Total Risk Integrated Methodology
TRIM.ExpO|nha|ation User's Document
Volume I: Air Pollutants Exposure Model
(APEX, version 3) User's Guide
Environmental Fate,
Transport, & Ecological
Exposure Module
-frRIM.FaTE) „
Risk Characterizalion
Module
(TRIM. Risk)
Exposure-Event Module
(TRIM.Expo) j
' Social, \
Economic,]
& Political J
\ Factors/,
/ Risk \
Management
v Decision/
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, NC 27711
Draft
April 24, 2003
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Total Risk Integrated Methodology
TRIM.ExpO|nhaiation User's Document
Volume I: Air Pollutants Exposure Model
(APEX, version 3) User's Guide
Prepared for:
Office of Air Quality Planning and Standards
US Environmental Protection Agency
Research Triangle Park, NC
Prepared by:
ICF Consulting
Fairfax, VA
and
ManTech Environmental Technology, Inc.
Research Triangle Park, NC
Draft
April 24, 2003
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Disclaimer
This document has been reviewed and approved for publication by the U.S. Environmental
Protection Agency. It does not constitute Agency policy. Mention of trade names or commercial
products is not intended to constitute endorsement or recommendation for use.
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Preface
This document, the APEX User's Guide, is part of a series of documentation for the overall Total
Risk Integrated Methodology (TRIM) modeling system, in particular the inhalation component of
the exposure module (TRIM.ExpO|nhaiation). The detailed documentation of TRIM'S logic,
assumptions, algorithms, equations, and input parameters is provided in comprehensive
technical support documents (TSDs) and/or user's guidance for each of the TRIM modules.
One of those documents is this user's guide, which is designed primarily to assist exposure
analysts with running the Air Pollutants Exposure model (APEX), a personal computer
(PC)-based program designed to estimate human exposure to criteria and air toxic pollutants at
the local, urban, and consolidated metropolitan level. The guide currently is divided into four
volumes. Volume I, User's Guide (this volume) is the first volume to be released. It describes
the scientific basis of the APEX model (version 3) and describes the steps involved in running
APEX for both basic and more advanced applications. Volume II, Programmer's Guide
describes the model and computer code in more detail and thus provides advanced users with a
greater understanding of the model. Volume III, Criteria Air Pollutants Case Study and Volume
IV, Hazardous Air Pollutants Case Study illustrate the use of APEX by applying it to carbon
monoxide (criteria air pollutant) and benzene and chromium (hazardous air pollutants),
respectively. Additional volumes or revisions to these volumes may be developed as the model
is upgraded, example applications are developed, or other needs arise.
Model enhancements, bug fixes, and other changes are occasionally made to APEX, and thus
users are encouraged to revisit the download website for notices of these changes, including
those listed in a readme.txt file. Also, although APEX has been tested during development, the
number of available computer configuration options preclude the possibility of testing all
possible scenario configurations. Thus, it is possible that bugs remain in the code for some
configurations. The current version of APEX is a draft release and users should be considered
beta-testers.
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Contents
Disclaimer N
Preface iii
1. INTRODUCTION 1
1.1 Organization of Volume I 2
1.2 Background and Overview 2
1.3 Strengths and Limitations of APEX 4
1.3.1 Strengths 4
1.3.2 Limitations 5
1.4 Applicability 6
1.5 Brief History of APEX 6
2. OVERVIEW OF MODEL DESIGN AND ALGORITHMS 9
2.1 Characterize the Study Area 10
2.1.1 Study Area 10
2.1.2 Sectors 13
2.1.3 Districts 14
2.1.4 Zones 14
2.2 Generate Simulated Individuals 15
2.2.1 Demographic variables 15
2.2.2 Residential Variables 17
2.2.3 Physiological Profile Variables 17
2.2.4 Daily Varying Variables 17
2.3 Construct a Sequence of Activity Events 17
2.4 Calculate Concentrations in Microenvironments 19
2.4.1 Define Microenvironments 19
2.4.2 Calculating Concentrations in Microenvironments 19
2.4.2.1 Microenvironment Parameters 19
2.4.2.2 Mass Balance Method 21
2.4.2.3 Factors Method 25
2.4.2.4 Stochastic Elements 25
2.5 Determine Exposure 26
2.6 Determine Dose 26
2.6.1 Ventilation Rate 27
2.6.2 Carboxyhemoglobin (COHb) Determination 29
3. INSTALLING APEX 31
3.1 Hardware and Software Requirements 31
3.2 Installing APEX to Run in MIMS 31
3.3 Installing APEX to Run in DOS Batch Mode 35
4. RUNNING APEX 3Z
4.1 Running APEX in MIMS 3Z
4.2 Running APEX in DOS Batch Mode 40
4.3 Setting Up an APEX Simulation 42
4.3.1 Overview 42
4.3.2 Detailed Steps 43
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4.4 Overview of Input and Output Files 44
4.4.1 Input Files 46
4.4.2 Output Files 46
4.5 Overview of Model Settings and Options 46
5. INPUT FILES 55
5.1 Input File Formats 55
5.2 Params File (Unit 10) 56
5.2.1 Input and Output File List Sections of Params File 58
5.2.2 Population Files Sections of Params File 61
5.2.3 Job Parameter Settings Section of Params File 63
5.2.4 Output Table Levels Sections of Params File 68
5.3 Sector Location File (Unit 11) 70
5.4 District Location File (Unit 12) 71
5.5 Temperature Zone Location File (Unit 13) 72
5.6 Employment by Age Group File (Unit 14) 72
5.7 Commuting Flow File (Unit 15) 73
5.8 Temperature Data File (Unit 16) 73
5.9 Air Quality Data File (Unit 17) 75
5.10 Activity-specific MET File (Unit 18) 76
5.11 Physiological Parameters File (Unit 19) 76
5.12 Profile Functions File (Unit 20) 78
5.13 Micro Mapping File (Unit 21) 81
5.14 Personal Info File (Unit 22) 82
5.15 Diary Events File (Unit 23) 84
5.16 Micro Descriptions File (Unit 24) 85
5.16.1 Micro Descriptions Section 85
5.16.2 Parameter Description Section 86
5.16.2.1 Keywords 87
5.16.2.2 Data 89
6. OUTPUT FILES 91
6.1 Log File (Unit 25) 91
6.2 Hourly Exposure File (Unit 26) 91
6.3 Hourly Dose File (Unit 27) 92
6.4 Profile Summary File (Unit 28) 92
6.5 Microenvironment Summary File (Unit 29) 93
6.6 Output Tables File (Unit 30) 93
6.7 Sites File (Unit 31) 98
REFERENCES 101
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Tables
Table 4-1. Overview of APEX Input Files 47
Table 4-2. Overview of APEX Output Files 48
Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and
Options 49
Table 5-1. Input Files for APEX Model 59
Table 5-2. Output Files for APEX Model 62
Table 5-3. Job Parameters in APEX Params File 63
Table 5-4. Output Parameter Levels in the Output Summary Table 69
Table 5-6. User-definable Functions in Profile Functions File 80
Table 5-8. Micro Parameters Required to Define a Microenvironment 87
Table 5-9. Keyword Definitions for the Parameter Descriptions Section of the Micro
Descriptions File 88
Table 5-10. Uses of Distribution Parameters for Each Standard Distribution Type 90
Table 6-1. Definitions of Variables in Summary Tables 96
Figure 2-1. Overview of APEX V\_
Figure 2-2. Example of Study Areas, Districts, Zones, and Sectors 13
Figure 2-3. Mass Balance Model 22
Figure 4-1. General Steps to Configure and Conduct an APEX Simulation 42
Figure 4-2. Steps for Setting up a "Standard" APEX Simulation 45
Figure 5-1. Example of Params File 57
Figure 5-2. Example Portion of Population Data File ("Wrapped" View) 63
Figure 5-3. Example Portion of Sector Location File 71
Figure 5-4. Example of District Location File 71
Figure 5-5. Example of Temperature Zone Location File 72
Figure 5-6. Example of Employment by Age Group File ("Wrapped" View) 73
Figure 5-7. Example Portion of Commuting Flow File 74
Figure 5-8. Example Portion of Temperature Data File 74
Figure 5-9. Example Portion of Air Quality Data File ("Wrapped" View) 75
Figure 5-10. Example Portion of Activity-Specific MET File 76
Figure 5-11. Portions of Four Data Tables in Physiological Parameters File 79
Figure 5-12. Example of WindowPos User-Defined Profile Function 80
Figure 5-13. Example Portion of Micro Mapping File 82
Figure 5-14. Example Portion of Personal Info File 83
Figure 5-15. Example Portion of Diary Events File 85
Figure 5-16. Example Portion of Micro Description File 86
Figure 6-1. Example Portion of Table #1 in Output Table File ("Truncated" View) 94
Figure 6-2. Example of Table #3 in Output Table File 95
Figure 6-3. Example of Table #6 in the Output Table File 97
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1. INTRODUCTION
The Air Pollutants Exposure model (APEX) is
part of EPA's overall Total Risk Integrated
Methodology (TRIM) model framework (EPA,
1999), in particular the inhalation exposure
component (TRIM.Expolnhalation). TRIM is a
time series modeling system with multimedia
capabilities for assessing human health and
ecological risks from hazardous and criteria
air pollutants; it is being 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 Exposure-Event module
(TRIM.Expo); and
• Risk Characterization module (TRIM.Risk).
APEX, a personal computer (PC)-based
program, is one of the tools being developed
to estimate human exposure via inhalation for
criteria and air toxic pollutants. APEX is
designed to estimate human exposure to
criteria and air toxic pollutants at the local, urban, and consolidated metropolitan level.
The TRIM.Expolnhalation user's document currently is divided into four volumes. Volume I, User's
Guide (this volume) is the first to be released. It describes the scientific basis of the APEX
model and describes the steps involved in running APEX for both basic and more advanced
applications. Volume II, Programmer's Guide describes the model and computer code in more
detail and thus provides users with a greater understanding of the model. Volume III, Criteria
Air Pollutants Case Study and Volume IV, Hazardous Air Pollutants Case Study illustrate the
use of APEX by applying it to carbon monoxide (criteria air pollutant) and benzene and
chromium (hazardous air pollutants), respectively. Additional volumes or revisions to these
volumes may be developed as the model is upgraded, example applications are developed, or
other needs arise. Users are encouraged to revisit the download website
(http://www.epa.qov/ttn/fera) for notices of these changes, including those listed in a readme.txt.
Note that APEX has been extensively reviewed. Any changes to the computer code may lead
to results that cannot be supported by this documentation.
Nomenclature used throughout this User's Guide
for key model components (defined later in this
guide):
~ Tips to users and other useful information
appear throughout in a shaded text box (such
as this one).
~ Key terms are underlined for emphasis.
~ Input file names and file types are in Italics.
~ Model Variables or parameters are in regular
bold italics, especially when first used in a
section. KEYWORDS, which are how the
variable and parameter names appear in the
input files, are in uppercase bold italics.
Input and output data
are in a
single lined box, indicating that the text inside
the box is shown exactly as it exists in its
electronic form.
Computer program and module names are
in all bold, non-italic.
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1.1 Organization of Volume I
This User's Guide is designed for all levels of expertise, from novice to advanced, and focuses
on how to run the APEX computer model, develop the appropriate input files, and utilize the
range of options. Volume I is organized into six chapters, plus a reference section at the end:
• Chapter 1, Introduction—Describes the nomenclature used in this guide (see above box),
provides a brief overview of the conceptual model, discusses the model's strengths,
limitations, and applicability, and provides a brief history of the model.
• Chapter 2, Overview of Model Design And Algorithms—Describes the key modeling steps,
databases, logic processes, and exposure and other equations used in APEX.
• Chapter 3, Installing APEX— Describes the hardware requirements and provides instructions
for installing APEX on a PC.
• Chapter 4, Running APEX— Provides step-by-step instructions and an overview of the basic
information needed to run the model and use the available model options.
• Chapter 5, Input Files—Provides a description of the format, data, and options for each of the
APEX input files.
• Chapter 6, Output Files—Provides a description of the format and data associated with each
of the APEX output files.
1.2 Background and Overview
This section describes some of the key terms used in this guide (see box below) and provides a
brief conceptual description of the model—additional detail is provided in Chapter 2.
APEX estimates human exposure to criteria and toxic air pollutants at the local, urban, and
consolidated metropolitan area level using a stochastic, "microenvironmental" approach. That
is, the model randomly selects data on a sample of hypothetical individuals in an actual
population database and simulates each individual's movements through time and space (e.g.,
at home, in vehicles) to estimate their exposure to and, optionally, dose of the subject pollutant.
APEX can assume people live and work in the same general area (i.e., that the ambient air
quality is the same at home and at work) or optionally can model commuting and thus exposure
at the work location for individuals who work. One caveat is that this option only applies to
people who both live and work in the study area—people who work inside the study area but
live outside of it are not modeled under this option, nor are people who live in the study area but
work outside of it.
APEX can be thought of as a simulation of a field study that would involve selecting an actual
sample of specific individuals who live in (or work and live in) a geographic area and then
continuously monitoring their activities and subsequent inhalation exposure to a specific air
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Key terms used throughout this User's Guide:
~ Diary—a set of events or activities (e.g., cooking, sleeping) for an individual in a given time frame
(e.g., a day).
~ District—the geographical area represented by a given set of ambient air quality data (either based
on a fixed-site monitor or output from an air quality model).
~ Event—an activity (e.g., cooking) with a known starting time, duration, microenvironment, and
location (usually home or work).
~ Microenvironment—a three-dimensional space in which human contact with an environmental
pollutant takes place.
~ Profile—a set of characteristics that describe the person being simulated (e.g., age, gender, height,
weight, employment status, whether an owner of a gas stove or air conditioner).
~ Sector—the basic geographical unit for estimating exposure to the study population (e.g., census
tract).
~ Study Area—the geographical area to be modeled (e.g., metropolitan region).
~ Study Area Population—total population of persons who live in the study area: when the commuting
option is used, the study area population does not include those who work outside the study area.
~ Zone—similar to district, but for ambient temperature data.
pollutant during a specific period of time. The main differences between the model and an
actual field study are that in the model:
• The sample of individuals is a "virtual" sample, created by the model according to various
demographic variables and census data of relative frequencies, in order to obtain a
representative sample (to the extent possible) of the actual people in the study area;
• The activity patterns of the sampled individuals (e.g., the specification of indoor and other
microenvironments, the duration of time spent in each) are assumed by the model to be the
same as for individuals with similar demographic characteristics, according to activity data
such as diaries compiled in EPA's Consolidated Human Activities Database (CHAD) (EPA,
2002c; McCurdy et al., 2000);
• The pollutant exposure concentrations and doses are estimated by the model using a set of
user-input ambient outdoor concentrations and information on the behavior of the pollutant in
various microenvironments; and
• Various reductions in ambient air quality levels can be simulated by either adjusting air quality
concentrations to just attain alternative ambient standards under consideration or by reducing
source emissions and obtaining resulting air quality modeling outputs that reflect these
potential emission reductions.
Thus, the model attempts to account for the most significant factors contributing to inhalation
exposure—the temporal and spatial distribution of people and pollutant concentrations
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throughout the study area and among the microenvironments—while also allowing the flexibility
to adjust some of these factors for regulatory assessment and other reasons.
The basic steps simulated by APEX for estimating exposure of each individual in the sample
are: (1) adjust the study area based on sectors (e.g., census tracts) and the availability of air
quality and weather data; (2) generate simulated individuals in the study area using census-
derived frequency (probability) distributions of demographic and other variables (age, gender,
home location, work location) to randomly select and develop a personal profile for each
individual; (3) construct a sequence of activity events for each profile, taking into consideration
the demographic variables (e.g., child, adult) and day type (e.g., weekday or weekend,
temperature) being modeled; (4) calculate hourly concentrations in the microenvironments by
determining the pollutant concentration for each hour of the profile diary using ambient outdoor
concentration data supplied by the user and information on outdoor-microenvironment
relationships or dynamics supplied in data input files and incorporated into the model;
(5) estimate the pollutant exposure for each activity in the diary and then average the
concentrations by hour to obtain an hourly exposure time series; and (6) estimate the dose,
which is an optional step and one that can be conducted only for carbon monoxide currently.
After the specified number of individuals are sampled and exposures and/or doses estimated,
APEX produces a set of summary tables that indicate the distributions of exposure and dose (if
the dose option was selected) across all the profiles.
1.3 Strengths and Limitations of APEX
All models have strengths and limitations. Therefore, for each application, it is important to
carefully select the model that has the desired attributes. With this in mind, it is equally
important to understand the strengths and weaknesses of the chosen model. The following
sections provide a summary of the strengths and potential limitations of APEX.
1.3.1 Strengths
APEX simulates the movement of individuals through time and space to estimate their exposure
to a given pollutant in indoor, outdoor, and in-vehicle microenvironments. Compared to
conducting a field study that would involve identifying, interviewing, and monitoring specific
individuals in a study area, APEX provides a vastly less expensive, more timely, and more
flexible approach. Compared to other air exposure models, APEX provides a good balance in
terms of precision and resource expenditure between the more narrowly focused site-specific
model and the broadly applicable national screening-level models.
The model also allows different air quality data, exposure scenarios, and other inputs and thus
is very useful for decision making.
Another important feature of APEX is its versatility. The model is designed with a great deal of
flexibility so that detailed input data can be applied to specific applications. For example, the
supplied input data sets for this model contain information for numerous microenvironments.
Another example is that the air quality data needed by the model can be in the form of
monitoring or modeling data. The data can be for specific locations, or political units such as
counties, or census units such as tracts, or even grid points used as air dispersion models
receptors. Furthermore, both criteria and hazardous air pollutants can be modeled.
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A key strength of APEX is its ability to estimate hourly exposures and doses for all simulated
individuals in the sample population from the study area. This ability allows for powerful
statistical analysis of a number of exposure characteristics (e.g., acute versus chronic exposure,
correlations with activities and demographics), many of which are provided automatically by
APEX in output tables.
APEX also estimates the exposures of workers in the geographic area where they work, in
addition to the geographic area where they live. The pollutant concentrations in these
respective locations may be very different from each other.
APEX incorporates stochastic processes representing the natural variability of personal profile
characteristics, activity patterns, and microenvironment parameters. In this way, APEX is able
to represent much of the variability in the exposure estimates resulting from the variability of the
factors effecting human exposure.
Exposure analysis with APEX has also been facilitated by the development of supplied input
files derived from the databases discussed above: national U.S. Census population and
commuting information; CHAD activity data; and microenvironment variables.
1.3.2 Limitations
A limitation of APEX is that uncertainty in the predicted distributions is not currently addressed.
Some of the uncertainties are as follows.
• The population activity pattern data supplied with APEX (CHAD activity data) are compiled
from a number of studies in different areas, and for different seasons and years. Therefore,
the combined data set may not constitute a representative sample. Nevertheless, the largest
portion of CHAD (about 40 percent) is from a study of national scope (which could be
extracted by the user if desired to create a representative sample). Also, research has shown
that activity patterns are generally similar once you take into account age, gender, day of
week, and season/temperature.
• Commuting pattern data were derived from the 1990 U.S. Census, and these data have been
updated to 2000 proportionally based on 2000 Census data. Therefore, the commuting
pattern data may not accurately reflect current commuting patterns. Moreover, the
commuting data address only home-to-work travel. The population not employed outside the
home is assumed to always remain in the residential census tract. Furthermore, although
several of the APEX microenvironments account for time spent in travel, the travel is
assumed to always occur in basically a composite of the home and work tract. No other
provision is made for the possibility of passing through other tracts during travel.
• APEX creates seasonal or year long sequences for a simulated individual by sampling human
activity data from more than one subject. Thus, uncertainty exists about season-long
exposure event sequences. This approach also tends to underestimate the variability from
person to person, because each simulated person essentially becomes a composite or an
"average" of several actual people in the underlying activity data (which tends to dampen the
variability). At the same time, this approach may overestimate the day to day variability for
any individual because each simulated person is represented by a sequence of potentially
dissimilar activities from different people rather than more similar activities from one person.
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• The model currently does not capture certain correlations among human activities that can
impact microenvironmental concentrations (e.g., cigarette smoking leading to an individual
opening a window, which in turn affects the amount of outdoor air penetrating the residence).
Also, certain aspects of the personal profiles are held constant, though in reality they change
every year (e.g., age). This is generally only an issue for simulations with long timeframes.
Other data and model limitations exist besides those identified above, including physiological,
meteorological, and those associated with estimating concentrations in microenvironments.
EPA will continue to refine the model and data to reduce these limitations to the extent possible.
1.4 Applicability
APEX is a moderate to advanced tier air exposure model for local, urban, and consolidated
metropolitan areas. As part of TRIM, for risk assessments it generally would be used after a
simpler, more conservative model or analysis has been applied that prioritizes exposure factors
(area, scenarios, pollutants) for further investigation. APEX will provide more detailed estimates
of exposure for scenarios identified in screening activities as high priority and/or for regulatory
analyses supporting national decisions (e.g., NAAQS reviews).
APEX is appropriate for assessing both average long-term and hourly short- and long-term
inhalation exposures of the general population or a specific sub-population. The model is
designed to look at the range of inhalation exposures of different groups of people across a
population.
Notwithstanding the ability of APEX to assess hourly exposure, however, the model should not
be used to quantify episodic "high-end" inhalation exposure that results from highly localized
pollutant concentrations and/or activities that, by their nature, could result in potentially high
exposures (e.g., emergency releases, occupational exposures). Furthermore, APEX cannot
address cumulative exposure from multiple pollutants nor pollutant mixtures.
1.5 Brief History of APEX
The APEX series of models derive from the probabilistic National Ambient Air Quality Standards
(NAAQS) Exposure Model for Carbon Monoxide (pNEM/CO). The evolution of these models
has been towards greater flexibility and accuracy. The NEM series was developed to estimate
exposure to the criteria pollutants (e.g., CO, ozone). In 1979, EPA began to develop NEM by
assembling a database of human activity patterns that could be used to estimate exposures to
outdoor pollutants (Roddin et al., 1979). The data were then combined with measured outdoor
concentrations in NEM to estimate exposures to CO (Biller et al., 1981; Johnson and Paul,
1983). In 1988, OAQPS began to incorporate probabilistic elements into the NEM methodology
and using activity pattern data based on various human activity diary studies in an early version
of probabilistic NEM for ozone (i.e., pNEM/03). In 1991, a probabilistic version of NEM was
developed for CO (pNEM/CO) that included a one compartment mass-balance model to
estimate CO concentrations in indoor microenvironments and the application of this model to
Denver, Colorado has been documented (Johnson et al., 1992). Several newer versions of
pNEM/03 were developed in the early to mid-1990's including applications to nine urban areas
for the general population, outdoor children, and outdoor workers (Johnson et al., 1996a,b,c).
During 1999-2001, updated versions of pNEM/CO (versions 2.0 and 2.1) were developed that
rely on activity diary data from CHAD and enhanced algorithms for simulating gas stove usage,
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estimating alveolar ventilation rate (a measure of human respiration), and modeling
home-to-work commuting patterns.
The first version of APEX was essentially identical to pNEM/CO (version 2.0) except that it ran
on a PC instead of a mainframe. The APEX2 model was substantially different, particularly in
the use of a personal profile approach rather than a cohort simulation approach. APEX3
introduced a number of new features including automatic site selection from large (e.g.,
national) databases, a series of new output tables providing summary statistics, and a
thoroughly reorganized method of describing microenvironments and their parameters. Most of
the spatial and temporal constraints were removed or relaxed in APEX3.
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2. OVERVIEW OF MODEL DESIGN
AND ALGORITHMS
This chapter describes the key modeling steps, logic processes, and equations, and data bases
used in APEX3. It is written primarily to give exposure assessors an overview of the model from
a technical perspective and an understanding of the scientific basis of the core elements; it is
not a comprehensive description of all algorithms. See Volume II for additional detail on the
algorithms and how they are incorporated into the model, and see Johnson (2002) for additional
detail regarding the derivation and scientific basis of these and other algorithms used in
exposure modeling.
