NISTIR 6461 

Measurement and Simulation of the IAQ Impact of 

Particle Air Cleaners in a Single-Zone Building

Steven J. Emmerich

Steven J. Nabinger

U.S. Department of Commerce

National Institute of Standards and Technology

Building and Fire Research Laboratory

Gaithersburg, Maryland 20899

United States Department of Commerce 

Technology Administration

National Institute of Standards and Technology
i

NISTIR 6461

Measurement and Simulation of the IAQ Impact of 

Particle Air Cleaners in a Single-Zone Building

Steven J. Emmerich

Steven J. Nabinger

February 2000

Building and Fire Research Laboratory

Gaithersburg, Maryland 20899

U.S. Department of Commerce 

William M. Daley, Secretary 

Technology Administration

Cheryl L. Shavers, Under Secretary for Technology

National Institute of Standards and Technology

Raymond Kammer, Director
i

ABSTRACT

This report describes the initial phase of an effort to evaluate the ability of multizone airflow and 

pollutant transport models to predict the impact of residential IAQ control technologies. 

Measurements of the performance of several particulate air cleaning devices and related particle 

transport parameters were performed in a one-room test house. These measurements were used 

to calculate building air change rates, particle deposition rates and penetration factors, and air 

cleaner removal efficiencies. Two separate 24 h tests were performed with two of the tested air 

cleaners, and the measured air change rates and particle concentrations were compared to 

predicted values obtained with the CONTAM model. For both tests, simulated 24 h average air 

change rates were within 5 % of measured air change rates and simulated 24 h average particle 

concentrations were within 30 % of measurements for all particle sizes. Simulations were also 

performed to predict the impact of the air cleaners compared to a typical furnace filter.

Key Words: air cleaners, airflow modeling, building technology, computer simulation, 

infiltration, multizone, residential buildings, and validation.
ii
iii

Table of Contents

Abstract i

List of Tables v

List of Figures vii

Introduction 1

Background 1

Literature Review 2

Experimental Procedure 4

Test House 4

Instrumentation 5

Air Cleaners 9

Experimental Results 10

Infiltration Rates 10

Deposition Rates 11

Penetration Factors 13

Filtration Efficiencies from Decay Tests 14

Filtration Efficiencies from Direct Measurements 17

Particle Generator Source Strengths 19

Ozone Generation 20

Long Term Test of MAC5 21

Simulation Procedure 23

CONTAM Model 23

Comparison of Predictions and Measurements 25

Statistical Evaluation of Model Predictions 25

Infiltration Rates 26

Tracer Gas Concentrations 26

Mechanical Air Cleaner Performance 27

Electronic Air Cleaner Performance 29

Statistical Evaluation 31

Impact of Air Cleaners 32

Discussion 34

Acknowledgements 35

References 36
iv
v

List of Tables

1 Summary of Total Decay Rates for Deposition Cases 13

2 Average Deposition Rates with HVAC System On and Off 13

3 Penetration Factors 14

4 Summary of Total Decay Rates for Air Cleaner Cases 15

5 Decay Test Filter Efficiencies (Subtracting System-Off Deposition) 16

6 Decay Test Filter Efficiencies (Subtracting System-On Deposition) 17

7 Direct Measurement Filtration Efficiencies 18

8 Particle Generator Source Strength 20

9 Average Ozone Concentrations During EAC1 Tests 21

10 Air Leakage Values 24
vi
vii

List of Figures

1 Schematic Elevation of Test House 4

2 Schematic Floorplan of Test House 5

3 Schematic of HVAC System 6

4 Outdoor Particle Counts Sampled with and without Diluter 7

5 Measured Hourly Infiltration Rates (Wind Speed < 0.5 m/s) 10

6 Measured Hourly Infiltration Rates (|Tin-Tout| < 5 °C) 11

7 Mixing in Test House for Case d74 12

8 Sample In-duct Particle Counts for EAC1 18

9 Comparison of Filtration Efficiencies from Three Test Methods 19

10 Transient Ozone Concentration due to EAC1 Operation 20

11 Long Term Efficiency Test of MAC5 22

12 Correlation of Filter Weight and Relative Humidity 22

13 CONTAM Sketchpad Representation of Test House 23

14 Measured and Simulated Blower Door Test Results 24

15 Measured and Simulated Air Change Rates 27

16 Measured and Simulated Tracer Gas Concentrations 28

17 Comparison of Measured and Simulated Particle Counts with 

Direct MAC1b Filtration Efficiency 28

18 Comparison of Measured and Simulated Particle Counts with 

Decay Test MAC1b Filtration Efficiency 29

19 Comparison of Measured and Simulated Particle Counts with 

Direct EAC1 Filtration Efficiency 30

20 Comparison of Measured and Simulated Particle Counts with 

Decay Test EAC1 Filtration Efficiency 31

21 Impact of MAC1b Compared to Furnace Filter 32

22 Impact of EAC Compared to Furnace Filter 33
1

INTRODUCTION

This report describes experiments and simulations performed to evaluate the capability to 

accurately simulate the impact of particle air cleaners with a multizone airflow and indoor air 

quality (IAQ) model, in this case CONTAM. The first task of this effort was to review published 

studies relevant to the performance of particulate air cleaning technologies. Various aerosol 

transport parameters and the performance of several particulate air cleaners were then measured 

in a single-zone test house. Measurements and CONTAM predictions were then compared to 

evaluate the ability of the model to predict the performance of air cleaners and to identify any 

model development needs.

Background

There is increasing interest world-wide in the use of consensus performance standards for 

housing. The potential benefits include the removal of barriers to the acceptance of housing 

innovation in the global marketplace and the improvement of communications between producers 

and consumers leading to enhanced quality and performance of housing. However, the state-ofthe-art in IAQ regulations are building codes based on prescribed ventilation rates such as in 

American Society of Heating, Refrigerating and Air-Conditioning Engineers Standard 62-1999 

(ASHRAE 1999). Standard 62 and many codes mandate ventilation rates based on occupancy 

and/or floor area for both residential and commercial buildings. This type of requirement makes it 

difficult to take credit for innovative IAQ control technology. It also ignores other important 

factors such as outdoor pollutant concentrations and variations in indoor source strengths. 

A major effort is underway within the Building and Fire Research Laboratory (BFRL) of National 

Institute of Standards and Technology (NIST) to develop residential performance standards 

covering a number of building attributes, including indoor air quality (Persily 1999). Performance 

standards specify how components must perform instead of the manner in which that performance 

is to be obtained. The standards relevant to the indoor environment will ultimately be based on the 

indoor levels of specific airborne contaminants and thermal comfort parameters. Early versions of 

the standards, however, will likely be based on performance in terms of building ventilation rates 

due to the current lack of knowledge of human response to indoor pollutant levels and other 

environmental parameters. Because measuring ventilation rates, contaminant concentrations and 

thermal comfort parameters in a large number of buildings would be expensive, compliance with 

these criteria will likely involve the use of predictive methods. These predictive methods will be 

based on building ventilation and indoor air quality models such as the CONTAM multizone IAQ 

model developed in BFRL (Walton 1997). Before a CONTAM-based compliance approach can 

be incorporated into a performance standard, its predictive reliability must be demonstrated 

through experimental validation. While a number of studies have examined this issue (such as 

Herrlin 1992, GEOMET 1992, and Yuill and Upham 1997), there is a need to compile the 

information and perform further validation work - particularly in simulating the impact of IAQ 

control technologies. 

Closely related to the issue of indoor environment performance standards is the issue of 

performance evaluation of specific indoor environment control technologies, such as residential 

ventilation systems and controls, air cleaning systems, humidity control technologies, and IAQ 

sensors. These potentially beneficial technologies have not gained wide acceptance in the 
2

marketplace, in part due to incomplete performance data from field tests or simulation studies. 

Therefore, validated predictive methods can be useful in evaluating the benefits and impacts of 

such technologies, both within the context of performance standards and potentially as a means of 

marketing and rating these technologies. Such performance evaluation is also needed to further 

develop these IAQ control technologies. 

Therefore, to support development of performance standards and to begin demonstrating the 

ability of models to predict the impact of IAQ control technology, NIST has begun a project to 

validate CONTAM’s predictive capability. The first effort in this project addressed the 

performance of particle air cleaners in a single-zone test house. This report describes this 

experimental validation effort with particle air cleaners. 

Literature Review

Before starting the validation experiments, the literature was reviewed for information related to 

particles in residential buildings including air cleaner test standards, air cleaner test studies, and 

aerosol transport parameters. A comprehensive review of over 100 reports of particles in indoor 

air was recently published by Wallace (1996). This review concluded that indoor particle 

concentrations ranged from about the same as outdoor particle concentrations up to double the 

outdoor concentration. The major sources of particles inside homes and other buildings were 

identified as cigarette smoke, cooking, and outdoor particles. Cleaning activities and combustion 

appliances are smaller contributing sources, while a significant fraction comes from unidentified 

sources. 

