# Total Risk Integrated Methodology (TRIM) Air Pollutants Exposure Model Documentation (TRIM.Expo / APEX, Version 4.3)

Volume I: User's GuideEPA-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 CarolinaDISCLAIMER

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 recommen dation 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 ).

iiACKNOWLEDGEMENTS

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

ivCHAPTER 5. .................................................................................... 79 APEX OUTPUT FILES 5.1 .......................................................................................................................... 81 Log File 5.2 ..................................................................................................................... 81 Hourly File 5.3 ................................................................................................................. 84 Timestep File 5.4 ....................................................................................................................... 85 Daily File 5.5 ..................................................................................... 88 Profile Summary (Persons) File 5.6 ................................................................................... 92 Microenvironmental Results File 5.7 ............................................................................... 95 Microenvironmental Summary File 5.8 .......................................................................................................... 96 Output Tables File 5.8.1 ....................................................................................... 96 Exposure Summary Tables 5.8.2 ............................................................................................ 102 Dose Summary Tables 5.9 ....................................................................................................................... 104 Sites File 5.10 ................................................................................................................... 105 Events File 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 Leve ls 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 Probabil ity Distributions in APEX. ........................................................... 49 Table 4-7. Parameters in the Physiological Input File ................................................................. 51 Table 4-8. Variables That Can Be De fined 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. Microenvironme nt 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 Succe ssful Completion of an APEX Run ......................................... 16 Exhibit 4-1. Input Files Sec tion of Simulation Control File ........................................................ 22 Exhibit 4-2. Output Files Sec tion of Simulation Control File ..................................................... 22 Exhibit 4-3. Pollutant Parameters Section of Simulation Control File ......................................... 26 Exhibit 4-4. Job Parameters Sectio ns of the Simulation Control File ......................................... 35 Exhibit 4-5. First Part of Population Sector Location File .......................................................... 36 Exhibit 4-6. First Part of Ex ample Air District Location File ..................................................... 37 Exhibit 4-7. First Part of Example Ai r 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 Exam ple 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 Part s 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 Porti on 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 Microe nvironment Descriptions Sec tion of the Microenvironment Descriptions File ........................................................................................................................... 70 Exhibit 4-24. Example Parameter Descrip tions 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 Mi croenvironmental 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 Tabl e Type #11 in the Output Tables File. ...................... 102

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### LIST OF FIGURES

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

............................................................................................................................... ........................ 55

## CHAPTER 1. INTRODUCTION

1.1 Overview of the APEX Model

The A ir P ollutants Ex posure 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, micr oenvironmental model that can be used to estimate human exposure via inhala tion for criteria and ai r 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 re lease of the model is Version 4. Human exposure to a contaminant is defined as “contact at a boun dary between a human and the environment at a specific contaminant concentration for a specific interval of ti me” (National Research Council, 1991). For air pollutants, the co ntact 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 microe nvironmental 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 mi croenvironments. The pollutant concentrations in the air in each microenvironment are estimated from ambient air pollutant concentrations and parameters specific to each microenvironmen t 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 th e characteristics of an individual that may affect th eir activities, their locations, or the concentrations in the microenvironments that they enc ounter. 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 situati onal variables such as living in a house with a gas stove or air conditioning. The situational variables are us ed to help determine the microenvironmental concentrations, and the physiological variables ar e used in the determination of ventilation rate

1and 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 hu man 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 denot e 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 pol lutant CO, APEX contains an algorithm for estimating the blood dose (percent carboxyhemoglobi n, %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 sy stem. 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 sa mple of the population in a given study area. To this end, demographic data from the decennial census are used, so appropriate probabilities for a ny 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. Ambi ent air quality and mete orology data for the study area are also required by the model; the area repres ented 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 appr opriate 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 pers on’s exposure and dose for each event

• Summarize the results for that profile

The APEX model reports the results for each prof ile 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 ta bles for each pollutant that indicate the distributions of exposure and dos e across all the profiles.

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

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### 1.2 Scope and Organization of This Guide

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

Volume II: Technical Support Document describes the scientific ba sis of the APEX model and provides scientific background for the model algorith ms. It covers the methods implemented in APEX for calculating microenvironmental concen trations, modeling ventil ation, estimating dose, and assembling activity diaries.

Additional volumes or revisions to these volum es may be developed as APEX is upgraded, example applications are deve loped, 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 instru ctions 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 fo rmat and data associated with each of the APEX output files.

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## CHAPTER 2. INSTALLING APEX

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

In addition to providing flexibility in modeling options, the APEX code is sp ecifically 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 Pentiu m 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 request ed, in which case the output fi les can take up more than 5,000 MB.

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

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## CHAPTER 3. SETTING UP AND RUNNING APEX

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

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



### 3.1 Setting Up an APEX Simulation

This section describes the steps involve d in performing an APEX simulation.

1. Select Model Options After identifying the scope of the analysis, the us er must decide which options to select. To determine the appropriate options for the applicati on, 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 pe rcentage 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 se lect a new diary every day for each simulated individual, or do I cons truct longitudinal diaries based on diary properties?)

• Which model settings should I select (e.g., m odel 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 i nput data files with the necessary data. One of these files, the Simulation Control file, is used to specify i nput and output file names and locations and the simulation settings. The remaini ng files contain the input data necessary to run APEX. The data contained in these remaining f iles varies depending on the configuration of the

5scenario to be modeled and the number of pollu tants 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 ou tput 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 th e user can run the model via one of the methods described in Section 3.4.



### 3.2 Overview of Input and Output Fil e s
This section provides a brief overv iew 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 file s; 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 th e hourly and events output files, may be very large (over 100 megabytes) and difficult for so me 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 a nd searches for particul ar 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. (C hapter 4 provides a deta iled 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 AP EX output file types. These f iles contain such information as (1) a summary of the properties of the simula ted persons, (2) hourly or event-level exposures,

6doses, 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 th e 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 fi les 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 seri es of model runs, the out put 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 cove red in detail in Chapter 5.

7Table 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

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### 3.3 Overview of Model Settings and Options