APEX is designed to simulate population exposure to criteria and air toxic pollutants at local,
urban, and regional scales. The user specifies the geographic area to be modeled and the
number of individuals to be simulated to represent this population. APEX then generates a
personal profile for each simulated person that specifies various parameter values required by
the model. The model next uses diary-derived time/activity data matched to each personal
profile to generate an exposure event sequence (also referred to as "activity pattern" or
"composite diary") for the modeled individual that spans a specified time period, such as one
year. Each event in the sequence specifies a start time, an exposure duration, a geographic
location, a microenvironment, and an activity. Probabilistic algorithms are used to estimate the
pollutant concentration and ventilation (respiration) rate associated with each exposure event.
The estimated pollutant concentrations account for the effects of ambient (outdoor) pollutant
concentration, penetration factor, air exchange rate, decay/deposition rate, and proximity to
emission sources, depending on the microenvironment, available data, and the estimation
method selected by the user. The ventilation rate is derived from an energy expenditure rate
estimated for the specified activity. Because the modeled individuals represent a random
sample of the population of interest, the distribution of modeled individual exposures can be
extrapolated to the larger population. The model simulation includes up to six steps:
1. Characterize the study area - APEX selects sectors (e.g., census tracts) within a study
area—and thus identifies the potentially exposed population—based on the user-defined
center and radius of the study area and availability of air quality and weather input data for
the area.
2. Generate simulated individuals - APEX stochastically generates a sample of simulated
individuals based on the census data for the study area and human profile distribution data
(such as age-specific employment probabilities). The user can specify the size of the
sample. The larger the sample, the more representative it is of the population in the study
area (but also the longer the computing time).
3. Construct a sequence of activity events - APEX constructs an exposure event sequence
(activity pattern) spanning the period of simulation for each of the simulated persons (based
on the supplied Consolidated Human Activity Database (CHAD) data, although other data
could be used).
4. Calculate hourly concentrations in microenvironments - APEX enables the user to define
microenvironments that people in a study area would visit (e.g., by grouping location codes
included in the supplied CHAD database). The model then calculates hourly
concentrations of a pollutant in each of the microenvironments for the period of simulation,
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based on the user-provided hourly ambient air quality data. All the hourly concentrations in
the microenvironments are re-calculated for each of simulated individuals.
5. Determine exposures - APEX assigns a concentration to each exposure event based on
the microenvironment occupied during the event and the person's activity. These values
are averaged by clock hour to produce a sequence of hourly-average exposures spanning
the specified exposure period (typically one year). These hourly values may be further
aggregated to produce daily, monthly, and annual average exposure values.
6. Determine doses - APEX optionally calculates hourly, daily, monthly, and annual average
dose values for each of the simulated individuals. This option currently is available only for
CO.
The model simulation continues until exposures are determined for the user-specified number of
simulated individuals. Figure 2-1 presents these steps within a schematic of the APEX model
design. The following sections provide addition detail on the key algorithms used in each of the
above simulation steps.
2.1 Characterize the Study Area
A study area in an APEX analysis consists of a set of basic geographic units called sectors
(typically defined as census tracts). The user generally provides the geographic center
(latitude/longitude) and radius of the study area. APEX calculates the distances to the center of
the study area of all the sectors included in the sector location database, and then selects the
sectors within the radius of the study area. APEX then maps the user-provided hourly air district
and daily temperature zone data to the selected sectors. The sectors identified as having
acceptable air and temperature data within the radius of the study area are selected to comprise
a final study area for the APEX simulation analysis.
The following sections describe in more detail how a study area is defined in an APEX
simulation analysis.
2.1.1 Study Area
The APEX study area has traditionally been on the scale of a city or slightly larger metropolitan
area, although it is now possible to model larger areas such as consolidated metropolitan
statistical areas (CMSAs). Even larger study areas may be possible, depending primarily on
computing capabilities, available data, and the desired precision of the run.
The user defines an initial study area by specifying the latitude and longitude of a central point,
together with a radius. The user also has the option of providing a list of counties to be
modeled. If present, this list further restricts the area to the countries to be modeled which are
within the specified study area radius. The final study area is a function of the availability of the
user-supplied demographic data, pollutant concentration data, and the location temperature
data within the initial or intermediate study area, as determined respectively by population
sectors, air data districts, and temperature zones. Figure 2-2 and the subsections below
provide additional details about these geographical units.
DRAFT—APRIL 24, 2003
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Figure 2-1 a. Overview of APEX
area
Step 1
Characterize study
Sector/Location data
(latitude/longitude)
Site-specific
air quality and
temperature data
r
Defined Study Area (sectors
within a city radius
and with air and
temperature data)
Step 2
Generate N number
of simulated
individuals
Population data
(age/gender/race)
Population within
a study area
Age-specific physiological
distribution data (body
weight, height, etc)
Distribution functions for
profile variables
(e.g, probability of air
conditioner)
Commuting flow data I
(origin/destination
sectors)
Stochastic
profile generator
Age group specific
employment
probabilities
Distribution functions
for daily varying profile
variables (e.g., window
status, car speed)
A simulated individual with the
following profile:
• Home sector
• Work sector
• Age
• Gender
• Race
• Employment status
• Gas stove
• Pilot gas light
• Air conditioner
• Car air conditioner
• Height
• Weight
• Amount of hemoglobin
• Lung diffusivity
• Endogenous CO production rate
• Plus 12 more variables
Next Page
C - National
database
¦ Simulation
step
- Area-specific
input data
- Data processor
- Intermediate step
or data
- Output data
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11
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Figure 2-1 b. Overview of APEX
Step 3
Construct sequence of
activity events for each
simulated individual
Diary events/activities
and personal information
(e.g., from CHAD)
The selected diary records for
each day in the simulation
period
Activity diary pools by day
type/temperature category
From
previous page
Stochastic diary
selector using
age, gender, and
employment
Consolidate
location codes into
microenvironments
A sequence of events
(i.e., microenvironments
visited and minutes spent)
in the simulation period
Each day m the simulation
period, is assigned with
activity pool # based on
daily max/mean temperature
Maximum/mean daily
temperature data
Step 4
Calculate concentrations
in microenvironments
for each simulated
individual
1
r
Microenvironments defined by
grouping of CHAD location codes
r
Select calculation methods for each
microenvironment:
~ Factors
~ Mass balance
r
Hourly ambient air quality data for
the home and work sectors
r
Step 6
Determine dose
for each simulated
individual
(optional; currently
only CO)
Hourly concentrations in all
microenvironments during
simulation period
Other physiological
parameters
Physiological parameters
from profile
Step 5
Determine exposure
for each simulated
individual
Identify
concentrations m
microenvironments
visited
Calculate
ventillation
rates
Hourly concentrations and
minutes spent in each
microenvironment visited by
the simulated individual
Calculate
doses
Average exposure
concentrations
for simulated person
Hourly
Daily
Monthly
Annual
Average dose tor
simulated person
Hourly
Daily
Monthly
Annual
DRAFT—APRIL 24, 2003
12
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Figure 2-2. Example of Study Areas, Districts, Zones, and Sectors
City (Study Area) Radius
\
N
\
Sector
(census
tract)
Final Study Area
(dark line; the
Sectors comprising
the five Districts)
Initial Study Area ^
(within City Radius Study Area Center
distance from Study y
Area Center)
Intermediate Study
Area (e.g., Charlotte,
NC CMSA)
/
Zone Center
t
a
Zone Radius
I
Zone (Zone
Radius distance,
from Zone
Center)
\ v
District Air Monitor
*
\ *
District Air Radius
District (Air Radius
distance from Air Monitor)
\
\
2.1.2 Sectors
The fundamental spatial unit in APEX is called a sector. The demographic data used by the
model to create personal profiles is provided at the sector level. For each sector the model
requires demographic information representing the distribution of age, gender, race, and work
status within the study population. Each sector must have a location specified by latitude and
longitude for some representative point (e.g., geographic center). The current release of APEX
includes input files that already contain this demographic and location data for all census tracts
in the 50 United States based on the 2000 Census. This database enables the user to model
any study area in the country without having to make any changes to these input files. Finer
scales, such as census block groups, could be used if the user provided suitable population
data files. If fewer (thus larger) sectors were desired, the existing population data files could be
aggregated to larger regions such as counties.
DRAFT—APRIL 24, 2003
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For each model run, APEX selects the sectors that meet the following conditions. First, the
sector location must be within the specified distance (city radius) of the designated study area
center (see initial study area in Figure 2-2). Second, if the user provided a specific list of
counties, then the sector must belong to one of these counties (see intermediate study area in
Figure 2-2). If no county list is provided, the initial study area is roughly circular, consisting of all
sectors with indicated locations within the specified radius. The final study area consists of the
subset of sectors in the initial study area that have suitable air quality and temperature zone
data, as described in the next two subsections.
2.1.3 Districts
The spatial units for ambient air quality data are called districts. The districts are used to assign
pollutant concentrations to the sectors and microenvironments being modeled. The ambient
outdoor air quality data must be provided by the user as an hourly time series for one location
within each district. The locations could be monitoring sites, the geographic centers of political
units such as counties, the centers of census units such as tracts, or even grid points used as
receptors by an air quality model. As with sectors, each district has a representative location
consisting of a latitude and a longitude. The user designates the effective radius of the districts
(see air radius in Figure 2-2). In APEX, all districts have the same effective radius. Districts can
reside outside of the study area.
APEX calculates the distance from each sector to each district center, and assigns the sector to
the nearest district, provided the sector's representative location point (e.g., geographic center)
is in the district. Each sector is assigned to only one district. If the sector does not fall within
any district, the sector is deleted from the study area and is not modeled.
2.1.4 Zones
The final spatial unit in APEX is the temperature zone. At a minimum, the daily maximum
1-hour temperature is needed. Optionally, the average or other temperature for the day also
can be provided. Either or both temperature variables can be used for modeling functions such
as assigning activity diaries to personal profiles and assigning conditional probability
distributions to microenvironmental parameters. As with air quality districts, each zone has a
location (latitude and longitude), an effective radius, and start and stop dates.
As with districts, APEX calculates the distance from each sector to each zone center and
assigns each sector to the nearest zone. If the sector is not in any zone, the sector is deleted
from the study area and is not modeled.
Thus, for the population in a given sector to be modeled, the central location of the sector must
be within a circular district, within a circular temperature zone, within the circular initial study
area, and in a county an the county list (if specified).
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2.2 Generate Simulated Individuals
APEX stochastically generates a user-specified number of simulated persons to represent the
population in the study area. Each simulated person is represented by a "personal profile."
APEX generates the simulated person or profile by probabilistically selecting values for a set of
profile variables (Table 2-1). The profile variables include:
• Demographic variables, which are generated based on the census data;
• Residential variables, which are generated based on sets of distribution data;
• Physiological variables, which are generated based on age group-specific distribution data;
and
• Daily varying variables, which are generated based on distribution data that change daily
during the simulation period.
APEX first selects and calculates demographic, residential, and physiological variables (except
for daily values) for all the specified number of simulated individuals, and then determines
exposures and optionally doses for each simulated person. The following subsections describe
these variables in more detail.
2.2.1 Demographic variables
The values of demographic variables (gender, age, etc.) for a simulated profile are selected
probabilistically according to the following steps:
1. Calculate fraction of people in each of the gender/race combinations in the study area and
then use the fractions as probabilities to randomly select a gender/race type for a simulated
individual.
2. Calculate fraction of the selected gender/race type of people in each sector within a study
area and then use the fractions as probabilities to randomly select a home tract for the
simulated person.
3. Calculate fraction of people in each age group in the selected sector/gender/race
combination and use the fractions as probabilities to randomly select an age group for the
simulated person.
4. Randomly select a specific age within the selected age group, assuming a uniform
distribution.
5. Use the user-provided employment probability for the selected age group to randomly
determine whether a simulated person will work.
6. If the commuting option is used and a simulated person works, use the fractions of people
commuting to each of the work sectors for the selected home sector to randomly select a
work sector that a simulated person will commute to. Discard the profile if the work sector
cannot be assigned air quality or temperature data (e.g., because the sector is outside the
study area) If the commuting option is not used, assume a person who works does so in
their home sector.
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Table 2-1. Profile Variables in APEX
Variable
Type
Profile Variables
Description
Demographic
variable
Gender
Male or Female
Race
White, Black, Native American, Asian, and Other
Age
Age (Years)
Home sector
Sector in which a simulated person lives
Work sector
Sector in which a simulated person works
Employment status
Indicates employment outside home
Residential
variables
Gas stove
Indicates presence of gas stove
Gas pilot
Indicates presence of gas pilot light
Air conditioner
Indicates presence of air conditioning at home
Car air conditioner
Indicates presence of air conditioning in the car
Daily varying
variables
Window position
Daily window position (open or closed) during the simulation
period
Daily average car
speed
Daily average car speed during the simulation period
Daily endogenous CO
production rate
Daily endogenous CO production rate in the simulation
period
Physiological
variables
Height
Height of a simulated person (in)
Weight
Body weight of a simulated person (lbs)
Blood volume
Blood volume of a simulated person (ml)
Lung diffusivity
Lung diffusivity parameter used in COHb calculation
(ml/min/torr)
Endogenous CO
production rate #1
Endogenous (internally produced) CO production rate #1
(ml/min)
Endogenous CO
production rate #2
Endogenous CO production rate #2 (ml/min) used only for
women between ages of 12 and 50 for half the menstrual
cycle
Hemoglobin in the
blood
Amount of hemoglobin in the blood (g/ml)
Resting metabolic rate
Resting metabolic activity rate (kcal/min)
Energy conversion
factor
Oxygen uptake per unit of energy expanded (liters/kcal)
Maximum permitted
MET value
Maximum metabolic activity level that can sustained for
about five minutes (dimensionless)
Starting day of
menstrual cycle
The day during the first 28 days of the simulation period that
menstruation begins; used for determining endogenous CO
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2.2.2 Residential Variables
The residential variables (gas stove, air conditioner, etc.) are categorical variables, that are
used to indicate whether a residence or a car associated with a simulated person has the
specified appliance or component. APEX randomly determines the result based on user-
specified probabilities. For example, a user could specify probabilities of 0.3 for not having an
air conditioner and 0.7 for having an air conditioner. APEX randomly generates a value in the
range of 0 to 1, assuming a uniform distribution. If this value is larger than 0.3, the simulated
person will own an air conditioner. If the value is less than 0.3, the person will not own an air
conditioner.
2.2.3 Physiological Profile Variables
The physiological variables (volume of blood, height etc.) are used primarily for calculating dose
(as described in Section 2.6). APEX provides gender- and age-specific normal distribution data
for lung capacity (maximum oxygen uptake), body mass, resting metabolic rate, and blood
volume. APEX randomly selects a value for each of these four variables based on the
distribution data of pre-determined age and gender for the simulated person. The energy
conversion factor is randomly selected, assuming that it is uniformly distributed in the range of
0.20-0.21 liters of oxygen per kcal. The other physiological variables are calculated from the
randomly selected values of lung capacity, body mass, resting metabolic rate, blood volume,
and demographic variables such as gender and age.
2.2.4 Daily Varying Variables
The daily varying variables are generated based on user-supplied rules and distribution data.
For example, the probabilities for the values of window position may depend on the value for
home air conditioner and zone temperatures (average and maximum), while the speed category
is determined randomly from a set distribution for each simulation day and does not depend on
any other variables. Endogenous CO production, which is used in the evaluation of the blood
COHb level, depends on age, gender, and menstrual phase. Thus, for males it always has the
same value from day to day, while for females it may have one of two values depending on the
phase of the menstrual cycle (pre- or post-menstrual).
2.3 Construct a Sequence of Activity Events
APEX probabilistically creates a composite diary for each of the simulated persons by selecting
a 24-hour diary record—or diary day—from an activity database for each day of the simulation
period. CHAD data have been supplied with APEX for this purpose. A composite diary is a
sequence of events that simulate the movement of a modeled person through geographical
locations and microenvironments during the simulation period. Each event is defined by
geographic location, start time, duration, microenvironment visited, and an activity performed.
For the activity database, APEX currently provides a personal information file and an events file
to summarize the CHAD data. The personal information file contains the following variables:
• CHAD ID
• Day type (e.g., Monday)
• Gender
DRAFT—APRIL 24, 2003
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• Race
• Status of employment
• Maximum temperature
• Age
• Occupation
• Count of missing time (when activity and/or location codes are missing from the activity file)
• Number of events
The events file contains the following variables:
• CHAD ID
• Start time (of the event)
• Duration
• Activity code
• Location code
The events file contains a record for each of the events indicated by the number of events in the
personal information file. Note that while CHAD data are provided with APEX, other activity
data could be used instead, as long as the input file format restrictions are met and the CHAD
coding conventions are used.
APEX develops a composite diary for each of the simulated individuals according to the
following steps:
1. Divide diary days in the CHAD database into user-defined activity pools, based on day type
and temperature.
2. Assign an activity pool number to each day of the simulation period, based on the
user-provided daily maximum/average temperature data.
3. Calculate a selection probability for each of the diary days in each of the activity pools,
based on age/gender/employment similarity of a simulated person to a diary day.
4. Probabilistically select a diary day from diary days in the activity pool assigned to each day
of the simulation period.
5. Evaluate a MET value for each activity performed while in a CHAD location, based on the
activity-specific MET distribution data. (MET is a dimensionless ratio of the
activity-dependent energy expenditure rate to the basal or resting expenditure rate. It is
used to calculate a ventilation rate for a simulated person performing a certain activity.
See Section 2.6.1 for details.)
6. Map the location codes in the selected diary to user-defined microenvironments.
7. Concatenate the selected diary days into a composite diary for a simulated individual.
These composite diaries are then used to calculate exposure concentrations, as described
below.
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2.4 Calculate Concentrations in
Microenvironments
APEX calculates air concentrations in the various microenvironments visited by the simulated
person by using the ambient air data for the relevant sectors and the user-specified method and
parameters that are specific to each microenvironment. The subsections below describe the
technical basis and algorithms for this approach.
2.4.1 Define Microenvironments
APEX defines microenvironments by grouping the more than 100 location codes defined in the
activity (CHAD) database into a smaller subset of user-defined microenvironments amenable to
modeling. The user has control over how many microenvironments will be modeled and which
need to be defined and what CHAD (or other activity database) locations should be grouped into
each of microenvironment. Table 2-2 lists the 115 CHAD location codes included in APEX and
the microenvironment to which each currently is assigned.
2.4.2 Calculating Concentrations in Microenvironments
APEX calculates hourly concentrations of the subject air pollutant in all the microenvironments
at each hour of the simulation period for each of the simulated individuals, based on the user-
provided hourly ambient air quality data specific to the geographic locations visited by the
individual. APEX provides two methods for calculating microenvironmental concentrations: the
mass balance method and the factors method. The user is required to specify a calculation
method for each of the microenvironments; some microenvironments can use one method while
the rest use the other, without restrictions. The parameters, algorithms, and stochastic
elements used in each of the methods are explained below.
2.4.2.1 Microenvironment Parameters
Table 2-3 lists and defines the parameters required by the mass balance and factors methods
(described in the next two subsections) to calculate concentrations in a microenvironment. Note
that the proximity factor is used to account for
differences in ambient concentrations
between the geographic location represented
by the ambient air quality data (e.g., a
regional fixed-site monitor) and the
geographic location of the microenvironment
(e.g., near a roadway). This factor could take
a value either greater than or less than 1.
The penetration factor represents the fraction
exchange.
Note that concentrations in Table 2-3 and throughout the equations in the following sections
must be in the same units as the ambient air quality data, i.e., either ppm or |jg/m3 (in the
equations only the latter is shown).
Tip. During exploratory analyses, you can
examine how a microenvironment affects overall
exposure by setting the microenvironment's
proximity or penetration factor to zero, thus
effectively eliminating the microenvironment
of a pollutant entering a microenvironment via air
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Table 2-2. Example of CHAD Location Codes Mapped to Microenvironments
CHAD
Microenvi-
CHAD
Microenvi-
Location
ronment
Location
ronment
Code
Description
codea
Code
Description codea
X
No data
-1
31210
Walk
4
u
Uncertain of correct code
-1
31230
In stroller or carried by adult
4
30000
Residence, general
1
31300
Waiting for travel
4
30010
Your residence
1
31310
..., bus or train stop
4
30020
Other residence
1
31320
..., indoors
3
30100
Residence, indoor
1
31900
Travel, other
2
30120
Your residence, indoor
1
31910
..., other vehicle
2
30121
..., kitchen
1
32000
Non-residence indoor, general
3
30122
..., living room or family room
1
32100
Office building/ bank/ post office
3
30123
..., dining room
1
32200
Industrial/ factory/ warehouse
3
30124
..., bathroom
1
32300
Grocery store/ convenience store
3
30125
..., bedroom
1
32400
Shopping mall/ non-grocery store
3
30126
..., study or office
1
32500
Bar/ night club/ bowling alley
3
30127
..., basement
1
32510
Bar or night club
3
30128
..., utility or laundry room
1
32520
Bowling alley
3
30129
..., other indoor
1
32600
Repair shop
3
30130
Other residence, indoor
1
32610
Auto repair shop/ gas station
2
30131
..., kitchen
1
32620
Other repair shop
3
30132
..., living room or family room
1
32700
Indoor gym /health club
3
30133
..., dining room
1
32800
Childcare facility
3
30134
..., bathroom
1
32810
..., house
3
30135
..., bedroom
1
32820
..., commercial
3
30136
..., study or office
1
32900
Large public building
3
30137
..., basement
1
32910
Auditorium/ arena/ concert hall
3
30138
..., utility or laundry room
1
32920
Library/ courtroom/ museum/ theater
3
30139
..., other indoor
1
33100
Laundromat
3
30200
Residence, outdoor
4
33200
Hospital/ medical care facility
3
30210
Your residence, outdoor
4
33300
Barber/ hair dresser/ beauty parlor
3
30211
..., pool or spa
4
33400
Indoors, moving among locations
3
30219
..., other outdoor
4
33500
School
3
30220
Other residence, outdoor
4
33600
Restaurant
3
30221
..., pool or spa
4
33700
Church
3
30229
..., other outdoor
4
33800
Hotel/ motel
3
30300
Residential garage or carport
4
33900
Dry cleaners
3
30310
..., indoor
4
34100
Indoor parking garage
2
30320
..., outdoor
4
34200
Laboratory
3
30330
Your garage or carport
4
34300
Indoor, none of the above
3
30331
..., indoor
4
35000
Non-residence outdoor, general
3
30332
..., outdoor
4
35100
Sidewalk, street
2
30340
Other residential garage or carport
4
35110
Wthin 10 yards of street
2
30341
..., indoor
4
35200
Outdoor public parking lot/garage
2
30342
..., outdoor
4
35210
..., public garage
2
30400
Residence, none of the above
1
35220
..., parking lot
2
31000
Travel, general
2
35300
Service station/ gas station
2
31100
Motorized travel
2
35400
Construction site
4
31110
Car
2
35500
Amusement park
4
31120
Truck
2
35600
Playground
4
31121
Truck (pickup or van)
2
35610
..., school grounds
4
31122
Truck (not pickup or van)
2
35620
..., public or park
4
31130
Motorcycle or moped
2
35700
Stadium or amphitheater
4
31140
Bus
2
35800
Park/ golf course
4
31150
Train or subway
2
35810
Park
4
31160
Airplane
0
35820
Golf course
4
31170
Boat
2
35900
Pool/ river/ lake
4
31171
Boat, motorized
2
36100
Outdoor restaurant/ picnic
4
31172
Boat, other
2
36200
Farm
4
31200
Non-motorized travel
4
36300
Outdoor, none of the above
4
a -1 = continue using the same microenvironment as appears previously in time in the full composite diary; 0 = concentration
of zero; 1 = indoor (residence); 2 = in or near vehicle; 3 = indoor(other); 4= outdoor.
