Num Profile number - Sequential index number for the simulated 

individual 

2 Micro Num Microenvironment number - Sequential index number for 

each microenvironment (as designated in the 

Microenvironment Mapping file) 

95
3 Name Char Microenvironment name (as designated in the 

Microenvironment Mapping file) (maximum of 40 

characters) 

4 Minutes Num Total time spent in the microenvironment by this individual 

(minutes) 

5 MeanConc Num Average concentration during the time spent in the 

microenvironment by this individual (ppm or μg/m3, as 

specified in the Control file) 

6 MaxConc Num Maximum concentration during the time spent in the 

microenvironment by this individual (ppm or μg/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 Name Minutes MeanConc MaxConc 

 0 0.0000 0.0000 

 1338 0.0028 0.0070 

 1 2 Indoors-bars_and_restaurants 60 0.0076 0.0080 

s-other 2 0.0004 0.0004 

 1 6 Outdoors-near_road 0 0.0000 0.0000 

 10 0.0089 0.0089 

0 0.0043 0.0056 

 0.0000 0.0000 

0000 0.0000 

 1 0 ZeroExposure 

 1 1 Indoors-residence 

 1 3 Indoors-schools 0 0.0000 0.0000 

 1 4 Indoors-day_care_centers 0 0.0000 0.0000 

 1 5 Indoor

 

 1 7 Outdoors-other 

 1 8 In 3

 1 9 In 0 

 2 0 ZeroExposure 0 0.

Exhibit 5-6. Portion of a Microenvironmental Summary File 

even different types 

 each exposure level by microenvironment 

. Person-days at or above each daily maximum 1-hour exposure level 

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 el

of exposure tables: 

1. Minutes in each exposure interval by microenvironment 

2. Minutes at or above

3

96
4. Person-days at or above each daily maximum 8-hour exposure level 

sures at or above each daily maximum 

n 

. All Persons. The table statistics are based on the entire population. 

ics are based on the population of children, as defined by the age 

nge given by the Control file settings ChildMin and ChildMax. 

n 

le simulation period that exceeds the 

e table statistics are based on the population of ill people. The population is 

itions. The table statistics are based on exposures experienced by the 

opulation subgroup under any ventilatory conditions. 

g generated. The “moderate” EVR ranges are defined by 

e Control file settings ModEVR1 and HeavyEVR1 (for 1-hour exposures) and ModEVR8 and 

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 expo

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 populatio

subgroups are as follows: 

1

2. Children. The table statist

ra

3. Active Persons. The table statistics are based on the population of people having a media

Physical Activity Index (PAI, mean MET) over the who

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. Th

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 Cond

p

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 bein

th

HeavyEVR8 (for 8-hour exposures). An individual’s EVR is in the moderate range if it is

97
greater than or equal to the ModEVR# setting and less than the HeavyEVR# setti

exposure period. 

ng for the 

r 

the table uniquely. For 

ple, 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 indi ext

c

Row_%—The percent of the minutes spent in the specified microenvironment that fall 

t 

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 HeavyEVR1 (for 1-hour exposures) and HeavyEVR8 (for 8-hour exposures). An 

individual’s EVR is in the heavy range if it is greater than or equal to the HeavyEVR# setting fo

the exposure period. 

For each table that is generated, APEX prints out a label that identifies 

exam

cated at the top of the column and the top of the n

olumn to the right; 

•

within the exposure concentration range; and 

• Tot_%—the percent of the total minutes that are spent in the microenvironment and tha

fall within the exposure concentration range. 

TIME,WITHIN,ALL,ALL 

Exposure: Minutes in each Exposure interval ( ppm ), by microenvironment, for N = 1000 Profiles 

 Minutes 315200. 0. 0. 0. 0. 0. 0. 0. 

0. 

