# The S tochastic H uman E xposure and

D ose Si mulation Model for Multimedia, Multipathway Chemicals (SHEDS-Multimedia):Residential Module

SHEDS-Residential version 4

Draft User Guide

June 16, 2010

Prepared by: Kristin Isaacs 1 

### , Casson Stallings 1 

### , Valerie Zartarian 2 

### , and Graham
Glen 1

1 Alion Science and Technology 2 US Environmental Protection Agency, Office of Resea rch and Development, National Exposure Research Laboratoryi 

# 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 Permethr in............................................. 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 ........ .................................................. 2 4 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 .........................

................................................... .... 29ii

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 Applicat ion Dates................... 35 5.5.3 Dermal Exposure Method....................... ................................................. 36 5.5.4 Diary Assembly Method........................ .................................................. 3 6 5.5.5 Simulate Product Handlers.................... .................................................. 3 7 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 .................... .................................................. 5 1 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 ...... .................................................. 6 1 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............. ................................................. 74iii 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.............. .................................................. 8 2
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 Sen sitivity 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................... ................................................. 12 5 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........................

................................................... ............. 133iv

C.11 Discrete Probability Density Functions ........

................................................... ... 133v 

# LIST OF FIGURES

Figure 2.1. Overview of the SHEDS-Residential Inter face at Version 4.................................. ...... 8 Figure 2.2. Example of List Box with a Blue Backgro und Indicating There are More Groups to Complete...........................................

................................................... ................................... 9 Figure 2.3. Sample of Two Buttons, One Normal and O ne Grayed Out (Bottom)......................... 9 Figure 2.4. Specify Application Times Screen Contai ning a Probability Vector. ........................ 1 0 Figure 2.5. Example Distribution Widget............

................................................... ...................... 13 Figure 2.6. Example Empirical Data File and File Sp ecification in the Distribution Widget. ..... 14 Figure 2.7. Example Uncertainty Dataset and File Sp ecification 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 a n 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 Scali ng 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 C hemical. ........................................... ...... 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 S creen. ............................................. ............. 46 Figure 5.20. Specify Chemicals in Scenario Screen. .

................................................... ................ 47 Figure 5.21. Specify Application Dates Screen for M odel-Determined Application Dates. ........ 48 Figure 5.22. Specify Application Dates: User Specif ed Screen.......................................... .......... 49 Figure 5.23. Specify Co-Occurrence Screen..........

................................................... .................... 50vi

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

................................................... .................. 51 Figure 5.25. Specify Fraction of Area Treated Scree n.................................................. ................ 52 Figure 5.26. Specify Re-entry Times Screen .........

................................................... .................... 53 Figure 5.27. Specify Decay and Dispersion Distribut ions for an Indoor Scenario. ...................... 5 6 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 Dis tributions 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 Variabl es are Selected for Correlation. .................. 6 9 Figure 5.39. Error Displayed if No Variable Pairs a re Selected for Correlation. ....................... .. 69 Figure 5.40. Specify Variable Correlations Screen..

................................................... .................. 70 Figure 5.41. Run Simulation Screen for an Uncertain ty Run. ............................................ .......... 71 Figure 5.42. The Run Progress Screen for a Variabil ity Run. ........................................... ........... 72 Figure 5.43. Log Screen after Running a Small Simul ation. ............................................. ........... 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 Pl ot................................................. ........... 80 Figure 5.49. Example Pie Chart Showing the Contribu tion 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 I ndividual. ......................................... ........ 87 Figure 5.54. Example Pie Chart Showing the contribu tion by pathway for an individual. .......... 88 Figure 5.55. Example Detailed Table for an Individu al................................................. ............... 89 Figure 5.56. View Uncertainty Results Screen. ......

................................................... ................... 90 Figure 5.57. Plotting the 5 th , 50 th , and 95 th Percentiles of Each Uncertainty Repetition........ ....... 91 Figure 5.58. Plotting the CDFs from Uncertainty Rep etitions whose Medians are at the 5 th , 50 th

, and 95 th Percentiles. ......................................

................................................... ..................... 92 Figure 5.59. View Sensitivity Results Screen.......

................................................... ..................... 93 Figure 5.60. Sensitivity Results for a Percentile S caling Run. ........................................ ............. 94 Figure 5.61. Sensitivity Results for a Sobol Analy sis Run............................................ .............. 95 Figure 5.62. Sensitivity Results for an Input-Outp ut Correlation Run. ................................ ....... 96 Figure 5.63. Example Diary Pool Size Table.........

................................................... .................... 97vii 

# 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..

................................................... ............. 127viii



## Acknowledgements

We would like to thank our colleagues in EPA’s Offi ce 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 scr oll down to see all of some dialogs. Refer to the images in this User Guide to ensure that all compon ents of a dialog are displayed.

It is highly recommended that the user pause or dis able 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 u p. Such programs may access SHEDS data files and interfere with model performance, causing unpredictable results.

Disclaimer
EPA's SHEDS-Residential version 4 model can simulat e cumulative (multiple chemicals) or aggregate (single chemical) residential exposures o ver time via multiple routes of exposure for different types of chemicals and scenarios. The Uni ted States Environmental Protection Agency, through its Office of Research and Development, dev eloped and funded SHEDS-Residential
version 4 with assistance from contractor Alion Sci ence and Technology, Inc.

SHEDS-Residential version 4 is one module (along wi th the separate SHEDS-Dietary module) of EPA’s more comprehensive human exposure model, the Stochastic Human Exposure and Dose Simulation model for multimedia, multipathway chemi cals (SHEDS-Multimedia), which can simulate aggregate or cumulative exposures over tim e via multiple routes of exposure (dietary & non-dietary) for different types of chemicals and s cenarios. SHEDS-Residential and SHEDSDietary will be merged together in a future version of SHEDS-Multimedia.

SHEDS-Residential version 4 includes a case study e xample 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-Residenti al model for a given application should be entered or reviewed by the researcher so that the m odel results are based on appropriate data sources for the given application.

Version 4 of SHEDS-Residential reflects comments fr om EPA's August 2007 external Scientific Advisory Panel that reviewed SHEDS-Multimedia versi on 3 (the aggregate residential version). SHEDS-Residential version 4 will undergo external p eer 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 wit h any questions, comments, or specific suggestions related to this beta version of the SHE DS model:

Dr. Valerie Zartarian, (617) 918-1541, zartarian.va lerie@epa.gov Dr. Jianping Xue, (919) 541-7962, xue.jianping@epa. govx 

# 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 Simulati on ug (in SAS printout or variable names) – microgram1 

# 1 Considerations for New Users of SHEDSResidential

1.1 Introduction

SHEDS-Residential version 4 (also referred to in th is user guide as ‘SHEDS’) is a sophisticated but user-friendly cumulative and aggregate human ex posure 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 inve st time to configure this model to exposure scenario(s) of their choice. Before attempting to r un 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 Gu ide, Technical Manual, annotated SAS code for use via the graphical user interface (GUI) , Consolidated Human Activity Database (CHAD) activity diary and population files, a heigh t/weight data set, and default input distributions. The installation process is explaine d in this User Guide, which is intended to guide the user through the GUI. The interface has three f unctions: specifying inputs, executing the model, and storing and viewing the results. The Tec hnical Manual contains a detailed description of the model’s structure and algorithms

.

The SHEDS model runs on a personal computer and req uires 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 W indows 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 Carl o) run takes about 1 hour for every 1000 persons being simulated and a typical run may be se veral thousand persons. Uncertainty (2-stage Monte Carlo) runs are much slower and may take seve ral days to complete.