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Table 2-3. Parameters Required by Mass Balance and Factors Method
Method
Variable
Definition
Units
Value Range
Default/ Supplied
Value
Mass
^ proximity
Proximity factor
unitless
fproximity — ^
1
Balance
^ penetration
Penetration factor
unitless
^ ^ fpenetration — 1
1
cs
Concentration source
|jg/m3 or
ppm
CS > 0
0
ES
Emission source
|jg/hr
ES > 0
0
D
removal
Removal rate due to
deposition, filtration, and
chemical reaction
1/hr
R >0
"removal —
0
D
" air exchange
Air exchange rate
1/hr
R > D
"air exchange — u
none
D
mean
p R
"removal "air exchange
1/hr
^mean - ^
R + R
"removal "air exchange
V
Volume of
microenvironment
m3
O
A
none
Factors
f proximity
Proximity factor
unitless
fproximity — ^
1
^ penetration
Penetration factor
unitless
^ ^ fpenetration — 1
1
CS
Concentration source
jjg/m3 or
ppm
CS> 0
0
2.4.2.2 Mass Balance Method
The mass balance method assumes that an enclosed microenvironment (e.g., a residence) is a
single well-mixed box in which the air concentration is spatially uniform at any time at any
location within the box. The concentration of an air pollutant in such a microenvironment is
estimated using the following four processes (as illustrated in Figure 2-3):
• Inflow of air into the microenvironment;
• Outflow of air from the microenvironment;
• Removal of a pollutant from the microenvironment due to deposition, filtration, and chemical
degradation; and
• Emissions from sources of a pollutant inside the microenvironment.
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Figure 2-3. Mass Balance Model
Microenvironment
Air
outflow
Air
inflow
Removal due to:
•Chemical reactions
Indoor sources
•Deposition
•Filtration
Change in microenvironmental concentration due to influx of air is represented by the following
equation:
ac = ^- = C x f x f x R (2-1)
in dt ambient proximity penetration air exchange
where:
aC„
C(t)
^ambient
^proximity
^penetration
Ra
Change in microenvironmental concentration due to influx of air
(pg/m3/hour)
Concentration in a microenvironment at time t (|jg/m3)
Time
Ambient hourly concentration (|jg/m3)
Proximity factor (unitless)
Penetration factor (unitless)
Air exchange rate (1/hour)
x air exchange
Change in microenvironmental concentration due to outflux of air is described by:
dC(t)
AC
, = R . . x C(t)
out dt air exchange v'
(2-2)
DRAFT—APRIL 24, 2003
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where:
aCout = Change in microenvironmental concentration due to outflux of air
(|jg/m3/hour)
Change in concentration due to deposition, filtration, and chemical degradation in a
microenvironment is simulated based on the first-order equation:
AC
dC(t)
,=r^L = (R + R +R . ) C(t) = R ,xC(t) (2-3)
removal deposition filtration chemicaly 1' removal 1' v '
where:
aC,
removal
x deposition
* filtration
xchemical
xremoval
= Change in microenvironmental concentration due to removal processes
(|jg/m3/hour)
= Removal rate of a pollutant from a microenvironment due to deposition
(1/hour)
= Removal rate of a pollutant from a microenvironment due to filtration (1/hour)
= Removal rate of a pollutant from a microenvironment due to chemical
degradation (1/hour)
= Removal rate of a pollutant from a microenvironment due to overall removal
(1/hour)
Sources of a pollutant from inside the microenvironment is described by the following equation:
AC =—xES.+R X CS. (2-4)
source \y i mean ^ i
where:
aC,
removal
v
ES,
cs,
Change in microenvironmental concentration due to source emission inside a
microenvironment (|jg/m3/hour)
Volume of a microenvironment (m3)
Emission rate for emission source I (|jg/hour)
Emission rate for concentration source I (|jg/m3)
^airexchange ^Removal (1/hOUT)
Number of emission sources in the microenvironment
Number of concentration sources in the microenvironment
(Note that concentration must be in the same units as the ambient air quality data, i.e., either
ppm or )jg/m3, although throughout these equations concentration is shown only in |jg/m3. The
above equation, 2-4, is the only one that needs modification if the units are switched.
Specifically, W would be replaced by fN, where f= 1/ppmFact. The value of ppmFact is a
user-supplied input parameter that expresses the number of )jg/m3 that equate to 1 ppm. For
CO, ppmFact=1,145.) Thus, the mass balance equation for a pollutant in a microenvironment is
described by:
DRAFT—APRIL 24, 2003
23
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dC(t)
= AC + AC. - AC , - AC , (2-5)
di source in out removal
where:
C(t) = Concentration in a microenvironment at time t (|jg/m3)
Within the time period of an hour, ACsource and ACjn can be assumed to be constant. Using
ACcombmed = ACsource + aC,„, Eq. (2-2), and Eq (2-3) in Eq. (2-5) leads to:
dC(t) _ Q(t) _ QU)
df combined air exchange (' removal ('
= AC .. .-R C(t)
combined mean v'
Solving the differential equation Eq. (2-6) leads to:
(2-6)
q^ = combined +
^mean
rC(0)-ACcombined^
^mean J
exp( Rmeant) (2-7)
where:
C(0) = Concentration of a pollutant in a microenvironment at the beginning of a hour
(|jg/m3)
C(t) = Concentration of a pollutant in a microenvironment at time t within the time
period of a hour (|jg/m3).
Based on Eq. (2-7), the following three hourly concentrations in a microenvironment are
calculated:
C -I — C(t y 00) -
ACcombined _ ACsource+ AC/'n (2"8)
equil r R , + R
mean air exchange removal
C. . .=C ..-\C(0)-C ..}exp(-R ) (2-9)
hourly end equil v equilj meany
1\C®dt 1-extX-R )
). = Q— = C .. + (C(O)-C ..) mean (2-10)
hourly mean 1 equil 1 1 ' equil' o
j dt mean
0
where:
Cgqun = Equilibrium concentration in a microenvironment (|jg/m3)
C(0) = Concentration in a microenvironment at the beginning of each hour (|jg/m3)
C hourly end = Concentration in a microenvironment at the end of each hour (|jg/m3)
DRAFT—APRIL 24, 2003
24
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Chourly mean = Hourly mean concentration in a microenvironment (|jg/m3)
^mean ~ ^air exchange ^removal (1/hOUT)
At each hour time step of the simulation period, APEX uses Eq. (2-8), Eq. (2-9), and Eq. (2-10)
to calculate the hourly equilibrium, hourly ending, and hourly mean concentrations. APEX
reports hourly mean concentration as hourly concentration for a specific hour. The calculation
continues to the next hour by using Chourlyend for the previous hour as C(0).
2.4.2.3 Factors Method
The factors method is simpler than the mass balance method. It does not calculate
concentration in a microenvironment from the concentration in the previous hour, and it has
many fewer parameters. The factors method uses the following equation to calculate hourly
concentration in a microenvironment from the user-provided hourly air quality data:
n
C = C f f + y CS (2-1-
hourly ambient proximity penetration ^ i
Hourly concentration in a microenvironment (|jg/m3)
Hourly concentration in ambient environment (|jg/m3)
Proximity factor (unitless)
Penetration factor (unitless)
Mean air concentration resulting from source I (|jg/m3)
number of concentration sources in the microenvironment
2.4.2.4 Stochastic Elements
To account for temporal and spatial variability of the microenvironment parameters required to
calculate an hourly microenvironmental concentration APEX allows, the user to provide
distribution data to randomly select a value for each of the parameters. The following
distribution types can be specified for each model-parameter:
• Single point
• Uniform
• Normal
• Log-normal
• Triangle
• Exponential
• Off/on
• Discrete
• Histogram
Also, the user can provide distribution data for any combination of the following temporal,
spatial, and conditional variables:
• Hour in a day
• Day in a week
• Month in a year (i.e., season)
where:
C,
hourly
c
wambient
fproximity
fpenetration
CS,
nr
DRAFT—APRIL 24, 2003
25
-------
• Air district
• Three conditional variables selected from the following profile variables:
~ Gender
~ Race
~ Employment status
~ Gas stove
~ Gas pilot light
~ Air conditioner
~ Car air conditioner
~ Window position
~ Maximum temperature categories
~ Average temperature categories
~ Car speed categories
APEX also allows the user to decide whether a new random value should be selected for a
microenvironmental factor from the same distribution data at every hour in a time block of a day
or every day in a simulation period.
2.5 Determine Exposure
APEX calculates exposure as a time series of exposure concentrations that a simulated
individual experiences during the simulation period. APEX determines the exposure by
identifying hourly concentrations and minutes spent in a sequence of microenvironments visited
according to the composite diary. The hourly exposure concentration at any clock hour during
the simulation period is determined using the following equation:
N { 1
°hourly (j) t(i), (212)
' ~ T
where:
Cj = Hourly exposure concentration at clock hour I of the simulation period (|jg/m3
or ppm)
N = Number of events (i.e., microenvironments visited) in clock hour I of the
simulation period.
Chourly (j) = Hourly concentration in microenvironment j (|jg/m3 or ppm)
ta = Time spent in microenvironment j (minutes)
T =60 minutes
From the hourly exposures, APEX calculates time series of 8-hour and daily average exposure
concentrations that a simulated individual would experience during the simulation period. APEX
then statistically summarizes and tabulates the hourly, 8-hour, and daily exposures.
2.6 Determine Dose
For some pollutants, such as CO, the toxicokinetics are sufficiently understood such that dose
can be modeled in addition to the exposure concentration. Dose may be more useful or
accurate than exposure for evaluating the effects of air pollutants because it accounts better for
DRAFT—APRIL 24, 2003
26
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differences in pollutant uptake resulting from (1) the variation in physiology and activities across
populations and (2) the variation in physiological responses to activities within an individual.
Therefore, APEX has been designed to allow the user the option of calculating either exposure
concentration, as described in the preceding section, or also calculating dose, as described in
this section. APEX currently has been designed to calculate dose for CO. To estimate dose for
other pollutants, the development of pollutant-specific dose algorithms is required.
As seen by the box to the right, dose can
have many definitions. In APEX, dose can
be calculated for CO, in particular the
delivered dose of CO as measured by the
biotransformation product
carboxyhemoglobin (COHb)—specifically
%COHb—in the blood. The estimated
%COHb, in addition to being a more refined
measure of exposure compared to exposure
concentration, is useful for comparing to
health-based benchmarks of %COHb.
Conceptually, APEX uses a number of
factors, in particular a time series estimate of
alveolar ventilation rate (which is activity and
physiology dependent) and a time series
estimate of exposure (which indicates the
pollutant concentration in the inhaled air for
specific moments in time), to calculate
%COHb. The ventilation rate algorithm is
discussed in Section 2.6.1 and the %COHb
algorithm is discussed in Section 2.6.2. For
other factors and additional detail, see
Johnson (2002).
Definitions of dose. The term dose is often
defined as the administered or delivered amount
of a substance to the body and generally is stated
as the total mass of the chemical or the mass per
unit body weight or related denominator. But
dose actually can be subdivided as follows:
~ Potential dose is the amount of chemical
contained in material ingested, air breathed, or
bulk material applied to the skin.
~ Applied dose is the amount of the chemical in
contact with the major absorption boundaries,
such as the skin, lungs, and gastrointestinal
tract, and available for absorption.
~ Absorbed dose is the amount of a chemical
penetrating across the absorption barrier. For
the respiratory route, the internal dose is the
amount of the chemical absorbed via the lung.
~ Internal dose is a more general term denoting
the amount absorbed without respect to
specific absorption barriers or exchange
boundaries.
~ Delivered dose is the amount of the chemical
available for interaction with any particular
organ or cell.
2.6.1 Ventilation Rate
Ventilation is a general term for the movement of air into and out of the lungs. Minute or total
ventilation is the amount of air moved in or out of the lungs per minute. Quantitatively, the
amount of air breathed in per minute (V,) is slightly greater than the amount expired per minute
(VE). Clinically, however, this difference is
not important, and by convention minute
ventilation is always measured on an expired
sample, VE. Alveolar ventilation (VA) is the
volume of air breathed in per minute that (1)
reaches the alveoli and (2) takes part in gas
exchange. The ventilation rate needed for
the %COHb determination is this ventilation
rate, VA, and is derived for use in APEX
based on work by Adams (1998), Astrand
and Rodahl (1977), Burmasterand Crouch (1997), Esmail etal. (1995), Galetti (1959), Johnson
(1998), Joumard et al. (1981), McCurdy (2000), McCurdy et al. (2000), Schofield (1985), and
many others. Only a brief description of VA is described below; for the complete derivation, see
Johnson (2002).
Total or expired ventilation rate, VE, also can
be calculated from V02. In fact, APEX currently
contains the equations for calculating VE in case
they are needed for other pollutants. See
Johnson (2002) for additional information on the
derivation of VE.
DRAFT—APRIL 24, 2003
27
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Conceptually, VA can be related to the oxygen ventilation rate of the individual at any given
moment. This relationship can be described as follows for a given activity event and personal
profile:
VA = VQ2 X CF02,A (2-13)
where
VA = Alveolar ventilation rate (ml of air/min)
V02 = Oxygen ventilation rate (I of 02/min)
CF02A = Oxygen to air conversion factor (19,530 ml of air/I of 02).
V02 in turn is related to the energy expenditure rate for the given event activity and the given
profile's physiology in terms of oxygen ventilation per unit energy expenditure, or:
V02 = EE x ECF (2-14)
where
EE = Energy expenditure (kcal/min)
ECF = Energy conversion factor (I of 02/kcal).
ECF is based on the physiology of the individual being modeled and is described in Section 2.2.
EE is related to the activity-specific energy expenditure rate and the basal or resting energy
expenditure (metabolic) rate of the given profile, or:
EE = MET x RMR (2-15)
where
MET = Metabolic equivalent (dimensionless)
RMR = Resting metabolic rate (kcal/min).
RMR is based on the physiology of the individual being modeled and is described in
Section 2.2. MET—which comes from "metabolic equivalents of task"—is a dimensionless ratio
of the activity-specific energy expenditure rate to the basal or resting energy expenditure rate.
While different people have very different basal metabolic rates, it is generally found that the
MET ratios do not exhibit as much variability. Thus, standing still might require two times the
basal energy expenditure, or two MET, for most people, with relatively little variation. Since the
basal rate is constant for each profile, it only has to be determined once and the activity-specific
MET ratio can be used to determine the absolute energy expenditure rate, EE, for each activity.
MET is discussed in more detail below as well as in Section 2.2.
The overall equation for VA for activity I of day j for person k is:
VA(i,j,k) = MET(i,j,k) x RMR(k) x ECF(k) x CFQ2 A (2-l6)
APEX incorporates these concepts using a variety of other parameters, limits, and probabilistic
data and algorithms. For example, before MET can be used in APEX for a given activity and
DRAFT—APRIL 24, 2003
28
-------
profile combination, it must be evaluated for whether it satisfies the condition that the average
level of metabolic activity over long time intervals cannot remain as high as it can for short
intervals. That is, the nominal value for the maximum MET for any individual, METmax,
represents the maximum activity level that can sustained for about five minutes. Shorter bursts
of activity can exceed this level, in part because a substantial non-aerobic contribution is usually
present. However, for longer time periods, the average MET cannot remain as high as the
nominal value for METmax. In particular, over one hour the average MET cannot exceed about
64% of METmax for any person. The average MET over a two hour time interval cannot exceed
about 54% of METmax. Similar limits exist for periods up to nine hours (33% of METmax).
Therefore, after first determining the time series for hourly mean MET values for the entire
simulation period—which may require aggregation across several diary events or
microenvironments within each hour—APEX calculates running averages from 1 to 9 hours for
the entire simulation period. Each set of 9 averages then are compared to the respective limits
on the maximum sustainable MET averages. If the limit is exceeded, the preceding MET values
are adjusted downwards sufficiently to place the average at the limit.
See Volume II of the User's Guide and the above references—especially Johnson (2002)—for
additional details regarding the incorporation of this and other limits, other parameters, and
probabilistic data and algorithms used in APEX.
2.6.2 Carboxyhemoglobin (COHb) Determination
The %COHb calculation in APEX uses the time series for exposure (CO concentration in the air)
and the time series for alveolar ventilation rate, VA, as inputs (among other factors). The dose
calculation is based on the solution to the non-linear Coburn, Forster, Kane (CFK) equation, as
detailed in Johnson (2002). As pointed out by that report, the CFK equation does not have an
explicit solution, so an iterative solution or approximation is needed to determine the %COHb.
An iterative solution, however, was determined to be unsuitable because of the model execution
time necessary (a typical model run of one calendar year represents roughly 14,000 events per
person and several thousand people, or tens of millions of diary events). Therefore, the CFK
equation is solved using a modified Taylor's series method in which the event duration is
restricted in time (if necessary) to ensure convergence with only a few terms. This method
avoids the dangers of non-convergence that arise in some other methods.
As the mathematical derivation in the above report is very detailed, only the main results are
presented here. First, it should be noted that the literature discusses two forms of the CFK
equation, namely a linear and a non-linear form. The linear form itself is an approximation that
allows an explicit solution, but is not accurate under all conditions. The non-linear form is
considered to be more correct and is the one being discussed here.
Restricting %COHb(t) to between 0 and 100 (percent), the CFK equation takes the form of the
following differential equation:
r- r- %COHb(t)
%COHb'(t) = C - C. x ^ (9-17)
o 1 100 - %COHb(t) ^ ' '>
where C0 and C1 are constants over the duration of one event that depend on physical and
physiological parameters, including VA, and on the CO concentration in the air.
Time zero represents the start of the current event. The concentration %COHb(0) (at time zero)
is assumed to be known. The first derivative, %COHb(0), can easily be found from the above
equation. The solution %COHb(t) is a smoothly varying function of time without sudden
discontinuities or changes in slope. It therefore can be expanded in a Taylor's series about
DRAFT—APRIL 24, 2003
29
-------
t = 0, which should converge fairly rapidly. One simplification is to rescale the time variable to
the unitless parameter z:
(C0 + Cj J x t
~ (100 X D0 X D0) (2-18)
where
(2.19)
The Taylor's series up to the fourth order term is:
,2
¦ +
T4 (z) = %COHb(0) + 100 x D0 x Dz - 100 x A >^po * Pz'
100xA,xD0xDx (A1-2D)xz3 100x A,x D0x Dx (A,2 -8DA, + 6D2)x z4 (2"2°)
6 24
where
ci
A = (2-21)
D = D0-A1 (2-22)
For typical values for the constants C0, C1t and %COHb(0), convergence occurs for z< 1. For
z values below this limit but still close to one, the convergence is slow, so the terms beyond
fourth order would be needed if high accuracy were desired. It is found that z< 1 generally
corresponds to %COHb(0) values below 40 to 50% for one-hour events.
The z value is proportional to t. In APEX, an event can have a duration of no more than one
hour. For one hour events there are conditions where z is close to one and convergence of the
Taylor's series may require more than four terms. However, it is not necessary to evaluate the
entire hour in one step. By dividing the event into shorter subevents, each will have a smaller
z value. For example, if a one-hour activity diary event has initial conditions that correspond to
z=0.9, then by dividing this into three 20 minute subevents, each will have a z value around 0.3.
Actually, the first subevent will have exactly z=0.3. The others will be slightly different as the
initial conditions for those subevents will have changed slightly. Thus, dose accumulates the
average %COHb level over the subevents. At the end of all subevents, the average dose is the
accumulated dose divided by the number of subevents, while the final value of the dose is
simply the final value of COHb itself. These values are saved and the next diary event is
processed.
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30
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3. INSTALLING APEX
This chapter provides the requirements and instructions for installing APEX on a personal
computer (PC). Section 3.1 describes the hardware and software requirements for installing
APEX. Section 3.2 describes the steps involved in a typical installation of APEX with the
Multimedia Integrated Modeling System (MIMS) graphical user interface (GUI). Section 3.3
describes the steps involved in installing APEX to run in DOS batch mode.
3.1 Hardware and Software Requirements
To use APEX, the user's PC should be equipped with at least:
• 256 MB of RAM;
• 600 MHz or faster processor; and
• 450 MB of available hard drive space.
PCs with less RAM and slower processors will also work, but performance (e.g., model run
time) will be less than optimal.
APEX is compatible with the following computer operating systems:
• Windows XP
• Windows 2000
• Wndows NT
• Wndows 95/98
However, Windows XP, Wndows 2000, and Wndows NT are the recommended operating
systems for running APEX because they best meet the memory requirements of the model. As
APEX was developed using Java, it can be run under a number of other operating systems,
such as Linux and Solaris; however, APEX has not been fully implemented in any non-
Wndows-based operating systems to date.
3.2 Installing APEX to Run in MIMS
The installation of APEX with the MIMS GUI consists of the following six steps. Note that the
first five steps can be completed in any order; however, Step 6 must be completed after Step
(5).
1. Download and unzip the APEX project file
Users should download the MIMS project for APEX from the internet
(http://www.epa.qov/ttn/fera) to their hard drive. This zip file, which contains a single file in BIN
format, should then be unzipped into the directory in which APEX will be installed (e.g.,
C:\APEX) using extraction software (e.g., WnZip). This directory will be referred to as the
"Default Directory."
2. Install the Java Runtime Environment
The Java Runtime Environment (JRE) is installed by completing the following steps.
DRAFT—APRIL 24, 2003
31
-------
• Download the J RE file from http://iava.sun.eom/i2se/1.3/download.html (select the
appropriate Windows download from the "JRE" column). Important note: During testing,
several issues have been identified with running APEX in MIMS using JRE version 1.4. If
you encounter problems and are using JRE version 1.4, consider switching to JRE version
1.3.
• Close all open applications.
• Run the downloaded JRE file (e.g., j2re-1_3_1_04-windows-i586.exe) and follow the
instructions on the screen.
• Reboot the computer.
• To free up hard drive space, delete the downloaded JRE file.
3. Download and unzip the APEX executable
Users should download the APEX executable from the internet (http://www.epa.qov/ttn/fera) to
their hard drive. This zip file should then be unzipped into the Default Directory using extraction
software (e.g., WinZip).
4. Download and unzip the APEX national input databases
Users should download the following national input databases from the internet
(http://www.epa.qov/ttn/fera) to their hard drive.
• Consolidated Human Activity Database Files (4 MB zipped). This database contains
activity diaries, as well as metabolic and physiological parameter data.
• Population Files (28 MB zipped). This databases contains 2000 tract-level U.S. Census
counts, tract locations, and national employment probabilities by age.
• Commuting Database (36 MB zipped). This database contains adult commuting patterns
based on the 1990 U.S. Census, updated to year 2000 population.
These zip files should then be unzipped into the Default Directory using extraction software
(e.g., WinZip). These databases can be used for most applications in the United States;
however, users can optionally use alternative databases (e.g., if the user wishes to model a
subpopulation). More details on these databases can be found in Chapter 5.
5. Install MIMS
Users must install the Multimedia Integrated Modeling System (MIMS) to run APEX in MIMS.
For instructions on installing MIMS, refer to http://www.epa.qov/ttn/fera.
DRAFT—APRIL 24, 2003
32
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6. Import the APEX project file into MIMS
To import the APEX project file into MIMS, the user must complete the following steps.
• Start MIMS as described in the MIMS installation instructions. The "Project Selection
Window" will open.
jjs xj
Available Projects
From Project Selection Window, select "Import Project" from the File menu.
[ MIMS - Project Selection Window
File Help
New Project
Import Project
Close
Edit Administration Information
Exit MIMS Framework
DRAFT—APRIL 24, 2003
33
-------
• After selecting "Import Project," a file browser will appear. Use this browser to select the
APEX project file (with extension ".BIN"). After selecting the file, click "Import."
> Select File
Look In: ~ MINIS
*]
£3 C3
n-n.
n—
LMJ.
u—
rl Expo Inhalation
L3 MIMS Tutorial
C3 MIMSFW
Pj APEX_mims_project.bin
[j APEX_mims_project.zip
|Jj HAPEM_mims_project.zip
File Name:
i AP EX_m i rn s_p roj e ct. b i n
Files of Type: All Files
Import
Cancel
In the "Import Project" window, enter a name for APEX project (e.g., "TRIM Inhalation
Exposure Assessment") and click "OK."
1 Import Project
*jI
Enter a unique name for the imported project
TRIM Inhalation Exposure Assessment
OK Cancel
After importing the project, the Project Selection Window will include the new APEX project.
To open the model, double-click on the project name.
I MIMS - Project Selection Window
File Help
- ~ x
Available Projects
TRIM Inhalation Exposure Assessment
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34
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3.3 Installing APEX to Run in DOS Batch Mode
To install APEX to run in DOS batch model, the user must download the zip files containing the
APEX executable and national input database files from http://www.epa.gov/ttn/fera. After
downloading these four zip files (i.e., one zip file containing the executable and three zip files
containing the national input databases and other supplied data), the user must unzip them
using extraction software (e.g., WinZip). These files can be unzipped anywhere on the hard
drive; however, the user must ensure that there is at least 450 MB of available hard drive space
in the target location for the national input database files. The user should note the name and
location of all of the unzipped files for later reference.