16 0.9356 0.0321 0.0013 0.0002 0.0000 0.0000 

54 0.1653 0.0057 0.0002 0.0000 0.0000 0.0000 

 4 Minutes 26980476. 2603103. 511191. 12511. 391. 0. 0. 0. 

 4 Row_% 89.6133 8.6460 1.6979 0.0416 0.0013 0.0000 0.0000 0.0000 

 4 Tot_% 5.1333 0.4953 0.0973 0.0024 0.0001 0.0000 0.0000 0.0000 

------------------------------------------------------------------------------------------------------------------------ 

 Level: 0.0000 2.0000 4.0000 10.0000 20.0000 30.0000 40.0000 50.0000 

Micro ----------------------------------------------------------------------------------------------------------------- 

 0 

 0 Row_% 100.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

 0 Tot_% 0.0600 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

 1 Minutes 319260868. 38420255. 5720925. 80294. 0. 0. 0. 0. 

 1 Row_% 87.8339 10.5700 1.5739 0.0221 0.0000 0.0000 0.0000 0.0000 

 1 Tot_% 60.7422 7.3098 1.0885 0.0153 0.0000 0.0000 0.0000 0.0000 

 2 Minutes 0. 10634094. 0. 28189514. 0. 0. 0. 

 2 Row_% 0.0000 27.3908 0.0000 72.6092 0.0000 0.0000 0.0000 0.0000 

 2 Tot_% 0.0000 2.0232 0.0000 5.3633 0.0000 0.0000 0.0000 0.0000 

 3 Minutes 87632542. 4338531. 868903. 29823. 1229. 150. 0. 0. 

 3 Row_% 94.3592 4.67

 3 Tot_% 16.6729 0.82

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
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. 

PERSONDAYS,DM1H,ALL,ALL 

Exposure: Person-Days at or above each Daily Maximum 1-Hour Exposure Level ( ppm ), for N = 1000 Profiles. Area Population =3976069 

Group: All People 

 Leve

--------------------------------------------------------------------------------------------------------- 

 Counts(Pop): 0.145E+10 0.951E+09 0.386E+09 0.755E+05 0.795E+04 0.000E+00 0.000E+00 0.000E+00 

 #Meet (Pop): 3976069 3976069 3976069 63617 7952 0 0 0 

 %Meet (Pop): 100.000 100.000 100.000 1.600 0.200 0.000 0.000 0.000 

 Mean : 365.000 239.258 97.140 0.019 0.002 0.000 0.000 0.000 

 Std.Dev. : 0.000 34.182 22.835 0.157 0.045 0.000 0.000 0.000 

 CV : 0.000 0.143 0.235 8.266 22.349 0.000 0.000 0.000 

 50.0 %ile : 365.000 246.000 96.0 0.000 0.000 

 75.0 %ile : 365.000 268.000 116.0 0.000 0.000 

 128.000 0.000 0.000 0.000 0.000 0.000 

 133.000 0.000 0.000 0.000 0.000 0.000 

 

 

 

 Min (%) : 

 

 

 

l: 0.000 5.000 10.000 20.000 30.000 40.000 50.000 75.000 

 Minimum : 365.000 137.000 42.000 0.000 0.000 0.000 0.000 0.000 

 10.0 %ile : 365.000 188.000 66.000 0.000 0.000 0.000 0.000 0.000 

 25.0 %ile : 365.000 214.000 82.000 0.000 0.000 0.000 0.000 0.000 

00 0.000 0.000 0.000 

00 0.000 0.000 0.000 

 90.0 %ile :

 95.0 %ile :

 365.000 278.000

 365.000 283.000

 99.0 %ile : 

 Maximum : 

 Mean (%) : 

 365.000 292.000 143.990 1.000 0.000 0.000 0.000 0.000 

 365.000 306.000 164.000 2.000 1.000 0.000 0.000 0.000 

 100.000 65.550 26.614 0.005 0.001 0.000 0.000 0.000 

 100.000 37.534 11.507 0.000 0.000 0.000 0.000 0.000 

 Max (%) : 

 Counts(Sim): 

 #Meet (Sim): 

 100.000 83.836 44.932 0.548 0.274 0.000 0.000 0.000 

0.365E+06 0.239E+06 0.971E+05 0.190E+02 0.200E+01 0.000E+00 0.000E+00 0.000E+00 

 1000 1000 1000 16 2 0 0 0 

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 "PersonDays" Based Tables. 

Table entry Interpretation 

Counts (Pop) 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]. 

#Meet (Pop) least 

ecified at the top of each column [while at this 

ts at the 

Number of persons [in the subgroup] in the study area population who have at 

one exposure at or above the level sp

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 even

exertion level. 

%Meet (Pop) 

: For exertion level tables this may not be 100% at the 0.0 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

since some persons may have no events at the exertion level. 

Mean 

ecified at the top of each column is experienced [while at this 

Mean number of days per person [in the subgroup] during which an exposure at or 

above the level sp

exertion]. 

