Building Science Approaches for Vapor Intrusion Studies

Abstract

Indoor air concentrations are susceptible to temporal and spatial variations and have long posed a challenge to characterize for vapor intrusion scientists; in part, because there was a lack of evidence to draw conclusions about the role that building and weather conditions played in altering vapor intrusion exposure risks. Importantly, a large body of evidence is available within the building science discipline that provides information to support vapor intrusion scientists in drawing connections about fate and transport processes that influence exposure risks. Modeling tools developed within the building sciences provide evidence of reported temporal and spatial variation of indoor air contaminant concentrations. In addition, these modeling tools can be useful by calculating building air exchange rates using building specific features. Combining building science models with vapor intrusion models, new insight to facilitate decision making by estimating indoor air concentrations and building ventilation conditions under various conditions can be gained. This review highlights existing building science research and summarizes the utility of building science models to improve vapor intrusion exposure risk assessments.

1. Introduction

The World Health Organization (WHO) has guidelines for indoor air quality for nine chemicals for which toxicological and epidemological data suggest health concerns exist at relevant environmental exposure levels (1). Three of the nine chemicals (e.g. benzene, trichloethylene, tetrachloroethylene) are directly relevant to the problem of volatile organic compound (VOC) vapor intrusion. Vapor intrusion is the process by which vapors emanating from groundwater plumes or contaminated soils migrate upward in the subsurface and ultimately enter indoor air spaces. VOC concentrations in indoor air resulting from vapor intrusion can vary spatially and temporally (e.g. 2, 3). There are many possible explanations for these variations, but above ground processes including environmental and structural conditions, occupant activities and climate variability are important factors that influence variability; and these factors have not been systematically considered as part of vapor intrusion exposure risk assessments.

Many of these above ground processes are impacted by building conditions that change over disparate timescales. Variations in building mechanical ventilation systems or weather conditions are examples of variations that could occur over short time scales, and subsequently influence indoor air quality. Over longer time scales, for instance when a building ages, variations in a building’s tightness will influence the building’s infiltration, exfiltration and ventilation rates (4). Song et al. highlights the importance of building tightness and climate variability on vapor intrusion exposure risks (5). They indicated that air-tight houses (energy-efficient) in different climate zones in U.S. may be more prone to vapor intrusion compared to the less air-tight houses (“conventional” and “low-income”) because energy-efficient houses have building characteristics that likely result in lower air exchange rates (AER) (5). Folks et al. suggest that ventilation caused by depressurization and air exchange rate contribute to spatial variation in indoor air more than building foundation type (2). Brewer et al. highlight the role of climate data, building specific designs and AERs for on subslab vapor concentrations and vapor intrusion exposure risks (6). These recent studies emphasize to account for season variability in building ventilation process as important for vapor intrusion studies.

Multizone indoor air quality models commonly used in building science studies can account for not only weather conditions but also building features (such as, layout, opening size and location, mechanical ventilation) and occupant behavior to calculate building AERs and indoor air concentrations (7–10). Integrating building science into exposure risk assessments at vapor intrusion sites, will assist vapor intrusion scientists by being able to account for climate variability (the climate that building is located in), seasons effect and occupant behavior in buildings which eventually influence the building condition and air quality. This review discusses the importance of building science in vapor intrusion processes and introduces multizone indoor air quality models that can be used to evaluate vapor intrusion exposure risks.

2. Building Science Modeling Techniques

Modeling approaches in building science have focused on a variety of goals, but commonly aim to reduce energy consumption and improve indoor air quality (11). Since the late 1980s, considerable effort has been placed on modeling building ventilation processes (10). Coupling building science models and vapor intrusion models can be a promising way to create an indoor environment that accomplishes the goals of building science (i.e. reduce energy consumption and improve air quality) and vapor intrusion (i.e. healthy indoor air quality). In building science and vapor intrusion research, various simulation models and techniques are employed.

For building science, the analytical models widely used in natural ventilation usually consider wind and stack effect or a combination of these forces in buildings (12–16). The analytical solutions used in indoor air quality usually consider both diffusive and convective transport of air contaminant in buildings (17, 18). Computational fluid dynamics (CFD) methods started gaining interest in building science research to predict detailed information of airflow, pressure, temperature and contaminate distribution in buildings (19–22). The CFD models used in indoor environment modeling are computationally expensive but are able to predict spatial contaminant, pressure and temperature distribution in a zone.

Multizone indoor air quality models are faster than CFD models. Multizone computational models usually solve a conservative of mass and concentration to calculate zonal air pressure, contaminant concentration; and interzonal airflows. In multizone approaches the building is divided into various zones relative to building layout with specific characteristics. Each zone is assumed as a well-mixed zone in which temperature and contaminant concentration is homogenously distributed. Zones are connected through flow paths and multizone model is able to calculate flowrate and pressure difference through these flow paths (8).

