The Stochastic Human Exposure and 

Dose Simulation Model 

for Multimedia, Multipathway Chemicals 

(SHEDS-Multimedia):Residential Module 

SHEDS-Residential version 4 

Draft User Guide 

June 16, 2010

Prepared by: Kristin Isaacs1, Casson Stallings1, Valerie Zartarian2, and Graham 

Glen1

1

 Alion Science and Technology

2

US Environmental Protection Agency, Office of Research and Development, National Exposure Research 

Laboratory
i 

TABLE OF CONTENTS 

LIST OF FIGURES......................................................................................................................... v 

LIST OF TABLES ........................................................................................................................ vii 

ACRONYMS AND ABBREVIATIONS ....................................................................................... x 

1 Considerations for New Users of SHEDS-Residential............................................................. 1 

1.1 Introduction............................................................................................................. 1 

1.2 Entering Distributions............................................................................................. 2 

1.3 Configuring SHEDS to the Scenarios of Interest.................................................... 3 

2 Overview................................................................................................................................... 5 

2.1 Introduction............................................................................................................. 5 

2.2 Using the Demonstration Case Study for Permethrin............................................. 6 

2.3 General Interface Hints ........................................................................................... 9 

2.3.1 Display Issues ............................................................................................ 9 

2.3.2 Grayed Out Buttons or Widgets ................................................................ 9 

2.3.3 Entering Probability Vectors ..................................................................... 9 

2.3.4 Distributions Supported........................................................................... 11 

2.3.5 Entering Distributions ............................................................................. 12 

2.3.5.1 Individual Distribution Widgets ................................................ 12 

2.3.5.2 Entering Empirical Distributions ............................................... 13 

2.3.5.3 Entering Uncertainty Distributions ............................................ 14 

3 Installation............................................................................................................................... 16 

3.1 Requirements ........................................................................................................ 16 

3.2 Installation under MS Windows ........................................................................... 17 

3.2.1 Starting With a CD .................................................................................. 17 

3.2.2 Starting with a Downloaded File............................................................. 17 

3.2.3 The Standard Installation Process............................................................ 17 

3.2.4 Starting the Model Interface .................................................................... 20 

3.2.5 Removing SHEDS-Residential ............................................................... 20 

4 The SAS User Interface .......................................................................................................... 21 

4.1 The SAS Screen .................................................................................................... 21 

5 SHEDS-Residential: The Graphical User Interface................................................................ 24 

5.1 SHEDS Mode........................................................................................................ 24 

5.2 SHEDS-Residential Main Interface Screen .......................................................... 24 

5.3 Specify Run Name and Files................................................................................. 26 

5.3.1 Specify Run Name Dialog....................................................................... 26

5.3.1.1 Edit Selected Run....................................................................... 27 

5.3.1.2 Copy Selected Run To New Run ............................................... 27 

5.3.1.3 Create a New Run ...................................................................... 28 

5.3.1.4 View Results of Selected Run.................................................... 28 

5.3.1.5 Delete Selected Run................................................................... 28 

5.3.2 New Run Name Dialog ........................................................................... 29

5.3.3 Specify Files Dialog ................................................................................ 29 
ii 

5.4 Specify Population and Sampling......................................................................... 30 

5.4.1 Specify Sensitivity Settings ..................................................................... 32 

5.4.1.1 Percentile Scaling Run Settings ................................................. 32 

5.4.1.2 Sobol’s Method Run Settings .................................................... 33 

5.5 Specify Simulation Information............................................................................ 34 

5.5.1 Simulation Length ................................................................................... 35 

5.5.2 Source-To-Concentration Approach and Application Dates................... 35 

5.5.3 Dermal Exposure Method........................................................................ 36

5.5.4 Diary Assembly Method.......................................................................... 36 

5.5.5 Simulate Product Handlers...................................................................... 37 

5.5.6 Export Data For PBPK Model................................................................. 37 

5.5.7 Keep Intermediate Variables ................................................................... 37

5.5.8 Save the Log File..................................................................................... 37 

5.6 Specify Chemicals................................................................................................. 39 

5.6.1 Add a User-Defined Chemical ................................................................ 40 

5.6.2 Specify Chemical Information................................................................. 40 

5.7 Specify Application Scenarios Simulated............................................................. 41 

5.7.1 Specify Application Scenarios................................................................. 42

5.7.1.1 Create User-Defined Scenario ................................................... 44 

5.7.2 Specify Exposure Scenario Details.......................................................... 44 

5.7.3 Specify Chemicals in Scenario................................................................ 46 

5.7.4 Specify Application Dates: Model-Determined ...................................... 47 

5.7.5 Specify Application Dates: User Specified ............................................. 49 

5.7.6 Specify Co-Occurrence............................................................................ 49 

5.7.7 Specify Application Times ...................................................................... 51 

5.7.8 Specify Fraction of Area Treated ............................................................ 52 

5.7.9 Specify Re-entry Times ........................................................................... 52 

5.8 Specify Concentration-Related Inputs .................................................................. 53 

5.8.1 Specify Decay and Dispersion Distributions........................................... 54 

5.8.2 Specify Interval Distributions.................................................................. 57 

5.8.3 Specify Handler Distributions ................................................................. 58

5.8.4 Background.............................................................................................. 59 

5.8.5 Specify Time Series Inputs...................................................................... 60 

5.9 Specify General Exposure and Dose Factors ........................................................ 61 

5.9.1 Variability Distributions.......................................................................... 61 

5.9.2 Edit Variability Distributions .................................................................. 63 

5.9.2.1 Days Between Baths .................................................................. 66 

5.9.3 Correlating Input Variables ..................................................................... 66 

5.9.3.1 Select Correlated Variables........................................................ 68 

5.9.3.2 Specify Variable Correlations.................................................... 69 

5.10 Run Simulation ..................................................................................................... 71 

5.11 View Results ......................................................................................................... 73 

5.11.1 Additional Outputs and Files................................................................... 74 

5.11.2 View Results for the Population.............................................................. 74
iii 

5.11.2.1 Summary Table........................................................................ 77 

5.11.2.2 CDF.......................................................................................... 78 

5.11.2.3 Box and Whiskers.................................................................... 79 

5.11.2.4 Contribution by Pathway.......................................................... 81 

5.11.3 View Results for an Individual................................................................ 82 

5.11.3.1 Time-Series.............................................................................. 84 

5.11.3.2 CDF.......................................................................................... 85 

5.11.3.3 Box and Whiskers.................................................................... 86 

5.11.3.4 Contribution by Pathway.......................................................... 87 

5.11.3.5 Summary Table........................................................................ 88 

5.11.3.6 Detailed Table.......................................................................... 88 

5.11.4 View Uncertainty Results........................................................................ 89 

5.11.5 View Sensitivity Results.......................................................................... 92 

5.11.5.1 Results for a Percentile Scaling Run........................................ 93 

5.11.5.2 Results for a Sobol Sensitivity Run ......................................... 95 

5.11.5.3 Results for a Input-Output Correlation Sensitivity Run........... 96 

5.11.6 View Diary Pool Sizes............................................................................. 97 

6 Case Study: Permethrin........................................................................................................... 98 

7 SHEDS-Residential: Batch Mode......................................................................................... 120 

7.1 Installing Batch Capability.................................................................................. 120 

7.2 Defining Inputs for a Batch Run ......................................................................... 120 

7.3 Submitting a Batch Run...................................................................................... 122 

7.4 Uncertainty and Sensitivity Runs........................................................................ 122 

Appendix A. Directories and Files.............................................................................................. 123 

A.1 Directories........................................................................................................... 123 

A.2 Critical Input Files .............................................................................................. 123 

A.3 User Specified Output Files ................................................................................ 124 

A.4 Other Output Files............................................................................................... 125 

A.4.1 Diary Related Output Files.................................................................... 125 

A.5 Exporting SAS Datasets...................................................................................... 125 

8 References............................................................................................................................. 126 

Appendix B. Reference Tables ................................................................................................... 127 

B.1 Variable Names................................................................................................... 127 

Appendix C. Probability Density Functions ............................................................................... 130 

C.1 Beta ..................................................................................................................... 130 

C.2 Exponential ......................................................................................................... 130 

C.3 Gamma................................................................................................................ 130 

C.4 Lognormal........................................................................................................... 131 

C.5 Normal ................................................................................................................ 131 

C.6 Point .................................................................................................................... 132 

C.7 Triangular............................................................................................................ 132 

C.8 Uniform............................................................................................................... 132 

C.9 Weibull................................................................................................................ 132 

C.10 Binomial Distributions........................................................................................ 133 
iv 

C.11 Discrete Probability Density Functions .............................................................. 133 
v 

LIST OF FIGURES 

Figure 2.1. Overview of the SHEDS-Residential Interface at Version 4........................................ 8 

Figure 2.2. Example of List Box with a Blue Background Indicating There are More Groups to 

Complete................................................................................................................................. 9 

Figure 2.3. Sample of Two Buttons, One Normal and One Grayed Out (Bottom)......................... 9 

Figure 2.4. Specify Application Times Screen Containing a Probability Vector. ........................ 10 

Figure 2.5. Example Distribution Widget..................................................................................... 13 

Figure 2.6. Example Empirical Data File and File Specification in the Distribution Widget. ..... 14 

Figure 2.7. Example Uncertainty Dataset and File Specification in the Distribution Widget. ..... 15 

Figure 3.1. Setup Screens: Initial Screen. .................................................................................... 17 

Figure 3.2. Setup Screens: Welcome and Information Screen...................................................... 18 

Figure 3.3. Setup Screens: Installation. Directory Screen............................................................. 18 

Figure 3.4. Setup Screens: Shortcut Folder Name. ....................................................................... 19 

Figure 3.5. Setup Screens: Confirmation Screen. ......................................................................... 19 

Figure 3.6. Setup Screens: Completion Confirmation. ................................................................. 20 

Figure 4.1. The Main Model GUI Interface Screen in the SAS Window on Startup. .................. 22 

Figure 4.2. The SAS Menu Bar and the View Menu.................................................................... 23 

Figure 4.3. The SAS Results Window.......................................................................................... 23 

Figure 4.4. The SAS Explorer Window........................................................................................ 23 

Figure 5.1. The SHEDS Mode Screen .......................................................................................... 24 

Figure 5.2. SHEDS-Residential Main Screen............................................................................... 25 

Figure 5.3. Specify Run Name Screen. ......................................................................................... 27 

Figure 5.4. Enter New Run Name screen...................................................................................... 28 

Figure 5.5. Specify Files Screen. .................................................................................................. 28 

Figure 5.6. Confirm Delete dialog. ............................................................................................... 28 

Figure 5.7. Specify Population and Sampling Screen................................................................... 30 

Figure 5.8. The Sampling Method selection box for an uncertainty run. .................................... 31 

Figure 5.9. The Sampling Method selection box for a Percentile Scaling or Sobol sensitivity run.

............................................................................................................................................... 31 

Figure 5.10. Subset CHAD Screen. .............................................................................................. 32 

Figure 5.11. Sensitivity Settings: Percentile Scaling Method....................................................... 33 

Figure 5.12. Sensitivity Settings: Sobol’s Method. ...................................................................... 34 

Figure 5.13. Specify Simulation Information Screen.................................................................... 38 

Figure 5.14. Specify Chemicals Screen. ....................................................................................... 39 

Figure 5.15. Enter Chemical Name for User-Defined Chemical. ................................................. 40 

Figure 5.16. Specify Chemical Information Screen...................................................................... 41 

Figure 5.17. Specify Application Scenarios – Select Scenarios Screen........................................ 43 

Figure 5.18. Add New Scenario Screen........................................................................................ 44 

Figure 5.19. Specify Application Scenario Details Screen. .......................................................... 46 

Figure 5.20. Specify Chemicals in Scenario Screen. .................................................................... 47 

Figure 5.21. Specify Application Dates Screen for Model-Determined Application Dates. ........ 48 

Figure 5.22. Specify Application Dates: User Specifed Screen.................................................... 49 

Figure 5.23. Specify Co-Occurrence Screen................................................................................. 50 
vi 

Figure 5.24. Specify Application Times Screen. .......................................................................... 51 

Figure 5.25. Specify Fraction of Area Treated Screen.................................................................. 52 

Figure 5.26. Specify Re-entry Times Screen ................................................................................ 53 

Figure 5.27. Specify Decay and Dispersion Distributions for an Indoor Scenario. ...................... 56 

Figure 5.28. Specify Post-Application Distributions Screen for An Indoor Scenario .................. 58 

Figure 5.29. Specify Handler Distributions Screen ...................................................................... 59 

Figure 5.30. Background Screen................................................................................................... 60 

Figure 5.31. Specify Time Series Inputs Screen. .......................................................................... 61 

Figure 5.32. Variability Distributions Screen. .............................................................................. 62 

Figure 5.33. An example of the Edit Variability Distributions Screen for Transfer-Related 

Variables. .............................................................................................................................. 64 

Figure 5.34. Variable with Two Conditions shown...................................................................... 65 

Figure 5.35. The Uncertainty Distribution # widget on the Edit Variability Distributions Screen 

when an Uncertainty distribution is Used. ............................................................................ 65 

Figure 5.36. Specify Days Between Baths Screen. ....................................................................... 66 

Figure 5.37. Select Correlated Variables Screen. ......................................................................... 67 

Figure 5.38. Error Displayed if Zero or One Variables are Selected for Correlation. .................. 69 

Figure 5.39. Error Displayed if No Variable Pairs are Selected for Correlation. ......................... 69 

Figure 5.40. Specify Variable Correlations Screen....................................................................... 70 

Figure 5.41. Run Simulation Screen for an Uncertainty Run. ...................................................... 71 

Figure 5.42. The Run Progress Screen for a Variability Run. ...................................................... 72 

Figure 5.43. Log Screen after Running a Small Simulation. ........................................................ 73 

Figure 5.44. View Results Screen................................................................................................. 74 

Figure 5.45. View Results for the Population Screen................................................................... 75 

Figure 5.46. Example Summary Table for a Population............................................................... 78 

Figure 5.47. Example CDF for a Population. ............................................................................... 79 

Figure 5.48. Example Population Box and Whiskers Plot............................................................ 80 

Figure 5.49. Example Pie Chart Showing the Contribution by Pathway for a Population. .......... 81 

Figure 5.50. View Results for an Individual Screen. .................................................................... 83 

Figure 5.51. Example Time-Series for an Individual.................................................................... 85 

Figure 5.52. Example CDF for an Individual. .............................................................................. 86 

Figure 5.53. Example Box and Whiskers Plot for an Individual. ................................................. 87 

Figure 5.54. Example Pie Chart Showing the contribution by pathway for an individual. .......... 88 

Figure 5.55. Example Detailed Table for an Individual................................................................ 89 

Figure 5.56. View Uncertainty Results Screen. ............................................................................ 90 

Figure 5.57. Plotting the 5th, 50th, and 95th Percentiles of Each Uncertainty Repetition............... 91 

Figure 5.58. Plotting the CDFs from Uncertainty Repetitions whose Medians are at the 5th, 50th

, 

and 95th Percentiles. .............................................................................................................. 92 

Figure 5.59. View Sensitivity Results Screen............................................................................... 93 

Figure 5.60. Sensitivity Results for a Percentile Scaling Run. ..................................................... 94 

Figure 5.61. Sensitivity Results for a Sobol Analysis Run.......................................................... 95 

Figure 5.62. Sensitivity Results for an Input-Output Correlation Run. ....................................... 96 

Figure 5.63. Example Diary Pool Size Table................................................................................ 97 

 
vii 

LIST OF TABLES 

Table 2-1. Probability Vector Errors Encountered ....................................................................... 11 

Table 2-2. Supported Variable Distributions ................................................................................ 12 

Table B-1. Variable Names From Distributions File.................................................................. 127 
viii 

Acknowledgements 

We would like to thank our colleagues in EPA’s Office of Pesticide Programs, and Dr. Andrew 

Geller in EPA's Office of Research and Development, for their review of this User Guide. 
ix 

Computing Issues, Disclaimer, and Support 

Computing Issues 

It is strongly advised that the SHEDS user maximize windows so that as much as possible of the 

full dialog is displayed. You may still need to scroll down to see all of some dialogs. Refer to the 

images in this User Guide to ensure that all components of a dialog are displayed. 

It is highly recommended that the user pause or disable any automated anti-virus or back-up 

programs that access the SHEDS installation or data output directories, or place these directories 

in locations that are not virus-checked or backed up. Such programs may access SHEDS data 

files and interfere with model performance, causing unpredictable results. 

Disclaimer 

EPA's SHEDS-Residential version 4 model can simulate cumulative (multiple chemicals) or 

aggregate (single chemical) residential exposures over time via multiple routes of exposure for 

different types of chemicals and scenarios. The United States Environmental Protection Agency, 

through its Office of Research and Development, developed and funded SHEDS-Residential 

version 4 with assistance from contractor Alion Science and Technology, Inc. 

SHEDS-Residential version 4 is one module (along with the separate SHEDS-Dietary module) of 

EPA’s more comprehensive human exposure model, the Stochastic Human Exposure and Dose 

Simulation model for multimedia, multipathway chemicals (SHEDS-Multimedia), which can 

simulate aggregate or cumulative exposures over time via multiple routes of exposure (dietary & 

non-dietary) for different types of chemicals and scenarios. SHEDS-Residential and SHEDSDietary will be merged together in a future version of SHEDS-Multimedia. 

SHEDS-Residential version 4 includes a case study example for illustrative purposes, as well as 

a default file for non-chemical specific inputs, as described in the Technical Manual and User 

Guide. All input values used in the SHEDS-Residential model for a given application should be 

entered or reviewed by the researcher so that the model results are based on appropriate data 

sources for the given application. 

Version 4 of SHEDS-Residential reflects comments from EPA's August 2007 external Scientific 

Advisory Panel that reviewed SHEDS-Multimedia version 3 (the aggregate residential version). 

SHEDS-Residential version 4 will undergo external peer review by EPA's Scientific Advisory 

Panel July, 2010, and should be considered draft at this time. 

Support

Please contact one of the following individuals with any questions, comments, or specific 

suggestions related to this beta version of the SHEDS model: 

Dr. Valerie Zartarian, (617) 918-1541, zartarian.valerie@epa.gov 

Dr. Jianping Xue, (919) 541-7962, xue.jianping@epa.gov 
x 

ACRONYMS AND ABBREVIATIONS 

CDFs – cumulative distribution functions 

CHAD – Consolidated Human Activity Database 

EPA – United States Environmental Protection Agency

GI – gastrointestinal 

GM – geometric mean 

GSD – geometric standard deviation 

GUI – graphical user interface 

NERL – National Exposure Research Laboratory 

NOAEL – no observed adverse effect level 

ORD –Office of Research and Development 

PBPK – physiologically-based pharmacokinetic 

PDFs – probability density functions 

SHEDS – Stochastic Human Exposure and Dose Simulation 

ug (in SAS printout or variable names) – microgram 
1 

1 Considerations for New Users of SHEDSResidential 

1.1 Introduction 

SHEDS-Residential version 4 (also referred to in this user guide as ‘SHEDS’) is a sophisticated 

but user-friendly cumulative and aggregate human exposure model for chemicals contacted in a 

residential setting. It requires the user to select appropriate inputs and to interpret the resulting 

outputs. Users should therefore be prepared to invest time to configure this model to exposure 

scenario(s) of their choice. Before attempting to run the model, it is recommended that new users 

review this User Guide and the Technical Manual to familiarize themselves with the model and 

the types of information that will be required. 

The SHEDS installation package includes the User Guide, Technical Manual, annotated SAS 

code for use via the graphical user interface (GUI), Consolidated Human Activity Database 

(CHAD) activity diary and population files, a height/weight data set, and default input 

distributions. The installation process is explained in this User Guide, which is intended to guide 

the user through the GUI. The interface has three functions: specifying inputs, executing the 

model, and storing and viewing the results. The Technical Manual contains a detailed 

description of the model’s structure and algorithms. 

The SHEDS model runs on a personal computer and requires that SAS 9.1 or higher be installed 

prior to the installation of SHEDS. It has been run successfully on various laptops and desktops 

using Windows XP. It has not yet been tested with Windows Vista. Though hardware 

requirements are modest, a full-scale model run may take a substantial amount of time. As a 

rough guide, a variability-only (1-stage Monte Carlo) run takes about 1 hour for every 1000 

persons being simulated and a typical run may be several thousand persons. Uncertainty (2-stage 

Monte Carlo) runs are much slower and may take several days to complete. 