99
Std. Dev. 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]. 

CV Coefficient of variation across persons [in the subgroup] in the number of days durin

which an exposure at or above the level specified at the top of each column is

experienced [while at this exertion]. 

g 

Minimum 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]. 

Percentiles The Nth percentile of number of days across persons [in the subgroup] during which

exposure at or above the level specified at the top of each column is experienced [while 

at this exertion]. 

 an 

Maximum 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 [w

at this exertion]. 

hile 

Mean (%) 

 each column [while at this exertion] is 

Mean number of days per person [in the subgroup] during which an exposure at or 

above the level specified at the top of

experienced, as percentage of possible days. 

Min (%) n 

or above the level specified at the top of each column is experienced [while 

at this exertion], as percentage of possible days. 

The lowest total number of days across persons [in the subgroup] during which a

exposure at 

Max (%) 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. 

Counts (Sim) Total number of simulated person-days [in the subgroup] during which an exposure a

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 e

t 

vents at the exertion level. 

#Meet (Sim) The total number of simulated persons [in the subgroup] who experience at leas

exposure at or above the level specified at the top of each column [while at this 

ex

t one 

ertion]. 

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 

e 

his 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. 

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 averag

exposure concentration. 

Exposure Table Type #5: Person-Days at or above each Daily Maximum Timestep 

Exposure Level 

T

100
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),for N = 1000 Profiles. 

Group: All People 

 At least 1 At least 2 At least 3 At least 4 At least 5 At least 6 

 Exposure Exposures Exposures Exposures Exposures Exposures 

 Level---------------------------------------------------------------------------- 

 0.000 1000 1000 1000 1000 1000 1000 

 5.000 1000 1000 1000 1000 1000 1000 

 10.

 20.

 30.000 2 0 0 0 0 0 

 40.000 0 0 0 0 0 0 

 50.000 0 0 0 

000 1000 1000 1000 1000 1000 1000 

000 16 3 0 0 0 0 

 

 0 0 0 

 75.000 0 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 

f simulated persons who have at least 1 (2, 3, 

he 

above each Daily Maximum 8-Hour Exposure Level 

This table simply provides a count of the number o

4, 5, 6) days in the simulation during which they have experienced an exposure above each of t

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
Exposure Table Type #8:Number of simulated persons with multiple exposures at or above 

 3, 6, 

ept 

re metric is the daily max timestep average exposure concentration. This table is 

ot 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 equa

xposure Table Type #10: Person-Days at or above each Daily Average Exposure Level

ummary of the cumulative person-days, for both simulated 

 a daily average exposure concentration that 

3 

ided in 

xhibit 5-10. 

each daily maximum timestep exposure level. 

This table provides a count of the number of simulated persons who have at least 1 (or 2,

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) exc

that the exposu

n

l to one hour. 

E

This table provides a statistical s

persons and the population in the study area, with

equals or exceeds specified levels. The table and its interpretation are the same as Table Type #

(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 prov

E

PERSONDAYS,SAVG,ALL,ALL 

Exposure: Persons at or above each Overall Average Exposure Level ( ppm ), for N = 1000 Profiles. 

Area Population = 3976069 

 Level: 0.000 0.500 1.000 2.000 3.000 4.000 5.000 

----------------------------------------------------------------------------------------------- 

 Counts(Pop): 0.398E+07 0.398E+07 0.392E+07 0.386E+06 0.000E+00 0.000E+00 0.000E+00 

 #Meet (Pop): 3976069 3976069 3916428 385679 0 0 0 

 %Meet (Pop): 100.000 100.000 98.500 9.700 0.000 0.000 0.000 

 Counts(Sim): 0.100E+04 0.100E+04 0.985E+03 0.970E+02 0.000E+00 0.000E+00 0.000E+00 

 #Meet (Sim): 1000 1000 985 97 0 0 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
tables for the definition of population subgroups and exertion levels. For the pollutant CO, dose

e 

evel

days for both simulated 

ersons and the population in the study area, for which the daily maximum end-of-hour dose is 

 dose 

finitions of the variables in this table can be found in Table 5-8. 

se Level

ose 

in Table 5-8. 

estep Dose Level 

sure 

hibit 5-8) except that the exposure metric is the daily max timestep average 

xposure concentration. This table is not written if the timestep is equal to one hour. The 

e entire simulation during which they have experienced an 

xceedance of each timestep threshold dose level. The different number of exceedances to 

g the keyword TSMultiLevels. The 

estep 

 the population in the study area, for which the daily average dose is equal to or 

xceeds specified levels. The format of the table is the same as Exposure Table #3 (Exhibit 5-8). 