This section briefly describes the primary settin gs 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 f iles and their content, how to edit or create them, and how they interact with other files.Table 3-2. APEX Settings and OptionsImpact of ChangingDefault SettingSETTING/OPTIONHow Option is Selectedon Other Input FilesGENERAL MODEL SETTINGS AND OPTIONSSimulation start/enddatesSpecified in YYYYMMDD format (e.g.,19960704 is July 4, 1996) using theStart_DateandEnd_Datekeywords in theControlfile. The user mustdefine the appropriate start andend dates for an application.The indicated start and end dates must beincluded in the date ranges includedin theAir district Location,Meteorology Zone Location,Meteorology Data,andAir Quality Datafiles. These files may contain additional data beforeand/or after the start and end dates, butmust contain data for the entire periodbetween the specified start and end dates.Adjust for DaylightSaving Time (DST)Specified using theDSTAdjustkeyword in theControlfile. If this parameteris set to “YES”, then the Air Quality Datafile will be adjusted for DST in thesummer; if it is set to “NO”, no adjustment is made. Thiskeyword should beset to “YES” if the Air Quality Data file is based on Standard Time yet theactivity data are based on DST.Changing this setting means that theAir Quality Datafile is based on DST (ittypically is in Standard Time) or that the activity data are based on StandardTime (the supplied CHADdata are based on DST).Regardless of thissetting, the output (hourly exposure and dose) for all simulated days willcontain exactly 24 hours, and all input activity diaries must contain exactly 24hours.Model workercommutingSpecified using theCommutingkeyword in theControlfile. If this keywordis set to “YES”, commuting to work isallowed and the user must provide aCommuting Flowfile in the appropriate formatand employment data must bespecified in theEmployment Probabilitiesfile; if it is set to “NO”, all workersare assumed to work at home and the user is not required to provide aCommuting Flowfile.The Commuting Flowfile accompanying APEXcontains commuting flows between all census tracts from the 2000 Census.These commuting data are sufficient for all applications in which the sectorsare defined as census tracts.If the user chooses to define sectors assomething other census tracts, a newCommuting Flowfile (in addition to a number of other input files) must becreated corresponding to the new sectors.Air quality rollbackadjustment (forestimating exposure inhypothetical controlscenarios)Specified using theRollbackkeyword in theControlfile. If this keyword isset to “YES”, the user must specify appropriate values for theRBTarget,RBBackgnd, andRBMaxkeywords in the Control file; if it is set to “NO”,values are not required for these keywords (and any present will be ignored).If theRollbackkeyword is changed to “YES” in theControlfileaccompanying APEX, theRBTarget,RBBackgnd, andRBMaxkeywordsmust be set to appropriate values.Time resolution (lengthof APEX timestep)Specified using theTimestepsPerDaykeyword in the Control file.The timestep can be eithersmaller or larger than an hour. However if thetimestep is larger than an hour, it must bean integer multiple of an hour. If itis smaller than an hour, there must be an integer number of timesteps in anhour. The default APEX timestep is one hour. IfTimestepsPerDayis not set,then APEX uses the default.The timestep dictates the required time resolution of the following air qualityinput. The time resolution of theAir Quality Datafile must match thatindicated byTimestepsPerDay.STUDY AREA LOCATIONCenter of study areaSpecified as the latitude and longitude of the center of the study area indecimal degrees using theLatitudeandLongitudekeywords in theControlfile. The user must always define the appropriate study area center for anapplication.If the study area is changed, the user must ensure that the following filescontain appropriate data for the new location:Population sector locationfile(unless the included file is used),Air district Locationfile,Meteorology ZoneLocationfile,Meteorology Datafile, andAir Quality Datafile.Radius of study areaSpecified as the distance (in km) from the center to the edge of the study areausing theCityRadiuskeyword in theControlfile. The user must alwaysIf the study area is changed, the user must ensure that the following filescontain appropriate data for the new location:Population sector locationfile10Impact of ChangingDefault SettingSETTING/OPTIONHow Option is Selectedon Other Input Filesdefine the appropriate study area radius for an application.(unless the included file is used),Air district Locationfile,Meteorology ZoneLocationfile,Meteorology Datafile, andAir Quality Datafile.Restrict study area toselected countiesSpecified using theCountyListkeyword in theControlfile. If the value ofthis keyword is set to “YES”, the user must list the FIPS code (or otherrelevant portion of the sector ID if the supplied sector files are not used) forthe counties to which the study area will be restricted using theCountykeyword in theControlfile. The county IDs for all census tracts in the 2000Census are included in the Population sector location file accompanyingAPEX, thus allowing the user to selectcounties in the Control file withoutmaking changes to the included Population sector location file.None, normally. However, if the user does not use the includedPopulationsector locationfile, they must ensure that the newPopulation sector locationfile provides the county ID for each sector as part of the sector ID in theappropriate format.Restrict study area toselected census tractsSpecified using theTractListkeyword in theControlfile. If the value of thiskeyword is set to “YES”, the user must list the sector (tract) ID for the tractsto which the study area will be restricted using theTractkeyword in theControlfile. The sector IDs for all census tracts in the 2000 Census areincluded in the Population sectorlocation file accompanying APEX.Locations of sectorsSpecified as sector IDsand locations (latitude and longitude) in thePopulation sector locationfile. ThePopulation sector locationfileaccompanying APEX use the census tracts from the 2000 Census as sectors.This file also specifies the county associated with each sector (via the firstfive characters of the sector ID, which are the county FIPS codes in thesupplied data), which allows the user to restrict the study area to selectedcounties. In most cases, the user willnot need to change this setting as itprovides sectors with the necessarypopulation and commuting data for theentire United States.Sectors identified inPopulation sector locationfile must match the sectorsidentified inPopulation Datafiles. If the user wishes to use census tractsfrom the 2000 Census, thePopulation sector locationfile accompanyingAPEX will be sufficient. All of the sectors used in the commuting file mustbe included in thePopulation sector locationfile and thePopulation Datafiles; if sectors other than 2000 Census tracts are used, the user must provide aCommutingfile compatible with these sectors. In addition, if the user wantsto restrict the study area to selected counties, thePopulation sector locationfile must include the county IDs associated with sector as part of the sectorIDs in the proper format (as in the supplied file).Locations of air districtsSpecified in theAir district Locationfile. The user must always define theappropriate air districts for an application.The locations of the air districts must be selected such that they can providereasonable estimates of air quality for the sectors and study period included inthe analysis. Data for each AQ monitor for each pollutant in the simulationmust be provided in the Air Quality Data files (one for each pollutant).Radius of air districtUsing theAirRadiuskeyword in theControlfile, the user can specify themaximum distance (in km) that a sector can be from the nearest air district toremain in the study. If all district centers are further thanAirRadiusfrom thesector center, the sector is removed from the study area and is not modeled.Users must always define an appropriatevalue for this radius based on theirapplication.The radius of the air districts must be selected such that they will include thesectors the user would like toinclude in the analysis.Type of Air QualityDataThe keywordModelAQVarspecifies the type of air quality data to be used inthe simulation. The air quality may be entered as raw values for each timestepin the simulation (the default,ModelAQVar=N) or as distributions for eachhour (ModelAQVar=Y).The value ofModelAQVardictates the expected format of theAir QualityDatafile. See Section4.5for details.Location ofmeteorological datastationsSpecified as zone IDs and locations (latitude and longitude) in theMeteorology Zone Locationfile. The user must always define the locationsof meteorological stations for an application.Data for each meteorological data station specified in theMeteorology ZoneLocationfile must be provided in theMeteorology Datafile.11Impact of ChangingDefault SettingSETTING/OPTIONHow Option is Selectedon Other Input FilesRadius ofmeteorological stationcoverageUsing theZoneRadiuskeyword in theControlfile, the user can specify themaximum distance (in km) from a sectorto the nearest meteorologicalstation. If all zone centers are further thanZoneRadiusfrom the sectorcenter, the sector is removed from thestudy area and is not modeled. Usersmust define an appropriate value for this radius based on their application.The radius of the zones must be selected such that they will include thesectors the user would like toinclude in the analysis.POLLUTANTSNumber of pollutantsThe number of different pollutants to be modeled mustbe specified using the#PollutantskeywordPollutant NamesThe user must specifyeach pollutant with the keywordPollutant. Thepollutant name may contain only alphanumeric characters and the underscore(“_”) character, as it is used to generate filenames.Must be followed in theControlfile by the pollutant-specific parameters andoutput table levels.Model dose forpollutantSpecified using theDoDosekeyword in theControlfile. Pollutant-specific.If this keyword is set to “YES”, APEXwill calculate dose for the pollutant; ifit is set to “NO”, the dose calculations will be suppressed.IfDoDoseis set to “YES” and CO is beingmodeled the user must specify thecorrect values for theAltitude,COHBFactkeywords in theControlfile.PROFILESNumber of profilesSet to an integer using the#Profileskeyword in theControlfile. Users mustdefine an appropriate value for thiskeyword based on their application.None.Modeled populationsSpecified in theControlfile following the specification of the file names.The user must provide a population filefor each population to be modeledand indicate the gender and race associated with the file. All gender/racecombinations without specified population files are assumed to have zeropopulations. Users can select from the sets of availablePopulation Datafilesaccompanying APEX (i.e., the national population files or the files specific tothe Houston example applications), or generate their own.If the user wishes to model a subpopulation, the user must supply alternativePopulation Datafiles with the appropriate counts.Profile function optionsSpecified in theProfile Functionsfile. The user must develop data relevantto a particular application prior to performing an APEX simulation.None.Employment statusSpecified in theEmployment Probabilityfile for implementation ofcommuting. The file accompanyingAPEX should be sufficient for allapplications where sectors are defined as census tracts.None.Minimum andmaximum ages forsimulated profilesSpecified using theAgeMinandAgeMaxkeywords in the Control file.None.Modeled age groupsSpecified in thePopulation Datafiles. The files that accompany APEXdefine the age groups as single years up to 99, and are sufficient for allapplications where sectors are defined as census tracts.None.Size of age windowTheAgeCutPctandAge2Probabkeywords in theControlfile are used tospecify the window around the assigned age of a profile from which activitydata can be selected.None.Probabilities forselecting diaries withmissing characteristicsUsing theMissGender,MissEmpl,andMissAgekeywords in theControlfile, the user can specify the probability that activity diary data with missinggender, employment status, or age will selected.None.1213Impact of ChangingDefault SettingSETTING/OPTIONHow Option is Selectedon Other Input FilesType of diary assemblyDetermined by theLongitDiarykeyword. If YES, longitudinal dairyassembly will be performed based on the statistic in theDiary Statisticsfile.If NO, APEX will randomly select a new activity diary for each day in thesimulation.IfLongitDiaryis YES, then theDiary Statisticsfile must be designated in theControlfile, and theDiaryDandDiaryAutoCkeywords must be set.Physiologicalparameters for thesimulated populationSpecified in thePhysiological Parametersfile. The default values in this fileare suitable for most APEX applications.None.Activity-specific energyexpenditures for thesimulated populationSpecified in theMET MappingandMET Distributioninput files. The defaultvalues in these files are suitable for most APEX applications.None.Modeling of diseaseprevalenceDetermined by theDiseasekeyword. IfDiseaseis given a value (a string ofmaximum length 12 characters containing the condition name, spacesallowed) in the input file, APEXwill then use data in thePrevalencefile toassign a YES/NO value to the physiological profile variableIll, and produceoutput tables for the subpopulation of modeled persons withIll=YES.IfDiseaseis given a value (a string ofmaximum length 12 characterscontaining the condition name, spaces allowed) in the input file, then APEXrequires that aPrevalencefile be designated as well.MICROENVIRONMENTSMaximum number ofmicroenvironmentsSet to an integer using the#Microkeyword in theControlfile; must notexceed 127.Number of APEX microenvironments in theMicroenvironment MappingandMicroenvironment Descriptionsfiles must not exceed the specified value intheControlfile.MicroenvironmentdefinitionsSpecified in theMicroenvironment Descriptionsfile. The user must developdata relevant to a particular application prior to performing an APEXsimulation.Each location referencedin the activity database(e.g., CHAD) must bemapped to one of the microenvironments specified in theMicroenvironmentDescriptionsfile using theMicroenvironment Mappingfile. The user maychoose to define custom microenvironmental parameter definitions thatdepend on conditional variables. If so,these variables must be defined on theProfile Functionsfile.OUTPUTSProduce hourly outputsSpecified using theHourlyOutkeyword in theControlfile. If this keywordis set to “YES”, the hourly output file is created;if it is set to “NO”, the file isnot created. The variables to be written are listed using the keywordHOURLYLIST.None.Produce daily outputsSpecified using theDailyOutkeyword in theControlfile. If this keyword isset to “YES”, the hourly output file is created; if it is set to “NO”, the file isnot created. The variables to be written are listed using the keywordDAILYLIST.None.ProducemicroenvironmentaloutputSpecified using theMSumOutandMResOutkeywords in theControlfile. Ifthese keywords are set to “YES”, theMicroenvironmental Summaryand/orMicroenvironmentalResultsoutput files are created; if they set to “NO”,these files are not created.None.Produce event outputSpecified using theEventsOutkeyword in theControlfile. If this keyword isset to “YES”, the events output file is created; if it is set to “NO”, this file isnot 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 executa ble 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 locat ions of all the require d 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:

