c I

t 

### 3 445b 0070928 

### bIORNL/TM-9867

HEALTH AND SAFETY RESEARCH DIVISION

MODELING AND TESTING 

### OF FORMALDEHYDE EMISSION CHPlRACTERISTICS 

### OF PRESSED-WOODPRODUCTS: Report:XVIII to the 

### U.S. Consumer Product Safety Commission 1985



### T. G. Matthews Contributors: 

### T. J. Reed,

### B. R. Tromber ,lK. 

### W. Fung,2 C.

### V. Thompson,

### J. 0. Simpson, 

## $ and A. 

### R. Hawthorne

Date Completed

## - November 1985

Date Published

## - September 1986

OAK RIDGE NATIONAL LABORATORY Oak Ridge, Tennessee 37830 operated

### by MARTIN 

### MARIETTA ENERGY SYSTEIMS, INC. 

### for the 

### U.S. DEPARTMENT 

### OF ENERGY

IDepartment of Chemistry,University of Tennessee,Knoxville,

### TN 37916 2Safety Office,University of Hong Kong,Hong 

### Kong 3Department of Chemistry, Spelman College Chattanooga,

### TN **37405 c-**  'i l. 1CONTENTS



## ......................................................... LIST OF FIGURES V LIST OF TABLES 

## .......................................................... vii ACKNOWLEDGMENT 

## .......................................................... ix SUMMARY 

## ................................................................. xi REPORT 

### XVIII



## .......................................................... INTRODUCTION 2 ENVIRONMENTAL PARAMETERS STUDY 11 3 

## .....................................



## ..................................................... Models 

### I and I1 3 Analysis of Particleboard,Paneling,and Medium Density Fiberboard Data 5 Modeling 

### of CH20 Emissions Data 9 Interproduct and Interstudy Comparisons ofModeling Results 

## ......... 11 Sensitivity Analysis 

### for Model 

### I,I1 Coefficients 

## ................... 18 Uncertainty Analysis for Model 

### I and Model I1 

## ....................... 23 

## .....................................................

.....................................

SINKS STUDY 

## ........................................................... 28 SLOW DECAY STUDY 

## ...................................................... 35 FAST DECAY STUDY 

## ...................................................... 38 Temperature,RH Correction Model 

## .................................... 39 Formaldehyde Emission Rate Decay Modeling 

## ........................... 42 Front/Back Emtssion Ratios 

### for Paneling 

## ............................. 43 PERMEATION BARRIERS STUDY 

## ............................................. 47 Simulated Flooring Experiments 

## ...................................... 47 Permeation Barriers Modeling 

## ........................................ 52 INTERLABORATORY TEST COMPARISON

### OF THE FSEM 

## ........................... 56 APPENDIX 

### I: Uncertainty Analysis 

### ofModels 

### I and I1 

## .................... A.l

iii

### LIST OF 

### FIGURES
REPORT 

### XVIII Figure 

### 1: at Constant 

### N/L 

# . 0.5

### m/h 

## ............................................. 19 Model 

### I Analyses **of**

### All PBU. PAN Data Set Figure 

### 2: Model I1 Analyses ofAll 

### PBU. 

### PAN Data Set at Constant [CH20]

# . 0.1 ppm 

## .......................................... 20 Figure 3: Summary of Sinks Sorption Data 

## ............................. 31 Figure 4: Summary 

### of Sinks Desorption Data 

## ........................... 34

V

### LIST OF TABLES

REPORT XVIII Table 

### 1. Temperature,

### RH Zest conditions used in



## ................................. the Environmental Parameters Study I1 5 values 

### for Table 2. 

### Summary of C 

### , CH20ERstd 7 VSt Environmental Parameters gtudy 

### I1 

## ..................................... Table 

### 3. Selected,standard-conditim,normalization factors for Environmental Parameters Study IT 

## ......................... 10 Table 4. Results ofnonlinear regression analyses for Model I 

## ........ 12 Table 5. Results 

### of nonlinear regression analyses €or Model I1

## ........ 13 for individual Table 6. Model I analyses. Comparison of C and combined product data sets as a function of environmental parameters. 15 

# 4 T,RH,N/L std 

### V

Table 

### 7. Model I1 Analyses. Comparison of CH OE for individual and combined test product data sets 2 

## %,RH[CH20]’CH20ERstd as a function of environmental parameters 

## ............................. 16 Table 8. Sensitivity Analysis of Model 

### I: and I1 Coefficients 

## ......... 21 Table 

### 9. Uncertainty analysis for ALLPBU,

### ALLPAN and ALLMDF Model 1 Analyses 

## ...................................................... 25 Table 

### 10. Uncertainty analysis for

### ALLPBU,ALLPAN and ALLMDF Model I1 Analyses 

## ..................................................... 25 Table 

### 11. Slow decay study data file 

## ................................. 36 Table 12. Environmental conditions inside the storage room for the fast decay studyboards at the time of FSEMmeasurements 

## .......... 40 Table 

### 13. Summary of decay periods (P, months) for individualboards in the fast decay study 

## ............................. 44 Table 

### 14. Summary of average decay periods (7,months) for the fast decay study 

## .............................................. 45 Table 

### 15. Summary of frontback CH 

### 0emission ratios 2 of fast decay study boards 

## ............................................ 45 Table 

### 16. Formaldehydevapor concentration data (ppm) from the simulated flooring experiments of the permeation barriers study 

## ....... 49

viiTable 

### 17. Modeled CH2O vapor concentration data (ppm) for uncovered particleboard during flooring-coveredparticleboard experiments 

## ....... 51 Table 

### 18. Linear regression analyses of the modeled CH28 concentration data for **uncovered** 

### particleboard**underlayment** during flooring

## - coveredparticleboard experiments 

## ".................. 54 a

Table 

### 19. Comparison ofmeasured and modeled CH 0vapor concentrations (ppm) from simulated flooring experiments 

## .............. 55 2
Table 20. the FSEM forparticleboard underlayment samples 

## ....................... 57 Interlaboratorytest comparison results 

### of
Table 21. Interlaboratory test comparison results 

### of the 

### FSEM forhardwood plywood paneling samples 

## ........................ 58

viiiACKNOWLEDGMENT
Research sponsored 

### by the 

### U.S. Consumer Product Safety Commission under Interagency Agreement 

### CPSC-IAG-82-1297under contract DE-AC05-840R21400with the Martin Marietta Energy Systems, Inc.



### ix

### SUMMARY OF PRESSED-WOODPRODUCT RESEARCH PROGW:REPORT

### XVIII
Research has been conducted at Oak Ridge National Laboratory to better understand the formaldehyde emission characteristics ofpressed-woodproducts that are manufactured in the U.S. and commonly incorporated in domestic environments. There were strong experimental and modeling components to this research including analytical method development, the survey of product emissions and the modeling of the interactionof these products in indoor environments. The results of these investigations havebeen reported to the sponsor, the 

### U.S. Consumer Product Safety Commission (CPSC), in the form of detailed bimonthly to quarterly reports. Report 

### XVIIT comprises the final progress report to CPSC, which discusses the final results of sixprojects conducted as part of the pressed-woodproducts research program. No final, comprehensive project reportwas written due to resource limitations.
The experimental results andmodeling of a second environmental chamber study of the environmental dependence of CH2Q emissions from selected pressed-woodproducts are reported. Results for particleboard underlayment, hardwood plywood paneling,and medium density fiberboard are given. Revised models for 

### (1) variation in CH2Q concentration inside a single compartment with a single emitter (i.e.,Model 

### I), and 

### (2) variation in CH2O emission rate of a single emitter (Model 11) as a function of environmental parameters are presented. The revised models include a 

### (1) a linear function for the temperature 

### (T) and relative humidity 

### (RH) dependence of the CH20 transport rate through the bulk phase (i.e.,board) and (2) a non-linearfunction for the RH dependence of the CH20 concentration in the bulk phase. Pressed-wood product emissions data from individual Study I1 boards and the combined data sets from Environmental Parameters Studies 

### I and I1 are analyzed using the revised models. Good fits between individual product data sets and

### Models 

### I and I1 are observed. Due to the complexity of the Models 1 and. IT (i.e., 5 term models), simple analyses of the model results (such as interproduct and interstudy comparisons) based onvalues of individualmodel coefficients are often inadequate. Instead, analyses of the model. results are performed 

### by substituting selected environmental conditions into the test-product models for comparison of the calculated dependent variables; that is, the proportionate changes in CH20 concentration (i.e.,Model 

### I) and CH20 emission
xirate (i.e., Model 11). The Model. 1 results €or combined particleboard, paneling and fiberboard data sets indicate two-fold increases in CH2O concentration with approximate increases of 7OC and 30-50%

### RH at constant air exchange and product loading conditions. The Model I1 results for combined product data sets indicate two-€old increases in CH20 emission rate with increases

### of 4-SoC and 20-40%W at constant CH2O concentration. Additional statistical analyses concerning 

### (1) the sensitivity of Models 

### 1 and I1 to variation 

### in individualmodel coefficients and (2) the uncertainties in Model 

### I and 11 estimates with changes in environmental parameters, are also presented. The sorption and subsequent desorption of CW20vapor on the surface of unpainted gypsum wallboard has been studied in environmental chamber experiments at 23OC and 

### 58%

### RH. Simple, three-term,single exponential models with riseJdecay periods of about three days describe the time dependent rise and fall of CH20 concentrations in chamber experimentswhere gypsum board is exposed to (step-function) increases and decreases in CH20 concentrations, respectively. Gypsum board acts as a time-dependentbuffer to changes in CH20 concentrationbut constitutes only aweak permanent CH2O 

### loss mechanism.


### The final results of two decay studies examining the time-dependent decline in CH20 emissions from selected particleboard underlapent, industrial particleboard, hardwood plywoodpaneling and medium density fiberboard are reported. 

### In the slow decay study, the decline in CH20 concentration generated from a collection of pressed-woodproducts, contained in a walk-in chamber about 23OC, 

### 50% 

### RN and a 0.4h’l air exchange rate,was monitored 

### for 

### 14 months. 

### In the fast decay study,che decline in CH20 emission rates from individual pressed-woodproducts, conditioned at about 23%, 

### 50%

### RH and typically

### < - 0.1ppm CH20,was monitored for 16 months. The 1Je decay period for the slow decay studywas 

### 2.2years. The average l/e decay periods 

### for particleboard,paneling and fiberboardproducts were 

### 1.1,0.9 and 

### 1.6 years. The shorter decay periods in the fast decay study are consistent with anticipatedhigher CH20 emissions from particularly weaker boards at reduced CH20 concentrations. at

xiiThe retardation

### of CH2O emissfons 

### from particleboard underlayment by three decorative flooring barriers has been studied in small scale environmental chamber experiments at approximately 23% and 

### 50% 

### RH. The permeation barriers consisted 

### of nylon carpet over sponge rubber and urethane foam cushion,and vinyl tile flooring. The effectiveness 

### of the flooring barrier in reducing CH20 emissions was experimentally evaluated through sequential measurements of CH20 emissions frombare and covered particleboard underlayment. The carpet and cushion barriers resulted in 

### 5 2.5 fold reductions in CH2O emissions in comparison to approximate 30 fold reductions with the vinyl flooring. Formaldehyde transport models based onmeasurement of the CH20 diffusion coefficients of the flooring products predicted reductions in CH20 emissions from the particleboard quite similar to the experimental results for two of three flooringbarriers.
The preliminary results of an incomplete interlaboratory comparison of measurements of 

### CH20 emission rate from particleboa.rd underlayment and hardwood plywood paneling samples using the formaldehyde surface emission monitor are reported. Correcting for interboardvariatlon inCH2O emission strength as determined from 

### 0RNL emission measurments, the coefficients of variation between the average results of six of sevenparticipants is 

### 10% and 

### 14% for the paneling and particleboardmeasurements,respectively.MODELING AND TESTING OF FORMALDEHYDE EMISSiON CHARACTERISTICS

### OF PRESSED-WOODPRODUCTS

Report Xi7

### I II

June 

### 1984 

### - May 1985



### T. G. Matthews,

### T. J. Reed, 

### B. R, 

### Tromberg,

### K.W. Fung,** C. 

### V. Thompson,J. 0. Simpson,and A. 

### R. Hawthorne Measurement andApplications Group Health and Safety Research Division 

### Oak Ridge National Laboratory Oak Ridge, Tennessee 

### 37831 **Safety Office, University of Hong Kong



# * Research sponsored 

### by the Consumer Product Safety Commission under Interagency Agreement 

### CPSC-IAG-84-1103under Martin Marietta Energy Systems, Inc., Contract DE-AC05-840R21400 with the 

### U.S. Department of Energy.Report 

### XVIII 

### 2 CPSC-IAG-84-1103

MODELING AND TESTING 

### OF FORMAIDEHYDE EMTSSJON CHARACTERISTICS 

### OF PRESSED-WOODPRODUCTS Report 

### XVXII June 

## - December 11984


### T. G,Matthews,

### T. J.Reed,B. 

### R. Tromberg,

### K.W. Fung,** 

### C.

### V. Thompson,

### J.0. Simpson,and A. 

### R. Hawthorne Measurement and Applications Group Health and Safety Research Division Oak Ridge National Laboratory Oak Ridge,Tennessee 37831

INTRODUCTION

The projects that are discussed in this report include:

1. the environmental parameters study 

### 'TI using particleboard underlapent, decorative paneling, and medium density fiberboard materials acquired in the commercial pressed-woodproduct survey,
2. the formaldehyde (CH20) 'sinks' (i.e., water bearing sorbent materials) study of gypsum wallboard and carpeting,
3. the 'slow' decay study for pressed-woodCH 0emissions at a fixed 2 air exchange and loading,


### 4. the 'fast' decay study for pressed-wood emissions at low CH20 concentrations,
5. the permeationbarriers study,and
6. the interlaboratory test comparison of the FSEM.
The final results from all projects will be reviewed 

# * Research sponsored by the Consumer Product Safety Commission under Interagency Agreement CPSC-IAG-84-1103under Martin Marietta Energy Systems, Inc.,Contract:DE-AC05-84OR21400with the U.S, Department of Energy

## .Report

### XVIII 3 CPSC-IAG-84-1103

ENVIRONMENTAL PARAMETERS 

### STUDY I1
The environmental chamber studies for particleboard underlapent, hardwood plywood paneling and medium density fiberboard 

