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liq UBRARY l
' Michigan State

University J

 

This is to certify that the
thesis entitled

AN EXPLORATION INTO THE USE OF STEPWISE
REGRESSION ANALYSIS TO DETERMINE POST-

CONSUMER RECYCLED PET CONTENT IN PET SHEET

presented by

DONGHO KANG

has been accepted towards fulfillment
of the requirements for the

MS. degree in __ Packaging

 

 

. /
v
A

 

 

 

o ssor's Signature
0 8 I 2.8 l 001

Date

 

MS ’J 1.9 an Affirmative Action/Equal Opportunity Employer

 

 

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
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AN EXPLORATION INTO THE USE OF STEPWISE REGRESSION ANALYSIS TO
DETERMINE POST-CONSUMER RECYCLED PET CONTENT IN PET SHEET

By

DONGHO KANG

A THESIS
Submitted to
Michigan State University

In partial fulfillment of the requirements
For the degree of

MASTER OF SCIENCE
Packaging

2009

 

ABSTRACT

AN EXPLORATION INTO THE USE OF STEPWISE REGRESSION ANALYSIS TO
DETERMINE POST—CONSUMER RECYCLED PET CONTENT TN PET SHEET

By

DONGHO KANG
The aim of this research was to explore the use of a stepwise regression analysis to
determine the post-consumer recycled polyethylene terephthalate (PET) content in PET
sheets. Six kinds of PET sheets with varying percent of virgin (V) and recycled (R) PET
contents were produced at Peninsula Packaging Company (Exeter, CA, USA). The
optical, thermal, barrier and thermo-mechanical properties of the PET sheets were
evaluated as function of RPET contents. There was a statistically significantly difference
between the UV and visible light absorption in the region between 200 and 350 nm and
670 and 700 nm, respectively. Color measurement indicates that more RPET contents in
PET sheets lead to greyer, greener and more yellow color. DSC indicates that the melting
(Tm) and cold crystallization temperatures follow a semi-linear trend with the amount of
RPET in the blends. Intrinsic viscosities were statistically significantly different between
100%V and 100%R PET sheets. The results of lH NMR indicates that protons of end
groups in 6OV40R, 40V60R and 20V80R PET were higher than 100V PET (11:005.). A
tentative stepwise regression model emerged with an adjusted R2 of 0.9740 for predicting
the amount of RPET, with intrinsic vi scosity, UV, color, Tm, and oxygen permeability
values as predictor variables. This model was developed for a specific mechanical RPET
stream provided by the ECOZ company (Modesto, CA. USA). At this stage. it is not

applicable for other recycled PET streams and products without new studies.

 

Dedicated to my family and fiiends

 

 

 

ACKNOWLEDGMENTS

It is difficult to express my deepest heartfelt thanks to Dr. Rafael A. Auras for
accepting me and giving me the opportunity to work on this project. Without his
educational and professional guidance, I would not have been writing this thesis.

I would like to thank to Dr. Susan E.M Seike and Dr. Satish .loshi for giving me a
valuable advice and guidance for this project as committee members.

I would like to express my sincere appreciation to Dr. Keith Vorst and Greg
Curtzwiler from California Polytech University for helping me to produce samples used
in this project and to make valuable discussion with me.

I would like to thank to Dr. Daniel Johns from Chemistry department of Michigan
State University for training and helping to interpret the nuclear magnetic resonance
study.

1 would like to thank to Dr. Wei Wang for providing me a SAS code and helping
me to establish stepwise regression model with verification of this model.

I would like to thank to Peninsula Packaging Company (Exter, CA, USA) to
give me an opportunity to visit their company and to provide excellent PET sheets for
this project.

I am grateful to Pactiv cooperation (Lake Forest, IL, USA) and C learlam
packaging Inc. (Elk Grove Village, IL, USA) for providing me their PET samples for
verifying stepwise regression model.

I am thankful to research group member, SungWook Hwang, Turk, Hayati.
Praveen, Sukeewan, Dhoot, Dhayalan and all other school of packaging students for their

support and encouragement.

iv

It is needless to say the extent of support and love from my family. My father.
GillUn Kang, and my mother, GuieOk Son, have always encouraged me during my entire
master’s year. Thanks to my two younger brother, DongHyuk Kang and DongWoo Kang.
for their support. I also want to thank to MinJung Joo for sharing pain and happiness all

the time.

DONGHO KANG

 

East Lansing, MI, USA

August 26, 2009

\l

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................................. ix
LIST OF FIGURES .......................................................................................................... xii
KEY TO ABBREVIATIONS OR SYMBOLS ................................................................ xiv
1. INTRODUCTION ........................................................................................................... 1
2. LITERATURE REVIEW ................................................................................................ 4
2.1 Introduction ................................................................................................................ 4
2.2 Virgin PET ................................................................................................................. 5
2.2.1 PET synthesis ...................................................................................................... 6
2.2.2 Morphology of PET ............................................................................................. 8
2.2.3 PET applications and processing ......................................................................... 9

2.3 Municipal solid waste of virgin and recycled PET resin ......................................... 10
2.3.1 Continued high price for virgin PET ................................................................. 13
2.3.2 Increasing demand for PET ............................................................................... 14
2.3.3 Increasing demand for Recycled PET (RPET)........................ .......................... 16
2.3.4 Low environmental footprint of RPET .............................................................. 17

2.4 Management method of PET .................................................................................... 19
2.4.1 Packaging in municipal solid waste ................................................................... 22
2.4.2 Source reduction of PET packaging .................................................................. 24
2.4.2.1 Lightweight............... ................................................................................. 25
2.4.2.2 Reuse and refill .......................................................................................... 27

2.4.3 Recycling of PET packaging ............................................................................. 2‘)

2.5 Legislation of PET recycling for food use ............................................................... 30
2.6 Recycled PET ........................................................................................................... 31
2.6.1 Collection .......................................................................................................... 32
2.6.2 Recyclables processing of PET ......................................................................... 34
2.6.2.1 Materials recovery facilities (MRFs) ......................................................... 34
2.6.2.2 Mixed waste processing ............................................................................. 35

2.6.3 Conventional recycling process ......................................................................... 35
2.6.3.1 Chemical recycling .................................................................................... 36
2.6.3.2 Mechanical recycling ................................................................................. 37

2.6.4 Effects of contaminants on recycling ofPET .................................................... 38
2.6.4.1 Acid producing contaminants .................................................................... 39
2.6.4.2 Water .......................................................................................................... 39
2.6.4.3 Coloring contaminants ............................................................................... 39
2.6.4.4 Acetaldehyde .............................................................................................. 40
2.6.4.5 Other contaminants .................................................................................... 40

2.6.5 End use applications of recycled PET ............................................................... 40

3. METHODOLOGY ........................................................................................................ 43

vi

3.1 Materials ................................................................................................................... 43

3.2 Optical properties ..................................................................................................... 43
3.3 Mechanical properties .............................................................................................. 44
3.4 Thermal properties ................................................................................................... 45
3.5 Barrier properties ...................................................................................................... 46
3.6 Nuclear Magnetic Resonance (N MR) Spectroscopy ............................................... 46
3.7 Viscosimetry ............................................................................................................. 47
3.8 Statistic Analysis ...................................................................................................... 47
. RESULTS AND DISCUSSION .................................................................................... 49
4.1 Optical analysis ........................................................................................................ 49
4.1.1 UV-Visible Spectroscopy .................................................................................. 49
4.1.2 Colorimeter ........................................................................................................ 53
4.2 Mechanical analysis ................................................................................................. 54
4.2.] Dynamic Mechanical Analysis (DMA) ............................................................. 54
4.2.2 Universal Material Testing ................................................................................ 55.
4.3 Thermal analysis ...................................................................................................... 57
4.4 Intrinsic viscosity ..................................................................................................... 59
4.5 Barrier properties ...................................................................................................... 60
4.6 Nuclear Magnetic Resonance analysis (NMR) ........................................................ 61
4.7 Stepwise regression analysis .................................................................................... 65
4.8 Preliminary verification of the model ...................................................................... 72
4.9 Limitation of the study and the model ..................................................................... 76
. CONCLUSION .............................................................................................................. 77
. APPENDICES ............................................................................................................... 80
6.1 Appendix A- Description of sample production and processing conditions ............ 80
6.1.1 Processing condition of 80R20V PET sheet ..................................................... 83
6.1.2 Processing condition of 100R PET sheet .......................................................... 85
6.1.3 Processing condition of 60R40V PET sheet ..................................................... 87
6.1.4 Processing condition of 40R60V PET sheet ..................................................... 89
6.1.5 Processing condition of 20R80V PET sheet ..................................................... 91
6.1.6 Processing condition of 100V PET sheet .......................................................... 93
6.2 Appendix B - Description of stepwise regression analysis and SAS code .............. 95
6.2.] Multiple linear regression analysis .................................................................... 95
6.2.2 Pearson correlation coefficient .......................................................................... 95
6.2.3 R, R Square and adjusted R Square ................................................................... 96
6.2.4 Stepwise regression ........................................................................................... 97
6.2.4.1 Forward selection ....................................................................................... 97
6.2.4.2 Backward selection .................................................................................... 97
6.2.4.3 Stepwise selection ...................................................................................... 98
6.2.5 SAS code for this study ..................................................................................... 98
6.3 Appendix C — Description for each linear regression and estimated parameter for
each step ....................................................................................................................... 103