SHEDS is a stochastic model in which each simulated individual is different. There are approximately 100 variables that can be sampled ran domly 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 through out the simulation period. Increasing the number of simulated individuals provides a better c haracterization of the population under study.

SHEDS separately constructs time series for the env ironmental concentrations in each simulated person’s house, as well as an activity sequence thr ough time based on the selection of human activity diaries from EPA’s Consolidated Human Acti vity Database (CHAD; http://www.epa.gov/chadnet1). These are combined, u sing exposure pathway-specific equations and exposure factors sampled from user-specified di stributions, to generate a time series of exposure for each simulated individual. The time st ep is variable and depends on the event duration from the activity diaries, ranging from on e minute to one hour. Therefore, a 1-year2

simulation will have a very large number of such ev ents (generally 10,000 to 20,000) for each simulated person. These results are automatically a ggregated over time to produce (for example) daily exposure totals, although for some purposes t he finer time resolution may be useful. Due to their size, the event-level exposure time series ar e not usually saved as permanent output; as a rule only summary statistics on daily and longer pe riods are saved.

SHEDS does not attempt to model the exposures of pa rticular individuals. Instead it randomly creates a population of simulated individuals who c ollectively 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 exces s of ...’, but it is not appropriate to say that a specific real-world individual receives any particu lar exposure.

SHEDS has a graphical user interface (GUI) that gui des the user through the various input
screens. The GUI comes with a demonstration scenari o. 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 ch emicals 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 permit s the use of co-occurrence factors that
control the likelihood of the various scenarios bei ng applied at the same house at the same time. The human exposure results are automatically aggreg ated 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-sp ecified distributions. SHEDS accepts a wide variety of continuous distributions as detaile d 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 (pr obability vectors) the user enters the probability
of each outcome.

The GUI will highlight invalid choices with a yello w background. This usually results from numeric parameters being specified that are incompa tible with the type of distribution. For example, the lognormal distribution requires a geom etric mean greater than zero and a geometric standard deviation greater than one. A missing num eric 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 genera tion produces values outside these limits3

then the values are automatically reset to the maxi mum 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 popu lation, the simulation period, the chemical and application method(s) of interest, and the distribu tions for many model parameters. As an example, SHEDS supports three methods of determinin g the chemical concentrations: usersupplied time series, a decay/dispersion model base d 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 i nput distributions for demonstration purposes, to help orient users in how to run the mo del. These values can be used as a starting point for becoming familiar with the GUI, or modifi ed by the user as appropriate.

SHEDS is designed to estimate human exposure in a r esidential setting, but is not geared to any specific chemical. The user customizes the model r un 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-determ ined 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 ex ample, 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 "simulat ion period" is the user-specified time over which the exposure is tracked for each simulated in dividual. 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-se ries data, then the period is limited to the
extent of this data. Note that SHEDS version 4 doe s 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 lon ger run times.

SHEDS calculates exposure from several different pa thways. If desired, the user may restrict the model to selected pathways by judicious specificati on of inputs. For example, ingestion of chemical via object mouthing can be "turned off" si mply 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 absorp tion, 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 distr ibutions for each run would then reflect the variation within the given region (but not across r egions). For example, pesticide usage may
differ in warm and cold climates. Seasonal variati on 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 i mportant for understanding health risks from chemicals. The Stochastic Human Exposure and Dose Simulation model for multimedia, multiroute/pathway chemicals (SHEDS-Multimedia), de veloped by EPA's Office of Research and Development (ORD), National Exposure Research L aboratory (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 sim ulating human exposures to a variety of multimedia, multipathway environmental chemicals su ch as pesticides, metals, and persistent bioaccumulative toxins. Exposure is defined in SHE DS-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 t he 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-Resid ential 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, plea se 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 rathe r than "SHEDS-Residential."

SHEDS-Residential is a physically-based, probabilis tic 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 activ ity data (e.g., from time/activity diary surveys and videography studies), environmental res idues and concentrations, and exposure factors to generate time series of exposure for sim ulated individuals. One-stage or two-stage Monte Carlo simulation is used to produce distribut ions 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-concentrati on module; user-entered time series from other models or field study measurements) for obtaining c oncentration inputs and dose outputs (SHEDS-Residential has a built-in simple pharmacoki netic (PK) model, and SHEDS-Residential exposure outputs can be used as inputs to physiolog ically-based pharmacokinetic (PBPK) models).

For a more detailed technical description of the SH EDS model, please refer to the SHEDSResidential version 4 Technical Manual. The purpos e of this User Guide is to assist the SHEDSResidential user in navigating through the graphica l user interface to apply SHEDS-Residential. Figure 2.1 provides an overview of the SHEDS-Reside ntial user interface. Differences between
the Version 3 interface and Version 4 are noted. T he major interface screens are each represented with one box; not all screens are repre sented in Figure 2.1 (page 8). In general, the6

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 depen ding on the type of run being defined and data required for that run. Typically, the interfac e 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 thes e screens contain default choices, or choices from a previous model run, that the user ma y either edit or accept. The best way to run SHEDS is to carefully prepare the inputs for an ini tial 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 rev isited 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 co efficients. Likewise, if the decay and dispersion module is being used to model media conc entrations, 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 w ith a completed sample run. This sample run is named “Permethrin Case Study” and is meant t o 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 longi tudinal 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 typi cal production run will require substantially more individuals. Chapter 6 of the manual instruct s the user how to re-create this run from
scratch.

The results from the file are available on installa tion and can be viewed by selecting the View Results of Selected Run button on the Specify Run N ame 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 t he original Permethrin Case Study . To view and edit inputs from the demonstration, g o to the Specify Run Name dialog (described on page 26), highlight “Permethrin Case Study”, and click on Copy Selected Run To7

New Run. You will be prompted for a new run name. A fter entering the run name and visiting the Run Files screen you will be free to make any d esired changes without affecting the original Permethrin Case Study.8Define Correlated Input VariablesSpecify Inputs for Variable GroupsSpecify Concentration-Related Inputs (Repeat for each Scenario)Specify Run NameSpecify Population andSamplingMainSpecify SimulationInformationRun SimulationView ResultsSpecify FilesNew or Copied Run(if needed)SpecifyScenarioApplicationTimesFraction ofIndoor AreaTreated(IndoorScenarios)Specify Inputs for Scenario (Repeat for Each Scenario)Specify CoOccurrence(if needed)Application Dates:User SpecifiedApplication Dates:Model SelectedSpecifyScenario DetailsVariability DistributionsEdit Distributions (Activity-,Dose-, Transfer-, RemovaRelated)Specify VariableCorrelationsSelect CorrelatedVariablesTime Series InputsBackgroundConcentrationDistributionsSpecify ChemicalsSpecify ChemicalDetailsModel DatesUser DatesScenarioApplicationRe-entryTimesIntervalConcentrationDistributionsDecay-DispersionIntervalsTime SeriesDecay andDispersionDistributionsHandlerDistributions(if needed)SpecifyChemicals inScenario(if cumulativerun)Specify General Exposure and DoseFactorsRun SHEDS Dietary(Future Implementation)BathsModel DatesUser DatesRun ProgressNew screen for V4Unchanged from V3Updated for V4Chemical-specific screenIndividual ResultsPopulation VariabilitySensitivity SettingsSensitivity ResultsUncertainty ResultsFigure 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 roo m 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 di splay to the appropriate figure in this manual. The easiest meth od 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 bot tom 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 necess ary.

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 continuin g. In these cases, the groups are listed on the left and all completed groups are listed on the rig ht. If the groups remain uncompleted, the completed list is highlighted in a light blue (Figu re 2.2). Another reason a button may be grayed out (Figure 2.3) is due to a current error on the s creen. 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 h ighlighting and often accompanied with a more specific error message.