### (MDF) samples are complete. Results of the modeling of the Environmental Parameters Study 

### I1 data arepresented in this report.
Models 

### I and I1
The 

### CM 0concentration model (i.e.,Model 

### I) and the CH20 emission rate 2 model (i.e.,Model 

### 11) that were originally presented inReport 

### XIV have been revised.
The final expression for Model 

### I is:

P std 

### 11 cV 

### -C(- 

# - -) [l+B(T-296)] 

# - [l+E(RH-SQ)] e 296 

# - (RH/5Q)* 

### [KB 

## + 0.51 s

### ta [l+B(T-296)] [l+E(RH-50)] * 

### KB -I- N/L std

where:
T = temperature (degrees Kelvin),


### RW = relative humidity (%),
N/L = air exchange to loading ratio (m/h),

Cv

# - CH 0vapor concentration (ppm), 2Report 

### XVIII 4 CPSC-IAG-84-1103



### K = modeled 

### CH 0transport coefficient for the bulk phase (m/h),

R 

### 2
std = standard test conditions (i.e.,

### 23"C,50%

### RH, 

### N/L

# - 0,5 m/h), and
A,B,C,E=model coefficients for temperature and RH terms.
The final expression forModel I1 is: 

### C"20EKT,RII,Cv CW20ERstd =c _- 1 

### 1 

## -e(- - -) 

### [l+B(T-296)] 

# - [1+E(RH-50)] [e 

### 296 (RH/50)A * C 

### -

## cvl 

## %td

where:


### CH OER = 

### 2
std =


# - - 0.1 std cB

2 CH **0** emission rate (mg/m h), 2
standard test conditions (i.e.,23°C. 50% RH, Cv = 0.1ppm), and


### CH **0** concentration in the bulk phase. 2

The revisions in Models 

### I and I1 are based upon two refinements in the assumptionsused in the mathematical development of the Models.



### 1. The CH 0 transport coefficient for the bulk phase,

### KB, is assumed to be a function of temperature and relative humidity (RH). Previously

### K was assumed tobe constant. 2 B

2. The KH dependence of the 

### CH 0vapor concentration in the porous bulk 2 phase isassumed to follow the nonlinear expression:

Previously 

### f (RH) was assumed to be a simple linear function. 

### cBReport 

### XVIII 5 CPSG-IAG-84-1103

The justification for these revised assumptions and the complete derivation of Models 

### I and I1 have beenpreviously reported.(1)
Analysis of Particleboard, Paneling,and Medium Density Fiberboard Data
The experimental testing sequences for the particleboard underlayment, hardwood plywood paneling,and medium density fiberboard products used in the Environmental Parameters Study I1 are listed inTable 

### 1. The testing of the particleboard and paneling products received a larger number of test cycles than the medium density fiberboard. The numbers 

### 1 through 5 in Table 

### 1 refer to successive measurement series taken at standard conditions of 23" C and 

### 50% RH. emissions and at standard test conditions. These data are used to determine C CW20ERstdvalues, which are the normalization factors used to treat 

## gff of the 

### CH 0emissions data forModel 

### I and I1 analyses. The numerical values of for Model 

### I and CH20ERstd for Model I1 are listed in Table 

### 2. The an3 CH OERstd values determined from 

## cv td cofumnheadings 1 through 5 are forC 's td individual data sets taken at standard conditions. The column headings 1 

### 2 and CH OERstd values determined from combinations of and 2 5 are for Cv two data sets (i. e.

### , ls$dand 2,5, respectively) taken at standard conditions. 

### The Study I1 design allowed for frequent determination 

### of CH 0 2 

### V 

# *
2
2
2

The selection 

### of appropriate normalization factors 

### for the experimental 

### CH 0 emissions data are required before Model 

### I and I1 analyses canbe performed. These factors are chosen to best account 

### for the aging of the test products during the enviromental parameters study and potential experimental 2

problems that might strongly affect the modeling results. For example, and CH OERstd values listed in Table 2 indicates that analysis of the Cv data taken at stana%!d conditions 4 were collected prior to adequate 2



### 1.

### T. G. Matthews, 

### T. J. Reed, C. R. Daffron and A. 

### R. Hawthorne, "Environmental Dependence of Formaldehyde 

### Emissions From Pressed-Wood Products: Experimental Studies and Modeling" Proceedings, 18th International Washington State University Particleboard/Composite Materials Symposium,pp 

### 10-23,1984. 

## * The calculations used to determine the CVstd and CH OERstd values have beenpreviously reported. See reference 

### 1,pages 21-3.Report XVIII 6 

### CPSC-IAG-84-1103

Table 1. Temperature, 

### RH test conditions used in the Environmental Parameters Study 11.
~.. Study Conditions Design

Standard



### A. Particleboard (i*e.,PRU3), Paneling (i.e., PPR2, PPR3) Study 23 23 23 23 28 33 23 26 30 23 23 40 50 75 50 50 50 50 80 65 50 50 1 Iso-Thermal 2 Iss-RH 3 Matrix Variation 4 5 

### B. Medium Density Fiberboard (i.e., MDF1,

### MDF2) Study 23 50 28 50 33 75 23 50 Matrix VariationReport XVIII 7 CPSC-IAG-84-1103

a Table 2. 

### Summary of Cv 9 CW20ERstd values for std Environmental Parameters Study 11.

- Test Product 

### Model 

### 1 2 3 

### 4 5 12 25
PBU3 PPR2 PPR3 MDFl MDF2 PBU3 PPR2 PPR3 

### MDFl MDF2 Ia 0.258 0.237 0.221 0.260 Ia 0,312 0.256 0.150 0.263 

### Ia 0.153 0.121 

### 0.102 0.150 Ia 

### 0.855 0,689 

## xa 0.434 0.395 

### IIb 0.422 

### 0.489 0.305 8.443 IIb 0.373 0.312 0.117 0.325 

### IIb 0.169 0.103 0.063 

### 0.161 

### IIb 1.69 1.95 Ilb 0.811 

### 0.960 0.251 0.247 0.240 0.185 0.282 0.214 0.120 0,136 0.121 0.787 0.415 0.437 0.447 0.459 0.177 0,340 0.231 0.096 0.132 0.101 1.78 0.866

a

Model 

### I: Cv23"C,508RH,O.5

### m/h bModel 

### 'I: CH20ER230C,50%

### RH,O.1ppm'Report 

### XVXPI 

### a CPSC-IAG-84-1103
conditioning of the particleboard and paneling test products, Forboth Models 

### I and 11, the standard conditions 4 values are high in comparison to all standard conditions 3 values,most 

### 2values, and some 

### 1values (see Table 2). Since product aging shouldhave occurred over the duration of the entire three to four month study,repeat tests were performed at standard conditions (i.e., 

### 5 values) following an additional two to three week conditioningperiod. The reductions in standard conditions 5values in comparison to 4 values (observed primari1.y in the paneling test products) confirm that insufficient conditioning time had been alotted prior to the standard conditions 4 tests. The high values for standard conditions4 may have been causedby relatively harsh environmental exposures of the particleboard and paneling test products at 30°C and 65%RH during the previous test cycle. For these reasons,data for standard conditions4 are not considered in further analysis and modeling. Further analysis of the standard conditions data 

### in Table 

### 2 indicates that the C and CH20ERstdvalues for standard conditions 3 are low relative to standard conditions 2 and 5. This is true for all three particleboard and paneling test products, particularly for 

### CH OER values. The low results for standard conditions 3 are inconsistent with an anticipated continuous decline in CH 0 emission strength between standard conditions 

### 2,3, and 5. In addition, the low results 

### for standard conditions 3 are particularly unexpected in light of the relativelyhigh results for standard conditions 5, which were taken following an additional one to two month conditioning and testing period. The results for standard conditions 3 are rejected from further analysis andmodeling based on two considerations. 'std
2 std
2

A higher confidence is placed on the results for standard conditions 5 than standard conditions 3 because of the lengthy conditioningperiod prior to standard conditions 5 testing. This lengthy conditioningperiod plus normal product aging between the standard conditions 3 and 5 tests would predict that the results for standard conditions 5 shouldbe lower than for standard conditions 3. Any potential error in the rejection of the data for standard conditions 3 should result in a more conservative treatment of the impact of environmental parameters on CH 0emissions from the test products. The 2Report XVIII 9 CPSC-IAG-84-1103

inclusion 

### of standard conditions 3 data would result in smaller normalization factors 

### for particularly the Iso-Relative Humidity and Matrix Variation experiments (see Table 

### I), thus increasing the sensitivity of the model to changes in the temperature and RH.

and CW DERstd normalization factors are listed in Table 3. The standad conditions 1,

### I 2, and 

### 2 5 refer to product-dependentnumerical values specified in Table 2 forboth Model 

### I and I1 analyses. The Cv and CH20ERstdnormalization factors are chosen to reduce the modeled impaztdof changes in product emission strength due to product aging between consecutive chamber tests at standard conditions. For most test cycles this is accomplished using combined normalization factors

(i.e., 

### 1 2, 

### 2 5) determined frompairs 

### of standard conditions data sets that bracket one or more data sets taken at non standard conditions, To value 

### for normalization exemplify the use of Tables 2 and 3, the 

### 2 of PBU3 emission data (i.e., 0.240ppm,Table 2) is applied to the consecutive test cycles at 23"C/50% RH, 28"C/50% RH, 33"C/50% RH, 26"G/80% RH, 30°C/65% 

### KH and 23"C/50% KH as specified 

### in Table 3. 2 The final selection 

### of the C vst



# *

std 

## cv

Modeling of CH 0Emissions Data 2
The normalized CH 0concentration and CH 0emission rate data for all test products were fit to Models h and 

### II, respectively,using nonlinear regression analyses (see Reference 

### I,pi). 25-6). 

### All model coefficients were bounded to positive valaes as a reasonable expectation of the physical theory. 

### The SAS nonlinear regression software with Marquardt iteration was used with analytical derivatives to analyze of all individualpressed-woodproduct data sets. The combined product data sets Erom Environmental Parameters Studies 

### I and I1 were analyzed using DUD iteration techniques with numerical derivatives to reduce computer costs. In the modeling of Environmental Parameters Study 

### I data, the 

### DUD iterationmethod was shown to give reliable estimates sfmodel. parameters when large,combinedproduct data sets were used. 2 2



## * For detailed discussion of calculations for CV and CH

### 2 OERstd, see reference 

### 1,pages 21-3. stdReport 

### XVIII 10 CPSC-IAG-84-1103

Table 3. Selected, standard-condition, normalization factors 

### for Environmental Parameters Study 

### II

..- Temp 

### ("C) RH (8) Standard Conditiona

23 23 23 23 23 23 28 33 26 30 23

23 28 33 23 A. Particleboard (i.e., 

### PBU3), Paneling (i.e., PPR2,PPR3) Study 40 50 

## so 75 50 50 50 50 80 65 50 1 1 12 12 12 25 25 25 25 25 25 **8.**Medium Density Fiberboard (i.e.,MDF1, MDF2) Study 50 60 75 50 12 12 12 12

a

Numerical values listed in Table 2.Report XVIII 

### 11 CPSC-IAG-84-1103

The results of the Model 

### I and 

### I1 analyses 

### of the particleboard,paneling and 

### MDF data sets are listed in Tables 4 and 5. Several analogies are observed with the results from Environmental.Parameters Study 

### I (See Reference 1,pp. 27-8).



### 1.

2.

3. A good fitbetween the experimental data and Models 

### I and I1 is indicated by the rgncorr values of 0.91 

## - 0.99 and root mean square errors of typically <0.5 for individualproduct data sets.
The Model 

### I and Model I1 coefficients 

### for individual particleboard data sets determined in Study 

### I typically overlap within 

### 95% confidence intervals with the same model coefficients for individual particleboard data sets determined 

### in Study 11. For both Studies 

### I and 

### I1 the 95% confidence intervals are generally broad.
The Model 

### I and Model I1 coefficients for various combinations of particleboard paneling products data sets determined in Study 

### I are closely comparable to the same model caefficients determined from both Study 

### I and Study 

### 11 data. A variation of <25% is typically observed between model coefficients determined for Study 

### I- and Study 

### 1,IIcombined product models. and

Interproduct and Pnterstudy Comparisons of Modeling Results
The method chosen for detailed interproduct and interstudy comparisons 

### of the environmental parameters models is to examine the variation 

### in CVT,~,,J/L/CV~~~ (ie.. Model I dependentvariable) and CH~OERT,RH,CV/CH~OERS~~ (le., Model 

### I1 dependent variable) for different product models 

### as a function of 

### T,RH, and 

### N/L or Cv parameters. 

### A comparison is performed by substituting the model coefficients for different product models and selected

### T,RH, and 

### N/L or Cv conditions back into Equations 1011 

### 2 for Model 

### I or I1 analyses, respectively. The result is a direct comparison of the predicted CVT,~,N/L/CV~~~ or CH~~ERT,RH,~V/CH~OERS~~ values far different product models under selected environmental conditions. An advantage of this type of comparison 

### is a reduced uncertainty (as estimated 

### by the root mean square error) in modeled CVT,~,.J/L/CV~~~ or CB~QERT,RH,CV/CH~OER~~~ values in13 

### c H Table 4. Randts of nonlinear regression analyses for Model 1



### c.

1-0 st 95% Confidence **li** 9% Confidence 95%Confidance 95%Confidence E 95% Coaffdence Root mea8 2 product intern rrl i**ut**ervnl intervnl interva1 qunre error 'wcorr 1aterv61 brn PW FER3 HDF1 

### m AIi RPB Study 1,XI All PAN stug I,I1 AI1WU, PAN

study 1.11

study 11 AI1WDF 8350 sSO0 13400 s**800** 9300 7200 5soo
6IO0
8700 110C+9500 4200-6800 730&9500 MOO-7 000 6660-12000 6800-7700
4800-6200
5600-6600
6300-1IO00 0.57 0.23 1.23 1.25 0.93 0.65
0.98
0.88
0.74 0.33-0.81 0.05-0.42 1.02-1.44 0.73-1.78 0.16-2.02 0.40-0.89 

### -

0.661.36

0.62-1 .14



### -0.23-1.71 0.93 0.40 om 1.25 1.18 6.6s
035
0.60
1.58 O.'P*f.lB 0.93-0.46 0.63-1.07 0.73-1.76 1.lb2.06 0.54-0.77 ! 0.40-0.ii
0.49-0.74
1.10-2.06 0.054 0.016 0.042 6.POO 0.624 0.074
0.121
0.107
0.026 0.000-0.108 0.013-0.129 0.009-0 .OB 0.039-0.161 0.050-0.097 0.042-0.105 

## -

-

0.045-0.197

0.063-0 .I50



### -0.055-0.108 0.019 0.03R 0.m 0.011 0.017 0.015
0.021
0.017
0.033 0.005-0.036 0.825-0.OS2 0.001-0.030 0.007-0.040 0.029-0.063 0.001-0.031 

