Simulation Program for Estimating Chemical Emissions from
Sources and Related Changes to
Indoor Environmental Concentrations in Buildings with
Conditioned and Unconditioned Zones
IECCU User's Guide
Software version: 1.1
Document version: 1.1
Released in 2019
Developed for
U.S. EPA Office of Pollution Prevention and Toxics, Washington, DC
by
ICF, Durham, NC
Under contract EP-W-12-010
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Contents
Contents ii
Notes on release of version 1.1 viii
Acknowledgments ix
Disclaimer x
1. Introduction 1
1.1 What is IECCU? 1
1.2 Intended users 2
1.3 Potential applications 2
1.4 Limitations 2
1.5 Appendix for Tutorials 4
2. Software installation 5
2.1 System requirements 5
2.2 Installation 5
2.3 Uninstallation 5
2.4 Reporting Errors 6
3. User interface 7
3.1 User interface design 7
3.2 Main menu and speed buttons 8
3.3 Pages and folder tabs 9
3.4 Model files 11
3.5 Simulation modes 12
3.6 Steps for using IECCU 12
4. Program specifications 13
4.1 Building and air exchange 13
4.1.1 Building configuration 13
4.1.2 Air exchange flows 13
4.1.3 Location of HVACsystem 13
4.1.4 Temperature profiles in unconditioned zones 13
4.2 Sources and sinks 14
4.3 Particulate matter 14
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4.3.1 Airborne particulate matter (PM) 14
4.3.2 Settled dust 14
4.4 Gas-phase chemical reactions 15
4.5 Simulation conditions 15
5. Tutorials 16
6. Technical details 17
6.1 General mass balance equation 17
6.2 Built-in building configurations 18
6.3 Indoor-outdoor and zone-to-zone air flows 18
6.4 Indoor temperatures 19
6.4.1 User-defined temperature functions 19
6.4.2 Imported temperature data table 20
6.5 Source models 20
6.5.1 Empirical source models 20
6.5.2 Generic models for chemical emissions from water and aqueous solutions 21
6.5.3 Emission rate table 22
6.5.4 Application-phase models 23
6.5.5 Diffusion-based models 24
6.6 Temperature-dependent emission parameters 26
6.6.1 Partition coefficient 26
6.6.2 Solid-phase diffusion coefficient 27
6.7 Sink models 28
6.7.1 First-order reversible Langmuir sink 28
6.7.2 Freundlich reversible sink 29
6.7.3 First-order irreversible sink 29
6.7.4 Molecular diffusion-based sink 29
6.8 Airborne PM 29
6.9 Settled dust 30
6.9.1 Mass transfer between room air and the exposed hollow sphere 31
6.9.2 Mass transfer within the particle 32
6.9.3 Thicknesses and number of concentric hollow spheres 32
6.10 Gas-phase chemical reactions 33
6.10.1 First-order reaction 33
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6.10.2 Second-order reaction 34
6.10.3 Temperature-dependence of reaction rate constants 34
6.11 Mass transfer rates as an option for simulation output 35
6.12 Mass balance as an option for simulation output 36
7. Parameter estimation assistance 38
7.1 Compiled data under the Params menu 38
7.2 QSAR and empirical models under the Tools menu 38
8. Using default building characteristics 41
References 43
Appendix: IECCU Tutorials 46
Introduction 51
Tutorial 1: Creating a simplest model 52
1.1 Objective 52
1.2 Case description 52
1.3 Create the model 53
1.3.1 Define building configuration 53
1.3.2 Define ventilation flow rate 54
1.3.3 Define the source 55
1.3.4 Define simulation conditions 57
1.4 Compile the model 59
1.5. Inspect the model 59
1.6 Run the model 60
1.7 Examine the results 60
Tutorial 2: Using enhanced ventilation 62
2.1 Objective 62
2.2 Case description 62
2.3 Create the model 62
2.4 Save, compile and run the model 63
Tutorial 3: TCPP emissions from SPF installed in attic 65
3.1 Objective 65
3.2 Case description 65
3.3. Create the model 67
3.3.1 Select building configuration 67
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3.3.2 Define airflow matrix 68
3.3.3 Define the source 69
3.3.4 Define the sink 70
3.3.5 Define simulation conditions 72
3.4 Save, compile, inspect, and run the model 73
Tutorial 4: Simulating temperature-dependent TCPP emissions 75
4.1 Objective 75
4.2 Case description 75
4.3 Create the model 76
4.3.1 Define temperature profile in attic 76
4.3.2 Modify the SPFsource 79
4.3.3 Define temperature-dependent functions for partition coefficient 81
4.3.4 Define temperature-dependent functions for diffusion coefficient 84
4.3.5 Select output data types 85
4.4 Save, compile, inspect and run the model 85
Tutorial 5: Using the batch mode 88
5.1 Objective 88
5.2 General steps 88
5.3 Case description 88
5.4 Run batch 88
5.4.1 Create an empty folder 88
5.4.2 Save or copy model files to that folder 88
5.4.3 Run batch simulations 89
5.4.4 Retrieve simulation results 93
Tutorial 6: Gas-phase chemical reactions 94
6.1 Objective 94
6.2 Case description 94
6.3 Create the model 95
6.3.1 Define building and ventilation 95
6.3.2 Define the first-order decay source 95
6.3.3 Define the chemical reaction 96
6.3.4 Define simulation conditions 98
6.4 Save, compile, inspect and run the model 98
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Tutorial 7: TCPP interactions with airborne particulate matter (PM) 100
7.1 Objective 100
7.2 Case description 100
7.3. Create the model 100
7.3.1 Open model MyTCPP-l.lEC 100
7.3.2 Define airborne PM 101
7.3.3 Define deposition rate constants and initial PM mass concentrations 102
7.3.4 Select output data types 103
7.4 Save, compile, inspect, and run the model 104
Tutorial 8: TCPP interactions with settled dust 105
8.1 Objective 105
8.2 Case description 105
8.3 Create the model 105
8.3.1 Load model MyTCPP-PM.lEC 105
8.3.2 Define settled dust 105
8.3.3 Define simulation conditions 109
8.4 Save, compile, inspect and run the model 109
Tutorial 9: Application-phase simulation Ill
9.1 Objective Ill
9.2 Case description Ill
9.3 Create the model 112
9.3.1 Define building configuration 112
9.3.2 Define airflow matrices for base and enhanced ventilation 112
9.3.3 Define application-phase model 113
9.3.4 Define simulation conditions 114
9.4 Save, compile, inspect and run the model 114
Tutorial 10: Importing indoor-outdoor and zone-to-zone air flow data 116
10.1 Objective 116
10.2 Case description 116
10.3 Create the model 116
10.4 Save, compile, inspect and run the model 117
Tutorial 11: Importing indoor temperature data 119
11.1 Objective 119
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11.2 Case description 119
11.3 Create the model 120
11.4 Save, compile, inspect and run the model 120
Tutorial 12: Including an HVAC system 122
12.1 Objective 122
12.2 Case description 122
12.3 Create the model 123
12.4 Compile and run the model 127
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Notes on release of version 1.1
IECCU Version 1.1 was derived from 1.0 by adding several new features intended to enhance
the performance of this program. Some of the improvements were made based on users' input.
The new features are as follows.
• Added two new options for simulation output
o Mass transfer rates at each time point (described in Section 6.11)
o Material mass balance at each time point (described in Section 6.12)
• Added three sets of compiled data under the Params menu (described in Section
7.1)
o Solid-phase diffusion coefficients: 1596 sets of data (Huang et al., 2017)
o Solid/air partition coefficients: 341 sets of data (Holmgren et al., 2012)
o Partitioning of SVOCs between indoor air and settled dust: 150 sets of data
(Weschler & Nazaroff, 2010)
• Added 11 empirical and QSAR models under the Tools menu for estimating key
parameters for VOCs and SVOCs (described in Section 7.2)
o Five models for estimating solid-phase diffusion coefficient
o Two models for estimating solid/air partition coefficient
o Two models for estimating aerosol/air partition coefficient
o Two models for estimating dust/air partition coefficient
• Added 27 sets of default building characteristics (i.e., building volume and air
exchange rate) based on EPA's Exposure Factors Handbook (described in Sections
4.1.1 and 8)
o Six residential building types
o Twenty-one non-residential building types
• Added source type 17 "Emission rate table" to page / .
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Acknowledgments
IECCU Version 1.0 was written with Lazarus 1.6.4 (www.lazarus-ide.org), an integrated
development environment (IDE) for Free Pascal 3.0.2. This program was re-compiled with
Lazarus 2.02 (Free Pascal 3.0.4) for the release of Version 1.1.
Most button icons (glyphs) were downloaded from the website
http://www.famfamfam.com/lab/icons/silk/ and were developed by Mark James of
Birmingham, UK.
The deployment package was created with InstallSimple PRO 3.0 (http://installsimple.com/).
We thank the following persons for testing the beta version of this program and commenting
on the documentation: Tom Armstrong, Charles Bevington, Michael Koontz, Xiaoyu Liu, Mark
Mason, Dustin Poppendieck, Shen Tian, and Jianyin Xiong.
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Disclaimer
The computer software described in this document was developed by the U.S. EPA for its own
use and for specific applications. The Agency makes no warranties, either expressed or implied,
regarding this computer software package, its merchantability, or its fitness for any particular
purpose, and accepts no responsibility for its use. Mention of trade names and commercial
products does not constitute endorsement or recommendation for use. The views expressed in
this document do not necessarily represent the views or policies of the Agency.
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1. Introduction
1.1 WhatislECCU?
IECCU, pronounced l-E-Q, stands for Simulation Program for Estimating Chemical Emissions
from Sources and Related Changes to Indoor Environmental Concentrations in Buildings with
Conditioned and Unconditioned Zones. The indoor environment includes concentrations of
chemical substances within vapor-phase indoor air, suspended particulates, settled dust and
how chemicals present in these media are transported throughout a building.
This program serves two purposes: (1) as a general-purpose indoor exposure model in buildings
with multiple zones, multiple chemicals and multiple sources and sinks, and (2) as a special-
purpose concentration model for simulating the effects of sources in unconditioned zones on
the indoor environmental concentrations in conditioned zones. A typical application of the
latter case is the chemical emissions from spray polyurethane foam (SPF) installed in attics,
crawlspaces, basements, or garages.
This program has several key features:
• Unconditioned zones (e.g., attics, crawlspaces, basements, and garages) can be
modeled. Temperatures in these zones are subject to diurnal and seasonal fluctuations.
• Partition and diffusion coefficients of the source and rate constants of gas-phase
chemical reactions to change in response to the temperature fluctuation in
unconditioned zones can be modeled.
• It can simulate interactions of gas-phase semi-volatile organic compounds (SVOCs) with
airborne particles and settled dust in a multiple zone environment.
• It allows the user to import zone temperature data and indoor-outdoor and zone-to-
zone air flow data from other models such as CONTAM and COMIS.
IECCU was developed by combining existing code and algorithms implemented in EPA's higher
tier indoor exposure models IAQX (EPA, 2000) and i-SVOC (EPA, 2013) and by adding new
components and methods. The general approach and key technical aspects in developing this
program are described by Bevington et al. (2017).
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1.2 Intended users
This program is for advanced users who are familiar with indoor exposure modeling and indoor
exposure assessment. A user may choose to use IECCU when exploring emission profiles of
VOCs and SVOCs, interaction of SVOCs with airborne particulate matter and dust, and transport
across multiple building zones. IEECU, unlike CEM and other indoor exposure models, does not
yet provide default values for input parameters. Model inputs can be derived from empirical
data or modeled estimates. It is the user's responsibility to choose appropriate modeling inputs
for the chemical and exposure scenario of interest.
1.3 Potential applications
This program complements and supplements EPA's Consumer Exposure Model (CEM) and
higher-tier Indoor Exposure models (such as IAQX, i-SVOC, and MCCEM) by providing a
modeling environment with several unique features. Examples of potential applications are as
follows:
• Modeling sources such as emissions from building insulation, appliances, stored supplies
located in unconditioned zones (e.g., attics, crawlspaces or basements).
• Modeling sources such as emissions from application-phase such as SPF insulation or
painting interior walls and furniture with oil-based or latex paint.
• Modeling emissions from SVOC sources such as vinyl flooring, carpeting, and caulking
material, in multiple zone buildings.
• Modeling formaldehyde emissions from engineered wood furniture in multiple zone
buildings.
• Modeling interactions of SVOCs with airborne PM and settled dust in multiple zone
buildings.
• Modeling short-term emissions that involve chemically reactive species.
• Indoor exposure modeling that requires importing air movements and/or zone
temperature data from other models.
1.4 Limitations
Program IECCU Version 1.1 has the following limitations:
The current version of IECCU does not include any models for behind-the-wall sources, such as
SPF insulation applied to the walls and covered by gypsum board. The chemicals emitted from
these types of sources can enter the living area by either convective transfer (air leakage) or
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molecular diffusion through the gypsum board layer. More data is needed to develop models
for such sources.
Inter-zonal air flows, such as the leakage from attic to living area, play an important role in
carrying air pollutants from unconditioned zones to conditioned zones. Relatively simple
predictive models for directional inter-zonal air flows are unavailable. Currently, this program
does not have built-in empirical models for inter-zonal air flows. The only way to incorporate
time-varying inter-zonal flows into a model is to import data from other models.
This program allows temperature-dependent partition and diffusion coefficients only in
unconditioned zones. The program treats the temperature in occupied zones as a constant.
This program has limited capability to handle gas-phase chemical reactions. It cannot handle
complex cases such as photochemical models. Nor can it simulate chemical reactions in
condensed phases (i.e., solid materials and aqueous solutions).
The temperature in unoccupied zones (i.e., attic, crawl space, unheated basement, and garage)
is subject to diurnal and seasonal fluctuations, which create a temperature gradient within the
source. Currently, this program assumes that the temperature inside the source material
follows the seasonal air temperature pattern. This assumption may overestimate the effect of
temperature on the emissions. A possible solution to this problem is to model the heat transfer
in the source and between the source and air.
This program can simulate interactions of airborne particles and SVOCs for multiple particle
types (e.g., different particle sizes) in a multiple-zone environment. However, it cannot simulate
such interactions for multiple chemicals. In other words, if a model contains more than one
SVOCs that interact with airborne particles, they must be simulated separately by creating a
model for each SVOC. Such restriction does not apply to settled dust, however.
This program uses a diffusion-based mass transfer model for SVOC interactions with settled
dust. Due to the computational complexity of this model, dust generation and removal are not
considered during a simulation.
This program does not provide the user with default values for input parameters. Parameters
are being developed over time as new empirical and modeling approaches emerge. For
example, a recent paper compiled existing measured data on Diffusion Coefficients from Solid
Materials and developed an estimation approach (QSAR) for over 1,000 chemicals (Huang et al.,
2017). It is the user's responsibility to choose proper values.
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1.5 Appendix for Tutorials
Twelve tutorials are provided in the Appendix of this User's Guide. The users are encouraged to
go through at least some of them to familiarize themselves with the user interface and key
features of the program.
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2. Software installation
2.1 System requirements
This program is compatible with Windows 7, 8, and 10 operating systems and requires a
minimum of 10 MB free disk space. The screen resolution should be at least 1024 x 768 pixels.
Internet connection is required only for downloading the installation package from the
designated website.
2.2 Installation
If your computer is connected to a local network, you may need Administrative Privileges to
install this program. Contact your IT support staff for details.
The setup program is available for download as a compressed (zipped) folder. Once
downloaded, right-click the folder name and then select "Extract" or "Extract all" from the pop-
up menu.
