Peer Review Results for the 

Formaldehyde Indoor Air Model – for 

Pressed Wood Products (FIAM-PWP) 

Prepared for:

U.S. Environmental Protection Agency

Economics, Exposure, and Technology Division 

Office of Pollution Prevention and Toxics 

1200 Pennsylvania Avenue, N.W. 

Washington, DC 20460 

Prepared by: 

Eastern Research Group, Inc.

14555 Avion Parkway 

Suite 200 

Chantilly, VA 20151-1102 

23 October 2009 

EPA Contract No. EP-W-05-014 

Work Assignment 5-10

i

TABLE OF CONTENTS 

Page 

1.0 INTRODUCTION ................................................................................................. 1-1 

1.1 Peer Review Logistics .......................................................................... 1-3 

1.2 Peer Review Experts............................................................................. 1-3 

2.0 PEER REVIEW COMMENTS ORGANIZED BY CHARGE QUESTION .......................... 2-1 

2.1 Part 1 - Algorithms and Exposure Assumptions .................................... 2-1 

2.1.1 Comment on the Adequacy of the Mathematical Equations and the 

Level of Confidence in Indoor Air Concentrations and Exposure 

Estimates Provided by the Model. ............................................. 2-1 

2.1.2 Comment on the Default Scenarios and Assumptions Used by the 

Model 2-31 

2.1.3 Comment on the Data Sources ................................................ 2-33 

2.1.4 Comment on Whether the Data Sources Provide Unused 

Information That Would Assist in Quantifying Uncertainty or

Variability for Subsequent Model Use..................................... 2-34 

2.1.5 Comment on Whether the Model Input Variables and the Estimates 

Assigned to Them Appropriately Reflect Variability............... 2-35 

2.1.6 Comment on the Adequacy of the Documentation Supporting the 

Overall Plausibility of the Exposure Estimates Generated by the 

Exposure Model...................................................................... 2-38 

2.1.7 Provide Any Other Types of Data to Assess the Reliability of the 

Overall Exposure Model or Specific Model Elements ............. 2-40 

2.1.8 General Comments on Algorithms and Exposure Assumptions2-41 

2.2 Part 2 - User Interface......................................................................... 2-44 

2.2.1 Provide Comments on the Ease of Use of the FIAM-PWP Model2-

44 

2.2.2 Comment on the Adequacy of the Model Help Screens........... 2-46 

2.2.3 General Comments on the User Interface ................................ 2-47 

2.3 Part 3 - Documentation....................................................................... 2-48 

2.3.1 Comment on Whether the References Have Been Accurately 

Identified ................................................................................ 2-48 

2.3.2 Provide Comments on the Model Documentation (Does It Present 

the Model Construct, Selected Model Inputs, and Model Results in 

a Clear, Complete and Useful Manner).................................... 2-50 

2.3.3 Provide Comments on Whether the Documentation for the FIAM - 

PWP Make Clear the Sources and Anticipated Magnitudes of 

Variability and Uncertainty in Model Results.......................... 2-54 

2.3.4 Comment on Whether the Model Algorithms are Consistent with 

the Descriptions in the Model Documentation......................... 2-56 

2.3.5 General Comments on Documentation.................................... 2-58 

2.4 Additional Comments and Materials Submitted.................................. 2-59 

3.0 PEER REVIEW COMMENTS ORGANIZED BY REVIEWER........................................ 3-1 

3.1 Jensen Zhang Review Comments ......................................................... 3-3 

3.2 Michael Jayjock Review Comments ..................................................... 3-9 
TABLE OF CONTENTS (Continued) 

Page 

ii

3.3 Panos Georgopoulos Review Comments............................................. 3-23 

3.4 Kenneth Unice Review Comments ..................................................... 3-87 

3.5 W. Gene Tucker Review Comments................................................. 3-123 

Appendix A: CHARGE TO PEER REVIEWERS .................................................................A-1 

Appendix B: FIAM-PWP MODEL.......................................................................................B-1 

Appendix C: SUPPORTING MATERIAL............................................................................C-1 
1-1

1.0 INTRODUCTION

On March 24, 2008, EPA was petitioned by the Sierra Club and others under 

TSCA Section 21 to adopt the California Air Resources Board’s Air Toxics Control Measure 

(CARB ATCM) under TSCA Section 6(a) concerning formaldehyde emissions from pressed 

wood products. EPA issued an advance notice of proposed rulemaking (ANPR) on December 3, 

2008 and held six public meetings to hear comments. Before EPA determines the next course of 

action, one step in the investigation process involves developing a formaldehyde exposure 

assessment. 

Estimating inhalation exposure to airborne chemicals emitted from products or 

materials used indoors involves the integration of information on location/activity patterns with 

concentrations encountered by individuals at indoor locations. When insufficient information 

exists on measured concentrations or personal exposures for the situation(s) of interest, then 

means of estimating or predicting concentrations are needed. 

OPPT evaluated a previous draft formaldehyde exposure model developed in the 

late 1990s and determined that with modifications, it could be used to estimate indoor air 

concentrations and exposures to individuals in various indoor environments. The Formaldehyde 

Indoor Air Model - Pressed Wood Products (FIAM – PWP) is designed to estimate human 

inhalation exposure to airborne formaldehyde (HCHO) emissions from pressed-wood products in 

new or existing residences and temporary buildings. 

FIAM is originally based on “the Matthews model,” which was developed by Dr. 

Thomas Matthews and others at Oak Ridge National Laboratory in the 1980s (Matthews et al. 

1983a). This model uses Fick’s Law to describe the bulk-vapor interphase at the surface of the 

pressed-wood emission source and estimate the steady-state formaldehyde concentration in an 

enclosed environment. The initial steady state indoor concentration calculated by the model is 

assumed to decrease over time as the reservoir of formaldehyde in the source (or sink) is 

gradually depleted. This decrease is assumed to follow a first-order exponential decay rate, 

which depends on the chosen emissions half-life of formaldehyde. 
1-2

In the mid-1990s, EPA conducted an assessment of the contribution of UFbonded wood products to formaldehyde levels in homes. Evaluations of then-current EPA 

exposure models were conducted and shortly thereafter, a modified version of the Matthews 

model was developed. The primary modifications were (1) estimation of steady-state 

formaldehyde concentrations for the case of a two-zone indoor environment, and (2) 

incorporation of reversible (re-emitting) indoor sinks. The modified model also included the 

option to be run in a single-zone mode. However, the model was not finalized. 

Early in 2009, FIAM was revised to include more features and additional scrutiny 

with regards to the estimating technologies. The purpose of this work assignment is to facilitate 

the external peer review of the FIAM. The primary product to be peer reviewed is the 

computerized model and associated user guide and documentation. The main focus of the peer 

reviewers should be the science and mathematics of the model, however comments on the 

overall functioning capacity and ease of use is important as well. The mechanism for the peer 

review of the FIAM will be individual letter peer review conducted using EPA’s peer review 

policy. 

 The purpose of this peer review was to review and comment on three main 

aspects of the FIAM-PWP model: the soundness of the algorithms and exposure assumptions; 

the ease of use of the graphical interface; and the completeness and clarity of the model 

documentation. 

The remainder of this report is comprised of the unedited written comments 

submitted to ERG by the peer reviewers in response to the peer review charge (see Appendix A). 

Section 2.0 presents peer review comments organized by charge question, and Section 3.0 

presents peer review comments organized by peer review expert. The source code for the FIAMPWP model is presented in Appendix B and additional supporting materials are included in 

Appendix C. 

The final peer review record for the FIAM-PWP Model will include this peer 

review report consisting of the peer review comments, as well as documentation indicating how 

peer review comments were addressed by EPA, and the final EPA work product. 
1-3

1.1 Peer Review Logistics

 ERG initiated the peer review for the FIAM-PWP on September 14, 2009. ERG 

held a pre-review conference call on September 21, 2009 to provide the peer reviewers with an 

opportunity to ask questions or receive clarification on the review materials or charge and to 

review the deliverable deadlines. Peer review comments were due to ERG on or before October 

12, 2009. 

 

1.2 Peer Review Experts

ERG researched potential reviewers through its proprietary consultant database; 

via Internet searches as needed; and by reviewing past files for related peer reviews or other 

tasks to identify potential candidates. ERG also considered several experts suggested by EPA. 

ERG contacted candidates to ascertain their qualifications, availability and interest in performing 

the work, and their conflict-of-interest (COI) status. ERG reviewed selected resumes, conflict-ofinterest forms, and availability information to select a panel of experts that were qualified to 

conduct the review. ERG submitted a list of candidate reviewers to EPA to either (1) confirm 

that the candidates identified met the selection criteria (i.e., specific expertise required to conduct 

the assay) and that there were no COI concerns, or (2) provide comments back to ERG on any 

concerns regarding COI or reviewer expertise. If the latter, ERG considered EPA's concerns and 

as appropriate proposed substitute candidate(s). ERG then confirmed the five individuals who 

were judged to be the most qualified and available reviewers to conduct the peer review. 

A list of the peer reviewers and a brief description of their qualifications is 

provided below. 

• Jensen Zhang, Ph.D., is the Director of the Building Energy and Environmental Systems 

Laboratory at Syracuse University. His expertise is in conducting emission studies in test 

houses and analyzing results, analyzing and modeling emissions from building materials, 

and developing and using mathematical modeling and computer simulation models. He 

has authored/co-authored over 100 research papers and three standard methods for testing 

organic emissions from building materials, including “Modeling the formaldehyde 

emission from multi-layer work surfaces used in office workstation systems” (2007) and 
1-4

an ASTM document, ASTM Standard Practice for Determination of Volatile Organic 

Compounds (excluding formaldehyde) Emissions from Wood-Based Panels Using Small 

Environmental Chambers in Defined Test Conditions (1997). 

• Michael Jayjock, Ph.D., CIH, is an industrial hygienist with the LifeLine Group that has 

expertise in conducting exposure assessments to chemicals in consumer products, 

experience with source and sink terms and activity patterns, expertise in quantification of 

uncertainty modeling; publications related to exposure to wood products and VOCs, but 

not formaldehyde specifically. He has also participated in peer review for the 

Canadaidan Environmental Protection Act, 2008 and has served on several peer 

consultation panels for the U.S. EPA Perfluorooctanoic Acid (PFOA) Site-Related 

Environmental Assessment Program and Voluntary Children's Chemical Evaluation 

Program (VCCEP). 

• Panos Georgopoulos, Ph.D., is the Director of the Computational Chemodynamics 

Laboratory (CCL) and Co-Director of the Center for Exposure and Risk Modeling 

(CERM) at the Rutgers University Environmental & Occupational Health Sciences 

Institute (EOHSI). He is also Associate Director of the EPA-supported environmental 

bioinformatics and Computational Toxicology Center (ebCTC), a research consortium of 

University of Medicine and Dentistry of New Jersey - Robert Wood Johnson Medical 

School (UMDNJ-RWJMS), Princeton University, Rutgers University and US FDA's 

Center for Toxicoinformatics.

• Kenneth Unice, M.S., is an environmental engineer with over nine years of quantitative 

human health risk and exposure assessment experience. He has expertise in developing 

computer models in programming languages such as Visual Basic, C++, Fortran, and 

MATLAB. He has completed a temperature-dependent assessment of formaldehyde 

emission rate from pressed wood products, which predicts indoor air concentrations and 

accounts for the back-pressure effect that causes emission rates to decrease with 

increasing ambient formaldehyde levels. He has experience using the EPA/Versar Multichambers Concentration and Exposure Model (MCCEM) to model emission rates and 

indoor air concentration for mercury and naphthalene mothballs, as well as experience 
1-5

conducting exposure assessments for the Voluntary Children's Chemical Evaluation 

Program (VCCEP) working group (ACC). 

• W. Gene Tucker, Ph.D., is a Professor in the Department of Integrated Science and 

Technology at James Madison University, specializing in Indoor Air Quality. He is a 

member of the International Academy of Indoor Air Sciences (elected in 1991) and has 

held various positions in the U.S. EPA Office of Research and Development (ORD). 

2-1

2.0 PEER REVIEW COMMENTS ORGANIZED BY CHARGE QUESTION

Peer review comments received for the FIAM-PWP model are presented in the 

sub-sections below and are organized by charge question (see Appendix A). Peer review 

comments are presented in full, unedited text as received from each reviewer.

2.1 Part 1 - Algorithms and Exposure Assumptions

2.1.1 Comment on the Adequacy of the Mathematical Equations and the Level of 

Confidence in Indoor Air Concentrations and Exposure Estimates Provided 

by the Model. 

Jensen Zhang: 

1) The mathematical equations are adequately explained except that there appears to be 

some confusion between diffusion and convective mass transfer. The model is based 

on convective mass transfer over the surface, which is not based on the Fick’s Law of 

diffusion. The air velocity over the surface would have significant effect on the “mass 

transfer coefficient”, and hence the model parameter, “slope”. The values of the 

“slope” appear to be small (maximum of 3.0 in the case of painted dry wall). This is 

likely that the most data are from small scale chamber tests where air velocity over 

the material surface is small compared to the typical airflow conditions in ventilated 

rooms. Therefore, the model may underestimate the emission rates if the emission is 

indeed controlled by the convective mass transfer process. 

2) However, it is more likely that except for the initial emission period, the emission rate 

will be controlled by the internal diffusion process as suggested by many studies 

including those cited in the report for pressed wood products. So the “slope” values 

derived from the measured data may have included the combined effects of 

convective mass transfer and internal diffusion resistances, resulting reasonable 

predictions. At the “steady state” (about 30 days from initial chamber test), the 

internal diffusion resistance should be the dominant resistance for formaldehyde 

emissions even for particleboard. To understand and proof this point, a more detailed 

numerical simulation can be made for homogeneous sources as assumed in the study 

(i.e., there were free formaldehyde uniformly distributed in the material). 
2-2

3) After establishing the steady state initial concentration based on Mathew’s model, the 

concentration in a zone that has a higher concentration is assumed to decay 

exponentially over time, given a half life time as the input parameter. This approach 

is unconventional, but practical considering the many uncertainties involved in real 

situation. The challenge would be to choose the right the half-life time. An alternative 

is to actually model the emission rates of various sources, and then calculate the 

concentrations under given ventilation rate conditions, as is typically done. 

4) Formaldehyde may not be distributed uniformly inside the material. They may be 

more concentrated in resin spots and less in the wood particles/chips. In addition, 

hydrolysis is possible for additional formaldehyde generation within the material, 

resulting longer and higher emission rates in the long term. This is still a research 

topic and no reliable model has been developed yet. Therefore, I support the idea of 

relying on measured field data to estimate the decay of formaldehyde concentration, 

and be conservative in the estimation, as intended by the model. 

5) Based on the data provided and the assessment analysis, the model should provide 

reasonable conservative estimate of the formaldehyde exposure given the relatively 

long half-life time. 

Michael Jayjock: 

While relatively simple and straightforward at its base using first principle scientific 

relationships, this model, in its totality, is by any measure quite complex. The reader who 

wishes to understand it has to have a competent background in the modeling sciences, be 

reasonably motivated and must be able to devote considerable time to studying the 

documentation in order to do so. This complexity puts a heavy burden on the person(s) 

providing the documentation in order to clearly explain its workings. In light of this 

challenge I found the explanation of the mathematical basis of the algorithms and the 

exposure assumptions to be remarkably well written and lucid. 

Regarding the appropriateness of the algorithms and assumptions, as mentioned above, 

Matthew’s basic approach appears to be based on solid first principles of conservation of 

mass and the validity of diffusion via Fick’s Law. Equation 3-2 appears to be relatively 

simple, self-evident and quite appropriate. The only term that gave me some pause 
2-3

regarding its suitability was F (the mixing factor). Some past scientific opinion has 

considered the use of the ventilation rate mixing factor to be basically invalid; however, 

after further reflection it is clear that relative to sources it is the local ventilation rate (that 

is the rate that is proximate to the emitting source) which is the determining factor and 

because of typically incomplete mixing within any room volume the inclusion of F is a 

perfectly legitimate and suitable modeling construct. 

Similarly, equation 3-5 forms the basis for the emission rate modeling engine. It is well 

explained and appears to me to be a reasonable approximation of reality. This equation is 

in complete agreement with previous work that I have done on “backpressure” modeling 

(ref: Jayjock, M.A.: Back Pressure Modeling of Indoor Air Concentration from 

Volatilizing Sources, Am. Ind. Hyg. Assoc. J. 55 (3): 230-235 (1994)). 

Equation 3-5 is reproduced below with slightly different notation along with an 

equivalent equation from my previous work. 

max Gss = −m(Css

) + G (equation 3-5 with different notation) 

Gss = steady state emission rate (mg/m2-hr). Equivalent to CH2OER’ 

Gmax = the maximum emission rate which occurs at zero backpressure; that is, at 

zero concentration of formaldehyde in the air (mg/m2-hr). Equivalent to b. 

m = the mass transfer coefficient (m/hr) 

Css = vapor-phase concentration of formaldehyde at steady state (mg/m3). 

Equivalent to [Ch2O]v
2-4

Equation 3-5 above is essentially identical to an algorithm that I have often used for 

backpressure modeling shown below: 

max

max

max

( )

:

1( )

C G

C

G

G

rearranged

C

C

G G

ss

sat

ss

sat

ss

ss

= − +

= −

Csat = the saturation concentration (mg/m3) of formaldehyde in the air over the 

emitter of interest. That is the concentration that would be expected in a 

volume (with high surface area/volume ratio) in which the emitting walls 

were made up entirely of the emitter of interest and there is zero 

ventilation. 

Note the equivalence of this last equation to 3-5 above and the identity of m: 

Csat

G

m

max =

Clearly, the relatively straightforward analytical measurement of Csat could provide a 

potentially valuable extended methodology for the evaluation and development of the 

model’s parameters relative to specific emitters. 

The subsequent development of the model’s complexity within the current documentation 

going forward after the combination of the concentration and emission rate algorithms is 

well explained and to my eyes seems to be fitting. 

The extension of the model from a single to two compartments, while necessarily quite 

involved, is logically explained and appears to me to be accurate. 

I believe that the treatment of indoor sinks as developed by and explained in the model 

represent a real step forward in indoor modeling science. From my experience few 

modelers have attempted to address this issue in detail and none have done a better job 
2-5

than demonstrated in this work. As noted by the author, the complex relationships 

regarding real sink behavior are not fully captured by the scheme used but I believe it is a 

credible “point-in-time” approximation. I would suggest that the author of the 

documentation in this area expand the explanation to include some example data and 

treatment that illustrates the estimation of parameters for the Langmuir model. That is, 

the last paragraph on page 3-7 supplies the estimated values but my sense is that the 

explanation would be significantly more lucid if the actual procedure and values used in 

the fitting exercise were demonstrated and included. 

The sections on decay of indoor concentration and the default value for half-life are very 

well written and, to the credit of the author, lay out all of the practical limitations incurred 

during the development of these aspects of the model. Clearly, the ideal data set was not 

collected and the practical alternatives were (for the reasons given) less than perfect. 

Despite these limitation the author does a very credible job of considering all the aspects 

and providing the reader/model user with a distillation of useful parameters and guidance. 

Similarly, the section on temperature and humidity adjustments is characteristically well 

presented and understandable. 

Regarding the level of confidence one might have in the model’s prediction of actual 

indoor concentration and exposure levels, my sense is that they should be considered 

accurate within a factor of 2. That is, given a true concentration or exposure of 1 that a 

competent estimate (i.e., with good inputs) should occur between 0.5 and 2. This is 

admittedly an intuitive judgment on my part borne of the approximations used in the 

methodology but more from the practical limitations and variability of the data used to 

parameterize or otherwise feed the model. For example, examining the equations in Table 

2-2 and setting the ambient formaldehyde concentration to zero, the emission rates for 

Particleboard Underlayment from the available sources range from 0.09 to 0.74 mg/m2/hr 

or a factor of about 8x. Industrial particleboard ranges from 0.12 to 1.24 or a factor of 

more than 10x. My sense is that this range represents true differences in emissions rates 

but also artifactual differences between testing laboratories. My estimate of a factor of 2 

comes from an assumption that the user has a good and accurate accounting of which 
2-6

sources and sinks are most germane to their particular scenario. If I am incorrect in this 

assumption then the range would, of course, broaden. 

Other evidence driving this estimate (factor of 2) is the results and comparison of 

modeled/measured values from the pilot study. Despite its well documented limitations 

the parameters in this study appear to be reasonably understood and the model appears to 

over predict measured values. During the air out period when re-emitting sinks were 

ignored there was an overestimation of about this order. 

Relative to the estimation of exposure there appears to be logical error in the defaults. 

When one invokes the Exposure Defaults within the model, the 5 age groups for children 

in the model all show 10 years for the exposure period. Of course, this is impossible for 

an infant of <1 year or, indeed for any of the age groups for children which are all less 

than 10 years in length. This is explained in the documentation and in the online help 

button; however, I found it somewhat confusing. My suggestion is that the default shown 

in the program for any age group should be the maximum time a person can spend in that 

age group. The user can then view the help file for specific guidance in changing the 

defaults. An additional measure would be to indicate on the screen that it is: “Age group 

at start of exposure.” 

Understanding the exposure to formaldehyde represents exactly half the information 

needed to understand the risk to human health from this exposure. Of course, the other 

critical piece of information includes the toxic effects that can occur as a result of the 

exposure. A very brief search of the Internet reveals the following relevant information 

regarding this compound. “Formaldehyde is a normal, essential human metabolite with a 

biological half-life of about 1.5 minutes.” Reference: 

http://justthevax.blogspot.com/2009/05/toxin-gambit-part-1-formaldehyde.html. Indeed, 

this is a relatively fast biological half-life and this speed can have serious implications for 

the time frame used to integrate the level of exposure. The best example to illustrate this 

issue and need that I can think of is carbon monoxide (CO). A constant exposure to CO 

of 10 ppm v/v per day everyday for 365 days should not be an issue with most folks but 
2-7

providing this combined dose over 5 days (730 ppm v/v) as a 5-day long bolus would be 

disastrous to anyone even in the first day (first hours) of this exposure. 

 

Of course, the differences in exposure magnitude and the mode of action of CO and 

CH2O are quite different but the biological half-life of CO is in hours and that of CH2O 

is in minutes. Thus, it is not difficult to imagine relatively high doses of CH2O potentially 

causing biological damage over a period of a few days. As such, the estimation exposure 

in the Results Screen of Average Daily Concentration (ADC) and Average Daily Dose 

(ADD) could be of particular significance to the toxicologist in assessing the overall risk 

from exposure to indoor formaldehyde. Depending on the specific details of the 

toxicokinetics of formaldehyde the toxicologist may be interested in understanding the 

exposure to humans on the worst (first) day of exposure. The program allowed me to put 

in a single day (0.00274 years) for the duration of the exposure but the results indicate 

that a calculation error occurs for this input. The calculated ADC is above the initial 

concentration and the time percentages come out to be >100%. If this error is not easy or 

practical to fix then an explanation should be included that advises the minimum time for 

duration of exposure. My sense is that this minimum calculable time frame should not, in 

any case, be longer than a few days for the reasons mentioned above. 

Generally, I did not find any errors in the algorithms, however, I did not attempt an 

explicit independent derivation of all of the algebraic equations that comprise the model. 

Relative to alternate calculations methodologies it is suggested that the modelers consider 

a modeling program based on The Advanced Continuous Simulation Language (ACSL) 

computer language. ACSL easily handles simultaneous differential equations while 

providing parameter estimates from data via optimization and an intuitive graphical 

interface. This is not to suggest that ASCL be used in the direct implementation of the 

FIAM. Indeed, this seems to be done quite well with the current software. However, 

ACSL could be used to independently confirm the modeling output or help refine the 

estimations of parameter values (from experimental data) for the model. ACSL is 

available in a PC implementation. Please refer to the following web site: 

(http://www.acslx.com/products/optimization.shtml). 
2-8

Panos Georgopoulos: 

The mathematical/algorithmic formulation and the computational implementation of the 

model under review (FIAM-pwp) are adequately explained, with sufficient clarity and 

level of detail; the computational implementation of the model also appears robust and 

accurate. Characterizing the mathematical equations (i.e. the basic formulation and 

assumptions of the model) as “appropriate,” as per question 1.1, depends of course on the 

types of questions the model is supposed to answer, and the desired accuracy/precision 

that is expected - or, at least, desired - for a given application. Nevertheless, given the 

simplifying assumptions (discussed further in the following paragraphs) in the 

formulation of the model, and the significant variabilities inherent in the data sets that 

were used to derive parameter values for FIAM-pwp, the level of confidence in the 

indoor air concentration and exposure estimates provided by the model, should in general 

be considered, at most, medium. In this reviewer’s opinion, the uncertainty and 

variability levels in the available data strongly suggest the need for a 

distributional/probabilistic model formulation that explicitly employs available data to 

develop ranges rather than point estimates of concentrations and exposures. 

Considering the (current) model formulation, FIAM-pwp essentially consists of three 

components, i.e. (a) estimation of formaldehyde emission rates from various types of 

pressed wood products (based on data from various field and chamber studies), (b) 

estimation of indoor mixing/dispersion through simple one-zone and two-zone models 

that incorporate sink and back-pressure effects, and (c) simple inhalation exposure 

calculations that employ average intakes for adults and of children in different age 

groups. Clearly, the unique - and most valuable - component of the model is component 

(a), i.e. the estimation of HCHO emission rates, as a wide variety of far more 

comprehensive models exist for either characterizing indoor air quality (addressing 

transport and mixing at various levels of detail as well as incorporating indoor air 

chemistry and physical transformations etc.) or assessing inhalation exposures and 

dosimetry. In this reviewer’s opinion, a major drawback in the formulation of the FIAMpwp is that components (a) and (b) are not “separated” in a way that would allow, in a 

straightforward manner, usage of the formaldehyde emission rates with other available 

indoor air quality and inhalation exposure models. Of course, for any given real-world 
2-9

application, there will be various bi-directional “links” and “feedback mechanisms” 

between such models (i.e. effects of airborne concentration levels on emission and sink 

rates etc.); however, the approach taken in the mathematical formulation of FIAM-pwp 

“lumps” these mechanisms in a manner that limits the usage and evaluation of individual 

model components. Specifically, though the literature – as well as the provided model 

documentation – explicitly recognize the fact that formaldehyde emission rates from 

pressed wood products decrease with time, the mathematical formulation of components 

(a) and (b) of FIAM-pwp is based on the assumptions of constant rate emissions and the 

establishment of steady state for indoor air concentration levels (see Sections 3.1 to 3.4 of 

model documentation). Then, (see Sections 3.5 to 3.6), a decay rate is imposed upon 

indoor concentrations, to account for depletion of the formaldehyde sources; this decay 

rate is parameterized (through half-life values) from experimental data so as for modeled 

concentration trends to fit the observations. The role of sinks, as well as of potential 

“new” and “unknown” sources is, of course, recognized in the literature, as well as in the 

model documentation: these factors are essentially “lumped” in the 

phenomenological/apparent concentration decay rate, that obviously is affected by a 

variety of chemical and physical transformations that either add or remove formaldehyde 

molecules to/from indoor air. It should in fact be expected that “sources” (including 

chemical reactions) of formaldehyde other than pressed wood products may affect the 

parameterization of concentration decay from experimental data. (Various relevant 

references are listed in an Addendum to the present review). In this reviewer’s opinion, 

the value of the information that has been incorporated in FIAM-pwp would be greatly 

enhanced if its formulation explicitly considered decaying (e.g. exponentially decreasing) 

emission rates and provided appropriate formulas for implementing them (either within 

FIAM-pwp or in conjunction with other, more comprehensive, indoor air quality and 

inhalation exposure systems). Simple implementations of exponentially decaying source 

with one-zone and two-zone indoor air models are well established (see, e.g. AIHA, 

2000, Mathematical Models for Estimating Occupational Exposure to Chemicals). 

Estimations of exponentially decaying formaldehyde emission rates have in fact been 

pursued in the past and have appeared long-ago in the scientific literature (see, e.g., 

Brown, Indoor Air, 1999; 9:209-215 and other related references in the Addendum of this 

review). 
2-10

Kenneth Unice: 

In summary, I concur with the calculation of initial concentration (high confidence in 

result with reliable chamber test data), however, the treatment of sinks and average daily 

concentration for chronic exposure appear to require some revisions to improve the 

quality of the result (low confidence in result). I believe the usefulness of the model could 

be strengthened discussing the incremental contribution of added products because 

regulations, if any, are likely to be developed on a product specific basis (e.g. MDF 

versus industrial panel). Currently, the model documentation and model results 

emphasize the aggregate contribution of all products (and background sources), and 

running the model with and without a product of interest can produce counterintuitive 

results as described below. Finally, the relationship between the HBF and Matthews 

model should be made clear in the model documentation. Please see my detailed 

comments below. 

General Comments – Acute Versus Chronic Exposure

One of the challenging aspects of reviewing this model and providing cohesive 

recommendations is that the current assessment of acute and chronic exposure is 

associated with different uncertainties and conceptual models. However, accurate 

assessment of exposure for each of these endpoints is important. For acute exposure, the 

interaction between products is important due to the back-pressure effect, whereas for 

chronic exposure, each product has a reservoir of formaldehyde and formaldehyde 

precursors that is finite and decays with time. The theory for acute exposure modeling for 

pressed wood products is well established and has been reasonably well validated (Myers 

and Nagaoka 1981; Salthammer et al. 1995; Groah 2006) and some literature exists for 

the effect of wallboard sinks (Matthews et al. (1987). The use of a pseudo steady-state 

approach with cross-sectional residential half-life for chronic exposure is empirical and 

pragmatic, but is inconsistent with the theoretical approach to acute modeling. 

Furthermore, the short term effects of reversible sinks are difficult to reliably model with 

a steady state approach. 

The model documentation should focus on both the determination of incremental 

exposure attributable to the introduction of a specific product and the total exposure for 
2-11

loaded home. Some users will be interested in understanding the total formaldehyde 

concentration, but other users, such as trade associations, importers and manufactures, 

will be most interested in understanding the potential risk associated with a specific 

product or collection of products. Furthermore, regulations are likely to differ based on 

the type of product, necessitating an ability to understand incremental or added 

contributions to exposure. For example, in addition to understanding total exposure, the 

manufacturer of a bookcase constructed of pressed-wood products should be able to 

intuitively use the model and model documentation to answer the 

questions: 

• what data do I need to collect to refine the default acute and chronic 

exposure predictions of the model? 

• what is the acute airborne concentration attributable to my product in the 

absence of other products? 

• what is the incremental increase in acute airborne concentration when my 

product is introduced into a new or existing home when a default baseline 

set of pre-existing products (new construction, existing residence, or 

policy based target concentration) are present? 

• what is the long term average exposure attributable to my product? 

Currently, the model does not provide a framework for answering questions about the 

effect of the introduction of new product into a pre-existing home, particularly for 

chronic exposure. I am concerned that the model does not provide guidance on the 

specific testing (chamber or alternative testing) that a manufacturer or other interested 

parties should perform to refine the estimate of chronic exposure. It is unclear to me that 

even if a manufacturer performed a robust 12-month study (or longer), that it would be 

intuitive how to modify an ‘overall residential’ halflife. I am less concerned about acute 

exposure, because the potential effect of a particular product is easily discernible by 

standard chamber testing and calculated equilibrium concentration on reasonable 

assumptions about mass transfer coefficients. My concern is that if a cancer risk in excess 

of the acceptable risk range is calculated with this model, there is not a clear 

recommendation for performing a laboratory study that could be used to assign a higher 
2-12

tier decay function. The half-life is assigned to the residence based on cross-sectional 

data. However, conceptually, the decay in concentration over time is due to source 

depletion from individual products. It may be prudent for EPA to consider a technical 

workshop prior to finalizing the model with the purpose of developing consensus 

recommendations for the model documentation regarding a specific set of tests that could 

be performed to determine product specific (e.g. MDF, wall-paneling, industrial panel, 

etc) ADC, LADC ADD, and LADD. In conjunction with this, a strategy could be 

developed for framing LADC and LADD in a manner that is consistent with product 

specific exposures rather than overall residential half-life. 

In the acute setting, the back-pressure effect may attenuate the contribution of a new 

product such that the total acute indoor exposure concentration is not affected by the 

added product. However, in a chronic, or long term, timeframe (e.g. 10 to 20 years), it is 

reasonable to expect that the majority of available formaldehyde and formaldehyde 

precursors will ultimately partition from the product into the indoor space. My 

recommendation is that conceptual framework be developed in the model documentation 

to ensure that users take these factors into consideration when investigating acute versus 

chronic timeframes. For the acute timeframe, it is important to consider the total 

collection of assembled indoor products, or alternatively, the background concentration 

attributable to the existing products. For chronic exposure, a more accurate 

characterization of dose attributable to a single product is likely obtained by 

considering the decay profile of that product that would be true in the absence of other 

products. The reason for this is that the attenuation that is observed due to the 

backpressure effect is temporary, and eventually, a source that is initially attenuated will 

begin to emit formaldehyde as the overall indoor air concentration level decreases. The 

model documentation should refer to the types of decay studies that could be done to 

understand the long term formaldehyde dose attributable to a single product or collection 

of related products. Examples of these studies include (Zinn et al. (1990), Mølhave et al. 

(1995), Myer and Hermanns 1985 and Brown 1999). Detailed comments for the acute 

and chronic timeframes are provided below. 
2-13

Acute Exposure

For acute exposure, the most straightforward approach is to determine a baseline 

background indoor air concentration and determine whether the introduction of a specific 

product (e.g. wall paneling at a specified loading rate) or collection of products (e.g. 

kitchen cabinets) will increase the indoor air concentration to a level exceeding a 

threshold of concern. The baseline concentration could be determined by: 

• A representative collection of products in compliance with voluntary or future 

emissions standards (or alternatively, current air chamber testing results); 

• Current actual background indoor air concentrations established by published data 

for new and existing homes; or 

• Future baseline background indoor air concentrations assigned based on policy 

and cost-benefit analysis. The future target background concentration would be a 

fraction of the threshold of concern to allow for initial increase in concentration 

attributable to the introduction of a new product or collection of products of 

concern. 

Under this approach, an option would be provided to the user to identify the ‘baseline 

products’ (or ‘indoor background from existing products’) and ‘added products’. In the 

model, output exposure and product specific emission rates would be presented with and 

without the added products. I believe this would greatly assist users of the model in 

intuitively understanding the backpressure effect, as well as assist specific manufacturers, 

regulators and other interested parties in understanding the incremental effect of specific 

products on indoor air levels. For example, for a small trailer, one question might be: how 

is the indoor air concentration affected by the introduction of 10 m2 of a paneling product 

that was not compliant with voluntary industry standards in the presence of other 

products that were compliant? Is it plausible that the other wood products in the trailer 

might have adsorbed formaldehyde from the non-compliant product and thus confound 

the interpretation of retrospective chamber testing? 

In the absence of this modification, the user could simply run the model with and without 

the source in question and simply compare the result and this approach was used in the 

model documentation in the evaluation of the addition of sinks. However, I believe that 
2-14

inclusion of this feature explicitly would greatly assist users unfamiliar with mass transfer 

theory and the interaction between formaldehyde sources. This feature would be 

particularly useful if the model were configured to output the emission rate and percent 

contribution to total emissions of the ‘baseline’ sources with and without the ‘added’ 

source. This feature would also provide a clear way to use and interpret the result of a 

product specific chamber test. A manufacturer could perform a chamber test, select a 

‘baseline’ configuration, then determine the incremental effect of their specific product, 

such as collection of kitchen cabinets. 

One basis for this comment is that the recent publication of FEMA temporary housing 

unit data failed to consider the potential implications of the backpressure effect for 

pressed wood products (Maddalena et al. 2009). The emissions equation relied upon by 

the authors did not account for the backpressure effect, and not surprisingly, the authors 

found that “the sum of all measured chemical emissions from the materials are general 

greater than the whole trailer emissions derived from measured concentrations”. 

Additionally, because the chamber testing was done retrospectively, the authors could not 

differentiate between primary and secondary sources. Therefore, although the results and 

conclusion of this paper give the impression that the extensive use of composite wood 

products and low air exchange rates were the primary explanation for high formaldehyde 

levels (averaging 440 ppb), I am concerned that these excessive levels may have been 

partially caused by a product or products that did not meet modern production criteria or 

perhaps even the voluntary standards (in combination with the temperature, humidity and 

air change rate conditions that were true in this particular case). If this occurred, then 

some of the lower emitting products may have been contaminated by the non-compliant 

products. 

In my view, one of the urgent federal policy questions regarding pressed wood products 

is whether the absence of federal regulations with performance based standards (with the 

exception of manufactured homes) has resulted an increased prevalence of imported 

products failing to meet the established voluntary industry standards or with potential 

emission rates higher than domestic production. I believe the slight reconfiguration of the 

model I am recommending would be extremely useful for explicitly addressing questions 
2-15

of this nature. From a policy perspective, after acute and/or chronic health based 

standards for formaldehyde are established, a focus on incremental exposure would be 

helpful for establishing the framework for the regulatory compliance program (e.g. the 

frequency of testing, documentation required for importers, how important is a 25% 

deviation above the compliance criteria for a single MDF panel, etc?). 

Chronic Exposure and Half-life/Decay

For chronic exposure, the most precise way to model formaldehyde exposure would be to 

use a transient finite difference model where the decay in the product specific equilibrium 

concentration or Matthews intercept is calculated as a function of time and as a time 

varying function of mass remaining of formaldehyde and formaldehyde precursors. In 

this approach, mass would be preserved because the equilibrium concentration for 

attenuated products would only being to decrease after the indoor air concentration 

decreased due to depletion of the other higher emitting sources. However, this would 

greatly increase the level of complexity of the model and the basic research that would 

provide a protocol to precisely define the mass reservoirs of formaldehyde, and 

particularly formaldehyde precursors, is limited. With the framework of the current 

model, it is probably most appropriate to estimate the chronic dose attributable to a 

product or set of products in the absence of other higher emitting sources, as I describe 

below. 

In contrast to the current model guidance and my recommendation for acute exposure, I 

believe the incremental chronic exposure attributable to a specific product (e.g. MDF 

panels) or defined collection of similar products (e.g. kitchen cabinets) should be 

assessed, rather than the aggregate cumulative exposure for all indoor products (i.e. the 

cross-sectional approach). Because the typical situation will reflect products of various 

ages, the chronic dose attributable to a specific product seems to be a more relevant 

metric than the total indoor concentration over time assuming an initial loading. 

Evaluation of the decay curve for a single product or class of products in isolation is 

likely to be more useful for understanding chronic risk and informing policy decisions 

about managing chronic risk than the suggested cross-sectional decay half-life approach. 
2-16

In addition, new construction represents a minor fraction of total residences, so the case 

where a new home is loaded with new products is the exception rather than the typical 

case for most of the population. In short, the emissions half-life is currently considered a 

‘house characteristic’, whereas I believe it would be more appropriate to frame this in 

terms of a ‘product-specific’ characteristic. 

For a specific product, a finite reservoir of free formaldehyde and formaldehyde 

precursors exists. Over a sufficiently large period of time, factors such as temperature or 

humidity are likely to affect the transient time-concentration profile, but less likely to 

affect cumulative exposure, or area under the curve. Similarly, the back-pressure effect or 

reversible sinks will temporarily suppress emissions from a new product, but it is likely 

that over a 10 to 12 year period, the reservoir of free formaldehyde and formaldehyde 

precursors from that product will be depleted, or released to the indoor space (for 

constant ventilation rate). Because the majority of the available reservoir is likely to be 

depleted over the lifetime of the product, incremental risk from separate products or 

collection of products can be added to derive total risk or an acceptable risk range by type 

of product (e.g. MDF) could be established. This incremental approach may slightly 

over-estimate true risk depending on the assumed tenure of the occupants, but this can 

be somewhat accounted for by either assuming a finite emission lifetime of an individual 

product (e.g. 10 years) or by selecting a target background indoor concentration higher 

than outdoor ambient air levels corresponding to the decay concentration where 

emissions from the source under consideration would be considered de minimus. One 

problem with a ‘product specific’ approach is that while this approach allows for a more 

accurate estimate of area under the curve (i.e. cumulative dose) for a product present for a 

reasonably long time (e.g. 20 years), it does not provide a way to calculate accurate total 

concentrations at specific points in time (e.g. 3 months, 6 months, etc.) This problem is 

caused by the difficulty in trying to reconcile a transient process with the limitations of a 

pseudo-steady state model. 

Under the current model guidance, the true increased cancer risk attributable to 

installation of a specific product such as wall-paneling in an existing home to repair 

damaged plaster or kitchen cabinets installed during remodeling would not be reliably 
2-17

determined. Initially, the backpressure effect will suppress a portion of the formaldehyde 

emissions, such that if the user were to compare cumulative dose with and without the 

product based on current model guidance, the lifetime dose for that product will be 

underestimated. If the equilibrium concentration (i.e. the theoretical concentration in the 

absence of ventilation) of a product such as kitchen cabinets is less than the pre-existing 

steady state concentration, running the model with and without kitchen cabinets would 

result in the physically impossible conclusion of negative incremental cancer risk 

because the cabinets would initially act as a net sink. To illustrate this point with an 

extreme example, consider a baseline mobile home with model defaults loaded with 90 

m

2

 decking with maximum HUD rate. The initial concentration is 0.3557 mg/m3, LADC 

is 0.0132 mg/m3 and percent of time > 10 ppb is 46.9%. If 45 m2 of kitchen cabinets with 

the EPA cabinet rate are added to the existing decking, the initial concentration is 0.3389 

mg/m3, LADC is 0.0125 mg/m3 and percent of time > than 0.01 ppm is 46.1%. Here the 

apparent LADC decreases after the kitchen cabinets are added to the assessment because 

the kitchen cabinets act as an implicit since. This can be observed from the kitchen 

cabinet equilibrium concentration equal to b/-m or 0.08 (mg/m2-hr) / 0.49 (m/h) = 0.16 

mg/m3. It seems likely that over the lifetime of the kitchen cabinets, there will a finite 

long term dose greater than zero that will occur once the original source attenuates. 

The assessment should be based on a conceptual model for decay in formaldehyde 

emissions over time and basic research on the decay profile of individual products should 

be encouraged in the model documentation (rather than exclusively relying on the 

historical data from the 1980’s). At a minimum the model should be revised to allow 

consideration of periods of rapid and slow decay in the emission rate as observed, for 

example, in Zinn et al. (1990), Mølhave et al. (1995), Myer and Hermanns 1985 and 

Brown 1999. Long term testing is not feasible on a routine basis, but I believe the model 

should have the framework in place for investigators, suppliers or manufacturers 

interested in more robustly characterizing chronic exposure than has been typically done 

to date. Particularly of concern is that the decay characteristics of modern and new to 

market resins are largely unknown. The current single compartment exponential model 

will provide a conservative estimate of chronic exposure, but does not necessarily 
2-18

provide a pathway forward or conceptual framework for refinement of the calculation of 

long term cumulative dose. 

One conceptual model for assessing chronic exposure for formaldehyde releasing 

products was published by Mølhave et al. (1995). In this study, a selection of furniture 

and fitments supplied by a retailer was placed into a large scale chamber and 

measurements were made over an 8-week period. Conceptually, three exponential decay 

compartments were attributed to three potential sources of formaldehyde emissions, 

including: 

• free formaldehyde (short-term compartment); 

• decay of paraformaldehyde and other complex structures (medium-term 

compartment); and 

• hydrolysis of the resin (long-term compartment). 

Using an exponential peeling procedure, the authors determined relative sources strengths 

and half-lives for each of these three compartments. A two-compartment (slow and fast 

decay) analysis using an EPA model also adequately represented the transient data. The 

corresponding accumulated dose was compared to the California Proposition 65 safe 

harbor level to determine the incremental contribution of a specific set of products (i.e. 

living room furnished with IKEA furniture). This product specific testing may be helpful 

in refining the estimate of LADD and LADC and the approach to understanding whether 

compliance with Proposition 65 was achieved was reasonable. I strongly recommend that 

the model documentation be modified to make clear how this type of testing could be 

incorporated into the model. Currently, the half-life parameter pertains to a structurebased decay rate rather than a product-based decay rate. 

For the default case, the decay rate presented in Zinn et al. (1990) seems more 

appropriate than the 2.92 year half-life derived from cross-sectional sectional data in the 

original Versar model. Zinn et al. (1990) estimated an apparent half-life of 216 days 

using approximately one year of large chamber data for particle board and a natural 

logarithm linear regression statistical analysis. The half-life reported in Zinn et al. (1990) 

is not directly comparable to that adopted in the original and current Versar model 
2-19

because Zinn et al. used the relationship HCHO = F + G x ln(time) with regression 

constants F and G whereas the EPA half-life was based on a traditional exponential decay 

model. The Zinn et al. logarithmic equation was used by CARB (2007; see Appendix B) 

to calculate the emissions inventory presented in the technical basis for the formaldehyde 

airborne toxic control measure. In lieu of the original logarithmic equation, the more 

generic two-compartment (i.e. fast and slow decay) exponential decay model could be fit 

the Zinn et al. data. 

Finally, one concern is the interaction between ventilation rate and decay rate. Given long 

term testing data, the total reservoir of formaldehyde and formaldehyde precursors for a 

given ventilation condition could be calculated. Therefore, in the future when decay 

characteristics are better understood, it should be possible to adjust for ventilation rate 

and account for total mass of formaldehyde generated over the lifetime of the product. 

Although the data to accomplish this is currently not available, it would a benefit to the 

scientific community to frame decay of emissions over time in terms of an accurate 

conceptual model, rather than current fully empirical and cross-sectional approach. 

Matthews Regression Model versus HBF Regression Model

The original Versar model presented the linear regression parameters both the Matthew’ 

model and the Hoetjer model (identified as HBF model in 1986 Versar model), as well as 

the steady equations for both models. These two models are both mass transfer based 

approaches, however, the mass transfer coefficient obtained by linear regression is not 

identical. This can be seen in the documentation for the 1986 Versar model, where the 

correlation coefficient is typically higher for the Hoetjer than for the Matthews model. 

For example, for PCB#3, the mass transfer coefficient was 0.48 m/hr in the Matthews 

regression (r=-0.84) and 0.70 m/hr in the Hoetjer linear regression (r=0.96). Because 

slightly different results are obtained depending on the regression model used and the 

Hoetjer model is widely cited in the literature, it is recommended that the model 

documentation be revised to include discussion of both approaches. 
2-20

To illustrate this point, I performed a linear regression analysis for the first loading of 

kitchen cabinets presented in Koontz et al. (1996). The regression model for the HBF 

mass transfer relationship is given in Myers and Nagaoka (1981). The linear regression 

models are: 

where: 

K = -m = mass transfer coefficient (m/h) 

CS = steady state concentration (mg/m3) 

N = air change rate (1/hr) 

L = loading rate (m2/m3) 

Ceq = concentration at zero ventilation rate (N=0) 

b = emission rate at zero formaldehyde concentration 

The simplified steady state models are: 

It can be shown these are identical models and that Ceq= b/-m. Therefore, the difference 

in models is in the regression equation 1 and 2 used to derive the parameters, not the 

theoretical construct. The equilibrium concentration is the vapor phase concentration at 

the surface of the board and the bulk phase concentration that would be true in the 

absence of ventilation. The Matthews parameter b is a combination of the mass transfer 

coefficient K and equilibrium concentration Ceq. The mass transfer coefficient is 

determined by the properties of the board or object surface, whereas the equilibrium 

concentration is determined by the formaldehyde generating properties of the panel and 

varies with temperature, humidity and age (Berge et al. 1980). These concepts are less 

transparently elucidated by the Matthews emissions equation. 
2-21

The easiest way to incorporate a discussion of the two approaches would be to show how 

m, b, Ceq and K are calculated for the kitchen cabinet data presented in Koontz et al. 

(1996) using both the HBF and Matthews regression equations (in an Appendix). The 

purpose of this appendix would be to provide clear guidance on the type of chamber tests 

(i.e. at least three N or L combinations for the linear regression) that would be needed to 

determine the parameters that are input into the model. 

The results show that the fit is slightly different depending on the method that is used 

(Figures 1a and 1b). In this example, the minor differences in regression parameters 

result in predicted steady state concentrations that are similar over a range of air 

exchange rates (Figure 2). This should be the case in most situations. 

Figure 1a: Matthews linear regression. m=-0.49 m/h, b=0.08 mg/m2/h, r=-0.973 
2-22

Figure 1b: HBF linear regression. Ceq = 0.19 mg/m3, K = 0.41 m/h, r=0.997 

Figure 2: Calculated steady state concentration for regression models in Figure 1 

assuming loading (L) of 0.13 ft2/ft3

My preference would be to allow input the parameters from either approach as was the 

case in the original model. Although the mass transfer basis is identical for each model, 

the parameters of the Hoetjer model are more intuitive. For example, based on the 

equilibrium concentration, it is easy to see that the worst case concentration in the 

absence of ventilation (N=0) is 0.19 mg/m3. It is easy to conceptualize that this is 

approximately the level that would be expected in a confined space like the inside of a 

closed kitchen cabinet. The Matthews model parameters are less intuitive. The maximum 

emission rate which can be derived directly from b is only true in the absence of 

formaldehyde in the bulk air, or at the beginning of the exposure period. However, the 
2-23

Ceq of the HBF model can be easily calculated. The concentration in the absence of 

ventilation (and background sources) is b/-m or Ceq= b/-m. 

Having made the recommendation to allow for both approaches, I recognize that is likely 

not possible due to time and financial constraints – and given the essential identical 

model construct perhaps of minimal benefit. My recommendation if only the Matthews 

model is retained in the model is to provide an example calculation in the model 

documentation showing how the user can start with the HBF linear regression or the HBF 

model parameters and convert the parameters to the equivalent Matthews model, or 

The caveat should be included that this conversion does not account for the 

slightly different result that is obtained using the HBF versus the Matthews linear 

regression models. Another option would be to provide the HBF equilibrium 

concentration as supplemental output. Knowledge about the equilibrium concentration 

allows an intuitive determination about whether a particular product is likely to act as a 

sink or a source based on an estimate of the anticipated indoor air concentration. 

In conjunction with this conversion equation, a statement should be included indicating 

that for plausible ranges of the N/L ratio, the selection of a particular linear regression 

model is not expected to appreciably affect the results. This could be demonstrated by a 

Monte Carlo analysis or reanalysis of the data in Table 2-2. 

Indoor Sink – Explicit Indoor Sinks

The model used to represent sinks accounts for reversible sinks. Prior research using 

unpainted drywall showed that this sink caused only a minor permanent loss of 

formaldehyde and that the wallboard serves as a buffer to sudden changes in indoor air 

concentrations (Matthews et al, 1987). However, the treatment of indoor sinks in the 

current EPA model is problematic because absorption and desorption of formaldehyde 

from indoor sinks is a transient process over relatively short time scales not well suited to 

a steady-state or pseudo steady state model construct. As shown in Figure 1 below 

reproduced from Tichenor et al. (1991), a reversible sink buffers changes in 

concentrations but does not necessarily affect cumulative exposure, or area under the 
2-24

curve. Therefore, for instances where the EPA model is used to calculate lifetime, or long 

term dose, accounting for reversible sinks could potentially underestimate true 

cumulative dose, depending on how the exponential decay over time is conceptualized. 

Figure 1: Chamber test results for a reversible sink reproduced from Fig. 2, p. 27 in 

Tichenor et al. (1991). 

When the Langmuir model is run to steady state, dM/dt = 0 and Cindoor = kd/ka*M. 

However, at steady state, there is no capacity for the sink to absorb more formaldehyde 

(at the given concentration), and the net absorption rate is zero. The Langmuir model 

does not consider irreversible sinks. Therefore, at steady state there is no net effect of the 

sink and if the EPA model guidance provided on page 3-7 is followed exactly (e.g. 

0.0375 mg/m2-h per 10 ppb indoor air), there should be no net effect of the sink 

(Matthews et al. 1987). This is also easily seen by noting that Ceq=b/-m and using the 

standard mass transfer equation. For drywall, Ceq = 0.0375 mg/m2-h / (-3 m/h) / (1.236 

mg/m3 / ppm) x 1000 ppb/ppm = 10 ppb. Therefore, when CS=Ceq = 10 ppb, then ER = 

K(Ceq-Cs) = 0, where ER is the emission rate. Note that as a result of rounding or 
2-25

significant digits, there could be a small (arbitrary) net positive or negative flux from a 

sink defined in this way. 

It appears that the guidance for the sink intercept given on EPA model guidance page 3-7 

was developed by setting intercept b = ka x Cindoor assuming dM/dt = 0. When there is a 

linear relationship between accumulated mass and indoor air concentration at equilibrium 

conditions, dM/dt must equal zero. Therefore, deviations of the intercept from the 

calculated value would imply a sustained loss of equilibrium, violating the assumption 

used in assigning the sink slope and intercept in the Mathew’s equation. Furthermore, the 

guidance provided for selection of the equilibrium intercept for indoor sinks appears to 

treat this parameter as calibration or adjustment factor rather than as a predictive input. 

For wallboard, the surface area is high in magnitude, therefore minor arbitrary decreases 

in the intercept from the values recommend in the model documentation will yield a 

noticeable apparent sink effect. However, there does not appear to be justification for 

assigning these deviations. For example, in Table 5-4, the Zone 1 concentration without 

the wallboard sink is 46 ppb. Taking 46 ppb as the starting concentration, the first 

estimate for the slope of the wallboard sink would be (46 ppb / 10 ppb) x 0.0375 mg/m2-h 

= 0.1725 mg/m2-h. When this value is entered for the wallboard slope, as expected, the 

Zone 1 concentration remains at 46 ppb. Due to rounding or insufficient significant 

digits, the calculated flux for this intercept actually reflects net generation rate (G) where 

positive G corresponds to desorption: 

G = 420 m2 x (0.05721 mg/m3 x -3 m/h + 0.1725 mg/m2-h) = 0.36 mg/hour 

Holding concentration constant in the prior example, a negligible decrease in the 

intercept to 0.1715 mg/m2-h would cause the wallboard to be considered a sink with net 

adsorption: 

G = 420 m2 x (0.05721 mg/m3 x -3 m/h + 0.1715 mg/m2-h) = - 0.05 mg/hour 
2-26

It is clear that minor decreases in the intercept from the recommended starting point will 

cause the model to reflect a net sink effect for wallboard. This is true because at the 

starting point (e.g. 0.0375 mg/m2-h per 10 ppb indoor air), the net generation rate from 

the sink is approximately zero, or dM/dt = 0. However, there does not appear to be a 

reliable way to a priori assign the final value of the intercept other than trial and error to 

achieve a modest decrease in indoor air concentration. 

The short term data from Loading 1 at the test house clearly show that the initial sink 

effect from wallboard can be appreciable. To correctly account for net adsorption on 

these short time scales within the framework of a pseudo steady state model, a non-zero 

value of dM/dt must be calculated using Equation 3-13 and set equal to the Matthews 

emission rate equation to derive the intercept. This value of dM/dt will vary as a function 

of time. Such an approach would appreciably increase the level of complexity needed to 

assign the sink term because indoor concentration and mass storage vary as a function of 

time. However, prior EPA models such as MCCEM have included this functionality. If 

an estimate of the indoor concentration profile is available as a function of time (e.g. for 

the test home), it should be possible to determine M(t) and dM(t)/dt as a function of time 

by numerical integration or finite difference model. However, at 30 days, dM/dt may be 

sufficiently small that a reasonable default recommendation in the model would be to 

neglect the effect of sinks. 

The treatment of sinks in the EPA formaldehyde model reflects a reduction in 

sophistication from that which is available in the prior EPA/Versar MCCEM model. 

Using the MCCEM model, it is possible to track dM(t)/dt and M(t) for the sink and make 

a determination about whether the short term effects of a particular sink are substantial 

enough to include in the final model. Of course, the adaption of a MCCEM-type 

approach is not straightforward because the formaldehyde model addresses long-term 

decay using a pseudo steady-state approach. It may be appropriate to have two versions 

of the model: 

• Pseudo steady-state model for long term exposure neglecting reversible sinks; and 

• Short term MCCEM-style model to understand whether the presence of sinks 

would appreciable reduce initial peak exposure. 
2-27

As an example, MCCEM was used to implement the Langmuir model for a carpet and 

pad sink from Koontz et al. (1996) and applied to Conventional Home 1. This home is 

characterized by high air exchange between the first floor and basement and low air 

exchange between the basement and outside. Therefore, the generation rate needed to 

achieve a Zone 1 steady state concentration of about 10 ppb can be roughly estimated 

using a one zone approximation, of G (mg/hr) = C (mg/m3) * Q (m3/hour). The following 

parameters were input into MCCEM: 

Formaldehyde generation rate = 3.434 mg/hour (to approximate 10 ppb steady state) 

Reversible sink, carpet: 

ka = 1.304 m/hr (Koontz et al. 1996 p. 6-44) 

kd = 0.196 hr-1 (Koontz et al. 1996 p. 6-44) 

A = 94 m2 (EPA model documentation Table 5-3) 

Home: 

Zone 1 volume = 304 m3 (EPA Conventional Home 1) 

Zone 2 volume = 167 m3 (EPA Conventional Home 1) 

Interzonal airflow = 111.5 m3/hr (EPA Conventional Home 1) 

Zone 0-1 airflow = 259.5 m3 (EPA Conventional Home 1) 

Zone 0-2 airflow = 19.6 m3 (EPA Conventional Home 1) 

As shown in Table 2, the presence of the carpet sink has a de minimus effect on the net 

emission rate in Zone 1 given a source generating a steady state formaldehyde 

concentration of 10 ppb. Approximately 7 or 8 hours after introduction of the source, the 

rate of increase in storage in the sink is negligible and therefore there is no net effect 

attributable to the presence of this sink. The results in Table 2 below can be confirmed by 

simple screening calculations for steady state: 

Csteady = 1000 ppb/ppm x 3.43 mg/hour / (471 m3 x 0.59 hr-1 x 1.236 mg/m3 per ppm) = 

10 ppb 

dM/dtsteady = 0 = 0.010 ppm x 1.236 mg/m3 per ppm x 1.304 m/h x 94 m2 – 0.196 hr-1 x M 
2-28

 M = 0.082 mg/m2  M*A = 0.082 mg/m2 x 94 m2 = 7.7 mg 

Note that at steady state, kd x M = 0.196 hr-1 * 0.082 mg/m2 = 0.016 mg/m2-hour. This is 

also the value recommended as the intercept for carpet on page 3-7 of the formaldehyde 

model guidance when the concentration is 10 ppb. From this example, it should clear that 

when the Matthews slope and intercept are assigned in accordance with the proposed 

guidance, dM/dt is zero and there should be no net effect of the sink on the emission rate. 

Any apparent effect is caused by minor deviations in the intercept or rounding errors, 

which do not appear to have a theoretical basis. 

Table 2: MCCEM model results for constant source and carpet set in a hypothetical twozone home (EPA Conventional Home 1) 

The Koontz et al. (1996) study concluded that the Langmuir model was not adequate to 

derive a reasonable fit to the data for wallboard (p. 6-48). The results of the study did 

confirm that the Langmuir model is appropriate for carpet and padding as expected from 

the literature (Tichenor et al. 1991). The documentation for the EPA formaldehyde model 

does not address the original findings by Koontz et al. (1996) with respect to wallboard or 

provide justification for application of the Langmuir model to wallboard given the prior 

findings. More discussion is warranted, and perhaps consideration of the unpainted 

wallboard studied in Matthews et al. (1987) would be helpful. 
2-29

The initial sink parameters specified in this model are less problematic theoretically 

because the rate of desorption (kd x M) is low initially. However, the inclusion of these 

parameters is questionable because the pseudo steady-state design of the model is not 

well equipped to handle transport processes that occur over relatively short time scales. 

As shown in Table 2, sinks can reach the maximum loading at a given concentration 

relatively rapidly. I recommend evaluating dM/dt as a function of time for the EPA test 

house and other data and making a determination about whether the current EPA 

formaldehyde model should be used to predict fate processes that change rapidly over 

hours to days. If sinks are to be included in the model, I recommend developing clear 

guidance for assignment of the Matthews parameters. One criteria should be that dM/dt 

does not change rapidly relative to the time scale being investigated (e.g. 24-hour 

average, etc.). 

Indoor Sink – Implicit Indoor Sinks

Some pressed wood formaldehyde “emitters” could theoretically act as sinks under 

certain conditions based on the properties of wood and the Matthews model (e.g. 

products with very low equilibrium concentration or, equivalently, low Matthews model 

intercept). For example, low emitting products with unreacted urea can act as scavengers 

(Meyer and Hermanns 1985). This could potentially be an interesting question for 

situations like manufactured home where a product with excessive free formaldehyde 

levels could ‘contaminate’ otherwise low emitting products. Therefore, there may be 

some usefulness in presenting the emission rates by product in the results, with negative 

emission rate indicating a net sink effect. Because a steady state model is used, one 

concern about implicit sinks, especially as more low emitting products become available 

on the market, is that it is difficult to account for whether or not the storage capacity of 

the implicit sink has been exceeded over the time frame of interest. This could be a 

minor potential concern in some situations, such as when few high emitting products are 

paired with several very low emitting products. Presentation of the emission rate as 

output would provide a starting point for understanding whether implicit sinks are 

present. 
2-30

To provide an extreme example, the Mathew’s mass transfer parameters for kitchen 

cabinets were paired with a range of assumed background concentrations. Here for 

simplicity, the ‘background concentration’ is used as a proxy to represent all other 

sources or a loaded room influencing an adjacent loaded road. The parameters used were 

m = -0.49 m/h, b=0.08 mg/m2/hr, ACH = 0.5 hr-1 and L = 0.13 ft2/ft3. The corresponding 

equilibrium concentration (Ceq) from the HBF model is approximately 0.163 mg/m3. As 

can be seen from the results in Table 3, when Cb > Ceq, the kitchen cabinets would act as 

a sink, resulting in a lower steady state concentration than the influent background 

concentration (∆Csb < 0). This result is expected from the mass transfer equation where 

ER = K(Ceq-Css). When Css > Ceq, the direction of the flux is from the bulk air in the room 

to the pressed wood product. This example illustrates two key points. First, the use of the 

HBF model equilibrium concentration provides a more intuitive way to anticipate the 

results than the Matthews intercept b. Second, the output in the model of the emission 

rate attributed to each of the individual components models could potentially provide 

useful diagnostic information to the user or modeler. As wood panel resin technologies 

improve and more ‘green resins’ become available, the potential exists for low observed 

equilibrium concentrations. Depending on the properties of the panel, these products may 

or may not act as reversible and/or irreversible sinks. I believe the model should provide 

sufficient ancillary information to understand the sensitive parameters and identify other 

potential areas for testing. 

Table 3: Illustration of transition from source to sink at the equilibrium concentration 

based on variation in background concentration or other sources. 
2-31

2.1.2 Comment on the Default Scenarios and Assumptions Used by the Model 

Michael Jayjock: 

For the most part the default scenarios and assumptions appear to be reasonably 

supported. Specifically, the air exchange rates for the homes agree with my 

understanding of national averages for this important variable. My suggestion is that the 

modelers should consider using and including the seminal study by Murray and 

Burmaster as an important reference for potential use with this model (ref: Murray, 

Donald M. and David E. Burmaster: Residential Air Exchange Rates in the United 

States: Empirical and Estimated Parametric Distributions by Season and Climatic Region, 

Risk Analysis, Vol 15, No. 4, 1995). Of particular value are data from different 

geographical sectors and seasons within the U.S. 

Also, I found the choice of housing types to be very reasonable. I also agree with the 

choice of a realistic house size as a default in that larger houses have a lower level 

surface area to volume loading for sources. 

As noted above the assumption (or possible interpretation) that any child in any of the 

age groups will have 10 years of exposure is confusing at best and should be easily 

corrected. Of course, the years of exposure should be equal to or less than the years 

within that age group. Indeed, my sense is that many analysts will be interested in the 

exposure within a particular age group and not necessarily extended across age groups. 

Panos Georgopoulos: 

Key default assumptions in the formulation of the FIAM-pwp (e.g. constant emission 

rates etc.) were discussed in detail above, in the answer to Question 1.1, as these 

assumptions in fact “drive” the mathematical equations of the model. Other assumptions 

involved in the formulation of specific scenarios should be considered generally 

reasonable, as long as the model results are not being “over-interpreted” by the user in 

terms of their accuracy and precision. 
2-32

Kenneth Unice: 

The default approaches and parameters are likely to result in a conservative estimate of 

acute and chronic exposure. My concern is that in some instances, there is not necessarily 

a clear pathway forward for refining the default parameters. 

Data Collection to Revise Default Assumptions

It is not clear how the manufacturer of a specific product (e.g. MDF panel) could do a 

study with their specific product to refine the cross-sectional residential half-life. 

Therefore, there is not clear guidance regarding how to assess the degree to which some 

parameters are conservative. Answering these questions is likely to require new data, as 

the literature on some components of the model (e.g. emissions decay) is limited. 

I am concerned that too much emphasis is placed on the large database of historical 

emissions parameters provided in the model (Table 2-2) and historical decay rate 

evaluations (Section 3.6). I believe the model formulation and model documentation 

should be more forward looking in two respects. First, it should be made clear that many 

of the default emissions parameters in the model are based on historical testing and may 

or may not be representative of current products (See also Response 1.2). Typically these 

rates should be conservative (i.e. likely to overestimate emissions), but it is plausible that 

the default parameters may underestimate true emissions from products, particularly 

imported products, as a result of exceptional free formaldehyde levels exhibiting nonconformance with the voluntary industry standards. Second, clear guidance should be 

provided to end users (e.g. importers, manufacturers, non-profit organizations or 

regulators) about the data and steps required to assess the HCHO incremental exposure 

attributable to the introduction of a specific product into the home. For example, a case 

study could be provided for a hypothetical wood paneling manufacturer showing all of 

the steps from the acquisition of chamber test results, to calculation of incremental 

exposure attributable to the product and finally performance of a sensitivity analysis. 

Typically the mass transfer coefficient is not determined in routine chamber testing, and 

the sensitivity analysis would be helpful in determining whether this additional product 

specific data is a data need or a data gap. Other questions addressed by the sensitivity 
2-33

analysis could include the effect of inter-zonal air change rates, whole-house air change 

rates, temperature, humidity or loading. 

2.1.3 Comment on the Data Sources 

Michael Jayjock: 

Note the above comment on residential air exchange rate and a referenced source of good 

information on this important parameter. The other critical sources within this model are 

the chamber tests for emission rates and the fitted values for the linear rate model. I am 

not familiar with these data sources but they seem to be well described and characterized 

by the author. I also do not know of other data sources on the emission of formaldehyde 

from wood. I considered and researched the significant effort on indoor emissions 

sources done in recent years by the Canadian National Research Council but this program 

turned out to be focused on volatile organics and did not include formaldehyde. 

Panos Georgopoulos: 

The data sources for FIAM-pwp appear reasonable – and they do in fact contain valuable 

information that has not been fully utilized up to now in modeling analyses. However, 

since most of them appear be to rather old, one may question whether they are still the 

most relevant data sources in relation to currently available/used pressed wood products 

(given changes in manufacturing procedures as well as in changes in relative levels of 

domestically manufactured versus imported pressed wood products). The answer may in 

fact be yes, but it should be explicitly stated and supported. 

Kenneth Unice: 

The sources of data in the model are reasonable and accurately represent the original 

studies, with the exception of the wallboard sink as noted below. 