### - 

## -
-

-0.005-0.050


## -0.001-0.035



### -a.027-0.o93 0.16 0.16 0.20 0.04 0.10 0.2&
0.66
0.53
0.14 0.99 0.99 0.99 5.99 0.99 0.9s
0.92
0.95
0.99Table 5. Results of nodincat regressloa rrmlyrar for Model 11 

# P w 0 Y r? 

# 2 H H W

Teat 95% Confidence A 93%Coafidence 951Confideam 95%Coafidencs E 95%Confidence loot mean 2 produet iatervsl int em81 

### CBatd LUt0tr.f latsrral intervd sqtmre error 'meorr 

### wm 7900 6800-9000 0.44 0.23-0.64 0.41 0.38-0.44 0.004 0.017-0.02s 0.013 0.006-0.021 0.25 0.96 gRu 6500 4SOO-8400 0.76 0.37-1.15 0.51 0.45-0.38 0.016 0.020-0.051 0.004 0.0O7-0.014 0.33 0.93 m3 7300 610&8SOO 0.94 032-1.15 0.25 o.zz-o.au 0.050 0.017-O.OM 0.028 0.01~-0.039 0.45 0.96 Mal 5WO 4900-7000 1.1s 0.83-1.48 1.05 6.89-1.21 0.091 0.057-0.125 0.022 0.01iF0.034 0.17 0.99 -


### - 

## -



# - mF2 9WO 6300-11000 0.88 0.38-1.37 0.36 0.46-0.63 0.000. 0.02S-0,025 0,023 -0.064-0.043 3.20 a.9s 

## - - All Ll.8. WU 9400 7800-11000 0.37 0.38-1.12 0.36 0.27-0.45 O.@ZS 0.013-0.062 0.016 0.012-0.043 1.38 0.84

stndy I.11 Study 1.11 stedy I,I1 stag LIZ All HDDP 5000 1500-8500 1.90 0.70-3.10 0.90 0.54-1.26 0.090 -0.009-0.190 0.000' -0.024-0.024 0.60 0.96 Study I1 

## - - All PBU 9100 7600-11000 0.36 0.43-1.14 0.33 0.24-0.43 0.01J -0.OOtO.MS 0.023 0.011-0.057 1.91 0.79
All PAW 6500 5100-7800 0.66 0.32-1.00 0.41 0.34-0.4'1 0.05s 0.02fM*OW 0.029 0.015-0.044 0.71 0.88
All PBU, PAN 8300 7400-9200 0.60 0.16-1.02 0.33 0.29-0.40 0.036 0.012-0.061 0.024 0.006-0.041 1.s 0.EO



### - P W

- 'Ibdel eoeffialentbounded torrlwr )O. Error estimate8 are ~pproriaats. I H 

# =; f **co** P P **0** WReport XVIII 14 CPSC-IAG-84-1103
comparison to the uncertainty for most individual model coefficients. In addition, a direct interproduct or interstudy comparison ofmodel coefficients couldbe misleading because of the complexity of Models 

### I and I1 and the use of dual temperature and RN coefficients.

An analysis of the interproduct variation in modeled CVT,~,N/L/CV~~~ (ie., Model I) and 

### CH~OERT,R~~,CV/CH~OERS~~ (ie., Model 11) as a function of environmental parameters for test products from Study 

### I has previously been reported (see Reference 

### 1, pp 29-36). To facilitate Study 

### I, Study I1 comparisons,the Study I1 analysis listed in Tables 6 and 

### 7 are given in a similar format to that used for Study 

### I (see *Tables VII, VIII,Reference 1).
For Model 

### I comparisons, several similarities are observed between the results for Environmental Parameters Studies 

### I and 11.



### 1. For potential seasonal changes in environmental conditions from 20"C, 35%RN to 28"C,

### 75% RN at a constantN/L 

### of 0.5 m/h, a range of 3 to 10 fold increases in the modeled CVT,RH,N/T/CV~~~ are predicted from the results of Study I. A smaller but overlaping range of 5 to 8 fold increases are predicted from the results of Study 11.
2. Twofold increases in modeled CV~,m,~/dCv~td are predicted with 

# * increases of 6 to 8 Celcius degrees and 

### 20 to >50 additionalpercent RH in both Studies 

### I and 11.
3. I.arger interproductvariation in C~~,m,N/dCv,tdis predicted as a function of variation in

### RH than temperature or 

### N/L parameters in both studies

## . Both similarities and differences are observed between the results of Model I1 comparisons for Study 

### I and Study 11. 

## * Certain testr products whose CH20 emissions are insensitive to changes in RH would require a >50% increase in RH from 50% to

## >-loo%RH to achieve a twofold modeled increase in cV~,w,N/L/cVs~d (ie.,Model I) at a constant temperature and N/L. A >-50% increase in RH from 50%R1.l is not considered because it is a non-physicalsolution.Report XVIII 15 CPSC-IAG-84-1103

Tabla 6. Modal I analysoe. Ccmprrison **of C+,**  for individual and combined product data sets 'L.RB.tl/L/'std
as a function of onvironmsntal parmnatars Ieo-RH.B/L Iso-Tamg.H/L Iso-Temp,W Standard Conditions Temperature ("C): 23 29 30 31 23 23 23 23 23 23 23 RII (XI: 50 50 50 50 70 80 90' 100' 50 50 50 **NIL** (mih): 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 1.5 2.0 2.5

PRODUCT PBU3 1 1.9 2.1 2.3 1.3 1.5 1.6 1.8 0.59 0.49 0.42 0.37 0.31 PPRZ 1 1.7 1.9 2.1 1.4 1.6 1.7 1.9 0.47 PPR3 1 1.9 2.1 2.3 1.7 2.0 2.4 2.8 0.57 0.47 0.60 All Pd 1 1.9 2.1 2.3 1.4 1.6 1.7 1.9 0.54 0.43 0.37 AllPANb 1 1.8 2.0 2.1 1.6 1.9 2.3 2.6 0.51 0.41 0.35 Allmu,PANb 1 1.8 2.0 2.2 1.5 1.8 2.1 2.3 0.52 0.42 0.35 HDF1 1 1.6 1.7 1.0 1.6 2.0 2.3 2.7 0.67 0.53 0.51 rnF2 1 1.9 2.1 2.h 1.5 1.7 1.8 2.1 0.67 0.55 0.51 AllmF 1 1.9 2.0 2.3 1.4 1.8 1.8 2.0 0.68 0.58 0.51
Standard Rporinuntal Seasonal Conditions TortCotrditionr Fluctuation

T__

PRODUCT PBU3 PPR2 PPR3 All PB#
All PBU.PAd3 All PANb

WF1 MlF2 AllMDF 23 50 0.5 23 23 28 33 26' 30 20' 28 40 75 50 50 50. 65 35' 75 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

0.81 1.4 1.7 2.6 2.1 2.6 0.71 1.s 1.6 2.4 2.0 2.4 0.71 1.8 1.7 2.8 2.8 3.1 0.80 1.5 1.7 2.7 2.1 2.6 0.71 1.6 1.7 2.5 2.6 2.8 0.75 1.7 1.7 2.6 2.6 2.7 0.50 2.4 0.36 2.3 0.kl 3.1 0.48 2.4 0.36 2.8 0.41 2.7 0.71 1.8 1.5 2.2 2.5 2.6 0.k3 2.6 0.77 1.5 1.7 2.9 2.3 2.9 0.47 2.7 0.76 1.5 1.7 2.7 2.2 2.7 0.44 2.5

Wodel extrapolated beyond tho range of rxporimontal trst conditions. bEnvironmental Paramators Study I and 11 data includod.Report XVIIT. 16 CPSC-IAG-84-1103

Table 7. Model I1Analysss. Cornparlaon ob CA20~,RB~CB201/~RZODRstd
for individualand combined te6tproduct. data sats an a function of mvirormnntal parameters
Im-RB,[cR201 Iso-Tmp.,[CB201 Standard Conditionn Exporimsntal TnstConditions Tomperatore (*C): RH (Z): ICAZ0l (piman):

PRODUCT PBU3 PPR2 PPR3 All PBUc A11US PBUC All PANC All PAN,PBUC MDF1 MDFZ AllMDF 23 50 0.1

1 1 1 1 1 1 1 1 1 1 27 28 50 50 0.1 0.1 29 23 50 70 0.1 0.1 23 23 23 23 23 28 33 26 30 80 goa looa 40 75 50 50 80 65 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

1.6 1.8 1.5 1.7 2.0 2.3 1.9 2.3 1.9 2.2 1.8 2.0 1.9 2.2 1.8 2.1 1.7 1.9 1.8 2.0 2.0 1.5 1.8 1.5 2.7 2.5 2.6 1.7 2.5 1.6 2.3 2.1 2.5 1.9 2.4 2.2 2.1 2.1 2.2 2.0 1.8 2.1 2.5 0.76 1.7 1.8 3.0 2.5 3.0 1.7 1.9 2.2 0.77 1.6 1.7 2.7 2.3 2.7 3.6 4.8 6.1 0.48 3.0 2.3 4.6 5.6 6.0 2.1 2.6 3.0 0.58 1.9 2.3 4.6 3.5 4.6 1.9 2.2 2.5 0.75 1.7 2.2 4.4 3.0 4.1 2.8 3.5 4.4 0.58 2.4 2.0 3.7 4.2 4.5 2.5 3.1 3.8 0.63 2.2 2.2 4.2 3.9 4.7 3.0 3.9 5.0 0.58 2.6 2.1 3.8 4.7 4.9 2.8 3.5 4.4 0.60 2.4 1.9 3.4 4.0 4.1 2.6 3.3 4.1 0.61 2.3 2.0 3.5 4.0 4.3

Standard Conditions Xso-Tomp, .88 Iso-Temp.,RR Seasonal Fluctuations

EKIDUCT PBU3 PPR2 PPR3
AllUS PBUc AllPAWc All PAN,PBUc KDEl MnF2 All. PBUC 23 23 23 23 23 28 20 28 20 28 208 28 50 50 SO 50 50 75 75 75 75 75 35 75 0.1 0.15 0.20 0.25 0.30 0.1 0.2 0.3 0.4 0.5 0.1 0.1

0.84 0.68 0.51 0.35 2.9 2.5 2.0 1.6 1.2 0.88 0.76 0.64 0.51 2.6 2.3 2.0 1.7 1.4 0.66 0.32 b b 6.5 5.0 3.5 2.1 0.6 0.79 0.57 0.38 0.14 4.2 3.5 2.7 1.Q 1.1 0.81 0.62 0.43 0.24 3.8 3.0 2.5 1.9 1.3 0.84 0.67 0.51 0.35 4.7 4.0 3.3 2.6 1.9 0.80 0.60 0.40 0.19 4.6 3.9 3.1 2.3 1.6 0.95 0.89 0.84 0.79 5.3 5.1 4.9 4.6 4.4 0.89 0.78 0.67 0.56 h.h 4.1 3.7 3.4 3.0 AllMDE **1** 0.94 0.87 0.81 0.75 4.5 4.3 4.1 3.9 3.8 

### - Wdels extrapolated boyond tha range of experimental test conditions. 0.42 0.46 0.12 0.29 0.35 0.24 0.26 0.24 0.27 0.26 2.9 2.6 6.5 4.2 3.6 4.7 4.6 5.3 4.4 4.5

bp'rojectsd CB OEX 5 0. 2 T,RII,O.lpp% cEoviromRnta1 Parameters Study I and I1 data included.Report

### XVIII 17 CPSC-IAG-84-1103

, 

### 1. For potential seasonal changes in temperature and RH from 20"C,35% RH to 28"C,

### 75%

### RH at a constant CH20 concentration 

### of 

### 0.1ppm,widely variable increases in modeled CW~QERT,RH,CV/CNZQERS~~ are predicted from the results of Study I and Study 11. For Study 

### I,the range 

### of modeled increase in CH2OER spans from sevenfold to unquantified values because several of the weaker emitting products have near zero or negative modeled CH20ERs at 20"C,35% RN and 

### 0.1ppm due to suppression effects. 

### For Study 

### XI, where generally stronger emitting products were studied, a smaller and overlaping range of 

### 7 to 54 fold increases inmodeled CH20ER is predicted.


### 2. Twofold increases in modeled CH~OERT,RH,CV/CH~OER~~~ are predicted with increases 

### of 3 to 

### 5 Celcius degrees in Study 

### I and 4 to 6 Celcius degrees in Study 11. For humidity, approximate increases of 

### 15 to >a50 additional percent RH are required for twofold increases in modeled CH20ER inboth studies. 

# *

3. Larger interproduct variation 

### in modeled CH~UERT,M,CV/CH~OERS~~ is predicted as a function of changes in RH and CH20 concentration than temperature inboth Study 

### I and Study 11.


### 4. The modeled suppression 

### of CH20ER with increases in CH20 concentration is typically 

### less variable for Study 

### I1 test products (see Table 

### 7) in comparison to Study 

### I products (see Table VIII, Reference 

### 1). For example, for Study 

### I products the range of modeled decrease in CH2OERT,RH,cv/CHZOERstd with a 0.1 to 

### 0.3 ppm increase in CH20 concentration (at 23"C, 50% RH) spans from twofold for PBU#2 to unquantified values for all other test products. In contrast, for Study I1 the range of modeled decrease in CH~OERT,RH,CV/CH~QERS~~ spans from 1.3 to 2 fold for 

### all products except PPR3. This is because the 

# * Certain test products whose CH20 emissions are insensitive to changes in RH would require a %50% increase 

### in.RH from 50% to >-loo% 

### RH to achieve a twofold modeled increase in CH~OER.T,RH,~/CH~~ERS~~ tie.,Model 11) at a constant temperature and Q. A -50% increase in RH from 50% 

### RH is not considered because it is a non-physicalsolution.Report XVIII 1.8 CPSC-IAG-84-1103
Study 11 products are typically stronger CH2Q emitters that have positive emission rates at 23"C, 50%

### RH and 

### 0.3ppm CM20.

A graphical presentation of the effects of variation 

### in temperature and RH is illustrated in Figures 

### 1 and 

### 2 for Models I and I1 analyses, respectively. These graphs are developed from the model coefficients for the Study 

### I and I1 combined particleboard and paneling models. The graphs illustrate the effect of variation in temperature at 

### RH levels of 

### 25, 50 and 

### 75%RH. Sensitivity Analysis forModel I,I1 Coefficients

An analysishas been performed to determine the impact of variation in model coefficients on the predicted C /C and CH2QER/CH2QERstd values of 

## vv Models I and 11. This analysis assumes thgtdcomplete independence of the coefficients in the models. 

### To calculate the sensitivity ofNodels 

### I and IT. (Sens) to variation in each model coefficient,the derivative of the model with respect to a given coefficient (e.g.,

### X) is normalized to the absolute value of the model and the coefficient. d Hodel 

### dx Sens 16 =

### X

# - (Model)

# -'

The resultant sensitivity value is the fractional change in the model per unit change in the coefficient. 

