# 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 5-10i

TABLE OF CONTENTS Page

1.0 I NTRODUCTION

................................................... .............................................. 1-1

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

2.0 P EER R EVIEW C OMMENTS O RGANIZED BY C HARGE Q UESTION .......................... 2-1

2.1 Part 1 - Algorithms and Exposure Assumptions ........... ......................... 2-1 2.1.1 Comment on the Adequacy of the Mathematical Equation s and the Level of Confidence in Indoor Air Concentrations and Expo sure Estimates Provided by the Model. ........................ ..................... 2-1 2.1.2 Comment on the Default Scenarios and Assumptions U sed 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 Generat ed by the Exposure Model........................................ .............................. 2-38 2.1.7 Provide Any Other Types of Data to Assess the Reli ability of the Overall Exposure Model or Specific Model Elements ....... ...... 2-40 2.1.8 General Comments on Algorithms and Exposure Assumptio ns2-41 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 Accur ately Identified .......................................... ...................................... 2-48 2.3.2 Provide Comments on the Model Documentation (Does It Present the Model Construct, Selected Model Inputs, and Model Resul ts 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 Consist ent 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 P EER R EVIEW C OMMENTS O RGANIZED BY R EVIEWER ........................................ 3-1

3.1 Jensen Zhang Review Comments ....................... .................................. 3-3 3.2 Michael Jayjock Review Comments .................... ................................. 3-9TABLE 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-11-1

1.0 I NTRODUCTION

On March 24, 2008, EPA was petitioned by the Sierra Club and ot hers under TSCA Section 21 to adopt the California Air Resources B oard’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 r ulemaking (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 deve loping a formaldehyde exposure

assessment.

Estimating inhalation exposure to airborne chemicals em itted from products or materials used indoors involves the integration of informat ion 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 nee ded.

OPPT evaluated a previous draft formaldehyde exposure model devel oped 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 des igned to estimate human inhalation exposure to airborne formaldehyde (HCHO) emissi ons 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 Laborat ory 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-st ate formaldehyde concentration in an enclosed environment. The initial steady state indoor con centration calculated by the model is

assumed to decrease over time as the reservoir of form aldehyde in the source (or sink) is gradually depleted. This decrease is assumed to follow a fir st-order exponential decay rate, which depends on the chosen emissions half-life of forma ldehyde.1-2 In the mid-1990s, EPA conducted an assessment of the contr ibution of UFbonded wood products to formaldehyde levels in homes. Evaluatio ns of then-current EPA exposure models were conducted and shortly thereafter, a mo dified version of the Matthews model was developed. The primary modifications were (1) e stimation of steady-state formaldehyde concentrations for the case of a two-zone indoor environment, and (2) incorporation of reversible (re-emitting) indoor sinks. Th e modified model also included the option to be run in a single-zone mode. However, the m odel was not finalized.

Early in 2009, FIAM was revised to include more features and a dditional scrutiny with regards to the estimating technologies. The purpose o f 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 documentatio n. 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 algo rithms and exposure assumptions; the ease of use of the graphical interface; and the comp leteness and clarity of the model

documentation.

The remainder of this report is comprised of the unedited wr itten comments submitted to ERG by the peer reviewers in response to the pee r 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 exper t. 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 wil l 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 EP A work product.1-3

1.1 Peer Review Logistics

ERG initiated the peer review for the FIAM-PWP on Sept ember 14, 2009. ERG held a pre-review conference call on September 21, 2009 to pro vide 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 we re 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 file s for related peer reviews or other tasks to identify potential candidates. ERG also conside red several experts suggested by EPA. ERG contacted candidates to ascertain their qualificatio ns, 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 revi ewers to EPA to either (1) confirm

that the candidates identified met the selection crit eria (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 lat ter, 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 simul ation models. He has authored/co-authored over 100 research papers and three s tandard methods for testing organic emissions from building materials, including “Mode ling the formaldehyde emission from multi-layer work surfaces used in office workstation systems” (2007) and1-4

an ASTM document, ASTM Standard Practice for Determinati on of Volatile Organic Compounds (excluding formaldehyde) Emissions from Wood-Based P anels 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 i n 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 C hemical Evaluation Program (VCCEP).

• Panos Georgopoulos, Ph.D., is the Director of the Computational Chemodynamics Laboratory (CCL) and Co-Director of the Center for E xposure and Risk Modeling (CERM) at the Rutgers University Environmental & Occupation al 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 - Ro bert Wood Johnson Medical School (UMDNJ-RWJMS), Princeton University, Rutgers Univ ersity and US FDA's

Center for Toxicoinformatics.

• Kenneth Unice, M.S., is an environmental engineer with over nine years of quanti tative 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 assessm ent of formaldehyde emission rate from pressed wood products, which predicts i ndoor air concentrations and accounts for the back-pressure effect that causes emissi on rates to decrease with increasing ambient formaldehyde levels. He has experience using the EPA/Versar Multichambers Concentration and Exposure Model (MCCEM) to mode l emission rates and indoor air concentration for mercury and naphthalene mot hballs, as well as experience1-5

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 Scien ces (elected in 1991) and has held various positions in the U.S. EPA Office of Resear ch and Development (ORD).2-1

2.0 P EER R EVIEW C OMMENTS O RGANIZED BY C HARGE Q UESTION

Peer review comments received for the FIAM-PWP model a re 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 recei ved from each reviewer.

2.1 Part 1 - Algorithms and Exposure Assumptions

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

Confidence in Indoor Air Concentrations and Exposure Estimat es 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 tra nsfer. The model is based on convective mass transfer over the surface, which i s 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 emis sion rates if the emission is indeed controlled by the convective mass transfer process. 2) However, it is more likely that except for the initia l 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 resist ances, resulting reasonable predictions. At the “steady state” (about 30 days from initial chamber test), the

internal diffusion resistance should be the dominant re sistance for formaldehyde emissions even for particleboard. To understand and proof this point, a more detailed numerical simulation can be made for homogeneous source s as assumed in the study (i.e., there were free formaldehyde uniformly distribute d in the material).2-2

3) After establishing the steady state initial concentrati on based on Mathew’s model, the concentration in a zone that has a higher concentrat ion is assumed to decay exponentially over time, given a half life time as t he input parameter. This approach is unconventional, but practical considering the many uncer tainties involved in real situation. The challenge would be to choose the right th e half-life time. An alternative is to actually model the emission rates of various sourc es, 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 pa rticles/chips. In addition, hydrolysis is possible for additional formaldehyde generati on 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. Therefo re, I support the idea of relying on measured field data to estimate the decay of for maldehyde concentration, and be conservative in the estimation, as intended by t he model. 5) Based on the data provided and the assessment analysis, th e model should provide reasonable conservative estimate of the formaldehyde e xposure 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 meas ure quite complex. The reader who wishes to understand it has to have a competent background i n the modeling sciences, be reasonably motivated and must be able to devote considerabl e time to studying the documentation in order to do so. This complexity puts a hea vy burden on the person(s) providing the documentation in order to clearly explain i ts 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 luci d.

Regarding the appropriateness of the algorithms and assumptio ns, as mentioned above, Matthew’s basic approach appears to be based on solid fir st principles of conservation of mass and the validity of diffusion via Fick’s Law. Equat ion 3-2 appears to be relatively simple, self-evident and quite appropriate. The only term that gave me some pause2-3

regarding its suitability was F (the mixing factor). Som e 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) w hich is the determining factor and because of typically incomplete mixing within any room volu me the inclusion of F is a perfectly legitimate and suitable modeling construct.

Similarly, equation 3-5 forms the basis for the emissio n 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 Con centration from Volatilizing Sources, Am. Ind. Hyg. Assoc. J . 55 (3): 230-235 (1994)).

Equation 3-5 is reproduced below with slightly different not ation along with an equivalent equation from my previous work.

max ) ( G C m G

ss ss +

− = (equation 3-5 with different notation)

G ss = steady state emission rate (mg/m 2 -hr). Equivalent to CH 2 OER’

G max = the maximum emission rate which occurs at zero backpr essure; that is, at zero concentration of formaldehyde in the air (mg/m 2 -hr). Equivalent to b

. m = the mass transfer coefficient (m/hr)

C ss = vapor-phase concentration of formaldehyde at steady st ate (mg/m 3 ). Equivalent to [Ch 2 O] v2-4

Equation 3-5 above is essentially identical to an algorithm that I have often used for backpressure modeling shown below:

max max max



### ) ( : ) 1(

G C C G G rearranged C

C G G

ss

sat ss sat

ss

ss



### +

− = − =

C sat = the saturation concentration (mg/m 3 ) of formaldehyde in the air over the

emitter of interest. That is the concentration tha t 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 th ere is zero

ventilation.

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

sat 

### C G m max 

### =

Clearly, the relatively straightforward analytical me asurement of C sat could provide a potentially valuable extended methodology for the evaluat ion and development of the model’s parameters relative to specific emitters.

The subsequent development of the model’s complexity wit hin 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 compartm ents, while necessarily quite involved, is logically explained and appears to me to be accur ate.

I believe that the treatment of indoor sinks as develo ped by and explained in the model represent a real step forward in indoor modeling science. Fr om my experience few modelers have attempted to address this issue in detail an d none have done a better job2-5

than demonstrated in this work. As noted by the author, t he complex relationships regarding real sink behavior are not fully captured by the sche me 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 incl ude some example data and treatment that illustrates the estimation of paramet ers 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 ac tual 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. Cle arly, 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 cred ible 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 adjus tments 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 th at they should be considered accurate within a factor of 2. That is, given a true conce ntration 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 th e approximations used in the methodology but more from the practical limitations an d 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 z ero, the emission rates for Particleboard Underlayment from the available sources ra nge from 0.09 to 0.74 mg/m 2 /hr or a factor of about 8x. Industrial particleboard ranges fro m 0.12 to 1.24 or a factor of more than 10x. My sense is that this range represents t rue differences in emissions rates but also artifactual differences between testing labora tories. My estimate of a factor of 2 comes from an assumption that the user has a good and ac curate accounting of which2-6

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 r esults and comparison of modeled/measured values from the pilot study. Despite its well documented limitations the parameters in this study appear to be reasonably under stood and the model appears to over predict measured values. During the air out period whe n 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, t he 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 fo r children which are all less than 10 years in length. This is explained in the documen tation 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 tim e a person can spend in that age group. The user can then view the help file for specif ic 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 exactl y half the information

needed to understand the risk to human health from this ex posure. 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, essenti al human metabolite with a biological half-life of about 1.5 minutes.” Reference: http://justthevax.blogspot.com/2009/05/toxin-gambit-part-1-forma ldehyde.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. T he 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 i ssue with most folks but2-7

providing this combined dose over 5 days (730 ppm v/v) as a 5-day l ong bolus would be disastrous to anyone even in the first day (first hour s) 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 CH 2 O is in minutes. Thus, it is not difficult to imagine rela tively high doses of CH 2 O potentially causing biological damage over a period of a few days. As suc h, the estimation exposure in the Results Screen of Average Daily Concentration (ADC) and Average Daily Dose (ADD) could be of particular significance to the toxicolo gist in assessing the overall risk from exposure to indoor formaldehyde. Depending on the speci fic details of the toxicokinetics of formaldehyde the toxicologist may be i nterested in understanding the exposure to humans on the worst (first) day of exposure. T he program allowed me to put in a single day (0.00274 years) for the duration of the expos ure but the results indicate that a calculation error occurs for this input. The cal culated 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 t hat advises the minimum time for duration of exposure. My sense is that this minimum calcu lable time frame should not, in any case, be longer than a few days for the reasons me ntioned above.

Generally, I did not find any errors in the algorithms, how ever, 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 Simulat ion Language (ACSL) computer language. ACSL easily handles simultaneous differ ential equations while providing parameter estimates from data via optimization a nd an intuitive graphical interface. This is not to suggest that ASCL be used in t he 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 dat a) for the model. ACSL is available in a PC implementation. Please refer to th e following web site: ( http://www.acslx.com/products/optimization.shtml ).2-8

Panos Georgopoulos: The mathematical/algorithmic formulation and the computa tional implementation of the model under review (FIAM-pwp) are adequately explained, with sufficient clarity and level of detail; the computational implementation of t he 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 de sired accuracy/precision that is expected - or, at least, desired - for a given a pplication. 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 lev el of confidence in the indoor air concentration and exposure estimates provided by t he model, should in general be considered, at most, medium. In this reviewer’s opinio n, the uncertainty and variability levels in the available data strongly suggest the need for a distributional/probabilistic model formulation that exp licitly employs available data to develop ranges rather than point estimates of concentra tions and exposures.

Considering the (current) model formulation, FIAM-pwp ess entially consists of three components, i.e. (a) estimation of formaldehyde emissi on rates from various types of pressed wood products (based on data from various field and c hamber studies), (b) estimation of indoor mixing/dispersion through simple one-z one and two-zone models that incorporate sink and back-pressure effects, and (c) si mple 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 indoo r air quality (addressing transport and mixing at various levels of detail as well a s incorporating indoor air chemistry and physical transformations etc.) or assessing inhalation exposures and dosimetry. In this reviewer’s opinion, a major drawback inthe 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 emissio n rates with other available indoor air quality and inhalation exposure models. Of course, for any given real-world2-9

application, there will be various bi-directional “links” and “feedback mechanisms” between such models (i.e. effects of airborne concent ration levels on emission and sink rates etc.); however, the approach taken in the mathem atical formulation of FIAM-pwp “lumps” these mechanisms in a manner that limits the us age and evaluation of individual model components. Specifically, though the literature – as well as the provided model documentation – explicitly recognize the fact that forma ldehyde emission rates from pressed wood products decrease with time, the mathematica l formulation of components (a) and (b) of FIAM-pwp is based on the assumptions of c onstant rate emissions and the establishment of steady state for indoor air concentra tion levels (see Sections 3.1 to 3.4 of model documentation). Then, (see Sections 3.5 to 3.6), a de cay rate is imposed upon indoor concentrations, to account for depletion of the fo rmaldehyde sources; this decay rate is parameterized (through half-life values) from ex perimental 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 “l umped” in the phenomenological/apparent concentration decay rate, th at obviously is affected by a variety of chemical and physical transformations that e ither add or remove formaldehyde molecules to/from indoor air. It should in fact be expec ted that “sources” (including chemical reactions) of formaldehyde other than pressed w ood products may affect the parameterization of concentration decay from experimen tal 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 decayi ng (e.g. exponentially decreasing) emission rates and provided appropriate formulas for impl ementing 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 e stablished (see, e.g. AIHA, 2000, Mathematical Models for Estimating Occupational Expos ure to Chemicals). Estimations of exponentially decaying formaldehyde emission rates have in fact been pursued in the past and have appeared long-ago in the scientif ic literature (see, e.g., Brown, Indoor Air, 1999; 9:209-215 and other related references in t he 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 be lieve the usefulness of the model could be strengthened discussing the incremental contribution o f 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 documenta tion and model results emphasize the aggregate contribution of all products (and b ackground sources), and running the model with and without a product of interest can pro duce counterintuitive results as described below. Finally, the relationship betw een the HBF and Matthews

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

comments below.

General Comments – Acute Versus Chronic Exposure One of the challenging aspects of reviewing this model and pr oviding cohesive

recommendations is that the current assessment of acu te and chronic exposure is associated with different uncertainties and conceptual m odels. However, accurate assessment of exposure for each of these endpoints is i mportant. 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 formalde hyde and formaldehyde precursors that is finite and decays with time. The theo ry for acute exposure modeling for pressed wood products is well established and has been reaso nably well validated (Myers and Nagaoka 1981; Salthammer et al. 1995; Groah 2006) and some lite rature exists for the effect of wallboard sinks (Matthews et al. (1987). Th e 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 appr oach to acute modeling. Furthermore, the short term effects of reversible si nks are difficult to reliably model with a steady state approach.

The model documentation should focus on both the determina tion of incremental exposure attributable to the introduction of a specific produc t and the total exposure for2-11

loaded home. Some users will be interested in understan ding the total formaldehyde concentration, but other users, such as trade associatio ns, importers and manufactures, will be most interested in understanding the potential ri sk associated with a specific product or collection of products. Furthermore, regulation s 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 un derstanding total exposure, the manufacturer of a bookcase constructed of pressed-wood pr oducts should be able to intuitively use the model and model documentation to answe r 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 co ncentration when my product is introduced into a new or existing home when a def ault baseline set of pre-existing products (new construction, existing res idence, 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 answ ering questions about the effect of the introduction of new product into a pre-existi ng 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’ halfli fe. I am less concerned about acute exposure, because the potential effect of a particular pro duct is easily discernible by standard chamber testing and calculated equilibrium concent ration on reasonable assumptions about mass transfer coefficients. My conc ern is that if a cancer risk in excess of the acceptable risk range is calculated with this mode l, there is not a clear recommendation for performing a laboratory study that co uld be used to assign a higher2-12

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 E PA 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-pa neling, 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 co nsistent with product specific exposures rather than overall residential half -life.

In the acute setting, the back-pressure effect may atten uate the contribution of a new product such that the total acute indoor exposure concentrati on is not affected by the added product. However, in a chronic, or long term, timefra me (e.g. 10 to 20 years), it is reasonable to expect that the majority of available fo rmaldehyde and formaldehyde precursors will ultimately partition from the product in to the indoor space. My recommendation is that conceptual framework be developed i n the model documentation

to ensure that users take these factors into considerat ion when investigating acute versus chronic timeframes. For the acute timeframe, it is im portant to consider the total collection of assembled indoor products, or alternativel y, 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 tha t 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 conc entration level decreases. The model documentation should refer to the types of decay st udies that could be done to understand the long term formaldehyde dose attributable to a s ingle product or collection of related products. Examples of these studies include (Zi nn et al. (1990), Mølhave et al. (1995), Myer and Hermanns 1985 and Brown 1999). Detailed comments f or 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 c ollection of products (e.g. kitchen cabinets) will increase the indoor air concentra tion to a level exceeding a

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

• A representative collection of products in compliance w ith voluntary or future emissions standards (or alternatively, current air cham ber testing results);

• Current actual background indoor air concentrations establi shed by published data for new and existing homes; or

• Future baseline background indoor air concentrations assigne d based on policy and cost-benefit analysis. The future target background conc entration would be a

fraction of the threshold of concern to allow for init ial increase in concentration attributable to the introduction of a new product or collec tion 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 wo uld be presented with and without the added products. I believe this would greatly assi st 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 introduct ion of 10 m 2 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 sim ply 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 o f sinks. However, I believe that2-14

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 a nd 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 publicati on 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 equa tion relied upon by the authors did not account for the backpressure effect, an d 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 me asured concentrations”. Additionally, because the chamber testing was done retro spectively, the authors could not differentiate between primary and secondary sources. Th erefore, although the results and conclusion of this paper give the impression that the ex tensive use of composite wood products and low air exchange rates were the primary expla nation for high formaldehyde levels (averaging 440 ppb), I am concerned that these excess ive levels may have been partially caused by a product or products that did not meet moder n production criteria or perhaps even the voluntary standards (in combination with the temperature, humidity and air change rate conditions that were true in this partic ular case). If this occurred, then some of the lower emitting products may have been contam inated by the non-compliant products.

In my view, one of the urgent federal policy questions rega rding pressed wood products is whether the absence of federal regulations with perf ormance based standards (with the exception of manufactured homes) has resulted an increas ed prevalence of imported products failing to meet the established voluntary industry s tandards or with potential emission rates higher than domestic production. I believ e the slight reconfiguration of the model I am recommending would be extremely useful for e xplicitly addressing questions2-15

of this nature. From a policy perspective, after acute an d/or chronic health based standards for formaldehyde are established, a focus on incre mental 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 forma ldehyde exposure would be to

use a transient finite difference model where the deca y 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 formal dehyde precursors. In this approach, mass would be preserved because the equilibriu m concentration for attenuated products would only being to decrease after the indoo r air concentration decreased due to depletion of the other higher emitting sourc es. However, this would greatly increase the level of complexity of the model a nd the basic research that would provide a protocol to precisely define the mass reservoirs of formaldehyde, and particularly formaldehyde precursors, is limited. With th e framework of the current model, it is probably most appropriate to estimate the c hronic 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 recommend ation 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. kitc hen cabinets) should be assessed, rather than the aggregate cumulative exposure f or all indoor products (i.e. the cross-sectional approach). Because the typical situati on will reflect products of various ages, the chronic dose attributable to a specific product see ms to be a more relevant

metric than the total indoor concentration over time as suming an initial loading. Evaluation of the decay curve for a single product or cla ss 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-section al decay half-life approach.2-16

In addition, new construction represents a minor fract ion of total residences, so the case where a new home is loaded with new products is the exce ption rather than the typical case for most of the population. In short, the emissio ns half-life is currently considered a ‘house characteristic’, whereas I believe it would be mo re appropriate to frame this in terms of a ‘product-specific’ characteristic.

For a specific product, a finite reservoir of free forma ldehyde and formaldehyde precursors exists. Over a sufficiently large period of ti me, factors such as temperature or humidity are likely to affect the transient time-con centration profile, but less likely to affect cumulative exposure, or area under the curve. Simil arly, 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 fo rmaldehyde 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 ri sk from separate products or collection of products can be added to derive total risk or a n 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 emi ssion lifetime of an individual product (e.g. 10 years) or by selecting a target background indo or concentration higher than outdoor ambient air levels corresponding to the decay concentration where

emissions from the source under consideration would be con sidered 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. cumulat ive 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 transi ent process with the limitations of a pseudo-steady state model.

Under the current model guidance, the true increased canc er 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 wo uld not be reliably2-17

determined. Initially, the backpressure effect will suppress a portion of the formaldehyde emissions, such that if the user were to compare cumula tive 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 cabi nets is less than the pre-existing steady state concentration, running the model with and wit hout kitchen cabinets would result in the physically impossible conclusion of negati ve incremental cancer risk because the cabinets would initially act as a net sink. To i llustrate 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 concentrati on is 0.3557 mg/m 3 , LADC is 0.0132 mg/m

3 and percent of time > 10 ppb is 46.9%. If 45 m 2 of kitchen cabinets with the EPA cabinet rate are added to the existing decking, the i nitial concentration is 0.3389 mg/m 3 , 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 a dded 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/m 2 -hr) / 0.49 (m/h) = 0.16 mg/m 3 . It seems likely that over the lifetime of the kitc hen cabinets, there will a finite long term dose greater than zero that will occur once t he 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 pr ofile of individual products should be encouraged in the model documentation (rather than ex clusively relying on the historical data from the 1980’s). At a minimum the model s hould be revised to allow consideration of periods of rapid and slow decay in the e mission rate as observed, for example, in Zinn et al. (1990), Mølhave et al. (1995), Myer an d Hermanns 1985 and Brown 1999. Long term testing is not feasible on a routin e basis, but I believe the model should have the framework in place for investigators, s uppliers or manufacturers interested in more robustly characterizing chronic exposur e than has been typically done to date. Particularly of concern is that the decay char acteristics of modern and new to market resins are largely unknown. The current single co mpartment exponential model will provide a conservative estimate of chronic exposure , but does not necessarily2-18

provide a pathway forward or conceptual framework for refin ement of the calculation of long term cumulative dose.

One conceptual model for assessing chronic exposure for for maldehyde 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 lar ge 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 (med ium-term compartment); and

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

Using an exponential peeling procedure, the authors determi ned 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 represen ted the transient data. The corresponding accumulated dose was compared to the Califo rnia 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 approac h to understanding whether compliance with Proposition 65 was achieved was reasonabl e. I strongly recommend that

the model documentation be modified to make clear how t his 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 e t al. (1990) seems more appropriate than the 2.92 year half-life derived from cros s-sectional sectional data in the original Versar model. Zinn et al. (1990) estimated an appare nt half-life of 216 days using approximately one year of large chamber data for parti cle board and a natural logarithm linear regression statistical analysis. The h alf-life reported in Zinn et al. (1990) is not directly comparable to that adopted in the origin al and current Versar model2-19

because Zinn et al. used the relationship HCHO = F + G x l n(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 tec hnical basis for the formaldehyde airborne toxic control measure. In lieu of the origina l logarithmic equation, the more generic two-compartment (i.e. fast and slow decay) exponen tial decay model could be fit

the Zinn et al. data.

Finally, one concern is the interaction between venti lation 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. There fore, in the future when decay characteristics are better understood, it should be possibl e to adjust for ventilation rate and account for total mass of formaldehyde generated over t he lifetime of the product. Although the data to accomplish this is currently not avail able, it would a benefit to the scientific community to frame decay of emissions over t ime in terms of an accurate conceptual model, rather than current fully empirical a nd 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 a re both mass transfer based approaches, however, the mass transfer coefficient ob tained 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 H oetjer 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 r egression (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 appro aches.2-20

To illustrate this point, I performed a linear regression a nalysis for the first loading of kitchen cabinets presented in Koontz et al. (1996). The regr ession 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)

C S = steady state concentration (mg/m 3 ) N = air change rate (1/hr) L = loading rate (m 2 /m 3 )

C eq = 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 C eq = 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 C eq . 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, C eq and K are calculated for the kitchen cabinet data present ed in Koontz et al. (1996) using both the HBF and Matthews regression equations (i n an Appendix). The purpose of this appendix would be to provide clear guidance o n the type of chamber tests (i.e. at least three N or L combinations for the linea r 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 differenc es in regression parameters result in predicted steady state concentrations that a re 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/m 2 /h, r=-0.9732-22

Figure 1b : HBF linear regression. C eq = 0.19 mg/m 3 , K = 0.41 m/h, r=0.997

Figure 2: Calculated steady state concentration for regression m odels in Figure 1 assuming loading (L) of 0.13 ft 2 /ft 3

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 th e worst case concentration in the absence of ventilation (N=0) is 0.19 mg/m 3 . It is easy to conceptualize that this is approximately the level that would be expected in a confined spa ce like the inside of a closed kitchen cabinet. The Matthews model parameters ar e less intuitive. The maximum emission rate which can be derived directly from b is onl y true in the absence of formaldehyde in the bulk air, or at the beginning of the e xposure period. However, the2-23

Ceq of the HBF model can be easily calculated. The con centration in the absence of ventilation (and background sources) is b/-m or C eq = 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 giv en the essential identical model construct perhaps of minimal benefit. My recommenda tion if only the Matthews model is retained in the model is to provide an example cal culation in the model documentation showing how the user can start with the H BF linear regression or the HBF model parameters and convert the parameters to the equiv alent 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 parti cular product is likely to act as a sink or a source based on an estimate of the anticipat ed indoor air concentration.

In conjunction with this conversion equation, a statemen t should be included indicating that for plausible ranges of the N/L ratio, the selec tion of a particular linear regression model is not expected to appreciably affect the results. T his could be demonstrated by a Monte Carlo analysis or reanalysis of the data in Ta ble 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 pe rmanent loss of formaldehyde and that the wallboard serves as a buffer t o sudden changes in indoor air concentrations (Matthews et al, 1987). However, the trea tment of indoor sinks in the current EPA model is problematic because absorption and de sorption 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 buf fers changes in concentrations but does not necessarily affect cumulat ive exposure, or area under the2-24

curve. Therefore, for instances where the EPA model i s used to calculate lifetime, or long term dose, accounting for reversible sinks could potentiall y underestimate true cumulative dose, depending on how the exponential decay o ver time is conceptualized.

Figure 1 : Chamber test results for a reversible sink reproduced fr om Fig. 2, p. 27 in Tichenor et al. (1991).

When the Langmuir model is run to steady state, dM/dt = 0 and C indoor = k d /k a *M. However, at steady state, there is no capacity for t he 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 stea dy state there is no net effect of the sink and if the EPA model guidance provided on page 3-7 is foll owed exactly (e.g. 0.0375 mg/m

2 -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 notin g that C eq =b/-m and using the standard mass transfer equation. For drywall, C eq = 0.0375 mg/m 2 -h / (-3 m/h) / (1.236 mg/m 3 / ppm) x 1000 ppb/ppm = 10 ppb. Therefore, when C S =C eq = 10 ppb, then ER = K(C eq -C s ) = 0, where ER is the emission rate. Note that as a result of rounding or2-25

significant digits, there could be a small (arbitrary) n et positive or negative flux from a sink defined in this way.

It appears that the guidance for the sink intercept given o n EPA model guidance page 3-7 was developed by setting intercept b = k a x C indoor assuming dM/dt = 0. When there is a linear relationship between accumulated mass and indoor ai r concentration at equilibrium conditions, dM/dt must equal zero. Therefore, deviations o f the intercept from the calculated value would imply a sustained loss of equilibr ium, 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 interc ept for indoor sinks appears to treat this parameter as calibration or adjustment facto r rather than as a predictive input.

For wallboard, the surface area is high in magnitude, the refore 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 con centration, the first estimate for the slope of the wallboard sink would be (46 ppb / 10 ppb) x 0.0375 mg/m 2 -h = 0.1725 mg/m

2 -h. When this value is entered for the wallboard slope, as expected, the Zone 1 concentration remains at 46 ppb. Due to rounding or insuf ficient significant digits, the calculated flux for this intercept actually reflects net generation rate (G) where positive G corresponds to desorption:

G = 420 m

2 x (0.05721 mg/m 3 x -3 m/h + 0.1725 mg/m 2 -h) = 0.36 mg/hour

Holding concentration constant in the prior example, a negligible decrease in the intercept to 0.1715 mg/m 2 -h would cause the wallboard to be considered a sink wit h net adsorption:

G = 420 m

2 x (0.05721 mg/m 3 x -3 m/h + 0.1715 mg/m 2 -h) = - 0.05 mg/hour2-26

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 wallb oard. This is true because at the starting point (e.g. 0.0375 mg/m 2 -h per 10 ppb indoor air), the net generation rate from the sink is approximately zero, or dM/dt = 0. However, the re does not appear to be a reliable way to a priori assign the final value of the intercept other than tria l and error to

achieve a modest decrease in indoor air concentration.

The short term data from Loading 1 at the test house c learly show that the initial sink effect from wallboard can be appreciable. To correctly a ccount for net adsorption on these short time scales within the framework of a pse udo steady state model, a non-zero value of dM/dt must be calculated using Equation 3-13 and set equa l 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 lev el of complexity needed to assign the sink term because indoor concentration and mas s storage vary as a function of time. However, prior EPA models such as MCCEM have incl uded this functionality. If an estimate of the indoor concentration profile is av ailable 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. Ho wever, at 30 days, dM/dt may be sufficiently small that a reasonable default recommen dation in the model would be to neglect the effect of sinks.

The treatment of sinks in the EPA formaldehyde model refl ects a reduction in sophistication from that which is available in the prio r 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 o f 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 mo del addresses long-term decay using a pseudo steady-state approach. It may be appropria te to have two versions

of the model:

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

• Short term MCCEM-style model to understand whether the pre sence of sinks would appreciable reduce initial peak exposure.2-27

As an example, MCCEM was used to implement the Langmui r 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 flo or and basement and low air exchange between the basement and outside. Therefore, t he 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/m 3 ) * Q (m

3 /hour). The following parameters were input into MCCEM:

Formaldehyde generation rate = 3.434 mg/hour (to approximate 10 ppb steady state) Reversible sink, carpet:

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

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

A = 94 m

2 (EPA model documentation Table 5-3)

Home:

Zone 1 volume = 304 m 3 (EPA Conventional Home 1)

Zone 2 volume = 167 m 3 (EPA Conventional Home 1)

Interzonal airflow = 111.5 m 3 /hr (EPA Conventional Home 1)

Zone 0-1 airflow = 259.5 m 3 (EPA Conventional Home 1)

Zone 0-2 airflow = 19.6 m 3 (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 ste ady state formaldehyde concentration of 10 ppb. Approximately 7 or 8 hours after i ntroduction of the source, the rate of increase in storage in the sink is negligible an d 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:

C steady = 1000 ppb/ppm x 3.43 mg/hour / (471 m 3 x 0.59 hr -1 x 1.236 mg/m 3 per ppm) = 10 ppb

dM/dt steady = 0 = 0.010 ppm x 1.236 mg/m 3 per ppm x 1.304 m/h x 94 m 2 – 0.196 hr -1 x M2-28  M = 0.082 mg/m 2  M*A = 0.082 mg/m 2 x 94 m 2 = 7.7 mg

Note that at steady state, k d x M = 0.196 hr -1 * 0.082 mg/m 2 = 0.016 mg/m 2 -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 a ccordance 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 int ercept or rounding errors, which do not appear to have a theoretical basis.

Table 2 : MCCEM model results for constant source and carpet s et 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 f or the EPA formaldehyde model does not address the original findings by Koontz et al. (1996) w ith respect to wallboard or provide justification for application of the Langmuir mo del to wallboard given the prior findings. More discussion is warranted, and perhaps cons ideration of the unpainted wallboard studied in Matthews et al. (1987) would be helpful

.2-29

The initial sink parameters specified in this model are les s problematic theoretically because the rate of desorption (k d x M) is low initially. However, the inclusion of thes e parameters is questionable because the pseudo steady-state design of the model is not well equipped to handle transport processes that occur ov er relatively short time scales. As shown in Table 2, sinks can reach the maximum loadi ng at a given concentration relatively rapidly. I recommend evaluating dM/dt as a fu nction of time for the EPA test house and other data and making a determination about wheth er 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 i nvestigated (e.g. 24-hour average, etc.).

Indoor Sink – Implicit Indoor Sinks Some pressed wood formaldehyde “emitters” could theoretica lly 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, equi valently, low Matthews model intercept). For example, low emitting products with unrea cted urea can act as scavengers (Meyer and Hermanns 1985). This could potentially be an interes ting question for situations like manufactured home where a product with exce ssive free formaldehyde levels could ‘contaminate’ otherwise low emitting product s. 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 em itting 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 whe n few high emitting products are paired with several very low emitting products. Presentati on 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 transf er parameters for kitchen cabinets were paired with a range of assumed background conc entrations. Here for simplicity, the ‘background concentration’ is used as a pr oxy 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/m 2 /hr, ACH = 0.5 hr -1 and L = 0.13 ft 2 /ft 3 . The corresponding equilibrium concentration (C eq ) from the HBF model is approximately 0.163 mg/m 3 . As can be seen from the results in Table 3, when C b > C eq , the kitchen cabinets would act as a sink, resulting in a lower steady state concentrati on than the influent background concentration ( ∆ C sb < 0). This result is expected from the mass transfer e quation where ER = K(C eq -C ss ). When C ss > C eq , 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 intui tive way to anticipate the results than the Matthews intercept b. Second, the ou tput in the model of the emission rate attributed to each of the individual components model s could potentially provide useful diagnostic information to the user or modeler. A s wood panel resin technologies improve and more ‘green resins’ become available, the pote ntial 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 sensi tive 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 so urces.2-31

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

Michael Jayjock: For the most part the default scenarios and assumption s appear to be reasonably supported. Specifically, the air exchange rates for the h omes agree with my understanding of national averages for this important vari able. 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 w ith this model (ref: Murray,

Donald M. and David E. Burmaster: Residential Air Exchan ge Rates in the United States: Empirical and Estimated Parametric Distribution s by Season and Climatic Region,

Risk Analysis , Vol 15, No. 4, 1995). Of particular value are data from dif ferent geographical sectors and seasons within the U.S.

Also, I found the choice of housing types to be very reas onable. 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 interpretati on) that any child in any of the age groups will have 10 years of exposure is confusing at bes t and should be easily corrected. Of course, the years of exposure should be e qual to or less than the years within that age group. Indeed, my sense is that many analyst s 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 answe r to Question 1.1, as these assumptions in fact “drive” the mathematical equations o f 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 i nstances, there is not necessarily a clear pathway forward for refining the default paramete rs.

Data Collection to Revise Default Assumptions It is not clear how the manufacturer of a specific pr oduct (e.g. MDF panel) could do a study with their specific product to refine the cross-sect ional 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. em issions decay) is limited.