In the past, the most relevant test method for in-duct residential particulate air cleaners was

ASHRAE Standard 52.1 (ASHRAE 1992), but this standard has several deficiencies that have 

been noted in the literature. For example, Hanley et al. (1994) points out that the weight 

arrestance test yields misleading results as it does not quantify results as a function of particle size 

and is biased by the large fraction by weight of larger, and easier to remove, particles. This and 

other deficiencies have led to a new ASHRAE Standard 52.2 “Method of Testing General 

Ventilation Air-Cleaning Devices for Removal Efficiency by Particle Size” that addresses this and 

other issues (ASHRAE 1999).

Another relevant test standard is the Association of Home Appliance Manufacturers (AHAM) 

Standard AC-1 for testing the performance of portable air cleaners (ANSI/AHAM 1988). This 

test method determines the performance of an air cleaner based on the decay rate of an elevated 

particle concentration in a test chamber. The air cleaner performance is expressed in terms of a 

Clean Air Delivery Rate (CADR) which is essentially the equivalent amount of particle-free 

ventilation air needed to achieve the same particle decay rate. Although not size-delineated, the 

test challenges an air cleaner with three different types of particles (cigarette smoke, Arizona road 

dust, and paper mulberry pollen) to yield three different CADR values. Although CADRs were 

not calculated, the method applied in this study resembled the AC-1 method in many aspects.

There have been several published reports of particle air cleaners for the residential market – most 

in the last decade. These include scientific studies of particle air cleaner performance in test 

chambers/houses (Offerman et al. 1985, Offerman et al. 1991, Hanley et al. 1994, and Bascom et 
3

al. 1996) and air cleaner tests in occupied homes (CMHC 1999, Burroughs and Kinzer 1998, 

Abraham 1999, Reisman et al. 1990, Swanson et al. 1985, Lofcoe and Inculet 1971, and 

Luczynska et al. 1990). A recent American Lung Association report summarizes many of these 

reports (ALA 1997). Among the reviewed reports is a recent article that rated 11 portable and 16 

in-duct air cleaners (Consumer Reports 2000). The air cleaners were challenged with cigarette 

smoke and dust and evaluated for odor removal, cost, upkeep, and noise. 

Two key particle-related parameters that impact indoor particle concentrations are particle 

deposition rates and penetration factors. Deposition can be a significant mechanism for removal of 

particles from indoor air through contact with room surfaces. It is typically accounted for as a 

first-order loss mechanism that is frequently treated as the product of a room surface-to-volume 

ratio and a deposition velocity. The particle penetration factor is the fraction of outdoor particles 

that enters an indoor space with infiltrating air as it moves through the building envelope. 

A review of 66 publications on deposition rates and the use of deposition velocity was published 

by Nazaroff et al. (1993). This review found that, despite a sound theoretical concept and 

successful empirical application of the deposition method, caution is warranted in its application 

due to several limitations. These limitations include possible lack of uniform mixing, deposition 

may vary with location, first order rate assumption may be inadequate, and transport rates 

through boundary layers may depend on near-surface airflow conditions. The review reports a 

range of published deposition velocities for ‘fine particles’ from 2 x 10-5 cm/s to 5 x 10-3 cm/s. 

Assuming a typical room surface-to-volume ratio of 3 m-1, the equivalent deposition rates would 

range from 7.2 x 10-4 h-1 to 0.18 h-1. Other published measurements of deposition rates have 

included an average from 5 tests of 0.48 h-1 for fine particles from a gas-fired range in a test 

chamber (Traynor et al. 1982), average values of 0.39 h-1 for particles smaller than 2.5 μm and 

1.10 h-1 for particles between 2.5 μm and 10.0 μm from a study in 178 homes (Wallace 1996), 

average values in a residence of 0.46 h-1 for 1 μm to 5 μm particles and 1.36 h-1 for 5 μm to 10 

μm particles (Thatcher and Layton 1994), and mass-weighted average values for tobacco smoke 

particles of 0.05 h-1 and 0.1 h-1 in a research house (Offerman et al. 1985 and 1991).

Fewer measurements of penetration factors have been reported. One study reports penetration of 

1 for various size particles in a single residence (Thatcher and Layton 1994), with another study 

also reporting 1 for all size particles in 178 homes (Wallace 1996). A value of 1 indicates no 

filtering of particles by the building envelope. One study reported a penetration of 0.4 for particles 

smaller than 0.5 μm in an environmental chamber (Traynor et al. 1982).
4

EXPERIMENTAL PROCEDURE

Measurements of the performance of several particulate air cleaners and related particle transport 

parameters were performed in a one-room test house. These measurements were used to calculate 

building air change rates, particle deposition rates and penetration factors, and air cleaner removal 

efficiencies. Most of the tests consisted of the generation of particles indoors and the monitoring 

of the decay of the indoor particle concentration. Some parameters were determined by 

monitoring approximately steady state particle concentrations in the house. Two separate 24 h 

tests were then performed with two of the tested air cleaners, and the measured air change rates 

and particle concentrations were compared to corresponding simulations performed with the 

CONTAM model.

Test House

The initial phase tests were performed in a single-room test house located on the NIST campus 

(Burch et al. 1982). The test house has a floor area of 37 m2 (400 ft2) and a ceiling height of 2.3 

m (7.5 ft). Its construction details include uninsulated wood-frame walls, paneled wood exterior, 

painted gypsum board interior, slab-on-grade foundation, unpainted concrete floors, vented attic 

and asphalt-shingled roof. The house also has two double-hung windows on the north and south 

walls and a metal exterior door filled with perlite insulation on the east wall. A fan pressurization 

test, performed according to American Society for Testing and Materials Standard E779-99 

(ASTM 1999), found the building air change rate at 50 Pa to be 7.3 h-1 and the effective leakage 

area at 4 Pa to be 140 cm2 (21.1 in2). A schematic elevation and a floorplan of the house are 

shown in Figure 1 and Figure 2, respectively. The test house has a heating, ventilating and airconditioning (HVAC) system featuring a 4.1 kW (14,000 Btu/h) electric-resistance furnace, a 3.8 

kW (13,000 Btu/h) air conditioner, and a nominal recirculation flow of 0.17 m3/s (360 cfm). As is 

typical for residences, the HVAC system has no outdoor air intake. A schematic of the system is 

shown in Figure 3.

2.3m (7.5 ft.)

6.1m (20.0 ft.)

7.3m (24.0 ft.)

Wall Pressure 3.9m (12.8 ft.)

 Transducer

Wall Pressure

 Transducer

1.5m

(5.0 ft.)

 Pressure

Transducer

Figure 1 Schematic Elevation of Test House
5

Figure 2 Schematic Floorplan of Test House

Instrumentation

Sample Locations

Figure 2 shows a schematic of the test house floorplan including instrumentation and sample 

locations. There were seven indoor sampling locations as follows: one location about 1.5 m (5 ft) 

above the floor and 0.3 m (1 ft) from the center of each wall and three locations in the center of 

the room at heights of 0.3 m (1 ft), 1.5 m (5 ft) and 2.0 m (6.6 ft) above the floor. Outdoor air 

samples were taken at a location sheltered by the eave of the roof, 2.1 m (6.9 ft) above the 

ground, 2.2 m (7.3 ft) from the west end of the north wall and 0.3 m (1 ft) from the wall. Particle 

counts were sampled at three locations in the HVAC duct including before the air cleaner, after 

the air cleaner, and after the standard furnace filter (see Figure 3). 

Infiltration

The air change rate was measured using the tracer gas decay technique as described in ASTM 

Standard E741(ASTM 1995) with sulfur hexafluoride (SF6) as the tracer gas. The automated air 

infiltration rate measurement system consists of a PC-based data acquisition and control system 

and a gas chromatograph (GC) with an electron capture detector (ECD). The system 

automatically injected SF6 into the house every 12 h to 24 h. The GC-ECD was used to determine 

SF6 concentrations over a range of 5 parts per billion (ppb(v)) to 150 ppb(v) with an accuracy of 

approximately 2 %. The tracer gas system uses a ten-port sample valve to sample air at seven 

indoor locations and one outdoor location every 10 min. The hourly air change rate is then 

determined by performing a linear regression of the logarithm of the SF6 concentration versus 

time. The uncertainty of the measured air change rates is approximately 10 %. 
6

Figure 3 Schematic of HVAC System (Front and Side Views)

Particles

Airborne particle concentrations were measured with an optical particle counter utilizing a wide 

angle light scattering technique, calibrated by the manufacturer to a nominal accuracy of 20 %. It 

yields counts of particles in six size ranges: 0.3 μm to 0.5 μm, 0.5 μm to 0.7 μm, 0.7 μm to 1.0 

μm, 1.0 μm to 5.0 μm, 5.0 μm to 10.0 μm, and >10 μm. The particle counter was used in 

conjunction with a thirty-port sample valve to sample sequentially from all of the indoor, outdoor 

and HVAC duct locations. The particle counter has a controlled sample flow of 5 x 10-4 m3/s (1 

cfm) and a total concentration limit of 4.5 x 107 particles/m3 (1.35 x 106 particles/ft3). 
7

With the tube sampling system, there will be some unavoidable loss of particles within the 

sampling tubes due to physical processes including diffusion, settling, impaction, static attraction, 

and other loss factors. Sample losses were minimized by ensuring that the manufacturer’s 

minimum flow rate was maintained through all tubes and minimizing the number of bends in the 

tube runs. Tests by the manufacturer estimated losses through a 15 m (50 ft) sample tube were 2 

% for 0.3 μm to 0.5 μm, 4 % for 0.5 μm to 1.0 μm, 8 % for 1.0 μm to 5.0 μm, and 15 % for >5 

μm particles (Climet 1994). Since the longest sample tube run in the test house was 11 m (36 ft), 

the potential particle loss was judged an acceptable trade-off for the better relative accuracy made 

possible by using a single counter for all indoor and outdoor locations.