6.3.1 Description for simple linear regression between TG and dependant variables 1 03
6.3.2 Description for simple linear regression between TM and dependant variables 1 ()4

vii

6.3.3 Description for simple linear regression between xc and dependant variables106
6.3.4 Description for simple linear regression between UV380 and dependant

variables .................................................................................................................... 107
6.3.5 Description for simple linear regression between IV and dependant variables] 09
6.3.6 Description for simple linear regression between OTR and dependant variables] 10
6.3.7 Description for simple linear regression between WVTR and dependant

variables .................................................................................................................... l 12
6.3.8 Description for simple linear regression between NMR424 and dependant
variables .................................................................................................................... 1 13

6.3.9 Description for simple linear regression between ‘L*’ and dependant variables] 14
6.3.10 Description for simple linear regression between ‘a* ’ and dependant variables] 16
6.3.11 Description for simple linear regression between ‘b*’ and dependant variables] 17
6.3.12 Description of the estimated parameter for each step .................................... ] 19

7. REFERENCES ............................................................................................................ 120

viii

LIST OF TABLES

Table 2-1. Trade names of PET and their manufacturers [22] ............................................ 6
Table 2-2. Common properties of PET ................................................................................ 8
Table 2-3. Required intrinsic viscosity for different PET applications [20, 22] ................ 10
Table 2-4. Values of damage categories for 100V, 50V50R and 100R PET bottle .......... 19
Table 2-5. Generation and recovery of products in MSW, 2007 [8] ................................. 23
Table 2-6. Energy and material saving of lightweight PET bottles compared to traditional
PET bottles [36] ................................................................................... . ............................. 25
Table 2-7. Examples of lightweight bottle productions with company [38—40] ................ 27
Table 2- 8. Costs of 500 ml refillable and one- way glass and PET beverage containers in
Europe [4]] ........................................................................................................................ 28
Table 2-9. Refillables as a portion of total beverage sales and policies in some countries
[4]] ..................................................................................................................................... 29
Table 2-10. Examples of recommended surrogates [42] ................................................... 30
Table 2-11. US FDA no objection letters, until December 2008 [43] 31
Table 2-12. Minimum requirements for PCR-PET flakes to be used for sheet applications
[13, 24] ............................................................................................................................... 32
Table 2-13. Number and population served by curbside recyclables collection programs
in the US. 2007 [8] ............................................................................................................ 33
Table 2-14. Material recovery facilities in US, 2007 [8] ................................................. 35
Table 2-15. U.S. consumption of recycled PET as different product categories [1] ......... 4]

Table 4-1. Light transmission (%) for PET sheets with varying percent of virgin and
recycled PET contents ........................................................................................................ 52

Table 4-2. Results of color measurement for varying percent of virgin and recycled PET
sheets .................................................................................................................................. 54

Table 4-3. Maximum loss, tan delta curve and onset of rubbery plateau as temperature
values 55

_l-r.'

Table 4-4. Mechanical properties for PET sheets with varying percent of virgin and

recycled PET contents ........................................................................................................ 56
Table 4-5. DSC data for PET sheets with varying percent of virgin and recycled PET

contents .............................................................................................................................. 57
Table 4-6. Intrinsic viscosity and viscosity molecular weight ........................................... 60

Table 4-7. Water vapor permeability for PET sheets with varying percent of recycled
PET as SI units ................................................................................................................... 61

Table 4-8. Composition ratio of PET sheets with varying percent of recycled and virgin
PET contents ...................................................................................................................... 63

Table 4-9. Pearson correlation of predictor variables for PET sheets with varying percent
of virgin and recycled PET contents .................................................................................. 65

Table 4-10. p-value, skewness, mean, median for the simple regression analysis for the
predictor variables for PET sheets with varying percent of virgin and recycled PET
content. (or and [3 values for the equation y=0t*X+[3 and the normal distribution of the
standard errors are shown in appendix C.) .................................................................... 68

Table 4-11. Backward elimination sequence for PET sheets with varying percent of
virgin and recycled PET as function of results from each different technique .................. 69

Table 4-12. Proposed linear model (PET= a+B*IV+x*OTR+8*Tm+n *b+a) .................. 70

Table 4-13. Results of each predictor parameter for 4 different kinds of unknown PET
samples ............................................................................................................................... 74

Table 4-14. Comparison between predicted fraction of virgin PET and company

specification ....................................................................................................................... 75
Table 6-1. Description of extruder zone ............................................................................ 8]
Table 6-2. The condition of two extruders for 80R20V PET sheet ................................... 83
Table 6-3. The temperature of dryer and plant for 80R20V PET sheet ............................. 83
Table 6-4. The condition of roller for 80R20V PET sheet ................................................ 84
Table 6-5. The condition of two extruders for 100R PET sheet ........................................ 85
Table 6—6. The temperature of dryer and plant for 100R PET sheet .................................. 85
Table 6-7. The condition of roller for 100R PET sheet ..................................................... 86
Table 6-8. The condition of two extruders for 60R40V PET sheet ................................... 87

Table 6-9. The temperature of dryer and plant for 6OR40V PET sheet ............................. 87

Table 6-10. The condition of roller for 60R4OV PET sheet .............................................. 88
Table 6-11. The condition of two extruders for 40R60V PET sheet ................................. 89
Table 6-12. The temperature of dryer and plant for 40R6OV PET sheet ........................... 89
Table 6-13. The condition of roller for 40R60V PET sheet .............................................. 90
Table 6-14. The condition of two extruders for 20R80V PET sheet ................................. 91
Table 6-15. The temperature of dryer and plant for 20R80V PET sheet ........................... 91
Table 6-16. The condition of roller for 20R80V PET sheet .............................................. 92
Table 6-17. The condition of two extruders for 100V PET sheet ...................................... 93
Table 6-18. The temperature of dryer and plant for 100V PET sheet ............................... 93
Table 6-19. The condition of roller for 100V PET sheet ................................................... 94

Table 6-20. Estimated parameter, P value and 95% confidence interval for step 0 ........ l 19

Table 6-21. Estimated parameter, P value and 95% confidence interval for step 1 ........ 1 19

xi

LIST OF FIGURES
Figure 2-1. PET synthesis reactions: (a) Esterification reaction and (b) trans-
Esteri fication reaction .......................................................................................................... 7

Figure 2-2. Materials generated in MSW, 1960 to 2007 [8], Others includes electrolytes
in batteries and fluff pulp, feces, and urine in disposable diapers ..................................... 1 1

Figure 2-3. Total plastics in MSW, by resin, 1996 to 2007 [8], Others includes
electrolytes in batteries and fluff pulp, feces, and urine in disposable diapers .................. 12

Figure 2-4. Recovery of plastics in MSW, by resin, 1996 to 2007 [8], others includes
electrolytes in batteries and fluff pulp, and plastic in disposable diapers. ......................... 13

Figure 2-5. U.S. price trends of gasoline and crude oil, according to the Energy
Information Administration (Data released on 07/13/2009 for gasoline and 07/15/2009
for crude oil) ...................................................................................................................... 14

Figure 2-6. Total weight of bottles on US. shelves and collected with gross recycling rate,
from 1995 to 2007 [1] ........................................................................................................ 15

Figure 2-7. Price of recycled and virgin PET, 1997 to 2009, according to the report of
Innovation Group “Chemical Profile-PET” and Plastics News.com “PET resin prices”.. 1 7

Figure 2-8. Comparison of damage categories for production of 100V, 50V50R, 100R
PET bottle; 100V PET bottle , 50V50R PET bottle , 100%R PET bottle ................. 18

Figure 2-9. Diagram of solid waste management [32] ...................................................... 20
Figure 2-10. MSW generation, recycling and % recycling in US, 1960 to 2007 [8] ...... 21
Figure 2-11. Municipal solid waste management, 1960 to 2007 [8] ................................. 21
Figure 2-12. Total MSW generation by category. 2007 [8] ..................... 22