The file name of the setup program is "IECCU_setup.exe". Double click the file name and then
follow instructions. The default target folder for installation is:
C:\Program Files (x86)\EPA_IECCU\
During installation, the setup program will create an icon or tile on your desktop screen. Click
the icon or tile to start the simulation program. You can also start the program from Windows'
"All programs" or "All apps" menu.
2.3 Uninstallation
To uninstall this program, right-click the application icon or application name, select "Uninstall",
and then follow the instructions.
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2.4 Reporting Errors
Please forward any questions, comments, suggestions, and errors encountered to:
Eva Wong
U.S. EPA Office of Pollution Prevention and Toxics
wong.eva@epa.gov
+202-564-0447
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3.2 Main menu and speed buttons
Menu items and speed buttons are summarized in Table 1.
Table 1. Menu items, speed button positions, and their functionalities.
Menu
Item
Submenu Item
Speed button
Position1
Functionality
New
1
Create a new model from scratch
New with default
2
Create a new model with default building
characteristics
File
Open
3
Open an existing model
Save
4
Save current model to a file
Save as
N/A
Save current model with a different file name
Close
N/A
Quit this program
Page navigator
5
Display all pages with a tree structure
Model
Compile
6
Check model errors
Inspect
7
Compilation report
Run normal
8
Run a simulation at normal speed
Run
Run slow
9
Run a simulation at a slower speed
Run batch
10
Run multiple simulations unattended
Solid-phase diffusion
coef.
N/A
Compiled data
Data
Solid/air partition coef.
N/A
Compiled data
Dust/air partitioning of
SVOCs
N/A
Compiled data
1 From left to right
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Table 1. Menu items, speed button positions, and their functionalities (cont.)
Menu
Item
Submenu Item
Speed button
Position
Functionality
Solid-phase diffusion coef.
N/A
Empirical and QSAR models
Solid/air partition coef.
N/A
Empirical and QSAR models
Tools
Aerosol/air partition coef.
N/A
Empirical and QSAR models
Dust/air partition coef.
N/A
Empirical and QSAR models
Help
Acknowledgments
About this program
N/A
N/A
3.3 Pages and folder tabs
The user interface contains 16 input pages and six output pages, which are grouped into eight
folders, as summarized in Tables 2 through 7.
Table 2. Functionalities under folder tab < (1) Building & Environment >.
Page name
Functionalities
a) Air zones
Building configuration, zone names, zone volumes
b) Ventilation (1)
Base air change flows, enhanced air change flows
c) Ventilation (2)
Imported air flow data from other models
d) Temperature (1)
User-defined zone temperatures
e) Temperature (2)
Imported zone temperatures from other models
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Table 3. Functionalities under folder tab < (2) Sources >.
Page name
Functionalities
a) Empirical source
models
Five empirical source models commonly used for short-term
emissions, two models for emission from water, emission rate
table for irregular source
b) Application-phase
Four models for chemical emissions during SPF application
c) Diffusion model
Diffusion-based model for long-term emissions
d) Temperature-
dependent K & D
Temperature-dependent partition and diffusion coefficients
Table 4. Functionalities under folder tab < (3) Sinks >.
Page name
Functionalities
a) Surface adsorption
Three surface sorption models
b) Diffusion sink
Diffusion-based sink model
Table 5. Functionalities under folder tab < (4) Airborne PM >.
Page name
Functionalities
a) Airborne PM
Properties of PM and chemicals
b) Airborne PM
Deposition rate constants and initial particle-phase
(cont.)
concentrations
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Table 6. Functionalities under folder tabs with a single page.
Page name
Functionalities
(5) Settled dust
Properties of settled dust and chemicals
(6) Chemical
reactions
First and second-order reactions; hydrolysis
(7) Simulation
Initial air concentrations, simulation duration, output data points,
conditions
and output data types
Table 7. Functionalities under folder tab < (8) Output >.
Page name
Functionalities
a) Air: gas-phase
Gas-phase chemical concentrations
b) Air: particle phase
Chemical concentrations in airborne particles
c) Air: PM masses
Mass concentrations of airborne particles
d) Settled dust
Chemical concentrations in settled dust
e) Temperature profiles
Temperature profiles in unconditioned zones
f) Time-varying K & D
Temperature dependent partition and diffusion coefficients
g) Transfer rates
Mass transfer rates for emission, adsorption, absorption, and
chemical reactions
h) Mass balance
Mass balance calculation results at each output points.
3.4 Model files
A model created by the user can be saved to an external file for future retrieval. This feature
allows the user to enter a set of parameters (e.g., building configuration and air flow matrix)
only once.
The model files use file extension ".IEC. When you save a file, simply type the file name and
there is no need to type the file extension. For example, if you type in "MyModel" and then
click , the model file will be saved as "MyModel.IEC".
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3.5 Simulation modes
Three simulation modes are available: , , and . The first
two modes run a single simulation at a time. Most simulations should be done with . The mode is for models with "stiff" differential equations. In other words,
if numerical difficulty is encountered with , may resolve the problem.
The batch mode allows the user to run multiple models unattended. See Tutorial 5 for details.
3.6 Steps for using IECCU
Making a simulation with IECCU involves five steps:
• Create a model
• Compile the model (i.e., error-checking by the program)
• Inspect the model (i.e., error-checking by user)
• Run the model
• Examine the results.
More details are illustrated in Tutorial 1.
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4. Program specifications
4.1 Building and air exchange
4.1.1 Building configuration
This program provides nine types of building configurations with one to three zones. See
Section 6.2 for details.
This program also provides the user with the option to create a new model with default
building volumes and air exchange rate, which are from EPA's Exposure Factors Handbook (EPA,
2018). The default values can be accessed by select / from the main
menu or click the speed button (second from left). See more details in Section 8.
4.1.2 Air exchange flows
This program allows three types of air exchange flows:
Constant air flows — a single air flow matrix
Enhanced ventilation in early hours followed by constant flows — two air flow matrixes
Time-varying air flows — data is imported from an external file.
4.1.3 Location of HVAC system
The building configuration can be with or without a heating, ventilation and air-conditioning
(HVAC) system, which can be located either outside the building or in an unconditioned zone
(e.g., garage, crawl space, or attic).
4.1.4 Temperature profiles in unconditioned zones
The temperature profile in an unconditioned zone can be constant, diurnal, seasonal and the
combination of the last two. See Section 6.4 for more details.
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4.2 Sources and sinks
Available source and sink models in the IECCU program are listed in Table 8.
Table 8. List of source and sink models available in IECCU Version 1.0/1.1
Source/sink category
Number of
models
Model descriptions
Max. number of
models allowed
Source
models
Empirical and other simple
models
Models for application-
phase simulation
Diffusion-based models
Sections 6.5.1 - 6.5.3
Section 6.5.4
Section 6.5.5
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10
10
Surface adsorption models
Sink
models Diffusion-based sink
model
Sections 6.7.1-6.7.3
Section 6.7.4
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4.3 Particulate matter
4.3.1 Airborne particulate matter (PM)
This program can simulate up to six types of airborne PM for a single chemical in a multizonal
building. Particles with the same composition but different sizes are treated as different PM
types.
4.3.2 Settled dust
This program can simulate up to six types of settled dust for multiple chemicals in a multizonal
building. Dust particles with different sizes are treated as different dust types. When the same
dust particles interact with two airborne chemicals, the two dust-chemical pairs are treated as
two different dust types.
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4.4 Gas-phase chemical reactions
Reaction orders
First-order, second order
Maximum number of reactants
Maximum number of products
Rate constant types
2
4
Constant or temperature dependent
6
Maximum number of reactions
4.5 Simulation conditions
Non-zero initial air concentrations
Simulation duration
Output data points
Allowed
10 to 20,000 hours
10 to 5,000
Maximum number of differential equations 200
Output data types:
Air concentrations
Chemical concentrations in airborne PM (|ag/m3 air)
Chemical concentrations in airborne PM (|ag/g PM)
Mass concentration of airborne PM (|-ig/m3 air)
Chemical concentrations in settled dust (|ag/g dust)
Temperature profiles in unconditioned zone(s)
Temperature-dependent partition coefficient (dimensionless)
Temperature-dependent diffusion coefficient (m2/h).
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5. Tutorials
Twelve tutorials are provided as the Appendix of this user's Guide. A summary is shown in Table
9. These tutorials show examples of exposure scenarios that could be evaluated using IECCU
and allow users to familiarize themselves with this program and explore its full functionality.
Table 9. List of tutorials.
Tutorial No.
Topic
1
Creating a simplest model
2
Using enhanced ventilation
3
TCPP emissions from SPF installed in attic
4
Temperature-dependent TCPP emissions
5
Using the batch mode
6
Gas-phase chemical reactions
7
TCPP interactions with airborne particulate matter (PM)
8
TCPP interactions with settled dust
9
Application-phase simulation
10
Importing indoor-outdoor and zone-to-zone air flow data
11
Importing indoor temperature data
12
Including an HVAC system
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6. Technical details
6.1 General mass balance equation
The general mass balance equation (Equation 1) for a chemical of interest is used to calculate
the time series of indoor concentrations (Bevington et al., 2017). This equation combines all
processes governing source emissions, convective transfer by bulk air, sorption and re-
remission by indoor sinks, interactions with airborne particles and settled dust and gas-phase
chemical reactions.
v, % = 1% AjEj - lnkl0 Qit C, + Qu ct - a=1 dm - rr ± fi x, (1)
where Vj = volume of zone /'(m3),
C, = air concentration in zone /' (|ag/m3),
t = time (h),
Aj = area of source j in zone /'(m2),
Ej = emission factor for source j in zone /' (|ag/m2/h),
Qik = air flow from zone /' to zone k,i * k (m3/h),
Qki = air flow from zone k to zone /', k * i (m3/h),
Ck = air concentration in zone k (|ag/m3),
dm = sorption rate onto interior surface m in zone /' (|ag/h),
rp = rate of sorption by particulate matter p in zone /' (|ag/h),
xq = rate of gas-phase chemical reaction q in zone /', plus sign for products and minus
sign for reagents (see notes below for units),
Subscripts j, k, I, m, p, and q are summation counters
ni through rt6are item numbers for their respective summations.
When chemical reactions are involved, the mass unit must be in either moles or molecules. For
example, term x in Equation 1 should be in either (mol/m3/h) or (molecules/m3/h) in the rate
calculation.
Note that Equation 1 is the differential form, hence bearing the units of (|_ig/h). The integral
form of the mass balance equation is discussed in Section 6.12.
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6.2 Built-in building configurations
This program provides nine built-in building configurations in two categories: (1) All zones are
conditioned, and (2) With unconditioned zones, as shown in Table 10. An unconditioned zone is
defined as an indoor space where temperature is subject to diurnal, seasonal, or other types of
fluctuations. Examples of unconditioned zones in residential buildings include the attic,
crawlspace, basement, and garage. If a diffusion source is located in an unconditioned zone,
the key source parameters (diffusion and partition coefficients) can change with temperature.
Table 10. lECCU's built-in building configurations.
Category
Conditioned zones
Unconditioned zones
One zone
None
Two zones
None
All zones are conditioned
Three zones (Configuration 1)
None
Three zones (Configuration 2)
None
Living area
Attic
Living area
Crawlspace or basement
With unconditioned zones
Living area
Attic and crawlspace
Living area
Garage
(None)
Motor vehicles
6.3 Indoor-outdoor and zone-to-zone air flows
The indoor-outdoor and zone-to-zone air flows are represented by a (Z+l) x (Z+l) matrix (Q)
where Z is the number of air zones. The ambient air is designated zone 0. Element Q,y (i * j) is
the air flow from zone /' to zone j.
In addition to constant air flows, this program has the following features:
• Allowing a period of enhanced ventilation (page < b) Ventilation (1) >) (See Tutorial 2.)
• Importing air flow data from CSV files generated by other models such as CONTAM and
COMIS (page < c) Ventilation (2) >). (See Tutorial 10.)
18
-------
6.4 Indoor temperatures
This program provides two ways to represent the temperatures in unconditioned zones:
• User-defined sine functions (page < d) Temperature (1) >)
• Imported temperature data table (page < e) Temperature (2) >). (See Tutorial 11).
6.4.1 User-defined temperature functions
Diurnal and seasonal temperature fluctuations are commonly modeled with either sine or
cosine functions. In this program, the sine function (Equation 2) is used. An example of
simulated temperature profile is shown in Figure 2.
T = T0 + Asm[a)(t-a)] (2)
where T= temperature at time t (°C),
To = vertical shift (i.e., average temperature) (°C),
A = amplitude (°C),
2n/aj = period (one day or one year),
t = elapsed time,
a = horizontal shift.
19
-------
50
August 1 = 40 °C
40
30
20
April 2 = 15 °C
Baseline = 15 °C
10
o
-10
February 1 = -10 °C
-20
0
50
100
150
200
250
300
350
400
Elapsed Days
Figure 2. Simulated annual temperature fluctuation with To = 15 °C, A = 25 °C and assuming the
peak temperature occurs on August 1. With zero horizontal shift (i.e., a= 0), the elapsed time
zero is April 2.
6.4.2 Imported temperature data table
This program allows the user to import zone temperature data generated by other models such
as CONTAM and COMIS. It is required that the data table be stored in a comma separated
values (CSV) file (See Tutorial 11).
6.5 Source models
6.5.1 Empirical source models
Empirical source models are often used for short-term emissions. This program includes four
commonly used empirical models: constant emission source, first-order decay source, dual first-
order decay source, and power law (Equations 3 through 6). Brief descriptions on these
empirical models can be found in Guo (2002). Model descriptions are also available within the
program.
R = constat (3)
20
-------
R = A E0 e~k t
R = A M0 k e~kt
R=A(E1 e~kl t + E2 e~k21)
R=A(M1 k± e~kit + M2k2 e~k2 c)
(4a)
(4b)
(5a)
(5b)
(6)
where R = emission rate (|-ig/h),
A = source area (m2),
E0, Ei, E2 = initial emission factor (|ag/m2/h),
Ei = initial emission factor for rapid emissions (|ag/m2/h),
£2 = initial emission factor for slow emissions (|ag/m2/h),
Mo = initial emittable mass of chemical in the source (|ag/m2),
Mi = initial emittable mass of chemical in the source for rapid emission (|ag/m2),
Mi = initial emittable mass of chemical in the source for slow emission (|ag/m2),
k = first-order decay rate constant (h-1),
ki = first-order decay rate constant for rapid emission (h_1),
k2 = first-order decay rate constant for slow emission (h_1),
t = time (h),
a, b = empirical constants.
Equations 4a and 4b are equivalent; so are Equations 5a and 5b.
6.5.2 Generic models for chemical emissions from water and aqueous solutions
The rate of chemical emission from contaminated water or aqueous solution can be described
by the two-resistance theory with Equation 7 or, equivalently, 8 (Layman et al., 1990):
R = A Kog (ClH - C)
where R = emission rate (|ag/h)
A = exposed area of liquid (m2)
Kol = overall liquid-phase mass transfer coefficient (m/h)
21
-------
Kog = overall gas-phase mass transfer coefficient (m/h)
Cl = chemical concentration in water (|ag/m3)
C = chemical concentration in air (|ag/m3)
H = dimensionless Henry's law constant and H = Cg/ Cl at equilibrium.
6.5.3 Emission rate table
An emission source with irregular rates, which cannot be represented by simple mathematical functions,
is handled by using an emission rate table saved in a plain text file (*.txt). The general format of the
table is elapsed time (h) versus emission rate (ng/h). The emission rates, measured or modeled, can be
either at multiple time points or time-averaged values (such as hourly and daily averages). The user is
required to put a statement in the first line of the text file — either "// Time-averaged = YES" or "//
Time-averaged = NO" — to tell IECCU how the input data should be interpreted, as shown in Table 11.
Table 11. Examples of the text file format. The statement at the beginning of the text file tells IECCU
how to interpret the emission rate data.