Emissions parameters

It is unknown the degree to which the data in Table 2-2 reflect manufacturing practices in 

2009, and the potential for low or high bias exists. Users of the model should be 

encouraged to collect and use data for products currently in the supply chain. This could 

be accomplished by deemphasizing the data in Table 2-2 (perhaps by moving to 
2-34

Appendix) or by requesting voluntary submission of chamber data from industry prior to 

release of the model. Alternatively, perhaps a mechanism could be put in place such that 

the database in Table 2-2 is routinely updated as new information becomes available. 

Conventional 1

Airflow between the basement and outside was low, which may or may not be 

representative for other structures. For example, if a lower efficiency furnace is located in 

the basement, make-up air for combustion could induce substantial airflow in the winter. 

To the casual user, it will not be immediately obvious that Conventional 1 represents the 

data for one test house under limited conditions. Therefore, I recommend that this home 

be explicitly labeled in the model as the pilot home to indicate that this data is for the 

home from the EPA pilot study. With regard to the underlayment in Conventional 1, were 

steps taken to prevent emissions to the basement from the underside of the floor panels? 

It is not clear whether the underlayment should be a source to Zone 1 or to both Zone 1 

and Zone 2. 

Conventional 2

More details regarding the analysis of PFT data used to derive the airflow rates 

Conventional 2 should be provided. 

Wallboard sink

The use of Langmuir isotherm for wallboard should be further explained, as this was 

found to not be valid in the original report for the pilot study (Koontz et al. 1996) 

2.1.4 Comment on Whether the Data Sources Provide Unused Information That 

Would Assist in Quantifying Uncertainty or Variability for Subsequent 

Model Use 

Jensen Zhang: 

Although the data sources are incomplete for quantifying the uncertainty, it is possible to 

conduct an uncertainty analysis using error propagation theory with assumptions on the 

uncertainties in the raw data. This would help establish the uncertainty in the predicted 

results. 
2-35

Michael Jayjock: 

I interpret the above question to mean the data used in this model plus “new” data sources 

not included in this work. See my comments above about the Murray/Burmaster database 

on air exchange rates in U.S. residences. Clearly these data could assist in gauging the 

variability of this parameter. Also, I believe the current data used in the model on 

emission sources discloses a level of uncertainty and variability that could also be mined 

by a person who is knowledgeable about these data and their origins. See comments 

below. 

Panos Georgopoulos: 

Yes: the variability in the available data could be used to derive distributional estimates 

of emission rates that would support probabilistic (and population based) indoor 

concentration and corresponding exposure estimates with explicit characterization of 

uncertainties and variabilities. 

Kenneth Unice: 

Wallboard sink

The approach to wallboard sinks used in the current EPA model should be consistent with 

the wallboard sink equations and data presented in Matthews et al. (1987). The wallboard 

in this study was unpainted, but latex paint was not expected to appreciably affect 

formaldehyde transport. The use of Langmuir isotherm should be further explained, as 

this was found to not be valid in the original report (Koontz et al. 1996). 

Uncertainty and sensitivity

The uncertainty and sensitivity analysis presented in Matthews et al. 1985 could be 

discussed.

2.1.5 Comment on Whether the Model Input Variables and the Estimates 

Assigned to Them Appropriately Reflect Variability 

Jensen Zhang: 

I did not see the uncertainty values for the model inputs. 
2-36

Michael Jayjock: 

From what I can determine all of the model input variables are entered as deterministic 

values – that is, as single numbers without variability. Indeed, I agree with the tone of the 

question that perhaps variability emanating from the model should be reasonably 

described because in its current form it is not. Clearly, which particular variable or data 

source one chooses will drive the outcome and the result will be variable if different input 

values are chosen. Thus, a user could choose to use inputted highest emission values (no 

sinks) which maximize the concentration and exposure within the range of his or her 

knowledge of the scenario to obtain a high end prediction. This could be followed by a 

run in which he or she would use inputs that were on the low end of the range (and 

include sinks) that again reflected the modeler’s knowledge or confidence in the 

situation. The comparison of outputs would provide some quantitative level of variability 

extant within the system and would be provided within the context of the user’s 

perspective and confidence. 

Another possibility would be to take the data in Table 2-2 and determine which data sets 

might be reasonably combined as presumably coming from the same population. 

Parameters from these data sets could be analyzed for the statistical variability and the 

parameters of the emission equations could be represented as best-fit probabilistic 

distribution functions. These distributions would then be incorporated into a Monte Carlo 

scheme to present a predicted output distribution of concentrations and exposures. This 

would add significantly to the complexity of the tool but would provide a direct and 

cogent measure of model variability as driven by the input variables. 

Panos Georgopoulos: 

As mentioned in the answers to previous questions, a distributional/probabilistic 

approach, for defining model input variables and deriving concentration and exposure 

estimates, would, in this reviewer’s opinion, be more appropriate in relation to this 

model, given the wide ranges of uncertainties in processes affecting the estimated 

variables and of variabilities in real world scenarios of inhalation exposures to 

formaldehyde. 
2-37

Kenneth Unice: 

Sinks

The model documentation does not provide a credible method for selecting the indoor 

sink parameters. Guidance for calculation of dM/dt should be provided in line with my 

comments elsewhere in this review. 

Airflow

The model screen and documentation should make clear the Conventional 1 represents a 

single unoccupied test home. The analysis used to derive Conventional 2 should be 

described. If possible, airflow rates should be made available for key determinants as was 

done in MCCEM (e.g. season, area of the country). 

Mass transfer coefficient

The mass transfer coefficient is not routinely measured in most chamber testing. EPA 

should perform a sensitivity analysis to determine whether measurement of the mass 

transfer coefficient is a data need or data gap when newly acquired chamber test data is 

entered into the model. The equilibrium concentration is likely to be the key determinant 

of exposure with the mass transfer coefficient of less importance but this has not been 

established in the current documentation. 

Half-life

The single exponential equation for decay is consistent with the historical cross sectional 

residential data but inconsistent with studies that have investigated single products or 

collection of products over time (Zinn et al. 1990, Mølhave et al. 1995, Myer and 

Hermanns 1985 and Brown 1999). The true area under the curve for dose given a long 

enough exposure time is likely better represented by the two- or three- compartment 

exponential models than the single exponential model because these models better 

represent the decay in the reservoir of formaldehyde precursors in a specific product or 

collection of products. My largest concern is that when the half-life is defined in terms of 

the residence rather than in terms of the products, there is no good conceptual model by 

which to collect product specific data to refine this parameter. It may be possible to 

address some of these questions using a sensitivity analysis to determine whether 
2-38

conclusions about risk would change depending on how dose from the products is 

conceptualized. 

Equilibrium concentration

The degree to which the historical data in Table 2-2 reflects domestic and imported 

production is not known. The opportunity should be provided for the voluntary 

submission of data representative of the current supply chain.

2.1.6 Comment on the Adequacy of the Documentation Supporting the Overall 

Plausibility of the Exposure Estimates Generated by the Exposure Model 

Michael Jayjock: 

My sense is that the estimates have been clearly shown to be plausible relative to results 

of comparing the modeled estimates to the measured data in the Pilot House study. Even 

through all of the practical difficulties, which were very well explained in the 

documentation, this study appears to provide adequate evidence that the model is 

certainly capable of providing credible estimates. I believe that this is particularly true for 

the model executed in the skillful hands of technical experts who had almost perfect 

knowledge of the scenario and the workings of the model. 

Perhaps a more practical test of the model’s accuracy and reliability might come from its 

comparison to measured data in some realistic scenarios as viewed and implemented by 

or from the perspective of a non-expert user. This would involve going into newly 

constructed residence(s) and modeling first (monitoring second) after determining the 

appropriate model inputs using available information. The modelers would still be 

technical experts but would be faced with and have to deal with a typical level of 

uncertainty borne of a finite lack of knowledge. Here invoking worst-case/best case 

models estimates of the real world scenario as described above (and then comparing them 

with measurements) could be very valuable in demonstrating the model’s value in 

predicting real world concentration and exposures to formaldehyde. 
2-39

Panos Georgopoulos: 

Ideally, the exposure estimates that are derived from FIAM-pwp should be characterized 

within a total exposure context that would take into account influences of numerous other 

indoor and outdoor sources and sinks as well as of indoor and outdoor gas and 

heterogeneous phase chemistry of formaldehyde (that may result in net production or 

removal in a given microenvironment). Very large variabilities should be expected across 

regions and populations, with differences in both geographical (e.g. climate variables) 

and socioeconomic factors (housing, occupation, etc.) driving these variabilities. Linking 

such estimates with corresponding population-based estimates of exposure to outdoor air 

formaldehyde (e.g. from the National Air Toxic Assessment [NATA] studies) would be 

very useful in that context. Comparison of model estimates with relevant observational 

data sets for indoor-outdoor relationships and of personal level (e.g. from studies such as 

RIOPA – see, e.g., the Liu et al., 2006, reference in the Addendum of this review) would 

be valuable in assessing, at least qualitatively, the plausibility and relevance of the 

exposure estimates derived from FIAM-pwp. 

Kenneth Unice: 

Use of Pilot Study

The EPA pilot study, while very useful, is limited to one structure. I recommend pulling 

together a collection of representative baseline loadings and comparing the model results 

to published concentrations of formaldehyde in new and existing structures. Examples of 

papers presenting indoor formaldehyde levels for recent times include Hodgson and 

Levin 2003, Hodgson et al. 2000 and Maddalena 2009. 

Average Daily Concentration/Dose

EPA has not shown how use of an overall residential half-life is to be used to derive 

product specific dose. Running the model with and without the product of interest will 

not result in meaningful conclusions as discussed previously. Accordingly, there is great 

uncertainty in product specific doses under the current model framework. EPA has not 

considered whether the historical 2.92 year cross-sectional half-life is representative of 

the decay profile of modern products or the potential variability in the formaldehyde 

reservoirs and decay between products.
2-40

2.1.7 Provide Any Other Types of Data to Assess the Reliability of the Overall 

Exposure Model or Specific Model Elements 

Jensen Zhang: 

I am not aware of additional field data for the assessment. 

Michael Jayjock: 

Please see the discussion in 1.1 above in which an additional critical emitter variable – 

Csat is explicated using the basic emission rate algorithm: Eqn 3-5. Data on this variable 

could be directly measured in a straightforward manner. This could occur by first 

constructing a box of the emitting material with an internal volume sufficient to provide a 

good limit of analytical detection. For example, if one wished to have analytical detection 

limit (LOD) of 2 ppb they would consult with the analytical chemist as to which sample 

volume would be able to detect that value. Say, for example that a 5 liter air sample 

would be required to render an LOD of 2 ppb formaldehyde. One would simply construct 

a box with an internal volume of 5 liters. Moderate care should be taken to seal the edges 

against leakage. The box should be allowed to equilibrate such that the internal 

concentration is no longer increasing. It is suggested that this would occur within a week 

but could be confirm experimentally. After this period, the exact internal air volume of 

the box should be sampled quickly (i.e., within a maximum time frame of minutes – for 

example 0.5 lpm x 10 minutes = 5 liters). The measured concentration represents 69% of 

the amount of formaldehyde in the box if good mixing occurred during relatively rapid 

sampling. (Note, having a small fan in the box will hasten equilibrium and assure good 

mixing during sampling.) Thus, the measured Csat would be equal to the measured 

concentration/0.69. As mentioned above having Csat should substantially increase the 

confidence in the validity of m. 

Panos Georgopoulos: 

There are various studies and related data sets, both from the US and abroad, that have 

appeared in recent years and could - potentially - be used for evaluation of specific 

FIAM-pwp elements. The Addendum to this review contains a selection of literature 

references pertaining to such studies and data sets. 
2-41

Kenneth Unice: 

Average Daily Concentration

As mentioned previously, I strongly believe a consensus framework must be in place to 

assess product specific long term average exposure. I believe the current lumped, or 

whole-residence based, approach will create confusion and greatly complicate risk 

management decisions if the end point of concern is based on chronic exposure. The 

emphasis should be on developing a consensus approach to quantifying the reservoir of 

free-formaldehyde and formaldehyde precursors in a specific product. Currently the data 

available to do this is somewhat limited, but it would be useful to have a theoretical 

framework in place. 

2.1.8 General Comments on Algorithms and Exposure Assumptions 

W. Gene Tucker: 

The general approach taken by this model, as I understand it, is to: 

1. Specify basic characteristics of a house such as volume, number of zones (1 or 2), 

and air exchange rates between indoors and outdoors and between zones. 

2. Put formaldehyde-containing sources into each zone, selecting types from a dropdown list or one’s own type, and then entering amounts (areas) of each type, and 

emission rate values based on a “slope and intercept” emission model. The slope 

value accounts for the influence of vapor-phase HCHO on the emission rate and 

the intercept value is the emission factor at zero HCHO in the vapor phase. A 

table of slope and intercept values derived from the literature is provided. Users 

can enter their own values if they choose. 

3. Calculate a “steady state” concentration of HCHO from these inputs by mass 

balance calculations, assuming complete mixing in each zone. This concentration 

is assumed to be the peak concentration in the house, after which the HCHO 

concentration decreases at a first-order exponential rate. 

4. The exponential rate of decay of the HCHO concentration is calculated by 

assuming a half life, or the time it is estimated it will take to decrease to half its 

concentration. A default value of 3 years is suggested, but other values can be 

used. 
2-42

5. Given the projected concentrations in the house, occupant exposures can be 

estimated based on their age, amount of time in the house, and number of years in 

the house. The results of exposure calculations include an estimate of the % of 

time occupants are exposed to concentrations above a user-specified 

concentration of concern. 

Step 2 seems like a convoluted way to model emissions: The dependent variable of 

primary interest—the HCHO concentration—is inherent in the in the prediction 

algorithm; i.e., it is also used as an independent variable. While the emission rate of 

HCHO is certainly a function of concentration in the air phase (as Fick’s law clearly 

implies), this is true for all out-gassing substances. High gas-phase concentrations can 

suppress emission rates. But if you look at the effect, say in Table 2-2 of the 

documentation, you can see that the suppression effect is small at low (and therefore 

presumably relevant) concentrations of formaldehyde. Nearly all the data appear to have 

been taken under conditions where the HCHO concentration was well above 0.01 ppm, 

which value is suggested by the model as a concentration of concern. Most of it is even 

above 0.1 ppm, which is the maximum concentration of concern that anyone is likely to 

use. So the practical value of the slope in the emission rate equation is not evident unless 

one is going to model situations that are clearly unhealthy. Why not just use the intercept 

values and simplify the model? Better, in my opinion, to use a model that predicts indoor 

concentration from some quantified source emissions data (over time) based more simply 

on loadings, air exchange rates and—where relevant—other variables such as 

temperature, relative humidity, etc. 

That said, the analysis provided in section 5.3 of the documentation suggests that 

whatever the convolutions involved, the model gives respectable predictions. My reading 

of the tables in that section, which summarize modeling results compared to measured 

values in the EPA pilot study house, is that the model ranged from about 24% low to 

about 65% high. Predictions within that range are quite good, given the uncertainties in 

input data and unavoidable modeling assumptions. 
2-43

Regarding the selection of a decay constant (or half-time if you prefer) for predicting the 

rate at which the HCHO concentration will decrease, I suspect the default choice of k = 

0.23 yr-1 (or t1/2 = 3 years) might be improved by having different values for different 

time periods. For example, the k value for the period 0-3 months may be higher than the 

one for 3-12 months, which may be higher than for 12-24 months, etc. I don’t have the 

Versar 1988 or Groah 2005 compilations at hand, so I didn’t check this but it would be 

simple to do once the data were compiled and segregated into appropriate time periods. 

First-order regressions could be determined for each time period; the k values would 

show whether the decay rates were changing significantly over time. This exercise might 

give you some insight into how conservative the 3-year (nee 2.92-year) half life is. 

One significant shortcoming of this model, and many indoor models that assume 

complete mixing within compartments, is that it doesn’t deal with what I refer to as 

“intimate” sources. These are sources that can lead to much higher exposures, especially 

for very young children or elderly people, than would be predicted by such models as 

FIAM. Examples are toys, cribs, bedding materials, clothing, and flooring materials for 

children and bedding and clothing for elderly people. To some extent as well, people 

working for long periods at workstations and around computers and peripherals can be 

more highly exposed than FIAM and most other models predict. 

I think the most straightforward approach to such sources is to assume a smaller 

compartment or zone around such sources for the purpose of predicting concentrations. 

Some years ago I made a stab at that in a paper for an indoor air conference1. In that 

paper I suggested a “volume of concern” of 10 m3 for dispersion of emissions from 

furniture and machines at workstations. The volume one might use for babies on bedding 

or flooring materials would presumably be much smaller; the resulting calculations 

would predict exposures that might be orders of magnitude higher than predicted by 

FIAM. 

 

1 Tucker, W. G. 1990. Building with low-emitting materials and products: Where do we stand? In Proc. Indoor Air 

’90, Vol. 3, pp. 251-256. Ottawa: Indoor Air Technologies. 
2-44

2.2 Part 2 - User Interface

2.2.1 Provide Comments on the Ease of Use of the FIAM-PWP Model 

Jensen Zhang: 

The interface design is easy to use in general. 

1) The online version is very, very slow in response to every click (submission, help, 

source selection, etc....) 

2) Berge and Myer --- temperature effects. It is better to use one only or combine it 

to provide a default number since users do not know which one to use. 

Alternatively, tell user how to select. 

3) Source selection: How is the area defined for the cabinet? The surface area or the 

foot print? 

4) It would be more convenient for users to select floor types and then provide 

model coefficients for all the materials involved instead of asking users to 

“construct the floor”. 

5) The screen on “Exposures” is too wide for my notebook (Lenovo/Thinkpad 

X61s). Also, the “Adult”, “Child” should be more visible. 

6) The help sign “?” is too visible. Suggest that make it smaller and place it after the 

data entry. 

7) The “results” file may be made more informative to conclude if the house would 

meet HUD or other standards. 

8) It would be useful to provide some sort of guide for users to step through the 

modeling process (such as step 1, 2, 3, ...., much like when completing a Tax 

return with TaxAct) 

Michael Jayjock: 

As mentioned above FIAM – PWP is a complicated tool that requires a considerable 

amount of input and performs a significant amount of calculation. Considering all 

that it does I found the user interface is remarkably clean and straightforward. The 

“tab” format is logical. Also understandable and obvious is the flow of operations 

from the first to the last tab. I found the “pull down” window input format to be 
2-45

easy and very intuitive. In short, I have no reasonable suggestions to make it more 

user friendly. 

Panos Georgopoulos: 

FIAM-pwp is a web-base program that is easy to use at the “client side” through a 

browser (MS Internet Explorer). Microsoft technology appears to be used throughout the 

implementation. Local use of the program in its current form would still require setting it 

up so it is accessed by the browser – this requires adjusting local computer settings 

(Internet Information Server, .NET/Framework/V2.0, etc.) in ways that may be 

challenging for some systems – and users. Nevertheless, the web-based version is 

sufficiently “user-friendly” and the data entry screens are clear. However, it should be 

pointed out that (as experience, especially with students, shows) a “well-polished” and 

“user-friendly” interface often raises (probably subconsciously) expectations regarding 

the precision and accuracy of the model calculated estimates. This is particularly true for 

a model with a deterministic formulation that performs point calculations like FIAMpwp. Therefore, maybe some “warnings” regarding the level of uncertainties in the 

calculations could be incorporated, as reminders, in the data-entry screens. 

Kenneth Unice: 

I was able to use the model successfully. I choose to use the local version of the software 

which performed reasonably. I found the interface to be more cumbersome than similar 

models like MCCEM, IAWX, EFAST or WPEM, but this is mostly attributable to the use 

of a web-based platform and not a fault of the developer. Specific comments are provided 

below: 

Air change rate

Although the help explained why this was grayed out, I initially tried to edit this field 

because it was a text box prior to reading the help function. Replacing this field with 

plain text would make clear that this value cannot be edited. 
2-46

Modifying sources

When a source is modified, the user should be required to rename the source and a 

separate library of user entered sources should be maintained. Currently, it is impossible 

to know whether someone overrode the default values or the values presented are the 

default values. I would prefer that the individual panel results not be a permanent part of 

the database, with several open slots for user defined emission rates. For example, for 

particleboard underlayment, I would recommend: AVG-PBU, MAX HUD, User Defined 

1, User Defined 2....Etc. Here, the user would not be permitted to edit the AVG and 

HUD parameters. If desired, the AVG-PBU could be supplemented with an upper 

confidence limit intercept. Note also that the codes in the model do not match Table 2-2 

in all instances. For example, Table 2-2 GP-6N is labeled HOW-6N(U) in the model. 

Printing

When a screen is printed in standard portrait view, the edge is cut off. It would extremely 

helpful to have a ‘Print All’ button that would generate a single page for printing with all 

the inputs and outputs suitable for printing in portrait view.

MS EXCEL

I successfully generated output using this function. Please consider writing a routine to 

allow the same information to be printed directly from the web-browser as noted above. 

Tab Key

Each data entry box has a tab order. Generally when the tab key is pressed, the next text 

box with focus is logical, but in some instances the next box is out of order. For example: 

House type [Tab] Number of Zones [Tab] House Volume

2.2.2 Comment on the Adequacy of the Model Help Screens 

Michael Jayjock: 

In general, I found the content of the help screen to be very good and, as expected, 

reflective of the documentation. As mentioned previously, I found the overall 

documentation to be very good. I do have a formatting issue, however. I have a relatively 
2-47

large 23” monitor on my computer, when I open a help screen (Web Page dialog) it 

comes up in a relatively small font and the width of the paragraph appears to be less than 

50% of the width of the window. My suggestion is to increase the length of the lines in 

the help window to fill up the space and also increase the font size to use up this 

additional utilized area. This will significantly add to the “readability” of the generally 

excellent help information. 

I was easily able to get the “larger fonts” options running by checking the box in the first 

window; however, I could not get the “audio help” to work. I am assuming that it is not 

connected at this point. 

Panos Georgopoulos: 

The model-help screens appear generally adequate; they could be enhanced by including 

some statements regarding the level of precision expected for some of the entries (that 

should be consistent with the high uncertainty in the estimates; in other words, it should, 

e.g., be made clear to the user that higher precision of the inputs does not necessarily 

produce improved model estimates). 

Kenneth Unice: 

The model help screens are intuitive and adequate. The audio prompts generally worked 

well, although some were missing failed to load (e.g. first prompt on house screen). 

2.2.3 General Comments on the User Interface 

W. Gene Tucker: 

I had little trouble with the user interface. Minor comments follow. 

1. More careful attention to significant figures is needed. The suggestion that inputs 

should or can be specified with more than 3 significant figures (and results with 

more than 2 SF’s) is outrageously silly. See House Screen for example. 

2. On the Sinks Screen, it seems counter-intuitive that the B value is positive rather 

than negative... 
2-48

2.3 Part 3 - Documentation

2.3.1 Comment on Whether the References Have Been Accurately Identified 

Michael Jayjock: 

The fourth reference (the CARB Final Regulation Order...) should be identified as 

available online at: http://www.arb.ca.gov/regact/2007/compwood07/fro-final.pdf (last 

accessed October 9, 2009). Similarly, the 8th reference (D. Hare...) can be found and 

should be referenced at: 

http://www.ecobind.com/research/Evaluating_the_Contribution.pdf (last accessed October 

9, 2009). Indeed, any and all the reference particularly from the EPA, GEOMET, Versar 

or industry groups should be identified by their web links, if available, and if not available 

on the web, should be considered for posting online with a link. 

The two additional references indicated above (Murray and Burmaster on residential 

ventilation rate database and Jayjock on “Backpressure” modeling) should be considered 

for inclusion. 

Panos Georgopoulos: 

The Addendum to this review presents a selection of references on indoor air 

formaldehyde emissions, concentration levels, and relevant physicochemical processes; 

the selection includes both experimental (field and laboratory studies) and modeling 

studies. This reviewer would recommend consideration of at least some of these 

references in future revisions of FIAM-pwp and its documentation. 

Kenneth Unice: 

The references are accurately identified, however I recommend replacing the two Groah 

citations. Please see below for recommendations for additional citations 

Picture of kitchen cabinets

The credit for the picture of the kitchen cabinets should be provided. 
2-49

Theory

For more information regarding formaldehyde emissions from pressed wood products, 

model users could be referred to U.S EPA (1996) ORD report – Sources and Factors 

Affecting Indoor Emissions from Engineered Wood Products. 

Background concentrations and 0.01 ppm threshold

A basis should be provided for the recommend range of 1 to 10 ppb on page 2-4. 

Similarly, it should be explained why the concentration 10 ppb is ‘hard coded’ into the 

model in the percent of time > 0.01 ppm output. 

Representative measured indoor air concentrations

It may be helpful to provide citations to studies that have summarized recent measured 

formaldehyde indoor air concentrations in new and existing structures. Examples include 

Hodgson and Levin 2003 and Hodgson et al. 2000. One of the concerns that these 

publications raise is that the Matthews parameter database including in the model is 

primarily for historical products, however, more recent indoor air data shows that 

emissions have declined. It is unclear the degree to which the decrease is due to changes 

in the product mix versus reduced emission rates. Therefore, users of the model should be 

encouraged to obtain emissions data for modern products if the results are appreciably 

outside the bounds expected. Central tendency indoor air concentrations reported in a 

survey of literature by Hodgson and Levin 2003 were 17 and 32 ppb for existing and new 

structures respectively. 

Decay in emission rate (Groah 1998 and 2005)

Groah’s white papers and reports have been invaluable to me in my past consulting work 

on formaldehyde. However, I recommend that these references (essentially a white paper 

and report prepared on behalf of HPVA) be replaced with peer-reviewed publications, 

conference proceedings, or governmental citations. Examples of publications addressing 

the long term decay of formaldehyde emissions from consumer products include: 

• Mølhave et al. 1995 

• Brown 1999 

• Zinn et al. 1990 (note this study was relied upon by CARB) 
2-50

• Myer and Hermanns 1985 

• CARB 2007 – see Appendix B 

One key point to be derived from these studies is that a single exponential equation does 

not describe the decay in emissions adequately. In turn, a single exponential equation is 

not likely to accurately predict the LADD or LADC attributable to a specific product. 

Backpressure effect

I recommend citing Jayjock 1994 in reference to the backpressure effect first introduced 

on page 2-16 of the documentation. This paper provides a good review of this concept for 

users not familiar with the concept. 

2.3.2 Provide Comments on the Model Documentation (Does It Present the Model 

Construct, Selected Model Inputs, and Model Results in a Clear, Complete 

and Useful Manner) 

Jensen Zhang: 

1) The “steady-state assumption” has been mentioned too many times while 

describing the user-interfaces. This is not necessary and it distracts users/readers 

from focusing the input parameters. Also, the mode is not truely a steady-state 

one since the emission source decays over time. It is a “quasi-steady state” model 

in which the concentration at a given calculation point was treated as “constant” 

for the purpose of simplifying the calculation without losing too much accuracy. 

An additional reference may be cited to justify such treatment (Zhang et al. 1997). 

 Zhang, J.S.; Wang, J.; Shaw, C.Y. 1997. Theoretical Examination of a 

Simplified Procedure for Data Analysis in Small Chamber Testing of Material 

Emissions. 8 pp.(Internal Report, Institute for Research in Construction, National 

Research Council Canada, 733)(IRC-IR-733) 

2) The “flow balance” should be changed to “mass flow rate balance” to be accurate. 

3) I am concerned that most data provided on formaldehyde emissions are from early 

studies. Much of the manufacturing processes and raw materials have been 

changed. Especially due to the use of non urea-formaldehyde resins, the 

formaldehyde emissions from pressed wood products have been reduced 

significantly. 
2-51

4) Validity of the exponential decay model is questionable. Recent data have shown 

that the power-law model would be more suitable, and secondary emissions as a 

result of hydrolysis are also possible. Limitations of the exponential decay model 

should be pointed out. 

5) Table 2.4: Why the “medium” and “low” emitting ensembles have the same slope 

and intercept for “Shelves”? 

6) Regarding Equation 3-5: 

CH2OER′ = -m * [CH2O]V+ b (Eqn. 3-5) 

 where: 

 m = the mass transfer coefficient (m/hr) 

 [CH2O]V = the CH2O concentration in the vapor phase (mg/m3) 

 b = a constant; the emission rate at zero CH2O concentration in the air (mg/m2- 

 hr). 

 6.1) The Fick’s law is for diffusion, while here the process is governed by 

convective mass transfer across the boundary layer. Air velocity and turbulence 

over the surface hence affect the mass transfer coefficient, instead of simply the 

diffusion coefficient in Fick’s law. 

 6.2) The definition of vapor phase concentration and bulk phase concentration 

is unclear. In Eqn. 3-5, [CH2O]V should simply be the concentration in the bulk 

air (outside the air boundary layer over the surface). I see no need to define a 

vapor phase concentration since by default, we are always dealing with the vapor 

concentration in the air or in the material in this model. This naturally then lead 

to the assumption that the concentration in the bulk air outside the boundary layer 

is the same as the steady-state concentration in the compartment. 

7) Page 4-2: “Product loading rate”---do you mean “loading ratio”? Same in Table 

4-1.

Michael Jayjock: 

As mentioned above, I see the clarity and consistency of explanation as a real strength of 

this documentation. At the risk of repeating myself – this is a complicated modeling 

construct. I believe that the author of the documentation is particularly gifted in providing 

a plan and useful explanation of all the various facets of the work. It definitely requires 
2-52

considerable study on the part of the reader to understand work but the author has 

acquitted his or herself very well in this process. 

A personal preference for improvement that occurred to me while reading the document 

involves the ordering of Chapters 2 and 3. As I was beginning to read the information in 

Chapter 2 (USER INTERFACE) I found myself compelled to go and read Chapter 3 

(MODEL CALCULATIONS AND ASSUMPTIONS). For me it would be more logical 

to change the order of these chapters. 

In another relatively minor area I found the use of “D” on page 3-4 to be unnecessarily 

complex. My advice is to simply incorporate the “D” algorithm in the Eqn 3-6 and 3.8.

Panos Georgopoulos: 

The documentation for FIAM-pwp is quite thorough in presenting the model formulation 

and implementation as well as the data sources that were used to develop parameter 

estimates for this implementation. One could note that there are some minor “awkward” 

points that could be fixed with careful editing (e.g. one reads on page 2-7 that “the flows 

from/to outside are exactly half the house volume” forgetting the temporal element in the 

concept of flow, while degrees Kelvin are denoted as oK rather than K, etc.). However, 

the main issue with the documentation is the justification of the formulation of certain 

elements of the model per se (e.g. the assumption of constant rather than decreasing 

emission rates, etc.) rather than of potential alternatives. 

Kenneth Unice: 

Concentration as a function of time

Consider explaining in the model documentation why the concentration time points of 3, 

6 and 12 months were selected for output. 

Estimation of sinks

As described in more detail earlier, the treatment of sinks is not transparent and confusing 

because the rate of storage changes with time but the model used is a steady state model. 

Groah (2006) also tried to address the effect of wallboard sinks for the pilot study home. 

This manuscript noted that much of the small chamber data was erratic, but that some 
2-53

data was usable. However, both in the model documentation and in the Groah (2006) 

publication, the approach used appears to be more an attempt to modify the model results 

to reflect the measured concentration than a rigorous handling of sinks. The approach to 

wallboard sinks used in the current EPA model should be consistent with the wallboard 

sink equations and data presented in Matthews et al. (1987). The wallboard in this study 

was unpainted, but latex paint was not expected to appreciably affect formaldehyde 

transport. 

Linear Estimation of Matthews Model Parameters

Some stakeholders that may choose to use the new EPA formaldehyde model may not be 

familiar with the linear regression protocol required to estimate the parameters for either 

the Matthews and Hoetjer formaldehyde mass transfer models. It is recommended that 

documentation be revised to show an example linear regression for the recent data 

Koontz et al. (1996). 

Hoetjer-equation

As described previously, the documentation should explain the relationship between the 

Matthews and Hoetjer equation. The Hoetjer equation or equivalent mass transfer 

equation is frequently cited in the literature and some stakeholders may not be familiar 

with the Matthews equation. Examples of papers relying on the standard mass transfer 

relationship (i.e. Ceq and K) include: 

• Berge et al. 1980 

• Myers and Nagaoka 1981(presents the use of linear regression to determine Ceq

and K) 

• Myers 1983 (presents the use of linear regression to determine Ceq and K) 

• Salthammer et al. 1995 

Langmuir Isotherm

The documentation should note that it is assumed that the number of occupied adsorption 

sites are much less than the available sites, reducing the isotherm equation to a simplified 

linear form (see for example, Tichenor et al. p. 24). At equilibrium, when dM/dt = 0, 

there is no net adsorption and Cindoor = kd/ka*M. 
2-54

Analysis of data

Consider presenting the analysis of PFT measurements and raw data in an appendix for 

Conventional 2 (p. 2-7). Is this data similar to data available in MCCEM? What is the 

basis of 0.5 ACH for manufactured home? 

Consider including in an appendix the analysis of the EPA Pilot Study data used to 

determine the mass transfer coefficient and intercept (p. 5-3). For example, it is not clear 

which loading (i.e. 1,2,3) is used to calculate the parameters without reproducing the 

calculation or whether the result is different based on HBF or Matthews regression 

equation. 

2.3.3 Provide Comments on Whether the Documentation for the FIAM - PWP 

Make Clear the Sources and Anticipated Magnitudes of Variability and 

Uncertainty in Model Results 

Jensen Zhang: 

There are good description of the possible sources variability in the model prediction. 

However, it would be helpful if a more quantitative analysis is conducted on the 

uncertainties of the model coefficients and how they would propagate to the predicted 

results. And thus the predicted results will be a range (e.g., mean +/-standard deviation) 

instead of a single concentration level. 

Michael Jayjock: 

I believe that the author does a particularly good job of indicating the sources of relative 

uncertainty within the model itself and within the basic data-sets and relationships that 

feed the tool; however, I would have liked to see a level of quantitative uncertainty 

analysis such as described above and herein. Specifically, the author should consider 

presenting a range of outputs caused by a reasonably anticipated range of input variables 

within all the particular categories (e.g., standard temperature (23C) and humidity (50% 

RH) algorithm parameter ranges, temperature and humidity ranges). That is, I would like 

to see a section (perhaps an appendix) in which the author approaches the estimation of 

indoor air formaldehyde levels through the eyes of a user. This would involve picking 
2-55

reasonable parameters for specific source strengths, temperature and humidity that might 

realistically maximize the estimate and then doing the same exercise with parameters that 

would minimize the predictions. This could provide the reader with a quantitative 

measure of the anticipated range of variability for the tool. 

Panos Georgopoulos: 

Though extensive information on the data that were used for the model is included, in this 

reviewer’s opinion, the types and the extents of variability and uncertainty associated 

with various model elements are not fully revealed in the documentation. An ideal 

solution would be a probabilistic “re-formulation” of the model, with explicit discussion 

in the documentation of the appropriate distributions of values for the various inputs. As 

an alternative, even with a deterministic formulation of the model, a table listing 

explicitly various sources of uncertainty and variability associated with specific processes 

and parameters of the model, along with a factor or range specifying the approximate 

magnitude of each uncertainty/variability, would be extremely useful. 

Kenneth Unice: 

Mass transfer coefficient

Consider incorporating a mass transfer coefficient sensitivity analysis into the model or 

model documentation. The uncertainty and sensitivity analysis presented in Matthews et 

al. 1985 could be discussed. 

Airflow

Consider providing a database of homes similar to MCCEM database to provide a larger 

range for interzonal airflows. 

Sensitivity Analysis

Consider including a simple Monte Carlo analysis as an appendix to provide some 

guidance on whether refinement of a particular input parameter is likely to change the 

conclusion. This could be done using the spreadsheet model already prepared. The 

uncertainty and sensitivity analysis presented in Matthews et al. 1985 could be discussed.
2-56

2.3.4 Comment on Whether the Model Algorithms are Consistent with the 

Descriptions in the Model Documentation 

Jensen Zhang: 

I did not check the code. 

Michael Jayjock: 

Indeed, from what I can determine from studying this work the model algorithms are for 

the most part consistent with their descriptions in the model documentation. I did detect 

either an error in sign or the omission of an explanation in the correlation coefficients 

presented in Table 2-2. All of the coefficients have a negative sign and we are told in 

footnote g that they are the “Correlation coefficient between the calculated emission rate 

and the measured chamber concentration”. Clearly, emission rate and concentration 

should be positively correlated. I would also prefer to see this “fit relationship” described 

as the correlation coefficient squared (R2) because this value represents the percentage of 

the variance in the model described by the algorithm. For example, a correlation 

coefficient R = 0.72 equals R2 = 0.52 indicating that 52% of the variance in the data is

attributable to the fit of the linear relationship and 48% is in random error or noise. 

Panos Georgopoulos: 

The model algorithms appear consistent with model documentation; issues with the 

algorithms were addressed in the answers to questions of Part 1. 

Kenneth Unice: 

Verification of Model Equations

The model equations provided in the documentation were reviewed. To further verify the 

model calculations were implemented as intended using an alternate approach, an 

example loading was run to steady state using IAQX Source Type 31. After the steady 

state concentration was determined, the other parameters were calculated by hand. The 

source used was the EPA kitchen cabinets, which corresponds to Cv of 0.1633 mg/m3 and 

Km of 0.49 m/hour in the mass transfer equation of IAQX. The results were evaluated 

with and without a background concentration of 0.010 mg/m3. IAQX Model Source Type 
2-57

14 was used to add the background concentration. The model results were successfully 

reproduced using this independent approach (Table 4). 

Table 4: Verification of model calculations for test case 

Matthews m

The slope in the Matthews equation is not consistently defined. For example on p 2-11, 

ER = mC+b, but on page 3-4, ER=-mC+b. 

ACD and LADC

One area that is particularly confusing is the model output of average daily concentration 

(ADC) and lifetime average daily concentration (LADC). From the model documentation 

it is not clear whether the background concentration is included in the ADC and LADC. 

For products with very low equilibrium concentrations in environments with above 

average background concentrations, the presence of the background sources could be 

important. Therefore, there could be cases where the user would like to include a 

background concentration in the model, but exclude the contribution of background from 

the dose. Consider providing a checkbox option to include or exclude the background 

concentration from ADC and LADC (and dose).
2-58

2.3.5 General Comments on Documentation 

W. Gene Tucker: 

I found the documentation to be generally clear and quite useful. Users should have little 

trouble following it. Minor comments follow. 

1. Page 2-4, 4th paragraph: you should not describe the slope as “...in the form of a 

first-order sink representation...”. The slope represents a linear function; firstorder implies exponential growth or decay, neither of which would describe 

absorption characteristics of sinks. A logarithmic equation might make more 

physical sense, but that would introduce further calculational complications. 

2. Page 3-2, 2nd paragraph: the phrase “...flows of formaldehyde mass into and out of 

a fixed volume must be equal...” is not correct. In fact, equation 3.1 contradicts 

that. Thorough treatment of mass balances should consider generation, 

consumption, and accumulation inside the volume as well as flow into and out of 

the volume. 

3. Page 3-4, first line: shouldn’t “independent” be “dependent”? 

4. While the term “half-life” has a certain value because of its understandability, the 

normal way to determine it is from the decay constant, which these days is a 

simple matter with spreadsheets like Excel, where k can be determined easily 

from the “trendline” equation for a first-order exponential decay of the 

concentration versus time data. For some reason, the documentation of the model 

suggests that the decay equation is derived from the half-life. [By the way: 

Reporting the average half-time of HCHO decay in homes as 2.92 years is a silly 

example of significant figures. It would actually be more accurate to report that 

value as about 3 years.] 

5. One area that I feel could be significantly improved is the mathematical 

introduction to the model. I have sketched out an alternative approach that I 

believe would be helpful to the general user, and have attached it. I don’t 

necessarily suggest this as a modification to FIAM, but as a general way to 

introduce mass balance concepts. Perhaps it is more relevant to other models if 

they should be developed for other indoor air quality situations and users who are 

less attuned to textbook-type math. 
2-59

2.4 Additional Comments and Materials Submitted

Panos Georgopoulos: 

Overall, it should be stated that the model under review is the result of a serious and 

commendable effort and represents an important step towards fulfilling a critical need to 

develop a scientifically valid framework for the characterization of human exposures to 

formaldehyde. Given the enormous complexity of this problem, it should be recognized 

that additional steps will be needed. In this reviewer’s opinion, development of statistical 

distributions of emission rates for different pressed wood products, that explicitly 

incorporate and quantify the uncertainty and variability in available data, is a much 

needed next step.

ADDENDUM: 

Selected References on Indoor Formaldehyde Emissions and Concentrations 

Ataka, Y., S. Kato, et al. (2004). "Study of effect of adsorptive building material on 

formaldehyde concentrations: development of measuring methods and modeling of 

adsorption phenomena." Indoor Air 14: 51-64. 

 In this paper, a method is developed to assess the performance of adsorptive 

building materials that are used for reducing indoor pollutant concentrations. 

Mass transfer has a great influence on the materials' performance. To control the 

mass transfer rate precisely in the performance test, the authors have developed 

the Boundary-Layer-Type Small Test Chamber in which airflow along the test 

materials can be controlled precisely. A new index of adsorption performance, the 

equivalent ventilation rate (Q(ads)), is defined that corresponds to the mass 

transfer coefficient when the surface pollutant concentration is zero. Modeling 

and experimental verification of adsorption were done, demonstrating the 

pollutant concentration decrease caused by adsorptive building materials. The 

pollutant reduction phenomena were modeled, including pollutant degradation by 

chemical reaction and adsorption in building materials. Adsorption tests of 

gypsum board containing a substance that decomposes HCHO within the board 
2-60

are reported. The adsorption rate of the gypsum board predicted-by numerical 

analysis (CFD, Computational Fluid Dynamics) corresponds well with 

experimental results. 

Bennett, J. S., C. E. Feigley, et al. (2003). "Comparison of Emission Models With 

Computational Fluid Dynamic Simulation and a Proposed Improved Model." AIHA 

Journal 64: 739–754. 

 Understanding source behavior is important in controlling exposure to airborne 

contaminants. Industrial hygienists are often asked to infer emission information 

from room concentration data. This is not easily done, but models that make 

simplifying assumptions regarding contaminant transport are frequently used. The 

errors resulting from these assumptions are not yet well understood. This study 

compares emission estimates from the single-zone completely mixed (CM-1), 

two-zone completely mixed (CM-2), and uniform diffusivity (UD) models with 

the emissions set as boundary conditions in computational fluid dynamic (CFD) 

simulations of a workplace. The room airflow and concentration fields were 

computed using Fluent 4. These numerical experiments were factorial 

combinations of three source locations, five receptor locations, three dilution 

airflow rates, and two generation rate profiles, constant and timevarying. The aim 

was to compute plausible concentration fields, not to simulate exactly the 

processes in a real workroom. Thus, error is defined here as the difference 

between model and CFD predictions. For the steady-state case the UD model had 

the lowest error. When the source near-field contained the breathing zone 

receptor, the CM-2 model was applied. Then, in decreasing agreement with CFD 

were UD, CM-2, and CM-1. Averaging over all source and receptor locations 

(CM-2 applied for only one), in decreasing order of agreement with CFD were 

UD, CM-1, and CM-2. Source and receptor location had large effects on emission 

estimates using the CM-1 model and some effect using the UD model. A locationspecific mixing factor (location factor) derived from steady-state concentration 

gradients was used to build a more accurate time-dependent emission model, CML. Total mass emitted from a timevarying source was modeled most accurately by 

CM-L, followed by CM-1 and CM-2. 
2-61

Bi, X., G. Sheng, et al. (2005). "Gas- and particulate-phase specific tracer and toxic 

organic compounds in environmental tobacco smoke." Chemosphere 61(10): 1512-22. 

 Cigarette smoke constituents are worthy of concern and characterized as 

carcinogens. Different experiment conditions may affect the environmental 

tobacco smoke (ETS) constituents. A study was undertaken in a 75.5-m3 spare 

office to evaluate ETS constituents in a real environment. Thirty-four volatile 

organic compounds (VOCs) including three ETS tracers: nicotine, 2,5-

dimethylfuran and 3-ethenylpyridine (3-EP), 19 carbonyl compounds, 54 semivolatile compounds (24 polycyclic aromatic hydrocarbons (PAHs) and 30 

alkanes) as well as CO and total particulate matter (TPM) from 15 leading 

commercial brands were determined. ETS constituents did not increase with 

increasing cigarette tar. ETS tracers nicotine and 3-EP were affected greatly due 

to more sorption and surface reactions in real world compared to other studies 

conducted in chamber, which resulted in 2-5 times lower. Benzene, toluene, 

ethylbenzene, xylenes, acrolein, 2-butanone and the high molecular weight 

compounds exhibited little affect. Pearson correlation analyses show that gasphase and particulate-phase ETS tracers did not show significant correlation, but 

within each homologue many of compounds correlated significantly. Indole and 

cholesta-3,5-diene were also detected in ETS. These results may be useful in 

efforts to better understand the health effect of ETS exposure and source 

apportionment. 

Brown, S. K. (1999). "Chamber assessment of formaldehyde and VOC emissions from 

wood-based panels." Indoor Air-International Journal of Indoor Air Quality and Climate

9(3): 209-215. 

 Volatile organic emissions from particleboard, medium density fibreboard (MDF) 

and office furniture have been measured in dynamic environmental chambers, 

both small and room-sized. Characterisation of product emission properties in 

small chambers was possible when inter- and intra-sheet variations were 

considered. Formaldehyde emission factors for all products were approximately 

double European low-emission specifications and did not decay to the latter for 
2-62

several months. Long term emission behaviour could not be predicted from shortterm measurements. Volatile organic compounds (VOC) emissions were low for 

the MDF product, higher for particleboard, and highest for laminated office 

furniture. The compounds emitted differed from those reported in other countries. 

VOC emissions from the sheet products decreased more quickly than 

formaldehyde, reaching low levels within two weeks, except for MDF which was 

found to become a low-level source of hexanal after several months. 

Brown, S. K., K. J. Mahoney, et al. (2004). "Room chamber assessment of the pollutant 

emission properties of (nominally) low-emission unflued gas heaters." Indoor Air 14 

(Suppl 8): 84-91. 

 Pollutant emissions from unflued gas heaters were assessed in CSIRO’s Room 

Dynamic Environmental Chamber. This paper describes the chamber assessment 

procedure and presents findings for major commercial heaters that are nominally 

‘‘low-emission’’. The chamber was operated at controlled conditions of 

temperature, humidity, ventilation and air mixing, representative of those 

encountered in typical indoor environments. A fixed rate of heat removal from the 

chamber air ensured that the heaters operated at constant heating rates, typically 

~6 MJ/h which simulated operation of a heater after warm-up in an insulated 

dwelling in south-east Australia. The pollutants assessed were nitrogen dioxide, 

carbon monoxide, formaldehyde, VOCs and respirable suspended particulates. 

One type of heater was lower emitting for nitrogen dioxide, but emitted greater 

amounts of carbon monoxide and formaldehyde (the latter becoming significant to 

indoor air quality). When operated with low line pressure or slight misalignment 

of the gas burner, this heater became a hazardous source of these pollutants. 

Emissions from the heaters changed little after continuous operation for up to 2 

months. 

Budaiwi, I. M. and M. S. Al-Homoud (2001). "Effect of ventilation strategies on air 

contaminant concentrations and energy consumption in buildings." International Journal 

of Energy Research 25(12): 1073-1089. 

 
2-63

Considering the diversity of indoor contaminant characteristics and generation 

patterns, finding an appropriate ventilation strategy that can secure acceptable 

indoor air quality with minimum energy consumption is a challenging task for 

HVAC system designers and operators. This study theoretically models and 

investigates the impact of various ventilation strategies on contaminant 

concentration behaviour and corresponding ventilation cooling energy 

requirements for a single-zone enclosure. Two types of contaminants are 

considered; carbon dioxide as an occupancy dependent and formaldehyde, which 

is independent of occupancy. An airflow model is used to predict space pressure 

and air leakage rates across the enclosure envelope, and an air quality model is 

used to predict time-varying contaminant concentrations. In addition, a building 

energy simulation model is utilized to predict the corresponding ventilation 

cooling energy requirements under hot climatic conditions. Results from this 

study show that acceptable contaminant concentrations during occupied periods 

can be achieved by different ventilation strategies but at substantially different 

ventilation energy requirements. More than 50 per cent reduction in ventilation 

energy requirements can be obtained while maintaining acceptable IAQ if proper 

ventilation strategy is employed. Copyright (C) 2001 John Wiley & Sons, Ltd. 

Buyuksari, U., N. Ayrilmis, et al. (2010). "Evaluation of the physical, mechanical 

properties and formaldehyde emission of particleboard manufactured from waste stone 

pine (Pinus pinea L.) cones " Bioresource Technology 101(1): 255-259 

 The objective of this study was to investigate some physical/mechanical 

properties and formaldehyde emission of particleboard containing particles of 

waste stone pine cone at various usage ratios using urea–formaldehyde resin. 

Some physical (thickness swelling, water absorption), mechanical (modulus of 

elasticity, modulus of rupture, internal bond strength) properties and 

formaldehyde emission of particleboards were evaluated. The addition of cone 

particle improved water resistance of the panels and greatly reduced their 

formaldehyde emissions. However, flexural properties and internal bond strength 

decreased with increasing cone particle content in the panel. The cone of the stone 

pine can be considered as an alternative to wood material in the manufacture of 
2-64

particleboard used in indoor environment due to lower thickness swelling, water 

absorption and formaldehyde emission. 

Carslaw, N. (2007). "A new detailed chemical model for indoor air pollution." 

Atmospheric Environment 41(6): 1164-1179. 

 A detailed chemical box model has been constructed based on a comprehensive 

chemical mechanism (the Master Chemical Mechanism) to investigate indoor air 

chemistry in a typical urban residence in the UK. Unlike previous modelling 

studies of indoor air chemistry, the mechanism adopted contains no 

simplifications such as lumping or the use of surrogate species, allowing more 

insight into indoor air chemistry than previously possible. The chemical 

mechanism, which has been modified to include the degradation reactions of key 

indoor air pollutants, contains around 15,400 reactions and 4700 species. The 

results show a predicted indoor OH radical concentration up to 4.0 x 10(5) 

molecule cm(-3), only a factor of 10-20 less than typically observed outdoors and 

sufficient for significant chemical cycling to take place. Concentrations of PANtype species and organic nitrates are found to be important indoors, reaching 

concentrations of a few ppb. Sensitivity tests highlight that the most crucial 

parameters for modelling the concentration of OH are the light-intensity levels 

and the air exchange rate. Outdoor concentrations of O-3 and NOX are also 

important in determining radical concentrations indoors. The reactions of ozone 

with alkenes and monoterpenes play a major role in producing new radicals, 

unlike outdoors where photolysis reactions are pivotal radical initiators. In terms 

of radical propagation, the reaction of HO2 with NO has the most profound 

influence on OH concentrations indoors. Cycling between OH and RO2 is 

dominated by reaction with the monoterpene species, whilst alcohols play a major 

role in converting OH to HO2. Surprisingly, the absolute reaction rates are similar 

to those observed outdoors in a suburban environment in the UK during the 

summer. The results from this study highlight the importance of tailoring a model 

for its particular location and the need for future indoor air measurements of 

radical species, nitrated species such as PANs and organic nitrates, photolysis 

rates of key species over the range of wavelengths observed indoors and 
2-65

concurrent measurements of outdoor air pollutant concentrations. (c) 2006 

Elsevier Ltd. All rights reserved. 

Carter, R. D. and J. S. Zhang (2007). "Definition of Standard Office Environments for 

Evaluating the Impact of Office Furniture Emissions on Indoor VOC Concentrations, LB07-049." ASHRAE Transactions 113, Part 2. 

 A representative “worst-case” office environment, which defines the size and 

volume of the office space, the amount and type of office furniture surface area, 

and the outdoor, clean airflow rate is necessary to estimate the impact of office 

furniture emissions on indoor VOC concentrations based on the emission rates 

measured from chamber tests. In this study, 31 randomly selected floor plans from 

North American office buildings were analyzed in detail. The floor plans were 

from projects in late 2004 and early 2005 and were provided by an industry cross 

section of seven major office furniture manufacturers. 

 The analysis included documenting the potential emitting surface area for 

each workstation and a determination of how much common office space (aisles, 

etc.) was present and shared between workstations and other adjoining spaces. 

The 90th percentile conditions for total furniture surface area within the 50th 

percentile workstation footprint sizes were identified from the more than 5000 

workstations analyzed to provide a representative “worst-case” office 

environment model (i.e., occupant exposure scenario). 

 Based on the analysis, the representative “worst-case” standard open plan 

office environment for a single workstation system is defined as 5.94 m2 (64 ft2) 

floor area by 2.74 m (9 ft) high (576 ft3 or 16.3 m3), accounting for a standard 

1.83 m × 1.83 m (6 ft × 6 ft) open plan workstation system, traffic area, and 

support space for shared copiers, files, storage, etc. The space is assumed to be 

occupied by a single occupant and has an outdoor or clean air ventilation rate of 

4.17 L/s (8.84 cfm), in accordance with ASHRAE Standard 62.1-2004. The 

representative “worst-case” standard private office environment for a single 

workstation system is defined as 23.78 m2 (256 ft2) floor area by 2.74 m (9 ft) 

high (2304 ft3 or 65.2 m3), accounting for a standard 13.38 m2 (144 ft2) private 

office workstation system, traffic area, and support space for shared copiers, files, 
2-66

storage, etc. The space is assumed to be occupied by a single occupant and has an 

outdoor or clean air ventilation rate of 9.63 L/s (20.4 cfm) in accordance with 

ASHRAE Standard 62.1-2004. A comparison to historical office environment 

models is included. 

Chang, J. C. S., Z. S. Guo, et al. (2002). "Characterization and reduction of formaldehyde 

emissions from a low-VOC latex paint." Indoor Air 12(1): 10-16. 

 The patterns of formaldehyde emission from a low volatile organic compound 

(VOC) latex paint applied to gypsum board were measured and analyzed by small 

environmental chamber tests. It was found that the formaldehyde emissions 

resulted in a sharp increase of chamber air formaldehyde concentration to a peak 

followed by transition to a long-term slow decay. A semi-empirical first-order 

decay in-series model was developed to interpret the chamber data. The model 

characterized the formaldehyde emissions from the paint in three stages: an initial 

"puff" of instant release, a fast decay, and a final stage of slow decay controlled 

by a solid-phase diffusion process that can last for more than a month. The model 

was also used to estimate the peak concentration and the amount of formaldehyde 

emitted during each stage. The formaldehyde sources were investigated by 

comparing emission patterns and modeling outcomes of different paint 

formulations. The biocide used to preserve the paint was found to be a major 

source of the formaldehyde. Chamber test results demonstrated that replacing the 

preservative with a different biocide for the particular paint tested resulted in an 

approximate reduction of 55% of formaldehyde emissions. But the reduction 

affected only the third-stage long-term emissions. 

Chen, J., B. Duffy, et al. (2001). "FTIR spectroscopy measurements and CFD simulations 

of the pollutants arising from unflued combustion in a room." Building and Environment

36(5): 597-603. 

 This paper reports on a study of indoor air quality in a simulated kitchen 

environment. Combustion products from unflued combustion from a gas cook-top 

in a ventilated room were measured using an extractive FTIR technique. Results 

were compared with those from conventional instruments and the FTIR technique 
2-67

was shown to give good agreement. Detection limits and the effect of H2O and 

CO2 in obscuring the spectrum were studied, in addition, Computational Fluid 

Dynamics (CFD) was used to explore the conditions in the room and to assist with 

experimental design. This revealed a complex flow situation that can arise when 

the plume from the cook top interacts with the extraction hood. (C) 2001 Elsevier 

Science Ltd. All rights reserved. 

Choi, D. W., K. W. Moon, et al. (2009). "Indoor Volatile Organic Compounds in Atopy 

Patients' Houses in South Korea." Indoor and Built Environment 18(2): 144-154. 

 This study was undertaken to determine the concentrations of volatile organic 

compounds (VOCs) in the indoor air of atopy patients' (atopic dermatitis 50, 

allergic asthma 36) and control houses (28 nonpatients). A goal of this study was 

also to investigate whether indoor VOCs were risk factors for the development of 

atopic sensitization. Eleven alkanes, 13 aromatics, 7 chlorinated hydrocarbons, 3 

terpenes, and 15 aldehyds were measured from 10 March to 15 June, 2006. 

Aldehyde compounds are the most abundant chemical group in all indoor air, 

followed by aromatic compounds. The geometric mean concentrations of total 

VOC (TVOC) in indoor air in atopic dermatitis and allergic asthma patients' 

houses were 317.1 and 219.2 mu g.m(-3), respectively. However, TVOC 

concentrations did not differ significantly between control and patient houses in 

indoor and outdoor air. The geometric mean concentrations of benzene, 

ethylbenzene (p < 0.05), o-xylene, m-, p-xylene, styrene, levels of 1,3,5-

trimethylbenzene and formaldehyde (p < 0.01) in the indoor air of houses of 

patients with atopic dermatitis, and levels of o-xylene and 1,3,5-trimethylbenzene 

(p < 0.01) in houses of allergic asthma patients were significantly higher than 

those in control houses. The multiple linear regression model in this study 

indicated several indoor origins of VOCs. House age and floor or wall coverings 

that had been refurbished within 1 year were correlated with higher 

concentrations of formaldehyde. Limonene and alpha-pinene concentrations were 

significantly increased by the replacement of furniture and the use of cleaning 

products. The type of heating system was significantly associated with indoor 

benzene, toluene, ethylbenzene, nonane, decane, and undecane concentrations in 
2-68

atopy patient houses. 

Clarisse, B., A. M. Laurent, et al. (2003). "Indoor aldehydes: measurement of 

contamination levels and identification of their determinants in Paris dwellings." 

Environmental Research 92(3): 245-253. 

 The recent increased prevalence of childhood asthma and atopy has brought into 

question the impact of outdoor pollutants and indoor air quality. The contributory 

role of aldehydes to this problem and the fact that they are mainly derived from 

the domestic environment make them of particular interest. This study therefore 

measures six different aldehyde levels in Paris dwellings from potentially 

different sources and identifies their indoor determinants. The study was carried 

out in the three principal rooms of 61 flats with no previous history of complaint 

for olfactory nuisance or specific symptoms, two-thirds of the flats having been 

recently refurbished. Aldehydes were sampled in these rooms using passive 

samplers, and a questionnaire on potential aldehyde sources was filled out at the 

same time. A multiple linear regression model was used to investigate indoor 

aldehyde determinants. Our study revealed that propionaldehyde and 

benzaldehyde were of minor importance compared to formaldehyde, 

acetaldehyde, pentanal, and hexanal. We found that levels of these last four 

compounds depended on the age of wall or floor coverings (renovations less than 

I year old), smoking, and ambient parameters (carbon dioxide levels, 

temperature). These results could help in the assessment of ndoor aldehyde 

emissions. (C) 2003 Elsevier Science (USA). All rights reserved. 

Daisey, J. M., K. R. R. Mahanama, et al. (1998). "Toxic volatile organic compounds in 

simulated environmental tobacco smoke: Emission factors for exposure assessment." 

Journal of Exposure Analysis and Environmental Epidemiology 8(3): 313-334. 

 Environmental tobacco smoke (ETS) is suspected to be a major source of 

exposure to many of the compounds identified as toxic air contaminants. 

However, we lack emission factors for many of the ETS air toxics for the brands 

of cigarettes which currently dominate the market and therefore cannot adequately 

estimate contributions of ETS to such exposures. This study provides up-to-date 
2-69

emission factors for Selected air toxics and other volatile organic compounds 

(VOCs) in simulated ETS and uses them in a mass balance model to evaluate the 

potential contribution of ETS to air toxics in indoor air and, therefore to indoor 

exposures to air toxics. 

 Emission factors (mu g/cigarette) were determined for 21 VOCs 

(including two aldehydes), nicotine and particulate matter in a room-sized (20-

m(3)) environmental chamber with stainless-steel walls, operated under static 

conditions, using diluted sidestream smoke (no exhaled mainstream smoke) to 

simulate ETS. Experiments were conducted for Kentucky Reference cigarette 

1R4F and for each of six commercial cigarette brands with major market shares. 

The variabilities in the ETS emission factors among brands of cigarettes were 

relatively small, ranging from 16 to 31% (expressed as the coefficient of 

variation) among the six brands. 

 The concentrations of most of the VOCs did not change over the 4-hour 

periods of the experiments. However concentrations of 3-ethenylpyridine, phenol, 

o-cresol and m,p-cresol showed consistent decreases over time, indicating 

removal by means other than the very low air infiltration rate (0.03 h(-1)), e.g., 

deposition onto the chamber surfaces. Emission factors for these compounds were 

calculated to take these losses into account and the rate constants for these losses 

were estimated. 

 To estimate indoor concentrations and inhalation exposures to 16 VOCs, 

nicotine and PM-2.5, the average emission factors for the six commercial brands 

were used in a time-dependent mass-balance model for two scenarios: a typical 

office building and art average residence. In general, the indoor concentrations of 

the air toxics from ETS, under conditions selected to be "typical" rather than 

extreme, are comparable in magnitude to average outdoor concentrations, 

indicating that ETS can be a significant contributor to the total indoor 

concentration and the inhalation exposure for these species. At higher smoking 

rates, exposures To VOCs from ETS could be several times higher than those 

modeled under more "typical" conditions. 

de Bruin, Y. B., K. Koistinen, et al. (2008). "Characterisation of urban inhalation 
2-70

exposures to benzene, formaldehyde and acetaldehyde in the European Union." 

Environmental Science and Pollution Research 15(5): 417-430. 

 Background, aim and scope All across Europe, people live and work in indoor 

environments. On average, people spend around 90% of their time indoors 

(homes, workplaces, cars and public transport means, etc.) and are exposed to a 

complex mixture of pollutants at concentration levels that are often several times 

higher than outdoors. These pollutants are emitted by different sources indoors 

and outdoors and include volatile organic compounds (VOCs), carbonyls 

(aldehydes and ketones) and other chemical substances often adsorbed on 

particles. Moreover, legal obligations opposed by legislations, such as the 

European Union's General Product Safety Directive (GPSD) and Registration, 

Evaluation, Authorisation and Restriction of Chemicals (REACH), increasingly 

require detailed understanding of where and how chemical substances are used 

throughout their life-cycle and require better characterisation of their emissions 

and exposure. This information is essential to be able to control emissions from 

sources aiming at a reduction of adverse health effects. Scientifically sound 

human risk assessment procedures based on qualitative and quantitative human 

exposure information allows a better characterisation of population exposures to 

chemical substances. In this context, the current paper compares inhalation 

exposures to three health-based EU priority substances, i.e. benzene, 

formaldehyde and acetaldehyde. 

 Materials and methods Distributions of urban population inhalation 

exposures, indoor and outdoor concentrations were created on the basis of 

measured AIRMEX data in 12 European cities and compared to results from 

existing European population exposure studies published within the scientific 

literature. By pooling all EU city personal exposure, indoor and outdoor 

concentration means, representative EU city cumulative frequency distributions 

were created. Population exposures were modelled with a microenvironment 

model using the time spent and concentrations in four microenvironments, i.e. 

indoors at home and at work, outdoors at work and in transit, as input parameters. 

Pooled EU city inhalation exposures were compared to modelled population 

exposures. The contributions of these microenvironments to the total daily 
2-71

inhalation exposure of formaldehyde, benzene and acetaldehyde were estimated. 

Inhalation exposures were compared to the EU annual ambient benzene air 

quality guideline (5 mu g/m(3)-to be met by 2010) and the recommended (based 

on the INDEX project) 30-min average formaldehyde limit value (30 mu g/m(3)). 

 Results Indoor inhalation exposure contributions are much higher 

compared to the outdoor or in-transit microenvironment contributions, accounting 

for almost 99% in the case of formaldehyde. The highest in-transit exposure 

contribution was found for benzene; 29.4% of the total inhalation exposure 

contribution. Comparing the pooled AIRMEX EU city inhalation exposures with 

the modelled exposures, benzene, formaldehyde and acetaldehyde exposures are 

5.1, 17.3 and 11.8 mu g/m(3) vs. 5.1, 20.1 and 10.2 mu g/m(3), respectively.

Together with the fact that a dominating fraction of time is spent indoors (> 90%), 

the total inhalation exposure is mostly driven by the time spent indoors. 

 Discussion The approach used in this paper faced three challenges 

concerning exposure and time-activity data, comparability and scarce or missing 

in-transit data inducing careful interpretation of the results. The results obtained 

by AIRMEX underline that many European urban populations are still exposed to 

elevated levels of benzene and formaldehyde in the inhaled air. It is still likely 

that the annual ambient benzene air quality guideline of 5 mu g/m(3) in the EU 

and recommended formaldehyde 30-min average limit value of 30 mu g/m(3) are 

exceeded by a substantial part of populations living in urban areas. Considering 

multimedia and multi-pathway exposure to acetaldehyde, the biggest exposure 

contribution was found to be related to dietary behaviour rather than to inhalation. 

 Conclusions In the present study, inhalation exposures of urban 

populations were assessed on the basis of novel and existing exposure data. The 

indoor residential microenvironment contributed most to the total daily urban 

population inhalation exposure. The results presented in this paper suggest that a 

significant part of the populations living in European cities exceed the annual 

ambient benzene air quality guideline of 5 mu g/m(3) in the EU and 

recommended (INDEX project) formaldehyde 30-min average limit value of 30 

mu g/m(3). 

 Recommendations and perspectives To reduce exposures and consequent 
2-72

health effects, adequate measures must be taken to diminish emissions from 

sources such as materials and products that especially emit benzene and 

formaldehyde in indoor air. In parallel, measures can be taken aiming at reducing 

the outdoor pollution contribution indoors. Besides emission reduction, 

mechanisms to effectively monitor and manage the indoor air quality should be 

established. These mechanisms could be developed by setting up appropriate EU 

indoor air guidelines. 

Delgado-Saborit, J. M., N. J. Aquilina, et al. (2009). "Model Development and Validation 

of Personal Exposure to Volatile Organic Compound Concentrations." Environmental 

Health Perspectives 117(10): 1571-1579. 

 Direct measurement of exposure to volatile organic compounds (VOCs) via 

personal monitoring is the most accurate exposure assessment method available. 

However, its wide-scale application to evaluating exposures at the population 

level is prohibitive in terms of both cost and time. Consequently, indirect 

measurements via a combination of microenvironment concentrations and 

personal activity diaries represent a potentially useful alternative. 

 Objective: The aim of this study was to optimize a model of personal 

exposures (PEs) based on microenvironment concentrations and time/activity 

diaries and to compare modeled with measured exposures in an independent data 

set. 

 Materials: VOC PEs and a range of microenvironment concentrations 

were collected with active samplers and sorbent tubes. Data were supplemented 

with information collected through questionnaires. Seven models were tested to 

predict PE to VOCs in 75% (n = 370) of the measured PE data set, whereas the 

other 25% (n = 120) was used for validation purposes. 

 Results: The best model able to predict PE with independence of 

measurements was based upon stratified microenvironment concentrations, 

lifestyle factors, and individual-level activities. The proposed model accounts for 

40–85% of the variance for individual VOCs and was validated for almost all 

VOCs, showing normalized mean bias and mean fractional bias below 25% and 

predicting 60% of the values within a factor of 2. 
2-73

 Conclusions: The models proposed identify the most important nonweather-related variables for VOC exposures ; highlight the effect of personal 

activities, use of solvents, and exposure to environmental tobacco smoke on PE 

levels ; and may assist in the development of specific models for other locations. 