• T yping the path and file name of the APEX execu table 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 co mmand, 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 othe r unit number is request ed, then that means that one of the other input file s (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 w ould input the locatio n 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 m ode, meaning that the m odel’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 te xt editor. On each line of this file, enter the file path and name of the APEX executable foll owed 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 ma nner, multiple runs using different model settings

14can 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 desi gnating 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 fi le in any of the following ways.

• Opening a DOS window and typing the batc h file name (and path, if necessary)

• Double-clicking on the batc h file in Explorer

• Selecting “Run” from the Windows Start menu an d entering the file pa th and name of the batch file

• Creating a shortcut to the batc h file on the desktop by selecti ng the batch file in Explorer, right-clicking the mouse, and se lecting “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 progr esses, 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

.

15Exhibit 1-2. Screenshot of the Start of an APEX Run

Exhibit 1-3. Screenshot of Successf ul 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 informa tion 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 distri cts, and meteorology zones), (3) th e simulated microenvironments. The Log file (which is discussed in Section 5.1) w ill 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 th e 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 thei r descriptions are given in Table 4-1 . Some of the input files are not required if certain feat ures 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 cons idered. These are noted in Table 4-1 . All input files are ASCII text files that can be edited usi ng 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 a nd 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 le tters, blanks, or commas. APEX uses the keyword to locate and set the input values. The values may be ch aracter, 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 characte r 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 us er to help document th e 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 sensi tive, 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 va lues or data do not have to be fixed in specific positions on an input line. Multiple items on an i nput line can be separated by either a blank or comma. The various site names and similar inputs should not contain inte rnal blanks, as these will be interpreted as delimiters between input fiel ds. This does not apply to keyword lines, as those lines have only two fields (separated by th e “=” sign), so either or both sides may contain internal blanks.

17Table 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 (deg rees latitude and long itude) of air quality monitoring or modeling locations. The file is used along with the user-defined AirRadius to define the geographical area c overed 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 (d egrees 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 de termine window positions, group activity pattern pools, and microenvironm ental parameters in APEX. Air Quality Data File Provides the air quality data fo r 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 polluta nts 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 dime nsionless 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-depende nt energy expenditure rate to the basal or resting energy expenditure (metabolic) rate. Physiological Parameters File Contains tables of age- and gender-s pecific physiological parameters.

18Input File Description Ventilation File This file contains regression parame ters 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 statis tic 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 vari ety 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 th e details of APEX input files and provide several examples. Note that these example files in this and th e next chapter are provided for illustration only. These are provided for the purpose of highlighting various aspects and opti ons 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 spec ific 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. Us ers are encouraged to view the example input files (which can be downloaded separately) fo r a complete set of input files.



### 4.2 Simulation Control File

The Simulation Control file (which we al so refer to as the Control file) is APEX’s master simulation file. The Simulation Control file names input and output f iles, sets model parameters, and controls formats of output files. APEX only processes keyw ord 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.

19When creating the Control file, the following rules should be used:

• The very first line of the file should identif y the specific simulation (up to 224 characters in length);

• Keywords (or parameter or variable names) ar e 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 fi rst line, with the fo llowing exceptions:

o Lines using the County keyword, which must immediat ely follow the line with the CountyList keyword;

o Lines using the Tract keyword, which must immediat ely 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 lin e is treated as a comment and ignored; and

• Any unexpected line without an equal si gn 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 ba sed 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 le vels), 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 Sect ions 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 de tails on the content and form at 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 c ontained 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, th en APEX will prin t an error listing the file that is missing.

The Air Quality Data files are the only input file s that are pollutant-specifi c, 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).

20The example in Exhibit 4-1 has 10 population data files. Th e 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 keyw ord input line in the Control File , followed by a comma and Gender and another comma and Race

. Gendermust be either male or female and it can be shortened to M or F. If the population files provid ed with APEX are to be used, the Race must be White, Black, Asian, NatAm, or Other.. If th e user provides th e 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 designati on in the header of the population files, or an error will result. Fu rther information on population files is given in Section 4.8.

It is not necessary to specify all genders and r ace combinations for APEX to run. However, the model assumes that any missing gender/race comb inations have zero population. A warning message is returned if one gender for a r ace 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 microenvironmen tal summary file creation, the corresponding output files will not be generated, and file names do not need to be specified. The Microenvironmental Summary, Mi croenvironmental 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 de tails 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 Sectio n 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 Sect ion 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. Thes e parameters are described in Table 4-2

.