### For example,a sensitivity of 

### 0.1means that a 

### 10% change in the model is expectedwith a 100% change in the coefficient. The sensitivity analysis depends on both the values of the model coefficients determined for a given pressed-woodproduct data set and the environmental conditions that are substituted into the model. Therefore, the sensitivity analysishas been performed for model coefficients determined from combinedparticleboard,paneling and 

### KDF data sets at several different environmental conditions (see Table 8). The ALL 

### PBU and ALL 

### PAN data sets represent both Environmental Parameters Studies I and I1 results. The results of the sensitivity analysis indicate several points.ReportXVIII 

# \

**M** ln

u u VI 4 4 a U 

## 9



# .. 4 W k 1 M 4 E4 CPSC-IAG-84-1103

**e4** 4Report XVIII 20 CPSC-ZAG-84-1103Report XVIII 21 CPSC-IAG-84-1103

Tabla 8. Sensitivityhnalysis ofHadrl 1 ond I1 Coefifcieats

I I I I I I I1 I1 If I1 11 I1 11

I I I I I I
I1 11 I1 11 I1 IS I1 23 28 23 23 20 28
23 28 23 23 20 28 28

23 28 23 23 20 28
23 28 23 23 20 28 28 50 50 75 50 35 75
50 50 75 50 35 75 75

50 50 75 50 35 75
50 I 50 75 50 35 75 75 0.5 0.5 0.5 1.0 0.5 0.5



# -
- - 

# - -

0.5 0.5 0.5 1.0 0.5 0.5



## - 

# - - - - 

# - - 

## -
-
0.1 0.1 0.1 0.2 0.1 0.1 0.9



# - - -

0.1 0.1 0.1 0.2 0.1 0.1 0.3 Tabla 8-A: **ALL** PBUData Sat 1.00 0.00 0.00 0.00 0.00 1.70 0.38 0.09 0.00 0.00 1.47 0.00 0.00 0.26 0.10 0.70 0.00 0.00 0.00 0.00 0.48 -0.26 -0.17 -0.24 -0.17 2.45 0.38 0.07 Q.25 0.07 

# - - 

# - - 

# - 1.00 0.00 0.00 0.00 0.00 2.27 0.§7 0.13 0.00 0.00 1.92 0.00 0.00 0.20 0.36 0.57 0.00 0.00 0.00 0.00 0.29 -0.62 -0.12 -0.25 -0.57 4.24 0.S5 0.13 0.16 0.33 2.68 0.88 0.12 0.25 0.31 

# - -

- 

# -
Table 8-8: **AIJ.**PAN Drta Set
1.00 0.00 0.00 0.00 0.00 1.66 0.20 0.13 0.00 0.00 1.78 0.00 0.00 0.40 0.13 0.68 0.00 0.00 0.00 0.00 0.36 

# - -0.20 -0.40 -0.36 -0.33 2.82 0.29 0.10 0.38 0.09 

## -
- 

# - 1.00 0.00 0.00 0.00 0.00 2.00 0.61 0.18 0.00 0.00
0.67 0.00 0.00 0.00 0.00 0.24 -0.38 -0.20 -0.40 -0.84 2.44 0.00 0.00 0.33 0.42



## - 4.74 0.30 0.18 0.29 0.39 

## - 3.31 0.5K 0.19 0.41 0.38 0.00 -0.07 -0.08 0.17 0.13 -0.13



## -

-


## -
-

0.00 -0*11 -0.10 0.17 0.21 -0.20



### - 

## -
-

0.00 0.17 0.08 1.07 0.40 -0.20 0.51



## -

0.00 -0.10 -0.09 0.65 0.29 -0.15 0.35Report XVIXI 22 CPSC-IAG-84-1103

Table 8. SanaitivityAnalysis of Ekrdel I and 11 Coafficienta (continued)

I 23 50 I 2a 50 I 23 15 I 23 50 I 20 3s I 28 75
I1 23 50 I1 28 50 I1 23 75 11 23 50 IT 20 35 rz 28 75 I1 28 75 0.5 0.5 0.5 1.0 0.s 0.5
0.1 0.1 0.1 0.2 0.1 0.1 0.3 Table 6-C: AIJ. UQF Data Set
1.00 0.00 1.67 0.45 1.51 0.00 0.81 0.00 0.44 -0.32 2.51 0.45 

## - -

- 0.00 1.00 1.98 0.29 2.30 0.00 

## - 0.87 0.00 0.28 -0.24 4.69 0.28 4.13 0.30 

### - 0.00 0.02 0.00 0.00 -0.04 0.01
0.00 0.30 0.00 0.00 -0.39 0.30 0.30 0.00 0.00 0.30 0.00 -0.28 0.28
0.00 0.00 0.81 0.00 -0.94

0.76 0.83 0.00 0.00 0.07 0:oo -0.42 0.06
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -0.02 -0.09 0.15 0.17 -0.10
0.00 -0.03 -0.07 0.16 0.22 -0.08 0.01Report 

### XVIII 23 CPSC-IAG-84-1103



### 1. For Model 

### I,the modeled C values are most sensitive to changes in coefficients C and A represen ing the temperature and RH dependence of C 

# .

Bs td This was observed for all three combined product data sets.


### 2. For Model 11, the results of the sensitivity analysis are highly product-dependent. The particleboard and paneling models are most



# . The sensitive to changes in coefficients C, E, and particularly is presumably based on the ma%$matical 

### B sensitivity to changes in C form of the denominator of ModEf'II (i.e.,C 

### -0.1). 

### In contrast, the 

### MDF model is relatively insensitive to ctanges in C, 

### , presumably cB

Bst std u because of the large value 

### of the modeled 

### C (i.e.,0.90 ppm). Bstd 3. In general,Model 

### 11 ismore sensitive thanModel 

### I to changes in model coefficients. For potential seasonal fluctuations 

### in environmental conditions from 20"C, 35%RH to 28"C, 

### 75%RH, the sensitivity numbers for Model 

### I coefficients range from **0.00** to 0.45. For the same environmental conditions 

### , the sensitivity numbers for Model I1 coefficients range from 0.00 to 0.94. Uncertainty Analysis 

### for Model 

### I and Model 

### IT

An analysis has been performed to estimate the uncertainty in modeled CV/CVstd and CH20ER/CH20ERstd values calculated from Model 

### I and Model 13: analyses,respectively,atvarious environmental conditions. The uncertainty analysis is performed for two quantities: the uncertainty in the modeled mean (%.-e.? populatlon) value 

### for a large number 

### of future observations under identical environmental conditions and the uncertainty in the modeled value for a single future observation, These statistics could he used, for example, to estimate the standard 

### error in the Model 

### 1prediction of the mean CH2O concentration inside a large population of uniformly produced compartments containing a single type of pressed-woodproducts under uniform environmental and air exchange conditions. The standard error in the modeled mean value would be the contribution 

### of the model to the uncertainty in the prediction of the mean 

### CH2O concentration inside the compartment. The standard error in an individualmodel prediction would be the model contribution to the uncertainty (i.e.,spread) of the distribution of CW20 concentrations predicted inside theReport

### XVIII 24 CPSC-TAG-84-1103
compartments. 

### A detailed mathematical presentation of this uncertainty analysis is given inAppendix 

### I.
A second order Taylor Series approximation of the variance in the dependent variable of Hodel 

### I andModel I1 is used to estimate the standard error inpredicted mean (t.e.,population) values for eachModel undervarious environmental conditions (seeAppendix 

### I). This analysis takes into account the combined uncertaintyof all model coefficients and the affect of any first order dependence between individual coefficients. This uncertaintyanalysis is therefore contrasted with the sensitivity analysis in the previous section where the iincertainty in CV/CVstd and CH20ER/CH2QERstd were calculatedas a result of variation in individualmodel coefficients that were assumed to be independent, The uncertainty analysis assumes that- (1) themathematical forms of Models 1 and I1 are correct and that pressed-wood data set under consideration (e.g., ALLPBU data set for Model 

### I) represent the environmetrtal dependance of the CH20 emission strengehof a futurepopulation of boards to be considered. Thus,the analysis does not account for interboardvariation in the environmental dependence of the CH20 emission strength,either between boards tested in OWL studies or other boards manufactured and used elsewhere.
The standard error inmodel predictions of individual observations is estimated from a combinationof 

### (1) the estimated variance in themodeled mean value as calculated with the Taylor Series approximation, and (2) the mean square error (mse) for the pressed-wood data set under consideration (see Appendix 

### I). The mse is the best estimate of the random variation in the dependent variable of Models 

### I and 

### TI about the truemean predicted value in future observations.
The results of the uncertainty analyses for the

### ALLPBU,ATALPANand ALIMDF data sets are given in Tables 

### 9 and 10 for Model 

### I and Model 11 treatments, respective1.y. For each Model (e.g.,ALLPBU for Model 

### I) the numerical value of the dependent variable (e.g.,Cv/Cv,,d for Model 

### I) the rootmean square error,and the standard error for the modeled mean value and modeled individual. values of future observations are given for environmental conditions spanning from 20°C, 35%

### M to 35"C, 75% RH. The coefficient of variation for the modeled mean and individualvalues of future observationsReport 

### XVIII 25 

### CPSC-IAG-84-1103



## -- Table 

### 9. Uncertainty analysis 

### for ALLPBU, ALLPAN and ALLMDF Model 

### I Analyses.
Standard Errar Caef. of Var. (8) Temp 

### RH 

### WL rmSe CV/CVstd Mean Single Mean Single ("C) 

### (%I (mm Qbs. Obs. Qbs

# . Qbs

## .

20 35 0.5 0.28 23 50 0.5 0.28 **28** 75 0.5 **0.28** 35 75 0.5 0.28 28 75 1.0 0.28 35 75 1.0 0.28
20 35 0.5 0.66 23 50 0.5 0.66 28 75 0.5 0.66 35 75 0.5 0.66 28 75 1.0 0.66 35 75 1.0 0.66
20 35 0.5 0.14 23 50 0.5 0.14 28 75 0.5 0.14 35 75 0.5 0.14 28 75 1.0 0.14 35 75 1.0 0.14 A. ALLPBU Data Model I 0.48 0.02 

### 0.28 1.00 **0.00** 0.28 

### 2.45 0.03 

### 0.28 **4.60** 0.04 **0.28** 1.90 0.04 0.28 3.74 0.04 0.28 

### B.ALLPAN Data Model 

### I

0.36 0.06 0.66 

### 1.00 0.00 0.66 2.81 0.07 0.66 4.70 0.10 0.66 2.22 0.08 0.66 3.94 0.11 0.67 C. ALLMDF Data Model I

0.44 0.90 0.17 1.00 0.00 **0.14** 2.50 0.24 0.27 4.92 0.98 

### 0.23 2.21 0.16 

### 0.21 4.41 0.13 0.19 4 58 0 28 1 11 1 6 2 15 1 7
17 183

0 66 2 **23** 2 14 

### 4 30 3 17
23 39

0 14 10 11

5 5 7 10 3 

### 4ReportXVlII 26 CPSC-IAG-84-1103

Table 10.Uncertainty analysis 

### forALLPBU, ALLPM and ALLMDF Model 

### ITAnalyses.

20 23 28 35 28 35
20 23 28 35 28 35
20 23 28 35 28 35 35 50 75 75 75 75
35 50 75 75 75 75
35 

## so 75 75 75 

### 75 0.10 0.10 

### 0.10 0.10 0.25 0.25


### 0.10 

### 0.18 0.10 0.10 0.25 0.25
0.10 0.10 0.10 0.19 0.25 0.25 1.91 1.91 1.91. 1.91 1.91 1.91
0.71 0.71 

### 0.71 0.71 0.71 0.71
0.60 0.60 

### 0.60 0.60 0.60 0.60 A. ALLPRlJ Data Model 0.29 0.05 1.00 0.00 4.26 0.31 10.99 0.43

3.07 0.22 9.59 0.34 B. ALLPAN Data Model 0.24 0.02 

### 1.00 0.00 4.74 

### 0.14 10.58 0.34

3.67 0.09 9.19 0.28 C. ALTXDF DaCa Model 0.26 0.05 

### 1.00 0.00 4.49 0.12 9.55 0.48 4.22 0.10 9.16 0.45 I1 1..91 1.91 1.94 1.96 1.93 1.94 I1 0.71 0.71 0.72 0.79 0.72 0.76 'I 0.60 

### 0.60 0.61 0.77 0.61 0.75 

### 1 'I 

### 0 7 4 7 4


## a 0 3 3 

### 2 3
19

0 3 5 2 5 660 191

46 18 63 20
296



### 71 15



### 7 20

8
231.

60 

### 14

8 1

4 8Report

### XVIII 27 CPSC-IAG-84-1103

are also given in Tables 9 and 

### 10 to facilitate direct comparisons between the uncertainty inModels 

### I and 11. The coefficient of variation is corrected for the absolute value of the model.
There are several similaritiesbetween the results of the Model 1 and Model I1 uncertainty analyses. First, the root mean square error is constant for each model (e.g.,ALLPBU for Model 

### I). This is because the nonlinear regression analyses used to determine the model coefficients were unweighted with regards to the numerical value of the model. Second,the standard error for the modeled mean Observation is much smaller than formodeled single observations. This is expected because the modeled mean observation is a result predicted from a large number 

### of individual observations and does not incorporate the randomness observed in individual observations. The coefficient of variation in the modeled mean values are typically less than 10%. A third similarity in the results of the Model 

### I and 

### I1 treatments is that the root mean square error is approximately equal to the standard error for individual observations. 

### This indicates that the uncertainty in the modeled mean observation is typically small in comparison to the randomness

(i.e+, breadth of the distribution) ofmodeled individual observations.