SHEDS is a stochastic model in which each simulated individual is different. There are 

approximately 100 variables that can be sampled randomly for each person (although not all of 

these variables apply for a given model simulation); many of these variables require multiple 

samples per person as they change over time throughout the simulation period. Increasing the 

number of simulated individuals provides a better characterization of the population under study. 

SHEDS separately constructs time series for the environmental concentrations in each simulated 

person’s house, as well as an activity sequence through time based on the selection of human 

activity diaries from EPA’s Consolidated Human Activity Database (CHAD; 

http://www.epa.gov/chadnet1). These are combined, using exposure pathway-specific equations 

and exposure factors sampled from user-specified distributions, to generate a time series of 

exposure for each simulated individual. The time step is variable and depends on the event 

duration from the activity diaries, ranging from one minute to one hour. Therefore, a 1-year 
2 

simulation will have a very large number of such events (generally 10,000 to 20,000) for each 

simulated person. These results are automatically aggregated over time to produce (for example) 

daily exposure totals, although for some purposes the finer time resolution may be useful. Due to 

their size, the event-level exposure time series are not usually saved as permanent output; as a 

rule only summary statistics on daily and longer periods are saved. 

SHEDS does not attempt to model the exposures of particular individuals. Instead it randomly 

creates a population of simulated individuals who collectively represent the target population. 

Thus, an appropriate result of a model run might be the statement ‘SHEDS indicates that 5% of 

the target population receives an exposure in excess of ...’, but it is not appropriate to say that a 

specific real-world individual receives any particular exposure. 

SHEDS has a graphical user interface (GUI) that guides the user through the various input 

screens. The GUI comes with a demonstration scenario. It may be useful to copy this under a 

new name and to make changes to this copy. This is described in more detail later in this 

manual. 

SHEDS version 4 allows consideration of multiple chemicals per model run. The user may also 

select several scenario categories (each containing one or more of the different chemicals) to be 

analyzed together in the same run. The model permits the use of co-occurrence factors that 

control the likelihood of the various scenarios being applied at the same house at the same time. 

The human exposure results are automatically aggregated across the scenarios used in the given 

model run. The cumulative exposure results for all chemicals in the simulation are also 

determined. 

1.2 Entering Distributions 

Many SHEDS inputs are randomly sampled from user-specified distributions. SHEDS accepts a 

wide variety of continuous distributions as detailed in Appendix C. Some inputs require 

probability vectors (see the Appendix and section 4.1.1 of the Technical Manual). For 

continuous distributions, the user selects the type from a pull-down menu and then specifies the 

desired parameters. For discrete distributions (probability vectors) the user enters the probability 

of each outcome. 

The GUI will highlight invalid choices with a yellow background. This usually results from 

numeric parameters being specified that are incompatible with the type of distribution. For 

example, the lognormal distribution requires a geometric mean greater than zero and a geometric 

standard deviation greater than one. A missing numeric parameter will also result in the yellow 

error indicator. For probability vectors, the sum of the probabilities must be one or else an error 

will be indicated. 

The user has the option of truncating distributions at one or both ends by specifying minimum 

and/or maximum values. If the random number generation produces values outside these limits 
3 

then the values are automatically reset to the maximum or minimum, depending on which was 

exceeded. 

1.3 Configuring SHEDS to the Scenarios of Interest 

The user has the ability and the responsibility to configure SHEDS to a particular scenario(s) of 

interest. This includes specifying the target population, the simulation period, the chemical and 

application method(s) of interest, and the distributions for many model parameters. As an 

example, SHEDS supports three methods of determining the chemical concentrations: usersupplied time series, a decay/dispersion model based on chemical application dates, or a postapplication decrease based on time intervals. The user must choose which one is most 

appropriate for the problem at hand. These three methods are described in more detail in the 

SHEDS Technical Manual. 

The SHEDS installation package comes with example input distributions for demonstration 

purposes, to help orient users in how to run the model. These values can be used as a starting 

point for becoming familiar with the GUI, or modified by the user as appropriate. 

SHEDS is designed to estimate human exposure in a residential setting, but is not geared to any 

specific chemical. The user customizes the model run for the chemical of interest by setting 

appropriate input parameters, for example, product types and usage frequencies, initial 

application amounts, and concentration decay rates. The model allows the user to select one or 

more scenario application methods from a pre-determined list in the GUI. 

The SHEDS GUI allows the user to select the gender and age range of the target population. 

Again, SHEDS is a population-based model; therefore it would be appropriate for simulating 

exposure for school-age children in general, for example, but should not be expected to be 

reliable for simulating a specific child or even a specific set of children. Beyond age and gender, 

the user may target populations by selecting input distributions that reflect characteristics of 

those groups. 

SHEDS follows the real-world calendar. The "simulation period" is the user-specified time over 

which the exposure is tracked for each simulated individual. The model allows this to range 

from one day to several years, but the user should be aware of certain considerations. For 

example, if the user supplies concentration time-series data, then the period is limited to the 

extent of this data. Note that SHEDS version 4 does not change the age of individuals within the 

simulation period, and therefore simulation periods longer than one year may not be advisable for 

children. Finally, longer simulations require longer run times. 

SHEDS calculates exposure from several different pathways. If desired, the user may restrict the 

model to selected pathways by judicious specification of inputs. For example, ingestion of 

chemical via object mouthing can be "turned off" simply by setting the distribution for object-tomouth contact frequency to a point value of zero. Similarly, other pathways such as inhalation, 

hand mouthing, direct soil ingestion, dermal absorption, and GI tract absorption could be turned 

off. 
4 

There is no facility to supply differing inputs by region within a single run in SHEDS version 4. 

To model regional variation the user would have to construct a separate model run for each 

region with distinct input distributions. The distributions for each run would then reflect the 

variation within the given region (but not across regions). For example, pesticide usage may 

differ in warm and cold climates. Seasonal variation in pesticide usage is built into the model, as 

is seasonal variation in the human activity diaries. However, other inputs are assumed not to 

have seasonal variation when input via the GUI. By bypassing the GUI, advanced SAS users 

have the option of incorporating seasonal variation in distributions within a single model run. 
5 

2 Overview 

2.1 Introduction 

Reliable models for assessing human exposures are important for understanding health risks from 

chemicals. The Stochastic Human Exposure and Dose Simulation model for multimedia, 

multiroute/pathway chemicals (SHEDS-Multimedia), developed by EPA's Office of Research 

and Development (ORD), National Exposure Research Laboratory (NERL), is a state-of-science 

computer model for improving estimates of aggregate (single-chemical, multi-route/pathway) 

and cumulative (multi-chemical, multi-route/pathway) human exposure and dose. SHEDSMultimedia is the EPA/ORD’s principal model for simulating human exposures to a variety of 

multimedia, multipathway environmental chemicals such as pesticides, metals, and persistent 

bioaccumulative toxins. Exposure is defined in SHEDS-Multimedia as the contact between a 

chemical agent and a simulated human target at the external surfaces (skin and oral/nasal 

passage). Dose is defined in SHEDS-Multimedia as the amount of chemical that enters the target 

after crossing the exposure surfaces. As stated in section 1.1, SHEDS-Multimedia version 4 is 

comprised of both a residential module (SHEDS-Residential version 4.0), described in this user 

guide and a related technical manual (Glen et al., 2010), and a dietary module (SHEDS-Dietary 

version 1.0; Xue et al., 2010; Isaacs et al., 2010). This user guide focuses on the SHEDSResidential version 4.0 module only. However, please note that in anticipation of merging the 

residential and dietary modules in SHEDS-Multimedia, the name "SHEDS-Multimedia" appears 

on some of the screenshots in this user guide rather than "SHEDS-Residential." 

SHEDS-Residential is a physically-based, probabilistic model that predicts, for user-specified 

population cohorts, exposures incurred via inhaling contaminated air, touching contaminated 

surface residues, and ingesting residues from hand- or object- to-mouth activities. To do this, it 

combines information on chemical usage, human activity data (e.g., from time/activity diary 

surveys and videography studies), environmental residues and concentrations, and exposure 

factors to generate time series of exposure for simulated individuals. One-stage or two-stage 

Monte Carlo simulation is used to produce distributions of exposure for various population 

cohorts (e.g., age/gender groups) that reflect the variability and/or uncertainty in the input 

variables. While the core of SHEDS-Residential is the concentration-to-exposure module, there 

are various options (built-in source-to-concentration module; user-entered time series from other 

models or field study measurements) for obtaining concentration inputs and dose outputs 

(SHEDS-Residential has a built-in simple pharmacokinetic (PK) model, and SHEDS-Residential 

exposure outputs can be used as inputs to physiologically-based pharmacokinetic (PBPK) 

models). 

For a more detailed technical description of the SHEDS model, please refer to the SHEDSResidential version 4 Technical Manual. The purpose of this User Guide is to assist the SHEDSResidential user in navigating through the graphical user interface to apply SHEDS-Residential. 

Figure 2.1 provides an overview of the SHEDS-Residential user interface. Differences between 

the Version 3 interface and Version 4 are noted. The major interface screens are each 

represented with one box; not all screens are represented in Figure 2.1 (page 8). In general, the 
6 

user will navigate through the interface from left to right and top to bottom as shown on the 

overview. The exact screens visited will vary depending on the type of run being defined and 

data required for that run. Typically, the interface will prevent the user from moving ahead unless 

all data for the current step have been entered. 

The user interface guides the user through a set of screens that define the inputs needed for a 

SHEDS run. When a new run is created, most of these screens contain default choices, or 

choices from a previous model run, that the user may either edit or accept. The best way to run 

SHEDS is to carefully prepare the inputs for an initial baseline run; thereafter, one can start with 

the baseline run and make a small number of changes from run to run, greatly speeding up the 

process. A default file for non-chemical specific inputs is included with SHEDS-Residential 

version 4 (see Appendix G of the Technical Manual); these can be used for a simulation or 

modified by the user. 

Some sections will need to be revisited a number of times to enter all information. In particular, 

the sections defining application details and dates, and those defining media concentrations will 

need to be defined for each application or scenario type being simulated. The screens used to 

enter variability distributions will need to be revisited for each group of variables being defined. 

Every effort has been made to reduce the amount of information entered by the user. For 

instance, if dermal transfer efficiencies are being used, then the user will not be presented with 

the opportunity to enter data on dermal transfer coefficients. Likewise, if the decay and 

dispersion module is being used to model media concentrations, users will only enter information 

relevant to that and not to time-series or interval distributions. 

2.2 Using the Demonstration Case Study for Permethrin 

When installed, SHEDS-Residential version 4 comes with a completed sample run. This sample 

run is named “Permethrin Case Study” and is meant to assist the user in becoming familiar with 

the interface. This Case Study simulates a single scenario: a crack-crevice aerosol containing 

Permethrin. The simulations last one year for each individual, use the decay and dispersion 

method for simulating concentrations, use transfer efficiencies rather than transfer coefficients 

for dermal exposure calculations, and use the longitudinal diary assembly method. The run 

supplied contains results for 500 people. The user may change this value and re-run the 

simulation if a different number is desired. A typical production run will require substantially 

more individuals. Chapter 6 of the manual instructs the user how to re-create this run from 

scratch. 

The results from the file are available on installation and can be viewed by selecting the View 

Results of Selected Run button on the Specify Run Name dialog (described on page 26). While 

the inputs in the Permethrin Case Study will not be changed when you use the View Results 

button, changes made after selecting the file with Edit Selected Run will overwrite the original 

values. It is strongly recommended that the user not edit the original Permethrin Case 

Study. To view and edit inputs from the demonstration, go to the Specify Run Name dialog 

(described on page 26), highlight “Permethrin Case Study”, and click on Copy Selected Run To 
7 

New Run. You will be prompted for a new run name. After entering the run name and visiting 

the Run Files screen you will be free to make any desired changes without affecting the original 

Permethrin Case Study. 
8 

Specify Inputs for Variable Groups Define Correlated Input Variables

Specify Concentration-Related Inputs (Repeat for each Scenario)

Specify Run Name

Specify Population and 

Sampling

Main

Specify Simulation

Information

Run Simulation 

View Results

Specify Files New or Copied Run (if needed)

Specify 

Scenario

Application 

Times

Fraction of 

Indoor Area 

Treated 

(Indoor 

Scenarios)

Specify Inputs for Scenario (Repeat for Each Scenario)

Specify CoOccurrence

(if needed)

Application Dates: 

User Specified

Application Dates: 

Model Selected

Specify 

Scenario Details

Variability Distributions Edit Distributions (Activity-, Dose-, Transfer-, RemovaRelated) Specify Variable Correlations Select Correlated Variables

Time Series Inputs

Background 

Concentration 

Distributions

Specify Chemicals Specify Chemical Details

Model Dates

User Dates

Interval 

Concentration 

Distributions

Decay-Dispersion 

Intervals

Time Series

Decay and 

Dispersion 

Distributions Handler 

Distributions

(if needed)

Specify 

Chemicals in 

Scenario

(if cumulative 

run)

Specify General Exposure and Dose Factors

Run SHEDS Dietary 

(Future Implementation)

Baths

Model Dates

User Dates

Run Progress

New screen for V4Unchanged from VUpdated for V4Chemical-specific 

Individual Results

Population Variability

Sensitivity Settings

Sensitivity Results

Uncertainty Results

Figure 2.1. Overview of the SHEDS-Residential Interface at Version 4. 
9

2.3 General Interface Hints 

2.3.1 Display Issues 

Display issues can arise when SAS does not have room to display 

the entire dialog. When a screen does not initially draw correctly, 

either the top title text or the bottom left button (Continue, or 

Return) do not display. If in doubt, compare the display to the 

appropriate figure in this manual. The easiest method of 

minimizing these issues is to maximize the main SAS window. On 

smaller monitors some screens may still not display fully. The 

screen’s scroll bars should be used to view the bottom of the 

screen. Unfortunately, SAS does not always display the scroll bars 

automatically. Resizing the SHEDS dialog will force SAS to 

redraw the dialog and include scroll bars if necessary. 

2.3.2 Grayed Out Buttons or Widgets 

Occasionally buttons will be grayed out (displayed with muted 

text, see Figure 2.3). This may mean that a 

function has not been implemented. In version 4 the Help and 

About buttons have not been implemented yet. 

In many cases a grayed out button 

means that additional steps are 

required before the user is permitted to 

enter certain data. This is particularly 

true on the main screen where data 

entry must be completed sequentially, 

by starting at the top button and 

working down. There are also several screens where the user must complete data entry or editing 

for each group of variables listed before continuing. In these cases, the groups are listed on the 

left and all completed groups are listed on the right. If the groups remain uncompleted, the 

completed list is highlighted in a light blue (Figure 2.2). Another reason a button may be grayed 

out (Figure 2.3) is due to a current error on the screen. Typically, the user is not allowed to 

continue or navigate away from a screen when there are data entry errors on the screen. These 

errors will always be identified by yellow or red highlighting and often accompanied with a more 

specific error message. 

2.3.3 Entering Probability Vectors 

 There are a number of places in the interface where probability vectors must be entered. These 

are used to enter probabilities associated with a set of mutually exclusive outcomes. Each uses a 

Figure 2.2. Example of 

List Box with a Blue 

Background Indicating 

There are More Groups 

to Complete. 

Figure 2.3. Sample of Two Buttons, One Normal 

and One Grayed Out (Bottom). 
10

similar graphical interface as can be seen on the Specify Application Times screen (Figure 2.4). 

This screen contains two probability vectors where the user enters information on how long after 

a treatment the simulated individual stays out of the treated area. Each probability vector is 

composed of: 

• A container box with a descriptive title. In this case this title is ‘Probabilities for Time of 

Application for Outdoor (Lawn or Garden) Scenarios’; 

• A series of labeled text entry boxes. In this case 12 of them. Each is labeled and contains 

a probability; 

• A space below the text entry boxes where error messages may be displayed; and 

• An OK button used to validate the entry. 

Each text box must contain a probability, thus a number between 0 and 1 inclusive. The total of 

all probabilities must sum to one. The user can enter values in all but the last box (the one with a 

bold outline). The last box 

automatically displays the 

amount necessary to sum all 

probabilities in the vector to 

1. When an inappropriate 

value is entered by the user, 

the background will turn 

yellow and an error message 

will be displayed. The 

probability vector as a whole 

will be validated, and the sum 

recalculated every time the 

user uses the return key or 

when the OK button is 

clicked. Examples of possible 

error messages are shown in 

Table 2-1. The error 

messages are not displayed in 

some contexts. The text boxes are always highlighted in yellow. If there are errors with 

individual probabilities or with the sum of probabilities, the user will not be allowed to continue 

to the next screen. The errors must be corrected and the vector validated, or the Cancel button 

must be used. No values will be saved if the Cancel button is used. 

Figure 2.4. Specify Application Times Screen Containing a 

Probability Vector. 
11

2.3.4 Distributions Supported 

Since the SHEDS-Residential model is a stochastic model, a large number of its input variables 

are defined by distributions rather than constants. The model supports point values (constants) 

and 8 distributions. The distributions, parameter names, and rules for the parameters are given in 

Table 2-2. Detailed information on the distributions and their parameters can be found in the 

SHEDS-Residential Technical Manual. 

Table 2-1. Probability Vector Errors Encountered 

Error Sample Display 

The value entered was not a 

number. 

A negative value was entered. 

A value outside the range of 0 

to 1 was entered. 

The sum of all values entered 

is too large. 
12

Table 2-2. Supported Variable Distributions 

Distribution Number of 

Parameters 

Parameter Names Rules for Valid Distribution 

Point 1 Value 

Uniform 2 Minimum, Maximum minimum < maximum 

Normal 2 Mean, Standard 

Deviation 

standard deviation > 0 

Log Normal 2 Geometric Mean 

(GM), Geometric 

Standard 

Deviation(GSD) 

GM>0, GSD>1 

Triangle 3 Minimum, Mode, 

Maximum 

minimum ≤ mode ≤ maximum, 

minimum < maximum 

Exponential 2 Minimum, Mean minimum < mean 

Gamma 2 Shape, Scale shape>0, scale>0 

Binomial 1 Probability of positive 

(yes) outcome 

0 ≤ Probability ≤ 1 

Beta 2 Shape1, Shape2 shape1>0, shape2>0 

Weibull 2 Shape, Scale shape>0, scale>0 

Empirical 1 Full filename that 

containing list of 

measurements 

Plain text file that contains one 

numerical value on each line. 

Uncertainty 

(Only 

available for 

uncertainty 

runs) 

1 Name of SAS dataset 

containing N 

uncertainty 

distributions, one on 

each observation. 

Dataset must be saved 

in the UNC directory 

under the runname. 

Distributions may be of any type; 

multiple distributions types are 

allowed within a single uncertainty 

file. Each distribution definition 

must follow the rules contained in 

this table for different types. 

 

2.3.5 Entering Distributions 

2.3.5.1 Individual Distribution Widgets 

Distribution widgets are an interface object used to enter parametric distributions. They may be 

found on various interface screens (e.g., Figure 5.27, Figure 5.30, and Figure 5.28) and on the 
13

Edit Variables screen which also includes visualizations of the resulting distributions. The 

distribution widget (Figure 2.5) is composed of: 

• a container box with a descriptive title; 

• a pull-down combo box with a list of distributions;

• a series of labeled text entry boxes. The number of text entry boxes varies with the 

number of parameters required; and 

• an OK button to force validation. 

Enter a distribution by clicking on the pull-down arrow and making a selection from the list that 

is displayed. Then enter values for each parameter. Pressing the tab key will move from 

parameter to parameter. However, you will need to either press the enter key or click the OK 

button to force the values to be validated. If one or more of the values are incorrect when 

validated, the background of the container box will turn yellow and you will not be permitted to 

go to the next screen. Truncation minimum or maximums

1

 may be left undefined. The text box 

containing these values will indicate an error, but the distribution as a whole will still validate. 

After entering corrections hit return or click on the OK button to force validation and clear errors. 

In some contexts specific error messages will be displayed. 

2.3.5.2 Entering Empirical Distributions 

The “Empirical” distributions type is new for Version 4. This feature allows the users to define 

an empirical distribution via a list of measurements, rather than using a continuous probability 

distribution. Empirical distributions are contained in plain text files, with each line of the file 

containing a single numerical measurement or value. The user creates these files outside SHEDS, 

and then selects the “Empirical” distribution type in the distribution widget. The interface will 

then prompt the user for the full path and filename of the empirical data file. The distribution 

widget will show an error if the file does not exist. An example of an empirical data file and its 

file specification in the distribution widget for the variable fraction of skin unclothed are shown 

in Figure 2.6. When this type of distribution is used, each of the values in the file will be 

sampled with equal probability. The user can enter histogram-type data by using multiple copies 

of the measurements in the file. For example, the file shown in Figure 2.6 essentially represents 

a histogram in which 75% of the outcomes are 0.3, 12.5% are 0.2, and 12.5% are 0.4. 