Figure 2-13. Depolymerization of PET: (a) Hydrolysis (b) Methanolysis (c) Glycolysis
[19, 22] ............................................................................................................................... 37

Figure 2-14. Degradation of PET: (a) hydrolysis (b) thermal degradation [14, 25] .......... 38

Figure 2-15. U.S. converter consumption of recycled PET as different product categories
[1]; Fiber (0), Sheet & Film (0), Strapping (V), Engineering resin (A), Food & Beverage
bottles (I), Non-food Bottles ( [1), Other (0) ................................................................... 42

Figure 4-1. Constitutional unit of PET .............................................................................. 49

xii

11"“
A
4 L

Figure 4-2. Light transmission of PET sheets with varying percent of virgin and recycled
PET contents between 323 and 450nm .............................................................................. 50

Figure 4-3. Light transmission of PET sheets with varying percent of virgin and recycled
PET contents between 650 and 750nm .............................................................................. 50

Figure 4-4. 500 MHz 1H-NMR spectrum of 100V PET samples measured in TFA/C DC 1362
Figure 4-5. Predicted percentage of PET contents in PET sheets as function of
experimental PET contents in PET sheets (left), Standardized residual vs percentage of

PET contents in PET sheets (right) .................................................................................... 71

Figure 6-1. The flow chart of PET sheet processing ......................................................... 82

xiii

ANOVA

APR

ASTM

BHET

C IWMB

CSD

DALY

DC

DMA

DMT

DP

DSC

EDI

EG

EPA

FDA

HDPE

HSD

LDPE

KEY TO ABBREVIATIONS OR SYMBOLS

ABBREVIATIONS

Analysis of variance

Association of Postconsumer Plastic Recyclers
American Society for Testing and Materials
Bis (hydroxyethyl) terephthalate

California Integrated Waste Management Board
Carbonate soda

Disability Adjusted Life Years

Dietary concentration

Dynamic mechanical analysis

Dimethyl terephthalate

Degree of polymerization

Differential scanning calorimeter

Estimated daily intake

Ethylene glycol

Environment Protection Agency

Food and Drug Administration

High density poly (ethylene)

Honestly significant differences

Low density poly (ethylene)

xiv

 

LLDPE

MRFs

MSW

NAPCOR

NMR

OTR

PCR

PDF

PET

RPET

PP

PS

PVC

RH

RPPC

SSP

TF A

TPA

WVTR

Linear low density poly (ethylene)

Materials recovery facilities

Municipal Solid Waste

The National Association for PET Container Resources
Nuclear magnetic resonance

Oxygen transmission rate

Post-consumer recycled

Potentially Disappeared Fraction

Poly (ethylene trepthalate)

Recycled poly (ethylene terepthalate)

Poly (propylene)

Poly (styrene)

Poly (vinyl Chloride)

Relative humidity

Rigid Plastic Packaging Container
Solid state polymerization
Trifluoroacetic acid

T erephthalic acid

Water vapor transmission rate

XV

CDCI3
C02
-COOR

d1

kPa
ksi

kWh

SYMBOLS

Thermal expansion coefficient, Scalar for Mark-Hauwink Equation
Significant level, Intercept of multi-linear model
Atmosphere

Estimated parameter for intrinsic viscosity
Parameters or regression coefficients

Celsius

Cent

Chloroform

Carbon dioxide

Ester group

Deciliter

Residue

Hydrogen proton

Hour

Intrinsic viscosity

Joule

Kelvin, Constant for Mark-Houwink Equation
Kilopascal

Kilopound per square inch

kilowatt hour

Thickness

xvi

MHz

mmlbs

NMR424
ppb
ppm

psi

std
Tc
ch
Tg
'I‘M
Tm
um
UV

UV350

Megahertz

Million pounds

Viscosity molecular weight
Megapascal

Estimated parameter for ‘b’ value
Intrinsic viscosity

Nanometer

Intensity ratio of 5 4.2 combined with 4.0 peak
Part per billion

Part per million

Pounds per square inch

Quantity

Pearson correlation coefficient
Recycled

Standard deviation
Crystallization temperature

Cold crystallization temperature
Glass transition temperature
"Trademark

Melting temperature

Micrometer

Ultra violet

Light transmission at 350 nm

xvii

UV380

UV678

~< ><l *

‘5

Mint

AHc

0

Light transmission at 380 nm

Light transmission at 678 nm

Virgin

Estimated parameter for oxygen permeability value

Percent of crystallinity

Sample mean of independent variables
Dependant variables

Predicted value

Sample mean of dependent variables
Heat of melting

Heat of crystallization

Heat of fusion of 100% crystalline polymer

Wavelength

Difference of NMR spectrum between standard and sample
intensity, Estimated parameter for melting temperature

Fiber

Sheet & Film

Strapping

Engineering resin, delta

Food & beverage bottles

Non-food bottles

Other

xviii

 

1. INTRODUCTION

Poly (ethylene terephthalate) (PET) is one of the most widely used thermoplastic
polyesters in the US. and around the world. In 2007, 5.7 billion pounds of PET bottle
resin v'Vere used by the US. bottle manufacturers utilizing recycled sources; excluding
post industrial regn'nd, and including exported bottles and pre-forms as well as bottles
less than eight ounces in sizes [1]. Since PET has good chemical, physical and
mechanical properties, and provides good oxygen and carbon dioxide barrier properties.
it is successfully being used in applications such as beverage bottles, fibers, moldings and
sheets. The most widely used application of PET in the US. is the manufacture of bottles
[2]. PET beverage bottles sales in the US. have grown approximately % annually, from
1995 to 2007 [1].

As the demand for non-renewable PET is increasing, recovering of post—consumer
PET (RPET) is also increasing. Recovering of PET is being managed by collection.
separation, cleaning and reprocessing it as new products. Total recycled bottle grade P 131‘
production by the US. reclaimers was recorded at 1,079 million pounds in 2007
compared to 588 million pounds in 1995, representing an increase of 83% [1]. The main
application of recycled PET is the manufacture of fiber (383 million pounds), beverage
bottles (136 million pounds), and sheet & film (128 million pounds) non-food bottles (60
million pounds) [1].

RPET from bottles can be recycled via mechanical and chemical recycling.
During mechanical recycling, PET is melt processed into other parts [3]. Chemical
recycling, on the other hand, by glycolysis, methanolysis, hydrolysis, amninolysis and

ammonolysis can recover the PET monomers (i.e., terephthalic acid and ethylene glycol)

[4]. According to David Cornell, technical director of the Association of Postconsumer
Plastic Recyclers (APR), at least 95% of PCR-PET was mechanically recycled in 2007.
On the other hand, the amount of PCR-PET chemically recycled was very small due to
higher processing cost than mechanical recycling. Cost efficiency of chemical recycling
can be achieved in quantities of 50,000 tons/year, whereas mechanical recycling is more
cost efficient with plant capacities within a range of 5,000 to 20,000 tons/year [5].

Generally, RPET recycling is performed by collecting scraps from homogeneous
deposits like carbonated and non-carbonated bottled drinks, and from heterogeneous
deposits contaminated by polyvinyl chloride (PVC) nylon and various additives. Among
the problems met in the reprocessing of PET bottle scraps, the degradation caused by the
simultaneous presence of retained moisture and the contaminants is a main drawback for
obtaining high quality RPET [6]. The retained moisture and contaminants generate
problems during processing, such as chain cleavage, an increase in carboxylic end groups.
a reduction in molecular weight and a decrease in intrinsic viscosity [6-7]. Thus. the final
quality of the RPET resin is lower than virgin PET indicating that RPET products
obtained from mechanical recycling have reduced physical, mechanical and chemical
properties.

Several approaches have been established to replace products containing virgin
PET with post-consumer recycled PET due to enviromnental responsibility. The
incentive to have a lower environmental footprint motivates producers to make claims of
higher recycled PET content in the final package. Hence, there is a need to know the

amount of RPET in the final product. However. to the best of authors’ knowledge. there

is not a current technique or model able to determine the post-consumer recycled content
of PET film, sheet and containers.

Thus, the aim of this study was to explore the use of stepwise regression analysis
to determine the amount of recycled PET content, which was previously recycled by
mechanical recycling, in PET/RPET sheets. The model includes the optical.
physicomechanical, thermal and barrier properties of PET sheets with varying percent of
recycled (R) and virgin (V) PET. The model was developed only considering a single
recycled PET stream obtained from the bottle deposited program and provided by the
ECO2 company (Modesto, CA, USA). Therefore, at this stage it is not applicable for

other recycled PET streams and products without new studies.