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4. RUNNING APEX
This chapter describes the steps involved in setting up
and running an APEX simulation, the purpose and
content of the input and output files, and the available
model options. This chapter is organized as follows:
Section 4.1 Running APEX in MIMS
Section 4.2 Running APEX in DOS Batch Mode
Section 4.3 Setting Up an APEX Simulation
Section 4.4 Overview of APEX Input and Output Files
Section 4.5 Overview of Model Settings and Options
Chapters 5 and 6 provide a detailed description of the
input and output files, respectively.
4.1 Running APEX in MIMS
What's a "unit number"? The
APEX computer code uses a unit
number to refer to a specific input or
output file. For example, Unit 10 is
the Params file (which specifies the
overall settings, or parameters, for
an APEX simulation—see Chapter
5). Thus, if a unit number is
requested during an APEX run, then
that means that one of the input files
could not be found. The user should
consult the appropriate section of
this user's guide. Unit numbers
have been included in section
headings for easy reference.
After installing APEX in MIMS as described in Section 3.2, the user can run the model by
starting MIMS and either:
• Selecting the APEX project from the "Available Projects" list in the "Project Selection
Window" and then selecting "Open Project" from the File menu, or
• Double-clicking on the APEX project in the "Available Projects" list in the "Project Selection
Window."
Either of these methods will bring up a window named with the name of the project (e.g., "TRIM
Inhalation Exposure Assessment"). This window is comprised of a drop-down menu of
"Category" types, a list of the items associated with the selected type, and five buttons that
correspond to the actions that can be performed on these items. There are three "Category"
types listed in the drop-down menu: Scenario, Domain Object, and Default External Module.
The user should refer to the MIMS guidance for detailed descriptions of these "Category" types.
I Hi TRIM Inhalation Exposure Assessment
-inlx]
File Edit Help
Contents
Category
Scenario ~
Exposure Assessment for Benzene (Houston test case)
Exposure Assessment for Chromium (Houston test case)
Exposure Assessment w/APEX
New
Delete
Rename...
Open
Duplicate...
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To configure and run an application using APEX in MIMS, the user must complete the following
steps.
1. Select "Scenario" from the "Category" drop-down menu. The list of scenarios
included in the project will appear in the space below the drop-down menu.
Initially, this list will include a generic scenario for U.S. locations (i.e., "Exposure
Assessment w/APEX") that can be used to develop a new scenario specific to a
user's application and two example application scenarios (i.e., "Exposure
Assessment for Benzene (Houston test case)" and "Exposure Assessment for
Chromium (Houston test case)"). Users wishing to run either of the example
applications should open the example scenario (by either double-clicking on the
scenario name or selecting the scenario name and clicking the "Open" button)
and then skip to Step (3). Users wishing to configure a new application should
proceed to Step (2).
2. Select the "Exposure Assessment w/APEX" scenario and click the "Duplicate"
button. The "Rename Library Member" pop-up window will appear. Enter a
name for the application scenario (e.g., "New Scenario") and click "OK." The
new scenario will then appear in the list of scenarios. Open the new scenario by
either double-clicking on the scenario name or selecting the scenario name and
clicking the "Open" button.
Rename Library Member
2^
Enter new name for "Exposure Assessment w/APEX"
OK Cancel
3. Select "Expand AN" from the "Object" drop-down menu in the "Graph View of
Scenario: " panel. Select "Calculate Inhalation Exposure:
APEX" in the "Graph View of Scenario: " panel. When
selected, the text will change to bold italics.
DRAFT—APRIL 24, 2003
38
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b Scenario New Scenario
File Scenario View Help
Edit Object Help
Graph View of Scenario: New Scenario
Edit Object Help
New Scenario
ED Exposed Individuals
: C Calculate Inhalation Exposure: APEX
Exposed Individuals
; Calculate toftafatioii Exposure: APEX
Parameter Table
BillII OilEi
Parameter I Value
Source
Status
Execution Method Local Execution
Edit
Itn
File Management Pa... Set of 12
Edit
local
Random Number Se...
lin
4. Double-click on "Calculate Inhalation Exposure: APEX" in the "Graph View of
Scenario: " panel. The "Module Instance" window will appear.
^ Module Instance APEX
-in. xj
File Edit Parameters Help
Parameters Module
4- *
©SHI [ajffif
ObiectType
Parameter
Value I
Additional Type...
Source
Status, I
Exposed Indivi...
Start Date
yyyyMMdd
in, reciuired
Exposed Indivi...
End Date
yyyyftlMdd
in. reouired
Use Daylight...
-------
6. In the "Parameter Table" at the bottom of the Scenario Window, press the left-
most button to expand the list of parameters. If necessary, check the "Create
Output Directories" parameter. When selected, the option allows MIMS to create
any required output directories if they do not exist when the simulation starts. If
the user specifies an output directory that already exists, this option does not
need to be selected. Set the "Default Directory" to correspond to directory
containing the APEX executable (i.e., the Default Directory from the installation).
Set the remaining scenario settings as desired. Refer to the MIMS User Guide
for more details about these parameters.
Scenario New Scenario
File Scenario View Help
Edit Object Help
^id xj
New Scenario
B Exposed Individuals
C Calculate Inhalation Exposure: APEX
Graph View of Scenario: New Scenario
Edit Object Help
Exposed Individuals
Calculate Inhalation Exposure: APEX
_Lii_
Parameter Table
TT
+
Parameter
Value
Source
Status
Execution Method
Local Execution
Edit
in
File Management Pa...
Set of 12
Edit
local
Delete Old Output Fil...
0
in
Execution Path
Browse
in
Delete Generated In...
~
in
Keep Module Logs
Yes
in
Create Output Direct -
0
in
Log Module Start and...
0
in
Overwrite Log Files
~
in
Delete Generated Ba...
~
in
Delete Intermediate ...
~
in
Overwrite Script Files
~
in
Delete Unused Final...
~
in
Default Directory
CAmodelslapex
Browse
in
Random Number Se...
in
7. To start the simulation, select "Execute All" from the Scenario drop-down menu
of the Scenario window.
4.2 Running APEX in DOS Batch Mode
The APEX executable can be run in DOS batch mode, meaning that the model's executable
(.exe) and Params files are specified in a single user-created file (referred to as a "batch" file)
that is submitted to the operating system for job execution. When running APEX in DOS batch
mode, there is no GUI. To run APEX in DOS batch mode, the user must complete the following
steps.
DRAFT—APRIL 24, 2003
40
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1. Create the APEX batch file
To create an APEX batch file, open a new file in a text editor (e.g., Notepad). On the first line of
this file, enter the file path and name of the APEX executable followed by a space and the file
path and name of the Params file. For example,
IAPEX_Batch.bat - Notepad
-|n]x|
File Edit Format Help
c:\apex\apex3.ex e c:\ap EX\i n p ut\P a r am s.t xt
M
Mi
J
1AA
In this example the APEX executable (i.e., APEX3.exe) is located in the "C:\APEX" directory
and the Params file (i.e., Params.txt) is located in the "C:\APEX\input" directory. After entering
this line, save the file. The file can be named anything, provided it ends with the extension
".bat" (e.g., APEX_Batch.bat).
2. Run the APEX batch file
APEX can be run using the batch file in any of the following ways.
• Double-clicking on the batch file in Explorer
• Typing the batch file name in a DOS window
• Selecting "Run" from the Start menu and entering the file path and name of the batch file
• Creating a shortcut to the batch file on the desktop by selecting the batch file in Explorer,
right-clicking the mouse, and selecting "Create Shortcut" from the menu. A shortcut file will
be created and this file can be dragged onto the desktop and optionally renamed. To run
APEX, double-click on this shortcut.
In addition to running in DOS batch mode, there are several other ways to run APEX outside of
the MIMS framework (described in the text box below). Refer to MS-DOS documentation for
additional information on these alternative options.
Additional Options for Running APEX Outside of MIMS or DOS Batch Mode
1. Typing the file name of the APEX executable at the prompt in a DOS window. APEX will prompt the
user for the "Unit(10)" file, at which time the user would input the location and name of the Params file.
2. Double-clicking on the APEX executable in Explorer. APEX will prompt the user for the "Unit(10)" file, at
which time the user would input the location and name of the Params file.
3. Typing the file names of the APEX executable and Params file at the prompt in a DOS window.
DRAFT—APRIL 24, 2003
41
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4.3 Setting Up an APEX Simulation
This section describes the steps involved in performing an APEX simulation. In particular, this
section provides an overview of these steps followed by more detailed descriptions.
4.3.1 Overview
Figure 4-1 lists the five general steps involved in configuring
and performing an APEX simulation. These steps are
described below. Because each of these steps builds on the
previous one, the user should proceed through these steps in
this order.
1. Identify the Scope of the Analysis
The first step in configuring an APEX simulation is to identify
the scope of the analysis. This step involves selecting the
study area, modeling period, pollutant, and populations of
interest for the analysis.
2. Select Model Options
After identifying the scope of the analysis, the user must decide
which options to select. To determine the appropriate options
for the application, the user must answer questions such as the
following.
• Do I want to model worker commuting?
• How many profiles (or what percentage of the population)
do I want to model?
• How many microenvironments do I want to model?
• How should I define my microenvironments?
• Which model settings should I select (e.g., model Daylight
Savings Time? use air quality controls, or "rollbacks"?)
• What types of outputs do I want from the model?
Each of these options is described in more detail in Section 4.4.
3. Set Up Input Files
Figure 4-1. General Steps to
Configure and Conduct an
APEX Simulation
1. Identify Scope
of Analysis
V
2. Select Model
Options
3. Set Up Input Files
4. Configure
Simulation Settings
5. Run APEX
After deciding which model options to use and how to configure
them, the next step in configuring an APEX simulation is to set
up the input data files with the necessary data. There are 16
types of input data files required by APEX. Wth the exception
of the population data file type, there is only one input file per input data file type. One of these
files, the Params file (see next step), is used to specify input and output file names and
locations and simulation settings. However, when running APEX in MIMS, the Params file is
generated by the model (see next step), as opposed to being supplied by the user (as is the
case when APEX is run in DOS batch mode). The remaining files contain the input data
necessary to run APEX. The data contained in these remaining files varies depending on the
DRAFT—APRIL 24, 2003
42
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options selected and the data contained in the other input files. The relationships between the
input files (e.g., if you change one input file, does it impact any of the others?) is described in
Table 4-3 in Section 4.5 and Chapter 5.
4. Configure the Simulation Settings
The final step before starting an APEX simulation is to configure the Params input file. This file
contains five sections:
• Input file names and locations (other than population files);
• Population file descriptions, names, and locations;
• Output file names and locations;
• Parameter settings; and
• Output table levels.
A detailed description of each of the sections of the Params file is provided in Chapter 5.
When running APEX using the DOS batch mode, the Params file must be created by the user.
When running APEX in MIMS, this information is specified by the user within the GUI and then
the model uses it to create the Params file automatically. The steps involved is specifying these
settings in the MIMS GUI are described in Section 4.1.
5. Running APEX
The final step in configuring and performing an APEX simulation is running the model. If APEX
is run in DOS batch mode, this step involves running the APEX executable. If APEX is run
using MIMS, it involves completing Step (7) in Section 4.1.
4.3.2 Detailed Steps
The usual manner for preparing an APEX model run is to start with an existing application and
modify it as necessary (e.g., change simulation settings, input file content, or output file names).
Because there are many different ways to run APEX, there is no single list of steps that will work
for every analysis. Users should always review the Params file (when running APEX in DOS
batch mode) or the settings in the MIMS scenario (when running APEX in MIMS) to ensure the
file locations and simulation settings are correct. The key factor in determining the effort
required to prepare an analysis, however, is the degree to which the remaining input files need
to be modified. In light of this, APEX applications can be grouped into two categories: standard
and advanced.
Standard applications are designed to use the national-scale input database files accompanying
APEX, to the extent possible. That is, these applications define sectors as census tracts, define
the age groupings as in the accompanying data files, and use the profile functions, commuting
data, population data, dose input data (if dose is modeled), microenvironment mapping, and
CHAD activity data provided with APEX. These settings are defined in the following input files:
• Sector Location file;
• Population Data files;
• Employment by Age Group file;
• Commuting file;
• Activity-specific MET file;
DRAFT—APRIL 24, 2003
43
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• Physiological Parameter file;
• Profile Functions file
• Microenvironment Mapping file;
• Personal Info file; and
• Diary Events file.
Thus, for the first run of a standard application for a given study area, pollutant, etc., the user
generally would only need to edit or create the following input files (in addition to the Params file
or settings in the MIMS scenario):
• District Location file;
• Temperature Zone Location file;
• Temperature Data file;
• Air Quality Data file;
• Profile Functions file;
• Micro Mapping file; and
• Microenvironment Descriptions file.
Subsequent runs for the same study area, pollutant, etc. could involve as little as a single
parameter change (e.g., the simulation start or stop dates) in the Params file (when running
APEX in DOS batch mode) or in the MIMS GUI (when running APEX in MIMS) - the most basic
standard application - or could involve changes in all of the same input files edited as indicated
above for the first run. Figure 4-2 contains a flow chart that describes each of the steps a user
must complete to configure and perform a standard APEX simulation.
Advanced applications involve modifying or replacing the national-scale input database files
accompanying APEX. These types of applications allow the user to perform analyses that are
specifically tailored to unique needs, such as use in a country other than the U.S. or using a
finer (or coarser) spatial resolution. Depending on the application, the user may need to edit or
replace all of the input data files. The steps required for an advanced application depend on
how much the application deviates from a standard application. Users should be aware that
advanced applications can require significantly more time to develop input data.
4.4 Overview of Input and Output Files
This section provides a brief overview of the input and output files associated with APEX. (For
more detailed descriptions of the input and output files, refer to Chapters 5 and 6, respectively.)
All of the input and output files used by APEX are ASCII text files, which allows them to be read
and/or modified by the user using any text editor. Note, however, that certain files, such as the
commuting input file and possibly the exposure and dose output files, may be very large (over
100 megabytes) and difficult for some text editors to handle.
DRAFT—APRIL 24, 2003
44
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Figure 4-2. Steps for Setting up a "Standard" APEX Simulation
Start and end dates
pararns
Study area name,
centroid, radius,
altitude, and
(optionally) list of
counties
Max distance to
nearest air district
Max distance to
nearest
m eteorological
station
Number of profiles
Max number of
microenvironmenls
Locations of input
and output files
Pollutant name.
Include commuting,
Estimate dose, Use
DST, Output units,
and Output table
levels
Identify modeling
period
Identify study area
Identify air districts
Prepare air quality
data
Identify
meteorological
stations
Prepare
temperature data
Select number of
profiles
Define profile
functions
f Update mapping
f between MEs and
V activity data
Define
microenvironments
Air
district
locations
Hourly air
concentrations
Meteorological
station
locations
district
location
air quality
daia
temperature
zone location
Daily
temperature
temperatures
data
Profile
functions
profile
functions
M icroenvironm ent _
mapping
M icroenvironm ent
descriptions
microenvironment
mapping
microenvionment
descriptions
Specify input and \
output file locations J
LEGEND
Set remaining \
modeling options j
o
User Action
APEX Input File
Run APEX
DRAFT—APRIL 24, 2003
45
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4.4.1 Input Files
There are 16 types of input data files required by APEX. Table 4-1 lists each file type and a
brief description of the content of the file. With the exception of the population data file type,
there is only one input file per input data type. When APEX is run in DOS batch mode, the
Params file will typically be edited prior to each simulation. When running APEX in MIMS, the
user will edit the inputs and settings for each simulation in the MIMS GUI and the model will
create the Params file based on the provided information. The remaining input data files may
need to be edited for a particular simulation depending on the type of application (i.e., standard
or advanced) and the options selected for the simulation (e.g., commuting, dose estimates).
(Table 4-3 in Section 4.5 provides an explanation of the input data file changes required with
changes to the different model options.)
Note that several of the APEX input files use a "keyword" approach. APEX processes these
files and searches for particular keywords followed by an equal sign and one or more values for
the keyword. Chapter 5 provides a detailed description of the keyword approach and its syntax.
4.4.2 Output Files
There are seven types of output files from APEX. Table 4-2 lists each of the output data files
and a description of the content of the file. The names and locations, as well as the output table
levels (e.g., output percentiles, cut-points) for these output files, are specified by the user in the
Params file (when running APEX in DOS batch mode) or in the MIMS GUI (when running APEX
in MIMS). If an output file is specified with the same name and location as an existing file, the
old files are overwritten. Therefore, if the user wishes to conduct a series of model runs, the
output files for each run should be named differently or the output should be copied elsewhere
before the next model run is submitted.
4.5 Overview of Model Settings and Options
This section describes the settings and options available in APEX. There are five general
categories of settings and options in APEX:
• General Model Settings and Options;
• Study Area Location;
• Profiles;
• Microenvironments; and
• Outputs.
Table 4-3 describes all of the settings and options in each of these categories, how the settings
and options are selected or changed, and the impact of changing a setting or option on the
other input files. Note that the impact of these settings and options on input files should be
distinguished from the changes in certain input files that may significantly affect other input files
(e.g.. the effect that changes in Population Data would have on Commuting Flow). As many of
the settings and options impact multiple APEX input files, it is important for the user to pay close
attention to the impacts that changing the various settings and options can have on the different
input files. The table includes the settings and selected options in the input data files
accompanying APEX to help the user understand the settings for a standard application and
DRAFT—APRIL 24, 2003
46
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Table 4-1. Overview of APEX Input Files
Input File Name
Description
Params
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). This file is the simulation control file and is the input file
most often changed by the user.
Sector Location*
Contains the sector IDs and locations (in degrees latitude and longitude) for each
sector.
Population Data*
Contain the number of people in each age range for each sector ID. There must
be one Population Data file for each gender/race combination included in the
simulation.
District Location
Includes the site ID and location (in degrees latitude and longitude) for each air
quality monitoring/modeling location included in the simulation.
Temperature Zone
Location
Includes the site ID and location (in degrees latitude and longitude) for each
meteorological station included in the simulation.
Employment by
Age Group*
Specifies the age group ranges included in the population files and the probability
of employment associated with each age group.
Commuting Flow*
Contains the probabilities of a worker commuting to different destination sectors
from any given home sector. This file is only required when worker commuting is
modeled.
Temperature Data
Contains the daily maximum and optionally average (or other) temperature data
for the meteorological stations and dates indicated in the Temperature Zone
Location file.
Air Quality Data
Contains the hourly air concentrations for the modeled pollutant for the
monitoring/modeling locations and dates indicated in the District Location file.
Activity-specific
MET*
Provides distributional shapes and parameters for calculating a metabolic (MET)
value for each activity code in the Diary Events file.
Physiological
Parameters*
Provides tables of physiological parameters (e.g., body mass) used in calculating
dose.
Profile Functions
Contains user-defined functions that define probabilities that simulated individuals
will have particular characteristics (e.g., probability a simulated individual will have
air conditioning at home).
Microenvironment
Mapping
Links the diary events location codes to the APEX microenvironments in the Micro
Descriptions file.
Personal Info*
Contains information relating to each 24-hour activity diary (e.g., day type, gender,
age, race, occupation) from the Diary Events file.
Diary Events*
Contains the event descriptions (i.e., start time, duration, activity, and location) for
all of the diary days in the activity database (e.g., CHAD).
Microenvironment
Descriptions
Contains the definitions of the APEX microenvironments referenced in the Micro
Mapping file.
* The input file of this type that accompanies APEX contains data that can be applied to any study area in
the United States and would only be edited or replaced for an Advanced application.
DRAFT—APRIL 24, 2003
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Table 4-2. Overview of APEX Output Files
Output File Name
Description
Log
The Log file contains the record of the APEX model simulation as it progresses.
If the simulation completes successfully, the log file indicates the input files and
parameter settings used for the simulation and reports on a number of different
factors. If the simulation ends prematurely, the log file contains error messages
describing the critical errors that caused the simulation to end.
Hourly Exposure
The Hourly Exposure file provides an hour-by-hour time series of exposure
estimates for each modeled profile.
Hourly Dose
The Hourly Dose file provides an hour-by-hour time series of dose estimates for
each modeled profile, if doses are modeled.
Profile Summary
The Profile Summary file provides a summary of each profile modeled in the
simulation.
Microenvironment
Summary
The Microenvironment Summary file provides a summary of the time and
exposure by microenvironment for each profile modeled in the simulation.
Sites
The Sites file lists the sectors, districts, and zones in the study area, and
identifies the mapping between them.
Output Tables
The Output Tables file contains a series of tables summarizing the results of the
simulation. The percentiles and cut-off points used in these tables are defined
in the Params file.
how deviating from these settings can significantly increase the effort required to setup the
required input files. Throughout this table, "keywords" (or variables or parameters) are
referenced in indicating how different options can be selected. See Chapters 5 and 6 for
additional details on the keywords and input files, how to change them, and how they interact
with other keywords and files. Also, see Section 1.3.2 for limitations on the use of this model,
especially in terms of the number of setting options it has available.
DRAFT—APRIL 24, 2003
48
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
GENERAL MODEL SETTINGS AND OPTIONS
Simulation start/end dates
Specified in YYYYMMDD format (e.g., 19960704 is July 4,
1996) using the STARTDATE and END DATE keywords in
the Params file. The user must define the appropriate start
and end dates for an application.
The indicated start and end dates must be included in the date
ranges included in the District Location, Temperature Zone
Location, Temperature Data, and Air Quality Data files. These
files may contain additional data before and/or after the start
and end dates, but must contain data for the entire period
between the specified start and end dates.
Adjust for Daylight Saving
Time (DST)
Specified using the DSTADJUST keyword in the Params file.
If this parameter is set to "YES", then the Air Quality Data file
will be adjusted for DST in the summer; if it is set to "NO", no
adjustment is made. This keyword should be set to "YES" if
the Air Quality Data file is based on Standard Time yet the
activity data are based on DST.
Changing this setting means that the Air Quality Data file is
based on DST (it typically is in Standard Time) or that the
activity data are based on Standard Time (the supplied CHAD
data are based on DST). Regardless of this setting, the output
(hourly exposure and dose) for all simulated days will contain
exactly 24 hours, and all input activity diaries must contain
exactly 24 hours.
Model worker commuting
Specified using the COMMUTING keyword in the Params file.
If this keyword is set to "YES", commuting to work is allowed
and the user must provide a Commuting Flow file in the
appropriate format and employment status must be specified
in the Employment by Age Group file; if it is set to "NO", all
workers are assumed to work at home and the user is not
required to provide a Commuting Flow file. If employment
status is not specified in the Employment by Age Group file,
commuting will not be modeled, regardless of the
COMMUTING keyword setting in the Params file. The
Commuting Flow file accompanying APEX contains
commuting flows between all census tracts from the 2000
Census. These commuting data are sufficient for all
applications where the sectors are defined as census tracts.
If the user changes the value of the COMMUTING keyword to
"NO", there are no additional changes required. Ifthe user
chooses to use sectors other than census tracts, a new
Commuting Flow file(in addition to a number of other input files)
must be created corresponding to the new sectors.
DRAFT—APRIL 24, 2003
49
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options (continued)
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
Model exposure dose
Specified using the DODOSE keyword in the Params file. If
this keyword is set to "YES", the model will create the hourly
dose file; if it is set to "NO", the dose calculations will be
suppressed and the hourly dose file will not be created. If
DODOSE is set to "YES", the user must specify the correct
values for the ALTITUDE, COHBFACT, and COTHRESH
keywords in the Params file. Regardless of the setting for
DODOSE, the user must provide the Activity-specific MET and
Physiology Data files; however, if DODOSE is set to "NO," the
content of these files does not impact the results.
The Activity-specific MET file accompanying APEX must be
changed if (1) the underlying MET distributions in the CHAD
database are changed or (2) activity data other than that
provided in the CHAD database are used. The user may edit
or replace the Physiology Data file provided with APEX,
provided the new or revised file is in the appropriate format.
Air quality rollback
adjustment (for estimating
exposure in hypothetical
control scenarios)
Specified using the ROLLBACK keyword in the Params file.