Eklund, B. M., S. Burkes, et al. (2008). "Spatial and temporal variability in VOC levels 

within a commercial retail building." Indoor Air 18(5): 365-374. 

 A study was performed to characterize the concentration of dozens of volatile 

organic compounds (VOCs) at 10 locations within a single large building and 

track these concentrations over a 2-year period. The study was performed at a 

shopping center (strip mall) in New Jersey. A total of 130 indoor air samples were 

collected from 10 retail stores within the shopping center and analyzed for 60 

VOCs by US EPA Method TO-15. Indoor concentrations of up to 55,100 mu 

g/m(3) were measured for individual VOCs. The indoor/outdoor ratio (I/O) was as 

high as 1500 for acetone and exceeded 100 at times for various compounds, 

indicating that significant indoor air sources were present. A large degree of 

spatial variability was observed between stores within the building, with 

concentrations varying by three to four orders of magnitude for some compounds. 

The spatial variability was dependent on the proximity of the sampling locations 

to the indoor sources. A large degree of temporal variability also was observed for 

compounds emitted from indoor sources, but the temporal variability generally 

did not exceed two standard deviations (sigma). For compounds not emitted from 

indoor sources at significant rates, both the spatial and temporal variability tended 

to range within an order of magnitude at each location. 

Gilbert, N. L., D. Gauvin, et al. (2006). "Housing characteristics and indoor 

concentrations of nitrogen dioxide and formaldehyde in Quebec City, Canada." 

Environmental Research 102(1): 1-8. 

 Concentrations of nitrogen dioxide and formaldehyde were determined in a study 

of 96 homes in Quebec City, Canada, between January and April 2005. In 

addition, relative humidity, temperature, and air change rates were measured in 

homes, and housing characteristics were documented through a questionnaire to 
2-74

occupants. Half of the homes had ventilation rates below 7.5 L/s person. Nitrogen 

dioxide (NO2) and formaldehyde concentrations ranged from 3.3 to 29.1 mu 

g/m(3) (geometric mean 8.3 mu g/m(3)) and from 9.6 to 90.0 mu g/m(3)

(geometric mean of 29.5 mu g/m(3)), respectively. The housing characteristics 

documented in the study explained approximately half of the variance of NO2 and 

formaldehyde. NO2 concentrations in homes were positively correlated with air 

change rates (indicating a significant contribution of outdoor sources to indoor 

levels) and were significantly elevated in homes equipped with gas stoves and, to 

a lesser extent, in homes with gas heating systems. Formaldehyde concentrations 

were negatively correlated with air change rates and were significantly elevated in 

homes heated by electrical systems, in those with new wooden or melamine 

furniture purchased in the previous 12 months, and in those where painting or 

varnishing had been done in the sampled room in the previous 12 months. Results 

did not indicate any significant contribution of indoor combustion sources, 

including wood-burning appliances, to indoor levels of formaldehyde. These 

results suggest that formaldehyde concentrations in Quebec City homes are 

caused primarily by off-gassing, and that increasing air change rates in homes 

could reduce exposure to this compound. More generally, our findings confirm 

the influence of housing characteristics on indoor concentrations of NO2 and 

formaldehyde. Crown Copyright (c) 2006 Published by Elsevier Inc. All rights 

reserved. 

Gilbert, N. L., M. Guay, et al. (2008). "Air change rate and concentration of 

formaldehyde in residential indoor air." Atmospheric Environment 42(10): 2424-2428. 

 The purpose of this study was to investigate the relationship between air change 

rates and indoor concentrations of formaldehyde. Concentrations of formaldehyde 

and air change rates were measured in 96 homes in Quebec City, Canada, in 

winter 2005. House characteristics such as heating systems or recent renovations 

were also documented. Formaldehyde concentrations were regressed to air change 

rates among the entire sample and among some sub-samples of homes, and 

predictive intervals were computed. The air change rate ensuring a formaldehyde 

concentration below Health Canada's guideline value of 50 mu g m(-3) in 95% of 
2-75

homes was 0.26 h(-1) based on the entire sample, 0.34 h-1 in homes with recent 

off-gassing sources of formaldehyde, and 0.37 h(-1) in homes heated mainly by 

electrical baseboard heaters. These results indicate that ventilation effectively 

decreases formaldehyde concentrations, but some categories of homes such as 

those with new off-gassing sources and homes heated by electrical baseboard 

heaters may require a higher air change rate to keep their formaldehyde levels 

within Health Canada's guidelines. (c) 2008 Elsevier Ltd. All rights reserved. 

Gilbert, N. L., M. Guay, et al. (2005). "Levels and determinants of formaldehyde, 

acetaldehyde, and acrolein in residential indoor air in Prince Edward Island, Canada." 

Environmental Research 99(1): 11-17. 

 This study was undertaken to determine the concentrations of formaldehyde, 

acetaldehyde, and acrolein in air samples taken in some Canadian houses and to 

determine the association between aldehyde levels and housing characteristics. 

Concentrations of formaldehyde, acetaldehyde, and acrolein were measured in 59 

homes in Prince Edward Island, Canada, during the winter of 2002. Housing 

characteristics were documented through inspection and by interviews of 

occupants. Formaldehyde, acetaldehyde, and acrolein concentrations ranged from 

5.5 to 87.5 mu g/m(3) (median, 29.6 mu g/m(3)), from 4.4 to 79.1 mu g/m(3) 

(median, 18.9 mu g/m(3)), and from 0.1 to 4.9 mu g/m(3) (median, 0.9 mu 

g/m(3)), respectively. Formaldehyde levels were elevated in homes built after 

1970. Acetaldehyde and acrolein levels were elevated in homes inhabited by at 

least one smoker and in homes built 1970-1985 and were correlated with absolute 

humidity and carbon dioxide, two variables likely to be surrogates for lower air 

exchange rates. In conclusion, lower air exchange rates appear to be important 

determinants of formaldehyde, acetaldehyde, and acrolein levels in homes. These 

data also confirm that smoking is a significant source of acetaldehyde and 

acrolein and indoor air. Crown Copyright (c) 2004 Published by Elsevier Inc. All 

rights reserved. 

Gillett, R. W., H. Kreibich, et al. (2000). "Measurement of indoor formaldehyde 

concentrations with a passive sampler." Environmental Science & Technology 34(10): 
2-76

2051-2056. 

 An existing Ferm type passive sampler technique has been further developed to 

measure concentrations of formaldehyde gas in indoor air. Formaldehyde forms a 

derivative after reaction with a filter coated with 2,4-dinitrophenylhydrazine (2,4-

DNPH). The formaldehyde 2,4-dinitrophenylhydrazine derivative (formaldehyde2,4-DNPH) is extracted from the filter, and the concentration is determined by 

high performance liquid chromatography. The technique has been Validated 

against an active sampling method, and the agreement is close when the 

appropriate laminar boundary layer depth is applied to the passive measurement. 

For this technique an exposure period of 3 days is equivalent to a limit of 

detection of formaldehyde of 3.4 ppbv and a limit of quantification of 7.6 ppbv. 

To test the performance of the passive samplers ambient formaldehyde 

measurements were carried out inside homes and in a range of workplace 

environments. 

Godish, T. (2001). Aldehydes. Indoor Air Quality Handbook. J. D. Spengler, J. Samet 

and J. McCarthy, McGraw-Hill Publishing Company, New York. 

Groah, W. J. (2006). "Predicting indoor-air formaldehyde concentrations from emissions 

of urea-formaldehyde-bonded wood products using the Versar model." Forest Products 

Journal 56(10): 97-100. 

 The Versar mathematical model, an outgrowth of research by the Environmental 

Protection Agency (EPA), is a tool for making home projections of formaldehyde 

concentrations. The model, based on mass balance principles, can accommodate 

input information from up to six formaldehyde sources. Laboratory data were 

available characterizing emission characteristics of four primary wood product 

formaldehyde sources used in an EPA and Composite Panel Association (CPA) 

home study project. Using product source inputs, Versar initial home 

concentration outputs were reasonably consistent with measured formaldehyde in 

the test home, particularly when the gypsum wallboard sink/re-emitter was 

considered a fifth formaldehyde source in the model. 
2-77

Guo, H., N. H. Kwok, et al. (2009). "Formaldehyde and volatile organic compounds in 

Hong Kong homes: concentrations and impact factors." Indoor Air 19(3): 206-217. 

 This paper presents formaldehyde and volatile organic compounds (VOC) 

concentrations, potential sources and impact factors in 100 homes. The 24-h 

average formaldehyde concentration in 37 homes exceeded the good class of the 

Hong Kong Indoor Air Quality Objectives (HKIAQO), whereas the total VOCs 

concentration in all homes was lower than the HKIAQO. Compared to other East 

Asian cities, indoor formaldehyde and styrene in Hong Kong was the highest, 

reflecting that the homes in Hong Kong were more affected by household 

products and materials. The formaldehyde concentration in newly built 

apartments was significantly higher than that in old buildings, whereas no 

relationship between the concentration and the building age was found for VOCs. 

There was no difference for formaldehyde and toluene between smoking and nonsmoking homes, suggesting that cigarette smoking was not the major source of 

these two species. Homes of a couple with a child had higher formaldehyde and 

acetic acid concentrations, while homes with more than three people had higher 

concentrations of 1-butanol, heptane and d-limonene. When shoes were inside the 

homes, heptane, acetic acid, nonane and styrene concentrations were statistically 

higher than that when shoes were out of the homes. Furthermore, higher levels of 

1,2,4-trimethylbenzene, styrene, nonane and heptane were found in gas-use 

families rather than in electricity-use homes.Long-term exposure to formaldehyde 

and volatile organic compounds (VOC) in indoor environments may cause a 

number of adverse health effects such as asthma, dizziness, respiratory and lung 

diseases, and even cancers. Therefore, it is critical to minimize indoor air 

pollution caused by formaldehyde and VOCs. The findings obtained in this study 

would significantly enhance our understanding on the levels, emission sources 

and factors which affect indoor concentrations of formaldehyde and VOCs. The 

results can help housing designers, builders, home residents, and housing 

department of the government to improve indoor air quality (IAQ) by means of 

appropriate building materials, clean household products and proper life styles. It 

can also help policy makers reconcile the IAQ objectives and guidelines. 
2-78

Hanrahan, L. P., K. A. Dally, et al. (1984). "Formaldehyde Vapor in Mobile Homes - a 

Cross-Sectional Survey of Concentrations and Irritant Effects." American Journal of 

Public Health 74(9): 1026-1027. 

 Sixty-five Wisconsin mobile home households volunteered for an assessment of 

indoor formaldehyde gas. Sixty-one teenage and adult occupants completed health 

questionnaires. Formaldehyde concentrations ranged from less than 0.10 to 0.80 

ppm, with the risk of ocular discomfort showing a positive dose-response 

relationship. 

Hawthorne, A. R. and T. G. Matthews (1987). "Models for Estimating Organic Emissions 

from Building-Materials - Formaldehyde Example." Atmospheric Environment 21(2): 

419-424. 

 One important source of chronic exposure to low levels of organic compounds in 

the indoor environment is emissions from building materials. Because removal of 

offending products may be costly or otherwise impractical, it is important that the 

emissions of organic pollutants be understood prior to incorporation of these 

materials into buildings. Once the organic pollutants of concern are identified, 

based on potential health effects and emission potential from the building 

material, it is necessary that an emission model be developed to predict the 

behavior of emission rates under various indoor conditions. Examples of the type 

of requirements that must be addressed in developing models for estimating 

organic emissions from building materials into the indoor environment are 

presented. Important factors include the products' characteristic source strengths 

at standard test conditions, impact of variations in environmental conditions (such 

as temperature and humidity), concentrations of the modeled organic pollutants in 

indoor environments and product ages. Ideally, emission models should have 

physical/chemical bases so that the important physical factors can be identified 

and their relative importance quantified. Although a universal model describing 

organic emissions from all building materials may not be feasible due to the 

tremendous variety of organic products and building materials in use, the most 

studied of the volatile organic compounds from building materials, formaldehyde, 

is used to illustrate an approach to the development of a specific model for 
2-79

organic emissions. 

Hayashi, M., M. Enai, et al. (2001). "Annual characteristics of ventilation and indoor air 

quality in detached houses using a simulation method with Japanese daily schedule 

model." Building and Environment 36(6): 721-731. 

 This paper presents the results of investigations that were made on a simulation 

program, which calculates the temperature, the heat loads, the ventilation rates 

and the indoor air quality considering the Japanese daily schedule and the 

dweller's behaviour toward keeping comfortable indoor climate, in order to 

explain the effect of ventilation systems. In the investigation, the concentrations 

of carbon dioxide, carbon monoxide and formaldehyde are regarded as indicators 

of indoor air quality. Firstly, three types of systems were designed in a house 

model; that is a basic passive ventilation system, a passive stack ventilation 

system and a mechanical ventilation system. Next, the simulation was performed 

using the standard weather data on three cities in Japan; and the simulation made 

clear the annual characteristics of ventilation and indoor air quality. The results 

show that in a house with a passive ventilation system, there is much risk of 

indoor air pollution in spring, autumn and when air conditioned, and that indoor 

air quality in the rooms on the first floor differs from that on the second floor. 

Lastly, the performance of the ventilation systems and the solution methods of 

realizing these ventilation systems were discussed on the basis of the results of the 

simulation. (C) 2001 Elsevier Science Ltd. All rights reserved. 

Hayashi, M. and H. Osawa (2008). "The influence of the concealed pollution sources 

upon the indoor air quality in houses." Building and Environment 43(3): 329-336. 

 This report presents the results of investigations on the indoor air quality of 

common Japanese detached houses. It is necessary to control the emission rates 

from the interior materials and the ventilation rates to keep indoor concentration 

of VOC enough low. And it is also necessary to consider the influence of the 

pollution sources in the concealed spaces for better indoor air quality in some 

kinds of building structures and some kinds of ventilation systems. In this study 

the influences of the concealed pollution sources upon the indoor concentrations 
2-80

of pollutants were investigated using three detached houses with four ventilation 

systems and the following results were obtained. When the ventilation system was 

changed from the air-supply type to the air-exhaust type, the indoor 

concentrations of formaldehyde increased. The infiltration ratios: the ratios of the 

infiltration rate to the indoor space toward the emission rate of a pollutant in the 

concealed space were measured using the tracer-gas method. The ratios from the 

beam spaces and the partition were about 100% in most cases. The ratios from the 

crawl space under the first floor and the truss space under the roof were lower 

than those from the beam space and partitions in most cases, because those spaces 

have ventilation openings. But the ratio from the crawl space reached about 100% 

in the house without ventilation openings at the crawl space. And even in the 

house with ventilation openings at crawl space, the ratio reached 50% in the house 

with the exhaust-ventilation system. Therefore, it became clear that the use of the 

medicine to prevent the deterioration of the wooden structure and the white ants 

in the crawl spaces must be limited. The ratio from the envelope wall was 

changed with the pressure difference between inside and outside. These results 

showed that it is necessary to prevent infiltration from the concealed spaces and to 

control the emission rate from the concealed pollution sources. (C) 2006 Elsevier 

Ltd. All rights reserved. 

Hirota, K. and D. Prasad (2005). Indoor Air Quality in a low-density residential 

environment; A study in Abuta post-disaster public-housing. World Sustainable Building 

Conference, Tokyo. 

 In this study the relationship between the duration of occupancy and of symptoms 

of sick building syndrome (SBS) is discussed in order to demonstrate the problem 

of indoor air quality (IAQ) in low-density built environments. Since the1970s 

energy efficient and/or high-rise buildings have been associated with IAQ 

problems; however, the type of building and the degree of human density may not 

be the most crucial causes of IAQ problems. Because IAQ problems occur as a 

result of intensive exposure levels to indoor air pollutants, the key factors are in 

fact duration of exposure time to them and their concentration levels. Therefore to 

look at these factors as potential environmental causes of adverse health effects, 
2-81

user activities in a low-density residential environment were studied by means of 

a post occupancy assessment, and a simulation of indoor airflow was also 

undertaken. The pattern of indoor usage and of indoor airflow has revealed that 

problems of indoor safety and livability can in fact be associated with IAQ even 

in a low-density context. 

Hodgson, A. T., D. Beal, et al. (2002). "Sources of formaldehyde, other aldehydes and 

terpenes in a new manufactured house." Indoor Air 12(4): 235-242. 

 Formaldehyde, less volatile aldehydes, and terpene hydrocarbons are generally 

the predominant air contaminants in new manufactured and site-built houses. This 

study was conducted to identify the major sources of these compounds in a 

typically constructed, new manufactured house and to evaluate several source 

reduction practices. Specimens of materials used within the house were collected. 

These were individually pre-conditioned for 19+/-4 days, and tested for emissions 

of formaldehyde and other target compounds using small-scale chambers. Several 

cabinetry materials, passage doors, and the plywood subfloor were the 

predominant sources of formaldehyde and other aldehydes. The plywood subfloor 

was the predominant terpene source. Whole-house emission rates for combined 

materials were predicted based on the emission factors and the corresponding 

material quantities. These predicted rates were compared with whole-house 

emission rates derived from measurements made at the house 3 months after its 

installation. For 10 of 14 target compounds including formaldehyde, the predicted 

and derived rates were within a factor of two. Four emission barriers applied to 

plywood were shown to reduce emission factors for formaldehyde, hexanal, and 

other aldehydes. 

Hodgson, A. T., J. M. Daisey, et al. (1996). "Use of volatile tracers to determine the 

contribution of environmental tobacco smoke to concentrations of volatile organic 

compounds in smoking environments." Environment International 22(3): 295-307. 

 Three volatile nitrogen-containing compounds, 3-ethenylpyridine (3-EP), pyridine 

and pyrrole, were investigated as potential tracers for determining the contribution 

of environmental tobacco smoke (ETS) to concentrations of volatile organic 
2-82

compounds (VOCs) in indoor environments with smoking. The source emission 

rates of the three tracers and ten selected VOCs in ETS were first measured in a 

room-size environmental chamber for a market-weighted selection of six 

commercial cigarettes. The ratios of the emission rates of the tracers to the 

emission rates of the selected VOCs were calculated and compared among the six 

brands. The utility of the tracers was then evaluated in a field study conducted in 

five office buildings. Samples for VOCs were collected in designated smoking 

areas and adjoining non-smoking areas, air change rates were measured, and 

smoking rates were documented. Concentrations of the three tracers in the 

smoking areas were calculated using a mass-balance model and compared to their 

measured concentrations. Based on this comparison, 3-EP was selected as the 

most suitable tracer for the volatile components of ETS, although pyrrole is also 

potentially useful. Using 3-EP as the tracer, the contributions of ETS to the 

measured concentrations of the selected VOCs in the smoking areas were 

estimated by apportionment. ETS was estimated to contribute 57% to 84% (4.1 to 

26 mu g m(-3)) of the formaldehyde concentrations, 44-69% (0.9 to 5.8 mu g m(-

3)) of the 2-butanone concentrations, 37 to 58% (1.3 to 8.2 mu g m(-3)) of the 

benzene concentrations, and 20 to 69% (0.5 to 3.0 mu g m(-3)) of the styrene 

concentrations. The fractional contributions of ETS to the concentrations of 

acetone, toluene, ethylbenzene, xylene isomers, and d-limonene were all less than 

50%. 

Hodgson, A. T., A. F. Rudd, et al. (2000). "Volatile organic compound concentrations 

and emission rates in new manufactured and site-built houses." Indoor Air 10(3): 178-

192. 

 Concentrations of 54 volatile organic compounds (VOCs) and ventilation rates 

were measured in four new manufactured houses over 2-9.5 months following 

installation and in seven new site-built houses 1-2 months after completion. The 

houses were in four projects located in hot-humid and mixed-humid climates. 

They were finished and operational, but unoccupied. 

 Ventilation rates ranged from 0.14-0.78 h(-1). Several of the site-built 

houses had ventilation rates below the ASHRAE recommended value. In both 
2-83

manufactured and site-built houses, the predominant airborne compounds were 

alpha-pinene, formaldehyde, hexanal, and acetic acid. Formaldehyde 

concentrations were below or near 50 ppb with a geometric mean value for all 

houses of 40 ppb. Similarities in the types of VOCs and in VOC concentrations 

indicated that indoor air quality in the houses was impacted by the same or similar 

sources. Major identified sources included plywood flooring, latex paint and sheet 

vinyl flooring. One site-built house was operated at ventilation rates of 0.14 and 

0.32 h(-1). VOC emission rates calculated at the two conditions agreed within +/-

10% for the most volatile compounds. Generally, the ratios of emission rates at 

the low and high ventilation rates decreased with decreasing compound volatility. 

Changes in VOC emission rates in the manufactured houses over 2-9.5 months 

after installation varied by compound. Only several compounds showed a 

consistent decrease in emission rate over this period. 

Hodgson, A. T., D. G. Shendell, et al. (2004). "Comparison of predicted and derived 

measures of volatile organic compounds inside four new relocatable classrooms." Indoor 

Air 14: 135-144. 

 Our objective was to develop a process for selecting interior finish materials 

having low impacts with respect to emissions of toxic and odorous volatile 

organic compounds (VOCs) for school relocatable classrooms (RCs). A 

laboratory study identified alternate materials with low VOC emissions. Two 

pairs of RCs then were constructed. One RC per pair contained standard interior 

materials; the other incorporated alternate materials. The pairs were sited side-byside at two California elementary schools in fall 2001. Fifteen target VOCs, 

including the toxicants formaldehyde, acetaldehyde, vinyl acetate, phenol, 

toluene, and naphthalene, were measured during school hours over 8 weeks in the 

succeeding fall cooling season. Indoor minus outdoor VOC concentrations with 

an advanced HVAC operated were low; only formaldehyde concentrations 

exceeded 5 p.p.b. Classroom VOC concentrations were predicted based on 

emission factors (mug/m(2)/h), material quantities and design ventilation rates. 

These were compared to average adjusted concentrations measured when the 

occupied classrooms were operating at near the code-minimum ventilation rate. 
2-84

For 16 of the possible 42 comparisons, measured concentrations agreed within a 

factor of two of predicted the predicted values. Concentrations of six of 10 VOCs 

were significantly lower in modified RCs though average differences were mostly 

less than 1 p.p.b. 

Hodgson, A. T., J. D. Wooley, et al. (1993). "Emissions of Volatile Organic-Compounds 

from New Carpets Measured in a Large-Scale Environmental Chamber." Journal of the 

Air & Waste Management Association 43(3): 316-324. 

 This study was undertaken to quantify the emissions of volatile organic 

compounds (VOCs) released by new carpets. Samples of four typical carpets, 

including two with styrene-butadiene rubber (SBR) latex adhesive and two with 

different backings, were collected from the finish lines at manufacturers' mills. 

Individual VOCs released from these samples were identified, and their 

concentrations, emission rates and mass emissions were measured under 

simulated indoor conditions in a 20 m3 environmental chamber over one week 

periods. Concentrations and emission rates of VOCs emitted by a new SBR carpet 

were also measured in a house. 

 The carpets emitted a variety of VOCs. The two SBR carpets primarily 

emitted 4-phenylcyclohexene (4-PCH), the source of ''new carpet'' odor, and 

styrene. The concentrations and emission rates of 4-PCH were similar for the two 

carpets, while the styrene values varied significantly. The carpet with a polyvinyl 

chloride backing emitted formaldehyde, vinyl acetate, isooctane, 1,2-propanediol, 

and 2-ethyl-1-hexanol. Of these, vinyl acetate and propanediol had the highest 

concentrations an emission rates. The carpet with a polyurethane backing 

primarily emitted butylated hydroxytoluene. With the exception of formaldehyde, 

little is known about the health effects of these VOCs at low concentrations. 

Hollowell, C., D. and R. R. Miksch (1981). "Sources and concentrations of organic 

compounds in indoor environments." Bull. N.Y. Acad. Med. 57(10): 962-977. 

 

Howard, E. M., R. C. McCrillis, et al. (1998). "Indoor emissions from conversion 

varnishes." Journal of the Air & Waste Management Association 48(10): 924-930. 
2-85

 Conversion varnishes are two-component, acid-catalyzed varnishes that are 

commonly used to finish cabinets. They are valued for their water and stain 

resistance, as well as their appearance. They have been found, however, to 

contribute to indoor emissions of organic compounds. For this project, three 

commercially available conversion varnish systems were selected. A U.S. 

Environmental Protection Agency (EPA) Method 24 analysis was performed to 

determine total volatile content, and a sodium sulfite titration method was used to 

determine uncombined (free) formaldehyde content of the varnish components. 

The resin component was also analyzed by gas chromatography/mass 

spectroscopy (GC/MS) (EPA Method 311 with an MS detector) to identify 

individual organic compounds. Dynamic small chamber tests were then 

performed to identify and quantify emissions following application to coupons of 

typical kitchen cabinet wood substrates, during both curing and aging. Because 

conversion varnishes cure by chemical reaction, the compounds emitted during 

curing and aging are not necessarily the same as those in the formulation. Results 

of small chamber tests showed that the amount of formaldehyde emitted from 

these coatings was 2.3-8.1 times the amount of free formaldehyde applied in the 

coatings. A long-term test showed a formaldehyde emission rate of 0.17 

mg/m(2)/hr after 115 days. 

Hui, P. S., K. W. Mui, et al. (2008). "Influence of indoor air quality (IAQ) objectives on 

air-conditioned offices in Hong Kong." Environmental Monitoring and Assessment

144(1-3): 315-322. 

 It is costly to sample all air pollutants of a general community. Air sampling 

should be conducted based on a practical assessment strategy and monitoring 

plan. In Hong Kong, the Environmental Protection Department (HKEPD) 

launched an Indoor Air Quality (IAQ) certification scheme to grade workplace 

IAQ as 'Excellent' or 'Good' by measuring the levels of nine common indoor air 

pollutants, namely carbon dioxide (CO2), carbon monoxide (CO), respirable 

suspended particulates (RSP), nitrogen dioxide (NO2), ozone (O-3), 

formaldehyde (HCHO), total volatile organic compounds (TVOC), radon (Rn), 

and airborne bacteria count (ABC). Although average office IAQ performance 
2-86

has been improved since the implementation of this certification scheme, there are 

still resource issues and technical difficulties. To streamline the assessment of 

office IAQ performance, this study proposes a simple index of IAQ benchmarks 

formulated in compliance with the HKEPD requirements. In particular, three of 

the nine listed common air pollutants were selected as the 'representatives' for the 

overall satisfactory IAQ. Together with the assessment results of 422 Hong Kong 

air-conditioned offices, the index was evaluated in terms of test sensitivity, 

specificity and predictive values. Proved to be feasible to describe the IAQ of 

some air-conditioned offices, this IAQ index would be a useful tool for 

policymakers, building owners and professionals to quantify IAQ performance in 

offices and to make decisions on resources and manpower management for 

efficient mitigation actions. 

Kelly, T. (1996). Determination of Formaldehyde and Toluene Diisocyanate Emissions 

from Indoor Residential Sources. Sacramento, CA, California Air Resources Board: 93-

315. 

 Building materials and consumer products found in California residences were 

subjected to chamber testing to determine the emission rates of formaldehyde 

(HCHO) and of Toluene DiIsocyanates (TDI). The emissions of formaldehyde 

were determined from bare Urea-Formaldehyde (UF) and Phenol-Formaldehye 

(PF) wood products, with vinyl, paper, and other coatings, and from decorative 

laminates, permanent press fabrics fiberglass insulation, paper goods, paints, 

cosmetics, and acid-cured coatings. Other compounds determined along with 

HCHO included acetaldehyde, propionaldehyde, methyl ethyl ketone (MEK), and 

Methyl IsoButyl Ketone (MIBK). A separate set of PolyUrethane (PU) products, 

including PU foam carpet padding, furniture cushions, sheet foam, PU varnishes, 

caulks and sealants, and a commercially-applied water stop product for concrete, 

were tested for emissions of toluene diisocyanate (TDI). 

Khoder, M. I., A. A. Shakour, et al. (2000). "Indoor and outdoor formaldehyde 

concentrations in homes in residential areas in Greater Cairo." Journal of Environmental

Monitoring 2(2): 123-126. 
2-87

 Indoor and outdoor measurements of formaldehyde were conducted at seven flats 

located in residential areas in Greater Cairo, during spring and summer seasons 

1999. The mean daytime formaldehyde concentrations in kitchens, bedrooms and 

living rooms were 89, 100 and 100 ppb, respectively, in the seven flats. 

Significant positive correlations were found between the concentrations of 

formaldehyde found in these three rooms. On the other hand, no significant 

differences were found between the mean formaldehyde concentrations in these 

three rooms. The maximum mean concentration of formaldehyde (147 ppb) was 

recorded in a new flat, while the minimum concentration (43 ppb) was observed 

in an old flat. The maximum hourly and daytime concentrations were 350 and 225 

ppb, respectively. Air temperature, relative humidity and the age of the flat are 

factors affecting the emission and concentration of formaldehyde. The maximum 

indoor and outdoor formaldehyde concentrations were recorded during the 

summer season. During the spring, 38% of the samples indicated that the 

concentration of formaldehyde in the seven flats exceeded 0.1 ppm, the American 

Society of Heating, Refrigerating, and Air Conditioning Engineers' (ASHRAE) 

standard; in the summer, this figure increased to 53%. 

Kim, S. and H. J. Kim (2005). "Comparison of formaldehyde emission from building 

finishing materials at various temperatures in under heating system; ONDOL." Indoor 

Air 15(5): 317-325. 

 The objective of this research was to investigate the effect of various 

temperatures, room, 37 and 50 degrees C, on formaldehyde emission from floor 

materials, such as laminate and plywood floorings, and furniture materials, such 

as MDF and particleboard veneered with decorative paper foil, by desiccator's 

method. The temperature conditions were set up by, measuring the temperature in 

a Korean under heating system. To maintain an indoor air temperature of 20 

degrees C, the temperature of the flooring surface was about 37 degrees C and the 

temperature of the cement mortar was 50 degrees C. The initial formaldehyde 

emission of the laminate flooring and plywood flooring was 1.44 and 0.63 mg/l, 

and for MDF and particleboard it was 4.73 and 4.95 mg/l, respectively. Floor 

materials were under E1 grade while furniture materials were under E-2 grade in 
2-88

terms of formaldehyde emission. Because of the under heating system, the 

flooring materials were exposed to 37 and 50 degrees C, while the furniture 

materials mostly existed at room temperature. At 37 and 50 degrees C, the 

formaldehyde emission level of the flooring materials was already under 0.3 ppm 

(F star star star star level by JIS A 1460, application possibility without area limit) 

after 10 days and the emission had decreased further (0.03-0.10 mg/l) after 28 

days. These levels are not injurious to the human body and will not cause sick 

house syndrome (SHS). The problem, however, is the furniture materials such as 

MDF and particleboard. As these materials are not exposed to high temperature 

(50 degrees C in this experiment) in living condition, it was still E-2 grade of 

formaldehyde emission level at room temperature remained even after 28 days. 

Although there will be variations with the volume of furniture materials and the 

indoor conditions, furniture materials are the principal cause of indoor air quality 

pollution in Korean with the under heating system. 

Kirkeskov, L., T. Witterseh, et al. (2009). "Health evaluation of volatile organic 

compound (VOC) emission from exotic wood products." Indoor Air 19(1): 45-57. 

 The purpose of this study was to measure and evaluate the impact of the 

emissions of selected products of exotic wood on health. Ten products were 

screened for chemical compounds, and five of the most used products which 

emitted more than 800 mu g/kg were selected for further quantitative analyses by 

climate chamber measurement (iroko, ramin, sheesham, merbau, and rubber tree). 

Samples of exotic wood (rubber tree and belalu) were further analyzed for 

emission of chemical compounds by migration into artificial saliva and for 

content of pesticides and allergenic natural rubber latex (NR latex) (rubber tree). 

The toxicological effects of all substances identified were evaluated and the 

lowest concentrations of interest (LCI) assessed. An R-value was calculated for 

each wood product (R-value below 1 is considered to be unproblematic as regards 

health). Emission from the evaluated exotic wood only took place to a very 

limited extent. None of the selected products, under the chosen rating system, is 

likely to cause adverse health effects. Products with surface treatment might pose 

a problem if used as kitchen utensils, as children's toys, or when they are in close 
2-89

contact with the skin for a long time.The authors investigated the chemical 

emissions from selected products from exotic wood by climate chamber 

measurement. Quantitative chemical analyses of emissions from the five most 

used exotic products in Denmark were performed, and all chemical compounds 

found were evaluated toxicologically. Emission from the evaluated exotic wood 

was very limited. None of the products is likely, under our exposure conditions, to 

cause health problems in relation to indoor air. 

Koziel, J. A., J. Noah, et al. (2001). "Field sampling and determination of formaldehyde 

in indoor air with solid-phase microextraction and on-fiber derivatization." 

Environmental Science & Technology 35(7): 1481-1486. 

 A new sampling and analysis method for formaldehyde in indoor air was tested in 

several indoor air surveys. The method was based on the use of solid-phase 

microextraction (SPME) poly(dimethylsiloxane)/divinylbenzene,65 mum fiber 

and gas chromatography. Indoor air surveys included grab and time-weighted 

average (TWA) sampling and were completed at six locations using (a) the SPME 

method employing on-fiber formaldehyde derivatization with o-(2,3,4,5,6-

pentafluorobenzyl)hydroxylamine hydrochloride and (b)the conventional National 

Institute for Occupational Safety and Health (NIOSH) 2451 method. Sampling 

time for SPME fiber ranged from 10 min for grab sampling to 8 h for TWA 

sampling. Sampling locations included a residential house, a rental apartment, an 

office building, and industrial workplaces. The air concentrations measured by 

SPME ranged from 10 to 380 ppbv and correlated well with those estimated by 

the NIOSH method. Results also indicated th at in some cases the formaldehyde 

concentrations measured in residential air could be much higher than those 

allowed in occupational settings. The SPME method proved to be accurate, fast, 

sensitive, and cost-efficient in field sampling applications. This research should 

be of interest to research, industrial, and regulatory agencies as well as to the 

general public concerned with indoor air quality. Introduction 

Lee, S. C. and M. Chang (2000). "Indoor and outdoor air quality investigation at schools 

in Hong Kong." Chemosphere 41(1-2): 109-113. 
2-90

 Five classrooms in Hong Kong (HK), air-conditioned or ceiling fans ventilated, 

were chosen for investigation of indoor and outdoor air quality. Parameters such 

as temperature, relative humidity (RH), carbon dioxide (CO2), sulphur dioxide 

(SO2), nitric oxide (NO), nitrogen dioxide (NO2), respirable particulate matter 

(PM10), formaldehyde (HCHO), and total bacteria counts were monitored indoors 

and outdoors simultaneously. The average respirable particulate matter 

concentrations were higher than the HK Objective, and the maximum indoor 

PM10 level exceeded 1000 mu g/m(3). Indoor CO2 concentrations often 

exceeded 1000 mu l/l in air-conditioning and ceiling fan classrooms, indicating 

inadequate ventilation. Maximum indoor CO2 level reached 5900 mu l/l during 

class at the classroom with cooling tower ventilation. Increasing the rate of 

ventilation or implementation of breaks between classes is recommended to 

alleviate the high CO2 level. Other pollution parameters measured in this study 

complied with the standards. The two most important classroom air quality 

problems in Hong Kong were PM10 and CO2 levels. (C) 2000 Elsevier Science 

Ltd. All rights reserved. 

Lee, S. C., H. Guo, et al. (2002). "Inter-comparison of air pollutant concentrations in 

different indoor environments in Hong Kong." Atmospheric Environment 36(12): 1929-

1940. 

 Indoor air quality in selected indoor environments in Hong Kong such as homes, 

offices, schools, shopping malls and restaurants were investigated. Average CO2 

levels and total bacteria counts in air-conditioned classrooms, shopping malls and 

restaurants were comparatively higher than those measured in occupied offices 

and homes. Elevated CO, levels exceeding 1000ppm and total bacteria counts 

resulted from high occupancy combined with inadequate ventilation. Average 

PM10 levels were usually higher indoors than outdoors in homes, shopping malls 

and restaurants. The highest indoor PM10 levels were observed at investigated 

restaurants due to the presence of cigarette smoking and extensive use of gas 

stoves for cooking. The restaurants and shopping malls investigated had higher 

formaldehyde levels than other indoor environments when building material, 

smoking and internal renovation work were present. Volatile organic compounds 
2-91

(VOCs) in both indoor and outdoor environments mainly resulted from vehicle 

exhaust emissions. It was observed that interior decoration work and the use of 

industrial solvents in an indoor environment could significantly increase the 

indoor levels of VOCs. (C) 2002 Published by Elsevier Science Ltd. 

Lee, S. C. and B. Wang (2004). "Characteristics of emissions of air pollutants from 

burning of incense in a large environmental chamber." Atmospheric Environment 38(7): 

941-951. 

 The objective of this study was to characterize the emissions of air pollutants 

from incense burning in a large environmental test chamber. Air pollutants 

emitted from ten types of commonly used incense manufactured in different 

regions were compared. The target pollutants included particulate matters (PM10, 

PM2.5), volatile organic compounds (VOCs), carbonyls, carbon monoxide (CO), 

carbon dioxide (CO2), nitrogen oxides (NOx), methane (CH4) and non-methane 

hydrocarbon (NMHC). The particulate matters emitted from all the incense 

significantly exceeded the Recommended Indoor Air Quality Objectives for 

Office Buildings and Public Places in Hong Kong (HKIAQO). The CO peak 

levels of seven incense types greatly exceeded the HKIAQO standard. The 

formaldehyde concentrations of six types of incense were higher than the 

HKIAQO. The highest formaldehyde level exceeded the standard by 2 times. The 

results indicated that the concentrations of benzene, toluene, methyl chloride and 

methylene chloride significantly increased with the burning of all incense tested. 

In addition, the benzene concentrations of all tested incense were significantly 

higher than the HKIAQO standard. Although Incense 2 and 6 were claimed to be 

environmental friendly, the quantity of the pollutants emitted was not observed to 

be lower than the others. It was observed that when comparing the gas pollutant 

emission factors between two major incense categories (i.e. traditional and 

aromatic), the traditional incense (i.e. Incense 1-6) had relatively higher values 

than aromatic incense (i.e. Incense 7-9). Generally, it was found that the VOCs 

emitted sequence was aromatic incense > tradition incense > church incense (i.e. 

Incense 10). However, the carbonyl compounds emission sequence was 

traditional incense > aromatic incense > church incense. The results show that 
2-92

incense burning is one of the important indoor air pollution sources for PM, CO 

and VOCs. (C) 2003 Elsevier Ltd. All rights reserved. 

Li, Y., K. Wang, et al. (2005). Measurement and Prediction of Indoor Formaldehyde 

Concentration in Northeast China. Air and Waste Management Association’s 98th 

Annual Meeting & Exhibition, Minneapolis, MN, USA. 

 With the development of economy and the improvement of living condition, 

decorating houses has been the hotspot of personal consumption in China for the 

past two decades. Indoor formaldehyde pollution is ubiquitous in China, while it 

has been mostly controlled in the developed countries. In this study, an 

investigation on the measurement of indoor formaldehyde concentration in 

residential houses was conducted in Harbin, located at the most chilly area in 

Northeast China. The results showed that the concentration of indoor 

formaldehyde ranged from 0.017 to 1.302mg/m3, and only 22.8% of the 

residential houses met the formaldehyde standard of 0.10 mg/m3 for National Air 

Quality Standard of China. The monthly average formaldehyde concentration in 

summer (June-August) was about twice higher than those in winter (NovemberMarch). A strong correlation between the monthly average indoor formaldehyde 

concentration and the monthly average temperature (R2=0.8652) was obtained. 

Furthermore, a mathematical model was successfully developed to predict the 

concentration of indoor formaldehyde in Chinese residential houses. Field 

measurements of indoor formaldehyde concentration in residential houses were 

also conducted for various decoration time in order to investigate the influence of 

decoration time on the indoor formaldehyde concentration. 

Li, Y. Y., P. C. Wu, et al. (2002). Effects of HVAC ventilation efficiency on the 

concentrations of formaldehyde and total volatile organic compounds in office buildings. 

Indoor Air, California. 

 Potential sources for emitting formaldehyde and volatile organic compounds are 

abundant in office buildings. Exposure to the above compounds may result in 

short-term, long-term, or carcinogenic effects at concentrations often measured. 

Our study conducts field measurements on six typical office buildings with 
2-93

different HVAC systems to evaluate the effects of ventilation efficiency on the 

concentration of formaldehyde and total volatile organic compounds (TVOC). 

Formaldehyde and TVOC concentrations were measured by continuous photoacoustic Multi-Gas monitor. The air-change rates were estimated by tracer gas 

concentration decay method in every test space. Air Exchange Efficiency (AEE) 

and Effective Ventilation Rate (EACH) were also calculated to characterize the 

ventilation pattern and mixing factor. Our results show that the increase of 

effective ventilation could reduce formaldehyde and TVOC in office buildings . 

We therefore suggest that increasing ventilation efficiency appears to bea 

plausible solution to diminish both formaldehyde and TVOC concentrations in 

office buildings. 

Lin, Z., T. T. Chow, et al. (2005). "CFD study on effect of the air supply location on the 

performance of the displacement ventilation system." Building and Environment 40(8): 

1051-1067. 

 The purpose of this paper is to investigate using a numerical simulation 

(computational fluid dynamics or CFD) the effect of the air supply location on the 

design and performance of the displacement ventilation (DV) system. The results 

are reported in terms of thermal comfort and indoor air quality. The study focuses 

on the typical Hong Kong office under local thermal and boundary conditions. 

This includes the high cooling load used in Hong Kong. Several pollutants 

typically found in the office such as carbon dioxide and volatile organic 

compounds (VOCs) were investigated. The results indicate that the supply should 

be located near the center of the room rather than to one side of the room. This 

will provide a more uniform thermal condition in the office. The DV system was 

found to be effective in dispersing VOCs within an office environment for all 

cases studied. The exhaust was found to have minimal effect on the thermal 

comfort. For a DV system in Hong Kong, it is possible to use 100% fresh air 

without extra energy consumption. (c) 2004 Elsevier Ltd. All rights reserved. 

Lin, Z., T. T. Chow, et al. (2005). "Comparison of performances of displacement and 

mixing ventilations. Part II: indoor air quality." International Journal of Refrigeration-
2-94

Revue Internationale Du Froid 28(2): 288-305. 

 A numerical simulation using a validated computational fluid dynamics model is 

used to investigate and compare the performances of displacement and mixing 

ventilations (MVs), under different boundary conditions. A companion paper will 

report the results in terms of thermal comfort, while this paper investigates the 

indoor air quality (IAQ). The IAQ will be measured in terms of carbon monoxide, 

mean age of air and the three volatile organic compounds, toluene, benzene and 

formaldehyde, which are commonly found in indoor room furnishings. The case 

studies include offices, classrooms, retail shops and industrial workshops, under 

typical Hong Kong thermal boundary conditions. Compared with conventional 

MV, displacement ventilation may provide better IAQ in the occupied zone. (C) 

2004 Elsevier Ltd and IIR. All rights reserved. 

Lin, Z., T. T. Chow, et al. (2005). "Effect of air supply temperature on the performance 

of displacement ventilation (Part II) - Indoor air quality." Indoor and Built Environment

14(2): 117-131. 

 The effect of air supply temperature on the performance of a displacement 

ventilation (DV) system has been investigated. This paper is the second part of a 2 

part series and the results are reported with regard to Indoor Air Quality (IAQ). 

The study is based on a typical office building in Hong Kong, under local thermal 

and flow boundary conditions. The criteria for IAQ were measurements of carbon 

dioxide levels, mean age of air and 3 volatile organic compounds (VOCs): 

toluene, benzene and formaldehyde. The change in supply temperature from 19 

degrees C to 22 degrees C was found to have no significant effect on the level and 

distribution of contaminants in the room. The DV system was found to operate 

satisfactorily under the range of supply temperatures studied. 

Lin, Z., T. T. Chow, et al. (2006). "Effects of headroom on the performance of the 

displacement ventilation system." Indoor and Built Environment 15(4): 333-346. 

 A numerical simulation applying a validated computational fluid dynamics model 

was used to investigate the effect of the headroom on a displacement ventilation 

(DV) system. Two different headroom heights in a space were simulated and 
2-95

compared. It was found that the effect of increased headroom was to improve the 

thermal comfort of the indoor space. It was also concluded that given the thermal 

boundary conditions commonly encountered and the typical low headroom found 

in Hong Kong, DV was found to work effectively in terms of thermal comfort and 

indoor air quality (IAQ). 

Liteplo, R. G. and M. E. Meek (2003). "Inhaled formaldehyde: Exposure estimation, 

hazard characterization and exposure-response analysis." Journal of Toxicology and 

Environmental Health, Part B 6(1): 85-114. 

 Formaldehyde has been assessed as a Priority Substance under the Canadian 

Environmental Protection Act. Probabilistic estimates of exposure of the general 

population in Canada to formaldehyde in ambient and indoor air are presented. 

Critical health effects include sensory irritation and the potential to induce tumors 

in the upper respiratory tract (the nasal region in rodents and potentially the lungs 

of humans). The majority of the general population is exposed to airborne 

concentrations of formaldehyde less than those typically associated with sensory 

irritation (i.e., 0.1 mg/m 3 ). Based primarily upon data derived from laboratory 

studies, the inhalation of formaldehyde under conditions that induce cytotoxicity 

and sustained regenerative proliferation within the respiratory tract is considered 

to present a carcinogenic hazard to humans. At airborne levels for which the 

prevalence of sensory irritation is minimal (i.e., 0.1 mg/m 3 ), risks of respiratorytract cancers for the general population estimated on the basis of a biologically 

motivated case-specific model are exceedingly low. This biologically motivated 

case-specific model incorporates two-stage clonal expansion and is supported by 

dosimetry calculations from computational fluid dynamics analyses of 

formaldehyde flux in various regions of the nose and single-path modeling for the 

lower respiratory tract. The degree of confidence in the underlying database and 

uncertainties in estimates of exposure and in characterization of hazard and dose 

response are delineated. 

Liu, W., J. Zhang, et al. (2006). "Concentrations and source characteristics of airborne 

carbonyl compounds measured outside urban residences." J Air Waste Manag Assoc
2-96

56(8): 1196-204. 

 This paper presents the analysis of ambient air concentrations of 10 carbonyl 

compounds (aldehydes and ketones) measured in the yards of 87 residences in the 

city of Elizabeth, NJ, throughout 1999-2001. Most of these residences were 

measured twice in different seasons; the sampling duration was 48 hr each time. 

The authors observed higher concentrations for most of the measured carbonyl 

compounds on warmer days, reflecting larger contributions of photochemical 

reactions on warmer days. The estimated contributions of photochemical 

production varied substantially across the measured carbonyl compounds and 

could be as high as 60%. Photochemical activity, however, resulted in a net loss 

for formaldehyde. The authors used stepwise multiple linear regression models to 

evaluate the impact of traffic sources and meteorological conditions on carbonyl 

concentrations using the data collected on colder days (with lower photochemical 

activities). They found that the concentrations of formaldehyde, acetaldehyde, 

acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyoxal, and 

methylglyoxal significantly decreased with increasing distance between a 

measured residence and one or more major roadways. They also found significant 

negative associations between concentrations for most of the measured carbonyl 

compounds and each of the following meteorological parameters: mixing height, 

wind speed, and precipitation. 

Liu, W., J. Zhang, et al. (2006). "Estimating contributions of indoor and outdoor sources 

to indoor carbonyl concentrations in three urban areas of the United States." Atmospheric 

Environment 40(12): 2202-2214. 

 Exposure to carbonyls (aldehydes and ketones) can produce adverse health 

effects. It is known that various sources of carbonyls are often present inside 

residences but little is known about their indoor source strengths. In the present 

paper, we used a database established in the relationships of indoor, outdoor, and 

personal air (RIOPA) study to estimate indoor source strengths of 10 carbonyls 

and outdoor contributions to measured indoor concentrations of these carbonyls. 

We applied a mass balance model to analyze paired indoor and outdoor carbonyl 

concentrations simultaneously measured in 234 RIOPA homes. Among all the 
2-97

measured carbonyls, formaldehyde, and acetaldehyde had the strongest indoor 

source strengths with the estimated median values of 3.9 and 2.6 mg h(-1), 

respectively. Hexaldehyde also had large indoor source strengths with a median of 

0.56 mg h(-1). Acetone had the largest variations in indoor source strengths 

ranging from undetected to 14 mg h(-1). The medians of the estimated indoor 

source strengths were 0.15 mg h(-1) for propionaldehyde, 0.18 mg h(-1) for 

glyoxal, 0.17 mg h(-1) for methylglyoxal, and 0.23 mg h(-1) for benzaldehyde. 

Acrolein and crotonaldehyde had the weakest indoor source strengths with no 

indoor sources detected in the majority of the RIOPA homes that were selected to 

have only nonsmoker residents. Consistent with the indoor source strength results, 

our estimated outdoor contributions to indoor concentrations were low for 

formaldehyde. In contrast, more than 90% of the indoor concentrations for 

acrolein and crotonaldehyde were from outdoor sources. The outdoor 

contributions to indoor concentrations for acetone, propionaldehyde, 

benzaldehyde, glyoxal, and methylglyoxal ranged from 10 to 90% across the 

RIOPA homes, suggesting that both indoor and outdoor sources had contributions 

to indoor concentrations of these compounds. (c) 2006 Elsevier Ltd. All rights 

reserved. 

Liu, W. L., J. F. Zhang, et al. (2003). "Mosquito coil emissions and health implications." 

Environmental Health Perspectives 111(12): 1454-1460. 

 Burning mosquito cods indoors generates smoke that can control mosquitoes 

effectively. This practice is currently used in numerous households in Asia, 

Africa, and South America. However, the smoke may contain pollutants of health 

concern. We conducted the present study to characterize the emissions from four 

common brands of mosquito coils from China and two common brands from 

Malaysia. We used mass balance equations to determine emission rates of fine 

particles (particulate matter < 2.5 pm in diameter; PM2.5), polycyclic aromatic 

hydrocarbons (PAHs), aldehydes, and ketones. Having applied these measured 

emission rates to predict indoor concentrations under realistic room conditions, 

we found that pollutant concentrations resulting from burning mosquito coils 

could substantially exceed health-based air quality standards or guidelines. Under 
2-98

the same combustion conditions, the tested Malaysian mosquito coils generated 

more measured pollutants than did the tested Chinese mosquito coils. We also 

identified a large suite of volatile organic compounds, including carcinogens and 

suspected carcinogens, in the coil smoke. In a set of experiments conducted in a 

room, we examined the size distribution of particulate matter contained in the coil 

smoke and found that the particles were ultrafine and fine. The findings from the 

present study suggest that exposure to the smoke of mosquito coils similar to the 

tested ones can pose significant acute and chronic health risks. For example, 

burning one mosquito coil would release the same amount of PM2.5 mass as 

burning 75-137 cigarettes. The emission of formaldehyde from burning one coil 

can be as high as that released from burning 51 cigarettes.

Lu, H. X., S. Wen, et al. (2006). "Indoor and outdoor carbonyl compounds and BTEX in 

the hospitals of Guangzhou, China." Science of the Total Environment 368(2-3): 574-

584. 

 Indoor and outdoor concentration levels of 21 carbonyl compounds and five 

BTEX (benzene, toluene, ethylbenzene and xylenes) were measured in four 

hospitals of Guangzhou from 2nd January to 20th March 2004. Samples were 

collected in five consecutive daytimes for each hospital. Among most of the 

samples, acetone was the most abundant carbonyl, followed by acetaldehyde, 2-

butanone or formaldehyde. Toluene was the most abundant BTEX and the others 

were at similar levels. The relatively higher acetone concentrations might have 

resulted from the high level of background in Guangzhou area due to emission of 

the factories and LPG-fuel vehicles, and also for the special weather conditions 

during sampling time. The high concentration of acetaldehyde, which was even 

higher than that of formaldehyde, might be resulted from the wide use of ethanol 

in hospital. The partial oxidation of ethanol may form acetaldehyde. The indoor 

concentrations of carbonyls and BTEX were found a little higher than their 

outdoor counterparts with only a few exceptions, which showed the 

anthropogenic sources for these compounds. The low correlations between most 

carbonyls and BTEX concentrations might be caused by their complex sources. 

Finally, the human exposure levels of formaldehyde and acetaldehyde in hospitals 
2-99

are discussed. (c) 2006 Elsevier B.V. All rights reserved. 

Lv, P., Z. Tang, et al. (2007). "Recognizing indoor formaldehyde in binary gas mixtures 

with a micro gas sensor array and a neural network." Measurement Science & 

Technology 18(9): 2997-3004. 

 Low-concentration formaldehyde (HCHO) together with 

ethanol/toluene/acetone/alpha-pinene (as an interference gas of HCHO) is 

detected with a micro gas sensor array, composed of eight tin oxide (SnO2) thin 

film gas sensors with Au, Cu, Pt or Pd metal catalysts. The characteristics of the 

multi- dimensional signals from the eight sensors are evaluated. A multilayer 

neural network with an error backpropagation ( BP) learning algorithm, plus the 

principal component analysis ( PCA) technique, is implemented to recognize 

these indoor volatile organic compounds ( VOC). The results show that the micro 

gas sensor array, plus the multilayer neural network, is very effective in 

recognizing 0.06 ppm HCHO in single gas component and in binary gas mixtures, 

toluene/ethanol/alpha-pinene with small relative error. 

Maddalena, R., M. Russell, et al. (2008). Aldehyde and other volatile organic chemical 

emissions in four fema temporary housing units – Final report Ernest Orlando Lawrence 

Berkeley National Laboratory (LBNL-254E), Environmental Energy Technologies 

Division 

 As part of an ongoing effort with the U.S. Centers for Disease Control and 

Prevention (CDC), Lawrence Berkeley National Laboratory (LBNL) entered into 

an interagency agreement with CDC to help identify mitigation strategies for 

reducing indoor emissions of volatile organic compounds (VOCs) including 

formaldehyde in Federal Emergency Management Administration (FEMA) 

temporary housing units (THUs)1. Four unoccupied FEMA THUs were studied to 

assess their indoor emissions of VOC including formaldehyde. Indoor 

measurement of whole-THU VOC and aldehyde emission factors (μg h-1 per m2 

of floor area) for each of the four THUs were made at FEMA’s Purvis Mississippi 

staging yard using a mass balance approach. 

 Measurements were made in the morning, and again in the afternoon in 
2-100

each THU. Steady-state indoor formaldehyde concentrations ranged from 378 μg 

m-3 (0.31ppm) to 632 μg m-3 (0.52 ppm) in the morning, and from 433 μg m-3 

(0.35 ppm) to 926 μg m-3 (0.78 ppm) in the afternoon. THU air exchange rates 

ranged from 0.15 h-1 to 0.39 h-1. A total of 45 small (approximately 0.025 m2) 

samples of surface material, 16 types, were collected directly from the four THUs 

and shipped to Lawrence Berkeley Laboratory. The material samples were 

analyzed for VOC and aldehyde emissions in small stainless steel chambers using 

a standard, accurate mass balance method. Quantification methods for the VOCs 

included high performance liquid chromatography for formaldehyde and 

acetaldehyde, ion chromatography for the acetic acid, and gas chromatographymass spectrometry for the remaining VOCs. Material specific emission factors 

(μg h-1 per m2 of material) were quantified. Approximately 80 unique VOCs 

were initially identified in the THU field samples, of which forty-five were 

quantified either because of their toxicological significance or because their 

concentrations were high. Whole-trailer and material specific emission factors 

were calculated for 33 compounds. The THU emission factors and those from 

their component materials were compared against those measured in other types 

of housing and the materials used in their construction. Whole THU emission 

factors for most VOCs were similar to those from comparative housing. The three 

exceptions were large emissions of formaldehyde, acetic acid, TMPD-DIB (a 

common plasticizer in vinyl products), and somewhat elevated emission of 

phenol. Of these compounds, formaldehyde was the only one with toxicological 

significance at the observed concentrations. Whole THU formaldehyde emissions 

ranged from 173 to 266 μg m-2 h-1 in the morning and 257 to 347 μg m-2 h-1 in 

the afternoon. Median formaldehyde emissions in previously studied site-built and 

manufactured homes were 31 and 45 μg m-2 h-1, respectively. Only one of the 

composite wood materials that was tested appeared to exceed the US Department 

of Housing and Urban Development (HUD) formaldehyde emission standard for 

new material but several of the materials exceeded if the decline in emission with 

aging is considered. The high loading factor (material surface area divided by 

THU volume) of composite wood products in the THUs and the low fresh air 

exchange relative to the material surface area may be responsible for the 
2-101

excessive concentrations observed for some of the VOCs and formaldehyde. 

Maddalena, R., M. Russell, et al. (2009). "Formaldehyde and Other Volatile Organic 

Chemical Emissions in Four FEMA Temporary Housing Units." Environmental Science 

& Technology 43(15): 5626-5632. 

 Indoor concentrations of 33 volatile organic chemicals were measured in four 

unoccupied temporary housing units (THUS) belonging to the U.S. Federal 

Emergency Management Administration (FEMA). The highest level contaminants 

in the THUS include formaldehyde, acetic acid, and 2,2,4-trimethyl-1,3-

pentanediol diisobutyrate (TXIB) with median concentrations of 440, 425, and 36 

ppb, respectively. A number of volatile organic compounds (VOCs) were higher 

than published concentrations in other dwellings, but whole THU emission factors 

for most chemicals were either lower than or similar to values reported for newly 

constructed homes. However, several chemicals exceeded previously measured 

new building emission rates by over a factor of 5. Materials were collected from 

the THUS, and emission factors were determined using small chambers to 

identify the potential source of indoor contaminants. The individual materials 

were grouped by material type, and emissions were used to derive exposure 

concentrations for comparison to reference values. Using material loading factors 

and ventilation rates that are relevant to the trailers, all of the material types we 

tested had at least two chemicals (formaldehyde and nonanal)with derived 

concentrations in excess of chronic reference exposure levels or odor thresholds. 

The extensive use of composite wood products, sealants, and vinyl coverings, 

combined with the low air exchange rates relative to material surface areas, may 

explain the high concentrations of some VOCs and formaldehyde. 

Mendell, M. J. (2007). "Indoor residential chemical emissions as risk factors forrespiratory and allergic effects in children: a review." Indoor Air 17(4): 259-277. 

 Most research into effects of residential exposures on respiratory health has 

focused on allergens, moisture/mold, endotoxin, or combustion products. A 

growing body of research from outside the US; however, has associated chemical 

emissions from common indoor materials with risk of asthma, allergies, and 
2-102

pulmonary infections. This review summarizes 21 studies in the epidemiologic 

literature on associations between indoor residential chemical emissions, or 

emission-related materials or activities, and respiratory health or allergy in infants 

or children. Associations, some strong, were reported between many risk factors 

and respiratory or allergic effects. Risk factors identified most frequently included 

formaldehyde or particleboard, phthalates or plastic materials, and recent painting. 

Findings for other risk factors, such as aromatic and aliphatic chemical 

compounds, were limited but suggestive. Elevated risks were also reported for 

renovation and cleaning activities, new furniture, and carpets or textile wallpaper. 

Reviewed studies were entirely observational, limited in size, and variable in 

quality, and specific risk factors identified may only be indicators for correlated, 

truly causal exposures. Nevertheless, overall evidence suggests a new class of 

residential risk factors for adverse respiratory effects, ubiquitous in modern 

residences, and distinct from those currently recognized. It is important to confirm 

and quantify any risks, to motivate and guide necessary preventive actions. 

Mentese, S. and G. Gullu (2006). "Variations and sources of formaldehyde levels in 

residential indoor air in Ankara, Turkey." Indoor and Built Environment 15(3): 273-281. 

 A study in Ankara was performed to examine any association between 

formaldehyde levels and housing characteristics. This involved collection of 309 

air samples which were analysed using a colorimetric method. Formaldehyde 

concentrations ranged from 2.34 mu g(.)m(-3) to 866.22 mu g(.)m(-3) (median, 

71.48 mu g(.)m(-3)). Formaldehyde levels were elevated in homes inhabited by at 

least one smoker and were correlated with indoor and outdoor temperature, age of 

house and density of plywood furniture. Sufficient sample numbers were 

collected to allow the data to be statistically divided into five daytime periods. 

These data suggest that the formaldehyde concentrations were generally slightly 

higher in the afternoon. A simple mathematical model involving smoking activity 

has been developed for estimating the formaldehyde decay rates for two rooms in 

one of the typical background homes. When the windows and doors were closed, 

the formaldehyde concentrations in indoor air decreased within 10h to 

background concentrations, although this change depended on the room volume 
2-103

and the natural air exchange rate. 

Molhave, L., L. E. Sparks, et al. (1996). "The Danish twin apartment study .2. 

Mathematical modeling of the relative strength of sources of indoor air pollution." Indoor 

Air-International Journal of Indoor Air Quality and Climate 6(1): 18-30. 

 This study deals with the modeling of air pollution in apartments from laboratory 

measurements of source strengths, using formaldehyde and Total Volatile Organic 

Compounds (TVOCs) as model pollutants. The sources in two test apartments 

were grouped into two: building-related sources and occupant-related sources. 

The measured source strengths and ventilation rates were used for the prediction 

of concentrations expected in the apartments. These predictions were compared to 

measurements in the apartment over 12 months. The conclusions were that the 

model predictions based on emission rates measured in the laboratory can be used 

to predict the long-term concentration of the two model pollutants in the 

apartments. Considering the measured differences in ventilation between the 

apartments, an occupant emission rate of between 0.2 and 0.3 mg/h/kg body 

weight could be estimated. Based on previous suggested limits of acceptable 

exposures of humans to VOCs, an acceptable average emission rate of VOCs 

from building materials in general was estimated to be about 30 mu g/m(2)/h. The 

modeling showed that during the first 200 days, building materials dominated the 

emissions. After this, sources relating to the occupants dominated. On average 

about half of the VOC pollution originated from the building materials. 

Morrison, G. C., W. W. Nazaroff, et al. (1998). "Indoor air quality impacts of ventilation 

ducts: Ozone removal and emissions of volatile organic compounds." Journal of the Air 

& Waste Management Association 48(10): 941-952. 

 The concentrations of contaminants in the supply air of mechanically ventilated 

buildings may be altered by pollutant emissions from and interactions with duct 

materials. We measured the emission rate of volatile organic compounds (VOCs) 

and aldehydes from materials typically found in ventilation ducts. The emission 

rate of VOCs per exposed surface area of materials was found to be low for some 

duct liners, but high for duct sealing caulk and a neoprene gasket. For a typical 
2-104

duct, the contribution to VOC concentrations is predicted to be only a few percent 

of common indoor levels. We exposed selected materials to similar to 100-ppb 

ozone and measured VOC emissions. Exposure to ozone increased the emission 

rates of aldehydes from a duct liner, duct sealing caulk, and neoprene gasket. The 

emission of aldehydes from these materials could increase indoor air 

concentrations by amounts that are as much as 20% of odor thresholds. We also 

measured the rate of ozone uptake on duct liners and galvanized sheet metal to 

predict how much ozone might be removed by a typical duct in ventilation 

systems. For exposure to a constant ozone mol fraction of 37 ppb, a lined duct 

would initially remove similar to 9% of the ozone, but over a period of 10 days 

the ozone removal efficiency would diminish to less than 4%. In an unlined duct, 

in which only galvanized sheet metal is exposed to the airstream, the removal 

efficiency would be much lower, similar to 0.02%. Therefore, ducts in ventilation 

systems are unlikely to be a major sink for ozone. 

Mui, K. W., W. Y. Chan, et al. (2007). "Fungi - an indoor air quality assessment 

parameter for air-conditioned offices." Building Services Engineering Research & 

Technology 28(3): 265-274. 

 Representative assessment parameters are proposed for indoor air quality (IAQ) 

audit in various strategies and guidelines.' In Hong Kong, assessment of indoor 

airborne fungi is not incorporated in many IAQ audits of air-conditioned offices, 

although the exposure to airborne fungi could cause a variety of adverse health 

effects. An IAQ assessment for a local office will audit 12 parameters, including 

air temperature, relative humidity, air velocity, carbon dioxide, carbon monoxide, 

respirable suspended particulates, nitrogen dioxide, ozone, formaldehyde, total 

volatile organic compounds, radon, and airborne bacteria. This paper reviews 

recent studies of the indoor airborne fungi levels and IAQ assessments in some 

air-conditioned offices of Hong Kong and evaluates the contribution of the 

airborne fungi to an unsatisfactory IAQ in the environment. The unsatisfactory 

rates regarding the assessment parameters were evaluated using the Monte Carlo 

simulations with measured data in Hong Kong Offices. In particular, the impact of 

selecting representative IAQ assessment parameters was examined against an 
2-105

express assessment protocol (EAP), which assessed some dominant contributors 

of unsatisfactory IAQ.(2) The results reported that the three top ranked 

contributors for unsatisfactory IAQ were total volatile organic compounds 

(TVOC), indoor airborne fungi count (AFC) and airborne bacteria count (ABC) 

for air-conditioned offices of Hong Kong. 

 Practical applications: This study has shown that the assessments of 

airborne fungi levels in office environment is an important issue and further 

investigations for the airborne fungi in the IAQ audits were thus recommended. 

The results of this study could be a useful source of reference for policymakers in 

evaluation of an effective IAQ assessment protocol with some representative IAQ 

assessment parameters. 

Nazaroff, W. W. and C. J. Weschler (2004). "Cleaning products and air fresheners: 

exposure to primary and secondary air pollutants." Atmospheric Environment 38(18): 

2841-2865. 

 Building occupants, including cleaning personnel, are exposed to a wide variety 

of airborne chemicals when cleaning agents and air fresheners are used in 

buildings. Certain of these chemicals are listed by the state of California as toxic 

air contaminants (TACs) and a subset of these are regulated by the US federal 

government as hazardous air pollutants (HAPs). California's Proposition 65 list of 

species recognized as carcinogens or reproductive toxicants also includes 

constituents of certain cleaning products and air fresheners. In addition, many 

cleaning agents and air fresheners contain chemicals that can react with other air 

contaminants to yield potentially harmful secondary products. For example, 

terpenes can react rapidly with ozone in indoor air generating many secondary 

pollutants, including TACs such as formaldehyde. Furthermore, ozone-terpene 

reactions produce the hydroxyl radical, which reacts rapidly with organics, 

leading to the formation of other potentially toxic air pollutants. Indoor reactive 

chemistry involving the nitrate radical and cleaning-product constituents is also of 

concern, since it produces organic nitrates as well as some of the same oxidation 

products generated by ozone and hydroxyl radicals. 

 Few studies have directly addressed the indoor concentrations of TACs 
2-106

that might result from primary emissions or secondary pollutant formation 

following the use of cleaning agents and air fresheners. In this paper, we combine 

direct empirical evidence with the basic principles of indoor pollutant behavior 

and with information from relevant studies, to analyze and critically assess air 

pollutant exposures resulting from the use of cleaning products and air fresheners. 