Since the indoor and outdoor particle counts at times exceeded the counter limit, a particle diluter 

with a nominal dilution ratio of 100 to 1 was used during some of the tests. The diluter operated 

by diverting 99 % of the sample flow through a zero filter and allowing 1 % of the flow to pass 

through unfiltered. The actual dilution ratio was found to vary by size of the particles but was 

consistent over the duration of the individual tests performed. The variation in dilution by size 

ratio and from test to test has no significant impact on any of the parameters estimated from 

particle measurements. However, caution must be used in calculating actual particle counts by 

simply multiplying the values reported with the diluter by 100. Figure 4 shows the impact of the 

diluter on particle counts. Due to the use of the diluter, the already low concentrations of larger 

particles and the magnitude of sample tube losses, no useful data was obtained for the two size 

ranges larger than 5.0 μm. 

1.0E+03

1.0E+04

1.0E+05

1.0E+06

1.0E+07

1.0E+08

0:05:30 28-Dec4:05:30 28-Dec8:05:30 28-Dec

12:05:30 28-Dec16:05:30 28-Dec20:05:30 28-Dec

0:05:30 29-Dec4:05:30 29-Dec8:05:30 29-Dec

12:05:30 29-Dec16:05:30 29-Dec20:05:30 29-Dec

Particle count (#/m

3

)

0.3 - 0.5 um 0.5 - 0.7 um

0.7 - 1.0 um 1.0 - 5.0 um

Figure 4 Outdoor Particle Counts Sampled with and without Diluter
8

Other Parameters

Indoor and outdoor temperatures were measured with thermistors having an uncertainty of about 

0.4 °C (0.7 °F). To measure wind speed and direction, an anemometer was installed on the west 

exterior wall about 2 m (6.6 ft) above the crest of the roof. Indoor and outdoor relative humidity 

was measured with bulk polymer resistance sensors with an accuracy of 3 % of the reading. The 

pressure differences across the exterior walls were measured by differential pressure transducers 

located 1.5 m (6 ft) above the floor at the midpoint of each wall. The transducers have a range of 

-25 Pa to 25 Pa (-0.1 in. to 0.1 in. of water) and an accuracy of 1 % of full scale. A similar 

pressure transducer with a range of -62.5 Pa to 62.5 Pa (-0.25 in. to 0.25 in. of water) was used 

to measure the pressure drop across the tested air cleaners.

Ozone was monitored to evaluate its generation as a side effect of electronic air cleaner operation. 

Indoor and outdoor ozone concentrations were measured with ultraviolet photometric ozone 

analyzers with a range of 0 ppm(v ) to 1.0 ppm(v). The ozone meters were calibrated against an 

ozone standard generated by a calibration subsystem of one of the meters. This calibration yielded 

a 95 % confidence interval for the meters of approximately ±5 ppb(v) over a measurement range 

of 5 ppb(v) to 300 ppb(v). 

The airflow rate through the HVAC system was measured by initially performing a velocity 

traverse with a hot wire anemometer (HWA) to find a point representative of the average velocity 

in the return duct. The HWA has an uncertainty of 2.5 % of the indicated reading. The 

measurements were performed in accordance ASHRAE Standard 111 (ASHRAE 1988) which is 

estimated to result in an uncertainty of 5 % to 10 % in field conditions. Then, another HWA was 

mounted at that point to measure an estimated average duct velocity during the individual tests. 

An interesting observation was made on the quality of installation of the air cleaner by the HVAC 

contractor. A velocity traverse performed after the contractor completed the installation yielded 

an average flow velocity of 5.65 m/s (18.6 ft/s). After the research technician sealed the joint 

between the air cleaner and duct, two additional velocity traverses were performed with an overall 

average flow velocity of 6.42 m/s (21.2 ft/s). This indicates the importance of careful installation 

to avoid significant leakage around air cleaning systems that degrade overall system performance.

Many of the tests involved raising the indoor particle concentration, using either a particle 

generator or a manual technique, and then monitoring the decay of the concentration. The particle 

generator is a constant output atomizer that directs compressed air through a 0.343 mm (0.0137 

in) hole, forming a high velocity jet. A reservoir with a hydrosol consisting of polystyrene latex 

particles is supplied to the atomizing section of the particle generator. The high velocity jet draws 

the hydrosol by aspiration to create an aerosol that is mixed with air from a pump to disperse it 

within the test house. The polystyrene latex spheres used in the particle ranged in size from 0.36 

μm to 1.53 μm. While very effective at generating high concentrations of the smaller particles, the 

particle generator was less effective at generating particles in the 1.0 μm to 5.0 μm size. For this 

reason, a manual technique was also used in some of the tests. This method consisted of pounding 

the test house floor with a large cardboard box and resulted in a strong spike in particle 

concentrations.
9

Air Cleaners

A total of five different air cleaners were tested during the study. All of the air cleaners tested 

were installed in the HVAC system ductwork. Particle removal tests were also performed with no 

air cleaner in the HVAC system. Three of the air cleaners were mechanical filters, including a 

typical furnace filter (labeled MAC4 in test results) and two higher efficiency mechanical air 

cleaners (MAC1 and MAC3). MAC1 has nominal dimensions of 0.13 m x 0.41 m x 0.61 m (5 in x 

16 in x 24 in) and a stated average arrestance of 93 %. Three different filter cartridges of the 

MAC1 type were tested and are labeled MAC1a, MAC1b, and MAC1c in the results. MAC3 has 

nominal dimensions of 0.025 m x 0.41 m x 0.64 m (1 in x 16 in x 25 in) and is described by the 

manufacturer as having electrostatically charged fibers that are more effective than ordinary 

fiberglass filters.

The remaining two air cleaners are electronic. The first electronic air cleaner (EAC1) is nominally 

0.18 m x 0.52 m x 0.64 m (7-1/4 in x 20-1/2 in x 25 in) and consists of ionizing wires at 6200 V 

that positively charge particle that are then deposited to ground collector plates. No quantified 

removal information is provided with EAC1 although the manual states that it will remove 

particles as small as 0.01 μm. EAC1 also has a mechanical prefilter that was tested separately. 

The manual also states that the unit will produce “minute” quantities of ozone and that the 

amount produced will be reduced after several weeks of operation. The second EAC (EAC2) is 

0.0051 m thick and uses a 24 V source to create a polarized charge on two replaceable collecting 

pads. EAC2 is stated as having a particle removal efficiency ranging from 33 % for 0.3 μm 

particles up to 99 % for 1.0 μm particles and larger. EAC2 is claimed to produce no ozone. 
10

EXPERIMENTAL RESULTS

Infiltration rates

As described above, the test house air change rate was measured using the tracer gas decay 

technique as described in ASTM Standard E741(ASTM 1995) with an automated multiport SF6

injection and measurement system. The SF6 concentration was measured every 10 min at 9 

locations in the test house. The test house air change rate is then determined by performing a 

linear regression of the logarithm of the concentration versus time for individual one hour periods. 

Test house infiltration rates under a range of indoor-outdoor temperature differences and wind 

speeds are shown in Figures 5 and 6, respectively. As expected, Figure 5 shows a minimum 

infiltration rate at Tin-Tout = 0 and increasing infiltration with increasing |Tin-Tout|, and Figure 6 

shows increasing infiltration with increasing wind speed.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

-10 -5 0 5 10 15

Tin - Tout (°C)

Air Change Rate (h-1

)

Figure 5 Measured Hourly Infiltration Rates (Wind Speed < 0.5 m/s)
11

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

Wind speed (m/s)

Air Change Rate (h-1)

Figure 6 Measured Hourly Infiltration Rates (|Tin-Tout| < 5°C)

Deposition rates

Particle deposition rates in the test house were determined both for use in the CONTAM model 

and for the analysis of filtration efficiencies. The analysis of deposition rates is very similar to a 

tracer gas decay test except for the need to account for the penetration of particles from outside. 