2.3.3 Entering Probability Vectors There are a number of places in the interface wher e probability vectors must be entered. These are used to enter probabilities associated with a s et 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 S pecify 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 t he treated area. Each probability vector is composed of:

• A container box with a descriptive title. In this c ase 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 mess ages may be displayed; and

• An OK button used to validate the entry.

Each text box must contain a probability, thus a nu mber between 0 and 1 inclusive. The total of all probabilities must sum to one. The user can en ter 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 highlighte d in yellow. If there are errors with individual probabilities or with the sum of probabi lities, the user will not be allowed to continue
to the next screen. The errors must be corrected an d 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 Contai ning a Probability Vector.11

2.3.4 Distributions Supported

Since the SHEDS-Residential model is a stochastic m odel, 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 n ames, and rules for the parameters are given in
Table 2-2. Detailed information on the distribution s 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 t o 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 the13

Edit Variables screen which also includes visualiza tions 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 a rrow 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 e ither 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 maximu ms 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 t he OK button to force validation and clear errors. In some contexts specific error messages will be di splayed.

2.3.5.2 Entering Empirical Distributions

The “Empirical” distributions type is new for Versi on 4. This feature allows the users to define an empirical distribution via a list of measurement s, rather than using a continuous probability distribution. Empirical distributions are contain ed 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 exis t. An example of an empirical data file and its file specification in the distribution widget for t he variable fraction of skin unclothed are shown in Figure 2.6. When this type of distribution is u sed, 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, 1 2.5% are 0.2, and 12.5% are 0.4.

1 Distributional parameters do not reflect the effe cts of truncation. Figure 2.5. Example Distribution Widget.14

Figure 2.6. Example Empirical Data File and File Sp ecification 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 run s and will not be visible for other types of runs. This feature allows the user to define a set, or “c loud” of distributions for a variable, one of which is then selected for use (with equal probabil ity) for each uncertainty repetition. See the
SHEDS Technical Manual for more information about u ncertainty runs.

The uncertainty distributions must be contained wit hin a SAS dataset, one distribution definition per row. Thus, it is helpful for the user who util izes this feature to have some knowledge of how
to create and edit SAS datasets. Each of the distr ibution definitions (each row) must contain a valid distribution form (Point, Uniform, Normal, Lo g Normal, Triangle, Exponential, Gamma, Binomial, Beta, Weibull, Empirical), and the requir ed parameters as defined in Table 2-2. The parameters are given the names V1-V3. Thus for a b eta distribution, v1 and v2 (shape1 and shape2) must be defined. Optionally, each distribu tion may contain a maximum and minimum (“maxval” and “minval”) values. For “Empirical” di stributions, the filename of the empirical data file is contained in the “empfile” variable.

The user creates the uncertainty dataset outside SH EDS, 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 valid15

uncertainty distribution dataset and its dataset sp ecification in the distribution widget are shown in Figure 2.7. These data are strictly for demonstr ations and are not meant to represent the value of any real variable.

Figure 2.7. Example Uncertainty Dataset and File Sp ecification 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 c omputer running 32-bit SAS version 9.1 or higher. A version of SHEDS for 64-bit SAS is avail able 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 wher e 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 dis able any automated antivirus or back-up programs that access the SHEDS ins tallation or data output directories, or place these directories in locations that are not v irus-checked or backed up. Such programs may access SHEDS data files and interfere with mode l 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 f iles on the CD. Double click on the SHEDS_Multimedia_Setup.exe file to initiate the installation. The installation may have version numbers after the “Se tup”. For instance ...Setup_4.14.exe.

3.2.2 Starting with a Downloaded File
You may obtain the setup file via FTP or another el ectronic means.
1. Save the attachment to a local or network hard driv e. 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 f ile.
3. Double click on the saved file to start the install ation.

3.2.3 The Standard Installation Process
Once the installation wizard is initiated, simply f ollow 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 i nterface within SAS. The program group will contain an additional shortcut (menu item) to unins tall the model and program data.

The screens encountered during install, and an expl anation 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 Multim edia 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. D ouble click on the icon (figure at right) to start SAS and the main screen of the S HEDS Interface.

3.2.5 Removing SHEDS-Residential
If SHEDS was installed using the installation wizar d, 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 sa ved 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 fi ne-tuning capabilities that are usually not necessary for typical model use. The average user m ay still find a brief review of this section
useful. If the user is unfamiliar with SAS and wish es to explore raw datasets used by the model,
then it is recommended the user read this section m ore carefully.



## 4.1 The SAS Screen

Assuming one uses the link in the MS Windows Progra ms menu or the screen icon to start the model, the main GUI screen will start inside the ma in SAS window (Figure 4.1). By default, the SAS log window will not open when the program start s, but can be opened by selecting View-> Log on the SAS toolbar.

The SAS window is split into a number of distinct a reas. 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 a ctivate a different window. In Figure 4.1, the main SHEDS screen is active as can be seen by the c olored 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, info rmational and error messages will be displayed in the log window. The pull-down menus ar e on the top of the screen, just under the title. The toolbar is below this. At the very botto m of the SAS window is a status bar, which will contain help text for many interface features as th e 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 g enerated 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 gen erally locked on the left side of the SAS
window. If additional windows are locked in this ar ea, they are accessed with tabs that appear below. The Results window may be used to navigate a mong the different outputs. However, it will not open the output or graph windows; this mus t be done manually.

The Explorer window (Figure 4.4) is used to navigat e through SAS libraries and files, data sets, forms, and programs. It can be used to access the r aw 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 are a. This screen may be toggled between tree mode (shown) and a single pane, similar to MS Windo ws 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 encounte r 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 Cu mulative 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 retur ned to after completing each main step. It contains the following buttons. Figure 5.1. The SHEDS Mode Screen25

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 pe ople 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-concen tration approach, and a number of other global simulation v ariables.

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 t he 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 pr oper 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 Fi les). Buttons that are not enabled are displayed with a gray tint to the font. The initial ly enabled buttons are Specify Run Name and
Files and Exit.

Before beginning to specify the inputs for a new si mulation run, editing the inputs for an existing simulation, or viewing the results of a previous ru n, 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 a nd 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 but tons 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 kee ps together all the information specific to a simulation. In technical terms, it relates to a dir ectory 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 editi ng. 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 o utput 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-sub mitted.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 simulati on runs. The currently selected run name is highlighted in this box. Below the list box, the de scription 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 cr eating 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 i s willing to overwrite the previous inputs and the resulting output. When becoming familiar with t he model using the Demonstration Permethrin Case Study it is recommended that you us e 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 th is 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 S pecify Files Dialog and allowed to edit
information there. As distinct from the “Edit Selec ted 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 valuesprovided 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 e nter 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 (immediatel y 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 t he 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 curr ent run name and run directory. The run directory should be similar to the run name, but al tered 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 st ored.

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

The “Cancel” button will leave the dialog without s aving any changes. The user will return to the Specify Run Name Dialog. The “Save” button will sav e any changes, and return the user to the
main menu.

When the Specify Files dialog is initialized, the S AS libraries are also set up for the simulation run or simulation results. If setup was for some re ason not carried out correctly upon installation, various errors may occur at this point. In this cas e, 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, uncertaint y runs, and three types of sensitivity analysis runs: percentile scaling, Sobol’s method, and inpu t-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 app ears (Figure 5.8) that allows the user to specify the number of uncertainty repetitions that are goin g to be performed. When either “Percentile Scaling” or “Sobol’s Method” is selected, an additi onal 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 req uires no additional input; see the Technical Manual for details of this type of sensitivity anal ysis.