I am concerned that too much emphasis is placed on the l arge database of historical emissions parameters provided in the model (Table 2-2) and his torical decay rate evaluations (Section 3.6). I believe the model formulati on and model documentation should be more forward looking in two respects. First, i t should be made clear that many of the default emissions parameters in the model are b ased on historical testing and may or may not be representative of current products (See al so Response 1.2). Typically these rates should be conservative (i.e. likely to overestim ate emissions), but it is plausible that the default parameters may underestimate true emissions from products, particularly imported products, as a result of exceptional free formalde hyde levels exhibiting nonconformance with the voluntary industry standards. Sec ond, clear guidance should be provided to end users (e.g. importers, manufacturers, non-pr ofit 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 manufac turer 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 deter mined in routine chamber testing, and the sensitivity analysis would be helpful in determining whet her this additional product specific data is a data need or a data gap. Other questions addressed by the sensitivity2-33

analysis could include the effect of inter-zonal air c hange 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 crit ical sources within this model are

the chamber tests for emission rates and the fitted va lues for the linear rate model. I am not familiar with these data sources but they seem to b e well described and characterized by the author. I also do not know of other data sources on t he 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 inc lude 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 questi on whether they are still the most relevant data sources in relation to currently avai lable/used pressed wood products (given changes in manufacturing procedures as well as in changes in relative levels of domestically manufactured versus imported pressed wood product s). The answer may in fact be yes, but it should be explicitly stated and suppo rted.

Kenneth Unice:

The sources of data in the model are reasonable and accura tely represent the original studies, with the exception of the wallboard sink as note d below.

Emissions parameters It is unknown the degree to which the data in Table 2-2 ref lect manufacturing practices in 2009, and the potential for low or high bias exists. Users o f the model should be encouraged to collect and use data for products currently in t he supply chain. This could be accomplished by deemphasizing the data in Table 2-2 (perhaps by moving to2-34

Appendix) or by requesting voluntary submission of chamber dat a 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 informa tion 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 substa ntial airflow in the winter. To the casual user, it will not be immediately obvious th at Conventional 1 represents the

data for one test house under limited conditions. Theref ore, 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 underlaym ent 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 so urce to Zone 1 or to both Zone 1

and Zone 2.

Conventional 2 More details regarding the analysis of PFT data used to der ive the airflow rates Conventional 2 should be provided.

Wallboard sink The use of Langmuir isotherm for wallboard should be f urther explained, as this was found to not be valid in the original report for the pil ot 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 Sub sequent Model Use

Jensen Zhang: Although the data sources are incomplete for quantifying th e uncertainty, it is possible to conduct an uncertainty analysis using error propagation the ory with assumptions on the uncertainties in the raw data. This would help establish t he uncertainty in the predicted

results.2-35

Michael Jayjock: I interpret the above question to mean the data used in t his 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 thes e data could assist in gauging the variability of this parameter. Also, I believe the curre nt data used in the model on emission sources discloses a level of uncertainty and va riability 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 popu lation 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 expecte d to appreciably affect formaldehyde transport. The use of Langmuir isotherm sh ould be further explained, as this was found to not be valid in the original report (Koon tz et al. 1996).

Uncertainty and sensitivity The uncertainty and sensitivity analysis presented in Ma tthews et al. 1985 could be

discussed.

2.1.5 Comment on Whether the Model Input Variables and the Estim ates

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 s hould 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 resu lt 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 wit hin 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 lo w 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 qua ntitative level of variability extant within the system and would be provided within the c ontext 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 t he statistical variability and the parameters of the emission equations could be represented as best-fit probabilistic

distribution functions. These distributions would then b e incorporated into a Monte Carlo scheme to present a predicted output distribution of concen trations and exposures. This would add significantly to the complexity of the tool but w ould provide a direct and cogent measure of model variability as driven by the input va riables.

Panos Georgopoulos: As mentioned in the answers to previous questions, a distri butional/probabilistic approach, for defining model input variables and deriving concentr ation and exposure estimates, would, in this reviewer’s opinion, be more appropr iate in relation to this model, given the wide ranges of uncertainties in proces ses 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 avail able 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 meas ured in most chamber testing. EPA should perform a sensitivity analysis to determine whet her 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 i s likely to be the key determinant of exposure with the mass transfer coefficient of les s 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 hav e 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 tw o- or three- compartment exponential models than the single exponential model be cause these models better represent the decay in the reservoir of formaldehyde pre cursors 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, the re is no good conceptual model by which to collect product specific data to refine this paramete r. It may be possible to address some of these questions using a sensitivity analysis t o determine whether2-38

conclusions about risk would change depending on how dose f rom 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 t he voluntary submission of data representative of the current supply c hain.

2.1.6 Comment on the Adequacy of the Documentation Supporting the Overall

Plausibility of the Exposure Estimates Generated by the Ex posure Model

Michael Jayjock: My sense is that the estimates have been clearly show n 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 v ery well explained in the documentation, this study appears to provide adequate evidence th at 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 ex perts who had almost perfect knowledge of the scenario and the workings of the model.

Perhaps a more practical test of the model’s accuracy a nd 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 i nvolve going into newly constructed residence(s) and modeling first (monitoring seco nd) after determining the appropriate model inputs using available information. The mode lers 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 inv oking worst-case/best case

models estimates of the real world scenario as describ ed above (and then comparing them with measurements) could be very valuable in demonstratin g the model’s value in predicting real world concentration and exposures to forma ldehyde.2-39

Panos Georgopoulos: Ideally, the exposure estimates that are derived from FI AM-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 o utdoor gas and heterogeneous phase chemistry of formaldehyde (that may r esult in net production or removal in a given microenvironment). Very large variabili ties should be expected across regions and populations, with differences in both geographic al (e.g. climate variables) and socioeconomic factors (housing, occupation, etc.) dr iving these variabilities. Linking such estimates with corresponding population-based estimat es of exposure to outdoor air formaldehyde (e.g. from the National Air Toxic Assessme nt [NATA] studies) would be very useful in that context. Comparison of model estima tes 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 plaus ibility 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 loadi ngs and comparing the model results to published concentrations of formaldehyde in new and existing s tructures. 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 h alf-life is to be used to derive product specific dose. Running the model with and without the pr oduct of interest will not result in meaningful conclusions as discussed previousl y. Accordingly, there is great uncertainty in product specific doses under the current mode l framework. EPA has not considered whether the historical 2.92 year cross-section al half-life is representative of the decay profile of modern products or the potential vari ability in the formaldehyde reservoirs and decay between products.2-40

2.1.7 Provide Any Other Types of Data to Assess the Reliability of t he Overall

Exposure Model or Specific Model Elements

Jensen Zhang:

I am not aware of additional field data for the assess ment.

Michael Jayjock:

Please see the discussion in 1.1 above in which an additi onal critical emitter variable –

C sat is explicated using the basic emission rate algorithm: Eqn 3-5. Data on this variable could be directly measured in a straightforward manner. T his could occur by first constructing a box of the emitting material with an int ernal volume sufficient to provide a good limit of analytical detection. For example, if o ne wished to have analytical detection limit (LOD) of 2 ppb they would consult with the analyt ical chemist as to which sample volume would be able to detect that value. Say, for exam ple that a 5 liter air sample would be required to render an LOD of 2 ppb formaldehyde. One w ould simply construct

a box with an internal volume of 5 liters. Moderate c are should be taken to seal the edges against leakage. The box should be allowed to equilibrate s uch that the internal concentration is no longer increasing. It is suggested tha t 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 conce ntration represents 69% of the amount of formaldehyde in the box if good mixing occurr ed during relatively rapid sampling. (Note, having a small fan in the box will haste n equilibrium and assure good mixing during sampling.) Thus, the measured C sat would be equal to the measured concentration/0.69. As mentioned above having C sat should substantially increase the confidence in the validity of m.

Panos Georgopoulos: There are various studies and related data sets, both fro m the US and abroad, that have appeared in recent years and could - potentially - be used fo r 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 belie ve the current lumped, or whole-residence based, approach will create confusion a nd greatly complicate risk management decisions if the end point of concern is base d on chronic exposure. The emphasis should be on developing a consensus approach to qua ntifying the reservoir of free-formaldehyde and formaldehyde precursors in a specific pr oduct. 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 volum e, number of zones (1 or 2), and air exchange rates between indoors and outdoors and b etween zones.

2. Put formaldehyde-containing sources into each zone, selecti ng 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” em ission model. The slope value accounts for the influence of vapor-phase HCHO on t he emission rate and the intercept value is the emission factor at zero HC HO in the vapor phase. A table of slope and intercept values derived from the liter ature is provided. Users can enter their own values if they choose.

3. Calculate a “steady state” concentration of HCHO fr om these inputs by mass balance calculations, assuming complete mixing in each zo ne. This concentration is assumed to be the peak concentration in the house, a fter which the HCHO concentration decreases at a first-order exponential r ate.

4. The exponential rate of decay of the HCHO concentratio n is calculated by assuming a half life, or the time it is estimated it w ill 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 hous e, and number of years in the house. The results of exposure calculations include a n 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: Th e 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. Hi gh gas-phase concentrations can suppress emission rates. But if you look at the effect, s ay 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. Nea rly all the data appear to have

been taken under conditions where the HCHO concentrat ion 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 con cern that anyone is likely to use. So the practical value of the slope in the emissio n rate equation is not evident unless one is going to model situations that are clearly unhealt hy. Why not just use the intercept values and simplify the model? Better, in my opinion, t o 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 v ariables such as temperature, relative humidity, etc.

That said, the analysis provided in section 5.3 of the docum entation suggests that whatever the convolutions involved, the model gives respec table predictions. My reading of the tables in that section, which summarize modeli ng results compared to measured values in the EPA pilot study house, is that the model r anged 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-t ime 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 t 1/2 = 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 mont hs, etc. I don’t have the Versar 1988 or Groah 2005 compilations at hand, so I didn’t che ck this but it would be simple to do once the data were compiled and segregated in to appropriate time periods. First-order regressions could be determined for each time period; the k values would show whether the decay rates were changing significantl y over time. This exercise might give you some insight into how conservative the 3-yea r (nee 2.92-year) half life is.

One significant shortcoming of this model, and many indoor m odels that assume complete mixing within compartments, is that it doesn’t de al with what I refer to as

“intimate” sources. These are sources that can lead t o much higher exposures, especially for very young children or elderly people, than would be pre dicted by such models as FIAM. Examples are toys, cribs, bedding materials, cl othing, and flooring materials for children and bedding and clothing for elderly people. To some e xtent 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 i s 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 m 3 for dispersion of emissions from furniture and machines at workstations. The volume one mig ht use for babies on bedding or flooring materials would presumably be much smaller; t he resulting calculations would predict exposures that might be orders of magnitude high er than predicted by

FIAM.

1 Tucker, W. G. 1990. Building with low-emitting materials and p roducts: 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 ev ery 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 t o use. Alternatively, tell user how to select. 3) Source selection: How is the area defined for the cabi net? The surface area or the foot print? 4) It would be more convenient for users to select floor t ypes and then provide

model coefficients for all the materials involved instea d of asking users to

“construct the floor”. 5) The screen on “Exposures” is too wide for my notebook (L enovo/Thinkpad X61s). Also, the “Adult”, “Child” should be more visible. 6) The help sign “?” is too visible. Suggest that make it sma ller and place it after the data entry. 7) The “results” file may be made more informative to con clude 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 c ompleting a Tax return with TaxAct)

Michael Jayjock: As mentioned above FIAM – PWP is a complicated tool tha t requires a considerable amount of input and performs a significant amount of ca lculation. Considering all that it does I found the user interface is remarkably clean and straightforward. The “tab” format is logical. Also understandable and obv ious is the flow of operations from the first to the last tab. I found the “pull down” window input format to be2-45

easy and very intuitive. In short, I have no reasonable sugg estions to make it more user friendly.

Panos Georgopoulos: FIAM-pwp is a web-base program that is easy to use at th e “client side” through a browser (MS Internet Explorer). Microsoft technology appears to be used throughout the implementation. Local use of the program in its curren t form would still require setting it up so it is accessed by the browser – this requires adjustin g 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 student s, shows) a “well-polished” and “user-friendly” interface often raises (probably subco nsciously) expectations regarding the precision and accuracy of the model calculated esti mates. 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 da ta-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 mo re cumbersome than similar models like MCCEM, IAWX, EFAST or WPEM, but this is most ly 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 initia lly tried to edit this field because it was a text box prior to reading the help funct ion. Replacing this field with plain text would make clear that this value cannot be ed ited.2-46

Modifying sources When a source is modified, the user should be required t o rename the source and a separate library of user entered sources should be maintai ned. Currently, it is impossible

to know whether someone overrode the default values or t he 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 em ission 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 permitte d to edit the AVG and HUD parameters. If desired, the AVG-PBU could be suppleme nted 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 labele d HOW-6N(U) in the model.

Printing When a screen is printed in standard portrait view, the e dge 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. Pleas e 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 th e tab key is pressed, the next text box with focus is logical, but in some instances the n ext 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 i ssue, however. I have a relatively2-47

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 incre ase 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 th e “readability” of the generally excellent help information.

I was easily able to get the “larger fonts” options runni ng 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 coul d be enhanced by including some statements regarding the level of precision expect ed for some of the entries (that should be consistent with the high uncertainty in the est imates; 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 aud io prompts generally worked well, although some were missing failed to load (e.g. firs t 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 com ments 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 Scree n 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 Ide ntified

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 8 th reference (D. Hare...) can be found and

should be referenced at: http://www.ecobind.com/research/Evaluating_the_Contributio n.pdf (last accessed October 9, 2009). Indeed, any and all the reference particularly fr om 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” m odeling) should be considered

for inclusion.

Panos Georgopoulos: The Addendum to this review presents a selection of refer ences on indoor air formaldehyde emissions, concentration levels, and releva nt physicochemical processes; the selection includes both experimental (field and labor atory studies) and modeling

studies. This reviewer would recommend consideration of at least some of these references in future revisions of FIAM-pwp and its documen tation.

Kenneth Unice: The references are accurately identified, however I r ecommend 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 shoul d be provided.2-49

Theory For more information regarding formaldehyde emissions fro m 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 h ave summarized recent measured formaldehyde indoor air concentrations in new and exist ing 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 databa se including in the model is primarily for historical products, however, more recent i ndoor 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 th e results are appreciably outside the bounds expected. Central tendency indoor air c oncentrations 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 refere nces (essentially a white paper and report prepared on behalf of HPVA) be replaced with peer-reviewed publications, conference proceedings, or governmental citations. Exam ples of publications addressing the long term decay of formaldehyde emissions from consume r 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 s ingle 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 attri butable to a specific product.

Backpressure effect I recommend citing Jayjock 1994 in reference to the backpres sure effect first introduced on page 2-16 of the documentation. This paper provides a good revie w of this concept for users not familiar with the concept.

2.3.2 Provide Comments on the Model Documentation (Does It Presen t 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 ma ny 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 t ruely 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 poin t was treated as “constant” for the purpose of simplifying the calculation without lo sing too much accuracy. An additional reference may be cited to justify such tr eatment (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 Constr uction, National Research Council Canada, 733)(IRC-IR-733)

2) The “flow balance” should be changed to “mass flow rat e balance” to be accurate. 3) I am concerned that most data provided on formaldehyde emis sions are from early studies. Much of the manufacturing processes and raw mater ials have been changed. Especially due to the use of non urea-formaldehyde r esins, the formaldehyde emissions from pressed wood products have be en 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 sec ondary 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 ensemble s have the same slope and intercept for “Shelves”? 6) Regarding Equation 3-5:

CH 2 OER 

### ′ = -m * [CH 2 O] V + b (Eqn. 3-5)

where:

m = the mass transfer coefficient (m/hr) [CH 2 O] V = the CH 2 O concentration in the vapor phase (mg/m 3 )

b = a constant; the emission rate at zero CH 2 O concentration in the air (mg/m 2

-

hr). 6.1) The Fick’s law is for diffusion, while here the process is governed by

convective mass transfer across the boundary layer. Ai r velocity and turbulence

over the surface hence affect the mass transfer coef ficient, 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, [CH 2 O] 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 alway s 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 a ir outside the boundary layer is the same as the steady-state concentration in th e compartment. 7) Page 4-2: “Product loading rate”---do you mean “loading ra tio”? 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 documentati on is particularly gifted in providing a plan and useful explanation of all the various facets of the work. It definitely requires2-52

considerable study on the part of the reader to understand w ork 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 woul d 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” algor ithm in the Eqn 3-6 and 3.8.

Panos Georgopoulos: The documentation for FIAM-pwp is quite thorough in presen ting the model formulation and implementation as well as the data sources that we re used to develop parameter estimates for this implementation. One could note th at there are some minor “awkward” points that could be fixed with careful editing (e.g. one re ads on page 2-7 that “the flows from/to outside are exactly half the house volume” fo rgetting the temporal element in the concept of flow, while degrees Kelvin are denoted as o K rather than K, etc.). However, the main issue with the documentation is the justifica tion of the formulation of certain elements of the model per se (e.g. the assumption of co nstant rather than decreasing emission rates, etc.) rather than of potential altern atives.

Kenneth Unice:

Concentration as a function of time Consider explaining in the model documentation why the co ncentration time points of 3, 6 and 12 months were selected for output.

Estimation of sinks As described in more detail earlier, the treatment of si nks is not transparent and confusing because the rate of storage changes with time but the m odel 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 some2-53

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 han dling of sinks. The approach to

wallboard sinks used in the current EPA model should be consis tent with the wallboard sink equations and data presented in Matthews et al. (1987). T he 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 fo rmaldehyde model may not be familiar with the linear regression protocol required to estimate the parameters for either the Matthews and Hoetjer formaldehyde mass transfer model s. It is recommended that documentation be revised to show an example linear regres sion for the recent data Koontz et al. (1996).

Hoetjer-equation As described previously, the documentation should explain th e relationship between the Matthews and Hoetjer equation. The Hoetjer equation or e quivalent mass transfer equation is frequently cited in the literature and some sta keholders may not be familiar with the Matthews equation. Examples of papers relying on the standard mass transfer relationship (i.e. C eq

and K) include:

• Berge et al. 1980

• Myers and Nagaoka 1981(presents the use of linear regression t o determine C eq and K)

• Myers 1983 (presents the use of linear regression to determine C eq and K)

• Salthammer et al. 1995

Langmuir Isotherm

The documentation should note that it is assumed that t he number of occupied adsorption sites are much less than the available sites, reducing th e 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 = k d /k a *M.2-54

Analysis of data Consider presenting the analysis of PFT measurements an d raw data in an appendix for Conventional 2 (p. 2-7). Is this data similar to data avail able 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 paramet ers without reproducing the

calculation or whether the result is different base d 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 Variab ility and Uncertainty in Model Results

Jensen Zhang: There are good description of the possible sources variabil ity in the model prediction. However, it would be helpful if a more quantitative anal ysis is conducted on the uncertainties of the model coefficients and how they w ould 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 antici pated range of input variables within all the particular categories (e.g., standard temper ature (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 picking2-55

reasonable parameters for specific source strengths, tem perature 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 rea der 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 variabi lity and uncertainty associated with various model elements are not fully revealed in the documentation. An ideal solution would be a probabilistic “re-formulation” of t he 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 variabili ty 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 extrem ely useful.

Kenneth Unice:

Mass transfer coefficient Consider incorporating a mass transfer coefficient sens itivity analysis into the model or model documentation. The uncertainty and sensitivity analy sis presented in Matthews et

al. 1985 could be discussed.

Airflow Consider providing a database of homes similar to MCCEM da tabase 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 para meter is likely to change the conclusion. This could be done using the spreadsheet model a lready prepared. The uncertainty and sensitivity analysis presented in Matth ews et al. 1985 could be discussed.2-56

2.3.4 Comment on Whether the Model Algorithms are Consistent wi th 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 th e model algorithms are for the most part consistent with their descriptions in th e model documentation. I did detect either an error in sign or the omission of an expla nation in the correlation coefficients presented in Table 2-2. All of the coefficients have a n egative 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, emissio n rate and concentration should be positively correlated. I would also prefer to s ee this “fit relationship” described as the correlation coefficient squared (R 2 ) 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 R 2 = 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 documen tation; issues with the algorithms were addressed in the answers to questions of Pa rt 1.

Kenneth Unice: Verification of Model Equations The model equations provided in the documentation were revie wed. 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 C v of 0.1633 mg/m 3 and

K m of 0.49 m/hour in the mass transfer equation of IAQX. Th e results were evaluated with and without a background concentration of 0.010 mg/m 3 . IAQX Model Source Type2-57

14 was used to add the background concentration. The model resu lts 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 outpu t 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 i n environments with above average background concentrations, the presence of the ba ckground sources could be important. Therefore, there could be cases where the use r would like to include a background concentration in the model, but exclude the con tribution of background from the dose. Consider providing a checkbox option to include or e xclude 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 use ful. Users should have little trouble following it. Minor comments follow.

1. Page 2-4, 4 th

paragraph: you should not describe the slope as “...in the form of a first-order sink representation...”. The slope represent s a linear function; firstorder implies exponential growth or decay, neither of whi ch would describe absorption characteristics of sinks. A logarithmic equa tion might make more physical sense, but that would introduce further calculatio nal complications.

2. Page 3-2, 2 nd

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 conside r 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, w hich these days is a simple matter with spreadsheets like Excel, where k can be determined easily from the “trendline” equation for a first-order exponenti al 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-l ife. [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 alterna tive approach that I believe would be helpful to the general user, and have at tached 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 rel evant to other models if they should be developed for other indoor air quality situat ions 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 towar ds fulfilling a critical need to develop a scientifically valid framework for the charac terization of human exposures to formaldehyde. Given the enormous complexity of this probl em, it should be recognized that additional steps will be needed. In this reviewer’s opi nion, development of statistical distributions of emission rates for different pressed w ood products, that explicitly incorporate and quantify the uncertainty and variability in ava ilable 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 adsor ptive building material on formaldehyde concentrations: development of measuring met hods and modeling of adsorption phenomena." Indoor Air 14 : 51-64. In this paper, a method is developed to assess the performa nce of adsorptive building materials that are used for reducing indoor pollutan t 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 airf low along the test materials can be controlled precisely. A new index of ads orption performance, the equivalent ventilation rate (Q(ads)), is defined that cor responds to the mass transfer coefficient when the surface pollutant concen tration is zero. Modeling and experimental verification of adsorption were done, demonstrating the pollutant concentration decrease caused by adsorptive build ing materials. The pollutant reduction phenomena were modeled, including polluta nt degradation by chemical reaction and adsorption in building materials. Adsorption tests of gypsum board containing a substance that decomposes HCHO w ithin the board2-60 are reported. The adsorption rate of the gypsum board pr edicted-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 Impr oved Model." AIHA

Journal 64 : 739–754. Understanding source behavior is important in controlling exposure to airborne contaminants. Industrial hygienists are often asked to inf er 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 wel l understood. This study compares emission estimates from the single-zone comp letely mixed (CM-1), two-zone completely mixed (CM-2), and uniform diffusivity (UD) models with the emissions set as boundary conditions in computation al fluid dynamic (CFD) simulations of a workplace. The room airflow and concent ration fields were computed using Fluent 4. These numerical experiments were f actorial combinations of three source locations, five receptor loc ations, three dilution airflow rates, and two generation rate profiles, consta nt and timevarying. The aim was to compute plausible concentration fields, not to s imulate exactly the processes in a real workroom. Thus, error is defined here as the difference between model and CFD predictions. For the steady-stat e case the UD model had

the lowest error. When the source near-field containe d the breathing zone receptor, the CM-2 model was applied. Then, in decreasing a greement with CFD were UD, CM-2, and CM-1. Averaging over all source and rec eptor 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 e ffects on emission estimates using the CM-1 model and some effect using the U D model. A locationspecific mixing factor (location factor) derived from st eady-state concentration gradients was used to build a more accurate time-dependent emission model, CML. Total mass emitted from a timevarying source was model ed most accurately by CM-L, followed by CM-1 and CM-2.2-61

Bi, X., G. Sheng, et al. (2005). "Gas- and particulate-phas e specific tracer and toxic organic compounds in environmental tobacco smoke." Chemosphe re 61 (10): 1512-22. Cigarette smoke constituents are worthy of concern and c haracterized as carcinogens. Different experiment conditions may affec t 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: nicot ine, 2,5- dimethylfuran and 3-ethenylpyridine (3-EP), 19 carbonyl compounds , 54 semivolatile compounds (24 polycyclic aromatic hydrocarbons (PA Hs) and 30 alkanes) as well as CO and total particulate matter (TP M) from 15 leading

commercial brands were determined. ETS constituents di d 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 com pared to other studies conducted in chamber, which resulted in 2-5 times lower. Be nzene, toluene, ethylbenzene, xylenes, acrolein, 2-butanone and the high mo lecular weight compounds exhibited little affect. Pearson correlation a nalyses show that gasphase and particulate-phase ETS tracers did not show signi ficant correlation, but within each homologue many of compounds correlated significa ntly. Indole and cholesta-3,5-diene were also detected in ETS. These resu lts may be useful in

efforts to better understand the health effect of ETS e xposure and source apportionment.

Brown, S. K. (1999). "Chamber assessment of formaldehyde a nd VOC emissions from wood-based panels." Indoor Air-International Journal of In door 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 environmen tal chambers, both small and room-sized. Characterisation of product e mission 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 deca y to the latter for2-62 several months. Long term emission behaviour could not be predicted from shortterm measurements. Volatile organic compounds (VOC) emis sions were low for the MDF product, higher for particleboard, and highest for laminated office furniture. The compounds emitted differed from those reporte d in other countries. VOC emissions from the sheet products decreased more quick ly than formaldehyde, reaching low levels within two weeks, except for MDF which was

found to become a low-level source of hexanal after s everal 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 assess ed in CSIRO’s Room Dynamic Environmental Chamber. This paper describes the cha mber assessment procedure and presents findings for major commercial heater s that are nominally ‘‘low-emission’’. The chamber was operated at controlled conditions of temperature, humidity, ventilation and air mixing, repres entative of those encountered in typical indoor environments. A fixed rate of heat removal from the chamber air ensured that the heaters operated at constan t 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 w ere 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 b ecoming significant to indoor air quality). When operated with low line pressure o r slight misalignment of the gas burner, this heater became a hazardous source of these pollutants. Emissions from the heaters changed little after contin uous operation for up to 2

months.

Budaiwi, I. M. and M. S. Al-Homoud (2001). "Effect of ventil ation strategies on air contaminant concentrations and energy consumption in bu ildings." International Journal of Energy Research 25 (12): 1073-1089.2-63 Considering the diversity of indoor contaminant character istics and generation patterns, finding an appropriate ventilation strategy that c an secure acceptable indoor air quality with minimum energy consumption is a challenging task for HVAC system designers and operators. This study theoreti cally models and investigates the impact of various ventilation strategies on contaminant concentration behaviour and corresponding ventilation coo ling energy requirements for a single-zone enclosure. Two types of contaminants are considered; carbon dioxide as an occupancy dependent and forma ldehyde, which is independent of occupancy. An airflow model is used to pre dict space pressure and air leakage rates across the enclosure envelope, and an air quality model is used to predict time-varying contaminant concentrations. I n addition, a building energy simulation model is utilized to predict the corres ponding ventilation cooling energy requirements under hot climatic conditions . Results from this study show that acceptable contaminant concentrations duri ng occupied periods can be achieved by different ventilation strategies but at substantially different ventilation energy requirements. More than 50 per cent r eduction in ventilation energy requirements can be obtained while maintaining acce ptable IAQ if proper ventilation strategy is employed. Copyright (C) 2001 Joh n Wiley & Sons, Ltd.

Buyuksari, U., N. Ayrilmis, et al. (2010). "Evaluation of the physical, mechanical properties and formaldehyde emission of particleboard manu factured from waste stone pine (Pinus pinea L.) cones " Bioresource Technology 101 (1): 255-259 The objective of this study was to investigate some physic al/mechanical properties and formaldehyde emission of particleboard cont aining particles of waste stone pine cone at various usage ratios using urea–f ormaldehyde resin. Some physical (thickness swelling, water absorption), me chanical (modulus of elasticity, modulus of rupture, internal bond strength) properties and formaldehyde emission of particleboards were evaluated. T he addition of cone particle improved water resistance of the panels and greatl y reduced their formaldehyde emissions. However, flexural properties and internal bond strength decreased with increasing cone particle content in the pan el. The cone of the stone pine can be considered as an alternative to wood materi al in the manufacture of2-64 particleboard used in indoor environment due to lower thickness swelling, water absorption and formaldehyde emission.

Carslaw, N. (2007). "A new detailed chemical model for in door 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. Unli ke previous modelling studies of indoor air chemistry, the mechanism adopted con tains no simplifications such as lumping or the use of surrogate spe cies, 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 spe cies. 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 typicall y observed outdoors and sufficient for significant chemical cycling to take pla ce. Concentrations of PANtype species and organic nitrates are found to be important i ndoors, reaching concentrations of a few ppb. Sensitivity tests highlight t hat the most crucial parameters for modelling the concentration of OH are th e 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 pro ducing new radicals, unlike outdoors where photolysis reactions are pivotal radi cal initiators. In terms of radical propagation, the reaction of HO2 with NO has the most profound influence on OH concentrations indoors. Cycling between O H 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 import ance of tailoring a model for its particular location and the need for future indoor a ir measurements of radical species, nitrated species such as PANs and organic nitrates, photolysis rates of key species over the range of wavelengths obser ved indoors and2-65 concurrent measurements of outdoor air pollutant concentr ations. (c) 2006 Elsevier Ltd. All rights reserved.

Carter, R. D. and J. S. Zhang (2007). "Definition of Standa rd Office Environments for Evaluating the Impact of Office Furniture Emissions on In door 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 offi ce furniture surface area, and the outdoor, clean airflow rate is necessary to es timate the impact of office

furniture emissions on indoor VOC concentrations based on the emission rates measured from chamber tests. In this study, 31 randomly selec ted floor plans from North American office buildings were analyzed in deta il. The floor plans were from projects in late 2004 and early 2005 and were provided by an i ndustry cross section of seven major office furniture manufacturers. The analysis included documenting the potential emitting surf ace area for

each workstation and a determination of how much common office space (aisles, etc.) was present and shared between workstations and ot her adjoining spaces. The 90th percentile conditions for total furniture surface area within the 50th percentile workstation footprint sizes were identified f rom 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-ca se” standard open plan office environment for a single workstation system is de fined as 5.94 m2 (64 ft2) floor area by 2.74 m (9 ft) high (576 ft3 or 16.3 m3), accounting f or a standard 1.83 m × 1.83 m (6 ft × 6 ft) open plan workstation system, tr affic 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 a ir 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 envir onment 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 spac e for shared copiers, files,2-66 storage, etc. The space is assumed to be occupied by a singl e occupant and has an outdoor or clean air ventilation rate of 9.63 L/s (20.4 cf m) 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). "Characterizat ion 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 vola tile organic compound (VOC) latex paint applied to gypsum board were measured and analyzed by small

environmental chamber tests. It was found that the formalde hyde 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 chambe r data. The model characterized the formaldehyde emissions from the paint i n three stages: an initial "puff" of instant release, a fast decay, and a final sta ge of slow decay controlled by a solid-phase diffusion process that can last for mo re 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 inve stigated by comparing emission patterns and modeling outcomes of differ ent paint formulations. The biocide used to preserve the paint was found to be a major source of the formaldehyde. Chamber test results demonstrat ed that replacing the preservative with a different biocide for the particul ar 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 measur ements 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 sim ulated kitchen environment. Combustion products from unflued combustion from a gas cook-top in a ventilated room were measured using an extractive FTI R technique. Results were compared with those from conventional instruments a nd the FTIR technique2-67 was shown to give good agreement. Detection limits and th e effect of H2O and CO2 in obscuring the spectrum were studied, in addition, C omputational Fluid Dynamics (CFD) was used to explore the conditions in t he room and to assist with experimental design. This revealed a complex flow situat ion that can arise when the plume from the cook top interacts with the extract ion hood. (C) 2001 Elsevier Science Ltd. All rights reserved.

Choi, D. W., K. W. Moon, et al. (2009). "Indoor Volatile Or ganic Compounds in Atopy

Patients' Houses in South Korea." Indoor and Built Enviro nment 18 (2): 144-154. This study was undertaken to determine the concentrations of volatile organic compounds (VOCs) in the indoor air of atopy patients' (at opic dermatitis 50, allergic asthma 36) and control houses (28 nonpatients). A goal of this study was also to investigate whether indoor VOCs were risk facto rs for the development of atopic sensitization. Eleven alkanes, 13 aromatics, 7 chlo rinated 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 conce ntrations of total VOC (TVOC) in indoor air in atopic dermatitis and allerg ic asthma patients' houses were 317.1 and 219.2 mu g.m(-3), respectively. However, TV OC concentrations did not differ significantly between con trol and patient houses in indoor and outdoor air. The geometric mean concentrations of benzene, ethylbenzene (p < 0.05), o-xylene, m-, p-xylene, styrene, l evels 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 sig nificantly higher than those in control houses. The multiple linear regressio n 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 wit h higher concentrations of formaldehyde. Limonene and alpha-pinen e concentrations were significantly increased by the replacement of furniture an d the use of cleaning products. The type of heating system was significantly as sociated with indoor benzene, toluene, ethylbenzene, nonane, decane, and undecan e concentrations in2-68 atopy patient houses.

Clarisse, B., A. M. Laurent, et al. (2003). "Indoor aldehydes: measurement of

contamination levels and identification of their determ inants in Paris dwellings."

Environmental Research 92 (3): 245-253. The recent increased prevalence of childhood asthma an d atopy has brought into question the impact of outdoor pollutants and indoor air qua lity. The contributory role of aldehydes to this problem and the fact that they a re 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 determinant s. The study was carried out in the three principal rooms of 61 flats with no pr evious 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 w as filled out at the same time. A multiple linear regression model was used t o investigate indoor aldehyde determinants. Our study revealed that propionaldehyde an d benzaldehyde were of minor importance compared to forma ldehyde, acetaldehyde, pentanal, and hexanal. We found that levels o f 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 re served.

Daisey, J. M., K. R. R. Mahanama, et al. (1998). "Toxic volatile organic compounds in

simulated environmental tobacco smoke: Emission factors f or exposure assessment." Journal of Exposure Analysis and Environmental Epidemiology 8 (3): 313-334. Environmental tobacco smoke (ETS) is suspected to be a maj or source of exposure to many of the compounds identified as toxic air con taminants. However, we lack emission factors for many of the ETS air toxics for the brands of cigarettes which currently dominate the market and ther efore cannot adequately estimate contributions of ETS to such exposures. This study provides up-to-date2-69 emission factors for Selected air toxics and other vola tile 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 a nd, therefore to indoor exposures to air toxics. Emission factors (mu g/cigarette) were determined for 21 VOCs (including two aldehydes), nicotine and particulate matter i n a room-sized (20- m(3)) environmental chamber with stainless-steel walls, o perated under static conditions, using diluted sidestream smoke (no exhaled mainst ream smoke) to simulate ETS. Experiments were conducted for Kentucky R eference cigarette 1R4F and for each of six commercial cigarette brands wit h major market shares. The variabilities in the ETS emission factors among br ands of cigarettes were relatively small, ranging from 16 to 31% (expressed as the c oefficient of variation) among the six brands.

The concentrations of most of the VOCs did not chan ge over the 4-hour periods of the experiments. However concentrations of 3 -ethenylpyridine, phenol, o-cresol and m,p-cresol showed consistent decreases ove r time, indicating removal by means other than the very low air infiltrat ion rate (0.03 h(-1)), e.g., deposition onto the chamber surfaces. Emission factors f or these compounds were

calculated to take these losses into account and the rat e constants for these losses

were estimated. To estimate indoor concentrations and inhalation exposure s to 16 VOCs, nicotine and PM-2.5, the average emission factors for th e 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 con centrations, indicating that ETS can be a significant contributor to the total indoor concentration and the inhalation exposure for these spec ies. At higher smoking rates, exposures To VOCs from ETS could be several time s higher than those modeled under more "typical" conditions.

de Bruin, Y. B., K. Koistinen, et al. (2008). "Character isation of urban inhalation2-70

exposures to benzene, formaldehyde and acetaldehyde in the Eur opean Union."