It is instructive to compare the coefficients 

### of variation for future single and mean observationsbetween the results of the Model 

### I and Model I1 uncertainty analyses. This comparison can only be directly made for the ALLPBU and ALLMDF Models where the pressed-wood product data sets are identicalbetween the Model 

### I and 

### IT analyses. For the ALLPBU Model, the coefficient 

### of varfaeion for single and mean observations in the Model 11 analyses are consistently a factor of 3 to 18 larger that the analogous coefficient 

### of variations in the Model 

### I analyses. 

### In contrast, the coefficients of variation in the single and mean observations for the ALLMDF Models are comparablebetween the Model 

### I and Model I1 analyses. This may be caused inpart by the mathematical form ofModel I1 and the selected standard test conditions of 23"C, 50% RH and 

### 0.1ppm. The resulting denominator of 

# * For the ALLPAN Models, certain data sets for weak emitting paneling products from Environmental Parameters Study 

### I could not be included in Model 

### 11 type analyses because the CH2QERs were 

### < zero at standard conditions of 23"C, 50% 

### RH and 

### 0.1ppm CHZO. 

# *Report

### XVIII 3% CPSC

## -IAG

### -84 

### -1103

Model 

### PI (i.e., Qstd 

### - 0.1) is unstable for weak emitting products whose Qstd values approach 0.1ppiii. This may cause increased uncertainty in Mode3 

### YT predictions of future olsservar.i..onskl'riere **the** Model. coefficients are developed from pressed-waod data sets of weak eiiiittlngboards. Consistrent with thishypothesis, the ALLPBU I':odel (which has the largest cmcertai.nties for Model I1 predictions) is developed from fourhoards with Qstd values of 0.14, 0.46, 0.24, and 0.41ppm. In contrast, the :model.edCBstd values for the two boards inthe ALLEIDF data setare !..05 and 0.56 ppm. A potential solution to the mathematical. singulari.tyin the denoiiiiriatror of Model 

### II would be to iio~ii~alize the Model. IT data sets **to** standard conditions **O€** 23"C, SO%RII and 0 ppm. Although the CH20ER at standard conditions could only**be** extrapolated from avai.Lable experimental data, the ilsw mathematical fomof the denoininator of Model I1 (i.e., C~~td) would then be more stable for a wider range of product: emission strengths.

SINKS STUDY
The CH 0 sinks study for gypsum-wallboard is complete. Several types of experimental sti.dbr?s have been performed 1.0 inves'l.i.gatr: r:he time dependent CH 0 sorption and desorption characteristics of gyps-mboard. The resul.ts of two 3 to 4 week long sorption studies were presented inReports XVI and

### XVII. Gypsum board coi~dit:i.on.;..dat

### <lo ppb CH c) was exposed to CH 0 from a generation apparatus at 100 and 400 ppb in separate experiments. Preliminary modeling indicated exponen(:ial risetiine values of 2.2 l:o 6.4 days an.d steady state CH 0 concent~rati.ons of91to 98%of the generated CH 0 I-evels. 

### 2
2
2 2
2 2
AddiGjonal 1

### co 2 day sorption studies have been pecforrned on gypsurn board to study the initial time-dependent behavior of gypsum board exposed to sudden increases in CI-E 0 vapor concentration. 1II these expprirneiits

~ gypsum board conditioned at 100 ppb CH 0 wzs exposed to 200 ppb CH2C from the generati.on apparatus

~ The temperature, ELF1 arid air exchanp?/loading ratio were maintained at 23"C, 50%

### RH and 0.43m/h, respecti-vcly, duringboth the 100ppb conditioning atid 200 exposur- periods. 2 2Report 

### XVIII 29 

### CPSC-IAG-84-1103

The results of the short duration sorption studies can be characterized by two separate phenomena. Within the first 

### 2hours following the change from 100 to 200 ppb from the CH20 generation apparatus, the 

### CH 0 concentration inside the gypsum board exposure chamber rose rapidly to about 120ppb. Two hours is the approximate time required to completely exchange the atmosphere inside chamber assuming perfect mixing and an air exchange rate of about 

### 1.5 h-l. From this time through the duration of the experiment, the CHZO concentration in the gypsum board exposure chamber rose very 

### slowly, consistent with the 

### 2 to 4 day risetimes observed in the previous long term sorption experiments. It is instructive to nate that an Initial rapid rise in 

### CH 0concentration was also observed in the first set of data taken 

### 2 to 

### 5 hours after the start of the long term sorption experiments. However, the short duration sorption experiments were needed to quantiEy this phenomena. 2

the

2

Tomodel the time-dependent sorption behavior of the gypsum board observed in both the 

### 1 to 

### 2 day and 3 to 4 week sorption experiments,the following expression is considered.



### R

# - Z 

### + (A

# - 2) ) -time/7 

### (1

## - e (5)

where:


### Z = the modeled value 

### of 

### R achieved during the first 

### 2 hours of the experiment,
A

# - the modeled steady state (i.e., maximum) value of R achieved at time infinity

### , and

7

# - the modeled exponential risetime of the sorptionprocess.

The expression 

### for 

### R is the ratio of the change in CH2O concentration inside the gypsum-board-exposure ([CH20]gyp) and reference ([CH20]ref)Report XV:C'T.I. 30 CPSC-TAG-84-1103

chambers. 

### This ratio of delta concentrations is normalized for differences in the potential span of CM20 concentrations in each chamber during the experiment. The normalization factorprovides an

### R value of unity in the ahscence of CH20 sinks in both the reference and gypsPLr71-boara-exposure chambers. R is calculated as

where:

= the final CH20 concentration in the abscence 

### of CM20 sinks

[CH201fina1 (e.g.,0.4ppm in the 

### 0to 0.4ppm sorption series), and

**0 0** [ 

## 1gyp ? [

# CHp 1ref = the measured CH20 concentrations in the gypsumboard-exposure and reference chambers at the start of the experiment.

The experimsntal data and the resulting fit to Equation 

### 5 are illustrated in Figure 3. The model coefficients determined from a SAS non-linear regressionanalysis are


### z = 0.15

### +- 0.01,

A = 0.94 k 0.01,and

7 3 3,1. -C 0.1 days
The root mean square error for the regression analysis is 0.065.

Two types of CH 0desorption studies have been performed. During **a** week-long study, the CH 0concentrationof the supply air to the gypsum board chamberwas dropped to and maintained at zero 1evel.s. 

### In duplicate one-day 2 2CPSC-IAG-84-1103

m u m **L3** c **0** -4 **c, a**  LI **0** m 111 x c -4 m w **0**

n al 

# k? **orl**

n m

w I

N I 4 v 

## + NReport XVII:I 

### 32 CPSC-IAG-84-1103
studies,the CH 0 concentrationin the supply air was dropped from 

### 100 ppb to 50 ppb

## . In 

### all experiments,the temperature,Rlll, and air exchange/loading ratios werc maintained at 23"C, 50% Hi, and 0.113 m/h, respectively. 2

The results of both experimental designs can be characterized by two phenomena analogous to those observed in the sorption experiments. Within the first 2 hours the concentrationinside the gypsyum board exposure chamber dropped about 

### 20% of the total change in CH 0concentrationinthe supply air from the generation apparatus. Froin 1:his period though the duration of the experimentthe CH 0 concentrat-iondroppedvery slowly,consistent with a decay period of several days. 2
2

To model the time-dependent desorption be!-t;ivior of the gypsum board observed in both the 

### 1 week a~d 1 day desorpt;on studies,the followjng expression is considered.

I -cime/q R = 

### (1 -

### z9e

where:

7 = 

### the model.ed exponential decay period of the desorption process The expression for 

### R' is analogous to that for

### R and is calculated as I.he quantity 

### 1 - 

### R. In conl;rast to the expressionfor 

### K,the ratio of delta CH20 concentrationsin the gypsum-board-exposure and reference chambers expressed in R' is normalized to provide an 

### R' of zero in the abscence of sinks in both chambers,Report

### XVIII 33 CPSC-IAG-84-1103

The experimental data and the resulting fit to Equation 

### 7 are illustrated in Figure 4. The model coefficients determined from a SAS non-linear regression analysis are
2 = 0.21

### f 0.01,and

7

# - 2.6 k 0.3 days.
The rootmean square error for the regression analysis is 0.04. Further nonlinear regression analyses of the 

### CH 0sorption and desorption data sets for gypsum board have been performed tor compare the temporal 2 dependence.of the 

### CH 0sorption and desorption processes. The goal was to evaluate the consistencybetween the nonlinear sorption and desorptionmodel coefficients. To accomplish this, non-linear regression analyses of the sorption desorption data sets have bee2performed using the sorption and desorption models with a single set of model coefficients A modified form of the desorption model was required to include both the A and 

### Z coefficients incorporated in the sorptionmodel. 2

and 

# *

-time/r R = (A

# - Z).e
Themodel coefficients determined from the non-linearregression analysis are Z

# - 0.15 k 0.01, A

# - 0.92 

### f 0.01,and 7 = 

### 2.9 _+ 

### 0.1days. The r value of 2.9 days is the approximate average of the 

### 3.1 and 2.6 day values of 7 for the individual sorption and desorptionmodels, respectively. These results indicate that gypsumboard canbe a potentially strong buffer against fluctuations in indoor CH **0** concentrations. The A value 

### of 0.92 may indicate a small (i.e.,

### 5-10s)permanent CH **0** loss mechanism for gypsum board. The root mean square error for the regression analysis is 0.06. 2 2 

## * This option is available in the SAS Institute non-linear regression analysis procedureReport WIII

m x c .rl VI %I 0

.-I aJ a 0 

### z 34

e ;cI / 

## / CPSC-IAG-84-1103

I- I I 

# i I 10 +¶Report

### XVIII 35 CPSC-PAG-84-1103



### SLOW DECAY STUDY The experimental investigation

### of the decline in 

### CH20 concentration in the slow decay study lasted 

### 14 months through March, 

### 1985. The final FSEM measurements 

### of the individual boards could not be performed due to resource restrictions. The raw CH 

### 0concentration data and a summary of environmental parameters are listed in Table 

### 11. Assuming no variation in environmental conditions, the raw CH 0concentration data canbe fit to a single exponential decay function. 2
2

-time/r ==A.t? [CH20

### 1vapor (9)

The calculated decay period r is 

### 2.25 0.2 years.


### To assess the impact 

### of variation in temperature, RH and air exchange/loading ratio on the calculated 

### CH 0 emission decay period, a correctionmodel for the CH 0concentration data is developed based onModel 

### I from the environmental parameters studies. However, additional assumptions for Model 

### Imust be considered 2 2



### 1.

2. Variation in 

### (N/L)std from 0.5

### m/h, used in the environmental parameters studies, to 

### 0.15m/h, used in the 

### slow decay study has aminimal impact on the Model 

### I coefficients.
Model 

### I coefficients determined from a combination 

### of individual particleboard, paneling and medium density fiberboard data sets canbe applied to an environmental chamber experiment with mixed pressed-wood products.



### To refine Model 

### I to better predict the impact of small changes in temperature and

### RH about standard conditions, a subset of available data taken in Envlronmental Parameters Studies 

### I and I1 is selected 

### for nonlinear regression analysis. 

### All particleboard underlayment, hardwood plywoodReport 

### XVIII 36 CPSC-ZAG-84-1103

1 

### 2 3 

### 4 5 

### 6 

### 7 8 

### 9 10 

### 11 12 13 14 1.5 

### 16 17 18 19 20 21 22 23 

### 24 25 26 

### 27 28 29 30 

### 31 32 33 

### 34 35 36 

### 37 38 39 

### 40 41 42 43 44 45 

### 46 0.00 0.07 

### 0.50 0.53 0.93 1.17 1.23 1.30 1.40 1.63 1.73 1.80 1.97 2.07 2.20 2.43 2.50 2.60 2.80 2.97 3.00 3.15 3.30 3.43 3.50 3.70 

### 3.83 3.87 4.10 4.17 4.33 

### 4.40 4.53 4.60 

### 4.67 4.77 4.90 5.82 5.99 

### 6.05 6.22 6.28 6.45 6.55 5.81 

### 6.91 23.0 23.0 23.0 

### 22,6 

### 22

~6 22.9 

### 23.0 

### 22.6 22.7 23.5 23.0 23.0 

### 22.7 22.6 

### 23.0 

### 22.6 22.7 

### 22.6 23.0 22.6 

### 23.1 23.0 23.0 

### 23.O 

### 23.0 22.4 

### 22.4 23.0 

### 23,O 23.0 23.0 23.0 23.0 23.0 23.0 

### 22.5 23.4 23.0 23.0 23.0 23.0 23.0 23.2 23.8 

### 23.0 23.0 57.0 57.0 

### 47

## .o 47.0 45.0 47.5 48.0 47.5 49.5 50.0 51.5 

### 50.0 50.5 49.5 

### 50.0 

### 47.O 

### 51..

### 5 50.1 50.0 48.9 

### 50.1 50.0 50.5 49.0 49.0 49.5 

### 51.2 49.5 50.1 

### 48.5 50.0 50.0 50.0 50.0 50.0 51.0 51.0 50.0 50.0 50.0 52.0 51.0 49.O 

### 51.5 49.5 49.O 

### 0.40 0.40 0.40 

### 0.40 0.45 0.45 0.45 0.45 0.45 0.40 0.40 0.40 0.40 

### 0.40 0.40 

### 0.40 0.40 0.42 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.42 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.40 0.37 0.37 0.37 

### 0.37 0.37 0.37 0.37 0.39 0.39 

### 0.523 0.513 0.409 0.407 0.382 0.431 0.382 0.437 0.453 0.399 0.417 0.393 0.411. 0.395 0.389 

### 0.366 0.438 0.401 0.391 0.387 0.398 0.390 0.390 0.371 0.372 0.355 0.343 0.353 

### 0.371 0.343 0.363 

### 0.356 0.362 0.349 0.352 0.343 0.355 

### 0.360 0.391 0.395 0.357 0.395 0.345 0.390 0.343 0.335 

### O.lr-57 0.448 0.434 0.448 0.451 0.468 0.406 0.488 0.480 0.380 0.403 0.392 

### 0.417 0.413 

### 0.388 0.403 0.435 0.418 0.390 0.409 0.392 0.389 0.385 0.377 0.378 0.382 0.353 0,355 0.369 0.352 0.362 0.355 0.361 0.348 0.351 0.351 0.335 0.354 0.384 0.388 0.337 0.381 0.340 0.348 0,344 0.339Report 