Assuming uniform particle concentrations in the test house, the mass balance equation for the 

indoor particle concentration is:

out in

in k C

V

S

aPC

dt

dC *

= + − 1

To evaluate the validity of the uniform particle concentration assumption, samples were taken at 

the seven interior locations discussed earlier. Figure 7 presents an example of the concentration 

uniformity in the house for one hour prior to turning the particle generator off for test case d74 

during which the HVAC system fan is off. 
12

2

3

45 6 89

73 73.2 73.4 73.6 73.8

Elapsed time (h)

1.0E+5

1.0E+6

1.0E+7

1.0E+8

Particle counts (#/m3)

0.3−0.5 μ

0.5−0.7 μ

0.7−1.0 μ

1.0−5.0 μ

Note: For each 10 minute series, sample order was Port 2, 3, 4, 5, 6, 8, 9.

Figure 7 - Mixing in test house for case d74

Assuming there is no indoor source (S) and that the outdoor particle concentration (Cout), the air 

change rate (a), the penetration factor (P), and the total decay rate (k*) are all constant, the 

solution to this linear, first order differential equation with arbitrary constant (C1) is:

out k t

in C e

k

aPC

C t

*

* 1

( )

−

= + 2

Thus, k* can then be determined by performing a linear regression of the logarithm of the indoor 

concentration minus aPCout/k* versus time. Since k* appears in the expression to be subtracted 

from the concentration, it was necessary to solve the linear regression through an iterative 

process. The penetration factor was assumed to be one (i.e. no filtration of particles on entry to 

building). For selected cases, the penetration factor was varied within the range of 0.5 to 1.0 with 

no significant effect on the decay rates. This decay analysis was applied to one hour of data 

following the particle generation and was performed with the HVAC system off and with the 

HVAC system on but no air cleaner in the system. Table 1 summarizes the total decay results for 

five cases with the system off and nine cases with the system on.
13

Table 1 Summary of Total Decay Rates for Deposition Cases

Run 

No.

Particle 

Generation 

Method

Duct 

Velocity 

(m/s)

Air Change 

Rate

(h-1)

Decay

.3-.5μm

(h-1)

Decay

.5-.7μm

(h-1)

Decay

 .7-1.0μm

(h-1)

Decay

1.0-5.0μm

(h-1)

Tin

(°C)

Tout

(°C)

RHin

(%)

RHou

t

(%)

d51x PGEN off 0.16 0.40 0.57 0.62 0.86 33.1 25.2 45 84

d71x PGEN off 0.21 0.60 0.90 1.00 1.06 27.6 11.7 32 29

d74x PGEN off 0.22 0.73 0.93 1.01 1.44 25.2 14.3 27 39

d75x BOX off 0.22 0.50 0.81 1.06 1.43 24.9 11.0 27 24

d76x BOX off 0.24 0.53 0.85 1.10 1.43 23.3 11.4 26 44

d40x PGEN 5.73 0.12 0.76 1.01 1.67 2.31 31.0 32.4 27 43

d61x PGEN 5.92 0.15 0.95 1.24 1.48 2.09 21.0 19.8 47 62

d62x PGEN 5.83 0.14 0.96 1.24 1.49 2.15 20.8 20.3 41 68

d66x PGEN 5.89 0.28 1.08 1.35 1.65 1.99 19.7 5.9 36 55

d67x PGEN 5.83 0.20 0.98 1.29 1.60 1.79 20.3 5.7 39 48

d79x BOX 5.90 0.20 0.98 1.47 1.85 2.24 19.7 16.0 31 25

a12x BOX 5.83 0.49 1.14 1.67 2.06 2.72 25.1 17.2 30 33

a12x BOX 5.79 0.31 0.94 1.61 2.03 2.64 19.1 19.0 36 39

a12x BOX 5.77 0.17 0.90 1.32 1.73 2.34 18.3 13.1 39 51

The deposition rate to the room surfaces can be obtained by subtracting the removal due to 

infiltration from the total decay. The total decay rates in Table 1 include other removal processes 

such as coagulation. However, for a test on the order of one hour, coagulation will be negligible 

for any particle concentration less than 1012 m-3 (Figure 12.3 of Hinds 1982). Since the particle 

concentration in the test house is less than 109 m-3 for all cases, coagulation will be neglected in 

this analysis. The average deposition rates for both the HVAC system on and off, and the 

corresponding standard deviations, are presented in Table 2. For all four size ranges, the 

deposition rate was about double with the system on vs. system off. However, it was not 

determined whether this increase was due primarily to increased deposition to room surfaces or 

deposition within the HVAC system itself. 

Table 2 Average Deposition Rates with HVAC System On and Off

Deposition 

.3-.5μm

(h-1)

Deposition

.5-.7μm

(h-1)

Deposition

 .7-1.0μm

(h-1)

Deposition 

1.0-5.0μm

(h-1)

System off

Mean 0.34 0.60 0.75 1.03

σ 0.11 0.12 0.16 0.24

System on

Mean 0.74 1.13 1.50 2.02

σ 0.08 0.12 0.14 0.24

Penetration factors

Penetration factors for the various particle sizes were determined from steady state particle 

concentration data. At steady state (and replacing k* with a+k), equation 2 becomes:

out

in

aC

a k C

P

( + )

= 3
14

The penetration factors were determined during tests with the HVAC system off so the values 

used for the deposition rates are the system-off values in Table 2. Table 3 summarizes the results 

of penetration factor calculations for five time periods of at least 1 hour during which the standard 

deviation of both Cin and Cout were less than 10 % of the average value (with the exception of the 

1.0 μm to 5.0 μm size for case d75_2). Other criteria for the time periods included in Table 3 

included the use of data measured without the diluter and a total outdoor count less than 2.5x106

particles per m3. The estimates for the smallest particles varied widely with an overall standard 

deviation that was over 35 % of the average of 0.76. The standard deviations for the larger sizes 

were all less than or equal to 20 % of the averages. However, since only five cases are included in 

Table 3, these should be used with caution and may not apply to other buildings. 

Table 3 Penetration Factors

P

.3-.5μm 

P

.5-.7μm 

P

.7-1.0μm 

P

1.0-5.0μm 

d75 0.67 0.74 0.67 0.61

d75_2 0.88 0.88 0.77 0.46

d75_3 0.82 0.78 0.68 0.69

d76 1.08 0.79 0.63 0.64

d76_3 0.35 0.49 0.55 0.59

Average 0.76 0.73 0.66 0.60

σ 0.27 0.15 0.08 0.09

Filtration efficiencies from decay tests

The decay tests to determine the filtration efficiencies of the tested air cleaners were performed in 

a manner similar to those described above for determining deposition rates. After the indoor 

generation of particles, the HVAC system with the air cleaner installed was turned on and the 

decay of particle concentration was monitored. The total decay rate (k*) for these tests was 

determined according to equation 2 above with the same assumptions of a uniform indoor particle 

concentration, no indoor source of particles, and constant Cout, a, P, and k*. Due to the rapid 

decay of particle concentrations for the electronic air cleaner EAC1, the decay rate was 

determined over 30 minutes instead of one hour. Table 4 summarizes the total decay rates for the 

air cleaner tests.
15

Table 4 Summary of Total Decay Rates for Air Cleaner Cases

Run

No.

Air

Cleaner

Particle 

Generation 

Method

Duct 

Velocity 

(m/s)

Air 

change 

rate (h-1)

Decay

.3-.5μm

(h-1)

Decay

.5-.7μm

(h-1)

Decay

 .7-1.0μm

(h-1)

Decay

1.0-5.0μm

(h-1)

Tin

(°C)

RHin

(%)

ΔP across 

air 

cleaner

(Pa)