Type of emission rate data
Rates at different time points Time averaged
// Time-averaged = NO
0 1.2E4
1 3.5E4
2 2.7E4
3 4.1E4
4 9.6E3
// Time-averaged = YES
0 1.2E4
1 3.5E4
2 2.7E4
3 4.1E4
4 9.6E3
If the rates are values at different time points (the left column in Table 11), IECCU interprets the data as
follows:
At elapsed time 0 h, the emission rate is 1.2E4 ng/h;
At elapsed time 1 h, the emission rate is 3.5E4 ng/h;
At elapsed time 2 h, the emission rate is 2.7E4 ng/h;
At elapsed time 3 h, the emission rate is 4.1E4 ng/h;
At elapsed time 4 h, the emission rate is 9.6E3 ng/h;
At any other time t, the emission rate is calculated by linear interpolation.
If the rates are hourly averaged values (the right column in Table 11), IECCU interprets the data as
follows:
Between
elapsed times 0 and
1
h,
the
emission
rate
is 1.2E4
ng/h;
Between
elapsed times 1 and
2
h,
the
emission
rate
is 3.5E4
ng/h;
Between
elapsed times 2 and
3
h,
the
emission
rate
is 2.7E4
ng/h;
Between
elapsed times 3 and
4
h,
the
emission
rate
is 4.1E4
ng/h;
Between
elapsed times 4 and
5
h,
the
emission
rate
is 9.6E3
M-g/h.
22
-------
The difference between these two cases is graphically illustrated in Figure 3.
6.0E+4
Time-averaged = YES
Time-averaged = NO
4.0E+4
2.0E+4
O.OE+O
0
1
2
3
4
5
Time (h)
Figure 3. Depending on the user's statement in the text file, the same data are interpreted
differently. The data are from Table 11.
This source type is available on page / and designated type 17. Please
note the following limitations when using this source type:
• The text file should contain no more than 100 data rows,
• Each model can include only one emission rate table.
6.5.4 Application-phase models
Most source emission models treat the source area as a constant. For sources such as painted
walls and application of spray polyurethane foam insulation, it takes a substantial amount of
time for the source area to increase from zero to the final area. Thus, to predict the short-term
emissions from such sources, the source area should be treated as a variable. The algorithm for
application-phase simulation is described in IAQX (EPA, 2000). Four empirical models can be
used for the emissions from an incremental piece of source:
• Rapid evaporation (i.e., instant emissions)
• First-order decay (Equation 4b)
• Dual first-order decay source (Equation 5b)
23
-------
• Power law model (Equation 6).
Tutorial 9 shows an example of an application-phase simulation.
6.5.5 Diffusion-based models
The emission of a chemical from a solid material and the diffusion of the chemical inside the
solid material are represented by the modified state-space (MSS) method, which divides the
solid phase into a finite number of slices or hollow spheres (Figure 4). More details about the
method development and validation can be found in Guo (2013). This method is more flexible
than other diffusion models because it permits:
• Multiple air zones
• Multiple sources and sinks
• Non-uniform initial concentrations in the source or sink
• Non-zero initial air concentrations.
ALj = 1 urn
Exposed surface /
_
AjL_? = 2 AL2
ALj = 2ALi_1
ALn = 2ALn_j
Figure 4. Representation of diffusion sources by the MSS method (not to scale).
24
-------
Mass transfer between the top slice and room air:
f C ^
Rma=AHa -=L-Cfl
V m/1 /
\ y
(9)
1 1 1
(10)
+ —
m
(11)
where Rma = rate of mass transfer from the top (exposed) slice to air (|ag/h)
A = exposed area of the source or sink (m2)
Ha = overall gas-phase mass transfer coefficient (m/h) from Equation 10 (m/h)
Cmi = SVOC concentration in the top (exposed) slice of the source or sink (|ag/m3)
Kma = solid-air partition coefficient (dimensionless)
C0 = SVOC concentration in room air (|ag/m3).
ha = gas-phase mass transfer coefficient (m/h)
hm = solid-phase mass transfer coefficient, from Equation 11 (m/h)
Dm = solid-phase diffusion coefficient (m2/h)
ALi = thickness of the top (exposed) slice (m).
Note that the solid-phase mass transfer coefficient is not only a function of diffusion coefficient
but also a function of the thickness of the slice.
Mass transfer between two adjacent slices of the same material:
where R-,j = rate of mass transfer from slice /' to slice j (|ag/h)
hm = solid-phase mass transfer coefficient (m/h)
Dm = solid-phase diffusion coefficient (m2/h)
AU, ALj = thicknesses of slices /' and j (m)
[AU+ ALj)/2 = travel distance for inter-slice diffusion (m)
Cmi = concentration in slice /' (|ag/m3)
Cm] = concentration in slice j (|ag/m3).
Rt]=Ahm(Cm-Cmj)
(12)
(13)
25
-------
Thicknesses and number of slices
The thickness of the exposed slice is set to 1 |am. The thicknesses of the interior slices are
determined by their depths: the ratio of the thicknesses of two adjacent slices is 1:2 (See Figure
The number of the MSS slices is determined by the thickness of the source. If the source is 1 cm
or less, ten slices will be used; otherwise, 15 slices.
6.6 Temperature-dependent emission parameters
The temperature dependence of partition and diffusion coefficients are estimated using
existing empirical models. Currently the program provides two methods for estimating partition
coefficients and three methods for solid-phase diffusion coefficient. Additional methods can be
added later. See Tutorial 4 for an example of modeling temperature-dependent emissions.
6.6.1 Partition coefficient
Method 1 (Zhang et al.. 2007):
4).
K =AX To s eA^T
(14)
where K = solid-air partition coefficient at temperature T (dimensionless),
T = absolute temperature (K),
Ai, A2 = empirical constants for a given material/chemical pair.
Method 2 (Tian et al.. 2017):
(15)
where Ki, K2 = partition coefficient at temperatures Ti and T2 (dimensionless),
AHV = vaporization enthalpy (J),
26
-------
Ti, T2 = absolute temperature corresponding to Ki and K2 (K),
R = gas constant (J/mol/K)
a = absolute value of the slope for the ln(/C)-ln(P) relationship, where P is the vapor
pressure.
6.6.2 Solid-phase diffusion coefficient
Method 1 (Baner et al.. 1994; Begley. 1997):
In D = Ap -0.101m- 10450 /T (16)
where D = solid-phase diffusion coefficient at temperature T (m2/s),
Ap = material-specific constant,
m = molecular weight of chemical (g/mol),
T = absolute temperature (K).
Method 2 (Begley et al.. 2005):
2 10454
InD = Ap — 0.1351 ms + 0.003 m — (17)
where D = solid-phase diffusion coefficient at temperature T (m2/s),
Ap = material specific coefficient,
m = molecular weight of chemical (g/mol),
T = absolute temperature (K).
Method 3 (Tian et al.. 2017):
D = Dne~AH/(R^
(18)
where D = solid-phase diffusion coefficient at temperature T (m2/s),
Do = material specific constant for a given chemical (m2/s),
AH = an equivalent of activation energy (J/mol),
R = gas constant = 8.314 (J/K/mol),
27
-------
T = absolute temperature (K).
Method 4 (Huang et al.. 2017)
T—34R6
logD = 6.39 — 2.49logm + b H -—
(19)
where D = solid-phase diffusion coefficient at temperature T (m2/s),
b and x are constants for a given material/chemical pair, obtained by statistical analysis,
m = molecular weight of the chemical (g/mol),
T = temperature (K).
Note that the values of constant b and x are obtained from a look-up table.
6.7 Sink models
Interior surfaces can act as a reservoir, or sink, of airborne pollutants. This sink effect is
especially important for SVOCs. Four sink models are implemented in this program:
• First-order reversible Langmuir sink
• Freundlich reversible sink
• First-order irreversible sink
• Molecular diffusion-based sink.
6.7.1 First-order reversible Langmuir sink
The adsorption and desorption rates for the dynamic Langmuir sink are given by Equations 20
and 21 (Tichenor et al., 1991):
Ra — A ka Ca
(20)
Rd — A kd Cs
(21)
where Ra = adsorption rate (|ag/h)
Rd = desorption rate (|ag/h)
A = area of sink surface (m2)
28
-------
ka = adsorption rate constant (m/h)
kd= desorption rate constant (h1)
C0 = concentration in air (|ag/m3)
Cs = concentration on sink surface (|ag/m2).
6.7.2 Freundlich reversible sink
The adsorption and desorption rates for the dynamic Freundlich sink are given by Equation 22
and 23 (Van Loyd et al., 1997):
Ra=AfaC% (22)
Rd=AfdCpa (23)
where Ra = adsorption rate (|ag/h)
Rd = desorption rate (|ag/h)
A = area of sink surface (m2)
fa = nonlinear adsorption rate constant (ng1_a m3a 2 h_1)
fd= nonlinear desorption rate constant (|ag1_|3 m2p"2 h_1)
C0 = concentration in air (|ag/m3)
Cs = concentration on sink surface (|ag/m2)
a and 6 = dimensionless constants.
6.7.3 First-order irreversible sink
The first-order irreversible sink is a special case of the first-order reversible Langmuir sink (i.e.,
the desorption rate is zero). The adsorption rate, or deposition rate, is calculated by Equation
19.
6.7.4 Molecular diffusion-based sink
The molecular diffusion-based sink is represented by the MSS method described in Section
6.5.5. The MSS method treats a sink the same as a source except that the initial concentration
in the sink is often zero.
6.8 Airborne PM
29
-------
Although models are available for tracking particle number (or mass) concentrations in a multi-
zone building (e.g., PM.EXE in IAQX), SVOC interactions with airborne PM can only be simulated
for a single zone and a single chemical with existing models (e.g., i-SVOC). Particle-SVOC
interactions for multiple particle types, multiple chemicals, and multiple zones are too complex
for a personal computer to handle. Thus, compromises were made to incorporate airborne PM
into this program. The PM model implemented in this program allows for:
• A single chemical
• Multiple particle type
• Multiple zones.
To further simplify the model, a key assumption is made: There is an instantaneous equilibrium
between the SVOC concentration in air and that in the particle phase (Weschler & Nazaroff,
2008; Liu et al., 2013). In general, this assumption is valid if neither the particle-air partition
coefficient (Kp) nor the particle diameter (d) is very large. Typically, Kp should be no greater than
108) and the particle diameter (d) no greater than 10 |am (Guo, 2014b). This assumption may
result in an overestimation of particle-phase SVOC concentrations if K > 108 and/or d > 10 |am.
(See Tutorial 7 for an example of incorporating chemical interactions with airborne PM.)
6.9 Settled dust
The interactions of airborne chemicals with settled dust are calculated by the modified state-
space (MSS) method (Guo, 2013), which divides a spherical dust particle into a finite number of
concentric hollow spheres (Figure 5). More details about the method development and
validation can be found in Guo (2014a).
30
-------
Figure 5. Representation of dust particles by the MSS method. The exposed hollow sphere is 0
|am thick. The thicknesses of interior hollow spheres depend on their depths. For example, (r^ ¦
r2) = 2 x {r2 - r±)
6.9.1 Mass transfer between room air and the exposed hollow sphere
RaP=AHa
c--
c„, ^
K
ma J
(24)
1 1
-+-
Ha Kpahp ha
(15)
<>o ~rtd)
(26)
where Rap = rate of mass transfer from room air to airborne particles (|ag/h)
A = surface area of the particle (m2)
Ha = overall gas-phase mass transfer coefficient, from Equation 18 (m/h)
Cpi = concentration in the exposed hollow sphere (|ag/m3)
Kpa = particle-air partition coefficient (dimensionless)
31
-------
C0 = concentration in room air (|ag/m3).
hp = particle-phase mass transfer coefficient, from Equation 30 (m/h)
Dp = particle-phase diffusion coefficient (m2/h)
ro = radius of the particle (m)
rtd = radius that divides the top hollow sphere into two parts with equal volumes
(Equation 27).
= (27)
where ro = outside radius of the top hollow sphere (m)
ri = inside radius of the top hollow sphere (m).
6.9.2 Mass transfer within the particle
The rate of mass transfer between two adjacent hollow spheres, /' and j, is determined by
Equation 28:
x„-4K(cp,-cJ (28)
Ai=4nrf (29)
D
hp = p— (30)
r y> — y>
tdi tdj
where Rjj = rate of mass transfer from hollow sphere /' to hollow sphere j (|ag/h)
Aj = contact area for hollow spheres /' and j, from Equation 28 (m2)
hp = particle-phase mass transfer coefficient between hollow spheres /' and j, from
Equation 30 (m/h)
n = inside radius of hollow sphere /' (i.e., the outer hollow sphere) (m)
rtdi = radius for travel distance in hollow sphere /', from Equation 27 (m)
rtdj = radius for travel distance in hollow sphere j, from Equation 27 (m)
(rtdi-rtdj) = travel distance between two adjacent hollow spheres /' and j (m).
6.9.3 Thicknesses and number of concentric hollow spheres
The thickness of the exposed hollow sphere is set to 0.1 |am. The thicknesses of the interior
slices are determined by their depths: ratio of the thicknesses of two adjacent slices it 1:2 (See
Figure 5).
32
-------
The number of the hollow spheres is determined by the diameter of the dust particles. If the
diameter is 10 |am or less, three hollow spheres will be used; otherwise, five hollow spheres.
6.10 Gas-phase chemical reactions
This program allows the user to define a limited number of gas-phase chemical reactions.
Because chemical reactions take place on a molecule-to-molecule (i.e., mole-to-mole) basis,
unit conversion is necessary to incorporate chemical reactions. This conversion is performed by
the program and the user needs only to provide the molecular weight of the chemical species
involved. See Tutorial 6 for an example of incorporating chemical reactions in a model.
6.10.1 First-order reaction
The generic form of first-order reactions is shown in Equation 31:
Ri = yi Pi + yi Pi + ¦¦¦
(31)
where Ri = reactant,
Pi, P2, ... = products,
yi, y2, ... = product yields.
The rate is calculated according to Equations 32 and 32:
® = -kx [*,]
(32)
(33)
where [R] = gas-phase concentration of the reactant (molecules/cm3)
t = time (s)
[Pi] = gas-phase concentration of product 1 (molecules/cm3)
ki = first-order reaction constant (s_1).
33
-------
6.10.2 Second-order reaction
A second-order reaction can be in the form of either Equation 34 or 35:
/?i + R2 = yi Pi + y2 P2 + "• (34)
2 R± = y1P1+ y2 P2 + "• (35)
where Ri, R2 = reactants
Pi, P2, ... = products
yi, y2, ... = product yields.
The reaction rate is calculated from Equations 36 and 37:
=-k2 [8J [«2] (36)
^! = Jc2yi[Ri][fi2] (37)
where k.2 = second-order reaction constant (molecule 1 m3 s)
6.10.3 Temperature-dependence of reaction rate constants
This program uses a simplified version of the Arrhenius equation (Equation 38) to calculate
temperature-dependent rate constants.
k(T) = A e~E"/T (38)
where k(T) = rate constant at temperature T,
A = constant specific to a chemical reaction,
Ea = a lumped parameter (i.e., activation energy divided by gas constant),
T = temperature (K).
34
-------
6.11 Mass transfer rates as an option for simulation output
IECCU 1.1 allows the user to add mass transfer rates to the output of a simulation. This is
achieved by including "9) Mass transfer rates" in the output selections (Figure 6).
IECCU (v 1.1) Model-I.IEC
File Model Run Data Tools Help
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
Simulation Conditions
initial air concentrations (ug/m3)
Species
Zone 1
FR1
0
Chemical names are automatically updated
Simulation duration
Number of data points
20
Output selections
1) Air concentrations
9) Mass transfer rates
App status: Awaiting user input
Current page = (7) Simulation conditions
lo Select
Figure 6. To include mass transfer rates in the simulation output, go to the page and add "9) Mass transfer rates" to the output selections.