 

1 Distributional parameters do not reflect the effects of truncation. 

Figure 2.5. Example Distribution Widget. 
14

Figure 2.6. Example Empirical Data File and File Specification in the Distribution Widget. 

2.3.5.3 Entering Uncertainty Distributions 

The “Uncertainty” type of distribution is also new in the SHEDS version 4 GUI. This 

distribution type is only valid for uncertainty runs and will not be visible for other types of runs. 

This feature allows the user to define a set, or “cloud” of distributions for a variable, one of 

which is then selected for use (with equal probability) for each uncertainty repetition. See the 

SHEDS Technical Manual for more information about uncertainty runs. 

The uncertainty distributions must be contained within a SAS dataset, one distribution definition 

per row. Thus, it is helpful for the user who utilizes this feature to have some knowledge of how 

to create and edit SAS datasets. Each of the distribution definitions (each row) must contain a 

valid distribution form (Point, Uniform, Normal, Log Normal, Triangle, Exponential, Gamma, 

Binomial, Beta, Weibull, Empirical), and the required parameters as defined in Table 2-2. The 

parameters are given the names V1-V3. Thus for a beta distribution, v1 and v2 (shape1 and 

shape2) must be defined. Optionally, each distribution may contain a maximum and minimum 

(“maxval” and “minval”) values. For “Empirical” distributions, the filename of the empirical 

data file is contained in the “empfile” variable. 

The user creates the uncertainty dataset outside SHEDS, and then selects the “Uncertainty” 

distribution type in the distribution widget. The user then must copy the dataset into the folder 

<SHEDS-Root>\runs\XXXX\input\unc, where XXXX is the run name. Thus the run must 

already be defined. The interface will prompt the user for dataset name. The distribution widget 

will show an error if the dataset does not exist in the UNC directory. An example of a valid 
15

uncertainty distribution dataset and its dataset specification in the distribution widget are shown 

in Figure 2.7. These data are strictly for demonstrations and are not meant to represent the value 

of any real variable. 

Figure 2.7. Example Uncertainty Dataset and File Specification in the Distribution Widget. 
16

3 Installation 

3.1 Requirements 

SHEDS-Residential 4 was developed under SAS version 9.1 on machines running MS Windows 

2003 and XP Professional. 

To install and use SHEDS-Dietary, you will need a computer running 32-bit SAS version 9.1 or 

higher. A version of SHEDS for 64-bit SAS is available upon request. SAS must be installed 

prior to installing SHEDS. Your computer hardware needs to be adequate to run SAS and MS 

Windows. Additionally you should have: 

a 600 MHz processor, 

64 MB of RAM, and 

150 MB of free disk space. 

However, it is recommended that you have: 

a faster processor, 

128 MB or more RAM, and 

more than 250 MB of free disk space. 

The software should run on other systems where SAS is implemented, but this has not been 

tested. 

Each run will consume about 16MB + (0.28*N) MB where N is the number of people simulated 

for 1 year. So a run of 200 people will take up 72 MB of disk space. 

WARNING: It is highly recommended that the user pause or disable any automated antivirus or back-up programs that access the SHEDS installation or data output directories, or 

place these directories in locations that are not virus-checked or backed up. Such programs 

may access SHEDS data files and interfere with model performance, causing unpredictable 

results. 
17

3.2 Installation under MS 

Windows 

Installation has been designed so that 

administrative privileges are not required. 

3.2.1 Starting With a CD 

If you have a CD, do the following: 

1. Insert the CD into your CD reader. 

2. Use Windows Explorer to navigate to the top level files on the CD. 

Double click on the SHEDS_Multimedia_Setup.exe file to initiate the installation. The 

installation may have version numbers after the “Setup”. For instance ...Setup_4.14.exe. 

3.2.2 Starting with a Downloaded File 

You may obtain the setup file via FTP or another electronic means. 

1. Save the attachment to a local or network hard drive. The method you use to do this will 

vary depending on the program you use to obtain the file. 

2. Use the Windows explorer to navigate to the saved file. 

3. Double click on the saved file to start the installation. 

3.2.3 The Standard Installation Process 

Once the installation wizard is initiated, simply follow the instructions. This will install the 

necessary program and data files, create a program group on the Start menu, and create an icon 

on the desktop. The desktop icon will execute the interface within SAS. The program group will 

contain an additional shortcut (menu item) to uninstall the model and program data. 

The screens encountered during install, and an explanation of each, are shown in the following 

figures. For a default install, users should simply continue to click the Next buttons until the final

screen. 

Figure 3.1. Setup Screens: Initial Screen. 

The initial screen informs the user what 

version will be installed. Click the Next button 

to continue 

WARNING: If you wish to save the results 

from model runs, copy the affected results 

files from the installation directories to 

another location before uninstalling or 

reinstalling SHEDS. 
18

Figure 3.2. Setup Screens: Welcome and 

Information Screen. 

This screen provides some information about 

the current state of the program and how to get 

support. 

Figure 3.3. Setup Screens: Installation. 

Directory Screen. 

The user may elect to install the files 

somewhere besides the default location. The 

default location is in the user’s My Documents 

directory. If the user desires, the Browse button 

can be clicked and a dialog allowing the choice 

of an alternate location will come up. The main 

reason one might want to install somewhere 

else is that the user generated simulation results 

are large and by default are stored under the 

install directory. Note that the user may redirect

the output to another location. 
19

Figure 3.4. Setup Screens: Shortcut Folder 

Name. 

Figure 3.4 shows the final window before 

install begins. Allows the user to set the name 

of the program group in the Start Menu. The 

user should not need to change this. 

Figure 3.5. Setup Screens: Confirmation 

Screen. 

The user has the chance to review installation 

specifications on this screen before the 

installation begins. 
20

Figure 3.6. Setup Screens: Completion 

Confirmation. 

After the files have been extracted and placed in 

the specified install directory, and the desktop 

icon has been placed, the final screen will 

indicate that the installation is complete. 

3.2.4 Starting the Model Interface 

The installation will place an icon on your desktop. The icon should appear as 

the standard SAS icon, with the label “SHEDS Multimedia 4”. However, this 

varies depending on the version of SAS the user is running. It will typically 

include an inverted triangle as part of the icon. Double click on the icon (figure 

at right) to start SAS and the main screen of the SHEDS Interface. 

3.2.5 Removing SHEDS-Residential 

If SHEDS was installed using the installation wizard, the user can uninstall it in 

a manner similar to other Windows programs. Removal of the program will remove all of the 

user’s simulation output files unless these were saved elsewhere. To start the removal 

process, click on the “Uninstall SHEDS Multimedia” choice in the SHEDS Multimedia group of 

the Programs menu. 

Figure 3.7. 

SHEDS 

Multimedia 

Desktop Icon.
21

4 The SAS User Interface 

Most of the SAS user interface provides detailed fine-tuning capabilities that are usually not 

necessary for typical model use. The average user may still find a brief review of this section 

useful. If the user is unfamiliar with SAS and wishes to explore raw datasets used by the model, 

then it is recommended the user read this section more carefully. 

4.1 The SAS Screen 

Assuming one uses the link in the MS Windows Programs menu or the screen icon to start the 

model, the main GUI screen will start inside the main SAS window (Figure 4.1). By default, the 

SAS log window will not open when the program starts, but can be opened by selecting View-> 

Log on the SAS toolbar. 

The SAS window is split into a number of distinct areas. The main area for viewing documents, 

forms, data sets, and graphs is in the middle. This area may have multiple windows active at one 

time. The user may activate a particular window by clicking on the title of the window. The bar 

immediately below this area contains one button for each window in the main area. The buttons 

indicate which window is active, and allow one to activate a different window. In Figure 4.1, the 

main SHEDS screen is active as can be seen by the colored title bar and the depressed appearing 

button. Note that since the main SHEDS screen does not have a title on the title bar, its button is 

unlabeled. As the SHEDS GUI and model are run, informational and error messages will be 

displayed in the log window. The pull-down menus are on the top of the screen, just under the 

title. The toolbar is below this. At the very bottom of the SAS window is a status bar, which will 

contain help text for many interface features as the user moves the mouse over the GUI. 

Additional SAS windows can be opened using the SAS View menu (Figure 4.2). The Graph 

window displays all graphical output generated. The interface uses a separate output window for 

this purpose so the Graph window will generally not be needed. It should also be noted, that 

since the model interface overwrites images of the same type, SAS’s graph window may appear 

unreliable. 

The SAS output window is where any tabular output generated is written by default. Generally, 

the model does not provide this type of output. 

The Results window (Figure 4.3) provides a list of tabular and graphical results generated and 

printed to the graph and output windows. It is generally locked on the left side of the SAS 

window. If additional windows are locked in this area, they are accessed with tabs that appear 

below. The Results window may be used to navigate among the different outputs. However, it 

will not open the output or graph windows; this must be done manually. 

The Explorer window (Figure 4.4) is used to navigate through SAS libraries and files, data sets, 

forms, and programs. It can be used to access the raw files used as input or output to the model. 
22

This screen may float in SAS’s main area or it may be locked on the left side of the SAS window 

and be accessed via a tab on the bottom of this area. This screen may be toggled between tree 

mode (shown) and a single pane, similar to MS Windows Explorer. 

Main Area

Status Bar

Figure 4.1. The Main Model GUI Interface Screen in the SAS Window on Startup. 
23

 

Figure 4.2. The SAS Menu Bar and the View Menu. 

Figure 4.3. The SAS Results 

Window. 

Figure 4.4. The SAS Explorer Window. 
24

5 SHEDS-Residential: The Graphical User 

Interface

5.1 SHEDS Mode 

When SHEDS-Residential is started, the first screen the user will encounter is a Disclaimer 

screen that provides some general information about SHEDS and indicates how to receive 

support. After this screen, the user will encounter an initialization screen that asks the user 

whether they want to run 

SHEDS in Aggregate or 

Cumulative Mode (Figure 5.1). 

If only single-chemical runs are 

going to be performed, the user 

may want to use Aggregate 

Mode, as some screens will be 

bypassed in this mode. 

However, single chemical runs 

can also be created in 

Cumulative mode, but the user 

may have to pass through a 

number of screens that are 

bypassed in Aggregate mode. 

Multi-chemical runs can only be 

created in Cumulative mode, and 

any defined multi-chemical runs 

should not be examined in 

Aggregate mode, as the behavior 

or the interface will be 

unpredictable. However, single 

chemical runs that are created in 

Aggregate mode can later be viewed and edited in Cumulative mode, for example, should the 

user want to add chemicals to an existing run. 

5.2 SHEDS-Residential Main Interface Screen 

After the SHEDS-Mode screen is completed, the main screen will be displayed (Figure 5.2). This 

is the main interface window that you will be returned to after completing each main step. It 

contains the following buttons. 

Figure 5.1. The SHEDS Mode Screen 
25

Specify Run Name and Files: Choose or define a new run name, identify existing input files. 

Specify Population and Sampling: Define basic information for the run: number of people 

sampled, type of run (variability, sensitivity, or uncertainty), ages of interest. Subset the CHAD 

database. 

Specify Simulation Information: Define the length of simulations, source-to-concentration 

approach, and a number of other global simulation variables. 

 

Specify Chemicals: Specify the chemicals to be included in the run and their general properties. 

Specify Application Scenarios: Specify the application scenarios to be used in the run. Define 

the dates and times of applications, reentry times, and relationships between application dates. 

 Specify Concentration-Related Inputs:

Specify decay and dispersion 

inputs, or interval distributions, or 

time-series data. 

Specify General Exposure and Dose 

Factors: Specify all other inputs 

including transfer variables, input 

variable correlations, etc.

Run Simulation: Run the current 

simulation.

Run SHEDS-Dietary Module. This is a 

non-functional placeholder button. 

In the future, this interface may be 

linked with the SHEDS-Dietary 

model.

View Results: View results from previous 

runs. 

Help: Bring up the contents for the help 

screens.

About: Bring up the help screen describing this version of the model (to be implemented).

Figure 5.2. SHEDS-Residential Main Screen. 
26

Exit: Close the SHEDS user interface. 

These buttons allow the user to move through the proper sequence of steps to conduct a new 

model run, or to view results and manage files from previous SHEDS simulations. Initially only 

one button will be enabled (Specify Run Name and Files). Buttons that are not enabled are 

displayed with a gray tint to the font. The initially enabled buttons are Specify Run Name and 

Files and Exit. 

Before beginning to specify the inputs for a new simulation run, editing the inputs for an existing 

simulation, or viewing the results of a previous run, the user will need to specify the run name. 

The run name is simply a title for a simulation run that references all input files for and output 

files from a run. 

Clicking on the “Specify Run Name and Files” button will bring up a screen allowing the user to 

enter the run name. After specifying the run name and if necessary, the files (see below), the user 

will be returned to the Main Window. If setting up a new run the Specify Population and 

Sampling button will now be enabled. If viewing the results of a previous run, then the View 

Results button will be enabled. The appropriate buttons will be enabled as the user completes 

each step, and returns to the main menu. 

5.3 Specify Run Name and Files 

The first step in SHEDS-Residential version 4 is to click on the “Specify Run Name and Files” 

button. The run name is like a file folder that keeps together all the information specific to a 

simulation. In technical terms, it relates to a directory where files are stored and a record in a 

database that stores information about a run. 

5.3.1 Specify Run Name Dialog 

The Specify Run Name dialog (Figure 5.3) allows the user to do several things: 

Edit Selected Run: Restore the contents of a previous run for editing. When this simulation is 

run, any results from previous submissions of this run will be overwritten. 

Copy Selected Run To New Run: Use the same inputs from a previous run in a new run and 

allow them to be edited. This avoids erasing the output from the previous run. 

Create a New Run: Enter a new run name and begin defining inputs. 

View Results of Selected Run: Select run so that the user can view its results. Edits of the 

inputs are not allowed and the run cannot be re-submitted. 
27

Delete Selected Run: Delete an existing run. 

The “Specify Run Name” dialog is composed of three main parts: The first is a list box 

containing the names of previously defined simulation runs. The currently selected run name is 

highlighted in this box. Below the list box, the description of the currently selected run name is 

displayed. This provides additional information on the run. The user enters it when the run is 

created. On the right of the dialog are the action buttons. These perform an action, usually on the 

selected run name. As in 

other dialogs the “Help” 

button (when implemented) 

will bring up a help screen 

for this dialog. The Cancel 

button closes the screen 

without selecting a run name. 

To select an existing run 

name simply click on that 

name in the “Select A 

Defined Run” list box. In 

most cases the user will need 

to select a run name before 

clicking on the action button. 

5.3.1.1 Edit Selected Run 

This button allows the user to 

continue editing an existing 

run. The user will be taken 

to the “Specify Files” screen 

(Figure 5.5). After that the user will be returned to the main menu. This feature is useful, for 

example, if one is interrupted in the process of creating a run. The inputs already entered may be 

saved and SHEDS exited. To finish creating the run, one selects the incompletely specified run, 

chooses this “Edit” button, and continues defining the run. This button is also useful in changing 

inputs on a previously completed run, if the user is willing to overwrite the previous inputs and 

the resulting output. When becoming familiar with the model using the Demonstration 

Permethrin Case Study it is recommended that you use the Copy Selected Run to New Run since 

any changes made using the Edit Selected Run button would overwrite the original file. 

5.3.1.2 Copy Selected Run To New Run 

A run name should be selected before clicking on this button. The information for that run will 

be copied. The user will be allowed to define a new run name using the “Enter New Run Name” 

screen (Figure 5.4) and will then be taken to the Specify Files Dialog and allowed to edit 

information there. As distinct from the “Edit Selected Run” button, this button is used to modify 

Figure 5.3. Specify Run Name Screen. 
28

inputs from a previous run, save the changes into a new run name, and still maintain the inputs 

and outputs from the original run. 

5.3.1.3 Create a New Run 

To create a new simulation from 

scratch, click on “Create A New Run”. 

 The “Enter New Run Name” screen 

(Figure 5.4) will appear allowing the 

user to enter the new run name and 

description. After this is completed, the 

“Specify Files” screen will be displayed 

(Figure 5.5). Initially, defaults for all 

values will be used. Note that the 

chemical-specific default input values 

provided for the case study in SHEDSResidential version 4 are for 

Permethrin, and the user must change 

them to fit their own chemical or 

scenario data. Chemical-specific inputs 

not used in the case study are set to a 

point value of zero.

5.3.1.4 View Results of Selected Run 

Clicking this button chooses the 

currently selected run name and returns 

the user to the main menu where the 

“View Results” button will be enabled. 

This will allow the user to view output 

from the selected run. The user will not 

be allowed to view or edit run inputs in 

this model. 

5.3.1.5 Delete Selected Run 

Clicking this button deletes the selected run 

name from the database. After a dialog 

confirming that the user wants to delete the 

run information (Figure 5.6) the user is 

returned to this dialog. 

Figure 5.5. Specify Files Screen.

Figure 5.4. Enter New Run Name screen. 

Figure 5.6. Confirm Delete dialog. 
29

5.3.2 New Run Name Dialog 

The dialog shown in Figure 5.4 allows the user to enter a new run name and a directory path in 

which to store the results. This screen is accessed when the user clicks on either “Create A New 

Run” or “Copy Selected Run To New Run” from the Run Name Dialog. There are three cases for 

the directory path. When copying from another run, this box shows the location of the prior run 

and the user can change this. When creating a new run, this box displays the storage location of 

the last run. If there is no prior run (immediately after the installation), this box displays the 

default run location. 

The default run name is “UntitledN” where N is the next integer after the last stored untitled run. 

 The user may enter any valid Windows file names. After entering the run name, press return and 

then click on the Continue button. If the name is the same as a previously used name an error will 

be displayed and the user will be allowed to enter a new name. Clicking on continue will in 

general take the user to the “Specify Files” Screen

5.3.3 Specify Files Dialog 

When creating, copying, or editing a run, the user will reach this dialog (Figure 5.5). This dialog 

allows the user to verify the main directories and specify alternate dietary inputs. 

The very top of the dialog simply displays the current run name and run directory. The run 

directory should be similar to the run name, but altered so that it is a valid directory name. The 

input and output files from the simulation run will be stored in this directory. The default data 

directory is where the basic model input data is stored. 

The run description will be displayed and may be edited in the next box down. 

The “Cancel” button will leave the dialog without saving any changes. The user will return to the 

Specify Run Name Dialog. The “Save” button will save any changes, and return the user to the 

main menu. 

When the Specify Files dialog is initialized, the SAS libraries are also set up for the simulation 

run or simulation results. If setup was for some reason not carried out correctly upon installation, 

various errors may occur at this point. In this case, reinstallation is recommended.
30

5.4 Specify Population and Sampling 

Clicking on this button of the Main Window displays the related screen (Figure 5.7). The run 

type is selected via the Sampling Method selection box. Five different types of runs are available 

through the interface: variability runs, uncertainty runs, and three types of sensitivity analysis 

runs: percentile scaling, Sobol’s method, and input-output correlation. In practice, the 

uncertainty and sensitivity analysis runs make use of multiple repetitions of variability runs; 

therefore, the variability results are produced for all run types. When “Uncertainty and 

Variability” is selected as the run type, a box appears (Figure 5.8) that allows the user to specify 

the number of uncertainty repetitions that are going to be performed. When either “Percentile 

Scaling” or “Sobol’s Method” is selected, an additional button (Figure 5.9) appears that takes the 

user to a new screen where settings specific to the selected method are entered (see next 

sections). The input/output correlation method requires no additional input; see the Technical 

Manual for details of this type of sensitivity analysis. 

The user may also enter a random number seed 

for the run. This seed initializes the random 

number stream used for all random sampling 

performed by the model. By setting this value 

to a positive integer, the user can repeat 

simulation runs. If the seed is set to 0, SAS 

chooses a random number seed from the 

system clock. This seed is saved; when the 

user reopens a run has already been run, the 

seed value used will be written in the text box. 

 If the user wishes to repeat the run with new 

simulated persons, they must reset this seed to 

a different integer or to 0. 

In the “Population: Age Groups and Sample 

Size” box, the user selects gender(s) and age(s) 

of interest in the simulation (all ages, or some 

subset of those ages are available for 

selection). The “Population Size” option 

allows the user to specify the sample size for 

the 1-stage simulation. SHEDS contains two 

different sets of age group definitions (“EPA 

Age Groups” and “Optional Group 

Definitions”); the user can decide which to use. 

 

Figure 5.7. Specify Population and 

Sampling Screen. 
31

Clicking on either “Clear Males” or 

“Clear Females” allows the user to 

specify a single gender simulation. 