Attention is focused on compounds that are listed as HAPs, TACs or Proposition 

65 carcinogens/reproductive toxicants and compounds that can readily react to 

generate secondary pollutants. The toxicity of many of these secondary pollutants 

has yet to be evaluated. The inhalation intake of airborne organic compounds 

from cleaning product use is estimated to be of the order of 10 mg d(-1) person(-

1) in California. More than two dozen research articles present evidence of 

adverse health effects from inhalation exposure associated with cleaning or 

cleaning products. Exposure to primary and secondary pollutants depends on the 

complex interplay of many sets of factors and processes, including cleaning 

product composition, usage, building occupancy, emission dynamics, transport 

and mixing, building ventilation, sorptive interactions with building surfaces, and 

reactive chemistry. Current understanding is sufficient to describe the influence of 

these variables qualitatively in most cases and quantitatively in a few. (C) 2004 

Elsevier Ltd. All rights reserved. 

Nemli, G. and I. Ozturk (2006). "Influences of some factors on the formaldehyde content 

of particleboard." Building and Environment 41(6): 770-774. 

 In this study, effects of specific gravity (SG), shelling ratio, wood species, and 

pressure on the formaldehyde content, physical (SG and thickness swelling (TS)), 

and mechanical properties (modulus of rupture (MOR), modulus of elasticity 

(MOE), and internal bond (IB) strength) of particleboard were examined. The best 

manufacturing parameters were determined for E-1 grade particleboard 

manufacturing from urea formaldehyde (UF) adhesive. Based on the findings of 

this study, increasing of SG, shelling ratio, and pressure increased the 

formaldehyde content. Particleboard made from particles consisting higher 

amount of beech particles had lower formaldehyde content than that of panel from 

particles consisting higher amount of pine particles. (C) 2005 Elsevier Ltd. All 
2-107

rights reserved. 

Neuhaus, T., R. Oppl, et al. (2008). "Formaldehyde emissions from mineral wool in 

building constructions into indoor air." Indoor Air (Denmark). 

 One stone wool insulation product containing phenol-urea-formaldehyde binder 

was tested for the emissions of formaldehyde and volatile organic compounds 

(VOC) simulating real use in roof constructions. Results are compared with 

earlier published results from tests with wall constructions and to international 

indoor air limit values. Possible future handling by using reductions factors when 

testing pure mineral wool products without constructions is discussed. 

Parent, D., S. Stricker, et al. (1998). "Optimum ventilation and air flow control in 

buildings." Energy and Buildings 27(3): 239-245. 

 The LTEE laboratory of Hydro-Quebec, in collaboration with Canada Mortgage 

and Housing conducted an indoor air quality study involving 30 single familydetached houses heated with electric baseboard heaters in the vicinity of TroisRivieres during the 1993-94 heating season. The houses were selected according 

to the measured air leakage at 50 Pa so as to have a sample distribution similar to 

the distribution of air leakage of houses in the province of Quebec. The 'source 

strength' of several air pollutants were calculated from measurements of ambient 

pollutant levels and total ventilation during a 2 week test. In addition: the indoor 

CO2 and humidity levels were recorded in eight of the houses continuously 

during the heating season. Model studies using the measured pollutant source 

strengths and measured equivalent leakage areas of the buildings indicated that 

the recommended health guidelines for airborne respirable solid particles (RSP's), 

CO2 and formaldehyde are exceeded during periods of low total ventilation, 

coinciding with mild outdoor temperatures and low wind conditions. With the 

room occupied and the door closed, CO2 levels in the bedroom increased steadily 

during the night until morning, when the door was opened, to levels in excess of 

3500 ppm with one person and in excess of 4500 ppm with two persons. Various 

different methods of ventilating some of the houses were tested, including quiet 

replacement exhaust fans, mixing fans for indoor air and a fresh air intake and 
2-108

mixing system. The effects of operating various air handling systems were 

monitored by keeping track of indoor CO2 and relative humidity in the master 

bedroom and occupancy in person-hours per day. (C) 1998 Elsevier Science S.A. 

ALI rights reserved. 

Park, J. S. and K. Ikeda (2004). "Exposure to the mixtures of organic compounds in 

homes in Japan." Indoor Air 14(6): 413-420. 

 The aim of the study reported herein was to characterize occupants' simultaneous 

exposure to mixtures of organic compounds in homes. Statistical distributions for 

concentrations of 28 organic compounds (17 VOCs and 11 aldehydes) measured 

in 1417 homes were generated to analyze concentration distributions. Three 

candidate distributions were identified for fitting the measured data: log-normal, 

exponential and gamma distributions. It appears from the results of fitting tests 

that gamma distributions are capable of representing 28 compound 

concentrations. Probability distributions show that formaldehyde and 

acetaldehyde ranged from 25 to 220 mug/m(3) at 90% probabilities and most 

VOCs ranged from 3 to 80 mug/m(3) at 90% probabilities. In order to 

characterize the occupant's exposure to the mixtures, the joint probability 

distributions of organic compounds were generated from the best-fitted 

distributions of individual compounds under the assumption that concentrations of 

organic compounds are mutually independent in homes. These joint distributions 

provided the statistical data for characterizing the occupant's exposure to the 

mixtures of organic compounds in homes. 

Park, J. S. and K. Ikeda (2006). "Variations of formaldehyde and VOC levels during 3 

years in new and older homes." Indoor Air 16(2): 129-135. 

 Indoor air organic compounds were continuously monitored during 3 years in new 

and older homes which were voluntarily selected throughout countries. The levels 

of volatile organic compounds (VOCs) in the new homes decreased markedly 

after 1 year, and steady emissions of VOCs were obtained in the initial months. 

Formaldehyde and a-pinene related to wooden materials need a longer flushing 

period than the other compounds in the new homes. The levels of the indoor air 
2-109

organic compounds in the older homes showed no significant fluctuation during 

the 3-year period. Decreases of the indoor-produced compounds in the new homes 

did not depend upon the ventilation systems. The results indicate that the indoorproduced compounds in the new homes will be more influenced by the aging 

decreases of emission source strengths than ventilation systems. The quantitative 

information on the trend of the indoor air organic compound levels will be useful 

for the risk assessment of indoor exposure to those compounds, and also for 

Japanese IAQ guidelines. 

Petrick, L. and Y. Dubowski (2009). "Heterogeneous oxidation of squalene film by ozone 

under various indoor conditions." Indoor Air 19(5): 381-391. 

 P>The effects of indoor conditions (ozone concentration, temperature, relative 

humidity (RH), and the presence of NOx) on heterogeneous squalene oxidation 

were studied with Attenuated Total Reflectance-Fourier Transform Infrared 

spectroscopy. The heterogeneous kinetics of squalene-ozone reaction revealed a 

pseudo-first-order reaction rate constant of 1.22 x 10-5/s at [O-3] = 40 ppb. 

Oxidation kinetics were insensitive to temperature over the range of 24-58 +/- 2 

degrees C as well as to RH and presence of NOx. Products, however, were 

affected by the environmental parameters. As temperature was increased, fewer 

surface products and more low molecular weight gaseous products were observed. 

Lower air exchange rates also enhanced gas phase reactions, allowing for 

formation of secondary gas phase products. As RH increased, there was a shift in 

product distribution from ketones to aldehydes, and the presence of NOx during 

squalene ozonolysis resulted in the formation of nitrated oxidation products. 

Identified surface products included 6-methyl-5-hepten-2-one, geranyl acetone, 

and long chain ketones and aldehydes, while gas phase products included 

formaldehyde, acetone, 4-oxopentanal (4-OPA), glyoxal, and pyruvic 

acid.Practical Implications 

 Heterogeneous oxidation of squalene resulted in surface products 

including long chain aldehydes and ketones, and gas phase products including 

formaldehyde, a known human carcinogen (IARC 2006), and bicarbonyl 

compounds like: 4-oxopentanal (4-OPA), glyoxal, and pyruvic acid that are 
2-110

characterized as asthma triggers and sensitizers (Anderson et al., 2007; Jarvis et 

al., 2005). In addition, ozonolysis experiments in the presence of NOx showed the 

formation of nitrated surface oxidation products. Such nitrated products may have 

higher mutagenicity, carcinogenicity, or allergenic potential than their nitrate free 

counterparts (Franze et al., 2005; Pitts, 1983). Kinetic studies determined that at 

moderate ozone levels of 40 ppb (Uhde and Salthammer, 2007), and an estimated 

skin surface density of 4 x 1015 molecules/cm2, surface reaction would lead to a 

minimum product formation flux of 4 x 1010 molecules cm2/s. As squalene is 

naturally occurring and continually produced by the human body, its 

concentration in the indoor environment cannot be controlled. However, this 

study highlights the importance of regulating air exchange rate, temperature, and 

ozone level in the indoor environment on the formation of potentially harmful or 

irritating squalene oxidation products. 

Petronella, S. A., R. Thomas, et al. (2005). "Clearing the air: A model for investigating 

indoor air quality in Texas schools." Journal of Environmental Health 67(10): 35-42. 

 This pilot project focused on the assessment of indoor air quality at a local high 

school in Galveston, Texas, using methods based on guidelines for the U.S. 

Environmental Protection Agency's Indoor Air Quality Tools for Schools 

program. Tools for Schools, developed for evaluating and ensuring acceptable air 

quality for schools, takes a low-cost, minimal-involvement, primarily educational 

approach. The authors also compared the findings from this approach with the 

results of an air-sampling program. The overall goal was to determine 9 use of 

Tools for Schools was sufficient to identify conditions with the potential to cause 

adverse health effects. The primary objectives were to 1) establish an indoor air 

quality committee for the school to implement Took for Schools assessments and 

management strategies, 2) collect air quality data in high-risk areas identified 

within the school by the indoor air quality committee, 3) collect outdoor air 

quality data at or in close proximity to the school, and 4) develop methods and 

instruments for assessing environmental risks associated with daily school 

attendance. Data were gathered on levels of formaldehyde and other volatile 

organic compounds (VOCs), ozone, particulate matter (PM10), mold, relative 
2-111

humidity, and temperature. Data values for each sampled pollutant were 

compared with federal standards, recommended values established by the 

American Conference of Governmental Industrial Hygienists for non-industrial 

populations, and effects screening levels developed by the Texas Commission on 

Environmental Quality. Levels of all VOCs except formaldehyde were found to 

be well within guidelines, as were ozone and particulate-matter levels. Mold, 

however, was widespread, including both common species and species associated 

with allergy and asthma, such as Aspergillus and Alternaria. In general, Tools for 

Schools provides an excellent foundation for a school indoor air quality program, 

although the authors did find it necessary to streamline data collection and did 

find that mold with the potential for adverse health effects was present, albeit not 

visible in some areas. 

Que, Z. L., T. Furuno, et al. (2007). "Evaluation of three test methods in determination of 

formaldehyde emission from particleboard bonded with different mole ratio in the ureaformaldehyde resin." Building and Environment 42(3): 1242-1249. 

 The use of urea-formaldehyde (UF) resins with lower contents of free 

formaldehyde in the board industry has led to products with very low emissions of 

formaldehyde. In this study, a detailed account is given of how UF resins with 

different mole ratios of formaldehyde to urea within the range of 0.97-1.27 

influence the formaldehyde emission. In order to evaluate simpler laboratory 

methods for determining the formaldehyde emission from particleboard, the 

desiccator (JIS A 5908, 2003) and the EN 120 (European Standard, 199 1) have 

been compared with the I m 3 chamber method SS 270236 (Swedish Standard of 

determining formaldehyde emission with chamber test, 1988). Good relationships 

were obtained between the methods studied with correlation coefficients of > 0.9. 

The value of formaldehyde emission decreased linearly with the mole ratio of 

formaldehyde to urea down to 1.05 where the effect smoothed out. The effect on 

the formaldehyde emission of temperature and storage time for tested boards also 

was studied. The heat treatment lowered the perforator value with resins that had 

mole ratios equal to or higher than 1.15, at the two lowest mole ratios 0.97 and 

1.01, there was a tendency for the heat treatment to increase the perforator value. 
2-112

After the boards were stored for 6 months at 23 degrees C and 50% RH, the 

perforator values were unchanged or negligibly changed with the lower mole 

ratios and there was a more pronounced change with a'higher mole ratio of 1.27. 

(c) 2005 Elsevier Ltd. All rights reserved. 

Que, Z. L., T. Furuno, et al. (2007). "The mathematical model for the formaldehyde 

emission from wood-based board in room." Building and Environment 42(6): 2321-2324. 

 A mathematical model which describes the influence of various parameters on 

formaldehyde concentration in the atmosphere of a room containing wood-based 

boards was developed. The physical meanings and measuring methods of the 

parameters of the model are also discussed. Based on this model, two indices for 

commenting the formaldehyde emission process of wood-based boards are 

proposed, and inequality estimation for the formaldehyde content of wood-based 

boards at any moment and a time estimation which shows when the room satisfies 

the environment quality standard are also given. (c) 2006 Elsevier Ltd. All rights 

reserved. 

Risholm-Sundman, M., A. Larsen, et al. (2007). "Formaldehyde emission - Comparison 

of different standard methods." Atmospheric Environment 41(15): 3193-3202. 

 The emission of formaldehyde is an important factor in the evaluation of the 

environmental and health effects of woodbased board materials. This article gives 

a comparison between commonly used European test methods: chamber method 

[EN 717-1, 2004. Wood-based panels-determination of formaldehyde release-Part 

1: formaldehyde emission by the chamber method. European Standard, October 

2004], gas analysis method [EN 717-2, 1994. Wood-based panels-determination 

of formaldehyde release-Part 2: formaldehyde release by the gas analysis method, 

European Standard, November 1994], flask method [EN 717-3, 1996. Woodbased panels-determination of formaldehyde release-Part 3: formaldehyde release 

by the flask method, European Standard, March 1996], perforator method [EN 

120, 1993. Wood based panels-determination of formaldehyde content-extraction 

method called perforator method, European Standard, September 1993], Japanese 

test methods: desiccator methods [JIS A 1460, 2001. Building boards. 
2-113

Determination of formaldehyde emission-desiccator method, Japanese Industrial 

Standard, March 2001 and JAS MAFF 233, 2001] and small chamber method [JIS 

A 1901, 2003. Determination of the emission of volatile organic compounds and 

aldehydes for building products-small chamber method, Japanese Industrial 

Standard, January 2003], for solid wood, particleboard, plywood and medium 

density fiberboard. 

 The variations between the results from different methods can partly be 

explained by differences in test conditions. Factors like edge sealing, conditioning 

of the sample before the test and test temperature have a large effect on the final 

emission result. The Japanese limit for F**** of 0.3 mg 1(-1) (in desiccator) for 

particleboards was found to be equivalent to 0.04 mg m(-3) in the European 

chamber test and 2.8 mg per 100 g in the perforator test. The variations in interlaboratory tests are much larger than in intra-laboratory tests; the coefficient of 

variation is 16% and 6.0% for the chamber method, 25% and 3.5% for the gas 

analysis method and 15% and 5.2% for the desiccator method. (C) 2006 Elsevier 

Ltd. All rights reserved. 

Rumchev, K. B., J. T. Spickett, et al. (2002). "Domestic exposure to formaldehyde 

significantly increases the risk of asthma in young children." European Respiratory 

Journal 20(2): 403-408. 

 Concern has arisen in recent years about indoor air pollution as a risk factor for 

asthma. Formaldehyde exposure vas examined in relation to asthma among young 

children (between 6 months and 3 yrs old) in a population-based control study 

carried out in Perth, Western Australia, between 1997-1999. An association 

between exposure to formaldehyde and asthma in young children has been 

suggested. Cases (n=88), whose parents were recruited at Princess Margaret 

Hospital Accident and Emergency Dept (Perth, Western Australia), were children 

discharged with asthma as the primary diagnosis. Controls (n=104), who were 

children in the same age group without asthma diagnosed by a doctor, were 

identified from birth records through the Health Dept of Western Australia (Perth, 

Western Australia). Health outcomes for the children were studied using a 

respiratory questionnaire and skin-prick tests. Formaldehyde, average temperature 
2-114

and relative humidity were measured on two occasions, winter (July-September 

1998) and summer (December 1998-March 1999) in the child's bedroom and in 

the living room. 

 The study found seasonal differences in formaldehyde levels in the 

children's bedrooms and living rooms with significantly greater formaldehyde 

exposure during the summer period for case and control subjects. The generalised 

estimating equation model showed that children exposed to formaldehyde levels 

of greater than or equal to60 mug.m(-3) are at increased risk of having asthma. 

The results suggest that domestic exposure to formaldehyde increases the risk of 

childhood asthma. 

Salthammer, T. and F. Fuhrmann (2007). "Photocatalytic surface reactions on indoor wall 

paint." Environmental Science & Technology 41(18): 6573-6578. 

 The reduction of indoor air pollutants by air cleaning systems has received 

considerable interest, and a number of techniques are now available, So far, the 

method of photocatalysis was mainly applied by use of titanium dioxide (TiO2) in 

flow reactors under UV light of high intensity. Nowadays, indoor wall paints are 

equipped with modified TiO2 to work as a catalyst under indoor daylight or 

artificial light. In chamber experiments carried out under indoor related conditions 

it was shown that the method works for nitrogen dioxide with air exchange and 

for formaldehyde without air exchange at high concentrations. In further 

experiments with volatile organic compounds (VOCs), a small effect was found 

for terpenoids with high k(OH) rate constants. For other VOCs and carbon 

monoxide there was no degradation at all or the surface acted as a reversible sink. 

Secondary emissions from the reaction of paint constituents were observed on 

exposure to light. From the results it is concluded that recipes of photocatalytic 

wall paints need to be optimized for better efficiency under indoor conditions. 

Sax, S. N., D. H. Bennett, et al. (2004). "Differences in source emission rates of volatile 

organic compounds in inner-city residences of New York City and Los Angeles." J Expo 

Anal Environ Epidemiol 14 Suppl 1: S95-109. 

 The Toxics Exposure Assessment Columbia-Harvard (TEACH) Project 
2-115

characterized personal, indoor, and outdoor concentrations of a suite of volatile 

organic compounds (VOCs) for high school students living in New York City 

(NYC) and Los Angeles (LA). This paper presents the analysis of VOC 

measurements collected indoors and outdoors for 46 students' homes in NYC and 

for 41 students' homes in LA across two seasons. Dual-sorbent thermal desorption 

tubes were used for the collection of 15 VOCs and C(18) 2,4-

dinitrophenylhydrazine-coated cartridges were used for the collection of seven 

aldehydes. Air-exchange rates (AERs) were also measured using a 

perfluorocarbon tracer gas method. The AERs were lower in the winter in both 

cities, averaging 1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) in 

NYC in the summer and 2.5 h(-1) in LA in the fall. Higher AERs were generally 

associated with lower indoor-outdoor ratios with significant differences for the 

compounds with indoor sources, including chloroform, 1,4-dichlorobenzene, and 

formaldehyde. Using a mass-balance model to account for AER and other housing 

parameters, effective source emission rates (SER) were calculated for each 

compound. Based on I/O ratios and source emission rates, VOCs could be divided 

into: (1). indoor-source-influenced compounds, (2). those with contributions from 

both indoor and outdoor sources, and (3). those with mostly outdoor sources. 

Significant indoor sources were found for the following six compounds (mean 

emission rates presented): chloroform (0.11 mg/h), 1,4-dichlorobenzene (19 

mg/h), formaldehyde (5 mg/h), acetaldehyde (2 mg/h), benzaldehyde (0.6 mg/h), 

and hexaldehyde (2 mg/h). Although chloroform had variable I/O ratios across 

seasons, SERs, which accounted for AER, were similar in both cities for both 

seasons (e.g., LA means 0.12 and 0.11 mg/h in winter and fall, respectively). 

Formaldehyde had substantially higher indoor emission rates in the summer in 

NYC compared to winter (3.8 vs. 1.6 mg/h) but lower in the fall in LA compared 

to winter (4.3 vs. 5.0 mg/h). Uncertainty analysis determined that source strength 

calculations were not sensitive to measurement error for a subset of homes in LA. 

Sax, S. N., D. H. Bennett, et al. (2004). "Differences in source emission rates of volatile 

organic compounds in inner-city residences of New York City and Los Angeles." Journal 

of Exposure Analysis and Environmental Epidemiology 14: S95-S109. 
2-116

 The Toxics Exposure Assessment Columbia-Harvard (TEACH) Project 

characterized personal, indoor, and outdoor concentrations of a suite of volatile 

organic compounds (VOCs) for high school students living in New York City 

(NYC) and Los Angeles ( LA). This paper presents the analysis of VOC 

measurements collected indoors and outdoors for 46 students' homes in NYC and 

for 41 students' homes in LA across two seasons. Dual-sorbent thermal desorption 

tubes were used for the collection of 15 VOCs and C-18 2,4-

dinitrophenylhydrazine-coated cartridges were used for the collection of seven 

aldehydes. Air-exchange rates (AERs) were also measured using a 

perfluorocarbon tracer gas method. The AERs were lower in the winter in both 

cities, averaging 1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) in 

NYC in the summer and 2.5 h(-1) in LA in the fall. Higher AERs were generally 

associated with lower indoor-outdoor ratios with significant differences for the 

compounds with indoor sources, including chloroform, 1,4-dichlorobenzene, and 

formaldehyde. Using a mass-balance model to account for AER and other housing 

parameters, effective source emission rates (SER) were calculated for each 

compound. Based on I/O ratios and source emission rates, VOCs could be divided 

into: (1) indoor-source-influenced compounds, (2) those with contributions from 

both indoor and outdoor sources, and (3) those with mostly outdoor sources. 

Significant indoor sources were found for the following six compounds ( mean 

emission rates presented): chloroform (0.11 mg/h), 1,4-dichlorobenzene (19 

mg/h), formaldehyde (5 mg/h), acetaldehyde (2 mg/h), benzaldehyde (0.6 mg/h), 

and hexaldehyde (2 mg/h). Although chloroform had variable I/O ratios across 

seasons, SERs, which accounted for AER, were similar in both cities for both 

seasons (e.g., LA means 0.12 and 0.11 mg/h in winter and fall, respectively). 

Formaldehyde had substantially higher indoor emission rates in the summer in 

NYC compared to winter (3.8 vs. 1.6 mg/h) but lower in the fall in LA compared 

to winter (4.3 vs. 5.0 mg/h). Uncertainty analysis determined that source strength 

calculations were not sensitive to measurement error for a subset of homes in LA. 

Schupp, T., H. M. Bolt, et al. (2005). "Maximum exposure levels for xylene, 

formaldehyde and acetaldehyde in cars." Toxicology 206(3): 461-470. 
2-117

 Although millions of individuals are exposed to emissions from articles inside 

cars, relatively little has been published about possible adverse health effects and 

about exposure levels that can be considered safe or "acceptable". Xylene, 

formaldehyde and acetaldehyde represent typical examples of relevant volatile 

organic substances (VOC) released from articles inside cars. Recently, a concept 

for derivation of maximum exposure levels for volatile organic substances in cars 

has been published. In the present study we applied this concept to derive 

maximum exposure levels for xylene, formaldehyde and acetaldehyde and 

compared the resulting concentrations to exposure levels usually found inside of 

cars. We derived Short Term Exposure Levels Inside Automotive Vehicles 

(STELIA) of 29, 0.125 and 15.3 mg/m(3) for xylene, formaldehyde and 

acetaldehyde, respectively. These STELIAs should not be exceeded during shortterm exposures, for instance when starting a car that had been heated up during 

parking in the sun. Exposure Levels Inside Automotive Vehicles (ELIA, chronic) 

for chronic exposure to non-genotoxic substances were 8.8, 0.125 and 0.635 

mg/m(3) for systemic as well as 17.6, 0.125 and 1.7 mg/m(3) for local exposure to 

xylene, formaldehyde and acetaldehyde, respectively. Although, it is known that 

exposure limits for carcinogenic substances should be treated with caution, 

encouraged by the well documented threshold mechanisms we nevertheless 

derived ELIAs for Carcinogenic and Mutagenic Substances (ELIA, cm) resulting 

in 0.125 and 0.635 mg/m(3) for formaldehyde and acetaldehyde. If these ELIAs 

are matched against average concentrations of xylene, formaldehyde and 

acetaldehyde found in cars at 23 degreesC (1.22, 0.048 and 0.042 mg/m(3)), there 

is no reason for concern. With respect to STELIAs and extrapolated 

concentrations at 65 degreesC (14.7, 1.47 and 1.68 mg/m(3), for xylene, 

formaldehyde and acetaldehyde, respectively), however, a reduction of the 

concentration of formaldehyde may be necessary. (C) 2004 Elsevier Ireland Ltd. 

All rights reserved. 

Sekine, Y. and A. Nishimura (2001). "Removal of formaldehyde from indoor air by 

passive type air-cleaning materials." Atmospheric Environment 35(11): 2001-2007. 

 We have developed a board-like air-cleaning material consisting of activated 
2-118

carbon particles and manganese oxides, by which HCHO gas is decomposed into 

carbon dioxide even at room temperature. In this study, we investigated removal 

efficiencies of the air-cleaning board in a passive mode using a kinetic approach. 

First-order removal rate constant, k, corresponding to air change rate was 

characterized for the board as a function of the ratio of applied board area to space 

volume, S/V, and was found directly proportional to S/V with a slope of 25 at 25 

degreesC. The performance of the board was evaluated in a full-size laboratory 

with a constant gas generation. The board suppressed the increase of indoor 

HCHO concentration and the time course fitted to a theoretical curve. Then, field 

tests of the air-cleaning board were conducted in newly constructed multi-family 

houses in Japan from May 1998 to January 1999. The board not only reduced 

indoor HCHO concentration from 0.21 to 0.04 ppm for more than 7 months, but 

also enhanced the loss of HCHO gas from building materials in apartments. (C) 

2001 Elsevier Science Ltd. All rights reserved. 

Sexton, K., M. X. Petreas, et al. (1989). "Formaldehyde Exposures inside Mobile 

Homes." Environmental Science & Technology 23(8): 985-988. 

 An age-stratified random sample of 470 mobile homes was selected from among 

the more than 500000 in California. One-week, average indoor formaldehyde 

concentrations were measured during both the summer (July-August 1984) and 

the winter (February-March 1985) seasons. Results indicate that (1) formaldehyde 

concentrations were well-mixed inside the trailers over a 1-week period, (2) 

relatively little variation was observed in formaldehyde concentrations between 

summer and winter, (3) average 1-week formaldehyde values were in the range of 

0.07-0.09 ppm, and (4) formaldehyde levels appear to be decreasing inside mobile 

homes manufactured since about 1980, probably as a result of the increased use of 

low-formaldehyde-emitting building materials. Based on the 470 mobile homes in 

this study, 31% exceeded the maximum concentration of 0.1 ppm formaldehyde 

recommended by the American Society of Heating, Refrigerating, and Airconditioning Engineers (ASHRAE), the American Industrial Hygiene Association 

(AIHA), and the Environmental Protection Agency (EPA). 
2-119

Sherman, M. H. and A. T. Hodgson (2004). "Formaldehyde as a basis for residential 

ventilation rates." Indoor Air 14(1): 2-9. 

 Traditionally, houses in the US have been ventilated by passive infiltration in 

combination with active window opening. However in recent years, the 

construction quality of residential building envelopes has been improved to 

reduce infiltration, and the use of windows for ventilation also may have 

decreased due to a number of factors. Thus, there has been increased interest in 

engineered ventilation systems for residences. The amount of ventilation provided 

by an engineered system should be set to protect occupants from unhealthy or 

objectionable exposures to indoor pollutants, while minimizing energy costs for 

conditioning incoming air. Determining the correct ventilation rate is a complex 

task, as there are numerous pollutants of potential concern, each having poorly 

characterized emission rates, and poorly defined acceptable levels of exposure. 

One ubiquitous pollutant in residences is formaldehyde. The sources of 

formaldehyde in new houses are reasonably understood, and there is a large body 

of literature on human health effects. This report examines the use of 

formaldehyde as a means of determining ventilation rates and uses existing data 

on emission rates of formaldehyde in new houses to derive recommended levels. 

Based on current, widely accepted concentration guidelines for formaldehyde, the 

minimum and guideline ventilation rates for most new houses are 0.28 and 0.5 air 

changes per hour, respectively. 

Shinohara, N., Y. Kai, et al. (2009). "On-site passive flux sampler measurement of 

emission rates of carbonyls and VOCs from multiple indoor sources." Building and 

Environment 44(5): 859-863. 

 In indoor environments with high levels of air pollution, it is desirable to remove 

major sources of emissions to improve air quality. In order to identify the 

emission sources that contribute most to the concentrations of indoor air 

pollutants. we used passive flux samplers (PFSs) to measure emission rates of 

carbonyl compounds and volatile organic compounds (VOCs) from many of the 

building materials and furnishings present in a room in a reinforced concrete 

building in Tokyo, Japan. The emission flux of formaldehyde from a desk was 
2-120

high (125 mu g/m(2)/h). whereas fluxes from a door and flooring were low (21.5 

and 16.5 mu g/m(2)/h. respectively). The emission fluxes of toluene from the 

ceiling and the carpet were high (80.0 and 72.3 mu g/m(2)/h, respectively), 

whereas that from the flooring was low (9.09 mu g/m(2)/h). The indoor and 

outdoor concentrations of formaldehyde were 61.5 and 8.64 mu g/m(3), 

respectively, and those of toluene were 43.2 and 17.5 mu g/m(3), respectively. 

The air exchange rate of the room as measured by the perfluorocarbon tracer 

(PFT) method was 1.84/h. Taking into consideration the area of the emission 

sources, the carpet, ceiling, and walls were identified as the principal emission 

sources, contributing 24%, 20%, and 22% of the formaldehyde, respectively, and 

22%, 27%, and 14% of the toluene, respectively, assuming that the emission rate 

from every major emission sources could be measured. in contrast, the door, the 

flooring, and the desk contributed little to the indoor levels of formaldehyde 

(1.0%. 0.54%, and 4.1%, respectively) and toluene (2.2%, 0.31%, and 0.85%, 

respectively). (C) 2008 Elsevier Ltd. All rights reserved. 

Singer, B. C., A. T. Hodgson, et al. (2003). "Gas-phase organics in environmental 

tobacco smoke: 2. Exposure-relevant emission factors and indirect exposures from 

habitual smoking." Atmospheric Environment 37(39-40): 5551-5561. 

 Sorption of emitted gas-phase organic compounds onto material surfaces affects 

environmental tobacco smoke (ETS) composition and exposures indoors. We 

have introduced a new metric, the exposure relevant emission factor (EREF) that 

accounts for sorptive uptake and reemission to give the mass of individual ETS 

constituents available for exposure over a day in which smoking occurs. This 

paper describes month-long experiments to investigate sorption effects on EREFs 

and potential ETS exposures under habitual smoking conditions. Cigarettes were 

smoked in a 50-m(3) furnished room over a 3-h period 6-7 days per week, with 

continuous ventilation at 0.3, 0.6, or 2.1 h(-1). Organic gas concentrations were 

measured every few days over 4-h "smoking", 10-h "post-smoking" and 10-h 

"background" periods. Concentration patterns of volatile ETS components 

including 1,3-butadiene, benzene and acrolein were similar to those calculated for 

a theoretical non-sorbing tracer, indicating limited sorption. Concentrations of 
2-121

ETS tracers, e.g. 3-ethenylpyridine (3-EP) and nicotine, and lower volatility toxic 

air contaminants including phenol, cresols, and naphthalene increased as 

experiments progressed, indicating mass accumulation on surfaces and higher 

desorption rates. Daily patterns stabilized after week 2, yielding a steady daily 

cycle of ETS concentrations associated with habitual smoking. EREFs for sorbing 

compounds were higher under steady cycle versus single-day smoking conditions 

by similar to50% for 3-EP, and by 2-3 times for nicotine, phenol, cresols, 

naphthalene, and methylnaphthalenes. Our results provide relevant information 

about potential indirect exposures from residual ETS (non-smoker enters room 

shortly after smoker finishes) and from reemission, and their importance relative 

to direct exposures (non-smoker present during smoking). Under the conditions 

examined, indirect exposures accounted for a larger fraction of total potential 

exposures for sorbing versus non-sorbing compounds, and at lower versus higher 

ventilation rates. Increasing ventilation can reduce indirect exposures to very low 

levels for non-sorbing ETS components, but indirect routes accounted for similar 

to50% of potential nicotine exposures during non-smoking periods at all 

ventilation rates. Published by Elsevier Ltd. 

Sorensen, D. N. and C. J. Weschler (2002). "Modeling-gas phase reactions in indoor 

environments using computational fluid dynamics." Atmospheric Environment 36(1): 9-

18. 

 This CFD modeling study examines the concentrations of two gaseous 

compounds that react in an indoor setting to produce a hypothetical product. The 

reactants are ozone and either d-limonene or alpha-terpinene (which reacts with 

ozone about 40 times faster than d-limonene). In addition to two different 

terpenes, the scenarios include two air exchange rates (0.5 and 2.0 h(-1)). The 

terpene is introduced as a floor source with an emission pattern similar to a floorcare product. These four scenarios have been set in a fairly large two-dimensional 

room (13.6 x 40.6 m) with a supply at the top of the left wall and an exhaust at the 

bottom of the right wall. The room has been deliberately scaled so that the 

Reynolds numbers for key flow regimes match those of a room in which the 

calculated flow field has been validated against measured data. It has been further 
2-122

assumed that ozone interacts with room surfaces while the terpenes do not. The 

results show that for all four scenarios, under steady-state conditions, there are 

large concentration gradients within the room for both reactants and product. To 

some extent this is due to imperfect mixing. However. it also reflects that 

reactions occur at different rates across the room (because of varying reactant 

concentrations) and that the time available for reactions to occur varies with the 

room location (because the "age of the air" varies from point to point). Locally, 

within the room, the concentrations calculated by the CFID method differ 

significantly from those calculated by a one-compartment mass-balance model 

assuming perfect mixing. (C) 2002 Elsevier Science Ltd. All rights reserved. 

Spengler, J. D., J. McCarthy, et al. (2001). Volatile Organic Compounds. Indoor Air 

Quality Handbook. 

Tichenor, B. A. and L. E. Sparks (1996). "Managing exposure to indoor air pollutants in 

residential and office environments." Indoor Air-International Journal of Indoor Air 

Quality and Climate 6(4): 259-270. 

 Sources of indoor air pollutants in residential and office environments can be 

managed to reduce occupant exposures. Techniques for managing indoor air 

pollution sources include: source elimination, substitution, modification, 

pretreatment, and altering the amount, location, or time of use. Intelligent source 

management requires knowledge of the source's emission characteristics, 

including chemical composition, emission rates, and decay rates. In addition, 

knowledge of mechanical and natural outdoor air exchange rates, heating/airconditioning duct flow rates, and local exhaust fan (e.g., kitchen, bathroom) flow 

rates is needed to determine pollutant concentrations. Finally, indoor air quality 

(IAQ) models use this information and occupant activity patterns to determine 

instantaneous and/or cumulative individual exposure. This paper describes a 

number of residential and office scenarios for various indoor air pollution sources, 

several ventilation conditions, and typical occupant activity patterns. IAQ model 

predictions of occupant exposures for these scenarios are given for selected 

source management options. A one-month period was used to compare exposures; 
2-123

thus, long-term exposure information is not presented in this paper. (C) Indoor Air 

(1996). 

Tucker, S., S. Brown, et al. (2008). Estimating Indoor Air Quality using Integrated 3D 

CAD Building Models. Third National Conference of the Coopeartive Research Centre 

(CRC) for Construction Innovation. 

 The indoor air quality (IAQ) in buildings is currently assessed by measurement of 

pollutants during building operation for comparison with air quality standards. 

Current practice at the design stage tries to minimise potential indoor air quality 

impacts of new building materials and contents by selecting low-emission 

materials. However low-emission materials are not always available, and even 

when used the aggregated pollutant concentrations from such materials are 

generally overlooked. This paper presents an innovative tool for estimating indoor 

air pollutant concentrations at the design stage, based on emissions over time 

from large area building materials, furniture and office equipment. The estimator 

considers volatile organic compounds, formaldehyde and airborne particles from 

indoor materials and office equipment and the contribution of outdoor urban air 

pollutants affected by urban location and ventilation system filtration. The 

estimated pollutants are for a single, fully mixed and ventilated zone in an office 

building with acceptable levels derived from Australian and international healthbased standards. The model acquires its dimensional data for the indoor spaces 

from a 3D CAD model via IFC files and the emission data from a building 

products/contents emissions database. This paper describes the underlying 

approach to estimating indoor air quality and discusses the benefits of such an 

approach for designers and the occupants of buildings. 

Tuomi, T. (2000). "Emission of ozone and organic volatiles from a selection of laser 

printers and photocopiers." Applied Occupational and Environmental Hygiene 15(8): 

629–634. 

 To estimate the impact of office equipment on the quality of indoor air, the 

emission of ozone and organic volatiles was measured from one photocopier and 

four laser printers, three of which operated according to traditional corona 
2-124

discharge technology. The laser printers equipped with traditional technology 

emitted significant amounts of ozone and formaldehyde. Lesser amounts of other 

volatile aldehydes were emitted during printing. The photocopier emitted mainly 

ozone. 

 In a well-ventilated office environment, the amounts encountered here for 

individual volatiles were within recommended maximum exposure limits for a 

reasonable density of printers. Because it is not known whether the concentration 

of irritating volatiles, such as formaldehyde, should be kept lower in an ozone rich 

environment or not, and because emissions in the immediate vicinity of the 

printers exceeded recommendations, the authors recommend that laser printers 

equipped with the traditional corona rods not be placed beside or immediately at 

the working site of office personnel. This way, ozone concentrations can be kept 

below recommended maximum exposure limits, provided that the ventilation rate 

is adequate. Further, it seems that if a reliable quantitative comparison of total 

organic volatiles prior to and during printing is to be made, the inertness of the 

sorbent toward ozone should be confirmed. 

Uhde, E. and T. Salthammer (2007). "Impact of reaction products from building materials 

and furnishings on indoor air quality - A review of recent advances in indoor chemistry." 

Atmospheric Environment 41(15): 3111-3128. 

 The variety of chemical substances present in modern building products, 

household products and furnishings provides potential for chemical reactions in 

the material (case 1), on the material surface (case 2) and in the gas phase (case 

3). Such "indoor chemistry" is known as one of the main reasons for primary and 

secondary emissions. The conditions of production often cause unwanted side 

reactions and a number of new compounds can be found in finished products. 

Elevated temperatures are responsible for the degradation of cellulose, 

decomposition of non-heat-resistant additives and other thermally induced 

reactions like Diels-Alder synthesis. Heterogeneous chemistry takes place on the 

surface of materials. Well-known examples are the formation of aliphatic 

aldehydes from the oxidation of unsaturated fatty acids or the cleavage of 

photoinitiators under the influence of light. In case of composite flooring 
2-125

structures hydrolysis is one of the major pathways for the appearance of alcohols 

from esters. If different kinds of material are fixed together, emissions of new 

VOCs formed by inter-species reactions are possible. Other indoor air pollutants 

are formed by rearrangement of cleavage products or by metabolism. Compounds 

with -C=C- bonds like terpenes, styrene, 4-phenylcyclohexene, etc. undergo gas 

phase reactions with O3, NOx. OH and other reactive gases. It has been shown 

that such products derived from indoor-related reactions may have a negative 

impact on indoor air quality due to their low odor threshold or health-related 

properties. Therefore, the understanding of primary and secondary emissions and 

the chemical processes behind is essential for the evaluation of indoor air quality. 

This publication gives an overview on the current state of research and new 

findings regarding primary and secondary emissions from building products and 

furnishings. 

Wang, B., S. C. Lee, et al. (2007). "Characteristics of carbonyls: Concentrations and 

source strengths for indoor and outdoor residential microenvironments in China." 

Atmospheric Environment 41(13): 2851-2861. 

 Indoor and outdoor carbonyl concentrations were measured simultaneously in 12 

urban dwellings in Beijing, Shanghai, Guangzhou, and Xi'an, China in summer 

(from July to September in 2004) and winter (from December 2004 to February 

2005). Formaldehyde was the most abundant indoor carbonyls species, while 

formaldehyde, acetaldehyde and acetone were found to be the most abundant 

outdoor carbonyls species. The average formaldehyde concentrations in summer 

indoor air varied widely between cities, ranging from a low of 19.3 mu g m(-3) in 

Xi'an to a high of 92.8 mu g m(-3) in Beijing. The results showed that the 

dwellings with tobacco smoke, incense burning or poor ventilation had 

significantly higher indoor concentrations of certain carbonyls. It was noticed that 

although one half of the dwellings in this study installed with low emission 

building materials or furniture, the carbonyls levels were still significantly high. It 

was also noted that in winter both the indoor and outdoor acetone concentrations 

in two dwellings in Guangzhou were significantly high, which were mainly 

caused by the usage of acetone as industrial solvent in many paint manufacturing 
2-126

and other industries located around Guangzhou and relatively longer lifetime of 

acetone for removal by photolysis and OH reaction than other carbonyls species. 

The indoor carbonyls levels in Chinese dwellings were higher than that in 

dwellings in the other countries. The levels of indoor and ambient carbonyls 

showed great seasonal differences. Six carbonyls species were carried out the 

estimation of indoor source strengths. Formaldehyde had the largest indoor source 

strength, with an average of 5.25 mg h(-1) in summer and 1.98 mg h(-1) in winter, 

respectively. However, propionaldehyde, crotonaldehyde and benzaldehyde had 

the weakest indoor sources. (C) 2006 Elsevier Ltd. All rights reserved. 

Wang, S. Y., T. H. Yang, et al. (2008). "Fire-retardant-treated low-formaldehydeemission particleboard made from recycled wood-waste." Bioresource Technology 99(6): 

2072-2077. 

 The objective of this study was to manufacture fire-retardant-treated lowformaldehyde-emission particleboard from recycled wood-waste particles using 

polymeric 4,4'-methylenediphenyl isocyanate (PMDI) and phenol-formaldehyde 

(PF) resins. The influence of the PMDI/PF ratio (ratio of particles sprayed with 

PMDI to particles sprayed with PF, w/w) after fire retardant treatment on 

formaldehyde emissions, mechanical properties, and surface fire resistant 

performance of the manufactured particleboard was investigated. The 

experimental results showed that the formaldehyde emissions linearly decreased 

with an increasing PMDI/PF ratio. Moreover, the bending strength, internal bond 

strength, and screw holding strength increased with an increasing PMDI/PF ratio. 

The thickness swelling of the particleboard was improved by using an increasing 

PMDI/PF ratio. Furthermore, the fire-retardant-treated low-formaldehydeemission particleboards fabricated in our study could pass the third grade standard 

of surface fire resistant performance as specified by CNS 6532. (C) 2007 Elsevier 

Ltd. All rights reserved. 

Wang, X. K. and Y. P. Zhang (2009). "A New Method for Determining the Initial Mobile 

Formaldehyde Concentrations, Partition Coefficients, and Diffusion Coefficients of Dry 

Building Materials." Journal of the Air & Waste Management Association 59(7): 819-
2-127

825. 

 The initial mobile formaldehyde concentration, C-m,C-0; the partition coefficient, 

K; and the diffusion coefficient, D, of a dry building material are key parameters 

to characterize formaldehyde emissions from the building material. The solvent 

extraction method and direct thermal desorption method can overestimate C-m,C0 because of high temperature. A new method has been developed to determine 

C-m,C-0 under similar conditions to common indoor environment, together with 

K and D. In the proposed method, the tested materials are placed in an airtight 

environmental chamber for which the temperature can be controlled by a water 

bath, then the materials undergo a multisorption/emission process and the 

instantaneous formaldehyde concentration in the chamber is recorded. The K and 

C-m,C-0 are determined from the equilibrium concentrations after every sorption 

by means of the linear least-square regression, and D is obtained by fitting the 

concentration at the emission stage into a mass-transfer-based model in the 

literature. Four kinds of wooden medium-density boards are tested. The C-m,C-0 

measured using this method is the mobile formaldehyde concentration in the 

material, which differs significantly from the total formaldehyde concentration in 

the material measured by using the traditional method recommended by the 

Chinese standard (GB/T 176S7-1999) extraction method. This means that the 

mobile formaldehyde takes only a small portion of the total quantity in the tested 

material. The K, D, and C-m,C-0 values measured using this new method are used 

to predict formaldehyde concentrations for sorption processes. The results agree 

well with experimental data. In addition, some factors influencing the accuracy 

are analyzed. 

Wong, L. T., K. W. Mui, et al. (2006). "A statistical model for characterizing common air 

pollutants in air-conditioned offices." Atmospheric Environment 40(23): 4246-4257. 

 Maintaining acceptable indoor air quality (IAQ) for a healthy environment is of 

primary concern, policymakers have developed different strategies to address the 

performance of it based on proper assessment methodologies and monitoring 

plans. It could be cost prohibitive to sample all toxic pollutants in a building. In 

search of a more manageable number of parameters for cost-effective IAQ 
2-128

assessment, this study investigated the probable correlations among the 12 indoor 

environmental parameters listed in the IAQ certification scheme of the Hong 

Kong Environment Protection Department (HKEPD) in 422 Hong Kong offices. 

These 12 parameters consists of nine indoor air pollutants: carbon dioxide (CO2), 

carbon monoxide (CO), respirable suspended particulates (RSP), nitrogen dioxide 

(NO2), ozone (O-3), formaldehyde (HCHO), total volatile organic compounds 

(TVOC), radon (Rn), airborne bacteria count (ABC); and three thermal comfort 

parameters: temperature (T), relative humidity (RH) and air velocity (P). The 

relative importance of the correlations derived, from largest to smallest loadings, 

was ABC, Rn, CO, RH, RSP, CO2, TVOC, O-3, T, V, NO2 and HCHO. 

 Together with the mathematical expressions derived, an alternative 

sampling protocol for IAQ assessment with the three,most representative and 

independent' parameters namely RSP, CO2 and TVOC measured in an office 

environment was proposed. The model validity was verified with on site 

measurements from 43 other offices in Hong Kong. The measured CO2, RSP and 

TVOC concentrations were used to predict the probable levels of the other nine 

parameters and good agreement was found between the predictions and 

measurements. This simplified protocol provides an easy tool for performing IAQ 

monitoring in workplaces and will be useful for determining appropriate 

mitigation measures to finally honor the certification scheme in a cost-effective 

way. (c) 2006 Elsevier Ltd. All rights reserved. 

Wong, L. T., K. W. Mui, et al. (2007). "Screening for indoor air quality of airconditioned offices." Indoor and Built Environment 16(5): 438-443. 

 It would be costly to sample all toxic air pollutants to which an entire community 

is exposed. In Hong Kong, a voluntary Indoor Air Quality (IAQ) certification 

scheme for IAQ assessment in workplaces proposes the measurement of the levels 

of 12 parameters: carbon dioxide, carbon monoxide, respirable suspended 

particulates, nitrogen dioxide, ozone, formaldehyde, total volatile organic 

compounds, radon, airborne bacteria count, temperature, relative humidity and air 

velocity. This study investigates the feasibility of a screening process for 

presumptive detection of unrecognised IAQ problems in an indoor environment. 
2-129

From the full IAQ assessment results of 422 air-conditioned offices in Hong 

Kong, three of nine listed common air pollutants are selected as "representative" 

pollutants for an overall "satisfactory IAQ". In particular, an "IAQ index" using 

the average fractional dose corresponding to given exposure limits of the 

representative pollutants as a simple screening test for asymptomatic IAQ 

problems in air-conditioned offices is proposed. The index was evaluated in terms 

of test sensitivity, specificity and predictive value. Such a screening test would be 

a useful tool for policyrnakers, building owners and professionals to identify 

offices with probable IAQ problems. Making better decisions regarding resources 

for an IAQ surveillance programme could help to ensure a healthy and safe 

workplace. 

Wu, P. C., Y. Y. Li, et al. (2003). "Risk assessment of formaldehyde in typical office 

buildings in Taiwan." Indoor Air 13(4): 359-363. 

 Our study conducts a series of investigations in five office buildings chosen 

according to the types of construction, ventilation, and building age. 

Formaldehyde was measured by continuous photoacoustic Multi-Gas monitor 

Type 1302 (Bruel Kjaer). The 8-h average concentrations in working hours were 

used to estimate the lifetime cancer probability (LCP) and chronic noncarcinogenic hazard index (HI). The carcinogenic effect of formaldehyde estimate 

by LCP (70 years old) is about 2.06 x 10(-4) to 1.75 x 10(-3) after adjusting their 

working time. The levels of risk are 100-1000 times of the acceptable 

carcinogenic risk. A similar trend is observed for the levels of HI calculated. 

Many studies have suggested that exposure to high levels of formaldehyde may 

cause nasal cancer and other health effects. Therefore, promoting the labeling 

system for low emission materials to protect consumers from exposure to 

excessive emissions and helping the industry to develop low emission materials is 

evidently urgent and deserves greater efforts. 

Xu, J., J. Grunewald, et al. (2007). MODELLING THE FORMALDEHYDE EMISSION 

FROM MULTI-LAYER WORK SURFACES USED IN OFFICE WORKSTATION 

SYSTEMS. Proc. of the 6th Int. Conf. on Indoor Air Quality. 
2-130

 Volatile organic compounds (VOCs) emitted from various sources may adversely 

affect human health, comfort and performance. In particular, formaldehyde has 

been identified as a major indoor pollutant whose emission is controlled by 

workstation systems. Engineered wood products such as particleboards have 

widely been used with wood veneer and laminate to form work surfaces of 

workstation systems, which is a major formaldehyde emission component. The 

emission rate of formaldehyde depends on the composition of each material layer, 

temperature and moisture content in the materials. The objective of this study is to 

determine the long-term formaldehyde emission characteristics of multi-layer 

work surfaces such as a wood veneer over a particleboard core. The work 

comprised experimental and numerical investigation of the emission 

characteristics. To reproduce the experimental results, a numerical simulation 

model for coupled heat, air, moisture and pollutant transport in porous materials 

and wall assemblies was used1. A parametric study for the model parameters 

under consideration, such as the partition coefficient, the diffusion coefficient and 

the initial formaldehyde content in each material layer showed that all parameters 

decide about the formaldehyde emissions. In particular, the initial conditions have 

a major influence on the evolution of the emission factor. It can be concluded that 

an unambiguous determination of all parameters is difficult since the problem has 

no unique solution yet. Further research needs can be identified. 

Yoshida, H., A. Kimura, et al. (2004). "Emission behavior of VOCs in a model room 

with sugi-wood interior paneling." Mokuzai Gakkaishi 50(3): 168-175. 

 A model test room was built with finish flooring of solid oak and wall paneling of 

sugi wood. Concentration of carbonyl compounds and volatile organic 

compounds (VOCs) in the indoor air of the test room were measured over one 

year. The following results were obtained: (1) The main compounds emitted were 

formaldehyde and acetaldehyde. The emission of formaldehyde was greatly 

dependent on room temperature and did not easily attenuated although the 

emission was low throughout the test period. On the other hand, the emission of 

acetaldehyde was high at the beginning, but decreased rapidly in the first two 

weeks and did not depend on temperature. (2) The main VOC constituents were 
2-131

terpenoids, especially a-pinene. The terpenoids were rapidly attenuated and 

diminished within three to four months. 

Zhang, J. F., Q. C. He, et al. (1994). "Characteristics of Aldehydes - Concentrations, 

Sources, and Exposures for Indoor and Outdoor Residential Microenvironments." 

Environmental Science & Technology 28(1): 146-152. 

 Simultaneous indoor and outdoor measurements of aldehydes were made at 6 

residential houses located in a suburban New Jersey area during the summer of 

1992. Each house was measured for six days and controlled for ventilation and 

gas combustion conditions during the study. Formaldehyde, acetaldehyde, and 

seven other aldehydes were identified in the residential air. The study presents the 

first measurements of nine aldehyde species in both indoor and outdoor air. The 

total concentrations of the nine aldehydes were 19.12 +/- 10.88 ppb outdoors and 

62.57 +/- 21.75 ppb indoors. Formaldehyde was the most abundant aldehyde. 

Except for propionaldehyde, the indoor concentrations were found higher than the 

outdoor concentrations for all the other compounds, indicating the presence of 

significant indoor sources such as direct emissions and indoor chemical 

formation. Ozone concentrations were measured simultaneously during the study, 

and it was observed that several aldehydes can be generated through indoor ozone 

chemistry. The study provided evidence to support laboratory results obtained by 

other investigators that predicted aldehyde generation through indoor ozone 

chemistry. The residential exposures to formaldehyde and total aldehydes were 

assessed based upon some assumptions, and the outdoor exposures were 

negligible compared to the indoor exposures. 

Zhang, J. F., W. E. Wilson, et al. (1994). "Indoor Air Chemistry - Formation of OrganicAcids and Aldehydes." Environmental Science & Technology 28(11): 1975-1982. 

 The formation of aldehydes and organic acids was examined for the gas-phase 

reactions of ozone with unsaturated VOCs. Formaldehyde and formic acid were 

produced via the reaction of ozone with each of the three selected unsaturated 

VOCs: styrene, limonene, and 4-vinylcyclohexene. In addition, benzaldehyde was 

detected in the styrene-ozone-air reaction system, and acetic acid was found in the 
2-132

limonene-ozone-air system. The study also examined the gas-phase reactions 

involving formaldehyde, ozone, and nitrogen dioxide and found the formation of 

formic acid, suggesting that the nitrate radical may play an important role in 

converting formaldehyde into formic acid. Experiments for all the reactions were 

conducted by using a 4.3-m(3) Teflon chamber. Since the conditions and 

chemicals employed in the reactions were similar to those for indoor 

environments, the results from this study may be extrapolated to typical indoor 

situations and support indications from previous studies that certain aldehydes and 

organic acids could be generated by indoor chemistry. 

Zhang, Y. P., X. X. Luo, et al. (2007). "Influence of temperature on formaldehyde 

emission parameters of dry building materials." Atmospheric Environment 41(15): 3203-

3216. 

 The diffusion coefficient, D, partition coefficient, K, and the initial volatile 

organic compounds (VOCs) in dry building materials, are the three key 

parameters used to predict the VOC emissions. D and K may be strongly affected 

by temperature. We have developed a new and simple method, the C-history 

method, to measure the diffusion coefficient, D and the partition coefficient, K of 

formaldehyde in dry building materials at temperatures of 18, 30, 40 and 50 

degrees C. The measured variations of the diffusion coefficients and the partition 

coefficients with temperature for particle board, vinyl floor, medium- and highdensity board are presented. A formula relating the partition coefficient and 

related factors is obtained through analysis. This formula can predict the partition 

coefficient in principle and provide an insight for fitting experimental data, and it 

agrees well with the experimental results. (C) 2006 Elsevier Ltd. All rights 

reserved. 

Kenneth Unice: 

Formaldehyde is a challenging molecule for indoor air modelers evaluating pressed wood 

products as a result of a complex long term emission profile, a backpressure effect not 

often observed in consumer product modeling and potential indoor sources and sinks. 

The purpose of the Formaldehyde Indoor Air Model – Pressed Wood Products (FIAM-
2-133

pwp) is to provide a tool to estimate indoor human inhalation exposure to airborne 

formaldehyde (HCHO) in residential, mobile home, or temporary structures such as 

classrooms. The model documentation is transparent and well written, however, several 

areas of potential technical improvement or correction are noted in this review. I found 

the model input and output screens to be clear and intuitive. 

The theoretical framework for modeling steady state levels of formaldehyde has been in 

place for approximately 30 years. One of the areas I reflected on as a reviewer is how the 

release of this model could help advance the science of evaluating pressed wood 

products, particularly with distinguishing data gaps from data needs. In this regard, I 

believe the incorporating a better defined conceptual model into the model 

documentation and guidance would encourage important basic research, particularly in 

regard to the long term decay characteristics of formaldehyde emissions. In addition, it 

would very useful to have in an ability to perform simple sensitivity analyses similar to 

the limited Monte Carlo options available in MCCEM. This could be as simple as 

allowing ‘batch inputs’ for certain parameters like mass transfer coefficient with 

a selection key outputs summarized when batch mode is used. 

One of the major themes of my comments is that I strongly believe that the model 

documentation should outline a conceptual framework (with case studies) for assessing 

the exposure attributable to a specific product while taking into account the unique 

backpressure and source decay effects observed for formaldehyde. This framework is 

important because federal future regulatory standards, if any, could vary as a function of 

the type of product (e.g. industrial panel versus MDF. This outcome is likely because the 

technologies, loadings or mass transfer coefficients are product specific and standards 

may be adopted in different phases. One of the confusing aspects of the model is that the 

purpose to assess exposure attributable to emissions from pressed wood products, but the 

model output of average daily concentration (ADC) and lifetime average daily 

concentration (LADC) appears to include the background concentration and the ability to 

include doses from non-pressed wood products. As currently framed, the model is useful 

for assessing total personal exposure to formaldehyde, but of equal interest to most 

stakeholders is the risk or hazard assignable to a specific class of products or 
2-134

collection of products. The modifications that can be made to the model are limited by 

the current state of the science, particularly for long term exposure. Therefore, my 

primary recommendation is to describe a conceptual model in the documentation that 

provides a framework for approaching questions about product specific hazard and risk. 

In the comments below, I sometimes refer to the equilibrium concentration which is 

related to the Matthews b and m by Ceq= b/-m. The equilibrium concentration is the 

theoretical concentration corresponding to a ventilation rate of zero.

References

Berge, A. Mellagaard, B. Hanetho, P., and Ormstad, E. 1980. Formaldehyde Release 

from Particleboard – Evaluation of a Mathematical Model. Holz Als Roh-und Werkstoff 

38: 252-255. 

Brown, S.K. (1999) “Chamber assessment of formaldehyde and VOC emissions from 

woodbased panels” Indoor Air, 9: 209–215.Groah 2006 

CalEPA (2007) California Air Resources Board (CARB), Initial Statement of Reasons for 

Proposed Rulemaking, Proposed Airborne Toxic Control Measure to Reduce 

Formaldehyde Emissions from Composite Wood Products, Office of Environmental 

Health Hazard Assessment, California Environmental Protection Agency (CalEPA). 

Groah, W. J. (2006). Predicting indoor-air formaldehyde concentrations from emissions 

of urea-formaldehyde bonded wood products using the Versar model. Forest Products 

Journal, 56(10):97-100. 

Hodgson A.T. and Levin, H. (2003). Volatile organic compounds in indoor Air: A review 

of concentrations measured in North America since 1990. Berkeley, CA, Lawrence 

Berkeley National Laboratory (LBNL-51715). http://eetd.lbl.gov/ie/pdf/LBNL-51715.pdf

Hodgson A.T, Rudd A.F, Beal D. and Sandra S. (2000) “Volatile organic compound 
2-135

concentrations and emission rates in new manufactured and site-built houses”, Indoor 

Air, 10,178-193. 

Jayjock 1994. Back pressure modeling of indoor air concentrations from volatizing 

sources. American Industrial Hygiene Association Journal, 55: 230-235. 

Koontz M.D., Rector H.E., Cade D.R., Wilkes C.R., and Niang L.L. (1996) Residential 

Indoor Air Formaldehyde Testing Program: Pilot Study, IE-2814. Washington, DC, U.S. 

Environmental Protection Agency (U.S. EPA). 

Maddalena R., Russell M., Sullivan D.P., Apte M.G. (2009). Formaldehyde and other 

volatile organic chemical emissions in four FEMA temporary housing units. Environ Sci 

Technol. Aug 1;43(15):5626-32. 

Matthews, T. Reed, B. Tromberg., K. Fung, C. Thompson, J. Simpson, and A. 

Hawthorne. 1985.Modeling and Testing of Formaldehyde Emission Characteristics of 

Pressed-Wood Products: Report XVIII to the U.S. Consumer Product Safety 

Commission. ORNL/TM-9867, Oak Ridge National Laboratory, Oak Ridge, TN. 

Matthews, T. Hawthorne, A. and Thompson, C. 1987. Formaldehyde Sorption and 

Desorption. Characteristics of Gypsum Wallboard. Environmental Science & Technology 

21: 629-634. 

Mølhave L., Dueholm L., and Jenson L.K. (1995) “Assessment of exposures and health 

risks related to formaldehyde emissions from furniture: A case study”, Indoor Air, 5: 

104-119. 

Meyer B., Hermanns K. (1985) “Reducing indoor air formaldehyde concentrations” 

Journal of the Air Pollution Control Association, 35, 816-821. 

Myers G. and Nagaoka M. (1981) “Emission of formaldehyde by particleboard: Effect of 
2-136

ventilation rate and loading on air-contamination levels” Forest Products Journal, 31(7), 

39-44. 

Myers, G. E. (1983). Formaldehyde emission from particleboard and plywood paneling: 

measurement, mechanism, and product standards. Forest Products Journal, 33: 27-37. 

Salthammer T., Fuhrmann F., Kaufhold S. Meyer B. and Schwad A. (1995) Effects of 

climatic parameters on formaldehyde concentrations in indoor air” Indoor Air, 5, 120-

128. 

Tichenor, B.A., Z. Guo, J.E. Dunn, L.E. Sparks, and M.A. Mason. The interaction of 

vapour phase organic compounds with indoor sinks. Indoor Air, 1, 23-35, 1991. 

U.S. EPA 1996. "Sources and Factors Affecting Indoor Emissions from Engineered 

Wood Products: Summary and Evaluation of Current Literature" (EPA-600/R-96-067, 

NTIS PB96-183876, June 1996). 

Zinn, T.W., Cline, D. and Lehmann, W.F. (1990) “Long-term study of formaldehyde 

emission decay from particleboard” Forest Products Journal, 40(6), 15-18. 

W. Gene Tucker: 

It seems to me the main potential users of a model of this type will be upscale home 

builders and home manufacturers. They might use it to predict whether certain types and 

amounts of formaldehyde-containing materials would lead to indoor HCHO 

concentrations that exceed some air quality standards or criteria. However, I doubt there 

will ever be many who use FIAM in this way. There are dozens (perhaps hundreds) of 

choices that need to be made in using this sort of model. Each choice has its uncertainty 

and the propagation of uncertainties can lead to very imprecise estimates. 

In the end, I have to wonder whether concentrations predicted by this model will lead to 

much more accurate or useful results than would be gotten from much simpler displays of 

emission factor data, loadings, and air exchange rates. Graphs relating these basic 

parameters to peak indoor concentrations could be created, similar to ones that I 
2-137

presented in the IAQ Handbook some years ago2 and that others have also suggested. 

Spreadsheets would probably be preferable. If exposure estimates are of interest the 

decay rate of formaldehyde concentration can be predicted based on selection of a decay 

constant (or a series of decay constants) that seems appropriate for the type of building 

being considered. While such an approach may arguably be simplistic, its assumptions 

are more transparent and its use by designers and builders is likely to be more 

widespread. If the ultimate concern is public health, these are important considerations. 

Thoughts on a General Introduction to Mass Balances for Indoor Air Quality 

Models 

Most indoor air quality models (and most environmental models, for that matter) are 

multi-compartment schemes where each compartment is assumed to be well mixed (i.e., 

has uniform concentrations of the substances of concern within the compartment, and has 

concentrations flowing out of the compartment that are the same as concentrations in the 

compartment). Mass flows of substances into and out of each compartment are 

simultaneously balanced with adjacent compartments. 

Textbook descriptions of such models, and documentation that accompanies their 

computer programs, often start out with mass balance equations that involve various 

forms of differential equations, summation expressions, etc. This tends to fog out most 

users of the software and they skim or skip this part. I believe that user understanding 

would often be improved if a more simplified introduction to mass balance concepts 

preceded any detailed mathematical discussion. The following rough notes sketch out my 

thoughts. With further development they might be helpful in some future indoor air 

modeling efforts. 

The mass balance around any compartment in a multi-compartment system will generally 

have five terms: what comes out of the compartment (OUT); what comes into it (IN); 

mass of substance generated in the compartment (GEN); mass of substance consumed 

(CONS); and mass of substance accumulated (ACCUM). The units of each term are 

usually mass per time (e.g., mg/h). 

 

2

 Spengler, Samet, McCarthy, eds., Indoor Quality Handbook, Chapter 31, McGraw-Hill, 2000. 
2-138

[A simple box and arrow diagram could be inserted here. My abilities with graphics are 

limited....]

The arithmetic version of this balance can be written in any order, but since estimating 

the concentration coming out of the compartment is so often of most interest the balance 

can be written as: 

OUT = IN + GEN – CONS – ACCUM 

Where 

• OUT = mass flow of the substance of interest from the compartment to its 

surroundings (to other compartments, outdoors) 

• IN = mass flow of the substance into the compartment (from outdoors, other 

compartments) 

• GEN = mass rate at which the substance is created or released into the air inside 

the compartment. This is often referred to as the “source term”. This can occur as 

a result of gas-phase chemical reaction, or physical release such as evaporation 

from solid or liquid materials in the compartment 

• CONS = mass rate at which the substance is removed from the air in the 

compartment by chemical reaction or irreversible sorption to a surface (including 

an air cleaner in the compartment). This term is often referred to as an 

“irreversible sink” effect. 

• ACCUM = mass rate at which the substance stays inside the compartment. 

Materials with accumulated substances may at times become sources (in which 

case the accumulation rate is negative). This term is often referred to as a 

“reversible sink” effect. 

An introduction of this type can then be followed by mathematical representations of 

each of the five terms. In most applications one or more of the terms are assumed to be 

zero and can be left out of the mathematical discussion. 
3-1

3.0 PEER REVIEW COMMENTS ORGANIZED BY REVIEWER

 Peer review comments received for the ER Binding assay are presented in the 

sub-sections below and are organized by reviewer. Peer review comments are presented in full, 

unedited text as received from each reviewer. 

3-3

3.1 Jensen Zhang Review Comments

Part 1. Algorithms and Exposure Assumptions 

1.1) Are the mathematical equations adequately explained, are they appropriate and are 

they accurately executed? What is your level of confidence in the indoor air concentrations 

and exposure estimates provided by the model? Please provide your rationale for 

determining the level of confidence. If the level of confidence is low, please provide the 

details as to why. Specifically, note any areas where errors were found, areas for 

improvement, or alternate calculation methodologies. 

1. The mathematical equations are adequately explained except that there appears to be 

some confusion between diffusion and convective mass transfer. The model is based on 

convective mass transfer over the surface, which is not based on the Fick’s Law of 

diffusion. The air velocity over the surface would have significant effect on the “mass 

transfer coefficient”, and hence the model parameter, “slope”. The values of the “slope” 

appear to be small (maximum of 3.0 in the case of painted dry wall). This is likely that 

the most data are from small scale chamber tests where air velocity over the material 

surface is small compared to the typical airflow conditions in ventilated rooms. 

Therefore, the model may underestimate the emission rates if the emission is indeed 

controlled by the convective mass transfer process. 

2. However, it is more likely that except for the initial emission period, the emission rate 

will be controlled by the internal diffusion process as suggested by many studies 

including those cited in the report for pressed wood products. So the “slope” values 

derived from the measured data may have included the combined effects of convective 

mass transfer and internal diffusion resistances, resulting reasonable predictions. At the 

“steady state” (about 30 days from initial chamber test), the internal diffusion resistance 

should be the dominant resistance for formaldehyde emissions even for particleboard. To 

understand and proof this point, a more detailed numerical simulation can be made for 

homogeneous sources as assumed in the study (i.e., there were free formaldehyde 

uniformly distributed in the material). 