If this keyword is set to "YES", the user must specify
appropriate values for the RBTARGET, RBBACKGND , and
RBMAX keywords in the Params file; if it is set to "NO", values
are not required for these keywords (and any present will be
ignored).
If the ROLLBACK keyword is changed to "YES" in the Params
file accompanying APEX, the RBTARGET, RBBACKGND ,
and RBMAX keywords must be set to appropriate values.
STUDY AREA LOCATION
Center of study area
Specified as the latitude and longitude of the center of the
study area in decimal degrees using the LATITUDE and
LONGITUDE keywords in the Params file. The user must
always define the appropriate study area center for an
application.
If the study area is changed, the user must ensure that the
following files contain appropriate data for the new location:
Sector Location file (unless the included file is used), District
Location file, Temperature Zone Location file, Temperature
Data file, and Air Quality Data file.
Radius of study area
Specified as the distance (in km) from the center to the edge
of the study area using the CITYRADIUS keyword in the
Params file. The user must always define the appropriate
study area radius for an application.
If the study area is changed, the user must ensure that the
following files contain appropriate data for the new location:
Sector Location file (unless the included file is used), District
Location file, Temperature Zone Location file, Temperature
Data file, and Air Quality Data file.
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50
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options (continued)
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
Restrict study area to
selected counties
Specified using the COUNTYLIST keyword in the Params file.
If the value of this keyword is set to "YES", the user must list
the FIPS code (or other relevant portion of the sector ID if the
supplied sector files are not used) for the counties to which the
study area will be restricted using the COUNTY keyword in the
Params file. The county IDs for all census tracts in the 2000
Census are included in the Sector Location file accompanying
APEX, thus allowing the user to select counties in the Params
file without making changes to the included Sector Location
file.
If the user does not use the included Sector Location file, they
must ensure that the new Sector Location file provides the
county ID for each sector as part of the sector ID in the
appropriate format.
Locations of sectors
Specified as sector IDs and locations (latitude and longitude)
in the Sector Location file. The Sector Location file
accompanying APEX use the census tracts from the 2000
Census as sectors. This file also specifies the county
associated with each sector (via the first five characters of the
sector ID, which are the county FIPS codes in the supplied
data), which allows the user to restrict the study area to
selected counties. In most cases, the user will not need to
change this setting as it provides sectors with the necessary
population and commuting data for the entire United States.
Sectors identified in Sector Location file must match the sectors
identified in Population Data files. If the user wishes to use
census tracts from the 2000 Census, the Sector Location file
accompanying APEX will be sufficient. All of the sectors used
in the commuting file must be included in the Sector Location
file and the Population Data files; if sectors other than 2000
Census tracts are used, the user must provide a Commuting
file compatible with these sectors. In addition, if the user wants
to restrict the study area to selected counties, the Sector
Location file must include the county IDs associated with sector
as part of the sector IDs in the proper format (as in the supplied
file).
Locations of air districts
Specified in the District Location file. The user must always
define the appropriate air districts for an application. The user
must always define the appropriate air districts for an
application.
The locations of the air districts must be selected such that they
can provide reasonable estimates of air quality for the sectors
and study period included in the analysis.
Radius of air district
Using the AIRRADIUS keyword in the Params file, the user
can specify the maximum distance (in km) that a sector can be
from the nearest air district to remain in the study. If all district
centers are further than AIRRADIUS from the sector center,
the sector is removed from the study area and is not modeled.
Users must always define an appropriate value for this
keyword based on their application.
The radius of the air districts must be selected such that they
will include the sectors the user would like to include in the
analysis.
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options (continued)
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
Location of meteorological
data stations
Specified as zone IDs and locations (latitude and longitude) in
the Temperature Zone Location file. In the absence of a
national database of temperature data, the user must always
define the location(s) of meteorological stations for an
application.
Temperature data for each meteorological data station
specified in the Temperature Zone Location file must be
provided in the Temperature Data file.
Radius of meteorological
station coverage
Using the ZONERADIUS keyword in the Params file, the user
can specify the maximum distance (in km) from a sector to the
nearest meteorological station. If all zone centers are further
than ZONERADIUS from the sector center, the sector is
removed from the study area and is not modeled. Users must
define an appropriate value for this keyword based on their
application.
The radius of the zones must be selected such that they will
include the sectors the user would like to include in the
analysis.
PROFILES
Number of profiles
Set to an integer using the ifPROFILES keyword in the
Params file. Users must define an appropriate value for this
keyword based on their application.
None.
Modeled populations
Specified in the Params file following the specification of the
file names. The user must provide a population file for each
population to be modeled and indicate the gender and race
associated with the file. All gender/race combinations without
specified population files are assumed to have zero
populations. Users can select from the sets of available
Population Data files accompanying APEX (i.e., the national
population files or the files specific to the Houston example
applications), or generate their own.
If the user wishes to model a subpopulation, the user must
supply alternative Population Data files with the appropriate
counts. The sector IDs in these population files must
correspond to sector IDs provided in the Sector Location file.
Profile function options
The existing profile functions can be edited by the user in the
Profile Functions file. This file can also be edited by the user
to add new functions. The Profile Functions file
accompanying APEX contains nine functions that can be
edited by the user as necessary for an application.
None, if the user edits one of the existing functions.
Employment status
Specified in the Employment by Age Group file for
implementation of commuting. The Employment by Age
Group file accompanying APEX should be sufficient for all
applications where sectors are defined as census tracts.
None.
DRAFT—APRIL 24, 2003
52
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options (continued)
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
Minimum and maximum
ages for simulated profiles
Specified using the AGEMIN and AGEMAX keywords in the
Params file.
None.
Modeled age groups
Specified in the Employment by Age Group file. The
Employment by Age Group file accompanying APEX defines
the age groups as single years up to 99 and three groups
beyond, and thus should be sufficient for all applications
where sectors are defined as census tracts.
The age groups specified in the Employment by Age Group file
must match the age groups used in the Population Data files. If
the user wishes to change the age groups in the Employment
by Age Group file, the associated changes must also be made
to the Population Data files.
Size of age window
The AGECUTPCT and AGE2PROBAB keywords in the
Params file are used to specify the window around the
assigned age of a profile from which activity data can be
selected.
None.
Probabilities for selecting
diaries with missing
characteristics
Using the MISSGENDER, MISSEMPL, and MISS AGE
keywords in the Params file, the user can specify the
probability that activity diary data with missing gender,
employment status, or age will selected.
None.
MICROENVIRONMENTS
Maximum number of micro-
environments
Set to an integer using the #MICRO keyword in the Params
file; must not exceed 127.
Number of APEX microenvironments in the Microenvironment
Mapping and Microenvironment Descriptions files must not
exceed the specified value in the Params file
Microenvironment
definitions
Specified in the Microenvironment Descriptions file. The user
must develop data relevant to a particular application prior to
performing an APEX simulation.
Each location referenced in the activity database (e.g., CHAD)
must be mapped to one of the microenvironments specified in
the Microenvironment Descriptions file using the
Microenvironment Mapping file.
OUTPUTS
Produce hourly outputs
Specified using the HOURLYOUT keyword in the Params file.
If this keyword is set to "YES", the hourly exposure and dose
(if applicable) output files are created; if it is set to "NO", these
files are not created.
None.
DRAFT—APRIL 24, 2003
53
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Table 4-3. Description of Steps and Implications Involved in Changes to APEX Settings and Options (continued)
Setting/Option
How Option is Selected
Impact of Changing Default Setting
on Other Input Files
Output table levels
Specified using the following keywords in the Params file:
PERCENTILES, EXPTIME, DM1HEXP, DM8HEXP,
DAVGEXP, ANNEXP, DM1HDOSE, DM8HDOSE,
H EHDOSE, DMEHDOSE, DAVGDOSE, ANNDOSE, and
DOSETIME. These keywords are described in detail in
Chapter 5.
None.
DRAFT—APRIL 24, 2003
54
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5. INPUT FILES
This chapter provides the details necessary for accessing, creating, and modifying, as needed,
the APEX input files. Addressed are input file format, the Params (or control) input file, and the
population and other input files. The user should have a general understanding of how the
APEX model works (from Chapter 2) and a clear understanding of the relationships between the
various input files (from Chapter 4—in particular Table 4-3) before using this chapter.
5.1 Input File Formats
APEX requires the following input files to run:
• A parameters file;
• 14 other input files; and
• A population file for each combination of gender/race to be modeled.
All input files are "ASCII text" files that can be edited on a text editor such as Notepad. 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 Params file to indicate to
APEX where the input files are located and what values should be assigned to certain
variables. A keyword line always contains an "=" sign. The part of the line to the left of "="
is called the "keyword" and the part to the right is called the "value." The keyword must start
with a letter and must match the spelling sought by the program code, after which the
keyword may contain other letters, blanks, or commas. APEX uses the keyword to locate
and set the input values. The values may be character, logical, or numeric values, or file
names.
2. Numeric line: Any line beginning with a digit (0-9) is recognized as a numerical data line by
APEX. Non-digits may appear later in a numeric line.
3. Character line: A line that begins with a character but does not contain an "=" sign is
recognized as a character data line.
4. Comment line: Any blank lines and any lines beginning with "!" generally are regarded as
comment lines by APEX and used only by the user to help document the input file data.
Comment lines inserted in the middle of a block of data, however, can be unpredictable.
That is, if the computer code is expecting to read a long series of numbers without a break,
then comments may break the flow. If in doubt, use comments only where they are used in
the supplied input files.
The keywords and input values are not case sensitive. 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
most input values (the Physiological Parameters input file—Section 5.11—is the exception).
This means that the values or data do not have to be fixed in specific positions on an input line.
Multiple items on an input line can be separated by either a blank or comma. The various site
names and similar inputs, however, should not contain internal blanks, as these will be
interpreted as delimiters between input fields. This does not apply to keyword lines, as those
DRAFT—APRIL 24, 2003
55
-------
lines have only two fields (separated by the "=" sign), so either or both sides may contain
internal blanks.
The following sections discuss the details of APEX input files and provide several examples.
Note that these example files in this and the next chapter are provided for illustration only! They
have been developed solely for the purpose of highlighting various aspects and options of
APEX. These example files are not necessarily related to each other nor to the supplied data
files that can be downloaded separately from this user's guide. In many cases these examples
are only portions of the necessary input files. Thus, these example files will not work as an
actual set of input files. Users are encouraged to view the EPA-supplied input files
(downloaded separately) for a complete and related set of input files. Also, Volumes III and
IV—which provide APEX case studies—are associated with complete and related sets of input
(and output) files.
5.2 Params File (Unit 10)
The parameter, or Params, file is APEX's
simulation control file. The Params file
names input and output files, sets model
parameters, and controls formats of output
files. APEX only processes keyword lines in
this file. Any other types of input lines are
ignored. As described in Chapter 4, the
Params file is created or modified directly by
the user when running APEX in DOS batch mode. Conversely, when running TRIM.ExpO|nhaiation,
the Params file is created or modified automatically based on the parameter settings provided
by the user in the TRIM.ExpO|nhaiation GUI. Although the remainder of this section is written from
the perspective of a user configuring a Params file to run APEX in DOS batch mode, users can
refer to the keyword tables in this section (i.e., Tables 5-1 through 5-4) for a description of how
the TRIM.Expolnhalation parameters relate to the keywords in the Params file. That is, each of
these tables contain a column titled "TRIM.Expo-lnh Parameter Name" that indicates the
parameter name in TRIM.Expolnhalation that corresponds to the keyword in the Params file. With
this information, users can determine how to set the parameter values in the TRIM.ExpO|nhaiation
GUI.
When accessing in DOS batch mode, the following rules should be used:
• Keywords (or parameters or variable names) are placed to the left of the equal sign in a
keyword line;
• Parameter values are to the right of the equal sign;
• Lines may appear in any order;
• Lines may be omitted if defaults are acceptable;
• Only one equal sign allowed per keyword line;
• Anything after an exclamation mark in a line is ignored; and
• Any line without an equal sign is ignored.
To ensure that the keywords are input properly, the user may want to use the example file as a
template. The user only needs to change values to the right of the "=" sign on the key word line.
An example of the Params file is provided in Figure 5-1.
Tip. Keep a copy of the Params file associated
with each simulation to provide a record of the
input and output files and model settings
associated with the simulation and to make it
easier to run the model again based on different
input data.
DRAFT—APRIL 24, 2003
56
-------
Figure 5-1. Example of Params File3
INPUT FILES:
sectors file
= C:\APEX3\input\tp geo.txt
districts
file
= C:\APEX3\input\districts houston61.txt
zones file
= C:\APEX3\input\zones houston.txt
employment
file
= C:\APEX3\input\employment.txt
commuting
file
= c:\APEX3\input\comm2000.txt
temperature file
= C:\APEX3\input\temperatures houston.txt
air quality file
= C:\APEX3\input\APEXHoustonAir61.txt
metabolic
file
= C:\APEX3\input\CHADMets.txt
physiology
file
= C:\APEX3\input\Physiology.txt
distribution file
= C:\APEX3\input\distrib houston.txt
microenv.
file
= C:\APEX3\input\MP houston.txt
diaryevent
file
= C:\APEX3\input\CHADEvents.txt
diarysum file
= C:\APEX3\input\CHADQuest.txt
diarymap file
= C:\APEX3\input\micromap34.txt
POPULATION FILES:
pop file,
Female,
White = C:\APEX3\input\tp FW.txt
pop file,
Female,
Black = C:\APEX3\input\tp FB.txt
pop file,
Female,
Asian = C:\APEX3\input\tp FA.txt
pop file,
Female,
NatAm = C:\APEX3\input\tp FN.txt
pop file,
Female,
Other = C:\APEX3\input\tp FO.txt
pop file,
Male,
White = C:\APEX3\input\tp MW.txt
pop file,
Male,
Black = C:\APEX3\input\tp MB.txt
pop file,
Male,
Asian = C:\APEX3\input\tp MA.txt
pop file,
Male,
NatAm = C:\APEX3\input\tp MN.txt
pop file,
Male,
Other = C:\APEX3\input\tp MO.txt
OUTPUT FILES
log file
= C:\APEX3\output\log.txt
exposure file
= C:\APEX3\output\exp.txt
dose file
= C:\APEX3\output\dose.txt
persons file
= C:\APEX3\output\psum.txt
microsum file
= C:\APEX3\output\msum.txt
tables file
= C:\APEX3\output\tablesb.txt
sites file
= C:\APEX3\output\sites.txt
PARAMETER SETTINGS:
pollutant
= Benzene
inputunit
= ppm
outputunit
= ppm
location
= Houston
scenario
= test
#profiles
= 20
#micros
= 4
(sources
= 3
start date
= 19960101
end date
= 19961231
Latitude
= 29.75533
Longitude
= -95
18716
CityRadius
= 20
AirRadius
= 0.5
ZoneRadius
= 300
DRAFT—APRIL 24, 2003
57
-------
Figure 5-1. Example of Params File (continued)
CountyList
=
YES
County
=
48201
County
=
48157
Commuting
=
YES
AgeMin
=
0
AgeMax
=
99
DSTadj ust
=
YES
HourlyOut
=
NO
DoDose
=
NO
rollback
=
NO
RBtarget
=
5.0
RBbackgnd
=
0.0
RBmax
=
10.0
PPMFact
=
1145 .
MissGender
=
0.1
MissEm.pl
=
0.1
MissAge
=
0.1
AgeCutPct
=
25.0
Age2Probab
=
0.1
Altitude
=
90
COHbFact
=
2.5
COThresh
=
100.
DebugLevel
=
0
Randomseed
=
547862400
OUTPUT TABLE LEVELS:
Percentiles
=
10, 25, 50, 75,
90, 95, 99
TimeEXP
=
2, 4,
6, 8, 10,
15, 20, 25,
30, 35, 40, 45, 50, 60
DMIHExp
=
5, 10
, 20, 30,
40, 50, 75
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
DMIHDose
=
0.5,
1.0, 1.25,
1.5, 1.75,
2.0, 2.25, 2.5, 2.75, 3.0,
4.0,
5.0,
6.0
DM8HDose
=
0.5,
1.0, 1.25,
1.5, 1.75,
2.0, 2.25, 2.5, 2.75, 3.0,
4.0,
5.0,
6.0
H EHDose
=
0.5,
1.0, 1.25,
1.5, 1.75,
2.0, 2.25, 2.5, 2.75, 3.0,
4.0,
5.0,
6.0
DMEHDose
=
0.5,
1.0, 1.25,
1.5, 1.75,
2.0, 2.25, 2.5, 2.75, 3.0,
4.0,
5.0,
6.0
DAvgDose
=
0.5,
0.75, 1.0,
1.25, 1.5,
1.75, 2.0, 2.25, 2.5, 2.75,
, 3.0,
. 4.0,
, 5.0
SavgDose
=
0.4,
0.5, 0.6,
0.7, 0.8, 0.
9, 1.0, 1.2, 1.4, 1.6, 1.8,
, 2.0,
. 2.5
TimeDose
=
0.5,
1.0, 1.25,
1.5, 1.75,
2.0, 2.25, 2.5, 2.75, 3.0,
4.0,
5.0,
6.0
a Note that COHbFact and COthresh parameters are needed only for CO dose calculation. For other pollutants,
DoDose should be set to NO. APEX currently only includes dose algorithms for CO.
There are five sections in this example (these same sections are recommended for all Params
files): input file, population files, output files, parameter settings, and output table levels. The
details of each section are discussed below.
5.2.1 Input and Output File List Sections of Params File
In the Input File section of the parameter file, the user needs to specify the names and path
names of 14 non-population input files. Table 5-1 provides a brief description of these files.
For a new scenario or standard application, the user needs to modify or replace the files of units
12, 13, 16, and 17. (See the introduction to Chapter 4 for a description of "Unit number"
DRAFT—APRIL 24, 2003
58
-------
Table 5-1. Input Files for APEX Model3
Input File
Keyword
APEX in MIMS
Parameter
Name
Unit
#
Uses
Sector Location
SECTOR
Input File -
Sector
Locations
11
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.
District Location
DISTRICT
Input File -
District
Locations
12
Provides the site IDs and locations (degrees
latitude and longitude) of air quality
monitoring or modeling locations. The file is
used along with the user-defined AirRadius
to define the geographical area covered by
the air quality data. The air quality data from
a monitoring or modeling location are used for
the sectors (e.g., census tracts) within its
covered area. Start and end dates indicate
the dates during which the data for a
particular location are valid.
Temperature
Zone Location
ZONE
Input File -
Meteorological
Zone Locations
13
Provides the site IDs and locations (degrees
latitude and longitude) of the meteorological
stations. The file is used along with the user-
defined ZoneRadius to determine the area
covered by the temperature data. Start and
end dates indicate the dates during which the
data for a particular location are valid.
Employment by
Age Group
EMPLOYMENT
(or
AGEGROUP)
Input File -
Employment
14
Provides a list of probabilities of employment
for each age group in the Population Data
Input files. The probabilities are used to
determine if a simulated person (i.e., a profile)
will commute to another census tract to work.
Commuting Flow
COMMUT
Input File -
Census
Commuting
Flow
15
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.
Temperature Data
TEMPER AT
Input File -
Temperature
Data
16
Contains the daily maximum and optionally
average (or other) temperature data for the
meteorological stations and dates indicated in
the Temperature Zone Location file.
Temperature is used to determine window
positions and group activity pattern pools in
APEX.
Air Quality Data
QUALITY
Input File - Air
Quality Data
17
Provides the hourly air quality data for the
modeled pollutant for each air
monitoring/modeling location listed in the
District Location file.
DRAFT—APRIL 24, 2003
59
-------
Table 5-1. Input Files for APEX Model3 (continued)
Input File
Keyword
APEX in MIMS
Parameter
Name
Unit
#
Uses
Activity-specific
MET
METABOL
Input File -
Activity
Specific METS
18
Provides distribution types and parameters for
calculating the metabolic (MET) value for
each activity code in the Diary Events file. A
MET value is a dimensionless ratio of the
activity-dependent energy expenditure rate to
the basal or resting energy expenditure
(metabolic) rate. This file is used for
calculating dose, not exposure
concentrations. It is needed for running
APEX even if the dose calculation is turned
off.
Physiological
Parameters
PHYSIOL
Input File -
Physiological
Parameters
19
Provides tables of certain physiological
parameters (e.g., body mass) by age and
gender. The file is used for calculating dose,
not exposure concentrations. It is needed for
running APEX even if the dose calculation is
turned off.
Profile Functions
DISTRIB
Input File -
Profile
Functions
20
Provides the definitions of the following user-
definable functions:
MaxTempCat - Binning daily 1-hour
maximum temperatures into categories
AvgTempCat - Binning daily mean
temperatures into categories
DiaryPools - Assigning diary pools using day
of week, MaxTempCat, and AvgTempCat
IDGRP - Group number for output labeling not
used in internal calculation
HasGasStove - Define probability of having
gas stove in a residence
HasPilot- Probability of having a pilot light,
based on HasGasStove
ACHome - Probability of having air
conditioning at home
AC Car- Probability of having air
conditioning in a car
WindowPos - Probability of windows open or
closed, based on AC Home, MaxTempCat,
and AvgTempCat
SpeedCat- Probability of average car speed
categories
Microen vironment
Mapping
DIARYMAP
Input File -
Microenvironm
ent Mapping
21
Provides the mapping from activity location
codes in Diary Events (e.g., from CHAD) to
user-defined microenvironments in Micro
Descriptions.
Personal Info
DIARYSUM
Input File -
Personal Info
22
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).
DRAFT—APRIL 24, 2003
60
-------
Table 5-1. Input Files for APEX Model3 (continued)
Input File
Keyword
APEX in MIMS
Parameter
Name
Unit
#
Uses
Diary Events
DIARYEVE
Input File -
Diary Events
23
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 Personal Info file,
in the same order.
Microen vironment
Descriptions
MICROENV
Input File -
Microenvironm
ent
Descriptions
24
Contains the definitions of the
microenvironments and the microenvironment
factors used to determine the exposure
concentrations in user-defined
microenvironments.
a Other than Params and Population Data files.
and how it is used by APEX; see the tables below for which input and output files have been
assigned which unit number.) If the user wants to redefine the set of microenvironments, the
files of units 21 and 24 should also be changed. Similarly, the user may want to redefine the
various distributions used in APEX (unit 20). The details of these input files are provided in the
subsequent sections of this chapter.
Note that 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 14 files are not found at the specified locations,
then APEX will prompt the user for the pathname of the missing file using the unit #.
In the Output File section of the Params file, the user needs to specify the names and path
names of six and optionally seven output files. If the user turns off the dose calculation, hourly
exposure, or dose outputs, the corresponding output files will not be created. Table 5-2
describes the output files. The details of these output files are further explained in Chapter 6.
5.2.2 Population Files Sections of Params File
In the Population Files section of the Params file, the user needs to specify the names and path
names of either the 10 supplied Population Data files or any Population Data files the user
creates. The number of population files could change, depending on how the user classifies the
population.
Similar to the other input files, the keywords POP and FILE must appear at the beginning of the
keyword part of the keyword input line in Params, followed by a comma and Gender and
another comma and Race. Gender must be either male or female and it can be shortened to
M or F. Currently, to correspond to the supplied data, the races must be White, Black, Asian,
NatAm, or Other, which may be shortened to W, B, A, N, or O. It is not necessary to specify all
genders and race combinations for APEX to run. However, the model assumes that any
missing gender/race combinations have zero population and it does not give any warning
messages.
DRAFT—APRIL 24, 2003
61
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Table 5-2. Output Files for APEX Model
Output file
Keyword
APEX in MIMS
Parameter Name
Unit#
Description
Log
LOG
Output File - Log
25
Contains the record of the APEX model
simulation as it progresses. Ifthe
simulation completes successfully, the log
file indicates the input files and parameter
setting used for the simulation, reports the
number of diaries available to match each
individual simulation, provides the total
runtime of the simulation, reports
statistical summaries for the simulated
individuals, and includes a series of
summary tables, identical to those found
in the Output Tables file. Ifthe simulation
ends prematurely, the log file contains
error messages describing the critical
errors that caused the simulation to end.
Hourly Exposure
EXPOSURE
Output File -
Hourly Exposure
Estimates
26
Provides an hour-by-hour time series of
exposure estimates for each modeled
profile.