2. LITERATURE REVIEW

2.] Introduction

Plastic materials are currently used for various applications, such as food
containers, beverage bottles, and electronic products. Due to their diverse usage and large
fraction by volume, plastic materials are treated as one of the important municipal solid
waste categories. In 2007, plastic materials composed over 12% of total MSW generation
[8]. The predominant method of waste disposal in US. has been and remains landfill,
representing 54% of total MSW generation [8-9]. However, discarding plastic waste to
landfill is undesirable due to legislation pressures, rising costs and the lack of
biodegradability of commonly used polymers [9]. As an alternative to landfill, recycling
of plastic waste has been proposed as a way to reduce the amount of plastic that ends in
the landfill. There are several methods for recycling of plastic waste, such as primary
recycling (e.g., plastic bottle to plastic bottle), mechanical recycling, chemical recycling
and energy recovery. Among those recycling techniques, mechanical recycling is
dominantly used in the US. for PET, poly (ethylene terephthalate).

PET is one of the most popular plastics, and it is widely used in various
applications, such as soft drink bottles and food containers. Although PET has the highest
recovery rate (18.1%) compared to other plastics, such as HDPE, LDPE, PP, and PS,
recycling of PET is still developing to satisfy economic benefit and environmental
responsibility. The main obstacle for the effective recycling of PET is contaminants, such
as a variety of additives, aluminum, polypropylene (PP) closures, and PVC. Therefore. in

mechanical recycling systems, the developments have been focused on effective

management of the different waste streams, such as selective sorting and automatic
separation [1 0].

The majority of current research focuses on comparison of various properties
between recycled PET and virgin PET [7, 11-13], analysis and the improvement of the
quality of recycled PET [6, 14-18] and evaluation and improvement of the current PET

recycling system [9, 19].

2.2 Virgin PET

PET, polyester, was developed by a small English company in 1941 as laboratory
samples. In the 19505, polyester research was based almost entirely on textiles —
DuPont’s DacronTM and ICI’s TeryleneTM. In 1962, Goodyear introduced the first
polyester tire fabric, and it was in the late 19605 that polyesters were developed
specifically for packaging; film, sheet, coatings, and bottles [20]. Nowadays, PET is one
of the most important commodity plastics. Since PET has excellent tensile and impact
strength, chemical resistance, clarity, processability, and reasonable thermal stability, it is
widely used for many applications, especially drink bottles [21]. Commercial PET has a
wide range of intrinsic viscosity [n] that varies from 0.45 to 1.2 dl/g with a polydispersity
index generally equal to 2. Above the glass transition temperature (T8), the PET chains
are stiff, unlike many other polymers. The low flexibility of the PET chain is a result of
the nature of the short ethylene group and the presence of the p-phenylene group [22].

Some of the trade names of commercialized PET are shown in Table 2-1 [22].

Table 2-1. Trade names of PET and their manufacturers [22]

 

Trade name Manufacturer

Amite DSM Engineering Plastics

Diolen ENKA-Glazstoff

Eastapac Eastman chemical company

Hostadur Farbwerke Hoechst AG

Mylar E. I. Du Pont de Nemours & Co., Inc.
Melinex Imperial Chemical Industries Ltd.

Rynite E. I. du Pont de Nemours and Company, Inc.

 

2.2.1 PET synthesis

PET is a condensation polymer, and it is produced from para-xylene and ethylene.
The para-xylene is converted into either dimethyl terephthalate (DMT) or terephthalic
acid (TPA), and the ethylene into ethylene glycol (EG) [2]. In an esterification reaction.
the TPA reacts with EG at a temperature between 240 and 260 °C and a pressure between
300 and 500 kPa, producing water as the byproduct molecule (Figure 2-1). In trans-
Esterification, DMT is reacted with EG between 150 and 220 °C and 100 kPa, producing
methanol as a byproduct molecule [23-25] (Figure 2-1). trans-Esterification is more
preferred than esterification due to easier purification. In both processes, bis
(hydroxyethyl) terephthalate (BHET) is produced. Next in the the pre—polymerization
step, BHET is polymerized to a degree of polymerization (DP) of up to 30 at 250-280 0C
and 2-3 kPa [24]. About the next step is the condensation polymerization where the DP is
further increased to 100 at 270-290 0C and 50-100 Pa. Up to this stage, PET is suitable
for fibers and sheets which do not require high molecular weight or intrinsic viscosity [1]].

For the application of bottle grade PET which requires high molecular weight or [n] of

0.7-0.81 dl/g, solid state polymerization (SSP) is applied to increase the DP to 150.

Operating conditions for SSP are 200-240 °C at 100 kPa and 5-25 hr [25].

HO\C/O \C/o
-l- HO—CHz—CHz—OH ——> —|-— “20
c c "
/
0% \OH 0/ \(l)
TPA EG (0‘42).
OH
(a)
/o\C/o \C/o
H3C
+ 2Ho-CH2—CH2—0H ——> + 2CH30H
C CH3 /C
0% \O/ o/ \(i)
DMT EG (Cl‘bb
OH
(b)

Figure 2-1. PET synthesis reactions: (a) Esterification reaction and (b) trans-
Esterification reaction

2. 2. 2 Morphology of PE T

PET is a linear molecule that exists either in an amorphous or a semi—crystalline
state. In the semi-crystalline state, the molecules are highly organized and form
crystallites. The maximum crystallinity level of PET may be no more than 55%. The rate
of crystallinity of virgin PET depends on processing conditions, molecular weight, the
presence of nucleating agents, the degree of chain orientation and the nature of the
polymerization catalyst. Virgin PET is well known for having a very slow crystallization
rate. The highest crystallization rate can be achieved between 170 and 190 0C [23, 26].
Since PET can be produced with high crystallinity, processing conditions for PET
depends on its application. Cooling PET rapidly from the melting temperature to a
temperature below Tg can produce an amorphous, transparent PET for films or bottles.
On the other hand, slow cooling of the molten resin can produce semi-crystalline, opaque
PET. Semi-crystalline PET deforms much less under stress, especially at elevated
temperatures, than amorphous PET [2]. Common properties of PET are shown in Table
2-2.

Table 2-2. Common properties of PET

 

Property Value (unit) Reference
Molecular weight (of repeating unit) 192 (g/mol) [27]
k = 3.72 x 10“ (d1/g),a = 0.73 at
0 [27]
Mark-Houw'nk aramet rs 30 C
1 p e k = 7.44 x 10‘4 (dl/g), a = 0.65 at [7]
25°C
Weight average molecular weight 30,000—80,000 (g/mol) [27-28l
Density 1.29-1.40 (g/cm3) [2]
Glass transition temperature (Tg) 69-115 (0C) [24. 28]
Melting temperature (Tm) 255-265 (”C) [23]
Heat of fusion 166 (J/g) [24]
Thermal expansion coefficient (a) 9.1 X 105 (K") [281

 

8

 

336 (K) at 264 (psi)

 

 

 

 

 

Heat deflection temperature , [279 291
344 (K) at 66 (psr)
Break strength 48.2-72.3 (MPa) [21
, 2756-4135 (MPa) [2]
Tensrle modulus (Young’s modulus)
1700 (MPa) [29]
Elongation at break 30-3000 (%) [2]
Yield strain 4 (%) [291
Impact strength 90 (J/m) [291
. . 390—510 g nrn/rn2 day at 37.8 "c ~
Water vapor transmrssron rate 90% RH [2]
c2 permeability at 25 °c 1.2-2.4 x 103 cm3 nrn/rn2 day atm [2]
C02 permeability at 25 °C 5.9-9.8 X 103 cm3 urn/m2 day atm [2]
0.1-0.2 (%) at 0.32 cm thick [2]
Water absorption after 24h
0.5 (%) [29]

 

Table 2-2. (Continued)

2. 2. 3 PET applications and processing

PET is used broadly in products such as bottles, electrical and electronic

instruments, automobile products, housewares, lighting products, power tools, material

handling equipment, and sporting goods [24]. After PET was introduced into the market

as fiber in 1962, it has been developed for packaging such as film, sheet, coating, and

bottles. Films are produced by biaxial orientation through heat and drawing. PET film

does not require the use of solid-stated resin. PET film is used in various applications

such as X—rays sheet, recording tapes and food packaging [20, 23]. PET is also used as an

electrical insulator due to the severe restriction of the dipole orientation at room

temperature which is well below the glass transition temperature [23]. Another important

application of PET is fibers where strength is achieved by applying tension to align the

chains through uniaxial stretching. Since PET can be used in various applications.

9

different application requires different properties, especially intrinsic viscosity of PET.
Table 2-3 shows the required intrinsic viscosity for different PET applications. The main
PET processes are extrusion, injection molding and blow molding.