3. After establishing the steady state initial concentration based on Mathew’s model, the 

concentration in a zone that has a higher concentration is assumed to decay exponentially 

over time, given a half life time as the input parameter. This approach is unconventional, 

but practical considering the many uncertainties involved in real situation. The challenge 

would be to choose the right the half-life time. An alternative is to actually model the 

emission rates of various sources, and then calculate the concentrations under given 

ventilation rate conditions, as is typically done. 

4. Formaldehyde may not be distributed uniformly inside the material. They may be more 

concentrated in resin spots and less in the wood particles/chips. In addition, hydrolysis is 

possible for additional formaldehyde generation within the material, resulting longer and 

higher emission rates in the long term. This is still a research topic and no reliable model 

has been developed yet. Therefore, I support the idea of relying on measured field data to 
3-4

estimate the decay of formaldehyde concentration, and be conservative in the estimation, 

as intended by the model. 

5. Based on the data provided and the assessment analysis, the model should provide 

reasonable conservative estimate of the formaldehyde exposure given the relatively long 

half-life time. 

1.2) Comment on the default scenarios and default assumptions used by the model. Are the 

default assumptions reasonable and adequately supported by relevant scientific data? If 

not, specifically note any unreasonable assumptions. Provide suggestions and references for 

alternate default assumptions. 

Yes. 

1.3) Comment on the data sources. Are the data sources reasonable and accurate? If not, 

specifically note any unreasonable or inaccurate data source. Provide suggestions and 

references for alternate data sources. 

Yes. 

1.4) Do the data sources provide unused information that would assist in quantifying 

uncertainty or variability for subsequent model use? 

Although the data sources are incomplete for quantifying the uncertainty, it is possible to 

conduct an uncertainty analysis using error propagation theory with assumptions on the 

uncertainties in the raw data. This would help establish the uncertainty in the predicted results. 

1.5) Do the model input variables and the estimates assigned to them appropriately reflect 

variability? 

I did not see the uncertainty values for the model inputs. 

1.6) Has EPA provided adequate documentation of the overall plausibility of the exposure 

estimates generated by the exposure model? If not, provide suggestions for characterizing 

the exposure assessment estimates. 

Yes. 

1.7) Are there any other types of data to assess the reliability of the overall exposure model 

or specific model elements? If so, provide suggestions and references for alternate data 

types. 

I am not aware of additional field data for the assessment. 

Part 2. User Interface 

2.1) Is the FIAM - PWP easy to use? Specifically note any data entry screens you 

found confusing or unclear. Provide suggestions to improve the userfriendliness 
3-5

of the model. 

The interface design is easy to use in general. 

1) The online version is very, very slow in response to every click (submission, help, source 

selection, etc....) 

2) Berge and Myer --- temperature effects. It is better to use one only or combine it to 

provide a default number since users do not know which one to use. Alternatively, tell 

user how to select. 

3) Source selection: How is the area defined for the cabinet? The surface area or the foot 

print? 

4) It would be more convenient for users to select floor types and then provide model 

coefficients for all the materials involved instead of asking users to “construct the floor”. 

5) The screen on “Exposures” is too wide for my notebook (Lenovo/Thinkpad X61s). Also, 

the “Adult”, “Child” should be more visible. 

6) The help sign “?” is too visible. Suggest that make it smaller and place it after the data 

entry. 

7) The “results” file may be made more informative to conclude if the house would meet 

HUD or other standards. 

8) It would be useful to provide some sort of guide for users to step through the modeling 

process (such as step 1, 2, 3, ...., much like when completing a Tax return with TaxAct) 

2.2) Are the model help screens adequate? Describe any additional help screens 

that you would find useful. 

Yes. 

Part 3. Documentation 

3.1) Are the references accurately identified? Would any additional reference citations be 

helpful? Please note any additional references that should be cited. 

Yes. 

3.2) Does the model documentation present the model construct, selected model inputs, 

model results in a clear, complete and useful manner? If not, specifically note areas that 

are unclear or needs improving. Provide suggestions for additionally information. 

1) The “steady-state assumption” has been mentioned too many times while describing the 

user-interfaces. This is not necessary and it distracts users/readers from focusing the 

input parameters. Also, the mode is not truely a steady-state one since the emission 

source decays over time. It is a “quasi-steady state” model in which the concentration at 

a given calculation point was treated as “constant” for the purpose of simplifying the 
3-6

calculation without losing too much accuracy. An additional reference may be cited to 

justify such treatment (Zhang et al. 1997). 

Zhang, J.S.; Wang, J.; Shaw, C.Y. 1997. Theoretical Examination of a Simplified 

Procedure for Data Analysis in Small Chamber Testing of Material Emissions. 8 

pp.(Internal Report, Institute for Research in Construction, National Research Council 

Canada, 733)(IRC-IR-733) 

2) The “flow balance” should be changed to “mass flow rate balance” to be accurate. 

3) I am concerned that most data provided on formaldehyde emissions are from early 

studies. Much of the manufacturing processes and raw materials have been changed. 

Especially due to the use of non urea-formaldehyde resins, the formaldehyde emissions 

from pressed wood products have been reduced significantly. 

4) Validity of the exponential decay model is questionable. Recent data have shown that the 

power-law model would be more suitable, and secondary emissions as a result of 

hydrolysis are also possible. Limitations of the exponential decay model should be 

pointed out. 

5) Table 2.4: Why the “medium” and “low” emitting ensembles have the same slope and 

intercept for “Shelves”? 

6) Regarding Equation 3-5: 

CH2OER′ = -m * [CH2O]V + b (Eqn. 3-5) 

where: 

m = the mass transfer coefficient (m/hr) 

[CH2O]V = the CH2O concentration in the vapor phase (mg/m3) 

b = a constant; the emission rate at zero CH2O concentration in the air (mg/m2-hr). 

 6.1) The Fick’s law is for diffusion, while here the process is governed by convective 

mass transfer across the boundary layer. Air velocity and turbulence over the surface hence 

affect the mass transfer coefficient, instead of simply the diffusion coefficient in Fick’s law. 

6.2) The definition of vapor phase concentration and bulk phase concentration is unclear. 

In Eqn. 3-5, [CH2O]V should simply be the concentration in the bulk air (outside the air 

boundary layer over the surface). I see no need to define a vapor phase concentration since by 

default, we are always dealing with the vapor concentration in the air or in the material in this 

model. This naturally then lead to the assumption that the concentration in the bulk air outside 

the boundary layer is the same as the steady-state concentration in the compartment. 

7) Page 4-2: “Product loading rate”---do you mean “loading ratio”? Same in Table 4-1. 

3.3) Does the documentation for the FIAM - PWP make clear the sources and 

anticipated magnitudes of variability and uncertainty in model results? 

Describe any additional information that you would find useful. 
3-7

There are good description of the possible sources variability in the model prediction. However, 

it would be helpful if a more quantitative analysis is conducted on the uncertainties of the model 

coefficients and how they would propagate to the predicted results. And thus the predicted 

results will be a range (e.g., mean +/-standard deviation) instead of a single concentration level. 

3.4) Are the model algorithms consistent with the descriptions in the model 

documentation? If not, specifically note areas that are inconsistent between 

the model and documentation. 

I did not check the code. 

3-9

3.2 Michael Jayjock Review Comments

Jayjock Response 

Technical Charge to Peer Reviewers of the Formaldehyde Indoor AirExposure Model – 

Pressed Wood Products (FIAM-PWP) 

Work Assignment No. 5-10 

Contract No. EP-W-05-014 

Part 1. Algorithms and Exposure Assumptions 

1.1) Are the mathematical equations adequately explained, are they appropriate and are 

they accurately executed? What is your level of confidence in the indoor air 

concentrations and exposure estimates provided by the model? Please provide your 

rationale for determining the level of confidence. If the level of confidence is low, 

please provide the details as to why. Specifically, note any areas where errors were 

found, areas for improvement, or alternate calculation methodologies. 

While relatively simple and straightforward at its base using first principle scientific 

relationships, this model, in its totality, is by any measure quite complex. The reader who 

wishes to understand it has to have a competent background in the modeling sciences, be 

reasonably motivated and must be able to devote considerable time to studying the 

documentation in order to do so. This complexity puts a heavy burden on the person(s) 

providing the documentation in order to clearly explain its workings. In light of this 

challenge I found the explanation of the mathematical basis of the algorithms and the 

exposure assumptions to be remarkably well written and lucid. 

Regarding the appropriateness of the algorithms and assumptions, as mentioned above, 

Matthew’s basic approach appears to be based on solid first principles of conservation of 

mass and the validity of diffusion via Fick’s Law. Equation 3-2 appears to be relatively 

simple, self-evident and quite appropriate. The only term that gave me some pause 

regarding its suitability was F (the mixing factor). Some past scientific opinion has 

considered the use of the ventilation rate mixing factor to be basically invalid; however, 

after further reflection it is clear that relative to sources it is the local ventilation rate (that 

is the rate that is proximate to the emitting source) which is the determining factor and 

because of typically incomplete mixing within any room volume the inclusion of F is a 

perfectly legitimate and suitable modeling construct. 
3-10

Similarly, equation 3-5 forms the basis for the emission rate modeling engine. It is well 

explained and appears to me to be a reasonable approximation of reality. This equation is 

in complete agreement with previous work that I have done on “backpressure” modeling 

(ref: Jayjock, M.A.: Back Pressure Modeling of Indoor Air Concentration from 

Volatilizing Sources, Am. Ind. Hyg. Assoc. J. 55 (3): 230-235 (1994)). 

Equation 3-5 is reproduced below with slightly different notation along with an 

equivalent equation from my previous work. 

max Gss = −m(Css

) + G (equation 3-5 with different notation) 

Gss = steady state emission rate (mg/m2-hr). Equivalent to CH2OER’ 

Gmax = the maximum emission rate which occurs at zero backpressure; 

that is, at zero concentration of formaldehyde in the air (mg/m2-hr). 

Equivalent to b. 

m = the mass transfer coefficient (m/hr) 

Css = vapor-phase concentration of formaldehyde at steady state (mg/m3). 

Equivalent to [Ch2O]v

Equation 3-5 above is essentially identical to an algorithm that I have often used for 

backpressure modeling shown below: 

max

max

max

( )

:

1( )

C G

C

G

G

rearranged

C

C

G G

ss

sat

ss

sat

ss

ss

= − +

= −

Csat = the saturation concentration (mg/m3) of formaldehyde in the air over 

the emitter of interest. That is the concentration that would be 

expected in a volume (with high surface area/volume ratio) in which 

the emitting walls were made up entirely of the emitter of interest 

and there is zero ventilation. 

Note the equivalence of this last equation to 3-5 above and the identity of m: 

Csat

G

m

max =
3-11

Clearly, the relatively straightforward analytical measurement of Csat could provide a 

potentially valuable extended methodology for the evaluation and development of the 

model’s parameters relative to specific emitters. 

The subsequent development of the model’s complexity within the current documentation 

going forward after the combination of the concentration and emission rate algorithms is 

well explained and to my eyes seems to be fitting. 

The extension of the model from a single to two compartments, while necessarily quite 

involved, is logically explained and appears to me to be accurate. 

I believe that the treatment of indoor sinks as developed by and explained in the model 

represent a real step forward in indoor modeling science. From my experience few 

modelers have attempted to address this issue in detail and none have done a better job 

than demonstrated in this work. As noted by the author, the complex relationships 

regarding real sink behavior are not fully captured by the scheme used but I believe it is a 

credible “point-in-time” approximation. I would suggest that the author of the 

documentation in this area expand the explanation to include some example data and 

treatment that illustrates the estimation of parameters for the Langmuir model. That is, 

the last paragraph on page 3-7 supplies the estimated values but my sense is that the 

explanation would be significantly more lucid if the actual procedure and values used in 

the fitting exercise were demonstrated and included. 

The sections on decay of indoor concentration and the default value for half-life are very 

well written and, to the credit of the author, lay out all of the practical limitations incurred 

during the development of these aspects of the model. Clearly, the ideal data set was not 

collected and the practical alternatives were (for the reasons given) less than perfect. 

Despite these limitation the author does a very credible job of considering all the aspects 

and providing the reader/model user with a distillation of useful parameters and guidance. 

Similarly, the section on temperature and humidity adjustments is characteristically well 

presented and understandable. 
3-12

Regarding the level of confidence one might have in the model’s prediction of actual 

indoor concentration and exposure levels, my sense is that they should be considered 

accurate within a factor of 2. That is, given a true concentration or exposure of 1 that a 

competent estimate (i.e., with good inputs) should occur between 0.5 and 2. This is 

admittedly an intuitive judgment on my part borne of the approximations used in the 

methodology but more from the practical limitations and variability of the data used to 

parameterize or otherwise feed the model. For example, examining the equations in 

Table 2-2 and setting the ambient formaldehyde concentration to zero, the emission rates 

for Particleboard Underlayment from the available sources range from 0.09 to 0.74 

mg/m2/hr or a factor of about 8x. Industrial particleboard ranges from 0.12 to 1.24 or a 

factor of more than 10x. My sense is that this range represents true differences in 

emissions rates but also artifactual differences between testing laboratories. My estimate 

of a factor of 2 comes from an assumption that the user has a good and accurate 

accounting of which sources and sinks are most germane to their particular scenario. If I 

am incorrect in this assumption then the range would, of course, broaden. 

Other evidence driving this estimate (factor of 2) is the results and comparison of 

modeled/measured values from the pilot study. Despite its well documented limitations 

the parameters in this study appear to be reasonably understood and the model appears to 

over predict measured values. During the air out period when re-emitting sinks were 

ignored there was an overestimation of about this order. 

Relative to the estimation of exposure there appears to be logical error in the defaults. 

When one invokes the Exposure Defaults within the model, the 5 age groups for children 

in the model all show 10 years for the exposure period. Of course, this is impossible for 

an infant of <1 year or, indeed for any of the age groups for children which are all less 

than 10 years in length. This is explained in the documentation and in the online help 

button; however, I found it somewhat confusing. My suggestion is that the default shown 

in the program for any age group should be the maximum time a person can spend in that 

age group. The user can then view the help file for specific guidance in changing the 

defaults. An additional measure would be to indicate on the screen that it is: “Age group 

at start of exposure.” 
3-13

Understanding the exposure to formaldehyde represents exactly half the information 

needed to understand the risk to human health from this exposure. Of course, the other 

critical piece of information includes the toxic effects that can occur as a result of the 

exposure. A very brief search of the Internet reveals the following relevant information 

regarding this compound. “Formaldehyde is a normal, essential human metabolite with 

a biological half-life of about 1.5 minutes.” Reference: 

http://justthevax.blogspot.com/2009/05/toxin-gambit-part-1-formaldehyde.html. Indeed, 

this is a relatively fast biological half-life and this speed can have serious implications for 

the time frame used to integrate the level of exposure. The best example to illustrate this 

issue and need that I can think of is carbon monoxide (CO). A constant exposure to CO 

of 10 ppm v/v per day everyday for 365 days should not be an issue with most folks but 

providing this combined dose over 5 days (730 ppm v/v) as a 5-day long bolus would be 

disastrous to anyone even in the first day (first hours) of this exposure. 

 

Of course, the differences in exposure magnitude and the mode of action of CO and 

CH2O are quite different but the biological half-life of CO is in hours and that of CH2O 

is in minutes. Thus, it is not difficult to imagine relatively high doses of CH2O 

potentially causing biological damage over a period of a few days. As such, the 

estimation exposure in the Results Screen of Average Daily Concentration (ADC) and 

Average Daily Dose (ADD) could be of particular significance to the toxicologist in 

assessing the overall risk from exposure to indoor formaldehyde. Depending on the 

specific details of the toxicokinetics of formaldehyde the toxicologist may be interested 

in understanding the exposure to humans on the worst (first) day of exposure. The 

program allowed me to put in a single day (0.00274 years) for the duration of the 

exposure but the results indicate that a calculation error occurs for this input. The 

calculated ADC is above the initial concentration and the time percentages come out to 

be >100%. If this error is not easy or practical to fix then an explanation should be 

included that advises the minimum time for duration of exposure. My sense is that this 

minimum calculable time frame should not, in any case, be longer than a few days for the 

reasons mentioned above. 
3-14

Generally, I did not find any errors in the algorithms, however, I did not attempt an 

explicit independent derivation of all of the algebraic equations that comprise the model. 

Relative to alternate calculations methodologies it is suggested that the modelers consider 

a modeling program based on The Advanced Continuous Simulation Language (ACSL) 

computer language. ACSL easily handles simultaneous differential equations while 

providing parameter estimates from data via optimization and an intuitive graphical 

interface. This is not to suggest that ASCL be used in the direct implementation of the 

FIAM. Indeed, this seems to be done quite well with the current software. However, 

ACSL could be used to independently confirm the modeling output or help refine the 

estimations of parameter values (from experimental data) for the model. ACSL is 

available in a PC implementation. Please refer to the following web site: 

(http://www.acslx.com/products/optimization.shtml). 

1.2) Comment on the default scenarios and default assumptions used by the model. 

Are the default assumptions reasonable and adequately supported by relevant 

scientific data? If not, specifically note any unreasonable assumptions. Provide 

suggestions and references for alternate default assumptions. 

For the most part the default scenarios and assumptions appear to be reasonably 

supported. Specifically, the air exchange rates for the homes agree with my 

understanding of national averages for this important variable. My suggestion is that 

the modelers should consider using and including the seminal study by Murray and 

Burmaster as an important reference for potential use with this model (ref: Murray, 

Donald M. and David E. Burmaster: Residential Air Exchange Rates in the United 

States : Empirical and Estimated Parametric Distributions by Season and Climatic 

Region, Risk Analysis, Vol 15, No. 4, 1995). Of particular value are data from

different geographical sectors and seasons within the U.S. 

Also, I found the choice of housing types to be very reasonable. I also agree with the 

choice of a realistic house size as a default in that larger houses have a lower level 

surface area to volume loading for sources. 
3-15

As noted above the assumption (or possible interpretation) that any child in any of the 

age groups will have 10 years of exposure is confusing at best and should be easily 

corrected. Of course, the years of exposure should be equal to or less than the years 

within that age group. Indeed, my sense is that many analysts will be interested in the 

exposure within a particular age group and not necessarily extended across age groups. 

1.3) Comment on the data sources. Are the data sources reasonable and accurate? If not, 

specifically note any unreasonable or inaccurate data source. Provide suggestions and 

references for alternate data sources. 

Note the above comment on residential air exchange rate and a referenced source of good 

information on this important parameter. The other critical sources within this model are 

the chamber tests for emission rates and the fitted values for the linear rate model. I am 

not familiar with these data sources but they seem to be well described and characterized 

by the author. I also do not know of other data sources on the emission of formaldehyde 

from wood. I considered and researched the significant effort on indoor emissions 

sources done in recent years by the Canadian National Research Council but this program 

turned out to be focused on volatile organics and did not include formaldehyde. 

1.4) Do the data sources provide unused information that would assist in 

quantifying uncertainty or variability for subsequent model use? 

I interpret the above question to mean the data used in this model plus “new” data sources 

not included in this work. See my comments above about the Murray/Burmaster 

database on air exchange rates in U.S. residences. Clearly these data could assist in 

gauging the variability of this parameter. Also, I believe the current data used in the 

model on emission sources discloses a level of uncertainty and variability that could also 

be mined by a person who is knowledgeable about these data and their origins. See 

comments below. 

1.5) Do the model input variables and the estimates assigned to them appropriately reflect 

variability? 

From what I can determine all of the model input variables are entered as deterministic 

values – that is, as single numbers without variability. Indeed, I agree with the tone of 
3-16

the question that perhaps variability emanating from the model should be reasonably 

described because in its current form it is not. Clearly, which particular variable or data 

source one chooses will drive the outcome and the result will be variable if different input 

values are chosen. Thus, a user could choose to use inputted highest emission values (no 

sinks) which maximize the concentration and exposure within the range of his or her 

knowledge of the scenario to obtain a high end prediction. This could be followed by a 

run in which he or she would use inputs that were on the low end of the range (and 

include sinks) that again reflected the modeler’s knowledge or confidence in the 

situation. The comparison of outputs would provide some quantitative level of 

variability extant within the system and would be provided within the context of the 

user’s perspective and confidence. 

Another possibility would be to take the data in Table 2-2 and determine which data sets 

might be reasonably combined as presumably coming from the same population. 

Parameters from these data sets could be analyzed for the statistical variability and the 

parameters of the emission equations could be represented as best-fit probabilistic 

distribution functions. These distributions would then be incorporated into a Monte 

Carlo scheme to present a predicted output distribution of concentrations and exposures. 

This would add significantly to the complexity of the tool but would provide a direct and 

cogent measure of model variability as driven by the input variables. 

1.6) Has EPA provided adequate documentation of the overall plausibility of the exposure 

estimates generated by the exposure model? If not, provide suggestions for 

characterizing the exposure assessment estimates. 

 

 My sense is that the estimates have been clearly shown to be plausible relative to results 

of comparing the modeled estimates to the measured data in the Pilot House study. Even 

through all of the practical difficulties, which were very well explained in the 

documentation, this study appears to provide adequate evidence that the model is 

certainly capable of providing credible estimates. I believe that this is particularly true 

for the model executed in the skillful hands of technical experts who had almost perfect 

knowledge of the scenario and the workings of the model. 
3-17

 Perhaps a more practical test of the model’s accuracy and reliability might come from its 

comparison to measured data in some realistic scenarios as viewed and implemented by 

or from the perspective of a non-expert user. This would involve going into newly 

constructed residence(s) and modeling first (monitoring second) after determining the 

appropriate model inputs using available information. The modelers would still be 

technical experts but would be faced with and have to deal with a typical level of 

uncertainty borne of a finite lack of knowledge. Here invoking worst-case/best case 

models estimates of the real world scenario as described above (and then comparing them 

with measurements) could be very valuable in demonstrating the model’s value in 

predicting real world concentration and exposures to formaldehyde. 

1.7) Are there any other types of data to assess the reliability of the overall exposure 

model or specific model elements? If so, provide suggestions and references for alternate 

data types. 

 Please see the discussion in 1.1 above in which an additional critical emitter variable – 

Csat is explicated using the basic emission rate algorithm: Eqn 3-5. Data on this variable 

could be directly measured in a straightforward manner. This could occur by first 

constructing a box of the emitting material with an internal volume sufficient to provide a 

good limit of analytical detection. For example, if one wished to have analytical 

detection limit (LOD) of 2 ppb they would consult with the analytical chemist as to 

which sample volume would be able to detect that value. Say, for example that a 5 liter 

air sample would be required to render an LOD of 2 ppb formaldehyde. One would 

simply construct a box with an internal volume of 5 liters. Moderate care should be taken 

to seal the edges against leakage. The box should be allowed to equilibrate such that the 

internal concentration is no longer increasing. It is suggested that this would occur 

within a week but could be confirm experimentally. After this period, the exact internal 

air volume of the box should be sampled quickly (i.e., within a maximum time frame of 

minutes – for example 0.5 lpm x 10 minutes = 5 liters). The measured concentration 

represents 69% of the amount of formaldehyde in the box if good mixing occurred during 

relatively rapid sampling. (Note, having a small fan in the box will hasten equilibrium 

and assure good mixing during sampling.) Thus, the measured Csat would be equal to the 
3-18

measured concentration/0.69. As mentioned above having Csat should substantially 

increase the confidence in the validity of m. 

Part 2. User Interface 

2.1) Is the FIAM - PWP easy to use? Specifically note any data entry screens you found 

confusing or unclear. Provide suggestions to improve the user-friendliness of the 

model. 

As mentioned above FIAM – PWP is a complicated tool that requires a considerable 

amount of input and performs a significant amount of calculation. Considering all 

that it does I found the user interface is remarkably clean and straightforward. The 

“tab” format is logical. Also understandable and obvious is the flow of operations 

from the first to the last tab. I found the “pull down” window input format to be 

easy and very intuitive. In short, I have no reasonable suggestions to make it more 

user friendly. 

2.2) Are the model help screens adequate? Describe any additional help screens that 

you would find useful. 

In general, I found the content of the help screen to be very good and, as expected, 

reflective of the documentation. As mentioned previously, I found the overall 

documentation to be very good. I do have a formatting issue, however. I have a relatively 

large 23” monitor on my computer, when I open a help screen (Web Page dialog) it 

comes up in a relatively small font and the width of the paragraph appears to be less than 

50% of the width of the window. My suggestion is to increase the length of the lines in 

the help window to fill up the space and also increase the font size to use up this 

additional utilized area. This will significantly add to the “readability” of the generally 

excellent help information. 

I was easily able to get the “larger fonts” options running by checking the box in the first 

window; however, I could not get the “audio help” to work. I am assuming that it is not 

connected at this point. 
3-19

Part 3. Documentation 

3.1) Are the references accurately identified? Would any additional reference 

citations be helpful? Please note any additional references that should be cited. 

The fourth reference (the CARB Final Regulation Order...) should be identified as 

available online at: http://www.arb.ca.gov/regact/2007/compwood07/fro-final.pdf 

(last accessed October 9, 2009). Similarly, the 8th reference (D. Hare...) can be found 

and should be referenced at: 

http://www.ecobind.com/research/Evaluating_the_Contribution.pdf (last accessed 

October 9, 2009). Indeed, any and all the reference particularly from the EPA, 

GEOMET, Versar or industry groups should be identified by their web links, if 

available, and if not available on the web, should be considered for posting online 

with a link. 

The two additional references indicated above (Murray and Burmaster on residential 

ventilation rate database and Jayjock on “Backpressure” modeling) should be 

considered for inclusion. 

3.2) Does the model documentation present the model construct, selected model inputs, 

model results in a clear, complete and useful manner? If not, specifically note 

areas that are unclear or needs improving. Provide suggestions for additionally 

information. 

As mentioned above, I see the clarity and consistency of explanation as a real strength 

of this documentation. At the risk of repeating myself – this is a complicated modeling 

construct. I believe that the author of the documentation is particularly gifted in 

providing a plan and useful explanation of all the various facets of the work. It 

definitely requires considerable study on the part of the reader to understand work but 

the author has acquitted his or herself very well in this process. 

A personal preference for improvement that occurred to me while reading the 

document involves the ordering of Chapters 2 and 3. As I was beginning to read the 

information in Chapter 2 (USER INTERFACE) I found myself compelled to go and 
3-20

read Chapter 3 (MODEL CALCULATIONS AND ASSUMPTIONS). For me it 

would be more logical to change the order of these chapters. 

In another relatively minor area I found the use of “D” on page 3-4 to be unnecessarily 

complex. My advice is to simply incorporate the “D” algorithm in the Eqn 3-6 and 3.8. 

3.3) Does the documentation for the FIAM - PWP make clear the sources and 

anticipated magnitudes of variability and uncertainty in model results? Describe 

any additional information that you would find useful. 

I believe that the author does a particularly good job of indicating the sources of 

relative uncertainty within the model itself and within the basic data-sets and 

relationships that feed the tool; however, I would have liked to see a level of 

quantitative uncertainty analysis such as described above and herein. Specifically, the 

author should consider presenting a range of outputs caused by a reasonably 

anticipated range of input variables within all the particular categories (e.g., standard 

temperature (23C) and humidity (50% RH) algorithm parameter ranges, temperature 

and humidity ranges). That is, I would like to see a section (perhaps an appendix) in 

which the author approaches the estimation of indoor air formaldehyde levels through 

the eyes of a user. This would involve picking reasonable parameters for specific 

source strengths, temperature and humidity that might realistically maximize the 

estimate and then doing the same exercise with parameters that would minimize the 

predictions. This could provide the reader with a quantitative measure of the 

anticipated range of variability for the tool. 

3.4) Are the model algorithms consistent with the descriptions in the model 

documentation? If not, specifically note areas that are inconsistent between the 

model and documentation. 

Indeed, from what I can determine from studying this work the model algorithms are 

for the most part consistent with their descriptions in the model documentation. I did 

detect either an error in sign or the omission of an explanation in the correlation 

coefficients presented in Table 2-2. All of the coefficients have a negative sign and we 
3-21

are told in footnote g that they are the “Correlation coefficient between the calculated 

emission rate and the measured chamber concentration”. Clearly, emission rate and 

concentration should be positively correlated. I would also prefer to see this “fit 

relationship” described as the correlation coefficient squared (R2) because this value 

represents the percentage of the variance in the model described by the algorithm. For 

example, a correlation coefficient R = 0.72 equals R2 = 0.52 indicating that 52% of the 

variance in the data is attributable to the fit of the linear relationship and 48% is in 

random error or noise. 

3-23

3.3 Panos Georgopoulos Review Comments

Review of the 

Formaldehyde Indoor Air Exposure Model – Pressed Wood Products (FIAM-pwp) 

Work Assignment No. 5-10 

Contract No. EP-W-05-014 

Part 1. Algorithms and Exposure Assumptions 

1.1) Are the mathematical equations adequately explained, are they appropriate and are they 

accurately executed? What is your level of confidence in the indoor air concentrations and 

exposure estimates provided by the model? Please provide your rationale for determining the 

level of confidence. If the level of confidence is low, please provide the details as to why. 

Specifically, note any areas where errors were found, areas for improvement, or alternate 

calculation methodologies. 

The mathematical/algorithmic formulation and the computational implementation of the model 

under review (FIAM-pwp) are adequately explained, with sufficient clarity and level of detail; the 

computational implementation of the model also appears robust and accurate. Characterizing the 

mathematical equations (i.e. the basic formulation and assumptions of the model) as 

“appropriate,” as per question 1.1, depends of course on the types of questions the model is 

supposed to answer, and the desired accuracy/precision that is expected - or, at least, desired - for 

a given application. Nevertheless, given the simplifying assumptions (discussed further in the 

following paragraphs) in the formulation of the model, and the significant variabilities inherent in 

the data sets that were used to derive parameter values for FIAM-pwp, the level of confidence in 

the indoor air concentration and exposure estimates provided by the model, should in general be 

considered, at most, medium. In this reviewer’s opinion, the uncertainty and variability levels in 

the available data strongly suggest the need for a distributional/probabilistic model formulation 

that explicitly employs available data to develop ranges rather than point estimates of 

concentrations and exposures. 

Considering the (current) model formulation, FIAM-pwp essentially consists of three 

components, i.e. (a) estimation of formaldehyde emission rates from various types of pressed 

wood products (based on data from various field and chamber studies), (b) estimation of indoor 

mixing/dispersion through simple one-zone and two-zone models that incorporate sink and backpressure effects, and (c) simple inhalation exposure calculations that employ average intakes for 

adults and of children in different age groups. Clearly, the unique - and most valuable - 
3-24

component of the model is component (a), i.e. the estimation of HCHO emission rates, as a wide 

variety of far more comprehensive models exist for either characterizing indoor air quality 

(addressing transport and mixing at various levels of detail as well as incorporating indoor air 

chemistry and physical transformations etc.) or assessing inhalation exposures and dosimetry. In 

this reviewer’s opinion, a major drawback in the formulation of the FIAM-pwp is that 

components (a) and (b) are not “separated” in a way that would allow, in a straightforward 

manner, usage of the formaldehyde emission rates with other available indoor air quality and 

inhalation exposure models. Of course, for any given real-world application, there will be various 

bi-directional “links” and “feedback mechanisms” between such models (i.e. effects of airborne 

concentration levels on emission and sink rates etc.); however, the approach taken in the 

mathematical formulation of FIAM-pwp “lumps” these mechanisms in a manner that limits the 

usage and evaluation of individual model components. Specifically, though the literature – as 

well as the provided model documentation – explicitly recognize the fact that formaldehyde 

emission rates from pressed wood products decrease with time, the mathematical formulation of 

components (a) and (b) of FIAM-pwp is based on the assumptions of constant rate emissions and 

the establishment of steady state for indoor air concentration levels (see Sections 3.1 to 3.4 of 

model documentation). Then, (see Sections 3.5 to 3.6), a decay rate is imposed upon indoor 

concentrations, to account for depletion of the formaldehyde sources; this decay rate is 

parameterized (through half-life values) from experimental data so as for modeled concentration 

trends to fit the observations. The role of sinks, as well as of potential “new” and “unknown” 

sources is, of course, recognized in the literature, as well as in the model documentation: these 

factors are essentially “lumped” in the phenomenological/apparent concentration decay rate, that 

obviously is affected by a variety of chemical and physical transformations that either add or 

remove formaldehyde molecules to/from indoor air. It should in fact be expected that “sources” 

(including chemical reactions) of formaldehyde other than pressed wood products may affect the 

parameterization of concentration decay from experimental data. (Various relevant references are 

listed in an Addendum to the present review). In this reviewer’s opinion, the value of the 

information that has been incorporated in FIAM-pwp would be greatly enhanced if its 

formulation explicitly considered decaying (e.g. exponentially decreasing) emission rates and 

provided appropriate formulas for implementing them (either within FIAM-pwp or in conjunction 

with other, more comprehensive, indoor air quality and inhalation exposure systems). Simple 

implementations of exponentially decaying source with one-zone and two-zone indoor air models 

are well established (see, e.g. AIHA, 2000, Mathematical Models for Estimating Occupational 

Exposure to Chemicals). Estimations of exponentially decaying formaldehyde emission rates 

have in fact been pursued in the past and have appeared long-ago in the scientific literature (see, 
3-25

e.g., Brown, Indoor Air, 1999; 9:209-215 and other related references in the Addendum of this 

review). 

1.2) Comment on the default scenarios and default assumptions used by the model. Are the default 

assumptions reasonable and adequately supported by relevant scientific data? If not, 

specifically note any unreasonable assumptions. Provide suggestions and references for 

alternate default assumptions. 

Key default assumptions in the formulation of the FIAM-pwp (e.g. constant emission rates etc.) 

were discussed in detail above, in the answer to Question 1.1, as these assumptions in fact “drive” 

the mathematical equations of the model. Other assumptions involved in the formulation of 

specific scenarios should be considered generally reasonable, as long as the model results are not 

being “over-interpreted” by the user in terms of their accuracy and precision. 

1.3) Comment on the data sources. Are the data sources reasonable and accurate? If not, 

specifically note any unreasonable or inaccurate data source. Provide suggestions and 

references for alternate data sources. 

The data sources for FIAM-pwp appear reasonable – and they do in fact contain valuable 

information that has not been fully utilized up to now in modeling analyses. However, since most 

of them appear be to rather old, one may question whether they are still the most relevant data 

sources in relation to currently available/used pressed wood products (given changes in 

manufacturing procedures as well as in changes in relative levels of domestically manufactured 

versus imported pressed wood products). The answer may in fact be yes, but it should be 

explicitly stated and supported. 

1.4) Do the data sources provide unused information that would assist in quantifying uncertainty or 

variability for subsequent model use? 

Yes: the variability in the available data could be used to derive distributional estimates of 

emission rates that would support probabilistic (and population based) indoor concentration and 

corresponding exposure estimates with explicit characterization of uncertainties and variabilities. 

1.5) Do the model input variables and the estimates assigned to them appropriately reflect 

variability? 

As mentioned in the answers to previous questions, a distributional/probabilistic approach, for 

defining model input variables and deriving concentration and exposure estimates, would, in this 
3-26

reviewer’s opinion, be more appropriate in relation to this model, given the wide ranges of 

uncertainties in processes affecting the estimated variables and of variabilities in real world 

scenarios of inhalation exposures to formaldehyde. 

1.6) Has EPA provided adequate documentation of the overall plausibility of the exposure estimates 

generated by the exposure model? If not, provide suggestions for characterizing the exposure 

assessment estimates. 

Ideally, the exposure estimates that are derived from FIAM-pwp should be characterized within a 

total exposure context that would take into account influences of numerous other indoor and 

outdoor sources and sinks as well as of indoor and outdoor gas and heterogeneous phase 

chemistry of formaldehyde (that may result in net production or removal in a given 

microenvironment). Very large variabilities should be expected across regions and populations, 

with differences in both geographical (e.g. climate variables) and socioeconomic factors (housing, 

occupation, etc.) driving these variabilities. Linking such estimates with corresponding 

population-based estimates of exposure to outdoor air formaldehyde (e.g. from the National Air 

Toxic Assessment [NATA] studies) would be very useful in that context. Comparison of model 

estimates with relevant observational data sets for indoor-outdoor relationships and of personal 

level (e.g. from studies such as RIOPA – see, e.g., the Liu et al., 2006, reference in the 

Addendum of this review) would be valuable in assessing, at least qualitatively, the plausibility 

and relevance of the exposure estimates derived from FIAM-pwp. 

1.7) Are there any other types of data to assess the reliability of the overall exposure model or 

specific model elements? If so, provide suggestions and references for alternate data types. 

There are various studies and related data sets, both from the US and abroad, that have appeared 

in recent years and could - potentially - be used for evaluation of specific FIAM-pwp elements. 

The Addendum to this review contains a selection of literature references pertaining to such 

studies and data sets. 

Part 2. User Interface 

2.1) Is the FIAM -PWP easy to use? Specifically note any data entry screens you found confusing 

or unclear. Provide suggestions to improve the user-friendliness of the model. 
3-27

FIAM-pwp is a web-base program that is easy to use at the “client side” through a browser (MS 

Internet Explorer). Microsoft technology appears to be used throughout the implementation. 

Local use of the program in its current form would still require setting it up so it is accessed by 

the browser – this requires adjusting local computer settings (Internet Information Server, 

.NET/Framework/V2.0, etc.) in ways that may be challenging for some systems – and users. 

Nevertheless, the web-based version is sufficiently “user-friendly” and the data entry screens are 

clear. However, it should be pointed out that (as experience, especially with students, shows) a 

“well-polished” and “user-friendly” interface often raises (probably subconsciously) expectations 

regarding the precision and accuracy of the model calculated estimates. This is particularly true 

for a model with a deterministic formulation that performs point calculations like FIAM-pwp. 

Therefore, maybe some “warnings” regarding the level of uncertainties in the calculations could 

be incorporated, as reminders, in the data-entry screens. 

2.2) Are the model help screens adequate? Describe any additional help screens that you would find 

useful. 

The model-help screens appear generally adequate; they could be enhanced by including some 

statements regarding the level of precision expected for some of the entries (that should be 

consistent with the high uncertainty in the estimates; in other words, it should, e.g., be made clear 

to the user that higher precision of the inputs does not necessarily produce improved model 

estimates). 

Part 3. Documentation 

3.1) Are the references accurately identified? Would any additional reference citations be helpful? 

Please note any additional references that should be cited. 

The Addendum to this review presents a selection of references on indoor air formaldehyde 

emissions, concentration levels, and relevant physicochemical processes; the selection includes 

both experimental (field and laboratory studies) and modeling studies. This reviewer would 

recommend consideration of at least some of these references in future revisions of FIAM-pwp 

and its documentation. 

3.2) Does the model documentation present the model construct, selected model inputs, model 

results in a clear, complete and useful manner? If not, specifically note areas that are unclear 

or needs improving. Provide suggestions for additionally information. 
3-28

The documentation for FIAM-pwp is quite thorough in presenting the model formulation and 

implementation as well as the data sources that were used to develop parameter estimates for this 

implementation. One could note that there are some minor “awkward” points that could be fixed 

with careful editing (e.g. one reads on page 2-7 that “the flows from/to outside are exactly half 

the house volume” forgetting the temporal element in the concept of flow, while degrees Kelvin 

are denoted as oK rather than K, etc.). However, the main issue with the documentation is the 

justification of the formulation of certain elements of the model per se (e.g. the assumption of 

constant rather than decreasing emission rates, etc.) rather than of potential alternatives. 

3.3) Does the documentation for the FIAM -PWP make clear the sources and anticipated 

magnitudes of variability and uncertainty in model results? Describe any additional 

information that you would find useful. 

Though extensive information on the data that were used for the model is included, in this 

reviewer’s opinion, the types and the extents of variability and uncertainty associated with 

various model elements are not fully revealed in the documentation. An ideal solution would be a 

probabilistic “re-formulation” of the model, with explicit discussion in the documentation of the 

appropriate distributions of values for the various inputs. As an alternative, even with a 

deterministic formulation of the model, a table listing explicitly various sources of uncertainty 

and variability associated with specific processes and parameters of the model, along with a 

factor or range specifying the approximate magnitude of each uncertainty/variability, would be 

extremely useful. 

3.4) Are the model algorithms consistent with the descriptions in the model documentation? If not, 

specifically note areas that are inconsistent between the model and documentation. 

The model algorithms appear consistent with model documentation; issues with the algorithms 

were addressed in the answers to questions of Part 1. 

Concluding Comments 

Overall, it should be stated that the model under review is the result of a serious and 

commendable effort and represents an important step towards fulfilling a critical need to develop 

a scientifically valid framework for the characterization of human exposures to formaldehyde. 

Given the enormous complexity of this problem, it should be recognized that additional steps will 

be needed. In this reviewer’s opinion, development of statistical distributions of emission rates 
3-29

for different pressed wood products, that explicitly incorporate and quantify the uncertainty and 

variability in available data, is a much needed next step. 

ADDENDUM: 

Selected References on Indoor Formaldehyde Emissions and Concentrations 

Ataka, Y., S. Kato, et al. (2004). "Study of effect of adsorptive building material on formaldehyde 

concentrations: development of measuring methods and modeling of adsorption phenomena." Indoor Air

14: 51-64. 

 In this paper, a method is developed to assess the performance of adsorptive building materials 

that are used for reducing indoor pollutant concentrations. Mass transfer has a great influence on 

the materials' performance. To control the mass transfer rate precisely in the performance test, the 

authors have developed the Boundary-Layer-Type Small Test Chamber in which airflow along 

the test materials can be controlled precisely. A new index of adsorption performance, the 

equivalent ventilation rate (Q(ads)), is defined that corresponds to the mass transfer coefficient 

when the surface pollutant concentration is zero. Modeling and experimental verification of 

adsorption were done, demonstrating the pollutant concentration decrease caused by adsorptive 

building materials. The pollutant reduction phenomena were modeled, including pollutant 

degradation by chemical reaction and adsorption in building materials. Adsorption tests of 

gypsum board containing a substance that decomposes HCHO within the board are reported. The 

adsorption rate of the gypsum board predicted-by numerical analysis (CFD, Computational Fluid 

Dynamics) corresponds well with experimental results. 

Bennett, J. S., C. E. Feigley, et al. (2003). "Comparison of Emission Models With Computational 

Fluid Dynamic Simulation and a Proposed Improved Model." AIHA Journal 64: 739–754. 

 Understanding source behavior is important in controlling exposure to airborne 

contaminants. Industrial hygienists are often asked to infer emission information from 

room concentration data. This is not easily done, but models that make simplifying 

assumptions regarding contaminant transport are frequently used. The errors resulting 

from these assumptions are not yet well understood. This study compares emission 

estimates from the single-zone completely mixed (CM-1), two-zone completely mixed 

(CM-2), and uniform diffusivity (UD) models with the emissions set as boundary 

conditions in computational fluid dynamic (CFD) simulations of a workplace. The room 
3-30

airflow and concentration fields were computed using Fluent 4. These numerical 

experiments were factorial combinations of three source locations, five receptor 

locations, three dilution airflow rates, and two generation rate profiles, constant and 

timevarying. The aim was to compute plausible concentration fields, not to simulate 

exactly the processes in a real workroom. Thus, error is defined here as the difference 

between model and CFD predictions. For the steady-state case the UD model had the 

lowest error. When the source near-field contained the breathing zone receptor, the CM-2 

model was applied. Then, in decreasing agreement with CFD were UD, CM-2, and CM1. Averaging over all source and receptor locations (CM-2 applied for only one), in 

decreasing order of agreement with CFD were UD, CM-1, and CM-2. Source and 

receptor location had large effects on emission estimates using the CM-1 model and some 

effect using the UD model. A location-specific mixing factor (location factor) derived 

from steady-state concentration gradients was used to build a more accurate timedependent emission model, CM-L. Total mass emitted from a timevarying source was 

modeled most accurately by CM-L, followed by CM-1 and CM-2. 

Bi, X., G. Sheng, et al. (2005). "Gas- and particulate-phase specific tracer and toxic organic compounds in 

environmental tobacco smoke." Chemosphere 61(10): 1512-22. 

 Cigarette smoke constituents are worthy of concern and characterized as carcinogens. Different 

experiment conditions may affect the environmental tobacco smoke (ETS) constituents. A study 

was undertaken in a 75.5-m3 spare office to evaluate ETS constituents in a real environment. 

Thirty-four volatile organic compounds (VOCs) including three ETS tracers: nicotine, 2,5-

dimethylfuran and 3-ethenylpyridine (3-EP), 19 carbonyl compounds, 54 semi-volatile 

compounds (24 polycyclic aromatic hydrocarbons (PAHs) and 30 alkanes) as well as CO and 

total particulate matter (TPM) from 15 leading commercial brands were determined. ETS 

constituents did not increase with increasing cigarette tar. ETS tracers nicotine and 3-EP were 

affected greatly due to more sorption and surface reactions in real world compared to other 

studies conducted in chamber, which resulted in 2-5 times lower. Benzene, toluene, ethylbenzene, 

xylenes, acrolein, 2-butanone and the high molecular weight compounds exhibited little affect. 

Pearson correlation analyses show that gas-phase and particulate-phase ETS tracers did not show 

significant correlation, but within each homologue many of compounds correlated significantly. 

Indole and cholesta-3,5-diene were also detected in ETS. These results may be useful in efforts to 

better understand the health effect of ETS exposure and source apportionment. 
3-31

Brown, S. K. (1999). "Chamber assessment of formaldehyde and VOC emissions from wood-based 

panels." Indoor Air-International Journal of Indoor Air Quality and Climate 9(3): 209-215. 

 Volatile organic emissions from particleboard, medium density fibreboard (MDF) and office 

furniture have been measured in dynamic environmental chambers, both small and room-sized. 

Characterisation of product emission properties in small chambers was possible when inter- and 

intra-sheet variations were considered. Formaldehyde emission factors for all products were 

approximately double European low-emission specifications and did not decay to the latter for 

several months. Long term emission behaviour could not be predicted from short-term 

measurements. Volatile organic compounds (VOC) emissions were low for the MDF product, 

higher for particleboard, and highest for laminated office furniture. The compounds emitted 

differed from those reported in other countries. VOC emissions from the sheet products decreased 

more quickly than formaldehyde, reaching low levels within two weeks, except for MDF which 

was found to become a low-level source of hexanal after several months. 

Brown, S. K., K. J. Mahoney, et al. (2004). "Room chamber assessment of the pollutant emission 

properties of (nominally) low-emission unflued gas heaters." Indoor Air 14 (Suppl 8): 84-91. 

 Pollutant emissions from unflued gas heaters were assessed in CSIRO’s Room Dynamic 

Environmental Chamber. This paper describes the chamber assessment procedure and presents 

findings for major commercial heaters that are nominally ‘‘low-emission’’. The chamber was 

operated at controlled conditions of temperature, humidity, ventilation and air mixing, 

representative of those encountered in typical indoor environments. A fixed rate of heat removal 

from the chamber air ensured that the heaters operated at constant heating rates, typically ~6 MJ/h 

which simulated operation of a heater after warm-up in an insulated dwelling in south-east 

Australia. The pollutants assessed were nitrogen dioxide, carbon monoxide, formaldehyde, VOCs 

and respirable suspended particulates. One type of heater was lower emitting for nitrogen dioxide, 

but emitted greater amounts of carbon monoxide and formaldehyde (the latter becoming 

significant to indoor air quality). When operated with low line pressure or slight misalignment of 

the gas burner, this heater became a hazardous source of these pollutants. Emissions from the 

heaters changed little after continuous operation for up to 2 months. 

Budaiwi, I. M. and M. S. Al-Homoud (2001). "Effect of ventilation strategies on air contaminant 

concentrations and energy consumption in buildings." International Journal of Energy Research

25(12): 1073-1089. 

 Considering the diversity of indoor contaminant characteristics and generation patterns, 

finding an appropriate ventilation strategy that can secure acceptable indoor air quality 
3-32

with minimum energy consumption is a challenging task for HVAC system designers and 

operators. This study theoretically models and investigates the impact of various 

ventilation strategies on contaminant concentration behaviour and corresponding 

ventilation cooling energy requirements for a single-zone enclosure. Two types of 

contaminants are considered; carbon dioxide as an occupancy dependent and 

formaldehyde, which is independent of occupancy. An airflow model is used to predict 

space pressure and air leakage rates across the enclosure envelope, and an air quality 

model is used to predict time-varying contaminant concentrations. In addition, a building 

energy simulation model is utilized to predict the corresponding ventilation cooling 

energy requirements under hot climatic conditions. Results from this study show that 

acceptable contaminant concentrations during occupied periods can be achieved by 

different ventilation strategies but at substantially different ventilation energy 

requirements. More than 50 per cent reduction in ventilation energy requirements can be 

obtained while maintaining acceptable IAQ if proper ventilation strategy is employed. 

Copyright (C) 2001 John Wiley & Sons, Ltd. 

Buyuksari, U., N. Ayrilmis, et al. (2010). "Evaluation of the physical, mechanical properties and 

formaldehyde emission of particleboard manufactured from waste stone pine (Pinus pinea L.) cones " 

Bioresource Technology 101(1): 255-259 

 The objective of this study was to investigate some physical/mechanical properties and 

formaldehyde emission of particleboard containing particles of waste stone pine cone at various 

usage ratios using urea–formaldehyde resin. Some physical (thickness swelling, water 

absorption), mechanical (modulus of elasticity, modulus of rupture, internal bond strength) 

properties and formaldehyde emission of particleboards were evaluated. The addition of cone 

particle improved water resistance of the panels and greatly reduced their formaldehyde 

emissions. However, flexural properties and internal bond strength decreased with increasing 

cone particle content in the panel. The cone of the stone pine can be considered as an alternative 

to wood material in the manufacture of particleboard used in indoor environment due to lower 

thickness swelling, water absorption and formaldehyde emission. 

Carslaw, N. (2007). "A new detailed chemical model for indoor air pollution." Atmospheric Environment

41(6): 1164-1179. 

 A detailed chemical box model has been constructed based on a comprehensive chemical 

mechanism (the Master Chemical Mechanism) to investigate indoor air chemistry in a typical 
3-33

urban residence in the UK. Unlike previous modelling studies of indoor air chemistry, the 

mechanism adopted contains no simplifications such as lumping or the use of surrogate species, 

allowing more insight into indoor air chemistry than previously possible. The chemical 

mechanism, which has been modified to include the degradation reactions of key indoor air 

pollutants, contains around 15,400 reactions and 4700 species. The results show a predicted 

indoor OH radical concentration up to 4.0 x 10(5) molecule cm(-3), only a factor of 10-20 less 

than typically observed outdoors and sufficient for significant chemical cycling to take place. 

Concentrations of PAN-type species and organic nitrates are found to be important indoors, 

reaching concentrations of a few ppb. Sensitivity tests highlight that the most crucial parameters 

for modelling the concentration of OH are the light-intensity levels and the air exchange rate. 

Outdoor concentrations of O-3 and NOX are also important in determining radical concentrations 

indoors. The reactions of ozone with alkenes and monoterpenes play a major role in producing 

new radicals, unlike outdoors where photolysis reactions are pivotal radical initiators. In terms of 

radical propagation, the reaction of HO2 with NO has the most profound influence on OH 

concentrations indoors. Cycling between OH and RO2 is dominated by reaction with the 

monoterpene species, whilst alcohols play a major role in converting OH to HO2. Surprisingly, 

the absolute reaction rates are similar to those observed outdoors in a suburban environment in 

the UK during the summer. The results from this study highlight the importance of tailoring a 

model for its particular location and the need for future indoor air measurements of radical 

species, nitrated species such as PANs and organic nitrates, photolysis rates of key species over 

the range of wavelengths observed indoors and concurrent measurements of outdoor air pollutant 

concentrations. (c) 2006 Elsevier Ltd. All rights reserved. 

Carter, R. D. and J. S. Zhang (2007). "Definition of Standard Office Environments for Evaluating the 

Impact of Office Furniture Emissions on Indoor VOC Concentrations, LB-07-049." ASHRAE 

Transactions 113, Part 2. 

 A representative “worst-case” office environment, which defines the size and volume of the 

office space, the amount and type of office furniture surface area, and the outdoor, clean airflow 

rate is necessary to estimate the impact of office furniture emissions on indoor VOC 

concentrations based on the emission rates measured from chamber tests. In this study, 31 

randomly selected floor plans from North American office buildings were analyzed in detail. The 

floor plans were from projects in late 2004 and early 2005 and were provided by an industry cross 

section of seven major office furniture manufacturers. 

 The analysis included documenting the potential emitting surface area for each 

workstation and a determination of how much common office space (aisles, etc.) was present and 
3-34

shared between workstations and other adjoining spaces. The 90th percentile conditions for total 

furniture surface area within the 50th percentile workstation footprint sizes were identified from 

the more than 5000 workstations analyzed to provide a representative “worst-case” office 

environment model (i.e., occupant exposure scenario). 

 Based on the analysis, the representative “worst-case” standard open plan office 

environment for a single workstation system is defined as 5.94 m2 (64 ft2) floor area by 2.74 m 

(9 ft) high (576 ft3 or 16.3 m3), accounting for a standard 1.83 m × 1.83 m (6 ft × 6 ft) open plan 

workstation system, traffic area, and support space for shared copiers, files, storage, etc. The 

space is assumed to be occupied by a single occupant and has an outdoor or clean air ventilation 

rate of 4.17 L/s (8.84 cfm), in accordance with ASHRAE Standard 62.1-2004. The representative 

“worst-case” standard private office environment for a single workstation system is defined as 

23.78 m2 (256 ft2) floor area by 2.74 m (9 ft) high (2304 ft3 or 65.2 m3), accounting for a 

standard 13.38 m2 (144 ft2) private office workstation system, traffic area, and support space for 

shared copiers, files, storage, etc. The space is assumed to be occupied by a single occupant and 

has an outdoor or clean air ventilation rate of 9.63 L/s (20.4 cfm) in accordance with ASHRAE 

Standard 62.1-2004. A comparison to historical office environment models is included. 

Chang, J. C. S., Z. S. Guo, et al. (2002). "Characterization and reduction of formaldehyde emissions from 

a low-VOC latex paint." Indoor Air 12(1): 10-16. 

 The patterns of formaldehyde emission from a low volatile organic compound (VOC) latex paint 

applied to gypsum board were measured and analyzed by small environmental chamber tests. It 

was found that the formaldehyde emissions resulted in a sharp increase of chamber air 

formaldehyde concentration to a peak followed by transition to a long-term slow decay. A semiempirical first-order decay in-series model was developed to interpret the chamber data. The 

model characterized the formaldehyde emissions from the paint in three stages: an initial "puff" 

of instant release, a fast decay, and a final stage of slow decay controlled by a solid-phase 

diffusion process that can last for more than a month. The model was also used to estimate the 

peak concentration and the amount of formaldehyde emitted during each stage. The formaldehyde 

sources were investigated by comparing emission patterns and modeling outcomes of different 

paint formulations. The biocide used to preserve the paint was found to be a major source of the 

formaldehyde. Chamber test results demonstrated that replacing the preservative with a different 

biocide for the particular paint tested resulted in an approximate reduction of 55% of 

formaldehyde emissions. But the reduction affected only the third-stage long-term emissions. 

Chen, J., B. Duffy, et al. (2001). "FTIR spectroscopy measurements and CFD simulations of the 
3-35

pollutants arising from unflued combustion in a room." Building and Environment 36(5): 597-

603. 

 This paper reports on a study of indoor air quality in a simulated kitchen environment. 

Combustion products from unflued combustion from a gas cook-top in a ventilated room 

were measured using an extractive FTIR technique. Results were compared with those 

from conventional instruments and the FTIR technique was shown to give good 

agreement. Detection limits and the effect of H2O and CO2 in obscuring the spectrum 

were studied, in addition, Computational Fluid Dynamics (CFD) was used to explore the 

conditions in the room and to assist with experimental design. This revealed a complex 

flow situation that can arise when the plume from the cook top interacts with the 

extraction hood. (C) 2001 Elsevier Science Ltd. All rights reserved. 

Choi, D. W., K. W. Moon, et al. (2009). "Indoor Volatile Organic Compounds in Atopy Patients' Houses 

in South Korea." Indoor and Built Environment 18(2): 144-154. 

 This study was undertaken to determine the concentrations of volatile organic compounds 

(VOCs) in the indoor air of atopy patients' (atopic dermatitis 50, allergic asthma 36) and control 

houses (28 nonpatients). A goal of this study was also to investigate whether indoor VOCs were 

risk factors for the development of atopic sensitization. Eleven alkanes, 13 aromatics, 7 

chlorinated hydrocarbons, 3 terpenes, and 15 aldehyds were measured from 10 March to 15 June, 

2006. Aldehyde compounds are the most abundant chemical group in all indoor air, followed by 

aromatic compounds. The geometric mean concentrations of total VOC (TVOC) in indoor air in 

atopic dermatitis and allergic asthma patients' houses were 317.1 and 219.2 mu g.m(-3), 

respectively. However, TVOC concentrations did not differ significantly between control and 

patient houses in indoor and outdoor air. The geometric mean concentrations of benzene, 

ethylbenzene (p < 0.05), o-xylene, m-, p-xylene, styrene, levels of 1,3,5-trimethylbenzene and 

formaldehyde (p < 0.01) in the indoor air of houses of patients with atopic dermatitis, and levels 

of o-xylene and 1,3,5-trimethylbenzene (p < 0.01) in houses of allergic asthma patients were 

significantly higher than those in control houses. The multiple linear regression model in this 

study indicated several indoor origins of VOCs. House age and floor or wall coverings that had 

been refurbished within 1 year were correlated with higher concentrations of formaldehyde. 

Limonene and alpha-pinene concentrations were significantly increased by the replacement of 

furniture and the use of cleaning products. The type of heating system was significantly 

associated with indoor benzene, toluene, ethylbenzene, nonane, decane, and undecane 

concentrations in atopy patient houses. 
3-36

Clarisse, B., A. M. Laurent, et al. (2003). "Indoor aldehydes: measurement of contamination levels and 

identification of their determinants in Paris dwellings." Environmental Research 92(3): 245-253. 

 The recent increased prevalence of childhood asthma and atopy has brought into question the 

impact of outdoor pollutants and indoor air quality. The contributory role of aldehydes to this 

problem and the fact that they are mainly derived from the domestic environment make them of 

particular interest. This study therefore measures six different aldehyde levels in Paris dwellings 

from potentially different sources and identifies their indoor determinants. The study was carried 

out in the three principal rooms of 61 flats with no previous history of complaint for olfactory 

nuisance or specific symptoms, two-thirds of the flats having been recently refurbished. 

Aldehydes were sampled in these rooms using passive samplers, and a questionnaire on potential 

aldehyde sources was filled out at the same time. A multiple linear regression model was used to 

investigate indoor aldehyde determinants. Our study revealed that propionaldehyde and 

benzaldehyde were of minor importance compared to formaldehyde, acetaldehyde, pentanal, and 

hexanal. We found that levels of these last four compounds depended on the age of wall or floor 

coverings (renovations less than I year old), smoking, and ambient parameters (carbon dioxide 

levels, temperature). These results could help in the assessment of ndoor aldehyde emissions. (C) 

2003 Elsevier Science (USA). All rights reserved. 

Daisey, J. M., K. R. R. Mahanama, et al. (1998). "Toxic volatile organic compounds in simulated 

environmental tobacco smoke: Emission factors for exposure assessment." Journal of Exposure Analysis 

and Environmental Epidemiology 8(3): 313-334. 

 Environmental tobacco smoke (ETS) is suspected to be a major source of exposure to many of the 

compounds identified as toxic air contaminants. However, we lack emission factors for many of 

the ETS air toxics for the brands of cigarettes which currently dominate the market and therefore 

cannot adequately estimate contributions of ETS to such exposures. This study provides up-todate emission factors for Selected air toxics and other volatile organic compounds (VOCs) in 

simulated ETS and uses them in a mass balance model to evaluate the potential contribution of 

ETS to air toxics in indoor air and, therefore to indoor exposures to air toxics. 

 Emission factors (mu g/cigarette) were determined for 21 VOCs (including two 

aldehydes), nicotine and particulate matter in a room-sized (20-m(3)) environmental chamber 

with stainless-steel walls, operated under static conditions, using diluted sidestream smoke (no 

exhaled mainstream smoke) to simulate ETS. Experiments were conducted for Kentucky 

Reference cigarette 1R4F and for each of six commercial cigarette brands with major market 

shares. The variabilities in the ETS emission factors among brands of cigarettes were relatively 
3-37

small, ranging from 16 to 31% (expressed as the coefficient of variation) among the six brands. 

 The concentrations of most of the VOCs did not change over the 4-hour periods of the 

experiments. However concentrations of 3-ethenylpyridine, phenol, o-cresol and m,p-cresol 

showed consistent decreases over time, indicating removal by means other than the very low air 

infiltration rate (0.03 h(-1)), e.g., deposition onto the chamber surfaces. Emission factors for these 

compounds were calculated to take these losses into account and the rate constants for these 

losses were estimated. 

 To estimate indoor concentrations and inhalation exposures to 16 VOCs, nicotine and 

PM-2.5, the average emission factors for the six commercial brands were used in a timedependent mass-balance model for two scenarios: a typical office building and art average 

residence. In general, the indoor concentrations of the air toxics from ETS, under conditions 

selected to be "typical" rather than extreme, are comparable in magnitude to average outdoor 

concentrations, indicating that ETS can be a significant contributor to the total indoor 

concentration and the inhalation exposure for these species. At higher smoking rates, exposures 

To VOCs from ETS could be several times higher than those modeled under more "typical" 

conditions. 

de Bruin, Y. B., K. Koistinen, et al. (2008). "Characterisation of urban inhalation exposures to benzene, 

formaldehyde and acetaldehyde in the European Union." Environmental Science and Pollution Research

15(5): 417-430. 

 Background, aim and scope All across Europe, people live and work in indoor environments. On 

average, people spend around 90% of their time indoors (homes, workplaces, cars and public 

transport means, etc.) and are exposed to a complex mixture of pollutants at concentration levels 

that are often several times higher than outdoors. These pollutants are emitted by different 

sources indoors and outdoors and include volatile organic compounds (VOCs), carbonyls 

(aldehydes and ketones) and other chemical substances often adsorbed on particles. Moreover, 

legal obligations opposed by legislations, such as the European Union's General Product Safety 

Directive (GPSD) and Registration, Evaluation, Authorisation and Restriction of Chemicals 

(REACH), increasingly require detailed understanding of where and how chemical substances are 

used throughout their life-cycle and require better characterisation of their emissions and 

exposure. This information is essential to be able to control emissions from sources aiming at a 

reduction of adverse health effects. Scientifically sound human risk assessment procedures based 

on qualitative and quantitative human exposure information allows a better characterisation of 

population exposures to chemical substances. In this context, the current paper compares 

inhalation exposures to three health-based EU priority substances, i.e. benzene, formaldehyde and 
3-38

acetaldehyde. 

 Materials and methods Distributions of urban population inhalation exposures, indoor 

and outdoor concentrations were created on the basis of measured AIRMEX data in 12 European 

cities and compared to results from existing European population exposure studies published 

within the scientific literature. By pooling all EU city personal exposure, indoor and outdoor 

concentration means, representative EU city cumulative frequency distributions were created. 

Population exposures were modelled with a microenvironment model using the time spent and 

concentrations in four microenvironments, i.e. indoors at home and at work, outdoors at work and 

in transit, as input parameters. Pooled EU city inhalation exposures were compared to modelled 

population exposures. The contributions of these microenvironments to the total daily inhalation 

exposure of formaldehyde, benzene and acetaldehyde were estimated. Inhalation exposures were 

compared to the EU annual ambient benzene air quality guideline (5 mu g/m(3)-to be met by 

2010) and the recommended (based on the INDEX project) 30-min average formaldehyde limit 

value (30 mu g/m(3)). 

 Results Indoor inhalation exposure contributions are much higher compared to the 

outdoor or in-transit microenvironment contributions, accounting for almost 99% in the case of 

formaldehyde. The highest in-transit exposure contribution was found for benzene; 29.4% of the 

total inhalation exposure contribution. Comparing the pooled AIRMEX EU city inhalation 

exposures with the modelled exposures, benzene, formaldehyde and acetaldehyde exposures are 

5.1, 17.3 and 11.8 mu g/m(3) vs. 5.1, 20.1 and 10.2 mu g/m(3), respectively. Together with the 

fact that a dominating fraction of time is spent indoors (> 90%), the total inhalation exposure is 

mostly driven by the time spent indoors. 

 Discussion The approach used in this paper faced three challenges concerning exposure 

and time-activity data, comparability and scarce or missing in-transit data inducing careful 

interpretation of the results. The results obtained by AIRMEX underline that many European 

urban populations are still exposed to elevated levels of benzene and formaldehyde in the inhaled 

air. It is still likely that the annual ambient benzene air quality guideline of 5 mu g/m(3) in the EU 

and recommended formaldehyde 30-min average limit value of 30 mu g/m(3) are exceeded by a 

substantial part of populations living in urban areas. Considering multimedia and multi-pathway 

exposure to acetaldehyde, the biggest exposure contribution was found to be related to dietary 

behaviour rather than to inhalation. 

 Conclusions In the present study, inhalation exposures of urban populations were 

assessed on the basis of novel and existing exposure data. The indoor residential 

microenvironment contributed most to the total daily urban population inhalation exposure. The 

results presented in this paper suggest that a significant part of the populations living in European 
3-39

cities exceed the annual ambient benzene air quality guideline of 5 mu g/m(3) in the EU and 

recommended (INDEX project) formaldehyde 30-min average limit value of 30 mu g/m(3). 

 Recommendations and perspectives To reduce exposures and consequent health effects, 

adequate measures must be taken to diminish emissions from sources such as materials and 

products that especially emit benzene and formaldehyde in indoor air. In parallel, measures can 

be taken aiming at reducing the outdoor pollution contribution indoors. Besides emission 

reduction, mechanisms to effectively monitor and manage the indoor air quality should be 

established. These mechanisms could be developed by setting up appropriate EU indoor air 

guidelines. 

Delgado-Saborit, J. M., N. J. Aquilina, et al. (2009). "Model Development and Validation of Personal 

Exposure to Volatile Organic Compound Concentrations." Environmental Health Perspectives 117(10): 

1571-1579. 

 Direct measurement of exposure to volatile organic compounds (VOCs) via personal monitoring 

is the most accurate exposure assessment method available. However, its wide-scale application 

to evaluating exposures at the population level is prohibitive in terms of both cost and time. 

Consequently, indirect measurements via a combination of microenvironment concentrations and 

personal activity diaries represent a potentially useful alternative. 

 Objective: The aim of this study was to optimize a model of personal exposures (PEs) 

based on microenvironment concentrations and time/activity diaries and to compare modeled 

with measured exposures in an independent data set. 

 Materials: VOC PEs and a range of microenvironment concentrations were collected with 

active samplers and sorbent tubes. Data were supplemented with information collected through 

questionnaires. Seven models were tested to predict PE to VOCs in 75% (n = 370) of the 

measured PE data set, whereas the other 25% (n = 120) was used for validation purposes. 

 Results: The best model able to predict PE with independence of measurements was 

based upon stratified microenvironment concentrations, lifestyle factors, and individual-level 

activities. The proposed model accounts for 40–85% of the variance for individual VOCs and was 

validated for almost all VOCs, showing normalized mean bias and mean fractional bias below 

25% and predicting 60% of the values within a factor of 2. 