Environmental Science and Pollution Research 15 (5): 417-430. Background, aim and scope All across Europe, people live and w ork in indoor environments. On average, people spend around 90% of their tim e indoors (homes, workplaces, cars and public transport means, etc.) and are exposed to a complex mixture of pollutants at concentration levels t hat are often several times higher than outdoors. These pollutants are emitted by diffe rent sources indoors and outdoors and include volatile organic compounds (VOCs), car bonyls (aldehydes and ketones) and other chemical substances ofte n adsorbed on particles. Moreover, legal obligations opposed by legislati ons, such as the European Union's General Product Safety Directive (GPSD) a nd Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), increasingly require detailed understanding of where and how chemical s ubstances are used throughout their life-cycle and require better characte risation 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 qua ntitative 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 re sults 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 cumulativ e frequency distributions were created. Population exposures were modelled with a microenvironment model using the time spent and concentrations in four mic roenvironments, i.e. indoors at home and at work, outdoors at work and in trans it, as input parameters. Pooled EU city inhalation exposures were compared to modelled population exposures. The contributions of these microenvironments t o the total daily2-71 inhalation exposure of formaldehyde, benzene and acetaldehyde w ere 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 recommende d (based on the INDEX project) 30-min average formaldehyde limit va lue (30 mu g/m(3)). Results Indoor inhalation exposure contributions are much higher compared to the outdoor or in-transit microenvironment co ntributions, accounting for almost 99% in the case of formaldehyde. The highest i n-transit exposure contribution was found for benzene; 29.4% of the total inhal ation exposure contribution. Comparing the pooled AIRMEX EU city inhalatio n 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 t ime 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 chal lenges concerning exposure and time-activity data, comparability and scarce or missing in-transit data inducing careful interpretation of the res ults. The results obtained by AIRMEX underline that many European urban populations are s till 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 m u 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 rat her than to inhalation. Conclusions In the present study, inhalation exposures o f urban populations were assessed on the basis of novel and existi ng exposure data. The

indoor residential microenvironment contributed most to the total daily urban population inhalation exposure. The results presented in thi s paper suggest that a significant part of the populations living in European citie s exceed the annual ambient benzene air quality guideline of 5 mu g/m(3) in the E U and recommended (INDEX project) formaldehyde 30-min average limit value of 30 mu g/m(3). Recommendations and perspectives To reduce exposures and c onsequent2-72 health effects, adequate measures must be taken to dimini sh emissions from sources such as materials and products that especially emi t benzene and formaldehyde in indoor air. In parallel, measures can be taken aiming at reducing the outdoor pollution contribution indoors. Besides emi ssion reduction, mechanisms to effectively monitor and manage the indoor a ir 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). "Mode l Development and Validation of Personal Exposure to Volatile Organic Compound Concentr ations." Environmental Health Perspectives 117 (10): 1571-1579. Direct measurement of exposure to volatile organic compo unds (VOCs) via personal monitoring is the most accurate exposure assessm ent method available. However, its wide-scale application to evaluating exposur es at the population level is prohibitive in terms of both cost and time. Con sequently, indirect

measurements via a combination of microenvironment concent rations and personal activity diaries represent a potentially useful alternative. Objective: The aim of this study was to optimize a m odel 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 con centrations were collected with active samplers and sorbent tubes . Data were supplemented with information collected through questionnaires. Seven m odels 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 independe nce of measurements was based upon stratified microenvironment con centrations, 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 t he 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 concentrati on of dozens of volatile organic compounds (VOCs) at 10 locations within a single la rge building and track these concentrations over a 2-year period. The s tudy 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 t o 55,100 mu g/m(3) were measured for individual VOCs. The indoor/outdoo r 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 prese nt. A large degree of spatial variability was observed between stores within th e 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 v ariability 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 character istics and indoor concentrations of nitrogen dioxide and formaldehyde in Quebec C ity, Canada."

Environmental Research 102 (1): 1-8. Concentrations of nitrogen dioxide and formaldehyde were det ermined in a study of 96 homes in Quebec City, Canada, between January and Apri l 2005. In addition, relative humidity, temperature, and air change rates were measured in homes, and housing characteristics were documented through a questionnaire to2-74 occupants. Half of the homes had ventilation rates bel ow 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 v ariance of NO2 and formaldehyde. NO2 concentrations in homes were positivel y correlated with air change rates (indicating a significant contribution of outdoor sources to indoor levels) and were significantly elevated in homes equippe d with gas stoves and, to a lesser extent, in homes with gas heating systems. F ormaldehyde concentrations were negatively correlated with air change rates and wer e 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 w here painting or varnishing had been done in the sampled room in the previous 12 months. Results did not indicate any significant contribution of indoor c ombustion sources, including wood-burning appliances, to indoor levels of formaldehyd e. These results suggest that formaldehyde concentrations in Quebec City homes are caused primarily by off-gassing, and that increasing air ch ange rates in homes could reduce exposure to this compound. More generally, our fi ndings confirm the influence of housing characteristics on indoor concent rations of NO2 and formaldehyde. Crown Copyright (c) 2006 Published by Elsevier In c. All rights

reserved.

Gilbert, N. L., M. Guay, et al. (2008). "Air change rate a nd concentration of formaldehyde in residential indoor air." Atmospheric Envir onment 42 (10): 2424-2428. The purpose of this study was to investigate the relations hip between air change rates and indoor concentrations of formaldehyde. Concent rations 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 re gressed to air change rates among the entire sample and among some sub-sampl es of homes, and predictive intervals were computed. The air change rate ensuring a formaldehyde concentration below Health Canada's guideline value of 50 m u g m(-3) in 95% of2-75 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 h eated mainly by

electrical baseboard heaters. These results indicate that ventilation effectively decreases formaldehyde concentrations, but some categori es of homes such as those with new off-gassing sources and homes heated by elec trical baseboard heaters may require a higher air change rate to keep the ir formaldehyde levels within Health Canada's guidelines. (c) 2008 Elsevier Ltd. All rights reserved.

Gilbert, N. L., M. Guay, et al. (2005). "Levels and determi nants of formaldehyde, acetaldehyde, and acrolein in residential indoor air in Pr ince 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 hous ing characteristics. Concentrations of formaldehyde, acetaldehyde, and acrolein were measured in 59 homes in Prince Edward Island, Canada, during the winter o f 2002. Housing characteristics were documented through inspection and by i nterviews of occupants. Formaldehyde, acetaldehyde, and acrolein concent rations 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 i n 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 correlat ed with absolute humidity and carbon dioxide, two variables likely to be surrogates for lower air exchange rates. In conclusion, lower air exchange rate s appear to be important determinants of formaldehyde, acetaldehyde, and acrolein leve ls in homes. These data also confirm that smoking is a significant source o f 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 Sci ence & Technology 34 (10):2-76

2051-2056. An existing Ferm type passive sampler technique has been furt her 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 concent ration is determined by high performance liquid chromatography. The technique has been Validated against an active sampling method, and the agreement is cl ose when the appropriate laminar boundary layer depth is applied to the pa ssive measurement. For this technique an exposure period of 3 days is equivalent t o a limit of detection of formaldehyde of 3.4 ppbv and a limit of quantific ation of 7.6 ppbv. To test the performance of the passive samplers ambient formaldehyde

measurements were carried out inside homes and in a ran ge 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 conc entrations 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 resea rch by the Environmental Protection Agency (EPA), is a tool for making home projec tions of formaldehyde concentrations. The model, based on mass balance princi ples, can accommodate input information from up to six formaldehyde sources. Labora tory data were available characterizing emission characteristics of f our primary wood product formaldehyde sources used in an EPA and Composite Panel As sociation (CPA) home study project. Using product source inputs, Versar init ial 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 volati le organic compounds in Hong Kong homes: concentrations and impact factors." Indoo r Air 19 (3): 206-217. This paper presents formaldehyde and volatile organic compo unds (VOC) concentrations, potential sources and impact factors in 100 homes. The 24-h average formaldehyde concentration in 37 homes exceeded th e good class of the Hong Kong Indoor Air Quality Objectives (HKIAQO), whereas the total VOCs concentration in all homes was lower than the HKIAQ O. 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 affec ted by household products and materials. The formaldehyde concentration in newly built apartments was significantly higher than that in old bui ldings, whereas no relationship between the concentration and the buildin g age was found for VOCs. There was no difference for formaldehyde and toluene be tween smoking and nonsmoking homes, suggesting that cigarette smoking was not t he major source of these two species. Homes of a couple with a child had high er formaldehyde and acetic acid concentrations, while homes with more tha n three people had higher concentrations of 1-butanol, heptane and d-limonene. When shoes were inside the homes, heptane, acetic acid, nonane and styrene concent rations were statistically higher than that when shoes were out of the homes. F urthermore, higher levels of 1,2,4-trimethylbenzene, styrene, nonane and heptane were foun d in gas-use families rather than in electricity-use homes.Long-te rm exposure to formaldehyde and volatile organic compounds (VOC) in indoor environments m ay cause a number of adverse health effects such as asthma, dizzine ss, respiratory and lung diseases, and even cancers. Therefore, it is critica l to minimize indoor air pollution caused by formaldehyde and VOCs. The findings obta ined in this study would significantly enhance our understanding on the levels, emission sources

and factors which affect indoor concentrations of formal dehyde and VOCs. The results can help housing designers, builders, home residen ts, 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 objective s 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 occupant s completed health questionnaires. Formaldehyde concentrations ranged from les s than 0.10 to 0.80 ppm, with the risk of ocular discomfort showing a posit ive dose-response relationship.

Hawthorne, A. R. and T. G. Matthews (1987). "Models for E stimating Organic Emissions from Building-Materials - Formaldehyde Example." Atmosph eric 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 materi als. Because removal of offending products may be costly or otherwise impractical , it is important that the emissions of organic pollutants be understood prior to inco rporation of these materials into buildings. Once the organic pollutants of co ncern 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' characte ristic source strengths at standard test conditions, impact of variations in envir onmental conditions (such as temperature and humidity), concentrations of the mode led organic pollutants in indoor environments and product ages. Ideally, emission models should have physical/chemical bases so that the important physical fa ctors 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 material s in use, the most studied of the volatile organic compounds from building mater ials, formaldehyde, is used to illustrate an approach to the development of a s pecific model for2-79 organic emissions.

Hayashi, M., M. Enai, et al. (2001). "Annual characteristi cs of ventilation and indoor air quality in detached houses using a simulation method with Ja panese daily schedule model." Building and Environment 36 (6): 721-731. This paper presents the results of investigations that we re made on a simulation program, which calculates the temperature, the heat loa ds, 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 inve stigation, the concentrations of carbon dioxide, carbon monoxide and formaldehyde are r egarded 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 pas sive 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 in door 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 conditione d, and that indoor air quality in the rooms on the first floor differs fro m that on the second floor. Lastly, the performance of the ventilation systems a nd the solution methods of realizing these ventilation systems were discussed on t he basis of the results of the simulation. (C) 2001 Elsevier Science Ltd. All rights rese rved.

Hayashi, M. and H. Osawa (2008). "The influence of the conc ealed pollution sources upon the indoor air quality in houses." Building and Environmen t 43 (3): 329-336. This report presents the results of investigations on t he indoor air quality of common Japanese detached houses. It is necessary to cont rol the emission rates

from the interior materials and the ventilation rate s 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 indo or air quality in some kinds of building structures and some kinds of ventilation s ystems. In this study the influences of the concealed pollution sources upon the indoor concentrations2-80 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 infiltrati on ratios: the ratios of the infiltration rate to the indoor space toward the emissio n rate of a pollutant in the concealed space were measured using the tracer-gas method. T he ratios from the beam spaces and the partition were about 100% in most case s. 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 c ases, because those spaces have ventilation openings. But the ratio from the craw l space reached about 100% in the house without ventilation openings at the crawl spa ce. And even in the house with ventilation openings at crawl space, the rati o reached 50% in the house with the exhaust-ventilation system. Therefore, it be came clear that the use of the medicine to prevent the deterioration of the wooden struct ure and the white ants in the crawl spaces must be limited. The ratio from t he envelope wall was changed with the pressure difference between inside and o utside. These results showed that it is necessary to prevent infiltration fro m 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 o ccupancy and of symptoms of sick building syndrome (SBS) is discussed in order to de monstrate the problem of indoor air quality (IAQ) in low-density built environme nts. Since the1970s energy efficient and/or high-rise buildings have been as sociated 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 pollutan ts, the key factors are in fact duration of exposure time to them and their concentr ation levels. Therefore to look at these factors as potential environmental causes o f adverse health effects,2-81 user activities in a low-density residential environment w ere 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 ass ociated with IAQ even in a low-density context.

Hodgson, A. T., D. Beal, et al. (2002). "Sources of forma ldehyde, other aldehydes and terpenes in a new manufactured house." Indoor Air 12 (4): 235-242. Formaldehyde, less volatile aldehydes, and terpene hydrocar bons are generally the predominant air contaminants in new manufactured and s ite-built houses. This study was conducted to identify the major sources of these compounds in a typically constructed, new manufactured house and to eva luate several source reduction practices. Specimens of materials used within the house were collected. These were individually pre-conditioned for 19+/-4 days, an d tested for emissions of formaldehyde and other target compounds using small-scale chambers. Several cabinetry materials, passage doors, and the plywood subfloor w ere the predominant sources of formaldehyde and other aldehydes. The p lywood 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 w ith whole-house

emission rates derived from measurements made at the ho use 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 emiss ion barriers applied to plywood were shown to reduce emission factors for for maldehyde, hexanal, and other aldehydes.

Hodgson, A. T., J. M. Daisey, et al. (1996). "Use of volat ile tracers to determine the

contribution of environmental tobacco smoke to concentrat ions of volatile organic compounds in smoking environments." Environment Internationa l 22 (3): 295-307. Three volatile nitrogen-containing compounds, 3-ethenylpyrid ine (3-EP), pyridine and pyrrole, were investigated as potential tracers for de termining the contribution of environmental tobacco smoke (ETS) to concentrations o f volatile organic2-82 compounds (VOCs) in indoor environments with smoking. The source emission

rates of the three tracers and ten selected VOCs in E TS were first measured in a room-size environmental chamber for a market-weighted sele ction of six commercial cigarettes. The ratios of the emission ra tes of the tracers to the

emission rates of the selected VOCs were calculated a nd compared among the six brands. The utility of the tracers was then evaluated i n 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 w ere measured, and smoking rates were documented. Concentrations of the t hree tracers in the smoking areas were calculated using a mass-balance model and compared to their measured concentrations. Based on this comparison, 3-EP w as selected as the most suitable tracer for the volatile components of E TS, although pyrrole is also potentially useful. Using 3-EP as the tracer, the contrib utions of ETS to the

measured concentrations of the selected VOCs in the smo king 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 t o 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-limone ne were all less than

50%.

Hodgson, A. T., A. F. Rudd, et al. (2000). "Volatile organic c ompound concentrations

and emission rates in new manufactured and site-built ho uses." 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 mont hs following

installation and in seven new site-built houses 1-2 month s after completion. The houses were in four projects located in hot-humid and mixe d-humid climates. They were finished and operational, but unoccupied. Ventilation rates ranged from 0.14-0.78 h(-1). Several of t he site-built

houses had ventilation rates below the ASHRAE recomme nded value. In both2-83 manufactured and site-built houses, the predominant airbor ne compounds were alpha-pinene, formaldehyde, hexanal, and acetic acid. Fo rmaldehyde 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 impact ed 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 vent ilation rates of 0.14 and 0.32 h(-1). VOC emission rates calculated at the two con ditions agreed within +/- 10% for the most volatile compounds. Generally, the ratio s of emission rates at the low and high ventilation rates decreased with decrea sing compound volatility. Changes in VOC emission rates in the manufactured houses over 2-9.5 months after installation varied by compound. Only several compoun ds showed a consistent decrease in emission rate over this period.

Hodgson, A. T., D. G. Shendell, et al. (2004). "Comparison o f predicted and derived measures of volatile organic compounds inside four new reloc atable classrooms." Indoor

Air 14 : 135-144. Our objective was to develop a process for selecting inte rior finish materials having low impacts with respect to emissions of toxic and o dorous volatile organic compounds (VOCs) for school relocatable classroo ms (RCs). A laboratory study identified alternate materials with low VOC emissions. Two pairs of RCs then were constructed. One RC per pair con tained 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 aceta te, phenol, toluene, and naphthalene, were measured during school hours over 8 weeks in the succeeding fall cooling season. Indoor minus outdoor VOC conc entrations with an advanced HVAC operated were low; only formaldehyde conc entrations exceeded 5 p.p.b. Classroom VOC concentrations were predict ed based on emission factors (mug/m(2)/h), material quantities and des ign ventilation rates. These were compared to average adjusted concentrations m easured when the occupied classrooms were operating at near the code-minimum ventilation rate.2-84 For 16 of the possible 42 comparisons, measured concentratio ns agreed within a factor of two of predicted the predicted values. Concent rations 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 C hamber." Journal of the Air & Waste Management Association 43 (3): 316-324. This study was undertaken to quantify the emissions of vo latile organic compounds (VOCs) released by new carpets. Samples of four typical carpets, including two with styrene-butadiene rubber (SBR) latex adhe sive and two with different backings, were collected from the finish line s at manufacturers' mills. Individual VOCs released from these samples were identi fied, and their concentrations, emission rates and mass emissions wer e measured under

simulated indoor conditions in a 20 m3 environmental chamber over one week periods. Concentrations and emission rates of VOCs emit ted 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 car pet'' odor, and styrene. The concentrations and emission rates of 4-P CH were similar for the two carpets, while the styrene values varied significantly. The carpet with a polyvinyl chloride backing emitted formaldehyde, vinyl acetate, isoocta ne, 1,2-propanediol, and 2-ethyl-1-hexanol. Of these, vinyl acetate and propanedi ol had the highest concentrations an emission rates. The carpet with a p olyurethane backing primarily emitted butylated hydroxytoluene. With the excepti on of formaldehyde,

little is known about the health effects of these VO Cs 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 emi ssions from conversion varnishes." Journal of the Air & Waste Management Ass ociation 48 (10): 924-930.2-85

Conversion varnishes are two-component, acid-catalyzed v arnishes that are commonly used to finish cabinets. They are valued for the ir water and stain resistance, as well as their appearance. They have bee n found, however, to contribute to indoor emissions of organic compounds. For this project, three commercially available conversion varnish systems wer e selected. A U.S. Environmental Protection Agency (EPA) Method 24 analysis wa s performed to determine total volatile content, and a sodium sulfite t itration method was used to determine uncombined (free) formaldehyde content of the varnish components. The resin component was also analyzed by gas chromatogr aphy/mass spectroscopy (GC/MS) (EPA Method 311 with an MS detector) to identify individual organic compounds. Dynamic small chamber tests we re then performed to identify and quantify emissions following appli cation to coupons of typical kitchen cabinet wood substrates, during both curing a nd aging. Because conversion varnishes cure by chemical reaction, the com pounds 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 forma ldehyde emitted from these coatings was 2.3-8.1 times the amount of free form aldehyde applied in the coatings. A long-term test showed a formaldehyde emissio n 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 Monit oring 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 strat egy and monitoring plan. In Hong Kong, the Environmental Protection Departmen t (HKEPD) launched an Indoor Air Quality (IAQ) certification sche me to grade workplace IAQ as 'Excellent' or 'Good' by measuring the levels of ni ne 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 offi ce IAQ performance2-86 has been improved since the implementation of this cert ification scheme, there are

still resource issues and technical difficulties. To stre amline the assessment of office IAQ performance, this study proposes a simple in dex of IAQ benchmarks formulated in compliance with the HKEPD requirements. In particular, three of the nine listed common air pollutants were selected as th e 'representatives' for the overall satisfactory IAQ. Together with the assessme nt results of 422 Hong Kong air-conditioned offices, the index was evaluated in ter ms 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 I AQ performance in offices and to make decisions on resources and manpower m anagement for efficient mitigation actions.

Kelly, T. (1996). Determination of Formaldehyde and Toluene D iisocyanate Emissions from Indoor Residential Sources. Sacramento, CA, Cali fornia Air Resources Board : 93-

315. Building materials and consumer products found in California residences were subjected to chamber testing to determine the emission rat es of formaldehyde (HCHO) and of Toluene DiIsocyanates (TDI). The emissi ons of formaldehyde were determined from bare Urea-Formaldehyde (UF) and Phen ol-Formaldehye (PF) wood products, with vinyl, paper, and other coatings, and fr om decorative laminates, permanent press fabrics fiberglass insulation, paper goods, paints, cosmetics, and acid-cured coatings. Other compounds determi ned along with HCHO included acetaldehyde, propionaldehyde, methyl ethyl keton e (MEK), and Methyl IsoButyl Ketone (MIBK). A separate set of PolyU rethane (PU) products, including PU foam carpet padding, furniture cushions, sheet foam , PU varnishes, caulks and sealants, and a commercially-applied water s top product for concrete, were tested for emissions of toluene diisocyanate (TDI)

.

Khoder, M. I., A. A. Shakour, et al. (2000). "Indoor and outd oor formaldehyde

concentrations in homes in residential areas in Great er Cairo." Journal of Environmental Monitoring 2 (2): 123-126.2-87

Indoor and outdoor measurements of formaldehyde were con ducted at seven flats located in residential areas in Greater Cairo, during spr ing and summer seasons 1999. The mean daytime formaldehyde concentrations in kitch ens, bedrooms and living rooms were 89, 100 and 100 ppb, respectively, in the seven fl ats. Significant positive correlations were found between the concentrations of formaldehyde found in these three rooms. On the other han d, no significant differences were found between the mean formaldehyde co ncentrations in these

three rooms. The maximum mean concentration of formal dehyde (147 ppb) was recorded in a new flat, while the minimum concentratio n (43 ppb) was observed in an old flat. The maximum hourly and daytime concentra tions were 350 and 225 ppb, respectively. Air temperature, relative humidity and the age of the flat are factors affecting the emission and concentration of f ormaldehyde. The maximum indoor and outdoor formaldehyde concentrations were recorded dur ing the summer season. During the spring, 38% of the samples indic ated that the concentration of formaldehyde in the seven flats exceede d 0.1 ppm, the American Society of Heating, Refrigerating, and Air Conditioning E ngineers' (ASHRAE) standard; in the summer, this figure increased to 53%.

Kim, S. and H. J. Kim (2005). "Comparison of formaldehyde em ission from building finishing materials at various temperatures in under heatin g system; ONDOL." Indoor

Air 15 (5): 317-325. The objective of this research was to investigate the ef fect of various temperatures, room, 37 and 50 degrees C, on formaldehyde emissio n from floor materials, such as laminate and plywood floorings, and furniture materials, such as MDF and particleboard veneered with decorative paper foi l, by desiccator's method. The temperature conditions were set up by, measuri ng 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 ab out 37 degrees C and the temperature of the cement mortar was 50 degrees C. The i nitial 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, respec tively. Floor materials were under E1 grade while furniture materials we re under E-2 grade in2-88 terms of formaldehyde emission. Because of the under heati ng 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 de grees C, the formaldehyde emission level of the flooring materials w as already under 0.3 ppm (F star star star star level by JIS A 1460, application po ssibility 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 furnitur e materials such as MDF and particleboard. As these materials are not expos ed 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 ev en after 28 days. Although there will be variations with the volume of f urniture materials and the indoor conditions, furniture materials are the principal c ause of indoor air quality pollution in Korean with the under heating system.

Kirkeskov, L., T. Witterseh, et al. (2009). "Health evalua tion of volatile organic compound (VOC) emission from exotic wood products." Indoor Ai r 19 (1): 45-57. The purpose of this study was to measure and evaluate the i mpact of the emissions of selected products of exotic wood on health. Ten products were screened for chemical compounds, and five of the most use d products which emitted more than 800 mu g/kg were selected for further quantit ative analyses by climate chamber measurement (iroko, ramin, sheesham, m erbau, and rubber tree). Samples of exotic wood (rubber tree and belalu) were f urther analyzed for emission of chemical compounds by migration into artific ial 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 unpro blematic as regards health). Emission from the evaluated exotic wood only too k place to a very limited extent. None of the selected products, under the c hosen rating system, is likely to cause adverse health effects. Products with surf ace treatment might pose a problem if used as kitchen utensils, as children's toys, o r when they are in close2-89 contact with the skin for a long time.The authors inves tigated the chemical emissions from selected products from exotic wood by clim ate chamber measurement. Quantitative chemical analyses of emissio ns from the five most used exotic products in Denmark were performed, and all chemic al 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 an d determination of formaldehyde in indoor air with solid-phase microextraction and on-f iber derivatization." Environmental Science & Technology 35 (7): 1481-1486. A new sampling and analysis method for formaldehyde in indo or air was tested in several indoor air surveys. The method was based on the us e of solid-phase microextraction (SPME) poly(dimethylsiloxane)/divinylbe nzene,65 mum fiber and gas chromatography. Indoor air surveys included grab and t ime-weighted average (TWA) sampling and were completed at six locatio ns using (a) the SPME method employing on-fiber formaldehyde derivatization with o-(2,3,4,5,6- pentafluorobenzyl)hydroxylamine hydrochloride and (b)the conventi onal National Institute for Occupational Safety and Health (NIOSH) 2451 m ethod. 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 conce ntrations 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 som e cases the formaldehyde

concentrations measured in residential air could be much higher than those allowed in occupational settings. The SPME method proved t o be accurate, fast, sensitive, and cost-efficient in field sampling applicati ons. This research should be of interest to research, industrial, and regulatory agencies as well as to the general public concerned with indoor air quality. Introducti on

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 cei ling fans ventilated, were chosen for investigation of indoor and outdoor air quali ty. Parameters such as temperature, relative humidity (RH), carbon dioxide (CO2), sulphur dioxide (SO2), nitric oxide (NO), nitrogen dioxide (NO2), respirable pa rticulate matter (PM10), formaldehyde (HCHO), and total bacteria counts were monitored indoors and outdoors simultaneously. The average respirable particula te matter concentrations were higher than the HK Objective, and t he maximum indoor PM10 level exceeded 1000 mu g/m(3). Indoor CO2 concentrations oft en exceeded 1000 mu l/l in air-conditioning and ceiling fan classro oms, indicating inadequate ventilation. Maximum indoor CO2 level reached 5900 m u l/l during class at the classroom with cooling tower ventilatio n. Increasing the rate of ventilation or implementation of breaks between clas ses is recommended to alleviate the high CO2 level. Other pollution parameters measured in this study complied with the standards. The two most important cla ssroom air quality problems in Hong Kong were PM10 and CO2 levels. (C) 2000 Elsevie r Science Ltd. All rights reserved.

Lee, S. C., H. Guo, et al. (2002). "Inter-comparison of a ir pollutant concentrations in different indoor environments in Hong Kong." Atmospheric Environment 36 (12): 1929-

1940. Indoor air quality in selected indoor environments in Hong K ong such as homes, offices, schools, shopping malls and restaurants were i nvestigated. Average CO2

levels and total bacteria counts in air-conditioned clas srooms, shopping malls and restaurants were comparatively higher than those measur ed in occupied offices and homes. Elevated CO, levels exceeding 1000ppm and total bacte ria counts resulted from high occupancy combined with inadequate ventila tion. Average PM10 levels were usually higher indoors than outdoors in ho mes, shopping malls and restaurants. The highest indoor PM10 levels were obser ved at investigated restaurants due to the presence of cigarette smoking and ext ensive use of gas stoves for cooking. The restaurants and shopping malls inves tigated had higher formaldehyde levels than other indoor environments when b uilding material, smoking and internal renovation work were present. Volat ile organic compounds2-91 (VOCs) in both indoor and outdoor environments mainly re sulted from vehicle

exhaust emissions. It was observed that interior decor ation work and the use of industrial solvents in an indoor environment could significant ly increase the indoor levels of VOCs. (C) 2002 Published by Elsevier Science L td.

Lee, S. C. and B. Wang (2004). "Characteristics of emissi ons of air pollutants from burning of incense in a large environmental chamber." Atmosph eric Environment 38 (7):

941-951. The objective of this study was to characterize the em issions of air pollutants from incense burning in a large environmental test chamber. A ir pollutants emitted from ten types of commonly used incense manufac tured in different regions were compared. The target pollutants included part iculate matters (PM10, PM2.5), volatile organic compounds (VOCs), carbonyls, carbo n monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), methane (CH4) and non-methane hydrocarbon (NMHC). The particulate matters emitted fr om 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 wer e higher than the HKIAQO. The highest formaldehyde level exceeded the standa rd by 2 times. The results indicated that the concentrations of benzene, toluene, methyl chloride and methylene chloride significantly increased with the burning o f all incense tested. In addition, the benzene concentrations of all teste d incense were significantly higher than the HKIAQO standard. Although Incense 2 and 6 we re claimed to be environmental friendly, the quantity of the pollutants emi tted was not observed to

be lower than the others. It was observed that when c omparing 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 seque nce was

traditional incense > aromatic incense > church incense. The results show that2-92 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 o f living condition, decorating houses has been the hotspot of personal consu mption 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 conc entration in residential houses was conducted in Harbin, located at the most chilly area in

Northeast China. The results showed that the concent ration 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 aver age indoor formaldehyde concentration and the monthly average temperature (R2=0.8652) was obtained. Furthermore, a mathematical model was successfully devel oped to predict the concentration of indoor formaldehyde in Chinese residential houses. Field measurements of indoor formaldehyde concentration in res idential houses were

also conducted for various decoration time in order to inv estigate the influence of decoration time on the indoor formaldehyde concentration

.

Li, Y. Y., P. C. Wu, et al. (2002). Effects of HVAC vent ilation efficiency on the concentrations of formaldehyde and total volatile organic compounds in office buildings

. Indoor Air, California. Potential sources for emitting formaldehyde and volatile o rganic compounds are abundant in office buildings. Exposure to the above compoun ds may result in short-term, long-term, or carcinogenic effects at conce ntrations often measured. Our study conducts field measurements on six typical offic e buildings with2-93 different HVAC systems to evaluate the effects of ve ntilation efficiency on the concentration of formaldehyde and total volatile organic c ompounds (TVOC). Formaldehyde and TVOC concentrations were measured by con tinuous photoacoustic Multi-Gas monitor. The air-change rates were e stimated by tracer gas concentration decay method in every test space. Air Ex change Efficiency (AEE) and Effective Ventilation Rate (EACH) were also calc ulated to characterize the ventilation pattern and mixing factor. Our results show t hat the increase of effective ventilation could reduce formaldehyde and TVOC in office buildings . We therefore suggest that increasing ventilation efficie ncy 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 th e 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 an d boundary conditions. This includes the high cooling load used in Hong Kong. Sever al pollutants typically found in the office such as carbon dioxide a nd volatile organic compounds (VOCs) were investigated. The results indicate t hat 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 off ice. 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 effe ct 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. A ll rights reserved.

Lin, Z., T. T. Chow, et al. (2005). "Comparison of perfor mances of displacement and mixing ventilations. Part II: indoor air quality." Inter national Journal of Refrigeration-2-94

Revue Internationale Du Froid 28 (2): 288-305. A numerical simulation using a validated computational fl uid dynamics model is used to investigate and compare the performances of displa cement 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 ter ms of carbon monoxide, mean age of air and the three volatile organic compounds, toluene, benzene and formaldehyde, which are commonly found in indoor room furnish ings. The case studies include offices, classrooms, retail shops and indu strial workshops, under typical Hong Kong thermal boundary conditions. Compared wi th 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 suppl y 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 wer e measurements of carbon dioxide levels, mean age of air and 3 volatile organic com pounds (VOCs): toluene, benzene and formaldehyde. The change in supply te mperature from 19 degrees C to 22 degrees C was found to have no significant eff ect on the level and distribution of contaminants in the room. The DV syste m was found to operate satisfactorily under the range of supply temperatures studie d.

Lin, Z., T. T. Chow, et al. (2006). "Effects of headroom on the performance of the displacement ventilation system." Indoor and Built En vironment 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 di splacement ventilation (DV) system. Two different headroom heights in a space were simulated and2-95 compared. It was found that the effect of increased hea droom was to improve the thermal comfort of the indoor space. It was also conclude d that given the thermal boundary conditions commonly encountered and the typical l ow 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 ai r are presented. Critical health effects include sensory irritation and th e potential to induce tumors in the upper respiratory tract (the nasal region in rode nts and potentially the lungs of humans). The majority of the general population is e xposed to airborne concentrations of formaldehyde less than those typical ly associated with sensory irritation (i.e., 0.1 mg/m 3 ). Based primarily upon data de rived from laboratory studies, the inhalation of formaldehyde under conditions th at induce cytotoxicity and sustained regenerative proliferation within the resp iratory 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 si ngle-path modeling for the lower respiratory tract. The degree of confidence in th e underlying database and uncertainties in estimates of exposure and in character ization of hazard and dose response are delineated.

Liu, W., J. Zhang, et al. (2006). "Concentrations and sourc e characteristics of airborne carbonyl compounds measured outside urban residences." J Ai r Waste Manag Assoc2-96

56 (8): 1196-204. This paper presents the analysis of ambient air concent rations of 10 carbonyl compounds (aldehydes and ketones) measured in the yards of 87 r esidences in the city of Elizabeth, NJ, throughout 1999-2001. Most of these r esidences 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 carbo nyl compounds and could be as high as 60%. Photochemical activity, however, r esulted in a net loss for formaldehyde. The authors used stepwise multiple linear regression models to evaluate the impact of traffic sources and meteorologic al conditions on carbonyl concentrations using the data collected on colder days (wi th lower photochemical activities). They found that the concentrations of fo rmaldehyde, acetaldehyde, acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyox al, and methylglyoxal significantly decreased with increasing dista nce between a measured residence and one or more major roadways. They a lso found significant negative associations between concentrations for mos t of the measured carbonyl compounds and each of the following meteorological parame ters: 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 adv erse health effects. It is known that various sources of carbonyls a re often present inside

residences but little is known about their indoor source st rengths. In the present paper, we used a database established in the relationships of indoor, outdoor, and personal air (RIOPA) study to estimate indoor source str engths of 10 carbonyls

and outdoor contributions to measured indoor concentrations o f these carbonyls. We applied a mass balance model to analyze paired indoor and outdoor carbonyl concentrations simultaneously measured in 234 RIOPA homes. Among all the2-97 measured carbonyls, formaldehyde, and acetaldehyde had the stro ngest indoor source strengths with the estimated median values of 3.9 and 2.6 mg h(-1), respectively. Hexaldehyde also had large indoor source strength s 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 es timated 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) fo r benzaldehyde. Acrolein and crotonaldehyde had the weakest indoor source s trengths with no indoor sources detected in the majority of the RIOPA ho mes that were selected to have only nonsmoker residents. Consistent with the indoor source strength results,

our estimated outdoor contributions to indoor concentrati ons were low for formaldehyde. In contrast, more than 90% of the indoor c oncentrations for acrolein and crotonaldehyde were from outdoor sources. The outdoor contributions to indoor concentrations for acetone, propi onaldehyde, 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 Elsevi er Ltd. All rights

reserved.

Liu, W. L., J. F. Zhang, et al. (2003). "Mosquito coil emis sions and health implications." Environmental Health Perspectives 111 (12): 1454-1460. Burning mosquito cods indoors generates smoke that can cont rol mosquitoes effectively. This practice is currently used in numerous households in Asia, Africa, and South America. However, the smoke may con tain pollutants of health concern. We conducted the present study to characterize t he emissions from four common brands of mosquito coils from China and two commo n brands from Malaysia. We used mass balance equations to determine emis sion rates of fine particles (particulate matter < 2.5 pm in diameter; PM2. 5), polycyclic aromatic hydrocarbons (PAHs), aldehydes, and ketones. Having applied th ese measured emission rates to predict indoor concentrations under realistic room conditions, we found that pollutant concentrations resulting from bur ning mosquito coils could substantially exceed health-based air quality standa rds or guidelines. Under2-98 the same combustion conditions, the tested Malaysian m osquito coils generated more measured pollutants than did the tested Chinese mosquit o coils. We also identified a large suite of volatile organic compounds, includ ing carcinogens and suspected carcinogens, in the coil smoke. In a set of exp eriments conducted in a room, we examined the size distribution of particulate m atter 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 co ils 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 burni ng one coil can be as high as that released from burning 51 cigarettes.