d42x* MAC1a PGEN 6.44 0.13 1.00 1.30 1.70 2.16 22.3 34 3.0

d44x* MAC1a PGEN 6.33 0.14 1.04 1.47 1.87 2.74 22.4 33 3.6

d46x MAC1a PGEN 6.34 0.29 1.09 1.50 2.02 2.83 28.5 28 2.5

d68x* MAC1a PGEN 5.96 0.37 1.33 1.53 1.85 2.42 22.1 29 2.8

d77x MAC1a BOX 5.99 0.12 0.93 1.57 2.05 2.47 19.4 34 3.2

d77x MAC1a BOX 5.96 0.13 0.86 1.58 2.11 2.80 19.8 30 3.2

d59x MAC1b PGEN 5.83 0.21 1.23 1.53 1.72 2.54 24.8 28 2.9

d60x MAC1b PGEN 5.94 0.15 1.09 1.35 1.64 2.08 21.5 31 3.2

d68x MAC1b PGEN 5.98 0.29 1.20 1.50 1.88 2.05 20.8 30 3.6

d68x MAC1b PGEN 5.94 0.28 1.38 1.71 2.15 2.38 22.0 31 3.1

d72x MAC1b PGEN 6.10 0.33 1.39 1.85 2.26 2.72 22.6 30 3.1

d81x MAC1b BOX 6.04 0.20 0.94 1.50 1.94 2.60 22.3 34 3.7

d86 MAC1c BOX 5.83 0.15 0.15 0.96 1.50 1.93 23.5 31 3.3

d86 MAC1c BOX 5.75 0.15 0.15 0.96 1.55 2.00 22.3 35 3.3

a01 MAC1c BOX 5.67 0.18 0.19 1.44 1.96 2.18 19.7 34 3.4

a01 MAC1c BOX 5.64 0.24 0.24 1.43 2.09 2.20 19.2 38 3.5

a02 MAC1c BOX 5.76 0.15 0.15 0.83 1.53 2.03 21.2 36 3.4

a02 MAC1c BOX 5.68 0.23 0.23 0.89 2.02 2.52 24.6 36 3.2

a04 MAC1c BOX 5.83 0.25 0.25 1.00 1.57 1.98 21.5 27 3.2

a04 MAC1c BOX 5.78 0.38 0.38 1.14 1.71 2.18 24.3 26 3.4

d47x MAC3 PGEN 6.09 0.30 2.84 3.32 3.69 3.95 28.5 30 7.6

d47x MAC3 PGEN 6.14 0.23 2.93 3.45 4.24 5.37 24.4 33 7.4

d48x MAC3 PGEN 6.07 0.23 2.89 3.34 4.03 4.33 29.9 30 6.8

d80x MAC3 BOX 5.57 0.15 2.32 3.30 4.04 5.12 19.3 32 6.3

d80x MAC3 BOX 5.66 0.10 2.12 3.34 4.16 5.35 18.6 44 6.4

d82x MAC4 BOX 5.61 0.31 1.22 1.63 1.93 2.23 21.7 25 **

d82x MAC4 BOX 5.47 0.32 1.10 1.50 1.86 2.39 25.3 24 **

d82x MAC4 BOX 5.45 0.20 0.77 1.36 1.81 2.49 22.3 28 **

d55xt EAC1 PGEN 6.02 0.16 6.64 6.77 7.16 8.18 26.5 30 0.6

d56Xt EAC1 PGEN 6.13 0.18 7.26 7.25 7.11 7.85 24.7 33 1.3

d56xt EAC1 PGEN 6.06 0.14 6.49 6.68 7.20 7.81 28.8 28 1.2

d56xt EAC1 PGEN 6.15 0.12 6.44 6.70 7.14 7.87 27.5 28 1.2

d56xt EAC1 PGEN 6.18 0.22 6.78 7.06 6.81 8.21 26.1 31 1.2

d56xt EAC1 PGEN 6.14 0.22 6.72 6.83 7.15 7.90 21.8 33 1.3

d78xt EAC1 BOX 5.84 0.35 5.19 6.45 6.85 7.70 19.8 33 1.4

d78xt EAC1 BOX 5.88 0.33 5.84 6.77 7.14 8.04 20.0 30 1.4

d58x EAC2 PGEN 5.05 0.10 1.17 1.51 2.00 2.54 21.7 43 ***

d58x* EAC2 PGEN 4.86 0.12 1.14 1.48 1.80 2.59 25.9 29 ***

d81x EAC2 BOX 4.81 0.16 1.38 2.12 2.49 3.26 18.6 46 ***

d81xtt EAC2 BOX 4.80 0.17 1.35 2.03 2.42 3.11 18.6 50 ***
16

Table 4 Notes: *Total decay rate for large particles based on less than 1 hr

** No ΔP available across MAC4 due to filter location

*** No ΔP available across EAC2 due to modified air cleaner frame 

t Total decay rates for EAC1 based on half hour 

tt Air change rate calculated for 50 minutes

Subtracting the air change rate and the deposition to the surfaces from the total removal rates of 

Table 3 yields the removal rate due to the air cleaner (kac). The filtration efficiency (η) is 

calculated from the removal rate due to the air cleaner using the following equation:

V

Q

k

sys

ac

h

= 4

where Qsys is the airflow rate through the HVAC system and V is the room volume. 

Since it is not known whether the increased deposition rate for the system on cases is due to 

increased deposition to room surfaces or removal within the HVAC system and ductwork, two 

options for modeling the removal of particles due to the air cleaner and deposition were explored. 

First, the air cleaner efficiencies were calculated by subtracting the deposition with the system off 

(values from Table 2) from the total decay rates. This method includes the additional removal as 

part of the filtration efficiency. These average air cleaner efficiencies and their standard deviations 

are presented in Table 5. Also included in Table 5 are the decay results for HVAC system 

operation with no air cleaner in the system (labeled none in table) calculated as a filtration 

efficiency. The total decay rates for these no air cleaner cases was presented earlier as the bottom 

nine cases in Table 1. 

Table 5 Decay Test Filter Efficiencies (Subtracting System-Off Deposition)

Air Cleaner η

.3-.5μm 

(%)

η

.5-.7μm 

(%)

η

.7-1.0μm 

(%)

η

1.0-5.0μm 

(%)

none 6.9 9.2 13.1 17.3

σ 1.3 2.1 2.5 4.3

MAC1a 8.3 11.5 16.4 22.1

σ 1.4 2.5 3.5 4.7

MAC1b 10.6 12.4 16.1 19.1

σ 2.3 2.1 3.0 4.5

MAC1c 9.3 16.4 20.6 23.2

σ 4.2 4.4 3.3 1.8

MAC3 35.6 44.0 53.3 62.1

σ 3.9 2.9 6.0 13.8

MAC4 7.5 11.4 15.6 19.6

σ 3.1 1.4 0.8 3.7

EAC1 98.3 100.7 102.6 112.5

σ 10.2 3.4 3.2 3.1

EAC2 16.3 22.0 27.1 35.7

σ 2.2 6.7 6.7 7.6
17

Alternatively, the air cleaner efficiencies were calculated by subtracting the deposition with the 

system on (values from Table 2) from the total decay rates. This method treats the additional 

particle removal as deposition to the room surfaces rather than as part of the filter removal. These 

average air cleaner efficiencies and their standard deviations are presented in Table 6.

Table 6 Decay Test Efficiencies (Subtracting System-On Deposition)

Air Cleaner η

.3-.5μm 

(%)

η

.5-.7μm 

(%)

η

.7-1.0μm 

(%)

η

1.0-5.0μm 

(%)

MAC1a 1.8 2.8 4.0 5.8

σ 1.4 2.3 3.4 4.6

MAC1b 3.9 3.4 3.2 2.2

σ 2.2 2.1 3.2 4.5

MAC1c 2.3 7.1 7.3 5.7

σ 4.1 4.3 3.2 1.7

MAC3 28.8 34.9 40.3 45.1

σ 4.2 2.5 5.6 13.3

MAC4 0.3 1.6 1.7 1.4

σ 3.2 1.6 0.9 3.5

EAC1 91.7 91.9 90.0 95.9

σ 10.3 3.5 3.2 3.0

EAC2 8.1 11.0 11.4 15.0

σ 2.1 6.6 6.5 7.2

Filtration efficiencies from direct measurements

As mentioned above and shown in Figure 3, particle samples were taken in 3 locations inside the 

HVAC ducts: immediately upstream and downstream of the air cleaner and downstream of the 

standard furnace filter. The in-duct measurements were used to directly calculate filtration 

efficiencies using equation 5. 

C

C

upstream

downstream

direct h =1−

5

The particle counts used in equation 5 were hourly averages of 50 s to 60 s particle counts taken 

every ten minutes. Since the upstream and downstream particle counts were taken as consecutive 

samples, an attempt was made to find extended periods of data with near steady state particle 

concentrations (see for example the data shown in Figure 8). Also, it was necessary to use 

measurements without the diluter to avoid getting particle counts near zero for the larger size 

particles with the more efficient filters.
18

100

1000

10000

100000

1000000

11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00

Elapsed time (h)

Particle count (#/m

3

)

Upstream 0.3-0.5

Downstream 0.3-0.5

Upstream 0.5-0.7

Downstream 0.5-0.7 

Upstream 0.7-1.0

Downstream 0.7-1.0

Upstream 1.0-5.0 

Downstream 1.0-5.0

Figure 8 Sample In-duct Particle Counts for EAC1

A summary of the average direct measurement filtration efficiencies along with standard 

deviations calculated from at least five single hour intervals is shown in Table 7. Figure 9 

compares the filtration efficiencies estimated with the three methods for air cleaners MAC1a, 

MAC1b, MAC3, EAC1, and EAC2. Figure 9 shows that the direct method yielded results close 

to the decay minus system-on depositions method for nearly all air cleaners and particle size 

ranges. However, the decay minus system-off depositions consistently yields significantly higher 

estimates due to the inclusion of deposition in the ductwork and additional deposition in the room 

as part of the filtration efficiency. 