 Conclusions: The models proposed identify the most important non-weather-related 

variables for VOC exposures ; highlight the effect of personal activities, use of solvents, and 

exposure to environmental tobacco smoke on PE levels ; and may assist in the development of 

specific models for other locations. 
3-40

Eklund, B. M., S. Burkes, et al. (2008). "Spatial and temporal variability in VOC levels within a 

commercial retail building." Indoor Air 18(5): 365-374. 

 A study was performed to characterize the concentration of dozens of volatile organic compounds 

(VOCs) at 10 locations within a single large building and track these concentrations over a 2-year 

period. The study was performed at a shopping center (strip mall) in New Jersey. A total of 130 

indoor air samples were collected from 10 retail stores within the shopping center and analyzed 

for 60 VOCs by US EPA Method TO-15. Indoor concentrations of up to 55,100 mu g/m(3) were 

measured for individual VOCs. The indoor/outdoor ratio (I/O) was as high as 1500 for acetone 

and exceeded 100 at times for various compounds, indicating that significant indoor air sources 

were present. A large degree of spatial variability was observed between stores within the 

building, with concentrations varying by three to four orders of magnitude for some compounds. 

The spatial variability was dependent on the proximity of the sampling locations to the indoor 

sources. A large degree of temporal variability also was observed for compounds emitted from 

indoor sources, but the temporal variability generally did not exceed two standard deviations 

(sigma). For compounds not emitted from indoor sources at significant rates, both the spatial and 

temporal variability tended to range within an order of magnitude at each location. 

Gilbert, N. L., D. Gauvin, et al. (2006). "Housing characteristics and indoor concentrations of nitrogen 

dioxide and formaldehyde in Quebec City, Canada." Environmental Research 102(1): 1-8. 

 Concentrations of nitrogen dioxide and formaldehyde were determined in a study of 96 homes in 

Quebec City, Canada, between January and April 2005. In addition, relative humidity, 

temperature, and air change rates were measured in homes, and housing characteristics were 

documented through a questionnaire to occupants. Half of the homes had ventilation rates below 

7.5 L/s person. Nitrogen dioxide (NO2) and formaldehyde concentrations ranged from 3.3 to 29.1 

mu g/m(3) (geometric mean 8.3 mu g/m(3)) and from 9.6 to 90.0 mu g/m(3) (geometric mean of 

29.5 mu g/m(3)), respectively. The housing characteristics documented in the study explained 

approximately half of the variance of NO2 and formaldehyde. NO2 concentrations in homes were 

positively correlated with air change rates (indicating a significant contribution of outdoor 

sources to indoor levels) and were significantly elevated in homes equipped with gas stoves and, 

to a lesser extent, in homes with gas heating systems. Formaldehyde concentrations were 

negatively correlated with air change rates and were significantly elevated in homes heated by 

electrical systems, in those with new wooden or melamine furniture purchased in the previous 12 

months, and in those where painting or varnishing had been done in the sampled room in the 

previous 12 months. Results did not indicate any significant contribution of indoor combustion 

sources, including wood-burning appliances, to indoor levels of formaldehyde. These results 
3-41

suggest that formaldehyde concentrations in Quebec City homes are caused primarily by offgassing, and that increasing air change rates in homes could reduce exposure to this compound. 

More generally, our findings confirm the influence of housing characteristics on indoor 

concentrations of NO2 and formaldehyde. Crown Copyright (c) 2006 Published by Elsevier Inc. 

All rights reserved. 

Gilbert, N. L., M. Guay, et al. (2008). "Air change rate and concentration of formaldehyde in residential 

indoor air." Atmospheric Environment 42(10): 2424-2428. 

 The purpose of this study was to investigate the relationship between air change rates and indoor 

concentrations of formaldehyde. Concentrations of formaldehyde and air change rates were 

measured in 96 homes in Quebec City, Canada, in winter 2005. House characteristics such as 

heating systems or recent renovations were also documented. Formaldehyde concentrations were 

regressed to air change rates among the entire sample and among some sub-samples of homes, 

and predictive intervals were computed. The air change rate ensuring a formaldehyde 

concentration below Health Canada's guideline value of 50 mu g m(-3) in 95% of homes was 0.26 

h(-1) based on the entire sample, 0.34 h-1 in homes with recent off-gassing sources of 

formaldehyde, and 0.37 h(-1) in homes heated mainly by electrical baseboard heaters. These 

results indicate that ventilation effectively decreases formaldehyde concentrations, but some 

categories of homes such as those with new off-gassing sources and homes heated by electrical 

baseboard heaters may require a higher air change rate to keep their formaldehyde levels within 

Health Canada's guidelines. (c) 2008 Elsevier Ltd. All rights reserved. 

Gilbert, N. L., M. Guay, et al. (2005). "Levels and determinants of formaldehyde, acetaldehyde, and 

acrolein in residential indoor air in Prince Edward Island, Canada." Environmental Research 99(1): 11-17. 

 This study was undertaken to determine the concentrations of formaldehyde, acetaldehyde, and 

acrolein in air samples taken in some Canadian houses and to determine the association between 

aldehyde levels and housing characteristics. Concentrations of formaldehyde, acetaldehyde, and 

acrolein were measured in 59 homes in Prince Edward Island, Canada, during the winter of 2002. 

Housing characteristics were documented through inspection and by interviews of occupants. 

Formaldehyde, acetaldehyde, and acrolein concentrations ranged from 5.5 to 87.5 mu g/m(3) 

(median, 29.6 mu g/m(3)), from 4.4 to 79.1 mu g/m(3) (median, 18.9 mu g/m(3)), and from 0.1 to 

4.9 mu g/m(3) (median, 0.9 mu g/m(3)), respectively. Formaldehyde levels were elevated in 

homes built after 1970. Acetaldehyde and acrolein levels were elevated in homes inhabited by at 

least one smoker and in homes built 1970-1985 and were correlated with absolute humidity and 

carbon dioxide, two variables likely to be surrogates for lower air exchange rates. In conclusion, 
3-42

lower air exchange rates appear to be important determinants of formaldehyde, acetaldehyde, and 

acrolein levels in homes. These data also confirm that smoking is a significant source of 

acetaldehyde and acrolein and indoor air. Crown Copyright (c) 2004 Published by Elsevier Inc. 

All rights reserved. 

Gillett, R. W., H. Kreibich, et al. (2000). "Measurement of indoor formaldehyde concentrations with a 

passive sampler." Environmental Science & Technology 34(10): 2051-2056. 

 An existing Ferm type passive sampler technique has been further developed to measure 

concentrations of formaldehyde gas in indoor air. Formaldehyde forms a derivative after reaction 

with a filter coated with 2,4-dinitrophenylhydrazine (2,4-DNPH). The formaldehyde 2,4-

dinitrophenylhydrazine derivative (formaldehyde-2,4-DNPH) is extracted from the filter, and the 

concentration is determined by high performance liquid chromatography. The technique has been 

Validated against an active sampling method, and the agreement is close when the appropriate 

laminar boundary layer depth is applied to the passive measurement. For this technique an 

exposure period of 3 days is equivalent to a limit of detection of formaldehyde of 3.4 ppbv and a 

limit of quantification of 7.6 ppbv. To test the performance of the passive samplers ambient 

formaldehyde measurements were carried out inside homes and in a range of workplace 

environments. 

Godish, T. (2001). Aldehydes. Indoor Air Quality Handbook. J. D. Spengler, J. Samet and J. McCarthy, 

McGraw-Hill Publishing Company, New York. 

Groah, W. J. (2006). "Predicting indoor-air formaldehyde concentrations from emissions of ureaformaldehyde-bonded wood products using the Versar model." Forest Products Journal 56(10): 97-100. 

 The Versar mathematical model, an outgrowth of research by the Environmental Protection 

Agency (EPA), is a tool for making home projections of formaldehyde concentrations. The 

model, based on mass balance principles, can accommodate input information from up to six 

formaldehyde sources. Laboratory data were available characterizing emission characteristics of 

four primary wood product formaldehyde sources used in an EPA and Composite Panel 

Association (CPA) home study project. Using product source inputs, Versar initial home 

concentration outputs were reasonably consistent with measured formaldehyde in the test home, 

particularly when the gypsum wallboard sink/re-emitter was considered a fifth formaldehyde 

source in the model. 

Guo, H., N. H. Kwok, et al. (2009). "Formaldehyde and volatile organic compounds in Hong Kong 
3-43

homes: concentrations and impact factors." Indoor Air 19(3): 206-217. 

 This paper presents formaldehyde and volatile organic compounds (VOC) concentrations, 

potential sources and impact factors in 100 homes. The 24-h average formaldehyde concentration 

in 37 homes exceeded the good class of the Hong Kong Indoor Air Quality Objectives 

(HKIAQO), whereas the total VOCs concentration in all homes was lower than the HKIAQO. 

Compared to other East Asian cities, indoor formaldehyde and styrene in Hong Kong was the 

highest, reflecting that the homes in Hong Kong were more affected by household products and 

materials. The formaldehyde concentration in newly built apartments was significantly higher 

than that in old buildings, whereas no relationship between the concentration and the building age 

was found for VOCs. There was no difference for formaldehyde and toluene between smoking 

and non-smoking homes, suggesting that cigarette smoking was not the major source of these two 

species. Homes of a couple with a child had higher formaldehyde and acetic acid concentrations, 

while homes with more than three people had higher concentrations of 1-butanol, heptane and dlimonene. When shoes were inside the homes, heptane, acetic acid, nonane and styrene 

concentrations were statistically higher than that when shoes were out of the homes. Furthermore, 

higher levels of 1,2,4-trimethylbenzene, styrene, nonane and heptane were found in gas-use 

families rather than in electricity-use homes.Long-term exposure to formaldehyde and volatile 

organic compounds (VOC) in indoor environments may cause a number of adverse health effects 

such as asthma, dizziness, respiratory and lung diseases, and even cancers. Therefore, it is critical 

to minimize indoor air pollution caused by formaldehyde and VOCs. The findings obtained in 

this study would significantly enhance our understanding on the levels, emission sources and 

factors which affect indoor concentrations of formaldehyde and VOCs. The results can help 

housing designers, builders, home residents, and housing department of the government to 

improve indoor air quality (IAQ) by means of appropriate building materials, clean household 

products and proper life styles. It can also help policy makers reconcile the IAQ objectives and 

guidelines. 

Hanrahan, L. P., K. A. Dally, et al. (1984). "Formaldehyde Vapor in Mobile Homes - a Cross-Sectional 

Survey of Concentrations and Irritant Effects." American Journal of Public Health 74(9): 1026-1027. 

 Sixty-five Wisconsin mobile home households volunteered for an assessment of indoor 

formaldehyde gas. Sixty-one teenage and adult occupants completed health questionnaires. 

Formaldehyde concentrations ranged from less than 0.10 to 0.80 ppm, with the risk of ocular 

discomfort showing a positive dose-response relationship. 

Hawthorne, A. R. and T. G. Matthews (1987). "Models for Estimating Organic Emissions from Building-
3-44

Materials - Formaldehyde Example." Atmospheric Environment 21(2): 419-424. 

 One important source of chronic exposure to low levels of organic compounds in the indoor 

environment is emissions from building materials. Because removal of offending products may 

be costly or otherwise impractical, it is important that the emissions of organic pollutants be 

understood prior to incorporation of these materials into buildings. Once the organic pollutants of 

concern are identified, based on potential health effects and emission potential from the building 

material, it is necessary that an emission model be developed to predict the behavior of emission 

rates under various indoor conditions. Examples of the type of requirements that must be 

addressed in developing models for estimating organic emissions from building materials into the 

indoor environment are presented. Important factors include the products' characteristic source 

strengths at standard test conditions, impact of variations in environmental conditions (such as 

temperature and humidity), concentrations of the modeled organic pollutants in indoor 

environments and product ages. Ideally, emission models should have physical/chemical bases so 

that the important physical factors can be identified and their relative importance quantified. 

Although a universal model describing organic emissions from all building materials may not be 

feasible due to the tremendous variety of organic products and building materials in use, the most 

studied of the volatile organic compounds from building materials, formaldehyde, is used to 

illustrate an approach to the development of a specific model for organic emissions. 

Hayashi, M., M. Enai, et al. (2001). "Annual characteristics of ventilation and indoor air quality in 

detached houses using a simulation method with Japanese daily schedule model." Building and 

Environment 36(6): 721-731. 

 This paper presents the results of investigations that were made on a simulation program, which 

calculates the temperature, the heat loads, the ventilation rates and the indoor air quality 

considering the Japanese daily schedule and the dweller's behaviour toward keeping comfortable 

indoor climate, in order to explain the effect of ventilation systems. In the investigation, the 

concentrations of carbon dioxide, carbon monoxide and formaldehyde are regarded as indicators 

of indoor air quality. Firstly, three types of systems were designed in a house model; that is a 

basic passive ventilation system, a passive stack ventilation system and a mechanical ventilation 

system. Next, the simulation was performed using the standard weather data on three cities in 

Japan; and the simulation made clear the annual characteristics of ventilation and indoor air 

quality. The results show that in a house with a passive ventilation system, there is much risk of 

indoor air pollution in spring, autumn and when air conditioned, and that indoor air quality in the 

rooms on the first floor differs from that on the second floor. Lastly, the performance of the 

ventilation systems and the solution methods of realizing these ventilation systems were 
3-45

discussed on the basis of the results of the simulation. (C) 2001 Elsevier Science Ltd. All rights 

reserved. 

Hayashi, M. and H. Osawa (2008). "The influence of the concealed pollution sources upon the indoor air 

quality in houses." Building and Environment 43(3): 329-336. 

 This report presents the results of investigations on the indoor air quality of common Japanese 

detached houses. It is necessary to control the emission rates from the interior materials and the 

ventilation rates to keep indoor concentration of VOC enough low. And it is also necessary to 

consider the influence of the pollution sources in the concealed spaces for better indoor air quality 

in some kinds of building structures and some kinds of ventilation systems. In this study the 

influences of the concealed pollution sources upon the indoor concentrations of pollutants were 

investigated using three detached houses with four ventilation systems and the following results 

were obtained. When the ventilation system was changed from the air-supply type to the airexhaust type, the indoor concentrations of formaldehyde increased. The infiltration ratios: the 

ratios of the infiltration rate to the indoor space toward the emission rate of a pollutant in the 

concealed space were measured using the tracer-gas method. The ratios from the beam spaces and 

the partition were about 100% in most cases. The ratios from the crawl space under the first floor 

and the truss space under the roof were lower than those from the beam space and partitions in 

most cases, because those spaces have ventilation openings. But the ratio from the crawl space 

reached about 100% in the house without ventilation openings at the crawl space. And even in the 

house with ventilation openings at crawl space, the ratio reached 50% in the house with the 

exhaust-ventilation system. Therefore, it became clear that the use of the medicine to prevent the 

deterioration of the wooden structure and the white ants in the crawl spaces must be limited. The 

ratio from the envelope wall was changed with the pressure difference between inside and 

outside. These results showed that it is necessary to prevent infiltration from the concealed spaces 

and to control the emission rate from the concealed pollution sources. (C) 2006 Elsevier Ltd. All 

rights reserved. 

Hirota, K. and D. Prasad (2005). Indoor Air Quality in a low-density residential environment; A 

study in Abuta post-disaster public-housing. World Sustainable Building Conference, Tokyo. 

 In this study the relationship between the duration of occupancy and of symptoms of sick 

building syndrome (SBS) is discussed in order to demonstrate the problem of indoor air 

quality (IAQ) in low-density built environments. Since the1970s energy efficient and/or 

high-rise buildings have been associated with IAQ problems; however, the type of 
3-46

building and the degree of human density may not be the most crucial causes of IAQ 

problems. Because IAQ problems occur as a result of intensive exposure levels to indoor 

air pollutants, the key factors are in fact duration of exposure time to them and their 

concentration levels. Therefore to look at these factors as potential environmental causes 

of adverse health effects, user activities in a low-density residential environment were 

studied by means of a post occupancy assessment, and a simulation of indoor airflow was 

also undertaken. The pattern of indoor usage and of indoor airflow has revealed that 

problems of indoor safety and livability can in fact be associated with IAQ even in a lowdensity context. 

Hodgson, A. T., D. Beal, et al. (2002). "Sources of formaldehyde, other aldehydes and terpenes in a new 

manufactured house." Indoor Air 12(4): 235-242. 

 Formaldehyde, less volatile aldehydes, and terpene hydrocarbons are generally the predominant 

air contaminants in new manufactured and site-built houses. This study was conducted to identify 

the major sources of these compounds in a typically constructed, new manufactured house and to 

evaluate several source reduction practices. Specimens of materials used within the house were 

collected. These were individually pre-conditioned for 19+/-4 days, and tested for emissions of 

formaldehyde and other target compounds using small-scale chambers. Several cabinetry 

materials, passage doors, and the plywood subfloor were the predominant sources of 

formaldehyde and other aldehydes. The plywood subfloor was the predominant terpene source. 

Whole-house emission rates for combined materials were predicted based on the emission factors 

and the corresponding material quantities. These predicted rates were compared with wholehouse emission rates derived from measurements made at the house 3 months after its 

installation. For 10 of 14 target compounds including formaldehyde, the predicted and derived 

rates were within a factor of two. Four emission barriers applied to plywood were shown to 

reduce emission factors for formaldehyde, hexanal, and other aldehydes. 

Hodgson, A. T., J. M. Daisey, et al. (1996). "Use of volatile tracers to determine the contribution of 

environmental tobacco smoke to concentrations of volatile organic compounds in smoking 

environments." Environment International 22(3): 295-307. 

 Three volatile nitrogen-containing compounds, 3-ethenylpyridine (3-EP), pyridine and pyrrole, 

were investigated as potential tracers for determining the contribution of environmental tobacco 

smoke (ETS) to concentrations of volatile organic compounds (VOCs) in indoor environments 

with smoking. The source emission rates of the three tracers and ten selected VOCs in ETS were 
3-47

first measured in a room-size environmental chamber for a market-weighted selection of six 

commercial cigarettes. The ratios of the emission rates of the tracers to the emission rates of the 

selected VOCs were calculated and compared among the six brands. The utility of the tracers was 

then evaluated in a field study conducted in five office buildings. Samples for VOCs were 

collected in designated smoking areas and adjoining non-smoking areas, air change rates were 

measured, and smoking rates were documented. Concentrations of the three tracers in the 

smoking areas were calculated using a mass-balance model and compared to their measured 

concentrations. Based on this comparison, 3-EP was selected as the most suitable tracer for the 

volatile components of ETS, although pyrrole is also potentially useful. Using 3-EP as the tracer, 

the contributions of ETS to the measured concentrations of the selected VOCs in the smoking 

areas were estimated by apportionment. ETS was estimated to contribute 57% to 84% (4.1 to 26 

mu g m(-3)) of the formaldehyde concentrations, 44-69% (0.9 to 5.8 mu g m(-3)) of the 2-

butanone concentrations, 37 to 58% (1.3 to 8.2 mu g m(-3)) of the benzene concentrations, and 20 

to 69% (0.5 to 3.0 mu g m(-3)) of the styrene concentrations. The fractional contributions of ETS 

to the concentrations of acetone, toluene, ethylbenzene, xylene isomers, and d-limonene were all 

less than 50%. 

Hodgson, A. T., A. F. Rudd, et al. (2000). "Volatile organic compound concentrations and emission rates 

in new manufactured and site-built houses." Indoor Air 10(3): 178-192. 

 Concentrations of 54 volatile organic compounds (VOCs) and ventilation rates were measured in 

four new manufactured houses over 2-9.5 months following installation and in seven new sitebuilt houses 1-2 months after completion. The houses were in four projects located in hot-humid 

and mixed-humid climates. They were finished and operational, but unoccupied. 

 Ventilation rates ranged from 0.14-0.78 h(-1). Several of the site-built houses had 

ventilation rates below the ASHRAE recommended value. In both manufactured and site-built 

houses, the predominant airborne compounds were alpha-pinene, formaldehyde, hexanal, and 

acetic acid. Formaldehyde concentrations were below or near 50 ppb with a geometric mean 

value for all houses of 40 ppb. Similarities in the types of VOCs and in VOC concentrations 

indicated that indoor air quality in the houses was impacted by the same or similar sources. Major 

identified sources included plywood flooring, latex paint and sheet vinyl flooring. One site-built 

house was operated at ventilation rates of 0.14 and 0.32 h(-1). VOC emission rates calculated at 

the two conditions agreed within +/-10% for the most volatile compounds. Generally, the ratios 

of emission rates at the low and high ventilation rates decreased with decreasing compound 

volatility. Changes in VOC emission rates in the manufactured houses over 2-9.5 months after 

installation varied by compound. Only several compounds showed a consistent decrease in 
3-48

emission rate over this period. 

Hodgson, A. T., D. G. Shendell, et al. (2004). "Comparison of predicted and derived measures of volatile 

organic compounds inside four new relocatable classrooms." Indoor Air 14: 135-144. 

 Our objective was to develop a process for selecting interior finish materials having low impacts 

with respect to emissions of toxic and odorous volatile organic compounds (VOCs) for school 

relocatable classrooms (RCs). A laboratory study identified alternate materials with low VOC 

emissions. Two pairs of RCs then were constructed. One RC per pair contained standard interior 

materials; the other incorporated alternate materials. The pairs were sited side-by-side at two 

California elementary schools in fall 2001. Fifteen target VOCs, including the toxicants 

formaldehyde, acetaldehyde, vinyl acetate, phenol, toluene, and naphthalene, were measured 

during school hours over 8 weeks in the succeeding fall cooling season. Indoor minus outdoor 

VOC concentrations with an advanced HVAC operated were low; only formaldehyde 

concentrations exceeded 5 p.p.b. Classroom VOC concentrations were predicted based on 

emission factors (mug/m(2)/h), material quantities and design ventilation rates. These were 

compared to average adjusted concentrations measured when the occupied classrooms were 

operating at near the code-minimum ventilation rate. For 16 of the possible 42 comparisons, 

measured concentrations agreed within a factor of two of predicted the predicted values. 

Concentrations of six of 10 VOCs were significantly lower in modified RCs though average 

differences were mostly less than 1 p.p.b. 

Hodgson, A. T., J. D. Wooley, et al. (1993). "Emissions of Volatile Organic-Compounds from New 

Carpets Measured in a Large-Scale Environmental Chamber." Journal of the Air & Waste Management 

Association 43(3): 316-324. 

 This study was undertaken to quantify the emissions of volatile organic compounds (VOCs) 

released by new carpets. Samples of four typical carpets, including two with styrene-butadiene 

rubber (SBR) latex adhesive and two with different backings, were collected from the finish lines 

at manufacturers' mills. Individual VOCs released from these samples were identified, and their 

concentrations, emission rates and mass emissions were measured under simulated indoor 

conditions in a 20 m3 environmental chamber over one week periods. Concentrations and 

emission rates of VOCs emitted by a new SBR carpet were also measured in a house. 

 The carpets emitted a variety of VOCs. The two SBR carpets primarily emitted 4-

phenylcyclohexene (4-PCH), the source of ''new carpet'' odor, and styrene. The concentrations 

and emission rates of 4-PCH were similar for the two carpets, while the styrene values varied 

significantly. The carpet with a polyvinyl chloride backing emitted formaldehyde, vinyl acetate, 
3-49

isooctane, 1,2-propanediol, and 2-ethyl-1-hexanol. Of these, vinyl acetate and propanediol had 

the highest concentrations an emission rates. The carpet with a polyurethane backing primarily 

emitted butylated hydroxytoluene. With the exception of formaldehyde, little is known about the 

health effects of these VOCs at low concentrations. 

Hollowell, C., D. and R. R. Miksch (1981). "Sources and concentrations of organic compounds in indoor 

environments." Bull. N.Y. Acad. Med. 57(10): 962-977. 

 

Howard, E. M., R. C. McCrillis, et al. (1998). "Indoor emissions from conversion varnishes." Journal of 

the Air & Waste Management Association 48(10): 924-930. 

 Conversion varnishes are two-component, acid-catalyzed varnishes that are commonly used to 

finish cabinets. They are valued for their water and stain resistance, as well as their appearance. 

They have been found, however, to contribute to indoor emissions of organic compounds. For 

this project, three commercially available conversion varnish systems were selected. A U.S. 

Environmental Protection Agency (EPA) Method 24 analysis was performed to determine total 

volatile content, and a sodium sulfite titration method was used to determine uncombined (free) 

formaldehyde content of the varnish components. The resin component was also analyzed by gas 

chromatography/mass spectroscopy (GC/MS) (EPA Method 311 with an MS detector) to identify 

individual organic compounds. Dynamic small chamber tests were then performed to identify and 

quantify emissions following application to coupons of typical kitchen cabinet wood substrates, 

during both curing and aging. Because conversion varnishes cure by chemical reaction, the 

compounds emitted during curing and aging are not necessarily the same as those in the 

formulation. Results of small chamber tests showed that the amount of formaldehyde emitted 

from these coatings was 2.3-8.1 times the amount of free formaldehyde applied in the coatings. A 

long-term test showed a formaldehyde emission rate of 0.17 mg/m(2)/hr after 115 days. 

Hui, P. S., K. W. Mui, et al. (2008). "Influence of indoor air quality (IAQ) objectives on air-conditioned 

offices in Hong Kong." Environmental Monitoring and Assessment 144(1-3): 315-322. 

 It is costly to sample all air pollutants of a general community. Air sampling should be conducted 

based on a practical assessment strategy and monitoring plan. In Hong Kong, the Environmental 

Protection Department (HKEPD) launched an Indoor Air Quality (IAQ) certification scheme to 

grade workplace IAQ as 'Excellent' or 'Good' by measuring the levels of nine common indoor air 

pollutants, namely carbon dioxide (CO2), carbon monoxide (CO), respirable suspended 

particulates (RSP), nitrogen dioxide (NO2), ozone (O-3), formaldehyde (HCHO), total volatile 

organic compounds (TVOC), radon (Rn), and airborne bacteria count (ABC). Although average 
3-50

office IAQ performance has been improved since the implementation of this certification scheme, 

there are still resource issues and technical difficulties. To streamline the assessment of office 

IAQ performance, this study proposes a simple index of IAQ benchmarks formulated in 

compliance with the HKEPD requirements. In particular, three of the nine listed common air 

pollutants were selected as the 'representatives' for the overall satisfactory IAQ. Together with the 

assessment results of 422 Hong Kong air-conditioned offices, the index was evaluated in terms of 

test sensitivity, specificity and predictive values. Proved to be feasible to describe the IAQ of 

some air-conditioned offices, this IAQ index would be a useful tool for policymakers, building 

owners and professionals to quantify IAQ performance in offices and to make decisions on 

resources and manpower management for efficient mitigation actions. 

Kelly, T. (1996). Determination of Formaldehyde and Toluene Diisocyanate Emissions from Indoor 

Residential Sources. Sacramento, CA, California Air Resources Board: 93-315. 

 Building materials and consumer products found in California residences were subjected to 

chamber testing to determine the emission rates of formaldehyde (HCHO) and of Toluene 

DiIsocyanates (TDI). The emissions of formaldehyde were determined from bare UreaFormaldehyde (UF) and Phenol-Formaldehye (PF) wood products, with vinyl, paper, and other 

coatings, and from decorative laminates, permanent press fabrics fiberglass insulation, paper 

goods, paints, cosmetics, and acid-cured coatings. Other compounds determined along with 

HCHO included acetaldehyde, propionaldehyde, methyl ethyl ketone (MEK), and Methyl 

IsoButyl Ketone (MIBK). A separate set of PolyUrethane (PU) products, including PU foam 

carpet padding, furniture cushions, sheet foam, PU varnishes, caulks and sealants, and a 

commercially-applied water stop product for concrete, were tested for emissions of toluene 

diisocyanate (TDI). 

Khoder, M. I., A. A. Shakour, et al. (2000). "Indoor and outdoor formaldehyde concentrations in homes in 

residential areas in Greater Cairo." Journal of Environmental Monitoring 2(2): 123-126. 

 Indoor and outdoor measurements of formaldehyde were conducted at seven flats located in 

residential areas in Greater Cairo, during spring and summer seasons 1999. The mean daytime 

formaldehyde concentrations in kitchens, bedrooms and living rooms were 89, 100 and 100 ppb, 

respectively, in the seven flats. Significant positive correlations were found between the 

concentrations of formaldehyde found in these three rooms. On the other hand, no significant 

differences were found between the mean formaldehyde concentrations in these three rooms. The 

maximum mean concentration of formaldehyde (147 ppb) was recorded in a new flat, while the 

minimum concentration (43 ppb) was observed in an old flat. The maximum hourly and daytime 
3-51

concentrations were 350 and 225 ppb, respectively. Air temperature, relative humidity and the 

age of the flat are factors affecting the emission and concentration of formaldehyde. The 

maximum indoor and outdoor formaldehyde concentrations were recorded during the summer 

season. During the spring, 38% of the samples indicated that the concentration of formaldehyde 

in the seven flats exceeded 0.1 ppm, the American Society of Heating, Refrigerating, and Air 

Conditioning Engineers' (ASHRAE) standard; in the summer, this figure increased to 53%. 

Kim, S. and H. J. Kim (2005). "Comparison of formaldehyde emission from building finishing materials 

at various temperatures in under heating system; ONDOL." Indoor Air 15(5): 317-325. 

 The objective of this research was to investigate the effect of various temperatures, room, 37 and 

50 degrees C, on formaldehyde emission from floor materials, such as laminate and plywood 

floorings, and furniture materials, such as MDF and particleboard veneered with decorative paper 

foil, by desiccator's method. The temperature conditions were set up by, measuring the 

temperature in a Korean under heating system. To maintain an indoor air temperature of 20 

degrees C, the temperature of the flooring surface was about 37 degrees C and the temperature of 

the cement mortar was 50 degrees C. The initial formaldehyde emission of the laminate flooring 

and plywood flooring was 1.44 and 0.63 mg/l, and for MDF and particleboard it was 4.73 and 

4.95 mg/l, respectively. Floor materials were under E1 grade while furniture materials were under 

E-2 grade in terms of formaldehyde emission. Because of the under heating system, the flooring 

materials were exposed to 37 and 50 degrees C, while the furniture materials mostly existed at 

room temperature. At 37 and 50 degrees C, the formaldehyde emission level of the flooring 

materials was already under 0.3 ppm (F star star star star level by JIS A 1460, application 

possibility without area limit) after 10 days and the emission had decreased further (0.03-0.10 

mg/l) after 28 days. These levels are not injurious to the human body and will not cause sick 

house syndrome (SHS). The problem, however, is the furniture materials such as MDF and 

particleboard. As these materials are not exposed to high temperature (50 degrees C in this 

experiment) in living condition, it was still E-2 grade of formaldehyde emission level at room 

temperature remained even after 28 days. Although there will be variations with the volume of 

furniture materials and the indoor conditions, furniture materials are the principal cause of indoor 

air quality pollution in Korean with the under heating system. 

Kirkeskov, L., T. Witterseh, et al. (2009). "Health evaluation of volatile organic compound (VOC) 

emission from exotic wood products." Indoor Air 19(1): 45-57. 

 The purpose of this study was to measure and evaluate the impact of the emissions of selected 

products of exotic wood on health. Ten products were screened for chemical compounds, and five 
3-52

of the most used products which emitted more than 800 mu g/kg were selected for further 

quantitative analyses by climate chamber measurement (iroko, ramin, sheesham, merbau, and 

rubber tree). Samples of exotic wood (rubber tree and belalu) were further analyzed for emission 

of chemical compounds by migration into artificial saliva and for content of pesticides and 

allergenic natural rubber latex (NR latex) (rubber tree). The toxicological effects of all substances 

identified were evaluated and the lowest concentrations of interest (LCI) assessed. An R-value 

was calculated for each wood product (R-value below 1 is considered to be unproblematic as 

regards health). Emission from the evaluated exotic wood only took place to a very limited 

extent. None of the selected products, under the chosen rating system, is likely to cause adverse 

health effects. Products with surface treatment might pose a problem if used as kitchen utensils, 

as children's toys, or when they are in close contact with the skin for a long time.The authors 

investigated the chemical emissions from selected products from exotic wood by climate chamber 

measurement. Quantitative chemical analyses of emissions from the five most used exotic 

products in Denmark were performed, and all chemical compounds found were evaluated 

toxicologically. Emission from the evaluated exotic wood was very limited. None of the products 

is likely, under our exposure conditions, to cause health problems in relation to indoor air. 

Koziel, J. A., J. Noah, et al. (2001). "Field sampling and determination of formaldehyde in indoor air with 

solid-phase microextraction and on-fiber derivatization." Environmental Science & Technology 35(7): 

1481-1486. 

 A new sampling and analysis method for formaldehyde in indoor air was tested in several indoor 

air surveys. The method was based on the use of solid-phase microextraction (SPME) 

poly(dimethylsiloxane)/divinylbenzene,65 mum fiber and gas chromatography. Indoor air surveys 

included grab and time-weighted average (TWA) sampling and were completed at six locations 

using (a) the SPME method employing on-fiber formaldehyde derivatization with o-(2,3,4,5,6-

pentafluorobenzyl)hydroxylamine hydrochloride and (b)the conventional National Institute for 

Occupational Safety and Health (NIOSH) 2451 method. Sampling time for SPME fiber ranged 

from 10 min for grab sampling to 8 h for TWA sampling. Sampling locations included a 

residential house, a rental apartment, an office building, and industrial workplaces. The air 

concentrations measured by SPME ranged from 10 to 380 ppbv and correlated well with those 

estimated by the NIOSH method. Results also indicated th at in some cases the formaldehyde 

concentrations measured in residential air could be much higher than those allowed in 

occupational settings. The SPME method proved to be accurate, fast, sensitive, and cost-efficient 

in field sampling applications. This research should be of interest to research, industrial, and 

regulatory agencies as well as to the general public concerned with indoor air quality. 
3-53

Introduction 

Lee, S. C. and M. Chang (2000). "Indoor and outdoor air quality investigation at schools in Hong Kong." 

Chemosphere 41(1-2): 109-113. 

 Five classrooms in Hong Kong (HK), air-conditioned or ceiling fans ventilated, were chosen for 

investigation of indoor and outdoor air quality. Parameters such as temperature, relative humidity 

(RH), carbon dioxide (CO2), sulphur dioxide (SO2), nitric oxide (NO), nitrogen dioxide (NO2), 

respirable particulate matter (PM10), formaldehyde (HCHO), and total bacteria counts were 

monitored indoors and outdoors simultaneously. The average respirable particulate matter 

concentrations were higher than the HK Objective, and the maximum indoor PM10 level 

exceeded 1000 mu g/m(3). Indoor CO2 concentrations often exceeded 1000 mu l/l in airconditioning and ceiling fan classrooms, indicating inadequate ventilation. Maximum indoor CO2 

level reached 5900 mu l/l during class at the classroom with cooling tower ventilation. Increasing 

the rate of ventilation or implementation of breaks between classes is recommended to alleviate 

the high CO2 level. Other pollution parameters measured in this study complied with the 

standards. The two most important classroom air quality problems in Hong Kong were PM10 and 

CO2 levels. (C) 2000 Elsevier Science Ltd. All rights reserved. 

Lee, S. C., H. Guo, et al. (2002). "Inter-comparison of air pollutant concentrations in different indoor 

environments in Hong Kong." Atmospheric Environment 36(12): 1929-1940. 

 Indoor air quality in selected indoor environments in Hong Kong such as homes, offices, schools, 

shopping malls and restaurants were investigated. Average CO2 levels and total bacteria counts in 

air-conditioned classrooms, shopping malls and restaurants were comparatively higher than those 

measured in occupied offices and homes. Elevated CO, levels exceeding 1000ppm and total 

bacteria counts resulted from high occupancy combined with inadequate ventilation. Average 

PM10 levels were usually higher indoors than outdoors in homes, shopping malls and restaurants. 

The highest indoor PM10 levels were observed at investigated restaurants due to the presence of 

cigarette smoking and extensive use of gas stoves for cooking. The restaurants and shopping 

malls investigated had higher formaldehyde levels than other indoor environments when building 

material, smoking and internal renovation work were present. Volatile organic compounds 

(VOCs) in both indoor and outdoor environments mainly resulted from vehicle exhaust 

emissions. It was observed that interior decoration work and the use of industrial solvents in an 

indoor environment could significantly increase the indoor levels of VOCs. (C) 2002 Published 

by Elsevier Science Ltd. 
3-54

Lee, S. C. and B. Wang (2004). "Characteristics of emissions of air pollutants from burning of incense in 

a large environmental chamber." Atmospheric Environment 38(7): 941-951. 

 The objective of this study was to characterize the emissions of air pollutants from incense 

burning in a large environmental test chamber. Air pollutants emitted from ten types of 

commonly used incense manufactured in different regions were compared. The target pollutants 

included particulate matters (PM10, PM2.5), volatile organic compounds (VOCs), carbonyls, 

carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), methane (CH4) and nonmethane hydrocarbon (NMHC). The particulate matters emitted from all the incense significantly 

exceeded the Recommended Indoor Air Quality Objectives for Office Buildings and Public 

Places in Hong Kong (HKIAQO). The CO peak levels of seven incense types greatly exceeded 

the HKIAQO standard. The formaldehyde concentrations of six types of incense were higher than 

the HKIAQO. The highest formaldehyde level exceeded the standard by 2 times. The results 

indicated that the concentrations of benzene, toluene, methyl chloride and methylene chloride 

significantly increased with the burning of all incense tested. In addition, the benzene 

concentrations of all tested incense were significantly higher than the HKIAQO standard. 

Although Incense 2 and 6 were claimed to be environmental friendly, the quantity of the 

pollutants emitted was not observed to be lower than the others. It was observed that when 

comparing the gas pollutant emission factors between two major incense categories (i.e. 

traditional and aromatic), the traditional incense (i.e. Incense 1-6) had relatively higher values 

than aromatic incense (i.e. Incense 7-9). Generally, it was found that the VOCs emitted sequence 

was aromatic incense > tradition incense > church incense (i.e. Incense 10). However, the 

carbonyl compounds emission sequence was traditional incense > aromatic incense > church 

incense. The results show that incense burning is one of the important indoor air pollution sources 

for PM, CO and VOCs. (C) 2003 Elsevier Ltd. All rights reserved. 

Li, Y., K. Wang, et al. (2005). Measurement and Prediction of Indoor Formaldehyde Concentration in 

Northeast China. Air and Waste Management Association’s 98th Annual Meeting & Exhibition, 

Minneapolis, MN, USA. 

 With the development of economy and the improvement of living condition, decorating houses 

has been the hotspot of personal consumption in China for the past two decades. Indoor 

formaldehyde pollution is ubiquitous in China, while it has been mostly controlled in the 

developed countries. In this study, an investigation on the measurement of indoor formaldehyde 

concentration in residential houses was conducted in Harbin, located at the most chilly area in 

Northeast China. The results showed that the concentration of indoor formaldehyde ranged from 

0.017 to 1.302mg/m3, and only 22.8% of the residential houses met the formaldehyde standard of 
3-55

0.10 mg/m3 for National Air Quality Standard of China. The monthly average formaldehyde 

concentration in summer (June-August) was about twice higher than those in winter (NovemberMarch). A strong correlation between the monthly average indoor formaldehyde concentration 

and the monthly average temperature (R2=0.8652) was obtained. Furthermore, a mathematical 

model was successfully developed to predict the concentration of indoor formaldehyde in Chinese 

residential houses. Field measurements of indoor formaldehyde concentration in residential 

houses were also conducted for various decoration time in order to investigate the influence of 

decoration time on the indoor formaldehyde concentration. 

Li, Y. Y., P. C. Wu, et al. (2002). Effects of HVAC ventilation efficiency on the concentrations of 

formaldehyde and total volatile organic compounds in office buildings. Indoor Air, California. 

 Potential sources for emitting formaldehyde and volatile organic compounds are abundant in 

office buildings. Exposure to the above compounds may result in short-term, long-term, or 

carcinogenic effects at concentrations often measured. Our study conducts field measurements on 

six typical office buildings with different HVAC systems to evaluate the effects of ventilation 

efficiency on the concentration of formaldehyde and total volatile organic compounds (TVOC). 

Formaldehyde and TVOC concentrations were measured by continuous photo-acoustic Multi-Gas 

monitor. The air-change rates were estimated by tracer gas concentration decay method in every 

test space. Air Exchange Efficiency (AEE) and Effective Ventilation Rate (EACH) were also 

calculated to characterize the ventilation pattern and mixing factor. Our results show that the 

increase of effective ventilation could reduce formaldehyde and TVOC in office buildings . We 

therefore suggest that increasing ventilation efficiency appears to bea plausible solution to 

diminish both formaldehyde and TVOC concentrations in office buildings. 

Lin, Z., T. T. Chow, et al. (2005). "CFD study on effect of the air supply location on the 

performance of the displacement ventilation system." Building and Environment 40(8): 1051-

1067. 

 The purpose of this paper is to investigate using a numerical simulation (computational 

fluid dynamics or CFD) the effect of the air supply location on the design and 

performance of the displacement ventilation (DV) system. The results are reported in 

terms of thermal comfort and indoor air quality. The study focuses on the typical Hong 

Kong office under local thermal and boundary conditions. This includes the high cooling 

load used in Hong Kong. Several pollutants typically found in the office such as carbon 

dioxide and volatile organic compounds (VOCs) were investigated. The results indicate 
3-56

that the supply should be located near the center of the room rather than to one side of the 

room. This will provide a more uniform thermal condition in the office. The DV system 

was found to be effective in dispersing VOCs within an office environment for all cases 

studied. The exhaust was found to have minimal effect on the thermal comfort. For a DV 

system in Hong Kong, it is possible to use 100% fresh air without extra energy 

consumption. (c) 2004 Elsevier Ltd. All rights reserved. 

Lin, Z., T. T. Chow, et al. (2005). "Comparison of performances of displacement and mixing ventilations. 

Part II: indoor air quality." International Journal of Refrigeration-Revue Internationale Du Froid 28(2): 

288-305. 

 A numerical simulation using a validated computational fluid dynamics model is used to 

investigate and compare the performances of displacement and mixing ventilations (MVs), under 

different boundary conditions. A companion paper will report the results in terms of thermal 

comfort, while this paper investigates the indoor air quality (IAQ). The IAQ will be measured in 

terms of carbon monoxide, mean age of air and the three volatile organic compounds, toluene, 

benzene and formaldehyde, which are commonly found in indoor room furnishings. The case 

studies include offices, classrooms, retail shops and industrial workshops, under typical Hong 

Kong thermal boundary conditions. Compared with conventional MV, displacement ventilation 

may provide better IAQ in the occupied zone. (C) 2004 Elsevier Ltd and IIR. All rights reserved. 

Lin, Z., T. T. Chow, et al. (2005). "Effect of air supply temperature on the performance of 

displacement ventilation (Part II) - Indoor air quality." Indoor and Built Environment 14(2): 117-

131. 

 The effect of air supply temperature on the performance of a displacement ventilation 

(DV) system has been investigated. This paper is the second part of a 2 part series and the 

results are reported with regard to Indoor Air Quality (IAQ). The study is based on a 

typical office building in Hong Kong, under local thermal and flow boundary conditions. 

The criteria for IAQ were measurements of carbon dioxide levels, mean age of air and 3 

volatile organic compounds (VOCs): toluene, benzene and formaldehyde. The change in 

supply temperature from 19 degrees C to 22 degrees C was found to have no significant 

effect on the level and distribution of contaminants in the room. The DV system was 

found to operate satisfactorily under the range of supply temperatures studied. 
3-57

Lin, Z., T. T. Chow, et al. (2006). "Effects of headroom on the performance of the displacement 

ventilation system." Indoor and Built Environment 15(4): 333-346. 

 A numerical simulation applying a validated computational fluid dynamics model was 

used to investigate the effect of the headroom on a displacement ventilation (DV) system. 

Two different headroom heights in a space were simulated and compared. It was found 

that the effect of increased headroom was to improve the thermal comfort of the indoor 

space. It was also concluded that given the thermal boundary conditions commonly 

encountered and the typical low headroom found in Hong Kong, DV was found to work 

effectively in terms of thermal comfort and indoor air quality (IAQ). 

Liteplo, R. G. and M. E. Meek (2003). "Inhaled formaldehyde: Exposure estimation, hazard 

characterization and exposure-response analysis." Journal of Toxicology and Environmental Health, Part 

B 6(1): 85-114. 

 Formaldehyde has been assessed as a Priority Substance under the Canadian Environmental 

Protection Act. Probabilistic estimates of exposure of the general population in Canada to 

formaldehyde in ambient and indoor air are presented. Critical health effects include sensory 

irritation and the potential to induce tumors in the upper respiratory tract (the nasal region in 

rodents and potentially the lungs of humans). The majority of the general population is exposed to 

airborne concentrations of formaldehyde less than those typically associated with sensory 

irritation (i.e., 0.1 mg/m 3 ). Based primarily upon data derived from laboratory studies, the 

inhalation of formaldehyde under conditions that induce cytotoxicity and sustained regenerative 

proliferation within the respiratory tract is considered to present a carcinogenic hazard to humans. 

At airborne levels for which the prevalence of sensory irritation is minimal (i.e., 0.1 mg/m 3 ), 

risks of respiratory-tract cancers for the general population estimated on the basis of a 

biologically motivated case-specific model are exceedingly low. This biologically motivated 

case-specific model incorporates two-stage clonal expansion and is supported by dosimetry 

calculations from computational fluid dynamics analyses of formaldehyde flux in various regions 

of the nose and single-path modeling for the lower respiratory tract. The degree of confidence in 

the underlying database and uncertainties in estimates of exposure and in characterization of 

hazard and dose response are delineated. 

Liu, W., J. Zhang, et al. (2006). "Concentrations and source characteristics of airborne carbonyl 

compounds measured outside urban residences." J Air Waste Manag Assoc 56(8): 1196-204. 

 This paper presents the analysis of ambient air concentrations of 10 carbonyl compounds 
3-58

(aldehydes and ketones) measured in the yards of 87 residences in the city of Elizabeth, NJ, 

throughout 1999-2001. Most of these residences were measured twice in different seasons; the 

sampling duration was 48 hr each time. The authors observed higher concentrations for most of 

the measured carbonyl compounds on warmer days, reflecting larger contributions of 

photochemical reactions on warmer days. The estimated contributions of photochemical 

production varied substantially across the measured carbonyl compounds and could be as high as 

60%. Photochemical activity, however, resulted in a net loss for formaldehyde. The authors used 

stepwise multiple linear regression models to evaluate the impact of traffic sources and 

meteorological conditions on carbonyl concentrations using the data collected on colder days 

(with lower photochemical activities). They found that the concentrations of formaldehyde, 

acetaldehyde, acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyoxal, and 

methylglyoxal significantly decreased with increasing distance between a measured residence and 

one or more major roadways. They also found significant negative associations between 

concentrations for most of the measured carbonyl compounds and each of the following 

meteorological parameters: mixing height, wind speed, and precipitation. 

Liu, W., J. Zhang, et al. (2006). "Estimating contributions of indoor and outdoor sources to indoor 

carbonyl concentrations in three urban areas of the United States." Atmospheric Environment 40(12): 

2202-2214. 

 Exposure to carbonyls (aldehydes and ketones) can produce adverse health effects. It is known 

that various sources of carbonyls are often present inside residences but little is known about their 

indoor source strengths. In the present paper, we used a database established in the relationships 

of indoor, outdoor, and personal air (RIOPA) study to estimate indoor source strengths of 10 

carbonyls and outdoor contributions to measured indoor concentrations of these carbonyls. We 

applied a mass balance model to analyze paired indoor and outdoor carbonyl concentrations 

simultaneously measured in 234 RIOPA homes. Among all the measured carbonyls, 

formaldehyde, and acetaldehyde had the strongest indoor source strengths with the estimated 

median values of 3.9 and 2.6 mg h(-1), respectively. Hexaldehyde also had large indoor source 

strengths with a median of 0.56 mg h(-1). Acetone had the largest variations in indoor source 

strengths ranging from undetected to 14 mg h(-1). The medians of the estimated indoor source 

strengths were 0.15 mg h(-1) for propionaldehyde, 0.18 mg h(-1) for glyoxal, 0.17 mg h(-1) for 

methylglyoxal, and 0.23 mg h(-1) for benzaldehyde. Acrolein and crotonaldehyde had the 

weakest indoor source strengths with no indoor sources detected in the majority of the RIOPA 

homes that were selected to have only nonsmoker residents. Consistent with the indoor source 

strength results, our estimated outdoor contributions to indoor concentrations were low for 
3-59

formaldehyde. In contrast, more than 90% of the indoor concentrations for acrolein and 

crotonaldehyde were from outdoor sources. The outdoor contributions to indoor concentrations 

for acetone, propionaldehyde, benzaldehyde, glyoxal, and methylglyoxal ranged from 10 to 90% 

across the RIOPA homes, suggesting that both indoor and outdoor sources had contributions to 

indoor concentrations of these compounds. (c) 2006 Elsevier Ltd. All rights reserved. 

Liu, W. L., J. F. Zhang, et al. (2003). "Mosquito coil emissions and health implications." Environmental 

Health Perspectives 111(12): 1454-1460. 

 Burning mosquito cods indoors generates smoke that can control mosquitoes effectively. This 

practice is currently used in numerous households in Asia, Africa, and South America. However, 

the smoke may contain pollutants of health concern. We conducted the present study to 

characterize the emissions from four common brands of mosquito coils from China and two 

common brands from Malaysia. We used mass balance equations to determine emission rates of 

fine particles (particulate matter < 2.5 pm in diameter; PM2.5), polycyclic aromatic hydrocarbons 

(PAHs), aldehydes, and ketones. Having applied these measured emission rates to predict indoor 

concentrations under realistic room conditions, we found that pollutant concentrations resulting 

from burning mosquito coils could substantially exceed health-based air quality standards or 

guidelines. Under the same combustion conditions, the tested Malaysian mosquito coils generated 

more measured pollutants than did the tested Chinese mosquito coils. We also identified a large 

suite of volatile organic compounds, including carcinogens and suspected carcinogens, in the coil 

smoke. In a set of experiments conducted in a room, we examined the size distribution of 

particulate matter contained in the coil smoke and found that the particles were ultrafine and fine. 

The findings from the present study suggest that exposure to the smoke of mosquito coils similar 

to the tested ones can pose significant acute and chronic health risks. For example, burning one 

mosquito coil would release the same amount of PM2.5 mass as burning 75-137 cigarettes. The 

emission of formaldehyde from burning one coil can be as high as that released from burning 51 

cigarettes. 

Lu, H. X., S. Wen, et al. (2006). "Indoor and outdoor carbonyl compounds and BTEX in the hospitals of 

Guangzhou, China." Science of the Total Environment 368(2-3): 574-584. 

 Indoor and outdoor concentration levels of 21 carbonyl compounds and five BTEX (benzene, 

toluene, ethylbenzene and xylenes) were measured in four hospitals of Guangzhou from 2nd 

January to 20th March 2004. Samples were collected in five consecutive daytimes for each 

hospital. Among most of the samples, acetone was the most abundant carbonyl, followed by 

acetaldehyde, 2-butanone or formaldehyde. Toluene was the most abundant BTEX and the others 
3-60

were at similar levels. The relatively higher acetone concentrations might have resulted from the 

high level of background in Guangzhou area due to emission of the factories and LPG-fuel 

vehicles, and also for the special weather conditions during sampling time. The high 

concentration of acetaldehyde, which was even higher than that of formaldehyde, might be 

resulted from the wide use of ethanol in hospital. The partial oxidation of ethanol may form 

acetaldehyde. The indoor concentrations of carbonyls and BTEX were found a little higher than 

their outdoor counterparts with only a few exceptions, which showed the anthropogenic sources 

for these compounds. The low correlations between most carbonyls and BTEX concentrations 

might be caused by their complex sources. Finally, the human exposure levels of formaldehyde 

and acetaldehyde in hospitals are discussed. (c) 2006 Elsevier B.V. All rights reserved. 

Lv, P., Z. Tang, et al. (2007). "Recognizing indoor formaldehyde in binary gas mixtures with a 

micro gas sensor array and a neural network." Measurement Science & Technology 18(9): 2997-

3004. 

 Low-concentration formaldehyde (HCHO) together with ethanol/toluene/acetone/alphapinene (as an interference gas of HCHO) is detected with a micro gas sensor array, 

composed of eight tin oxide (SnO2) thin film gas sensors with Au, Cu, Pt or Pd metal 

catalysts. The characteristics of the multi- dimensional signals from the eight sensors are 

evaluated. A multilayer neural network with an error backpropagation ( BP) learning 

algorithm, plus the principal component analysis ( PCA) technique, is implemented to 

recognize these indoor volatile organic compounds ( VOC). The results show that the 

micro gas sensor array, plus the multilayer neural network, is very effective in 

recognizing 0.06 ppm HCHO in single gas component and in binary gas mixtures, 

toluene/ethanol/alpha-pinene with small relative error. 

Maddalena, R., M. Russell, et al. (2008). Aldehyde and other volatile organic chemical emissions in four 

fema temporary housing units – Final report Ernest Orlando Lawrence Berkeley National Laboratory 

(LBNL-254E), Environmental Energy Technologies Division 

 As part of an ongoing effort with the U.S. Centers for Disease Control and Prevention (CDC), 

Lawrence Berkeley National Laboratory (LBNL) entered into an interagency agreement with 

CDC to help identify mitigation strategies for reducing indoor emissions of volatile organic 

compounds (VOCs) including formaldehyde in Federal Emergency Management Administration 

(FEMA) temporary housing units (THUs)1. Four unoccupied FEMA THUs were studied to 

assess their indoor emissions of VOC including formaldehyde. Indoor measurement of whole-
3-61

THU VOC and aldehyde emission factors (μg h-1 per m2 of floor area) for each of the four THUs 

were made at FEMA’s Purvis Mississippi staging yard using a mass balance approach. 

 Measurements were made in the morning, and again in the afternoon in each THU. 

Steady-state indoor formaldehyde concentrations ranged from 378 μg m-3 (0.31ppm) to 632 μg 

m-3 (0.52 ppm) in the morning, and from 433 μg m-3 (0.35 ppm) to 926 μg m-3 (0.78 ppm) in 

the afternoon. THU air exchange rates ranged from 0.15 h-1 to 0.39 h-1. A total of 45 small 

(approximately 0.025 m2) samples of surface material, 16 types, were collected directly from the 

four THUs and shipped to Lawrence Berkeley Laboratory. The material samples were analyzed 

for VOC and aldehyde emissions in small stainless steel chambers using a standard, accurate 

mass balance method. Quantification methods for the VOCs included high performance liquid 

chromatography for formaldehyde and acetaldehyde, ion chromatography for the acetic acid, and 

gas chromatography-mass spectrometry for the remaining VOCs. Material specific emission 

factors (μg h-1 per m2 of material) were quantified. Approximately 80 unique VOCs were 

initially identified in the THU field samples, of which forty-five were quantified either because of 

their toxicological significance or because their concentrations were high. Whole-trailer and 

material specific emission factors were calculated for 33 compounds. The THU emission factors 

and those from their component materials were compared against those measured in other types 

of housing and the materials used in their construction. Whole THU emission factors for most 

VOCs were similar to those from comparative housing. The three exceptions were large 

emissions of formaldehyde, acetic acid, TMPD-DIB (a common plasticizer in vinyl products), 

and somewhat elevated emission of phenol. Of these compounds, formaldehyde was the only one 

with toxicological significance at the observed concentrations. Whole THU formaldehyde 

emissions ranged from 173 to 266 μg m-2 h-1 in the morning and 257 to 347 μg m-2 h-1 in the 

afternoon. Median formaldehyde emissions in previously studied site-built and manufactured 

homes were 31 and 45 μg m-2 h-1, respectively. Only one of the composite wood materials that 

was tested appeared to exceed the US Department of Housing and Urban Development (HUD) 

formaldehyde emission standard for new material but several of the materials exceeded if the 

decline in emission with aging is considered. The high loading factor (material surface area 

divided by THU volume) of composite wood products in the THUs and the low fresh air 

exchange relative to the material surface area may be responsible for the excessive concentrations 

observed for some of the VOCs and formaldehyde. 

Maddalena, R., M. Russell, et al. (2009). "Formaldehyde and Other Volatile Organic Chemical Emissions 

in Four FEMA Temporary Housing Units." Environmental Science & Technology 43(15): 5626-5632. 

 Indoor concentrations of 33 volatile organic chemicals were measured in four unoccupied 
3-62

temporary housing units (THUS) belonging to the U.S. Federal Emergency Management 

Administration (FEMA). The highest level contaminants in the THUS include formaldehyde, 

acetic acid, and 2,2,4-trimethyl-1,3-pentanediol diisobutyrate (TXIB) with median concentrations 

of 440, 425, and 36 ppb, respectively. A number of volatile organic compounds (VOCs) were 

higher than published concentrations in other dwellings, but whole THU emission factors for 

most chemicals were either lower than or similar to values reported for newly constructed homes. 

However, several chemicals exceeded previously measured new building emission rates by over a 

factor of 5. Materials were collected from the THUS, and emission factors were determined using 

small chambers to identify the potential source of indoor contaminants. The individual materials 

were grouped by material type, and emissions were used to derive exposure concentrations for 

comparison to reference values. Using material loading factors and ventilation rates that are 

relevant to the trailers, all of the material types we tested had at least two chemicals 

(formaldehyde and nonanal)with derived concentrations in excess of chronic reference exposure 

levels or odor thresholds. The extensive use of composite wood products, sealants, and vinyl 

coverings, combined with the low air exchange rates relative to material surface areas, may 

explain the high concentrations of some VOCs and formaldehyde.

Mendell, M. J. (2007). "Indoor residential chemical emissions as risk factors for-respiratory and allergic 

effects in children: a review." Indoor Air 17(4): 259-277. 

 Most research into effects of residential exposures on respiratory health has focused on allergens, 

moisture/mold, endotoxin, or combustion products. A growing body of research from outside the 

US; however, has associated chemical emissions from common indoor materials with risk of 

asthma, allergies, and pulmonary infections. This review summarizes 21 studies in the 

epidemiologic literature on associations between indoor residential chemical emissions, or 

emission-related materials or activities, and respiratory health or allergy in infants or children. 

Associations, some strong, were reported between many risk factors and respiratory or allergic 

effects. Risk factors identified most frequently included formaldehyde or particleboard, phthalates 

or plastic materials, and recent painting. Findings for other risk factors, such as aromatic and 

aliphatic chemical compounds, were limited but suggestive. Elevated risks were also reported for 

renovation and cleaning activities, new furniture, and carpets or textile wallpaper. Reviewed 

studies were entirely observational, limited in size, and variable in quality, and specific risk 

factors identified may only be indicators for correlated, truly causal exposures. Nevertheless, 

overall evidence suggests a new class of residential risk factors for adverse respiratory effects, 

ubiquitous in modern residences, and distinct from those currently recognized. It is important to 

confirm and quantify any risks, to motivate and guide necessary preventive actions. 
3-63

Mentese, S. and G. Gullu (2006). "Variations and sources of formaldehyde levels in residential indoor air 

in Ankara, Turkey." Indoor and Built Environment 15(3): 273-281. 

 A study in Ankara was performed to examine any association between formaldehyde levels and 

housing characteristics. This involved collection of 309 air samples which were analysed using a 

colorimetric method. Formaldehyde concentrations ranged from 2.34 mu g(.)m(-3) to 866.22 mu 

g(.)m(-3) (median, 71.48 mu g(.)m(-3)). Formaldehyde levels were elevated in homes inhabited 

by at least one smoker and were correlated with indoor and outdoor temperature, age of house 

and density of plywood furniture. Sufficient sample numbers were collected to allow the data to 

be statistically divided into five daytime periods. These data suggest that the formaldehyde 

concentrations were generally slightly higher in the afternoon. A simple mathematical model 

involving smoking activity has been developed for estimating the formaldehyde decay rates for 

two rooms in one of the typical background homes. When the windows and doors were closed, 

the formaldehyde concentrations in indoor air decreased within 10h to background 

concentrations, although this change depended on the room volume and the natural air exchange 

rate. 

Molhave, L., L. E. Sparks, et al. (1996). "The Danish twin apartment study .2. Mathematical modeling of 

the relative strength of sources of indoor air pollution." Indoor Air-International Journal of Indoor Air 

Quality and Climate 6(1): 18-30. 

 This study deals with the modeling of air pollution in apartments from laboratory measurements 

of source strengths, using formaldehyde and Total Volatile Organic Compounds (TVOCs) as 

model pollutants. The sources in two test apartments were grouped into two: building-related 

sources and occupant-related sources. The measured source strengths and ventilation rates were 

used for the prediction of concentrations expected in the apartments. These predictions were 

compared to measurements in the apartment over 12 months. The conclusions were that the 

model predictions based on emission rates measured in the laboratory can be used to predict the 

long-term concentration of the two model pollutants in the apartments. Considering the measured 

differences in ventilation between the apartments, an occupant emission rate of between 0.2 and 

0.3 mg/h/kg body weight could be estimated. Based on previous suggested limits of acceptable 

exposures of humans to VOCs, an acceptable average emission rate of VOCs from building 

materials in general was estimated to be about 30 mu g/m(2)/h. The modeling showed that during 

the first 200 days, building materials dominated the emissions. After this, sources relating to the 

occupants dominated. On average about half of the VOC pollution originated from the building 

materials. 
3-64

Morrison, G. C., W. W. Nazaroff, et al. (1998). "Indoor air quality impacts of ventilation ducts: Ozone 

removal and emissions of volatile organic compounds." Journal of the Air & Waste Management 

Association 48(10): 941-952. 

 The concentrations of contaminants in the supply air of mechanically ventilated buildings may be 

altered by pollutant emissions from and interactions with duct materials. We measured the 

emission rate of volatile organic compounds (VOCs) and aldehydes from materials typically 

found in ventilation ducts. The emission rate of VOCs per exposed surface area of materials was 

found to be low for some duct liners, but high for duct sealing caulk and a neoprene gasket. For a 

typical duct, the contribution to VOC concentrations is predicted to be only a few percent of 

common indoor levels. We exposed selected materials to similar to 100-ppb ozone and measured 

VOC emissions. Exposure to ozone increased the emission rates of aldehydes from a duct liner, 

duct sealing caulk, and neoprene gasket. The emission of aldehydes from these materials could 

increase indoor air concentrations by amounts that are as much as 20% of odor thresholds. We 

also measured the rate of ozone uptake on duct liners and galvanized sheet metal to predict how 

much ozone might be removed by a typical duct in ventilation systems. For exposure to a 

constant ozone mol fraction of 37 ppb, a lined duct would initially remove similar to 9% of the 

ozone, but over a period of 10 days the ozone removal efficiency would diminish to less than 4%. 

In an unlined duct, in which only galvanized sheet metal is exposed to the airstream, the removal 

efficiency would be much lower, similar to 0.02%. Therefore, ducts in ventilation systems are 

unlikely to be a major sink for ozone. 

Mui, K. W., W. Y. Chan, et al. (2007). "Fungi - an indoor air quality assessment parameter for airconditioned offices." Building Services Engineering Research & Technology 28(3): 265-274. 

 Representative assessment parameters are proposed for indoor air quality (IAQ) audit in various 

strategies and guidelines.' In Hong Kong, assessment of indoor airborne fungi is not incorporated 

in many IAQ audits of air-conditioned offices, although the exposure to airborne fungi could 

cause a variety of adverse health effects. An IAQ assessment for a local office will audit 12 

parameters, including air temperature, relative humidity, air velocity, carbon dioxide, carbon 

monoxide, respirable suspended particulates, nitrogen dioxide, ozone, formaldehyde, total volatile 

organic compounds, radon, and airborne bacteria. This paper reviews recent studies of the indoor 

airborne fungi levels and IAQ assessments in some air-conditioned offices of Hong Kong and 

evaluates the contribution of the airborne fungi to an unsatisfactory IAQ in the environment. The 

unsatisfactory rates regarding the assessment parameters were evaluated using the Monte Carlo 

simulations with measured data in Hong Kong Offices. In particular, the impact of selecting 
3-65

representative IAQ assessment parameters was examined against an express assessment protocol 

(EAP), which assessed some dominant contributors of unsatisfactory IAQ.(2) The results reported 

that the three top ranked contributors for unsatisfactory IAQ were total volatile organic 

compounds (TVOC), indoor airborne fungi count (AFC) and airborne bacteria count (ABC) for 

air-conditioned offices of Hong Kong. 

 Practical applications: This study has shown that the assessments of airborne fungi levels 

in office environment is an important issue and further investigations for the airborne fungi in the 

IAQ audits were thus recommended. The results of this study could be a useful source of 

reference for policymakers in evaluation of an effective IAQ assessment protocol with some 

representative IAQ assessment parameters. 

Nazaroff, W. W. and C. J. Weschler (2004). "Cleaning products and air fresheners: exposure to primary 

and secondary air pollutants." Atmospheric Environment 38(18): 2841-2865. 

 Building occupants, including cleaning personnel, are exposed to a wide variety of airborne 

chemicals when cleaning agents and air fresheners are used in buildings. Certain of these 

chemicals are listed by the state of California as toxic air contaminants (TACs) and a subset of 

these are regulated by the US federal government as hazardous air pollutants (HAPs). California's 

Proposition 65 list of species recognized as carcinogens or reproductive toxicants also includes 

constituents of certain cleaning products and air fresheners. In addition, many cleaning agents and 

air fresheners contain chemicals that can react with other air contaminants to yield potentially 

harmful secondary products. For example, terpenes can react rapidly with ozone in indoor air 

generating many secondary pollutants, including TACs such as formaldehyde. Furthermore, 

ozone-terpene reactions produce the hydroxyl radical, which reacts rapidly with organics, leading 

to the formation of other potentially toxic air pollutants. Indoor reactive chemistry involving the 

nitrate radical and cleaning-product constituents is also of concern, since it produces organic 

nitrates as well as some of the same oxidation products generated by ozone and hydroxyl radicals. 

 Few studies have directly addressed the indoor concentrations of TACs that might result 

from primary emissions or secondary pollutant formation following the use of cleaning agents 

and air fresheners. In this paper, we combine direct empirical evidence with the basic principles 

of indoor pollutant behavior and with information from relevant studies, to analyze and critically 

assess air pollutant exposures resulting from the use of cleaning products and air fresheners. 

Attention is focused on compounds that are listed as HAPs, TACs or Proposition 65 

carcinogens/reproductive toxicants and compounds that can readily react to generate secondary 

pollutants. The toxicity of many of these secondary pollutants has yet to be evaluated. The 

inhalation intake of airborne organic compounds from cleaning product use is estimated to be of 
3-66

the order of 10 mg d(-1) person(-1) in California. More than two dozen research articles present 

evidence of adverse health effects from inhalation exposure associated with cleaning or cleaning 

products. Exposure to primary and secondary pollutants depends on the complex interplay of 

many sets of factors and processes, including cleaning product composition, usage, building 

occupancy, emission dynamics, transport and mixing, building ventilation, sorptive interactions 

with building surfaces, and reactive chemistry. Current understanding is sufficient to describe the 

influence of these variables qualitatively in most cases and quantitatively in a few. (C) 2004 

Elsevier Ltd. All rights reserved. 

Nemli, G. and I. Ozturk (2006). "Influences of some factors on the formaldehyde content of 

particleboard." Building and Environment 41(6): 770-774. 