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 s tudies (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” butt on, 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 diari es being available for certain age groups, day types etc. If this happens, an error will be writt en 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 sensitivi ty runs, some additional input is required by
the user. This information is entered on one of tw o 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 scree n shown in Figure 5.11 appears when “Sensitivity Settings” is clicked. This screen con tains 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 Scali ng Method.

Note that selecting more variables for analysis res ults in a longer SHEDS run. The total number SHEDS variability repetitions that will be performe d in a Percentile Scaling run is 2N+1, where N is the number of variables selected. The percent ile method performs a baseline run plus two runs for each variable analyzed: one with the varia ble 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 sh own in Figure 5.12 appears when “Sensitivity Settings” is clicked. This screen con tains a list of all the variables in the run whose sensitivity can be examined. The purpose of this s creen 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 ass ign to each group by highlighting a group, then highlighting one or more variables in the “Variable s 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 “Cont inue” 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 performe d in a Sobol Analysis run is 2N+2, where N is the number of Sobol groups defined. Thus performin g 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 gr oups, which perhaps could eliminate a large34

number of variables as being non-influential, and i dentify a subset of important variables. Then further runs could be performed that examine the va riables contained in the influential groups more completely. See the SHEDS Technical Manual fo r 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. Cl icking the “Save” button commits any changes. The “Cancel” button prevents changes from being sav ed.35

5.5.1 Simulation Length

The box labeled “SIMULATION START AND LENGTH” allow s the user to specify the beginning date (month, day, and year) and the numbe r of days the simulation will track each individual. One common choice of simulation period is to start on January 1 st 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 exercis ed when specifying very long periods as they take longer to run and the model does not alter man y personal variable settings (including age) over the simulation period.

5.5.2 Source-To-Concentration Approach and Application Da tes There are three options to generate residues and co ncentrations 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 me dia. The concentrations on the media are determined by distr ibutions 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 applicatio ns. Additionally, background distributions can be defined for the various media when Decay/Dispers ion is used.

The Interval Distributions selection will require t he user (in subsequent screens) to enter
distributions of relevant media residues and concen trations 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 conce ntrations for each medium of interest (e.g., from a measurement study or outputs from an externa l source-to-concentration model).36

If either Decay/Dispersion or Interval Distribution s are chosen, a box will appear (to the right of the Source-To-Concentration radio box in Figure 5.1 3) that allows the user to specify whether the application dates will be User-Specified or Model-D etermined. Details will be input on subsequent screens. For user-specified dates, the u ser will enter specific day numbers for each application type, where day 1 is the first day of t he simulation period. Applications will always occur on the dates given. For modeled dates, the u ser will specify probability vectors for month, day of week, number of applications, and time of ap plications.

5.5.3 Dermal Exposure Method
For dermal exposure, the user can select the Transf er Coefficient approach or the Transfer Efficiency approach. These two methods are describ ed in the SHEDS-Residential version 4 Technical Manual. Changing this value on a previous ly defined run will result in the user having to visit the Specify General Exposure and Dose Inpu ts screen to define related variables.

5.5.4 Diary Assembly Method

SHEDS-Residential version 4 allows the user to sele ct 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 databas e based on an algorithm that reproduces certain population statistics, diversity (D) and da y-to-day autocorrelation (A), for a key diary variable relevant to exposure for the pollutant bei ng studied. If this option is selected, the user must provide target D and A values for the populati on, 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 mode l persons who specifically handle the chemical of interest in their own home (not profess ional applicators). If this options is selected, the user will be required to enter additional infor mation 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 modele d, 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 expo rt 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 d irectory, 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 simula tion run, the user can click on “Write to Log File” which saves the log to a permanent file outsi de SAS, thus ensuring the log is saved even if SAS crashes during the run. With this option the st andard SAS log screen is not used, so the user cannot track the progress of the run during executi on.

If the log file is not saved, a line of output is w ritten 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 wit h a text editor from time to time to check the status of the run. The name of the log file is fixe d. 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 mode l. 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 s creen (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, carbamat es, or metals.

The user selects the chemicals to include in the ru n by clicking on the name of the chemical in the Select Chemicals list. Highlighted chemicals ar e 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 sele ct 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) co mpletely from scratch, rather than base their simulation on the defined SHEDS default data for pe rmethrin. 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 w ith the
default Permethrin data. Thus the user must carefu lly update any input distributions for their new chemic al to
reflect their own data.

5.6.2 Specify Chemical Information

Once the user completes the Specify Chemicals scree n, 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 metabol ite of the chemical being studied.

• Chemical/Metabolite mass ratio. The ratio of the c hemical mass to that of its bioactive
metabolite.

• NOAELs. The user must enter the No Adverse Effect L evels (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; t he user clicks on each chemical in turn and
enters the data. The user can not move onto a diff erent chemical if there is an error in the data for the current chemical; in this case the error wi ll 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 entir ety 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 visit ed:

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 ea ch scenario and is used to get to the Application Dates and Co-Occurrence screens for eac h scenario. Specify Application Scenario Details (Figure 5.19)

These screens are visited once for each scenario, a fter which the user is returned to the Specify Exposure Scenario Details screen:

Specify Chemicals in Scenario . (Figure 5.20). This screen only available when SH EDS 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 applicat ion 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 Applica tion Scenario Details screen takes the user to these screens. They are visited once for each simul ation.

Specify Application Times (Figure 5.24. Only visited when model-determined application dates are used.)

Specify Fraction of House Treated for Indoor Scenar ios (Figure 5.25)

Specify Re-entry Times ( Figure 5.26 )

5.7.1 Specify Application Scenarios
The specific scenarios or applications to be simula ted are specified on this screen (Figure 5.17). In the later screens, additional information will n eed to be entered for each scenario defining the probability, dates, and co-occurrence of applicatio ns, fraction of indoor area treated, and re-entry times. The exact screens visited will depend on opt ions chosen by the user. If the user is becoming familiar with the interface, it is recomme nded that only one or two scenarios be
chosen.

This screen will not be shown (the button on the ma in screen will be grayed out) if the UserSpecified Time Series was chosen as the source-to-c oncentration method. If the user is simulating a multimedia measurements study then spe cific applications are not specified.

Each scenario chosen is assigned a priority. The pr iority becomes important when application cooccurrence is of interest. That is, when one is int erested 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 av ailable in SHEDS. These appear in the Scenario Library. The available scenarios and thei r 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 exposur e equations that are used, and thus the appearance of future screens and the information th e 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 scenari os 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 scenari os are prioritized from top (1st) to bottom in
the Selected Scenarios list. Click on a scenario de scription to select it. Use the up and down arrows on the right to change the priority of the s elected scenario. Clicking on the “Delete Selection” button will delete the currently selecte d scenario from the Selected Scenarios list. When all desired scenarios are selected and priorit ized, 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 byclicking 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 th e 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 c licking 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 s cenario’s dates (not active for the scenario that is first in the priority list).
3. Click the Specify Inputs button to proceed to scree ns 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 an d co-occurrence are acceptable, the user is not required to edit these values.

When using model-determined dates, the scenario’s p robability and co-occurrence status are displayed. The Application Probability is the proba bility 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 th e dates of application for each scenario, and this presupposes that the simulated population is restri cted 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 meeti ng 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 pr ofiles 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, th e “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 bo x. If Specify Parameters is selected, then the application dates of other scenarios will be al lowed to influence the application dates of this scenario. Selecting this here will cause the “Speci fy Co-Occurrence” screen to be displayed at the appropriate time.

Once the application, handler, and co-occurrence in formation is entered for a particular scenario, the user may click on the “Specify Inputs” button t o 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 use r 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 sc enarios. Clicking on the Continue button will take the user to the Specify Re-entry Times and pos sibly the Specify Application Times screens.46

Figure 5.19. Specify Application Scenario Details S creen.