Methods for calculating the transfer rates are discussed in Sections 6.5 through 6.10. Note that,
in some cases, the transfer rates can be positive or negative or both. For example, for a
diffusional sink, a negative transfer rate means the sink is absorbing contaminants from air
whereas a positive transfer rate means the sink is re-emitting contaminants into the air. More
information about the signs of transfer rates is provided in Table 12.
35
-------
Table 12. The meanings of transfer rate signs
Indoor Media
Positive value
Negative value
Sources
Sinks
Airborne PM
Settled dust
Chemical reactions
Emission into air
Emission into air
Emission into air
Emission into air
Absorption from air
Adsorption/absorption from air
See discussion below
Absorption from air
Absorption from air
N/A
Also note that all the mass transfer rates are in the units of (|-ig/h) except those for chemical
reactions, which are in (mole/h). The example below show how to convert the reaction rate to
(l-ig/h) for individual reactants and products.
Assume the chemical reaction is:
A+ B = 0.5 C + 0.35 D
The disappearance rates for reactants A and B are:
Ra = Rx* iwax 106
Rb = Rx x me x 106
where Ra and Rb are disappearance rates for reactants A and B (|-ig/h),
Rx is the reported reaction rate (mol/h),
rriA and me are molecular weights for reactants A and B (g/mol).
Similarly, the generation rates for reaction products C and D are:
Rc = 0.5 x Rxx mc x 106
Rd = 0.35 x Rx x De x 106
6.12 Mass balance as an option for simulation output
IECCU 1.1 also allows the user to add mass balance to the output of a simulation. The mass
balance at a given time t can be calculated from Equation 39, in which all terms are in the unit
of mass (e.g., |ag),
Et = Wva + + (At - 4,) + (JVt - JV0) + (Pt - P0) + 0?t - AO + (.Xr ~ XP) (39)
36
-------
where Et is the amount of contaminant emitted from sources between times 0 and t,
l/l/ra is the amount of gas-phase contaminant leaving the building between times 0 and t
(Equation 40),
Wvp is the amount of particle-borne contaminant leaving the building between times 0
and t (Equation 41),
At and Ao are the amounts of contaminant in indoor air at times t and 0,
Nt and No are the amounts of contaminant in indoor sinks at times t and 0,
Pt and Po are the amounts of contaminant in airborne PM at times t and 0,
Dt and Do are the amounts of contaminant in settled dust at times t and 0,
Xr is the amount of contaminant reacted (i.e., disappeared) due to chemical reactions,
Xp is the amount of contaminant produced due to chemical reactions.
where Q is the ventilation flow rate at time r (m3/h),
Ca(t) is the contaminant concentration in indoor air at time r (|ag/m3),
Cp(z) is the contaminant concentration in suspended particles at time r (|ag/m3),
r is time (h).
Note that Equations 39, 40, and 41 are the integral form of the mass balance equation. Its
differential form is shown in Equation 1.
Ka= Jo<2(T)Ca(T)dT
= Jo <2 CO Cp(t) dr
(40)
(41)
37
-------
7. Parameter estimation assistance
Parameter estimation is a key to meaningful indoor environmental quality modeling. Model
parameters can be obtained from measured values or calculated with empirical or QSAR
(quantitative structure-activity relationship) models.
7.1 Compiled data under the Params menu
IECCU 1.1 includes three compiled data sets, which can be accessed from the Params menu:
• Solid-phase diffusion coefficients: 1596 sets of data (Huang et al., 2017)
• Solid/air partition coefficients: 341 sets of data (Holmgren et al., 2012)
• Partitioning of SVOCs between indoor air and settled dust: sets of data (Weschler &
Nazaroff, 2010)
7.2 QSAR and empirical models under the Tools menu
IECCU 1.1 provides 11 QSAR and empirical models for estimating solid-phase diffusion
coefficient, solid/air partition coefficient, aerosol/air partition coefficient, and dust/air partition
coefficient (Table 13). To access these models, click from the main menu.
Please be aware of the limitations associated with each model. The user is encouraged to read
the original publication for more details. Some of the models contain empirical constants that
are applicable to specific chemicals and materials. If those constants are available, they can be
viewed by clicking the button in the Tools window (Figure 7).
38
-------
Table 13. List of QSAR and empirical models for estimating diffusion and partition coefficients
Parameter Name
Model Equation
Reference
log D
= 6.39 — 2.49 logm + b -1
3486
T
Huang et al. (2017)
10450
InD = A„ — 0.101 m
y rp
Baner et al. (1994)
Solid-phase diffusion
coefficient
In D =
2
Ap — 0.1351 m3 + 0.003 m —
D = B1 T125 exp(^)
Da pn
D= K
10454
T
Begley et al. (2005)
Deng et al. (2009)
Millington et al. (1961)
Solid/air partition
coefficient
InK = 8.76 - 0.785 InPv
K = Pt T0-5 exp(^)
Guo (2002)
Zhang et al. (2007)
Aerosol/air partition
coefficient
log Kp = ct log Koa + c2
„ foe Koa
Kv~ d
Finizio et al. (1997)
Weschler & Nazaroff
(2010)
Dust/air partition
coefficient
Kd = 0.411 d foe Koa
logKd = 0.98logKOA-9.09
Shoeib et al. (2005)
Weschler & Nazaroff
(2010)
Symbols:
D = solid-phase diffusion coefficient (m2/s),
Da = diffusion coefficient in air (m2/s),
foc= organic carbon content (fraction),
K = solid/air partition coefficient (dimensionless),
Kd = dust/air partition coefficient (dimensionless or m3/ng depending on methods,
Koa = octanol-air partition coefficient (dimensionless),
Kp = particle/air partition coefficient (dimensionless),
m = molecular weight (g/mol),
n = constant (3/2 or 4/3),
p = porosity (fraction),
Pv = vapor pressure (mm Hg),
T = temperature (K).
Other parameters (b, r, Ap, Bi, B2, Pi, P2, Ci, and c2) are constants for a given pair of chemical and solid
media.
39
-------
E Tools
Model Desciption
Solid-phase diffusion coefficient by Begley et al. (2005) method
Input Parameters
Solid-phase diffusion coefficient
Begley et al. (2005) Method
In(D) = Ap - 0.1351 mA0.667 + 0.003 m - 10450 / T
where
D — soild-phase diffusion coefficient at
temperature Tl (m2/s),
Ap material specific coefficient,
m — molecular weight of chemical (g/mol),
T — absolute temperature (F.) .
NOTE: D is in (m2/s). IECCU uses (m2/h) for
calculations.
NOTE: Tian et al. (2017) suggested that Ap = 10
for PU foam.
NOTE: Ap is temperature dependent. Click
button for details.
Ref: Begley et al. (2005)
et al. (2017)
Ap
Molecular weight (g/mol)
Temperature (C)
, Parameters
Sci°
Figure 7. If the parameter estimation model contains empirical constants, they can be accessed
by clicking the button in the calculation sheet.
40
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3 IECCU (v 1.1) Model-1.IEC
File Model Run Data Tools Help
eeeoco;
(1) Building & Environment (2) Sources (J) Sinks (4) Airborne PM (S) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Air Zones b) Ventilation (1) c) Ventilation (2) d) Temperature (1) e) Temperature (2)
Notepad
| Recommended volume and ventilation rate for
| use as a central estimate for all single family homes,
i including mobile homes and multi-family units
Volume =446 mA3
Ventilation rate = 0.45 per hour
The ventilation rate is the median value recommended
to be used as a central estimate based across all US
census regions an various housing types.
Source:
U.S. EPA (2018). Exposure Factors Handbook
[chapter 19 (Update): Building Characteristics.
(Table 19-1).
® Help
Select Building Configuration
Zone ID
Conditioned?
Zone Name Volume (m3)
1
Yes
Zonel 446
Zone 1
Number of air zones
Has an HVAC systenr
Time with HVAC o
Conditioned zone
Unconditioned zone
App status: Awaiting user input
Current page = (1) Building & Environment / a) Air Zones
Figure 9. Building volume and air exchange flow rate for use as a central estimate for ail single-family
homes (EPA, 2018), shown as a partially completed model file.
Users should be aware of the following limitations when using these model files:
• The model files contain only building volume and air exchange flow rate. It is the user's
responsibility to complete the remaining parts of the model, such as sub-models for sources,
sinks, airborne particles, and settled dust, whichever is applicable.
• Because the EFH gives the volume and ventilation rate for the entire building, the data can only
be used for single-zone models. If a multi-zone model is needed, it is up to the user to divide the
building into zones.
• Because of their large sizes, non-residential buildings often require multi-zone models. Thus, use
the default data for non-residential buildings with caution.
42
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References
Baner, A. L., Franz, R., and Piringer, 0. (1994). Alternative methods for the determination and
evaluation of migration potential from polymeric food contact materials. Deutsche
Lebensmittel-Rundschau, 90:181-185.
Begly, T. H. (1997). Methods and approaches used by FDA to evaluate the safety of food
packaging materials. Food Additives and Contaminants, 14: 545-553.
Begley, T., Castle, L., Feigenbaum, A., Franz, R., Hinrichs, K., Lickly, T., Mercea, P., Milana, M.,
O'Brien, A., Rebre, S., Rijk, R., and Piringer, 0. (2005). Evaluation of migration models that might
be used in support of regulations for food-contact plastics. Food Additives & Contaminants,
22(l):73-90.
Bevington, C., Guo, Z., Hong, T., Hubbard, H., Wong, E., Sleasman, K., and Hetfield, H. (2017). A
modeling approach to quantify exposures from emissions of spray polyurethane foam
insulation in indoor environments. In: ASTM STP 1589— Developing Consensus Standards for
Measuring Chemical Emissions from Spray Polyurethane Foam (SPF) Insulation, pp 199-227.
Dole, P., Feigenbaum, A.E., De La Cruz, C., Pastorelli, S., Paseiro, P., Hankemeier, T., Voulzatis,
Y., Aucejo, S., Saillard, P., Papaspyrides, C. (2006). Typical diffusion behaviour in packaging
polymers-application to functional barriers. Food Additives & Contaminants, 23(2): 202-211.
EPA (2000). Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure (IAQX) Version
1.0 User's Guide, U.S. Environmental Protection Agency, National Risk Management Research
Laboratory, Research Triangle Park, NC, Report No. EPA-600/R-00-094, 76 pp.
https://www.epa.gov/air-research/simulation-tool-kit-indoor-air-quality-and-inhalation-
exposure-iaqx
EPA (2013). Simulation program i-SVOC user's guide, U.S. EPA Report EPA/600/R-13/212.
http://nepis.epa.gov/Exe/ZyPURL.cgi?Dockev=P100HYEF.txt
EPA (2018). Exposure Factors Handbook Chapter 19 (Update): Building Characteristics. US EPA
Office of Research and Development, Washington, DC, EPA/600/R-18/121F.
https://www.epa.gov/expobox/exposure-factors-handbook-chapter-19
Finizio, A., Mackay, D., Bidleman, D., and Harner, T. (1997). Octanol-air partition coefficient as a
predictor of partitioning of semi-volatile organic chemicals to aerosols. Atmospheric
Environment, 31: 2289-2296.
Guo, Z. (2002). Review of indoor emission source models - Part 1. Overview. Environmental
Pollution, 120: 533-549.
43
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Guo, Z. (2002). Review of indoor emission source models - Part 2. Parameter estimation,
Environmental Pollution, 120: 551-564.
Guo, Z. (2013). A framework for modeling non-steady state concentrations of semivolatile
organic compounds indoors — I. Emissions from diffusional sources and sorption by interior
surfaces. Indoor and Built Environment, 22:685-700.
Guo, Z. (2014a). A framework for modeling non-steady state concentrations of semivolatile
organic compounds indoors — II. Interactions with particulate matter. Indoor and Built
Environment, 23:26-43.
Guo, Z. (2014b). Improve our understanding of semivolatile organic compounds in buildings.
Indoor and Built Environment, 23:769-773.
Huang, L., Fantke, P., Ernstoff, A., & Jolliet, O. A (2017) Quantitative Property-Property
Relationship for the Internal Diffusion Coefficients of Organic Compounds in Solid Materials.
Indoor Air, 27:1128-1140.
Lyman, W. L., Reehl, W. F., Rosenblatt, D. H. (1990). Handbook of chemical property estimation
methods: environmental behavior of organic compounds. American Chemical Society,
Washington, DC.
Liu, C., Shi, S., Weschler, C., Zhao, B., and Zhang, Y. (2013). Analysis of the dynamic interaction
between SVOCs and airborne particles. Aerosol Science & Technology, 47:125-136.
Millington, R. and Quirk, J. (1961). Permeability of porous solids. Transactions of the Faraday
Society, 57:1200-1207. Cited in Pei, J., Yin, Y., Cao, J., Sun, Y., Liu, J., and Zhang, Y. (2017). Time
dependence of characteristic parameter for semi-volatile organic compounds (SVOCs) emitted
from indoor materials. Building and Environment, 125: 339-347.
Tian, S., Sebroski, J., and Ecoff, S. (2017). Predicting TCPP Emissions and Airborne
Concentrations from Spray Polyurethane Foam Using USEPA i-SVOC software: Parameter
Estimation and Result Interpretation. In: ASTM STP 1589 — Developing Consensus Standards for
Measuring Chemical Emissions from Spray Polyurethane Foam (SPF) Insulation, pp 167-198.
Tichenor, B.A., Guo, Z., Dunn, J.E., Sparks, L.E. and Mason, M.A. (1999). The interaction of vapor
phase organic compounds with indoor sinks, Indoor Air, 1:23-35.
Van Loy, M.D., Lee, V.C., Gundel, L.A., Daisey, J. M., Sextro, R.G. and Nazaroff, W.W. (1997).
Dynamic behavior of semivolatile organic compounds in indoor air. 1. Nicotine in a stainless
steel chamber, Environmental Science & Technology, 31:2554-2561.
Weschler, C.J. and Nazaroff, W.W. (2008). Semivolatile organic compounds in indoor
environments, Atmospheric Environment, 42:9018-9040.
44
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Weschler, C. J. and Nazaroff, W. W. (2010). SVOC partitioning between the gas phase and
settled dust indoors. Atmospheric Environment, 44: 3609-3620.
Won, D., Nong, G., Lusztyk, E., and Schleibinger, H. (2013). Emissions of MDI from do-it-yourself
products. NRC-CNRC Institute for Research and Construction, Canada. Report Al-002093.
Xiong, J., Wei, W., Huang, S., Zhang, Y. (2013). Association between the emission rate and
temperature for chemical pollutants in building materials: General correlation and
understanding. Environmental Science & Technology, 47(15):8540-8547.
Zhang, Y., Luo, X., Wang, X., Qian, K., and Zhao, R. (2007). Influence of temperature on
formaldehyde emission parameters of dry building materials. Atmospheric Environment, 41(15):
3203-3216.