Once cleared, cohorts can be added 

back by clicking on them. 

The time taken to carry out the 

simulation increases linearly with the 

Size of Population and Number of 

Populations selected. There is a 

lesser increase in run time if longer 

time-periods are chosen. Depending 

on the computer hardware, a run of 

1000 persons will typically take 

about an hour to complete. 

SHEDS-Residential makes use of 

EPA’s Consolidated Human Activity 

Database (CHAD). CHAD contains 

human activity diaries from a number of different studies (see the Technical Manual for further 

information). The user can also choose to select a subset of these studies for use in a run. When 

the user clicks the “Subset the CHAD Database” button, the screen seen in Figure 5.10 appears. 

By default, all the studies in CHAD are selected. The user can click on any study to unselect in 

and remove it from the run. Note that if the user chooses to include a small number of studies, 

the run may fail due to inadequate numbers of diaries being available for certain age groups, day 

types etc. If this happens, an error will be written to the SAS log when the run is initiated. 

Figure 5.8. The Sampling Method selection box for 

an uncertainty run.

Figure 5.9. The Sampling Method selection box for 

a Percentile Scaling or Sobol sensitivity run.
32

Figure 5.10. Subset CHAD Screen.

5.4.1 Specify Sensitivity Settings 

For Percentile Scaling and Sobol’s Method sensitivity runs, some additional input is required by 

the user. This information is entered on one of two screens that appear when the “Sensitivity 

Settings” button (Figure 5.9) is clicked. 

5.4.1.1 Percentile Scaling Run Settings 

When performing a Percentile Scaling run, the screen shown in Figure 5.11 appears when 

“Sensitivity Settings” is clicked. This screen contains a list of all the variables in the run whose 

sensitivity can be examined. The user selects the variables to analyze by highlighting them in the 

“Variables Remaining” list and moving them to the “Variables Selected for Sensitivity Analysis” 

list via the arrow buttons. 
33

Figure 5.11. Sensitivity Settings: Percentile Scaling Method.

Note that selecting more variables for analysis results in a longer SHEDS run. The total number 

SHEDS variability repetitions that will be performed in a Percentile Scaling run is 2N+1, where 

N is the number of variables selected. The percentile method performs a baseline run plus two 

runs for each variable analyzed: one with the variable set to a high percentile and the other with it 

set to a low percentile. See the Technical Manual for more information about sensitivity runs. 

5.4.1.2 Sobol’s Method Run Settings 

When performing a Sobol’s Method run, the screen shown in Figure 5.12 appears when 

“Sensitivity Settings” is clicked. This screen contains a list of all the variables in the run whose 

sensitivity can be examined. The purpose of this screen is then to take these variables and sort 

them into groups (“Sobol Groups”). The model then assesses the influence of each group on the 

model output. The user selects the variables to assign to each group by highlighting a group, then 

highlighting one or more variables in the “Variables Remaining” list and moving them to the 

“Variables in this Sobol Group” list via the arrow buttons. All of the variables must be assigned 

to a group; the user will get an error if the “Continue” button is clicked while variables remain. 

Groups can consist of a single variable if the user wishes to ascertain the influence of that 

variable alone. However, the number of runs being performed is dependent on the number of 

Sobol Groups, so caution is needed when defining a large number of groups. The total number 

SHEDS variability repetitions that will be performed in a Sobol Analysis run is 2N+2, where N is 

the number of Sobol groups defined. Thus performing runs with a large number of groups may 

be time-prohibitive. It is recommended that Sobol’s analysis be used in a hierarchical fashion. 

First, an analysis is performed with a few Sobol groups, which perhaps could eliminate a large 
34

number of variables as being non-influential, and identify a subset of important variables. Then 

further runs could be performed that examine the variables contained in the influential groups 

more completely. See the SHEDS Technical Manual for more information about Sobol’s 

Analysis. 

 

Figure 5.12. Sensitivity Settings: Sobol’s Method.

5.5 Specify Simulation Information 

This screen (Figure 5.13) allows the user to select a number of options that determine overall 

simulation variables; each is discussed shortly. Clicking the “Save” button commits any changes. 

The “Cancel” button prevents changes from being saved. 
35

5.5.1 Simulation Length 

The box labeled “SIMULATION START AND LENGTH” allows the user to specify the 

beginning date (month, day, and year) and the number of days the simulation will track each 

individual. One common choice of simulation period is to start on January 1st and continue for 1 

year (365 or 366 days). However, the model allows a great deal of flexibility. A simulation may 

begin on any day of the year and can be as short as one day or as long as desired and may cross 

calendar years. However, caution should be exercised when specifying very long periods as they 

take longer to run and the model does not alter many personal variable settings (including age) 

over the simulation period. 

5.5.2 Source-To-Concentration Approach and Application Dates 

There are three options to generate residues and concentrations for scenario-relevant media: 

• Decay/Dispersion Model: Specific applications leave a residue on surfaces, in the soil, 

and in the air. These residues decay with time and are moved to untreated areas. 

• Interval Distributions: Specific applications leave residues on various media. The 

concentrations on the media are determined by distributions that change with the time 

since the application. 

• User-Specified Concentration Time Series: The user supplies a time series of 

concentrations for each medium. 

The Decay/Dispersion model is a built-in source-to-concentration model that requires the user (in 

subsequent screens) to enter application and decay rates, and the ratio of residue concentrations 

in untreated to treated media for indoor applications. Additionally, background distributions can 

be defined for the various media when Decay/Dispersion is used. 

The Interval Distributions selection will require the user (in subsequent screens) to enter 

distributions of relevant media residues and concentrations for discrete post-application time 

periods (<1 day, 1-7 days, 8-30 days, 31-365 days). 

The User-Specified Concentration Time Series option will require the user (in subsequent 

screens) to enter time series of residues and concentrations for each medium of interest (e.g., 

from a measurement study or outputs from an external source-to-concentration model). 
36

If either Decay/Dispersion or Interval Distributions are chosen, a box will appear (to the right of 

the Source-To-Concentration radio box in Figure 5.13) that allows the user to specify whether the 

application dates will be User-Specified or Model-Determined. Details will be input on 

subsequent screens. For user-specified dates, the user will enter specific day numbers for each 

application type, where day 1 is the first day of the simulation period. Applications will always 

occur on the dates given. For modeled dates, the user will specify probability vectors for month, 

day of week, number of applications, and time of applications. 

5.5.3 Dermal Exposure Method 

For dermal exposure, the user can select the Transfer Coefficient approach or the Transfer 

Efficiency approach. These two methods are described in the SHEDS-Residential version 4 

Technical Manual. Changing this value on a previously defined run will result in the user having 

to visit the Specify General Exposure and Dose Inputs screen to define related variables. 

5.5.4 Diary Assembly Method 

SHEDS-Residential version 4 allows the user to select one of two algorithms for constructing the 

longitudinal human activity diaries for each person upon which the exposure time-series are 

based. The first method (the Eight Diary method), uses repetitions of 8 activity diaries for each 

person (a weekday and weekend diary in each season) to construct the year-long diary. The 

second method selects diaries from the CHAD database based on an algorithm that reproduces 

certain population statistics, diversity (D) and day-to-day autocorrelation (A), for a key diary 

variable relevant to exposure for the pollutant being studied. If this option is selected, the user 

must provide target D and A values for the population, as well the diary variable to be targeted. 

The available key diary variables are as follows: 

• Time Spent Outdoors 

• Time Spent Outdoors at Home 

• Time Spent Outdoors (Not at home) 

• Time Spent in Travel 

• Time Spent in Vehicles 

• Time Spent in Residences 

• Time Spent Indoors (Nonresidential) 

• Time Spent at Work 

• Time Spent at School 

• Time Spent Indoors While Awake 

• Time Spent at Home While Awake 

• Time Spent Outdoors While Awake 

See the SHEDS Technical Manual for more information on the longitudinal diary algorithms and 

parameters. 
37

5.5.5 Simulate Product Handlers 

SHEDS-Residential version 4 allows the user to model persons who specifically handle the 

chemical of interest in their own home (not professional applicators). If this options is selected, 

the user will be required to enter additional information later in the interface (see Section 5.8.3), 

that determines how many of the simulated profiles are handlers and the chemical concentrations 

that they experience. If handlers are to be modeled, the user must specify a minimum age for 

handlers; no profiles younger than this minimum age will be identified as chemical handlers. 

5.5.6 Export Data For PBPK Model 

SHEDS-Residential version 4 allows the user to export SHEDS exposure time series so that the 

files can be read by an external PBPK model. When enabled, this option produces one extra 

SAS data set and two text files in the run output directory, in addition to the usual output files. 

5.5.7 Keep Intermediate Variables 

If the user checks the “Keep Intermediate Variables” box, SHEDS will retain variables used in 

intermediate calculations for simulated individuals. This is useful to check the internal workings 

of the model. 

5.5.8 Save the Log File 

To save the log that is generated during the simulation run, the user can click on “Write to Log 

File” which saves the log to a permanent file outside SAS, thus ensuring the log is saved even if 

SAS crashes during the run. With this option the standard SAS log screen is not used, so the user 

cannot track the progress of the run during execution. 

If the log file is not saved, a line of output is written to the log window before each individual is 

simulated, and this is the best way to tell how the simulation is proceeding. If the log is written 

to a permanent file, the user can open the file with a text editor from time to time to check the 

status of the run. The name of the log file is fixed. It is stored in the output library. 
38

Note: To utilize the 

co-occurrence 

option, the user must 

select ModelDetermined Dates on 

this screen. The user 

must also select 

Specify Parameters 

before clicking the 

Specify Inputs 

button on the 

Specify Application 

Scenario Details 

screen for each 

scenario for which 

co-occurrence inputs 

are to be specified. 

Application cooccurrence is 

explained in section 

5.7.6. 

Figure 5.13. Specify Simulation Information Screen.
39

5.6 Specify Chemicals 

SHEDS-Residential version 4 is a multichemical model. Thus, the user has the opportunity to 

select or define which chemical(s) of interest are to be modeled in a specific SHEDS Run. This 

information is specified in the Specify Chemicals screen (Figure 5.14). 

Figure 5.14. Specify Chemicals Screen. 

Currently, SHEDS contains default chemical-specific information for Permethrin and two 

additional pyrethroid chemicals (here, generically called Pyrethroid1 and Pyrethroid2). Note that 

these chemicals are initialized with the same data as for Permethrin; the user may alter the values 

as they step through the interface. In the future, SHEDS may contain default data for other 

chemical classes such as organophosphates, carbamates, or metals. 

The user selects the chemicals to include in the run by clicking on the name of the chemical in 

the Select Chemicals list. Highlighted chemicals are selected for simulation, and the user will be 

asked to enter information for each of the selected chemicals on future screens. 

In Aggregate Mode (see Section 5.1) runs, the user can select just a single chemical at this point. 

 However, it is a valid option for the user to select a single chemical in Multichemical 

(Cumulative) mode. SHEDS will operate identically as in Aggregate Mode, with the exception 

that the user will have to visit a few screens that may be bypassed in Aggregate mode (such as 

assigning chemicals to scenarios; see Section 5.7.3). 
40

5.6.1 Add a User-Defined Chemical 

The user may opt to define their own chemical(s) completely from scratch, rather than base their 

simulation on the defined SHEDS default data for permethrin. In this case, the user clicks the 

“Add a User-Defined Chemical” button on the Specify Chemicals Screen, upon which an 

additional widget (Figure 5.15) appears. The user then 

enters a name for the new chemical, and clicks “OK”. The 

new chemical will be added to the Select Chemicals list, 

where the user can then select it to be included in the 

current run. All chemical-specific input data for userdefined chemicals will be initially populated with point 

distributions having a value of zero, rather than with the 

default Permethrin data. Thus the user must carefully 

update any input distributions for their new chemical to 

reflect their own data. 

5.6.2 Specify Chemical Information 

Once the user completes the Specify Chemicals screen, they will proceed to the Specify 

Chemical Information screen (Figure 5.16). On this screen, the user enters the following 

information: 

• Metabolite name. The name of the bioactive metabolite of the chemical being studied. 

• Chemical/Metabolite mass ratio. The ratio of the chemical mass to that of its bioactive 

metabolite. 

• NOAELs. The user must enter the No Adverse Effect Levels (NOAELs) for dermal, 

ingestion, and inhalation exposures. 

The user must complete this information for each of the chemicals in the run. All the chemicals 

in the run are visible in the Chemicals list box; the user clicks on each chemical in turn and 

enters the data. The user can not move onto a different chemical if there is an error in the data 

for the current chemical; in this case the error will be highlighted in yellow and the user must 

correct it before another chemical can be selected. 

Figure 5.15. Enter Chemical 

Name for User-Defined 

Chemical. 
41

Figure 5.16. Specify Chemical Information Screen. 

5.7 Specify Application Scenarios Simulated 

Clicking on “Specify Application Scenarios” on the main screen begins a series of screens 

through which the user must navigate in their entirety before returning to the main screen. The 

exact screens vary depending on options selected. See Figure 2.1 for an overview of the screens 

in this section. The following screens may be visited: 

The first screen is used to identify the scenarios to be simulated. 

Specify Application Scenarios - Select Scenarios (Figure 5.17) 

The second screen is used to specify details for each scenario and is used to get to the 

Application Dates and Co-Occurrence screens for each scenario. 

Specify Application Scenario Details (Figure 5.19)

These screens are visited once for each scenario, after which the user is returned to the Specify 

Exposure Scenario Details screen: 

Specify Chemicals in Scenario. (Figure 5.20). This screen only available when SHEDS 

in being run in cumulative mode. 
42

Specify Application Dates (Figure 5.21 and Figure 5.22. The version visited depends on 

whether user-specified or model-determined application dates are being used.) 

Specify Co-Occurrence (Figure 5.23. Only available when model-determined

application dates are being used.) 

Clicking the Continue button on the Specify Application Scenario Details screen takes the user to 

these screens. They are visited once for each simulation. 

Specify Application Times (Figure 5.24. Only visited when model-determined 

application dates are used.) 

Specify Fraction of House Treated for Indoor Scenarios (Figure 5.25)

Specify Re-entry Times (Figure 5.26) 

5.7.1 Specify Application Scenarios 

The specific scenarios or applications to be simulated are specified on this screen (Figure 5.17). 

In the later screens, additional information will need to be entered for each scenario defining the 

probability, dates, and co-occurrence of applications, fraction of indoor area treated, and re-entry 

times. The exact screens visited will depend on options chosen by the user. If the user is 

becoming familiar with the interface, it is recommended that only one or two scenarios be 

chosen. 

This screen will not be shown (the button on the main screen will be grayed out) if the UserSpecified Time Series was chosen as the source-to-concentration method. If the user is 

simulating a multimedia measurements study then specific applications are not specified. 

Each scenario chosen is assigned a priority. The priority becomes important when application cooccurrence is of interest. That is, when one is interested in using the dates of one scenarios’ 

applications to influence the dates of applications in other scenarios. The dates of an application 

can only be influenced by applications occurring in scenarios given a higher priority. 

There are nine pre-defined application scenarios available in SHEDS. These appear in the 

Scenario Library. The available scenarios and their locations are as follows: 

• Lawn (Granular-Push Spreader). Outdoor, Lawn. 

• Lawn (Liquid-Hand Wand). Outdoor, Lawn. 

• Vegetable Garden (Dust, Powder). Outdoor, Garden. 

• Indoor Crack and Crevice (Aerosol). Indoor. 

• Indoor Crack and Crevice (Liquid). Indoor. 
43

• Indoor Flying Insect Killer (Aerosol). Indoor. 

• Indoor Fogger (Broadcast). Indoor. 

• Pet Treatment (Spot-On). Pet. 

• Pet Treatment (Liquid). Pet. 

The location of the scenario determines the exposure equations that are used, and thus the 

appearance of future screens and the information the user must supply for each scenario. (See the 

SHEDS Technical Manual for details of the exposure calculations). In addition to these built-in 

scenarios, the users can also add their own scenarios to the run (see next section). 

Clicking on an application in the Scenario Library list box copies it to the list of “Selected 

Scenarios” in the middle of the screen. The scenarios are prioritized from top (1st) to bottom in 

the Selected Scenarios list. Click on a scenario description to select it. Use the up and down 

arrows on the right to change the priority of the selected scenario. Clicking on the “Delete 

Selection” button will delete the currently selected scenario from the Selected Scenarios list. 

When all desired scenarios are selected and prioritized, clicking on the Continue button will take 

the user to the remaining screens. 

Figure 5.17. Specify Application Scenarios – Select Scenarios Screen. 
44

5.7.1.1 Create User-Defined Scenario 

SHEDS version 4 allows the 

users the option of adding their 

own custom scenarios to a run. 

This is accomplished by 

clicking on the “Create UserDefined Scenario” button on 

the Application Scenarios 

screen. This brings up the Add 

New Scenario screen (Figure 

5.18). The user gives their 

scenario a name and a location, 

and clicks Add Scenario. The 

name given to the scenario will 

identify it on future screens. 

The location will determine the 

exposure equations that will be 

used for the scenario, and thus 

the appearance of future screens 

related to the scenario. The 

new scenario will be added to 

the Scenario Library on the previous screen, and the user can then add it to their run. 

5.7.2 Specify Exposure Scenario Details 

Once all application scenarios for a run have been selected, the user proceeds to the Specify 

Exposure Scenario Details screen (Figure 5.19) by clicking the “Continue” button on the 

previous screen. The list box on the left of this screen, labeled “Scenario”, displays the scenarios 

chosen by the user in the previous screen. Clicking on one of these entries selects that scenario as 

the current one (and highlights it). Once selected, the user needs to do the following for each 

scenario: 

1. Specify or edit the application probability. 

2. Specify whether co-occurrence will influence this scenario’s dates (not active for the 

scenario that is first in the priority list). 

3. Click the Specify Inputs button to proceed to screens to enter application dates, times, and 

co-occurrence. 

Figure 5.18. Add New Scenario Screen. 
45

Only when these items have been completed for each scenario will the user be permitted to 

continue. If the existing values for probability and co-occurrence are acceptable, the user is not 

required to edit these values. 

When using model-determined dates, the scenario’s probability and co-occurrence status are 

displayed. The Application Probability is the probability that this application will be used by an 

individual that meets any requirement for usage (e.g., the person must have a garden for a garden 

application to occur). If user-specified dates are being used, this information is not required, 

because in that case the user directly specifies the dates of application for each scenario, and this 

presupposes that the simulated population is restricted to those who can apply the specified 

scenarios. 

When simulating product handlers, a Probability of Being a Handler entry box is visible. The 

user enters the probability that each profile meeting the age requirement is a handler. For 

example, if the user has previously specified that the minimum age for handlers is 16 years, this 

probability determines how many of the simulated profiles age 16 or greater are handlers. If 

handlers are not included in the run (see Section 5.5.5) then this entry box will not be present. 

Even when model-determined dates are being used, the “Specify Co-Occurrence” radio box will 

be grayed out for the application with the highest priority since no other scenarios are allowed to 

influence it. If co-occurrence is active, the user may select either No Co-occurrence or Specify 

Parameters in the “Scenario Co-Occurrence” radio box. If Specify Parameters is selected, then 

the application dates of other scenarios will be allowed to influence the application dates of this 

scenario. Selecting this here will cause the “Specify Co-Occurrence” screen to be displayed at the 

appropriate time. 

Once the application, handler, and co-occurrence information is entered for a particular scenario, 

the user may click on the “Specify Inputs” button to proceed to the Specify Chemicals, Specify 

Application Dates and Specify Co-Occurrence screens for that scenario (see next sections). After 

completing the information on these screens the user will be returned to this screen to work on 

the remaining scenarios. 

Scenarios that have been completed are shown in the list box on the right. The user will not be 

allowed to continue (click on the Continue button) until the application date and co-occurrence 

information has been filled out for all selected scenarios. Clicking on the Continue button will 

take the user to the Specify Re-entry Times and possibly the Specify Application Times screens. 
46

Figure 5.19. Specify Application Scenario Details Screen. 

5.7.3 Specify Chemicals in Scenario 

In SHEDS, not all chemicals in a run need be present in all scenarios. In this screen (Figure 

5.20) the user specifies which of the chemicals included in the simulation are present in the 

current scenario. At least one chemical must be present in the scenario, (otherwise, the scenario 

should not be included in the run since it has no influence on exposure). If SHEDS is being run 

in Aggregate mode, this screen will not appear, as it will be assumed that the single chemical 

being studied is present in all scenarios. If a single-chemical run is being performed in 

Cumulative mode, the user will visit this screen but only one chemical will be available for 

selection. 