22#Pollutants must be equal to the number of differen t 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 de finition 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 polluta nts must start with th e characters “PM.” The Size and Density parameters must be defi ned 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
μ g/m 3 ).
OutputUnits Char(40) Pollutant concentration units used for the output data for the pollutant (ppm or
μ g/m 3 ).

#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/m 3 that equate to 1 ppm. For CO, ppmfact = 1,145 (i.e., 1 ppm = 1,145 ug/m 3 ). 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/cm 3 ) 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 ta bles 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 polluta nt must come after the corresponding Pollutant keyword. Each parameter is identified by a single keyword, a nd the values are a list of numbers ordered from smallest to largest and se parated by commas. All the values are read as real numbers, although the decimal points are optional if the values happen to be integers. Items

23in each list must be separated by commas. Except for the Percentiles , all of these parameters are used to bin exposures or doses in to categories in order to create out put 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 omitte d, then the corresponding table is simply not written in the output file. See Ch apter 5 for more information on the APEX output tables.

Table 4-3. Output Parameter Leve ls 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 ex posure 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 gene rated 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 gene rated with the APEX timestep is greater than one hour.) Daily Max Timestep Exposure Cut points DMTSEXP Real This parameter specifies da ily 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 ov er 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-po ints 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.

24Table 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 th e 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 po ints 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 tim estep 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 pol lutant parameters section for a simulation of two pollu tants: 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 S ection 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 AP EX 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 la st occurrence overwrites the others. Exhibit 4-4 shows an example of this section of the Control file.

26When APEX runs, the values of all the job setti ngs (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 sli ghtly 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 YY YYMMDD 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 tim esteps: 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 th e center of the study area. Note that latitude south of the equator is negative. Longitude Real Longitude in decimal degrees for th e center of study area. Note that longitude west of the prime meridian is negative (e.g., in the United States).

27Altitude 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 th e 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 representa tive 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 ex pected 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 (k m) 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 s ector (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 outp ut 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

28Commuting 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 se lected for each simulated profile based on the probabilities of work sectors a person may travel to from a home sector. If N, then wo rkers 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 concentratio n 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-w ide 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 sa me 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 permitte d 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 unkn own 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.

29MissGender 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 se lected 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 al gorithm. 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 dist ricts will be selected for each person for calculating the air quality for diary events with location=O (“Other”). The number of district s 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 concen tration. Use same units as InputUnits

. RbMax Real Rollback maximum concentr ation. Use same units as InputUnits

. RbTarget Real Rollback target concentr ation. 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 am bient 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.

30Log 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 fo r 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 fo r 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 stud y 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 a nd 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 th e 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 commaor spaceseparated strings List of keywords indicating which variables are to be written to the Daily output file. See section 5.4 for details.

31DailyOut 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 commaor 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”, “w ork”, and ‘other” locations.

MResList commaor 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 creat ed. Otherwise, the file is not written. MSumOut Char(1) Y = the Microenvironmental Summary file will be created. Otherwise, the file is not written. PsumList commaor 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. Ot herwise, the file is not written. If the default timestep (1 hour) is used, then this file will not be written because it w ill be identical to the Hourly file. TimeStepList commaor spaceseparated strings List of keywords indicating which variables are to be written to the Timestep output file. See Section 5.3 for 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.

32ChildMin 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 reflect s 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 Sectio ns of the Simulation Control File



### 4.3 Population Sector Location File

The Population Sector Location file provides the lat itude and longitude of a representative location such as the geographic cen ter 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 charac ter, and is stored as a character string (up to length 40). The string may contain any characters except ! or em bedded spaces. The sector ID must match the sector IDs in the Commuting Flow file (if worker commuting is be ing modeled). The ID is casesensitive, so the values in the two files must match exactly.

35The population sector location file is used along with the user-specified CityRadius to automatically select population sectors within th e 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 st udy area and then compares it with the CityRadius . Sectors with a distance from the st udy 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. Ce nsus tracts. APEX expects that the left-most five characters of a sector ID will be the st ate 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 leas t three significant digits should be provided after the decimal point to prevent significant rounding e rror. 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 Po pulation 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 m onitoring) sites included in the Air Quality Data file (Section 4.5). The site ID may be any string, numeric or ch aracter, 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 Exam ple Air District Location File

APEX uses the Air District Location file to determine the “air di strict” 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 on ly 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 da ta covering the entire simulation pe riod 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 af ter the simulation period are simply ignored.

APEX then calculates the distan ce 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 distri ct’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 locatio ns 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 neares t 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 quali ty input file need sectors assigne d to them. Such air districts are simply not included in the modeling. This featur e 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 stat e. This same input file could then be run on several study areas in the state without having to al ter the air quality input file.

Internally, APEX refers to air quality districts by a sequential i ndex (district #1, #2, etc.) that is assigned when the district-secto r 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 ca se district #1 might ch ange meaning from year to year. This can be avoided by preparing an Air Quality Data input file (see ne xt Section) that

37has 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 proces sed and other types of input lin es 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 shou ld 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 e ach air district for each ti mestep (for example, hour) in the simulation. The second type of AQ data file contains distri butions 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 head er 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 nume ric 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 Cont rol file for the pollutant. The data values can be either comma or space delimite d. 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 aver age 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 porti on 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 m odel person-to-person variability within an hour within an AQ district. This type of data can only be used if the APEX ti mestep is equal to 1 hour ( TimestepsPerDay =24, the APEX default).

Within this file the data for each site begins with a header section co ntaining 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 th is type of input is to be used, the Control file flag ModelAQVar must be set to Y, otherwise an APEX e rror will result. An example of the first part of an AQ Data file (distri bution type) is shown below in Exhi bit 4-8. In this example, the AQ value for each hour is defined by a normal di stribution. 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 Qu ality 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 s ite 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 conveni ence. 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 Exampl e Meteorology Zone Location File



### 4.7 Meteorology Data File

This file provides hourly temperature and me teorological data for th e 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 i nput lines are ignored. The meteorology sites may be in a ny order in this file. The sec tion of data for each site must begin with the “name” keyword inpu t 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 mo re comment lines in the header section of a data set.

Temperatures can be used to assign activity diarie s 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 microenvironmen t parameters (see Section 4.15.2 and Volume II ).

40The “site name” input line is followed by the mete orological 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 column s and may be separated by whitespace only.

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

The precipitation code may be a ny character string, up to 12 char acters in length (no spaces), although it is assumed that this code will be no mo re than 2 letters under normal circumstances. (The codes used for precipitati on 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 us er 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 simulati on period. A data set ca n 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 diffe rent 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

4120040101 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 Portio n of Meteorology Data File



### 4.8 Population Data Files

Each Population Data file contains sector-level data fo r 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/gend er 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 (w hich start with “!”) and before the population data records (i.e., the actual popul ation counts). The data on these four records are read starting to the right of the ‘=’ sign, if pres ent. 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) Desc riptor 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-charac ter label for race also appear s as a column header on the Profile Summary output file. If the populatio n 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 exampl e, 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 th e 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 al l the population data files must contain the same

42number of population groups, and furthermore, all the group age limits (minima and maxima) must match as well, or APEX will exit with a Fa tal 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 mu st 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 se ctors do not necessarily ha ve 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 wr itten 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 th e 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 reco rd 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 wo rk 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

43APEX 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 usi ng the cumulative fractions as commuting probabilities.