Lu, H. X., S. Wen, et al. (2006). "Indoor and outdoor carbony l 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 com pounds and five BTEX (benzene, toluene, ethylbenzene and xylenes) were meas ured in four hospitals of Guangzhou from 2nd January to 20th March 2004. Sa mples were collected in five consecutive daytimes for each hospita l. Among most of the samples, acetone was the most abundant carbonyl, follo wed by acetaldehyde, 2- butanone or formaldehyde. Toluene was the most abundant BTEX and the others were at similar levels. The relatively higher aceton e 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 s pecial weather conditions during sampling time. The high concentration of acetaldehy de, 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 sh owed the anthropogenic sources for these compounds. The low correlat ions between most carbonyls and BTEX concentrations might be caused by thei r complex sources. Finally, the human exposure levels of formaldehyde and ac etaldehyde in hospitals2-99 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." Mea surement Science & Technology 18 (9): 2997-3004. Low-concentration formaldehyde (HCHO) together with ethanol/toluene/acetone/alpha-pinene (as an interfere nce gas of HCHO) is detected with a micro gas sensor array, composed of eigh t 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 al gorithm, plus the principal component analysis ( PCA) technique, is impleme nted to recognize these indoor volatile organic compounds ( VOC). The resu lts 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 v olatile organic chemical emissions in four fema temporary housing units – Final report Ernest Orlando Lawrence Berkeley National Laboratory (LBNL-254E), Environmental E nergy Technologies

Division As part of an ongoing effort with the U.S. Centers fo r Disease Control and Prevention (CDC), Lawrence Berkeley National Laborat ory (LBNL) entered into an interagency agreement with CDC to help identify mitiga tion strategies for reducing indoor emissions of volatile organic compounds (VOCs ) including formaldehyde in Federal Emergency Management Administrat ion (FEMA) temporary housing units (THUs)1. Four unoccupied FEMA THUs w ere studied to assess their indoor emissions of VOC including formaldehyde. Indoor measurement of whole-THU VOC and aldehyde emission facto rs ( μ g h-1 per m2 of floor area) for each of the four THUs were made a t FEMA’s Purvis Mississippi staging yard using a mass balance approach. Measurements were made in the morning, and again in the afternoon in2-100 each THU. Steady-state indoor formaldehyde concentrations ranged from 378 μ g m-3 (0.31ppm) to 632 μ g m-3 (0.52 ppm) in the morning, and from 433 μ g m-3 (0.35 ppm) to 926 μ g 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 (approximate ly 0.025 m2) samples of surface material, 16 types, were collected di rectly 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 ga s chromatographymass spectrometry for the remaining VOCs. Material spec ific emission factors ( μ g 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 significa nce or because their concentrations were high. Whole-trailer and material s pecific emission factors were calculated for 33 compounds. The THU emission factor s and those from their component materials were compared against those me asured in other types of housing and the materials used in their construction. Whole THU emission

factors for most VOCs were similar to those from co mparative housing. The three exceptions were large emissions of formaldehyde, acetic a cid, TMPD-DIB (a common plasticizer in vinyl products), and somewhat eleva ted 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 μ g m-2 h-1 in the morning and 257 to 347 μ g m-2 h-1 in the afternoon. Median formaldehyde emissions in previously studied site-built and

manufactured homes were 31 and 45 μ g m-2 h-1, respectively. Only one of the composite wood materials that was tested appeared to excee d the US Department of Housing and Urban Development (HUD) formaldehyde emissio n standard for

new material but several of the materials exceeded if the decline in emission with aging is considered. The high loading factor (material s urface area divided by THU volume) of composite wood products in the THUs and th e low fresh air exchange relative to the material surface area may be r esponsible for the2-101 excessive concentrations observed for some of the VOCs and formaldehyde.

Maddalena, R., M. Russell, et al. (2009). "Formaldehyde and Ot her Volatile Organic Chemical Emissions in Four FEMA Temporary Housing Units." Environmental Science & Technology 43 (15): 5626-5632. Indoor concentrations of 33 volatile organic chemicals we re 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-trim ethyl-1,3- pentanediol diisobutyrate (TXIB) with median concentra tions of 440, 425, and 36 ppb, respectively. A number of volatile organic compounds (VOC s) 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 pr eviously measured new building emission rates by over a factor of 5. Mat erials were collected from the THUS, and emission factors were determined using smal l chambers to identify the potential source of indoor contaminants. The individual materials were grouped by material type, and emissions were used to deriv e exposure concentrations for comparison to reference values. Usi ng material loading factors

and ventilation rates that are relevant to the trail ers, all of the material types we tested had at least two chemicals (formaldehyde and nonan al)with derived concentrations in excess of chronic reference exposure l evels or odor thresholds. The extensive use of composite wood products, sealants, and vinyl coverings, combined with the low air exchange rates relative to mate rial surface areas, may explain the high concentrations of some VOCs and form aldehyde.

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 o n respiratory health has focused on allergens, moisture/mold, endotoxin, or combusti on products. A growing body of research from outside the US; however, has associated chemical

emissions from common indoor materials with risk of as thma, allergies, and2-102 pulmonary infections. This review summarizes 21 studies in the epidemiologic

literature on associations between indoor residential c hemical emissions, or emission-related materials or activities, and respirat ory health or allergy in infants or children. Associations, some strong, were reported b etween many risk factors and respiratory or allergic effects. Risk factors identi fied most frequently included formaldehyde or particleboard, phthalates or plastic mate rials, and recent painting. Findings for other risk factors, such as aromatic and alipha tic chemical compounds, were limited but suggestive. Elevated risks were a lso reported for renovation and cleaning activities, new furniture, and carpet s or textile wallpaper. Reviewed studies were entirely observational, limited i n size, and variable in quality, and specific risk factors identified may only be i ndicators for correlated, truly causal exposures. Nevertheless, overall evidence s uggests a new class of residential risk factors for adverse respiratory effect s, ubiquitous in modern residences, and distinct from those currently recognized. It is important to confirm and quantify any risks, to motivate and guide necessary prev entive 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 associati on between formaldehyde levels and housing characteristics. This invo lved collection of 309 air samples which were analysed using a colorimetric met hod. 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 home s inhabited by at

least one smoker and were correlated with indoor and out door 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 w ere generally slightly higher in the afternoon. A simple mathematical model involving smoking activity has been developed for estimating the formaldehyde decay ra tes for two rooms in one of the typical background homes. When the windows an d doors were closed, the formaldehyde concentrations in indoor air decreased wi thin 10h to background concentrations, although this change depended on the room volume2-103 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 source s of indoor air pollution." Indoor Air-International Journal of Indoor Air Quality and Clima te 6 (1): 18-30. This study deals with the modeling of air pollution in apart ments from laboratory measurements of source strengths, using formaldehyde and Tota l Volatile Organic Compounds (TVOCs) as model pollutants. The sources in two test apartments were grouped into two: building-related sources and occupant-rel ated sources. The measured source strengths and ventilation rates were used for the prediction of concentrations expected in the apartments. These pre dictions were compared to measurements in the apartment over 12 months. The concl usions 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 ventil ation 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 emiss ion rate of VOCs from building materials in general was estimated to be a bout 30 mu g/m(2)/h. The modeling showed that during the first 200 days, building materia ls dominated the emissions. After this, sources relating to the occupants dominated. On average about half of the VOC pollution originated from the buil ding materials.

Morrison, G. C., W. W. Nazaroff, et al. (1998). "Indoor a ir quality impacts of ventilation ducts: Ozone removal and emissions of volatile organic c ompounds." Journal of the Air & Waste Management Association 48 (10): 941-952. The concentrations of contaminants in the supply air o f mechanically ventilated buildings may be altered by pollutant emissions from and i nteractions with duct

materials. We measured the emission rate of volatile organic compounds (VOCs) and aldehydes from materials typically found in ventilati on 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 gaske t. For a typical2-104 duct, the contribution to VOC concentrations is predict ed 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 incre ased the emission rates of aldehydes from a duct liner, duct sealing caulk, and n eoprene gasket. The emission of aldehydes from these materials could increa se indoor air concentrations by amounts that are as much as 20% of od or 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 fractio n 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 th an 4%. In an unlined duct, in which only galvanized sheet metal is exposed to the airs tream, the removal efficiency would be much lower, similar to 0.02%. There fore, 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 Service s 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 vari ety of adverse health effects. An IAQ assessment for a local office will audit 12 parameters, including air temperature, relative humidity, air velocity, car bon dioxide, carbon monoxide, respirable suspended particulates, nitrogen dioxide, ozone, formaldehyde, total volatile organic compounds, radon, and airborne bacteria. T his paper reviews recent studies of the indoor airborne fungi levels and I AQ assessments in some air-conditioned offices of Hong Kong and evaluates the c ontribution of the airborne fungi to an unsatisfactory IAQ in the environmen t. The unsatisfactory rates regarding the assessment parameters were evaluated us ing the Monte Carlo simulations with measured data in Hong Kong Offices. In pa rticular, the impact of selecting representative IAQ assessment parameters was examined against an2-105 express assessment protocol (EAP), which assessed some do minant contributors of unsatisfactory IAQ.(2) The results reported that th e 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 import ant 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 refe rence 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 a nd air fresheners: exposure to primary and secondary air pollutants." Atmospheri c Environment 38 (18):

2841-2865. Building occupants, including cleaning personnel, are exposed to a wide variety of airborne chemicals when cleaning agents and air freshe ners 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 regula ted by the US federal government as hazardous air pollutants (HAPs). California's Proposition 65 list of species recognized as carcinogens or reproductive toxicants a lso includes constituents of certain cleaning products and air freshener s. In addition, many cleaning agents and air fresheners contain chemicals tha t can react with other air contaminants to yield potentially harmful secondary product s. For example, terpenes can react rapidly with ozone in indoor air gen erating many secondary pollutants, including TACs such as formaldehyde. Furthermore, ozone-terpene reactions produce the hydroxyl radical, which reacts rapidl y with organics, leading to the formation of other potentially toxic air pol lutants. Indoor reactive chemistry involving the nitrate radical and cleaning-product co nstituents 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 concent rations of TACs2-106 that might result from primary emissions or secondary pollutant formation following the use of cleaning agents and air fresheners. I n 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 r eadily react to generate secondary pollutants. The toxicity of many of th ese secondary pollutants has yet to be evaluated. The inhalation intake of airborn e 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 article s present evidence of adverse health effects from inhalation exposure associa ted with cleaning or cleaning products. Exposure to primary and secondary pollutants depends on the complex interplay of many sets of factors and processe s, including cleaning product composition, usage, building occupancy, emission dyna mics, transport and mixing, building ventilation, sorptive interactions w ith building surfaces, and reactive chemistry. Current understanding is sufficient to describe the influence of these variables qualitatively in most cases and quantitat ively 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), shelli ng ratio, wood species, and pressure on the formaldehyde content, physical (SG and thic kness swelling (TS)), and mechanical properties (modulus of rupture (MOR), modulus o f elasticity (MOE), and internal bond (IB) strength) of particleboar d were examined. The best manufacturing parameters were determined for E-1 grade partic leboard manufacturing from urea formaldehyde (UF) adhesive. Based o n 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 t han that of panel from particles consisting higher amount of pine particles. (C) 2005 Elsevier Ltd. All2-107 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-for maldehyde binder was tested for the emissions of formaldehyde and volatil e organic compounds (VOC) simulating real use in roof constructions. Resul ts are compared with earlier published results from tests with wall constructio ns and to international indoor air limit values. Possible future handling by using reduct ions factors when testing pure mineral wool products without constructions is discussed.

Parent, D., S. Stricker, et al. (1998). "Optimum ventilat ion 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 sing le familydetached houses heated with electric baseboard heaters i n the vicinity of TroisRivieres during the 1993-94 heating season. The houses were sele cted according to the measured air leakage at 50 Pa so as to have a samp le 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 h ouses continuously during the heating season. Model studies using the measured pol lutant source strengths and measured equivalent leakage areas of the buil dings indicated that the recommended health guidelines for airborne respirable solid particles (RSP's), CO2 and formaldehyde are exceeded during periods of low total ven tilation, coinciding with mild outdoor temperatures and low wind cond itions. With the room occupied and the door closed, CO2 levels in the bedroom i ncreased steadily during the night until morning, when the door was opened, to le vels in excess of 3500 ppm with one person and in excess of 4500 ppm with two person s. Various different methods of ventilating some of the houses we re tested, including quiet replacement exhaust fans, mixing fans for indoor air and a fresh air intake and2-108 mixing system. The effects of operating various air handl ing 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 S cience 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 character ize occupants' simultaneous exposure to mixtures of organic compounds in homes. Statist ical distributions for concentrations of 28 organic compounds (17 VOCs and 11 aldehydes) measured in 1417 homes were generated to analyze concentration dis tributions. 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 com pound concentrations. Probability distributions show that fo rmaldehyde 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 or der 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 th at concentrations of organic compounds are mutually independent in homes. These jo int distributions provided the statistical data for characterizing the occupan t'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 durin g 3 years in new and older homes which were voluntarily selected throughout countries. The levels of volatile organic compounds (VOCs) in the new homes dec reased markedly after 1 year, and steady emissions of VOCs were obtaine d 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 lev els of the indoor air2-109 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 ventilatio n systems. The quantitative information on the trend of the indoor air organic compoun d levels will be useful for the risk assessment of indoor exposure to those compoun ds, 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 concentra tion, temperature, relative humidity (RH), and the presence of NOx) on heterogeneous squalene oxidation

were studied with Attenuated Total Reflectance-Fourier Tra nsform 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 t he range of 24-58 +/- 2 degrees C as well as to RH and presence of NOx. Products, h owever, were affected by the environmental parameters. As temperature w as increased, fewer surface products and more low molecular weight gaseous produc ts were observed. Lower air exchange rates also enhanced gas phase reactio ns, allowing for formation of secondary gas phase products. As RH increased, there was a shift in product distribution from ketones to aldehydes, and the presenc e of NOx during squalene ozonolysis resulted in the formation of nitrat ed oxidation products. Identified surface products included 6-methyl-5-hepten-2-one, gera nyl acetone, and long chain ketones and aldehydes, while gas phase products in cluded formaldehyde, acetone, 4-oxopentanal (4-OPA), glyoxal, a nd pyruvic acid.Practical Implications Heterogeneous oxidation of squalene resulted in surface pr oducts including long chain aldehydes and ketones, and gas phase products including formaldehyde, a known human carcinogen (IARC 2006), and bicar bonyl compounds like: 4-oxopentanal (4-OPA), glyoxal, and pyruvic acid that are2-110 characterized as asthma triggers and sensitizers (Anderso n et al., 2007; Jarvis et al., 2005). In addition, ozonolysis experiments in the pres ence of NOx showed the formation of nitrated surface oxidation products. Such nitrat ed products may have higher mutagenicity, carcinogenicity, or allergenic potential than their nitrate free counterparts (Franze et al., 2005; Pitts, 1983). Kinetic studie s 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 reac tion 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 contr olled. 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 t he air: A model for investigating indoor air quality in Texas schools." Journal of Environmen tal 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 guidel ines for the U.S. Environmental Protection Agency's Indoor Air Quality Tools f or Schools program. Tools for Schools, developed for evaluating and ensur ing acceptable air quality for schools, takes a low-cost, minimal-involveme nt, primarily educational approach. The authors also compared the findings from this approach with the results of an air-sampling program. The overall goal wa s to determine 9 use of Tools for Schools was sufficient to identify condition s 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 S chools assessments and management strategies, 2) collect air quality data in high -risk areas identified within the school by the indoor air quality committee, 3) c ollect outdoor air quality data at or in close proximity to the school, and 4) develop methods and instruments for assessing environmental risks associated w ith daily school attendance. Data were gathered on levels of formaldehyde an d other volatile organic compounds (VOCs), ozone, particulate matter (PM10) , mold, relative2-111 humidity, and temperature. Data values for each sampled pollutant were compared with federal standards, recommended values establis hed by the American Conference of Governmental Industrial Hygienist s for non-industrial populations, and effects screening levels developed by the Tex as Commission on Environmental Quality. Levels of all VOCs except formalde hyde 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 Alterna ria. In general, Tools for Schools provides an excellent foundation for a school indo or air quality program, although the authors did find it necessary to streamline dat a collection and did find that mold with the potential for adverse health effec ts 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 con tents 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 evaluat e simpler laboratory methods for determining the formaldehyde emission from parti cleboard, 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 correlati on coefficients of > 0.9. The value of formaldehyde emission decreased linearly wi th the mole ratio of formaldehyde to urea down to 1.05 where the effect smoothe d out. The effect on the formaldehyde emission of temperature and storage time for tested boards also was studied. The heat treatment lowered the perforator v alue 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 incr ease 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 mode l for the formaldehyde emission from wood-based board in room." Building and Envir onment 42 (6): 2321-2324.

A mathematical model which describes the influence of var ious parameters on formaldehyde concentration in the atmosphere of a room containing wood-based boards was developed. The physical meanings and measuring meth ods of the parameters of the model are also discussed. Based on this model, two indices for commenting the formaldehyde emission process of wood-bas ed boards are proposed, and inequality estimation for the formaldehyde co ntent of wood-based boards at any moment and a time estimation which shows w hen the room satisfies the environment quality standard are also given. (c) 2006 Elsevie r Ltd. All rights

reserved.

Risholm-Sundman, M., A. Larsen, et al. (2007). "Formalde hyde 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 materi als. This article gives a comparison between commonly used European test methods: c hamber method [EN 717-1, 2004. Wood-based panels-determination of formaldehyde release-Part 1: formaldehyde emission by the chamber method. European Sta ndard, October 2004], gas analysis method [EN 717-2, 1994. Wood-based panels-determi nation of formaldehyde release-Part 2: formaldehyde release by the gas analysis method, European Standard, November 1994], flask method [EN 717-3, 1996. Woo dbased panels-determination of formaldehyde release-Part 3: formaldehyde release by the flask method, European Standard, March 1996], perforator m ethod [EN 120, 1993. Wood based panels-determination of formaldehyde conten t-extraction method called perforator method, European Standard, Septembe r 1993], Japanese test methods: desiccator methods [JIS A 1460, 2001. Building boar ds.2-113 Determination of formaldehyde emission-desiccator method, Japanese Industrial Standard, March 2001 and JAS MAFF 233, 2001] and small chamber meth od [JIS A 1901, 2003. Determination of the emission of volatile organi c compounds and aldehydes for building products-small chamber method, Japanes e Industrial Standard, January 2003], for solid wood, particleboard, plywoo d and medium density fiberboard.

The variations between the results from different methods can partly be explained by differences in test conditions. Factors li ke edge sealing, conditioning of the sample before the test and test temperature hav e 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-laborat ory 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 e xposure to formaldehyde significantly increases the risk of asthma in young childr en." 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 a sthma among young children (between 6 months and 3 yrs old) in a population-ba sed 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 Pr incess Margaret Hospital Accident and Emergency Dept (Perth, Western Aust ralia), were children discharged with asthma as the primary diagnosis. Contro ls (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 W estern Australia (Perth, Western Australia). Health outcomes for the children w ere studied using a respiratory questionnaire and skin-prick tests. Formaldehyde, average temperature2-114 and relative humidity were measured on two occasions, w inter (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 lev els in the children's bedrooms and living rooms with significantly great er formaldehyde exposure during the summer period for case and control subjec ts. The generalised estimating equation model showed that children exposed to for maldehyde levels of greater than or equal to60 mug.m(-3) are at increased ri sk of having asthma. The results suggest that domestic exposure to formaldehyde increases the risk of

childhood asthma.

Salthammer, T. and F. Fuhrmann (2007). "Photocatalytic surfa ce reactions on indoor wall paint." Environmental Science & Technology 41 (18): 6573-6578. The reduction of indoor air pollutants by air cleaning syste ms has received considerable interest, and a number of techniques are now available, So far, the method of photocatalysis was mainly applied by use of tit anium 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 concentratio ns. In further experiments with volatile organic compounds (VOCs), a sm all 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 a cted as a reversible sink. Secondary emissions from the reaction of paint constitue nts 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) Project2-115 characterized personal, indoor, and outdoor concentration s 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 analy sis of VOC

measurements collected indoors and outdoors for 46 students ' homes in NYC and

for 41 students' homes in LA across two seasons. Dual-sor bent thermal desorption tubes were used for the collection of 15 VOCs and C(18) 2, 4- dinitrophenylhydrazine-coated cartridges were used for the col lection of seven aldehydes. Air-exchange rates (AERs) were also measured usi ng 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, compar ed with 1.8 h(-1) in NYC in the summer and 2.5 h(-1) in LA in the fall. Highe r AERs were generally associated with lower indoor-outdoor ratios with significa nt differences for the compounds with indoor sources, including chloroform, 1,4-dichl orobenzene, and formaldehyde. Using a mass-balance model to account for AER and other housing parameters, effective source emission rates (SER) wer e 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 wi th contributions from both indoor and outdoor sources, and (3). those with mos tly outdoor sources. Significant indoor sources were found for the following si x compounds (mean emission rates presented): chloroform (0.11 mg/h), 1,4-dichlor obenzene (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 rat es 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 deter mined that source strength

calculations were not sensitive to measurement error fo r 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 concentration s 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 anal ysis of VOC

measurements collected indoors and outdoors for 46 students ' homes in NYC and

for 41 students' homes in LA across two seasons. Dual-sor bent thermal desorption tubes were used for the collection of 15 VOCs and C-18 2,4

- dinitrophenylhydrazine-coated cartridges were used for the col lection of seven aldehydes. Air-exchange rates (AERs) were also measured usi ng 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, compar ed with 1.8 h(-1) in NYC in the summer and 2.5 h(-1) in LA in the fall. Highe r AERs were generally associated with lower indoor-outdoor ratios with significa nt differences for the compounds with indoor sources, including chloroform, 1,4-dichl orobenzene, and formaldehyde. Using a mass-balance model to account for AER and other housing parameters, effective source emission rates (SER) wer e 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 most ly outdoor sources. Significant indoor sources were found for the following si x compounds ( mean emission rates presented): chloroform (0.11 mg/h), 1,4-dichlor obenzene (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 rat es 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 deter mined that source strength

calculations were not sensitive to measurement error fo r a subset of homes in LA.

Schupp, T., H. M. Bolt, et al. (2005). "Maximum exposure leve ls 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 possib le adverse health effects and about exposure levels that can be considered safe or "ac ceptable". 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 o rganic substances in cars has been published. In the present study we applied this conc ept to derive maximum exposure levels for xylene, formaldehyde and acetal dehyde 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 a nd acetaldehyde, respectively. These STELIAs should not be e xceeded during shortterm exposures, for instance when starting a car that had been heated up during parking in the sun. Exposure Levels Inside Automotive Vehicl es (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, i t is known that exposure limits for carcinogenic substances should be tr eated with caution, encouraged by the well documented threshold mechanisms we n evertheless derived ELIAs for Carcinogenic and Mutagenic Substances (EL IA, cm) resulting in 0.125 and 0.635 mg/m(3) for formaldehyde and acetaldehyde. If thes e ELIAs are matched against average concentrations of xylene, for maldehyde 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 El sevier 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 consis ting of activated2-118 carbon particles and manganese oxides, by which HCHO gas i s decomposed into carbon dioxide even at room temperature. In this study, w e investigated removal efficiencies of the air-cleaning board in a passive mode usi ng a kinetic approach. First-order removal rate constant, k, corresponding to air change rate was

characterized for the board as a function of the rati o of applied board area to space volume, S/V, and was found directly proportional to S/V wi th 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 i ncrease of indoor

HCHO concentration and the time course fitted to a the oretical curve. Then, field tests of the air-cleaning board were conducted in newly con structed 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 th an 7 months, but also enhanced the loss of HCHO gas from building materi als in apartments. (C) 2001 Elsevier Science Ltd. All rights reserved.

Sexton, K., M. X. Petreas, et al. (1989). "Formaldehyde Ex posures inside Mobile Homes." Environmental Science & Technology 23 (8): 985-988. An age-stratified random sample of 470 mobile homes was s elected from among the more than 500000 in California. One-week, average indoor fo rmaldehyde concentrations were measured during both the summer (July -August 1984) and the winter (February-March 1985) seasons. Results indica te that (1) formaldehyde

concentrations were well-mixed inside the trailers over a 1-week period, (2) relatively little variation was observed in formaldehy de concentrations between summer and winter, (3) average 1-week formaldehyde values w ere 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, Refrige rating, 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 b asis 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 ha s been improved to reduce infiltration, and the use of windows for ventilatio n also may have decreased due to a number of factors. Thus, there has bee n increased interest in engineered ventilation systems for residences. The amo unt of ventilation provided by an engineered system should be set to protect occupants fr om unhealthy or objectionable exposures to indoor pollutants, while minimi zing energy costs for conditioning incoming air. Determining the correct ventila tion rate is a complex task, as there are numerous pollutants of potential conce rn, 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 exa mines the use of formaldehyde as a means of determining ventilation rates a nd 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 h ouses are 0.28 and 0.5 air changes per hour, respectively.

Shinohara, N., Y. Kai, et al. (2009). "On-site passive fl ux sampler measurement of emission rates of carbonyls and VOCs from multiple indo or 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 or der to identify the

emission sources that contribute most to the concentra tions of indoor air pollutants. we used passive flux samplers (PFSs) to measur e emission rates of carbonyl compounds and volatile organic compounds (VOCs) from many of the building materials and furnishings present in a room in a reinf orced concrete building in Tokyo, Japan. The emission flux of formaldehy de from a desk was2-120 high (125 mu g/m(2)/h). whereas fluxes from a door and floori ng were low (21.5 and 16.5 mu g/m(2)/h. respectively). The emission fluxes of t oluene from the ceiling and the carpet were high (80.0 and 72.3 mu g/m(2)/h, respe ctively), 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 perf luorocarbon 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, res pectively, 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 lev els 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 orga nics in environmental tobacco smoke: 2. Exposure-relevant emission factors an d indirect exposures from habitual smoking." Atmospheric Environment 37 (39-40): 5551-5561. Sorption of emitted gas-phase organic compounds onto materi al surfaces affects environmental tobacco smoke (ETS) composition and exposures indoors. We have introduced a new metric, the exposure relevant emis sion factor (EREF) that accounts for sorptive uptake and reemission to give the mas s of individual ETS constituents available for exposure over a day in which smoking occurs. This paper describes month-long experiments to investigate sorpt ion 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 ga s concentrations were measured every few days over 4-h "smoking", 10-h "post-smo king" 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 sorp tion. Concentrations of2-121 ETS tracers, e.g. 3-ethenylpyridine (3-EP) and nicotine, and lower volatility toxic air contaminants including phenol, cresols, and naphthale ne 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, ph enol, cresols, naphthalene, and methylnaphthalenes. Our results provide relev ant information about potential indirect exposures from residual ETS (non -smoker enters room shortly after smoker finishes) and from reemission, a nd their importance relative to direct exposures (non-smoker present during smoking). Under the conditions examined, indirect exposures accounted for a larger fracti on of total potential exposures for sorbing versus non-sorbing compounds, and at lower versus higher ventilation rates. Increasing ventilation can reduce indi rect exposures to very low levels for non-sorbing ETS components, but indirect rout es 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 tw o gaseous compounds that react in an indoor setting to produce a hypoth etical product. The reactants are ozone and either d-limonene or alpha-te rpinene (which reacts with ozone about 40 times faster than d-limonene). In additio n 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 emissio n pattern similar to a floorcare product. These four scenarios have been set in a fai rly large two-dimensional room (13.6 x 40.6 m) with a supply at the top of the left wa ll and an exhaust at the bottom of the right wall. The room has been deliberatel y 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 further2-122 assumed that ozone interacts with room surfaces while t he terpenes do not. The results show that for all four scenarios, under steady-s tate conditions, there are large concentration gradients within the room for both r eactants and product. To some extent this is due to imperfect mixing. However. it also reflects that reactions occur at different rates across the room (be cause of varying reactant concentrations) and that the time available for reacti ons to occur varies with the room location (because the "age of the air" varies fro m point to point). Locally, within the room, the concentrations calculated by the C FID method differ significantly from those calculated by a one-compartme nt mass-balance model assuming perfect mixing. (C) 2002 Elsevier Science Ltd. All ri ghts reserved.

Spengler, J. D., J. McCarthy, et al. (2001). Volatile Orga nic Compounds. Indoor Air Quality Handbook

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Tichenor, B. A. and L. E. Sparks (1996). "Managing exposure to indoor air pollutants in

residential and office environments." Indoor Air-Internatio nal Journal of Indoor Air Quality and Climate 6 (4): 259-270. Sources of indoor air pollutants in residential and off ice environments can be managed to reduce occupant exposures. Techniques for managing indoo r air pollution sources include: source elimination, substitution, modification, pretreatment, and altering the amount, location, or tim e of use. Intelligent source management requires knowledge of the source's emission ch aracteristics, including chemical composition, emission rates, and decay rates. In addition, knowledge of mechanical and natural outdoor air exchange r ates, heating/airconditioning duct flow rates, and local exhaust fan (e.g., kitchen, bathroom) flow rates is needed to determine pollutant concentrations. Fina lly, indoor air quality (IAQ) models use this information and occupant activity patt erns 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 act ivity patterns. IAQ model predictions of occupant exposures for these scenarios ar e 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 t his 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 Coo peartive 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 pot ential indoor air quality impacts of new building materials and contents by select ing low-emission

materials. However low-emission materials are not a lways available, and even when used the aggregated pollutant concentrations from such materials are generally overlooked. This paper presents an innovative tool f or 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 airbor ne particles from indoor materials and office equipment and the contributio n of outdoor urban air pollutants affected by urban location and ventilation sys tem filtration. The estimated pollutants are for a single, fully mixed and ven tilated zone in an office building with acceptable levels derived from Australian an d international healthbased standards. The model acquires its dimensional data fo r 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 t he underlying approach to estimating indoor air quality and discusses the b enefits 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 Environmen tal Hygiene 15 (8):

629–634. To estimate the impact of office equipment on the qual ity of indoor air, the emission of ozone and organic volatiles was measured fr om one photocopier and four laser printers, three of which operated according to t raditional corona2-124 discharge technology. The laser printers equipped with tr aditional technology emitted significant amounts of ozone and formaldehyde. Les ser amounts of other volatile aldehydes were emitted during printing. The photoco pier emitted mainly

ozone. In a well-ventilated office environment, the amounts en countered here for individual volatiles were within recommended maximum exposur e limits for a reasonable density of printers. Because it is not known w hether the concentration of irritating volatiles, such as formaldehyde, should be kept lower in an ozone rich environment or not, and because emissions in the immediat e vicinity of the printers exceeded recommendations, the authors recommend t hat laser printers equipped with the traditional corona rods not be placed bes ide or immediately at the working site of office personnel. This way, ozone conc entrations can be kept below recommended maximum exposure limits, provided that the ventilation rate is adequate. Further, it seems that if a reliable quantitat ive comparison of total organic volatiles prior to and during printing is to be made, t he inertness of the

sorbent toward ozone should be confirmed.

Uhde, E. and T. Salthammer (2007). "Impact of reaction produc ts from building materials and furnishings on indoor air quality - A review of recent adv ances 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 r eactions 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 c ause unwanted side reactions and a number of new compounds can be found in fi nished products. Elevated temperatures are responsible for the degradation of cellulose, decomposition of non-heat-resistant additives and other t hermally induced reactions like Diels-Alder synthesis. Heterogeneous che mistry takes place on the surface of materials. Well-known examples are the fo rmation of aliphatic aldehydes from the oxidation of unsaturated fatty acids or t he cleavage of photoinitiators under the influence of light. In case of composite flooring2-125 structures hydrolysis is one of the major pathways for t he appearance of alcohols

from esters. If different kinds of material are fixed together, emissions of new VOCs formed by inter-species reactions are possible. Oth er indoor air pollutants are formed by rearrangement of cleavage products or by met abolism. Compounds with -C=C- bonds like terpenes, styrene, 4-phenylcyclohexe ne, 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 ma y have a negative impact on indoor air quality due to their low odor thresh old or health-related properties. Therefore, the understanding of primary and sec ondary emissions and the chemical processes behind is essential for the eval uation of indoor air quality. This publication gives an overview on the current state of research and new findings regarding primary and secondary emissions from b uilding products and furnishings.

Wang, B., S. C. Lee, et al. (2007). "Characteristics of carbonyls: Concentrations and source strengths for indoor and outdoor residential microe nvironments 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, C hina in summer (from July to September in 2004) and winter (from Decembe r 2004 to February 2005). Formaldehyde was the most abundant indoor carbonyls sp ecies, while formaldehyde, acetaldehyde and acetone were found to be th e most abundant outdoor carbonyls species. The average formaldehyde conce ntrations 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 sh owed that the dwellings with tobacco smoke, incense burning or poor ventila tion had significantly higher indoor concentrations of certain ca rbonyls. It was noticed that although one half of the dwellings in this study installed wi th 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 a cetone concentrations in two dwellings in Guangzhou were significantly high, whic h were mainly caused by the usage of acetone as industrial solvent in ma ny paint manufacturing2-126 and other industries located around Guangzhou and relatively l onger lifetime of acetone for removal by photolysis and OH reaction than other carbonyls species. The indoor carbonyls levels in Chinese dwellings were highe r than that in dwellings in the other countries. The levels of indoor an d ambient carbonyls showed great seasonal differences. Six carbonyls species were carried out the estimation of indoor source strengths. Formaldehyde had the l argest 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 be nzaldehyde had the weakest indoor sources. (C) 2006 Elsevier Ltd. All righ ts reserved.

Wang, S. Y., T. H. Yang, et al. (2008). "Fire-retardant-t reated low-formaldehydeemission particleboard made from recycled wood-waste." Bioresource Technology 99 (6):

2072-2077. The objective of this study was to manufacture fire-ret ardant-treated lowformaldehyde-emission particleboard from recycled wood-wa ste particles using polymeric 4,4'-methylenediphenyl isocyanate (PMDI) and phenol- formaldehyde (PF) resins. The influence of the PMDI/PF ratio (rati o of particles sprayed with PMDI to particles sprayed with PF, w/w) after fire ret ardant treatment on formaldehyde emissions, mechanical properties, and surface fire resistant performance of the manufactured particleboard was investi gated. The experimental results showed that the formaldehyde emissi ons linearly decreased with an increasing PMDI/PF ratio. Moreover, the bend ing strength, internal bond strength, and screw holding strength increased with an in creasing PMDI/PF ratio. The thickness swelling of the particleboard was improved by using an increasing PMDI/PF ratio. Furthermore, the fire-retardant-treate d low-formaldehydeemission particleboards fabricated in our study could pass t he third grade standard of surface fire resistant performance as specified by CN S 6532. (C) 2007 Elsevier Ltd. All rights reserved.