Table 2-3. Required intrinsic viscosity for different PET applications [20, 22]

 

Application [1]] (dl/g)
Common PET film 0.6-0.65
Recording tape 0.6
Fibers 0.65
Carbonated soft drink bottles 0.71-0.84
Industrial tire cord 0.85

 

2.3 Municipal solid waste of virgin and recycled PET resin
Plastics are a rapidly growing segment of total MSW in the United States. In 2007.
30.7 million tons of plastic MSW was generated in US. compared to 29.48 million tons
in 2006, representing 4.2% increased (Figure (2-2)) [8]. Specifically, the containers and
packaging category in used the most plastics, representing 30.9% of total plastic MSW.
Among the total plastic MSW, 3.76 million tons of PET MSW were generated (Figure (2-
3)) [8]. A big amount of PET resin was used for soft drink bottles. Even though total
plastic MSW has rapidly increased, overall recovery of plastics for recycling is relatively
small, amounting to 2.1 million tons, or 6.8 % of plastics generation in 2007 [8]. PET
resin had the highest recovery rate (18.1 %), compared to HDPE, PP, LDPE/LLDPE and
other resins in 2007 (Figure (2-4)). PET soft drink bottles (including water bottles) were

recovered at a rate of 36.6 % in 2007 [8].

10

 

 

 

 

 

 

100
___-A———- Paper and paper board A
—~—--Cl-—-- Glass / TTTTT A ~~~~ ‘2]

80 - ———-o—-—- Metals
—0— Plastics
-——-<>—-—— Rubber and leather

E1 60 _ ———-v———- Textiles
O
+.> —— -<> —— Wood
E ——-—-o———- Others
5 4o — /._.
E l ///
K
20

 

—-—-—'-

   

  

0 - . n .
1960 1970 1980 1990 2000 2004 2007

   

 

Figure 2-2. Materials generated in MSW, 1960 to 2007 [8], Others includes electrolytes
in batteries and fluff pulp, feces, and urine in disposable diapers

11

 

 

 

 

 

 

10 —0— PET
" ——El—— HDPE
——v-—— PVC
——o—— LDPE/LLDPE
8 -‘ -—<>-- PP
—0—- Otherresins ’0-_____0_____

 

 

Million tons

 

 

0 1 r L r 1 1 J ‘

1996 1997 1998 1999 2000 2001 2003 2005 2006 2007

Figure 2-3. Total plastics in MSW, by resin, 1996 to 2007 [8], Others includes
electrolytes in batteries and fluff pulp, feces, and urine in disposable diapers.

12

 

0.8

 

 

 

 

 

-¢-PET
-0--FEWE
06 P --D-- LDPE/LLDPE
—£~-PP
a, Ohter resins
E
/
§ 0.4
s 3---..-
/
/ /
02- // /,D/
,,{}——%}———D’
:::8::: :7‘583
//
\

/

———a
0.0 ‘ l 1
1996 1997 1998 1999 2000 2001 2003 2005

Figure 24. Recovery of plastics in MSW, by resin, 1996 to 2007 [8], others includes

electrolytes in batteries and fluff pulp, and plastic in disposable diapers.

In this situation, the market dynamics of both virgin and recycled PET (RPET) are

   
   

Y>——«o———o———o—--§E~—<>
2006 2007

 

continually changing. The key factors impacting PET recycling are discussed below.

2.3.1 Continued high price for virgin PET

The price of virgin PET has remained high due to the high price of petroleum.
Both virgin PET and gasoline production compete for the same petroleum precursor.
paraxylene. Therefore, as long as gasoline prices remain high, virgin PET prices will
remain high. Another PET precursor, isopthalic acid, was also in short supply in the

spring of 2007, which further increased virgin PET pricing [30]. In general, high virgin

U

PET prices also allow PET reclaimers to charge higher prices for recycled PET flakes. As
shown in Figure 2-5, the price of both crude oil and gasoline had been increasing until
September, 2008. Following the trend for gasoline pricing, virgin PET prices are

expected to remain high, even in the presence of excess supply.

 

 

 

 

 

 

 

 

 

 

 

 

150
140 -
130 ’ 5 ' Crude oil
110 - '33 .
3 100 a T 3 ‘ i! :8
l: a 2 3:
CU 90 >- m 2 l- .
E 80 — E I i
Q) ‘5 I .—
3 70 ' G if -,
3360— 0‘*"““* .;i
— 1 :
no 50 _ 1980 1990 2000 20 0 3“ 3
40 - i
30 - °
20 — . ~ . ,: »
10 ‘ O I .
0 r 1 r . 1 . . r . 1 . r . . 1 . . .
I970 1980 1990 2000 2010

Figure 2-5. U.S. price trends of gasoline and crude oil, according to the Energy
Information Administration (Data released on 07/ 13/2009 for gasoline and 07/ 15/2009
for crude oil)
2. 3.2 Increasing demandfor PET

According to a report of The National Association for PET Container Resources
(NAPCOR), illustrated in Figure 2—6, 5,683 million pounds of PET bottles were on US.

store shelves in 2007 compared to 1,950 million pounds in 1995, representing a 191 %

increase [1]. However, market growth of about 4.8% for PET bottles and jars sold in the

14

US. during 2007 slowed down from 6.9% in 2006 [30]. The staggering sale of bottled
water in the past decade is predicted to slow down as the market saturates. In 2006.
isotonic drinks, tea, and the energy drink segments led the market growth of PET bottles
and jars. In 2007, not only did those segments continue to perform well, but the first
luxury wine bottle was offered in PET bottles. “Not only were 375 ml bottles used to
access aWay-from-home markets, but 750 ml bottles were introduced at retail, primarily
by Australian vineyards selling in North America [1].” The overall global PET demand is
expected to grow at a rate of 7% per year between 2006 and 2011, with most of the new

virgin PET production capacity in Asia and the Middle East.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6000 50

- Total US. Bottles Collected . I

A , , Bottles on US. Shelves - l ;

. 5000 t ,
LS '\ + Gross Recycling Rate . . ' " 40 Q
E 4000 — — 9;;
E ‘t - 30 04
g 3000 ‘ ED
.0 - .- z —
w \«Hr . — 20 9
“Eb ., . a:
-5 2000 - :: z;
3 1: e
33 , <3

f3 1000 -

C\ 0\ ON 05 ON 0 O O O O O O O

O\ O‘ Q C\ ON C O O O C O O O

r—4 I—‘ v—3 —t -— N N (\l N N N N N

Figure 2-6. Total weight of bottles on- US. shelves and collected with gross recycling
rate, from 1995 to 2007 [1]

2. 3. 3 Increasing demand for Recycled PE T (RPE T)

Demand for RPET is at a record high due to increasing demand for all end-use
applications such as carpets, filters, fabrics, roofing, paintbrushes and brooms, and
packaging. David Cornell, the technical director of the Association of Postconsumer
Plastics Recyclers (APR), believes that “demand will grow from the current 1 billion
pounds per year to between 2 and 2.5 billion pounds per year [30].” This demand is
driven by manufacturers of PET products who, by using RPET, obtain a cost advantage
as high as 40 cents per pound when compared to virgin PET (Figure (2-7)) [30]. In
addition, environmental concerns, as evidenced by the Wal-Mart(Bentonvi11e, AR)
packaging sustainability initiative, are motivating some packaging manufacturers to shift
substrates from polystyrene (PS) and PVC towards recycled content PET. In September
2008, The Coca-Cola Co. (Atlanta, GA, USA), partnered with United Resource Recovery
Corp. (Spartanburg, SC, USA), spent $45 million to build what the company is calling
the largest plastic bottle-to-bottle recycling plant. One of the Coke officials expects that
the company may achieve a recycle or reuse rate of at least 30 % by 2010. Moreover,
California has passed a Rigid Plastic Packaging Container (RPPC) law (amended 2005),
which requires that non-food plastic packaging be source - reduced (light-weighted) by at
least 10%, reused a minimum of 5 times, or contain a minimum of 25% recycled content
[30]. Therefore, increased enforcement of the RPPC by the California Integrated Waste
Management Board (CIWMB), which has been eliminated, would further increase RPET

demand.

16

 

.9 .O
\l 00
l
o
J.)