The user can create their own co mmuting databases using the form at 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 sect ors 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 be en prepared for ages 16 and above, covering all the tracts from the 2000 census. Each record (tract) contains 26 proba bilities (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 th e file format is followed. The ag es in the employment file may extend beyond those in the population files, but be aware that APEX will ne ver 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 lin e 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 colu mn). The first item on each line below the header

44lines is the sector ID, followed by the eight employment probabil ities 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 ra nge and gender. Whenever the total sector population for a particular age range and gende r is zero, then obviously the employed persons must also be zero. These data are reported as zero probabilities in the fi le. It should not matter what values are assigned, since no simulated persons of that type should ev er be generated by the model. Note that a custom employment proba bility 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 em ployment 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) ac tivity code to an inte rnal APEX distribution number, for calculating the energy expended by a si mulated person for each diary event. Energy expenditures are used for estimating activity le vel and ventilation for each simulated person. These quantities are used for used in creating tabl es of exposures at diffe rent 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 resti ng 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 curre nt 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

45Activity 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

46Activity 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 Par ticipate 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 inte rnal APEX distribution number; activities that have identical energy ex penditure associated with them ma p to the same distribution. The distributions themselves ar e 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 C HAD 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 ma ps 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 be ing 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 Mappi ng 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 Portio n of the MET Mapping File.

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



### 4.12 MET Distribution File

This file provides the actual distributions fo r calculating the MET value for each diary event (activity). The distributions are defined by APEX distribution numb er 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 ener gy expenditure (metabolic ) rate, and the CHAD activity code is an identifier associated with each diary event that indica tes 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 experi mental data on human energy expenditures.

The distribution definitions make use of the stan dard APEX distribution format (a distribution shape, followed by 4 distribution paramete rs, 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 t ype 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 pr obability 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, ra ther 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)

49Distribution 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 plac eholders in the file if a paramete r 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 numb er 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-O 2 /(min-kg)

( Note : while the APEX inputs for NVO2MAX are in ml-O 2 /(min-kg), APEX outputs VO 2 Max in the Profile Summary file in L-O 2 /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/inches 3
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-O 2 /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 2 nd half of menstrual cycle) ml/min

Distributions for the above parameters are a ssigned to persons of every age and gender combination in the Physiology file. The distributions are de fined in the APEX distribution format (a distribution shape, followed by 4 dist ribution 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.

• Genderfor the current parameter distribution.

• Distribution Shape . This variable gives the t ype 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 pointof the distribution.

• UTrunc . Upper truncation pointof 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 distribu tions in this file should not be changed from their default values, as they were de rived 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 ventila tion 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 (D istributions) File

The Profile Functions input file defines functions for vari ables associated with each simulated profile. There are two types of functi ons 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 ci rcumstances can be customized by the functions defined in this file. Most of th ese 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 wi shes. 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 variab les can vary by region (either county or sector) and thus may be evalua ted differently for individuals who reside in these different regions. Up to five of these functions may be defined.

The relationships among the different f unctions 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 V C , which are functions of input APEX variables (V I ). These conditional variables are used in determining microenvironmental parameters. Microenvironment parameters are qu antities that appear in the equations for the microenvironmental concentrations . The relationship between th e conditional variables and the microenvironment parameters are described in the Microenvironmental Descriptions file (see Section 4.19).

54Built-in profile functions User-defined profile functions

Built-in and user-defined conditional

variables V C Profile Functions File

Micro parameters, MP

Micro concentrations Micro Descriptions File Input variables

V I

DiaryPools Built-in profile functions User-defined profile functions

Built-in and user-defined conditional

variables V C Profile Functions File

Micro parameters, MP

Micro concentrations Micro Descriptions File Input variables

V I

DiaryPools

Figure 4-1. Relationship between Profile F unctions 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 (RegionalC onditional1-5), then a statement is required to define how the regions are defined, either by co unty or sector, and how many different regions are being modeled.

554. 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 le ast 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 vari able in the function, the Type of Input Variable , and the Number of Values (Nvals) allowed for the input variable. At the e nd of this input line , the user may add comments in double quotes to explain input variables. The line s directly following define the input variable data – specifical ly, they define how the input va riable 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 fixe d probabilities. The sum of the probabilities must equal 1. Realrange means a set of discrete categories, each cons isting of a range of r eal numbers. In this case, the categories are defined by Nvals-1 cut poin ts. (If the input variable falls on a cut point, it falls into the higher bin.) Intrange is similar, except each cate gory consists of a range of integers. Intvalue means that each possible value that th e input variable may take on is listed on the data line. Intindex means that the input variable is inte ger and is to be used to index the table of results directly ( e.g. , a value of 3 means use the third ce ll 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 approp riate use of these input variable types.

5. After all the input variables are specifie d, 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 subs equent lines. If the result type is designated as integer, the results must be a list of inte gers 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 point s that define Nresults bins.

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

56The types of profile functions are discussed in de tail below, with examples. Note that when preparing or editing a profile func tions file, be careful not to us e Tab to separate the items on a line. APEX explicitly searches for blanks (space s) as delimiters, and does not recognize Tabs as such.

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

The built-in APEX variables for which f unctions 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 variab le DiaryPools. (Note that a few other APEX variables, such as gender, can be used as c onditional variables, see Section 4.19.2). DiaryPools is the only function that APEX re quires be defined, as it is used in the selection of appropriate CHAD diaries for different days in the simulation. The input variables requi red for each of these functions are hard coded; the re quired 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 vari ables are listed in th e 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, thes e category numbers can be used in defining the microenvironment parameters in the Microenvi ronment 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 cat egory number for the average temperature, which will be used in the definition of one or more microe nvironment parameters. Recall that the input parameters for this function are fi xed, and that the text in quotes is not used by APEX. The first and only input variable defi nes the integer ranges (via intrange ) for the three categories of average temperature. In this case, th e ranges are < 50 degrees, 50-77 degrees, and ≥ 78 degrees. The function essentially reads the daily averag e 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 it s two possible integer values (via intvalue ), as 1 or 2. The second input variable is the maximum daily temp erature; 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 point s 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 pr obabilities 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,