The user selects the chemicals for the current scenario (the name of which will be included on the 

third header bar) by simply clicking in the Chemicals selection box. The user can remove a 

previously selected chemical via the Delete Selection button. 
47

Figure 5.20. Specify Chemicals in Scenario Screen. 

5.7.4 Specify Application Dates: Model-Determined 

If model-determined application dates are being used, the Specify Application Dates screen 

appears as in Figure 5.21. Model-determined dates are determined stochastically during the 

simulation. The dates will typically vary for each individual simulated. The user enters the 

blackout period, the probability vectors for month, day of week, and number of applications. 

These are used together to determine randomly the application date or dates for each person. 

During a simulation the actual dates chosen may be influenced by other scenarios if cooccurrence was specified. 
48

Taken together, the 

probabilities define the 

likelihood of an application 

occurring on each day of the 

year. For multiple applications 

the blackout period comes into 

play. The blackout days 

indicate how many days must 

pass before an additional 

similar application is allowed. 

The probabilities for each 

vector (weekday, monthly, and 

number of applications) must 

total 1.0. The user can enter 

probabilities in the first boxes 

of each probability vector. The 

last box of the vector, with a 

darker border, will always 

contain the remainder and 

cannot be edited by the user. 

Additional information about 

entering probability vectors is 

given in the section “Entering 

Probability Vectors” on page 9. 

Figure 5.21. Specify Application Dates Screen for ModelDetermined Application Dates. 
49

5.7.5 Specify Application Dates: User Specified 

This screen 

(Figure 5.22) is 

used to enter 

application dates 

when the “userspecified dates” 

option is selected 

(see Section 

5.5.2). These 

dates are 

specified by day 

number (with 1 

being the first day 

of the simulation 

period). There is 

no probability 

associated with 

these application 

dates, as an 

application will be made on each of these dates for all persons in the run. In addition to the days 

of application, the user should select the time. All applications in a scenario will be made at the 

same time of day. 

5.7.6 Specify Co-Occurrence 

This screen (Figure 5.23) is used to specify how the application dates of other scenarios affect the 

application dates of this scenario. Scenarios must have 

been specified as being of a higher priority in the Specify 

Exposure Scenarios screen to affect a scenario. Only 

those scenarios of a higher priority are listed in 

“Application Types of Influence”. For purposes of 

discussion let us call the scenario we are working with 

the “current” scenario, and let us call applications from 

scenarios with higher priority “previous” applications. In 

the model code, the dates of the previous applications 

will be determined first. Here "previous" refers to the 

order in which the application dates are determined; these do not necessarily occur earlier in the 

simulation. 

Figure 5.22. Specify Application Dates: User Specifed Screen. 

Note: Co-occurrence can only be 

selected in SHEDS if the chemical 

application dates are model-determined. 

If user-specified chemical application 

dates are selected in the Simulation 

Information Screen, then the cooccurrence will be disabled. 
50

The probability of an application from the current scenario occurring on any day of the year is 

determined based on the probability vectors entered earlier for month and day of week. When 

working on the current scenario, the application dates for the higher priority scenarios will 

already have been determined. The probabilities for the current scenario are altered (multiplied) 

by the influence factor for all days within the influence width of previous applications. This 

obviously has no effect for those days whose probability is already 0. The influence factor, also 

called the co-occurrence probability is discussed and illustrated in the “Application Dates and 

Co-occurrence” section of the Technical Manual. 

If the influence factor exceeds one, then the likelihood of the current scenario happening near in 

time to a previous scenario is increased. If the influence factor is less than one, the likelihood is

decreased. An influence factor of zero means that a ‘blackout window’ is created around each of 

the dates for the previous scenarios, so that the current scenario cannot occur on those dates. The 

two scenarios become mutually exclusive for that period of time around an application. 

The user must choose an effective combination to continue. That is, at least one application type 

must be highlighted and the influence factor must be different from 1. If the user wants to turn 

off co-occurrence for this scenario, then enter an effective combination and return to the Specify 

Scenario Details screen. On that screen click the No Co-Occurrence choice for this scenario. This 

will turn off co-occurrence.

Figure 5.23. Specify Co-Occurrence Screen. 
51

5.7.7 Specify Application Times 

When model-determined dates are specified, the user will also need to specify probability vectors 

for the application times. This screen (Figure 5.24) allows the user to enter one probability vector 

for all applications occurring inside, one probability vector for all applications occurring 

outdoors, and one for all pet applications. If the current run does not contain scenarios in one of 

these locations (indoors, outdoors, or pet), then the corresponding vector will not be visible. For 

a fixed application time for each simulated individual simply enter a probability of 1 in the 

appropriate box. For general information on entering data in probability vectors see the section 

“Entering Probability Vectors” on page 9. 

Figure 5.24. Specify Application Times Screen. 
52

5.7.8 Specify Fraction of Area Treated 

For indoor scenarios, SHEDS requires the user to enter the fraction of the house being treated 

(Figure 5.25). See the Technical Manual for how this information is used in the exposure 

calculation. The indoor scenarios included in the current run will be listed in the list box on the 

left side of the screen; the user selects each of these in turn and enters the distribution for the 

variable. For general information on entering data in distributions see Section 2.3.5. 

Figure 5.25. Specify Fraction of Area Treated Screen. 

5.7.9 Specify Re-entry Times 

Simulated individuals may be restricted from entering treated areas for a specified number of 

hours. This restriction is split into reentry times for indoor areas and outdoor areas, and a ban 

time for contact with pet. If scenarios for any of these locations are not present in the current 

simulation, the distributions for the location will not be present (for example, if there are no pet 

scenarios in the run, the ban time on contact with pet distribution will not be visible.) Within 

each area the probability of re-entry is the same for all scenarios affecting that area. The 

probabilities are entered on the Specify Re-entry Times screen (Figure 5.26). For general 

information on entering data in distributions see Section 2.3.5. 
53

Figure 5.26. Specify Re-entry Times Screen 

5.8 Specify Concentration-Related Inputs 

Clicking on “Specify Concentration-Related Inputs” from the main screen begins a series of 

screens through which the user must navigate in their entirety. The exact screens vary depending 

on the source-to-concentration options selected earlier. Since these screens may have to be 

revisited for each scenario, the scenario being edited is always displayed in the third (blue) title at 

the top of the screen. These screens are also chemical-dependent, so a chemical selection widget 

is also present on each screen. 
54

 

WARNING: Different surface residue collection devices are available (e.g., aluminum 

plates, rollers, sleds, hand presses, hand wipes); some collect dislodgeable residues and some 

collect total residues. These methods, as well as current methods for obtaining dermal 

transfer efficiencies and dermal transfer coefficients, have inherent uncertainties. Thus, it is 

important to consider matching the correct type of surface loading with the corresponding 

transfer factor (i.e., transfer efficiency or transfer coefficient) when developing inputs for 

modeling dermal exposure. 

Please see the technical manual (section on Dermal Exposure to Surface Residues) for a 

discussion of entering compatible concentrations and transfer factors (e.g., to prevent double 

counting of residue transfer from surfaces to skin). 

The following screens will be visited once for each scenario selected, depending on the overall 

method used. The exception is the Background screen which is only visited once. 

Decay and Dispersion: Specify Decay and Dispersion Distributions (Figure 5.27) 

 Handler Distributions (if needed) (Figure 5.29) 

 Background Concentration Distributions(Figure 5.30)

Intervals: Specify Interval Concentration Distributions (Figure 5.28) 

 Handler Distributions (if needed) (Figure 5.29) 

 Background Concentration Distributions (Figure 5.30) 

The Time-Series option only requires a single input in this section: 

Time series: Specify Time Series Input (Figure 5.31) 

5.8.1 Specify Decay and Dispersion Distributions 

Use of the decay and dispersion method requires that a number of distributions be defined for 

each scenario. These distributions define the initial media concentrations and the decay rate of 

the chemical for the current scenario. Additionally, for indoor scenarios the rate of dispersion to 

the untreated part of the house must be calculated. To do this, SHEDS requires as input a 

distribution for the untreated to treated area concentration ratios. (See the Technical Manual for 

more details.) If the user chooses to ignore dispersion into the untreated area, then this ratio 

should be set to a point value of zero. 

The following are the required distributions for each type of scenario: 
55

• Indoor Scenarios 

o Concentration in indoor air immediately after application 

o Concentration in indoor air 24 hours post-application 

o Initial concentration on carpet 

o Initial concentration on hard floors 

o Initial concentration in dust 

o Chemical decay rate 

o Ratio of treated to untreated indoor room concentrations 

• Lawn Scenarios 

o Initial concentration on the lawn 

o Initial concentration in the lawn soil 

o Chemical decay rate 

• Garden Scenarios 

o Initial concentration on the garden 

o Initial concentration in the garden soil 

o Chemical decay rate 

• Pet Scenarios 

o Initial concentration on the pet 

o Chemical decay rate 

There will be one distribution entry widget for each of these scenarios. All this information must 

be entered for each chemical. The user selects the current chemical from the list on the left of the 

screen. The user will not be able to move to a new chemical if errors are present in the data for 

the current chemical. 

General information on distributions are provided in section “Distributions Supported” on page 

11 and information on entering distributions on this screen are discussed in “Individual 

Distribution Widgets” on page 11. 
56

Figure 5.27. Specify Decay and Dispersion Distributions for an Indoor Scenario. 
57

5.8.2 Specify Interval Distributions 

Interval distributions might be used when measurement studies have determined the actual 

concentrations over time after applications. SHEDS uses four time periods: 

1. The day of application (< 1 day) 

2. The day after application to 7 days after application (1-7 days) 

3. The 8th day after application to the 30th day (8-30 days) 

4. The 31st day after application and the remainder of the simulation period. 

The user must define these four distributions for each medium affected by each scenario for each 

chemical. Once an application is made for a scenario, these distributions will determine the 

concentrations on each medium. When another application is made in the same scenario, the first 

distribution is used once again; there is no persistence of chemical from the previous application. 

The concentrations on a medium from different scenarios are added when determining exposure 

of an individual. It is assumed that background values are included in the distributions; the user 

cannot define background concentrations on media not included in the scenarios. 

As on the previous screens, the third title, in blue, indicates the current scenario. Clicking on a 

medium/chemical combination in the Interval Variable list box selects and highlights that 

variable. The distributions displayed are related to that variable for the current scenario. The user 

is not forced to enter data for each combination. Any distributions not entered by the user will 

retain their previous values whether desirable or not. Once the distributions have been edited as 

desired, the user should click on Continue to go on to the next scenario. If this is the only or last

scenario, then the next screen will be used to define background values. 
58

General information on distributions are provided in section “Distributions Supported” on page 

11 and information on entering distributions on this screen are discussed in “Individual 

Distribution Widgets” on page 11. 

5.8.3 Specify Handler Distributions 

If handlers are being modeled, the following screen (Figure 5.29) appears for each scenario. On 

this screen the user must enter the following distributions: 

• Application Rate of chemical being applied. 

• Unit dermal exposure of the handlers. 

• Unit Inhalation exposure of the handlers. 

See the Technical Manual for details of the handler exposure calculations. 

Figure 5.28. Specify Post-Application Distributions Screen for An Indoor Scenario 
59

5.8.4 Background 

A background screen (Figure 5.30) will be visited for both Decay and Dispersion and Interval 

Distribution options (the only difference will be the title on the middle header bar). On this 

screen the user must enter the background concentrations for outside surfaces. This is the only 

background concentration distribution required by the model. The concentration must be entered 

for each of the chemicals in the via the Chemical selection list box on the left side of the screen. 

The user will not be able to move to a new chemical if there is an error in the data for the current 

chemical. 

Figure 5.29. Specify Handler Distributions Screen 
60

5.8.5 Specify Time Series Inputs 

Time series inputs allow the user to specify the exact concentrations on each medium for specific 

dates. This is a convenient method of using data derived from studies of multiple households. 

Details on the file format required are discussed in the SHEDS Technical Manual. 

The burden is on the user to create the file containing time series for all affected media. The 

interface expects to be given a single SAS dataset which is copied into the input directory for the 

run. The dataset is specified by clicking on Copy Time Series Dataset (Figure 5.31) and then 

using the explorer to identify the dataset. 

When using time series inputs the Specify Application Scenarios button on the main screen is 

grayed out. The model does not simulate specific applications in this case. 

Figure 5.30. Background Screen. 
61

5.9 Specify General Exposure and Dose Factors 

Clicking this button on the main screen begins a sequence of screens allowing the user to enter or 

edit the remaining inputs. These inputs fall into two broad categories: 

1. Individual exposure and dose factor variables, typically defined by a distribution. 

2. Correlation between input variables (optional). 

Each of these categories is discussed in the sections below. 

Initially the user is taken to the Variability Distributions screen (Figure 5.32). From this screen 

the user repeatedly visits the Edit Variability Distributions screen (Figure 5.33). 

If the user desires to define correlated inputs, clicking on Define Correlated Input Variables will 

lead to the following two screens: Select Correlated Variables (Figure 5.37), and Specify 

Variable Correlations (Figure 5.40). The first “Select Correlated Variables” screen is used to 

select which variables are to be correlated; the “Specify” screen is used to specify the correlation 

values defined. 

5.9.1 Variability Distributions 

The variables set using the first two screens in this series are grouped as follows: 

Figure 5.31. Specify Time Series Inputs Screen.
62

• Baths (time between baths). 

• Dose-Related (GI and dermal absorption rate, elimination rate, etc.) 

• Removal-Related (hand washing frequency, removal efficiencies, etc.) 

• Transfer-Related (skin adherence, non-dietary ingestion, etc) 

• Activity-Related (Probabilities related to lawns, gardens, and pets) 

Each variable is defined by a distribution, except for the time between baths, which is a 

probability vector. 

The initial Variability Distributions screen (Figure 5.32) is used as a jump point. The user selects 

a variable group by clicking on the group name in the Variable Groups list box. The group is 

highlighted and the descriptions of each variable in the group are displayed in the center list box. 

Clicking on the Specify Inputs button will take the user to the next screen where individual 

distributions can be edited. After clicking Continue (or “Save” for the Baths screen) , the user 

will be returned to this screen. The variable group just edited will be added to the Groups 

Completed list box if it was not already there. While one or more variable groups remain to be 

edited, the background of the Groups Completed list box will be light blue and both the Define 

Correlated Input Variables and the Continue button will be disabled. When all groups have been 

completed the user may continue contact distribution screens. 

Figure 5.32. Variability Distributions Screen. 
63

If the user returns to the Simulation Information screen and changes options, she will be forced to 

return here and enter values for any variables not previously defined. For example if the 

simulation options are switched to Transfer Coefficients from Transfer Efficiencies, the user will 

need to return here to edit the Transfer-Related group. Only then will the user be able to continue 

and run the simulation. 

Once all groups are completed, the user will be able to define correlated inputs. By default, 

correlated inputs are turned off; no input variables are correlated. To turn correlation on, click on 

the check box labeled Correlate Input Variables. This will enable the Define Correlated input 

Variables button. Click on the button to proceed to the two screens used to select and define 

correlated inputs. After defining correlated inputs, the user will be returned to this screen. If the 

definition of correlated inputs is not completed, input correlation will be turned off when the user 

returns to this screen. 

Only when all variable groups have been completed will the user be allowed to continue. If 

correlation was turned on, the correlated pairs must be defined or correlation must be turned off 

before the user may continue. Once enabled, clicking on the Continue button takes the user to the 

screens used to define contact probabilities. 

5.9.2 Edit Variability Distributions 

The user comes to this screen (Figure 5.33) when the Specify Inputs button is clicked from the 

Variability Distributions Screen. The screen will always have the same basic layout, but the 

specific variables that can be edited will change based on the variable group highlighted when 

the Specify Inputs button was clicked. The second title will always indicate the variable group 

being edited. 

The variable to be edited is chosen in the left hand list box. If the variable has several 

distributions associated with it, for different ages perhaps, then a list of conditions will be listed

on the right (see Figure 5.34). A variable is selected by Clicking on the variable description, or 

the condition if present. When selected, the current distribution parameters for that variable will 

be loaded into the widget. The title of the box surrounding the distribution widget will show the 

actual variable name, a vertical bar, and then the description for that variable. Use of the 

distribution widget is covered on page 12. 

Whenever a valid distribution is loaded or redefined a frequency histogram will be drawn 

showing a representative sample for the distribution as defined. To turn this off, uncheck the 

histogram check box on the right. The mean and standard deviation of the sample will also be 

shown in the box on the right. It should be emphasized that the sample shown is not used in the 

model. The distribution will be sampled during the model run to generate values used in the run. 

Some features, particularly due to truncation, are easier to see if the number of bins are increased 

using the spin box on the right. If the current run is an uncertainty run (see Section 5.4), the 

“Uncertainty” distribution definition may be selected for any variable. (See section 2.3.5.3 for 
64

information on defining uncertainty distributions). When an uncertainty distribution is used, the 

user can view any of the distributions defined on the uncertainty dataset via a new widget labeled 

“Unc Distribution #” that will appear when “Uncertainty” is selected (Figure 5.35). By clicking 

the up and down arrows, the user can view any of the defined distributions. 

The Print Plot button will route a copy of the plot to the default printer. 

Figure 5.33. An example of the Edit Variability Distributions Screen for TransferRelated Variables. 
65

Figure 5.34. Variable with Two Conditions shown. 

Figure 5.35. The Uncertainty Distribution # widget on the Edit Variability 

Distributions Screen when an Uncertainty distribution is Used. 

To accept the current values, click the Continue button. If any of the parameter values are in 

error, they will be highlighted in red or yellow and the Continue button will be disabled. Clicking 

on the Cancel button returns the user to the Variability Distributions screen without saving any 

changes. 
66

More detailed information on editing distributions is given in “Individual Distribution Widgets” 

in Section 2.3.5. 

5.9.2.1 Days Between Baths 

The Days Between Baths screen is a special case. When “baths” is selected from the Edit 

Variability Distributions screen, the specify Days Between Baths Screen (Figure 5.36) appears. 

On this screen the user enters the probability vector describing the distribution of days between 

baths for the population. See Section 2.3.3 for more information about entering probability 

vectors. 

5.9.3 Correlating Input Variables 

All of the variables in this section (General Exposure and Dose Factors) are randomly sampled 

from the specified input distributions. In certain cases, the user might want some of these 

variables to be correlated with each other. For example, perhaps the hand-to-mouth transfer 

efficiency and the object-to-mouth transfer efficiency should have a tendency to track each other, 

Figure 5.36. Specify Days Between Baths Screen. 
67

since the physical/chemical properties should be similar in both cases. This can be achieved in 

SHEDS by requesting that these inputs be correlated. 

Any of the variables in the General Exposure and Dose Factors section (with the exception of 

probability vectors) may be correlated with others. The user selects the subset of input variables 

that will be subject to correlation, and then specifies the pair-wise Spearman correlations. If ‘N’ 

variables are selected for correlation, there are N(N-1)/2 distinct pairs. The user does not have to 

specify all pairs; any that are not given a definite target correlation are assumed to have a target 

correlation of zero. 

SHEDS uses a modified NORTA2

 method to generate the correlations. The random values for 

the selected set of variables are first generated from a multivariate normal distribution with the 

correct Spearman correlations. Each normal variate is then transformed to the specified 

distribution using a rank-preserving transformation function. Since Spearman correlations 

depend only on rank, the Spearman correlations are preserved. The result is that the inputs will 

pair-wise exhibit the desired correlations, but will also have the marginal distributions requested 

by the user. 

Figure 5.37. Select Correlated Variables Screen. 

 

2 The NORTA method is described in the SHEDS technical manual. 
68

It is possible to specify correlations that cannot be achieved. As an example, if two variables are 

to have a perfect correlation of 1.0, then each must have the same correlation as the other with 

any third variable. Mathematically, a correlation matrix is valid if and only if all its eigenvalues 

are non-negative. If the set of requested correlations is not allowed, a message is printed on the 

SAS log when the model is run. 

Two screens are used to select and define the correlations. The first screen Select Correlated 

Variables (Figure 5.37) is used to choose the variables of interest. After choosing the variables, 

clicking on the Continue screen takes the user to Specify Variable Correlations (Figure 5.40) 

where specific pairs are assigned target correlation values. 

5.9.3.1 Select Correlated Variables 

The Select Correlated Variables screen (Figure 5.37) is used to choose which variables will be 

used to define correlated pairs in the next screen. It does not matter if variables are selected here 

which are not used later. Only valid variables will be displayed in the Input Variables list box. 

Move variables to the Correlate These Variables list box to include them in correlated pairs on 

the next screen. The single arrow moves the selected variables, the double arrows move all 

variables. If the user has previously defined correlated pairs, the right hand list box will initially

be populated only with variables in those correlated pairs. 