45
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Appendix: IECCU Tutorials
46
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Contents of Appendix
Introduction 51
Tutorial 1: Creating a simplest model 52
1.1 Objective 52
1.2 Case description 52
1.3 Create the model 53
1.3.1 Define building configuration 53
1.3.2 Define ventilation flow rate 54
1.3.3 Define the source 55
1.3.4 Define simulation conditions 57
1.4 Compile the model 59
1.5. Inspect the model 59
1.6 Run the model 60
1.7 Examine the results 60
Tutorial 2: Using enhanced ventilation 62
2.1 Objective 62
2.2 Case description 62
2.3 Create the model 62
2.4 Save, compile and run the model 63
Tutorial 3: TCPP emissions from SPF installed in attic 65
3.1 Objective 65
3.2 Case description 65
3.3. Create the model 67
3.3.1 Select building configuration 67
3.3.2 Define airflow matrix 68
3.3.3 Define the source 69
3.3.4 Define the sink 70
3.3.5 Define simulation conditions 72
3.4 Save, compile, inspect, and run the model 73
Tutorial 4: Simulating temperature-dependent TCPP emissions 75
4.1 Objective 75
47
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4.2 Case description 75
4.3 Create the model 76
4.3.1 Define temperature profile in attic 76
4.3.2 Modify the SPFsource 79
4.3.3 Define temperature-dependent functions for partition coefficient 81
4.3.4 Define temperature-dependent functions for diffusion coefficient 84
4.3.5 Select output data types 85
4.4 Save, compile, inspect and run the model 85
Tutorial 5: Using the batch mode 88
5.1 Objective 88
5.2 General steps 88
5.3 Case description 88
5.4 Run batch 88
5.4.1 Create an empty folder 88
5.4.2 Save or copy model files to that folder 88
5.4.3 Run batch simulations 89
5.4.4 Retrieve simulation results 93
Tutorial 6: Gas-phase chemical reactions 94
6.1 Objective 94
6.2 Case description 94
6.3 Create the model 95
6.3.1 Define building and ventilation 95
6.3.2 Define the first-order decay source 95
6.3.3 Define the chemical reaction 96
6.3.4 Define simulation conditions 98
6.4 Save, compile, inspect and run the model 98
Tutorial 7: TCPP interactions with airborne particulate matter (PM) 100
7.1 Objective 100
7.2 Case description 100
7.3. Create the model 100
7.3.1 Open model MyTCPP-l.lEC 100
7.3.2 Define airborne PM 101
7.3.3 Define deposition rate constants and initial PM mass concentrations 102
48
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7.3.4 Select output data types 103
7.4 Save, compile, inspect, and run the model 104
Tutorial 8: TCPP interactions with settled dust 105
8.1 Objective 105
8.2 Case description 105
8.3 Create the model 105
8.3.1 Load model MyTCPP-PM.lEC 105
8.3.2 Define settled dust 105
8.3.3 Define simulation conditions 109
8.4 Save, compile, inspect and run the model 109
Tutorial 9: Application-phase simulation Ill
9.1 Objective Ill
9.2 Case description Ill
9.3 Create the model 112
9.3.1 Define building configuration 112
9.3.2 Define airflow matrices for base and enhanced ventilation 112
9.3.3 Define application-phase model 113
9.3.4 Define simulation conditions 114
9.4 Save, compile, inspect and run the model 114
Tutorial 10: Importing indoor-outdoor and zone-to-zone air flow data 116
10.1 Objective 116
10.2 Case description 116
10.3 Create the model 116
10.4 Save, compile, inspect and run the model 117
Tutorial 11: Importing indoor temperature data 119
11.1 Objective 119
11.2 Case description 119
11.3 Create the model 120
11.4 Save, compile, inspect and run the model 120
Tutorial 12: Including an HVAC system 122
12.1 Objective 122
12.2 Case description 122
12.3 Create the model 123
49
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12.4 Compile and run the model 127
50
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Introduction
This is an appendix of the IECCU User's Guide containing 12 tutorials. IECCU is a simulation
program for estimating chemical emissions from sources and related changes to Indoor
Environmental Concentrations in Buildings with Conditioned and Unconditioned Zones. As such,
IECCU is an indoor exposure model. A model simulation is one run of the model and involves
creating, compiling, inspecting, and running the model. Users are encouraged to examine their
results in comparison to other modeled estimates or indoor monitoring data for a similar
exposure scenario, if available.
These 12 tutorials aimed to familiarize the users with most features of this program. Through
this practice, the users are expected to design their own scenarios for use with IECCU. To assist
this process, the model files for the tutorials are also available from the Secure File Sharing Site
where users downloaded the set-up file.
The scenarios and parameters used in these tutorials are intended to cover most of the
features of this program. Some of them are real and some are hypothetical, and none are
intended to represent specific brands of commercial products. Users are encouraged to use this
program to consider their own applications and scenarios.
CAUTION: To demonstrate this program's capability to simulate sources in unconditioned
zones, spray polyurethane foam (SPF) applications were used in several tutorials. Due to the
lack of experimental data, most parameters for SPF were obtained either from limited data
(such as initial chemical concentration in SPF) or from existing empirical or quantitative
structure-activity relationship (QSAR) models (such as the partition coefficient) or based on
educated guesses (such as the solid-phase diffusion coefficient) and, thus, may contain large
errors.
Disclaimer: The computer software described in this document was developed by the U.S. EPA
for its own use and for specific applications. The Agency makes no warranties, either expressed
or implied, regarding this computer software package, its merchantability, or its fitness for any
particular purpose, and accepts no responsibility for its use. Mention of trade names and
commercial products does not constitute endorsement or recommendation for use. The views
expressed in this document do not necessarily represent the views or policies of the Agency.
51
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Tutorial 1: Creating a simplest model
1.1 Objective
To demonstrate the general steps for using IECCU by creating and running a simplest model.
Description of the user interface is given in Section 3 in the Tester's Guide.
1.2 Case description
Doing a simulation with IECCU involves five steps:
• Create the model,
• Compile the model (i.e., error-checking by the program),
• Inspect the model (i.e., error-checking by user),
• Run the model,
• Examine the results.
The first model we will create is for a constant source in a single zone with parameters listed in
Table 1.1.
Table 1.1. Parameters for the simplest IECCU model.
Parameter name
Value
Zone name
Bedrooml
Room volume
30 m3
Ventilation flow rate
30 m3/h
Chemical name
HCHO
Constant emission rate
100 ng/h
This simple model will need four input pages:
• Page < a) Air zones > under folder < (1) Building & environment >,
• Page < b) Ventilation (1) > under folder < (1) Building & environment >,
• Page < a) Empirical models > under folder < (2) Sources >,
• Folder/page < (7) Simulation conditions >.
52
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1.3 Create the mode!
Launch IECCU; click the button with a right arrow to proceed (Figure 1.1).
Simulation Program for Estimating Chemical Emissions from Sources and Related Changes
To Indoor Environmental Concentrations in Buildings with Conditioned and Unconditioned Zones
IECCU
V 1.1 (2018)
Developed By ICJfor U.S. IM Office of Toffutton Prevention & Toxics
/
Click here to proceed
Figure 1.1. IECCU front page.
1.3.1 Define building configuration
The main window is shown in Figure 1.2. The notepad on the left provides a space for the user
to make notes, such as a verbal description of the model. Try to type a few words in the box.
The default building configuration is a single unconditioned zone. For this tutorial, there is no
need to make any changes. If you want to change the building configuration, click the button <
Select building configuration >, which will be described in Section 3.3.1.
Enter "Bedrooml" for zone name and 30 for zone volume. Now you are done with the < a) Air
zones > page (see Figure 1.2).
53
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& IECCU (v 1.1 ) MyModel-l.lEC
File Model Run Data Tools Help
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Air Zones b) Ventilation (l) c) Ventilation (2) d) Temperature (1) e) Temperature (2)
Notepad
IECCU Tutorial 1
A simple model for demonstrating the basic steps of
using IECCU.
Created on June 6,2016
\
Write your notes here.
Select Building Configuration
Zone ID
Conditioned?
Zone Name
Volume (m3)
1
Yes
Bedroomlj
30
/ /
User input
Number of air zones
Has an HVAC system
9 9
Time with HVAC on
0 %
Conditioned zone
Unconditioned zone
App status: Awaiting user input
Current page = (1) Building & Environment / a) Air Zones
Figure 1.2, IECCU main window, showing completed page < a) Air zones > under folder tab < (1)
Building & environment >.
1.3.2 Define ventilation flow rate
To enter ventilation data, click the < Ventilation (1) > page tab,
Click the < Visualize > button to view a graphic representation of the air flows.
Enter 30 in the blank cell in Table 1 on top-left corner (the on-screen table is titled "Normal air
exchange flow rates (m3/h)"). The completed page is shown in Figure 1.3,
Note that the column for "To zone 0" in the air exchange flow table is not editable because
those cells do not require any input from the user.
54
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Click here to select an empirical model
¦ Emppirical Source Models
Empirical source models
Model parameters
Select model
Chemical name
Model description
Source location
VQ* | X Cancel
Figure 1.4. User input page for empirical source models.
¦ ' Emppirical Source Models
Empirical source models
(11) Constant source
Constant emission source
R= RO
where
R = emission rate (ug/h).
RO = constant emission rate (ug/h).
Model parameters
Chemical name
Source location
RO (ug/h)
User input
Bedroom'
X Cancel
Figure 1.5. Completed user input window for empirical source model 11.
56
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First, click on this item
¦ Select output data types
Available output data type^
Selected output data types
1) Air concentrations
2) Chemical concentrations in airborne PM (ug/m3 air)
3) Chemical concentrations in airborne PM (ug/g PM)
Select
4) Mass concentration of airborne PM (ug/nt3 air)
5) Chemical concentrations in settled dust (ug/g dust)
Second, click this button
Tentperature profiles in unconditioned zone(s)
Temperature-dependent partition coef (K)
Teicperature-dependent diffusion coef (D)
Finally, click this button
X Cancel
1/ Help
Figure 1.7. Form for selecting output data types
The completed < (7) Simulation conditions > page is shown in Figure 1.8.
! IECCU (v 1.1 ) MyModel-l.lEC
I File Model Run Data Tools Help
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
Simulation Conditions
Simulation duration
Initial air concentrations (ug/m3)
Species Zone 1
HCHO
Chemical names are automatically updated
20 hours
Number of data points
Output selections
01) Air concentration
L • .
58
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Now, you have finished creating your first model. Save this model using the file name
"MyModel-l.lEC" by clicking the < Save > speed button (The fourth from left). You will need this
file later.
1.4 Compile the model
Click the < Compile > speed button to allow the program to check for potential errors in your
model. If an error message pops up, correct the error and then try again.
1.5. Inspect the model
Click the < Inspect > speed button (the seventh from left) to bring up a report that lists all the
parameters you entered. This list is not a carbon copy of what you entered. Rather, it is the
program's interpretation of your input. Go over this report carefully to find potential
inconsistencies. This step is highly recommended but not required. The report for this model is
shown in Figure 1.9.
13 Model Inspector — X
Program: IECCU (v 1.0 ) / File name = MyModel-l.lEC *
4/4/2017 9:19:02
(1)Building configuration
Number of room(s)/unconditions space(s) = 1
Including HVAC? = No
Zone 1 = Bedrooml; Volume = 3.00E+01 (m3)
(2) Base air flow matrix
From Zone 0 to Zone 1, Q[0,1] = 3.00E+01 (m3/h)
From Zone 1 to Zone 0, Q[1»0] = 3.00E+01 (m3/h)
(3)Number of chemical species = 1
HCHO
(4)Empirical source models
1)Constant emission source
Chemical = HCHO
Location = Bedrooml
R0 (ug/h) = 1.00E+02
(5)Non-zero initial air concentrations
(None)
v
Pnnt £lose
Figure 1.9. Inspection report for 'MyModel-l.lEC". Use the scroll bar on the right side to roll
down for more information.
59
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1.6 Run the mode!
Click the < Run > speed button (the eighth from left) to start the simulation. After the
simulation is complete, click < OK >. (Figure 1.10).
* ' Simulation status
X
Calculating... Done!
Simulation duration:
20(h)
Elapsed time:
20(h)
A Cancel
^ OK
Figure 1.10. Simulation status window.
1.7 Examine the results
Click < (8) Output> page tab. There are six output pages. The first page is for air concentrations
(Figure 1.11).
Use the < Copy > or < Copy all > button to transfer data to a spreadsheet or click the < Save
CSV > button to save the data as a comma separated values (CSV) file.
Note that the < Copy > and < Copy all > buttons work differently. The former copies the
highlighted area only, while the latter copies all data to the Windows clipboard without
highlighting. Figure 1.12 was created by Microsoft Excel.
60
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Tutorial 2: Using enhanced ventilation
2.1 Objective
To demonstrate how to define an air flow matrix that is different from the baseline air flow
matrix. This feature is often useful when enhanced ventilation is required during product
installation or application. Representation of indoor-outdoor and zone-to-zone air flows in
IECCU is described in Section 5.3 in the Tester's Guide.
2.2 Case description
The case we are trying to simulate is the same as that in Tutorial 1 except in this scenario 4 air
changes per hour (i.e., 120 m3/h ventilation flow rate) will be applied in the period between 0
to 6 elapsed hours.
2.3 Create the model
If the model "MyModel-l.lEC" 1 is not currently active, click the < Open > speed button (the
third from left) to open it.
Click the < b) Ventilation (1) > page tab under the < (1) Building & environment > folder tab. On-
screen Table 2 located near the bottom-left corner is for entering a second air flow matrix
(Figure 2.1).
Table 2 is disabled by default. To active it, click the < Enabled > radio button in the "Table 2
status" box.
Enter 120 in the empty cell in Table 2.
In the "Duration (elapsed hours)" box, enter 0 for start time and 6 for end time (Figure 2.1).
62
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4
3
2
1
0
0
20
Elapsed Time (h)
Figure 2.2. Simulation results of MyModel-2.IEC.
64
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Tutorial 3: TCPP emissions from SPF installed in attic
3.1 Objective
To create a two-zone model to simulate the TCPP [tris (chloropropyl) phosphate] concentration
in the living area due to emissions from SPF insulation installed in the attic. The technical
approach to modeling chemical emissions from diffusional sources is described in Section 5.5.3
in the Tester's Guide.
3.2 Case description
TCPP is an organophosphate chemical used as a flame retardant in spray polyurethane foam
(SPF) insulation. When the SPF is installed in attic, the TCPP emitted from the source can enter
the living area through inter-zone air flows causes by a pressure difference, especially under the
influence of the reversed stack effect. Input parameters to be used are from Bevington et al.
(2017) and presented in Tables 3.1 through 3.3.
Table 3.1. Zone volumes, ventilation rates, and inter-zone air flows.
Parameter
Value
Volume of Zone 1 (living area)
Volume of Zone 2 (attic)
300 m3
150 m3
Ventilation rate of living area
Ventilation rate of vented attic
0.5 h1 (i.e., Q01 = 150 m3/h)
2.0 h1 (i.e., Q02 = 300 m3/h)
Air leakage flow from living area to attic (Q12)
Air leakage flow from attic to living area (Q21)
15 m3/h
15 m3/h
65
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Table 3.2 Low-density/open-cell SPF in attic as a source of TCPP.
Parameter
Value
SPF area
180 m2
SPF thickness
0.1 m
Initial TCPP content
1.01E9 (ng/m3)
TCPP Partition coefficient (K) at 25 °C
3.6E5 (dimensionless)
TCPP Diffusion coefficient (D) at 25 °C
1.0E-10 (m2/h)
TCPP gas-phase mass transfer coefficient
0.4 m/h
Table 3.3. Gypsum board walls in the living area as a sink of TCPP.
Parameter
Value
Gypsum board area
800 m2
Gypsum board thickness
0.01 m
TCPP Partition coefficient (K) at 23 °C
3.75E7 (-)
TCPP Diffusion coefficient (D) at 23 °C
7.54E-11 (m2/h)
TCPP gas-phase mass transfer coefficient
0.6 m/h
Note that, when entering numerical values in the scientific notation, you should follow the
standard format. For example, the following formats are valid:
1.23E4
1.23e4
1.23E+4
1.23E-15
123E2 (acceptable but not recommended)
+1.23E4 (acceptable but not recommended)
But the following formats are invalid and will result in an error message:
1.23*10A4
1.23X10M
1.23 10A4
66
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3.3. Create the model
3.3.1 Select building configuration
Launch the SPF program;
If the < a) Air zones > page is not in current view, click the < (1) Building and environment >
folder tab and then click the < a) Air zones > page tab.