Table 5-8. 

is blood dose (%COHb), and for any PM pollutant the dose is the rate of mass deposited in th

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 L

This table provides a statistical summary of the cumulative personp

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

is equal to or exceeds specified levels. The format of the table is the same as Exposure Table #3 

(Exhibit 5-8). The de

Dose Table Type #3—Person-Days at or above each Daily Max 8-Hour Do

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 d

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 

Dose Table Type #4: Person-Days at or above each Daily Maximum Tim

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 Expo

Table #3 (Ex

e

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 th

e

include in the table are listed in the Control file usin

threshold exposures are listed using the keyword TSDose. This table is not written if the tim

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

e

The definitions of the variables in this table can be found in

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

103
This table provides a statistical summary of cumulative numbers of both simulated persons an

the people in the study area whose overall average doses are equal to or exceed a specified lev

d 

el. 

The overall average dose is the average of hourly dose levels over the whole period of 

urs, for both simulated 

ersons and the population in the study area, for which each end-of-hour dose level is equal to or 

e format of the table is the same as Exposure Table #3 (Exhibit 

ays. The definitions of the variables in this 

each Dose Interval 

minutes, for both simulated 

e (for example, blood %COHb 

are specified by the levels at the 

he definitions of the variables in 

, except that the time units are in minutes rather 

on-minutes spent by both simulated 

 study area, for which the dose (for example, blood %COHb 

The definitions of the variables in this table are 

 in Table 5-8, except that the time units are in minutes rather than days. 

he Sites output file lists the sectors, air districts, and zones in the study area, and identifies the 

: 

grees) 

km) 

grees) 

Temdistance—Distance from zone to sector (km) 

gitude—Zone longitude (decimal degrees) 

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-ho

p

exceeds specified levels. Th

5-8), except that the time units are hours rather than d

table can be found in Table 5-8.

Dose Table #9— Minutes in 

This table provides a statistical summary of cumulative personpersons and the population in the study area, for which the dos

level) is within a specified range. The bounds of the dose range 

top of each column and the top of the next column to the right. T

this table are similar to those found in Table 5-8

than days. 

Dose Table #10— Minutes at or above each Dose Level 

This table provides a statistical summary of cumulative pers

persons and the population in the

level) is equal to or exceeds specified levels. 

similar to those found

5.9 Sites File 

T

mapping between them. Thus, each record contains the following

• Sector#—Sector ID 

• Latitude—Sector latitude (decimal de

• Longitude—Sector longitude (decimal degrees) 

• Sectorname—Sector name 

• Air#—Air district ID 

• Airdistance—Distance from air district to sector (

• Airlatitude—Air district latitude (decimal degrees) 

• Airlongitude—Air district longitude (decimal de

• Airname—Air district name 

• Tem#—Meteorology zone ID 

•

• Temlatitude—Zone latitude (decimal degrees) 

• Temlon

• Temname—Zone name 

104
5.10 Events File 

The Events file contains a summary of the activity diary with accompanying exposure and dose, 

t the diary event level. The variables printed in this file include: 

Day – the day number of the simulation, incremented from Day 1 of simulation 

4-digit) 

 12) 

Dur – the duration of the event (integer minutes) 

ctivity 

sector, 3=elsewhere 

Exposure – Exposure level during the event (ppm or μg/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 ev

 of the EVENTSLIST keyword would be: 

EventsList = UMET VA VE EVR METS DEFICIT

a

• Person – the profile number of the simulated individual 

• Seq – the event number for the profile 

•

• Year – the year of the event (

• Mn – the month of the event (1 to

• Dy – the day of the week the event (1 to 7) 

• Hr – the hour of the event (1 to 24) 

•

• Act – the MET distribution code for the event a

• Mic – the microenvironment code for the event 

• HW – 1=event in home sector, 2=event in work 

•

• ent 

• FDose – Final dose for the event 

• DepDose – Deposited mass dose for PM events 

• IntakeDose – Intake dose rate for the PM event 

An example

105
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
107

REFERENCES 

Graham S.E. and T. McCurdy (2005). Revised ventilation rate (VR

ER) 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: 

HTUhttp://www.epa.gov/ttn/fera/trim_fate.html#1999historicalUT
United States 

Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Health and Environmental Impacts Division 

Research Triangle Park, NC 

Publication N