Table 7 Direct Measurement Filtration Efficiencies

Air Cleaner η

.3-.5 μm 

(%)

η

.5-.7 μm 

(%)

η

.7-1.0 μm 

(%)

η

1.0-5.0 μm 

(%)

none 0.24 0.18 -0.61 -8.48

σ 0.24 0.49 1.07 3.19

MAC1a 1.41 2.21 2.68 9.06

σ 0.52 0.84 3.67 5.26

MAC1b 4.81 5.47 6.52 7.92

σ 3.65 4.31 5.58 14.87

MAC3 25.96 29.74 33.39 36.67

σ 1.00 1.58 2.56 3.45

EAC1 96.57 96.26 95.45 91.46

σ 0.15 0.29 0.55 1.77

EAC2 7.27 9.56 10.12 13.07

σ 0.88 1.29 1.91 6.14
19

Decay (off)

Decay (on)

Direct

Decay (off)

Decay (on)

Direct

Decay (off)

Decay (on)

Direct

Decay (off)

Decay (on)

Direct

Decay (off)

Decay (on)

Direct

0

20

40

60

80

100

120

Filtration efficiency (%)

Test method

0.3−0.5 μ

0.5−0.7 μ

0.7−1.0 μ

1.0−5.0 μ

Figure 9 - Comparison of filtration efficiencies from three test methods

Particle generator source strengths

For the purpose of modeling in CONTAM, the source strength of the particle generator was 

estimated following the analysis described by Traynor for determining pollutant emissions from a 

gas-fired range (Traynor et al. 1982). With a constant indoor source and letting C(0) equal the 

indoor concentration at time zero, the solution to equation 1 can be written as:

[ ]

k t k t

out

in e C e

k

V

S

aPC

C t

* *

( ) 1 (0)

*

− −

− +

+

= 6

By rearranging, the source strength can be found from the increase in Cin after time T (equation 3 

of Traynor et al. 1982):

[ ]

out k T

k T

aPC

e

C T C e

k

V

S

−

−

−

=

−

−

*

*

1

( ) (0) *

7

Since there is the possibility of inconsistency of setting the air pressure regulator on the particle 

generator and of depletion of particles in the reservoir mixture, the particle generator source 

strength was tested before and after the EAC1 and MAC1 tests described in the simulation 

section of this report. Table 9 gives the resulting source strengths by particle size for each one 
20

hour test and the average source strength. The source strength tests were performed with 

measurements through the diluter and a nominal multiplier of 100 was applied to the results.

Table 8 Particle Generator Source Strength

0.3−0.5μm

(#/m3h)

 0.5−0.7μm

(#/m3h)

0.7−1.0μm

(#/m3h)

1.0−5.0μm

(#/m3h)

Before 21300000 3820000 900000 241000

After 23800000 2630000 1030000 224000

Average 22500000 3230000 966000 233000

Ozone generation

As mentioned in the air cleaner description above, one consequence of operating EAC1 is the 

generation of ozone. An example of the ozone buildup due to EAC1 operation, and its subsequent 

decay after turning off EAC1, is shown in Figure 10. Table 8 summarizes the average indoor and 

outdoor ozone concentrations measured during the decay periods while testing EAC1. The ozone 

concentrations in Table 8 should not be taken as indicative of the concentrations that would result 

in a typical residential application of EAC1 because the test house has a much smaller volume and 

is tighter than the typical house. EAC2 was found to produce no ozone as claimed.

0

25

50

75

100

125

150

175

1.8 2.2 2.6 3.0 3.4 3.8 4.2 4.6 5.0 5.4 5.8 6.2 6.6 7.0

Elapsed Time (hr)

Ozone Concentration (ppb)

Indoor

Outdoor

Figure 10 Transient Ozone Concentration due to EAC1 Operation

The ozone generation rate of EAC1 was estimated using Equation 6. Estimates were made for 

five one-hour EAC1 operation periods similar to Figure 10. Table 8 summarizes the initial and 

final indoor ozone concentrations, average outdoor ozone concentrations, and measured air 

change rates for the five periods. The ozone concentrations in Table 8 should not be taken as 

indicative of the concentrations that would result in a typical residential application of EAC1 

because the test house has a much smaller volume and is tighter than the typical house. The decay 

constant, k, was taken from the literature as concerns about the continued generation of ozone 
21

after turning EAC1 off prevented using measured decay rates. Nazaroff et al. (1993) summarized 

measured ozone decay rates ranging from 1.44 h-1 for a stainless steel room to 7.56 h-1 for a 

cleanroom. Since the test house is furnished approximately like an office, the average value 

reported for offices (3.7 h-1) was chosen. The penetration factor, P, was assumed to be 1.0, 

although varying it had little effect on the estimates. The average ozone generation rate for the 

five test periods was 5.4 x 10-4 m3/h with a standard deviation of 9.4 x 10-5 m3/h. 

EAC2 was found to produce no ozone as claimed by the manufacturer.

Table 9 Ozone Concentrations During EAC1 Tests

Test

Cinitial

(ppb(v))

Cfinal

(ppb(v))

Cout

(ppb(v))

Air change 

rate

(h-1)

d56 70 147 42 0.19

d56 63 135 50 0.14

d56 63 151 39 0.12

d56 93 182 52 0.22

d56 114 200 22 0.22

Long term test of MAC5

A long term test of one mechanical air cleaner was performed as an initial attempt to characterize 

the change in filter performance with loading for modeling purposes. For the long term test, a new 

mechanical air cleaner cartridge (MAC5) was inserted in the system and the initial performance 

was measured by the decay method with the box method of particle generation as described 

above. Then the HVAC system was operated continuously with particle decay tests performed at 

approximately one week intervals. Also, the filter cartridge was weighed weekly to determine if 

the filter loading could be tracked by the weight.

The analysis of the results indicates that a weak trend of increasing pressure drop and filtration 

efficiency for the largest particles could be seen after about 80 days of operation (see Figure 11). 

However, the relative cleanliness of the NIKE test house (as evidenced by the lack of a mat of 

fibers on the filter) limited the usefulness of this test. In fact, the variability in filter weight 

correlated with relativity humidity better than time in service (see Figure 12) This test will be 

repeated in an occupied house which should involve more significant and realistic loading of the 

filter.
22

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80

Days of operation

Efficiency (%)

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Pressure drop

0.3 − 0.5 μ 

0.5 − 0.7 μ 

0.7 − 1.0 μ 

1.0 − 5.0 μ 

Pressure drop

Figure 11 Long Term Efficiency Test of MAC5

y = 0.3681x + 962.83

R

2

 = 0.8893

970

972

974

976

978

980

982

15 20 25 30 35 40 45 50 55

Relative Humidity (%)

Weight (g )

Filter weight

Linear Trendline

Figure 12 Correlation of Filter Weight and Relative Humidity 
23

SIMULATION PROCEDURE

This section of the report describes the CONTAM model of the test house. This model was used 

to compare CONTAM predictions of air change rates and pollutant concentrations to 

measurements.

CONTAM Model

The test house described in the measurement section was modeled using CONTAM (Walton 

1997) - a program for analyzing the air movement and IAQ in multizone buildings. CONTAM has 

a graphic interface, or Sketchpad, used to create and edit a description of a building’s features 

relating to airflow and the generation and removal of contaminants. This data along with ambient 

weather and pollutant contaminant data are used to calculate the airflows and concentrations of 

indoor contaminants. 

Figure 13 CONTAM Sketchpad Representation of Test House

The graphical representation of the main floor of the test house as it appears in CONTAM is 

shown in Figure 13. The test house attic was included in the model but is not shown. Ideally, the 

air leakage model of the house could be created by performing leakage tests on the individual 

airflow paths (wall joints, windows, etc.). However, such an impractical experimental effort was 

avoided by a two-step modeling process. First, individual air leakage elements were created in 

CONTAM based on best estimate values from Table 25-3 of the ASHRAE Handbook of 

Fundamentals (ASHRAE 1997). This step ensures a realistic distribution of appropriate airflow 

elements. Then, the leakage values of the individual elements were adjusted such that the resulting 

flows from a simulated blower door test matched those from a real blower door test. A 
24

comparison of the simulated and real blower door test results is shown in Figure 14, and the 

resulting airflow leakage elements are summarized in Table 10. The leakage elements in Table 10 

are for a reference pressure difference of 4 Pa and a discharge of 1.0 with a flow exponent of 0.63 

based on the blower door test.

