Everything on this website belongs to one or more intellectual projects with defined hypotheses, goals, methods, and accomplishments. This online book contains background information and links for all the exposure-related research projects. In each chapter of this book, we provide descriptions of the history, methods and results of each research project. Note: Project and the different materials associated with each project (document, software, data set, etc.) have their own convenient summary webpage in addition to the information given here.
Please visit the HAP Summary Page for a quick description of the aims, investigators, and materials associated with the Human Activity Patterns (HAP) hosted project.
The HAP project hosted on this website was begun in the early 1990's at Stanford University by Wayne Ott, John Robinson, and Paul Switzer. At that time a set of two ground-breaking activity pattern studies by the California Air Resources Board had been recently completed, and the Stanford investigators wrote several reports analyzing the data with regard to secondhand smoke exposures. Subsequently, the USEPA sponsored a large nationwide activity pattern study, called NHAPS, which interviewed Americans in 1992-1994 on their exposure to many different pollutants in household air and water. Neil Klepeis led a team that analyzed the NHAPS data for the EPA, producing a journal article and several reports (
[Bad Link: Plugin Not Found]).
One of the most significant aspects of these seminal activity pattern studies, NHAPS and CAPS, were their measurement of the minute-by-minute activities of human beings over a complete 24-hour period using a computerized survey instrument. These highly-resolved activity pattern data have proved to be vital in the modeling of human exposure to hazardous air pollutants.
Please visit the IAQ Summary Page for a list of the aims, investigators, and materials associated with the Indoor Air Quality (IAQ) hosted project.
The IAQ project hosted here investigates a wide variety of factors that impact the concentrations of air pollution that can occur in typical indoor environments. These factors include building construction, mass emission rates of different sources, ventilation rates, particle deposition rates, chemical reaction rates (including surface interaction), and indoor-outdoor particle penetration rates.
A key goal of the IAQ project is the validation and application of models for predicting indoor concentrations. Through the use of real-time monitoring techniques, it is possible to verify the performance of indoor air models, as well as to estimate model parameters. The indoor air models used in this project typically rely on a simple mass balance approach. The MIAQ model is a good example.
Several key studies of the IAQ project have illustrated the combined approach of measuring airborne pollutants in specific microenvironments and validating or parameterizing deterministic models (e.g., Klepeis et al. 1996 and Ott et al. 2003).
Since many investigations for the IAQ project involve the general study of ventilation, they are relevant to a range of different sources of indoor air pollution. However, because secondhand tobacco smoke (SHS) is a ubiquitous pollutant and information is needed to understand exposures in everyday locations, much of the work for the IAQ project has been focused on SHS. For example, investigators have estimated source strengths for cigars and cigarettes and particle deposition for SHS emissions (e.g., Klepeis et al. 2003).
In the remaining sections of this chapter on the IAQ project, we describe its various sub-projects in more detail.
MIAQ is a Multi-chamber Indoor Air Quality model orginally authored by William W. Nazaroff as part of his Ph.D. disseration research in the Environmental Engineering Science Department at the California Institute of Technology, Pasadena, CA.
The current maintainer of MIAQ is Dr. Neil E. Klepeis.
The program simulates concentrations of airborne particles and gaseous species taking into account processes such as deposition, ventilation, filtration, coagulation, and chemical reactivity.
MIAQ is highly-configurable research software written in Fortran-77. The source code is known to compile with GNU g77 and Absoft F77. The model requires, as input, a text file containing detailed commands.
MIAQ is free software and is released under the GNU General Public License.
Note: To uncompress the tar.gz archive on Unix or GNU/Linux, use the following command in the directory where you wish the software distribution to be located:
tar zxvf miaq.tar.gz
Note that the gzipped Unix archive can be uncompressed using a variety of free and commercial Windows utilities, such as WinZip. Please visit http://www.gzip.org for more information.
In the software distribution directory you will find the following text files containing useful information:
...and the following sub-directories containing
the essential files:
The MIAQ manual, included in the software distribution, contains a complete command reference and an example input file. To use MIAQ do the following:
Please cite the following references when publishing or presenting work that uses MIAQ:
MIAQ is research software, intended for use by indoor air quality and exposure scientists. It has been used in a variety of studies, but has not been thoroughly tested in all respects. It currently may be executed as a stand-alone program, or as a shared library. For example, the Human Exposure Research Package (heR) includes a function for executing MIAQ aerosol dynamics simulations.
Please visit the IESM Summary Page for a quick description of the aims, investigators, and materials associated with the Inhalation Exposure Simulation Modeling (IESM) hosted project.
The IESM project integrates the results of other projects into a deterministic and stochastic modeling framework, which can be used to predict and explore human exposures to airborne pollutants for a wide range of locations and scenarios. The framework incorporates human activity patterns, indoor air monitoring data and models, building factors, and a range of simulation techniques. The framework is currently manifested as a series of routines programmed in the Human Exposure Research Package (heR).