### XVIII **37**

Table **11. Slow**  decay study data file (cont.) **CPSG-IAG-84-1103**

**47 48**  **49 50**  **51 52**  **53 54**  **55 56**  **57 58**  **59 60**  **61 62**  

### 63 **64 65**  **7.05 7.14**  **7.61 7.74**  **7.87 7.94**  **8.10 8.40**  

### 8.57 **9.03 9.56**  

### 9.82 

### 9.92 **10.30 10.70**  **12.50 13.0**  **13.9 14.4**  

### 23

### .O **22.5 23.0**  

### 22.7 **22.8 23.0**  **22.8 23** 

### .O **23.5** 

### 22.5 **23.0 23.0**  

### 22.5 **22.9 23.0**  **23.0 22.9**  **23.0 22.0**  **49.0 49.7**  **50.0 50.0**  **47**

### .O **50.0 50.0**  **50.0 48.0**  **48**.O **48.0 50.0**  **48.0 49.8**  **50.0 50.0**  **46**.O **47**.O **48.0 0.39**  **0.39 0.40**  **0.40 0.40**  **0.40 0.40**  **0.40 0.40**  **0.4C 0.40**  **0.40 0.40**  **0.40 0.40**  **0.40 0.40**  **0.40 0.4~1**  **0.304 0.326**  **0.354 0.323**  **0.309 0.242**  **0.301 0.272**  **0.337 0.348**  **0,296 0.289**  **0.286 0.331**  **0.351 0.283**  **0.239 0.259**  **0.270 0.308**  **0.313 0.344**  **0.331 0.334**  **0.242 0,306**  **0.335 0,272**  **0.379 0.308**  **0.288 0.312**  **0.335** 0.351 **0.283 0.262**  0
I**275 0.309**  Formaldehyde concentration data corrected to standard conditions (i.e., **23"C, a**  **50%** RH, **0.15**m/h) using Equation 

### 2.Report 

### XVIII 38 CPSC

## -IAG

## -84

### -1103
paneling and medium density fiberboarddata taken at 23-28°C and 40-808RH are included. These environmental conditions bracket the range of conditions encountered with the slow decay study. The resultingmodel coefficients are


## c => 5290,

A

# - 0.927,

= 0.656, std Kg B = 0.163,and


### E

# - 0.017.

The 

### CH 0concentration data corrected to 23”C, 50%

### M, and 0.15

### m/h are listed in Table **11.** Fitting this data to Equation 9, the calculated decay period is 2.3

### i 0.2years. Based on approximately **14** months of data, the impact of the small experimental variation in temperature,RH, and 

### N/L during the slow decay study appears to be small. 2

Care shouldbe used in the interpretation of the resul-ts of the slow decay study. The **14** month duration of the study may be i-nadequateto accurately measure the 

### CH **0** emission decay period of this collection of boards. The data may reflect a relatively rapid decay 

### of CM 0 emissions from a few of the strongest emitting boards as opposed to the entire.collection of products. 2 2

FAST DECAY STUDY
The “fast”decay study has been completed with data taken through December 1984. This includes seven measurement series of medi.m density fiberboard, particleboard underlapent, industrial particleboard, print paneling, paper (overlayed)paneling, and domestic paneling samples acquired during the pressed-woodproduet survey. During each measurement series, CH20Report 

### XVIII **39** CPSC-IAG-84-1103
emission rate measurements were performed 

### on three identical sites on a specific side **of** each 

### 4x 

### 4 footboard. Paneling samples were measured on bath the decorative face and back sides. The experimental data spans an 

### 16 month decay period starting approximately 

### 6-12months after board manufacture,
A summary 

### of the environmental conditions inside the storage room at the time of the 

### FSEM measurements is given in Table 

### 12. Temperature control is quite uniform throughout the study. Relative humidity values tend to follow seasonal fluctuations, particularly for the first seven test cycles. The lowest

### RH levels occur during winter months of 1983-84while the highest W levels occur during late spring and summer,1984. After the firstmeasurement series,the CH 0vapor concentration was maintained at low levelsbetween 0.04 and 

### 0.11ppm. 2

Due to the sub-50%

### RH levels for measurement series 3 to 5 and greater than 50%KH levels for measurement series 6 to 8, the measured decay periods may be lengthened in comparison to what would have been determined from these test products under constant temperature and RH conditions (i.e.,23"C,50% RH). As a result,a correction model for the temperature and RH dependence of the measured CH20 emission rates from the fast decay study boards is considered

# . Temperature,

### RH Correction Model Several simplifying assumptions are considered 

### for Model I1 (l.e., Equation 3), the 

### CH 0 emission rate model that was developed in the environmental parameters studies. 2



### 1. The environmentalparameters studies data and modeling canbe applied to 

### FSEMmeasurements.
**2.** For small variation in temperature and KH about **23°C** and **50%** 

### RH, F and F (RH) are approximately equal to unity. KgReportXVIXI **40**

Tabla 12. Envlrarrmantal conditions inaid. the stors80 soom for the fast decay studyboards at the tiw02 FSEMmeaausemasts CPSC-TAG-84-1103

MeaaurPment Series 1 2 3 4 5 6 

### - 

### _-- ._- Temp ('C) 23 + 1 23 f 1 22.5 + 0.9 23.0 + 0.7 22.5 + 0,4 22.8+ 0.6
RB (7.1 50+ 10 50 + 10 43+ 10 45+ 7 48 + 4 52+ 3 [CB201 (PPI 0.22+ 0.04 0.0s + 0.02 0.09+ 0.02 0.07+ 0.02 0.05 + 0.02 0.07+ 0.02
1.1 3.0 4.5 6.4 8.0 9.6

Date 8/83 10183 11/83 1/84 3/64 4/84

I 7 6 S Tamp ('C) 23.2 f 0.4 22.7 t 0.5 23.0

### * 0.4
RE (X) 56 f 4 46 **f** 1 52 t 2 [CH20J (PPI 0.11 f 0.03 0.09 **f** 0.06 0.06 f 0.01 Elapse Time 12.5 (montha) 14.9 17.3

Data 7/84 10164 12/84Report 

### XVIIf
Equation 

### 2 then becomes 

### 49



### CH OERstd 2



### To refine this model to better predict the impact 

### of small changes in temperature and RH about standard conditions, a subset of available data taken 

### in Environmental Parameters Studies 

### I and I1 is selected for non-linear regression analysis. 

### All particleboard underlayment, hardwood plywood paneling and medium density fiberboarddata taken at 23-28°C and 40-80%RH are included. These environmental conditions bracket the range of conditions for the fast decay study. The resultingmodel coefficients are:


### c

# - 10500,

A = 1.43, and 

# - 0.461ppm. std cB

To further simplify Equation 

### 10,one additional assmption is considered.
3. 

### A low

### CH **0**vapor concentration (i.e.,C 

### << CB ) is maintained during std 2 V
the monitoring period due to the design of the 

### FSEM.Report 

### XVIII
Therefore, 

### 42 CPSC-IAG-84-1103

CH20E%, RH 

### CH OERstd 2 

### 11 A -C(T 

## - -)*(RH/50) .CBstd 296 **P** I 'v -, 

## e -0.1 - Bstd Collecting constants and rearranging, the fi.nalexpression for the 

### CH 0emission rate correctionmodel is: 

### 2

CH OERT RH **h)** 

### 2 , 

### .1 1 = -10500(, 

# - ;-;) CH20ER23 C

### , 50%RH
e 1-28

Formaldehyde EmieonRate Decay Modeling

A single-exponential, CH OER decay model with a zero steady-state CH20ER 2 is considered for the fast decay study data, CH~QER 

# - CH~OERO.~ 

## -t**ime/r**

where CH20ERo equals the modeled CH20ER at the beginning 

### of the study. Multiple exponential decay models and positive steady-stateCH OERs were considered but could notbe properly evaluated due to resource restrictions. 2

The experimental. CH20ER data plus the 

### CH OER data corrected for temperature and RH (using Equation 12) were fit to Equation 13usingnonlinear regression analyses. The normal regression assumption of equal absolute errors in all measured CH 

### OERs was modified to assume equal errors in proportion to the measured CH 

### OERs (i.e.,equal coefficients of variation). This procedure tends to deweight the initialmeasurement serieswhere Lhe CH OEKs and thus the absolute magnitude of the measurement errors are largest. This weighting procedure is accomplished by weighting the sums of squares of 2

2 2
2Report 

### XVIII 43 CPSC-IAG-84-1103

residuals in the regressionanalysisby the magnitude of the inverse of the Model (i.e.,Equation 

### 13). ‘2’ The resulting r values obtained from for all 

### of the decay study boards are listed in Table 

### 13 and summarized

### by product category in Table 

### 14. The temperature and RH corrected decay periods are typically 0 to 3 months shorter than those calculated from the uncorrected data. 

### The corrected z values range 

### from about 8 to 25 months for all test products. The average corrected r values rank from 10.72 2.1months for paneling to 

### 13.2 13.0months for particleboard to 18.8 2 4.4 months for medium density fiberboard, These 7 values correlate generically with the order 

### of increasing product emission strength and increasing product thickness. fast

Front/Back Emission Ratios for Paneling
A secondary objective 

### of the fast decay studywas to examine front to back 

### CH 0emission ratios of the hardwood plywood paneling samples as measured by the FSEM. This information could impact environmental chamber test designs for paneling and the modeling of the impact of paneling on indoor 

### CH 0 concentrations. The front to back 

### CH20 emission ratios for each measurement series of the fast decay study are summarized in Table 15. These ratios are calculated as the average of three FSEMmeasurements taken on the decorative front 

### of the board dividedby the average 

### of three FSEMmeasurements taken on the back of the board. 2
2

For print paneling the average frontback ratios for individual boards vary from 

### 0.5 to 

### 1.4with an overall mean of 

### 1.0. Four out of five of the boards have mean ratios within approximately one standard deviation 

### of unity. For the paper overlayed paneling the average frontback ratios for individual boards vary from 

### 0.3 to 0.6. The overallmean ratio of 

### 0.4 k 

### 0.2 indicates that CW 0emission strength from the back of paper overlayed paneling is typically 

### 2 to 3 times stronger than the emissions from the front of the panels. For domestic veneer overlayedpaneling, the average front to back ratios range from 

### 0.8to 2.1. With the exception of PAND1#3, which was 

### by far the strongest emitting domestic paneling in the pressed-woodproduct survey, the 2



### 2.McCullagh and Nelder,General Linear Models,Chapman and Hall.Report XVIII 44 CPSC-IAG-84-1103

Table 13. Summary of decay periods (7,months) for individual boards in the fast decay study. .----._.I - ll__l Board r:T,RH Corrected 7:

### T,RHUncorrected -I.._ MDF1#3 17.3

### f 4.4 19.6-C 4.7 MDF2#5 20,O-t 7.2 23.2

### k 9.4 MDF2#6 25.2 111.3 29.7f 14.6 14.0 F: 1.8 15.0d- 2.6 MDF3#9 PBU1#1 

### 11.02 2.7 14.2

### I 3.6 PBU1#5 13.3

### f 3.0 14.6 f. 3.5 PBU3#6 14.3f. 3.5 

### 16.01- 4.4 PRXl#4 11.0f 2.7, 10.92 2.8 PBI2#5 19.5-C 5.7 22.15 7.8 PBI3#4 11.6

### f 1.9 13.0

### k 2.3 PB13#5 11.9

### t 2.5 14.0

### I 3.5 PANPRP#2 Face 

### 11.0

### +. 2.2 

### 11.0

### t- 2.3 PANPR1#2 Back 10.8

### t- 1.9 

### 11.0f. 1.6 PANPR1#6 Face 12.0 rt 1.9 13.4k 1.8 PANPK2#4 Face 

### 10.0k 

### 1.4 10.9 rt 1.8 PANPR2#4 Back 7.9 9 

### 1.5 8.0

### t 7..6 MDF3#3 17.7zf: 3.5 20.0

### I h.3

PANPR1#6 Back 

### 10.4zf: 1.6 11.2 

### I 2.0
PANPR2#6 Face 8.0f. 

### 1.4 7.9 I1.2 PANPR2#6 

### Back 9.8? 2.3, 

### 9.0 2 1.9, PANPR3#2 Face 25.5 zf: 13.1 31.5 15.5 PANPR3#2 Back 15.3

### f 

### 4.1 15.5-t 3.5 9.9f 

### 2.1 12.0k 2.6 PANP1#6 Face PANP1#6 Back 12.4 F: 1.6 12.8-C 2.5 BANP2#2 Face 8.4 

### f 1.3 8.5

### t- 1.3 PANP2#5 Fack 8.3

### t 1.4 9.4k 1.9 

### PANP2#5 Back 

### 10.0-t 1.8 9.9

### 2 1.7 15.0 It 5.7 14.7

### t- 1.7 PANP3#6 Face 12.8d- 4.0 PANP3#6 Back 12.6

### t- 3.3 PAND1#3 Face 20.4f 6.3 22.6

### t- 8.0 PAND1#3 Back PAND1#4 Face 8.9 rt 2.0 10.0

### 2 2.7 PAND1#4 Back 8.0? 0.2 8.0-f- 1.8 13.0F: 2.9 14.7

### P 3.1 PAND3#3 Back PAND3#4 Face 13.3 -t 3.4 14.3 k 3.4 

### 10.02 1.3 

### 10.2

### a 1.6 PAND3#4 Back *Data Q-testieioved at a >96% confidence level in subsequent calculations of average 7 values for each product category (i.e.,Table 14). PANP2#2 Back 

### 10.0f 

### 2.3 9.9

### 2 2.2 

# * * 10.7 

### 2 1.5 

### 11.12 2.0
PAND3#3 Face 10.9 F: 3.5 12.7-I- 3.7Report XVIII 45 CPSC-IAG-84-1103

Table 14. Summary 

### of average decay periods (7,months) 

### for the fast decay study.

7:

### T,RMCorrected 7:

### T,RHUncorrected Average 

### Range Average Range Product



### 18.8 rf:4.4 

### 14.0

# - 25.2 21.5

### C 5.4 15.0

## - 29.7 Medium Density Fiberboard Particleboard 

### (All data) 

# - Underlayment 

# - Industrial 13.2

### +. 3.0 11.0

## - 14.3 

### 15.0 -b 3.9 

### 10.92 22.1 12.92 1.7 

### 11.5 2 

### 0.5 11.0

## - 14.3 11.0

## - 11.9 14.9 4 0.9 

### 15.0? 4.9 14.2

## - 16.0 

### 10.9

## - 22.1 Paneling (All data) 

# - Print 

## - Face


### - Back 

### 10.7

### k 2.1 

### 10.6 Lt: 2.2 10.3 -_t 1.7 

### 10.8 k 2.7 7.9

## - 15.3 7.9

## - 15.3 8.0 

## - 12.0 7.9 

## - 15.3 11.2& 2.3 

### 10.94 2.5 

### 10.8**5** 2.3 10.9 .fr 

### 2.9 7.9 

### - 15.5 7.9

## - 15.5 7.9

## - 13.4 

### 8.0

### - 15.5



## - Paper 

## - Face 

## - Back 10.8k 2.3 

### 10.4-_t 3.2 11.3 2 

### 1.4 8.3 

## - 15.0 8.3

# - 15.0 

### 10.0

# - 12.6 11.34 2.1 11.2 rt 2.8 11.44 1.7 8.5 

## - 14.7 

### 8.5 

## - 14.7 9.9 

## - 12.8 Domestic 

## - Face 

## - Back 

### 10.7k 2.0 11.0

### f 2.2 10.4-C 2.1 ' 

### 8.0

## - 13.3 a,9

# - 13.3 8-0

## - 1.3.0 11.6 

### t **2.4** 12.3 2 

### 2.3 11.0 k 2.8 

### 8.0 

## - 14.7 10.0 14.3

8.0

# - 14.7Report XVIIX 46 CPSC-IAG-84-1103

TabLa 1s. Surrr~asyof irmtlback CB2Q miarionratios wffaat decay atudy bud..