Wang, X. K. and Y. P. Zhang (2009). "A New Method for Deter mining the Initial Mobile Formaldehyde Concentrations, Partition Coefficients, and Diffusion Coefficients of Dry Building Materials." Journal of the Air & Waste Manage ment 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 ma terial. The solvent extraction method and direct thermal desorption method can overestimate C-m,C0 because of high temperature. A new method has been deve loped to determine C-m,C-0 under similar conditions to common indoor environm ent, together with K and D. In the proposed method, the tested materials a re placed in an airtight environmental chamber for which the temperature can be cont rolled by a water bath, then the materials undergo a multisorption/emis sion process and the instantaneous formaldehyde concentration in the chamber is recorded. The K and C-m,C-0 are determined from the equilibrium concentratio ns 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-trans fer-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 concent ration in the material, which differs significantly from the total f ormaldehyde concentration in the material measured by using the traditional method reco mmended 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 process es. 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 mode l for characterizing common air pollutants in air-conditioned offices." Atmospheric En vironment 40 (23): 4246-4257. Maintaining acceptable indoor air quality (IAQ) for a heal thy environment is of primary concern, policymakers have developed different str ategies to address the performance of it based on proper assessment methodologi es and monitoring plans. It could be cost prohibitive to sample all toxic pol lutants in a building. In search of a more manageable number of parameters for c ost-effective IAQ2-128 assessment, this study investigated the probable correlatio ns among the 12 indoor environmental parameters listed in the IAQ certification scheme of the Hong Kong Environment Protection Department (HKEPD) in 422 Hong Ko ng offices. These 12 parameters consists of nine indoor air pollutants: c arbon dioxide (CO2), carbon monoxide (CO), respirable suspended particulates (R SP), nitrogen dioxide (NO2), ozone (O-3), formaldehyde (HCHO), total volatile organic compounds (TVOC), radon (Rn), airborne bacteria count (ABC); an d three thermal comfort parameters: temperature (T), relative humidity (RH) and air velocity (P). The relative importance of the correlations derived, from la rgest to smallest loadings, was ABC, Rn, CO, RH, RSP, CO2, TVOC, O-3, T, V, NO2 an d HCHO. Together with the mathematical expressions derived, an alternative sampling protocol for IAQ assessment with the three,mos t representative and independent' parameters namely RSP, CO2 and TVOC measured in an office environment was proposed. The model validity was verified w ith on site measurements from 43 other offices in Hong Kong. The mea sured CO2, RSP and TVOC concentrations were used to predict the probable lev els of the other nine parameters and good agreement was found between the predicti ons 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 a ir 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 m easurement of the levels of 12 parameters: carbon dioxide, carbon monoxide, respira ble suspended particulates, nitrogen dioxide, ozone, formaldehyde, total v olatile organic compounds, radon, airborne bacteria count, temperature, r elative 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-condit ioned offices in Hong Kong, three of nine listed common air pollutants are sele cted as "representative" pollutants for an overall "satisfactory IAQ". In partic ular, 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 profes sionals to identify offices with probable IAQ problems. Making better decision s regarding resources for an IAQ surveillance programme could help to ensure a hea lthy and safe workplace.

Wu, P. C., Y. Y. Li, et al. (2003). "Risk assessment of fo rmaldehyde in typical office buildings in Taiwan." Indoor Air 13 (4): 359-363. Our study conducts a series of investigations in five offi ce buildings chosen according to the types of construction, ventilation, a nd building age. Formaldehyde was measured by continuous photoacoustic Multi-G as 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) aft er adjusting their working time. The levels of risk are 100-1000 times of the ac ceptable carcinogenic risk. A similar trend is observed for the l evels of HI calculated. Many studies have suggested that exposure to high levels of for maldehyde 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 FORMALD EHYDE EMISSION

FROM MULTI-LAYER WORK SURFACES USED IN OFFICE WORKS TATION

SYSTEMS . Proc. of the 6th Int. Conf. on Indoor Air Quality.2-130

Volatile organic compounds (VOCs) emitted from various so urces may adversely affect human health, comfort and performance. In parti cular, formaldehyde has been identified as a major indoor pollutant whose emissi on is controlled by workstation systems. Engineered wood products such as parti cleboards have widely been used with wood veneer and laminate to form wor k surfaces of workstation systems, which is a major formaldehyde emiss ion 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 characterist ics of multi-layer work surfaces such as a wood veneer over a particleboa rd 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 transpor t 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, t he initial conditions have a major influence on the evolution of the emission fact or. It can be concluded that an unambiguous determination of all parameters is difficu lt since the problem has no unique solution yet. Further research needs can be ident ified.

Yoshida, H., A. Kimura, et al. (2004). "Emission behavior o f 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 s olid oak and wall paneling of sugi wood. Concentration of carbonyl compounds and volati le 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 othe r 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 c onstituents were2-131 terpenoids, especially a-pinene. The terpenoids were rapid ly 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 Mi croenvironments." Environmental Science & Technology 28 (1): 146-152. Simultaneous indoor and outdoor measurements of aldehydes w ere made at 6 residential houses located in a suburban New Jersey are a during the summer of 1992. Each house was measured for six days and controlled for ventilation and gas combustion conditions during the study. Formaldehyde, a cetaldehyde, 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 al dehyde. Except for propionaldehyde, the indoor concentrations were found higher than the outdoor concentrations for all the other compounds, ind icating the presence of significant indoor sources such as direct emissions and i ndoor chemical

formation. Ozone concentrations were measured simultan eously during the study, and it was observed that several aldehydes can be generate d through indoor ozone chemistry. The study provided evidence to support laborator y results obtained by other investigators that predicted aldehyde generation through indoor ozone chemistry. The residential exposures to formaldehyde and t otal aldehydes were assessed based upon some assumptions, and the outdoor exposur es were negligible compared to the indoor exposures.

Zhang, J. F., W. E. Wilson, et al. (1994). "Indoor Air Chemi stry - Formation of OrganicAcids and Aldehydes." Environmental Science & Technology 28 (11): 1975-1982. The formation of aldehydes and organic acids was examined f or the gas-phase reactions of ozone with unsaturated VOCs. Formaldehyde an d formic acid were produced via the reaction of ozone with each of the thre e selected unsaturated VOCs: styrene, limonene, and 4-vinylcyclohexene. In additi on, benzaldehyde was detected in the styrene-ozone-air reaction system, an d acetic acid was found in the2-132 limonene-ozone-air system. The study also examined the gas-phase reactions involving formaldehyde, ozone, and nitrogen dioxide and found th e 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 condit ions and chemicals employed in the reactions were similar to t hose for indoor environments, the results from this study may be extrapola ted 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 temper ature on formaldehyde emission parameters of dry building materials." Atmosphe ric Environment 41 (15): 3203-

3216. The diffusion coefficient, D, partition coefficient , K, and the initial volatile organic compounds (VOCs) in dry building materials, are th e 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 coef ficients and the partition coefficients with temperature for particle board, vinyl fl oor, medium- and highdensity board are presented. A formula relating the partition coefficient and related factors is obtained through analysis. This formu la can predict the partition coefficient in principle and provide an insight for fitti ng experimental data, and it agrees well with the experimental results. (C) 2006 Else vier Ltd. All rights

reserved.

Kenneth Unice:

Formaldehyde is a challenging molecule for indoor air mode lers evaluating pressed wood products as a result of a complex long term emission pro file, a backpressure effect not often observed in consumer product modeling and potential indoo r sources and sinks. The purpose of the Formaldehyde Indoor Air Model – Pressed Wo od Products (FIAM-2-133

pwp) is to provide a tool to estimate indoor human inhalation e xposure to airborne formaldehyde (HCHO) in residential, mobile home, or tem porary structures such as classrooms. The model documentation is transparent and well written, however, several areas of potential technical improvement or correction ar e noted in this review. I found the model input and output screens to be clear and intuitive

.

The theoretical framework for modeling steady state lev els of formaldehyde has been in place for approximately 30 years. One of the areas I re flected 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 re search, particularly in regard to the long term decay characteristics of formal dehyde 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. Th is could be as simple as allowing ‘batch inputs’ for certain parameters like mass t ransfer coefficient with a selection key outputs summarized when batch mode is us ed.

One of the major themes of my comments is that I st rongly believe that the model documentation should outline a conceptual framework (with case studies) for assessing the exposure attributable to a specific product while taking in to account the unique backpressure and source decay effects observed for formald ehyde. This framework is important because federal future regulatory standards, if a ny, 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 a spects of the model is that the purpose to assess exposure attributable to emissions from pres sed wood products, but the model output of average daily concentration (ADC) and life time average daily concentration (LADC) appears to include the background con centration and the ability to include doses from non-pressed wood products. As currently fr amed, 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 specif ic class of products or2-134

collection of products. The modifications that can be made to the model are limited by the current state of the science, particularly for lo ng term exposure. Therefore, my primary recommendation is to describe a conceptual model i n the documentation that provides a framework for approaching questions about product speci fic hazard and risk.

In the comments below, I sometimes refer to the equi librium concentration which is related to the Matthews b and m by Ceq= b/-m. The equilib rium concentration is the theoretical concentration corresponding to a ventilat ion 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 V OC emissions from woodbased panels” Indoor Air, 9: 209–215.Groah 2006

CalEPA (2007) California Air Resources Board (CARB), Initia l Statement of Reasons for Proposed Rulemaking, Proposed Airborne Toxic Control Mea sure to Reduce Formaldehyde Emissions from Composite Wood Products, Offic e of Environmental Health Hazard Assessment, California Environmental Protec tion Agency (CalEPA).

Groah, W. J. (2006). Predicting indoor-air formaldehyde concen trations from emissions of urea-formaldehyde bonded wood products using the Versar mo del. 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. Ber keley, 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 compound2-135

concentrations and emission rates in new manufactured a nd site-built houses”, Indoor Air, 10,178-193.

Jayjock 1994. Back pressure modeling of indoor air concentrations f rom volatizing sources. American Industrial Hygiene Association Journ al, 55: 230-235.

Koontz M.D., Rector H.E., Cade D.R., Wilkes C.R., and N iang 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). F ormaldehyde and other volatile organic chemical emissions in four FEMA tempora ry 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 C haracteristics of Pressed-Wood Products: Report XVIII to the U.S. Consumer Product Safety Commission. ORNL/TM-9867, Oak Ridge National Laboratory, O ak Ridge, TN.

Matthews, T. Hawthorne, A. and Thompson, C. 1987. Formalde hyde Sorption and Desorption. Characteristics of Gypsum Wallboard. Enviro nmental 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 c ase study”, Indoor Air, 5:

104-119.

Meyer B., Hermanns K. (1985) “Reducing indoor air formaldehyde c oncentrations” Journal of the Air Pollution Control Association, 35, 816 -821.

Myers G. and Nagaoka M. (1981) “Emission of formaldehyde by par ticleboard: Effect of2-136

ventilation rate and loading on air-contamination leve ls” Forest Products Journal, 31(7),

39-44.

Myers, G. E. (1983). Formaldehyde emission from particleboa rd and plywood paneling: measurement, mechanism, and product standards. Forest Product s Journal, 33: 27-37. Salthammer T., Fuhrmann F., Kaufhold S. Meyer B. and Sc hwad A. (1995) Effects of climatic parameters on formaldehyde concentrations in i ndoor 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 Emissio ns from Engineered Wood Products: Summary and Evaluation of Current Literatur e" (EPA-600/R-96-067, NTIS PB96-183876, June 1996).

Zinn, T.W., Cline, D. and Lehmann, W.F. (1990) “Long-term stud y of formaldehyde emission decay from particleboard” Forest Products Journa l, 40(6), 15-18.

W. Gene Tucker: It seems to me the main potential users of a model of t his type will be upscale home builders and home manufacturers. They might use it to p redict 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 d ozens (perhaps hundreds) of choices that need to be made in using this sort of model. E ach choice has its uncertainty and the propagation of uncertainties can lead to very im precise estimates.

In the end, I have to wonder whether concentrations pred icted by this model will lead to much more accurate or useful results than would be gotten fr om much simpler displays of emission factor data, loadings, and air exchange rates . Graphs relating these basic parameters to peak indoor concentrations could be created, s imilar to ones that I2-137

presented in the IAQ Handbook some years ago 2 and that others have also suggested. Spreadsheets would probably be preferable. If exposure estim ates are of interest the decay rate of formaldehyde concentration can be predict ed based on selection of a decay constant (or a series of decay constants) that seems a ppropriate for the type of building being considered. While such an approach may arguably be simp listic, 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, the se are important considerations.

Thoughts on a General Introduction to Mass Balances for Indoor Air Quality

Models Most indoor air quality models (and most environmental mode ls, for that matter) are multi-compartment schemes where each compartment is as sumed to be well mixed (i.e.,

has uniform concentrations of the substances of concer n 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 o f each compartment are simultaneously balanced with adjacent compartments.

Textbook descriptions of such models, and documentation th at accompanies their computer programs, often start out with mass balance equa tions 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 t o 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-comp artment system will generally have five terms: what comes out of the compartment (O UT); what comes into it (IN); mass of substance generated in the compartment (GEN); m ass 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 wi th 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 t he 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 re leased into the air inside the compartment. This is often referred to as the “sour ce term”. This can occur as a result of gas-phase chemical reaction, or physical r elease such as evaporation from solid or liquid materials in the compartment

• CONS = mass rate at which the substance is removed fr om the air in the compartment by chemical reaction or irreversible sorp tion to a surface (including an air cleaner in the compartment). This term is ofte n 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 bec ome sources (in which case the accumulation rate is negative). This term i s often referred to as a

“reversible sink” effect.

An introduction of this type can then be followed by mathem atical representations of each of the five terms. In most applications one or mo re of the terms are assumed to be

zero and can be left out of the mathematical discuss ion.3-1

3.0 P EER R EVIEW C OMMENTS O RGANIZED BY R EVIEWER

Peer review comments received for the ER Binding assay are presented in the sub-sections below and are organized by reviewer. Peer revie w 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 t hey appropriate and are they accurately executed? What is your level of confidence in t he indoor air concentrations and exposure estimates provided by the model? Please provide you r rationale for determining the level of confidence. If the level of confi dence 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 tra nsfer. 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 dr y wall). This is likely that the most data are from small scale chamber tests wher e air velocity over the material surface is small compared to the typical airflow condit ions in ventilated rooms. Therefore, the model may underestimate the emission r ates if the emission is indeed controlled by the convective mass transfer process. 2. However, it is more likely that except for the initia l 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. S o the “slope” values derived from the measured data may have included the combined effects of convective mass transfer and internal diffusion resistances, res ulting reasonable predictions. At the “steady state” (about 30 days from initial chamber test ), the internal diffusion resistance should be the dominant resistance for formaldehyde emiss ions even for particleboard. To understand and proof this point, a more detailed numerical si mulation 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 concentrati on based on Mathew’s model, the concentration in a zone that has a higher concentrat ion is assumed to decay exponentially over time, given a half life time as the input paramete r. This approach is unconventional, but practical considering the many uncertainties involve d in real situation. The challenge would be to choose the right the half-life time. An alt ernative 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 particle s/chips. In addition, hydrolysis is possible for additional formaldehyde generation within the m aterial, 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 r elying on measured field data to3-4

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, th e model should provide reasonable conservative estimate of the formaldehyde e xposure 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 rel evant scientific data? If not, specifically note any unreasonable assumptions. Provide su ggestions and references for alternate default assumptions.

Yes.

1.3) Comment on the data sources. Are the data sources reasonab le and accurate? If not, specifically note any unreasonable or inaccurate data source. P rovide 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 th e uncertainty, it is possible to conduct an uncertainty analysis using error propagation the ory 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 plaus ibility of the exposure estimates generated by the exposure model? If not, provide su ggestions for characterizing the exposure assessment estimates.

Yes.

1.7) Are there any other types of data to assess the reliabili ty of the overall exposure model or specific model elements? If so, provide suggestions and re ferences for alternate data types.

I am not aware of additional field data for the assess ment.

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 userfriendliness3-5

of the model.

The interface design is easy to use in general. 1) The online version is very, very slow in response to ev ery click (submission, help, source selection, etc....) 2) Berge and Myer --- temperature effects. It is better t o 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 cabi net? The surface area or the foot print? 4) It would be more convenient for users to select floor t ypes and then provide model coefficients for all the materials involved instead of as king users to “construct the floor”. 5) The screen on “Exposures” is too wide for my notebook (L enovo/Thinkpad X61s). Also, the “Adult”, “Child” should be more visible. 6) The help sign “?” is too visible. Suggest that make it sm aller and place it after the data entry. 7) The “results” file may be made more informative to con clude 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 addit ional help screens that you would find useful.

Yes.

Part 3. Documentation 3.1) Are the references accurately identified? Would any addi tional reference citations be helpful? Please note any additional references that should b e cited.

Yes.

3.2) Does the model documentation present the model construc t, 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 additi onally information.

1) The “steady-state assumption” has been mentioned too ma ny times while describing the user-interfaces. This is not necessary and it distrac ts 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” f or the purpose of simplifying the3-6

calculation without losing too much accuracy. An addition al 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 Construct ion, National Research Council Canada, 733)(IRC-IR-733)

2) The “flow balance” should be changed to “mass flow rat e balance” to be accurate. 3) I am concerned that most data provided on formaldehyde emis sions are from early studies. Much of the manufacturing processes and raw mat erials 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 emi ssions as a result of hydrolysis are also possible. Limitations of the expone ntial decay model should be pointed out. 5) Table 2.4: Why the “medium” and “low” emitting ensemble s have the same slope and intercept for “Shelves”? 6) Regarding Equation 3-5:

CH 2 OER 

### ′ = -m * [CH 2 O] V + b (Eqn. 3-5) where:

m = the mass transfer coefficient (m/hr) [CH 2 O] V = the CH 2 O concentration in the vapor phase (mg/m 3 ) b = a constant; the emission rate at zero CH 2 O concentration in the air (mg/m 2 -hr).

6.1) The Fick’s law is for diffusion, while here the pro cess 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 simp ly the diffusion coefficient in Fick’s law.

6.2) The definition of vapor phase concentration and bulk p hase concentration is unclear. In Eqn. 3-5, [CH 2 O] V should simply be the concentration in the bulk air (ou tside 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 concentra tion 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 con centration in the compartment.

7) Page 4-2: “Product loading rate”---do you mean “loading rati o”? Same in Table 4-1.

3.3) Does the documentation for the FIAM - PWP make clear t he 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 variabil ity in the model prediction. However, it would be helpful if a more quantitative analysis is c onducted on the uncertainties of the model coefficients and how they would propagate to the predicted r esults. And thus the predicted results will be a range (e.g., mean +/-standard deviatio n) instead of a single concentration level.

3.4) Are the model algorithms consistent with the descrip tions in the model documentation? If not, specifically note areas that are inconsis tent 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 Formaldeh yde 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 mode l? 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, not e any areas where errors were found, areas for improvement, or alternate calculatio n methodologies.

While relatively simple and straightforward at its base using first principle scientific relationships, this model, in its totality, is by any meas ure quite complex. The reader who wishes to understand it has to have a competent background i n the modeling sciences, be reasonably motivated and must be able to devote considerabl e time to studying the documentation in order to do so. This complexity puts a he avy burden on the person(s) providing the documentation in order to clearly explain i ts 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 luci d.

Regarding the appropriateness of the algorithms and assumptio ns, as mentioned above, Matthew’s basic approach appears to be based on solid fir st principles of conservation of mass and the validity of diffusion via Fick’s Law. E quation 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). So me 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) w hich is the determining factor and because of typically incomplete mixing within any room volu me the inclusion of F is a perfectly legitimate and suitable modeling construct.3-10

Similarly, equation 3-5 forms the basis for the emissio n 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 Con centration from Volatilizing Sources, Am. Ind. Hyg. Assoc. J . 55 (3): 230-235 (1994)).

Equation 3-5 is reproduced below with slightly different not ation along with an equivalent equation from my previous work.

max ) ( G C m G

ss ss +

− = (equation 3-5 with different notation)

G ss = steady state emission rate (mg/m 2 -hr). Equivalent to CH 2 OER’ G max = the maximum emission rate which occurs at zero backpr essure; that is, at zero concentration of formaldehyde in the a ir (mg/m 2 -hr). Equivalent to b

. m = the mass transfer coefficient (m/hr) C ss = vapor-phase concentration of formaldehyde at steady st ate (mg/m 3 ). Equivalent to [Ch 2 O] 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(

G C C G G rearranged C

C G G

ss

sat ss sat ss

ss



### +

− = − =

C sat = the saturation concentration (mg/m 3 ) 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 rat io) in which the emitting walls were made up entirely of the emitte r of interest and there is zero ventilation.

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

sat 

### C G m max 

### =3-11

Clearly, the relatively straightforward analytical me asurement of C sat could provide a potentially valuable extended methodology for the evaluat ion and development of the model’s parameters relative to specific emitters.

The subsequent development of the model’s complexity wit hin 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 compartm ents, while necessarily quite involved, is logically explained and appears to me to be accur ate.

I believe that the treatment of indoor sinks as develo ped by and explained in the model represent a real step forward in indoor modeling science. F rom my experience few modelers have attempted to address this issue in detail an d 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 sche me 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 incl ude some example data and treatment that illustrates the estimation of paramet ers 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 ac tual 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. Cl early, 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 cred ible 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 adjus tments 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 th at they should be considered accurate within a factor of 2. That is, given a true con centration 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 th e approximations used in the methodology but more from the practical limitations an d 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 source s range from 0.09 to 0.74 mg/m 2 /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 betw een 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 r esults and comparison of modeled/measured values from the pilot study. Despite it s well documented limitations the parameters in this study appear to be reasonably under stood and the model appears to over predict measured values. During the air out period wh en 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, t he 5 age groups for children in the model all show 10 years for the exposure period. O f course, this is impossible for an infant of <1 year or, indeed for any of the age groups fo r children which are all less than 10 years in length. This is explained in the documen tation 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 tim e a person can spend in that age group. The user can then view the help file for speci fic 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 exactl y half the information

needed to understand the risk to human health from this ex posure. 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 reve als the following relevant information regarding this compound. “Formaldehyde is a normal, essen tial human metabolite with a biological half-life of about 1.5 minutes.” Referenc e: http://justthevax.blogspot.com/2009/05/toxin-gambit-part-1-forma ldehyde.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 i ssue with most folks but providing this combined dose over 5 days (730 ppm v/v) as a 5-day l ong bolus would be disastrous to anyone even in the first day (first hour s) 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 CH 2 O is in minutes. Thus, it is not difficult to imagine rela tively high doses of CH 2 O potentially causing biological damage over a period of a few days. As such, the estimation exposure in the Results Screen of Average D aily Concentration (ADC) and Average Daily Dose (ADD) could be of particular signific ance to the toxicologist in assessing the overall risk from exposure to indoor formalde hyde. Depending on the specific details of the toxicokinetics of formaldehyde the toxicologist may be interested in understanding the exposure to humans on the worst (fir st) 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 e rror 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 expos ure. 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, how ever, 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 Simulat ion Language (ACSL) computer language. ACSL easily handles simultaneous dif ferential equations while providing parameter estimates from data via optimization a nd 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 dat a) for the model. ACSL is available in a PC implementation. Please refer to th e 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 adequate ly supported by relevant scientific data? If not, specifically note any unreasona ble assumptions. Provide suggestions and references for alternate default as sumptions.

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 variabl e. 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 wi th this model (ref: Murray,

Donald M. and David E. Burmaster: Residential Air Exchan ge Rates in the United States : Empirical and Estimated Parametric Distributi ons 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 reas onable. 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 interpretatio n) 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 e qual to or less than the years within that age group. Indeed, my sense is that many analy sts 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 source s reasonable and accurate? If not, specifically note any unreasonable or inaccurate data sour ce. 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 cri tical sources within this model are

the chamber tests for emission rates and the fitted va lues for the linear rate model. I am not familiar with these data sources but they seem to b e well described and characterized by the author. I also do not know of other data sources o n 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 inc lude formaldehyde.

1.4) Do the data sources provide unused informatio n that would assist in quantifying uncertainty or variability for subsequent mode l use?

I interpret the above question to mean the data used in t his 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. C learly these data could assist in gauging the variability of this parameter. Also, I belie ve the current data used in the

model on emission sources discloses a level of uncertai nty and variability that could also be mined by a person who is knowledgeable about these data a nd their origins. See

comments below.

1.5) Do the model input variables and the estimates assig ned 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 of3-16

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 resu lt will be variable if different input values are chosen. Thus, a user could choose to use input ted highest emission values (no sinks) which maximize the concentration and exposure wit hin 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 lo w 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 qua ntitative level of variability extant within the system and would be provided w ithin 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 t he 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 b ut would provide a direct and cogent measure of model variability as driven by the input va riables.

1.6) Has EPA provided adequate documentation of the over all 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 sho wn 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 v ery well explained in the documentation, this study appears to provide adequate evidence th at the model is certainly capable of providing credible estimates. I belie ve that this is particularly true

for the model executed in the skillful hands of technica l 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 seco nd) after determining the appropriate model inputs using available information. The mo delers 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 describ ed above (and then comparing them with measurements) could be very valuable in demonstratin g the model’s value in predicting real world concentration and exposures to forma ldehyde.

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 addit ional critical emitter variable –

C sat 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 int ernal 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 t he 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 form aldehyde. One would simply construct a box with an internal volume of 5 l iters. Moderate care should be taken to seal the edges against leakage. The box should be allow ed 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 t he box will hasten equilibrium and assure good mixing during sampling.) Thus, the measured C sat would be equal to the3-18

measured concentration/0.69. As mentioned above having C sat should substantially increase the confidence in the validity of m.

Part 2. User Interface

2.1) Is the FIAM - PWP easy to use? Specifically not e any data entry screens you found confusing or unclear. Provide suggestions to improv e the user-friendliness of the model.

As mentioned above FIAM – PWP is a complicated tool tha t requires a considerable amount of input and performs a significant amount of ca lculation. Considering all that it does I found the user interface is remarkably clean and straightforward. The “tab” format is logical. Also understandable and o bvious is the flow of operations from the first to the last tab. I found the “pull do wn” window input format to be easy and very intuitive. In short, I have no reasonable su ggestions to make it more user friendly.

2.2) Are the model help screens adequate? Desc ribe 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 i ssue, 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 increa se 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 runni ng 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 a ny additional reference citations be helpful? Please note any additional refe rences 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 8 th reference (D. Hare...) can be found

and should be referenced at: http://www.ecobind.com/research/Evaluating_the_Contributio n.pdf (last accessed October 9, 2009). Indeed, any and all the reference partic ularly from the EPA, GEOMET, Versar or industry groups should be identified by the ir web links, if available, and if not available on the web, should be con sidered for posting online

with a link.

The two additional references indicated above (Murray and Burmaster on residential ventilation rate database and Jayjock on “Backpressure” m odeling) should be

considered for inclusion.

3.2) Does the model documentation present the model constr uct, selected model inputs, model results in a clear, complete and useful manne r? 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 documenta tion 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 mysel f compelled to go and3-20

read Chapter 3 (MODEL CALCULATIONS AND ASSUMPTIONS). For me it would be more logical to change the order of these chapter s.

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” a lgorithm in the Eqn 3-6 and 3.8.

3.3) Does the documentation for the FIAM - PWP make cl ear 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 t he basic data-sets and relationships that feed the tool; however, I would have li ked 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 partic ular 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 sec tion (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 re alistically maximize the estimate and then doing the same exercise with paramete rs that would minimize the predictions. This could provide the reader with a quantita tive measure of the anticipated range of variability for the tool.

3.4) Are the model algorithms consistent with the d escriptions in the model documentation? If not, specifically note areas that are inc onsistent between the model and documentation.

Indeed, from what I can determine from studying this work th e 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 coeffic ients have a negative sign and we3-21

are told in footnote g that they are the “Correlation c oefficient 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 (R 2 ) because this value represents the percentage of the variance in the model de scribed by the algorithm. For example, a correlation coefficient R = 0.72 equals R 2 = 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 Produ cts (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, pl ease 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 suffi cient clarity and level of detail; the computational implementation of the model also appears robust an d accurate. Characterizing the mathematical equations (i.e. the basic formulation and assu mptions of the model) as “appropriate,” as per question 1.1, depends of course on the ty pes of questions the model is supposed to answer, and the desired accuracy/precision that i s expected - or, at least, desired - for a given application. Nevertheless, given the simplifying assumption s (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 fo r 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 distributiona l/probabilistic model formulation that explicitly employs available data to develop ranges r ather than point estimates of concentrations and exposures.

Considering the (current) model formulation, FIAM-pwp essen tially 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 st udies), (b) estimation of indoor mixing/dispersion through simple one-zone and two-zone models th at incorporate sink and backpressure effects, and (c) simple inhalation exposure calcu lations 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 cha racterizing 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 formulat ion 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 a vailable indoor air quality and inhalation exposure models. Of course, for any given real-worl d 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 mechani sms in a manner that limits the usage and evaluation of individual model components. Specificall y, though the literature – as well as the provided model documentation – explicitly recognize the f act 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 assumption s of constant rate emissions and the establishment of steady state for indoor air concentrat ion levels (see Sections 3.1 to 3.4 of model documentation). Then, (see Sections 3.5 to 3.6), a deca y rate is imposed upon indoor concentrations, to account for depletion of the formaldehyde sources; this decay rate is parameterized (through half-life values) from experiment al 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 we ll as in the model documentation: these factors are essentially “lumped” in the phenomenological/appare nt concentration decay rate, that obviously is affected by a variety of chemical and physic al 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 pre ssed 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 revie wer’s opinion, the value of the information that has been incorporated in FIAM-pwp woul d be greatly enhanced if its formulation explicitly considered decaying (e.g. exponentiall y 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 inhala tion 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 us ed by the model. Are the default assumptions reasonable and adequately supported by relevant scientifi c 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 involve d 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 accura cy 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. Provi de 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 model ing 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 w ood products (given changes in manufacturing procedures as well as in changes in relative l evels of domestically manufactured versus imported pressed wood products). The answer may in f act be yes, but it should be explicitly stated and supported.

1.4) Do the data sources provide unused information that would ass ist 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 populati on based) indoor concentration and corresponding exposure estimates with explicit characteriz ation of uncertainties and variabilities.

1.5) Do the model input variables and the estimates assigned to th em appropriately reflect variability?

As mentioned in the answers to previous questions, a distri butional/probabilistic approach, for defining model input variables and deriving concentration and exp osure estimates, would, in this3-26

reviewer’s opinion, be more appropriate in relation to this model, given the wide ranges of uncertainties in processes affecting the estimated vari ables and of variabilities in real world scenarios of inhalation exposures to formaldehyde.

1.6) Has EPA provided adequate documentation of the overall plausibili ty of the exposure estimates generated by the exposure model? If not, provide suggestions for char acterizing 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 influe nces of numerous other indoor and outdoor sources and sinks as well as of indoor and outdoor gas a nd heterogeneous phase chemistry of formaldehyde (that may result in net production o r removal in a given microenvironment). Very large variabilities should be expected across regions and populations, with differences in both geographical (e.g. climate vari ables) and socioeconomic factors (housing, occupation, etc.) driving these variabilities. Linking such es timates with corresponding population-based estimates of exposure to outdoor air formalde hyde (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 L iu et al., 2006, reference in the Addendum of this review) would be valuable in assessing, at l east 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 reliabili ty of the overall exposure model or specific model elements? If so, provide suggestions and referenc es for alternate data types.

There are various studies and related data sets, both fr om 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-friendlin ess of the model.3-27

FIAM-pwp is a web-base program that is easy to use at th e “client side” through a browser (MS Internet Explorer). Microsoft technology appears to be used t hroughout 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 challengi ng for some systems – and users. Nevertheless, the web-based version is sufficiently “user-fr iendly” and the data entry screens are clear. However, it should be pointed out that (as experi ence, 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 esti mates. This is particularly true for a model with a deterministic formulation that perfor ms point calculations like FIAM-pwp. Therefore, maybe some “warnings” regarding the level of u ncertainties in the calculations could be incorporated, as reminders, in the data-entry screens.

2.2) Are the model help screens adequate? Describe any additional h elp 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 som e of the entries (that should be consistent with the high uncertainty in the estimates; i n other words, it should, e.g., be made clear to the user that higher precision of the inputs does not necess arily produce improved model estimates).

Part 3. Documentation

3.1) Are the references accurately identified? Would any additi onal reference citations be helpful? Please note any additional references that should be cited.

The Addendum to this review presents a selection of refer ences on indoor air formaldehyde emissions, concentration levels, and relevant physicochemic al 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, s pecifically note areas that are unclear or needs improving. Provide suggestions for additionally information.3-28

The documentation for FIAM-pwp is quite thorough in present ing the model formulation and implementation as well as the data sources that were us ed 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 flow s from/to outside are exactly half the house volume” forgetting the temporal element in the concept of flow, while degrees Kelvin

are denoted as o K rather than K, etc.). However, the main issue with t he 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.) r ather 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? Desc ribe 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 variabilit y and uncertainty associated with various model elements are not fully revealed in the documentat ion. An ideal solution would be a probabilistic “re-formulation” of the model, with explicit di scussion 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 explici tly various sources of uncertainty and variability associated with specific processes and par ameters of the model, along with a factor or range specifying the approximate magnitude of eac h uncertainty/variability, would be extremely useful.

3.4) Are the model algorithms consistent with the description s in the model documentation? If not, specifically note areas that are inconsistent between the mode l and documentation.

The model algorithms appear consistent with model documentati on; 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 towa rds fulfilling a critical need to develop a scientifically valid framework for the characteriza tion of human exposures to formaldehyde. Given the enormous complexity of this problem, it should be r ecognized that additional steps will be needed. In this reviewer’s opinion, development of statis tical distributions of emission rates3-29

for different pressed wood products, that explicitly incorpo rate and quantify the uncertainty and variability in available data, is a much needed next step.

ADDENDUM:

Selected References on Indoor Formaldehyde Emissions and C oncentrations

Ataka, Y., S. Kato, et al. (2004). "Study of effect of a dsorptive 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 performa nce of adsorptive building materials that are used for reducing indoor pollutant concentrations. M ass 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 c orresponds to the mass transfer coefficient when the surface pollutant concentration is zero. Modeling and experimental verification of adsorption were done, demonstrating the pollutant concentration de crease caused by adsorptive building materials. The pollutant reduction phenomena were mode led, including pollutant degradation by chemical reaction and adsorption in building materials. Adsorption tests of gypsum board containing a substance that decomposes HCHO with in the board are reported. The adsorption rate of the gypsum board predicted-by numerica l 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." A IHA Journal 64 : 739–754. Understanding source behavior is important in controlling exposure to airborne contaminants. Industrial hygienists are often asked to inf er emission information from room concentration data. This is not easily done, but mode ls 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 emiss ions set as boundary conditions in computational fluid dynamic (CFD) simulat ions of a workplace. The room3-30

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 generat ion rate profiles, constant and timevarying. The aim was to compute plausible concentratio n fields, not to simulate exactly the processes in a real workroom. Thus, error i s defined here as the difference between model and CFD predictions. For the steady-stat e case the UD model had the

lowest error. When the source near-field contained the b reathing 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 a pplied 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 estima tes using the CM-1 model and some effect using the UD model. A location-specific mixing fact or (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-phas e specific tracer and toxic organic compounds in environmental tobacco smoke." Chemosphere 61 (10): 1512-22. Cigarette smoke constituents are worthy of concern and char acterized 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 con stituents in a real environment. Thirty-four volatile organic compounds (VOCs) including thr ee ETS tracers: nicotine, 2,5- dimethylfuran and 3-ethenylpyridine (3-EP), 19 carbonyl compounds, 54 s emi-volatile compounds (24 polycyclic aromatic hydrocarbons (PAHs) and 30 al kanes) 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 react ions 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 compo unds exhibited little affect. Pearson correlation analyses show that gas-phase and part iculate-phase ETS tracers did not show significant correlation, but within each homologue many of compo unds 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 V OC emissions from wood-based panels." Indoor Air-International Journal of Indoor Air Qualit y and Climate 9 (3): 209-215. Volatile organic emissions from particleboard, medium den sity fibreboard (MDF) and office furniture have been measured in dynamic environmental chambers , both small and room-sized. Characterisation of product emission properties in smal l chambers was possible when inter- and intra-sheet variations were considered. Formaldehyde emiss ion factors for all products were approximately double European low-emission specifications a nd did not decay to the latter for several months. Long term emission behaviour could not be pre dicted from short-term measurements. Volatile organic compounds (VOC) emissions were low for the MDF product, higher for particleboard, and highest for laminated offic e furniture. The compounds emitted differed from those reported in other countries. VOC em issions 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 sever al months.