Click the < Select building configuration > button (Figure 3.1).
3 IECCU (v 1.1 ) MyTCPP-O.lEC
File Model Run Data Tools Help
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (S) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Air Zones b) Ventilation (1) c) Ventilation (2) d) Temperature (1) e) Temperature (2)
IEQ-CU Tutorial 3: TCPP
attic — base case.
Both K and D are constant.
from SPF applied ir
Select Building Configuration
Zone ID
Conditioned?
Zone Name
Volume (m3)
1
Yes
LvArea
300
2
No
attic
150
Number of air
Has an HVAC
Time with HVAC o
Conditioned zone
Unconditioned zone
App status: Awaiting user input
Current page = (1) Building & Environment / a) Air Zones
iifl Close |
Figure 3.1. Creating a new model by clicking button < Select Building Configuration >.
In the next window, click the < With unconditioned zone(s) > radio button located in the
"Indoor climate" box at the top-left corner. A drawing showing the living area/attic
configuration will appear (Figure 3.2). Click the < Select > button.
67
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jj? Built-in building configuration
Indoor Climate
O All zones are conditioned
® With unconditioned zone(s)
Including the HVAC?
(•) No O Yes
Time fraction with HVAC on
0 %
Conditioned zone
Unconditioned zone
Zone 1
(living area)
With unconditioned zone(s) — Case 1 of 5
X Cancel
Figure 3,2, Selecting a building configuration.
Note that if you need a different configuration (e.g., living area/crawlspace or living
area/attic/crawlspace), use the < Prev > and < Next > buttons to browse available
configurations.
After you have selected a configuration, return to the main window, and enter zone volumes:
300 for living area and 150 for attic (see Figure 3.1 above);
3.3.2 Define airflow matrix
Move to the < b) Ventilation 1 > page by clicking its page tab.
Enter the air flow data shown in Table 3.4 in the air flow matrix table near the upper-left corner
of the page (i.e., "Table 1. Normal air exchange flow rates").
68
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* EXWaSton sou fees
o
X
Initial concentrations (CO)
SoUTOMMFTM
SPF
J
CO |ug/m£>
Slic« niflrbB : 15
, ImZ'to)
1 11-10
tm
•L.'ie#llT|
1.0H4
Sid 121
1.01E4
0L4
Sit«i 131
1.01E9
S6t*|14|
1 0'E9
/
it
1
K Circtl
Figure 3.4, Defining the SPF insulation in attic as a diffusion source of TCPP.
Enter the parameters shown in Table 3.2. The completed form is shown in Figured 3.4. Click the
< OK > button to accept.
Note that you do not have to enter the initial concentration (1.01E9 in this case) 15 times. Enter
the value in the first cell (i.e., SI ice [0]) and then click the < Propagate > button.
Also note that the number of slices for the modified state-space (MSS) method is determined
by the thickness of the source. For thick sources (e.g., SPF), 15 slices are used. Thin sources (<1
cm) and sinks have 10 slices. Use the < Adjust > button to adjust the slice number.
3.3.4 Define the sink
Click the < (3) Sinks > folder tab and then click the < b) Diffusion sinks > page tab (see Figure
3.5).
-------
3 IECCU (v 1.1 ) MyTCPP-O.lEC
Re Model Run Data Tools Help
-
X
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (S) Settled Oust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Surface adsorption b) Diffusion sinks
Diffusion-based sink model
1
2
3
4
5
6
7
8
-
Sink name
Chemical
Zone ID
Area (m2)
Thickness (m)
KM
0 (m2/h)
h (m/h)
COJO] (ug/mB)
COH] (ug/m3)
COJ2] (ug/m3)
CO[3] (Ug/mB)
COJ4] (ug/m3)
V
¦J Add
App status: Awaiting user input
Current page = (3) Sinks / b} Diffusion sinks
Figure 3,5, Page < b) Diffusion sinks > under folder tab < (3) Sinks >.
Click the < Add > button. The form for diffusional sink is almost identical to that for diffusional
sources except that the sink material is divided into 10 slices while sources are divided into 10
or 15 slices depending on the thickness of the material. The completed sink form is shown in
Figure 3.6.
71
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fij Diffusion sinks — O X
Sink material name | Gypsum
Initial concentrations (CO)
CO (ug/m3)
Slice number = 10
Chemical name | TCPP
Slice[0]
0
SliccCI]
0
Sink location Zone 1 v
Slice[2]
0
Slice[3]
0
Sink area. A, (m2) | 800
Slice[4]
0
| Propagate
Slice[5]
0
Thickness, L, (m) | 0.01
Slice[6]
0
Slice[7]
0
Clear
Solid/air partition coef, K, (-) j 3.75E7 fflj
Slice[8]
0
S1ice[9]
0
Solid-phase diffusion coef, D, (m2/h) | 7.5E-11
Gas-phase mass transfer coef, h, (m/h) | 0.6)
X Cancel
Figure 3.6. Defining gypsum board walls in living area as a TCPP sink, This form is almost
identical to that for diffusion sources except that the number of slices is set to 10,
The distance that a chemical can travel into the sink material, known as the travel distance, is
limited for common indoor pollutants and within the timeframe of interest (from a few days to
several years). Thus, it is recommended that, for thick sink materials such as brick or concrete
walls, the thickness of the sink be set to 0,01 m.
3.3.5 Define simulation conditions
To complete the model, go to the < (7) Simulation conditions > folder. A table for initial air
concentrations has already been created, if there are non-zero initial concentrations, enter the
values here. For this tutorial, we assume the initial concentrations are all zeros. On the right-
side of the screen, select 6 months for simulation duration and 100 for output data points.
Finally, select the output data type by clicking the < Select > button, then choose "1) Air
concentrations" and return to the main window (Figure 3.7).
72
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3 IECCU (v 1.1) MyTCPP-O.lEC
File Model Run Data Tools Help
-
X
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (?) Simulation conditions (8) output
Simulation Conditions
Initial air concentrations (ug/m3)
Species
Zone 1
Zone 2
TCPP
0
0
Chemical names are automatically updated
App status: Awaiting user input
Simulation duration
Number of data points
Output selections
01) Air concentrations
Current page = (7) Simulation conditions
5,000 hours (~6 months)
Figure 3.7, Completed page < (7) Simulation conditions >.
3.4 Save., compile, inspect, and run the model
Save this model to as "MyTCPP-O.lEC".
Click the < Compile > speed button (sixth from left).
After successful compilation, click the < Inspect > speed button (seventh from left) to view the
compilation results.
Click the < Run > speed button (eighth from left) to start the simulation. The results are shown
in Figure 3.8.
73
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l.OE+3
ro
£
1
¦= 1.0E+2
c
o
c
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Tutorial 4: Simulating temperature-dependent TCPP emissions
4.1 Objective
To demonstrate how to define time-varying temperatures in unconditioned zones and
temperature-dependent partition and diffusion coefficients. The technical approach to
temperature functions are described in Sections 5.4 and 5.6 in the Tester's Guide.
4.2 Case description
In model "MyTCPP-O.lEC" developed in Tutorial 3, we assumed that the partition and diffusion
coefficients for TCPP in the SPF are both constant. In real world, the temperature in the
unconditioned zones can vary substantially following diurnal and seasonal patterns. This
program allows the user to define the temperature profiles in unconditioned zones and
temperature-dependent partition and diffusion coefficients.
We will build the new model from "MyTCPP-O.lEC". The temperature profile in the attic is
simulated as a sine function, as described in Section 5.4.1 in the Tester's Guide. The input
parameters are shown in Table 4.1.
Note that the dates for peak temperature and SPF application must be in the form of
mm/dd/yyyy because the sine function considers the leap day (February 29) in a leap year.
Table 4.1. Parameters for the temperature profile in attic.
The empirical model for temperature dependence described by Tian et al. (2017) will be used to
determine the partition coefficient as a function of temperature (see Section 5.5.1 in the
Tester's Guide for details). Input parameters are shown in Table 4.2.
Table 4.2. Parameters for the temperature-dependent partition coefficient for TCPP in SPF.
Parameter
Value
Temperature function type
Annual average temperature
Amplitude for seasonal temperature cycle
Day of the year with highest temperature
Day of the year for SPF application
Sine function (seasonal)
20 °C
25 °C
07/17/2016
05/01/2016
75
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Parameter
Value
TCPP-SPF partition coefficient Ki (dimensionless)
3.06E5
Temperature Ti (K)
298.2
Absolute value of slope (a)
0.9
Evaporation enthalpy, AHV (J)
8.1E4
The method for estimating the diffusion coefficient as a function of temperature is also from
Tien et al. (2016). See Section 5.6.2 in the Tester's Guide for details. Input parameters are
shown in Table 4.3.
Table 4.3. Parameters for the temperature-dependent diffusion coefficient for TCPP in SPF.
Parameter
Value
Material specific constant (m2/h)
6.05E6
Activation energy, AE (J/mol)
9.58E4
4.3 Create the model
Three steps are needed to use the temperature functions:
1. Define the temperature profile;
2. Modify the SPF source to allow K and D to vary with temperature;
3. Define the temperature functions of partition and diffusion coefficients.
4.3.1 Define temperature profile in attic
Open the model "MyTCPP-O.lEC" if it is not currently active.
Click the < (1) Building & environment > folder tab and then click the < d) Temperature (1) >
page tab. This page is disabled by default. Click the < Enabled > radio button to activate this
page (Figure 4.1).
Click the < Get Zone Name > button to collect information about unconditioned zones. Now the
table header shows that Zone 2 (attic) is an unconditioned zone (Figure 4.1).
76
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¦ ' profile
— X
Parameters to* dium*l cycles
Zone 2 * rtljc
y
Drily vi-erage temperature (Q
- Sefea - v ^
AmpKude of cyc*e {C>
Dsta-iime for pe#* tempeeptur* occurence
Pwk trrnpr jrli-rr eLit* of Sh# ;rrr nVTVO-l ff-ff
Pji for tutorial tydn
Peak temperature lime of the d*y hhtmmtss
Amuarf [impbilurt i'Q
Dane/lime for SPf app4»c*t»on
5PF it-plicamcri slvt cwte rr«-n cid'yyyy
AmpLfcud» of (Q
SPF appfitaSioii sLart limr hlvrnr* is
S2^ | X C«n«»
Figure 4.2. Input form for temperature profiles. Select temperature function at up-left corner
first.
Select "Sine function (Seasonal)".
Enter the parameters according to Table 4.1. Ignore the input boxes that are greyed out. The
completed form is shown in Figure 4.3.
Note that the input boxes for date and time are "masked" fields. To enter the date 07/17/2016,
move the cursor to the beginning of the input box and then simply enter 07172016 without the
slashes.
After completing data entry, click < OK > to accept.
78
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¦ Temperature profile
"
X 1
Zone j » atte
^Kameters for diurnal cycSes
Temperature functions
Da#/ a. era 9*temperature tC)
Sin* function CSeatonaf}
Aflipl page under the < (2) Sources > folder
tab.
Click a cell in column 1 in the data table and then click < Edit > (Figure 4.4).
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3 IECCU (v 1.1 ) MyTCPP-1.IEC
File Model Run Data Tools Help
¦rn
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (S) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Empirical models b) Application-phase
c) Diffusion model d) Temperature-dependent K & D
Difuslon model for long-term emissions
1
2
3
4
5 6
7
8 9
1
Source name
SPF
Chemical
*
Q Add
Zone ID
\
Area (m2)
180
Click on data column first
Thickness (m)
0.1
E Edit
M-)
3.6E5
0 (m2/h)
IE-10
Then click buttc
/
h (m/h)
0.4
O Delete
C010] (ug/m3)
1.01E9
COfl) (ug/m3)
101E9
CO{2] (ug/m3)
1.01E9
CO(3] (ug/m3)
1.01E9
i niFQ
V
*
App status: Awaiting u
Current page = (2) Sources / c) Diffusion model
Figure 4,4, To make changes to an existing item, click the data column first and then click
< Edit >.
In the data entry form for diffusion sources, there is a button next to the input box for partition
coefficient with the caption of "f(Tj", which is for "function of temperature". Click that button.
After a confirmation message appears, click < Yes > to confirm the change.
Do the same for the diffusion coefficient. The completed form is shown in Figure 4.5.
80
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¦ Diffuksiifi
— ~ X
Initial concp^traf^ns (CO)
Scuicc niim | 5PF
CG-jug/mSl
She* numbfi r I 5
yiceJOJ
ChameiBl unit | TCPP
Slice|l]
1.0IE9
] C* -Miust
Siutf
1.0SE9
Seurc* lautian ZOfW 2 v
1.0H9
fevcm*. frnB |'«
Slice! 5]
1.0IE9
1.0IH
1.01H
, ; Prnp*girt*
fla^
101£9
SJitelB]
1.DIE'S
Cte*
drttaM* coef, D, tym&hji |^[
Slic«W
5i.ceJ 1 If
51ic«l 12L
1.0IE4
1.01»
1.0IES
1.01E9
Eta-ptitse miss utndtf cot#, K IrrvKi | C4
Stk«|13|
14W
SficeJUJ
1.01 E5
~ QK
X C«nc*l
Figure 4.5. Completed data entry form for diffusion sources.
4.3.3 Define temperature-dependent functions for partition coefficient
Click the < d) Temperature-dependent K & D > page tab. Note that this page is automatically
enabled when the model contains temperature dependent K and D. Click the
button (Figure 4.6) to allow the program to search for temperature dependent K and D from
the model.
81
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3 IECCU (V 1.1 ) MyTCPP-1.IEC
Pile Model Run Data Tools Help
- X
(1) Building & Environment (2) Sources (3) sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Empirical models b) Application-phase
c) Diffusion model d) Temperature-dependent K & D
Temperature-dependent partition and diffusion coefficients
Page status
Partition coefficient
Enabled
Serial No
Source name
Zone ID
ii Fill
Method ID
Parameter 1
Parameter 2
E Edit
Parameter 3
Parameter 4
0 Get Source ID
Solid-phase diffusion coefficient
Serial No
Source name
Zone ID
Method ID
Parameter 1
| i_ti Fill
® Help
Parameter 2
IS Edit
Parameter 3
Parameter 4
App status: Awaiting user input
Current page = (2) Sources / d) Temperature-dependent K & D | j| £lose |
Figure 4,6, Page < d) Temperature-dependent K & D > is automatically enabled if the model
contains temperature-dependent K and D.
To define the temperature function for the partition coefficient, click the < Fill > button on top
(see Figure 4.6) to bring up the input form, as shown in Figure 4.7.
¦ iPanifcon coot. (IC) as a lunnion or leir.nor
-------
From the box at the top left corner for "Select a method for K", select "Tian et al. (2017)" by
using the pull-down menu.
Enter the values listed in Table 4,4 in the panel on the right side.
Table 4.4. Parameters for the temperature-dependent partition coefficient for TCPP in SPF.
Parameter
Value
Partition coefficient K1 (-)
3.06E5 (for TCPP / LD/OC SPF)
Temperature T1 (K)
298.2 (i.e., 25 °C)
Absolute value of slope a
0.9 (See on-screen description on the right)
Evaporation enthalpy, dHv (J)
8.1E4 (See on-screen description on the right)
The completed form is shown in Figure 4.8. Click < OK > to accept.