The earliest activity-pattern based exposure model was developed by Wayne Ott in the 1980's, called the Simulation of Human Activity and Pollutant Exposure (SHAPE) model. The more recent THEM model, developed at Stanford University in the early 1990's, was an offshoot of this original model (Klepeis et al. 1994).
Most recently, investigators in the IESM project have simulated exposure to secondhand tobacco smoke (SHS) in residences (Klepeis and Nazaroff 2006), for the purpose of identifying building and occupant-activity factors that most heavily influence exposure.
In the sections of this chapter, we describe in more detail the various sub-projects and software implementations that are part of the IESM project.
This page describes the Total Human Exposure Model (THEM) for exploring particle exposures in the San Francisco Bay Area. Please visit the THEM Summary Page for a complete list of all the THEM project details.
The Total Human Exposure Model (THEM) program, version 1.0 was developed at Stanford University from July 1991 to April 1994 by Wayne R. Ott, Neil E. Klepeis, and Elena Tracy. THEM is written in MicroSoft Professional BASIC Development System version 7.1.
THEM is not currently being maintained, but questions can be directed to Dr. Neil E. Klepeis.
THEM is released under the GNU General Public License.
The current version calculates exposure to Respirable Suspended Particles (RSP) from Environmental Tobacco Smoke (ETS) and ambient sources. It uses the California Activity Pattern (CAP) Survey data from the California Air Resources Board (Sacramento, CA) and ambient RSP data from the Bay Area Air Quality Management District (David Fairley). The so-called Sequential Cigarette Exposure Model (SCEM), based on the mass balance equation, is used to determine concentrations of secondhand tobacco smoke for single cigarettes.
A zipped archive is available containing all of the Microsoft Professional Basic source-code files, a variety of documentation files, and a Windows/DOS executable (themrsp3.exe).
The user interface to the program is fairly self-explanatory.
Execution of THEM for the calculation of exposures across populations requires the input of (1) activity pattern data, (2) mass balance parameters, (3) microenvironmental distributions, (4) activity, location, and calculation method reduced codes, and (5) ambient data (optional).
All parameters are specified using input data files, which have already been set at default values for the simulation of exposure to RSP from cigarettes and ambient sources for people living in the San Francisco Bay Area.
The documentation files in the software distribution contain more information on using THEM.
The main reference for THEM is the following AWMA conference paper:
Klepeis NE, Ott WR, Switzer P. A Total Human Exposure Model (THEM) for Respirable Suspended Particles (RSP), Presented at the 87th Annual Meeting and Exhibition of the Air and Waste Management Association, Cincinnati, OH, June 1994.
Please cite this paper if you use or describe THEM in any published research.
The THEM user's and programmer's manual contains a technical description of the program, including all the subprograms and variable declarations.
This page provides details on the human exposure research (heR) software project. You may also want to visit the heR Summary Page page, which lists the main heR highlights.
The heR Project is officially part of the Inhalation Exposure Simulation Modeling project, because it includes sophisticated tools for modeling individual and population exposures. However, it also contains many tools, sub-models, and data sets that are likely to be useful in many different areas of human exposure research. For example, it contains subroutines for manipulating and statistically analyzing activity pattern data, and it also contains routines for executing advanced indoor air quality models.
heR is a free software package implemented in the R computing environment that contains routines and data sets for use in conducting human exposure research. The field of human exposure is concerned with the processes by which environmental contaminants in air, water, soil, and food come into contact with human biological boundaries.
heR originated as part of the Ph.D. research of Neil E. Klepeis at the University of California at Berkeley. His research was focused on the simulation of residential secondhand tobacco smoke exposure. As a result, heR currently contains substantial functionality for airborne exposures, indoor air quality modeling, and human activity pattern analysis.
The aim is for heR to be a community-supported project, containing the most advanced techniques in all types of exposure-related modeling and data analysis.
Both R and heR are free software released under the GNU General Public License.
New testers and contributors to the software package, especially those in the food or dermal exposure areas, are most welcome. If you are interested, please send email to Dr. Klepeis using the contact form at http://neil.klepeis.net. Make sure to include some information on your background in exposure research.
The current component packages of heR are as follows:
You can download and view the documentation for each package using the links in the table below.
The following are some advantages of using the R environment as a platform for heR:
Online HTML documentation is available for each heR component sub-package (module) by following the "[Docs]" links in the following table. Some packages you can download directly using the "[Download]" link, others you need to request the package files by using the "[Request Package]" link.
Note: When you install a heR package all of the documentation is included in your local installation.
If you use a heR package in your research, please cite the listed paper(s) as appropriate, or the ExposureScience.Org website, in any of your publications.
|Miscellaneous Plotting and Statistics||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Time-Activity Pattern Analysis||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Human Activity Pattern Data||Klepeis et al. 2001.|
|Inhalation Data and Modeling||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Indoor Air Modeling||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Exposure Simulation||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Exposure Survey Data||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
|Pollutant Monitoring Data||Klepeis, N.E. Exposure Science Website. http://ExposureScience.Org, 2004.|
In addition to the online HTML heR documentation available by following the links in the above table, you may wish to view the online HTML documentation for the current standard version of R, although it is typically included on local machines where R is installed.