Brown, S. K., K. J. Mahoney, et al. (2004). "Room chamber a ssessment 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 asse ssed in CSIRO’s Room Dynamic Environmental Chamber. This paper describes the chamber as sessment 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 envir onments. 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 a n insulated dwelling in south-east Australia. The pollutants assessed were nitrogen dioxide, ca rbon monoxide, formaldehyde, VOCs and respirable suspended particulates. One type of heater wa s 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 the se 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 ventil ation strategies on air contaminant concentrations and energy consumption in buildings." Int ernational Journal of Energy Research

25 (12): 1073-1089. Considering the diversity of indoor contaminant characte ristics and generation patterns, finding an appropriate ventilation strategy that can secur e acceptable indoor air quality3-32

with minimum energy consumption is a challenging task f or HVAC system designers and operators. This study theoretically models and investigat es the impact of various ventilation strategies on contaminant concentration be haviour and corresponding ventilation cooling energy requirements for a single-zo ne enclosure. Two types of contaminants are considered; carbon dioxide as an occupan cy dependent and formaldehyde, which is independent of occupancy. An airflo w 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 concen trations. In addition, a building energy simulation model is utilized to predict the corres ponding ventilation cooling energy requirements under hot climatic conditions. Res ults 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 ventilati on energy requirements can be obtained while maintaining acceptable IAQ if proper ventila tion 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 wast e 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 (thic kness 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 great ly reduced their formaldehyde emissions. However, flexural properties and internal bond str ength 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 a ir 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 typical3-33

urban residence in the UK. Unlike previous modelling studies o f indoor air chemistry, the mechanism adopted contains no simplifications such as lumpi ng or the use of surrogate species, allowing more insight into indoor air chemistry than previo usly possible. The chemical mechanism, which has been modified to include the degradati on reactions of key indoor air pollutants, contains around 15,400 reactions and 4700 species. The re sults 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 signif icant 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 highli ght that the most crucial parameters for modelling the concentration of OH are the light-intensit y 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 pla y a major role in producing new radicals, unlike outdoors where photolysis reactions are pivot al radical initiators. In terms of radical propagation, the reaction of HO2 with NO has the mo st profound influence on OH concentrations indoors. Cycling between OH and RO2 is dominat ed 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 highli ght the importance of tailoring a model for its particular location and the need for future indoo r air measurements of radical species, nitrated species such as PANs and organic nitra tes, photolysis rates of key species over the range of wavelengths observed indoors and concurrent measur ements of outdoor air pollutant concentrations. (c) 2006 Elsevier Ltd. All rights reserved.

Carter, R. D. and J. S. Zhang (2007). "Definition of Stand ard Office Environments for Evaluating the Impact of Office Furniture Emissions on Indoor VOC Concentra tions, LB-07-049." ASHRAE

Transactions 113, Part 2

. A representative “worst-case” office environment, which de fines the size and volume of the office space, the amount and type of office furniture sur face area, and the outdoor, clean airflow rate is necessary to estimate the impact of office furni ture emissions on indoor VOC

concentrations based on the emission rates measured from ch amber tests. In this study, 31 randomly selected floor plans from North American offic e 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 spa ce (aisles, etc.) was present and3-34

shared between workstations and other adjoining spaces. T he 90th percentile conditions for total furniture surface area within the 50th percentile workstat ion footprint sizes were identified from the more than 5000 workstations analyzed to provide a represen tative “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 St andard 62.1-2004. The representative “worst-case” standard private office environment for a si ngle 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 as sumed 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). "Characterizat ion 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 o rganic 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 sh arp increase of chamber air formaldehyde concentration to a peak followed by transition t o 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 dur ing 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 replac ing the preservative with a different biocide for the particular paint tested resulted in an a pproximate reduction of 55% of formaldehyde emissions. But the reduction affected only the t hird-stage long-term emissions.

Chen, J., B. Duffy, et al. (2001). "FTIR spectroscopy measur ements and CFD simulations of the3-35

pollutants arising from unflued combustion in a room." Bu ilding and Environment 36 (5): 597-

603. This paper reports on a study of indoor air quality in a sim ulated kitchen environment. Combustion products from unflued combustion from a gas cook-to p in a ventilated room were measured using an extractive FTIR technique. Results we re compared with those from conventional instruments and the FTIR technique was s hown to give good agreement. Detection limits and the effect of H2O and C O2 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 th e 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 Or ganic Compounds in Atopy Patients' Houses

in South Korea." Indoor and Built Environment 18 (2): 144-154. This study was undertaken to determine the concentrations o f volatile organic compounds (VOCs) in the indoor air of atopy patients' (atopic dermat itis 50, allergic asthma 36) and control houses (28 nonpatients). A goal of this study was also to inves tigate whether indoor VOCs were risk factors for the development of atopic sensitizati on. Eleven alkanes, 13 aromatics, 7 chlorinated hydrocarbons, 3 terpenes, and 15 aldehyds were measur ed from 10 March to 15 June, 2006. Aldehyde compounds are the most abundant chemical group in a ll indoor air, followed by aromatic compounds. The geometric mean concentrations of to tal VOC (TVOC) in indoor air in atopic dermatitis and allergic asthma patients' houses wer e 317.1 and 219.2 mu g.m(-3), respectively. However, TVOC concentrations did not differ s ignificantly between control and patient houses in indoor and outdoor air. The geometric mean c oncentrations of benzene, ethylbenzene (p < 0.05), o-xylene, m-, p-xylene, styrene, levels o f 1,3,5-trimethylbenzene and formaldehyde (p < 0.01) in the indoor air of houses of patients wi th atopic dermatitis, and levels of o-xylene and 1,3,5-trimethylbenzene (p < 0.01) in houses of alle rgic asthma patients were significantly higher than those in control houses. The multipl e 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 c oncentrations of formaldehyde. Limonene and alpha-pinene concentrations were significantly i ncreased by the replacement of furniture and the use of cleaning products. The type of heating s ystem was significantly associated with indoor benzene, toluene, ethylbenzene, nonane, de cane, 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 ato py has brought into question the impact of outdoor pollutants and indoor air quality. The contr ibutory role of aldehydes to this problem and the fact that they are mainly derived from the dome stic environment make them of particular interest. This study therefore measures six dif ferent aldehyde levels in Paris dwellings from potentially different sources and identifies their i ndoor determinants. The study was carried out in the three principal rooms of 61 flats with no previous hi story of complaint for olfactory nuisance or specific symptoms, two-thirds of the flats havi ng been recently refurbished. Aldehydes were sampled in these rooms using passive samplers, an d a questionnaire on potential aldehyde sources was filled out at the same time. A multi ple linear regression model was used to investigate indoor aldehyde determinants. Our study revealed th at propionaldehyde and benzaldehyde were of minor importance compared to formaldehyde, acetaldehyde, pentanal, and hexanal. We found that levels of these last four compounds dep ended on the age of wall or floor coverings (renovations less than I year old), smoking, and amb ient parameters (carbon dioxide levels, temperature). These results could help in the as sessment 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 asse ssment." 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 c urrently dominate the market and therefore cannot adequately estimate contributions of ETS to such expos ures. 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 e valuate the potential contribution of ETS to air toxics in indoor air and, therefore to indoor expo sures 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 conditi ons, 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 a mong brands of cigarettes were relatively3-37

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 m eans other than the very low air infiltration rate (0.03 h(-1)), e.g., deposition onto the cha mber surfaces. Emission factors for these compounds were calculated to take these losses into ac count and the rate constants for these

losses were estimated. To estimate indoor concentrations and inhalation exposure s to 16 VOCs, nicotine and PM-2.5, the average emission factors for the six commercia l 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 toxi cs from ETS, under conditions selected to be "typical" rather than extreme, are compa rable in magnitude to average outdoor concentrations, indicating that ETS can be a significant c ontributor to the total indoor concentration and the inhalation exposure for these specie s. 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). "Characteris ation 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 mixt ure of pollutants at concentration levels that are often several times higher than outdoors. These pol lutants are emitted by different sources indoors and outdoors and include volatile organic compo unds (VOCs), carbonyls (aldehydes and ketones) and other chemical substances often ads orbed on particles. Moreover, legal obligations opposed by legislations, such as the Eur opean Union's General Product Safety Directive (GPSD) and Registration, Evaluation, Authorisat ion and Restriction of Chemicals (REACH), increasingly require detailed understanding of where and how chemical substances are used throughout their life-cycle and require better chara cterisation of their emissions and exposure. This information is essential to be able to c ontrol emissions from sources aiming at a reduction of adverse health effects. Scientifically sound h uman risk assessment procedures based on qualitative and quantitative human exposure information al lows a better characterisation of population exposures to chemical substances. In this context, t he current paper compares inhalation exposures to three health-based EU priority subst ances, i.e. benzene, formaldehyde and3-38

acetaldehyde. Materials and methods Distributions of urban population inhal ation exposures, indoor

and outdoor concentrations were created on the basis of meas ured AIRMEX data in 12 European cities and compared to results from existing European popula tion exposure studies published within the scientific literature. By pooling all EU city personal exposure, indoor and outdoor concentration means, representative EU city cumulative f requency 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 inhalati on exposures were compared to modelled population exposures. The contributions of these microenvironments t o the total daily inhalation exposure of formaldehyde, benzene and acetaldehyde were estimate d. Inhalation exposures were compared to the EU annual ambient benzene air quality guideli ne (5 mu g/m(3)-to be met by 2010) and the recommended (based on the INDEX project) 30-min ave rage formaldehyde limit value (30 mu g/m(3)). Results Indoor inhalation exposure contributions are much highe r compared to the outdoor or in-transit microenvironment contributions, accounting f or almost 99% in the case of formaldehyde. The highest in-transit exposure contribution was fo und for benzene; 29.4% of the total inhalation exposure contribution. Comparing the pooled AIRM EX EU city inhalation exposures with the modelled exposures, benzene, formaldehyde and a cetaldehyde 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), respect ively. 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 cha llenges concerning exposure and time-activity data, comparability and scarce or miss ing in-transit data inducing careful interpretation of the results. The results obtained by AI RMEX 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 ai r 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. Conside ring 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 ur ban populations were assessed on the basis of novel and existing exposure data. Th e indoor residential microenvironment contributed most to the total daily urban populat ion inhalation exposure. The results presented in this paper suggest that a significant part of the populations living in European3-39

cities exceed the annual ambient benzene air quality guide line 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 co nsequent health effects, adequate measures must be taken to diminish emissions from so urces such as materials and products that especially emit benzene and formaldehyde in indoo r 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). "Mode l Development and Validation of Personal Exposure to Volatile Organic Compound Concentrations." Environm ental Health Perspectives 117 (10):

1571-1579. Direct measurement of exposure to volatile organic compound s (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 m icroenvironment 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 diari es and to compare modeled with measured exposures in an independent data set. Materials: VOC PEs and a range of microenvironment concent rations were collected with active samplers and sorbent tubes. Data were supplemented w ith 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 us ed for validation purposes. Results: The best model able to predict PE with independenc e of measurements was based upon stratified microenvironment concentrations, lifestyl e factors, and individual-level activities. The proposed model accounts for 40–85% of the vari ance 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 perso nal 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 tempor al 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 tra ck 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 w ithin 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 tha t 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 t he sampling locations to the indoor sources. A large degree of temporal variability also wa s 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 s ignificant rates, both the spatial and temporal variability tended to range within an order of m agnitude at each location.

Gilbert, N. L., D. Gauvin, et al. (2006). "Housing charact eristics and indoor concentrations of nitrogen dioxide and formaldehyde in Quebec City, Canada." Environmenta l Research 102 (1): 1-8. Concentrations of nitrogen dioxide and formaldehyde were deter mined in a study of 96 homes in Quebec City, Canada, between January and April 2005. In addi tion, relative humidity, temperature, and air change rates were measured in homes , and housing characteristics were documented through a questionnaire to occupants. Half of t he homes had ventilation rates below 7.5 L/s person. Nitrogen dioxide (NO2) and formaldehyde concentr ations 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 m u g/m(3) (geometric mean of 29.5 mu g/m(3)), respectively. The housing characteristics docu mented 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. F ormaldehyde concentrations were negatively correlated with air change rates and were si gnificantly 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 con tribution of indoor combustion sources, including wood-burning appliances, to indoor levels of f ormaldehyde. These results3-41

suggest that formaldehyde concentrations in Quebec City homes are caused primarily by offgassing, and that increasing air change rates in homes c ould 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 relationsh ip 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 documente d. 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 rec ent off-gassing sources of formaldehyde, and 0.37 h(-1) in homes heated mainly by electric al baseboard heaters. These results indicate that ventilation effectively decreases f ormaldehyde concentrations, but some categories of homes such as those with new off-gassing sour ces 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 right s reserved.

Gilbert, N. L., M. Guay, et al. (2005). "Levels and determ inants of formaldehyde, acetaldehyde, and

acrolein in residential indoor air in Prince Edward Isla nd, Canada." Environmental Research 99 (1): 11-17. This study was undertaken to determine the concentrations o f formaldehyde, acetaldehyde, and acrolein in air samples taken in some Canadian houses an d 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 inspect ion 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 m u 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 ele vated in homes inhabited by at

least one smoker and in homes built 1970-1985 and were correlated w ith absolute humidity and carbon dioxide, two variables likely to be surrogates for l ower air exchange rates. In conclusion,3-42

lower air exchange rates appear to be important determinan ts 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 o f 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-DNP H). The formaldehyde 2,4- dinitrophenylhydrazine derivative (formaldehyde-2,4-DNPH) is extrac ted from the filter, and the concentration is determined by high performance liquid chr omatography. The technique has been Validated against an active sampling method, and the a greement is close when the appropriate laminar boundary layer depth is applied to the passive measurem ent. For this technique an exposure period of 3 days is equivalent to a limit of det ection of formaldehyde of 3.4 ppbv and a limit of quantification of 7.6 ppbv. To test the performan ce 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 concent rations 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 forma ldehyde concentrations. The model, based on mass balance principles, can accommodate i nput information from up to six formaldehyde sources. Laboratory data were available chara cterizing emission characteristics of four primary wood product formaldehyde sources used in an EPA an d Composite Panel Association (CPA) home study project. Using product source i nputs, Versar initial home concentration outputs were reasonably consistent with measur ed formaldehyde in the test home, particularly when the gypsum wallboard sink/re-emitter wa s considered a fifth formaldehyde

source in the model.

Guo, H., N. H. Kwok, et al. (2009). "Formaldehyde and volatile o rganic compounds in Hong Kong3-43

homes: concentrations and impact factors." Indoor Air 19 (3): 206-217. This paper presents formaldehyde and volatile organic compou nds (VOC) concentrations, potential sources and impact factors in 100 homes. The 24-h a verage formaldehyde concentration in 37 homes exceeded the good class of the Hong Kong Indoor Air Qua lity Objectives (HKIAQO), whereas the total VOCs concentration in all home s was lower than the HKIAQO. Compared to other East Asian cities, indoor formaldehyde and s tyrene in Hong Kong was the highest, reflecting that the homes in Hong Kong were more af fected by household products and materials. The formaldehyde concentration in newly built apa rtments 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 forma ldehyde and toluene between smoking and non-smoking homes, suggesting that cigarette smoking was n ot the major source of these two species. Homes of a couple with a child had higher formalde hyde and acetic acid concentrations, while homes with more than three people had higher concent rations of 1-butanol, heptane and dlimonene. When shoes were inside the homes, heptane, acetic aci d, nonane and styrene concentrations were statistically higher than that when s hoes were out of the homes. Furthermore, higher levels of 1,2,4-trimethylbenzene, styrene, nonane and hepta ne were found in gas-use families rather than in electricity-use homes.Long-term e xposure to formaldehyde and volatile organic compounds (VOC) in indoor environments may cause a num ber 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 l evels, 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 m akers 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." America n 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 Est imating 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 remova l of offending products may be costly or otherwise impractical, it is important th at the emissions of organic pollutants be understood prior to incorporation of these materials into build ings. 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 devel oped to predict the behavior of emission rates under various indoor conditions. Examples of the type of r equirements that must be addressed in developing models for estimating organic emi ssions from building materials into the indoor environment are presented. Important factors include t he products' characteristic source strengths at standard test conditions, impact of variati ons in environmental conditions (such as temperature and humidity), concentrations of the modeled o rganic 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 a ll building materials may not be feasible due to the tremendous variety of organic products an d building materials in use, the most studied of the volatile organic compounds from building mater ials, formaldehyde, is used to illustrate an approach to the development of a specific mode l for organic emissions.

Hayashi, M., M. Enai, et al. (2001). "Annual characterist ics of ventilation and indoor air quality in detached houses using a simulation method with Japanese dail y schedule model." Building and

Environment 36 (6): 721-731. This paper presents the results of investigations that we re made on a simulation program, which calculates the temperature, the heat loads, the ventilati on rates and the indoor air quality considering the Japanese daily schedule and the dweller's beh aviour toward keeping comfortable indoor climate, in order to explain the effect of ventilat ion systems. In the investigation, the concentrations of carbon dioxide, carbon monoxide and formalde hyde are regarded as indicators of indoor air quality. Firstly, three types of systems w ere designed in a house model; that is a basic passive ventilation system, a passive stack ventilati on system and a mechanical ventilation system. Next, the simulation was performed using the stand ard weather data on three cities in Japan; and the simulation made clear the annual character istics 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 fl oor. Lastly, the performance of the ventilation systems and the solution methods of realizing the se ventilation systems were3-45

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 c oncealed 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 rat es 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 concea led spaces for better indoor air quality in some kinds of building structures and some kinds of ventilat ion systems. In this study the influences of the concealed pollution sources upon the indoor conc entrations 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 r eached 50% in the house with the exhaust-ventilation system. Therefore, it became clear t hat the use of the medicine to prevent the

deterioration of the wooden structure and the white ants in t he crawl spaces must be limited. The ratio from the envelope wall was changed with the pressure d ifference between inside and outside. These results showed that it is necessary to preven t 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 o ccupancy 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 problem s; however, the type of3-46

building and the degree of human density may not be the m ost crucial causes of IAQ problems. Because IAQ problems occur as a result of inten sive exposure levels to indoor air pollutants, the key factors are in fact duration of e xposure time to them and their

concentration levels. Therefore to look at these fac tors as potential environmental causes of adverse health effects, user activities in a low-dens ity residential environment were studied by means of a post occupancy assessment, and a simu lation of indoor airflow was also undertaken. The pattern of indoor usage and of indoor airf low has revealed that problems of indoor safety and livability can in fact be ass ociated with IAQ even in a lowdensity context.

Hodgson, A. T., D. Beal, et al. (2002). "Sources of formalde hyde, other aldehydes and terpenes in a new

manufactured house." Indoor Air 12 (4): 235-242. Formaldehyde, less volatile aldehydes, and terpene hydrocarbons a re 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 construc ted, 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 da ys, and tested for emissions of formaldehyde and other target compounds using small-scale ch ambers. Several cabinetry materials, passage doors, and the plywood subfloor were the predom inant sources of formaldehyde and other aldehydes. The plywood subfloor was the predomin ant terpene source. Whole-house emission rates for combined materials were predi cted based on the emission factors and the corresponding material quantities. These predictedrates 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 form aldehyde, the predicted and derived

rates were within a factor of two. Four emission barrie rs 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 volatil e tracers to determine the contribution of environmental tobacco smoke to concentrations of volatile orga nic 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 trac ers and ten selected VOCs in ETS were3-47

first measured in a room-size environmental chamber for a market-weighted selection of six commercial cigarettes. The ratios of the emission rate s of the tracers to the emission rates of the selected VOCs were calculated and compared among the six br ands. The utility of the tracers was then evaluated in a field study conducted in five office buil dings. Samples for VOCs were collected in designated smoking areas and adjoining non-smoking areas, air change rates were measured, and smoking rates were documented. Concentration s 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 selecte d as the most suitable tracer for the volatile components of ETS, although pyrrole is also potent ially 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 b enzene 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 organi c 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 install ation and in seven new sitebuilt houses 1-2 months after completion. The houses were in f our projects located in hot-humid and mixed-humid climates. They were finished and oper ational, 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 bot h manufactured and site-built houses, the predominant airborne compounds were alpha-pinene, f ormaldehyde, 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 o f 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 volatil e compounds. Generally, the ratios of emission rates at the low and high ventilation rates de creased with decreasing compound volatility. Changes in VOC emission rates in the manufactur ed houses over 2-9.5 months after installation varied by compound. Only several compounds show ed a consistent decrease in3-48

emission rate over this period.

Hodgson, A. T., D. G. Shendell, et al. (2004). "Comparison of pr edicted and derived measures of volatile organic compounds inside four new relocatable classrooms." Indoo r Air 14 : 135-144. Our objective was to develop a process for selecting inte rior finish materials having low impacts with respect to emissions of toxic and odorous volatile or ganic compounds (VOCs) for school relocatable classrooms (RCs). A laboratory study identifi ed 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 napht halene, were measured during school hours over 8 weeks in the succeeding fall cooling se ason. Indoor minus outdoor VOC concentrations with an advanced HVAC operated were l ow; only formaldehyde concentrations exceeded 5 p.p.b. Classroom VOC concentrations w ere 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 volat ile 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 th ese 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 we re 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, a nd 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 emi tted formaldehyde, vinyl acetate,3-49

isooctane, 1,2-propanediol, and 2-ethyl-1-hexanol. Of these, vinyl ace tate and propanediol had the highest concentrations an emission rates. The carpet wit h a polyurethane backing primarily emitted butylated hydroxytoluene. With the exception of forma ldehyde, little is known about the

health effects of these VOCs at low concentrations.

Hollowell, C., D. and R. R. Miksch (1981). "Sources and co ncentrations 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 emi ssions from conversion varnishes." Journal of the Air & Waste Management Association 48 (10): 924-930. Conversion varnishes are two-component, acid-catalyzed var nishes that are commonly used to finish cabinets. They are valued for their water and s tain resistance, as well as their appearance. They have been found, however, to contribute to indoor emissi ons of organic compounds. For this project, three commercially available conversion varni sh 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 wa s used to determine uncombined (free) formaldehyde content of the varnish components. The resin compone nt 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 test s 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 necessari ly the same as those in the

formulation. Results of small chamber tests showed tha t the amount of formaldehyde emitted from these coatings was 2.3-8.1 times the amount of free fo rmaldehyde 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 a ir quality (IAQ) objectives on air-conditioned offices in Hong Kong." Environmental Monitoring and Assessmen t 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 pla n. 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), re spirable suspended particulates (RSP), nitrogen dioxide (NO2), ozone (O-3), fo rmaldehyde (HCHO), total volatile organic compounds (TVOC), radon (Rn), and airborne bacteria count (ABC). Although average3-50

office IAQ performance has been improved since the implemen tation of this certification scheme,

there are still resource issues and technical difficult ies. 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, th ree of the nine listed common air pollutants were selected as the 'representatives' for th e overall satisfactory IAQ. Together with the assessment results of 422 Hong Kong air-conditioned offices, the i ndex was evaluated in terms of test sensitivity, specificity and predictive values. Prove d to be feasible to describe the IAQ of some air-conditioned offices, this IAQ index would be a useful t ool for policymakers, building owners and professionals to quantify IAQ performance in offices and to make decisions on resources and manpower management for efficient mitigati on actions.

Kelly, T. (1996). Determination of Formaldehyde and Toluene Di isocyanate Emissions from Indoor Residential Sources. Sacramento, CA, California Air Re sources Board : 93-315. Building materials and consumer products found in Califor nia residences were subjected to chamber testing to determine the emission rates of forma ldehyde (HCHO) and of Toluene DiIsocyanates (TDI). The emissions of formaldehyde weredetermined from bare UreaFormaldehyde (UF) and Phenol-Formaldehye (PF) wood products, with vinyl, paper, and other coatings, and from decorative laminates, permanent press f abrics fiberglass insulation, paper goods, paints, cosmetics, and acid-cured coatings. Other com pounds 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 Environme ntal 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 sum mer seasons 1999. The mean daytime formaldehyde concentrations in kitchens, bedrooms and living r ooms were 89, 100 and 100 ppb, respectively, in the seven flats. Significant positive co rrelations 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 concent rations in these three rooms. The maximum mean concentration of formaldehyde (147 ppb) was recorde d in a new flat, while the minimum concentration (43 ppb) was observed in an old flat. The maximum hourly and daytime3-51

concentrations were 350 and 225 ppb, respectively. Air tempera ture, relative humidity and the age of the flat are factors affecting the emission and c oncentration of formaldehyde. The maximum indoor and outdoor formaldehyde concentrations were rec orded during the summer season. During the spring, 38% of the samples indicated that t he concentration of formaldehyde in the seven flats exceeded 0.1 ppm, the American Society of H eating, Refrigerating, and Air Conditioning Engineers' (ASHRAE) standard; in the summer, thi s figure increased to 53%.

Kim, S. and H. J. Kim (2005). "Comparison of formaldehyde emiss ion 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 ef fect 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 parti cleboard 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 a bout 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 pa rticleboard it was 4.73 and 4.95 mg/l, respectively. Floor materials were under E1 grade w hile 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 f urniture materials mostly existed at room temperature. At 37 and 50 degrees C, the formaldehyde em ission 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 emi ssion 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 mat erials such as MDF and particleboard. As these materials are not exposed to hi gh 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 wi ll be variations with the volume of furniture materials and the indoor conditions, furniture mate rials are the principal cause of indoor air quality pollution in Korean with the under heating system

.

Kirkeskov, L., T. Witterseh, et al. (2009). "Health evaluat ion 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 scre ened for chemical compounds, and five3-52

of the most used products which emitted more than 800 mu g/kg were selected for further quantitative analyses by climate chamber measurement (ir oko, ramin, sheesham, merbau, and rubber tree). Samples of exotic wood (rubber tree and belalu) we re further analyzed for emission of chemical compounds by migration into artificial saliv a 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 po se a problem if used as kitchen utensils, as children's toys, or when they are in close contact w ith the skin for a long time.The authors investigated the chemical emissions from selected products f rom 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 comp ounds 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 a nd 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 chromatog raphy. 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 derivat ization with o-(2,3,4,5,6- pentafluorobenzyl)hydroxylamine hydrochloride and (b)the convention al National Institute for Occupational Safety and Health (NIOSH) 2451 method. Sampling ti me for SPME fiber ranged from 10 min for grab sampling to 8 h for TWA sampling. Sampl ing 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 c orrelated 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 o f 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 qualit y 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 s uch as temperature, relative humidity (RH), carbon dioxide (CO2), sulphur dioxide (SO2), nitric oxide (N O), nitrogen dioxide (NO2), respirable particulate matter (PM10), formaldehyde (HCHO), an d total bacteria counts were monitored indoors and outdoors simultaneously. The average resp irable particulate matter concentrations were higher than the HK Objective, and the ma ximum 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 quali ty problems in Hong Kong were PM10 and CO2 levels. (C) 2000 Elsevier Science Ltd. All rights res erved.

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 s uch as homes, offices, schools, shopping malls and restaurants were investigated. Average CO 2 levels and total bacteria counts in air-conditioned classrooms, shopping malls and restaurants wer e comparatively higher than those measured in occupied offices and homes. Elevated CO, leve ls exceeding 1000ppm and total bacteria counts resulted from high occupancy combined with ina dequate ventilation. Average PM10 levels were usually higher indoors than outdoors in homes, shoppi ng malls and restaurants. The highest indoor PM10 levels were observed at investigated r estaurants 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 indo or environments when building material, smoking and internal renovation work were present . Volatile organic compounds (VOCs) in both indoor and outdoor environments mainly resulted f rom 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 emis sions 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 emis sions 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 orga nic compounds (VOCs), carbonyls, carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx) , methane (CH4) and nonmethane hydrocarbon (NMHC). The particulate matters emit ted from all the incense significantly exceeded the Recommended Indoor Air Quality Objectives for Offi ce 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 si x types of incense were higher than the HKIAQO. The highest formaldehyde level exceeded the standa rd 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 tes ted. In addition, the benzene concentrations of all tested incense were significantl y higher than the HKIAQO standard. Although Incense 2 and 6 were claimed to be environmental fr iendly, the quantity of the pollutants emitted was not observed to be lower than the ot hers. It was observed that when comparing the gas pollutant emission factors between two ma jor 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 incens e (i.e. Incense 10). However, the carbonyl compounds emission sequence was traditional incens e > 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 r eserved.

Li, Y., K. Wang, et al. (2005). Measurement and Predicti on of Indoor Formaldehyde Concentration in

Northeast China . Air and Waste Management Association’s 98th Annual Meeti ng & Exhibition, Minneapolis, MN, USA. With the development of economy and the improvement of living condi tion, 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 Harbi n, 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 of3-55

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 averag e indoor formaldehyde concentration and the monthly average temperature (R2=0.8652) was obtained. F urthermore, 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 venti lation 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 s hort-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 v olatile organic compounds (TVOC). Formaldehyde and TVOC concentrations were measured by continu ous photo-acoustic Multi-Gas monitor. The air-change rates were estimated by tracer g as concentration decay method in every test space. Air Exchange Efficiency (AEE) and Effective V entilation Rate (EACH) were also calculated to characterize the ventilation pattern and m ixing factor. Our results show that the increase of effective ventilation could reduce formaldehyde a nd TVOC in office buildings . We therefore suggest that increasing ventilation efficiency a ppears 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 loca tion on the design and performance of the displacement ventilation (DV) sys tem. The results are reported in terms of thermal comfort and indoor air quality. The st udy 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 investigate d. The results indicate3-56

that the supply should be located near the center of th e room rather than to one side of the room. This will provide a more uniform thermal condition i n the office. The DV system was found to be effective in dispersing VOCs within an o ffice environment for all cases

studied. The exhaust was found to have minimal effect on t he thermal comfort. For a DV system in Hong Kong, it is possible to use 100% fresh air wi thout extra energy consumption. (c) 2004 Elsevier Ltd. All rights reserved.

Lin, Z., T. T. Chow, et al. (2005). "Comparison of perform ances of displacement and mixing ventilations. Part II: indoor air quality." International Journal of R efrigeration-Revue Internationale Du Froid 28 (2):

288-305. A numerical simulation using a validated computational f luid 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 r esults 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 vo latile organic compounds, toluene, benzene and formaldehyde, which are commonly found in indoor room fur nishings. The case studies include offices, classrooms, retail shops and indust rial workshops, under typical Hong Kong thermal boundary conditions. Compared with conventional MV, d isplacement 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 suppl y 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 secon d part of a 2 part series and the results are reported with regard to Indoor Air Quality (I AQ). 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 for maldehyde. The change in supply temperature from 19 degrees C to 22 degrees C was found t o 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 displ acement ventilation (DV) system. Two different headroom heights in a space were simulate d and compared. It was found that the effect of increased headroom was to improve th e thermal comfort of the indoor space. It was also concluded that given the thermal bounda ry conditions commonly encountered and the typical low headroom found in Hong Kon g, 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." Journa l of Toxicology and Environmental Health, Part

B 6 (1): 85-114. Formaldehyde has been assessed as a Priority Substance unde r the Canadian Environmental Protection Act. Probabilistic estimates of exposure of the general population in Canada to formaldehyde in ambient and indoor air are presented. Criti cal health effects include sensory irritation and the potential to induce tumors in the uppe r 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 typi cally 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 cytotoxic ity 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 irr itation is minimal (i.e., 0.1 mg/m 3 ), risks of respiratory-tract cancers for the general po pulation estimated on the basis of a biologically motivated case-specific model are exceedingly l ow. This biologically motivated case-specific model incorporates two-stage clonal expansion and is supported by dosimetry calculations from computational fluid dynamics analyses of f ormaldehyde 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 exp osure and in characterization of hazard and dose response are delineated.

Liu, W., J. Zhang, et al. (2006). "Concentrations and sourc e 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 conce ntrations of 10 carbonyl compounds3-58

(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 twi ce in different seasons; the sampling duration was 48 hr each time. The authors observed hi gher concentrations for most of the measured carbonyl compounds on warmer days, reflecting l arger contributions of photochemical reactions on warmer days. The estimated cont ributions of photochemical production varied substantially across the measured carbonyl compounds and could be as high as 60%. Photochemical activity, however, resulted in a net lo ss for formaldehyde. The authors used stepwise multiple linear regression models to evaluate t he impact of traffic sources and meteorological conditions on carbonyl concentrations using the d ata collected on colder days (with lower photochemical activities). They found that the c oncentrations of formaldehyde, acetaldehyde, acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyoxal, and methylglyoxal significantly decreased with increasing distan ce between a measured residence and one or more major roadways. They also found significant ne gative associations between concentrations for most of the measured carbonyl compounds a nd each of the following meteorological parameters: mixing height, wind speed, and pr ecipitation.

Liu, W., J. Zhang, et al. (2006). "Estimating contributions o f 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 hea lth 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 dat abase established in the relationships of indoor, outdoor, and personal air (RIOPA) study to esti mate indoor source strengths of 10 carbonyls and outdoor contributions to measured indoor concentrat ions 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 mea sured carbonyls, formaldehyde, and acetaldehyde had the strongest indoor source stre ngths with the estimated median values of 3.9 and 2.6 mg h(-1), respectively. Hexalde hyde also had large indoor source strengths with a median of 0.56 mg h(-1). Acetone had the la rgest variations in indoor source strengths ranging from undetected to 14 mg h(-1). The median s 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 detecte d in the majority of the RIOPA homes that were selected to have only nonsmoker residents. C onsistent with the indoor source strength results, our estimated outdoor contributions to indoo r concentrations were low for3-59

formaldehyde. In contrast, more than 90% of the indoor concentr ations for acrolein and crotonaldehyde were from outdoor sources. The outdoor contributions t o indoor concentrations for acetone, propionaldehyde, benzaldehyde, glyoxal, and methylglyoxal r anged from 10 to 90% across the RIOPA homes, suggesting that both indoor and outdoor s ources had contributions to indoor concentrations of these compounds. (c) 2006 Elsevier Lt d. All rights reserved.

Liu, W. L., J. F. Zhang, et al. (2003). "Mosquito coil em issions and health implications." Environmental Health Perspectives 111 (12): 1454-1460. Burning mosquito cods indoors generates smoke that can contr ol 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 conducte d the present study to characterize the emissions from four common brands of mosqui to 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; P M2.5), polycyclic aromatic hydrocarbons (PAHs), aldehydes, and ketones. Having applied these measured e mission rates to predict indoor concentrations under realistic room conditions, we found that pollutant concentrations resulting from burning mosquito coils could substantially exceed healt h-based air quality standards or guidelines. Under the same combustion conditions, the tested Ma laysian mosquito coils generated more measured pollutants than did the tested Chinese mosqu ito 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 exa mined 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 hea lth risks. For example, burning one mosquito coil would release the same amount of PM2.5 m ass 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 a nd five BTEX (benzene, toluene, ethylbenzene and xylenes) were measured in four hosp itals of Guangzhou from 2nd January to 20th March 2004. Samples were collected in five con secutive daytimes for each hospital. Among most of the samples, acetone was the most a bundant carbonyl, followed by acetaldehyde, 2-butanone or formaldehyde. Toluene was the most abun dant BTEX and the others3-60

were at similar levels. The relatively higher acetone conc entrations 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 th at of formaldehyde, might be resulted from the wide use of ethanol in hospital. The parti al oxidation of ethanol may form acetaldehyde. The indoor concentrations of carbonyls and BTEX we re found a little higher than their outdoor counterparts with only a few exceptions, which s howed the anthropogenic sources for these compounds. The low correlations between most car bonyls 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 et hanol/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 w ith Au, Cu, Pt or Pd metal catalysts. The characteristics of the multi- dimensi onal signals from the eight sensors are evaluated. A multilayer neural network with an error backpr opagation ( BP) learning algorithm, plus the principal component analysis ( PCA) technique, is implemented to recognize these indoor volatile organic compounds ( VOC). Th e results show that the micro gas sensor array, plus the multilayer neural net work, 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 vol atile 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 D isease Control and Prevention (CDC), Lawrence Berkeley National Laboratory (LBNL) entered i nto an interagency agreement with CDC to help identify mitigation strategies for reducing ind oor emissions of volatile organic compounds (VOCs) including formaldehyde in Federal Emergenc y 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 ( μ g h-1 per m2 of floor area) for each of the four THUs were made at FEMA’s Purvis Mississippi staging yard usi ng 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 μ g m-3 (0.31ppm) to 632 μ g m-3 (0.52 ppm) in the morning, and from 433 μ g m-3 (0.35 ppm) to 926 μ g 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 c hambers using a standard, accurate mass balance method. Quantification methods for the VOCs i ncluded 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 ( μ g 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 concentrat ions 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 aga inst those measured in other types of housing and the materials used in their construction. Whol e THU emission factors for most VOCs were similar to those from comparative housing. The th ree 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 μ g m-2 h-1 in the morning and 257 to 347 μ g m-2 h-1 in the afternoon. Median formaldehyde emissions in previously studied site-built and manufactured

homes were 31 and 45 μ g m-2 h-1, respectively. Only one of the composite wood mate rials that was tested appeared to exceed the US Department of Housi ng 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 loa ding 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 re sponsible 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 Scie nce & Technology 43 (15): 5626-5632. Indoor concentrations of 33 volatile organic chemicals were m easured in four unoccupied3-62

temporary housing units (THUS) belonging to the U.S. Federal Em ergency Management Administration (FEMA). The highest level contaminants in t he 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 organ ic compounds (VOCs) were higher than published concentrations in other dwellings, but whol e THU emission factors for

most chemicals were either lower than or similar to va lues reported for newly constructed homes. However, several chemicals exceeded previously measured new buildi ng 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 c ontaminants. The individual materials were grouped by material type, and emissions were used to derive exposure concentrations for comparison to reference values. Using material loading fa ctors and ventilation rates that are relevant to the trailers, all of the material types w e 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 t o material surface areas, may explain the high concentrations of some VOCs and formaldehyde.