* Pi-T liewi eoef. ;Ki ** a Aura toe n al wwiporwrun*
-
X
SaIbcI a method for l€
T«netal, f2CH5) w
Sowce «a«ne - SPF / location * Zone 2
Parameters
Method desenphon
Partition coefficient Kl (-> 3.06ES
Partrtwn coefficient as a'unction erf ttropvwjit
METHOD 2
In 0Q/K1) = Rl X (1/T2 -1 Al)
where
Kl. K2 = partrticn c efficient «t 1crnpeiatare-v T1 and T2 |dim«rvuoTile*«l-.
rtHf = vaponjaiion enthalpy tfL
T1, T2 * •fcsolvte temperature corresp-onchng to K* »npor1«<£ to fc# b#tw*pn G.7J3 end 1.05- Far op»n-c*ll tPU foirn;
1 Constant dWv has the value of 8k 1 E4 (!)•
Evaporation enthalpy-, dNv UJ B.1E4
F.rf Tien e*. ml (201 Sj
10
/SK | X Cind
Figure 4.8. Completed temperature function form for partition coefficient.
83
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4.3.4 Define temperature-dependent functions for diffusion coefficient
To define the temperature function for diffusion coefficient, click the < Fill > button in the lower
part of the screen (See Figure 4.6 above). The temperature function form for diffusion
coefficient is similar to that for partition coefficient.
Use the pull-down menu in the "Select a method for D" box at the top-left corner to select
"Tian etal. (2017)".
Enter the values in Table 4.5 the right-side panel:
Table 4.5. Parameters for the temperature-dependent diffusion coefficient for TCPP in SPF.
Parameter
Value
Material specific constant (m2/h)
6.05E6
Activation energy, AE (J/mol)
9.58E4
These parameters give a D value of 1.0E-10 (m2/h) at 25 C for TCPP.
The completed form is shown in Figure 4.9. Click the button to accept.
¦ Dxffuskm coei- IjDl as a krsticfi ol lemperatxre
— ~ X
Select » method D
Tien el aJ. <2015) *g|
Source iwme = SPF / locffcc*i - Zone 2
Pinmrtm
Mrthod ^escnptjon
Mitrrtll bprc
rfic cnmtjint, DO (*n2/h| 6.QSE6
Seidl-pfrwse ddfufccet coetfeterx is a function of tervip«ifiur«
METHOD 3
D = 00 *xjj(-dH t FT}
where
0 * soad-ph«« diffusion codfkieMt rt temperature T
00 = m#te«4l ipectfic constant 'or a flN-en thtirscii
dH = jn pqur.flWrit of Klivatn «n»iyy IJ/mpfJ'.
R r gat ccrwibM = 3.31-i Cl/Kj'mofj
T * absolute temperature iJU.
Activation enugv. d£ U'Vnol"- 9,58f.4
NQfTfe T^n « «l. mpgoi that
-------
4.3.5 Select output data types
Click the < (7) Simulation conditions > folder tab. Select "10,000 hours (~1 year)" for simulation
duration and 200 for output data points.
Click < Select > and then choose the following output types:
1) Air concentrations,
6) Temperature profiles in unconditioned zone(s),
7) Temperature-dependent partition coef. (K),
8) Temperature-dependent diffusion coef. (D).
4.4 Save, compile, inspect and run the model
Save the model to file "MyTCPP-l.lEC".
Compile, inspect and then run the model.
Simulation results are shown in Figures 4.10 through 4.13.
1000
Living area
100
Attic
10
1
0.1
0
100
200
Elapsed Time (days)
300
400
Figure 4.10. Simulated TCPP concentrations in living area and attic with model "MyTCPP-l.lEC".
85
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60
July 17, 2016
50
40
30
May 1, 2016
20
10
0
Jan. 15, 2017
-10
-20
0
50
100
150
Elapsed Time (days)
200
250
300
350
400
Figure 4.11. Simulated air temperature in attic with model "MyTCPP-l.lEC".
l.OE+8
1.0E+7
0)
£
O
£ 1.0E+6
-------
1.0E-8
1.0E-9
1.0E-10
l.OE-11
l.OE-12
l.OE-13
0
100
200
300
400
Elasped Time (days)
Figure 4.13. Simulated diffusion coefficient for TCPP-SPF as a function of temperature with
model "MyTCPP-l.lEC".
87
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Tutorial 5: Using the batch mode
5.1 Objective
To demonstrate how to run multiple simulations sequentially unattended. Under the batch
mode, the user can run an unlimited number of models. Available simulation modes in IECCU
are discussed in Section 3.5 in the Tester's Guide.
5.2 General steps
Running simulations in batch mode involves four steps:
1. Create an empty folder,
2. Save or copy model files to that folder,
3. Click the < Run batch > speed button,
4. Retrieve simulation results from comma separated value (CSV) files.
5.3 Case description
We have created four models so far. In this practice we will run these four models all together.
5.4 Run batch
5.4.1 Create an empty folder
Create a folder in your hard drive, USB drive, or remote storage device and name it \IEC_batch.
5.4.2 Save or copy model files to that folder
Copy the following four model files to folder \IEC_batch.
• MyModel-l.lEC,
88
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Confirmation
X
o
l You are entering the batch mode. Do you need any
help?
Yes
No
Cancel
Figure 5.2. Confirmation message for batch mode.
After viewing the help window, an open file dialog will be displayed (Figure 5.3). Locate the
folder \lEC-batch, and press Ctrl-A to select all four files in the folder, then click < Open >.
Open existing file
~ Libraries ~ Documents ~ My Documents ~ IEC-CU
» +t Search IEC-CU
Organize T New folder
*¦
Favorites
¦ Desktop
if Downloads
ij. Recent Places
i? Dropbox
Libraries
Documents
Music
Jg, Pictures
Videos
ifc Computer
?Sr nsnisk fC:)
Documents library
IEC-CU
ss_- &
Arrange by: Folder"
'Jk
Name
Date modified
Type
MyModel-l.IEC
9/16/201611:35 A...
IEC File
MyModel-2,IEC
9/16/201611:41 A...
IEC File
MyTCPP-O.IEC
9/16/2016 12:57 PM
IEC File
MyTCPP-l.IEC
9/16/2016 1:05 PM
IEC File
File name: "MyTCPP-O.IEC" "MyTCPP-l.IEC" "MyModel-l.IEC" "MyModel-2JEC" -
IEC-CU model
Open
Cancel
Figure 5.3. Open file dialog,
Another message will appear asking you whether you want to compile the selected models
before the simulations start (Figure 5.4).
90
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Click < Continue > to start simulations.
During batch simulations, the status is updated in real time (Figure 5.6).
J1 Batch simulation status — X
Running batch file J of 4
Simulation duration: 5000 (h)
Elapsed time: 1775(h)
<^GK
X Cancel
Figure 5.6. The status window for a batch simulation .
When simulations are completed, a batch report will be displayed (Figure 5.7).
92
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|i' Batch mode ~ Simulation summary
Folder = C:\Users\37591\Documents\IEC-CU\
MyModel-1. IEC Success
MyModel-2 .IEC Success
MyTCPP-0 . IEC . Success
MyTCPP-1. IEC Success
Start date/time
Finish date/time
Elapsed time
= 9/19/2016 8:46:47
= 9/19/2016 8:53:45
= 0 hr 6 min 58 sec
^ OK
Figure 5.7. Batch simulation report.
5.4.4 Retrieve simulation results
Use Windows File Explorer to locate folder \IEC_batch. You can find six CVS files created by the
batch simulations. The data can be retrieved by any spreadsheet and database applications. Try
to double-click on a file name to open it.
93
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Tutorial 6: Gas-phase chemical reactions
6.1 Objective
To demonstrate how to include gas-phase chemical reactions in a model. Representation of
gas-phase chemical reactions is discussed in Section 5.10 in the User's Guide.
6.2 Case description
Methylene diphenyl diisocyanate (MDI) is an aromatic diisocyanate commonly used to
manufacture polyurethane. When SPF or polyurethane foam sealant is installed in a home by
on-site application, unreacted MDI may be introduced into the air. It is known that isocyanate
can react with moisture in air to form amines and carbon dioxide (Equation 1):
RNCO + H2O -> RNH2 + CO2 (1)
Note that MDI hydrolysis may be more complex than Equation 1 because MDI contains two
isocyanate function groups. As a practical matter, we will treat MDI hydrolysis as an apparent
second order process (Equation 2):
MDI + [H2O] —~ amines (2)
We omit CO2 because it occurs in large volumes in natural air; we placed water vapor in a pair
of square brackets because there is an excess amount of water vapor in air and there is no need
to track its concentration change over time. We also assume that, after formed, amines remain
in air.
The input parameters listed in Table 6.1 are for application of a polyurethane foam sealant in a
hypothetical small room. The source emission parameters are from the NRC-CNRC report (Won
et al., 2013). The second-order rate constant was roughly estimated from Figure A.4 in the
report: the MDI concentration reduced by one half when the relative humidity changed from 0
to 20%. Do not cite this number.
94
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Table 6.1. Input parameters for investigating the effect of hydrolytic reaction on MDI
concentrations.
Parameter
Value
Room volume
Air change flow
Source area
MDI emission factor, EO
MDI decay rate constant, k
26 m3
10.9 m3/h (equivalent to 0.42 ach)
0.01 m2
153 ng/m2/h (at 40 °C)
0.344 h1
Second-order reaction rate constant at 40 °C 2.5E-24 (cm3/molecule/s)
Molecular weight for MDI
Molecular weight for amines
Relative humidity
250
224
20% (at 40 °C)
6.3 Create the model
6.3.1 Define building and ventilation
Select < File > / < New > from the main menu or click the < New > speed button (first from left).
Use the default building configuration - a single conditioned zone.
Enter 26 for zone volume.
Click the < b) Ventilation (1) > page tab; locate Table 1 (for normal air exchange flows); enter
10.9 for air flow Qoi (i.e., from Zone 0 to Zone 1).
6.3.2 Define the first-order decay source
Click the < (2) Sources > folder tab and then click the < a) Empirical models > page tab.
Click the < Add > button.
In the input form for empirical sources, select model (12) First-order decay.
Enter the values in the required field (Figure 6.1). Click < OK >.
95
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!_' Emppirical Source Models
Empirical source models
(12) First-order decay
First-order decay source
R = A EO exp(-kt)
where
R = emission rate (ug/h)
A = source area (m2)
EO = initial emission factor (ug/m2/h)
k = First-order decay constant (1/h)
t = elapsed time (h)
Model parameters
Chemical name
Source location
MDI
Zone!
A(m2)
EO (ug/m2/h)
k (1/h)
[~00
153
0.344
^ OK
X Cancel
Figure 6.1. Representing MDI emission by the first-order decay source model.
6.3.3 Define the chemical reaction
Click the < (6) Chemical reactions > folder tab; click the < Add > button to bring up the input
form for chemical reactions.
Enter or select the values listed in Table 6,2.
Table 6.2. Input parameters for chemical reactions.
Parameter
Value
Reaction order
Second order
Type of rate constant (k)
K=constant
Value of rate constant
2.5 x icr24
Reactant A
MDI
Reactant B
[H20]
Number of reaction products
1
Yield 1
1
Product 1
amines
96
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The completed form is shown in Figure 6.2. Click < OK > to return to the main window.
¦ Gas-phase dwnlc-as neacilo
P-Mcbon crdei
— X
RttttinCi
S*ccntl ordei v.
Reartvit " MDI riant J [HZOI
Number of PMCtwn products
1 ~
TTyp« erf «at* c orv»*ant >[k)
k = CcraUrA w
^.pict'On p«cdudt ard ywrida
YwAd 1 [ 1 Prodkict 1 |
V«Iub of rmtm conat«nl i.'kj
k (cm3/molKul/ij | 25l-24
•> U Ur+*s v Mytfrolysw [ S QK | X Cwcd
Figure 6,2, Completed input form for chemical reactions.
Locate the molecular weight table on page < (6) Chemical reactions >; enter 250 for MDI and
224 for RNH2.
At the bottom-right corner, enter 20 for relative humidity and 40 for temperature.
The completed page is shown in Figure 6.3.
97
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0.012
MDI
0.010
m
amines
£
c3 0.008
£
~ 0.006
c
£ 0.004
o
u
0.002
0.000
0
2
4
6
8
10
Elapsed Time (h)
Figure 6.4. Simulated MDI and amines concentrations.
This model does not include MDI deposition to interior surfaces. Interior surfaces can act as an
irreversible sink for MDI. According to Won et al. (2013), the first-order deposition rate
constant for MDI in a glass chamber was 1.2 m/h. To add a MDI sink, click the < (3) Sinks >
folder tab and then the < a) Surface adsorption > page tab. Select sink model "(33) First-order
irreversible".
Be aware that chemical reactions may cause numerical difficulty during simulation. In case the
simulation fails, try < Run slow > — the second speed button from right.
99
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Tutorial 7: TCPP interactions with airborne particulate matter (PM)
7.1 Objective
To demonstrate how to include airborne PM in a model. Technical approach to modeling SVOC
interactions with airborne PM is given in Section 5.8 in the Tester's Guide.
7.2 Case description
As shown in Figure 4.10 above, the yearly average TCPP concentration in the living area is 2.7
l-ig/m3. We would like to estimate the particle-phase concentration for TCPP by assuming the
conditions in Table 7.1.
Table 7.1. Assumed properties for airborne PM.
Parameter
Value
Particle size
2.5 pirn
Particle density
1 g/cm3
Outdoor PM mass concentration
30 ng/m3
TCPP concentration in outdoor PM
0 M-g/g
Initial PM mass concentration in living area
14.4 ng/m3
Initial PM mass concentration in attic
25.1 ng/m3
Particle-air partition coefficient for TCPP[11
1E6 (dimensionless)
PM penetration factor
0.8
PM deposition rate constant in attic
0.60
PM deposition rate constant in living area
0.65
[11 The dimensionless particle-air partition coefficient is defined as Cp/Ca at equilibrium, where
Cp and Ca are the chemical concentrations in the particles and air, respectively, in the units of
(lag TCPP/m3dust).
7.3. Create the model
7.3.1 Open model MyTCPP-l.lEC
We will build this model by adding the PM component to the model you previously created in
Tutorial 1 (default file "MyTCPP-l.lEC").
100
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To open this model, click the < Open > speed button (third from left) to load MyTCPP-l.lEC.
7.3.2 Define airborne PM
Click the < (4) Airborne PM > folder tab to access the two input tables for PM, as shown in
Figure 7.1.
43 IECCU (v 1.1 ) Model- 1.IEC
- X
File Model Run
Data Tools Help
h ¦ 1
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (s) Settled Dust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Airborne PM b) Airborne PM (cont)
Airborne particulate matter (PM) — (1)
PM sources
Chemical name
1
2 1
3
4
5
6 1
PM name
Source type
Source location
Enter
chemical name^
PM size (um)
PM density (g/mL)
Q Add
Initial conc. (ug/g)
Partition coef (-)
C\\r\e folder tab, there are two pages: < a) Airborne PM >
(shown) and < b) Airborne PM (cont) >.
Enter chemical name "TCPP" in the box near the top-right corner.
Click the < Add > button to bring up the input form for PM.
Enter the required parameters according to Table 7.1. The completed form is shown in in Figure
7.2.
Click < OK > to return to the main window.
101
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7.3.4 Select output data types
Click the < (7) Simulation conditions > folder tab; click the < Select > button to choose the
following output types:
1) Air concentrations,
2) Chemical concentrations in airborne PM (ng/m3 air),
3) Chemical concentrations in airborne PM (|ig/g PM),
4) Mass concentration of airborne PM (ng/m3 air).
The completed page is shown in Figure 7.4.
3 IECCU M.I J MyTCPP-PM.lEC
File Model Run Data Tools Help
- X
u m.MMM ¦ ¦ ¦!