 In this study, effects of specific gravity (SG), shelling ratio, wood species, and pressure on the 

formaldehyde content, physical (SG and thickness swelling (TS)), and mechanical properties 

(modulus of rupture (MOR), modulus of elasticity (MOE), and internal bond (IB) strength) of 

particleboard were examined. The best manufacturing parameters were determined for E-1 grade 

particleboard manufacturing from urea formaldehyde (UF) adhesive. Based on the findings of this 

study, increasing of SG, shelling ratio, and pressure increased the formaldehyde content. 

Particleboard made from particles consisting higher amount of beech particles had lower 

formaldehyde content than that of panel from particles consisting higher amount of pine particles. 

(C) 2005 Elsevier Ltd. All rights reserved. 

Neuhaus, T., R. Oppl, et al. (2008). "Formaldehyde emissions from mineral wool in building 

constructions into indoor air." Indoor Air (Denmark). 

 One stone wool insulation product containing phenol-urea-formaldehyde binder was tested for the 

emissions of formaldehyde and volatile organic compounds (VOC) simulating real use in roof 

constructions. Results are compared with earlier published results from tests with wall 

constructions and to international indoor air limit values. Possible future handling by using 

reductions factors when testing pure mineral wool products without constructions is discussed. 

Parent, D., S. Stricker, et al. (1998). "Optimum ventilation and air flow control in buildings." Energy and 

Buildings 27(3): 239-245. 

 The LTEE laboratory of Hydro-Quebec, in collaboration with Canada Mortgage and Housing 

conducted an indoor air quality study involving 30 single family-detached houses heated with 

electric baseboard heaters in the vicinity of Trois-Rivieres during the 1993-94 heating season. 

The houses were selected according to the measured air leakage at 50 Pa so as to have a sample 
3-67

distribution similar to the distribution of air leakage of houses in the province of Quebec. The 

'source strength' of several air pollutants were calculated from measurements of ambient pollutant 

levels and total ventilation during a 2 week test. In addition: the indoor CO2 and humidity levels 

were recorded in eight of the houses continuously during the heating season. Model studies using 

the measured pollutant source strengths and measured equivalent leakage areas of the buildings 

indicated that the recommended health guidelines for airborne respirable solid particles (RSP's), 

CO2 and formaldehyde are exceeded during periods of low total ventilation, coinciding with mild 

outdoor temperatures and low wind conditions. With the room occupied and the door closed, CO2 

levels in the bedroom increased steadily during the night until morning, when the door was 

opened, to levels in excess of 3500 ppm with one person and in excess of 4500 ppm with two 

persons. Various different methods of ventilating some of the houses were tested, including quiet 

replacement exhaust fans, mixing fans for indoor air and a fresh air intake and mixing system. 

The effects of operating various air handling systems were monitored by keeping track of indoor 

CO2 and relative humidity in the master bedroom and occupancy in person-hours per day. (C) 

1998 Elsevier Science S.A. ALI rights reserved. 

Park, J. S. and K. Ikeda (2004). "Exposure to the mixtures of organic compounds in homes in Japan." 

Indoor Air 14(6): 413-420. 

 The aim of the study reported herein was to characterize occupants' simultaneous exposure to 

mixtures of organic compounds in homes. Statistical distributions for concentrations of 28 

organic compounds (17 VOCs and 11 aldehydes) measured in 1417 homes were generated to 

analyze concentration distributions. Three candidate distributions were identified for fitting the 

measured data: log-normal, exponential and gamma distributions. It appears from the results of 

fitting tests that gamma distributions are capable of representing 28 compound concentrations. 

Probability distributions show that formaldehyde and acetaldehyde ranged from 25 to 220 

mug/m(3) at 90% probabilities and most VOCs ranged from 3 to 80 mug/m(3) at 90% 

probabilities. In order to characterize the occupant's exposure to the mixtures, the joint probability 

distributions of organic compounds were generated from the best-fitted distributions of individual 

compounds under the assumption that concentrations of organic compounds are mutually 

independent in homes. These joint distributions provided the statistical data for characterizing the 

occupant's exposure to the mixtures of organic compounds in homes. 

Park, J. S. and K. Ikeda (2006). "Variations of formaldehyde and VOC levels during 3 years in new and 

older homes." Indoor Air 16(2): 129-135. 

 Indoor air organic compounds were continuously monitored during 3 years in new and older 
3-68

homes which were voluntarily selected throughout countries. The levels of volatile organic 

compounds (VOCs) in the new homes decreased markedly after 1 year, and steady emissions of 

VOCs were obtained in the initial months. Formaldehyde and a-pinene related to wooden 

materials need a longer flushing period than the other compounds in the new homes. The levels of 

the indoor air organic compounds in the older homes showed no significant fluctuation during the 

3-year period. Decreases of the indoor-produced compounds in the new homes did not depend 

upon the ventilation systems. The results indicate that the indoor-produced compounds in the new 

homes will be more influenced by the aging decreases of emission source strengths than 

ventilation systems. The quantitative information on the trend of the indoor air organic compound 

levels will be useful for the risk assessment of indoor exposure to those compounds, and also for 

Japanese IAQ guidelines. 

Petrick, L. and Y. Dubowski (2009). "Heterogeneous oxidation of squalene film by ozone under various 

indoor conditions." Indoor Air 19(5): 381-391. 

 P>The effects of indoor conditions (ozone concentration, temperature, relative humidity (RH), 

and the presence of NOx) on heterogeneous squalene oxidation were studied with Attenuated 

Total Reflectance-Fourier Transform Infrared spectroscopy. The heterogeneous kinetics of 

squalene-ozone reaction revealed a pseudo-first-order reaction rate constant of 1.22 x 10-5/s at 

[O-3] = 40 ppb. Oxidation kinetics were insensitive to temperature over the range of 24-58 +/- 2 

degrees C as well as to RH and presence of NOx. Products, however, were affected by the 

environmental parameters. As temperature was increased, fewer surface products and more low 

molecular weight gaseous products were observed. Lower air exchange rates also enhanced gas 

phase reactions, allowing for formation of secondary gas phase products. As RH increased, there 

was a shift in product distribution from ketones to aldehydes, and the presence of NOx during 

squalene ozonolysis resulted in the formation of nitrated oxidation products. Identified surface 

products included 6-methyl-5-hepten-2-one, geranyl acetone, and long chain ketones and 

aldehydes, while gas phase products included formaldehyde, acetone, 4-oxopentanal (4-OPA), 

glyoxal, and pyruvic acid.Practical Implications 

 Heterogeneous oxidation of squalene resulted in surface products including long chain 

aldehydes and ketones, and gas phase products including formaldehyde, a known human 

carcinogen (IARC 2006), and bicarbonyl compounds like: 4-oxopentanal (4-OPA), glyoxal, and 

pyruvic acid that are characterized as asthma triggers and sensitizers (Anderson et al., 2007; 

Jarvis et al., 2005). In addition, ozonolysis experiments in the presence of NOx showed the 

formation of nitrated surface oxidation products. Such nitrated products may have higher 

mutagenicity, carcinogenicity, or allergenic potential than their nitrate free counterparts (Franze 
3-69

et al., 2005; Pitts, 1983). Kinetic studies determined that at moderate ozone levels of 40 ppb 

(Uhde and Salthammer, 2007), and an estimated skin surface density of 4 x 1015 molecules/cm2, 

surface reaction would lead to a minimum product formation flux of 4 x 1010 molecules cm2/s. 

As squalene is naturally occurring and continually produced by the human body, its concentration 

in the indoor environment cannot be controlled. However, this study highlights the importance of 

regulating air exchange rate, temperature, and ozone level in the indoor environment on the 

formation of potentially harmful or irritating squalene oxidation products. 

Petronella, S. A., R. Thomas, et al. (2005). "Clearing the air: A model for investigating indoor air quality 

in Texas schools." Journal of Environmental Health 67(10): 35-42. 

 This pilot project focused on the assessment of indoor air quality at a local high school in 

Galveston, Texas, using methods based on guidelines for the U.S. Environmental Protection 

Agency's Indoor Air Quality Tools for Schools program. Tools for Schools, developed for 

evaluating and ensuring acceptable air quality for schools, takes a low-cost, minimalinvolvement, primarily educational approach. The authors also compared the findings from this 

approach with the results of an air-sampling program. The overall goal was to determine 9 use of 

Tools for Schools was sufficient to identify conditions with the potential to cause adverse health 

effects. The primary objectives were to 1) establish an indoor air quality committee for the school 

to implement Took for Schools assessments and management strategies, 2) collect air quality data 

in high-risk areas identified within the school by the indoor air quality committee, 3) collect 

outdoor air quality data at or in close proximity to the school, and 4) develop methods and 

instruments for assessing environmental risks associated with daily school attendance. Data were 

gathered on levels of formaldehyde and other volatile organic compounds (VOCs), ozone, 

particulate matter (PM10), mold, relative humidity, and temperature. Data values for each 

sampled pollutant were compared with federal standards, recommended values established by the 

American Conference of Governmental Industrial Hygienists for non-industrial populations, and 

effects screening levels developed by the Texas Commission on Environmental Quality. Levels 

of all VOCs except formaldehyde were found to be well within guidelines, as were ozone and 

particulate-matter levels. Mold, however, was widespread, including both common species and 

species associated with allergy and asthma, such as Aspergillus and Alternaria. In general, Tools 

for Schools provides an excellent foundation for a school indoor air quality program, although the 

authors did find it necessary to streamline data collection and did find that mold with the potential 

for adverse health effects was present, albeit not visible in some areas. 

Que, Z. L., T. Furuno, et al. (2007). "Evaluation of three test methods in determination of formaldehyde 
3-70

emission from particleboard bonded with different mole ratio in the urea-formaldehyde resin." Building 

and Environment 42(3): 1242-1249. 

 The use of urea-formaldehyde (UF) resins with lower contents of free formaldehyde in the board 

industry has led to products with very low emissions of formaldehyde. In this study, a detailed 

account is given of how UF resins with different mole ratios of formaldehyde to urea within the 

range of 0.97-1.27 influence the formaldehyde emission. In order to evaluate simpler laboratory 

methods for determining the formaldehyde emission from particleboard, the desiccator (JIS A 

5908, 2003) and the EN 120 (European Standard, 199 1) have been compared with the I m 3 

chamber method SS 270236 (Swedish Standard of determining formaldehyde emission with 

chamber test, 1988). Good relationships were obtained between the methods studied with 

correlation coefficients of > 0.9. The value of formaldehyde emission decreased linearly with the 

mole ratio of formaldehyde to urea down to 1.05 where the effect smoothed out. The effect on the 

formaldehyde emission of temperature and storage time for tested boards also was studied. The 

heat treatment lowered the perforator value with resins that had mole ratios equal to or higher 

than 1.15, at the two lowest mole ratios 0.97 and 1.01, there was a tendency for the heat treatment 

to increase the perforator value. After the boards were stored for 6 months at 23 degrees C and 

50% RH, the perforator values were unchanged or negligibly changed with the lower mole ratios 

and there was a more pronounced change with a'higher mole ratio of 1.27. (c) 2005 Elsevier Ltd. 

All rights reserved. 

Que, Z. L., T. Furuno, et al. (2007). "The mathematical model for the formaldehyde emission from woodbased board in room." Building and Environment 42(6): 2321-2324. 

 A mathematical model which describes the influence of various parameters on formaldehyde 

concentration in the atmosphere of a room containing wood-based boards was developed. The 

physical meanings and measuring methods of the parameters of the model are also discussed. 

Based on this model, two indices for commenting the formaldehyde emission process of woodbased boards are proposed, and inequality estimation for the formaldehyde content of wood-based 

boards at any moment and a time estimation which shows when the room satisfies the 

environment quality standard are also given. (c) 2006 Elsevier Ltd. All rights reserved. 

Risholm-Sundman, M., A. Larsen, et al. (2007). "Formaldehyde emission - Comparison of different 

standard methods." Atmospheric Environment 41(15): 3193-3202. 

 The emission of formaldehyde is an important factor in the evaluation of the environmental and 

health effects of woodbased board materials. This article gives a comparison between commonly 

used European test methods: chamber method [EN 717-1, 2004. Wood-based panels-
3-71

determination of formaldehyde release-Part 1: formaldehyde emission by the chamber method. 

European Standard, October 2004], gas analysis method [EN 717-2, 1994. Wood-based panelsdetermination of formaldehyde release-Part 2: formaldehyde release by the gas analysis method, 

European Standard, November 1994], flask method [EN 717-3, 1996. Wood-based panelsdetermination of formaldehyde release-Part 3: formaldehyde release by the flask method, 

European Standard, March 1996], perforator method [EN 120, 1993. Wood based panelsdetermination of formaldehyde content-extraction method called perforator method, European 

Standard, September 1993], Japanese test methods: desiccator methods [JIS A 1460, 2001. 

Building boards. Determination of formaldehyde emission-desiccator method, Japanese Industrial 

Standard, March 2001 and JAS MAFF 233, 2001] and small chamber method [JIS A 1901, 2003. 

Determination of the emission of volatile organic compounds and aldehydes for building 

products-small chamber method, Japanese Industrial Standard, January 2003], for solid wood, 

particleboard, plywood and medium density fiberboard. 

 The variations between the results from different methods can partly be explained by 

differences in test conditions. Factors like edge sealing, conditioning of the sample before the test 

and test temperature have a large effect on the final emission result. The Japanese limit for F**** 

of 0.3 mg 1(-1) (in desiccator) for particleboards was found to be equivalent to 0.04 mg m(-3) in 

the European chamber test and 2.8 mg per 100 g in the perforator test. The variations in interlaboratory tests are much larger than in intra-laboratory tests; the coefficient of variation is 16% 

and 6.0% for the chamber method, 25% and 3.5% for the gas analysis method and 15% and 5.2% 

for the desiccator method. (C) 2006 Elsevier Ltd. All rights reserved. 

Rumchev, K. B., J. T. Spickett, et al. (2002). "Domestic exposure to formaldehyde significantly increases 

the risk of asthma in young children." European Respiratory Journal 20(2): 403-408. 

 Concern has arisen in recent years about indoor air pollution as a risk factor for asthma. 

Formaldehyde exposure vas examined in relation to asthma among young children (between 6 

months and 3 yrs old) in a population-based control study carried out in Perth, Western Australia, 

between 1997-1999. An association between exposure to formaldehyde and asthma in young 

children has been suggested. Cases (n=88), whose parents were recruited at Princess Margaret 

Hospital Accident and Emergency Dept (Perth, Western Australia), were children discharged 

with asthma as the primary diagnosis. Controls (n=104), who were children in the same age group 

without asthma diagnosed by a doctor, were identified from birth records through the Health Dept 

of Western Australia (Perth, Western Australia). Health outcomes for the children were studied 

using a respiratory questionnaire and skin-prick tests. Formaldehyde, average temperature and 

relative humidity were measured on two occasions, winter (July-September 1998) and summer 
3-72

(December 1998-March 1999) in the child's bedroom and in the living room. 

 The study found seasonal differences in formaldehyde levels in the children's bedrooms 

and living rooms with significantly greater formaldehyde exposure during the summer period for 

case and control subjects. The generalised estimating equation model showed that children 

exposed to formaldehyde levels of greater than or equal to60 mug.m(-3) are at increased risk of 

having asthma. The results suggest that domestic exposure to formaldehyde increases the risk of 

childhood asthma. 

Salthammer, T. and F. Fuhrmann (2007). "Photocatalytic surface reactions on indoor wall paint." 

Environmental Science & Technology 41(18): 6573-6578. 

 The reduction of indoor air pollutants by air cleaning systems has received considerable 

interest, and a number of techniques are now available, So far, the method of 

photocatalysis was mainly applied by use of titanium dioxide (TiO2) in flow reactors 

under UV light of high intensity. Nowadays, indoor wall paints are equipped with 

modified TiO2 to work as a catalyst under indoor daylight or artificial light. In chamber 

experiments carried out under indoor related conditions it was shown that the method 

works for nitrogen dioxide with air exchange and for formaldehyde without air exchange 

at high concentrations. In further experiments with volatile organic compounds (VOCs), 

a small effect was found for terpenoids with high k(OH) rate constants. For other VOCs 

and carbon monoxide there was no degradation at all or the surface acted as a reversible 

sink. Secondary emissions from the reaction of paint constituents were observed on 

exposure to light. From the results it is concluded that recipes of photocatalytic wall 

paints need to be optimized for better efficiency under indoor conditions. 

Sax, S. N., D. H. Bennett, et al. (2004). "Differences in source emission rates of volatile organic 

compounds in inner-city residences of New York City and Los Angeles." J Expo Anal Environ Epidemiol

14 Suppl 1: S95-109. 

 The Toxics Exposure Assessment Columbia-Harvard (TEACH) Project characterized personal, 

indoor, and outdoor concentrations of a suite of volatile organic compounds (VOCs) for high 

school students living in New York City (NYC) and Los Angeles (LA). This paper presents the 

analysis of VOC measurements collected indoors and outdoors for 46 students' homes in NYC 

and for 41 students' homes in LA across two seasons. Dual-sorbent thermal desorption tubes were 

used for the collection of 15 VOCs and C(18) 2,4-dinitrophenylhydrazine-coated cartridges were 

used for the collection of seven aldehydes. Air-exchange rates (AERs) were also measured using 
3-73

a perfluorocarbon tracer gas method. The AERs were lower in the winter in both cities, averaging 

1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) in NYC in the summer and 2.5 h(-1) 

in LA in the fall. Higher AERs were generally associated with lower indoor-outdoor ratios with 

significant differences for the compounds with indoor sources, including chloroform, 1,4-

dichlorobenzene, and formaldehyde. Using a mass-balance model to account for AER and other 

housing parameters, effective source emission rates (SER) were calculated for each compound. 

Based on I/O ratios and source emission rates, VOCs could be divided into: (1). indoor-sourceinfluenced compounds, (2). those with contributions from both indoor and outdoor sources, and 

(3). those with mostly outdoor sources. Significant indoor sources were found for the following 

six compounds (mean emission rates presented): chloroform (0.11 mg/h), 1,4-dichlorobenzene 

(19 mg/h), formaldehyde (5 mg/h), acetaldehyde (2 mg/h), benzaldehyde (0.6 mg/h), and 

hexaldehyde (2 mg/h). Although chloroform had variable I/O ratios across seasons, SERs, which 

accounted for AER, were similar in both cities for both seasons (e.g., LA means 0.12 and 0.11 

mg/h in winter and fall, respectively). Formaldehyde had substantially higher indoor emission 

rates in the summer in NYC compared to winter (3.8 vs. 1.6 mg/h) but lower in the fall in LA 

compared to winter (4.3 vs. 5.0 mg/h). Uncertainty analysis determined that source strength 

calculations were not sensitive to measurement error for a subset of homes in LA. 

Sax, S. N., D. H. Bennett, et al. (2004). "Differences in source emission rates of volatile organic 

compounds in inner-city residences of New York City and Los Angeles." Journal of Exposure Analysis 

and Environmental Epidemiology 14: S95-S109. 

 The Toxics Exposure Assessment Columbia-Harvard (TEACH) Project characterized personal, 

indoor, and outdoor concentrations of a suite of volatile organic compounds (VOCs) for high 

school students living in New York City (NYC) and Los Angeles ( LA). This paper presents the 

analysis of VOC measurements collected indoors and outdoors for 46 students' homes in NYC 

and for 41 students' homes in LA across two seasons. Dual-sorbent thermal desorption tubes were 

used for the collection of 15 VOCs and C-18 2,4-dinitrophenylhydrazine-coated cartridges were 

used for the collection of seven aldehydes. Air-exchange rates (AERs) were also measured using 

a perfluorocarbon tracer gas method. The AERs were lower in the winter in both cities, averaging 

1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) in NYC in the summer and 2.5 h(-1) 

in LA in the fall. Higher AERs were generally associated with lower indoor-outdoor ratios with 

significant differences for the compounds with indoor sources, including chloroform, 1,4-

dichlorobenzene, and formaldehyde. Using a mass-balance model to account for AER and other 

housing parameters, effective source emission rates (SER) were calculated for each compound. 

Based on I/O ratios and source emission rates, VOCs could be divided into: (1) indoor-source-
3-74

influenced compounds, (2) those with contributions from both indoor and outdoor sources, and 

(3) those with mostly outdoor sources. Significant indoor sources were found for the following 

six compounds ( mean emission rates presented): chloroform (0.11 mg/h), 1,4-dichlorobenzene 

(19 mg/h), formaldehyde (5 mg/h), acetaldehyde (2 mg/h), benzaldehyde (0.6 mg/h), and 

hexaldehyde (2 mg/h). Although chloroform had variable I/O ratios across seasons, SERs, which 

accounted for AER, were similar in both cities for both seasons (e.g., LA means 0.12 and 0.11 

mg/h in winter and fall, respectively). Formaldehyde had substantially higher indoor emission 

rates in the summer in NYC compared to winter (3.8 vs. 1.6 mg/h) but lower in the fall in LA 

compared to winter (4.3 vs. 5.0 mg/h). Uncertainty analysis determined that source strength 

calculations were not sensitive to measurement error for a subset of homes in LA. 

Schupp, T., H. M. Bolt, et al. (2005). "Maximum exposure levels for xylene, formaldehyde and 

acetaldehyde in cars." Toxicology 206(3): 461-470. 

 Although millions of individuals are exposed to emissions from articles inside cars, relatively 

little has been published about possible adverse health effects and about exposure levels that can 

be considered safe or "acceptable". Xylene, formaldehyde and acetaldehyde represent typical 

examples of relevant volatile organic substances (VOC) released from articles inside cars. 

Recently, a concept for derivation of maximum exposure levels for volatile organic substances in 

cars has been published. In the present study we applied this concept to derive maximum 

exposure levels for xylene, formaldehyde and acetaldehyde and compared the resulting 

concentrations to exposure levels usually found inside of cars. We derived Short Term Exposure 

Levels Inside Automotive Vehicles (STELIA) of 29, 0.125 and 15.3 mg/m(3) for xylene, 

formaldehyde and acetaldehyde, respectively. These STELIAs should not be exceeded during 

short-term exposures, for instance when starting a car that had been heated up during parking in 

the sun. Exposure Levels Inside Automotive Vehicles (ELIA, chronic) for chronic exposure to 

non-genotoxic substances were 8.8, 0.125 and 0.635 mg/m(3) for systemic as well as 17.6, 0.125 

and 1.7 mg/m(3) for local exposure to xylene, formaldehyde and acetaldehyde, respectively. 

Although, it is known that exposure limits for carcinogenic substances should be treated with 

caution, encouraged by the well documented threshold mechanisms we nevertheless derived 

ELIAs for Carcinogenic and Mutagenic Substances (ELIA, cm) resulting in 0.125 and 0.635 

mg/m(3) for formaldehyde and acetaldehyde. If these ELIAs are matched against average 

concentrations of xylene, formaldehyde and acetaldehyde found in cars at 23 degreesC (1.22, 

0.048 and 0.042 mg/m(3)), there is no reason for concern. With respect to STELIAs and 

extrapolated concentrations at 65 degreesC (14.7, 1.47 and 1.68 mg/m(3), for xylene, 

formaldehyde and acetaldehyde, respectively), however, a reduction of the concentration of 
3-75

formaldehyde may be necessary. (C) 2004 Elsevier Ireland Ltd. All rights reserved. 

Sekine, Y. and A. Nishimura (2001). "Removal of formaldehyde from indoor air by passive type aircleaning materials." Atmospheric Environment 35(11): 2001-2007. 

 We have developed a board-like air-cleaning material consisting of activated carbon particles and 

manganese oxides, by which HCHO gas is decomposed into carbon dioxide even at room 

temperature. In this study, we investigated removal efficiencies of the air-cleaning board in a 

passive mode using a kinetic approach. First-order removal rate constant, k, corresponding to air 

change rate was characterized for the board as a function of the ratio of applied board area to 

space volume, S/V, and was found directly proportional to S/V with a slope of 25 at 25 degreesC. 

The performance of the board was evaluated in a full-size laboratory with a constant gas 

generation. The board suppressed the increase of indoor HCHO concentration and the time course 

fitted to a theoretical curve. Then, field tests of the air-cleaning board were conducted in newly 

constructed multi-family houses in Japan from May 1998 to January 1999. The board not only 

reduced indoor HCHO concentration from 0.21 to 0.04 ppm for more than 7 months, but also 

enhanced the loss of HCHO gas from building materials in apartments. (C) 2001 Elsevier Science 

Ltd. All rights reserved. 

Sexton, K., M. X. Petreas, et al. (1989). "Formaldehyde Exposures inside Mobile Homes." Environmental 

Science & Technology 23(8): 985-988. 

 An age-stratified random sample of 470 mobile homes was selected from among the more than 

500000 in California. One-week, average indoor formaldehyde concentrations were measured 

during both the summer (July-August 1984) and the winter (February-March 1985) seasons. 

Results indicate that (1) formaldehyde concentrations were well-mixed inside the trailers over a 

1-week period, (2) relatively little variation was observed in formaldehyde concentrations 

between summer and winter, (3) average 1-week formaldehyde values were in the range of 0.07-

0.09 ppm, and (4) formaldehyde levels appear to be decreasing inside mobile homes 

manufactured since about 1980, probably as a result of the increased use of low-formaldehydeemitting building materials. Based on the 470 mobile homes in this study, 31% exceeded the 

maximum concentration of 0.1 ppm formaldehyde recommended by the American Society of 

Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE), the American Industrial 

Hygiene Association (AIHA), and the Environmental Protection Agency (EPA). 

Sherman, M. H. and A. T. Hodgson (2004). "Formaldehyde as a basis for residential ventilation rates." 

Indoor Air 14(1): 2-9. 
3-76

 Traditionally, houses in the US have been ventilated by passive infiltration in combination with 

active window opening. However in recent years, the construction quality of residential building 

envelopes has been improved to reduce infiltration, and the use of windows for ventilation also 

may have decreased due to a number of factors. Thus, there has been increased interest in 

engineered ventilation systems for residences. The amount of ventilation provided by an 

engineered system should be set to protect occupants from unhealthy or objectionable exposures 

to indoor pollutants, while minimizing energy costs for conditioning incoming air. Determining 

the correct ventilation rate is a complex task, as there are numerous pollutants of potential 

concern, each having poorly characterized emission rates, and poorly defined acceptable levels of 

exposure. One ubiquitous pollutant in residences is formaldehyde. The sources of formaldehyde 

in new houses are reasonably understood, and there is a large body of literature on human health 

effects. This report examines the use of formaldehyde as a means of determining ventilation rates 

and uses existing data on emission rates of formaldehyde in new houses to derive recommended 

levels. Based on current, widely accepted concentration guidelines for formaldehyde, the 

minimum and guideline ventilation rates for most new houses are 0.28 and 0.5 air changes per 

hour, respectively. 

Shinohara, N., Y. Kai, et al. (2009). "On-site passive flux sampler measurement of emission rates of 

carbonyls and VOCs from multiple indoor sources." Building and Environment 44(5): 859-863. 

 In indoor environments with high levels of air pollution, it is desirable to remove major sources 

of emissions to improve air quality. In order to identify the emission sources that contribute most 

to the concentrations of indoor air pollutants. we used passive flux samplers (PFSs) to measure 

emission rates of carbonyl compounds and volatile organic compounds (VOCs) from many of the 

building materials and furnishings present in a room in a reinforced concrete building in Tokyo, 

Japan. The emission flux of formaldehyde from a desk was high (125 mu g/m(2)/h). whereas 

fluxes from a door and flooring were low (21.5 and 16.5 mu g/m(2)/h. respectively). The 

emission fluxes of toluene from the ceiling and the carpet were high (80.0 and 72.3 mu g/m(2)/h, 

respectively), whereas that from the flooring was low (9.09 mu g/m(2)/h). The indoor and 

outdoor concentrations of formaldehyde were 61.5 and 8.64 mu g/m(3), respectively, and those of 

toluene were 43.2 and 17.5 mu g/m(3), respectively. The air exchange rate of the room as 

measured by the perfluorocarbon tracer (PFT) method was 1.84/h. Taking into consideration the 

area of the emission sources, the carpet, ceiling, and walls were identified as the principal 

emission sources, contributing 24%, 20%, and 22% of the formaldehyde, respectively, and 22%, 

27%, and 14% of the toluene, respectively, assuming that the emission rate from every major 

emission sources could be measured. in contrast, the door, the flooring, and the desk contributed 
3-77

little to the indoor levels of formaldehyde (1.0%. 0.54%, and 4.1%, respectively) and toluene 

(2.2%, 0.31%, and 0.85%, respectively). (C) 2008 Elsevier Ltd. All rights reserved. 

Singer, B. C., A. T. Hodgson, et al. (2003). "Gas-phase organics in environmental tobacco smoke: 2. 

Exposure-relevant emission factors and indirect exposures from habitual smoking." Atmospheric 

Environment 37(39-40): 5551-5561. 

 Sorption of emitted gas-phase organic compounds onto material surfaces affects environmental 

tobacco smoke (ETS) composition and exposures indoors. We have introduced a new metric, the 

exposure relevant emission factor (EREF) that accounts for sorptive uptake and reemission to 

give the mass of individual ETS constituents available for exposure over a day in which smoking 

occurs. This paper describes month-long experiments to investigate sorption effects on EREFs 

and potential ETS exposures under habitual smoking conditions. Cigarettes were smoked in a 50-

m(3) furnished room over a 3-h period 6-7 days per week, with continuous ventilation at 0.3, 0.6, 

or 2.1 h(-1). Organic gas concentrations were measured every few days over 4-h "smoking", 10-h 

"post-smoking" and 10-h "background" periods. Concentration patterns of volatile ETS 

components including 1,3-butadiene, benzene and acrolein were similar to those calculated for a 

theoretical non-sorbing tracer, indicating limited sorption. Concentrations of ETS tracers, e.g. 3-

ethenylpyridine (3-EP) and nicotine, and lower volatility toxic air contaminants including phenol, 

cresols, and naphthalene increased as experiments progressed, indicating mass accumulation on 

surfaces and higher desorption rates. Daily patterns stabilized after week 2, yielding a steady 

daily cycle of ETS concentrations associated with habitual smoking. EREFs for sorbing 

compounds were higher under steady cycle versus single-day smoking conditions by similar 

to50% for 3-EP, and by 2-3 times for nicotine, phenol, cresols, naphthalene, and 

methylnaphthalenes. Our results provide relevant information about potential indirect exposures 

from residual ETS (non-smoker enters room shortly after smoker finishes) and from reemission, 

and their importance relative to direct exposures (non-smoker present during smoking). Under the 

conditions examined, indirect exposures accounted for a larger fraction of total potential 

exposures for sorbing versus non-sorbing compounds, and at lower versus higher ventilation 

rates. Increasing ventilation can reduce indirect exposures to very low levels for non-sorbing ETS 

components, but indirect routes accounted for similar to50% of potential nicotine exposures 

during non-smoking periods at all ventilation rates. Published by Elsevier Ltd. 

Sorensen, D. N. and C. J. Weschler (2002). "Modeling-gas phase reactions in indoor 

environments using computational fluid dynamics." Atmospheric Environment 36(1): 9-18. 

 This CFD modeling study examines the concentrations of two gaseous compounds that 
3-78

react in an indoor setting to produce a hypothetical product. The reactants are ozone and 

either d-limonene or alpha-terpinene (which reacts with ozone about 40 times faster than 

d-limonene). In addition to two different terpenes, the scenarios include two air exchange 

rates (0.5 and 2.0 h(-1)). The terpene is introduced as a floor source with an emission 

pattern similar to a floor-care product. These four scenarios have been set in a fairly large 

two-dimensional room (13.6 x 40.6 m) with a supply at the top of the left wall and an 

exhaust at the bottom of the right wall. The room has been deliberately scaled so that the 

Reynolds numbers for key flow regimes match those of a room in which the calculated 

flow field has been validated against measured data. It has been further assumed that 

ozone interacts with room surfaces while the terpenes do not. The results show that for all 

four scenarios, under steady-state conditions, there are large concentration gradients 

within the room for both reactants and product. To some extent this is due to imperfect 

mixing. However. it also reflects that reactions occur at different rates across the room 

(because of varying reactant concentrations) and that the time available for reactions to 

occur varies with the room location (because the "age of the air" varies from point to 

point). Locally, within the room, the concentrations calculated by the CFID method differ 

significantly from those calculated by a one-compartment mass-balance model assuming 

perfect mixing. (C) 2002 Elsevier Science Ltd. All rights reserved. 

Spengler, J. D., J. McCarthy, et al. (2001). Volatile Organic Compounds. Indoor Air Quality Handbook. 

Tichenor, B. A. and L. E. Sparks (1996). "Managing exposure to indoor air pollutants in residential and 

office environments." Indoor Air-International Journal of Indoor Air Quality and Climate 6(4): 259-270. 

 Sources of indoor air pollutants in residential and office environments can be managed to reduce 

occupant exposures. Techniques for managing indoor air pollution sources include: source 

elimination, substitution, modification, pretreatment, and altering the amount, location, or time of 

use. Intelligent source management requires knowledge of the source's emission characteristics, 

including chemical composition, emission rates, and decay rates. In addition, knowledge of 

mechanical and natural outdoor air exchange rates, heating/air-conditioning duct flow rates, and 

local exhaust fan (e.g., kitchen, bathroom) flow rates is needed to determine pollutant 

concentrations. Finally, indoor air quality (IAQ) models use this information and occupant 

activity patterns to determine instantaneous and/or cumulative individual exposure. This paper 

describes a number of residential and office scenarios for various indoor air pollution sources, 

several ventilation conditions, and typical occupant activity patterns. IAQ model predictions of 
3-79

occupant exposures for these scenarios are given for selected source management options. A onemonth period was used to compare exposures; thus, long-term exposure information is not 

presented in this paper. (C) Indoor Air (1996). 

Tucker, S., S. Brown, et al. (2008). Estimating Indoor Air Quality using Integrated 3D CAD Building 

Models. Third National Conference of the Coopeartive Research Centre (CRC) for Construction 

Innovation. 

 The indoor air quality (IAQ) in buildings is currently assessed by measurement of pollutants 

during building operation for comparison with air quality standards. Current practice at the design 

stage tries to minimise potential indoor air quality impacts of new building materials and contents 

by selecting low-emission materials. However low-emission materials are not always available, 

and even when used the aggregated pollutant concentrations from such materials are generally 

overlooked. This paper presents an innovative tool for estimating indoor air pollutant 

concentrations at the design stage, based on emissions over time from large area building 

materials, furniture and office equipment. The estimator considers volatile organic compounds, 

formaldehyde and airborne particles from indoor materials and office equipment and the 

contribution of outdoor urban air pollutants affected by urban location and ventilation system 

filtration. The estimated pollutants are for a single, fully mixed and ventilated zone in an office 

building with acceptable levels derived from Australian and international health-based standards. 

The model acquires its dimensional data for the indoor spaces from a 3D CAD model via IFC 

files and the emission data from a building products/contents emissions database. This paper 

describes the underlying approach to estimating indoor air quality and discusses the benefits of 

such an approach for designers and the occupants of buildings. 

Tuomi, T. (2000). "Emission of ozone and organic volatiles from a selection of laser printers and 

photocopiers." Applied Occupational and Environmental Hygiene 15(8): 629–634. 

 To estimate the impact of office equipment on the quality of indoor air, the emission of ozone and 

organic volatiles was measured from one photocopier and four laser printers, three of which 

operated according to traditional corona discharge technology. The laser printers equipped with 

traditional technology emitted significant amounts of ozone and formaldehyde. Lesser amounts of 

other volatile aldehydes were emitted during printing. The photocopier emitted mainly ozone. 

 In a well-ventilated office environment, the amounts encountered here for individual 

volatiles were within recommended maximum exposure limits for a reasonable density of 

printers. Because it is not known whether the concentration of irritating volatiles, such as 

formaldehyde, should be kept lower in an ozone rich environment or not, and because emissions 
3-80

in the immediate vicinity of the printers exceeded recommendations, the authors recommend that 

laser printers equipped with the traditional corona rods not be placed beside or immediately at the 

working site of office personnel. This way, ozone concentrations can be kept below 

recommended maximum exposure limits, provided that the ventilation rate is adequate. Further, it 

seems that if a reliable quantitative comparison of total organic volatiles prior to and during 

printing is to be made, the inertness of the sorbent toward ozone should be confirmed. 

Uhde, E. and T. Salthammer (2007). "Impact of reaction products from building materials and furnishings 

on indoor air quality - A review of recent advances in indoor chemistry." Atmospheric Environment

41(15): 3111-3128. 

 The variety of chemical substances present in modern building products, household products and 

furnishings provides potential for chemical reactions in the material (case 1), on the material 

surface (case 2) and in the gas phase (case 3). Such "indoor chemistry" is known as one of the 

main reasons for primary and secondary emissions. The conditions of production often cause 

unwanted side reactions and a number of new compounds can be found in finished products. 

Elevated temperatures are responsible for the degradation of cellulose, decomposition of nonheat-resistant additives and other thermally induced reactions like Diels-Alder synthesis. 

Heterogeneous chemistry takes place on the surface of materials. Well-known examples are the 

formation of aliphatic aldehydes from the oxidation of unsaturated fatty acids or the cleavage of 

photoinitiators under the influence of light. In case of composite flooring structures hydrolysis is 

one of the major pathways for the appearance of alcohols from esters. If different kinds of 

material are fixed together, emissions of new VOCs formed by inter-species reactions are 

possible. Other indoor air pollutants are formed by rearrangement of cleavage products or by 

metabolism. Compounds with -C=C- bonds like terpenes, styrene, 4-phenylcyclohexene, etc. 

undergo gas phase reactions with O3, NOx. OH and other reactive gases. It has been shown that 

such products derived from indoor-related reactions may have a negative impact on indoor air 

quality due to their low odor threshold or health-related properties. Therefore, the understanding 

of primary and secondary emissions and the chemical processes behind is essential for the 

evaluation of indoor air quality. This publication gives an overview on the current state of 

research and new findings regarding primary and secondary emissions from building products 

and furnishings. 

Wang, B., S. C. Lee, et al. (2007). "Characteristics of carbonyls: Concentrations and source strengths for 

indoor and outdoor residential microenvironments in China." Atmospheric Environment 41(13): 2851-

2861. 
3-81

 Indoor and outdoor carbonyl concentrations were measured simultaneously in 12 urban dwellings 

in Beijing, Shanghai, Guangzhou, and Xi'an, China in summer (from July to September in 2004) 

and winter (from December 2004 to February 2005). Formaldehyde was the most abundant 

indoor carbonyls species, while formaldehyde, acetaldehyde and acetone were found to be the 

most abundant outdoor carbonyls species. The average formaldehyde concentrations in summer 

indoor air varied widely between cities, ranging from a low of 19.3 mu g m(-3) in Xi'an to a high 

of 92.8 mu g m(-3) in Beijing. The results showed that the dwellings with tobacco smoke, incense 

burning or poor ventilation had significantly higher indoor concentrations of certain carbonyls. It 

was noticed that although one half of the dwellings in this study installed with low emission 

building materials or furniture, the carbonyls levels were still significantly high. It was also noted 

that in winter both the indoor and outdoor acetone concentrations in two dwellings in Guangzhou 

were significantly high, which were mainly caused by the usage of acetone as industrial solvent in 

many paint manufacturing and other industries located around Guangzhou and relatively longer 

lifetime of acetone for removal by photolysis and OH reaction than other carbonyls species. The 

indoor carbonyls levels in Chinese dwellings were higher than that in dwellings in the other 

countries. The levels of indoor and ambient carbonyls showed great seasonal differences. Six 

carbonyls species were carried out the estimation of indoor source strengths. Formaldehyde had 

the largest indoor source strength, with an average of 5.25 mg h(-1) in summer and 1.98 mg h(-1) 

in winter, respectively. However, propionaldehyde, crotonaldehyde and benzaldehyde had the 

weakest indoor sources. (C) 2006 Elsevier Ltd. All rights reserved. 

Wang, S. Y., T. H. Yang, et al. (2008). "Fire-retardant-treated low-formaldehyde-emission particleboard 

made from recycled wood-waste." Bioresource Technology 99(6): 2072-2077. 

 The objective of this study was to manufacture fire-retardant-treated low-formaldehyde-emission 

particleboard from recycled wood-waste particles using polymeric 4,4'-methylenediphenyl 

isocyanate (PMDI) and phenol-formaldehyde (PF) resins. The influence of the PMDI/PF ratio 

(ratio of particles sprayed with PMDI to particles sprayed with PF, w/w) after fire retardant 

treatment on formaldehyde emissions, mechanical properties, and surface fire resistant 

performance of the manufactured particleboard was investigated. The experimental results 

showed that the formaldehyde emissions linearly decreased with an increasing PMDI/PF ratio. 

Moreover, the bending strength, internal bond strength, and screw holding strength increased with 

an increasing PMDI/PF ratio. The thickness swelling of the particleboard was improved by using 

an increasing PMDI/PF ratio. Furthermore, the fire-retardant-treated low-formaldehyde-emission 

particleboards fabricated in our study could pass the third grade standard of surface fire resistant 

performance as specified by CNS 6532. (C) 2007 Elsevier Ltd. All rights reserved. 
3-82

Wang, X. K. and Y. P. Zhang (2009). "A New Method for Determining the Initial Mobile Formaldehyde 

Concentrations, Partition Coefficients, and Diffusion Coefficients of Dry Building Materials." Journal of 

the Air & Waste Management Association 59(7): 819-825. 

 The initial mobile formaldehyde concentration, C-m,C-0; the partition coefficient, K; and the 

diffusion coefficient, D, of a dry building material are key parameters to characterize 

formaldehyde emissions from the building material. The solvent extraction method and direct 

thermal desorption method can overestimate C-m,C-0 because of high temperature. A new 

method has been developed to determine C-m,C-0 under similar conditions to common indoor 

environment, together with K and D. In the proposed method, the tested materials are placed in an 

airtight environmental chamber for which the temperature can be controlled by a water bath, then 

the materials undergo a multisorption/emission process and the instantaneous formaldehyde 

concentration in the chamber is recorded. The K and C-m,C-0 are determined from the 

equilibrium concentrations after every sorption by means of the linear least-square regression, 

and D is obtained by fitting the concentration at the emission stage into a mass-transfer-based 

model in the literature. Four kinds of wooden medium-density boards are tested. The C-m,C-0 

measured using this method is the mobile formaldehyde concentration in the material, which 

differs significantly from the total formaldehyde concentration in the material measured by using 

the traditional method recommended by the Chinese standard (GB/T 176S7-1999) extraction 

method. This means that the mobile formaldehyde takes only a small portion of the total quantity 

in the tested material. The K, D, and C-m,C-0 values measured using this new method are used to 

predict formaldehyde concentrations for sorption processes. The results agree well with 

experimental data. In addition, some factors influencing the accuracy are analyzed. 

Wong, L. T., K. W. Mui, et al. (2006). "A statistical model for characterizing common air pollutants in 

air-conditioned offices." Atmospheric Environment 40(23): 4246-4257. 

 Maintaining acceptable indoor air quality (IAQ) for a healthy environment is of primary concern, 

policymakers have developed different strategies to address the performance of it based on proper 

assessment methodologies and monitoring plans. It could be cost prohibitive to sample all toxic 

pollutants in a building. In search of a more manageable number of parameters for cost-effective 

IAQ assessment, this study investigated the probable correlations among the 12 indoor 

environmental parameters listed in the IAQ certification scheme of the Hong Kong Environment 

Protection Department (HKEPD) in 422 Hong Kong offices. These 12 parameters consists of nine 

indoor air pollutants: carbon dioxide (CO2), carbon monoxide (CO), respirable suspended 

particulates (RSP), nitrogen dioxide (NO2), ozone (O-3), formaldehyde (HCHO), total volatile 
3-83

organic compounds (TVOC), radon (Rn), airborne bacteria count (ABC); and three thermal 

comfort parameters: temperature (T), relative humidity (RH) and air velocity (P). The relative 

importance of the correlations derived, from largest to smallest loadings, was ABC, Rn, CO, RH, 

RSP, CO2, TVOC, O-3, T, V, NO2 and HCHO. 

 Together with the mathematical expressions derived, an alternative sampling protocol for 

IAQ assessment with the three,most representative and independent' parameters namely RSP, 

CO2 and TVOC measured in an office environment was proposed. The model validity was 

verified with on site measurements from 43 other offices in Hong Kong. The measured CO2, RSP 

and TVOC concentrations were used to predict the probable levels of the other nine parameters 

and good agreement was found between the predictions and measurements. This simplified 

protocol provides an easy tool for performing IAQ monitoring in workplaces and will be useful 

for determining appropriate mitigation measures to finally honor the certification scheme in a 

cost-effective way. (c) 2006 Elsevier Ltd. All rights reserved. 

Wong, L. T., K. W. Mui, et al. (2007). "Screening for indoor air quality of air-conditioned offices." 

Indoor and Built Environment 16(5): 438-443. 

 It would be costly to sample all toxic air pollutants to which an entire community is exposed. In 

Hong Kong, a voluntary Indoor Air Quality (IAQ) certification scheme for IAQ assessment in 

workplaces proposes the measurement of the levels of 12 parameters: carbon dioxide, carbon 

monoxide, respirable suspended particulates, nitrogen dioxide, ozone, formaldehyde, total volatile 

organic compounds, radon, airborne bacteria count, temperature, relative humidity and air 

velocity. This study investigates the feasibility of a screening process for presumptive detection 

of unrecognised IAQ problems in an indoor environment. From the full IAQ assessment results of 

422 air-conditioned offices in Hong Kong, three of nine listed common air pollutants are selected 

as "representative" pollutants for an overall "satisfactory IAQ". In particular, an "IAQ index" 

using the average fractional dose corresponding to given exposure limits of the representative 

pollutants as a simple screening test for asymptomatic IAQ problems in air-conditioned offices is 

proposed. The index was evaluated in terms of test sensitivity, specificity and predictive value. 

Such a screening test would be a useful tool for policyrnakers, building owners and professionals 

to identify offices with probable IAQ problems. Making better decisions regarding resources for 

an IAQ surveillance programme could help to ensure a healthy and safe workplace. 

Wu, P. C., Y. Y. Li, et al. (2003). "Risk assessment of formaldehyde in typical office buildings in 

Taiwan." Indoor Air 13(4): 359-363. 

 Our study conducts a series of investigations in five office buildings chosen according to the 
3-84

types of construction, ventilation, and building age. Formaldehyde was measured by continuous 

photoacoustic Multi-Gas monitor Type 1302 (Bruel Kjaer). The 8-h average concentrations in 

working hours were used to estimate the lifetime cancer probability (LCP) and chronic noncarcinogenic hazard index (HI). The carcinogenic effect of formaldehyde estimate by LCP (70 

years old) is about 2.06 x 10(-4) to 1.75 x 10(-3) after adjusting their working time. The levels of 

risk are 100-1000 times of the acceptable carcinogenic risk. A similar trend is observed for the 

levels of HI calculated. Many studies have suggested that exposure to high levels of 

formaldehyde may cause nasal cancer and other health effects. Therefore, promoting the labeling 

system for low emission materials to protect consumers from exposure to excessive emissions 

and helping the industry to develop low emission materials is evidently urgent and deserves 

greater efforts. 

Xu, J., J. Grunewald, et al. (2007). MODELLING THE FORMALDEHYDE EMISSION FROM MULTILAYER WORK SURFACES USED IN OFFICE WORKSTATION SYSTEMS. Proc. of the 6th Int. 

Conf. on Indoor Air Quality. 

 Volatile organic compounds (VOCs) emitted from various sources may adversely affect human 

health, comfort and performance. In particular, formaldehyde has been identified as a major 

indoor pollutant whose emission is controlled by workstation systems. Engineered wood products 

such as particleboards have widely been used with wood veneer and laminate to form work 

surfaces of workstation systems, which is a major formaldehyde emission component. The 

emission rate of formaldehyde depends on the composition of each material layer, temperature 

and moisture content in the materials. The objective of this study is to determine the long-term 

formaldehyde emission characteristics of multi-layer work surfaces such as a wood veneer over a 

particleboard core. The work comprised experimental and numerical investigation of the emission 

characteristics. To reproduce the experimental results, a numerical simulation model for coupled 

heat, air, moisture and pollutant transport in porous materials and wall assemblies was used1. A 

parametric study for the model parameters under consideration, such as the partition coefficient, 

the diffusion coefficient and the initial formaldehyde content in each material layer showed that 

all parameters decide about the formaldehyde emissions. In particular, the initial conditions have 

a major influence on the evolution of the emission factor. It can be concluded that an 

unambiguous determination of all parameters is difficult since the problem has no unique solution 

yet. Further research needs can be identified. 

Yoshida, H., A. Kimura, et al. (2004). "Emission behavior of VOCs in a model room with sugi-wood 

interior paneling." Mokuzai Gakkaishi 50(3): 168-175. 
3-85

 A model test room was built with finish flooring of solid oak and wall paneling of sugi wood. 

Concentration of carbonyl compounds and volatile organic compounds (VOCs) in the indoor air 

of the test room were measured over one year. The following results were obtained: (1) The main 

compounds emitted were formaldehyde and acetaldehyde. The emission of formaldehyde was 

greatly dependent on room temperature and did not easily attenuated although the emission was 

low throughout the test period. On the other hand, the emission of acetaldehyde was high at the 

beginning, but decreased rapidly in the first two weeks and did not depend on temperature. (2) 

The main VOC constituents were terpenoids, especially a-pinene. The terpenoids were rapidly 

attenuated and diminished within three to four months. 

Zhang, J. F., Q. C. He, et al. (1994). "Characteristics of Aldehydes - Concentrations, Sources, and 

Exposures for Indoor and Outdoor Residential Microenvironments." Environmental Science & 

Technology 28(1): 146-152. 

 Simultaneous indoor and outdoor measurements of aldehydes were made at 6 residential houses 

located in a suburban New Jersey area during the summer of 1992. Each house was measured for 

six days and controlled for ventilation and gas combustion conditions during the study. 

Formaldehyde, acetaldehyde, and seven other aldehydes were identified in the residential air. The 

study presents the first measurements of nine aldehyde species in both indoor and outdoor air. 

The total concentrations of the nine aldehydes were 19.12 +/- 10.88 ppb outdoors and 62.57 +/- 

21.75 ppb indoors. Formaldehyde was the most abundant aldehyde. Except for propionaldehyde, 

the indoor concentrations were found higher than the outdoor concentrations for all the other 

compounds, indicating the presence of significant indoor sources such as direct emissions and 

indoor chemical formation. Ozone concentrations were measured simultaneously during the 

study, and it was observed that several aldehydes can be generated through indoor ozone 

chemistry. The study provided evidence to support laboratory results obtained by other 

investigators that predicted aldehyde generation through indoor ozone chemistry. The residential 

exposures to formaldehyde and total aldehydes were assessed based upon some assumptions, and 

the outdoor exposures were negligible compared to the indoor exposures. 

Zhang, J. F., W. E. Wilson, et al. (1994). "Indoor Air Chemistry - Formation of Organic-Acids and 

Aldehydes." Environmental Science & Technology 28(11): 1975-1982. 

 The formation of aldehydes and organic acids was examined for the gas-phase reactions of ozone 

with unsaturated VOCs. Formaldehyde and formic acid were produced via the reaction of ozone 

with each of the three selected unsaturated VOCs: styrene, limonene, and 4-vinylcyclohexene. In 

addition, benzaldehyde was detected in the styrene-ozone-air reaction system, and acetic acid was 
3-86

found in the limonene-ozone-air system. The study also examined the gas-phase reactions 

involving formaldehyde, ozone, and nitrogen dioxide and found the formation of formic acid, 

suggesting that the nitrate radical may play an important role in converting formaldehyde into 

formic acid. Experiments for all the reactions were conducted by using a 4.3-m(3) Teflon 

chamber. Since the conditions and chemicals employed in the reactions were similar to those for 

indoor environments, the results from this study may be extrapolated to typical indoor situations 

and support indications from previous studies that certain aldehydes and organic acids could be 

generated by indoor chemistry. 

Zhang, Y. P., X. X. Luo, et al. (2007). "Influence of temperature on formaldehyde emission parameters of 

dry building materials." Atmospheric Environment 41(15): 3203-3216. 

 The diffusion coefficient, D, partition coefficient, K, and the initial volatile organic compounds 

(VOCs) in dry building materials, are the three key parameters used to predict the VOC 

emissions. D and K may be strongly affected by temperature. We have developed a new and 

simple method, the C-history method, to measure the diffusion coefficient, D and the partition 

coefficient, K of formaldehyde in dry building materials at temperatures of 18, 30, 40 and 50 

degrees C. The measured variations of the diffusion coefficients and the partition coefficients 

with temperature for particle board, vinyl floor, medium- and high-density board are presented. A 

formula relating the partition coefficient and related factors is obtained through analysis. This 

formula can predict the partition coefficient in principle and provide an insight for fitting 

experimental data, and it agrees well with the experimental results. (C) 2006 Elsevier Ltd. All 

rights reserved. 
3-87

3.4 Kenneth Unice Review Comments

Peer Review 

Formaldehyde Indoor Air Exposure Model – Pressed Wood Products (FIAM-pwp) 

Prepared for: ERG 

Chantilly, VA 

Prepared by: Ken Unice, ChemRisk, Inc. 

Pittsburgh, PA 

October 12, 2009 

I. Overview and General Comments 

Formaldehyde is a challenging molecule for indoor air modelers evaluating pressed wood 

products as a result of a complex long term emission profile, a backpressure effect not often 

observed in consumer product modeling and potential indoor sources and sinks. The purpose of 

the Formaldehyde Indoor Air Model – Pressed Wood Products (FIAM-pwp) is to provide a tool 

to estimate indoor human inhalation exposure to airborne formaldehyde (HCHO) in residential, 

mobile home, or temporary structures such as classrooms. The model documentation is 

transparent and well written, however, several areas of potential technical improvement or 

correction are noted in this review. I found the model input and output screens to be clear and 

intuitive. 

The theoretical framework for modeling steady state levels of formaldehyde has been in place for 

approximately 30 years. One of the areas I reflected on as a reviewer is how the release of this 

model could help advance the science of evaluating pressed wood products, particularly with 

distinguishing data gaps from data needs. In this regard, I believe the incorporating a better 

defined conceptual model into the model documentation and guidance would encourage 

important basic research, particularly in regard to the long term decay characteristics of 

formaldehyde emissions. In addition, it would very useful to have in an ability to perform simple 

sensitivity analyses similar to the limited Monte Carlo options available in MCCEM. This could 

be as simple as allowing ‘batch inputs’ for certain parameters like mass transfer coefficient with 

a selection key outputs summarized when batch mode is used. 
3-88

One of the major themes of my comments is that I strongly believe that the model 

documentation should outline a conceptual framework (with case studies) for assessing the 

exposure attributable to a specific product while taking into account the unique backpressure and 

source decay effects observed for formaldehyde. This framework is important because federal 

future regulatory standards, if any, could vary as a function of the type of product (e.g. industrial 

panel versus MDF. This outcome is likely because the technologies, loadings or mass transfer 

coefficients are product specific and standards may be adopted in different phases. One of the 

confusing aspects of the model is that the purpose to assess exposure attributable to emissions 

from pressed wood products, but the model output of average daily concentration (ADC) and 

lifetime average daily concentration (LADC) appears to include the background concentration 

and the ability to include doses from non-pressed wood products. As currently framed, the model 

is useful for assessing total personal exposure to formaldehyde, but of equal interest to most 

stakeholders is the risk or hazard assignable to a specific class of products or 

collection of products. The modifications that can be made to the model are limited by the 

current state of the science, particularly for long term exposure. Therefore, my primary 

recommendation is to describe a conceptual model in the documentation that provides a 

framework for approaching questions about product specific hazard and risk. 

In the comments below, I sometimes refer to the equilibrium concentration which is related to 

the Matthews b and m by Ceq= b/-m. The equilibrium concentration is the theoretical 

concentration corresponding to a ventilation rate of zero.

II. Charge Questions 

Part 1. Algorithms and Exposure Assumptions 

Question 1.1) Are the mathematical equations adequately explained, are they appropriate and 

are they accurately executed? What is your level of confidence in the indoor air 

concentrations and exposure estimates provided by the model? Please provide 

your rationale for determining the level of confidence. If the level of confidence is 

low, please provide the details as to why. Specifically, note any areas where 

errors were found, areas for improvement, or alternate calculation 

methodologies. 

In summary, I concur with the calculation of initial concentration (high confidence in result with 

reliable chamber test data), however, the treatment of sinks and average daily concentration for 

chronic exposure appear to require some revisions to improve the quality of the result (low 
3-89

confidence in result). I believe the usefulness of the model could be strengthened discussing the 

incremental contribution of added products because regulations, if any, are likely to be 

developed on a product specific basis (e.g. MDF versus industrial panel). Currently, the model 

documentation and model results emphasize the aggregate contribution of all products (and 

background sources), and running the model with and without a product of interest can produce 

counterintuitive results as described below. Finally, the relationship between the HBF and 

Matthews model should be made clear in the model documentation. Please see my detailed 

comments below. 

General Comments – Acute Versus Chronic Exposure

One of the challenging aspects of reviewing this model and providing cohesive recommendations 

is that the current assessment of acute and chronic exposure is associated with different 

uncertainties and conceptual models. However, accurate assessment of exposure for each of 

these endpoints is important. For acute exposure, the interaction between products is important 

due to the back-pressure effect, whereas for chronic exposure, each product has a reservoir of 

formaldehyde and formaldehyde precursors that is finite and decays with time. The theory for 

acute exposure modeling for pressed wood products is well established and has been reasonably 

well validated (Myers and Nagaoka 1981; Salthammer et al. 1995; Groah 2006) and some 

literature exists for the effect of wallboard sinks (Matthews et al. (1987). The use of a pseudo 

steady-state approach with cross-sectional residential half-life for chronic exposure is empirical 

and pragmatic, but is inconsistent with the theoretical approach to acute modeling. Furthermore, 

the short term effects of reversible sinks are difficult to reliably model with a steady state 

approach. 

The model documentation should focus on both the determination of incremental exposure 

attributable to the introduction of a specific product and the total exposure for loaded home. 

Some users will be interested in understanding the total formaldehyde concentration, but other 

users, such as trade associations, importers and manufactures, will be most interested in 

understanding the potential risk associated with a specific product or collection of products. 

Furthermore, regulations are likely to differ based on the type of product, necessitating an ability 

to understand incremental or added contributions to exposure. For example, in addition to 
3-90

understanding total exposure, the manufacturer of a bookcase constructed of pressed-wood 

products should be able to intuitively use the model and model documentation to answer the 

questions: 

• what data do I need to collect to refine the default acute and chronic exposure 

predictions of the model? 

• what is the acute airborne concentration attributable to my product in the absence 

of other products? 

• what is the incremental increase in acute airborne concentration when my product 

is introduced into a new or existing home when a default baseline set of preexisting products (new construction, existing residence, or policy based target 

concentration) are present? 

• what is the long term average exposure attributable to my product? 

Currently, the model does not provide a framework for answering questions about the effect of 

the introduction of new product into a pre-existing home, particularly for chronic exposure. I am 

concerned that the model does not provide guidance on the specific testing (chamber or 

alternative testing) that a manufacturer or other interested parties should perform to refine the 

estimate of chronic exposure. It is unclear to me that even if a manufacturer performed a robust 

12-month study (or longer), that it would be intuitive how to modify an ‘overall residential’ 

halflife. I am less concerned about acute exposure, because the potential effect of a particular 

product is easily discernible by standard chamber testing and calculated equilibrium 

concentration on reasonable assumptions about mass transfer coefficients. My concern is that if a 

cancer risk in excess of the acceptable risk range is calculated with this model, there is not a 

clear recommendation for performing a laboratory study that could be used to assign a higher 

tier decay function. The half-life is assigned to the residence based on cross-sectional data. 

However, conceptually, the decay in concentration over time is due to source depletion from 

individual products. It may be prudent for EPA to consider a technical workshop prior to 

finalizing the model with the purpose of developing consensus recommendations for the model 

documentation regarding a specific set of tests that could be performed to determine product 

specific (e.g. MDF, wall-paneling, industrial panel, etc) ADC, LADC ADD, and LADD. In 

conjunction with this, a strategy could be developed for framing LADC and LADD in a manner 

that is consistent with product specific exposures rather than overall residential half-life. 
3-91

In the acute setting, the back-pressure effect may attenuate the contribution of a new product 

such that the total acute indoor exposure concentration is not affected by the added product. 

However, in a chronic, or long term, timeframe (e.g. 10 to 20 years), it is reasonable to expect 

that the majority of available formaldehyde and formaldehyde precursors will ultimately 

partition from the product into the indoor space. My recommendation is that conceptual 

framework be developed in the model documentation to ensure that users take these factors into 

consideration when investigating acute versus chronic timeframes. For the acute timeframe, it is 

important to consider the total collection of assembled indoor products, or alternatively, the 

background concentration attributable to the existing products. For chronic exposure, a more 

accurate characterization of dose attributable to a single product is likely obtained by 

considering the decay profile of that product that would be true in the absence of other products. 

The reason for this is that the attenuation that is observed due to the backpressure effect is 

temporary, and eventually, a source that is initially attenuated will begin to emit formaldehyde as 

the overall indoor air concentration level decreases. The model documentation should refer to the 

types of decay studies that could be done to understand the long term formaldehyde dose 

attributable to a single product or collection of related products. Examples of these studies 

include (Zinn et al. (1990), Mølhave et al. (1995), Myer and Hermanns 1985 and Brown 1999). 

Detailed comments for the acute and chronic timeframes are provided below. 

Acute Exposure

For acute exposure, the most straightforward approach is to determine a baseline background 

indoor air concentration and determine whether the introduction of a specific product (e.g. wall 

paneling at a specified loading rate) or collection of products (e.g. kitchen cabinets) will increase 

the indoor air concentration to a level exceeding a threshold of concern. The baseline 

concentration could be determined by: 

• A representative collection of products in compliance with voluntary or future emissions 

standards (or alternatively, current air chamber testing results); 

• Current actual background indoor air concentrations established by published data for 

new and existing homes; or 

• Future baseline background indoor air concentrations assigned based on policy and costbenefit analysis. The future target background concentration would be a fraction of the 
3-92

threshold of concern to allow for initial increase in concentration attributable to the 

introduction of a new product or collection of products of concern. 

Under this approach, an option would be provided to the user to identify the ‘baseline products’ 

(or ‘indoor background from existing products’) and ‘added products’. In the model, output 

exposure and product specific emission rates would be presented with and without the added 

products. I believe this would greatly assist users of the model in intuitively understanding the 

backpressure effect, as well as assist specific manufacturers, regulators and other interested 

parties in understanding the incremental effect of specific products on indoor air levels. For 

example, for a small trailer, one question might be: how is the indoor air concentration affected 

by the introduction of 10 m2 of a paneling product that was not compliant with voluntary 

industry standards in the presence of other products that were compliant? Is it plausible that the 

other wood products in the trailer might have adsorbed formaldehyde from the non-compliant 

product and thus confound the interpretation of retrospective chamber testing? 

In the absence of this modification, the user could simply run the model with and without the 

source in question and simply compare the result and this approach was used in the model 

documentation in the evaluation of the addition of sinks. However, I believe that inclusion of this 

feature explicitly would greatly assist users unfamiliar with mass transfer theory and the 

interaction between formaldehyde sources. This feature would be particularly useful if the model 

were configured to output the emission rate and percent contribution to total emissions of the 

‘baseline’ sources with and without the ‘added’ source. This feature would also provide a clear 

way to use and interpret the result of a product specific chamber test. A manufacturer could 

perform a chamber test, select a ‘baseline’ configuration, then determine the incremental effect 

of their specific product, such as collection of kitchen cabinets. 

One basis for this comment is that the recent publication of FEMA temporary housing unit data 

failed to consider the potential implications of the backpressure effect for pressed wood products 

(Maddalena et al. 2009). The emissions equation relied upon by the authors did not account for 

the backpressure effect, and not surprisingly, the authors found that “the sum of all measured 

chemical emissions from the materials are general greater than the whole trailer emissions 

derived from measured concentrations”. Additionally, because the chamber testing was done 
3-93

retrospectively, the authors could not differentiate between primary and secondary sources. 

Therefore, although the results and conclusion of this paper give the impression that the 

extensive use of composite wood products and low air exchange rates were the primary 

explanation for high formaldehyde levels (averaging 440 ppb), I am concerned that these 

excessive levels may have been partially caused by a product or products that did not meet 

modern production criteria or perhaps even the voluntary standards (in combination with the 

temperature, humidity and air change rate conditions that were true in this particular case). If this 

occurred, then some of the lower emitting products may have been contaminated by the noncompliant products. 

In my view, one of the urgent federal policy questions regarding pressed wood products is 

whether the absence of federal regulations with performance based standards (with the exception 

of manufactured homes) has resulted an increased prevalence of imported products failing to 

meet the established voluntary industry standards or with potential emission rates higher than 

domestic production. I believe the slight reconfiguration of the model I am recommending would 

be extremely useful for explicitly addressing questions of this nature. From a policy perspective, 

after acute and/or chronic health based standards for formaldehyde are established, a focus on 

incremental exposure would be helpful for establishing the framework for the regulatory 

compliance program (e.g. the frequency of testing, documentation required for importers, how 

important is a 25% deviation above the compliance criteria for a single MDF panel, etc?). 

Chronic Exposure and Half-life/Decay

For chronic exposure, the most precise way to model formaldehyde exposure would be to use a 

transient finite difference model where the decay in the product specific equilibrium 

concentration or Matthews intercept is calculated as a function of time and as a time varying 

function of mass remaining of formaldehyde and formaldehyde precursors. In this approach, 

mass would be preserved because the equilibrium concentration for attenuated products would 

only being to decrease after the indoor air concentration decreased due to depletion of the other 

higher emitting sources. However, this would greatly increase the level of complexity of the 

model and the basic research that would provide a protocol to precisely define the mass 

reservoirs of formaldehyde, and particularly formaldehyde precursors, is limited. With the 
3-94

framework of the current model, it is probably most appropriate to estimate the chronic dose 

attributable to a product or set of products in the absence of other higher emitting sources, as I 

describe below. 

In contrast to the current model guidance and my recommendation for acute exposure, I believe 

the incremental chronic exposure attributable to a specific product (e.g. MDF panels) or defined 

collection of similar products (e.g. kitchen cabinets) should be assessed, rather than the aggregate 

cumulative exposure for all indoor products (i.e. the cross-sectional approach). Because the 

typical situation will reflect products of various ages, the chronic dose attributable to a specific 

product seems to be a more relevant metric than the total indoor concentration over time 

assuming an initial loading. Evaluation of the decay curve for a single product or class of 

products in isolation is likely to be more useful for understanding chronic risk and informing 

policy decisions about managing chronic risk than the suggested cross-sectional decay half-life 

approach. In addition, new construction represents a minor fraction of total residences, so the 

case where a new home is loaded with new products is the exception rather than the typical case 

for most of the population. In short, the emissions half-life is currently considered a ‘house 

characteristic’, whereas I believe it would be more appropriate to frame this in terms of a 

‘product-specific’ characteristic. 