0.1

0.12

0.14

0.16

0.18

0.2

10 20 30 40 50 60 70

Pressure (Pa)

Flow (m

3/s)

M easured

Simulated

Figure 14 Measured and Simulated Blower Door Test Results

Table 10 Air Leakage Values

Airflow element description Effective Leakage 

Area at 4 Pa

Wall-wall joint 0.864 cm2/m

Ceiling-wall joint 0.864 cm2/m

Floor-wall joint 2.08 cm2/m

Window 3.37 cm2

Ceiling 0.908 cm2/m2

Door frame 1.7 cm2/m2

Door (distributed at 3 locations vertically) 21 cm2

Wall penetration (4 on N wall, 2 on S wall, 1 on W wall) 1.3 cm2

Ceiling penetration 2.13 cm2

Attic vent (on N and S walls) 0.045 m2

Attic vent (on E and W walls) 613 cm2
25

COMPARISON OF PREDICTIONS AND MEASUREMENTS

This section of the report compares the results of model predictions and measurements for two of 

the tested air cleaners. The two air cleaners chosen for comparison of simulations and 

measurements were the electronic air cleaner EAC1 and the mechanical air cleaner MAC1b. Both 

cases modeled cover a 24 h time period during which the HVAC system was operated 

continuously with an air cleaner installed and operating. In the results below, the 24 h test with 

MAC1b is called case d72 and the 24 h test with EAC1 is called case d74. In both cases, the 

particle generator was used as a continuous source of particles for four hours. During the 24 h 

tests, infiltration rates, indoor and outdoor particle counts, temperatures, duct flow, and relative 

humidities were measured as described in the procedure section. The temperature in the attic was 

not measured but was modeled as equal to the average of the indoor and outdoor temperature. 

For each air cleaner, two approaches to modeling the air cleaner performance were considered. 

First, the air cleaners were modeled with the removal efficiencies determined by direct in-duct 

measurements (values in Table 7) in combination with the deposition rates determined for system 

on (values in Table 2). Second, the total removal efficiencies associated with the air cleaner as 

determined by decay tests (values in Table 5) were used in combination with the deposition rates 

for system off (values in Table 2). 

Statistical Evaluation of Model Predictions

ASTM D5157 “Standard Guide for Statistical Evaluation of Indoor Air Quality Models” provides 

quantitative and qualitative tools for evaluation of IAQ models (ASTM 1991). It provides 

guidance in choosing data sets for model evaluation and focuses on evaluating the accuracy of 

indoor concentrations predicted by a model. As part of the comparison of CONTAM predictions 

to test house measurements, the ASTM D5157 criteria were applied. The data sets collected 

during this study meet the ASTM D5157 criteria for model evaluation as they are entirely 

independent of the data used to develop the model and to estimate model inputs. Also, the data is 

of sufficient temporal and spatial detail to evaluate the CONTAM predictions of both inert 

pollutants and particles in a single zone.

ASTM D5157 provides three statistical tools for evaluating the accuracy of IAQ predictions and 

two additional statistical tools for assessing bias. Values for these statistical criteria are provided 

to indicate whether the model performance is adequate. The tools for assessing agreement 

between predictions include:

1) The correlation coefficient of predictions vs. measurements should be 0.9 or greater.

2) The line of regression between the predictions and measurements should have a slope between 

0.75 and 1.25 and an intercept less than 25 % of the average measured concentration.

3) The normalized mean square error (NMSE) should be less than 0.25. NMSE is calculated as:

∑=

= −

N

i

NMSE Cpi Coi CoCp

1

2

( ) / 2 8

where Cp is the predicted concentration and Co is the observed concentration.

ASTM D5157 also provides two statistical measures of bias with values for judging adequate 

model performance. These bias measures include:
26

1) Normalized fractional bias (FB) of the mean concentrations. Fractional bias should be 0.25 or 

lower and is calculated as:

( ) FB = Cp −Co Cp +Co 2( ) / 9

2) Fractional bias based on the variance (FS) which should be 0.5 or lower. FS is calculated as:

( ) FB s Cp s Co s Cp s Co

2 2 2 2 = 2( − ) / + 10

Infiltration Rates

The building air change rate is the best parameter to compare the simulated and measured airflow 

results as it is a commonly used parameter to evaluate the adequacy of building ventilation. 

Measured air change rates were determined from log curve fits to the SF6 tracer gas decay data as 

described above. Simulated air change rates were determined from the CONTAM results by 

adding all of the flows to the building from the ambient zone and dividing by the building volume. 

Figures 15a and 15b compare the one hour air change rates for cases d72 and d74, respectively. 

For Case d72, the average of the hourly measured and simulated air change rates were both 0.24 

h

-1

. For Case d74, the average of the hourly measured and simulated air change rates were 0.22 h1 and 0.21 h-1

, respectively. For case d72, the absolute average percent difference between the 

measured and modeled hourly air exchange rates was 20 % with the percent differences ranging 

from –31 % to 40 %. For case d74, the absolute average percent difference between the measured 

and modeled hourly air exchange rates was 16 % with the percent differences ranging from –46 % 

to 29 %.

a) Case d72

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Infiltration (h-1

)

Measured

CONTAM

b) Case d74

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Infiltration (h-1

)

Measured

CONTAM

Figure 15 Measured and Simulated Air Change Rates

Tracer Gas Concentrations

Since SF6 was injected during the 24 h tests to measure air change rates, it was included in the 

simulation to compare predictions to measurements for an inert indoor air contaminant. An inert 

pollutant is the simplest contaminant to model as there is no need to include deposition, air 

cleaning, or contaminant reactions in the model. The resulting concentration of the contaminant 

will depend only on the calculated airflow rates, outdoor concentrations, and pollutant source 

strength and schedule. The outdoor concentration of SF6 was assumed to be zero. Since the 
27

injection rates and time were not recorded, the source strength used in CONTAM was adjusted 

such that the increase in concentration over a five minute simulation time step approximately 

matched the measured increase in concentration. 

Figures 16a and 16b compare the measured and simulated SF6 concentrations for cases d72 and 

d74, respectively. The simulated 24 h average SF6 concentration was 11 % less than the average 

measured value for Case d72 and 2 % less than the average measured value for Case d74.

a) Case d72

0

10

20

30

40

50

60

70

80

90

100

12:00 AM

2:00 AM4:00 AM6:00 AM8:00 AM

10:00 AM

12:00 PM

2:00 PM4:00 PM6:00 PM8:00 PM

10:00 PM

12:00 AM

SF6 concentration (ppb)

Measured

CONTAM

b) Case d74

0

10

20

30

40

50

60

70

80

90

10:00 AM

12:00 PM

2:00 PM4:00 PM6:00 PM8:00 PM

10:00 PM

12:00 AM

2:00 AM4:00 AM6:00 AM8:00 AM

10:00 AM

SF6 concentration (ppb)

Measured

CONTAM

Figure 16 Measured and Simulated Tracer Gas Concentrations

Mechanical Air Cleaner Performance

As mentioned above, one of the mechanical air cleaners (MAC1b) was modeled two different 

ways in CONTAM. First, the air cleaners were modeled with the removal efficiencies determined 

by direct in-duct measurements (values in Table 7) in combination with the deposition rates 

determined for system on (values in Table 2). The simulated indoor particle concentrations using 

this method are presented in Figures 17a through 17d (for each of the four size ranges) along with 

measured particle counts. The particle counts in Figure 17 (and 18 through 22) were measured 

through the diluter and were multiplied by 100 to yield total concentrations. For this case the 

HVAC system with MAC1b installed was operating prior to the start of the test resulting in the 

initial steady concentrations in Figure 17. The particle generator was on from 10:00 a.m. to 2:00 

p.m.

The percent difference between measured and simulated 24 h average particle concentrations was 

8.9 % for 0.3 μm to 0.5 μm particles, -6.0 % for 0.5 μm to 0.7 μm, -17.9 % for 0.7 μm to 1.0 

μm, and -29.7 % for 1.0 μm to 5.0 μm. The percent differences at any point in time ranged from 

–80 % to 72 %.
28

d) 1.0 - 5.0 μ

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

c) 0.7 - 1.0 μ

0

100000

200000

300000

400000

500000

600000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

b) 0.5 - 0.7 μ

0

500000

1000000

1500000

2000000

2500000

3000000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

a) 0.3 - 0.5 μ

0.0E+00

5.0E+06

1.0E+07

1.5E+07

2.0E+07

2.5E+07

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

Figure 17 Comparison of Measured and Simulated Particle Counts with Direct MAC1b 

Filtration Efficiency

Next, MAC1b was modeled for the same case using the total removal efficiencies determined by 

decay tests (values in Table 5) in combination with the deposition rates for system off (values in 

Table 2). The simulated indoor particle concentrations using this method are presented in Figures 

18a through 18d. The percent difference between measured and simulated 24 h average particle 

concentrations was 11.5 % for 0.3 μm to 0.5 μm particles, -1.2 % for 0.5 μm to 0.7 μm, -10.3 

% for 0.7 μm to 1.0 μm, and -21.4 % for 1.0 μm to 5.0 μm. The percent differences at any point 

in time ranged from –75 % to 55 %. The CONTAM predictions with this method were slightly 

closer to the measurements with the exception of the smallest size particles.
29

d) 1.0 - 5.0 μ

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

c) 0.7 - 1.0 μ

0

100000

200000

300000

400000

500000

600000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

b) 0.5 - 0.7 μ

0

500000

1000000

1500000

2000000

2500000

3000000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

a) 0.3 - 0.5 μ

0.0E+00

5.0E+06

1.0E+07

1.5E+07

2.0E+07

2.5E+07

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Measured

CONTAM

Figure 18 Comparison of Measured and Simulated Particle Counts with Decay Test 

MAC1b Filtration Efficiency

Electronic Air Cleaner Performance

Similarly, one of the electronic air cleaners (EAC1) was modeled initially with the removal 

efficiencies determined by direct in-duct measurements (values in Table 7) in combination with the 

deposition rates determined for system on (values in Table 2). The simulated indoor particle 

concentrations using this method and the measured particle counts are presented in Figures 19a 

through 19d. Unlike the case above, the air cleaner was turned on at the start of the test resulting 

in the initial sharp decline seen in Figure 19. The particle source was on from 12:00 p.m. to 4:00 

p.m. 