5.7.3 Specify Chemicals in Scenario

In SHEDS, not all chemicals in a run need be presen t in all scenarios. In this screen (Figure 5.20) the user specifies which of the chemicals inc luded in the simulation are present in the current scenario. At least one chemical must be pr esent in the scenario, (otherwise, the scenario
should not be included in the run since it has no i nfluence 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 si ngle-chemical run is being performed in Cumulative mode, the user will visit this screen bu t only one chemical will be available for
selection.

The user selects the chemicals for the current scen ario (the name of which will be included on the third header bar) by simply clicking in the Chemica ls selection box. The user can remove a previously selected chemical via the Delete Selecti on 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 use d, 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 a pplication 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 M odelDetermined 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. Al l 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 th e 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. Onl y 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 application s from scenarios with higher priority “previous” applicati ons. In the model code, the dates of the previous applicati ons will be determined first. Here "previous" refers t o 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 Specif ed 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 SimulationInformation 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 da tes 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 inf luence width of previous applications. This obviously has no effect for those days whose probab ility is already 0. The influence factor, also called the co-occurrence probability is discussed a nd illustrated in the “Application Dates and
Co-occurrence” section of the Technical Manual.

If the influence factor exceeds one, then the likel ihood of the current scenario happening near in time to a previous scenario is increased. If the i nfluence 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 c urrent scenario cannot occur on those dates. The two scenarios become mutually exclusive for that pe riod of time around an application.

The user must choose an effective combination to contin ue. That is, at least one application type must be highlighted and the influence factor must b e 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 N o 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 probabil ity 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 t he corresponding vector will not be visible. For a fixed application time for each simulated individ ual simply enter a probability of 1 in the appropriate box. For general information on enterin g 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 en ter the fraction of the house being treated (Figure 5.25). See the Technical Manual for how th is 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 t hese 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 Scree n.

5.7.9 Specify Re-entry Times
Simulated individuals may be restricted from enteri ng 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 f or all scenarios affecting that area. The probabilities are entered on the Specify Re-entry T imes screen (Figure 5.26). For general information on entering data in distributions see S ection 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 the ir entirety. The exact screens vary depending on the source-to-concentration options selected ear lier. Since these screens may have to be revisited for each scenario, the scenario being edi ted is always displayed in the third (blue) title a t the top of the screen. These screens are also chem ical-dependent, so a chemical selection widget is also present on each screen.54

WARNING: Different surface residue collection devices are a vailable (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 coefficie nts, 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 trans fer 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 an d 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 tha t a number of distributions be defined for
each scenario. These distributions define the init ial 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 conc entration ratios. (See the Technical Manual for more details.) If the user chooses to ignore dispe rsion into the untreated area, then this ratio should be set to a point value of zero.

The following are the required distributions for ea ch type of scenario:55

• Indoor Scenarios

o Concentration in indoor air immediately after appli cation

o Concentration in indoor air 24 hours post-applicati on

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 concentra tions

• 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 eac h 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 i n section “Distributions Supported” on page 11 and information on entering distributions on thi s screen are discussed in “Individual Distribution Widgets” on page 11.56

Figure 5.27. Specify Decay and Dispersion Distribut ions for an Indoor Scenario.57

5.8.2 Specify Interval Distributions
Interval distributions might be used when measureme nt 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 applicati on (1-7 days)
3. The 8 th day after application to the 30 th day (8-30 days)
4. The 31 st

day after application and the remainder of the sim ulation period.

The user must define these four distributions for e ach medium affected by each scenario for each chemical. Once an application is made for a scenar io, these distributions will determine the concentrations on each medium. When another applica tion is made in the same scenario, the first distribution is used once again; there is no persis tence of chemical from the previous application.
The concentrations on a medium from different scena rios are added when determining exposure of an individual. It is assumed that background val ues are included in the distributions; the user cannot define background concentrations on media no t included in the scenarios.

As on the previous screens, the third title, in blu e, indicates the current scenario. Clicking on a
medium/chemical combination in the Interval Variabl e list box selects and highlights that variable. The distributions displayed are related t o that variable for the current scenario. The user
is not forced to enter data for each combination. A ny distributions not entered by the user will retain their previous values whether desirable or n ot. 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 defi ne background values.58

General information on distributions are provided i n section “Distributions Supported” on page 11 and information on entering distributions on thi s 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 distr ibutions:

• 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 Scenario59

5.8.4 Background

A background screen (Figure 5.30) will be visited f or both Decay and Dispersion and Interval Distribution options (the only difference will be t he title on the middle header bar). On this screen the user must enter the background concentra tions for outside surfaces. This is the only background concentration distribution required by t he model. The concentration must be entered
for each of the chemicals in the via the Chemical s election 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 Screen60

5.8.5 Specify Time Series Inputs
Time series inputs allow the user to specify the ex act concentrations on each medium for specific dates. This is a convenient method of using data de rived from studies of multiple households. Details on the file format required are discussed i n the SHEDS Technical Manual.

The burden is on the user to create the file contai ning 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 T ime Series Dataset (Figure 5.31) and then using the explorer to identify the dataset.

When using time series inputs the Specify Applicati on Scenarios button on the main screen is grayed out. The model does not simulate specific ap plications 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 se quence of screens allowing the user to enter or edit the remaining inputs. These inputs fall into t wo broad categories:

1. Individual exposure and dose factor variables, typi cally defined by a distribution.
2. Correlation between input variables (optional).

Each of these categories is discussed in the sectio ns below.

Initially the user is taken to the Variability Distributions screen (Figure 5.32). From this screen the user repeatedly visits the Edit Variability Distribution s screen (Figure 5.33).

If the user desires to define correlated inputs, cl icking 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 Variab les” screen is used to select which variables are to be correlated; the “S pecify” screen is used to specify the correlation
values defined.

5.9.1 Variability Distributions The variables set using the first two screens in th is 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, elimin ation rate, etc.)

• Removal-Related (hand washing frequency, removal ef ficiencies, etc.)

• Transfer-Related (skin adherence, non-dietary inges tion, etc)

• Activity-Related (Probabilities related to lawns, g ardens, 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 (Figur e 5.32) is used as a jump point. The user selects a variable group by clicking on the group name in t he Variable Groups list box. The group is highlighted and the descriptions of each variable i n 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 Continu e (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. Whi le 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 distributio n screens.

Figure 5.32. Variability Distributions Screen.63

If the user returns to the Simulation Information s creen 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 Coeffic ients from Transfer Efficiencies, the user will need to return here to edit the Transfer-Related gr oup. Only then will the user be able to continue
and run the simulation.

Once all groups are completed, the user will be abl e to define correlated inputs. By default, correlated inputs are turned off; no input variable s are correlated. To turn correlation on, click on the check box labeled Correlate Input Variables. Th is 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, i nput correlation will be turned off when the user
returns to this screen.

Only when all variable groups have been completed w ill the user be allowed to continue. If correlation was turned on, the correlated pairs mus t be defined or correlation must be turned off before the user may continue. Once enabled, clickin g 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 th e Specify Inputs button is clicked from the Variability Distributions Screen. The screen will a lways have the same basic layout, but the specific variables that can be edited will change b ased on the variable group highlighted when the Specify Inputs button was clicked. The second t itle will always indicate the variable group being edited.