Hourly Dose
DOSE
Output File -
Hourly COHb Dose
Estimates
27
Provides an hour-by-hour time series of
dose estimates for each modeled profile.
Personal
Summary Data
PERSON
Output File -
Person Summary
28
Provides a summary of each profile
modeled in the simulation.
Microen viron merit
Summary
MICROSUM
Output File -
Microen vi ron ment
Summary
29
Provides a summary of the time and
exposure by microenvironment for each
profile modeled in the simulation.
Summary
Tables
TABLE
Output File -
Tables
30
Contains a series oftables summarizing
the results of the simulation. The
percentiles and cut-off points used in
these tables are defined in the Params
file.
Sites
SITES
Output File - Site
Mapping
31
The Sites file lists the sectors, districts,
and zones in the study area, and
identifies the mapping between them.
Each Population Data file used in a model run must have exactly the same format and a record
for each sector listed in the sector location file. Each record has the Sector ID, followed by a
Count for each population age group (youngest first). The number of age groups and their age
ranges are provided in the Employment by Age Group file (Unit 14). The counts are the number
of a given age group of people living in the sector.
Ten gender/race specific population data files for all 65,443 Year 2000 Census tracts have been
prepared and provided with APEX. These population files should be adequate for most
purposes. Figure 5-2 provides an example of a portion of a Population Data File. The first
column, sector ID, is the census tract FIPS code. The 23 numbers that follow are the
population counts for each of the 23 defined age groups starting with the youngest.
DRAFT—APRIL 24, 2003
62
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Figure 5-2. Example Portion of Population Data File ("Wrapped" View)
01001020100
44
75
79
52
18
13
7
32
60
61
90
87
68
70
56
18 23
14
19
23
17
7
15
01001020200
77
86
61
42
25
17
9
47
76
68
60
86
71
73
51
24 19
19
21
34
21
17
23
01001020300
130
125
141
75
41
12
21
53
117
134
155
139
106
91
80
32 44
31
35
68
48
46
76
01001020400
129
172
166
87
60
24
21
52
121
144
196
191
145
150
146
58 114
63
73
115
70
38
39
01001020500
239
281
241
138
57
20
23
84
195
205
394
282
206
188
141
54 65
33
53
58
54
41
16
5.2.3 Job Parameter Settings Section of Params File
In the Job Parameter Settings section of the Params file, the user can specify a number of
different job parameters for APEX runs. Table 5-3 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 Params input line that is necessary to allow APEX to identify the parameter. Data type is
either integer (I), real (R), or character (C)). 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 except County, if the same keyword appears more
than once, the last occurrence overwrites the others.
Table 5-3. Job Parameters in APEX Params File
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
Pollutant
POLL
Pollutant
C(40)
Pollutant name (for output only; not
used internally).
In Units
INPUTUNIT
Input
Concentration
Units
C(40)
Pollutant concentration units used for
the input data, in ppm or ug/m3.
OutUnits
OUPUTUNIT
Output
Concentration
Units
C(40)
Pollutant concentration units used for
the output data, in ppm or ug/m3.
Location
LOCATION
Location
C(40)
Study area location (for output only; not
used internally).
Scenario
SCENARIO
Scenario
C(40)
Scenario description (for output only;
not used internally).
#Profiles
PROFILE
Number of
Profiles
Integer
Number of profiles to simulate.
#Micros
MICRO
Maximum
Microenvironm
ent Number
Integer
Number of microenvironments defined
in the Micro Mapping file (Unit 21) and
on the Micro Descriptions file (Unit 24).
#Sources
SOURCE
Number of
Sources
Integer
Largest number of sources in any
microenvironment.
StartDate
START_
Start Date
Integer
Simulation start date in YYYYMMDD
format (e.g., 19960704 for July 4,
1996).
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Table 5-3. Job Parameters in APEX Params File (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
EndDate
END_
End Date
Integer
Simulation end date in YYYYMMDD
format.
Latitude
LATIT
Latitude
Real
Latitude in decimal degrees for the
center of the study area. Note that
latitude south of the equator is
negative.
Longitude
LONGIT
Longitude
Real
Longitude in decimal degrees for the
center of study area. Note that
longitude west of the primary meridian
is negative (e.g., in the United States).
CityRadius
CITYRAD
Study Area
Radius
Real
Radius of study area in km. The
sectors (e.g., census tracts) with
representative locations within this
radius will be automatically selected for
modeling.
AirRadius
AIRRAD
Air Quality
District Radius
Real
Maximum application radius (km) of air
quality data collected at an air
monitoring station or modeled at that
location. Air quality data are applied to
the sectors within this radius.
ZoneRadius
ZONERAD
Meteorological
Zone Radius
Real
Maximum application radius (km) of
daily temperature data collected at a
weather station.
CountyList
COUNTYL
Use County
List?
C(1)
Y = the study area is restricted to
sectors in the listed counties (next
variable) and within CityRadius, N =
the study area is restricted to sectors
within the specified CityRadius only.
The default value is N.
County
COUNTY
County FIPS
Code
C(5)
FIPS code for listed county (or other
relevant portion ofthe 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.
Commuting
COMMUT
Include
Commuting to
Work?
C(1)
Y = allow a simulated profile (or
person) to commute to a work sector
(or census tract), N = No commuting.
If Y, a work sector (e.g., census tract)
is randomly selected for each
simulated profile based on the
probabilities of work sectors a person
may travel to from a home sector. If N,
then workers are assumed to work in
their home sector. The commute
database provided with this model is
only for Y2000 Census tracts and can
only be used with Y2000 population
data.
AgeMin
AGEMIN
Minimum Age
Integer
Minimum age for simulated profiles
(persons).
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Table 5-3. Job Parameters in APEX Params File (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
AgeMax
AGEMAX
Maximum Age
Integer
Maximum age for simulated profiles
(persons).
DSTAdjust
DST
Use Daylight
Savings Time?
C(1)
Y = use Daylight Saving Time (DST) in
summer, N = don't use DST. In areas
that use DST, one day per year (in
April) is only 23 hours long and another
(in October) is 25 hours long.
However, most air quality data sets are
reported in Standard Time throughout
the year. If DSTAdjust is set to Y, the
first and last days of summer time
(using different rules before 1986) are
determined, and the concentration from
2-3 a.m. on the short day is duplicated,
while the concentration from 2-3 a.m.
on the long day is deleted. Regardless
of this setting, the output (hourly
exposure and dose) for all simulated
days will contain exactly 24 hours, and
all input activity diaries must contain
exactly 24 hours.
HourlyOut
HOURLY
Write Hourly
Output?
C(1)
Y = write hourly exposure and dose
files, N = don't write files. If this flag is
set to NO, the output files of hourly
exposures and doses will not be
generated. Note that the hourly
exposure or dose file could be as large
as 200 megabytes for every 2,000
simulated profiles (or persons).
DoDose
DODOSE
Do COHb Dose
Calculations?
C(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. Note that the
physiology input file must still be
provided, even though physiology is
needed exclusively for the dose
calculations.
RollBack
ROLLBACK
Do Rollback
Adjustments?
C(1)
Y = use air quality rollback
adjustments, N = don't use
adjustments. Rollback adjusts the
ambient air quality data before the
exposure calculations occur. The
purpose is to determine exposure in
hypothetical scenarios where the
ambient concentrations have been
reduced by various controls.
RbTarget
RBTARGET
Rollback target
concentration
Real
Rollback target concentration. Use
same units as InUnits.
RbBackgnd
RBBACK
Rollback
background
concentration
Real
Rollback background concentration.
Use same units as InUnits.
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Table 5-3. Job Parameters in APEX Params File (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
RbMax
RBMAX
Rollback
maximum
concentration
Real
Rollback maximum concentration. Use
same units as InUnits.
PPMFactor
PPM
PPM to ug/m3
Factor
Real
Units conversion factor (1 ppm =
ppmfact |jg/m3). For CO, ppmfact =
1,145 (i.e., 1 ppm = 1,145 ug/m3). It is
used when source strengths are
expressed in micrograms per hour, but
concentrations are in parts per million
(ppm), and when InUnits and
OutUnits are in different units.
MissGender
MISSGEND
Missing Gender
Diary
Probability
Factor
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 selection
probability. If MissGender=0, then
diaries with missing gender will never
be selected. If MissGender=1, then
such diaries are equally likely to be
selected as diaries of the correct
gender. MissGender can also be set
to values between zero and one.
Allowing a small but nonzero value for
MissGender expands the pool size
without permitting very much chance of
selecting a diary with missing gender
(which would cause APEX to stop
prematurely).
MissEmploymen t
MISSEMP
Missing
Employment
Diary
Probability
Factor
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
MissEmpI = 0, then such diaries will
never be selected.
MissAge
MISSAGE
Missing Age
Diary
Probability
Factor
Real
Diary probability factor for missing age.
Some of the supplied CHAD diaries are
for persons of unknown age. This
factor operates just like MissGender
and MissEmpI to lower the selection
probability for such diaries.
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Table 5-3. Job Parameters in APEX Params File (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
AgeCutPCT
AGECUT
Primary Age
Window Width
Real
Width of main age window (%). Each
simulated profile (person) is assigned a
specific year of age. A window is
created around this target age, of size
equal to AgeCutPCT percent of the
target age. If the target age is 40 and
AgeCutPCT = 25, then the age
window is ten years wide (25% of 40)
and diaries for persons from 30 to 50
years of age inclusive are permitted to
be selected. The age window is always
at least 1 year wide.
Age2Probability
AGE2PROB
Shoulder Age
Window Width
Real
Diary probability factor for "shoulder"
ages. This parameter allows an
optional shoulder window of ages
outside the primary age window. The
shoulders have the same width in
years as the main age window, so in
the example under AgeCutPCT the
shoulders are ages 20-29 and 51-60.
The Age2Probab parameter operates
like MissAge, by suppressing the
selection probability in the shoulders. If
Age2Probab = 0 then shoulder ages
are never selected.
Altitude
ALTITUDE
Altitude
Real
Altitude of study area in feet. The
altitude in feet is assumed constant for
the study area. It is used in the
Coburn-Forster-Kane (CFK) equation
for determining blood COHb
concentration. Note, however, that the
altitude correction that was used in
pNEM and earlier versions of APEX
was found to be in error and so this
factor has been temporarily eliminated
from the CFK equations. The use of
altitude to adjust for air pressure as a
function of altitude still exists.
COHbFactor
COHBFACT
COHb
Convergence
Factor
Real
Convergence parameter for COHb
algorithm. This is a safety factor that
limits the permitted error in determining
the solution to the CFK equation.
Larger factors mean greater accuracy
but slower evaluation. Numerical tests
indicate that factors in the range of 2 -
3 are optimal for most purposes.
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Table 5-3. Job Parameters in APEX Params File (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Type
(Length)
Description
COThreshold
COTHRESH
CO Notification
Threshold
Real
CO concentration threshold for user
notification. If a simulated individual
experiences a concentration above
COThresh, then a message is printed
both to the screen and to the log file.
DebugLevel
DEBUG
Debug Level
Integer
A value of one results in more
information being written to the log file
than for a value of zero.
Randomseed
RANDOM
Random Seed
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. Otherwise, the same 100
profiles will be generated over again.
Control of the random number seeds is
an important part of using APEX for
sensitivity analysis. For example,
when performing multiple runs with
slightly different inputs, it may be
convenient to sample the same set of
profiles, activity diaries, and
microenvironmental concentrations, in
order to prevent stochastic differences
between the runs from obscuring the
differences due to the changed input.
5.2.4 Output Table Levels Sections of Params File
In the Output Table Levels section of the Params file, the user could specify the value levels of
each of 12 output parameters in the output summary tables. Each parameter is identified by a
single keyword and the values are a list of numbers ordered from smallest to largest and
separated by a comma. All the values are read as real numbers, although the decimal points
are optional if the values happen to be integers. Items in each list must be separated by
commas. Except for the Percentiles, all of other parameters are used to bin exposures or
doses into categories in order to create output tables. Note that there is always one more bin
than there are number of values in the list, since the first bin is below the first value in the list
and the last bin is above the last number. The specific meanings of the parameters are
explained in Table 5-4.
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Table 5-4. Output Parameter Levels in the Output Summary Table
Variable
Keyword
APEX in MIMS
Parameter
Name
Data
Type
Description
Percentiles
PERCENTILES
Table -
Percentiles
Real
This parameter specifies the levels of
percentile 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).
Percentiles can only be distinguished from
nearby ones if there are enough profiles in the
model run. For example, at least 100 profiles
are needed to properly determine a 99th
percentile, and unless at least 200 profiles are
used, the 99.5 and 99.9 percentiles will both
report the results for the highest individual
profile.
Exposure
Outpoints
TIMEEXP
Table -
Exposure
Outpoints
Real
This parameter specifies the exposure
cutpoints (ppm) 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.
The first table is non-cumulative, meaning that
only the time spent at a level between one
cutpoint and the next is totaled. The other
table is cumulative, meaning that all time spent
at levels above the cutpoint is reported, even if
it is also above higher cutpoints. For both
tables, the second dimension is provided by
the microenvironment number.
Daily Max 1-
Hour
Exposure
Outpoints
DM1HEXP
Table - Daily
Max 1-Hour
Exposure
Outpoints
Real
This parameter specifies the daily maximum 1-
hour exposure cut-points (ppm) for binning all
the person-days in the simulation period.
Daily Max 8-
Hour
Exposure
Outpoints
DM8HEXP
Table - Daily
Max 8-Hour
Exposure
Outpoints
Real
This parameter specifies daily maximum 8-
hour average exposure cut-points in ppm for
binning all the person days in the simulation
period. It is similar to DMIHExp except for the
longer averaging time. Typically, DM8HExp
values are about 1/3 of DMIHExp values.
Daily
Average
Exposure
Outpoints
DAVGEXP
Table - Daily
Average
Exposure
Outpoints
Real
This parameter specifies daily average
exposure cut-points (ppm) for binning all the
person-days in the simulation period.
Simulation
Average
Exposure
Outpoints
SAVGEXP
Table -
Simulation
Average
Exposure
Outpoints
Real
This parameter specifies cut-points (ppm) 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
Outpoints
DM1HDOSE3
Table - Daily
Max 1-Hour
COHb Dose
Outpoints
Real
This parameter specifies cutpoints in %COHb
for Daily Maximum 1-Hour Blood Dose. The
cut points were used to bin all the person-days
in the simulation period.
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69
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Table 5-4. Output Parameter Levels in the Output Summary Table (continued)
Variable
Keyword
APEX in MIMS
Parameter
Name
Data
Type
Description
Daily Max 8-
Hour Dose
Outpoints
DM8HDOSE3
Table - Daily
Max 8-Hour
COHb Dose
Outpoints
Real
This parameter specifies cutpoints in %COHb
for Daily Maximum 8-Hour Blood Dose. The
cut points were used to bin all the person-days
in the simulation period.
Daily Max
End-of-hour
Dose
Outpoints
DMEHDOSE3
Table - Daily
Max End-of-
Hour COHb
Dose Cutpoints
Real
This parameter specifies cutpoints in %COHb
for Daily Maximum End-of-Hour Blood Dose.
The cut-points are used to bin all the
person/days in the simulation period. Note
that DMEHDose uses the instantaneous level
at the end of each hour, whereas DMIHDose
uses the time-averaged level over each hour.
These two statistics usually track each other
fairly closely. DMEHDose is reported since it
is the dose statistic calculated in the pneum.
model.
Hourly
End-of-hour
Dose
HEHDOSE3
Table - Number
of Hours
End-of-Hour
Dose
Cutpoints
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 cutpoints in %COHb used for tabulating
the dose results.
Daily
Average
Dose
Outpoints
DAVGDOSE*
Table - Daily
Average COHb
Dose Cutpoints
Real
This parameter specifies cutpoints in %COHb
for the Daily Average Blood Dose. The cut-
points are used to bin all the person/days in
the simulation period.
Simulation
Average
Dose
Outpoints
SAVEDOSEa
Table -
Simulation
Average COHb
Dose Cutpoints
Real
This parameter specifies cutpoints in %COHb
for the Average Blood Dose over the entire
simulation. The cut-points are used to bin all
the persons (or profiles) created in the APEX
run.
Dose
Outpoints
TIMEDOSE*
Table - COHb
Dose Cutpoints
Real
This parameter specifies cut-points in %COHb
for summing time spent at various blood dose
levels. Apart from the statistic, the tables
resemble the Time Exp tables.
a Note that these variables are used only for summarizing dose results. The current version of APEX can only
calculate doses for CO. For other pollutants the dose calculation should be turned off.
5.3 Sector Location File (Unit 11)
The Sector Location file provides the latitude and longitude of a representative location such as
the geographic center of all the sectors (e.g., census tracts) to be included in the Population
Data files. The file includes only numeric lines. Each line includes a Sector ID (starting with a
digit), Latitude, and Longitude. The sector IDs must match and be in the same order as the
sector IDs in the Population Data files. In addition, the sector ID must match the sector IDs in
the Commute Flow file as well (if worker commute is being modeled).
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70
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The sector location file is used along with the user-specified CityRadius to automatically select
sectors (or census tracts) within the study area (after also addressing an optional county test
and ensuring suitable air district and temperature zone data). APEX calculates the distance
between the location of a sector and the center of the study area and then compares it with the
CityRadius. All the sectors with a distance less than the city radius will be selected and
included in the exposure assessment.
The current default sector location file contains the 11-digit ID and latitudes and longitudes of
65,443 Year 2000 US Census tracts. An example of this file is provided in Figure 5-3. APEX
expects that the left most five characters of a sector ID should be the state and county FIPS
code or at least whatever county-level code is used in the County list (if the study area will be
limited in that way).
The latitude and longitude should be in decimal degrees. At least three significant digits should
be provided after the decimal point to prevent significant rounding error. Note that the longitude
west of the primary meridian (e.g., United States locations) should be negative.
Figure 5-3. Example Portion of Sector Location File
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
5.4 District Location File (Unit 12)
The District Location file provides the Site ID, Latitude, Longitude, air data Start Date, and air
data End Date for all air quality (modeling or monitoring) sites included in the Air Quality Data
file (Section 5.9). The site ID is stored as a character string (up to length 40). Latitude and
longitude are in decimal degrees. The start and end dates are in YYYYMMDD format (for
example, 19951231 is December 31, 1995). This file contains only character or comment lines.
The order of the listed sites must match the order of the sites in the Air Quality Data file. See
Figure 5-4 for an example of the District Location file.
Figure 5-4. Example of District Location File
Sitel
29
76112
-95.27645
19960101
19961231
Site2
29
81707
-95.27897
19960101
19961231
Site3
29
83677
-95.25692
19960101
19961231
Site4
29
82384
-95.19532
19960101
19961231
Site5
29
80085
-95.25586
19960101
19961231
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71
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APEX uses the District Location file to
determine the "district" or geographical area
represented by the set of ambient air quality
data collected at a specified location. APEX
first compares the start and end dates for
each air quality site with the start and end
dates for the APEX exposure simulation.
Only the sites with air quality data covering
the entire simulation period are accepted. Air
quality data before or after the simulation
period are simply ignored.
APEX also calculates the distance of a 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) district even if the district's location is outside the study area.
Only the sites with a distance less than this sum are used.
APEX then calculates the distances of a site from the locations of sectors (e.g., census tracts).
Sectors with distances less than AirRadius will be mapped to an air site. Based on this
mapping, APEX will use each set of air quality data in the Air Quality file only for the sectors
within its AirRadius. APEX assigns the sector to the nearest district. Each sector is assigned to
only one district.
5.5 Temperature Zone Location File (Unit 13)
The format and use of the Temperature Zone Location file is exactly like that of the District
Location file. Each record represents one site, and contains five values: Site ID, Latitude,
Longitude, Start Date, and End Date. The site selection process is analogous to that
described above for the District Location file. The file is used to map the set of temperature
data collected at a weather station to sectors within its zone radius for exposure calculations.
An example file is provided in Figure 5-5. Similar to air quality districts, zones within the sum of
CityRadius and ZoneRadius are used.
Figure 5-5. Example of Temperature Zone Location File
TempSitel
39
742
-105
045
19950101
19951231
TempSite2
39
103
-105
521
19950101
19951231
5.6 Employment by Age Group File (Unit 14)
This file provides employment probabilities for all the age groups included in the Population
Data files. The file contains only three records: Min_Age, Max_Age, and Empioy_Prob. The
format for each record is a keyword input line with a keyword, an "=", and a list of values.
APEX only reads the first three letters of each input line as keywords (i.e., MIN, MAX, and
BMP), although the user can spell out the record names in full if desired. The Min_Age input
line is used to list the minimum ages of each age group from the youngest to the oldest, while
the Max_Age input line to list the maximum ages of the corresponding population age groups.
Tip. Not all districts on the air quality input file
need sectors assigned to them. Such districts are
simply not included in the modeling. This feature
allows the user to prepare an input file in the
simplest manner, perhaps containing more
districts than are necessary. For example, a
single input file could be prepared for all districts
in a given state. This same input file could then
be run on several study areas in the state without
having to alter the air quality input file.
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72
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The Employ_Prob input line lists employment probabilities for each population group. The
probabilities should be a real value between 0 and 1. See Figure 5-6 for an example of this file.
Figure 5-6. Example of Employment by Age Group File ("Wrapped" View)
Min Age = 0
5
10
15
18
20
21
22
25
30
35
40
45
50
55
60
62
65
67
70 75 80
85
Max Age = 4
9
14
17
19
20
21
24
29
34
39
44
49
54
59
61
64
66
69
74 79 84
99
Employ prob =
0.0
0.0
0.1
0.5
0.6
0.8
0.9
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.8
0.5 0.5 0.2
0.1
0.0
0.0
5.7 Commuting Flow File (Unit 15)
This file provides cumulative fractions of the population in a home sector commuting to different
work sectors. An example of a portion of this file is provided in Figure 5-7. Each record
contains a Sector ID and a Cumulative Fraction of the population commuting to this sector.
The home sector is indicated by a negative value of -1 for cumulative fraction. The subsequent
records provide the Work Tract IDs and the Cumulative Fractions. The cumulative fraction
for the last work sector should always be 1. APEX uses this file to determine which work sector
a simulated individual may commute to by using the cumulative fractions as commuting
probabilities.
If the sectors used in the simulation are Year 2000 Census tracts, the default commuting flow
file provided with APEX should be used. This data base file contains all the 65,443 year 2000
Census tracts and their associated work tracts. The mean number of associated work tracts
per home tract is 104, with a minimum of one and a maximum of 829. The flows in the data
base file were calculated from the 1994 national commuting database and then mapped to the
Year 2000 Census tracts.
5.8 Temperature Data File (Unit 16)
This file provides daily maximum and optionally average (or other) temperature data collected at
the sites listed in the Temperature Zone Location file (Unit 13). Only keyword or numeric input
lines are processed and other types of input lines are ignored in this file. The data set from
each site begins with a header section with selected site information (see Figure 5-8). The
subsequent numeric lines include Date, Maximum Temperature (Fahrenheit), and other
temperature data such as mean or minimum daily temperature (if present).
The date should be in YYYYMMDD format (e.g., 20010507 is May 7, 2001) and the temperature
data should be in Fahrenheit. Each data set should cover the exposure simulation period. A
data set can include more days than the exposure simulation period. APEX only uses the data
within the simulation period. Thus, the user may prepare a file with a full year or many years of
data for each site and then use the same temperature file for a series of different simulation
periods.
DRAFT—APRIL 24, 2003
73
-------
Figure 5-7. Example Portion of Commuting Flow File
01001020100
-1
01001020100
0. 050060
01001020200
0. 057040
01001020300
0. 097790
01001020500
0.336685
01001020700
0.513635
01001020800
0.544820
01011952200
0.550640
01051031100
0.562280
01073012903
0.570430
01085981000
0.576250
01101000100
0. 620490
01101000200
0. 694990
01101000300
0.713620
01101000600
0.757860
01101000700
0.770660
01101001000
0.783470
01101001400
0.788130
01101001800
0.810240
01101002000
0.814900
01101002201
0.820666
01101002202
0.821890
01101002400
0.821892
01101002800
0.828872
01101002900
0.852152
01101003000
0.873112
01101003200
0.881262
01101003301
0.887082
01101005301
0.894062
01101005401
0.932482
01101005402
0.947612
01101005403
0.954602
01101005902
0.961580
01101006000
1.000000
01001020200
-1
01001020100
0.065350
01001020200
0.085080
01001020300
0.177560
Figure 5-8. Example Portion of Temperature Data File
Name = TempSitel
Denver Daily Maximum and Mean Temperatures
Degrees Fahrenheit
Start = 19950101
End = 19951231
Lat = 39.742
Lon = -105.045
19950101 41
17
19950102 25
20
19950103 20
14
19950104 20
10
19950105 36
23
DRAFT—APRIL 24, 2003
74
-------
The data sets may be in any order. However, each site must begin with the "name" keyword
input line. APEX matches a site name in the Temperature Zone Location file with the data set
site name to locate its data in this file. If desired, the user could add more comment or
character lines in the header section of a data set.