Clicking on the Continue button will normally take the user to the Specify Variable Correlations 

screen. If the user selects less than two variables and clicks on Continue, an error will be 

displayed (Figure 5.38), correlation will be turned off, and the user will be returned to the 

Variability Distributions screen. 

If no correlated pairs are chosen, then an error screen will be displayed (Figure 5.39), and 

correlation will be turned off in the simulation. Begin from the Variability Distributions screen to 

turn correlated inputs on once again. 
69

Figure 5.38. Error Displayed if Zero or One 

Variables are Selected for Correlation. 

Figure 5.39. Error Displayed if No Variable 

Pairs are Selected for Correlation. 

5.9.3.2 Specify Variable Correlations 

This screen (Figure 5.40) is used to define or edit variable pairs and assign a correlation value to 

the pairs. A correlated pair is represented as two variable names and a correlation value from -1 

to 1, inclusive. Note that the numbers in Figure 5.40 are hypothetical and for illustration purposes 

only; they are not intended to be recommended values. 

The variables are ordered. Initially, all but the last variable are displayed in the First Variable list 

box. The Second Variable list box will contain all variables below the variable highlighted in the 

First Variable list box. The Second Variable list box will also always include the last variable. 

The basic method of selecting a variable pair is to select the first variable in the First Variable list 

box, select the next variable from the Second Variable list box, specify the correlation value in 

the spin box to the right, and click on the Add Pair Button. Once added, the variable pair will be 

displayed in the Selected Pairs Specified box on the lower portion of the screen. 

If a variable pair selected in the upper list boxes was previously specified and is already listed 

below, then the Add Pair button will not be enabled. Instead, the Replace Pair button is enabled 

and will replace the correlation value currently specified with the one previously specified for the 

pair. 
70

The user may find it necessary to resize the columns in the Correlated Pairs Specified area. This 

area is capable of displaying both variables in the pair and the correlation value. Sometimes the 

columns are not initialized such that all three are visible. 

To delete a pair, highlight the pair in the Correlated Pairs Specified area. This will enable the 

Delete Pair button. Click on this button and the pair will be removed from the list. 

Figure 5.40. Specify Variable Correlations Screen. 
71

Clicking on Continue saves the values defined and returns the user to the Variability 

Distributions screen. Once uncertainty is implemented, the user will be returned to the 

Uncertainty Distributions screen if doing an uncertainty run. 

If no correlated pairs are chosen, then an error screen will be displayed (Figure 5.39), and 

correlation will be turned off in the simulation. Begin from the Variability Distributions screen to 

turn correlated inputs on once again. 

5.10 Run Simulation 

Only when all information has been specified will the Run Simulation button on the main menu 

(see Figure 5.2) be enabled. Clicking on it brings the user to the Run Simulation screen (Figure 

5.41). The screen displays the current run name, the number of simulated profiles, the number of 

sensitivity or uncertainty repetitions (if any), the number of chemicals, and estimated run time. 

 If 20 or fewer people are being simulated, then the user will have the option of turning on the 

diagnostic mode. 

“Write Inputs to Excel” 

generates a file containing 

all of the user editable 

model inputs. The file is an 

XML file, but can be read 

by MS Excel 2003 or later. 

The file is placed in the 

install directory and is 

named using the run name 

and the standard Excel file 

extension (.xls). 

“Check Input for Errors” 

forces two routines to run 

and check inputs. 

Comments and errors will 

be displayed to the log 

which will be made visible 

if is not already. These 

same checks are also 

carried out when the 

simulation is run. 

Clicking on “Run Simulation” will begin the simulation. This will open the Run Progress Screen 

(Figure 5.42). This screen contains information about the progress of the run, including how 

Figure 5.41. Run Simulation Screen for an Uncertainty Run. 
72

many profiles and chemicals have been completed, the estimated remaining time, and the average 

time per profile. For a sensitivity or variability run, the screen will also indicate which sensitivity 

or uncertainty repetition is currently being performed. In addition, informational messages will 

be displayed in the log (Figure 5.43). Among other items, the number of people completed and 

the number total are indicated as the run progresses. When the simulation is completed, the final 

timing information will be displayed in the log. Clicking the Continue button after run 

completion will return one to the main menu where View Results can be selected. 

Typically you will want to 

open the log window before 

running a simulation. If the 

log window has been 

minimized, clicking the 

button along the bottom of 

the main SAS window will 

open it. This can be done 

after the run has started. If 

not open yet, the log 

window can be opened by 

selecting the View menu on 

the main SAS menu bar and 

then selecting Log. This 

must be done before the 

simulation has started. 

The correlated pairs are 

checked for validity at the 

beginning of the run. If 

problems are found an error message will be printed in the log. 

The diagnostic mode is only available for simulations with twenty or fewer people. Typically, a 

user will not want to run in diagnostic mode. If one is very familiar with the model it may be 

helpful in locating errors. Three things happen when the model is run in diagnostic mode. 

1. SAS prints detailed notes to the log detailing how macros were compiled and data steps 

completed. 

Figure 5.42. The Run Progress Screen for a Variability Run. 
73

Figure 5.43. Log Screen after Running a Small Simulation. 

2. Intermediate variables are saved on the datasets. This option is also available on the 

Simulation Information screen. 

3. Event level datasets and variables are saved for each individual simulated. 

Once started, the run can be cancelled by following the instructions on the Run Dialog. 

5.11 View Results 

Model results from previous or current SHEDS simulations can be viewed by selecting the View 

Results button on the main window. This button will become active once a simulation run has 

been made or after a previously run simulation is specified in the Run Name dialog. Pressing this 

button opens a dialog (Figure 5.44) allowing the user to select one of the following: 

• View Results for the Population; 

• View Results for an Individual; 

• View Uncertainty Results; 
74

• View Sensitivity Results; 

• View Diary Pool Sizes. 

Each of these buttons opens a new dialog. 

Figure 5.44. View Results Screen. 

5.11.1 Additional Outputs and Files 

A number of outputs cannot be viewed through the interface. For information on the log files, 

export files, and exporting files from SAS for analysis in other software, see Appendix A for 

more information. 

5.11.2 View Results for the Population 

The View Results for the Population window is used to generate graphical or tabular results for 

output variables for the population as a whole, or for subgroups of the population. The outputs 

will utilize the average daily values for the simulation just run or that specified most recently in 

the Run Names dialog. When considering the population, the output variables utilized are the 

daily values (of exposure, dose, etc.) for each person, averaged over the simulation period. The 

outputs generated examine the variability of these personal mean daily values over the 

population. In addition, the personal daily maximums for each person for each variable can also 

be viewed. 
75

Figure 5.45. View Results for the Population Screen. 

In general the user will want to work from the top down, selecting the output units and thus the 

output dataset of interest, then the sub-population of interest, output type, and specific variables 

desired. 

The Run Name box shows the name of the current run, while the Output Data Set supplies the 

name of the corresponding SAS dataset that will be used to generate the results. 

The Output Units menu is used to indicate the units for the output data, either Milligrams per 

Kilogram body weight or Micrograms. The appropriate output dataset will be displayed in the 

Output Data Set box. 
76

The menus in the Select Population box (Gender, Start Age, Stop Age, Min Rank, and Max 

Rank) can be used to select a subgroup of the run population for analysis. Subsetting is based on 

the fact that each simulated individual is assigned a specific age, gender and bin rank. The entire 

simulated population is divided into 100 bins labeled 0 to 99; as nearly as possible, the bins 

contain the same number of people. (If the simulated population is less than 100, some of the 

bins will be empty and will not appear in the pull down menu.) The bins are ranked based on the 

total chemical absorption over the entire simulation period. The user may subset the population 

by restricting the age range, gender, bin rank, or any combination of these. For example, the user 

may choose to examine only the women or only the children. The pull down menus only display 

genders, ages, and ranks that exist in the output dataset. The final selections and count of 

individuals will appear on any resulting tables and graphics generated. The Selected Count field 

updates after each user selection to display the final number of people in the sub-group. 

The Output Type list box includes the analyses that may be performed. The user selects one 

option from this list at a time. The options for results analyses in SHEDS-Residential version 4 

are the following: 

• Summary Table; 

• CDF (Cumulative Distribution Function); 

• Box and Whiskers; and 

• Contribution by Pathway. 

The Chemical list box lets the user select the chemical for which to view any chemical-specific 

results (like exposures and doses). All chemicals in the simulation will be available for viewing. 

 In addition, for cumulative runs, the variable “Cumulative” will also be available in the chemical 

list. Selecting this variable will allow the user to view the results that result from combining the 

results for all the chemicals in the run. Any non-chemical specific variables (such as Ventilation) 

will display the same results for any selection from the chemical list box. 

For uncertainty and sensitivity runs, the summary sensitivity and uncertainty results are viewed 

on screens specific to these types of runs (see following sections). However, for each of these 

types the user can also view the variability results from each variability repetition. For these 

types of runs, there will be an additional list box on the View Results for the Population screen 

labeled “Uncertainty Repetition” or “Sensitivity Repetition”. This box will contain a list of the 

available repetitions. The user can then select any of the repetitions to view. 

The Variable Groups list box allows the user to select a subgroup of the variables to view. When 

the user selects a group, the available variables will appear in the Select Variables selection box. 

The available variable groups are: 

• New exposure; 

• New exposure normalized to body mass; 
77

• New handler exposure; 

• Running exposure; 

• New dose; 

• New dose normalized to body mass; 

• Ventilation; 

• Chemical and metabolite entering blood; 

• Eliminated chemical; and 

• Margin of exposure. 

See the Technical Manual for the definitions of these terms. 

The Output Variable Type list box lets the user select either: 

• Personal Means; or 

• Personal Maximums. 

Pressing the Display button then performs the analysis and displays the results in a new window. 

That window must be closed to return to this dialog to define new outputs. 

The Variable Groups and Select Variables menus are used to select the model output variables to 

analyze. The Variable Groups menu is used to pick a general category of model variables (such 

as dose, exposure, or loading variables). Selecting this variable group will update the Select 

Variables menu to include all corresponding model variables. For example, in Figure 5.45 the 

Variable Group selected is New Exposure, so the Select Variables menu has been updated to 

include all the corresponding exposure variables. The user then selects one or more variables 

from this list to analyze. Clicking on display generates the output. Specific details of each of the 

Output Types are covered next. 

5.11.2.1 Summary Table 

Selecting this option yields a summary statistics table for the selected variable(s) and specified 

model simulation, including sample size, mean, standard deviation, median, 5th,25tt, 75th

, 95th, 

and 99th percentiles. An example is shown in Figure 5.46. If multiple variables are analyzed, the 

results are displayed on individual rows of the table; the variable name and description (label) are 

included on each row. Again, note that the subpopulation that is being examined is printed in the 

table window – in this hypothetical example the user is examining males and females between 

the ages of 1 and 20 years. 
78

Figure 5.46. Example Summary Table for a Population. 

5.11.2.2 CDF 

This option yields a cumulative distribution function (CDF) plot for the selected variable(s) and 

specified model simulation. The plot illustrates how the percentiles of the selected variable(s) 

behave as a function of the variable value. Each selected variable will appear as a separate line 

on the plot; a legend appears at the bottom of the plot to identify each variable. An example is 

shown in Figure 5.47. In the example, the CDFs for six new exposure variables are plotted (only 

three can be seen in this particular case, since all the percentiles for the others were zero in this 

simulation.) The plot can be printed by clicking on the Print button. The default printer will be 

used and the plot will be formatted for default SAS printer. 
79

Figure 5.47. Example CDF for a Population. 

5.11.2.3 Box and Whiskers 

Selecting the Box and Whiskers option yields a box and whiskers plot for the selected variable(s) 

for the current simulation for the defined population subgroup. Multiple variables are shown on 

a single plot. An example for seven absorption variables is given in Figure 5.48. Unlike other 

plots, the Box and Whiskers plots use the variable names rather than the variable labels. The 

longer labels will overwrite one another or be suppressed by SAS. The boxes, whiskers, and 

other symbols on the plot are interpreted as follows: 
80

Figure 5.48. Example Population Box and Whiskers Plot. 

• The midlines of the boxes are equal to the median. 

• The plus (+) symbol inside the boxes is equal to the mean. 

• The upper edge of the box is the 75th percentile of the population, while the lower 

edge is the 25th percentile. Thus, these edges define the width of the interquartile 

range (IQR). 

• The whiskers define the maximum or minimum observations that fall within 1.5 

times the IQR, measured from the quartile value (i.e., the 75th or 25th percentile). 
81

• The square symbols indicate data points outside of the range defined by 1.5 times 

the IQR. 

5.11.2.4 Contribution by Pathway 

The Contribution by Pathway option is different from the other options in the Output Type menu. 

It does not require (or allow) selection of individual model variables. Only a selection from the 

Variable Group menu is required: New Exposure, New Exposure Normalized to Body Mass, 

New Handler Exposure, Running Exposure, New Dose, or New Dose Normalized to Body Mass. 

Clicking on Display yields a pie chart showing percent contribution to one of these summary 

variables (based on population or population subgroup means or maxes) for the following 

pathways: 

• Dermal; 

• Inhalation; 

• Ingestion; 

• Hand-to-Mouth; and 

• Object-to-Mouth. 

Figure 5.49. Example Pie Chart Showing the 

Contribution by Pathway for a Population. 
82

5.11.3 View Results for an Individual 

The second results window accessible from View Results is the View Results for Individual. 

Selecting this button brings up the window for performing analysis of the results for a single 

individual within a simulation run. Many of these options are similar to those for View Results 

for Population. When considering an individual, the output variables of interest are the daily 

values for the selected individual. A specific simulated individual must be selected. Additionally, 

the analysis may be limited to a specific time period. As on the population results screen, it is 

best to work from the top down on the left side of the screen, and then choose the Variable Group 

and specific variables of interest. All resulting outputs will contain a second title giving the basic

individual statistics and dates considered in the analysis. 

The View Results for an Individual dialog is shown in Figure 5.50. The Run Name box shows 

the name of the current run, while the Output Data Set supplies the name of the corresponding 

SAS dataset that will be used as the basis of the results. The output dataset is dependent on the 

units chosen. As in the Results for Population window, one can select genders, an age range, and 

a rank range in the Select Population box. In this case, the Select Individuals list box is populated 

only with individuals meeting these criteria. The individual list box provides minimal 

information on each individual: the identifier used in the simulation, the gender (shown as ‘M’ or 

‘F’), age, and the individual’s rank or percentile of total absorption. The user clicks on an 

individual to select and then analyze data from that individual. 

In addition to selecting an individual, the user may also select a particular range of dates to 

analyze from the Dates of Interest menu. The Start Date and Stop Date may be selected from the 

corresponding menus, which are populated with all the dates covered by the current simulation. 

The output options for viewing variability results for an individual are listed in the Output Type 

list box. These include: 

• Time-Series; 

• CDF (Cumulative Distribution Function); 

• Box and Whiskers; 

• Contribution by Pathway; 

• Summary Table; and 

• Detailed Table. 
83

Figure 5.50. View Results for an Individual Screen.
84

The user also must select the chemical for which to view results, and a Variable Group. These 

list boxes behave the same as on the View Results for Population Screen (Section 5.11.2). 

The user may also view individual results for uncertainty and sensitivity runs; however, in this 

case, only the individuals simulated in the very last sensitivity or uncertainty repetition are 

available. Due to space limitations, SHEDS does not retain daily-level information for every 

repetition (only the most recent). It should be noted that while all repetitions are valid variability 

runs, one should use caution when viewing results from a percentile scaling run, because in this 

type of run certain variables (most sensitivity input variables) may be being held at their median 

values in the last sensitivity repetition. 

As in the View Results by Population dialog, the output units may be selected as either 

Microgram or Milligrams per Kilogram from the Output Units menu, and the Variable Groups 

and Select Variables menus are used to select the model output variables to analyze. As before, 

multiple variables may be selected for analysis. The appropriate analysis variables will 

automatically be chosen for Contribution By Pathway. All variables will automatically be used 

for the detailed table. Each of the output types are described next. 

5.11.3.1 Time-Series 

Selecting the Time-Series button produces a time-dependent plot of the selected variable(s). 

Each data value on the plot is the value for a single day in the simulation. Multiple variables will 

be plotted as multiple curves on the same time-series plot; the legend that appears at the bottom 

of the plot identifies which variable is associated with each plotted curve. Time-Series 

simulations are useful for observing the behavior of doses and exposures in the days following a 

pesticide application. An example showing six exposure variables (some of them essentially 

equal to 0) is given in Figure 5.51. 
85

Figure 5.51. Example Time-Series for an Individual.

5.11.3.2 CDF 

The CDF option for an individual is similar to that for the population (See Figure 5.47). The 

option yields a cumulative distribution function plot for the daily values of the selected 

variable(s) for the specified individual. Each selected variable will appear as a separate line on 

the plot; a legend appears at the bottom of the plot to identify each variable. An example of a 

CDF for an individual for new dermal exposure for a year-long simulation is given in Figure 

5.52. 
86

Figure 5.52. Example CDF for an Individual. 

5.11.3.3 Box and Whiskers 

The Box and Whiskers option for an individual is similar to that for the population (see Figure 

5.48 on page 80 and the previous discussion), with the exception that the plot is generated by 

examining the daily variable values for a single person rather than the mean daily values for the 

population. Selecting Box and Whiskers and clicking on Display will yield a plot for the selected 

variable(s) for the current simulation, selected person, and selected dates. Multiple variables are 

shown on a single plot. An example box and whiskers plot for an individual’s daily values of 

several new dose variables for a year-long simulation is shown in Figure 5.53. 
87

Figure 5.53. Example Box and Whiskers Plot for an Individual. 

5.11.3.4 Contribution by Pathway 

The interpretation of the Contribution by Pathway option for an individual is identical to that for 

the population. As before, this option does not require or permit selection of individual model 

variables; only the Variable Group needs to be specified-- New Exposure, New Exposure 

Normalized to Body Mass, New Handler Exposure, Running Exposure, New Dose, or New Dose 

Normalized to Body Mass. (The Select Variables menu will be inactive if Contribution by 

Pathway is selected). Selecting Display then yields a pie chart showing percent contribution to 

one of these summary variables by pathway. 
88

Figure 5.54. Example Pie Chart Showing the 

contribution by pathway for an individual. 

5.11.3.5 Summary Table 

If Summary Table is selected, clicking on Display will open a new window containing the 

percentiles of the selected variable(s), with each variable appearing on its own row in the table. 

Specifically, the table contains the sample size, mean, standard deviation, median (p50), 5th

percentile (p05), 25th percentile (p25), 75th percentile (p75), 95th percentile (p95), and 99th

percentile (p99). The age and gender of the individual being examined appears in the descriptive 

heading. The resulting table looks very similar to the summary table for the population (see 

Figure 5.46), with the exception that the statistics represent the variation in the variables across 

days for a single person (rather than the variation in the averaged daily values across persons). 

5.11.3.6 Detailed Table 

Selecting the Detailed Table option opens a new window and displays a table that contains 

detailed information for all daily average variables generated by the model (Figure 5.55). It is not 

required or permitted to select a variable group or specific variables. The detailed table contains 

one row for each of the days being analyzed. The table contains the year, month, and day, the 

number of diary events for the day, and the values for each model variable related to the Variable 

Group. All variables will not fit on the screen at once. The scroll bar at the bottom of the 

window can be used to view the variables that appear to the right. 
89

Figure 5.55. Example Detailed Table for an Individual. 

5.11.4 View Uncertainty Results 

Selecting the View Uncertainty Results button from the View Results screen will open the 

window shown in Figure 5.56. This window allows the user to view several types of plots that 

summarize the uncertainty of the model as estimated from the uncertainty repetitions that were 

performed (i.e. the uncertainty that results from any uncertainty clouds that were defined for 

model variables using the “Uncertainty” type distribution.) 

The variable group list is the same as on the other results screens. However, in the case of 

uncertainty runs, only a single variable can be selected at a time. 

There are two types of output summary plots that are available for uncertainty runs: 

• Plot the 5th, 50th, and 95th percentile from each uncertainty repetition. In this type of 

plot, the persons in each repetition with the 5

th, 50th, and 95th population percentile 

average values for the variable are identified and these percentile values are retained and 

plotted as a CDF. An example of this type of plot is shown in Figure 5.57. In this 

example, five uncertainty repetitions were performed. A CDF is plotted of the population 

5

th, 50th, and 95th percentiles of total dose from each of these runs (and thus each CDF on 

the plot has 5 points). In this example, all the values of the 5th percentiles were 0, as were 

a number of the medians. 
90

• Plot the CDFs of repetitions whose medians are at the 5th, 50th, and 95th percentiles. 

