Indoor exposure models
Utilization
Mass-balance models are used to simulate average indoor air pollutant concentrations as a function of outdoor concentrations, building and pollutant characteristics and indoor sources. These models consider transport of air pollutants between outdoors and indoors, as well as between indoor compartments in the buildings, and are widely used due to the simplicity of the mathematics involved. The strength of these models is the simulation of air pollutant concentrations that may be well compared with results from experimental measurements.
Statistical regression models are mass-balance models in steady-state form and they are the simplest models available to predict indoor air pollutant concentrations. These entirely empirical techniques are quick and easy to apply since they do not require complicated input parameters. Several forms of such statistical regression models exist, and in general require input parameters such as penetration factors, outdoor concentration, room/building volume, indoor surface area, air exchange rate, deposition/adsorption rate.
Micro-environmental models are based on the concept of the micro-environment (ME). This is defined as a generic space with a homogeneous pollutant concentration in which people spend time. This has been the key concept in modeling of personal exposure and, as a result, microenvironmental models are often used together with exposure models. A micro-environment may be a whole building, a section of a building (i.e. multiple rooms) or individual rooms. According to this definition, the air in a micro-environment is assumed to be instantaneously well-mixed (i.e. the pollutant concentration is the same everywhere). Micro-environmental models are used to predict average concentrations in one or two indoor compartments based on a simple parameterization of the flow rates between them and between the compartments and the outdoor air.
Whereas statistical regression models and micro-environmental models assume the air within a building to be instantaneously well-mixed, the real airflow pattern within a building may be extremely complex and not adequately represented by a model with only a single compartment (or few compartments). Often some parts of a building, particularly basements or rooms with closed doors, exchange air only very slowly with other parts of the building and, thus, the actual mixing is far from instantaneous as assumed by statistical and micro-environmental models. Therefore, real buildings are often more suitably represented as a large number of connected well-mixed chambers. This is the approach used in multizone modelling techniques, which are especially used to simulate ventilation rates. Multizone IAQ models require the user to identify and describe all the zones (rooms) of interest and the links (e.g. flow paths) between those zones (and with the outside air). They generally take into account mechanical ventilation, tightness of buildings, terrain, shielding and climate conditions. The outputs of these models include air flow rates across the envelopes, between the rooms and through the mechanical ventilation system. The network of links is described by a series of flow equations which are solved simultaneously to provide air flow rates between rooms. Assuming that air flow patterns are unaffected by any contaminant present, a mass balance calculation in each zone at each time step can be included in a multizone model to predict the variation of concentrations with time. Multizone models use average or representative values for the parameters describing the conditions in a single zone (pressure, temperature, etc.).
Limitations
Data
Indoor air source/concentration models available in Internet
| Multi- Chamber Concentration and Exposure Model (MCCEM) | |
| Short description |
With MCCEM you can estimate average and peak indoor air concentrations of chemicals released from products or materials in houses, apartments, townhouses, or other residences. The data libraries contained in MCCEM are limited to residential settings. However, the model can be used to assess other indoor environments (e.g. schools, offices) if the user can supply the necessary inputs. You can also estimate inhalation exposures to these chemicals, calculated as single day doses, chronic average daily doses, or lifetime average daily doses. (All dose estimates are potential doses; they do not account for actual absorption into the body.) |
| Regional coverage | |
| Multizone Airflow and Contaminant Transport Analysis Software (CONTAM) | |
| Short description |
CONTAM is a multizone indoor air quality and ventilation analysis computer program designed to help you determine:
CONTAM can be useful in a variety of applications. Its ability to calculate building airflows is useful to assess the adequacy of ventilation rates in a building, to determine the variation in ventilation rates over time and the distribution of ventilation air within a building, and to estimate the impact of envelope air tightening efforts on infiltration rates. The prediction of contaminant concentrations can be used to determine the indoor air quality performance of a building before it is constructed and occupied, to investigate the impacts of various design decisions related to ventilation system design and building material selection, and to assess the indoor air quality performance of an existing building. Predicted contaminant concentrations can also be used to estimate personal exposure based on occupancy patterns in the building being studied. Exposure estimates can be compared for different assumptions of ventilation rates and source strengths. |
| Regional coverage | |
| ConsExpo | |
| Short description |
ConsExpo is a set of coherent, general models that enables the estimation and assessment of the exposure to substances from consumer products and their uptake by humans. Data about the application of products and data from mathematical models are used to build up the program. The program is based on relatively simple exposure and uptake models. Using ConsExpo, it is possible to calculate the exposure to consumer products in a standardized way. ConsExpo can carry out not only calculations with point values but also calculations with distributions and for both acute and chronic situations. Sensitivity analyses can be carried out as well. |