5758 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 FileConditional VariablePurposeInput VariablesNumber ofCategoriesFunctionReevaluatedTempCatBinning hourly temperatures intocategoriesINPUT1: Temperature on hour of simulationany numberhourlyHumidCatBinning hourly humidities intocategoriesINPUT1: Humidity on hour of simulationany numberhourlyWindCatBinning hourly wind speeds intocategoriesINPUT1: Wind speed on hour of simulationany numberhourlyDirCatBinning hourly wind directions intocategoriesINPUT1: Wind direction on hour of simulationany numberhourlyPrecipCatAssigning precipitation codes tocategoriesINPUT1: Precipitation code on hour of simulationany number(equal to orless than thenumber ofprecipitationcodes in theMeteorologyDatafile)hourlyMaxTempCatBinning daily maximum temperaturesinto categoriesINPUT1: Temperature on hour of simulationany numberdailyAvgTempCatBinning daily average temperaturesinto categoriesINPUT1: 24-hour average temperature on day of simulation(AvgTemp)any numberdailyDiary Pools(Required)Assigning diary poolsINPUT1: Maximum temperature on simulated day (MaxTemp)INPUT2: Average temperature on simulated day (AvgTemp)INPUT3: Day of the weekany numberdailyHasGasStoveProbability of having a gas stoveINPUT1: Probabilities for the 2 results2 (Y/N)once per profileHasGasPilotProbability of having a pilot light,conditional on HasGasStoveINPUT1: Has Gas Stove (Y/N)? (HasGasStove)INPUT2: Conditional Probabilitiesfor the result categories forboth HasGasStove=Y and HasGasStove=N2 (Y/N)once per profileAC_HomeProbability of having different types ofhome air conditioning or ventilationINPUT1: Fixed probabilities forthe types of air conditioning /ventilation (the number of types is user-defined)any numberonce per profileAC_CarProbability of having A/C in carINPUT1: Probabilities for the 2 results2 (Y/N)once per profileWindowResProbability of residence windowsbeing open or closed, conditional onAC_Home, MaxTempCat, andAvgTempCatINPUT1: Type of home A/C (AC_Home)INPUT2: Max. temperature on day of simulation (MaxTemp)INPUT3: Average temperature onday of simulation (AvgTemp)INPUT4: Conditional probabilitiesfor the result categories forevery combination of input1-input3 categories2 (Y/N)dailyWindowCarProbability of car windows being openINPUT1: Has car A/C (AC_Car)2 (Y/N)daily5960Conditional VariablePurposeInput VariablesNumber ofCategoriesFunctionReevaluatedor closed, conditional on AC_Car,MaxTempCat, and AvgTempCatINPUT2: Max. temperature on day of simulation (MaxTemp)INPUT3: Average temperature onday of simulation (AvgTemp)INPUT4: Conditional probabilitiesfor the result categories forevery combination of input1-input3 categoriesSpeedCatProbability of average speed categoriesfor vehiclesINPUT1: Fixed probabilities for the result categoriesany numberdailyDailyConditional1Generic daily conditional variable #1INPUT1: Fixed probabilities for the resultcategoriesany numberdailyDailyConditional2Generic daily conditional variable #2INPUT1: Fixed probabilities for the resultcategoriesany numberdailyDailyConditional3Generic daily conditional variable #3INPUT1: Fixed probabilities for the resultcategoriesany numberdailyProfileConditional1Generic profile conditional variable #1INPUT1: Fixed probabilities for the resultcategoriesany numberonce per profileProfileConditional2Generic profile conditional variable #2INPUT1: Fixed probabilities for the resultcategoriesany numberonce per profileProfileConditiona3Generic profile conditional variable #3INPUT1: Fixed probabilities for the resultcategoriesany numberonce per profileProfileConditional4Generic profile conditional variable #4INPUT1: Fixed probabilities for the resultcategoriesany numberonce per profileProfileConditional5Generic profile conditional variable #5INPUT1: Fixed probabilities for the resultcategoriesany numberonce per profileRegionalConditional1Generic regional conditional variable#1INPUT1: Fixed probabilities for the result categories, defined foreach region (sector or county) modeledany numberonce per profile,based on profile’shome sectorRegionalConditional2Generic regional conditional variable#2INPUT1: Fixed probabilities for the result categories, defined foreach region (sector or county) modeledany numberonce per profile,based on profile’shome sectorRegionalConditional3Generic regional conditional variable#3INPUT1: Fixed probabilities for the result categories, defined foreach region (sector or county) modeledany numberonce per profile,based on profile’shome sectorRegionalConditional4Generic regional conditional variable#4INPUT1: Fixed probabilities for the result categories, defined foreach region (sector or county) modeledany numberonce per profile,based on profile’shome sectorRegionalConditional5Generic regional conditional variable#5INPUT1: Fixed probabilities for the result categories, defined foreach region (sector or county) modeledany numberonce once perprofile, based onprofile’s homesector profileAvgTempCat ! 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 anal ogous manner. The only valid input type for the user-defined conditi onal variables is PROBABILITY. Note the probabilities for the

61four 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 us ed to describe difference in housing conditions (presence of an attached garage) in different sectors of the study area. The BY statement indicates how the prev alence vary regionally, either by county or by sector (in this case, sector). This line must additionally contai n the number of regions (ie. counties or sectors) that will be used (in this case, 14). After this BY line, the pr obability input for each sector or county is listed. APEX matches th ese regions to the appropriate st udy area sector (or sectors, in the case of a county), and uses them when assign ing 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 RESU LT,1=yes, 2=no) based on their sector’s listed probabilities.

The minimum number of categories fo r all the variables defined in the Profile Functions file is one, in which case all profiles will have th e same value for the variable. However, microenvironment parameters cannot depend on th e 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 locati on code followed by a short descript ion, 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 desi gnations are used to assign a set of microenvironment concentrations to each event; as th ree sets of concentrati ons 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’).

63Table 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

64Location 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 informati on component of each 24-hour activity diary ( Exhibit 4-20 ). Each record contains valu es 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 c odes are missing for this diary day)

• Record count(the number of records in the CHAD Diary Events file corresponding to this diary day)

65The user should not change this input file unless the CHAD database has changed or other activity data are to be us ed 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

66Code Description

MACH Machine operators, assemblers, and inspectors

TRANS Transportation a nd 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 ar e 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 fi le. 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 Port ion of Diary Events File

67

### 4.19 Diary Statistics File

This file contains a diary statis tic for each diary in the CHAD database. This file is used in constructing multi-day (longitudinal) diaries in AP EX 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-leng th 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 fo r selecting diaries based on some key statistic of each CHAD diary. Details of this l ongitudinal diary algorithm are provided in Volume II: Technical Support Document . In short, the algorithm require s the selection of a diary based on some key diary statistic relevant to the pollutant being studied. Fo r example, the statistic may be time spent outdoors or time spent in a vehicle.

The Diary Stati stics 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 CH AD and are included in the APEX Version 4 release. These files are for time spen t outdoors and time spent in vehicles. The files were constructed by summing the time spent in lo cations considered “out doors” 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 fr om the CHAD database. An example portion of a diary statistic file is shown in Exhibit 4-22

. The use of the longitudinal algo rithm is invoked by setting the Si mulation 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 Constr ucting 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 purpos es. Firstly, it defines the methods by which pollutant concen trations 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 microenviro nment for each pollutant (with the exception of the parameters air exchange rate and micr oenvironment volume, which are not pollutantspecific). Thus, the Microenvironment Descriptions file has two sections following the general header records: Microenvironment Descriptions and Parameter Descriptio ns. An example of the Microenvironment Descrip tion 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 microenvironm ents 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 ba lance 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.

69Micro Name Method 1 Residence MASSBAL 2 Car MASSBAL 3 InsideOther FACTORS 4 Outside FACTORS Exhibit 4-23. Example Microenvironment Des criptions 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 distri butions for the microenvironmenta l parameters that are required for calculating pollutant concentratio ns in the microenvironments. See Volume II: Technical Support Document for further information on the microe nvironmental parameters required for the MASSBAL and FACTORS concentration calc ulation methods. Three microenvironmental parameters can be defined for the FACTORS me thod 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 ar e only defined once. Otherwise, there must be one definition for each microenvironmental parameter for each poll utant 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 μ g/m 3 (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 m 3 none
MeanR MR 1/hr AirExRate+DecayRate

Csource CS ppm or μ g/m 3 (depends on InputUnits) 0 MASSBAL

ESource ES μ g/hr 0

70As mentioned above, not all of the paramete rs 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 paramete rs. If no parameters are defined for microenvironments using the FACTORS method, then the microenvironment con centration is always equal to the current ambient concentration. For a MASSBAL microenvi ronment, the air exchange rate parameter must always be defined as it has no default valu e. The volume parameter does not have a default either, but it is only used if ESource terms exis t 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 concen trations immediately outside a nd inside a microenvironment. The air exchange rate and volum e variables define the air fl ow rate in and out of the microenvironment and the microenvironment air vol ume. 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 pa rameters and the microenvironmen tal concentration equations.

As part of the estimation of microenvironm ent 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 ma y not be different from the valu es at other hours, depending on choices in the microenvironmental parameters de finition. Some microenvironmental parameters, such as house volume, typically remain constant throughout the simulation, while others may change seasonally, daily, or hourly. Values may r ecur in patterns, such as the same set of 24 hourly values for some parameter may recur each Sa turday in the Winter season. These patterns are determined from the four ma pping options and the three resampling options specified in each microenvironmental parameter definition.

The definitions for the microenvironment para meters may appear in any order in the Microenvironment Descriptions file. Therefore, the user (f or 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 de scription 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 para meter (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 a ny 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 desc riptions are provided in Table 4-13

. The conditional variable keywor ds must be either one of th e 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, Prof ileConditional1-Pr ofileConditional5, RegionalConditional1- RegionalConditional5 ), or Gender
, Employed , or PopCat . All variables, with the exception of the la st 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 correlati ng 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 simu lated 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 samp ling them using the same random numbers. This results in values being selected for correl ated 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 an d area mappings, and resampling rates and thus have the same number of required distri butions and samples. Otherwise the samples get out of phase and any correlation is lost. AP EX checks that the conditionals, mappings, and resampling are the same when correlating paramete rs, and writes a warni ng 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 in teger 1-N, where N is the total number of correlated subsets.