The percent difference between measured and simulated 24 h average particle concentrations was 

11.7 % for 0.3 μm to 0.5 μm particles, 12.6 % for 0.5 μm to 0.7 μm, -15.2 % for 0.7 μm to 1.0 

μm, and –27.2 % for 1.0 μm to 5.0 μm. The percent differences at any point in time ranged from 

–82 % to 142 % but fluctuated much more than for MAC1b. This larger fluctuation is likely due 

to the smaller absolute particle concentrations in the building as a result of the highly effective air 

cleaner.
30

d) 1.0 - 5.0 μ

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

c) 0.7 - 1.0 μ

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

b) 0.5 - 0.7 μ

0

200000

400000

600000

800000

1000000

1200000

1400000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

a) 0.3 - 0.5 μ

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

8000000

9000000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

Figure 19 Comparison of Measured and Simulated Particle Counts with Direct EAC1 

Filtration Efficiency

Next, EAC1 was modeled for the same case using the total removal efficiencies determined by 

decay tests (values in Table 5) in combination with the system-off deposition rates (values in 

Table 2). The simulated indoor particle concentrations using this method are presented in Figures 

20a through 20d. The percent difference between measured and simulated 24 h average particle 

concentrations was 16.0 % for 0.3 μm to 0.5 μm particles, 16.8 % for 0.5 μm to 0.7 μm, -9.7 % 

for 0.7 μm to 1.0 μm, and -23.4 % for 1.0 μm to 5.0 μm. The percent differences at any point in 

time ranged just as wide as the previous method from –87 % to 153 %. Almost like the MAC1b 

predictions, the CONTAM predictions with this method were somewhat closer to the 

measurements for the two larger size ranges but somewhat further from the measurements for the 

two smaller size ranges.
31

d) 1.0 - 5.0 μ

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

c) 0.7 -1.0 μ

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

b) 0.5 - 0.7 μ

0

200000

400000

600000

800000

1000000

1200000

1400000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

a) 0.3 - 0.5 μ

0.0E+00

1.0E+06

2.0E+06

3.0E+06

4.0E+06

5.0E+06

6.0E+06

7.0E+06

8.0E+06

9.0E+06

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Measured

CONTAM

Figure 20 Comparison of Measured and Simulated Particle Counts with Decay Test EAC1 

Filtration Efficiency

Statistical Evaluation 

The statistical measures from ASTM D5157 were calculated for the predicted particle and SF6

concentrations for the cases presented in Figures 16 to 20 above. All of the model predictions met 

the criteria given above for adequate model performance for all the statistical measures with very 

few exceptions. For example, the correlation coefficient for all cases was greater than 0.94 for all 

cases and was 0.98 to 0.99 for all cases except the two smallest size particles with the electronic 

air cleaner operating. Similarly, the NMSE was less than 0.2 for all cases and was less than 0.1 for 

many cases. The bias measures fared nearly as well with the model predictions meeting the criteria 

for all cases except for the predictions for the largest size particles which were slightly outside the 

adequate criteria for FB.
32

IMPACT OF AIR CLEANERS

As an example of how CONTAM would be used to evaluate the impact of IAQ controls, the two 

cases simulated above with the MAC1b and EAC1 air cleaners were also simulated with a typical 

furnace filter. The method used was the simulation with filtration efficiency from the decay test 

(MAC4 data from Table 5 above) as no direct measurement efficiency was available. All the 

remaining simulation parameters remained the same as discussed above. 

The simulated particle concentrations for case d72 with MAC1b and the typical furnace filter 

along with measured outdoor particle concentrations are shown in Figures 21a through 21d. The 

mechanical air cleaner MAC1b reduced the 24 h average particle concentrations by 15 % for 0.3 

μm to 0.5 μm particles, 4 % for 0.5 μm to 0.7 μm, 2 % for 0.7 μm to 1.0 μm, and –1 % for 1.0 

μm to 5.0 μm compared to the furnace filter. 

d) 1.0 - 5.0 μ

0

50000

100000

150000

200000

250000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Furnace filter

MAC1b

Outdoor

c) 0.7 - 1.0 μ

0

100000

200000

300000

400000

500000

600000

700000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Furnace filter

MAC1b

Outdoor

b) 0.5 - 0.7 μ

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Furnace filter

MAC1b

outdoor

a) 0.3 - 0.5 μ

0.0E+00

5.0E+06

1.0E+07

1.5E+07

2.0E+07

2.5E+07

3.0E+07

3.5E+07

4.0E+07

4.5E+07

5.0E+07

12:00 AM

3:00 AM6:00 AM9:00 AM

12:00 PM

3:00 PM6:00 PM9:00 PM

12:00 AM

Particle count (#/m

3

)

Furnace filter

MAC1b

Outdoor

Figure 21 Impact of MAC1b Compared to Furnace Filter

The simulated particle concentrations for case d74 with EAC1 and the typical furnace filter along 

with measured outdoor particle concentrations are shown in Figures 22a through 22d. The 

electronic air cleaner EAC1 reduced the 24 h average particle concentrations by 85 % for 0.3 μm 

to 0.5 μm particles, 78 % for 0.5 μm to 0.7 μm, 73 % for 0.7 μm to 1.0 μm, and 67 % for 1.0 

μm to 5.0 μm compared to the furnace filter.
33

d) 1.0 - 5.0 μ

0

100000

200000

300000

400000

500000

600000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Furnace filter

EAC1

Outdoor

c) 0.7 - 1.0 μ

0

500000

1000000

1500000

2000000

2500000

3000000

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Furnace filter

EAC1

Outdoor

b) 0.5 - 0.7 μ

0.0E+00

5.0E+06

1.0E+07

1.5E+07

2.0E+07

2.5E+07

3.0E+07

3.5E+07

4.0E+07

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Furnace filter

EAC1

outdoor

a) 0.3 - 0.5 μ

0.0E+00

2.0E+07

4.0E+07

6.0E+07

8.0E+07

1.0E+08

1.2E+08

1.4E+08

1.6E+08

1.8E+08

10:00 AM

1:00 PM4:00 PM7:00 PM

10:00 PM

1:00 AM4:00 AM7:00 AM

10:00 AM

Particle count (#/m

3

)

Furnace filter

EAC1

Outdoor

Figure 22 Impact of EAC1 Compared to Furnace Filter
34

DISCUSSION

The primary objective of this effort was to evaluate the capability of the multizone IAQ model 

CONTAM to simulate the impact of particle air cleaners in a real building subject to real ambient 

conditions. As shown in Figures 15 through 20, it is possible to adequately predict the air cleaner 

performance, at least for a single zone building without occupants present. Future work is 

underway to extend the project to include measurements and predictions of particle air cleaners in 

an occupied home.

Although both the decay and direct methods resulted in good predictive accuracy, it is not 

surprising that the decay method was somewhat more accurate than the direct method. This is 

almost certainly because it yielded a filtration efficiency for the HVAC system and air cleaner as 

an installed unit. Thus, factors such as leakage around a poor fitting air cleaner and deposition in 

the ductwork is accounted for in the measured efficiencies. However, for typical design 

applications, one would not have such an “installed” efficiency available but rather would rely on 

manufacturer test data that might be similar to the direct method efficiencies. These efficiencies 

would need to be combined with appropriate deposition factors to account for the total removal 

of particles. Additional study into the issue of particle removal throughout the HVAC system 

ductwork and deposition dependence on ventilation flows is needed to enable such modeling.

Another objective of this effort was to identify model development needs. However, based on the 

comparison of predictions and measurements, it can be concluded that the current CONTAM 

capabilities for modeling particulate air filters are adequate. The more pressing need is availability 

of accurate performance data for air cleaning devices and other model input data. A useful but not 

essential issue for model development is a contaminant model to represent various size fractions 

of airborne particles. While it is possible to model particles with the current capabilities of 

CONTAM, a specific contaminant model representing particles would make this task far easier for 

the CONTAM user.
35

ACKNOWLEDGEMENTS

The authors wish to acknowledge the efforts of Dan Greb, Stuart Dols, Kevin Denton, and 

Elisabeth Ivy in support of this project. The authors also acknowledge the support of Dilip 

Vyavaharkar of Carrier Corporation in providing technical information and some of the tested air 

cleaners.
36

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