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (?) Simulation conditions (8) Output
Simulation Conditions
initial air concentrations (ug/m3)
Species
Zone 1 Zone 2
TCPP
0 0
Simulation duration
10,000 hours ("1 year)
Number of data points
Output selections
1) Air concentrations
2) Chemical concentrations in airborne PM (ug/m3 air)
3) Chemical concentrations in airborne PM (ug/g PM)
4) Mass concentration of airborne PM (ug/m3 air)
\'a Select
„o Clear
Chemical names are automatically updated
App status: Awaiting user input
Current page = (7) Simulation conditions
| U Qose |
Figure 7.4, Completed simulation conditions page. Output selection includes three types of PM
data.
103
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7.4 Save, compile, inspect, and run the model
Save the new model to file "MyTCPP-PM.lEC".
Compile, inspect and then run the model.
The results are shown in Figure 7.5.
1000
Attic
ao
no
ii. 100
Living area
10
l
o.i
0
50
100
150
200
250
300
350
400
Time (days)
Figure 7.5. Simulated particle-phase TCPP concentrations.
104
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Tutorial 8: TCPP interactions with settled dust
8.1 Objective
To demonstrate how to include settled dust in a model. Technical approach to modeling SVOC
interactions with airborne PM is given in Section 5.8 in the Tester's Guide.
8.2 Case description
In this tutorial, we will use the model you created in the previous section: MyTCPP-PM.IEC.
Additional parameters are shown in Table 8.1:
Table 8.1. Assumed properties for settled dust in living area (zone 1).
Parameter Value
Surface area 120 m2
Dust loading 5g/m2
Dust size 50 pirn
Dust density 1.2 g/cm3
Dust-air partition coefficient 1E6
Gas-phase mass transfer coefficient for TCPP/dust 5 m/h
Initial TCPP concentration in dust 0 ng/g
8.3 Create the model
8.3.1 Load model MyTCPP-PM.IEC
Open file TCPP-PM.IEC if it is not currently active.
8.3.2 Define settled dust
Click the < (5) Settled dust > folder tab.
Click the < Add > button to bring up the input form for settled dust (Figure 8.1).
105
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Give the dust a name, e.g., "D50"; select "Zone 1" for location; enter 50 for dust diameter and
1.2 for density. Now the form should look like Figure 8.1.
¦ Settled dust
Dust properties
X
Chemical properties
Oust rt»rn< 050
Cherrwcal name P
Location Zone 1 --
Oust air partition ccef {-)
Dust diwncCer Iwnj 50
Drtf usicn coef (m2/h)
Purt citflfity (3.'cm Si 12
Gas phase mau trailer ccef (m/h)
Oirft numb**
Initial content luejVg)
1 0 tfeip H | ~ QK A X Ctnctl
Figure 8.1. Input form for settled dust prior to calculating dust number.
Parameter "Dust number" is a calculated field. Click the button next to it (See Figure 8,1) to
display the calculation sheet (Figure 8.2). Note that, dust diameter and density have already
been copied to the sheet. Enter values on the left side of Figure 8.2 and then click the <
Calculate > button. Now the value "1.146E10" should appear in the box for "Dust number".
Click the < Paste > button to go back to the main window.
106
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Unit conversion — ~ X
Converting dust coverage (ug/m2) to dust number
Input
Diameter (um) 50
Density (g/cm3) 1-2
Loading (g/mZ) 5
Surface area (m2) 120
) Help
@ Calculate
Dust number
7.639E+09
Paste
)( Cancel
Figure 8.2. Calculation sheet for dust number.
Finish the right-side of input form for dust. The completed form is shown in Figure 8.3.
Click < OK > to return to the main window.
Now the < (5) Settled dust > page should look like Figure 8.4.
107
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8.3.3 Define simulation conditions
Click the < (7) Simulation conditions > folder tab and include "5) Chemical concentrations in
settled dust (ng/g dust)" in output selections (Figure 8.5):
y? IECCU (v 1.1 ) MyTCPP- PM -Dust.lEC
File Model Run Data Tools Help
¦Til
(1) Building & Environment (2) Sources (J) Sinks (4) Airborne PM (5) Settled Dust (6) Chemical reactions (?) Simulation conditions (g) Output
Simulation Conditions
Simulation duration
Initial air concentrations (ug/m3)
Species
Zone 1
Zone 2
TCPP
0
0
/
Chemical names are automatically updated (all Auto Fill
10,000 hours (~1 year)
Number of data points
Output selections
1) Air concentrations
5) Chemical concentrations in settled dust (ug/g dust)
r
lo Select
App status: Awaiting user input
Current page = (7) Simulation conditions
Figure 8.5. Including settled dust in output selections.
8.4 Save, compile, inspect and run the model
Save the model to file TCPP-PM-Dust.lEC.
Compile, inspect and then run the model.
The simulation results are presented in Figure 8.6.
109
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8
6
4
2
0
0
100
200
300
400
Elapsed Time (days)
Figure 8.6. Simulated TCPP concentration in settled dust in living area.
110
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Tutorial 9: Application-phase simulation
9.1 Objective
Demonstrate how to use application-phase simulation to predict short-term emissions of
hydrofluorocarbon blowing agent HCF-245fa (1,1,1,3,3-Pentafluoropropane) during SPF
insulation installation. The technical approach to application-phase simulation is described in
Section 5.5.2 in the Tester's Guide.
9.2 Case description
Hydrofluorocarbon HFC-245fa is used primarily as a blowing agent for closed-cell SPF insulation.
As an extremely volatile chemical, a vast majority of HFC-245fa is emitted during SPF
application with a tiny fraction being trapped in the foam and subject to long-term, low-level
emissions.
We will use the parameters in Table 9.1 for the building configuration and air flow matrix. The
parameters for the HFC-245fa source are based on conditioned described in Bevington et al.
(2017). We assume a total of 180 m2 of SPF insulation is installed in the attic during a 6-hour
period. Parameters for short emissions are shown in Tables 9.2.
Table 9.1. Zone volumes and ventilation rates
Parameter
Value
Volume of Zone 1 (living area)
Volume of Zone 2 (attic)
Ventilation rate of living area
Base ventilation rate in vented attic
Enhanced ventilation rate in vented attic
Duration of enhanced ventilation rate in vented attic
Air leakage flow from living area to attic (Q12)
Air leakage flow from attic to living area (Q21)
300 m3
150 m3
0.5 h1 (i.e., Qoi = 150 m3/h)
2.0 h1 (i.e., Q02 = 300 m3/h)
10 h1 (i.e., Qdz =1500 m3/h)
8 h
15 m3/h
15 m3/h
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Table 9.2. Parameters for short-term HFC245fa emissions
Parameter Value
Location of SPF insulation Attic
SPF area 180 m2
HCF245fa content formulation (Mo) 2.55E8 |-ig/m2
First-order decay rate constant for short-term 1 h 1
HFC245fa emission (k)
Application duration 6 hours
9.3 Create the model
9.3.1 Define building configuration
Click the < New > speed button (the first from left).
Click the < Select building configuration > button, then select the living area - attic
configuration.
Enter zone volumes.
9.3.2 Define airflow matrices for base and enhanced ventilation
Click the < b) Ventilation (1) > page tab, then enter the values in Tables 9.3 and 9.4 to Tables 1
and 2 on the screen. Before entering the data for enhanced ventilation, activate Table 2 by
clicking < Enabled > in the "Table 2 status" box. After finishing the tables, enter the start and
finish times (0 and 8 hours) for enhanced ventilation.
Table 9.3. Air flow matrix for base ventilation
To Zone 0
To Zone 1
To Zone 2
From Zone 0
XXX
150
300
From Zone 1
Calculated
XXX
15
From Zone 2
Calculated
15
XXX
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Table 9.4. Air flow matrix for enhanced ventilation during first 8 hours
To Zone 0
To Zone 1
To Zone 2
From Zone 0
XXX
150
1500
From Zone 1
Calculated
XXX
15
From Zone 2
Calculated
15
XXX
9.3.3 Define application-phase model
Click the < (2) Sources > folder tab and then click the < b) Application phase > page tab.
Click the < Add > button to bring up the input form for application-phase simulation.
To select an emission model, click the box near the top-left corner (Figure 9.1).
Select model "(22) First-order decay". Then enter the parameters as required (Figure 9.2).
¦ Emission during application otiase
Applicatiar.-ph.aia lourca modaii
- Select moW -
Modte description
Modal ?<'imrfn
Oieir»cal name
Source location
• a>- |
Figure 9.1. Input form for application-phase simulation.
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¦ 1 Emission during application phase
-
X
Application-phase source models
Model parameters
(22) First-order decay v
Chemical name
| HCF245f»
]
Source location
attic
Application-phase model for slower evaporation
Ri(t) = Ai MO k exp[-k (t - tO)J
Application start time (h)
1°
¦
where
Ri(t) = emission rate for an incremental area at time t (ug/h)
Ai = area of the incremental sourcee (m2)
MO = emittable amount of chemical (ug/m2/h)
k = first-order decay constant (1/h)
Application end time (h)
|6
1
Total area (A) (m2)
| 180
¦
t = elapsed time and t > = tO (h)
tO = time when the incremental area if applied (h)
NOTES:
Emittable amount (M0) (ug/m2)
[ 2.55E8
¦
To simulate the application-phase emissions, the source is divided into 200
incremental areas and the emission rate for each incremental area is calculated
separately.
First-order decay constant (It) (1/h)
P
1
1 1
X Cancel
Figure 9.2, Input form for application-phase simulation after the emission model is selected and
parameters entered.
9.3.4 Define simulation conditions
Click the < (7) Simulation conditions > folder tab; enter 20 hours for simulation duration and
100 for output data points.
For output data types, select "1) Air concentrations".
9.4 Save, compile, inspect and run the model
Save this model to "HFC-245fa.lEC".
Compile, inspect, and then run the model. The results are shown in Figure 9.3.
114
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7.0E+6
6.0E+6
E
So 5.0E+6
c 4.0E+6
o
o
K 3.0E+6
2.0E+6
1.0E+6
0.0E+0
SPF application ends
Enhanced ventilation ends
¦Living area
¦Attic
5 10 15
Elapsed Time (h)
20
Figure 9.3. Simulation results for HFC-245fa concentrations in attic and living area.
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Tutorial 10: Importing indoor-outdoor and zone-to-zone airflow data
10.1 Objective
To demonstrate how to import air flow data from a comma separated values (CSV) file
generated by other models. Representation of indoor-outdoor and zone-to-zone air flows in
IECCU is described in Section 5.3 in the Tester's Guide.
10.2 Case description
In this tutorial we will use the MyModel-l.lEC, which you created in Tutorial 1 and is for a
constant source in a single zone with a constant air change rate. We will replace the constant
air change flows with a set of dummy air flow data stored in file "Dummy air flows.CSV", which
is downloadable from the Secure File Sharing Website (Figure 10.1).
50
40
30
20
10
0
0
5
10
15
20
Elapsed Time (h)
Figure 10.1. Hypothetical air exchange flow from file "Dummy temperatures.CSV".
10.3 Create the model
Open the file MyModel-l.lEC.
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6
4
2
w/ imported air flows
w/ constant air flows
0
0
20
Elapsed Time (h)
Figure 10.3. Simulation results from models "Imported flows.IEC" (the blue curve) and
"MyModel-l.lEC" (the red curve).
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Tutorial 11: Importing indoor temperature data
11.1 Objective
To demonstrate how to import temperature data generated by other models. Representation
of indoor temperatures in unconditioned zones is described in Section 5.4 in the Tester's
Guide.
11.2 Case description
We will build this model by modifying the file "MyTCPP-l.lEC", in which the temperature profile
in the attic is defined by the user. In this tutorial, we will import hypothetical temperature
profiles from file "Dummy temperatures.CSV" (See Figure 11.1).
55
50
45
40
35
30
25
20
0
500
1000
1500
2000
2500
3000
Elapsed Time (h)
Figure 11.1. Hypothetical temperature profile in attic from file "Dummy temperatures.CSV".
119
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800
400
200
0
0
500
1000
1500
2000
2500
Elapsed Time (h)
Figure 11.3. Simulated TCPP concentration in attic.
20
15
10
5
0
0
500
1000
1500
2000
2500
Elapsed Time (h)
Figure 11.4. Simulated TCPP concentration in living area.
121
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Tutorial 12: Including an HVAC system
12.1 Objective
To demonstrate how to include an HVAC system in the model.
12.2 Case description
In this tutorial, we will use the case described in Tutorial 3 — TCPP emissions from SF applied in
attic. The only change is that there is an HVAC system in the attic. As shown in Figure 12.1, air
flows Q13, Q.31, Q23 and Q.32 represent, respectively, return air, supply air, air leakage from
attic into the HVAC system, and air leakage from the HVAC system into attic. Because the TCPP
source is located in the attic, the magnitude of the "leak-in" flow — Q23 — has the most
significant effect on the contaminant concentration in the living area.
Zone 2
(attic)
Q02
Q20
Zone 3
(HVAC)
Q21
Q23
Q32
Q12
Q13
Zone 1
(living area)
Q31
Q01
*Q10
*Calculated
Figure 12.1. Air zones and interzone air flows for modeling TCPP emission from SPF applied in
attic, where the HVAC system is located.
122
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IECCU treats the HVAC system as a special air zone. The volumes of the three zones are shown
in Table 12.1. In this tutorial, we set both the supply and return air flows (Q31 and Q13) to 1500
m3/h. We also assume that the leak-in (Q23) and leak-out (Q32) flows are both 150 m3/h (Table
12.2). Other interzonal air flows are the same as those in Tutorial 3.
Table 12.1. Zone names and volumes for Tutorial 12.
Zone ID
Zone Name
Volume (m3)
1
LvArea
300
2
Attic
150
3
HVAC
2.5
Table 12.2. Interzonal air flows for Tutorial 12 (Unit: m3/h)
To zone 0
To zone 1
To zone 2
To zone 3
From zone 0
XXX
150
300
0
From zone 1
Calculated
XXX
15
1500
From zone 2
Calculated
15
XXX
100
From zone 2
Calculated
1500
100
XXX
Note that the air flows moving in and out of the HVAC system (Q13, Q23, Q31, and Q32) are
those when the system is running. Because the HVAC switches frequently between on and off,
the simulation uses the time-averaged air flows, which are obtained by multiplying the HVAC
flow rates in Table 12.2 by the time fraction with the system turned on. In this tutorial, we
assume the HVAC is turned on 25% of the time. Thus, for example, the time-averaged return
flow is Q13 = 1500 x 25% = 375 m3/h.
12.3 Create the model
Open the model you created in Tutorial 3 ("MyTCPP-O.lEC"). To add the HVAC system to attic,
click the
-------
1 ¦ < IECCU (v 1.0) MyTCPP-O.lEC
File Model Run Tools Help
X 1
\wnrmiwm-
LLJl
(1) Building & Environment (2) Sources (3) Sinks (4) Airborne PM (S) Settled Oust (6) Chemical reactions (7) Simulation conditions (8) Output
a) Air Zones b) Ventilation (1) c) Ventilation (2) d) Temperature (1) e) Temperature (2)
IECCU Tutorial 3: TCPP
attic - base case
Both K and D are constant
from SPF applied in
_S, Select Building Configuration
Conditioned? Zone Name Volume (m3)
(living area)
f?) Help
Number of atr zones Has an HVAC system Time with HVAC on
I 0 %
Conditioned zone
Unconditioned zone
App status: Awaiting user input Current page = (1) Building & Environment / a) Air Zones
Figure 12.2. The building configuration for Tutorial 3. Click the
-------
¦No HVAC
¦With HVAC
50 100
Elapsed Time (days)
150
200
Figure 12.8. The effect of the HVAC system on the simulated TCPP concentrations in the living
area. The blue curve is from Tutorial 3. When the HVAC is in the source zone, the leak-in air
flow increases the chemical concentration in the conditioned zones.
128