Mendell, M. J. (2007). "Indoor residential chemical emissions a s 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 reside ntial chemical emissions, or emission-related materials or activities, and respira tory health or allergy in infants or children. Associations, some strong, were reported between many ris k factors and respiratory or allergic effects. Risk factors identified most frequently inc luded 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. E levated risks were also reported for renovation and cleaning activities, new furniture, and carpet s 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 correlate d, truly causal exposures. Nevertheless, overall evidence suggests a new class of residential risk f actors for adverse respiratory effects, ubiquitous in modern residences, and distinct from those curr ently recognized. It is important to confirm and quantify any risks, to motivate and guide ne cessary 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 sa mples 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 we re elevated in homes inhabited by at least one smoker and were correlated with indoor an d outdoor temperature, age of house and density of plywood furniture. Sufficient sample numbers w ere 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 apart ments from laboratory measurements of source strengths, using formaldehyde and Total Volatile O rganic Compounds (TVOCs) as model pollutants. The sources in two test apartments wer e grouped into two: building-related sources and occupant-related sources. The measured source s trengths and ventilation rates were used for the prediction of concentrations expected in the a partments. 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 labo ratory can be used to predict the long-term concentration of the two model pollutants in the apart ments. Considering the measured differences in ventilation between the apartments, an oc cupant 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 emissi on 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 me chanically ventilated buildings may be altered by pollutant emissions from and interactions with d uct materials. We measured the emission rate of volatile organic compounds (VOCs) and aldehyde s from materials typically found in ventilation ducts. The emission rate of VOCs pe r exposed surface area of materials was found to be low for some duct liners, but high for duct sea ling caulk and a neoprene gasket. For a typical duct, the contribution to VOC concentrations is predic ted to be only a few percent of common indoor levels. We exposed selected materials to sim ilar to 100-ppb ozone and measured VOC emissions. Exposure to ozone increased the emission rate s of aldehydes from a duct liner, duct sealing caulk, and neoprene gasket. The emission of al dehydes 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 galva nized sheet metal to predict how much ozone might be removed by a typical duct in ventilation s ystems. For exposure to a constant ozone mol fraction of 37 ppb, a lined duct would initial ly 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 i s exposed to the airstream, the removal efficiency would be much lower, similar to 0.02%. Therefo re, 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 ai r quality assessment parameter for airconditioned offices." Building Services Engineering Research & Technology 28 (3): 265-274. Representative assessment parameters are proposed for i ndoor 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 asses sment 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-conditione d offices of Hong Kong and evaluates the contribution of the airborne fungi to an unsatisfa ctory 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 selecting3-65

representative IAQ assessment parameters was examined ag ainst an express assessment protocol (EAP), which assessed some dominant contributors of unsatis factory 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 airbo rne bacteria count (ABC) for air-conditioned offices of Hong Kong. Practical applications: This study has shown that the as sessments of airborne fungi levels in office environment is an important issue and further inves tigations for the airborne fungi in the IAQ audits were thus recommended. The results of this study c ould be a useful source of reference for policymakers in evaluation of an effective I AQ assessment protocol with some representative IAQ assessment parameters.

Nazaroff, W. W. and C. J. Weschler (2004). "Cleaning produc ts and air fresheners: exposure to primary and secondary air pollutants." Atmospheric Environment 38 (18): 2841-2865. Building occupants, including cleaning personnel, are expose d 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 toxi c air contaminants (TACs) and a subset of these are regulated by the US federal government as hazardo us air pollutants (HAPs). California's Proposition 65 list of species recognized as carcinogens or r eproductive 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 ot her 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 rea cts rapidly with organics, leading to the formation of other potentially toxic air pollutant s. Indoor reactive chemistry involving the nitrate radical and cleaning-product constituents is also o f 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 concentration s of TACs that might result from primary emissions or secondary pollutant formation follow ing the use of cleaning agents and air fresheners. In this paper, we combine direct empiri cal evidence with the basic principles of indoor pollutant behavior and with information from rele vant studies, to analyze and critically assess air pollutant exposures resulting from the use of cle aning 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 rea dily react to generate secondary pollutants. The toxicity of many of these secondary pollutant s has yet to be evaluated. The inhalation intake of airborne organic compounds from cleaning product use is estimated to be of3-66

the order of 10 mg d(-1) person(-1) in California. More tha n two dozen research articles present evidence of adverse health effects from inhalation exposure as sociated 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 pr oduct composition, usage, building occupancy, emission dynamics, transport and mixing, building ventilation, sorptive interactions with building surfaces, and reactive chemistry. Current unders tanding is sufficient to describe the influence of these variables qualitatively in most case s and quantitatively in a few. (C) 2004 Elsevier Ltd. All rights reserved.

Nemli, G. and I. Ozturk (2006). "Influences of some facto rs on the formaldehyde content of particleboard." Building and Environment 41 (6): 770-774. In this study, effects of specific gravity (SG), shell ing 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 parame ters were determined for E-1 grade particleboard manufacturing from urea formaldehyde (UF) adhesi ve. Based on the findings of this study, increasing of SG, shelling ratio, and pressure in creased the formaldehyde content. Particleboard made from particles consisting higher amount of beech particles had lower formaldehyde content than that of panel from particles consis ting higher amount of pine particles. (C) 2005 Elsevier Ltd. All rights reserved.

Neuhaus, T., R. Oppl, et al. (2008). "Formaldehyde emissions fr om mineral wool in building constructions into indoor air." Indoor Air (Denmark)

. One stone wool insulation product containing phenol-urea-formalde hyde 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 re sults 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 witho ut constructions is discussed.

Parent, D., S. Stricker, et al. (1998). "Optimum ventilati on 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-det ached houses heated with electric baseboard heaters in the vicinity of Trois-Rivi eres during the 1993-94 heating season. The houses were selected according to the measured air l eakage at 50 Pa so as to have a sample3-67

distribution similar to the distribution of air leakage of hous es in the province of Quebec. The 'source strength' of several air pollutants were calculat ed from measurements of ambient pollutant levels and total ventilation during a 2 week test. In addit ion: the indoor CO2 and humidity levels were recorded in eight of the houses continuously during the he ating season. Model studies using the measured pollutant source strengths and measured equiva lent 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 ve ntilation, coinciding with mild outdoor temperatures and low wind conditions. With the room occ upied and the door closed, CO2 levels in the bedroom increased steadily during the night unti l morning, when the door was opened, to levels in excess of 3500 ppm with one person and in e xcess 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 characteri ze occupants' simultaneous exposure to mixtures of organic compounds in homes. Statistical distribut ions for concentrations of 28 organic compounds (17 VOCs and 11 aldehydes) measured in 1417 homes w ere generated to analyze concentration distributions. Three candidate distribut ions were identified for fitting the measured data: log-normal, exponential and gamma distribution s. It appears from the results of fitting tests that gamma distributions are capable of repre senting 28 compound concentrations. Probability distributions show that formaldehyde and acetaldehyde r anged 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 expo sure to the mixtures, the joint probability distributions of organic compounds were generated from the be st-fitted distributions of individual compounds under the assumption that concentrations of orga nic compounds are mutually independent in homes. These joint distributions provided the stat istical data for characterizing the occupant's exposure to the mixtures of organic compounds in home s.

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 dur ing 3 years in new and older3-68

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 compou nds in the new homes. The levels of the indoor air organic compounds in the older homes showed no signi ficant 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 e mission source strengths than ventilation systems. The quantitative information on the tr end of the indoor air organic compound levels will be useful for the risk assessment of indoor expo sure to those compounds, and also for Japanese IAQ guidelines.

Petrick, L. and Y. Dubowski (2009). "Heterogeneous oxidation of sq ualene film by ozone under various

indoor conditions." Indoor Air 19 (5): 381-391. P>The effects of indoor conditions (ozone concentration, tem perature, relative humidity (RH), and the presence of NOx) on heterogeneous squalene oxidation were studied with Attenuated Total Reflectance-Fourier Transform Infrared spectro scopy. 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 temper ature 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, fe wer 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 oxi dation 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 prod ucts including long chain aldehydes and ketones, and gas phase products including formaldehyde , a known human carcinogen (IARC 2006), and bicarbonyl compounds like: 4-oxopentan al (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 t he presence of NOx showed the formation of nitrated surface oxidation products. Such nitr ated products may have higher mutagenicity, carcinogenicity, or allergenic potential than the ir nitrate free counterparts (Franze3-69

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 de nsity 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 stud y 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 a ir: 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 f or 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. Th e overall goal was to determine 9 use of Tools for Schools was sufficient to identify conditions wit h 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 s chool, and 4) develop methods and instruments for assessing environmental risks associated w ith daily school attendance. Data were gathered on levels of formaldehyde and other volatile organic compounds (VOCs), ozone, particulate matter (PM10), mold, relative humidity, and tem perature. Data values for each sampled pollutant were compared with federal standards, r ecommended values established by the American Conference of Governmental Industrial Hygienists fo r 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 with in guidelines, as were ozone and particulate-matter levels. Mold, however, was widespread, i ncluding both common species and species associated with allergy and asthma, such as Aspe rgillus and Alternaria. In general, Tools for Schools provides an excellent foundation for a school indoo r air quality program, although the authors did find it necessary to streamline data collec tion 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 formaldehyde3-70

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 conten ts of free formaldehyde in the board industry has led to products with very low emissions of for maldehyde. In this study, a detailed account is given of how UF resins with different mole rat ios 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 particl eboard, the desiccator (JIS A 5908, 2003) and the EN 120 (European Standard, 199 1) have been compar ed with the I m 3 chamber method SS 270236 (Swedish Standard of determining fo rmaldehyde emission with chamber test, 1988). Good relationships were obtained betwee n the methods studied with

correlation coefficients of > 0.9. The value of formal dehyde emission decreased linearly with the mole ratio of formaldehyde to urea down to 1.05 where the effec t 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 resin s that had mole ratios equal to or higher than 1.15, at the two lowest mole ratios 0.97 and 1.01, there w as 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 rat io of 1.27. (c) 2005 Elsevier Ltd. All rights reserved.

Que, Z. L., T. Furuno, et al. (2007). "The mathematical mode l for the formaldehyde emission from woodbased board in room." Building and Environment 42 (6): 2321-2324.

A mathematical model which describes the influence of vari ous parameters on formaldehyde concentration in the atmosphere of a room containing wood-bas ed 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 formaldehydeemission process of woodbased boards are proposed, and inequality estimation for t he 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 Lt d. All rights reserved.

Risholm-Sundman, M., A. Larsen, et al. (2007). "Formaldehyde emi ssion - Comparison of different standard methods." Atmospheric Environment 41 (15): 3193-3202. The emission of formaldehyde is an important factor in t he evaluation of the environmental and

health effects of woodbased board materials. This artic le 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 emi ssion by the chamber method. European Standard, October 2004], gas analysis method [EN 717- 2, 1994. Wood-based panelsdetermination of formaldehyde release-Part 2: formaldehyde rel ease by the gas analysis method, European Standard, November 1994], flask method [EN 717-3, 1996. W ood-based panelsdetermination of formaldehyde release-Part 3: formaldehyde rel ease by the flask method, European Standard, March 1996], perforator method [EN 120, 1993. W ood 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-desi ccator method, Japanese Industrial Standard, March 2001 and JAS MAFF 233, 2001] and small chambe r method [JIS A 1901, 2003. Determination of the emission of volatile organic compounds and aldehydes for building products-small chamber method, Japanese Industrial Standa rd, January 2003], for solid wood, particleboard, plywood and medium density fiberboard.

The variations between the results from different method s can partly be explained by differences in test conditions. Factors like edge sealing, c onditioning of the sample before the test and test temperature have a large effect on the final e mission 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 perfora tor test. The variations in interlaboratory tests are much larger than in intra-laborato ry tests; the coefficient of variation is 16% and 6.0% for the chamber method, 25% and 3.5% for the gas an alysis 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 expo sure to formaldehyde significantly increases the risk of asthma in young children." European Respirat ory Journal 20 (2): 403-408. Concern has arisen in recent years about indoor air pollut ion 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 carrie d out in Perth, Western Australia, between 1997-1999. An association between exposure to formaldehyde an d asthma in young children has been suggested. Cases (n=88), whose parents wer e recruited at Princess Margaret Hospital Accident and Emergency Dept (Perth, Western Austr alia), 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 fr om birth records through the Health Dept of Western Australia (Perth, Western Australia). Heal th outcomes for the children were studied using a respiratory questionnaire and skin-prick tests. For maldehyde, average temperature and relative humidity were measured on two occasions, winter (July-September 1998) and summer3-72

(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 expo sure during the summer period for case and control subjects. The generalised estimating equa tion model showed that children exposed to formaldehyde levels of greater than or equal to 60 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 surfa ce reactions on indoor wall paint." Environmental Science & Technology 41 (18): 6573-6578. The reduction of indoor air pollutants by air cleaning syste ms has received considerable interest, and a number of techniques are now available, S o far, the method of photocatalysis was mainly applied by use of titanium dio xide (TiO2) in flow reactors under UV light of high intensity. Nowadays, indoor wall pa ints 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 forma ldehyde without air exchange at high concentrations. In further experiments with vo latile organic compounds (VOCs), a small effect was found for terpenoids with high k(OH) r ate constants. For other VOCs and carbon monoxide there was no degradation at all or th e surface acted as a reversible sink. Secondary emissions from the reaction of paint c onstituents 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 i ndoor 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 an d 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 or ganic 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-s orbent thermal desorption tubes were used for the collection of 15 VOCs and C(18) 2,4-dinitrophenylh ydrazine-coated cartridges were used for the collection of seven aldehydes. Air-exchange rate s (AERs) were also measured using3-73

a perfluorocarbon tracer gas method. The AERs were lower i n the winter in both cities, averaging 1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) i n 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 source s, including chloroform, 1,4- dichlorobenzene, and formaldehyde. Using a mass-balance model t o 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 co uld be divided into: (1). indoor-sourceinfluenced compounds, (2). those with contributions from bo th indoor and outdoor sources, and (3). those with mostly outdoor sources. Significant indoor so urces 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 r atios across seasons, SERs, which accounted for AER, were similar in both cities for bo th 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 analys is 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 an d 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 or ganic 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-s orbent thermal desorption tubes were used for the collection of 15 VOCs and C-18 2,4-dinitrophenylh ydrazine-coated cartridges were used for the collection of seven aldehydes. Air-exchange rate s (AERs) were also measured using a perfluorocarbon tracer gas method. The AERs were lower i n the winter in both cities, averaging 1 h(-1) in NYC and 1.4 h(-1) in LA, compared with 1.8 h(-1) i n 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 source s, including chloroform, 1,4- dichlorobenzene, and formaldehyde. Using a mass-balance model t o 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 co uld 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 so urces were found for the following six compounds ( mean emission rates presented): chlorofor m (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 r atios across seasons, SERs, which accounted for AER, were similar in both cities for bo th 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 analys is 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 f rom articles inside cars, relatively little has been published about possible adverse health effect s and about exposure levels that can be considered safe or "acceptable". Xylene, formaldehyde and a cetaldehyde represent typical examples of relevant volatile organic substances (VOC) rel eased from articles inside cars. Recently, a concept for derivation of maximum exposure le vels for volatile organic substances in cars has been published. In the present study we applied this c oncept to derive maximum exposure levels for xylene, formaldehyde and acetaldehyde and compar ed the resulting concentrations to exposure levels usually found inside of ca rs. 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 sh ould not be exceeded during short-term exposures, for instance when starting a car t hat had been heated up during parking in the sun. Exposure Levels Inside Automotive Vehicles (ELIA, chron ic) for chronic exposure to non-genotoxic substances were 8.8, 0.125 and 0.635 mg/m(3) for syste mic as well as 17.6, 0.125 and 1.7 mg/m(3) for local exposure to xylene, formaldehyde and a cetaldehyde, respectively. Although, it is known that exposure limits for carcinogenic subst ances should be treated with caution, encouraged by the well documented threshold mechanism s 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 r espect 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 of3-75

formaldehyde may be necessary. (C) 2004 Elsevier Ireland Ltd. All rights reserved.

Sekine, Y. and A. Nishimura (2001). "Removal of formaldehyde fr om indoor air by passive type aircleaning materials." Atmospheric Environment 35 (11): 2001-2007. We have developed a board-like air-cleaning material cons isting of activated carbon particles and manganese oxides, by which HCHO gas is decomposed into car bon dioxide even at room temperature. In this study, we investigated removal effi ciencies of the air-cleaning board in a passive mode using a kinetic approach. First-order removal rat e constant, k, corresponding to air change rate was characterized for the board as a functi on 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-s ize laboratory with a constant gas generation. The board suppressed the increase of indoor HCHO conce ntration 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 Jan uary 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 Exposure s inside Mobile Homes." Environmental Science & Technology 23 (8): 985-988. An age-stratified random sample of 470 mobile homes was sele cted from among the more than 500000 in California. One-week, average indoor formaldehyde concentr ations were measured during both the summer (July-August 1984) and the winter (Februa ry-March 1985) seasons. Results indicate that (1) formaldehyde concentrations were we ll-mixed inside the trailers over a 1-week period, (2) relatively little variation was observe d 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 insi de mobile homes manufactured since about 1980, probably as a result of the incr eased use of low-formaldehydeemitting building materials. Based on the 470 mobile homes in t his 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 Age ncy (EPA).

Sherman, M. H. and A. T. Hodgson (2004). "Formaldehyde as a ba sis for residential ventilation rates."

Indoor Air 14 (1): 2-9.3-76

Traditionally, houses in the US have been ventilated by pas sive infiltration in combination with active window opening. However in recent years, the construct ion 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, ther e has been increased interest in engineered ventilation systems for residences. The amount o f ventilation provided by an engineered system should be set to protect occupants from u nhealthy or objectionable exposures to indoor pollutants, while minimizing energy costs for conditi oning 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 m eans of determining ventilation rates and uses existing data on emission rates of formaldehyde i n new houses to derive recommended levels. Based on current, widely accepted concentration guide lines 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 s ampler 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 pass ive flux samplers (PFSs) to measure emission rates of carbonyl compounds and volatile organic comp ounds (VOCs) from many of the building materials and furnishings present in a room in a rei nforced 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 w ere high (80.0 and 72.3 mu g/m(2)/h, respectively), whereas that from the flooring was low (9.09 m u 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 e xchange 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 w alls 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 e mission rate from every major emission sources could be measured. in contrast, the door, the flooring, and the desk contributed3-77

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. A ll rights reserved.

Singer, B. C., A. T. Hodgson, et al. (2003). "Gas-phase orga nics 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 mater ial 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 inves tigate sorption effects on EREFs and potential ETS exposures under habitual smoking conditions. Cig arettes were smoked in a 50- m(3) furnished room over a 3-h period 6-7 days per week, with con tinuous ventilation at 0.3, 0.6, or 2.1 h(-1). Organic gas concentrations were measured eve ry few days over 4-h "smoking", 10-h "post-smoking" and 10-h "background" periods. Concentration pat terns of volatile ETS components including 1,3-butadiene, benzene and acrolein were simi lar 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 toxi c air contaminants including phenol, cresols, and naphthalene increased as experiments progresse d, indicating mass accumulation on surfaces and higher desorption rates. Daily patterns stabili zed after week 2, yielding a steady daily cycle of ETS concentrations associated with habi tual 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 sm oker finishes) and from reemission, and their importance relative to direct exposures (non-smoke r 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 lowe r 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 tw o gaseous compounds that3-78

react in an indoor setting to produce a hypothetical product. T he 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 s cenarios include two air exchange rates (0.5 and 2.0 h(-1)). The terpene is introduced as a f loor source with an emission pattern similar to a floor-care product. These four scenar ios have been set in a fairly large two-dimensional room (13.6 x 40.6 m) with a supply at the top o f the left wall and an exhaust at the bottom of the right wall. The room has b een 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 ar e large concentration gradients within the room for both reactants and product. To some ex tent 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 th e 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 c alculated by the CFID method differ significantly from those calculated by a one-compartme nt mass-balance model assuming perfect mixing. (C) 2002 Elsevier Science Ltd. All rights re served.

Spengler, J. D., J. McCarthy, et al. (2001). Volatile Organ ic 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 I ndoor 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 polluti on sources include: source elimination, substitution, modification, pretreatment, and a ltering the amount, location, or time of use. Intelligent source management requires knowledge of the s ource's emission characteristics, including chemical composition, emission rates, and decay rates. In addition, knowledge of mechanical and natural outdoor air exchange rates, heating/a ir-conditioning duct flow rates, and local exhaust fan (e.g., kitchen, bathroom) flow rates i s needed to determine pollutant concentrations. Finally, indoor air quality (IAQ) models us e this information and occupant activity patterns to determine instantaneous and/or cumula tive 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 of3-79

occupant exposures for these scenarios are given for sel ected source management options. A onemonth period was used to compare exposures; thus, long-term e xposure information is not presented in this paper. (C) Indoor Air (1996).

Tucker, S., S. Brown, et al. (2008). Estimating Indoor Air Q uality 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 asse ssed by measurement of pollutants during building operation for comparison with air quality stan dards. Current practice at the design stage tries to minimise potential indoor air quality im pacts of new building materials and contents by selecting low-emission materials. However low-emission m aterials 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, f ully mixed and ventilated zone in an office building with acceptable levels derived from Australian and int ernational health-based standards. The model acquires its dimensional data for the indoor space s 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 qualit y 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 quali ty 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 ph otocopier emitted mainly ozone. In a well-ventilated office environment, the amounts enco untered here for individual volatiles were within recommended maximum exposure limits fo r 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 emissions3-80

in the immediate vicinity of the printers exceeded recommenda tions, 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 concentra tions can be kept below recommended maximum exposure limits, provided that the vent ilation 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 produ cts from building materials and furnishings on indoor air quality - A review of recent advances in i ndoor chemistry." Atmospheric Environment

41 (15): 3111-3128. The variety of chemical substances present in modern buildi ng 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 condi tions 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 degrada tion of cellulose, decomposition of nonheat-resistant additives and other thermally induced reacti ons like Diels-Alder synthesis. Heterogeneous chemistry takes place on the surface of materia ls. Well-known examples are the formation of aliphatic aldehydes from the oxidation of unsatura ted fatty acids or the cleavage of photoinitiators under the influence of light. In case of compo site 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 forme d by inter-species reactions are possible. Other indoor air pollutants are formed by rearr angement of cleavage products or by metabolism. Compounds with -C=C- bonds like terpenes, styre ne, 4-phenylcyclohexene, etc. undergo gas phase reactions with O3, NOx. OH and other react ive 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 pr operties. Therefore, the understanding of primary and secondary emissions and the chemical proces ses behind is essential for the evaluation of indoor air quality. This publication gives an ove rview on the current state of research and new findings regarding primary and secondary e missions 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." Atmo spheric Environment 41 (13): 2851-

2861.3-81

Indoor and outdoor carbonyl concentrations were measured simul taneously in 12 urban dwellings in Beijing, Shanghai, Guangzhou, and Xi'an, China in summ er (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 ac etone 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 dwe llings with tobacco smoke, incense burning or poor ventilation had significantly higher indoor conc entrations 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 st ill significantly high. It was also noted

that in winter both the indoor and outdoor acetone concentrat ions 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 reac tion 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 a nd benzaldehyde had the weakest indoor sources. (C) 2006 Elsevier Ltd. All rights res erved.

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-retar dant-treated low-formaldehyde-emission particleboard from recycled wood-waste particles using polyme ric 4,4'-methylenediphenyl isocyanate (PMDI) and phenol-formaldehyde (PF) resins. The in fluence of the PMDI/PF ratio (ratio of particles sprayed with PMDI to particles spray ed with PF, w/w) after fire retardant treatment on formaldehyde emissions, mechanical properties, and surface fire resistant performance of the manufactured particleboard was investig ated. The experimental results showed that the formaldehyde emissions linearly decreased wit h an increasing PMDI/PF ratio. Moreover, the bending strength, internal bond strength, and scr ew 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-ret ardant-treated low-formaldehyde-emission particleboards fabricated in our study could pass the thir d grade standard of surface fire resistant performance as specified by CNS 6532. (C) 2007 Elsevier Ltd. A ll rights reserved.3-82

Wang, X. K. and Y. P. Zhang (2009). "A New Method for Det ermining the Initial Mobile Formaldehyde Concentrations, Partition Coefficients, and Diffusion Coef ficients 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 hi gh 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 ca n be controlled by a water bath, then the materials undergo a multisorption/emission process and t he 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 o f the linear least-square regression, and D is obtained by fitting the concentration at the emis sion stage into a mass-transfer-based model in the literature. Four kinds of wooden medium-density b oards are tested. The C-m,C-0 measured using this method is the mobile formaldehyde concentra tion in the material, which differs significantly from the total formaldehyde concentrat ion 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. Th e 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 heal thy 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 cos t prohibitive to sample all toxic pollutants in a building. In search of a more manageable num ber of parameters for cost-effective IAQ assessment, this study investigated the probable correl ations among the 12 indoor environmental parameters listed in the IAQ certification sc heme of the Hong Kong Environment Protection Department (HKEPD) in 422 Hong Kong offices. Thes e 12 parameters consists of nine indoor air pollutants: carbon dioxide (CO2), carbon monoxide (CO), respirable suspended particulates (RSP), nitrogen dioxide (NO2), ozone (O-3), fo rmaldehyde (HCHO), total volatile3-83

organic compounds (TVOC), radon (Rn), airborne bacteria cou nt (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 sm allest loadings, was ABC, Rn, CO, RH, RSP, CO2, TVOC, O-3, T, V, NO2 and HCHO. Together with the mathematical expressions derived, an alt ernative sampling protocol for IAQ assessment with the three,most representative and inde pendent' 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 leve ls of the other nine parameters and good agreement was found between the predictions and me asurements. This simplified protocol provides an easy tool for performing IAQ monitoring i n 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 res erved.

Wong, L. T., K. W. Mui, et al. (2007). "Screening for indoor a ir quality of air-conditioned offices."

Indoor and Built Environment 16 (5): 438-443. It would be costly to sample all toxic air pollutant s to which an entire community is exposed. In Hong Kong, a voluntary Indoor Air Quality (IAQ) certificati on scheme for IAQ assessment in workplaces proposes the measurement of the levels of 12 para meters: carbon dioxide, carbon monoxide, respirable suspended particulates, nitrogen dioxide, ozone, formaldehyde, total volatile organic compounds, radon, airborne bacteria count, tempera ture, relative humidity and air velocity. This study investigates the feasibility of a s creening process for presumptive detection of unrecognised IAQ problems in an indoor environment. From the fu ll IAQ assessment results of 422 air-conditioned offices in Hong Kong, three of nine listed c ommon air pollutants are selected as "representative" pollutants for an overall "satisfacto ry IAQ". In particular, an "IAQ index" using the average fractional dose corresponding to given exposure li mits of the representative pollutants as a simple screening test for asymptomatic IAQ pr oblems in air-conditioned offices is proposed. The index was evaluated in terms of test sensit ivity, specificity and predictive value. Such a screening test would be a useful tool for policyrn akers, building owners and professionals to identify offices with probable IAQ problems. Making be tter 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 the3-84

types of construction, ventilation, and building age. Formalde hyde 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 p robability (LCP) and chronic noncarcinogenic hazard index (HI). The carcinogenic effect of for maldehyde estimate by LCP (70 years old) is about 2.06 x 10(-4) to 1.75 x 10(-3) after adjusting the ir working time. The levels of risk are 100-1000 times of the acceptable carcinogenic risk. A sim ilar trend is observed for the levels of HI calculated. Many studies have suggested that expo sure to high levels of formaldehyde may cause nasal cancer and other health effec ts. 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 FORMAL DEHYDE EMISSION FROM MULTILAYER WORK SURFACES USED IN OFFICE WORKSTATION SYST EMS . Proc. of the 6th Int. Conf. on Indoor Air Quality. Volatile organic compounds (VOCs) emitted from various so urces may adversely affect human health, comfort and performance. In particular, formaldehyde has been identified as a major indoor pollutant whose emission is controlled by workstatio n systems. Engineered wood products such as particleboards have widely been used with wood vene er and laminate to form work surfaces of workstation systems, which is a major form aldehyde emission component. The emission rate of formaldehyde depends on the composition of ea ch material layer, temperature and moisture content in the materials. The objective of t his 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 n umerical investigation of the emission characteristics. To reproduce the experimental results, a numerical simulation model for coupled heat, air, moisture and pollutant transport in porous mate rials and wall assemblies was used1. A parametric study for the model parameters under consideration, s uch as the partition coefficient, the diffusion coefficient and the initial formaldehyde content i n each material layer showed that all parameters decide about the formaldehyde emissions. In parti cular, the initial conditions have a major influence on the evolution of the emission factor. I t can be concluded that an unambiguous determination of all parameters is difficult s ince 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 comp ounds (VOCs) in the indoor air of the test room were measured over one year. The following re sults were obtained: (1) The main compounds emitted were formaldehyde and acetaldehyde. The em ission of formaldehyde was greatly dependent on room temperature and did not easily a ttenuated although the emission was low throughout the test period. On the other hand, the emissi on 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 condi tions during the study. Formaldehyde, acetaldehyde, and seven other aldehydes were identifi ed 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 fo r propionaldehyde, the indoor concentrations were found higher than the outdoor concen trations for all the other compounds, indicating the presence of significant indoor sourc es such as direct emissions and

indoor chemical formation. Ozone concentrations were measure d simultaneously during the study, and it was observed that several aldehydes can be gener ated through indoor ozone chemistry. The study provided evidence to support laboratory res ults obtained by other investigators that predicted aldehyde generation through indoor o zone chemistry. The residential exposures to formaldehyde and total aldehydes were assessed bas ed upon some assumptions, and the outdoor exposures were negligible compared to the indoor expos ures.

Zhang, J. F., W. E. Wilson, et al. (1994). "Indoor Air Chemi stry - 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: styr ene, limonene, and 4-vinylcyclohexene. In addition, benzaldehyde was detected in the styrene-ozone-air rea ction system, and acetic acid was3-86

found in the limonene-ozone-air system. The study also examined the gas-phase reactions involving formaldehyde, ozone, and nitrogen dioxide and found the for mation of formic acid, suggesting that the nitrate radical may play an important r ole in converting formaldehyde into formic acid. Experiments for all the reactions were conduct ed 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 extrapolat ed to typical indoor situations and support indications from previous studies that certain alde hydes and organic acids could be generated by indoor chemistry.

Zhang, Y. P., X. X. Luo, et al. (2007). "Influence of tempe rature 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 parame ters used to predict the VOC emissions. D and K may be strongly affected by temperat ure. 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 coeffi cients and the partition coefficients with temperature for particle board, vinyl floor, medi um- and high-density board are presented. A formula relating the partition coefficient and related f actors 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 experime ntal 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 Produ cts (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 mode lers evaluating pressed wood products as a result of a complex long term emission pro file, a backpressure effect not often observed in consumer product modeling and potential indoor sour ces and sinks. The purpose of the Formaldehyde Indoor Air Model – Pressed Wood Products (F IAM-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 i nput and output screens to be clear and

intuitive.

The theoretical framework for modeling steady state lev els of formaldehyde has been in place for approximately 30 years. One of the areas I reflected on a s 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 bel ieve the incorporating a better defined conceptual model into the model documentation and guidan ce would encourage important basic research, particularly in regard to the l ong 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 Ca rlo options available in MCCEM. This could be as simple as allowing ‘batch inputs’ for certain param eters like mass transfer coefficient with a selection key outputs summarized when batch mode is us ed.3-88

One of the major themes of my comments is that I st rongly 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 frame work is important because federal future regulatory standards, if any, could vary as a functio n of the type of product (e.g. industrial panel versus MDF. This outcome is likely because the tec hnologies, loadings or mass transfer coefficients are product specific and standards may be adopt ed 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 dai ly concentration (ADC) and lifetime average daily concentration (LADC) appears to i nclude the background concentration and the ability to include doses from non-pressed wood product s. As currently framed, the model is useful for assessing total personal exposure to formalde hyde, but of equal interest to most stakeholders is the risk or hazard assignable to a specif ic 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 te rm exposure. Therefore, my primary recommendation is to describe a conceptual model in the documentation that provides a framework for approaching questions about product specific haz ard and risk.

In the comments below, I sometimes refer to the equi librium concentration which is related to the Matthews b and m by C eq = b/-m. The equilibrium concentration is the theoreti cal concentration corresponding to a ventilation rate of ze ro.



### 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 provi de your rationale for determining the level of confidence. If the lev el 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 t he quality of the result (low3-89

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 industr ial panel). Currently, the model documentation and model results emphasize the aggregate co ntribution of all products (and background sources), and running the model with and without a p roduct 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 document ation. Please see my detailed

comments below.

General Comments – Acute Versus Chronic Exposure One of the challenging aspects of reviewing this model and pr oviding cohesive recommendations is that the current assessment of acute and chronic expo sure is associated with different uncertainties and conceptual models. However, accurate as sessment of exposure for each of these endpoints is important. For acute exposure, the int eraction between products is important due to the back-pressure effect, whereas for chronic exposur e, each product has a reservoir of formaldehyde and formaldehyde precursors that is finite and de cays with time. The theory for acute exposure modeling for pressed wood products is well establ ished 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 (Mat thews 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 diffic ult to reliably model with a steady state approach.

The model documentation should focus on both the determina tion of incremental exposure attributable to the introduction of a specific product and t he 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 manufac tures, 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 th e type of product, necessitating an ability to understand incremental or added contributions to exposure. F or example, in addition to3-90

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 co ncentration when my product is introduced into a new or existing home when a default ba seline 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 answ ering 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 inte rested 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, be cause the potential effect of a particular product is easily discernible by standard chamber testing and calculated equilibrium concentration on reasonable assumptions about mass tra nsfer coefficients. My concern is that if a cancer risk in excess of the acceptable risk range is cal culated with this model, there is not a clear recommendation for performing a laboratory study tha t 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 t ime is due to source depletion from individual products. It may be prudent for EPA to consider a t echnical workshop prior to finalizing the model with the purpose of developing consensus recommendations for the model documentation regarding a specific set of tests that coul d 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 f raming 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 atten uate the contribution of a new product such that the total acute indoor exposure concentration i s 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 formalde hyde precursors will ultimately partition from the product into the indoor space. My reco mmendation is that conceptual framework be developed in the model documentation to ensur e that users take these factors into consideration when investigating acute versus chronic timefr ames. For the acute timeframe, it is important to consider the total collection of assembled i ndoor products, or alternatively, the background concentration attributable to the existing products . For chronic exposure, a more accurate characterization of dose attributable to a singl e 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 o bserved due to the backpressure effect is temporary, and eventually, a source that is initially att enuated will begin to emit formaldehyde as

the overall indoor air concentration level decreases. T he model documentation should refer to the types of decay studies that could be done to understand the lo ng term formaldehyde dose attributable to a single product or collection of relate d products. Examples of these studies include (Zinn et al. (1990), Mølhave et al. (1995), Myer and Herma nns 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 intro duction of a specific product (e.g. wall paneling at a specified loading rate) or collection of product s (e.g. kitchen cabinets) will increase the indoor air concentration to a level exceeding a th reshold of concern. The baseline concentration could be determined by:

• A representative collection of products in compliance w ith voluntary or future emissions standards (or alternatively, current air chamber testing r esults);

• Current actual background indoor air concentrations establi shed by published data for new and existing homes; or

• Future baseline background indoor air concentrations assigne d based on policy and costbenefit analysis. The future target background concentratio n would be a fraction of the3-92

threshold of concern to allow for initial increase in c oncentration 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 present ed with and without the added products. I believe this would greatly assist users of the m odel in intuitively understanding the backpressure effect, as well as assist specific manufac turers, regulators and other interested parties in understanding the incremental effect of specif ic 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 m 2 of a paneling product that was not compliant with volunt ary industry standards in the presence of other products that wer e compliant? Is it plausible that the other wood products in the trailer might have adsorbed for maldehyde from the non-compliant product and thus confound the interpretation of retrospective chamber testing?