Various multizone software have been developed in building research including: CONTAM, COMIS, AIRNET, BREEZE and ASCOS (10). CONTAM and COMIS are two of the more popular multizone airflow programs. CONTAM was developed by the “Building and Fire Research Laboratory of the National Institute of Standards and Technology” (NIST) in 1993. CONTAM is freely available software though the Building and Fire Research Laboratory of NIST with a relatively user-friendly interface and the results in post processing are easy to understand and follow. The first version was CONTAM 93 developed from AIRNET (1989) (23). After Version 3.0, CONTAM was developed to be integrated with CFD models to account for non-uniform mixing within buildings and wind flow effects around the building envelop.

COMIS (Conjunction of Multizone Infiltration Specialists) (9) was developed by an international group of experts (The Energy Performance of Building Group) at the Lawrence Berkeley National Laboratory (LBNL). Both CONTAM and COMIS account for wind, stack, and mechanical ventilation effect in changing building airflow and indoor contaminant distribution. These multizone modeling approaches have been validated in different studies that predict air flow rates or contaminant transport in buildings. Li (24) reported good agreements between the model predictions and experimental data collected in a controlled environment test laboratory and field measurement data (24, 25). Wang et al. demonstrated that the multizone model predictions agreed well with the field measurements (26).

CFD approach can calculate contaminant spatial variability in a zone while multizone models consider a uniform value of contaminant and temperature in each zone. CFD methods are computationally expensive which can be a main disadvantage of this approach (Figure 1). Coupling CFD models and multizone models is a promising way to take advantages of each method and reduce the disadvantages. The CFD model introduced by NIST to be integrated with CONTAM is CFD0 which is able to incorporate turbulence models to CONTAM.

Figure 1:

Advantages (pros) and disadvantages (cons) of various building simulation tools

In coupled CONTAM and CFD0 program, CFD0 applies to the zone where the multizone assumption fail and CONTAM applies to the rest of zones. Wang and Chen (2007) validated the results of the coupled CONTAM and CFD0 programs with experimental data from a four-zone facility at Purdue University (27). The results indicated that the coupled program (CONTAM-CFD0) calculated more accurate airflow rates compared to CONTAM and used less computing time compared to CFD0. Coupled CONTAM-CFD0 program reduced computational time up to one order of magnitude compared to CFD0 and were able to correctly predict the airflow and contaminant distribution in all zones (27).

CFD0 is a CFD program originally developed for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) project RP-927 (28) which is currently freely available through NIST. CFD0 solves a set of partial differential equations for pressure, air velocity, temperature and species concentration calculations (29). CFD0 can be internally and externally coupled to CONTAM (8, 29). In internal coupling method the CFD zone is a zone assumed poorly mixed in a well-mixed multizone building. Spatial variation of contaminant and temperature is calculated in the CFD zone and remaining zones behave like a well-mixed zone. In the internally linked method, CONTAM gives pressure boundary conditions to CFD0, and CFD0 gives the pressure boundary condition back to CONTAM until both the inputs and outputs stabilize, and solution converge (30).

In the externally coupled method, which is the method of interest in this study, outdoor air is considered as the CFD zone and building zones (rooms) are considered as well-mixed zones in CONTAM. The outdoor CFD zone accounts for wind pressure effect as a function of, wind direction, wind speed, building configuration and local terrain effects. CFD0 calculates pressure coefficients (C_p) on building envelope for each leakage path for a range of wind directions. Pressure coefficient values are a function of location of the paths on a building surface and wind direction, thus CFD does not need to run whenever wind speed changes which considerably saves computational time in coupling method. After pressure coefficient (C_p) values are calculated by CFD0 for different wind directions, CONTAM will be linked to CFD0 and uses appropriate pressure coefficient values for each flow path defined on building envelope in CONTAM. To calculate building airflows, zonal pressure, AER and indoor air concentration, CONTAM uses conservative mass and concentration equations (8, 29). In following sections, the possibility and advantage of external link of CONTAM and CFD0 in vapor intrusion studies is discussed.

3. CONTAM-CFD0 Application in vapor intrusion studies

Early versions of CONTAM has been used in some radon transport studies to predict radon concentration and interzone airflow rates in a large multizone buildings (31, 32). Persily investigated the effect of radon source terms, indoor and outdoor temperature difference and exterior and interior walls’ leakage characteristics and mechanical ventilation operation on airflow rates and radon concentration distribution in a twelve-story residential building (31). Persily reported that radon distribution within the building is not only affected by radon entry rate but also affected by the airflow pattern in the building (31).

Existing vapor intrusion models (33–35) typically focus on problem identification in single family residential buildings and the subsurface soil, without considering above ground processes effect (such as weather condition, building configuration, climate effect and occupant behavior) on contaminant concentration distribution and dynamic building AER and pressure (Table 1). Coupling vapor intrusion models with CFD0-CONTAM program is a potential field of study in vapor intrusion investigations that introduce the ability of CFD and multizone indoor air quality programs in considering weather and building condition effect on contaminant concentration distribution to vapor intrusion community (Table 1 and Figure 2). Additionally, multizone indoor air quality models can predict contaminant concentration in multiple zones of buildings, while previous vapor intrusion models usually predict indoor concentration in a single zone of building (typically the basement).