.o
O\
r
O

O

 

O

U!
_n
'Y
9

C5

—0—- Recycled PET
""0"" Virgin PET

 

 

 

Resin price ($/1b)

.9
N
1

0.1 1-

 

 

 

0.0 A I L L I l L l J l l

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Figure 2-7. Price of recycled and virgin PET, 1997 to 2009, according to the report of
Innovation Group “Chemical Profile-PET” and Plastics News.com “PET resin prices”
2. 3. 4 Low environmental footprint of RPE T

Figure 2-8 show the environmental burden of 100V, 50V 50R and 100R PET as
damage categories obtained from Simapro software (Amersfoort, Netherlands). Even
though several assumptions were applied to simplify the model such as that the same
transportation vehicles were applied for all scenarios and distances between every step of
manufacturing, reprocessing and bottling process were assumed to be same for every
scenario, the data support the advantage of using recycled PET. Among damage
categories, human health represent several midpoint categories such as human toxicity

(carcinogenic and non-carcinogenic effects), respiratory effects (inorganics and organics),

l7

ionizing radiation, and ozone layer depletion [31]. Ecosystem quality is composed of
terrestrial acidification, terrestrial nutrification, and land occupation. The global warming
was considered as a stand-alone endpoint category affected by carbon dioxide. The two
midpoint categories contributing to resources were mineral extraction and non-renewable
energy consumption [31]. The results indicate that 50% recycled PET contents in PET

sheets reduce approximately 15 to 18% of value of each damage category.

 

100

80-

60-

40»

Relative percentage

20]-

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0

 

Human Health Ecosystem Quality Climate change Resources

Figure 2-8. Comparison of damage categories for production of 100V, 50V50R, 100R
PET bottle; 100V PET bottle E] , 50V50R PET bottle I, 100%R PET bottle

Table 2-4. Values of damage categories for 100V, 50V50R and 100R PET bottle

 

 

 

Human Health _ 6 Ecosyste‘rén quality Climate chan e Resources A
(DALY*)>< 10 (PDFXm xyr/kg ) (kg C02 69 ) (MJpnmaw )
100V 3.80 0.141 . 3.95 93.3
50V50R 3.21 0.191 3.34 76.1
A 100R 2.61 0.096 2.73 58.9

 

* Disability Adjusted Life Years
1:1 Potentially Disappeared Fraction over a certain area and during a certain time per kg of
emitted substance

V Amount of C02 eq that equal the impact of a considered pollutants into the air
A Amount of additional primary energy required per unit of mineral and of total non-
renewable primary energy for energy carriers

2. 4 Management method of PE T

In the mid 19805, the majority of municipal solid waste (MSW) management was
landfill, accounting for 88.6% of total MSW. Soon, theiland used for MSW became a
public environmental issue, and plastic packaging industries were a major target of
proposed legislation due to large fraction by volume of materials and poor
biodegradability [2]. Furthermore, in some other countries such as most European
countries and Japan in Asia, this problem was much more serious than in the US. due to
lack of available land. In order to minimize landfill disposal, incineration and recycling
were considered as alternative methods. However, in the late 19805 and early 19905, the
effort on the incineration resulted in many failures due to public concern about heavy
metals in incinerator ash, and the poor economical efficiency to build and manage these
facilities. In consequence, source reduction and recycling were rapidly increased, and
packaging materials were the primary initial target.

According to the report of the Environmental Protection Agency (EPA).

integrating waste management strategies, such as source reduction (or waste prevention),

recycling, combustion with energy recovery and disposal through landfills (Figure 2-9),
are still ongoing [32]. Source reduction has the effect of reducing MSW generation,
whereas other management methods just deal with MSW once it is generated. Figure 2-
10 indicates that total MSW generation of US. is about 254 million tons of trash and
recycled and composted 85 million tons of this material, equivalent to a 33.4 % recycling
rate. Among these 85 million tons, 63 million tons were recovered through recycling,
representing 1.9 million tons more than in 2006. Composting recovered almost 22 million
tons of waste [8]. The recovery rate of recycling and composting is continuously
increased, while combustion with energy recovery and landfill of MSW are steady or
somewhat decreased since the mid-19805 (Figure 2-11) [8].

Generation of waste for

 

 

management
r-WW —-—--—----~ --—----—~-~-—- 3 WW1
} Changesin T F Changes in 1‘ Changes in l ZTRecoveryforrecycling 1
'package designl purchasing habits J [industrial practices] :1 (including composting) I

 

 

._ _--__l ._,-m L--,___-_ l - -_l _ __-_ _-.__--..
i T Fl 2 C Landfill/Other 3

I I I 3 disposal i
[_._.___.. ~——~j ——- u--- -.-._ ____1: -_-_ l __ -_.._--___-__-

 

 

 

 

Backyard composting] Increased l ; Other changes in 1 ; lCombustion with
l grasscyling J reuse l I use patterns ' i energy recovery
__-.-,_.__._,___ a- - -_--__ - l _ ._ ._.__- . __ .-___ __ _
SOURCE REDUCTION
WASTE REDUCTION

Figure 2-9. Diagram of solid waste management [32]

20

 

MSW (million tons)

 

 

 

:1 Total MSW generation . - -. i 35
Total MSW recycling _

Kl

 

 

+ Percent recycling
fl
- 25

 

 

N
0
Percent recycling (%)

 

 

 

 

 

 

 

 

 

m

 

1960 1970 1980 1990 2000 2007

Figure 2-10. MSW generation, recycling and % recycling in US, 1960 to 2007 [8]

300

250

200 -

150

Million tons

 

 

i—l
O
O

M
O

  
       

MSW generation

 

Recovery for combusting
with energy recovery

 

Landfill. other disposal

0
1 960 1970 1980 1990 2000 2004 2007

Figure 2-11. Municipal solid waste management, 1960 to 2007 [8]

21

2. 4. 1 Packaging in municipal solid waste
Data of waste generated in 2007 by product items by weight is shown in Figure 2-
12 [8]. Containers and packaging made up the largest portion of waste generated, 30.9 %,

or 78 million tons.

Food Scraps
12.5 %

Containers and Packaging

30.9 %

     
  

Yard Trimmings
12.8 %

 

Nondurable Goods
24.5 %

Durable Goods
17.9 %

Other Wastes
1.5 %

Figure 2-12. Total MSW generation by category, 2007 [8]

22

As shown in Table 2-5, total MSW recovered was about 33.4 % in 2007. Steel,

paper products and aluminum were the highest recycled materials. Therecycling

percentage for steel packaging (mostly cans) was more than 64 %, and 62 % of paper and

paperboard containers and packaging was recycled. In the case of aluminum packaging, it

was recycled at a rate of 39 % [8]. Among the 11.7% recovery of plastic packaging waste.

PET soft drink bottle (including water bottles) was the highest recovery rate at 36.6 %,

and HDPE milk and water bottle was the next highest recovery rate at 28 % [8]. There are

several reasons that the recovery rate of plastic packaging is relatively smaller than other

packaging materials. One reason is that the recovery process requires that plastic

materials undergo decontamination [33]. Another reason is that present recycling, sorting

and cleaning techniques cannot handle all kinds of plastic packaging because many

common packages do not consist of a single-type polymer but rather of polymer mixtures

or copolymers.

Table 2-5. Generation and recovery of products in MSW, 2007 [8]

 

 

 

 

Weight Weight

Products Generated Recovered Recovery

(millions of (millions of (%)

tons) tons)

Steel _ 13.0 3.55 _ 27.3
Aluminum 1.26 Negligible Negligible
Glass 2.] 1 Negligible Negligible

Durable Plastics 10.5 0.50 4.8

goods Rubber and leather 6.48 1.10 17.0
Wood 5.63 Negligible Negligible

Textiles 3 .33 0.46 13.8

Other materials 3.17 2.38 75.1

Total durable goods 45.4 7.99 17.6

Nondurable Paper and paperboard 43.1 20.3 47.1

 

 

 

 

 

 

 

80°95 Plastics 6.68 Negligible Negligible
Rubber and leather 0.97 Negligible Negligible
Textiles 8.34 1 .44 1 7.3
Other materials 3.15 Negligible Negligible
Total nondurable goods 62.2 21.8 35.0
Steel 2.68 1.73 64.6
Aluminum 1.87 0.73 39.0
Glass 11.5 3.22 28.1
Containers Paper and paperboard 39.9 24.9 62.4
and. Plastics 13.6 1.59 11.7
packaging
Wood 8.54 1.32 15.5
Other materials 0.31 Negligible Negligible
ESELE’P‘I‘EPPC“ and 78.4 33.5 42.7
Food, other 31.7 0.81 2.6
Other Yard trimmings . 32.6 20.9 64.1
wastes Itvligféllaneous inorganic 3 .75 Negligible Negligible
Total other wastes 68.0 21 .7 31.9
Total municipal solid 254.1 85.0 ‘ 33 .4

waste

Table 2-5. (Continued)

2. 4.2 Source reduction of PE T packaging

Source reduction, called “waste prevention,” is defined by the EPA as “any

change in the design, manufacturing, purchase, or use of materials or products (including

packaging) to reduce their amount or toxicity before they become MSW. Prevention also

refers to the reuse of products or materials” [8]. Source reduction can be achieved by a

broad range of activities by private citizens, communities, commercial establishment,

institutional agencies, and manufacturers and distributors [8]. Redesigning products or

packages to reduce the amount of materials by replacing lighter materials for heavier

ones is one of the examples of source reduction actions. Reusing products or packages is
another action. Redesigning and reusing are considered better, according to the EPA, than
recycling because the product does not need to be reprocessed before it can be used again.