In this type of plot, three repetitions are identified: those whose population medians are at 

the 5th, 50th, and 95th percentile of all the repetition medians. An example of this type of 

plot is shown in Figure 5.58. In this example, total new dose was examined for an 

uncertainty run of 5 repetitions of 25 profiles each. Three repetitions were identified: that 

with a median with the 5th percentile of all medians. In this case, since only 5 repetitions 

were performed, the 5th percentile corresponded to the repetition with the lowest median. 

The 50th percentile corresponded to the repetition with the 3rd highest median out of the 5 

run, and the 95th percentile corresponded to the repetition having the highest median. 

Then the population CDFs for total new dose are plotted for those three repetitions; note 

that each CDF has 25 points because 25 profiles were run. Note that this run is only for 

example purposes; many more profiles and repetitions would be needed to develop real, 

useful uncertainty results. 

Figure 5.56. View Uncertainty Results Screen. 
91

Figure 5.57. Plotting the 5th, 50th, and 95th Percentiles of Each Uncertainty 

Repetition. 
92

5.11.5 View Sensitivity Results 

Selecting the View Sensitivity Results button from the View Results screen will open the 

window shown in Figure 5.59. This window allows the user to view a table of sensitivity results 

for the run. The format and contents of the table will vary based on the type of sensitivity run that 

was performed (Percentile Scaling, Sobol’s Analysis, or Input-Output Correlation). 

Figure 5.58. Plotting the CDFs from Uncertainty Repetitions whose Medians are at 

the 5th, 50th, and 95th Percentiles. 
93

Figure 5.59. View Sensitivity Results Screen. 

The user may select to view sensitivity results based on the population average of any model 

variable. The available variable groups are the same as described in Section 5.11.2 . The user 

specifies a variable group, a variable, and then clicks Display to view the sensitivity table. 

5.11.5.1 Results for a Percentile Scaling Run 

If a Percentile Scaling run was performed, the table of sensitivity results will resemble that 

shown in Figure 5.61. This table includes a list of all the model input variables in the run for 

which sensitivity was considered. (See Section 5.4.1 for information on how to specify a list of 

sensitivity inputs). Recall that a percentile scaling run performs a baseline (median) run with all 

the sensitivity inputs at their median values, and then repeats the run with each of the input 

values at a high and low percentile. (See the SHEDS Technical Manual for detailed information 

about the percentile scaling method.) The results of these runs are summarized in the table. The 

table contains the following information: 
94

• Variable. The input variable name. For space reasons, the variables are listed by their 

short (code) names. See the SHEDS technical manual for a longer description of each 

variable. 

• Number of Persons. The number of profiles in the run. 

• Ratio of Low Result to Median Result. Ratio of the result for low-percentile run to that 

for the median run for the output variable selected. 

• Ratio of High Result to Median Result. Ratio of the result for high-percentile run to 

that for the median run for the output variable selected. 

• Ratio of High Result to Low Result. Ratio of the result for high-percentile run to that 

for low-percentile run. 

• Score. A variable that indicates the relative difference between the high and low results 

for all input variables; it is equal to the Ratio of High Result to Low Result if this number 

is greater than 1, or its inverse if it is less than 1. It is used to rank the items in the table. 

In the example shown in Figure 5.60, the sensitivity of the new dermal dose to four input 

variables was examined. Of the four variables being examined, the model was most sensitive 

to the area of the vegetable garden (area_garden). Note that this run is only for example 

purposes; many more profiles would be needed to develop real, useful sensitivity results. 

 

Figure 5.60. Sensitivity Results for a Percentile Scaling Run. 
95

5.11.5.2 Results for a Sobol Sensitivity Run 

An example of the sensitivity results for a Sobol run are shown in Figure 5.61. For this type of 

run, a number of output sensitivity variables are presented for each Sobol Group (see Section 

5.4.1.2 for instructions on defining Sobol Groups). The output variables are as follows: 

• Main Effect. The combined main effect of all the variables in the Sobol group. 

• Total Effect. The combined total effect of all the variables in the Sobol group. 

• Percent of Total Variance. The percent of the total variance in the output variable that 

is explained by variation in the variables in the Sobol group. This is calculated as the total 

effect of the group divided by sum of the total effect for all groups multiplied by 100. 

• Variables. A list of the input variables in the Sobol group. For space reasons, the 

variables are listed by their short (code) names. See the SHEDS Technical Manual for a 

longer description of each variable. 

Note that it may require large numbers of profiles to be run to capture adequately the sensitivity 

of the model to the Sobol groups. In this example, the fact that a total effect of greater than 1 

was found indicates that there is considerable uncertainty in these estimates. See the SHEDS 

Technical Manual for details on performing Sobol runs. 

Figure 5.61. Sensitivity Results for a Sobol Analysis Run. 
96

5.11.5.3 Results for a Input-Output Correlation Sensitivity Run 

If the type of sensitivity analysis being performed is an input-output correlation run, the table of 

sensitivity results will be similar to that shown in Figure 5.62. This table contains a list of all the 

input variables in the run, and their correlation with the selected variable (Total New Dose in the 

example in Figure 5.62). The absolute value of this correlation is also given. It is used to 

determine the order of the variables in the table; variables with the highest correlations with the 

output variable will be at the top of the table. For space reasons, the variables are listed by their

short (code) names. See the SHEDS Technical Manual for a longer description of each variable 

and for more information about calculating input-output correlations.

Figure 5.62. Sensitivity Results for an Input-Output Correlation Run. 
97

5.11.6 View Diary Pool Sizes 

Activity diaries are selected at random from pools that are characterized by different personal and 

temporal characteristics. Figure 5-39 provides an example of counts of diaries available for each 

diary pool as determined by the user’s inputs for the simulations. The user is reminded that 

larger diary pools better represent the population. 

 

Figure 5.63. Example Diary Pool Size Table. 
98

6 Case Study: Permethrin 

This chapter provides an example of creating a SHEDS-Residential run from start to finish. The 

run presented herein is a single-chemical variability run for Permethrin. The run considers a 

single application scenario (an indoor crack-crevice aerosol); the application dates are modeldetermined. This example run is included in the SHEDS-Residential installation; it will be 

available for selection when Edit an Existing Run is selected under the name Permethrin Case 

Study. However, the steps presented here show the user how to create the run from scratch. Each 

step in creating the run will be illustrated with an accompanying screenshot. 

Note: Since SHEDS is in development, the results seen here may differ from that seen by the 

user. 

Start the SHEDSResidential interface. 

Select Cumulative 

Mode. Although this 

is a single-chemical 

run, this example will 

step through the 

Cumulative Model 

screens so the user 

can see the steps they 

would need to 

complete for a 

multichemical run. 

Click <Start \SHEDSResidential>. 
99

Click <Specify Run 

Name and Files>. 

Click <Create a New 

Run >. Enter a name 

for the run, in this 

case, “Permethrin.” 

Click <Continue>. 

The location of the 

information for the 

run (input and output) 

can be changed on 

this screen, if desired. 
100

Enter a description 

for the run, if desired 

(this is optional). 

Click <Save>. 

Click <Specify 

Population and 

Sampling>. The run 

type “Variability” 

will be selected by 

default. Select 

“Optional Group 

Definitions,” and 

choose to run males 

and females 3-5 years 

of age by highlighting 

the age groups. Enter 

a population size of 

500 profiles (this can 

be directly typed in, 

or the arrows can be 

used to select 

common population 

sizes). (The number 

of total iterations is 

automatically 

updated). Click 

<Save>. 
101

Click on <Specify 

Simulation 

Information> on the 

Main screen. Select 

January, 1, 2010 as 

the start date and 

enter 365 as the 

number of days in the 

year. Select “ModelDetermined Dates” as 

the Application Dates 

method. Select 

“Transfer Efficiency” 

as the dermal 

exposure method. For 

the Diary Assembly 

method, highlight 

“Longitudinal Diary.” 

 This will enable the 

key variable, 

diversity, and 

autocorrelation 

widgets. Select 

“Time Spent at Home 

While Awake” as the 

key variable, 0.2 as 

the diversity statistic, 

and 0 for mean dayto-day 

autocorrelation. 

Leave other variables 

at defaults, and Click 

<Save>. 
102

Click <Specify 

Chemicals> on the 

main screen. Choose 

to model Permethrin 

by highlighting it 

(and only it) in the 

Select Chemicals list 

box. Chemicals can 

be toggled between 

selected/unselected 

by clicking on them 

in the list box. Click 

<Continue>. 

Accept the default 

values for Permethrin 

on the Specify 

Chemical Information 

screen by clicking 

<Continue>. This 

will return the user to 

the main screen. 
103

Click <Specify 

Application 

Scenarios> on the 

Main Screen. This 

will open the Select 

Scenarios screen. 

Select “Indoor Crack 

and Crevice 

(aerosol)” from the 

Scenario Library. 

When the scenario 

appears in the 

Selected Scenarios 

box, click 

<Continue> to move 

to the Specify 

Scenario Details 

screen. 

Click <Specify 

Inputs> to enter 

information for the 

crack/crevice 

scenario. 
104

The first scenario 

screen is the Specify 

Chemicals in 

Scenario screen. 

Click on Permethrin 

to add the chemical to 

the scenario. In 

Aggregate mode, this 

screen is skipped 

because the model 

assumes the single 

chemical will be 

present in the 

scenario. If more 

than one chemical 

were available, the 

user could assign a 

subset of the 

chemicals to each 

scenario. Click <Save 

and Continue> to 

proceed. 
105

The next screen in the 

scenario cascade is 

the Application 

Probabilities screen. 

Accept the defaults 

by clicking <Save and 

Continue>. This 

returns the user to the 

Specify Scenarios 

Screen. Click 

<Continue> again to 

proceed. 
106

The next screen is the 

Application Times 

screen, where the user 

specifies a probability 

vector for the time of 

application of the 

chemical for any 

indoor scenarios. 

Accept the defaults 

by clicking <Save and 

Continue>. 

The next screen 

appears only when an 

indoor scenario is 

included in the run. 

Accept the default 

fraction of the house 

treated with the 

crack/crevice aerosol 

by clicking <Save and 

Continue>. This 

proceeds to the Reentry screen. 
107

Only a re-entry time 

for indoor areas is 

available because this 

run only includes a 

single indoor 

scenario. If outdoor 

or pet scenarios were 

included in the run, 

this screen would 

contain more 

distributions to 

specify. Click <Save 

and Return> to accept 

the default re-entry 

time and return to the 

Main screen. 
108

Click on 

<Concentration 

Related Inputs> on 

the main screen. This 

initiates the 

Concentration screen 

cascade. After a 

warning related to 

chemical transfer, the 

first screen is the 

Decay and Dispersion 

Distributions. This 

screen is present 

because Decay and 

Dispersion was 

selected as the 

Source-toConcentration 

Approach earlier in 

the run. Note that 

these variables are 

chemical-dependent; 

if there were more 

than one chemical 

present in the run, 

they would be 

included in the list 

box on the left side of 

the screen. Click 

<Save and Continue> 

to accept the defaults 

for Permethrin. 
109

Click <Save and 

Continue> to accept 

the default value of 0 

for permethrin 

background 

concentration. This 

returns the user to the 

Main screen. 

Click <Specify 

General Exposure and 

Dose Variables> on 

the Main screen. This 

opens the Variability 

Distributions screen. 

The user will need to 

visit each of the 

variable groups 

before being allowed 

to continue. Click 

<Specify Inputs> to 

view/edit the Baths 

variable group. 
110

The Baths group is a 

special case: it 

consists of a single 

probability vector for 

days between baths. 

Accept the defaults 

by clicking <Save>. 

When the user is 

returned to the prior 

screen, the next 

Variable group, 

“Dose-Related,” 

should be highlighted. 

Click <Specify 

Inputs> again to edit 

this group. This opens 

the Edit Variable 

Distributions 

window, which 

allows the user to 

view or edit any of 

the distributions in 

the group, for any 

available conditions. 

Click <Continue> to 

accept the defaults for 

permethrin and return 

to the prior screen. 
111

Click <Specify 

Inputs> to edit 

variables in the 

“Removal-Related” 

group. Click 

<Continue> to accept 

the defaults and 

return to the prior 

screen. 

Click <Specify 

Inputs> to edit 

variables in the 

“Transfer-Related” 

group. Click 

<Continue> to accept 

the defaults and 

return to the prior 

screen. 
112

Click <Specify 

Inputs> to edit 

variables in the 

“Activity-Related” 

group. Click 

<Continue> to accept 

the defaults and 

return to the prior 

screen. Then click 

<Continue> once 

more to return to the 

Main screen. 

Click <Run 

Simulation> on the 

Main screen. This 

brings up the Run 

Simulation Screen. 

The screen should 

indicate that 500 

profiles will be run 

for one chemical. 

Click <Run 

Simulation> to 

initiate the 

simulation. 
113

This opens the 

SHEDS-Residential 

Run Progress screen. 

This gives the user an 

idea how long the 

simulation will take 

to complete. This run 

should take between 

20 minutes and an 

hour depending on 

the age/configuration 

of the user’s 

computer. When the 

run is complete, this 

window will close 

automatically and 

return to the Run 

screen. Click 

<Continue> to return 

to the Main screen. 

Select <View 

Results> from the 

Main screen. Then 

click <View Results 

for the Population>. 
114

Select “New Dose” as 

the variable group, 

then Select “Total 

New Dose”, and the 

New Dose variables 

for “Hands”, “Body”, 

and “Dermal” from 

the available 

variables. Click 

<Display> to view the 

default output type, 

CDF. 

This draws a plot 

with CDFs for the 4 

variables that were 

selected. Click 

<Close> to return to 

View Results for the 

Population. 
115

Select “Summary 

Table” as the output 

type. Select “New 

Exposure” as the 

variable group, 

highlight all the 

available variables, 

and click <Display>. 

This creates the table. 

 Click<Close> to 

return to the previous 

screen. 

Select “Box and 

Whiskers” as the 

output type. Select 

“New Dose 

Normalized to Body 

Mass” as the variable 

group, highlight all 

the available 

variables, and click 

<Display>. This 

creates the box plot. 

Click<Close> to 

return to the previous 

screen. 
116

Select “Contribution 

By Pathway” as the 

output type. Select 

“New Exposure as” 

as the variable group 

and click <Display>. 

This creates the pie 

chart. Click<Close> 

to return to the 

previous screen. 

Click <Close> to 

return to the View 

Results screen. Click 

<View Results for an 

Individual>. Select 

person 5, or any other 

person with a higher 

ranking. Select 

“Time Series” as 

output type, “New 

Exposure” as variable 

group, and “Hands to 

Mouth” as the 

variable. 
117

Click <Display> to 

view the time series 

plot. Click <Close> 

to return to the 

previous screen. 

Select “CDF” as the 

output type. Select 

“New Exposure” as 

the variable group, 

highlight dermal and 

hand to mouth 

exposure, and click 

<Display>. This 

creates the CDF. 

Click<Close> to 

return to the previous 

screen. 
118

Select “Box and 

Whiskers” as the 

output type. Select 

“Chemical and 

Metabolite Entering 

Blood” as the variable 

group, highlight all 

the available 

variables, and click 

<Display>. This 

creates the box plot. 

Click<Close> to 

return to the previous 

screen. 

Select “Contribution 

by Pathway” as the 

output type. Select 

“New Dose 

Normalized to Body 

Mass” as the variable 

group and click 

<Display>. This 

creates the pie chart. 

Click<Close> to 

return to the previous 

screen. 
119

Select “Summary 

Table” as the output 

type. Select 

“Eliminated 

Chemical” as the 

variable group, 

highlight all 

variables, and click 

<Display>. This 

creates the table. 

Click<Close> to 

return to the previous 

screen. 

Select “Detailed 

Table” as the output 

type. Select “New 

Exposure” as the 

variable group, and 

click <Display>. This 

creates the table. You 

may need to page 

down to see the nonzero exposure 

estimates. Click 

<Close> to return to 

the previous screen. 
120

7 SHEDS-Residential: Batch Mode 

The SHEDS model may also be run in batch mode. Runs in batch mode do not open any SAS 

windows. They are usually submitted via the Run dialog on the Start menu in Windows. Batch 

mode uses fewer computer resources, which may speed up long runs. This may be appropriate 

for overnight runs where the user has no need to view the progress of the job. Multiple batch jobs 

may be submitted at one time, also useful for overnight runs. Finally, sensitivity analysis or 

uncertainty analysis runs may also be conducted in batch mode, or by submitting the appropriate 

commands in a standard SAS session. 

7.1 Installing Batch Capability 

Along with the SAS program “Multimedia4.sas” and the default input files used by the interface, 

two additional files (“batch.sas” and “SHEDS.bat”) are needed to run SHEDS-Residential in 

batch mode. 

The file “batch.sas” does not require editing. Its contents are: 

%Let comma = %index(%quote(&sysparm),%str(,)); 

%Let dir = %substr(%quote(&sysparm),1,%eval(&comma-1)); 

%Include "&dir\prg\multimedia4.sas"; 

%multimedia4(&sysparm); 

The other file is “SHEDS.bat”, which must have its path names altered to match the SHEDS 

installation directory on the user’s machine. The default contents of “SHEDS.bat” are shown 

below. 

"C:\Program Files\SAS64\SASFoundation\9.2\sas.exe" 

"C:\SHEDS_Multimedia4\prg\batch.sas" 

-sysparm "C:\SHEDS_Multimedia4,%1 %2 %3 %4 %5,64" 

In the batch file, the three lines above should appear on a single line, as they are all part of the 

same command. The pathnames may need to be edited to conform to the user's computer. The 

first is the location of the sas.exe file itself. The second gives the location of the batch.sas 

program, which is usually in the \prg directory under the SHEDS-Residential installation 

directory. The third path (from the C: in the third line above, up to the comma) gives the location 

of the SHEDS installation directory. This file can be edited in any text editor. 

7.2 Defining Inputs for a Batch Run 

The main difficulty in submitting a SHEDS run is ensuring that all the necessary inputs are 

defined. This is a primary function of the interface itself. Hence, the easiest way to prepare a 

batch run is to define and save all the inputs using the interface. Inputs for several runs could be 

defined and saved without submitting any of these jobs. Alternatively, the user could prepare the 
121

required input files using a standard SAS editor, but this places a greater burden on the user to 

ensure that all inputs have been supplied in a consistent manner. 

Each set of inputs and settings is saved under a user-supplied job name. For example, suppose 

the user chooses the name “job1”. Whether defined through the interface or not, this requires the 

addition of a new record to the “runinfo” file found in the SHEDS installation directory, and new 

directories called “runs\job1\input” and “runs\job1\output” need to be created. Appropriate 

versions of the following SAS datasets must be defined for the run, either placed in the \input 

directory for the run or else found in the default data directory: 

 agegroups 

 areatreated 

 bwsa 

 chem_distributions 

 chemicals 

 cohorts 

 contactmedia 

 correlations 

 dates_fixed 

 dates_variable 

 diaryevents 

 diarylocs 

 diaryQArules 

 diaryquest 

 distributions 

 handlers 

 intervals 

 metsdists 

 metsmap 

 pop2000 

 scenarios 

 timeseries 

 variables 

Even if the defaults are acceptable for all the above files, each job requires its own record in the 

RunInfo file. Either an existing record on the RunInfo file can be edited, or a new record added. 

Open the existing RunInfo file in the SAS editor, copy any record to a form a new record, and 

then hand-edit that new record. Alternatively, a new record may be added using SAS 

programming. For many users, these options can be performed more easily through the SHEDS 

graphical user interface (GUI). It is possible to prepare the RunInfo file using the GUI and then 

later submit the job in batch mode. 
122

7.3 Submitting a Batch Run 

To submit a SHEDS run in batch mode, use the Run dialog on the Windows Start menu. 

Enter the full path to the “batchrun.bat” file (with quotes needed if the path contains blanks or 

spaces), followed by a space and the name of the job to be run. For example, 

“C:\SHEDS_Multimedia4\SHEDS.bat” job1 

 

Do not quote the name of the job itself, even if it contains spaces. To submit the job “lawn and 

garden” (assuming that the “multimedia.bat” file is located in “C:\SHEDS_Multimedia4”), type 

“C:\SHEDS_Multimedia4\SHEDS.bat” lawn and garden 

 

and hit the return key to submit the commands. 

A black DOS window should appear, along with another SAS window indicating the location of 

the source code, output, and log files. The file batch.log contains the information normally found 

in the SAS log window. The rest of the output from the run should be located in the \output 

directory under the job name. 