The variable to be edited is chosen in the left han d list box. If the variable has several distributions associated with it, for different age s perhaps, then a list of conditions will be listed on the right (see Figure 5.34). A variable is sele cted by Clicking on the variable description, or the condition if present. When selected, the curren t distribution parameters for that variable will be loaded into the widget. The title of the box sur rounding 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 redefine d a frequency histogram will be drawn showing a representative sample for the distributio n as defined. To turn this off, uncheck the histogram check box on the right. The mean and stan dard deviation of the sample will also be shown in the box on the right. It should be emphasi zed 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 ru n is an uncertainty run (see Section 5.4), the “Uncertainty” distribution definition may be select ed for any variable. (See section 2.3.5.3 for64

information on defining uncertainty distributions). When an uncertainty distribution is used, the user can view any of the distributions defined on t he uncertainty dataset via a new widget labeled “Unc Distribution #” that will appear when “Uncerta inty” is selected (Figure 5.35). By clicking the up and down arrows, the user can view any of th e 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 Dis tributions 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 distributi on is Used.

To accept the current values, click the Continue bu tton. If any of the parameter values are in error, they will be highlighted in red or yellow an d the Continue button will be disabled. Clicking
on the Cancel button returns the user to the Variab ility 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. W hen “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 vect or describing the distribution of days between baths for the population. See Section 2.3.3 for mo re information about entering probability

vectors.

5.9.3 Correlating Input Variables
All of the variables in this section (General Expos ure 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 ex ample, perhaps the hand-to-mouth transfer efficiency and the object-to-mouth transfer efficie ncy should have a tendency to track each other, Figure 5.36. Specify Days Between Baths Screen.67

since the physical/chemical properties should be si milar 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 Do se 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 speci fies 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 definit e target correlation are assumed to have a target
correlation of zero.

SHEDS uses a modified NORTA 2 method to generate the correlations. The random v alues for the selected set of variables are first generated f rom 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 wil l 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 techni cal 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 mus t have the same correlation as the other with any third variable. Mathematically, a correlation m atrix is valid if and only if all its eigenvalues are non-negative. If the set of requested correlati ons 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 corre lations. The first screen Select Correlated
Variables (Figure 5.37) is used to choose the variables of i nterest. 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 correlatio n 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 lis t box to include them in correlated pairs on the next screen. The single arrow moves the selecte d variables, the double arrows move all variables. If the user has previously defined corre lated pairs, the right hand list box will initially be populated only with variables in those correlate d 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 sc reen will be displayed (Figure 5.39), and
correlation will be turned off in the simulation. B egin 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 value s.

The variables are ordered. Initially, all but the l ast variable are displayed in the First Variable li st box. The Second Variable list box will contain all variables below the variable highlighted in the
First Variable list box. The Second Variable list b ox 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 li st box, select the next variable from the Second Varia ble list box, specify the correlation value in the spin box to the right, and click on the Add Pai r Button. Once added, the variable pair will be displayed in the Selected Pairs Specified box on th e 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 sp ecified with the one previously specified for the pair.70

The user may find it necessary to resize the column s 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 Correla ted Pairs Specified area. This will enable the Delete Pair button. Click on this button and the pa ir will be removed from the list.

Figure 5.40. Specify Variable Correlations Screen.71

Clicking on Continue saves the values defined and r eturns the user to the Variability Distributions screen. Once uncertainty is implement ed, the user will be returned to the Uncertainty Distributions screen if doing an uncert ainty run.

If no correlated pairs are chosen, then an error sc reen will be displayed (Figure 5.39), and
correlation will be turned off in the simulation. B egin from the Variability Distributions screen to turn correlated inputs on once again.



## 5.10 Run Simulation

Only when all information has been specified will t he 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, th e number of simulated profiles, the number of sensitivity or uncertainty repetitions (if any), th e number of chemicals, and estimated run time. If 20 or fewer people are being simulated, then th e 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 simulat ion. This will open the Run Progress Screen (Figure 5.42). This screen contains information ab out the progress of the run, including how Figure 5.41. Run Simulation Screen for an Uncertain ty Run.72

many profiles and chemicals have been completed, th e estimated remaining time, and the average time per profile. For a sensitivity or variability run, the screen will also indicate which sensitivi ty or uncertainty repetition is currently being perfor med. 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 progresse s. When the simulation is completed, the final timing information will be displayed in the log. Cl icking the Continue button after run completion will return one to the main menu where V iew 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 simulatio ns with twenty or fewer people. Typically, a user will not want to run in diagnostic mode. If on e is very familiar with the model it may be helpful in locating errors. Three things happen whe n 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 Variabil ity Run.73 Figure 5.43. Log Screen after Running a Small Simul ation.

2. Intermediate variables are saved on the datasets. T his option is also available on the
Simulation Information screen.
3. Event level datasets and variables are saved for e ach 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 simula tions can be viewed by selecting the View
Results button on the main window. This button wil l become active once a simulation run has been made or after a previously run simulation is s pecified in the Run Name dialog. Pressing this button opens a dialog (Figure 5.44) allowing the us er 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 in terface. For information on the log files, export files, and exporting files from SAS for anal ysis 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 simul ation just run or that specified most recently in the Run Names dialog. When considering the populati on, the output variables utilized are the daily values (of exposure, dose, etc.) for each per son, 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 maximu ms 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, Sta rt Age, Stop Age, Min Rank, and Max Rank) can be used to select a subgroup of the run p opulation 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 label ed 0 to 99; as nearly as possible, the bins contain the same number of people. (If the simulat ed 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 simulatio n 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 ch ildren. The pull down menus only display genders, ages, and ranks that exist in the output d ataset. 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 fi nal 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 re sults 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 chem ical 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 “Cu mulative” 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 fro m the chemical list box.

For uncertainty and sensitivity runs, the summary s ensitivity and uncertainty results are viewed on screens specific to these types of runs (see fol lowing sections). However, for each of these types the user can also view the variability result s 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 Re petition”. This box will contain a list of the available repetitions. The user can then select an y of the repetitions to view.

The Variable Groups list box allows the user to sel ect a subgroup of the variables to view. When the user selects a group, the available variables w ill 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 the se terms.

The Output Variable Type list box lets the user sel ect either:

• Personal Means; or

• Personal Maximums.

Pressing the Display button then performs the analy sis 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 v ariables. For example, in Figure 5.45 the Variable Group selected is New Exposure, so the Sel ect 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 gen erates 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 t able for the selected variable(s) and specified model simulation, including sample size, mean, stan dard deviation, median, 5 th ,25 tt , 75 th

, 95 th

, and 99 th percentiles. An example is shown in Figure 5.46. I f multiple variables are analyzed, the results are displayed on individual rows of the tab le; the variable name and description (label) are included on each row. Again, note that the subpopu lation that is being examined is printed in the table window – in this hypothetical example the use r 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 functi on (CDF) plot for the selected variable(s) and specified model simulation. The plot illustrates ho w the percentiles of the selected variable(s)
behave as a function of the variable value. Each s elected 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 al l the percentiles for the others were zero in this simulation.) The plot can be printed by clicking o n 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 populati on subgroup. Multiple variables are shown on a single plot. An example for seven absorption vari ables 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 supp ressed by SAS. The boxes, whiskers, and other symbols on the plot are interpreted as follow s:80

Figure 5.48. Example Population Box and Whiskers Pl ot.

• The midlines of the boxes are equal to the median.

• The plus (+) symbol inside the boxes is equal to th e mean.

• The upper edge of the box is the 75 th percentile of the population, while the lower edge is the 25 th percentile. Thus, these edges define the width of the interquartile range (IQR).