The efforts on refilling and light weighting of PET bottles are good examples.

2. 4. 2.1 Lightweight

The lightweighting of PET bottles started in the mid 905 with developments in
PET resin technology and conversion equipment. By the mid 905, 2-liter, 1.5-liter and
500 ml PET water bottles were 58, 40 and 22 g, respectively. By 2006, the lightest 1.5-
liter PET water bottles weighed 30 g, and 2-1iter PET water bottles were 47 g, while 500
ml bottles had slimmed down to 12.5 g [34-35]. In the last few years, the concern 0f
lightweighting has continually increased as one of the source reduction actions.

Lightweight PET bottles must satisfy bottle specifications. Table 2-6 shows
energy and material saving of lightweight PET bottles compared to traditional PET
bottles.

Table 2-6. Energy and material saving of lightweight PET bottles compared to traditional
PET bottles [36]

Per million 500 ml PET Per million 2 liter PET

 

bottles bottles
(Using 20g rather than 25g (Using 40g rather than 42g
. preforms) preforms)
PET weight savings 5 tonnes 2 tonnes
PET material cost savings at $6,503 $2,601
$1,300/t .
Carbon emission savings 0.41 tonnes 0.10 tonnes
Energy savings 4,133 kWh 1,653 kWh

 

25

In theory, lightweighting involves removing weight from the neck finish area and
the body. However, in practice, there are several issues, especially for lightweight PET
bottles [35]. One of the problems is that product rigidity and top load resistance is
decreased with decreasing wall thickness. Another possible problem is nesting of
preforms (body of preform is less than opening of the neck) in the blow stage. Moreover,
decreasing bottle weights affects not only bottle production and product filling speed but
also shelf life of bottles. In order to solve these issues, three major technologies can be
applied in practice. Redesigning preform shape, moulds and injection-stretch blow
machine can be one of the technologies. Another technology is to develop a new PET
material that is able to achieve light weighting along with improved processing and
barrier performance. Eastman chemical introduced a new PET resin series named
“Vorcalor PET CB1 1E,9921W, and AQUALOR PET 18696,” which can get up to 30 %
energy saving and is very compatible with recycling processes [3 7]. The third developing
technology is preform re-heat profile in an IR oven that obtains a perfect heat distribution
between the inside and outside temperature of the preform, and the PET bottle can
achieve the same stiffness at reduced material thickness. Table 2-7 show commercialized

lightweight PET bottles by company.

26

Table 2-7. Examples of lnght bottle productions with company [3 8-40]

 

 

 

 

 

 

 

 

Company Product Description
Colgate- Sofisoapé hand soap 50% weight reduction compared to like-
Palmolive pouch refill » sized PET bottle
Easterform 500 ml CSD bottle (25 g to 20g)
Packaging CSD homes 2 L cso bottle (42g to 40g)
0 ' ' ..
Kraft Salad dressing PET bottle 19 /0 weight reduction by process
refinement
o . .
CSD bottles 23 /o.less PET in 600 ml CSD bottles in
Mexrco
Coca-Cola Dasani water bottle 35% less PET in 500 ml Dasani bottle
Cap for PET bottle 38% smaller cap for PET bottles
Sidel NoBottle ' 9.9 g per 500 ml bottle
Krones PET lite 6. 6 6.6 g per 500 ml bottle (lightest bottle on
the market)
. . 16 g per 500 ml bottle compared to
Filmatlc - traditional 26g
2. 4. 2. 2 Reuse and refill

In the US. today, most consumer packages are not designed to be returned for
reuse because the design and implementation of the collection, return and cleaning are
not considered. Two-thirds of consumer packages are landfilled, and the remaining one-
third are reprocessed and recycled into new products. Not too long ago, refilling systems
gained popularity as a more efficient way of handling used containers, especially
beverage containers, than recycling systems. In some European countries, refillable PET
bottles are common for soft drinks, water and beer. One of the most general refillable
PET bottles is the 1.5 liter soft drink bottle, which has enabled refilling system to
package beverages in plastic that is more light-weight than glass or metal, shatterproof

for handling, and multi-serve containers in distribution level. Table 2-8 indicates costs of

500 ml. refillable and one-way glass and PET beverage containers in Europe.

27

Table 2-8. Costs of 500 ml refillable and one-way glass and PET beverage containers in

 

 

Europe [41]

Type Congilrlirzrsfost Trips /Li fe Producgfiir ((583350 Trip
Refillable Glass Bottle 0.103 20 0.005
Refillable PET Bottle 0.133 20 ' 0.007
One-Way Glass Bottle 0.047 1 0.047
One-Way PET Bottle 0.069 1 0.069
Aluminum Can 0.103 1 0.103

 

However, even though refilling system have many advantages, such as increasing
cost benefit and decreasing environmental burden, the beer and soft drink industries in
the US. have dismantled their refilling systems. “While American soft drink companies
have replaced refillable glass bottles with single-use plastic bottles and aluminum cans in
the US, they have been using state-of-the-art refillable containers in many European and
Latin-American countries [41].” In many European countries and some Canadian
provinces, policies to promote or require the use of refillable beverage containers have
been enacted since the 19705. Table 2-9 shows refilling rates and legislations for refilling

system in some of European countries, and some Canadian provinces.

28

Table 2-9. Refillables as a portion of total beverage sales and policies in some countries
[41]

Soda Beer Policies

 

Prince Edward Island 100% 100% Bans non refillables

 

 

 

 

(Canada) .

Ontario (Canada) NA 81% ~9¢ tax on one-way beer container

Quebec (Canada) NA 800/ No more than 37.5% of beer can be in
o one-ways

Finland 98% 73% Levy on one-way containers

Denmark 90% 100% Banned cans and required refillables

for domestic soda/beer

 

Cannot substitute one-way for

 

 

The Netherlands :3; 100% refillables unless environmental
o impact is same or less
72% most be packaged in refillables or
_ 0 0
Germany 75 /° 75 /o be subject to mandatory deposits
U.S. <3% <5%

 

2. 4. 3 Recycling of PE T packaging

Recycling has environmental benefits at every stage in the life cycle of PET
packages [8]. Recycling reduces air, and water pollution and greenhouse gas emissions.
In the US, 85 million tons of MSW were recycled, and 680 thousand tons of PET MSW
were recycled [8]. Recycling 85 million tons of MSW provides an annual benefit of 193
million metric tons of CO2 equivalent emission reduced, representing the emissions from
35 million passenger cars [8]. However, some barriers exist in increasing plastic
recycling systems. Consumers’, municipalities’ and manufacturers’ lack of understanding
about the benefits provided by recycling systems is one of the obstacles. Many consumers,
municipalities and manufacturers continue to be unaware of the significant benefits.
demand, and value of recycled plastic. Another barrier to increased recycling is lack of

sufficient access to recycling collection opportunities for post-consumer products.

29

2.5 Legislation of PE T recycling for food use

Food-contact plastic packaging made from recycled plastic must ensure that
recycled plastic has suitable purity and performance of virgin plastic. The 21 Code of
Federal Regulation (CFR), Parts 174 through 179, shows the framework for testing and
evaluation procedures for each type of recycled plastic and recycling system [42]. This
guidance document recommends the maximum level of a chemical contaminant in the
recycled material that would result in an estimated daily intake (EDI) that does not
exceed 1.5 micrograms/person/day (0.5 ppb dietary concentration (DC)). This is the level
that FDA would generally consider to be of negligible risk for a contaminant migrating
from recycled plastic for food application. The guideline also recommends surrogate
contaminants for use in evaluating a recycling process based on volatility and polarity
(Table 2-10).