Maasurrmmt Sar1as 1 2 3 4 S 6 7 8 Q Msan Product

PAUPRMZ PAUFRlC6 PANPR2Wh PANPR2#6 PANE'R3#2 AllPMFR

PANPlM PMpp292 PANP2+5 PMP3#6 All PANP

PANDlY3 PmM4 Prn3#3 PAND3C4 All PAN2 0.96 0.90 0.86 0.58 0.80 1.63 0.44 0.4Q 0.72 1.07

0.43 0.28 0.37 0.45 0.26 0.10 0.52 0.S3

1.74 1-28 0.30 1.30 1.00 0.86 0.83 0.80 

### -..- 0.70 0.85 0.94 1.33 1.00 1.31 1.15 0.84 0.86 

## --- 1.M 1.27 1.33 1.01 0.9$* 0.S6 0.S0 0.58 0.46 

### _-- 0.7s 0.91 1.10 1.81

0.42 0.38 0.30 0.6s 0.41 0.36 0.34 0.so

2.0s 1.21 0.88 0.87 0.68 0.33 0.20 0.S4 0.38 0.32 0.33 0.21 0.41 0.82 0.71 0.29-

2.13 2.05 2.07 0.88 0.56 1.42 0.79 1.2s 0.40 1.13 1.21 0.93 0.75 1.00 1.20 0.27* 1.23

0.55 0.28 0.27 0.82

2.70 1.46 0.m 1.4s 1.20 1.05 2.12 0.02 1.42

0.28 0.32 0.15 0.84

4.23. 0.89 0.71 1.01 0.90 2 0.16 0.97 2 0.21 1.422 0.45 0.53 0.07 1.04 0.26 0.382 0.38

0.38

### +- 0.10 0.302 0.08 0.272 0.09 0.82 f: 0.11 0.412 0.16

2.12 0.31 1.092 0.26 0.84 f: 0.23 1.01 t 0.20 1.212 0.53

-1 

## - 1 'Data Q-teat reamvad at a > $02 confidmcaluval Srmmubmqmtealculationa olnuen irantlb8ckamiraion ratios.Report 

### XVIII 

### 47 CPSC-IAG-84-1103

the average ratios for domestic paneling are within one standard deviation 

### of unity. Thus, on the basis 

### of the fast decay study data, the majority of the print and domestic paneling appear to have fairly uniform CH Q emission strength from the front andback of the panels. 

### In contrast,paper overlayed paneling appears 

### to have consistently weaker 

### CH 0emission strength from the decorative front 

### of the panels. 2
2

PERMEATION 

### BARRIERS STUDY
The permeation barriers study has been divided into three major parts: 

### (1) the measurement of the CH 0transport coefficients 

### of decorative floor 3 coverings, 

### (2) simulated flooring experiments using an 

### QRNL 0.2 m environmental chamber, and (3) permeation barriers modeling to predict the impact of decorative flooringmaterials on 

### CH O emissions from particleboard underlapent. results 

### of the measurement of CH 

### 0transport coefficients of common decorative floor coverings were summarized in Report 

### XV. A preliminary evaluation 

### of the results 

### of the simulated flooring experiments and comparisons to permeation barriers modeling are given in this report. 

### 2

2 The 2

Simulated Flooring Experiments
Three separate floor coverings

### were tested in the simulated flooring experiments. Permeation Barrier 

### I consistedof waffled 

### sponge rubber cushion and 

### cut and loop pile nylon carpet. Permeation Barrier 

### II consisted 

### of urethane foam cushion and cut pile nylon carpet. Permeation Barrier 1x1 consisted 

### of vinyl tile flooring. The physical specifications of these decorative flooring materials have been summarized in Table I1 of Report 

### XV. The basic experimental design of the simulated flooring experiments has remained unchanged from the outline 

### of the study presented in Report 

### XV. 

# me testing sequence was to measure the CM20 emissions 

### from uncovered particleboard underlayment, floorlng covered underlayment and finally repeat measurements of the uncovered underlayment. The dual measurements 

### of the uncovered particleboard are used to estimate the temporally dependent decline in the CH 0emission strength of the board during the study. The experimental apparatus consisted of a 

### 0.2m3 Teflon-linedchamber with one 

### wall removed and 2Report

### XVIII 48 CPSC-IAG-84-1103
replacedby the simulated floor. Formaldehyde emissions testing was performed 23 at for both uncovered and flooring covered underlapent. Four different air flow rates from 2 to 

### 15 L/min (i-e., 

### 0.6 to 4.4 air exchangesper hour) were used to create a wide range 

### of CH 0concentrations inside the test chamber. The resulting air exchange/loading ratios were 0.37to 2,8

### m/h. A small fanwas operated inside 

### the chamber to create turbulent mixing independent of the air flow rate through the chamber. Separate conditioning procedures were used €or measurements of uncovered and flooring covered underlayment. For bare underlayment, environmental conditions 

### of 23"C,

### 50% 

### RH and

### <0.1 ppm CH 0were maintained for 

### 32weeks prior to CH 0emission measurements. A second, brief conditioning period equal to 3 to 4 air exchanges of the chamber was then used prior to CH **0**measurements at each of the four different air flow rates. For carpet-covered-particleboard,a minimum of one week conditioning periodwas used at each air flow rate prior to CH2Q emission measurements. For tilecovered-particleboard, sixweek conditioning period was used prior to CH **0** emission measurements. 23 2 

### 0.5"C, 50 2 3% 

### RH and a floor loading of 

### 1.6 m **/sn**

2

2 2
2

8 2

The average CH 0concentration data for uncovered and flooring covered particleboard underlayment as a function'dfair flow through the environmental chamber are summarized in Table 16. Examination of the uncovered particleboard data indicates a twofold decrease in CH 0emission strength betweenmeasurement series 

### I and 

### XI and a comparatively small change between series I1 and 111. 

### The strong decline in CH 0emissionsbetween series 

### I and I1 may be caused in part 

### by the lenghty sevenmonth duration of this portion of the permeation barriers studies. Following the initial measurements of the uncovered underlayment,approximately 3 months were lost due to various experimental problems including 

### (1) shifting the 0.2m measurement chamber from our Elotpack environmental chamber to a laboratorybench with the start of the Environmental Parameters Study 11, 

### (2) eliminating air leaks at the joint between the simulated floor and the base of the chamber,and (3) determining how long the carpet, carpet cushion,and underlayment system would take to reach a steady state 

### CH 0concentration. In contrast the second phase of the permeation barriers study between particleboard measurement series I1 and I11 required approximately 3months. 2

2
2

3

2Table 16. Formaldehyde vapor concentration data (pp)from the simulated flooring experiments of thepermeation barriers studya
Air Flow Particleboard Carpet, Cushion Particleboard Carpet, Cushion Particleboard Tile Floor Barrier 11 Series I11 Barrier I11 rate (L/min) Seriea I Barrier I Series I1
2 0.429

## * 0.024 0.147 f 0.016 0.220 f 0.011 0.232 t 0.011 0.238 f 0.005 0.008 i 0.005 5 0.319 f 0.022 0.086 f 0.005 0.156 f 0.008 0.147 t 0.005 0.168 **f** 0.005 

### - 8 0.254

## * 0.020 

### - 

## - - - - 

# - 0.063 f 0.005 0,100 f 0.005 0.089 f 0.005 0.129 f 0.005 10 15 0.154 f 0.012 0.038 t 0.005 0.078 f 0.005 0.041 t 0.005 0.087 **f** 0.005 

## - -

~ ~ ~ aAL1data listed to three signifioant digsts to reduce routad off error in subsequent calculations.Report

### XVIII 50 CPSC-IAG-84-1103



### To investigate the impact of the decorative €loor coverings on the CH20 emissions from the particleboard underlayment, estimates of the 

### CH 0 emission strength of the uncovered particleboard during flooring-covered experiments are required. These temporal-dependent estimates of board emission strength are simplest to model when the CH 0 emissions from the uncovered underlayment change littlebetweenmeasurements taken before and after the flooring covered experiments. Thus, for the carpet,cushion Barrier I1 experiments a simple average of particleboard measurement series I1 and I11 is used to determine the 

### CH **0** emission strength of the board. For the tile floor barrier 

### III experiments,particleboard measurment series 111 data are used. It is presuNed that the 

### CH 0 emission strength of the particleboard remained unchanged during the 

### 1.5months during which it was coveredby the very effective vinyl floor permeation barrier. Tomodel the CH 0 emissions of the uncovered 2 particleboard during the carpet, cushion Barrier 

### 1 experiments, the particleboard measurement series 

### I and I1 data have been fit to a single exponential decay model (i.e., Equation 13). 

### An average decay period,

### T,of 10.4k 0.4 months is determined from the CH 0emission data taken at 2, 5 and 15 L/min air flow rates. 

### This decay period is consistentwith some of the particleboard underlayment products measured in the fast decay study (see Tables 

### 13 and 14). The CK 0 concentration data for uncovered particleboard during the middle of the carpet,cushion barrier 

### I experiments (ie., 19.5 weeks following particleboard measurevent series 

### I) are then determined from the following expression: 2

2

2
2 approximate

2

2

-19.5/45 a[CH201~eries 

### I *e [CH20 Model
where 45 weeks is the 

### 10.4month decay period, The results of the modeled 

### @H 0 emissions data for uncovered underlayment during Barriers 

### I,11,and I11 experiments are summarized in Table 17. 2

The general effectiveness of the test flooring materials as CH20 permeation barriers can be evaluated by comparing the modeled CH20 concentrations for uncovered underlayment from Table 17with the measured 

### CH 0 concentrations for flooring-covered underlayment; listed in Table 16. The waffled sponge rubber cushion and nylon carpet barrier resulted in approximate twofold reductions in CH 0 concentrations in comparison to the uncovered 2

2Table 17. Modeled CAZO vapor concentration data (ppn) for uncovered particleboard during flooring-covered particleboard experiments Carpet, Cushion Barrier I Carpet, Cushion Barrier I1 Air Flow (Modeled from PCB (Modeled from PCB Tile Floor Barrier Rate (Lfmin) Series I, II)a Series 11, IIIlb (FCB Series 111 data)

2 0.276 0.229 r 0.010 0.238 f 0.005 0.169 

## * 0.0U5 5 0.206 10 0.129 0.111 f 0.012 0.122

## * 0.005 15 0.100 0.088 0.011 0.097 **2** 0.505 0.163 f 0.008

aThe modeled CHZO concentration for umovered particleboard during the midpoint of Carpet, Cushion Barrier I experiments from weeks 12 to 27 of the 31week period between particleboard

bThsm~deld CHzO concentration for mcovered underiayment age of Particleboard Series I1 and 111. Measurement Series 1 and I1 is calculated as -19.5145 rCB201SeriesI * e during the Carpet, Cushion Barrier I1 experiments is the simple aver-Report XVIII 

### 52 CPSC-IAG-84-1103
particleboard. 

### In contrast,the effectiveness of the urethane foam cushion and nylon carpet varied 

### from near zero changes at 2 L/min flow rates to twofold reductions at 

### 15 L/min flow rates. The vi.ny1 floor caused approximate 30-foldreductions in CH 0concentrations. 2

Permeation Barriers Modellng

A steady state model to predict the potential impact of decorative floor coverings on CH 0 emissions from particleboard underlayment has been previously published. The final expression for the steady state CI120 concentration inside a single indoor compartment wLth uniform mixing and a single 

### CH Q emission source coveredby a permeation barrier 

### of uniform CH20 permeability (i.e.,Equation 

### ll*) is 

# **

2

where:

[CH20]*

# - the steady state 

### CH **8** concentration inside the single compartment (mg/m ), 2 3

the CH **0** concentration outside the compartment, 2 2 -1 3 the area of the emission source (m ) dividedby the product of the pollutant exchange rate (h j and the volume (m ) of the compartment, and

-ir T.G.Matthews,

### T.J. Reed, 

### B. J. Tromberg, C. R. Daffron and A. R. Hawthorne, (1985) "Formaldehyde Emission from Combustion Sources and Solid Formaldehyde-Resin-Containing Products: Potential Impact on Indoor Formaldehyde Concentrations" Advances in Chemistry Series No. 210, Formaldehyde:Analytical Chemistry and Toxicology, 131-50.Report

### XVIII 53 CPSC-TAG-84-1103



### KThe quantities least squares the CH 

### 0transport coefficient for the permeation barrier 

### 2 (m/h) *
m and b are the slope and intercept determined from a linear

analysis of the CH20 emission rate of the uncovered 

### CH 0 2 emission source (€.e.,particleboard underlayment) as 

### a function 

### of CH20 concentration.

Them and b values are determined from the modeled CH20 emissions of the underlayment during flooring-coveredunderlayment measurements (see Table 

### 18). Assuming a zero [CH20J0 for the laboratory supply air to the environmental chamber,Equation 

### 16 simplifies to

A-b 

### [l

## + (:/K) +)m 

## - A] [CH201§S

A comparison

### of the measured CH20 vapor concentrations from the carpetcovered underlayment experiments with 

### [CH2OJSsvalues calculated using Equation 

### 17 are summarized in Table 

### 19. Good agreement is observed between the measured and modeled 

### GH 0 concentrations for both the waffled sponge rubber,nylon carpet barrier and the vinyl tile floorbarrier. These data are consistent with the permeation barriers modeling. In contrast,the modeling results for the urethane foam cushion, nylon carpet barrier generally overpredict the CH 0 permeation resistance of these decorative floaring materials,particularly at the lower air flow rates. The reason for the discrepancy between the experimental and modeled 