• The whiskers define the maximum or minimum observat ions that fall within 1.5 times the IQR, measured from the quartile value (i. e., the 75 th or 25 th 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 fro m the other options in the Output Type menu. It does not require (or allow) selection of individ ual 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, o r New Dose Normalized to Body Mass. Clicking on Display yields a pie chart showing perc ent contribution to one of these summary variables (based on population or population subgro up 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 Resu lts is the View Results for Individual. Selecting this button brings up the window for perf orming analysis of the results for a single individual within a simulation run. Many of these o ptions are similar to those for View Results for Population. When considering an individual, th e output variables of interest are the daily values for the selected individual. A specific simu lated individual must be selected. Additionally, the analysis may be limited to a specific time peri od. 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 o utputs will contain a second title giving the basic
individual statistics and dates considered in the a nalysis.

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 r esults. The output dataset is dependent on the units chosen. As in the Results for Population wind ow, 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 i ndividual 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 tha t individual.

In addition to selecting an individual, the user ma y 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 t he 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 f or Population Screen (Section 5.11.2).

The user may also view individual results for uncer tainty and sensitivity runs; however, in this case, only the individuals simulated in the very la st sensitivity or uncertainty repetition are available. Due to space limitations, SHEDS does no t retain daily-level information for every repetition (only the most recent). It should be no ted that while all repetitions are valid variabilit y runs, one should use caution when viewing results f rom a percentile scaling run, because in this type of run certain variables (most sensitivity inp ut variables) may be being held at their median values in the last sensitivity repetition.

As in the View Results by Population dialog, the ou tput units may be selected as either Microgram or Milligrams per Kilogram from the Outpu t Units menu, and the Variable Groups
and Select Variables menus are used to select the m odel output variables to analyze. As before, multiple variables may be selected for analysis. Th e 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 ar e described next.

5.11.3.1 Time-Series

Selecting the Time-Series button produces a time-de pendent plot of the selected variable(s). Each data value on the plot is the value for a sing le day in the simulation. Multiple variables will be plotted as multiple curves on the same time-seri es 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 o f doses and exposures in the days following a pesticide application. An example showing six expo sure 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 pl ot for the daily values of the selected variable(s) for the specified individual. Each sel ected variable will appear as a separate line on the plot; a legend appears at the bottom of the plo t 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 si milar 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 pe rson 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 pe rson, and selected dates. Multiple variables are shown on a single plot. An example box and whiske rs plot for an individual’s daily values of several new dose variables for a year-long simulati on is shown in Figure 5.53.87

Figure 5.53. Example Box and Whiskers Plot for an I ndividual.

5.11.3.4 Contribution by Pathway The interpretation of the Contribution by Pathway o ption for an individual is identical to that for the population. As before, this option does not req uire or permit selection of individual model variables; only the Variable Group needs to be spec ified-- New Exposure, New Exposure Normalized to Body Mass, New Handler Exposure, Runn ing 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 yield s 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 w ill 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, m ean, standard deviation, median (p50), 5 th percentile (p05), 25 th percentile (p25), 75 th percentile (p75), 95 th percentile (p95), and 99 th percentile (p99). The age and gender of the individ ual 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 statistic s 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 win dow and displays a table that contains detailed information for all daily average variable s 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 t able 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 appea r to the right.89

Figure 5.55. Example Detailed Table for an Individu al.

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 th e 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 a ny uncertainty clouds that were defined for model variables using the “Uncertainty” type distri bution.)

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 sel ected at a time.

There are two types of output summary plots that ar e available for uncertainty runs:

• Plot the 5 th , 50 th , and 95 th percentile from each uncertainty repetition . In this type of plot, the persons in each repetition with the 5 th , 50 th , and 95 th 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 performe d. A CDF is plotted of the population
5 th , 50 th , and 95 th percentiles of total dose from each of these runs ( and thus each CDF on the plot has 5 points). In this example, all the va lues of the 5 th percentiles were 0, as were
a number of the medians.90

• Plot the CDFs of repetitions whose medians are at t he 5 th , 50 th , and 95 th percentiles. In this type of plot, three repetitions are identif ied: those whose population medians are at
the 5 th , 50 th , and 95 th percentile of all the repetition medians. An exam ple of this type of plot is shown in Figure 5.58. In this example, tot al new dose was examined for an uncertainty run of 5 repetitions of 25 profiles eac h. Three repetitions were identified: that
with a median with the 5 th percentile of all medians. In this case, since on ly 5 repetitions were performed, the 5 th percentile corresponded to the repetition with the lowest median.
The 50 th percentile corresponded to the repetition with the 3 rd highest median out of the 5 run, and the 95 th percentile corresponded to the repetition having t he highest median. Then the population CDFs for total new dose are plo tted for those three repetitions; note that each CDF has 25 points because 25 profiles wer e run. Note that this run is only for example purposes; many more profiles and repetition s would be needed to develop real, useful uncertainty results.

Figure 5.56. View Uncertainty Results Screen.91

Figure 5.57. Plotting the 5 th , 50 th , and 95 th 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 th e user to view a table of sensitivity results
for the run. The format and contents of the table w ill 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 Rep etitions whose Medians are at the 5 th , 50 th , and 95 th Percentiles.93 Figure 5.59. View Sensitivity Results Screen.

The user may select to view sensitivity results bas ed on the population average of any model variable. The available variable groups are the sa me as described in Section 5.11.2 . The user specifies a variable group, a variable, and then cl icks Display to view the sensitivity table.

5.11.5.1 Results for a Percentile Scaling Run

If a Percentile Scaling run was performed, the tabl e 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 scal ing 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 SHED S Technical Manual for detailed information about the percentile scaling method.) The results o f these runs are summarized in the table. The table contains the following information:94

• Variable. The input variable name. For space reasons, the va riables 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 tha t 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 sel ected.

• Ratio of High Result to Low Result . Ratio of the result for high-percentile run to th at 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 o f High Result to Low Result if this number is greater than 1, or its inverse if it is less tha n 1. It is used to rank the items in the table.

In the example shown in Figure 5.60, the sensitivit y of the new dermal dose to four input
variables was examined. Of the four variables bein g 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 dev elop real, useful sensitivity results.

Figure 5.60. Sensitivity Results for a Percentile S caling Run.95

5.11.5.2 Results for a Sobol Sensitivity Run

An example of the sensitivity results for a Sobol r un are shown in Figure 5.61. For this type of run, a number of output sensitivity variables are p resented 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 v ariable that is explained by variation in the variables in the S obol group. This is calculated as the total effect of the group divided by sum of the total eff ect 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 unce rtainty in these estimates. See the SHEDS Technical Manual for details on performing Sobol ru ns.

Figure 5.61. Sensitivity Results for a Sobol Analy sis 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 i n Figure 5.62. This table contains a list of all t he input variables in the run, and their correlation w ith the selected variable (Total New Dose in the example in Figure 5.62). The absolute value of thi s 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. F or 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-ou tput correlations.

Figure 5.62. Sensitivity Results for an Input-Outp ut 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 t he 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 SHED S-Residential run from start to finish. The run presented herein is a single-chemical variabili ty run for Permethrin. The run considers a single application scenario (an indoor crack-crevic e aerosol); the application dates are modeldetermined. This example run is included in the SH EDS-Residential installation; it will be available for selection when Edit an Existing Run i s 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 a n accompanying screenshot.

Note: Since SHEDS is in development, the results s een 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 theyear. 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>. Thisproceeds 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 dia log 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 vi ew the progress of the job. Multiple batch jobs may be submitted at one time, also useful for overn ight 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 th e 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 app ear 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 und er the SHEDS-Residential installation directory. The third path (from the C: in the thir d 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 en suring that all the necessary inputs are defined. This is a primary function of the interfa ce itself. Hence, the easiest way to prepare a batch run is to define and save all the inputs usin g the interface. Inputs for several runs could be defined and saved without submitting any of these j obs. Alternatively, the user could prepare the121

required input files using a standard SAS editor, b ut this places a greater burden on the user to ensure that all inputs have been supplied in a cons istent manner.