This file should contain data sets for the sites and time duration indicated on the Temperature
Zone Location file (Unit 13). Any missing dates within the simulation period are written to the
log file.
5.9 Air Quality Data File (Unit 17)
This file provides hourly air concentration data for air sites listed in the District Location file.
Only keyword or numeric input lines are processed and other types of input lines are ignored in
this file. The data set for each site begins with a header section containing selected site
information (see Figure 5-9). Each of the subsequent numeric input lines includes 24 Hourly
Average Air Concentrations and a Date. The date should be in YYYYMMDD format (e.g.,
20010507 is May 7, 2001). Air quality data should be in units of parts per million (ppm) or
ug/m3. Hourly data could be either comma or space delimited. In the example file, the number
of cumulative hours for each day also is included (for quality control)—APEX ignores this
column. Note that the length of each data line in air quality file should not exceed 256
characters.
Air data sets can be in any order. APEX locates the air data set by matching a site name in the
District Location file with the site name in this file. Any missing dates within the simulation
period will be written to the log file.
Figure 5-9. Example Portion of Air Quality Data File ("Wrapped" View)
Name = #48201212100
Houston TX Modeling Receptor Location # 1
Units = ppm
Start
Date =
19960101
End Date =
19961231
Lat
=
29.76113
Lon
=
-95.27644
0. 00,
0. 65,
0.57,
0.45,
0. 87,
1.24,
3.46,
3.89
2.88,
0. 00,
1.20,
1.59,
1.89,
1. 04
1. 21
1. 25
1. 08
1. 05
1. 01
0.86
0.
71
0.55
0.58
0.52
19960101
1
CT)
CM
O
0.23,
0.22,
0.17,
0.28,
0.38,
1. 00,
1. 57
1. 52,
1.14,
1. 05,
1. 03,
0. 96,
1.20
1. 03
1. 02
1. 53
3.38
4 .20
4 . 30
2 .
79
1. 01
0.52
0.56
19960102
25
0.25,
0.31,
0.16,
0.29,
0. 98,
2.21,
4.76,
6.33
3.10,
1.45,
1. 61,
1. 31,
0.54,
0.59
1. 01
1.44
1. 08
0. 00
2 . 62
0. 00
3.
58
3. 04
2 . 64
2 . 06
1 99€
50103
49
1. 53,
1.19,
0. 93,
0. 00,
0. 00,
1.74,
7 . 25,
6.17
2 . 62,
0.59,
0. 63,
0.78,
0.37,
0.79
0.71
0. 82
1. 00
0. 82
1.79
6.20
3.
10
3.74
0. 00
3.84
1 99€
50104
73
i—1
CTi
CO
0. 00,
0. 00,
0. 00,
0. 68,
1.54,
5. 81,
5.56
0. 00,
4 . 00,
4 . 23,
2.29,
2 . 83,
2 . 63
3.13
5. 98
2 . 35
1.72
1. 56
1. 98
1.
59
0. 82
0.52
0.47
1 9 9f
50105
97
0. 60,
0.59,
0.32,
0.23,
0.17,
0.21,
0.56,
0. 67
0.88,
1.07,
1. 01,
1. 53,
1. 35,
1.24
0. 97
1. 04
0. 97
0.88
1.10
0.74
0.
60
0.50
0.75
0.55
1 9 9f
50106
121
o
-j
o
0.27,
0.23,
0.23,
0.23,
0.24,
0.41,
0.59
0.56,
0.69,
0. 62,
0. 66,
0. 97,
0. 91
1 . 07
1. 04
1. 05
1. 34
3.24
3. 87
5.
36
1. 92
3. 00
3.46
19960107
145
DRAFT—APRIL 24, 2003
75
-------
5.10 Activity-specific MET File (Unit 18)
This file provides distributional shapes and parameters for calculating the MET value for each
CHAD (or other) activity code. A MET value is a dimensionless ratio of the activity-dependent
energy expenditure rate to the basal or resting energy expenditure (metabolic) rate. The file is
inherited from APEX2 unchanged. The user should not change this file unless the MET
distribution data in the CHAD database are revised.
Each data line in this file provides the following information in list format:
• MET Distribution Number,
• Activity Code from supplied CHAD data (see Table 5-5);
• Age Category;
• Occupation,
• Distribution Type,
• Mean,
• Median,
• Standard Deviation,
• Minimum,
• Maximum, and
• Description of Activity Type.
A portion of this file is shown in Figure 5-10.
Figure 5-10. Example Portion of Activity-Specific MET File
1
10000
0
ADMIN
LogNormal
1.7
1.7
0.3
1.4
2.7
9
Work,
general
2
10000
0
ADMSUP
LogNormal
1.7
1.7
0.3
1.4
2.7
9
Work,
general
3
10000
0
FARM
LogNormal
7.5
7.0
3.0
3.6
17. 0
9
Work,
general
4
10000
0
HSHLD
LogNormal
3.6
3.5
0.8
2.5
6.0
9
Work,
general
5
10000
0
LABOR
Triangle
8.5
8.4
2.1
3.6
13. 8
9
Work,
general
5.11 Physiological Parameters File (Unit 19)
This file provides four tables of age/gender specific data for the following physiological
parameters (also see Figure 5-11):
• NV02Max,
• Body Mass,
• Resting Metabolic Rate (RMR); and
• Blood Volume Factor and Hemoglobin Content.
This file requires the data to be in fixed column positions. Each table has three header lines
and 202 numerical lines of data. The first table contains age/gender specific distribution data on
normalized lung capacity (V02-max). APEX only reads the Mean NV02Max in columns 24-30 in
F7.1 Fortran format and the NV02Max standard deviation in columns 31-37 (F7.1).
DRAFT—APRIL 24, 2003
76
-------
Table 5-5. CHAD Activity Codes
CHAD
CHAD
Activity
Activity
Code
Description
Code
Description
10000
Work and other income producing activities,
13600
Obtain car services
general
13700
Other repairs
10100
Work, General
13800
Other services
10110
Work, general, for organizational activities
14000
Personal needs and care, general
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
13200
Shop / run errands
17142
Create domestic crafts
13210
Shop for food
17143
Create art
13220
Shop for clothes or household goods
17144
Perform music / drama / dance
13230
Run errands
17150
Play games
13300
Obtain personal care service
17160
Use of computers
13400
Obtain medical service
17170
Participate in recess and physical education
13500
Obtain government / financial services
17180
Other sports and active leisure
DRAFT—APRIL 24, 2003
77
-------
Table 5-5. CHAD Activity Codes (continued)
CHAD
CHAD
Activity
Activity
Code
Description
Code
Description
17200
Participate in passive leisure
17242
Write for leisure / pleasure / paperwork
17210
Watch
17250
Think and relax
17211
Watch adult at work
17260
Other passive leisure
17212
Watch someone provide childcare
17300
Other leisure
17213
Watch personal care
18000
Travel, general
17214
Watch education
18100
Travel during work
17215
Watch organizational activities
18200
Travel to/from work
17216
Watch recreation
18300
Travel for child care
17220
Listen to radio/listen to recorded
18400
Travel for goods and services
music/watch T.V.
18500
Travel for personal care
17221
Listen to radio
18600
Travel for education
17222
listen to recorded music
18700
Travel for organizational activity
17223
Watch TV
18800
Travel for event / social activity
17230
Read, general
18900
Travel for leisure
17231
Read books
18910
Travel for active leisure
17232
Read magazines / not ascertained
18920
Travel for passive leisure
17233
Read newspaper
U
Unknown
17240
Converse / write
X
Missing
17241
Converse
The second table contains age/gender specific body mass (kg) distribution data. APEX only
reads the mean body mass in columns 22-30 (F9.1) and the body mass standard deviation in
columns 31-38 (F8.3).
The third table contains regression parameters for fitting the resting metabolic rate. APEX
reads the slope in columns 30-38 (F9.3), the intercept in columns 39-47 (F9.3), and the residual
error in columns 48-54 (F7.3).
The fourth table contains blood parameters. APEX reads the blood factor in columns 7-15
(F9.1), the hemoglobin mean in columns 16-24 (F9.1), and the hemoglobin standard deviation in
columns 25-32 (F8.1).
5.12 Profile Functions File (Unit 20)
This file provides the user-definable functions required in generating profiles or simulated
persons. The profile functions that can be defined in this file are summarized in Table 5-6.
Note that all user-definable functions must be included in this file except those identified as not
required in Table 5-6. Also, note that when preparing or editing a profile functions file, be
careful not to use Tab to separate the items on a line. APEX is explicitly searching for blanks
(spaces) as delimiters, and fails to recognize Tabs as such. An example of the user-defined
function for WindowPos is provided in Figure 5-12. The box after this example provides a
general description of the procedures for defining a function.
DRAFT—APRIL 24, 2003
78
-------
Figure 5-11. Portions of Four Data Tables in Physiological Parameters File
(Columns in this view are not in their required positions)
Males
age
0-100,
then females age 0-100
(last
revised
6-11-98)
NV02max distribution
Age
Source
Distr
Mean SD
Lower
Upper
Assumptions
0
1
Normal
44.0 5.2
33.7
54 . 3
2-yr-old mean
1
1
Normal
44.0 5.2
33.7
54 . 3
2-yr-old mean
2
1
Normal
44.0 5.2
33.7
54 . 3
CV = 6.9/57.
9
3
1
Normal
46.0 5.5
35.3
56.7
CV = 6.9/57.
9
4
1
Normal
48.0 5.7
36.8
59.2
CV = 6.9/57.
9
5
1
Normal
50.0 6.0
38 . 3
61.7
CV = 6.9/57.
9
6
1
Normal
52.0 6.2
39. 9
64 . 1
CV = 6.9/57.
9
7
1
Normal
54.0 6.4
41.4
66.6
CV = 6.9/57.
9
8
1
Normal
56.0 6.7
42 . 9
69. 1
CV = 6.9/57.
9
Males
age
0-100,
then females age 0-100
(last
revised
6-11-98)
Body mass distribution,
kg
Age
Source
Distr
GM GSD
Lower
Upper
Assumptions
0
4
LN
9.3 1.141
7.2
12 . 0
1
4
LN
11.7 1.126
9.3
14 . 8
2
4
LN
13.5 1.127
10.7
17 . 1
3
4
LN
15.6 1.121
12 . 5
19.5
4
4
LN
17.6 1.142
13. 6
22 . 8
5
4
LN
19.9 1.148
15.2
26.1
6
4
LN
22.9 1.156
17.2
30.4
7
4
LN
24.8 1.163
18 . 4
33.3
8
4
LN
27.9 1.198
19. 6
39. 8
Males
age
0-100
then females age 0-100
(last revised 6
1
I—1
I—1
1
KD
CO
Regression equation Estimate for
RMR
Age
Source
DV
IV Slope
Interc
SE
Units med.
wgt
0
R4 7g
BMR
BM 0.244
-0.127
0.290
MJ/day
2 . 1
1
R4 7g
BMR
BM 0.244
-0.127
0.290
MJ/day
2 . 7
2
R4 7g
BMR
BM 0.244
-0.127
0.280
MJ/day
3.2
3
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
3.6
4
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
3.8
5
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
4 . 0
6
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
4 . 3
7
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
4 . 5
8
R47h
BMR
BM 0.095
2 . 110
0.280
MJ/day
4 . 8
Males
age
0-100
then females age 0-100
Blood
Volume factor and
Hemoglobin content
Age
BLDFAC
HGMN
HGSTD
0
17 . 0
16.0
1.0
1
17 . 0
16.0
1.0
2
17 . 0
16.0
1.0
3
17 . 0
16.0
1.0
4
17 . 0
16.0
1.0
5
17 . 0
16.0
1.0
6
17 . 0
16.0
1.0
7
17 . 0
16.0
1.0
8
17 . 0
16.0
1.0
DRAFT—APRIL 24, 2003
79
-------
Users may enter additional functions for use with the microenvironmental concentration
calculations. These additional functions may be given any names that start with "M" (except for
"MaxTempCat", already used for another purpose). These functions are used if they are
referenced on the Micro Descriptions input file (unit 24). The user also can define functions in
this input file that are not actually referenced by the model. This could be useful if the user has
two versions of some function and for convenience would like to store the definitions of both in
the same file. One function would then be given the function name expected by APEX and the
other would be given some related name. After the model is run, the functions could be
interchanged simply by switching function names, and the job run again. This would permit a
comparison of the effects of the two versions of the function.
Table 5-6. User-definable Functions in Profile Functions File
Function
Purpose
MaxTempCat
Binning daily 1-hour maximum temperatures into categories
AvgTempCat
Binning daily average temperatures into categories
Diary Pools
Assigning diary pools using day of week, MaxTempCat, and AvgTempCat
IDGRP
pneum. group number (for output labeling, not used internally in APEX)
HasGasStove
Probability of having a gas stove
HasPilot
Probability of having a pilot light, based on HasGasStove
AC Home
Probability of having air conditioning at home
AC Car
Probability of having air conditioning in car
WindowPos
Probability of windows being open or closed, based on AC_Home, MaxTempCat, and
AvgTempCat
SpeedCat
Probability of average speed categories for vehicles
M1S1I2 (not required)
Cigarette emissions micro #1, block #2 in ug/hr
M1S1I1 (not required)
Cigarette emissions micro #1, block #1 in ug/hr
M2S1 (not required)
Cigarette emissions micro #2 in ppm
Figure 5-12. Example of WindowPos User-Defined Profile Function
WindowPos
! Home
windows open(l)
or closed (2)
TABLE
INPUT
1
INTVALUE 2
"AC Home"
1 2
INPUT
2
INTRANGE 3
"MaxTemp"
56 80
INPUT
3
INTRANGE 1
"AvgTemp"
INPUT
4
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
DRAFT—APRIL 24, 2003
80
-------
General procedures for defining a profile function:
1. A function definition begins with its name on the first input line.
2. Add as many comment lines as necessary to describe the profile function or units of the involved parameters.
3. A function type—Table or Continuous—is specified on the subsequent input line. At the present time, APEX
can only recognize the function type of Table.
4. For the function type Table, the number of subsequent input lines varies with the number of input variable
required to define a function. At least two input lines are needed for each input variable of the function. In
addition, at least two lines are also needed for the function result. For each input variable (table dimension),
the first line starts with the keyword INPUT, followed by the indexing number of Input Variable in the function,
the Type of Input Variable, and the Number of Values allowed for the input variable. At the end of this
input line, the user may add comments in double quotes to explain input variables. The type of input variables
must be one of the following six types:
conditional,
probability,
realrange,
intrange,
intvalue, or
intindex.
"Conditional" refers to conditional probabilities that depend on the values of other input variables. "Probability"
means fixed probabilities for each outcome, not dependent on the input data. "Realrange" means a set of
discrete categories, each consisting of a range of real numbers. "Intrange" is similar, except each category
consists of a range of integers. "Intvalue" means that each possible value that the input variable may take on
is listed. "Intindex" means that the input variable is integer and is to be used to index the table directly (e.g., a
value of 3 means use the third cell along that dimension). For each input variable, the remaining lines
(beyond the first) contain the data.
5. After all the input variables are specified, the next line must contain the keyword RESULT, followed by a type
(either integer or real) and the number of possible results.
6. List the results in order in subsequent lines.
7. End the profile function with a new line that has a # sign.
5.13 Micro Mapping File (Unit 21)
This file provides the mapping of the Location Codes (e.g., for CHAD) to Microenvironments
defined in APEX. An example of a portion of this file is provided in Figure 5-13. This file only
allows comment lines and keyword input lines, except for the first two header lines. Each
keyword input line begins with a location code followed by a short description, an and an
integer that designates a microenvironment defined in the Micro Description file. APEX only
reads the location codes and the code for the APEX microenvironments.
The supplied file contains 115 CHAD location codes. The user must assign each location code
to microenvironments defined in the Micro Description file by specifying the microenvironment
number in the APEX Micro column. The user could place a zero in the APEX Micro column if no
exposure occurs in a CHAD microenvironment location, or-1 if the CHAD locations are 'U' or
'X' (unknown). The value of -1 means that APEX should use whichever microenvironment was
previously in use in the composite diary time series. See Table 2-2 for a description of the
CHAD location codes supplied with APEX and mapped in the Micro Description file.
DRAFT—APRIL 24, 2003
81
-------
Figure 5-13. Example Portion of Micro Mapping File
CHAD
Loc. Description
APEX micro
X
No data
= -1
U
Uncertain of correct code
= -1
30000
Residence, general
1
30010
Your residence
1
30020
Other residence
1
30100
Residence, indoor
1
30120
Your residence, indoor
1
30121
. .., kitchen
1
30122
..., living room or family room
1
30123
..., dining room
1
30124
..., bathroom
1
30125
. . . , bedroom
1
30126
. .., study or office
1
30127
..., basement
1
30128
..., utility or laundry room
1
30129
..., other indoor
1
30130
Other residence, indoor
1
30131
. .., kitchen
1
30132
..., living room or family room
1
30133
..., dining room
1
30134
. .., bathroom
1
30135
. .., bedroom
1
30136
. .., study or office
1
30137
..., basement
1
30138
..., utility or laundry room
1
30139
..., other indoor
1
30200
Residence, outdoor
4
30210
Your residence, outdoor
4
30211
. .., pool or spa
4
30219
... , other outdoor
4
30220
Other residence, outdoor
4
30221
..., pool or spa
4
30229
... , other outdoor
4
30300
Residential garage or carport
4
30310
..., indoor
4
30320
..., outdoor
4
30330
Your garage or carport
4
30331
..., indoor
4
30332
..., outdoor
4
30340
Other residential garage or carport
4
30341
..., indoor
4
30342
..., outdoor
4
30400
Residence, none of the above
1
5.14 Personal Info File (Unit 22)
This file provides the personal information component of each 24-hour activity diary (Figure 5-
14). Each record contains values for the following variables:
• CHAD ID,
• Day Type (MON, TUE, etc., Missing (X));
• Gender (Male (M), Female (F), Missing (X));
• Race (White (W), Black (B), Asian (A), Hispanic (H), Other (O), Information not available
(X));
• Employment Status (Yes (Y), No (N), Missing (X));
• Maximum Temperature (degrees C);
DRAFT—APRIL 24, 2003 82
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• Age (Years);
• Occupation (see Table 5-7);
• Count of Missing Time (the total number of minutes associated with events in the Diary
Events file for which the activity and/or location codes are missing); and
• Record Count.
This file is identical to the Diary Questionnaire file produced by the Access® version of the
CHAD database (see next section). The user should not change this input file unless the CHAD
database has changed or other activity data are to be used instead. If the latter, the input file
format restrictions must be met and the CHAD coding conventions used. Note that this file has
only one record per CHAD ID, whereas the CHAD Diary Events file has Record Count of
records per CHAD ID.
Figure 5-14. Example Portion of Personal Info File
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
o,
28
BAL97001E
TUE
F
W,
N,
77,
47
X
o,
27
BAL97001F
WED
F
W,
N,
77,
36
X
o,
28
BAL97001G
THU
F
W,
N,
77,
38
X
o,
26
BAL97001H
FRI
F
W,
N,
77,
43
X
o,
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
DRAFT—APRIL 24, 2003
83
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Table 5-7. 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
MACH
Machine operators, assemblers, and inspectors
TRANS
Transportation and material moving
LABOR
Handling, equipment cleaners, helpers, and laborers
X
Missing
5.15 Diary Events File (Unit 23)
This file provides descriptions of events occurring hourly or in shorter duration in each day for all
the diary days in the CHAD database. 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 5-5); and
• Location Code (see Table 2-2).
This file should be generated from the CHAD database at the same time as the Personal Info
(questionnaire) file to ensure that the CHAD IDs are in the same order. Each diary day begins
and ends at midnight and there should be exactly twenty-four hours of data per diary. See
Figure 5-15 for an example of a portion of this file. And see the previous section on the
Personal Info file if user-supplied date are to be provided.
DRAFT—APRIL 24, 2003
84
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Figure 5-15. Example Portion of Diary Events File
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,
5.16 Micro Descriptions File (Unit 24)
The Micro Descriptions file provides microenvironment definitions and parameters required to
calculate pollutant concentrations in microenvironments. As described below, the Micro
Descriptions file has two sections: Micro Descriptions and Parameter Descriptions. A portion of
an example file is provided in Figure 5-16.
5.16.1 Micro Descriptions Section
In the Micro Descriptions section of the Micro Descriptions file, the user specifies a
Microenvironment Number, a Name, and a Calculation Method for each microenvironment,
as shown in Figure 5-16. The microenvironment number cannot exceed the number of
microenvironments specified in the Params file and nor can it exceed 127. It also has to
correspond with each of the microenvironment numbers in the Micro Mapping file. A
microenvironment name may be a word up to 12 characters. The calculation method could be
either MASSBAL or FACTORS. In the MASSBAL method, the concentration in a
microenvironment is calculated using a mass balance approach, while in the FACTORS method
the microenvironment concentration is assumed to be a linear function of ambient
concentration.
DRAFT—APRIL 24, 2003
85
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Figure 5-16. Example Portion of Micro Description File
! First section - micro descriptions
Micro
1
2
3
4
Name
Residence
Car
InsideOther
Outside
Method
MASSBAL
MASSBAL
FACTORS
FACTORS
! Second section - parameter descriptions
Micro number
=
1
Parameter Type
=
PRX
Hours - Block
=
1 1
1
1
1
1
1
Weekday - Daytype
=
1 1
1
1
1
1
1
Month - Season
=
1 1
2
2
2
3
3
District- Area
=
1 1
1
1
1
1
Condition # 1
=
0
Condition # 2
=
0
Condition # 3
=
0
ResampHours
=
NO
ResampDays
=
YES
ResampWork
=
YES
Randomseed
=
0
22222222222211111
3 4 4 4 1
Block DType Season
Area
CI
C2
C3
Shape Min
Max
Pari
Par2
1 1
1
1
1
1
1
Normal
0.
2
1.2
0.4
2 1
1
1
1
1
1
Point
2 .
1 1
2
1
1
1
1
Lognormal
0.
2
1.2
1.5
2 1
2
1
1
1
1
Exponential
1.
2 .
1 1
3
1
1
1
1
Triangle
0.
3
2 .
2 1
3
1
1
1
1
Normal
1.
2
5
1.5
0.5
1 1
4
1
1
1
1
Uniform
0.
1
6
2 1
4
1
1
1
1
Lognormal
1.
3.
1.4
Micro number
= 1
Parameter Type
= AER
Hours - Block
= 11
1 1
1
1
1
2 2
2 2 2 2 2 2
2 2
2 2 1
1
Ill
Weekday - Daytype
= 11
1 1
1
1
1
Month - Season
= 11
1 1
1
1
1
1 1
111
District- Area
= 11
1 1
1
1
Condition # 1
= AC HOME
Condition # 2
= 0
Condition # 3
= 0
ResampHours
= NO
ResampDays
= NO
ResampWork
= YES
Randomseed
= 0
Block DType Season
Area
CI
C2
C3
Shape
Min
Max
Pari
1 1
1
1
1
1
1
Uniform
0.5
4.
2 1
1
1
1
1
1
Normal
0.
2.5
1 1
1
1
2
1
1
Point
3.
2 1
1
1
2
1
1
Triangle
1.
5.
2 .
Par2
1.0
5.16.2 Parameter Description Section
In the Parameter Description section of the Micro Descriptions file, the user defines a number of
parameters for each microenvironment, depending in the calculation method: three parameters
for the FACTORS method and eight parameters for the MASSBAL method. These parameters
are required for calculating concentrations in microenvironments. If a default or supplied value
(in Table 5-8) is acceptable, the user does not have to define the parameters further. A
Parameter Description section is needed for each parameter and consists of keywords and
DRAFT—APRIL 24, 2003
86
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data. The following two sections provide additional details on the parameter keywords and
data.