### CH 0concentrations for the urethane foam cushion, nylon carpet barrier is currently unknown. 2

2
2a Table 18. Linear regression analyses of the modeled CH20 concentration data for uncovered **particleboard** underlayment during flooring 

### - covered particleboard experiments Carpet, Cushion Carpet, Cushion Tile Floor Barrier I Barrier I1 Barrier PCB Series I, 11) PCB Series 11, 111) PCB Series 111) (Modeled from (Modeled from (Modeled from Slope 0.94 Intercept 0.47 

### 1.02k 

### 0.11 1.29 5 0.06 0.40 k 0.02 0.48 k 0.01 %ee Equation 16.Table 19. Comparison ofmeasured andmodeled CHzO vapor concentrations (ppn)from simulated flooring experiments Carpet, waffled 6ponpe Carpet, urethane Air flow Rubber Barrier I FomBarrier I1 rate (Llmin) A Measured Modeled Measured Modeled Tile floor Barrier Measured Modeled
2 2.71 0.15 5 0.02 0.18 0.23 f 0.01 0.16 t 0.02 0.008 k 0.005 0.002 i 0.001
5 1.08 0.09 f 0.01 0.10 0.15 f 0.01 0.03 f 0.02 

## -
10 0.54 0.06 f 0.01 0.06 0.08 f 0.01 0.05 f 0.01 

## -
15 0.36 **0.04** i 0.01 **0.04** 0.04 f 0.01 **0.04** P 0.01 

## -



# . I **co** F- +." +." **0** W IReport 

### XVIII 56 CPSC-IAG-84-1103

INTERLABORATORYTE_T COMPARISON

### OF THE 

### FSEM
Thepreliminary experimental results and analysis of the interlaboratory test comparison of the 

### FSEM are given in this report. The test data consist of 

### FSEMmeasurements 

### of the particleboard and paneling samples taken initially at ORNL and thenby participants in the interlaboratory test comparison. The final set of FSEM measurements, to be taken at ORNL after the return of all test samples from the participants, could notbe performed due to time and resource restrictions. Two of the original ten participants that contributed experimental results to the interlaboratory comparison of the CH 0 analysis of CH 0-exposedmolecular sieve samples did not contribute 

### FSEM data. These groups used molecular sieve and filterpaper that had been suppliedby 

### ORNL but hadbecome contaminated inmailing. They were unable to repeat the FSEM tests with uncontaminated sieve and filter paper due to time and resource restrictions. The results of one additional participant were deleted because the reported CH OERs of the test products were all zero. This is the same participant that got twofold low results in the original measurements of the CH 0-exposed molecular sieve samples. The close results from the remaining nine participants in the first interlaboratory comparison (i.e.? coefficient of variation 

### of 

### 7%) indicate that this participant continued to have problems with the analysis of the molecular sieve. 2 2

2
2

The average results of 

### FSEM measurements taken initially at ORNP. and subsequently by participants in the interlaboratory comparison of the FSEM are listed in Table 20 for particleboard underlayment and Table 21 for hardwood plywood paneling 

### (ice., domestic veneer) samples. 

### The participant,product sample numbers in the tables do not represent the same institutions as the participant numbers that were given in Report XI11 for the first interlaboratory test comparison of the CH 0-exposedmolecular sieve samples. 

### The columns ORNL/0.301 and ORNL/O.163 in Tables 20 and 21, respectively, represent the relatjve CH 0 emission strength of the test samples as determined from the initial OWL 

### FSEMmeasurements. The correctedparticipant data are simply normalized for the relative CH OER determined from the ORNL FSEM measurements. No corrections for product aging during the study canbe applied since the final series of FSEM measurements at OWL could not be performed. The average results for the particleboard samples (i.e., Table 20) 2
2
2Table 20. Interlaboratory test comparison results 

### of the 

### FSEM for particleboard underlapent samples Partici ants Corrected Partici ants bg/m

# s h) 

### ORNL/O.163 

# s Sample No. (mg/m2h) (mg/m h) Participant OWLMeas.

Average 

## cv 0.392 

### f 0.039 0.322 

### 2 0.018 0.261 2 0.084 0.326 

### f 0.072 0.215 

### f 0.034 0.285 

### k 0.015 0.308 50.020 0.301 2 0.056 

### 19% ~~

### 1.30 

### 1.07 0.87 1.08 0.71 0.95 1.02 

### '1.00 

### 0.212

### f 0.025 

### 0.276 +_ 0.033 0.192 

### f 0.036 **0,246**k 0.031 **0.174** 

### k 0.062 

### 0.185 2 0.032 0.222 

### f 0.042 0.215 k **0.036** 

### 17% 0.163 0.258 0.221 8.228 0.245 0.195 

### 0.218 0.218 k **0** 14% 

### 031Table 21. Interlaboratory test comparison results of the FSEM for hardwood plywood paneling samples Corrected Partici ants Partici ants bg/m

# 4h) ORNL/O. 163 

### (w/m 

# 4

h) Participant OWLMeas. Sample No. (mg/m2h> 1 0.171 2 0.036 1.05 0.088 2 0.020 0.084 2 0.198 5 0.014 1.21 0.175 2 0.011* 0.145* 3 0.183 

### f 0.013 1.12 0.096 2 0.026 0.086 4 0.191

### k 0.048 1.17 0.109 5 0.033 0.093 5 0.126 5 0.015 0.77 0.074 

### 2 0.018 0.096 6 0.115

### 2 0.024 0.70 0.067 

### 2 0.025 0.095 7 0.158 k 0.028 0.97 0.103 2 0.030 0.I06 Average 0.163 

### f 0.032 

## cv 20% Q-tested**hV** CV 0.102 0.036 0.101 k 0.021 35% 21% 0.090 ? 0.014 0.093 9 0.809 16% 10% "Q-test positive at **2** 96%confidence interval.

HReport 

### XVIII 59 CPSC-IAG-84-1103

indicate coefficients of variation 

### (CV) 

### of 

### 19% and 

### 17% for 

### ORNL and participant measurements of the test samples. This is within the range of 07s for interboardvariation determined 

### for particleboard materials from the pressed-wood product survey (see Table 

### VII, Report

### XII). The CV for the corrected participants data 

### (14%)is somewhat improvedpresumably because some of the interboard variation has been removedby the normalizationprocedure. The average results for paneling indicate 

### CVs of 

### 21%, 35% and 

### 21% for the ORNL, participants and corrected participants data. 

### If the results for participant 2 are Q-tested (ie.,at,a

### 96% confidence level) the CVs for the participant and corrected partichpants data are 16% and lo%, respectively. The CVs for both the Q-tested and non-Q-testedparticipant data sets are within the range of CVs for combined intraboard and interboardvariation determined for paneling products from the pressed-woodproduct survey (see Table VZII, Report 

### XII). Analogous to the particleboard results, the CVs 

### for the corrected participants paneling data are improved presumably because some of the interboard variation has been removed. The overall results for this preliminary interlaboratory comparison indicate that several independent laboratories could perform FSEM measurements with a precision of approximately a 10-20%CV.

### 61
APPENDIX 

### I: Uncertainty Analysis 

### of Models 

### I and 

### I1

The mathematical development of 

### the uncertainty analyses for both Models 

### I and 

### IT is presented 

### for a general five term model 

### of functionality 

### f, independent variables x 

### x2 

# ...x and model coefficients

## el, e2


# ...e5. 5’

where:



### y

# - single observation,and

e randomness in

### y,

The functional form 

### f,of the model is assumed to be true.


### x2 

## ...x values 5 The population mean value 

### for y for a 

### given set 

### of

### x is

There is no randomness inE(y) so no E term is included.

For a given experimental data set (e.g., 

### ALLPBU for Model 

### I), the mathematical form 

### of EquationA1 is62

where:



### y = estimate of y for a single observation, and b' = estimate of 6' based on a given data set 

### D.

D

E is unknown and not included mathematically inModel 

### I or Model 

### IT. y may be used to estimate future values of y as given in Equation A1 or values of E(y) as given inEquation A2. described in the following discussion.

D The uncertainty in such predictions is

Consider the uncertainty in E(y) as estimatedby y. (i.e.,error) between the two functions is The difference

All uncertainty in E(y) is in dD1, OD2 

## ... eD5. (i.e.,V) in E(y) for complexmodels,a second order Taylor Series Approxima- 

# * tion is commonly used, To estimate the variance

and 0


### . 'Di Dj where COV is the Covariance between two model coefficients,



## * A. M. Mood, 

### F. A. Graybill,

### D. C. Base, "Introduction to the Theory of Statistics,"McGraw-Hill,

### NY, 1974,pp. 181.63

The expanded form of Equation A5 is

The estimate of the standard error of E(y) is the square root of

### V[E(y)]. Consider the uncertainty in y as predicted 

### by y. The difference (i.e., error) between the two functions is

Error =

### y

# -y64
Uncertainty in y comes from two sources: cients d 

### The variance of y Fs the uncertainty in the model coeffiand E, the randomness involved in future observations. 

### D1' 'D2 "* 

### 'D5

where o2 is the variance of the randomness component E. the mean square error (mse) of y for the given pressed-wood product model (e.g., ALLPBU forModel 

### I) under consideration. The estimated standard error (SE) of y is a2 **is** estimated by65 ORNL/TM-9867 

### INTERNAL DISTRIBUTION


### 1. C. R.Daffron , 39. 8.

### J.Tromberg 2. C. S.Dudney 40. P.J. 

### Walsh 3. 

### R. B.Gammage 

### 41-42. Central Research Library 4. A. R.Hawthorne 43. Document Reference Section 5. S.V. Kaye 44-45. Laboratory Records 6-36. 

### T.G. Matthews 45. Laboratory Records,RC 37. D. C. Parzyck 46. OWL Patent Office 38. C. V. Thompson

EXTERNAL DISTRIBUTION
47. Frank Brauer,

### U.S. Consumer Product Safety Commission, 

### 5401 Westbard Avenue,Washington, DC 20207. 48. M. Brownstein,Consumer 

### and Corporate Affairs, Place du Portage 

### 1,Hull, Quebec KlAOC9, CANADA 49. Steven G. Clarkson,Conswner and Corporate Affairs, Tunney’s Pasture, Ottawa, Ontario,CANADA KlAOC9 50. Murray Cohn,

### US Consumer Product Safety Commission, 

### 5401Westbard Avenue, Washington, DC 20207 

### 51. 

### R.A. Jewel,Research Division, Plywood Product Development,Weyerhaeuser Company,Tacoma,

### WA 98477 52. Joseph Fandey,

### U.S. Consumer 

### Product Safety Commission, 

### 5401 Westbard Avenue,Washington, DC 20207. 

### 53. K.W. 

### Fung,University 

### of Hong 

### Kong, PokfulamRoad,Hong Kong. 54. Peter Gaudert, Building Performance Section, Division of Building Research,National Research Council,Ottawa,CANADA KlAOROl 

### 55. William J. Groah, Technical Director, Hardwood Plywood Manufacturers Association, 

### P. 0. Box 2789,Reston,Virginia 22090 56. K. C. Gupta,U.S. Consumer Product Safety Commission, 5401 Westbard Avenue,Washington, DC 20207. 57. David E. Jacobs,Safety and Health Consultant, Georgia Institute of Technology, Engineering Experiment Station,EnvironmentalHealth and Safety Division, Atlanta,Georgia 30332.66


### 58. Helmut Knoppel,Head,Environmental Chemicals Sector,Chemistry Division, Joint Research Centre, Ispra Establishment, 1-21020Ispra (Varese), ITALY. 59. Chris Korf, Centre for Surface Technology, Stichting Centrum Voor Oppervlaktetechnologie, Postbus 

### 98,2015 Ab Overveen,HOLLAND 

### 60. Ron Medford,U.S. Consumer Product Safety Commission, 5401 Westbard Avenue,Washington,DC 20207. 61.. Rick Mendlen,Office ofMobile Home Standards,Department of Housing and Urban Development,451 Seventh Street,SW,Washington,DC 20410 

### 62. Beat Meyer, Department of Chemistry 

### BG-10, University of Washington, Seattle,WA 98195 63. Lars Molhave, Cand. Scient, Arhus Universitet, Hygiejnisk Institut, Bygning 181, Universitetsparken,DK 8000Arhus C, Danmark. 64. LarryMulligan,

### U.S. Consumer Product Safety Commission, 

### 5401 Westbard Avenue,Washington,DC 20207. 65. George Myers,

### US Department ofAgriculture,Forest Products Laboratory, P. 0. Box 5130, Madison,WI 53705 66. Larry 

### R. Newton, Georgia-Pacific Corporation, Technical Center, 2883 Miller Road,Decatur,GA 30035 67. Ronald 

### H. Peters,CIH,Environmental Research Group, Incorporated, 

### 117 North First,Ann Arbor,MI 48104 68. Edmone Roffael, Fraunhofer-Institutfur Holzforschung, Wilhelm Klauditz Institut,Bien roder Weg 

### 54E,D-3300 Braunschweig, West Germany 69. David Sanchez, U.S. Environmental Protection Agency, Mail Drop 56, Research Triangle Park,NC 27711. 

### 70. Clifford J. Shirtliffe,National Research Council Canada, Division of Buildi-ngResearch,Ottawa,Ontario

### KlAOR6, CANADA 

### 71. 

### E. N. Skiest,Corporate Technical Director, Chemicals, Borden, Inc., 960Kingsmill Parkway, Columbus,OH 43229 72. Birger Sundin,AB Casco,

### P. 0. 

### Box 11010,S-10061 Stockholm, SWEDEN 

### 73. Kevin Teichman,Office of Building Energy Research and Developement,U.S. Department of Energy, 

### 1000 IndependenceAve, S.W. Washington DC,20585 74. Bruce Tichenor,

### U.S. Environmental Protection Agency, Mail Drop 56, Research Triangle Park,NC 27711.

### 75. Gene Tucker,

### U.S. Environmental ProtectionAgency,Mail Drop 

### 56,Research Triangle Park,

### NC 27711. 76. Theodore 

### G. Whippie,Manager

# - Product Evaluation, Technical Center, Building Products Division, Champion International Carp., Drawer C,Brewster, 

### NY 10509 77. D. Walkinshaw,National Research Council Canada, Division of Building Research, Ottawa,Ontario KlAOR6,CANADA 

### 78. Terry Zinn,National ParticleboardASSOC., 2306 Perkins 

### Place, Silver Springs, 

### MD 20910 79. Office ofAssistant Manager 

### for Energy Research and Development. Oak Ridge Operations Office,Oak Ridge, TN 37831. 80-82. Technical Information Center,Oak Ridge, Tennessee 37830.