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| Multi-Chamber Indoora Air Quality Model (MIAQ) | |
| Short description |
Research software for predicting the time-evolution of gaseous and particulate air pollutants in an arbitrary number of connected zones. MIAQ accounts for emissions, ventilation, deposition, coagulation, and chemical reactivity. The program is written in Fortran-77 and Compiles with GNU gfortran on a wide variety of platforms. |
| Regional coverage | |
Exposure models for indoor environments available in Internet
| The Air Pollutants Exposure Model | |
| Short description |
The Air Pollutants Exposure Model (APEX) is intended to be applied at the local, urban, or consolidated metropolitan area scale and currently only addresses inhalation exposures. The model simulates the movement of individuals through time and space and their exposure to the given pollutant in various microenvironments (e.g., outdoors, indoors residence, in-vehicle). The user may choose the number and types of microenvironments to be included, select the time period of interest, use either monitored ambient air quality data or values provided from dispersion or other modeling runs, and use either a mass balance approach or an empirical ratio-based (factor) approach to estimate indoor and/or in-vehicle concentrations. Results of the APEX simulations are provided as hourly and summary exposure and/or dose estimates, depending on the application, for each individual included in the simulation as well as summary statistics for the population modeled. |
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| Hazardous Air Pollutant Exposure Model (HAPEM) | |
| Short description |
The HAPEM model has been designed to estimate inhalation exposure for selected population groups to various air toxics. Through a series of calculation routines, the model makes use of ambient air concentration data, indoor/outdoor microenvironment concentration relationship data, population data, and human activity pattern data to estimate an expected range of inhalation exposure concentrations for groups of individuals. |
| Regional coverage | |
| RISK Indoor Air Quality model | |
| Short description |
The latest published version of the RISK computer model is designed to allow calculation of individual exposure to indoor air pollutants from sources. The model runs in the MS-Windows operating environment and is designed to calculate exposure due to individual, as opposed to population, activity patterns and source use. The model also provides the capability to calculate risk due to the calculated exposure |
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| Simulation Tool Kit for Indoor Air Quality and Inhalation Exposure (IAQX) | |
| Short description |
IAQX is a Microsoft Windows-based IAQ simulation software package that complements and supplements existing IAQ simulation programs (such as RISK) and is designed mainly for advanced users. In addition to performing conventional IAQ simulations, which compute the time/concentration profile and inhalation exposure, IAQX can estimate the adequate ventilation rate when certain air quality criteria are provided by the user, a unique feature useful for product stewardship and risk management. |
| Regional coverage | |
| Wall Paint Exposure Model (WPEM) | |
| Short description |
WPEM estimates the potential exposure of consumers and workers to the chemicals emitted from wall paint which is applied using a roller or a brush. WPEM is a software product that uses mathematical models developed from small chamber data to estimate the emissions of chemicals from oil-based (alkyd) and latex wall paint. This is then combined with detailed use, workload and occupancy data (e.g., amount of time spent in the painted room, etc,) to estimate exposure. |
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| Stochastic Human Exposure and Dose Simulation (SHEDS) | |
| Short description |
SHEDS-Multimedia version 3 is a probabilistic aggregate residential exposure model. Other SHEDS models, with similar approaches but addressing different chemical classes and exposure scenarios, have been developed by EPA/ORD’s exposure modeling research program to address exposures to particulate matter (SHEDS-PM), air toxics (SHEDS-ATOX), and wood (SHEDS-Wood) This modeling tool can help predict ranges of exposure in a population, enhance dose model estimates, identify critical pathways and factors, quantify uncertainties, and compare model predictions against real-world data. It has a number of unique features that advance the science of human exposure assessment, and has been peer reviewed and applied for research and regulatory support. SHEDS can link with measurements, source models, and PBPK models to quantify and reduce uncertainty in risk assessments. |
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| Exposure and Fate Assessment Screening Tool (E-FAST) | |
| Short description |
The Exposure and Fate Assessment Screening Tool, Version 2.0, also known as E-FAST V2.0, is a screening-level computer tool that allows users to estimate chemical concentrations in water to which aquatic life may be exposed, as well as generate human inhalation, drinking water ingestion, and fish ingestion exposures resulting from chemical releases to air, water, and land. E-FAST V2.0 is appropriate for use as a screening tool to assess potential exposures from chemical discharges to air (stack or fugitive releases), surface water, or land. E-FAST V2.0 can also be used to estimate potential inhalation and dermal exposures to consumer products, such as hard surface cleaners, soaps, air fresheners, paints, gasoline, and motor oil. The exposed populations assessed by the model are either some segment of the general population or consumers. |
| Regional coverage | |