Table 5-8. Micro Parameters Required to Define a Microenvironment
Calculation
Method
Parameter Type
Code
Units
Default/Supplied Value
FACTORS
Proximity
PR
None
1
Penetration
PE
None
1
Csource
CS
ppm or |jg/m3 (depends
on InputUnits)
0
MASSBAL
Proximity
PR
None
1
Penetration
PE
None
1
Csource
CS
ppm or |jg/m3 (depends
on InputUnits)
0
DecayRate
DE
1/hr
0
AlrExRate
AE
Air changes/hr
none
Volume
VO
m3
none
MeanR
MR
1/hr
Ai rExRate+DecayRate
ESource
ES
|jg/m3
0
5.16.2.1 Keywords
The user needs to specify values for the 13 parameters on keyword input lines, as shown in
Figure 5-16. A brief description of each parameter is provided in Table 5-9. The keyword list
needs to end with a character line that is the header line for the data section and begins with the
word Block, which APEX recognizes as an indicator for ending of the keyword section. The
Esource and Csource terms, unlike the others, may have multiple definitions within the same
microenvironment. These terms are then added or multiplied together, depending on the source
numbering. If source terms are multiplied, then only the final product must have the proper
units. This feature allows the source terms to be expressed in any suitable units, with the units
conversion expressed as a multiplicative factor.
DRAFT—APRIL 24, 2003
87
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Table 5-9. Keyword Definitions for the Parameter Descriptions Section of the
Micro Descriptions File
Keyword
Description
Micro Number
These numbers must match the micro numbers in the Microenvironment Description
section.
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.
Hours - Block
This variable is used to map hours of a day to different time blocks. 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 a
hour belongs to. The hours in a time block do not need to be consecutive, nor does a
time block have to have the same number of hours. If this line is missing, the default
value is that all 24 hours are in a single time block - block #1.
Weekday - Daytype
This variable is used to map days in a week to different day types. 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 daytype #1.
Month - Season
This variable is used to map months of a year to different seasons. Twelve integers must
be given in this input line. The position of an integer represents a month of a year,
beginning in January and ending in December. The integer represents the season that a
month belongs to. If this line is missing, all 12 months belong to season #1.
District - Area
This variable is used to map air quality districts to larger areas. The number of integers in
this line must match the number of air quality 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.
Condition # 1
Choice for the first conditional variable. If not used, this line may either be omitted or the
value set to zero. APEX accepts the following variables as conditional variable : Gender,
Race, Employed, GasStove, GasPilot, AC_Home, AC_Car, WindowPos, , MaxTempCat,
AvgTempCat, SpeedCat.
Condition # 2
Choice for the second conditional variable.
Condition # 3
Choice for the third conditional variable.
ResampHours
Either YES or NO. If YES, a random value is selected from distribution for a parameter in
each hour within a time block. If NO, a random value is selected for a parameter for a
time block and used for every hour within the time block. The default value is NO.
ResampDays
Either YES or NO. If YES, a random value is selected from a distribution for a parameter
for each day within a day type. If NO, a random value is selected for a day type and used
for every day within the same day type. The default is NO.
ResampWork
Either YES or NO. If YES, a separate set of random values is selected from a distribution
for the workplace. If NO, the same set of random values are used (for the same day and
hour) both for home and at work. The default is YES.
RandomSeed
Eitherzero or a positive integer up to about 2.1 billion. If zero, the random number seed
for a parameter is determined from the internal clock, and the results will differ from one
run to another. If not zero, then Seed = (RandomSeed x 232) + RandomSeed. Multiple
model runs with the same seed will generate the same sequence of random numbers for
the parameters (as long as the MP definition is unchanged). The default value is zero.
DRAFT—APRIL 24, 2003
88
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5.16.2.2 Data
The data are sets of distribution data for all possible combinations of the user-specified cases of
the following seven indexing parameters:
• Block — time block
• Daytype — day time
• Season — season
• Area — area
• C1 — conditional variable # 1
• C2 — conditional variable # 2
• C3 — conditional variable # 3
Note that the cases of each indexing parameter must be represented by integers ranging from 1
to the maximum number of cases for an indexing parameter. The number of cases for a
indexing parameter is specified in the keyword section.
In the example file in Figure 5-16, there are two time blocks and four types of seasons for the
PRX parameter of microenvironment 1. Thus, the user needs eight data lines in the data
section to specify eight sets of distribution data. In the second parameter description section,
there are two time blocks and C1 specified as AC-Home. Since AC-Home has two options—off
(1) or on (2)—the user needs four data lines to specify distribution data in the data section.
The meaning of integers for conditional variables can could be found in the Profile Function file
(Unit 20).
The user needs to specify the following parameters for a set of distribution data:
• Shape — distribution type
• Min — minimum;
• Max—maximum;
• Pari, and
• Par2.
Shape represents the distribution type. APEX allows the user to specify one of the six standard
distribution types—point, uniform, normal, lognormal, triangle, and exponential—plus user-
defined functions. APEX only examines the first letter of a distribution type. The user could
specify a shape value by using P, U, N, L, T, and E or spelling out the name of a distribution
type. The letter M is for the user-defined functions.
A real value must be specified for a required parameter. The parameters that are not used for
specifying a distribution should be marked with a period (see Figure 5-16).
The optional Min and Max parameters are used only when the user wants to set the limits to
selected random values from a distribution. If the optional parameters are not used, they should
be marked with a period as well. Note that the Pari and Par2 represent different parameters for
different distribution types.
Table 5-10 lists the required and optional parameters for specifying each type of distribution.
DRAFT—APRIL 24, 2003
89
-------
Table 5-10. Uses of Distribution Parameters for Each Standard Distribution Type
Shape
Min
Max
Pari
Par2
Point
Required
Not used
Not used
Not used
Uniform
Required
Required
Not used
Not used
Normal
Optional
Optional
Mean - Required
Required (Standard Deviation)
Lognormal
Optional
Optional
Geometric Mean -
Required
Geometric Standard Deviation
- Required
Triangle
Required
Required
Mode - Required
Not used
Exponential
Required
Optional
Mean - Required
No used
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90
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6. OUTPUT FILES
APEX produces the following six output files:
1. Log file;
2. Hourly Exposure file;
3. Hourly Dose file;
4. Profile Summary file;
5. Microenvironment Summary file;
6. Output Table file; and
7. Sites file.
Most of these output files can be opened and reviewed using a text editor. The larger files,
Hourly Exposure and Hourly Dose, may need a spreadsheet or other program. Details of each
of these output files are provided in the following sections. Additional discussion and a
description of how these files were set up in the Params file can be found in Sections 5.2.1 and
5.2.4.
6.1 Log File (Unit 25)
The Log file records the following information as a model run progresses:
Input files used;
Model parameters used;
Number of diaries available to match each simulated person (or profile);
Model execution time (sec.);
Sectors in the study area;
• Air districts in the study area;
• Temperature zones in the study area:
Mappings of sectors to air districts and temperature zones;
Statistical summaries of each simulated person (or profile); and
Output summary tables.
If a model run stops abnormally, a error message will be written to the log file. The user should
review the Log file after a run to ensure that a model run is executed and terminated normally
and the output results are valid. Note that output summary tables in this file are exactly the
same as the tables in the Output Table file.
6.2 Hourly Exposure File (Unit 26)
The Hourly Exposure file contains hourly time series of exposure concentrations for each
simulated person or profile. Each record provides 24 hourly exposure values for a simulation
day in the following format:
Profile number—Sequential index number for simulated individual
Day number—Sequential index number for the day of the simulation
• Year—Part of the date for the simulated day
Month—Part of the date for the simulated day
Day—Part of the date for the simulated day
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91
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Hour 1—Mean exposure concentration from midnight to 1 a.m. for the profile on that day
Hour 2, etc.—Mean exposure concentration from 1 a.m. to 2 a.m., etc.
Hour 24—Mean exposure concentration from 11 p.m. to midnight
The units of exposure concentrations are the same as those of the air quality data. Note that
the hourly exposure file could be very large if a large number of profiles are simulated. The user
could block generation of the hourly exposure file by setting the HourlyOut parameter to NO in
the parameter file.
6.3 Hourly Dose File (Unit 27)
The Hourly Dose file contains hourly time series of doses for each simulated person or profile.
In APEX, dose is defined as the percent of carboxyhemoglobin (%COHB) in the blood. Thus,
as currently formulated, APEX calculates dose only for carbon monoxide.
Each record in Hourly Dose provides 24 hourly dose values for a simulation day in the same
format as the Hourly Exposure file, except the hourly values are in dose rather than
concentration.
The hourly dose file could be very large if a large number of profiles are simulated. The user
could block generation of the hourly dose file by setting the HourlyOut parameter to NO in the
parameter file.
6.4 Profile Summary File (Unit 28)
This file provides a summary of profile characteristics and exposure/dose for each simulated
person. Each record contains values for the following variables for each simulated individual:
Profile number—Sequential index number for simulated individual
HSect—Sector in which the person lives (home)
• WSect—Sector in which the person works (=HSect for non-workers)
HDis—Air quality district for HSect
• WDis—Air quality district for WSect
• Zone—Temperature zone for HSect
DGRP—Demographic group # (1-11) as defined in pNEM/CO
• Age—Age (years)
Gender—Male or female
Race—Such as White, Black, Asian, Native American (NatAm), Other (depending on pop.
files)
Employed—Indicates employment outside the home
Stove—Indicates the presence of a gas stove in the home
Pilot—Indicates the presence of a gas pilot light
• ACHom—Indicates the presence of air conditioning in the home
• ACCar—Indicates the presence of air conditioning in the car
Height—Person height (inches)
• Weight—Body mass (pounds)
Hemoglob—The amount of hemoglobin in the blood (g/ml)
DiffDay—A lung diffusivity parameter used in the COHB calculation (ml/min/torr)
BloodVol—The volume of blood in the body (ml)
HemFac—The change in the hemoglobin level with altitude (1 /ft)
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Endgnl—Endogenous CO production rate (ml/min)
Endgn2—Endogenous CO production rate (ml/min) used only for women between ages of
12 and 50 for half the menstrual cycle
• #Events—Number of diary events covering the simulation period
• AvgExp—Mean exposure concentration over the simulation (ppm or |jg/m3, as specified in
Params file)
• AvgDose—Mean dose over the simulation (blood %COHB level)
MaxExp—Maximum 1-hour exposure concentration over the simulation (ppm or |jg/m3, as
specified in Params file)
MaxDose—Maximum 1-hour average dose over the simulation (blood %COHB level)
The file can be opened using a text editor or imported into a spreadsheet or other file type.
6.5 Microenvironment Summary File (Unit 29)
This file provides the amount of time spent, mean exposure concentration, and maximum
exposure concentration in each microenvironment during the period of simulation, for each
simulated person. Each record in the file contains the following variables:
Profile number—Sequential index number for simulated individual
Microenvironment—Sequential index number for each microenvironment
Minutes—Total time spent in the microenvironment by the profile
MeanConc—Average (mean) concentration during the time spent in the microenvironment
(ppm or |jg/m3, as specified in Params file)
MaxConc—Maximum concentration during the time spent in the microenvironment (ppm or
|jg/m3, as specified in Params file)
6.6 Output Tables File (Unit 30)
This file provides 14 summary tables. The first six are exposure summary tables:
1. Non-cumulative person-minutes at each exposure range by microenvironment
2. Cumulative person-minutes at each exposure level by microenvironment
3. Cumulative person-days of daily max 1-hour exposure levels
4. Cumulative person-days of daily max 8-hour exposure levels
5. Cumulative person-days of daily average exposure levels
6. Cumulative # persons at each overall (simulation) average exposure level
The remaining eight are dose summary tables:
1. Cumulative person-days of daily max end-of-hour dose levels
2. Cumulative person-days of daily max 1-hour average dose levels
3. Cumulative person-days of daily max 8-hour average dose levels
4. Cumulative person-days of daily average dose levels
5. Cumulative # persons at each overall (simulation) average dose level
6. Cumulative person-hours at each end-of-hour dose level
7. Non-cumulative person-minutes at each dose level
8. Cumulative person-minutes at each dose level
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There are two types of tables in this file: cumulative and non-cumulative time tables. The
cumulative time tables summarize the minutes or days spent by simulated individuals when the
exposure concentration in a microenvironment is equal to or greater than various threshold
levels. The non-cumulative time tables summarize the minutes or days spent by simulated
individuals when exposure is within various ranges.
In the follow sections, each of the 14 summary tables is discussed in more detail.
Table #1—Non-cumulative minutes at each exposure range by microenvironment
This table lists the total minutes spent by all simulated persons in each microenvironment when
exposure concentration is within various ranges. The bounds of a range are specified at the top
of each column and the top of the next column to the right (Figure 6-1). For each
microenvironment, the table provides three rows of data for the following three variables:
Minutes—The number of person-minutes summed over all the simulated persons that are
spent in the specified microenvironment and that fall within the exposure concentration
range bounded by the values indicated at the top of the column and the top of the next
column to the right;
Row_%—The percent of the minutes spent in the specified microenvironment that fall within
the exposure concentration range; and
• Tot_%—the percent of the total minutes that are spent in the microenvironment and that fall
within the exposure concentration range.
Figure 6-1. Example Portion of Table #1 in Output Table File ("Truncated" View)3
Non-cumulative minutes at each exposure level by microenvironment, for
N = 2000 Profiles
Level: 0.0000 2.0000 4.0000 6.0000 8.0000
Micro
0
Minutes
0 .
0 .
0 .
0 .
0 .
0
Row %
NaN
NaN
NaN
NaN
NaN
0
Tot %
0 . 0000
0 . 0000
0.0000
0 . 0000
0.0000
1
Minutes
37602112 .
35900088 .
32791732 .
26165204.
18736580.
1
Row %
21 .2988
20 . 3347
18 . 5741
14 . 8206
10 . 6129
1
Tot %
1.2713
1 .2138
1 .1087
0 .8846
0.6335
2
Minutes
3911714 .
2669300 .
1258124 .
678414 .
431163.
2
Row %
40 . 9246
27 . 9264
13 .1626
7 .0976
4 .5109
2
Tot %
0 .1323
0.0902
0 . 0425
0 . 0229
0 .0146
3
Minutes
951714 .
823961 .
593331.
397681.
262075.
3
Row %
28.5896
24.7519
17 . 8237
11 . 9464
7.8728
3
Tot %
0 . 0322
0 . 0279
0 . 0201
0.0134
0.0089
aBecause this table is truncated (i.e., it actually extends to the right), not all columns are visible and
Row % does not add to 100%.
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Table #2—Cumulative minutes at each exposure level by microenvironment
This table is similar to Table #1, except that it reports the cumulative person-minutes that are
spent in a microenvironment with an exposure concentration that equals or exceeds the value
indicated at the top of the column.
Tables #3—Cumulative Person-days of Daily Max 1-Hour Exposure levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum 1-hour (hourly) average
exposure concentration that equals or exceeds the value indicated at the top of the column
(Figure 6-2). The definitions of variables in Table #3 are provided in Table 6-1.
Figure 6-2. Example of Table #3 in Output Table File
Cumulative Person-days of Daily Max 1-Hour Exposure levels for N = 2000 Profiles,
with Area Population = 44732
Leve1:
0 .000
5.000
10.000
20.000
30
000
40
000
Counts(Pop)
0 .164E+08
0 .158E+08
0.803E+07
0.845E+06 0
311E+06 0
155E+0 6
#Meet(Pop)
44732
44732
44732
44732
44732
42741
%Meet(Pop)
100 .000
100.000
100.000
100.000
100
000
95
550
Mean
366.000
353.592
179.612
18.880
6
945
3
462
Std.Dev.
0 .000
28.169
116.865
9.762
4
155
2
572
CV
0 .000
0.080
0 . 651
0.517
0
598
0
743
Minimum
366.000
197.000
27 . 000
2.000
1
000
0
000
10.0 %ile
366.000
321.000
62.000
9.000
3
000
1
000
25.0 %ile
366.000
360.000
81.000
12.000
4
000
2
000
50.0 %ile
366.000
365.000
127.000
17.000
6
000
3
000
75.0 %ile
366.000
366.000
315.000
23.000
9
000
5
000
90.0 %ile
366.000
366.000
363.000
31. 900
12
000
7
000
95.0 %ile
366.000
366.000
365.000
39.000
15
000
9
000
99.0 %ile
366.000
366.000
366.000
52.000
21
000
12
990
Maximum
366.000
366.000
366.000
74.000
27
000
18
000
Me an (%)
100 .000
96.610
49.074
5 .158
1
898
0
946
Min (%)
100.000
53.825
7.377
0.546
0
273
0
000
Max (%)
100 .000
100.000
100.000
20.219
7
377
4
918
Counts(Sim)
0.732E+06
0.707E+06
0.35 9E+ 0 6
0 . 37 8E+05 0
139E+05 0
692E+04
#Meet(Sim)
2000
2000
2000
2000
2000
1911
Table #4—Cumulative person-days of daily max 8-hour exposure levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily maximum 8-hour average exposure
concentration that equals or exceeds specified levels. The table is the same as Table #3
(Figure 6-2) except that the exposure metric is the daily max 8-hour average exposure
concentration.
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Table 6-1. Definitions of Variables in Summary Tables
Counts(pop)
The number of study area person-days for which the exposure metric is equal to or
greater than the level specified at the top of each column of the table.
#Meet(pop)
The number of persons in the study area whose exposure metric is equal to or
greater than the level specified at the top of each column at least once during the
period of simulation.
%Meet(pop)
The percent of the population in the study area whose exposure metric is equal to or
greater than the level specified at the top of each column at least once during the
period of simulation.
Mean
The average of the number of days for each simulated person for which the exposure
metric is equal to or greater than the level specified at the top of each column.
Std. Dev.
The standard deviation of the number of days for each simulated person for which
exposure metric is equal to or greater than the level specified at the top of each
column.
CV
The coefficient of variation, which is the ratio of the standard deviation to the mean.
Minimum
The minimum number of days for any simulated person for which the exposure
metric is equal to or exceeds the level specified at the top of each column.
%ile
The nth percentile value of the number of days for each simulated person for which
the exposure metric is equal to or exceeds the level specified at the top of each
column.
Maximum
The maximum number of days for any simulated person for which the exposure
metric is equal to or exceeds the level specified at the top of each column.
Mean(%)
The average percent of days during the period of simulation for which a simulated
person's exposure metric is equal to or exceeds the level specified at the top of each
column. (This variable is calculated by dividing the Mean by the total number of days
in the simulation period and then multiplying by 100.)
Minimum(%)
This variable represents the minimum percent of days during the period of simulation,
in which a simulated person experience exposure at or above a level specified at the
top row of each column of a table. This variable is calculated by dividing the
Minimum by the total number of days in the simulation period and then multiplying by
100.
Maximum(%)
The maximum percent of days during the period of simulation for which a simulated
person's exposure metric is equal to or exceeds the level specified at the top of each
column. (This variable is calculated by dividing the Maximum by the total number of
days in the simulation period and then multiplying by 100.)
Counts(Sim)
The number of simulated person-days for which the exposure metric is equal to or
exceeds the level specified at the top of each column.
#Meet(Sim)
The number of simulated persons for whom the exposure metric is equal to or
exceeds the level specified at the top of each column at least once during the period
of simulation.
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Table #5—Cumulative person-days of daily average exposure levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, with a daily average exposure concentration that
equals or exceeds specified levels. The table is the same as Table #3 (Figure 6-2) except that
exposure metric is the daily average exposure concentration.
Table #6—Cumulative number of persons at each overall average exposure level
This table provides a statistical summary of cumulative numbers of both simulated persons and
people in the study area whose overall average exposure concentrations equal or exceed
specified levels. The overall average exposure concentration is the average of hourly exposure
concentrations over the whole period of simulation. An example of this table is provided in
Figure 6-3. The definitions of the variables in this example can be found in Table 6-1.
Figure 6-3. Example of Table #6 in the Output Table File
Cumulative
# Persons at each
Overall Average Exposure
level for
N = 2000
Profiles,
with Area Populat
ion = 44732
Leve1:
0 .000
0.500
1.000
1.250
1.500
1.750
Counts(Pop)
0 . 447E+05
0 . 447E+05
0 . 447E+05
0 . 447E+05
0.447E+05 0
447E+05
#Meet(Pop)
44732
44732
44732
44732
44732
44732
%Meet(Pop)
100 .000
100.000
100.000
100.000
100.000
100.000
Counts(Sim)
0.200E+04
0 . 200E+04
0 . 200E+04
0 . 200E+04
0.200E+04 0
200E+04
#Meet(Sim)
2000
2000
2000
2000
2000
2000
Table #7—Cumulative person-days of daily max
end-of-hour dose levels
This table provides a statistical summary of the
cumulative person-days for both simulated persons
and the population in the study area, for which the
daily maximum end-of-hour dose is equal to or exceeds specified levels. The format of the table
is the same as Table #3 (Figure 6-2). The definitions of the variables in this table can be found
in Table 6-1.
Table #8—Cumulative person-days of daily max 1-hour dose levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily maximum 1-hour average dose
is equal to or exceeds specified levels. The format of the table is the same as Table #3 (Figure
6-2). The definitions of the variables in this table can be found in Table 6-1.
Table #9—Cumulative person-days of daily max 8-hour dose levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily maximum 8-hour average dose
is equal to or exceeds specified levels. The format of the table is the same as Table #3 (Figure
6-2). The definitions of variables in this table can be found in Table 6-1.
Note that Table #7 through #13 are
produced only for CO dose calculation.
For other pollutants, dose calculation
should be turned off.
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Table #10—Cumulative person-days of daily average dose levels
This table provides a statistical summary of the cumulative person-days, for both simulated
persons and the population in the study area, for which the daily average dose is equal to or
exceeds specified levels. The format of the table is the same as Table #3 (Figure 6-2). The
definitions of the variables in the table can be found in Table 6-1.
Table #11—Cumulative # persons at each overall average dose level
This table provides a statistical summary of cumulative numbers of both simulated persons and
the people in the study area whose overall average doses are equal to or exceed a specified
level. The overall average dose is the average of hourly dose levels over the whole period of
simulation. The format of this table is the same as Table #6 (Figure 6-3). The definitions of the
variables in this table can be found in Table 6-1.
Table #12—Cumulative person-hours at each end-of-hour dose level
This table provides a statistical summary of the number of person-hours, for both simulated
persons and the population in the study area, for which each end-of-hour dose level is equal to
or exceeds specified levels. The format of this table is the same as Table #3 (Figure 6-2). The
definitions of the variables in the table can be found in Table 6-1, except that the time units are
hours rather than days.
Table #13—Non-cumulative minutes at each dose level
This table provides a statistical summary of cumulative person-minutes, for both simulated
persons and the population in the study area, for which the dose (i.e., blood %COHb level) is
within a specified range. The bounds of the dose range are specified by the levels at the top of
each column and the top of the next column to the right. The format of this table is similar to
the exposure summary table, Table #3 (Figure 6-2). The definitions of the variables in this table
are similar to those found in Table 6-1, except that the time units are minutes rather than days.
Table #14—Cumulative minutes at each dose level
This table provides a statistical summary of cumulative person-minutes spent by both simulated
persons and the population in the study area, for which the dose (i.e., blood %COHb level) is
equal to or exceeds specified levels. The format of this table is the same as Table #3 (Figure 6-
2). The definitions of the variables in this table are similar to those found in Table 6-1, except
that the time units are minutes rather than days
6.7 Sites File (Unit 31)
The Sites output file lists the sectors, districts, and zones in the study area, and identifies the
mapping between them. Thus, each record contains the following:
Sector#—Sector ID
Latitude—Sector latitude
Longitude—Sector longitude
Sectorname—Sector name
• Air#—Air district ID
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• Airdistance—Distance from district to sector
• Airlatitude—Air district latitude
• Airlongitude—Air district longitude
• Airname—Air district name
• Tern#—Tempurature zone ID
• Temdistance—Distance from zone to sector
• Temlatitude—Zone latitude
• Temlongitude—Zone longitude
• Temname—Zone name
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