7.4 Uncertainty and Sensitivity Runs 

Uncertainty and sensitivity runs are submitted in exactly the same way as other batch runs. Note 

that these runs may take a long time to complete. A run of 200 populations of 1000 persons each 

takes the same time to complete as a variability-only run of 200,000 persons. This may take 

several days. 

Uncertainty runs require extra input files for the "uncertainty clouds" that represent the possible 

parameter spaces for the uncertain inputs. These must be placed in the \input\unc folder under 

the location for the given run, or else in the data\unc folder under the SHEDS installation. The 

uncertainty clouds are in SAS data sets that must be prepared outside of SHEDS. However, the 

version 4 GUI allows the user to specify the file names for these clouds, and even allows the user 

to submit uncertainty runs. 

The percentile scaling and Sobol's method of sensitivity analysis require special two-stage runs. 

However, these are submitted exactly like any other runs. Switches on the RunInfo file indicate 

the type of sensitivity analysis to be performed. Also, the variables input file will indicate which 

variables are being analyzed. The SHEDS GUI now handles these file edits and the submission 

of sensitivity runs, although the user may still submit them in batch mode. 
123

Appendix A. Directories and Files 

All of the directories that SHEDS-Residential uses are placed underneath the installation 

directory which is chosen by the user at install time. By default this is in the user’s My 

Documents/Multimedia3.14 (or similar) directory. The install directory will be referred to as the 

install directory or <install> in the following discussion and diagrams. 

A.1 Directories 

The directories are laid out as follows on installation. The indentation of a directory name 

implies that it is within the directory above it. 

<install> 

 Data 

 Default Default and constant input files

 Diet Currently unused 

 Prg SAS catalogs and macros implementing model 

 Runs All input and output related to specific runs 

Permethrin Case Study All input and output related to the example Permethrin 

Case Study 

 Input User edited files for run 

 Output Results for demonstration run 

 Setup Files related to installation and un-installation 

 

A.2 Critical Input Files 

If using the interface, it is not necessary for the user to know where files are stored. For batch 

runs and advanced post-run analysis it becomes important. The table below shows where critical 

files are placed at installation or when a run is defined through the interface. All files in the 

Runs/<run name>/Input directory are modified by the interface (except the 

contactmedia.sas7bdat dataset). Additional input files (e.g., CHAD diaries) needed for runs can 

be found in the <install>/Data/Default/ directory. 

<install>/ 

 autoexec.sas SAS start-up file. Many SAS options can be 

set here 

 multimedia.bat File used to run SHEDS in batch mode 

 runinfo.sas7bdat File containing run specific information 

generated by the interface 

Runs/<run name>/Input/ 
124

agegroups.sas7bdat Defines age and genders to be used in 

simulation 

areatreated.sas7bdat Fraction of area treated for indoor scenarios 

chemicals.sas7bdat Chemicals present in the run 

chem_distributions.sas7bdat Chemical specific variable distributions as 

defined for run 

scenarios.sas7bdat Information for the application scenarios 

defined in the run 

correlations.sas7bdat Correlation information 

cohorts.sas7bdat Cohort information 

handlers.sas7bdat Required for handler runs 

distributions.sas7bdat Variable distributions as defined for run 

Required for 

Batch Runs 

contactmedia.sas7bdat List of contact media and their short names 

decay.sas7bdat Decay and dispersion application 

information 

intervals.sas7bdat Interval concentration information 

One of These is 

Required 

timeseries.sas7bdat User defined time series concentrations for 

each media 

dates_variable.sas7bdat Data required for model to determine 

stochastic application dates 

One of These is 

Required 

dates_fixed.sas7bdat Data for user defined application dates 

A.3 User Specified Output Files 

The major output files for a typical variability run, their structure, and variable definitions are 

discussed in the SHEDS-Residential Technical Manual. Files related to sensitivity and 

uncertainty runs are discussed in the section on batch runs in this manual. 

If a log file is specified by the user, on the Simulation Information screen, then it is put in 

<install>/Runs/<run name>/Output/saslog.txt. This file can be read in the SAS editor or any 

other editor of the user’s choosing. 

If a user requests a spreadsheet of inputs, on the Run screen, it will be placed in the installation 

directory and named after the run name: <install>/<run name>.xls. This file can be read from MS 

Excel 2003 or later. 
125

A.4 Other Output Files 

A.4.1 Diary Related Output Files 

The number of available one-day activity diaries for each cohort and day type is listed in the file 

“diarycounts” in the \output directory for the given run. 

A.5 Exporting SAS Datasets 

To facilitate additional analyses in the software of your choosing, you may export data in a 

variety of formats. The export wizard can be accessed by selecting a dataset in SAS and then 

selecting Export Data from the main SAS File menu. For more information on the export wizard 

check the SAS help file index under “exporting data/Export Wizard for”. To export data 

programmatically, use Proc Export. Again, information on specifics can be found in the SAS 

help files. 
126

8 References 

Glen G., Zartarian V.G., Smith, L., and Xue J. (2010). The Stochastic Human Exposure and 

Dose Simulation (SHEDS)-Residential Model Technical Manual. Prepared for the July 20-22, 

2010 EPA FIFRA SAP, Crystal City, VA. 

Isaacs K., Xue J., Stallings C., Zartarian V.G. (2010) Stochastic Human Exposure and Dose 

Simulation (SHEDS) Model for Multimedia, Multipathway Chemicals: Version 1 SHEDSDietary Module User Guide. Prepared for the July 20-22, 2010 EPA FIFRA SAP, Crystal City, 

VA. 

Xue J. 2010. SHEDS-Dietary version 1.0 SAS code. 

Xue J., Zartarian V.G., Nako S. (2010). The Stochastic Human Exposure and Dose Simulation 

(SHEDS)-Dietary Model Technical Manual. Prepared for the July 20-22, 2010 EPA FIFRA 

SAP, Crystal City, VA. 
127

Appendix B. Reference Tables 

B.1 Variable Names 

Table B-1. Variable Names From Distributions File 

Variable Label Units 

Gender Gender, M=male, F=female [-] 

Age Age (full years) years 

Weight Body weight kg 

DiaryT Personal mean for DiaryKey ranking [-] 

DiaryA Autocorrelation in diary ranks [-] 

DiaryNums Pool selections for one-day diaries [-] 

DiaryReorder Selections for diary re-ordering [-] 

Height Height in cm cm 

BMR Basal metabolic rate megajoules/day 

BVA Basal alveolar ventilation rate m3/day 

Mets_max Maximum allowed mets mets 

OxyDebt_max Maximum allowed oxygen debt (ml of O2)/kg 

Slope_fast Slope of fast anaerobic process mets/min

Recovery Recovery time for maximum debt hr 

p_Handler Probability of being product handler [-] 

p_Lawn Probability of having a lawn [-] 

p_Garden Probability of having a vegetable garden [-] 

p_Pet Probability of having a dog or cat [-] 

Area_House Floor area of house m2 

Area_Lawn Area of lawn to be treated m2 

Area_Garden Area of garden to be treated m2 

Area_Pet Surface area of pet to be treated m2 

f_Carpet Fraction of indoor time on carpet [-] 

f_Lawn Fraction of out-home time on lawn [-] 

f_Garden Fraction of out-home time in garden [-] 

f_Pet Fraction of time at home near pet [-] 

Background Outdoor background concentration ug/cm2 

Dust_loading Indoor dust loading on floor ug/cm2 

HouseNum House number (for timeseries input) [-] 

HandWash_mean Mean # of hand washings per day 1/day

v_BathDays 

Vector for maximum # days between 

baths days 

v_ReEntry_in Vector for indoor contact prohibition time [-] 

v_ReEntry_out Vector for outdoor contact prohibition time [-] 

v_ReEntry_pet Vector for pet contact prohibition time [-] 
128

v_TimeOfUse_in Vector for indoor application hour hr 

v_TimeOfUse_out Vector for outdoor application hour hr 

v_TimeOfUse_pet Vector for hour of pet application hr 

f_AreaTreated Fraction of house treated [-] 

f_Decay_in Fraction lost per day indoors 1/day 

f_Decay_out Fraction lost per day outdoors 1/day 

f_Decay_pet Fraction lost per day on pet 1/day 

f_UTratio Untreated/treated ratio at Umax [-] 

Treated Fraction of time in treated area [-] 

SurfaceType Fraction of time on various surfaces [-] 

PetContact Fraction of time around pet [-] 

Mets Mets level for inhalation mets 

HandWash Hand washing: 1=yes, 0=no [-] 

SoilIngest Daily soil ingestion rate mg/day 

Dermal_Contact Skin-Surface contact rate 1/hr 

Dermal_TC Surface-to-skin transfer coefficient cm2/hr 

Dermal_TE Surface-to-skin transfer efficiency [-] 

Dermal_MaxLoad Maximum Dermal Loading ug/cm2 

Dermal_Binding Rate of penetration into skin surface 1/hr 

Dermal_BrushOff Fraction removed per hour by brush-off 1/hr 

f_DermalHands Fraction of dermal exposure on hands [-] 

f_Uncloth Fraction of skin not clothed [-] 

f_HandMouth Fraction of one hand that enters mouth [-] 

f_ObjFloor Object-to-floor concentration ratio [-] 

Unit_Handler Unit exposure during handling ug/g 

HandMouth_freq Hand-mouthing events per hour events/hr 

HandMouth_TE Removal efficiency during hand mouthing [-] 

ObjMouth_area Object-mouth contact area cm2 

ObjMouth_freq Object-mouthing events per hour events/hr 

ObjMouth_TE Object-to-mouth transfer efficiency [-]

f_RemovBath Fraction removed during bath or shower [-] 

f_RemovHandWash Fraction removed during hand washing [-] 

f_DermalBlood Fraction absorbed from skin into blood [-] 

f_InhalBlood Fraction absorbed from lungs into blood [-] 

f_IngestBlood Fraction absorbed from GI tract into blood [-] 

f_Urine Fraction of blood dose eliminated in urine [-] 

Freq_Lawn_Granul Usage frequency for Lawn_Granul [-] 

Dates_Lawn_Granul Usage dates for Lawn_Granul [-] 

Amount_Lawn_Granul Amount used for Lawn_Granul [-] 

Freq_Lawn_Liquid Usage frequency for Lawn_Liquid [-] 

Dates_Lawn_Liquid Usage dates for Lawn_Liquid [-] 

Amount_Lawn_Liquid Amount used for Lawn_Liquid [-] 

Freq_Veg_Powder Usage frequency for Veg_Powder [-] 

Dates_Veg_Powder Usage dates for Veg_Powder [-] 

Amount_Veg_Powder Amount used for Veg_Powder [-] 

Freq_CC_Aerosol Usage frequency for CC_Aerosol [-] 
129

Dates_CC_Aerosol Usage dates for CC_Aerosol [-] 

Amount_CC_Aerosol Amount used for CC_Aerosol [-] 

Freq_CC_Liquid Usage frequency for CC_Liquid [-] 

Dates_CC_Liquid Usage dates for CC_Liquid [-] 

Amount_CC_Liquid Amount used for CC_Liquid [-] 

Freq_Ind_FIK Usage frequency for Ind_FIK [-] 

Dates_Ind_FIK Usage dates for Ind_FIK [-] 

Amount_Ind_FIK Amount used for Ind_FIK [-] 

Freq_Ind_Fogger Usage frequency for Ind_Fogger [-] 

Dates_Ind_Fogger Usage dates for Ind_Fogger [-] 

Amount_Ind_Fogger Amount used for Ind_Fogger [-] 

Freq_Pet_Spot Usage frequency for Pet_Spot [-] 

Dates_Pet_Spot Usage dates for Pet_Spot [-] 

Amount_Pet_Spot Amount used for Pet_Spot [-] 

Freq_Pet_Liquid Usage frequency for Pet_Liquid [-] 

Dates_Pet_Liquid Usage dates for Pet_Liquid [-] 

Amount_Pet_Liquid Amount used for Pet_Liquid [-] 
130

Appendix C. Probability Density Functions 

The explicit probability density functions (pdf’s) utilized by SHEDS are listed below. Note that 

some of these may have alternate parametrizations, so the user must be careful when obtaining 

distributions from the literature. The expressions “Exp,” “Sqrt,” “Log,” and “Г” refer to the exponential, 

square root, natural logarithm, and gamma functions, respectively. 

C.1 Beta 

The beta distribution in SHEDS has a lower bound of zero, an upper bound of one, and two shape 

parameters v1 and v2. The restrictions are v1>0 and v2>0. When v1< v2 then the mean is below 1⁄2 and 

the distribution is positively skewed, whereas when v1 > v2 the mean is above 1⁄2 and the distribution is 

negatively skewed. For v1=v2 the mean is at 1⁄2 and the shape is symmetric. The PDF is 

Equation E-1 

p(x) = xv1-1 (1-x)v2-1 Г(v1+v2) / ( Г(v1) Г(v2)), for 0<x<1 

Here ‘Г’ is the mathematical gamma function, not the gamma distribution. The gamma function is a 

generalization of the factorial function to non-integer arguments; for integers, Г(1+n) = n!. The beta is a 

useful form for variables known to be bounded, due to the wide variety of shapes that it can have. For 

v1>1 and v2>1, the PDF of the beta has a single peak, away from the bounds. When 0<v1<=1, the PDF is 

large near zero, and when 0<v2<=1, it is large near one. These properties allow the beta to have the socalled ‘J’ or ‘U’ shapes. The mean of a beta distribution is at μ = v1 / (v1+v2), and the standard deviation 

is σ = Sqrt[v1 v2 / (v1+v2+1)] / (v1+v2). If one wishes to construct a beta with a given mean μ and 

standard deviation σ, then choose v1 = (μ2-μ

3

)/σ

2 -μ, and v2 = v1 (1-μ) /μ. This will only be possible if 

0<μ<1 and σ

2 < μ (1-μ)≤1/4. 

C.2 Exponential 

The exponential in SHEDS has two parameters, the minimum (v1) and the mean (v2), with the 

restriction that v1 < v2. Some users may be more familiar with a single parameter exponential distribution, 

which has a minimum of zero and is characterized by a decay rate constant. The SHEDS exponential is 

similar, apart from a shift of v1 units to the right. The decay rate of the SHEDS exponential is given by 

1/(v2-v1). The standard deviation of an exponential is (v2-v1). If the user wants an exponential with a 

half-life τ, then set v2 = v1+ τ / Log[2] . The PDF of the SHEDS exponential is 

Equation E-2 

p(x) = Exp[-(x-v1)/(v2-v1)] / (v2-v1), for x>v1 

C.3 Gamma 

The gamma distribution in SHEDS is bounded below by zero and has two parameters, the shape 

parameter v1 and the scale parameter v2. The restrictions are v1>0 and v2>0. The shape parameter v1

controls the appearance of the PDF. Shape parameters less than one lead to a monotonically decreasing

form with the highest probability at zero. If v1=1, then the gamma is identical to an exponential that starts 
131

at zero and has a mean given by the gamma parameter v1. If v1>1, then the gamma somewhat resembles 

the lognormal, rising from zero to a peak probability, and then gradually declining with an overall positive 

skewness. The mean of the gamma is at μ = v1 v2, and the standard deviation is σ = v2 Sqrt(v1). The 

PDF of the SHEDS gamma is 

Equation E-3 

p(x) = v2-v1 x

 v1-1 Exp(-x/v2) / Γ(v1), for x>0 

C.4 Lognormal 

The lognormal in SHEDS is bounded below by zero and has two parameters, the geometric mean 

GM (v1) and the geometric standard deviation GSD (v2). The restrictions are v1>0 and v2>1. Many 

variables in exposure science are approximately lognormally distributed, so its use is fairly common. If a 

variable ‘x’ has a lognormal distribution, then log(x) has a normal distribution. 

The geometric mean (GM) of a lognormal distribution is also its median. Log(GM) is the mean of 

the distribution of log(x). Log(GSD) is the standard deviation of log(x). Since standard deviations must 

be positive, then Log(GSD)>0, which implies GSD>1. The PDF of the SHEDS lognormal is 

Equation E-4 

p(x) = Exp[(-1/2) (Log[x/v1] /Log[v2])2 ] / (x Sqrt[2 π ] Log[v2] ), for x>0 

If GM and GSD are given, then the lognormal has arithmetic mean and standard deviation 

Equation E-5 

μ = GM Exp[(1/2) (Log(GSD))2 ], 

σ = GM Sqrt[Exp( [Log(GSD)]2) (Exp( [Log(GSD)]2)-1)]. 

If the user knows the arithmetic mean μ and arithmetic standard deviation σ of the lognormal 

instead of the GM and GSD, then these can be converted as follows: 

Equation E-6 

GM = μ / Sqrt(1 + σ

2

 /μ2), 

GSD = Exp(Sqrt(Log(1 + σ

2

/μ2 ))). 

If instead, one has the mean μlog and standard deviation σlog of log(x), then use 

Equation E-7 

GM = Exp(μlog), 

GSD = Exp(σlog). 

C.5 Normal 

This is the normal or Gaussian distribution commonly used in statistics. The normal has two 

parameters: the mean (v1) and the standard deviation (v2), with v2>0. Note that the normal is unbounded, 

so it is a good idea to provide lower and upper truncation points to prevent physically impossible values 

from being returned. The PDF of the normal is 
132

Equation E-8 

p(x) = Exp[-(x-v1)2/(2 v22)] / (Sqrt[2 π] v2) 

C.6 Point 

A point value means that the same value is always returned. This is sometimes called a fixed or 

constant form. The point has one numeric argument (v1) which is the value that is to be returned. The 

mean is v1 and the standard deviation is zero. The sampling frequency does not matter for points. While 

points are technically discrete, here they are classified with the continuous distributions since they are 

applied to variables that are expected to reside on a continuous scale, but happen to be assigned no 

variability. 

C.7 Triangular 

The triangular distribution has a probability density function (PDF) that is shaped like a triangle. 

The three parameters locate the vertices, with v1=minimum, v2=peak, v3=maximum. The restrictions are 

v1<= v2 <= v3, with v1<v3. The mean value of this distribution is located at μ = (v1+v2+v3)/3, which

coincides with the peak only when v2 is midway between v1 and v3. The standard deviation is σ = 

Sqrt[(v12+v22+v32-v1v2-v1v3-v2v3)/18]. It is possible for the peak to be located at either extreme, 

forming a right triangle. The PDF of the triangular is 

Equation E-9 

p(x) = 2 (x-v1) / [(v2-v1) (v3-v1)], for v1≤ x ≤ v2 

 = 2 (v3-x) / [(v3-v2) (v3-v1)], for v2 ≤ x ≤ v3 

C.8 Uniform 

The uniform is characterized by two parameters, the minimum (v1) and the maximum (v2), with 

v1<v2. All values between v1 and v2 are equally likely to be returned. The mean is μ = (v1+v2)/2 and the 

standard deviation is σ = (v2-v1) / Sqrt(12). The PDF of the uniform is 

Equation E-10 

p(x) = 1 / (v2-v1), for v1 < x < v2. 

C.9 Weibull 

The Weibull distribution in SHEDS is bounded below by zero and has two parameters, the shape 

parameter v1 and the scale parameter v2. The restrictions are v1>0 and v2>0. The Weibull has slightly 

different properties from a gamma, but there is a strong overall resemblance. When the shape parameter 

v1 ≤ 1, the Weibull is monotonically decreasing. For v1=1, it reduces to an exponential. For v1>1, it rises 

to a peak and then declines gradually in a long tail. The mean is μ = v2 Г(1+1/v1), and the standard 

deviation is σ = v2 Sqrt[Г(1+2/v1) – (Г(1+1/v1) )2]. Here ‘Г’ is the mathematical gamma function, not 
133

the gamma distribution. The gamma function is a generalization of the factorial function to non-integer 

arguments; for integers, Г(1+n) = n!. The PDF of the Weibull distribution is

Equation E-11 

p(x) = v1 v2-v1 x

v1-1 Exp [-(x/v2)v1], for x>0. 

C.10Binomial Distributions 

Binomial distributions have only two possible outcomes, for example, the outcome of yes/no tests. 

The usual statistical notation would be (p1, p2), where p1 and p2 are between 0 and 1 and sum to 1. 

However, the SHEDS code implements binomial distributions by having the user specify only the 

probability of a “yes”. The probability of “no” is implied by 1 - “yes”. 

C.11Discrete Probability Density Functions 

Multinomial variables allow more than two possible outcomes. The usual statistical notation would 

be (p1, p2, ..., pn), where each pi is between 0 and 1 and the pi’s sum to 1. In SHEDS, multinomial 

variables are called probability vectors. The user must supply the entire set of probabilities.