Table 1:

Advantages and disadvantages of models used in vapor intrusion and building science

	Models/methods	Proposed by	Advantages	Disadvantages
Vapor intrusion	J&E	Johnson and Ettinger (35)	Faster than finite element and finite difference methods	Do not account for above ground processes such as weather and building condition in calculating indoor air concentration
	Finite difference methods	Abreu and Johnson (33)	Gives details of soil concentration and pressure
	Finite element methods	Pennell et al. (34)	Gives details of soil concentration and pressure
Building science	CONTAM	NIST (8)	Accounts for building characteristics in calculating indoor air concentration and faster than CFD models	Not able to give details of concentration and temperature distribution
	CFD models	NIST (8)	Calculates indoor air concentration in details	Computationally expensive
	CFD0-CONTAM	NIST (8)	Accounts for building characteristics and weather condition in calculating indoor air concentration and faster than CFD models, results are more accurate than CONTAM only model	Not as fast as CONTAM only method

Figure 2:

Combination of vapor intrusion models, CFD and multizone indoor air quality programs to predict indoor air quality impacted by vapor intrusion sites.

Notes: Inputs and outputs are shown for each model. Wind pressure coefficients are the output of CFD0, which is required as input for CONTAM. CONTAM requires contaminant flux as the input to predict indoor air concentration. Contaminant flux can be estimated by vapor intrusion models or from field site measurements.

In CONTAM, we need to identify an appropriate representation of the building as a collection of zones that exchange air with each other through the air flow paths with appropriate leakage characteristics between the zones (zones can be the building rooms or outdoor area). Leakage characteristics can be measured using the air leakage measuring methods (4, 36) or can be specified using the suggested air leakage area (Effective leakage area (ELA)) values in ASHRAE Handbook of Fundamentals (37). In general, there are too many leakage paths in a building to be measured, therefore the range of ELA values for different kind of pathways suggested by ASHRAE Handbook of Fundamentals are a reliable source of ELA values to be used in multizone indoor air quality programs (37).

CONTAM can account for an unlimited number of contaminants and sources within a given building model (8). The rate at which contaminant enters a building is the link between vapor intrusion models and CFD0-CONTAM program (Figure 2). Entry rate of contaminant is an input value in multizone indoor air quality models that can be determined using vapor intrusion models (33–35) or measured in a building located on vapor intrusion sites. Shirazi and Pennell linked a 3D vapor intrusion model to CFD0-CONTAM to improve previous vapor intrusion modeling approaches and predicted building AER, indoor pressure and indoor air concentrations based on weather conditions and building characteristics (38).

Table 2 indicates the advantages of new developed vapor intrusion model (which is a combination of previous vapor intrusion models with CFD0-CONTAM) (38) compared to previous vapor intrusion models. As shown in Table 2, the building AER’s and pressure difference between indoor and outdoor was a user defined value in previous vapor intrusion models, however building AER and pressure difference between indoor and outdoor is a function of many factors including, weather conditions, building characteristics and occupants behavior. Shirazi and Pennell indicated that vapor intrusion models can be improved by being coupled with building science programs and predict building AER and indoor air concentration considering above ground processes (38).

Table 2:

Values calculated in previous vapor intrusion models compared to values calculated in vapor intrusion model linked to CFD0-CONTAM programs

Values	Previous vapor intrusion models	vapor intrusion model linked to CFD0-CONTAM programs
Indoor pressure	User defined	Calculated Based on building and weather condition
Outdoor air pressure profile	Not calculated	Calculated
Building air exchange rate	User defined	Calculated Based on building and weather condition
Mass entry rate	Calculated	Calculated
Soil concentration profile	Calculated	Calculated
Soil pressure profile	Calculated	Calculated
Indoor air concentration	Calculated	Calculated

Indoor air concentration variations in vapor intrusion studies have multiple explanations including mass entry rate variation, building and weather condition variations, climate zone in which the building is located, etc. Considering building simulation technique capabilities in estimating indoor air concentration and building airflow rates, this review suggests incorporating building simulation tools at vapor intrusion studies could provide useful information. The new developed model by Shirazi and Pennell calculated AER and indoor air concentration under different weather conditions and compared the model results with previous models (33, 34) in vapor intrusion studies (38). Shirazi and Pennell reported that their model compares qualitatively well with field data collected by Luo et al. (39).

4. Conclusion

Vapor intrusion is well-known to be difficult to characterize using field data because indoor air concentrations exhibit considerable temporal and spatial variability throughout impacted communities. Using building science information, vapor intrusion scientists can evaluate how weather and building conditions may impact vapor intrusion exposure risks, in particular indoor air concentrations. Incorporating building science perspectives and tools is advantageous over focusing primarily on subsurface fate and transport processes. Figure 2 and Table 2 highlight that by integrating building science into vapor intrusion modelling approaches, the role that building and weather conditions play in altering vapor intrusion exposure risks can be better understood.