For a specific product, a finite reservoir of free formaldehyde and formaldehyde precursors 

exists. Over a sufficiently large period of time, factors such as temperature or humidity are likely 

to affect the transient time-concentration profile, but less likely to affect cumulative exposure, or 

area under the curve. Similarly, the back-pressure effect or reversible sinks will temporarily 

suppress emissions from a new product, but it is likely that over a 10 to 12 year period, the 

reservoir of free formaldehyde and formaldehyde precursors from that product will be depleted, 

or released to the indoor space (for constant ventilation rate). Because the majority of the 

available reservoir is likely to be depleted over the lifetime of the product, incremental risk from 

separate products or collection of products can be added to derive total risk or an acceptable risk 

range by type of product (e.g. MDF) could be established. This incremental approach may 

slightly over-estimate true risk depending on the assumed tenure of the occupants, but this can 

be somewhat accounted for by either assuming a finite emission lifetime of an individual product 

(e.g. 10 years) or by selecting a target background indoor concentration higher than outdoor 
3-95

ambient air levels corresponding to the decay concentration where emissions from the source 

under consideration would be considered de minimus. One problem with a ‘product specific’ 

approach is that while this approach allows for a more accurate estimate of area under the curve 

(i.e. cumulative dose) for a product present for a reasonably long time (e.g. 20 years), it does not 

provide a way to calculate accurate total concentrations at specific points in time (e.g. 3 months, 

6 months, etc.) This problem is caused by the difficulty in trying to reconcile a transient process 

with the limitations of a pseudo-steady state model. 

Under the current model guidance, the true increased cancer risk attributable to installation of a 

specific product such as wall-paneling in an existing home to repair damaged plaster or kitchen 

cabinets installed during remodeling would not be reliably determined. Initially, the backpressure 

effect will suppress a portion of the formaldehyde emissions, such that if the user were to 

compare cumulative dose with and without the product based on current model guidance, the 

lifetime dose for that product will be underestimated. If the equilibrium concentration (i.e. the 

theoretical concentration in the absence of ventilation) of a product such as kitchen cabinets is 

less than the pre-existing steady state concentration, running the model with and without kitchen 

cabinets would result in the physically impossible conclusion of negative incremental cancer risk 

because the cabinets would initially act as a net sink. To illustrate this point with an extreme 

example, consider a baseline mobile home with model defaults loaded with 90 m2 decking with 

maximum HUD rate. The initial concentration is 0.3557 mg/m3, LADC is 0.0132 mg/m3 and 

percent of time > 10 ppb is 46.9%. If 45 m2 of kitchen cabinets with the EPA cabinet rate are 

added to the existing decking, the initial concentration is 0.3389 mg/m3, LADC is 0.0125 mg/m3

and percent of time > than 0.01 ppm is 46.1%. Here the apparent LADC decreases after the 

kitchen cabinets are added to the assessment because the kitchen cabinets act as an implicit since. 

This can be observed from the kitchen cabinet equilibrium concentration equal to b/-m or 0.08 

(mg/m2-hr) / 0.49 (m/h) = 0.16 mg/m3. It seems likely that over the lifetime of the kitchen 

cabinets, there will a finite long term dose greater than zero that will occur once the original 

source attenuates. 

The assessment should be based on a conceptual model for decay in formaldehyde emissions 

over time and basic research on the decay profile of individual products should be encouraged in 

the model documentation (rather than exclusively relying on the historical data from the 1980’s). 
3-96

At a minimum the model should be revised to allow consideration of periods of rapid and slow 

decay in the emission rate as observed, for example, in Zinn et al. (1990), Mølhave et al. (1995), 

Myer and Hermanns 1985 and Brown 1999. Long term testing is not feasible on a routine basis, 

but I believe the model should have the framework in place for investigators, suppliers or 

manufacturers interested in more robustly characterizing chronic exposure than has been 

typically done to date. Particularly of concern is that the decay characteristics of modern and new 

to market resins are largely unknown. The current single compartment exponential model will 

provide a conservative estimate of chronic exposure, but does not necessarily provide a pathway 

forward or conceptual framework for refinement of the calculation of long term cumulative dose. 

One conceptual model for assessing chronic exposure for formaldehyde releasing products was 

published by Mølhave et al. (1995). In this study, a selection of furniture and fitments supplied 

by a retailer was placed into a large scale chamber and measurements were made over an 8-week 

period. Conceptually, three exponential decay compartments were attributed to three potential 

sources of formaldehyde emissions, including: 

• free formaldehyde (short-term compartment); 

• decay of paraformaldehyde and other complex structures (medium-term compartment); 

and 

• hydrolysis of the resin (long-term compartment). 

Using an exponential peeling procedure, the authors determined relative sources strengths and 

half-lives for each of these three compartments. A two-compartment (slow and fast decay) 

analysis using an EPA model also adequately represented the transient data. The 

corresponding accumulated dose was compared to the California Proposition 65 safe harbor level 

to determine the incremental contribution of a specific set of products (i.e. living room furnished 

with IKEA furniture). This product specific testing may be helpful in refining the estimate of 

LADD and LADC and the approach to understanding whether compliance with Proposition 65 

was achieved was reasonable. I strongly recommend that the model documentation be modified 

to make clear how this type of testing could be incorporated into the model. Currently, the halflife parameter pertains to a structure-based decay rate rather than a product-based decay rate. 
3-97

For the default case, the decay rate presented in Zinn et al. (1990) seems more appropriate than 

the 2.92 year half-life derived from cross-sectional sectional data in the original Versar model. 

Zinn et al. (1990) estimated an apparent half-life of 216 days using approximately one year of 

large chamber data for particle board and a natural logarithm linear regression statistical analysis. 

The half-life reported in Zinn et al. (1990) is not directly comparable to that adopted in the 

original and current Versar model because Zinn et al. used the relationship HCHO = F + G x 

ln(time) with regression constants F and G whereas the EPA half-life was based on a traditional 

exponential decay model. The Zinn et al. logarithmic equation was used by CARB (2007; see 

Appendix B) to calculate the emissions inventory presented in the technical basis for the 

formaldehyde airborne toxic control measure. In lieu of the original logarithmic equation, the 

more generic two-compartment (i.e. fast and slow decay) exponential decay model could be fit 

the Zinn et al. data. 

Finally, one concern is the interaction between ventilation rate and decay rate. Given long term 

testing data, the total reservoir of formaldehyde and formaldehyde precursors for a given 

ventilation condition could be calculated. Therefore, in the future when decay characteristics are 

better understood, it should be possible to adjust for ventilation rate and account for total mass of 

formaldehyde generated over the lifetime of the product. Although the data to accomplish this is 

currently not available, it would a benefit to the scientific community to frame decay of 

emissions over time in terms of an accurate conceptual model, rather than current fully empirical 

and cross-sectional approach. 

Matthews Regression Model versus HBF Regression Model

The original Versar model presented the linear regression parameters both the Matthew’ model 

and the Hoetjer model (identified as HBF model in 1986 Versar model), as well as the steady 

equations for both models. These two models are both mass transfer based approaches, however, 

the mass transfer coefficient obtained by linear regression is not identical. This can be seen in the 

documentation for the 1986 Versar model, where the correlation coefficient is typically higher 

for the Hoetjer than for the Matthews model. For example, for PCB#3, the mass transfer 

coefficient was 0.48 m/hr in the Matthews regression (r=-0.84) and 0.70 m/hr in the Hoetjer 

linear regression (r=0.96). Because slightly different results are obtained depending on the 
3-98

regression model used and the Hoetjer model is widely cited in the literature, it is recommended 

that the model documentation be revised to include discussion of both approaches. 

To illustrate this point, I performed a linear regression analysis for the first loading of kitchen 

cabinets presented in Koontz et al. (1996). The regression model for the HBF mass transfer 

relationship is given in Myers and Nagaoka (1981). The linear regression models are: 

where: 

K = -m = mass transfer coefficient (m/h) 

CS = steady state concentration (mg/m3) 

N = air change rate (1/hr) 

L = loading rate (m2/m3) 

Ceq = concentration at zero ventilation rate (N=0) 

b = emission rate at zero formaldehyde concentration 

The simplified steady state models are: 

It can be shown these are identical models and that Ceq= b/-m. Therefore, the difference in 

models is in the regression equation 1 and 2 used to derive the parameters, not the theoretical 

construct. The equilibrium concentration is the vapor phase concentration at the surface of the 

board and the bulk phase concentration that would be true in the absence of ventilation. The 

Matthews parameter b is a combination of the mass transfer coefficient K and equilibrium 

concentration Ceq. The mass transfer coefficient is determined by the properties of the board or 

object surface, whereas the equilibrium concentration is determined by the formaldehyde 

generating properties of the panel and varies with temperature, humidity and age (Berge et al. 

1980). These concepts are less transparently elucidated by the Matthews emissions equation. 
3-99

The easiest way to incorporate a discussion of the two approaches would be to show how m, b, 

Ceq and K are calculated for the kitchen cabinet data presented in Koontz et al. (1996) using both 

the HBF and Matthews regression equations (in an Appendix). The purpose of this appendix 

would be to provide clear guidance on the type of chamber tests (i.e. at least three N or L 

combinations for the linear regression) that would be needed to determine the parameters that are 

input into the model. 

The results show that the fit is slightly different depending on the method that is used (Figures 1a 

and 1b). In this example, the minor differences in regression parameters result in predicted 

steady state concentrations that are similar over a range of air exchange rates (Figure 2). This 

should be the case in most situations. 

Figure 1a: Matthews linear regression. m=-0.49 m/h, b=0.08 mg/m2/h, r=-0.973 
3-100

Figure 1b: HBF linear regression. Ceq = 0.19 mg/m3, K = 0.41 m/h, r=0.997 

Figure 2: Calculated steady state concentration for regression models in Figure 1 assuming 

loading (L) of 0.13 ft2/ft3

My preference would be to allow input the parameters from either approach as was the case in 

the original model. Although the mass transfer basis is identical for each model, the parameters 

of the Hoetjer model are more intuitive. For example, based on the equilibrium concentration, it 

is easy to see that the worst case concentration in the absence of ventilation (N=0) is 0.19 mg/m3. 

It is easy to conceptualize that this is approximately the level that would be expected in a 

confined space like the inside of a closed kitchen cabinet. The Matthews model parameters are 

less intuitive. The maximum emission rate which can be derived directly from b is only true in 

the absence of formaldehyde in the bulk air, or at the beginning of the exposure period. 

However, the Ceq of the HBF model can be easily calculated. The concentration in the absence 

of ventilation (and background sources) is b/-m or Ceq= b/-m. 
3-101

Having made the recommendation to allow for both approaches, I recognize that is likely not 

possible due to time and financial constraints – and given the essential identical model construct 

perhaps of minimal benefit. My recommendation if only the Matthews model is retained in the 

model is to provide an example calculation in the model documentation showing how the user 

can start with the HBF linear regression or the HBF model parameters and convert the 

parameters to the equivalent Matthews model, or 

The caveat should be included that this conversion does not account for the slightly different 

result that is obtained using the HBF versus the Matthews linear regression models. Another 

option would be to provide the HBF equilibrium concentration as supplemental output. 

Knowledge about the equilibrium concentration allows an intuitive determination about whether 

a particular product is likely to act as a sink or a source based on an estimate of the anticipated 

indoor air concentration. 

In conjunction with this conversion equation, a statement should be included indicating that for 

plausible ranges of the N/L ratio, the selection of a particular linear regression model is not 

expected to appreciably affect the results. This could be demonstrated by a Monte Carlo analysis 

or reanalysis of the data in Table 2-2. 

Indoor Sink – Explicit Indoor Sinks

The model used to represent sinks accounts for reversible sinks. Prior research using unpainted 

drywall showed that this sink caused only a minor permanent loss of formaldehyde and that the 

wallboard serves as a buffer to sudden changes in indoor air concentrations (Matthews et al, 

1987). However, the treatment of indoor sinks in the current EPA model is problematic because 

absorption and desorption of formaldehyde from indoor sinks is a transient process over 

relatively short time scales not well suited to a steady-state or pseudo steady state model 

construct. As shown in Figure 1 below reproduced from Tichenor et al. (1991), a reversible sink 

buffers changes in concentrations but does not necessarily affect cumulative exposure, or area 

under the curve. Therefore, for instances where the EPA model is used to calculate lifetime, or 

long term dose, accounting for reversible sinks could potentially underestimate true cumulative 

dose, depending on how the exponential decay over time is conceptualized. 
3-102

Figure 1: Chamber test results for a reversible sink reproduced from Fig. 2, p. 27 in Tichenor et 

al. (1991). 

When the Langmuir model is run to steady state, dM/dt = 0 and Cindoor = kd/ka*M. However, at 

steady state, there is no capacity for the sink to absorb more formaldehyde (at the given 

concentration), and the net absorption rate is zero. The Langmuir model does not consider 

irreversible sinks. Therefore, at steady state there is no net effect of the sink and if the EPA 

model guidance provided on page 3-7 is followed exactly (e.g. 0.0375 mg/m2-h per 10 ppb 

indoor air), there should be no net effect of the sink (Matthews et al. 1987). This is also easily 

seen by noting that Ceq=b/-m and using the standard mass transfer equation. For drywall, Ceq = 

0.0375 mg/m2-h / (-3 m/h) / (1.236 mg/m3 / ppm) x 1000 ppb/ppm = 10 ppb. Therefore, when 

CS=Ceq = 10 ppb, then ER = K(Ceq-Cs) = 0, where ER is the emission rate. Note that as a result of 

rounding or significant digits, there could be a small (arbitrary) net positive or negative flux from 

a sink defined in this way. 
3-103

It appears that the guidance for the sink intercept given on EPA model guidance page 3-7 was 

developed by setting intercept b = ka x Cindoor assuming dM/dt = 0. When there is a linear 

relationship between accumulated mass and indoor air concentration at equilibrium conditions, 

dM/dt must equal zero. Therefore, deviations of the intercept from the calculated value would 

imply a sustained loss of equilibrium, violating the assumption used in assigning the sink slope 

and intercept in the Mathew’s equation. Furthermore, the guidance provided for selection of the 

equilibrium intercept for indoor sinks appears to treat this parameter as calibration or adjustment 

factor rather than as a predictive input. 

For wallboard, the surface area is high in magnitude, therefore minor arbitrary decreases in the 

intercept from the values recommend in the model documentation will yield a noticeable 

apparent sink effect. However, there does not appear to be justification for assigning these 

deviations. For example, in Table 5-4, the Zone 1 concentration without the wallboard sink is 46 

ppb. Taking 46 ppb as the starting concentration, the first estimate for the slope of the wallboard 

sink would be (46 ppb / 10 ppb) x 0.0375 mg/m2-h = 0.1725 mg/m2-h. When this value is entered 

for the wallboard slope, as expected, the Zone 1 concentration remains at 46 ppb. Due to 

rounding or insufficient significant digits, the calculated flux for this intercept actually reflects 

net generation rate (G) where positive G corresponds to desorption: 

G = 420 m2 x (0.05721 mg/m3 x -3 m/h + 0.1725 mg/m2-h) = 0.36 mg/hour 

Holding concentration constant in the prior example, a negligible decrease in the intercept to 

0.1715 mg/m2-h would cause the wallboard to be considered a sink with net adsorption: 

G = 420 m2 x (0.05721 mg/m3 x -3 m/h + 0.1715 mg/m2-h) = - 0.05 mg/hour 

It is clear that minor decreases in the intercept from the recommended starting point will cause 

the model to reflect a net sink effect for wallboard. This is true because at the starting point (e.g. 

0.0375 mg/m2-h per 10 ppb indoor air), the net generation rate from the sink is approximately 

zero, or dM/dt = 0. However, there does not appear to be a reliable way to a priori assign the 

final value of the intercept other than trial and error to achieve a modest decrease in indoor air 

concentration. 
3-104

The short term data from Loading 1 at the test house clearly show that the initial sink effect from 

wallboard can be appreciable. To correctly account for net adsorption on these short time scales 

within the framework of a pseudo steady state model, a non-zero value of dM/dt must be 

calculated using Equation 3-13 and set equal to the Matthews emission rate equation to derive 

the intercept. This value of dM/dt will vary as a function of time. Such an approach would 

appreciably increase the level of complexity needed to assign the sink term because indoor 

concentration and mass storage vary as a function of time. However, prior EPA models such as 

MCCEM have included this functionality. If an estimate of the indoor concentration profile is 

available as a function of time (e.g. for the test home), it should be possible to determine M(t) 

and dM(t)/dt as a function of time by numerical integration or finite difference model. However, 

at 30 days, dM/dt may be sufficiently small that a reasonable default recommendation in the 

model would be to neglect the effect of sinks. 

The treatment of sinks in the EPA formaldehyde model reflects a reduction in sophistication 

from that which is available in the prior EPA/Versar MCCEM model. Using the MCCEM model, 

it is possible to track dM(t)/dt and M(t) for the sink and make a determination about whether the 

short term effects of a particular sink are substantial enough to include in the final model. Of 

course, the adaption of a MCCEM-type approach is not straightforward because the 

formaldehyde model addresses long-term decay using a pseudo steady-state approach. It may be 

appropriate to have two versions of the model: 

• Pseudo steady-state model for long term exposure neglecting reversible sinks; and 

• Short term MCCEM-style model to understand whether the presence of sinks would 

appreciable reduce initial peak exposure. 

As an example, MCCEM was used to implement the Langmuir model for a carpet and pad sink 

from Koontz et al. (1996) and applied to Conventional Home 1. This home is characterized by 

high air exchange between the first floor and basement and low air exchange between the 

basement and outside. Therefore, the generation rate needed to achieve a Zone 1 steady state 

concentration of about 10 ppb can be roughly estimated using a one zone approximation, of G 

(mg/hr) = C (mg/m3) * Q (m3/hour). The following parameters were input into MCCEM: 
3-105

Formaldehyde generation rate = 3.434 mg/hour (to approximate 10 ppb steady state) 

Reversible sink, carpet: 

ka = 1.304 m/hr (Koontz et al. 1996 p. 6-44) 

kd = 0.196 hr-1 (Koontz et al. 1996 p. 6-44) 

A = 94 m2 (EPA model documentation Table 5-3) 

Home: 

Zone 1 volume = 304 m3 (EPA Conventional Home 1) 

Zone 2 volume = 167 m3 (EPA Conventional Home 1) 

Interzonal airflow = 111.5 m3/hr (EPA Conventional Home 1) 

Zone 0-1 airflow = 259.5 m3 (EPA Conventional Home 1) 

Zone 0-2 airflow = 19.6 m3 (EPA Conventional Home 1) 

As shown in Table 2, the presence of the carpet sink has a de minimus effect on the net 

emission rate in Zone 1 given a source generating a steady state formaldehyde concentration of 

10 ppb. Approximately 7 or 8 hours after introduction of the source, the rate of increase in 

storage in the sink is negligible and therefore there is no net effect attributable to the presence of 

this sink. The results in Table 2 below can be confirmed by simple screening calculations for 

steady state: 

Csteady = 1000 ppb/ppm x 3.43 mg/hour / (471 m3 x 0.59 hr-1 x 1.236 mg/ m3 per ppm) = 10 ppb 

dM/dtsteady = 0 = 0.010 ppm x 1.236 mg/m3 per ppm x 1.304 m/h x 94 m2 – 0.196 hr-1 x M  

M = 0.082 mg/m2  M*A = 0.082 mg/m2 x 94 m2 = 7.7 mg 

Note that at steady state, kd x M = 0.196 hr-1 * 0.082 mg/m2 = 0.016 mg/m2-hour. This is also the 

value recommended as the intercept for carpet on page 3-7 of the formaldehyde model guidance 

when the concentration is 10 ppb. From this example, it should clear that when the Matthews 

slope and intercept are assigned in accordance with the proposed guidance, dM/dt is zero and 

there should be no net effect of the sink on the emission rate. Any apparent effect is caused by 

minor deviations in the intercept or rounding errors, which do not appear to have a theoretical 

basis. 
3-106

Table 2: MCCEM model results for constant source and carpet set in a hypothetical two-zone 

home (EPA Conventional Home 1) 

The Koontz et al. (1996) study concluded that the Langmuir model was not adequate to derive a 

reasonable fit to the data for wallboard (p. 6-48). The results of the study did confirm that the 

Langmuir model is appropriate for carpet and padding as expected from the literature (Tichenor 

et al. 1991). The documentation for the EPA formaldehyde model does not address the original 

findings by Koontz et al. (1996) with respect to wallboard or provide justification for application 

of the Langmuir model to wallboard given the prior findings. More discussion is warranted, and 

perhaps consideration of the unpainted wallboard studied in Matthews et al. (1987) would be 

helpful. 

The initial sink parameters specified in this model are less problematic theoretically because the 

rate of desorption (kd x M) is low initially. However, the inclusion of these parameters is 

questionable because the pseudo steady-state design of the model is not well equipped to handle 

transport processes that occur over relatively short time scales. As shown in Table 2, 

sinks can reach the maximum loading at a given concentration relatively rapidly. I recommend 

evaluating dM/dt as a function of time for the EPA test house and other data and making a 

determination about whether the current EPA formaldehyde model should be used to predict fate 

processes that change rapidly over hours to days. If sinks are to be included in the model, I 
3-107

recommend developing clear guidance for assignment of the Matthews parameters. One criteria 

should be that dM/dt does not change rapidly relative to the time scale being investigated (e.g. 

24-hour average, etc.). 

Indoor Sink – Implicit Indoor Sinks

Some pressed wood formaldehyde “emitters” could theoretically act as sinks under certain 

conditions based on the properties of wood and the Matthews model (e.g. products with very low 

equilibrium concentration or, equivalently, low Matthews model intercept). For example, low 

emitting products with unreacted urea can act as scavengers (Meyer and Hermanns 1985). This 

could potentially be an interesting question for situations like manufactured home where a 

product with excessive free formaldehyde levels could ‘contaminate’ otherwise low emitting 

products. Therefore, there may be some usefulness in presenting the emission rates by product in 

the results, with negative emission rate indicating a net sink effect. Because a steady state model 

is used, one concern about implicit sinks, especially as more low emitting products become 

available on the market, is that it is difficult to account for whether or not the storage capacity of 

the implicit sink has been exceeded over the time frame of interest. This could be a 

minor potential concern in some situations, such as when few high emitting products are paired 

with several very low emitting products. Presentation of the emission rate as output would 

provide a starting point for understanding whether implicit sinks are present. 

To provide an extreme example, the Mathew’s mass transfer parameters for kitchen cabinets 

were paired with a range of assumed background concentrations. Here for simplicity, the 

‘background concentration’ is used as a proxy to represent all other sources or a loaded room 

influencing an adjacent loaded road. The parameters used were m = -0.49 m/h, b=0.08 mg/m2/hr, 

ACH = 0.5 hr-1 and L = 0.13 ft2/ft3. The corresponding equilibrium concentration (Ceq) from the 

HBF model is approximately 0.163 mg/m3. As can be seen from the results in Table 3, when Cb

> Ceq, the kitchen cabinets would act as a sink, resulting in a lower steady state concentration 

than the influent background concentration (∆Csb < 0). This result is expected from the mass 

transfer equation where ER = K(Ceq-Css). When Css > Ceq, the direction of the flux is from the 

bulk air in the room to the pressed wood product. This example illustrates two key points. First, 

the use of the HBF model equilibrium concentration provides a more intuitive way to anticipate 

the results than the Matthews intercept b. Second, the output in the model of the emission rate 
3-108

attributed to each of the individual components models could potentially provide useful 

diagnostic information to the user or modeler. As wood panel resin technologies improve and 

more ‘green resins’ become available, the potential exists for low observed equilibrium 

concentrations. Depending on the properties of the panel, these products may or may not act as 

reversible and/or irreversible sinks. I believe the model should provide sufficient ancillary 

information to understand the sensitive parameters and identify other potential areas for testing. 

Table 3: Illustration of transition from source to sink at the equilibrium concentration based on 

variation in background concentration or other sources. 

Question 1.2) Comment on the default scenarios and default assumptions used by the model. Are the 

default assumptions reasonable and adequately supported by relevant scientific data? If 

not, specifically note any unreasonable assumptions. Provide suggestions and references 

for alternate default assumptions. 

The default approaches and parameters are likely to result in a conservative estimate of acute and 

chronic exposure. My concern is that in some instances, there is not necessarily a clear pathway 

forward for refining the default parameters. 

Data Collection to Revise Default Assumptions

It is not clear how the manufacturer of a specific product (e.g. MDF panel) could do a study with 

their specific product to refine the cross-sectional residential half-life. Therefore, there is not 

clear guidance regarding how to assess the degree to which some parameters are conservative. 

Answering these questions is likely to require new data, as the literature on some components of 

the model (e.g. emissions decay) is limited. 
3-109

I am concerned that too much emphasis is placed on the large database of historical emissions 

parameters provided in the model (Table 2-2) and historical decay rate evaluations (Section 3.6). 

I believe the model formulation and model documentation should be more forward looking in 

two respects. First, it should be made clear that many of the default emissions parameters in the 

model are based on historical testing and may or may not be representative of current products 

(See also Response 1.2). Typically these rates should be conservative (i.e. likely to overestimate 

emissions), but it is plausible that the default parameters may underestimate true emissions from 

products, particularly imported products, as a result of exceptional free formaldehyde levels 

exhibiting non-conformance with the voluntary industry standards. Second, clear guidance 

should be provided to end users (e.g. importers, manufacturers, non-profit organizations or 

regulators) about the data and steps required to assess the HCHO incremental exposure 

attributable to the introduction of a specific product into the home. For example, a case study 

could be provided for a hypothetical wood paneling manufacturer showing all of the steps from 

the acquisition of chamber test results, to calculation of incremental exposure attributable to the 

product and finally performance of a sensitivity analysis. Typically the mass transfer coefficient 

is not determined in routine chamber testing, and the sensitivity analysis would be helpful in 

determining whether this additional product specific data is a data need or a data gap. Other 

questions addressed by the sensitivity analysis could include the effect of inter-zonal air change 

rates, whole-house air change rates, temperature, humidity or loading. 

Question 1.3) Comment on the data sources. Are the data sources reasonable and accurate? If 

not, specifically note any unreasonable or inaccurate data source. Provide suggestions 

and references for alternate data sources. 

The sources of data in the model are reasonable and accurately represent the original studies, 

with the exception of the wallboard sink as noted below. 

Emissions parameters

It is unknown the degree to which the data in Table 2-2 reflect manufacturing practices in 2009, 

and the potential for low or high bias exists. Users of the model should be encouraged to collect 

and use data for products currently in the supply chain. This could be accomplished by 

deemphasizing the data in Table 2-2 (perhaps by moving to Appendix) or by requesting 

voluntary submission of chamber data from industry prior to release of the model. Alternatively, 
3-110

perhaps a mechanism could be put in place such that the database in Table 2-2 is routinely 

updated as new information becomes available. 

Conventional 1

Airflow between the basement and outside was low, which may or may not be representative for 

other structures. For example, if a lower efficiency furnace is located in the basement, make-up 

air for combustion could induce substantial airflow in the winter. To the casual user, it will not 

be immediately obvious that Conventional 1 represents the data for one test house under limited 

conditions. Therefore, I recommend that this home be explicitly labeled in the model as the pilot 

home to indicate that this data is for the home from the EPA pilot study. With regard to the 

underlayment in Conventional 1, were steps taken to prevent emissions to the basement from the 

underside of the floor panels? It is not clear whether the underlayment should be a source to 

Zone 1 or to both Zone 1 and Zone 2. 

Conventional 2

More details regarding the analysis of PFT data used to derive the airflow rates Conventional 2 

should be provided. 

Wallboard sink

The use of Langmuir isotherm for wallboard should be further explained, as this was found to 

not be valid in the original report for the pilot study (Koontz et al. 1996) 

Question 1.4) Do the data sources provide unused information that would assist in quantifying 

uncertainty or variability for subsequent model use? 

Wallboard sink

The approach to wallboard sinks used in the current EPA model should be consistent with the 

wallboard sink equations and data presented in Matthews et al. (1987). The wallboard in this 

study was unpainted, but latex paint was not expected to appreciably affect formaldehyde 

transport. The use of Langmuir isotherm should be further explained, as this was found to not be 

valid in the original report (Koontz et al. 1996). 

Uncertainty and sensitivity

The uncertainty and sensitivity analysis presented in Matthews et al. 1985 could be discussed. 
3-111

Question 1.5) Do the model input variables and the estimates assigned to them appropriately reflect 

variability? 

Sinks

The model documentation does not provide a credible method for selecting the indoor sink 

parameters. Guidance for calculation of dM/dt should be provided in line with my comments 

elsewhere in this review. 

Airflow

The model screen and documentation should make clear the Conventional 1 represents a single 

unoccupied test home. The analysis used to derive Conventional 2 should be described. If 

possible, airflow rates should be made available for key determinants as was done in MCCEM 

(e.g. season, area of the country). 

Mass transfer coefficient

The mass transfer coefficient is not routinely measured in most chamber testing. EPA should 

perform a sensitivity analysis to determine whether measurement of the mass transfer coefficient 

is a data need or data gap when newly acquired chamber test data is entered into the model. The 

equilibrium concentration is likely to be the key determinant of exposure with the mass transfer 

coefficient of less importance but this has not been established in the current documentation. 

Half-life

The single exponential equation for decay is consistent with the historical cross sectional 

residential data but inconsistent with studies that have investigated single products or collection 

of products over time (Zinn et al. 1990, Mølhave et al. 1995, Myer and Hermanns 1985 and 

Brown 1999). The true area under the curve for dose given a long enough exposure time is likely 

better represented by the two- or three- compartment exponential models than the single 

exponential model because these models better represent the decay in the reservoir of 

formaldehyde precursors in a specific product or collection of products. My largest concern is 

that when the half-life is defined in terms of the residence rather than in terms of the products, 

there is no good conceptual model by which to collect product specific data to refine this 

parameter. It may be possible to address some of these questions using a sensitivity analysis to 
3-112

determine whether conclusions about risk would change depending on how dose from the 

products is conceptualized. 

Equilibrium concentration

The degree to which the historical data in Table 2-2 reflects domestic and imported production is 

not known. The opportunity should be provided for the voluntary submission of data 

representative of the current supply chain.

Question 1.6) Has EPA provided adequate documentation of the overall plausibility of the exposure 

estimates generated by the exposure model? If not, provide suggestions for 

characterizing the exposure assessment estimates. 

Use of Pilot Study

The EPA pilot study, while very useful, is limited to one structure. I recommend pulling together 

a collection of representative baseline loadings and comparing the model results to published 

concentrations of formaldehyde in new and existing structures. Examples of papers presenting 

indoor formaldehyde levels for recent times include Hodgson and Levin 2003, Hodgson et al. 

2000 and Maddalena 2009. 

Average Daily Concentration/Dose

EPA has not shown how use of an overall residential half-life is to be used to derive product 

specific dose. Running the model with and without the product of interest will not result in 

meaningful conclusions as discussed previously. Accordingly, there is great uncertainty in 

product specific doses under the current model framework. EPA has not considered whether the 

historical 2.92 year cross-sectional half-life is representative of the decay profile of modern 

products or the potential variability in the formaldehyde reservoirs and decay between products. 

1.7) Are there any other types of data to assess the reliability of the overall exposure model or specific 

model elements? If so, provide suggestions and references for alternate data types. 

Average Daily Concentration

As mentioned previously, I strongly believe a consensus framework must be in place to assess 

product specific long term average exposure. I believe the current lumped, or whole-residence 

based, approach will create confusion and greatly complicate risk management decisions if the 

end point of concern is based on chronic exposure. The emphasis should be on developing a 
3-113

consensus approach to quantifying the reservoir of free-formaldehyde and formaldehyde 

precursors in a specific product. Currently the data available to do this is somewhat limited, but 

it would be useful to have a theoretical framework in place. 

Part 2. User Interface 

Question 2.1) Is the FIAM - PWP easy to use? Specifically note any data entry screens you found 

confusing or unclear. Provide suggestions to improve the user friendliness of the model. 

I was able to use the model successfully. I choose to use the local version of the software which 

performed reasonably. I found the interface to be more cumbersome than similar models like 

MCCEM, IAWX, EFAST or WPEM, but this is mostly attributable to the use of a web-based 

platform and not a fault of the developer. Specific comments are provided below: 

Air change rate

Although the help explained why this was grayed out, I initially tried to edit this field because it 

was a text box prior to reading the help function. Replacing this field with plain text would make 

clear that this value cannot be edited. 

Modifying sources

When a source is modified, the user should be required to rename the source and a separate 

library of user entered sources should be maintained. Currently, it is impossible to know whether 

someone overrode the default values or the values presented are the default values. I would 

prefer that the individual panel results not be a permanent part of the database, with several open 

slots for user defined emission rates. For example, for particleboard underlayment, I would 

recommend: AVG-PBU, MAX HUD, User Defined 1, User Defined 2....Etc. Here, the user 

would not be permitted to edit the AVG and HUD parameters. If desired, the AVG-PBU could 

be supplemented with an upper confidence limit intercept. Note also that the codes in the model 

do not match Table 2-2 in all instances. For example, Table 2-2 GP-6N is labeled HOW-6N(U) 

in the model. 

Printing
3-114

When a screen is printed in standard portrait view, the edge is cut off. It would extremely helpful 

to have a ‘Print All’ button that would generate a single page for printing with all the inputs and 

outputs suitable for printing in portrait view. 

MS EXCEL

I successfully generated output using this function. Please consider writing a routine to allow the 

same information to be printed directly from the web-browser as noted above. 

Tab Key

Each data entry box has a tab order. Generally when the tab key is pressed, the next text box with 

focus is logical, but in some instances the next box is out of order. For example: House type 

[Tab] Number of Zones [Tab] House Volume

Question 2.2) Are the model help screens adequate? Describe any additional help screens 

that you would find useful. 

The model help screens are intuitive and adequate. The audio prompts generally worked well, 

although some were missing failed to load (e.g. first prompt on house screen). 

Part 3. Documentation 

Question 3.1) Are the references accurately identified? Would any additional reference 

citations be helpful? Please note any additional references that should be 

cited. 

The references are accurately identified, however I recommend replacing the two Groah 

citations. Please see below for recommendations for additional citations 

Picture of kitchen cabinets

The credit for the picture of the kitchen cabinets should be provided. 

Theory

For more information regarding formaldehyde emissions from pressed wood products, model 

users could be referred to U.S EPA (1996) ORD report – Sources and Factors Affecting Indoor 

Emissions from Engineered Wood Products. 
3-115

Background concentrations and 0.01 ppm threshold

A basis should be provided for the recommend range of 1 to 10 ppb on page 2-4. Similarly, it 

should be explained why the concentration 10 ppb is ‘hard coded’ into the model in the percent 

of time > 0.01 ppm output. 

Representative measured indoor air concentrations

It may be helpful to provide citations to studies that have summarized recent measured 

formaldehyde indoor air concentrations in new and existing structures. Examples include 

Hodgson and Levin 2003 and Hodgson et al. 2000. One of the concerns that these publications 

raise is that the Matthews parameter database including in the model is primarily for historical 

products, however, more recent indoor air data shows that emissions have declined. It is unclear 

the degree to which the decrease is due to changes in the product mix versus reduced emission 

rates. Therefore, users of the model should be encouraged to obtain emissions data for modern 

products if the results are appreciably outside the bounds expected. Central tendency indoor air 

concentrations reported in a survey of literature by Hodgson and Levin 2003 were 17 and 32 ppb 

for existing and new structures respectively. 

Decay in emission rate (Groah 1998 and 2005)

Groah’s white papers and reports have been invaluable to me in my past consulting work on 

formaldehyde. However, I recommend that these references (essentially a white paper and report 

prepared on behalf of HPVA) be replaced with peer-reviewed publications, conference 

proceedings, or governmental citations. Examples of publications addressing the long term decay 

of formaldehyde emissions from consumer products include: 

• Mølhave et al. 1995 

• Brown 1999 

• Zinn et al. 1990 (note this study was relied upon by CARB) 

• Myer and Hermanns 1985 

• CARB 2007 – see Appendix B 

One key point to be derived from these studies is that a single exponential equation does not 

describe the decay in emissions adequately. In turn, a single exponential equation is not likely to 

accurately predict the LADD or LADC attributable to a specific product. 
3-116

Backpressure effect

I recommend citing Jayjock 1994 in reference to the backpressure effect first introduced on page 

2-16 of the documentation. This paper provides a good review of this concept for users not 

familiar with the concept. 

Question 3.2) Does the model documentation present the model construct, selected model inputs, model 

results in a clear, complete and useful manner? If not, specifically note areas that are 

unclear or needs improving. Provide suggestions for additionally information. 

Concentration as a function of time

Consider explaining in the model documentation why the concentration time points of 3, 6 and 

12 months were selected for output. 

Estimation of sinks

As described in more detail earlier, the treatment of sinks is not transparent and confusing 

because the rate of storage changes with time but the model used is a steady state model. Groah 

(2006) also tried to address the effect of wallboard sinks for the pilot study home. This 

manuscript noted that much of the small chamber data was erratic, but that some data was usable. 

However, both in the model documentation and in the Groah (2006) publication, the approach 

used appears to be more an attempt to modify the model results to reflect the measured 

concentration than a rigorous handling of sinks. The approach to wallboard sinks used in the 

current EPA model should be consistent with the wallboard sink equations and data presented in 

Matthews et al. (1987). The wallboard in this study was unpainted, but latex paint was not 

expected to appreciably affect formaldehyde transport. 

Linear Estimation of Matthews Model Parameters

Some stakeholders that may choose to use the new EPA formaldehyde model may not be 

familiar with the linear regression protocol required to estimate the parameters for either the 

Matthews and Hoetjer formaldehyde mass transfer models. It is recommended that 

documentation be revised to show an example linear regression for the recent data Koontz et al. 

(1996). 

Hoetjer-equation

As described previously, the documentation should explain the relationship between the 
3-117

Matthews and Hoetjer equation. The Hoetjer equation or equivalent mass transfer equation is 

frequently cited in the literature and some stakeholders may not be familiar with the Matthews 

equation. Examples of papers relying on the standard mass transfer relationship (i.e. Ceq and K) 

include: 

• Berge et al. 1980 

• Myers and Nagaoka 1981(presents the use of linear regression to determine Ceq and K) 

• Myers 1983 (presents the use of linear regression to determine Ceq and K) 

• Salthammer et al. 1995 

Langmuir Isotherm

The documentation should note that it is assumed that the number of occupied adsorption sites 

are much less than the available sites, reducing the isotherm equation to a simplified linear form 

(see for example, Tichenor et al. p. 24). At equilibrium, when dM/dt = 0, there is no net 

adsorption and Cindoor = kd/ka*M. 

Analysis of data

Consider presenting the analysis of PFT measurements and raw data in an appendix for 

Conventional 2 (p. 2-7). Is this data similar to data available in MCCEM? What is the basis of 

0.5 ACH for manufactured home? 

Consider including in an appendix the analysis of the EPA Pilot Study data used to determine the 

mass transfer coefficient and intercept (p. 5-3). For example, it is not clear which loading (i.e. 

1,2,3) is used to calculate the parameters without reproducing the calculation or whether the 

result is different based on HBF or Matthews regression equation. 

Question 3.3) Does the documentation for the FIAM - PWP make clear the sources and anticipated 

magnitudes of variability and uncertainty in model results? Describe any additional 

information that you would find useful. 

Mass transfer coefficient

Consider incorporating a mass transfer coefficient sensitivity analysis into the model or model 

documentation. The uncertainty and sensitivity analysis presented in Matthews et al. 1985 could 

be discussed. 
3-118

Airflow

Consider providing a database of homes similar to MCCEM database to provide a larger range 

for interzonal airflows. 

Sensitivity Analysis

Consider including a simple Monte Carlo analysis as an appendix to provide some guidance on 

whether refinement of a particular input parameter is likely to change the conclusion. This could 

be done using the spreadsheet model already prepared. The uncertainty and sensitivity analysis 

presented in Matthews et al. 1985 could be discussed. 

Question 3.4) Are the model algorithms consistent with the descriptions in the model documentation? If 

not, specifically note areas that are inconsistent between the model and documentation. 

Verification of Model Equations

The model equations provided in the documentation were reviewed. To further verify the model 

calculations were implemented as intended using an alternate approach, an example loading was 

run to steady state using IAQX Source Type 31. After the steady state concentration was 

determined, the other parameters were calculated by hand. The source used was the EPA kitchen 

cabinets, which corresponds to Cv of 0.1633 mg/m3 and Km of 0.49 m/hour in the mass transfer 

equation of IAQX. The results were evaluated with and without a background concentration of 

0.010 mg/m3. IAQX Model Source Type 14 was used to add the background concentration. The 

model results were successfully reproduced using this independent approach (Table 4). 

Table 4: Verification of model calculations for test case 
3-119

Matthews m

The slope in the Matthews equation is not consistently defined. For example on p 2-11, ER = 

mC+b, but on page 3-4, ER=-mC+b. 

ACD and LADC

One area that is particularly confusing is the model output of average daily concentration (ADC) 

and lifetime average daily concentration (LADC). From the model documentation it is not clear 

whether the background concentration is included in the ADC and LADC. For products with 

very low equilibrium concentrations in environments with above average background 

concentrations, the presence of the background sources could be important. Therefore, there 

could be cases where the user would like to include a background concentration in the model, but 

exclude the contribution of background from the dose. Consider providing a checkbox option to 

include or exclude the background concentration from ADC and LADC (and dose).

III. References 

Berge, A. Mellagaard, B. Hanetho, P., and Ormstad, E. 1980. Formaldehyde Release from 

Particleboard – Evaluation of a Mathematical Model. Holz Als Roh-und Werkstoff 38: 252-255. 
3-120

Brown, S.K. (1999) “Chamber assessment of formaldehyde and VOC emissions from 

woodbased panels” Indoor Air, 9: 209–215.Groah 2006 

CalEPA (2007) California Air Resources Board (CARB), Initial Statement of Reasons for 

Proposed Rulemaking, Proposed Airborne Toxic Control Measure to Reduce Formaldehyde 

Emissions from Composite Wood Products, Office of Environmental Health Hazard Assessment, 

California Environmental Protection Agency (CalEPA). 

Groah, W. J. (2006). Predicting indoor-air formaldehyde concentrations from emissions of ureaformaldehyde bonded wood products using the Versar model. Forest Products Journal, 

56(10):97-100. 

Hodgson A.T. and Levin, H. (2003). Volatile organic compounds in indoor Air: A review of 

concentrations measured in North America since 1990. Berkeley, CA, Lawrence Berkeley 

National Laboratory (LBNL-51715). http://eetd.lbl.gov/ie/pdf/LBNL-51715.pdf

Hodgson A.T, Rudd A.F, Beal D. and Sandra S. (2000) “Volatile organic compound 

concentrations and emission rates in new manufactured and site-built houses”, Indoor Air, 

10,178-193. 

Jayjock 1994. Back pressure modeling of indoor air concentrations from volatizing sources. 

American Industrial Hygiene Association Journal, 55: 230-235.

Koontz M.D., Rector H.E., Cade D.R., Wilkes C.R., and Niang L.L. (1996) Residential Indoor 

Air Formaldehyde Testing Program: Pilot Study, IE-2814. Washington, DC, U.S. Environmental 

Protection Agency (U.S. EPA). 

Maddalena R., Russell M., Sullivan D.P., Apte M.G. (2009). Formaldehyde and other volatile 

organic chemical emissions in four FEMA temporary housing units. Environ Sci Technol. Aug 

1;43(15):5626-32. 
3-121

Matthews, T. Reed, B. Tromberg., K. Fung, C. Thompson, J. Simpson, and A. Hawthorne. 

1985.Modeling and Testing of Formaldehyde Emission Characteristics of Pressed-Wood 

Products: Report XVIII to the U.S. Consumer Product Safety Commission. ORNL/TM-9867, 

Oak Ridge National Laboratory, Oak Ridge, TN. 

Matthews, T. Hawthorne, A. and Thompson, C. 1987. Formaldehyde Sorption and Desorption. 

Characteristics of Gypsum Wallboard. Environmental Science & Technology 21: 629-634. 

Mølhave L., Dueholm L., and Jenson L.K. (1995) “Assessment of exposures and health risks 

related to formaldehyde emissions from furniture: A case study”, Indoor Air, 5: 104-119. 

Meyer B., Hermanns K. (1985) “Reducing indoor air formaldehyde concentrations” Journal of 

the Air Pollution Control Association, 35, 816-821. 

Myers G. and Nagaoka M. (1981) “Emission of formaldehyde by particleboard: Effect of 

ventilation rate and loading on air-contamination levels” Forest Products Journal, 31(7), 39-44. 

Myers, G. E. (1983). Formaldehyde emission from particleboard and plywood paneling: 

measurement, mechanism, and product standards. Forest Products Journal, 33: 27-37. 

Salthammer T., Fuhrmann F., Kaufhold S. Meyer B. and Schwad A. (1995) Effects of climatic 

parameters on formaldehyde concentrations in indoor air” Indoor Air, 5, 120-128. 

Tichenor, B.A., Z. Guo, J.E. Dunn, L.E. Sparks, and M.A. Mason. The interaction of vapour 

phase organic compounds with indoor sinks. Indoor Air, 1, 23-35, 1991. 

U.S. EPA 1996. "Sources and Factors Affecting Indoor Emissions from Engineered Wood 

Products: Summary and Evaluation of Current Literature" (EPA-600/R-96-067, NTIS PB96-

183876, June 1996). 

Zinn, T.W., Cline, D. and Lehmann, W.F. (1990) “Long-term study of formaldehyde emission 

decay from particleboard” Forest Products Journal, 40(6), 15-18. 

3-123

3.5 W. Gene Tucker Review Comments

REVIEW COMMENTS ON THE 

FORMALDEHYDE INDOOR AIR MODEL-PRESSED WOOD PRODUCTS (FIAM-PWP) 

Algorithms and Exposure Assumptions

The general approach taken by this model, as I understand it, is to: 

1. Specify basic characteristics of a house such as volume, number of zones (1 or 2), and air 

exchange rates between indoors and outdoors and between zones. 

2. Put formaldehyde-containing sources into each zone, selecting types from a drop-down 

list or one’s own type, and then entering amounts (areas) of each type, and emission rate 

values based on a “slope and intercept” emission model. The slope value accounts for the 

influence of vapor-phase HCHO on the emission rate and the intercept value is the 

emission factor at zero HCHO in the vapor phase. A table of slope and intercept values 

derived from the literature is provided. Users can enter their own values if they choose. 

3. Calculate a “steady state” concentration of HCHO from these inputs by mass balance 

calculations, assuming complete mixing in each zone. This concentration is assumed to 

be the peak concentration in the house, after which the HCHO concentration decreases at 

a first-order exponential rate. 

4. The exponential rate of decay of the HCHO concentration is calculated by assuming a 

half life, or the time it is estimated it will take to decrease to half its concentration. A 

default value of 3 years is suggested, but other values can be used. 

5. Given the projected concentrations in the house, occupant exposures can be estimated 

based on their age, amount of time in the house, and number of years in the house. The 

results of exposure calculations include an estimate of the % of time occupants are 

exposed to concentrations above a user-specified concentration of concern. 

Step 2 seems like a convoluted way to model emissions: The dependent variable of primary 

interest—the HCHO concentration—is inherent in the in the prediction algorithm; i.e., it is also 

used as an independent variable. While the emission rate of HCHO is certainly a function of 

concentration in the air phase (as Fick’s law clearly implies), this is true for all out-gassing 

substances. High gas-phase concentrations can suppress emission rates. But if you look at the 
3-124

effect, say in Table 2-2 of the documentation, you can see that the suppression effect is small at 

low (and therefore presumably relevant) concentrations of formaldehyde. Nearly all the data 

appear to have been taken under conditions where the HCHO concentration was well above 0.01 

ppm, which value is suggested by the model as a concentration of concern. Most of it is even 

above 0.1 ppm, which is the maximum concentration of concern that anyone is likely to use. So 

the practical value of the slope in the emission rate equation is not evident unless one is going to 

model situations that are clearly unhealthy. Why not just use the intercept values and simplify the 

model? Better, in my opinion, to use a model that predicts indoor concentration from some 

quantified source emissions data (over time) based more simply on loadings, air exchange rates 

and—where relevant—other variables such as temperature, relative humidity, etc. 

That said, the analysis provided in section 5.3 of the documentation suggests that whatever the 

convolutions involved, the model gives respectable predictions. My reading of the tables in that 

section, which summarize modeling results compared to measured values in the EPA pilot study 

house, is that the model ranged from about 24% low to about 65% high. Predictions within that 

range are quite good, given the uncertainties in input data and unavoidable modeling 

assumptions. 

Regarding the selection of a decay constant (or half-time if you prefer) for predicting the rate at 

which the HCHO concentration will decrease, I suspect the default choice of k = 0.23 yr-1 (or t1/2

= 3 years) might be improved by having different values for different time periods. For example, 

the k value for the period 0-3 months may be higher than the one for 3-12 months, which may be 

higher than for 12-24 months, etc. I don’t have the Versar 1988 or Groah 2005 compilations at 

hand, so I didn’t check this but it would be simple to do once the data were compiled and 

segregated into appropriate time periods. First-order regressions could be determined for each 

time period; the k values would show whether the decay rates were changing significantly over 

time. This exercise might give you some insight into how conservative the 3-year (nee 2.92-year) 

half life is. 

One significant shortcoming of this model, and many indoor models that assume complete 

mixing within compartments, is that it doesn’t deal with what I refer to as “intimate” sources. 

These are sources that can lead to much higher exposures, especially for very young children or 
3-125

elderly people, than would be predicted by such models as FIAM. Examples are toys, cribs, 

bedding materials, clothing, and flooring materials for children and bedding and clothing for 

elderly people. To some extent as well, people working for long periods at workstations and 

around computers and peripherals can be more highly exposed than FIAM and most other 

models predict. 

I think the most straightforward approach to such sources is to assume a smaller compartment or 

zone around such sources for the purpose of predicting concentrations. Some years ago I made a 

stab at that in a paper for an indoor air conference3. In that paper I suggested a “volume of 

concern” of 10 m3 for dispersion of emissions from furniture and machines at workstations. The 

volume one might use for babies on bedding or flooring materials would presumably be much 

smaller; the resulting calculations would predict exposures that might be orders of magnitude 

higher than predicted by FIAM. 

User Interface

I had little trouble with the user interface. Minor comments follow. 

1. More careful attention to significant figures is needed. The suggestion that inputs should 

or can be specified with more than 3 significant figures (and results with more than 2 

SF’s) is outrageously silly. See House Screen for example. 

2. On the Sinks Screen, it seems counter-intuitive that the B value is positive rather than 

negative... 

Documentation

I found the documentation to be generally clear and quite useful. Users should have little trouble 

following it. Minor comments follow. 

1. Page 2-4, 4th paragraph: you should not describe the slope as “...in the form of a firstorder sink representation...”. The slope represents a linear function; first-order implies 

exponential growth or decay, neither of which would describe absorption characteristics 

of sinks. A logarithmic equation might make more physical sense, but that would 

introduce further calculational complications. 

 

3

 Tucker, W. G. 1990. Building with low-emitting materials and products: Where do we stand? In Proc. Indoor Air 

’90, Vol. 3, pp. 251-256. Ottawa: Indoor Air Technologies. 
3-126

2. Page 3-2, 2nd paragraph: the phrase “...flows of formaldehyde mass into and out of a fixed 

volume must be equal...” is not correct. In fact, equation 3.1 contradicts that. Thorough 

treatment of mass balances should consider generation, consumption, and accumulation 

inside the volume as well as flow into and out of the volume. 

3. Page 3-4, first line: shouldn’t “independent” be “dependent”? 

4. While the term “half-life” has a certain value because of its understandability, the normal 

way to determine it is from the decay constant, which these days is a simple matter with 

spreadsheets like Excel, where k can be determined easily from the “trendline” equation 

for a first-order exponential decay of the concentration versus time data. For some 

reason, the documentation of the model suggests that the decay equation is derived from 

the half-life. [By the way: Reporting the average half-time of HCHO decay in homes as 

2.92 years is a silly example of significant figures. It would actually be more accurate to 

report that value as about 3 years.] 

5. One area that I feel could be significantly improved is the mathematical introduction to 

the model. I have sketched out an alternative approach that I believe would be helpful to 

the general user, and have attached it. I don’t necessarily suggest this as a modification to 

FIAM, but as a general way to introduce mass balance concepts. Perhaps it is more 

relevant to other models if they should be developed for other indoor air quality situations 

and users who are less attuned to textbook-type math. 

General Comments

It seems to me the main potential users of a model of this type will be upscale home builders and 

home manufacturers. They might use it to predict whether certain types and amounts of 

formaldehyde-containing materials would lead to indoor HCHO concentrations that exceed some 

air quality standards or criteria. However, I doubt there will ever be many who use FIAM in this 

way. There are dozens (perhaps hundreds) of choices that need to be made in using this sort of 

model. Each choice has its uncertainty and the propagation of uncertainties can lead to very 

imprecise estimates. 

In the end, I have to wonder whether concentrations predicted by this model will lead to much 

more accurate or useful results than would be gotten from much simpler displays of emission 

factor data, loadings, and air exchange rates. Graphs relating these basic parameters to peak 
3-127

indoor concentrations could be created, similar to ones that I presented in the IAQ Handbook 

some years ago

4

 and that others have also suggested. Spreadsheets would probably be preferable. 

If exposure estimates are of interest the decay rate of formaldehyde concentration can be 

predicted based on selection of a decay constant (or a series of decay constants) that seems 

appropriate for the type of building being considered. While such an approach may arguably be 

simplistic, its assumptions are more transparent and its use by designers and builders is likely to 

be more widespread. If the ultimate concern is public health, these are important considerations. 

Attachment to review of FIAM 

Thoughts on a General Introduction to Mass Balances for Indoor Air Quality Models 

Most indoor air quality models (and most environmental models, for that matter) are multicompartment schemes where each compartment is assumed to be well mixed (i.e., has uniform 

concentrations of the substances of concern within the compartment, and has concentrations 

flowing out of the compartment that are the same as concentrations in the compartment). Mass 

flows of substances into and out of each compartment are simultaneously balanced with adjacent 

compartments. 

Textbook descriptions of such models, and documentation that accompanies their computer 

programs, often start out with mass balance equations that involve various forms of differential 

equations, summation expressions, etc. This tends to fog out most users of the software and they 

skim or skip this part. I believe that user understanding would often be improved if a more 

simplified introduction to mass balance concepts preceded any detailed mathematical discussion. 

The following rough notes sketch out my thoughts. With further development they might be 

helpful in some future indoor air modeling efforts. 

The mass balance around any compartment in a multi-compartment system will generally have 

five terms: what comes out of the compartment (OUT); what comes into it (IN); mass of 

substance generated in the compartment (GEN); mass of substance consumed (CONS); and mass 

of substance accumulated (ACCUM). The units of each term are usually mass per time (e.g., 

mg/h). 

[A simple box and arrow diagram could be inserted here. My abilities with graphics are 

limited....]

The arithmetic version of this balance can be written in any order, but since estimating the 

concentration coming out of the compartment is so often of most interest the balance can be 

written as: 

OUT = IN + GEN – CONS – ACCUM 

Where 

 

4 Spengler, Samet, McCarthy, eds., Indoor Quality Handbook, Chapter 31, McGraw-Hill, 2000. 
3-128

• OUT = mass flow of the substance of interest from the compartment to its surroundings 

(to other compartments, outdoors) 

• IN = mass flow of the substance into the compartment (from outdoors, other 

compartments) 

• GEN = mass rate at which the substance is created or released into the air inside the 

compartment. This is often referred to as the “source term”. This can occur as a result of 

gas-phase chemical reaction, or physical release such as evaporation from solid or liquid 

materials in the compartment 

• CONS = mass rate at which the substance is removed from the air in the compartment by 

chemical reaction or irreversible sorption to a surface (including an air cleaner in the 

compartment). This term is often referred to as an “irreversible sink” effect. 

• ACCUM = mass rate at which the substance stays inside the compartment. Materials with 

accumulated substances may at times become sources (in which case the accumulation 

rate is negative). This term is often referred to as a “reversible sink” effect. 

An introduction of this type can then be followed by mathematical representations of each of the 

five terms. In most applications one or more of the terms are assumed to be zero and can be left 

out of the mathematical discussion. 
Appendix A 

TECHNICAL CHARGE TO PEER REVIEWERS 

A-1 

Technical Charge to Peer Reviewers of the Formaldehyde Indoor Air 

Exposure Model – Pressed Wood Products (FIAM-PWP) 

Work Assignment No. 5-10 

Contract No. EP-W-05-014 

BACKGROUND 

The United States Environmental Protection Agency (EPA) estimates inhalation exposure to 

airborne chemicals emitted from products or materials used indoors. This exposure estimation 

involves the integration of information on location/activity patterns (i.e., how and where people 

spend their time) and concentrations encountered by individuals at indoor locations. The 

exposure is used by EPA along with hazard and dose-response information to estimate risks of 

chemicals in products. If insufficient information exists on measured concentrations or personal 

exposures for the situation(s) of interest, then some means of estimating or predicting 

concentrations is needed. The EPA has developed a computerized Formaldehyde Indoor Air 

Exposure Model – Pressed Wood Products (FIAM - PWP) to assist in estimating human 

inhalation exposure to airborne formaldehyde (HCHO) emissions from pressed-wood products in 

new or existing residences, small buildings and trailers. 

The FIAM - PWP model is an adaptation of a model developed during the 1980s by Dr. Thomas 

Matthews and colleagues at the Oak Ridge National Laboratory (Matthews et al. 1983a). The 

“Matthews model” was designed to estimate the steady-state formaldehyde concentration 

resulting from emission sources such as pressed-wood products in a single indoor compartment 

or zone. Product emission rates in the model are dependent on the HCHO concentration in the 

vapor phase, in accordance with Fick’s Law describing the bulk-vapor inter-phase at the surface 

of a pressed-wood emission source. The initial (steady-state) indoor concentration calculated by 

the model is assumed to decrease over time as the reservoir of formaldehyde in various sources 

(or sinks) is gradually depleted. The gradual decrease over time is assumed to follow a first-order 

exponential process, at a decay rate that depends on the chosen emissions half life for HCHO. 

 

In the mid-1990s an EPA-sponsored pilot study was undertaken by Versar/GEOMET (Koontz et 

al. 1996) to assess the contribution of UF-bonded wood products to formaldehyde levels in 

homes and to evaluate current EPA exposure models. Shortly after this study was completed, 

EPA tasked Versar to develop a modified version of the Matthews model. The primary 

modifications were (1) estimation of steady-state formaldehyde concentrations for the case of a 

two-zone indoor environment, and (2) incorporation of reversible (re-emitting) indoor sinks. The 

modified model also included the option to be run in a single-zone mode. The model was not 

finalized due to shifting priorities at the time of its development. 

In April 2008, the California Air Resources Board adopted an Airborne Toxics Control Measure 

to reduce formaldehyde emissions from composite wood products sold in that state. This new 

regulation governs the formaldehyde emissions from both raw composite wood products and 

finished products sold or used in California. In 2008, EPA was petitioned to adopt the California 

regulation as a national standard. EPA denied the petition, but in so doing, stated its intention to 

initiate a proceeding to investigate whether and what type of regulatory or other action might be 
A-2 

appropriate to protect against potential risks posed by formaldehyde emitted from pressed wood 

products. 

Receipt of the recent petition has prompted EPA to renew its interest in viability of the model as 

a tool to estimate the exposure to individual in indoors environments such as residences, travel 

trailers, temporary classrooms, etc. Therefore, the model was updated with new features, and a 

literature search was conducted to find new data sources or models that would be of importance 

to the updating and revision of FIAM - PWP. For example, some of the model changes include 

the following: 

• Correction of an error in code for temperature and humidity adjustments; 

• Correction of an error in unit conversion; 

• Revisions to exposure calculations 

• Improved user interface; and 

• Improved documentation. 

FIAM - PWP will be used by EPA to estimate indoor air concentrations and inhalation exposures 

to support a risk assessment of formaldehyde from pressed wood products. It is anticipated that 

many model runs will be generated to model a variety of settings and that the model output data 

will be used in the decision-making process of evaluating the potential health risks of 

formaldehyde’s use in pressed-wood products. 

 

TECHNICAL CHARGE 

The peer review is being conducted to evaluate the adequacy of the model for predicting indoor 

air concentrations of and inhalation exposures to formaldehyde from pressed wood products. 

Below you will find the technical charge questions in three parts: 1) Algorithms and Exposure 

Assumptions; 2) User Interface; and 3) Documentation. You are requested to provide comments 

for each charge below, and when doing so to make clear the rationale for your conclusions. In 

addition, please assess the level of confidence (or, conversely, the degree of uncertainty) 

associated with each response (e.g., low. medium, high) and provide an appropriate explanation. 

You are also requested, when discussing or presenting specific data, to justify your response, and 

to qualify this data to indicate acceptability and quality (e.g., whether these data have been peer 

reviewed, the extent of QA/QC, etc.). You may also provide any other comments that you feel 

will improve the model. 
A-3 

Part 1. Algorithms and Exposure Assumptions 

1.1) Are the mathematical equations adequately explained, are they appropriate and are 

they accurately executed? What is your level of confidence in the indoor air 

concentrations and exposure estimates provided by the model? Please provide your 

rationale for determining the level of confidence. If the level of confidence is low, 

please provide the details as to why. Specifically, note any areas where errors were 

found, areas for improvement, or alternate calculation methodologies. 

1.2) Comment on the default scenarios and default assumptions used by the model. Are 

the default assumptions reasonable and adequately supported by relevant scientific 

data? If not, specifically note any unreasonable assumptions. Provide suggestions and 

references for alternate default assumptions. 

1.3) Comment on the data sources. Are the data sources reasonable and accurate? If not, 

specifically note any unreasonable or inaccurate data source. Provide suggestions and 

references for alternate data sources. 

1.4) Do the data sources provide unused information that would assist in quantifying 

uncertainty or variability for subsequent model use? 

1.5) Do the model input variables and the estimates assigned to them appropriately reflect 

variability? 

1.6) Has EPA provided adequate documentation of the overall plausibility of the exposure 

estimates generated by the exposure model? If not, provide suggestions for 

characterizing the exposure assessment estimates. 

1.7) Are there any other types of data to assess the reliability of the overall exposure 

model or specific model elements? If so, provide suggestions and references for 

alternate data types. 

Part 2. User Interface 

2.1) Is the FIAM - PWP easy to use? Specifically note any data entry screens you found 

confusing or unclear. Provide suggestions to improve the user-friendliness of the 

model. 

2.2) Are the model help screens adequate? Describe any additional help screens that you 

would find useful. 
A-4 

Part 3. Documentation

3.1) Are the references accurately identified? Would any additional reference citations be 

helpful? Please note any additional references that should be cited. 

3.2) Does the model documentation present the model construct, selected model inputs, 

model results in a clear, complete and useful manner? If not, specifically note areas 

that are unclear or needs improving. Provide suggestions for additionally 

information. 

3.3) Does the documentation for the FIAM - PWP make clear the sources and anticipated 

magnitudes of variability and uncertainty in model results? Describe any additional 

information that you would find useful. 

3.4) Are the model algorithms consistent with the descriptions in the model 

documentation? If not, specifically note areas that are inconsistent between the 

model and documentation. 
Appendix B 

FIAM-PWP MODEL

B-1 

Appendix B - FIAM-PWP Source Code (PDF) (70 pp, 553K) 

During review, the FIAM PWP Model was located at http://63.139.120.41/

Appendix C 

SUPPORTING MATERIALS 

C-1

Appendix 1. Formaldehyde Indoor Air Model – Pressed Wood Products (FIAM-pwp) 

Model Documentation 

Model Documentation and User Guide (August 21, 2009) (PDF) (77 pp, 4.1 MB) 

Appendix 2. ASTM International Test Method E1333-96 

Standard Test Method for Determining Formaldehyde Concentrations in Air and Emission Rates 

from Wood Products Using a Large Chamber (PDF) (12 pp, 93K) 

Appendix 3. ASTM International Test Method D6007-02 

Standard Test Method for Determining Formaldehyde Concentrations in Air from Wood 

Products Using a Small-Scale Chamber (PDF) (8 pp, 113K)

Appendix 4. Berge et al., 1980. Formaldehyde Release from Particleboard - Evaluation of a 

Mathematical Model (PDF) (5 pp, 551K) 

Appendix 5. CARB, 2008. Final Regulation Order – Airborne Toxic Control Measure to Reduce 

Formaldehyde Emissions from Composite Wood Products (PDF) (59 pp, 239K) 

Appendix 6. GEOMET, 1994. Residential Indoor Air Formaldehyde Testing Program: Pilot Study. 

IE-2695 Quality Assurance Project Plan (PDF) (188 pp, 15.9 MB) 

Appendix 7. Groah, 2005. Decay or the Decrease in Formaldehyde Concentrations or 

Emissions over Time and UF-bonded Wood Panel Products (PDF) (14 pp, 109K) 

Appendix 8. Groah and Gramp, 1988. An Estimate of Home Occupant Exposures to 

Formaldehyde Gas From Plywood and Reconstituted Wood Products Bonded With 

Formaldehyde Based Adhesives (PDF) (60 pp, 1,007K) 

Appendix 9. Hare et al., 1996. Evaluating the Contribution of UF-Bonded Building Materials to 

Indoor Formaldehyde Levels in a Newly Constructed House (PDF) (34 pp, 263K) 

Appendix 10. Koontz et al., 1996. Residential Indoor Air Formaldehyde Testing Program: Pilot 

Study. IE-2814 Final Report (PDF) (183 pp, 36.1 MB) 

Appendix 11. Matthews et al., 1983a. Formaldehyde Emissions from Combustion Sources and 

Solid Formaldehyde Resin Containing Products: Potential Impact on Indoor Formaldehyde 

Concentrations and Possible Corrective Measures (PDF) (22 pp, 1.89 MB) 

Appendix 12. Matthews et al., 1983b. Formaldehyde Release from Pressed-Wood Products 

(PDF) (49 pp, 3.64 MB) 

Appendix 13. Matthews, 1985. Modeling and Testing of Formaldehyde Emission 

Characteristics of Pressed-Wood Products: Report XVII to the U.S. Consumer Product Safety 

Commision.(PDF) (83 pp, 5.52 MB) 

Appendix 14. Matthews, 1987. Formaldehyde Sorption and Desorption Characteristics of 

Gypsum Wallboard (PDF) (6 pp, 781K) 
C-2

Appendix 15. Myers, 1985. The Effects of Temperature and Humidity on Formaldehyde 

Emission from UF-Bonded Boards: A Literature Critique (PDF) (12 pp, 321K) 

Appendix 16. Silberstein, 1988. Validation of Models for Predicting Formaldehyde 

Concentrations In Residences due to Pressed-Wood Products (PDF) (9 pp, 1.72 MB) 

Appendix 17. USEPA, 1990. Compendium of Methods for the Determination of Air Pollutants 

in Indoor Air – Part 1 of 2 (PDF) (446 pp, 14.5 MB) 

Appendix 18. USEPA, 1990. Compendium of Methods for the Determination of Air Pollutants 

in Indoor Air – Part 2 of 2 (PDF) (402 pp, 12.1 MB) 

Appendix 19. Versar, 1988. Formaldehyde Exposure in Residential Settings: Sources, Levels, 

and Effectiveness of Control Options (PDF) (327 pp, 10.6 MB) 

Appendix 20. Versar, 1989. Indoor Formaldehyde Concentration from Pressed-Wood Products

Model Documentation (PDF) (84 pp, 3.65 MB)