All the keywords for the microenvironmenta l 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 indi cating the end of the keyword section. (See Exhibit 4-24 for an example of an appropriate header.)

72Table 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 be ing 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 us er desires be correlated (sampled at the same percentile each hour) are assigned a un ique 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 sa me 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 intege rs 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 numbe r 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.

73Keyword 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 w ithin 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 determin ed from the internal clock, and the results will differ from one run to another. If not zero, then Seed = (RandomSeed x 232) + RandomSeed. Multip le model runs with the same seed will generate the same sequence of random numbers for the parameters (as long as the microenvironmental parame ter 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 tim es or under different circumstances during the simulation. Sets of distribution da ta may exist for all possible comb inations 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 W eekday – 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 descri bed by the District – Area ma pping in the keyword section

• C1 — conditional variable # 1

• C2 — conditional variable # 2

• C3 — conditional variable # 3

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

74above list. Note that the cases of each indexing parameter mu st 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 RegionalConditional 1-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 indica ted 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 w ould correspond to the case PopCat =1).

The user specifies the microparameter distributio n using the standard APEX distribution format (a distribution shape, followed by 4 distribut ion 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 pointof the distribution.

• UTrunc . Upper truncation pointof 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 dist ribution definitions work.

In the first example, the microenviro nment 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 th e conditional variable AvgTempCat has five possible values (1-5) and AC_Home has two possible values (1-2); thes e variables and their values were defined in the Profile Functions file. Thus, probability distributions for AE must be defined at

75all 10 combinations of the two conditional variab les. The ten distribut ions are lognormal in shape (although they have different parameters), and ar e listed in order – fi rst 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 ra ther 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 a nd 2) roughly defining ni ght 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 t ypes, “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 si ngle 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 paramete rs. 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.

76Micro 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 Descriptio ns in the Microenvironment Description File



### 4.21 Prevalence File

The Prevalence file is an optional APEX input file fo r modeling a subpopulation of persons with a particular disease or condition. The Preval ence 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 pe rsons 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 fi le contains an age, followed by the values for males, then females. The values in the prevalen ce 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 ed itor or other software (e.g., spreadsheet, database, statisti cal 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 descrip tions 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.

79Table 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 complete s 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 desc ribing 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 lin e lists the person’s age, gender and race, in addition to a number of ot her personal profile variab les 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 exposu re/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 distri cts, 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 indi viduals 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 pa rameters 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 informa tion as a model run progresses:

• Input files used;

• Model parameters used;

• Number of diaries available to matc h 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 dist ricts and meteorology zones;

• Statistical summaries of each simulated person (profile); and

• Output summary tables.

If a model run stops abnormally, an error message w ill be written to the log file. The user should review the Log file after a m odel run to ensure that the simulation executed and terminated normally and that the output result s are valid. Note that output su mmary 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, th e more information is written to the log. The Control file settings LogDistrict
, LogPopulation

, LogProfiles

, LogSectors
, LogTables , and LogZones also control the writing of in formation 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 thei r 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

81Variable 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 th e time-weighted averages of the event values for these variables. The ambi ent concentration is time-averag ed over the events because the simulated individual may move be tween 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 microenviro nment N, equal to:

ExpN = 60 * 

# ∑ Duration ConcN , for events in the hour in microenvironment N

82where ConcN is the concentration in microenviro nment N for the event a nd Duration is the event duration in minutes. A weighted average is used because it is po ssible 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 h ourly exposure. Hourly exposure factor EF is just the ratio of the hourly exposure to the hour ly 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 f ile in the order they appear in the table. The list should be on a single line and may be comma or space-delimite d. The EXP, DOSE, EXPN, AMB, and EF keywords control the writi ng 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-po llutant 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 larg e 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 se ries 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 corre sponding 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 con centration are the time-weighted averages of the event values

84for these variables. The ambi ent concentration is time-averag ed over the events because the simulated individual may move be tween home/work/other locations (and thus possibly between air districts) in the course of an timestep. T hus, 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 f ile 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, DOS E, 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 AP EX variables for each simulated person or profile. Writi ng 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

85using the Control file keyword DailyList . The variables and thei r 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 temp erature for the day (as determined by profile functions file) MAXTEMPCAT Y

86Variable 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 li st. The exposure and dose keywords will control printing for all pollutants in the simulation; the f ile headers for these variables will contain the pollutant name.

Note that the Daily file could be very large if a larg e 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 eith er spaces or commas. An example DailyList would be:

87DailyList = 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 co rresponding label in the file head er (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 char acteristics 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 th e 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 ke ywords. The available variables and their correspondi ng 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

88Variable 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

89Variable 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 (m 2 ) BSA Y

Energy Conversion Factor Energy conversion factor for person (L-O 2 /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 oxygenuptake rate for person (LO 2 /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) RECTI ME Y Resting Metabolic Rate in) RMR Y Resting metabolic rate (kcal/m

VE Intercept VEINTER Y Regression parameter for the ventilation routine

VE Slope VERESID Y Regression parameter for the ventilation routine

90Variable 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 μ g/m 3 , as specified in Contro file)

Maximum Exposure over the simulation

MAXEXP Y Maximum 1-hour exposure concentration (ppm or μ g/m 3 , 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 fo r all pollutants in a multiple-polluta nt 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

P SumList = PAI, AVGEXP

Note that each record in the f il e could be much longer, as many more variables could be printed.

APEX Diary Questionnaire File ebruary 19, 2007) Ru APEX Version 4.0 (dated F 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

Exh ibit 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 fo r each pollutant in the simulation. The variable

e

ault is NO , as these files are very large, and riting them greatly affects th e 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 a ll 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 ble keywords. The MResList will control the writing of the Microenvironment Re o f ile 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 rofile - N The number of the simulated p

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 S ection 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.

Penetratio n PEN Y Penetration factor: microenvironment parameter, ranging from 0 to 1.

CSum Sum of concentration s ources CSUM Y (CSource) terms

Ambien t Concentration ion associated

the Air Quality Data file). AMB

Y Pollutant concentrat with the location sector and hour (as determined from

92Variable Description Control File Keyword Optional Micro Y Concentration Pollutant concentration in the microenvironment CONC

ESum ion Sources (ESource) ESUM Sum of Emiss terms ( μ g/hr). Y

Source Strengt h bined source strength for

on sources SOURCE

Y Com emission and concentrati in μ g/m 3 /hr.

Micro Volume Volume of the microenvironment in

m 3

. 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 fun ctions file) MAXTEMPCAT Y

AvgTempC at me

ions file) AT Y Daily average temperature category 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 w hich 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

DailyCond itional2 iable 2 Value of daily conditional var for the hour DCOND2 Y

DailyCondi tional3 ur Value of daily conditional variable 3 for the ho DCOND3 Y

TempCat Hourly temperature category conditional variable TEMPCAT Y

HumidCa t ditional Hourly humidity category con variable HUMIDCAT Y

PrecipC at T Hourly precipitation category conditional variable PRECIPCA Y

93Variable Description Control File Keyword Optional

WindCat gory CAT Y Hourly wind speed cate 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 param eters, al variables.