Each set of inputs and settings is saved under a us er-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 foun d 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 defi ned 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 abo ve files, each job requires its own record in the RunInfo file. Either an existing record on the Run Info file can be edited, or a new record added. Open the existing RunInfo file in the SAS editor, c opy any record to a form a new record, and then hand-edit that new record. Alternatively, a n ew 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 di alog on the Windows Start menu. Enter the full path to the “batchrun.bat” file (wit h quotes needed if the path contains blanks or spaces), followed by a space and the name of the jo b 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 anothe r SAS window indicating the location of the source code, output, and log files. The file b atch.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 e xactly 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-on ly 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 m ust 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 b e prepared outside of SHEDS. However, the version 4 GUI allows the user to specify the file n ames for these clouds, and even allows the user to submit uncertainty runs.

The percentile scaling and Sobol's method of sensit ivity 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 ha ndles these file edits and the submission of sensitivity runs, although the user may still su bmit 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 ti me. By default this is in the user’s My Documents/Multimedia3.14 (or similar) directory. Th e install directory will be referred to as the install directory or <install> in the following dis cussion and diagrams.



## A.1 Directories

The directories are laid out as follows on installa tion. 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 r uns

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-inst allation



## 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 impo rtant. The table below shows where critical files are placed at installation or when a run is d efined through the interface. All files in the Runs/<run name>/Input directory are modified by the interface (except the contactmedia.sas7bdat dataset). Additional input fi les (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 c an be
set here
multimedia.bat File used to run SHEDS in batch mod e runinfo.sas7bdat File containing run specific info rmation generated by the interface Runs/<run name>/Input/124 agegroups.sas7bdat Defines age and genders to be u sed in
simulation
areatreated.sas7bdat Fraction of area treated for i ndoor 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 d efined for run Required for
Batch Runs

contactmedia.sas7bdat List of contact media and the ir short names

decay.sas7bdat Decay and dispersion application
information
intervals.sas7bdat Interval concentration informati on One of These is Required

timeseries.sas7bdat User defined time series concen trations 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 applicat ion dates



## A.3 User Specified Output Files

The major output files for a typical variability ru n, 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 ba tch runs in this manual.

If a log file is specified by the user, on the Simu lation Information screen, then it is put in <install>/Runs/<run name>/Output/saslog.txt. This f ile 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 fo r each cohort and day type is listed in the file “diarycounts” in the \output directory for the give n run.



## A.5 Exporting SAS Datasets

To facilitate additional analyses in the software o f your choosing, you may export data in a variety of formats. The export wizard can be access ed 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, informati on on specifics can be found in the SAS help files.126 

# 8 References

Glen G., Zartarian V.G., Smith, L., and Xue J. (201 0). 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. (20 10) Stochastic Human Exposure and Dose Simulation (SHEDS) Model for Multimedia, Multipathw ay 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 Stochas tic Human Exposure and Dose Simulation (SHEDS)-Dietary Model Technical Manual. Prepared f or 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 prohibitio n time [-] v_ReEntry_pet Vector for pet contact prohibition ti me [-]128

v_TimeOfUse_in Vector for indoor application hour h r 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 surfac e 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 mouthin g [-] ObjMouth_area Object-mouth contact area cm2 ObjMouth_freq Object-mouthing events per hour event s/hr ObjMouth_TE Object-to-mouth transfer efficiency [-] f_RemovBath Fraction removed during bath or shower [-] f_RemovHandWash Fraction removed during hand washin g [-] f_DermalBlood Fraction absorbed from skin into bloo d [-] f_InhalBlood Fraction absorbed from lungs into bloo d [-] 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 an d 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 i s negatively skewed. For v1=v2 the mean is at 1⁄2 and the shape is symmetric. The PDF is

Equation E-1
p(x) = x v1-1 (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-int eger 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. Fo r v1>1 and v2>1, the PDF of the beta has a single pea k, 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 distr ibution is at μ = v1 / (v1+v2), and the standard de viation
is σ = Sqrt[v1 v2 / (v1+v2+1)] / (v1+v2). If one wishe s to construct a beta with a given mean μ and
standard deviation σ , then choose v1 = (μ 2 -μ 3 )/ σ 2 -μ, and v2 = v1 (1-μ) /μ. This will only be possib le if 0<μ<1 and σ 2 < μ (1-μ) ≤ 1/4.



## C.2 Exponential

The exponential in SHEDS has two parameters, the mi nimum (v1) and the mean (v2), with the restriction that v1 < v2. Some users may be more f amiliar with a single parameter exponential distrib ution, 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 righ t. The decay rate of the SHEDS exponential is give n by 1/(v2-v1). The standard deviation of an exponenti al is (v2-v1). If the user wants an exponential wi th 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 restr ictions are v1>0 and v2>0. The shape parameter v1 controls the appearance of the PDF. Shape paramete rs 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 tha t starts131

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 probabili ty, and then gradually declining with an overall po sitive 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 (v 2). The restrictions are v1>0 and v2>1. Many variables in exposure science are approximately log normally 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 standa rd 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 ari thmetic 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 arithme tic standard deviation σ of the lognormal instead of the GM and GSD, then these can be conver ted as follows:

Equation E-6
GM = μ / Sqrt(1 + σ 2 /μ 2 ), GSD = Exp(Sqrt(Log(1 + σ 2 /μ 2 ))). If instead, one has the mean μ log and standard deviation σ log of log(x), then use

Equation E-7
GM = Exp(μ log ), GSD = Exp( σ log ).



## C.5 Normal

This is the normal or Gaussian distribution commonl y used in statistics. The normal has two parameters: the mean (v1) and the standard deviatio n (v2), with v2>0. Note that the normal is unbound ed, so it is a good idea to provide lower and upper tru ncation points to prevent physically impossible val ues from being returned. The PDF of the normal is132 Equation E-8
p(x) = Exp[-(x-v1) 2 /(2 v2 2 )] / (Sqrt[2 π ] v2)



## C.6 Point

A point value means that the same value is always r eturned. This is sometimes called a fixed or

constant form. The point has one numeric argument (v1) whic h 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. Wh ile points are technically discrete, here they are clas sified 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 densi ty function (PDF) that is shaped like a triangle. The three parameters locate the vertices, with v1=m inimum, 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 betw een v1 and v3. The standard deviation is σ = Sqrt[(v1 2 +v2 2 +v3 2 -v1v2-v1v3-v2v3)/18]. It is possible for the peak to be located at either extreme, forming a right triangle. The PDF of the triangula r 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 li kely 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 restr ictions are v1>0 and v2>0. The Weibull has slightl y different properties from a gamma, but there is a s trong overall resemblance. When the shape paramete r v1 ≤ 1, the Weibull is monotonically decreasing. For v 1=1, it reduces to an exponential. For v1>1, it ri ses to a peak and then declines gradually in a long tai l. 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, not133

the gamma distribution. The gamma function is a ge neralization of the factorial function to non-integ er 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.10 Binomial Distributions

Binomial distributions have only two possible outco mes, for example, the outcome of yes/no tests. The usual statistical notation would be (p 1 , p 2 ), where p 1 and p 2 are between 0 and 1 and sum to 1. However, the SHEDS code implements binomial distrib utions by having the user specify only the probability of a “yes”. The probability of “no” is implied by 1 - “yes”.



## C.11 Discrete Probability Density Functions

Multinomial variables allow more than two possible outcomes. The usual statistical notation would be (p 1 , p 2 , ..., p n ), where each p i is between 0 and 1 and the p i ’s sum to 1. In SHEDS, multinomial variables are called probability vectors. The user must supply the entire set of probabilities.