In the absence of this modification, the user could sim ply 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 sink s. 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 wo uld be particularly useful if the model were configured to output the emission rate and percent co ntribution to total emissions of the

‘baseline’ sources with and without the ‘added’ source. Th is feature would also provide a clear way to use and interpret the result of a product specific c hamber 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 publicati on of FEMA temporary housing unit data failed to consider the potential implications of the bac kpressure effect for pressed wood products (Maddalena et al. 2009). The emissions equation relied upon by t he authors did not account for the backpressure effect, and not surprisingly, the authors f ound that “the sum of all measured chemical emissions from the materials are general gre ater than the whole trailer emissions derived from measured concentrations”. Additionally, beca use the chamber testing was done3-93

retrospectively, the authors could not differentiate betw een primary and secondary sources. Therefore, although the results and conclusion of this pa per 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 s tandards (in combination with the temperature, humidity and air change rate conditions th at were true in this particular case). If this occurred, then some of the lower emitting products may h ave been contaminated by the noncompliant products.

In my view, one of the urgent federal policy questions rega rding pressed wood products is whether the absence of federal regulations with perform ance based standards (with the exception of manufactured homes) has resulted an increased prevalen ce of imported products failing to meet the established voluntary industry standards or with potential emission rates higher than domestic production. I believe the slight reconfiguratio n of the model I am recommending would be extremely useful for explicitly addressing questions o f this nature. From a policy perspective,

after acute and/or chronic health based standards for fo rmaldehyde are established, a focus on incremental exposure would be helpful for establishing the f ramework for the regulatory compliance program (e.g. the frequency of testing, documen tation required for importers, how important is a 25% deviation above the compliance criteri a for a single MDF panel, etc?).

Chronic Exposure and Half-life/Decay

For chronic exposure, the most precise way to model forma ldehyde 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 concentrat ion 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 increa se 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 pr ecursors, is limited. With the3-94

framework of the current model, it is probably most appropr iate 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 recommend ation for acute exposure, I believe the incremental chronic exposure attributable to a specifi c product (e.g. MDF panels) or defined collection of similar products (e.g. kitchen cabinets) sho uld be assessed, rather than the aggregate cumulative exposure for all indoor products (i.e. the cros s-sectional approach). Because the typical situation will reflect products of various ages, t he chronic dose attributable to a specific product seems to be a more relevant metric than the tota l indoor concentration over time assuming an initial loading. Evaluation of the decay curve f or a single product or class of products in isolation is likely to be more useful for unde rstanding chronic risk and informing policy decisions about managing chronic risk than the suggest ed 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 h alf-life is currently considered a ‘house characteristic’, whereas I believe it would be more appr opriate to frame this in terms of a ‘product-specific’ characteristic.

For a specific product, a finite reservoir of free forma ldehyde and formaldehyde precursors exists. Over a sufficiently large period of time, facto rs 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 f rom that product will be depleted, or released to the indoor space (for constant ventilat ion rate). Because the majority of the available reservoir is likely to be depleted over the li fetime of the product, incremental risk from separate products or collection of products can be added to deri ve total risk or an acceptable risk range by type of product (e.g. MDF) could be established. This i ncremental approach may slightly over-estimate true risk depending on the assumed t enure of the occupants, but this can be somewhat accounted for by either assuming a finite emi ssion lifetime of an individual product (e.g. 10 years) or by selecting a target background indoor conc entration higher than outdoor3-95

ambient air levels corresponding to the decay concentra tion 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 ac curate estimate of area under the curve (i.e. cumulative dose) for a product present for a reason ably 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 i n trying to reconcile a transient process with the limitations of a pseudo-steady state model.

Under the current model guidance, the true increased canc er risk attributable to installation of a specific product such as wall-paneling in an existing home to re pair damaged plaster or kitchen cabinets installed during remodeling would not be reliably determ ined. Initially, the backpressure effect will suppress a portion of the formaldehyde emissio ns, such that if the user were to compare cumulative dose with and without the product based o n 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 ventilat ion) 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 conclus ion of negative incremental cancer risk because the cabinets would initially act as a net sink. To i llustrate this point with an extreme example, consider a baseline mobile home with model defa ults loaded with 90 m 2 decking with maximum HUD rate. The initial concentration is 0.3557 mg/m 3 , LADC is 0.0132 mg/m 3 and percent of time > 10 ppb is 46.9%. If 45 m 2 of kitchen cabinets with the EPA cabinet rate are added to the existing decking, the initial concentration is 0. 3389 mg/m 3 , LADC is 0.0125 mg/m 3 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 equilibriu m concentration equal to b/-m or 0.08 (mg/m 2 -hr) / 0.49 (m/h) = 0.16 mg/m 3 . It seems likely that over the lifetime of the kit chen cabinets, there will a finite long term dose greater tha n 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 indi vidual 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 conside ration of periods of rapid and slow decay in the emission rate as observed, for example, i n Zinn et al. (1990), Mølhave et al. (1995), Myer and Hermanns 1985 and Brown 1999. Long term testing is not f easible on a routine basis, but I believe the model should have the framework in pla ce 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 singl e compartment exponential model will provide a conservative estimate of chronic exposure, but doe s not necessarily provide a pathway forward or conceptual framework for refinement of the calc ulation of long term cumulative dose.

One conceptual model for assessing chronic exposure for for maldehyde 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 m easurements were made over an 8-week period. Conceptually, three exponential decay compartment s were attributed to three potential sources of formaldehyde emissions, including:

• free formaldehyde (short-term compartment);

• decay of paraformaldehyde and other complex structures (med ium-term compartment);

and

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

Using an exponential peeling procedure, the authors determi ned relative sources strengths and half-lives for each of these three compartments. A tw o-compartment (slow and fast decay) analysis using an EPA model also adequately represented the transient data. The corresponding accumulated dose was compared to the Califo rnia 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 co mpliance 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 incorporat ed into the model. Currently, the halflife parameter pertains to a structure-based decay rate ra ther than a product-based decay rate.3-97

For the default case, the decay rate presented in Zinn e t al. (1990) seems more appropriate than the 2.92 year half-life derived from cross-sectional sec tional 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 logarit hm linear regression statistical analysis. The half-life reported in Zinn et al. (1990) is not directl y 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 equatio n was used by CARB (2007; see Appendix B) to calculate the emissions inventory presente d 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) e xponential decay model could be fit

the Zinn et al. data.

Finally, one concern is the interaction between venti lation rate and decay rate. Given long term testing data, the total reservoir of formaldehyde and forma ldehyde 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 vent ilation rate and account for total mass of formaldehyde generated over the lifetime of the product. A lthough the data to accomplish this is currently not available, it would a benefit to the scie ntific community to frame decay of emissions over time in terms of an accurate conceptua l 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 Versa r model), as well as the steady equations for both models. These two models are both mass tr ansfer based approaches, however, the mass transfer coefficient obtained by linear regress ion is not identical. This can be seen in the documentation for the 1986 Versar model, where the correla tion coefficient is typically higher for the Hoetjer than for the Matthews model. For exa mple, 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 re sults are obtained depending on the3-98

regression model used and the Hoetjer model is widely cit ed in the literature, it is recommended

that the model documentation be revised to include discussio n of both approaches.

To illustrate this point, I performed a linear regression a nalysis 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/m 3 ) N = air change rate (1/hr) L = loading rate (m 2 /m 3 ) 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 C eq = b/-m. Therefore, the difference in models is in the regression equation 1 and 2 used to derive th e parameters, not the theoretical construct. The equilibrium concentration is the vapor ph ase 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 tran sfer coefficient K and equilibrium

concentration C eq . The mass transfer coefficient is determined by the pro perties of the board or object surface, whereas the equilibrium concentration is determined by the formaldehyde generating properties of the panel and varies with tempera ture, 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,

C eq and K are calculated for the kitchen cabinet data present ed 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 tes ts (i.e. at least three N or L combinations for the linear regression) that would be nee ded 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 regr ession 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/m 2 /h, r=-0.9733-100

Figure 1b : HBF linear regression. Ceq = 0.19 mg/m 3 , K = 0.41 m/h, r=0.997

Figure 2: Calculated steady state concentration for regression m odels in Figure 1 assuming loading (L) of 0.13 ft 2 /ft 3

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/m 3

. 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 b e derived directly from b is only true in the absence of formaldehyde in the bulk air, or at the be ginning of the exposure period. However, the Ceq of the HBF model can be easily calcu lated. The concentration in the absence of ventilation (and background sources) is b/-m or C eq = 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 th e 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 m odel 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 Matthew s linear regression models. Another option would be to provide the HBF equilibrium concentra tion as supplemental output. Knowledge about the equilibrium concentration allows an i ntuitive 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 statemen t 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 de monstrated 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 curre nt EPA model is problematic because absorption and desorption of formaldehyde from indoor sin ks is a transient process over relatively short time scales not well suited to a ste ady-state or pseudo steady state model construct. As shown in Figure 1 below reproduced from Tiche nor et al. (1991), a reversible sink buffers changes in concentrations but does not necess arily affect cumulative exposure, or area under the curve. Therefore, for instances where the EP A model is used to calculate lifetime, or long term dose, accounting for reversible sinks could potenti ally 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 fr om Fig. 2, p. 27 in Tichenor et al. (1991).

When the Langmuir model is run to steady state, dM/dt = 0 and C indoor = k d /k a *M. However, at steady state, there is no capacity for the sink to abs orb 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 i s 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/m 2 -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 C eq =b/-m and using the standard mass transfer equation. For dr ywall, Ceq = 0.0375 mg/m

2 -h / (-3 m/h) / (1.236 mg/m 3 / ppm) x 1000 ppb/ppm = 10 ppb. Therefore, when

C S =C eq = 10 ppb, then ER = K(C eq -C s ) = 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 o n EPA model guidance page 3-7 was developed by setting intercept b = k a x C indoor assuming dM/dt = 0. When there is a linear relationship between accumulated mass and indoor air conce ntration at equilibrium conditions, dM/dt must equal zero. Therefore, deviations of the interce pt from the calculated value would imply a sustained loss of equilibrium, violating the as sumption 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 t his parameter as calibration or adjustment factor rather than as a predictive input.

For wallboard, the surface area is high in magnitude, the refore minor arbitrary decreases in the intercept from the values recommend in the model document ation 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 concent ration 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/m 2 -h = 0.1725 mg/m 2 -h. When this value is entered for the wallboard slope, as expected, the Zone 1 concentr ation remains at 46 ppb. Due to rounding or insufficient significant digits, the calcu lated flux for this intercept actually reflects net generation rate (G) where positive G corresponds t o desorption:

G = 420 m

2 x (0.05721 mg/m 3 x -3 m/h + 0.1725 mg/m 2 -h) = 0.36 mg/hour

Holding concentration constant in the prior example, a negligible decrease in the intercept to 0.1715 mg/m

2 -h would cause the wallboard to be considered a sink wit h net adsorption:

G = 420 m

2 x (0.05721 mg/m 3 x -3 m/h + 0.1715 mg/m 2 -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. T his is true because at the starting point (e.g. 0.0375 mg/m

2 -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 b e a reliable way to a priori assign the final value of the intercept other than trial and error t o achieve a modest decrease in indoor air

concentration.3-104

The short term data from Loading 1 at the test house c learly 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 e mission rate equation to derive the intercept. This value of dM/dt will vary as a functi on of time. Such an approach would appreciably increase the level of complexity needed to ass ign the sink term because indoor concentration and mass storage vary as a function of t ime. However, prior EPA models such as MCCEM have included this functionality. If an estimate o f 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 integra tion or finite difference model. However, at 30 days, dM/dt may be sufficiently small that a reas onable default recommendation in the model would be to neglect the effect of sinks.

The treatment of sinks in the EPA formaldehyde model refl ects a reduction in sophistication from that which is available in the prior EPA/Versar M CCEM 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 substanti al enough to include in the final model. Of course, the adaption of a MCCEM-type approach is not stra ightforward because the formaldehyde model addresses long-term decay using a pseudo ste ady-state approach. It may be appropriate to have two versions of the model:

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

• Short term MCCEM-style model to understand whether the pre sence of sinks would appreciable reduce initial peak exposure.

As an example, MCCEM was used to implement the Langmui r 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 n eeded 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/m 3 ) * Q (m 3 /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:

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

k d = 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 m 3 (EPA Conventional Home 1)

Zone 2 volume = 167 m 3 (EPA Conventional Home 1)

Interzonal airflow = 111.5 m 3 /hr (EPA Conventional Home 1)

Zone 0-1 airflow = 259.5 m 3 (EPA Conventional Home 1)

Zone 0-2 airflow = 19.6 m 3 (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 ste ady state formaldehyde concentration of 10 ppb. Approximately 7 or 8 hours after introduction of the s ource, the rate of increase in storage in the sink is negligible and therefore there i s 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 m 3 x 0.59 hr -1 x 1.236 mg/ m 3 per ppm) = 10 ppb

dM/dt steady = 0 = 0.010 ppm x 1.236 mg/m 3 per ppm x 1.304 m/h x 94 m 2 – 0.196 hr -1 x M  M = 0.082 mg/m 2  M*A = 0.082 mg/m 2 x 94 m

2 = 7.7 mg

Note that at steady state, k d x M = 0.196 hr -1 * 0.082 mg/m 2 = 0.016 mg/m 2 -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 emis sion rate. Any apparent effect is caused by minor deviations in the intercept or rounding errors, whi ch do not appear to have a theoretical

basis.3-106

Table 2 : MCCEM model results for constant source and carpet s et 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 r esults of the study did confirm that the Langmuir model is appropriate for carpet and padding as expecte d from the literature (Tichenor et al. 1991). The documentation for the EPA formaldehyde m odel 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 les s problematic theoretically because the rate of desorption (k d

x M) is low initially. However, the inclusion of the se parameters is questionable because the pseudo steady-state design of the mo del is not well equipped to handle transport processes that occur over relatively short t ime scales. As shown in Table 2, sinks can reach the maximum loading at a given concentr ation 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 m odel should be used to predict fate processes that change rapidly over hours to days. If si nks are to be included in the model, I3-107

recommend developing clear guidance for assignment of the Matthews parameters. One criteria should be that dM/dt does not change rapidly relative t o the time scale being investigated (e.g. 24-hour average, etc.).

Indoor Sink – Implicit Indoor Sinks Some pressed wood formaldehyde “emitters” could theoretica lly act as sinks under certain conditions based on the properties of wood and the Matt hews model (e.g. products with very low equilibrium concentration or, equivalently, low Matthe ws model intercept). For example, low emitting products with unreacted urea can act as scavenger s (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 ‘conta minate’ otherwise low emitting products. Therefore, there may be some usefulness in pres enting 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 ac count 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 whe n 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 transf er parameters for kitchen cabinets were paired with a range of assumed background concentration s. Here for simplicity, the ‘background concentration’ is used as a proxy to represent al l other sources or a loaded room influencing an adjacent loaded road. The parameters used we re m = -0.49 m/h, b=0.08 mg/m 2 /hr,

ACH = 0.5 hr -1 and L = 0.13 ft 2 /ft 3 . The corresponding equilibrium concentration (C eq ) from the HBF model is approximately 0.163 mg/m 3 . As can be seen from the results in Table 3, when C b > C eq , the kitchen cabinets would act as a sink, resulting in a lower steady state concentration than the influent background concentration ( ∆ C sb < 0). This result is expected from the mass transfer equation where ER = K(C eq -C ss ). When C ss > C eq , the direction of the flux is from the bulk air in the room to the pressed wood product. This examp le 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, th e output in the model of the emission rate3-108

attributed to each of the individual components models coul d potentially provide useful diagnostic information to the user or modeler. As wood panel resin technologies improve and more ‘green resins’ become available, the potential exist s 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 m odel should provide sufficient ancillary information to understand the sensitive parameters and ide ntify 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 scientifi c data? If not, specifically note any unreasonable assumptions. Provide suggestions and r eferences 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 pr oduct (e.g. MDF panel) could do a study with their specific product to refine the cross-sectional res idential 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 l arge database of historical emissions parameters provided in the model (Table 2-2) and historical dec ay 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 o f 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 param eters may underestimate true emissions from products, particularly imported products, as a result of exce ptional free formaldehyde levels exhibiting non-conformance with the voluntary industry sta ndards. 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 manufacture r 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. T ypically the mass transfer coefficient is not determined in routine chamber testing, and the sensit ivity 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, humid ity or loading.

Question 1.3) Comment on the data sources. Are the data sources reasonable and accurat e? 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 accura tely represent the original studies, with the exception of the wallboard sink as noted belo w.

Emissions parameters It is unknown the degree to which the data in Table 2-2 ref lect manufacturing practices in 2009, and the potential for low or high bias exists. Users of t he 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 t o release of the model. Alternatively,3-110

perhaps a mechanism could be put in place such that the datab ase 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 furn ace 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 th e 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 th e 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 der ive the airflow rates Conventional 2 should be provided.

Wallboard sink The use of Langmuir isotherm for wallboard should be f urther 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 quanti fying 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 a l. (1987). The wallboard in this study was unpainted, but latex paint was not expected to apprec iably affect formaldehyde transport. The use of Langmuir isotherm should be furth er 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 Ma tthews et al. 1985 could be discussed.3-111

Question 1.5) Do the model input variables and the estimates assigned to them appropriat ely 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 provide d 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 Convention al 2 should be described. If possible, airflow rates should be made available for key de terminants as was done in MCCEM (e.g. season, area of the country).

Mass transfer coefficient The mass transfer coefficient is not routinely meas ured in most chamber testing. EPA should perform a sensitivity analysis to determine whether meas urement 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 deter minant of exposure with the mass transfer coefficient of less importance but this has not been es tablished 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 hav e investigated single products or collection of products over time (Zinn et al. 1990, Mølhave et al. 1995, My er and Hermanns 1985 and Brown 1999). The true area under the curve for dose given a l ong enough exposure time is likely better represented by the two- or three- compartment ex ponential 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 res idence 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 ques tions using a sensitivity analysis to3-112

determine whether conclusions about risk would change dependi ng 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 volunta ry submission of data representative of the current supply chain.

Question 1.6) Has EPA provided adequate documentation of the overall plausibility of the e xposure estimates generated by the exposure model? If not, provide suggestions f or 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 co mparing the model results to published concentrations of formaldehyde in new and existing structur es. 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 h alf-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. EP A has not considered whether the historical 2.92 year cross-sectional half-life is repres entative of the decay profile of modern products or the potential variability in the formaldehyde re servoirs 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 compli cate risk management decisions if the end point of concern is based on chronic exposure. The em phasis should be on developing a3-113

consensus approach to quantifying the reservoir of free-for maldehyde and formaldehyde precursors in a specific product. Currently the data availa ble to do this is somewhat limited, but it would be useful to have a theoretical framework in pl ace.



### 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 c umbersome than similar models like MCCEM, IAWX, EFAST or WPEM, but this is mostly attri butable to the use of a web-based platform and not a fault of the developer. Specific comm ents are provided below:

Air change rate Although the help explained why this was grayed out, I initia lly tried to edit this field because it was a text box prior to reading the help function. Repl acing 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 t o rename the source and a separate library of user entered sources should be maintained. Cur rently, it is impossible to know whether someone overrode the default values or the values presen ted are the default values. I would prefer that the individual panel results not be a perman ent 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 Define d 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. Not e 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.

Printing3-114

When a screen is printed in standard portrait view, the e dge 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. Pleas e consider writing a routine to allow the same information to be printed directly from the web-br owser as noted above.

Tab Key Each data entry box has a tab order. Generally when th e tab key is pressed, the next text box with focus is logical, but in some instances the next box i s 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 scre ens

that you would find useful.

The model help screens are intuitive and adequate. The aud io prompts generally worked well, although some were missing failed to load (e.g. first pro mpt on house screen).



### Part 3. Documentation

Question 3.1) Are the references accurately identified? Would any addition al reference

citations be helpful? Please note any additional reference s that should be cited.

The references are accurately identified, however I r ecommend 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 shoul d be provided.

Theory For more information regarding formaldehyde emissions fro m 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 code d’ 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 h ave summarized recent measured formaldehyde indoor air concentrations in new and exist ing 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 includi ng in the model is primarily for historical products, however, more recent indoor air data shows tha t emissions have declined. It is unclear the degree to which the decrease is due to changes in the pr oduct mix versus reduced emission rates. Therefore, users of the model should be encourage d to obtain emissions data for modern products if the results are appreciably outside the bounds expe cted. 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 referenc es (essentially a white paper and report prepared on behalf of HPVA) be replaced with peer-reviewe d publications, conference proceedings, or governmental citations. Examples of public ations 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 s ingle exponential equation does not describe the decay in emissions adequately. In turn, a sin gle exponential equation is not likely to accurately predict the LADD or LADC attributable to a spe cific product.3-116

Backpressure effect I recommend citing Jayjock 1994 in reference to the backpres sure 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 mode l 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 co ncentration time points of 3, 6 and 12 months were selected for output.

Estimation of sinks As described in more detail earlier, the treatment of si nks is not transparent and confusing because the rate of storage changes with time but the m odel used is a steady state model. Groah (2006) also tried to address the effect of wallboard sinks f or the pilot study home. This manuscript noted that much of the small chamber data wa s erratic, but that some data was usable. However, both in the model documentation and in the Gro ah (2006) publication, the approach used appears to be more an attempt to modify the model res ults to reflect the measured concentration than a rigorous handling of sinks. The approac h to wallboard sinks used in the

current EPA model should be consistent with the wallboa rd sink equations and data presented in Matthews et al. (1987). The wallboard in this study was unpa inted, 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 fo rmaldehyde 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 regres sion for the recent data Koontz et al. (1996).

Hoetjer-equation As described previously, the documentation should explain th e relationship between the3-117

Matthews and Hoetjer equation. The Hoetjer equation or e quivalent 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 t ransfer relationship (i.e. Ceq and K)

include:

• Berge et al. 1980

• Myers and Nagaoka 1981(presents the use of linear regression t o 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 t he number of occupied adsorption sites are much less than the available sites, reducing the is otherm equation to a simplified linear form (see for example, Tichenor et al. p. 24). At equilibriu m, when dM/dt = 0, there is no net adsorption and C indoor

= k d /k a *M.

Analysis of data Consider presenting the analysis of PFT measurements an d raw data in an appendix for Conventional 2 (p. 2-7). Is this data similar to data avail able 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 e xample, 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 regressi on 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 sens itivity 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 da tabase 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 li kely to change the conclusion. This could be done using the spreadsheet model already prepared. The unc ertainty 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 mode l 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 revie wed. To further verify the model calculations were implemented as intended using an alter nate approach, an example loading was run to steady state using IAQX Source Type 31. After the st eady state concentration was determined, the other parameters were calculated by hand. T he source used was the EPA kitchen cabinets, which corresponds to C v of 0.1633 mg/m 3 and K m of 0.49 m/hour in the mass transfer equation of IAQX. The results were evaluated with and wi thout a background concentration of 0.010 mg/m3. IAQX Model Source Type 14 was used to add the backgroun d concentration. The model results were successfully reproduced using this independen t approach (Table 4).

Table 4 : Verification of model calculations for test case3-119

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 outpu t 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 wit h above average background concentrations, the presence of the background sources co uld be important. Therefore, there could be cases where the user would like to include a backgro und concentration in the model, but exclude the contribution of background from the dose. Consi der 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. Hol z Als Roh-und Werkstoff 38: 252-255.3-120

Brown, S.K. (1999) “Chamber assessment of formaldehyde and V OC emissions from woodbased panels” Indoor Air, 9: 209–215.Groah 2006

CalEPA (2007) California Air Resources Board (CARB), Initia l Statement of Reasons for Proposed Rulemaking, Proposed Airborne Toxic Control Mea sure to Reduce Formaldehyde Emissions from Composite Wood Products, Office of Environme ntal Health Hazard Assessment, California Environmental Protection Agency (CalEPA).

Groah, W. J. (2006). Predicting indoor-air formaldehyde concen trations from emissions of ureaformaldehyde bonded wood products using the Versar model. For est 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. Berkele y, 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 a nd site-built houses”, Indoor Air, 10,178-193.

Jayjock 1994. Back pressure modeling of indoor air concentrations f rom volatizing sources. American Industrial Hygiene Association Journal, 55: 230-235.

Koontz M.D., Rector H.E., Cade D.R., Wilkes C.R., and N iang L.L. (1996) Residential Indoor Air Formaldehyde Testing Program: Pilot Study, IE-2814. Washingto n, DC, U.S. Environmental Protection Agency (U.S. EPA).

Maddalena R., Russell M., Sullivan D.P., Apte M.G. (2009). F ormaldehyde 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 Characterist ics of Pressed-Wood Products: Report XVIII to the U.S. Consumer Product Safe ty Commission. ORNL/TM-9867, Oak Ridge National Laboratory, Oak Ridge, TN.

Matthews, T. Hawthorne, A. and Thompson, C. 1987. Formalde hyde Sorption and Desorption. Characteristics of Gypsum Wallboard. Environmental Scien ce & 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 s tudy”, Indoor Air, 5: 104-119.

Meyer B., Hermanns K. (1985) “Reducing indoor air formaldehyde c oncentrations” Journal of the Air Pollution Control Association, 35, 816-821.

Myers G. and Nagaoka M. (1981) “Emission of formaldehyde by par ticleboard: Effect of ventilation rate and loading on air-contamination leve ls” Forest Products Journal, 31(7), 39-44.

Myers, G. E. (1983). Formaldehyde emission from particleboa rd and plywood paneling: measurement, mechanism, and product standards. Forest Product s Journal, 33: 27-37. Salthammer T., Fuhrmann F., Kaufhold S. Meyer B. and Sc hwad 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 Emissio ns from Engineered Wood Products: Summary and Evaluation of Current Literature" (E PA-600/R-96-067, NTIS PB96- 183876, June 1996).

Zinn, T.W., Cline, D. and Lehmann, W.F. (1990) “Long-term stud y 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 volum e, number of zones (1 or 2), and air exchange rates between indoors and outdoors and between z ones.

2. Put formaldehyde-containing sources into each zone, selecti ng types from a drop-down list or one’s own type, and then entering amounts (area s) of each type, and emission rate values based on a “slope and intercept” emission model. T he slope value accounts for the influence of vapor-phase HCHO on the emission rate an d the intercept value is the emission factor at zero HCHO in the vapor phase. A tabl e of slope and intercept values derived from the literature is provided. Users can enter t heir own values if they choose.

3. Calculate a “steady state” concentration of HCHO fr om 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 concentratio n 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 numbe r 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 concent ration of concern.

Step 2 seems like a convoluted way to model emissions: Th e 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 clearl y implies), this is true for all out-gassing substances. High gas-phase concentrations can suppress e mission rates. But if you look at the3-124

effect, say in Table 2-2 of the documentation, you can s ee 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 HCH O concentration was well above 0.01 ppm, which value is suggested by the model as a concentratio n of concern. Most of it is even above 0.1 ppm, which is the maximum concentration of con cern 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 predict s 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, re lative humidity, etc.

That said, the analysis provided in section 5.3 of the docum entation 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 mea sured values in the EPA pilot study house, is that the model ranged from about 24% low to abo ut 65% high. Predictions within that range are quite good, given the uncertainties in input data a nd unavoidable modeling assumptions.

Regarding the selection of a decay constant (or half-t ime if you prefer) for predicting the rate at which the HCHO concentration will decrease, I suspect t he default choice of k = 0.23 yr -1 (or t 1/2 = 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 th e one for 3-12 months, which may be higher than for 12-24 months, etc. I don’t have the Vers ar 1988 or Groah 2005 compilations at hand, so I didn’t check this but it would be simple to do on ce the data were compiled and segregated into appropriate time periods. First-order regre ssions could be determined for each time period; the k values would show whether the decay ra tes 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 m odels that assume complete mixing within compartments, is that it doesn’t deal wit h what I refer to as “intimate” sources. These are sources that can lead to much higher exposures, especially for very young children or3-125

elderly people, than would be predicted by such models as FI AM. Examples are toys, cribs, bedding materials, clothing, and flooring materials for chil dren 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 th an FIAM and most other models predict.

I think the most straightforward approach to such sources i s to assume a smaller compartment or zone around such sources for the purpose of predicting conce ntrations. Some years ago I made a stab at that in a paper for an indoor air conference 3 . In that paper I suggested a “volume of

concern” of 10 m 3 for dispersion of emissions from furniture and machines at workstations. The volume one might use for babies on bedding or flooring ma terials would presumably be much smaller; the resulting calculations would predict exposur es that might be orders of magnitude higher than predicted by FIAM.

User Interface

I had little trouble with the user interface. Minor com ments 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 examp le.

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 use ful. Users should have little trouble following it. Minor comments follow.

1. Page 2-4, 4 th

paragraph: you should not describe the slope as “...in the form of a firstorder sink representation...”. The slope represents a li near 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 p roducts: Where do we stand? In Proc. Indoor Air ’90 , Vol. 3, pp. 251-256. Ottawa: Indoor Air Technologies.3-126

2. Page 3-2, 2 nd

paragraph: the phrase “...flows of formaldehyde mass into and out of a fixed volume must be equal...” is not correct. In fact, equati on 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 th ese days is a simple matter with spreadsheets like Excel, where k can be determined easily f rom the “trendline” equation for a first-order exponential decay of the concentrati on 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-t ime 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 tha t I believe would be helpful to the general user, and have attached it. I don’t necess arily suggest this as a modification to FIAM, but as a general way to introduce mass balance co ncepts. 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 t his type will be upscale home builders and home manufacturers. They might use it to predict wheth er certain types and amounts of formaldehyde-containing materials would lead to indoor HCHO c oncentrations that exceed some air quality standards or criteria. However, I doubt ther e 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 pred icted by this model will lead to much more accurate or useful results than would be gotten fr om much simpler displays of emission factor data, loadings, and air exchange rates. Graphs relating these basic parameters to peak3-127

indoor concentrations could be created, similar to ones th at I presented in the IAQ Handbook

some years ago 4 and that others have also suggested. Spreadsheets would prob ably be preferable. If exposure estimates are of interest the decay rate o f formaldehyde concentration can be predicted based on selection of a decay constant (or a s eries 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 hea lth, 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 mode ls, 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 co ncentrations in the compartment). Mass flows of substances into and out of each compartment ar e simultaneously balanced with adjacent compartments.

Textbook descriptions of such models, and documentation th at 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 furth er development they might be helpful in some future indoor air modeling efforts.

The mass balance around any compartment in a multi-comp artment 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 su bstance consumed (CONS); and mass of substance accumulated (ACCUM). The units of each te rm are usually mass per time (e.g., mg/h).

[A simple box and arrow diagram could be inserted here. My abilities wi th 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 ofte n 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 t he 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 re leased into the air inside the compartment. This is often referred to as the “source te rm”. 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 fr om the air in the compartment by chemical reaction or irreversible sorption to a surfac e (including an air cleaner in the compartment). This term is often referred to as an “ir reversible 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 mathem atical representations of each of the five terms. In most applications one or more of the t erms are assumed to be zero and can be left out of the mathematical discussion.Appendix A

TECHNICAL CHARGE TO PEER REVIEWERSA-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 u sed indoors. This exposure estimation involves the integration of information on location/act ivity patterns (i.e., how and where people spend their time) and concentrations encountered by individ uals at indoor locations. The exposure is used by EPA along with hazard and dose-response i nformation to estimate risks of chemicals in products. If insufficient information exist s 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 computer ized Formaldehyde Indoor Air Exposure Model – Pressed Wood Products (FIAM - PWP) to assis t in estimating human inhalation exposure to airborne formaldehyde (HCHO) emiss ions from pressed-wood products in new or existing residences, small buildings and trailers

. The FIAM - PWP model is an adaptation of a model develope d during the 1980s by Dr. Thomas Matthews and colleagues at the Oak Ridge National Labora tory (Matthews et al. 1983a). The “Matthews model” was designed to estimate the steady-st ate 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 dependen t 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-s tate) indoor concentration calculated by the model is assumed to decrease over time as the reser voir of formaldehyde in various sources (or sinks) is gradually depleted. The gradual decrease over t ime is assumed to follow a first-order exponential process, at a decay rate that depends on the c hosen 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 produc ts to formaldehyde levels in homes and to evaluate current EPA exposure models. Shortl y after this study was completed, EPA tasked Versar to develop a modified version of the Ma tthews model. The primary modifications were (1) estimation of steady-state form aldehyde concentrations for the case of a two-zone indoor environment, and (2) incorporation of reve rsible (re-emitting) indoor sinks. The modified model also included the option to be run in a sing le-zone mode. The model was not finalized due to shifting priorities at the time of its devel opment.

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 ra w composite wood products and finished products sold or used in California. In 2008, EPA was pet itioned 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 t ype of regulatory or other action might beA-2

appropriate to protect against potential risks posed by form aldehyde 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 en vironments such as residences, travel trailers, temporary classrooms, etc. Therefore, the m odel 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 humid ity 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 co ncentrations and inhalation exposures to support a risk assessment of formaldehyde from pressed w ood products. It is anticipated that many model runs will be generated to model a variety of se ttings and that the model output data will be used in the decision-making process of evaluating t he 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 forma ldehyde 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. Yo u are requested to provide comments for each charge below, and when doing so to make clear th e rationale for your conclusions. In addition, please assess the level of confidence (or, co nversely, 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 specifi c 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 provi de 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 t hey 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 th e 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 calculatio n methodologies.

1.2) Comment on the default scenarios and default assumptio ns used by the model. Are the default assumptions reasonable and adequately supported by relevant scientific data? If not, specifically note any unreasonable assumpt ions. Provide suggestions and references for alternate default assumptions.

1.3) Comment on the data sources. Are the data sources reas onable and accurate? If not, specifically note any unreasonable or inaccurate data s ource. Provide suggestions and references for alternate data sources.

1.4) Do the data sources provide unused information that would ass ist 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 plausi bility 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 reliabi lity 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 da ta entry screens you found confusing or unclear. Provide suggestions to improve the user-f riendliness of the model.

2.2) Are the model help screens adequate? Describe any additional h elp screens that you would find useful.A-4 

### Part 3. Documentation

3.1) Are the references accurately identified? Would any add itional reference citations be helpful? Please note any additional references that s hould be cited.

3.2) Does the model documentation present the model construct, selected model inputs, model results in a clear, complete and useful manner? I f not, specifically note areas that are unclear or needs improving. Provide suggestions fo r additionally information.

3.3) Does the documentation for the FIAM - PWP make clear t he sources and anticipated magnitudes of variability and uncertainty in model result s? 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 ar e inconsistent between the model and documentation.Appendix B

FIAM-PWP MODELB-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 MATERIALSC-1

Appendix 1. Formaldehyde Indoor Air Model – Pressed Wood Prod ucts (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 Concentrat ions 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 Concentrat ions 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 o r 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 Produc ts Bonded With Formaldehyde Based Adhesives (PDF) (60 pp, 1,007K)

Appendix 9. Hare et al., 1996. Evaluating the Contribution of UF-Bonded Building Material s to Indoor Formaldehyde Levels in a Newly Constructed House (PD F) (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 Indoo r 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 t o 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 (PD F) (12 pp, 321K)

Appendix 16. Silberstein, 1988. Validation of Models for Predicting Formaldehyde Concentrations In Residences due to Pressed-Wood Products (PD F) (9 pp, 1.72 MB)

Appendix 17. USEPA, 1990. Compendium of Methods for the Determination of Air Pol lutants 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 Pol lutants in Indoor Air – Part 2 of 2 (PDF) (402 pp, 12.1 MB)

Appendix 19. Versar, 1988. Formaldehyde Exposure in Residential Settings: Sources, Lev els, 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)