EMPCAT, WINDOWRES

file for an example pollutant (Pol1) is given r the le size). m icroenvironment concentration equations, and condition

A number of the parameters in the file ar e undefined for a FACTORS microenvironment (See

ection 4.20.1 ). These parameters will be padded with 0 in that case. S

An example use of MResList in the Control file is:

ResList = AER, PRX, PEN, AMB, CONC, MAXTEMPCAT, AVGT M

T he 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

94APEX 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 Si mulation = ! 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 co lumns of the subsequent records in the file. These labels and

escriptions of the values in th e 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 roenvironmen t during the peri ula person. The icroen nmental Summary file is pollutant-speci fic, and thus o ulation. Af ter the six header records and one blank recor

d

a

1 Person Num Profile number - Sequentia l index number for the simulated individual

2 Micro Num Microenvironment numbe r - Sequential index number for each microenvironment (as designated in the Microenvironment Mapping file)

953 Name Char Microenvironment name (as designated in the Microenvironment Mapping file) (maximum of 40 characters) 4 Minutes Num Total time spent in th e microenvironment by this individual (minutes) 5 MeanConc Num Average concentration during the time spent in the microenvironment by this individual (ppm or μ g/m3, as specified in the Control file) 6 MaxConc Num Maximum concentration during the time spent in the microenvironment by this individual (ppm or μ g/m3, as specified in the Control file)

A PEX Microenvironmental Summar y 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 vers ion 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.
Ex hibit 5-6. Portion of a Microenvironmental Summary File

even different types

each e xposure level by microenvironment

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

### 5. 8 Output Tables File

Th is file provides up to 242 summary tables, depending on the table specifications in the Si mulation Control file. The first 130 are exposure summ ary 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

A PEX writes out up to 130 differe nt exposure summary tables. Th ere are el of exposure tables:

1. Minutes in each exposure in terval by microenvironment

. Minutes at or above 2 3

964. Person-days at or above each dail y maximum 8-hour exposure le vel

sures at or above each daily maximum

n

. All Persons. The table statistics are ba sed on the entire population. ics are based on the popul ation 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 popul ation of ill people. The population is

itions . The table statistics are base d on exposures experienced by the opulation subgroup under any ve ntilatory conditions.

g gene rated. 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 dail y 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 on ce, for the entire population. Table types 3 to 9 are generated for six population subgroups, unde r 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 th e 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 th e 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 popul ation of ill people. The population is determined by the proba bilities 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 proba bilities given in the Prevalence file and the Control file settings ChildMin and ChildMax . This population is only cons idered 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 base d on exposures experienced by the population subgroup only during periods in which their average equivale nt 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

97greater 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 si mulated 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 statis tics are based on exposures e xperienced by the population subgroup only during periods in which their averag e 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 ge nerated. The “heavy” EVR ranges are defined by the Control file ttings HeavyEVR1 (for 1-h s e our exposures) and HeavyEVR8 (for 8-hour exposures). An individual’s EVR is in th e heavy range if it is greater than or equal to the HeavyEVR # setting fo

e exposure period. t h

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

exam

cated at the top of the column and the top of the n olumn to the right;

• within the exposure co ncentration 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 Tabl e Type #1 in the Output Tables File

Exposure Table Type #2: Minutes in each Exposure Interval by Microenvironment

98This 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 equa ls or exceeds the value indicate d 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

t 5-8. Example of Exposure Tabl e Type #3 in the Output Tables File Exhibi

Table 5-8. Int sonerpretation of the Variables in Exposure Table Type #3 and Other "Per Days" Based Tables. Interpretation Table entry Counts (Pop) of person-days at or above the level specified at the top of each column Total number 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 th e 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 (Po p)

: 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 s ubgroup] during which an exposure at or above the level sp exertion].

99Std. 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 [whi le 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 pe rsons [in the subgroup] during which an exposure at or above the level specified at th e 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 th e 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 th e 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 s ubgroup] 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 th e top of each column is experienced [while at this exertion], as percentage of possible days. The lowest total number of days across pe rsons [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 th e top of each column is experienced [while at this exertion], as percentage of possible days. Counts (Sim) Total number of simulated pe rson-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 ex posure

e

his table provides a statistical summary of the cumulative person-days, for both simulated persons and the population in the study area, w ith a daily maximum timestep average exposure concentration that equals or exceeds specified le vels. 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 wr itten if the timestep is equal to one hour. c oncentration that equals or exceeds specified le vels. 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

100Exposure Table Type #6: Number of Simulate d 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 leve ls. 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 Tabl e Type #6 in the Output Tables File.

E xposure Table Type #7: Number of Simulate d 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. Th e table is the same as Table #6 ( Exhibit 5-9 ) except that the exposure metric is the daily ma x 8-hour average exposure concentration.

101Exposure Table Type #8:Number of simulated pers ons with multiple exposures at or ab ove

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 simu lated persons who have at least 1 (or 2, 30, or 300, for example) timesteps in the entire simulation during whic h they have experienced an exceedance of each timestep threshold exposure le vel. 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 exposur e concentration that 3

ided in xhibit 5-10. each daily maximum timestep exposure level. This table provides a count of the number of simu lated 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 t able 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 th e daily average exposure concentration.

Exposure Table Type #11: Persons at or above each Overall Average Exposure Level This table provides a statistical summary of cu mulative numbers of both simulated persons and people in the study area whose overall average exposure concen trations equa l or exceed specified levels. The overall average exposure concentration is the av erage of hourly exposure concentrations over the whole peri od 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 Tabl e Type #11 in the Output Tables File.

5.8.2 Dose Summary Tables

APEX writes out up to 112 differe nt exposure summary tables. Th ere 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 popula tion. Table types 1-6 are each gener ated for

ix population subgroups, under thre e exertion levels. See the previous section on Exposure s

102tables for the definition of popul ation subgroups and exertion levels. For the pollutant CO, dose

e

evel days for both simulated ersons and the population in the study area, fo r which the daily maximum end-of-hour dose is

dose

finitions of the variab les 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 writ ten if the timestep is equal to one hour. The

e entire simulation during whic h they have experienced an xceedance of each timestep threshold dose leve l. 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 th e 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 pollut ants dose is simply exposure*ventilation.

Dose Table Type #1— Person-Days at or above each Da ily 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, fo r 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 ab ove 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, fo r 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 variab les in this table can be found

Dose Table Type #4: Person-Days at or ab ove 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, w ith 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 Pers ons with Multiple Timestep Doses at or above some Threshold Timestep Dose Level. This table provides a count of the number of simu lated 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

103This table provides a statistical summary of cu mulative numbers of both simulated persons an the people in the study area whose overall average dos es 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 wh ich 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 specifie d 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, fo r which the dose (for example, blood %COHb The definitions of the vari ables 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 district s, and zones in the study area, and identifies the

:

grees)

km)

grees)

Temdistance —Distance from zone to sector (km)

gitude —Zone longitude (d ecimal degrees) sim ulation.

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

e xceeds specified levels. Th 5 -8 ), except that the time units are hours rather th an d
t able can be found in Table 5-8

.

D ose Table #9— Minutes in T his table provides a statistical summary of cumulative personos p ersons and the population in the study area, fo r which the d l evel) is within a specified range. The bounds of the dose range next column to the right. T t op of each column and the top of the
t his table are similar to those found in Table 5-8
t han days.

D ose Table #10— Minutes at or above each Dose Lev e l This table provides a statistical summary of cu mulative pers
p ersons and the population in the leve l) is equal to or exceeds specified levels. similar to those found



### 5.9 Sites File

T

m apping 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 longit ude (decimal de

• Airname —Air district name

• Tem# —Meteorology zone ID

•

• Temlatitude —Zone latitude (decimal degrees)

• T emlon

• Temname —Zone name

104

### 5 .10 Events File

T he Events file contains a summary of the activit y diar y with accompanying exposure and dose, t the diary event level. The variab les 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 duri ng the event (ppm or μ g/m 3 )

Optionally, the user can ask AP EX 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 EVENTSLI ST, 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

105Exhibit 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 pe r person-year. For this reason, the user is given the option of writing the events for only a fraction of the si mulated persons. This is controlled by the Control file settings EventSample and CustomSample . See Section 4.2.3 for more information on these keywords.

106107 REFERENCES

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

R E

R ) equations for use in inhalation-oriented exposure models. EPA/600/X-05/008.

McCurdy, T., G. Glen, L. Smith, and Y. La kkadi (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:

H T U http://www.epa.gov/ttn/fera/t rim_fate.html#1999historical

U TUnited StatesEnvironmental ProtectionAgencyOffice of Air Quality Planning and StandardsHealth and Environmental Impacts DivisionResearch Triangle Park, NCPublication No. EPA-452/B-08-001aOctober 2008