Before installing heR from source-code package files, you must first install R itself. Binary packages of R are available from the Comprehensive R Archive Network (CRAN).
After installing R, download each desired heR sub-package archive. Note that there are dependencies among the packages, so the easiest approach is to install everything.
Once downloaded, the packages are installed on GNU/Linux or Unix-like systems by using the following command when logged in as root: R INSTALL package-file-name
Unfortunately, pre-compiled packages are not currently available for Windows. However, the source-code packages available here may be used to port each package to other platforms.
heR is intended to be a collaborative free software project among exposure science researchers. The heR source code is available through this website to members of the research community. Although it has been tested and used extensively as part of the PhD research of Neil Klepeis, heR is currently in an early state of development and is not yet ready for an official public release. This website will serve as a focal point for the future development of heR.
Please visit the LAPD Summary Page for a quick description of the aims, investigators, and materials associated with the Local Air Pollutant Dispersion (LAPD) hosted project.
As the field of human exposure has grown, the realization that we need to focus on processes occurring near the person being exposed has also grown. For example, initially it was thought that measuring air pollution levels in ambient air, e.g., on top of buildings or weather stations, was sufficient to estimate people's exposure. However, investigators soon realized that measurements in backyards, or inside homes were more reflective of true exposures. Ultimately, the use of personal (mobile) monitoring devices placed on individuals was identified as the best way to accurately measure exposure.
The "personal cloud" is a phenomenon that, after it was observed, led to increased study of pollutant mixing and dispersion from sources immediately near people. The personal cloud effect is an observed elevation in human exposure when measured at a personal monitor relative to a fixed room monitor. It was attributed, in part, to cooking, smoking, or other pollutant-generating activities that occur in proximity to the subject wearing a personal monitor.
The LAPD project continues the elucidation of the personal cloud effect through systematic study of the "proximity effect", aiming to characterize and model the effect of being close to a source for a range of source types and common air flow conditions & human activities in homes and other locations. It examines sources, measures levels of pollutants, and considers human activities occurring within a few inches, feet, or yards from a subject.
Sandra McBride investigated and statistically modeled the proximity effect for continuous indoor sources as part of her Stanford University dissertation in 1999. Subsequently, Neil Klepeis, Wayne Ott, Paul Switzer, and Lynn Hildemann expanded the study to outdoor locations, along with continued study of indoor locations using custom multi-point sensor arrays, which measure real-time particle or tracer gas concentrations in 3 dimensions.
Please visit the RTPMM Summary Page for a complete listing of the aims, investigators, and materials associated with the Real-Time Particle Monitoring Methods (RTPMM) hosted project.
More and more researchers in health-related disciplines and offices are becoming interested in the real-time monitoring particulate air pollution, using portable and affordable devices that have recently entered the market. However, in the measurement of aerosol concentrations using light scattering and other techniques one must take care to consider various complicating factors, which can erode the accuracy of measurements, such as mixtures of aerosol from different sources, compositional sensitivity of monitors, size-specific sensitivity of monitors, aerosol age, etc.
Hence, the RTPMM project was started to carefully study a range of airborne particle monitor types, testing them in the field, measuring their precision, understanding their response characteristics, comparing them to other types of real-time monitors and to standard methods, and identifying calibration factors for conversion to mass units.
The RTPMM project was initiated by Wayne Ott, Jim Repace and others as several monitoring units, such as the TSI Piezobalance, the Ecochem PAS PAH analyzer, and the GRIMM particle counter were acquired and used in exposure monitoring studies. However, recently there has arisen a need for careful examination of the extremely compact and user-friendly TSI SidePak and other popular real-time particle monitoring devices.
Please visit the VM Summary Page for a complete listing of the aims, investigators, and materials associated with the Vehicle Microenvironment (VM) hosted project.
The motor vehicle is a special kind of indoor environment, which requires special attention. Firstly, vehicles have much smaller volumes than most other indoor environments, and, therefore, pollutants emitted in their interior have the potential to reach peak levels that far exceed anything that would occur in homes, offices, and other indoor locations.
Furthermore, since vehicles are, by their nature, in motion, the ventilation characteristics of motor vehicles are much more volatile than stationary indoor locations. The motor vehicle speed, position of windows, and the operation of air conditions or force-air ventilation all affect the levels of interior air pollutant concentrations.
Hence, the VM project is focused on elucidating the unique physical parameters associated with motor vehicles and to measure and model air pollutant levels that can occur in motor vehicles. Recently, a landmark paper has been published that measured air change rates in different types of passenger vehicles for wide-ranging conditions, as well as verifying the application of the mass balance equation to interior pollutant concentrations due to secondhand smoke (Ott et al. 2007).