Table 2-10. Examples of recommended surrogates [:12]

 

Volatile Non-volatile
Chloroform
Polar Chlorobenzene Benzophenone
l .1 , 1 —Trichloroethane Methyl salicylate
Diethyl ketone
Tetracosane
Lindane
Methyl stearate
Non polar Toluene Phenylcyclohexane

l-Phenyldecane
2,4,6-Trichloroani sole

The FDA provided letters of non-objection for recycling process of PET if they
could be shown to remove all surrogates to less than the 0.5 ppb dietary concentration
level. Generally, letters of non-objection for PET can be categorized into 3 different

groups (Table 2-11). By December 2008, 85 letters of non-objection for PET had been

30

issued [43]. In case of chemically recycled PET, FDA letters of non-obj ection were
issued to virgin PET producers for chemical processes as methanolysis and glycolysis.
Physical recycling of PET is considered a better option than chemical recycling due to
less controlled sources of recycled resin and less extreme recycling processes. Most non—
objection letters for physical recycled PET for food contact were issued for processes
with special cleaning steps, high temperature treatments and solid stating to optimize
contaminant removal from the recycled polymer. In addition, in 1993, the FDA provided
a letter of non-objection to Continental PET Technologies for the use of a trilayer PET
container having recycled material as a middle polymer layer [44]. The internal food-
contact layer serves as a functional barrier to contaminant migration from the bulk
recycle layer in the center of the container wall [44].

Table 2-11. US FDA no objection letters, until December 2008 [43]

 

 

Subjects No objection letters
Chemically recycled PET for food contact 18
Physically recycled PET for food contact 54
Multilayer technology 13
2.6 Recycled PET

The first recycling effort of PCR—PET (Post Consumer Recycled PET) bottles in
the world was in 1977 [45]. As a result of environmental concerns, PET recycling
industry started to improve PET waste management strategy. Another driving force for
PET recycling industry is that PET products have a very slow rate of natural
decomposition [46]. PET is a non-degradable plastic in normal conditions since no
organism can consume its large molecules. Therefore, recycling processes are the best

way to economically reduce PET waste [47]. Since the price of virgin PET remains and it

31

should continuous to be high as explained in section 2.3.3, new and cheaper technologies
for recycling PET can generate large value for the PET recycling industry. Recycled PET
flakes must meet certain requirement to be used [13, 24]. Table 2-12 shows the minimum
requirement for the PCR-PET flakes.

Table 2-12. Minimum requirements for PCR-PET flakes to be used for sheet applications

 

 

[13, 24]

Property Value
[11], dl/g >0.7
Tm, °C >240
Water content, wt.% <0.02
Flake size, mm 0.4< D < 8
Dye content, ppm <10
Yellowing index <20
Metal content, ppm <3
PVC content, ppm <50
Polyolefin content, ppm ' ' <10

 

2. 6.] Collection

Before recyclable materials are reprocessed to be new products, they must be
collected. There are several types of residential collection systems, such as curbside
recyclables collection, drop-off programs, buy-back operation, and container deposit
systems. Collection of recyclables from commercial establishments is usually not counted
as residential recyclables collection. In 2007, more than 8,600 curbside recyclables
collection programs were reported in US, nearly 60 % of the US. population with
access to curbside recyclables collection programs [8]. Table 2-13 indicates the number

and population served by curbside recyclables collection programs. Table 2-13 also

shows how residential curbside recycling programs are distributed to various regions,
with the most extensive curbside collection occurring in the Northeast.

Table 2-13. Number and population served by curbside recyclables collection programs
in the US. 2007 [8]

 

 

 

Region Number Of Population Population Served

programs

(in thousands) (in thousands) %

NORTHEAST 3,299 50,557 42,592 84%
SOUTH 797 84,524 25,386 30%
MIDWEST 3,749 46,473 28,236 61%
WEST ' 814 63,985 48,702 76%
Total : 8,659 245,539 144,916 ‘ 59%
Tom] U:S° 301,621
Population

 

In case of drop off centers, located in grocery stores, sheltered workshops,
charitable organizations, city-sponsored sites, and apartment complexes, can accept more
materials than curbside collection programs. In the US, 12,694 programs were estimated
in 1997 [8]. In 2007, it was estimated that over 20,000 communities have drop—off centers
[48].

A buy-back center is operated commercially. Scrap metal dealers, aluminum can
centers, waste haulers, or paper dealers pay individuals for recovered materials. Materials
are collected by individuals, small businesses, and charitable organizations.

To date, eleven states have container deposit systems: California, Connecticut.
Delaware, Hawaii, Iowa, Maine, Massachusetts, Michigan, New York, Oregon, and
Vermont. In these programs consumer pays a deposit on beverage containers at the point

of purchase, which is redeemed on return of the empty containers. Generally, deposit

33

systems were planned for beverage containers, especially beer and soft drink, which

account for less than 6 % of total MSW generation.

2. 6. 2 Recyclables processing of PE T

Afier collecting recyclable materials containing PET, they must be sorted, washed
and ground to remove label, aluminum, adhesive and other plastics before producing
recycled PET products. These processes are performed at materials recovery facilities
(MRFs) and mixed waste processing facilities [8]. Generally, reprocessing technologies
are composed of sortation, granulation, air classification, washing, flotation, drying and
electrostatic separation. At the sortation step, bales of unsorted PET bottles are screened
by color and polymer type. The dirty, sorted PET bottles are first reduced to 0125-0375
inch flake by granulation [20]. After that, those flakes are delivered to air classification to
remove labels. Basically, most labels are removed from PET flakes by granulation and air
classification generally by using a hydrocyclone. The washing step removes the last
traces of label material and disperses and dissolves the adhesives. Cleaned flake or chip
moves into a flotation tank which separates the heavy PET and aluminum from light
HDPE in a water medium [20]. After drying, the dried and cleaned PET and aluminum

chips are fed into an electrostatic separator to remove aluminum chips.
2. 6. 2.1 Materials recovery facilities (MRFs)

Materials recovery facilities are distributed widely across the US. In 2007, 567

MRFs were operating in the US, with an estimated total daily throughput of over 91,000

34

tons per day (Table 2-14) [8]. The most extensive reclaiming process occurs in the
Northeast and West.

Table 2-14. Material recovery facilities in US, 2007 [8]

 

 

 

Region Number 52123322188288“
NORTHEAST 146 24,848
SOUTH 158 20,905
MIDWEST 138 20,455
WEST 125 25,242
us. Total 567 91,450

 

2.6.2.2 Mixed waste processing

The number of mixed waste processing facilities is smaller than conventional
MRFs. Mixed solid waste (including recyclable and non-recyclable materials) is
delivered to mixed waste processing facilities. Recyclable materials are removed by
mechanical and manual sorting. In 2007, there were reported 34 mixed waste processing
facilities in the US, handling about 43,000 tons of waste per day [8]. The largest number
of these processing facilities is located in the Western region of the US. representing

over 80 % of the daily per capita throughput [8].

2. 6.3 Conventional recycling process
Once the PET bottles are collected and reprocessed, two major processes have
been applied to PCR-PET flakes. These processes are chemical recycling (feedstock

recycling) and mechanical recycling.

35

2. 6. 3. 1 Chemical recycling

As shown in Figure 2-l, esterification and trans-esterification reactions are
reversible (depolymerization). The chemicals used for depolymerization of PET include
water (hydrolysis), methanol (methanolysis) and EG (glycolysis). For hydrolysis, PCR—
PET flakes are treated with water in excess at an elevated temperature of 150-250 0C in
the presence of sodium acetate as a catalyst to produce TPA and EG in four hours (Figure
2-13 (a))[20]. Acids or bases are used as catalyst to enhance the hydrolysis reaction [20].
An acid catalyst will promote the hydrolysis in 10-30 minutes at 60-95 0C [20]. In
methanolysis, PCR-PET flakes are treated with an excess of methanol and 1:4 volume
ratio (PET: methanol) to produce DMT and EG (Figure 2-13 (b)). A typical methanolysis
process is performed with a catalyst at 160-240 0C under a pressure of 20-70 atm for less
than an hour [20]. If PCR-PET flakes are recycled with an excess of a glycol, glycol ysis
process occurrs to produce BHET (bis-(hydroxyethyl)terephthalate) and EG (Figure 2-13
(c)). Typical catalysts are amines, alkoxides, or metal salts of acetic acid [20]. Glycolysis
reactions are performed at 200 °C for over 8 hours with an EG/PET ratio of 1.521 [20].

The main disadvantage of chemical recycling is its higher cost than mechanical recycling.

36

High temp
PET + HQO > TPA + EG-

High pressure

 

(a)

High temp
PET + CH3OH2 + DMT + EG

High pressure
0))

 

High temp
PET + EG > BHET+ EG

High pressure
(C)

Figure 2-13. Depolymerization of PET: (a) Hydrolysis (b) Methanolysis (c) Glycolysis
[19, 22]

 

2. 6. 3. 2 Mechanical recycling

PCR-PET flakes can be processed by normal extrusion systems. However, unlike
chemical recycling, PCR-PET flakes for mechanical recycling may contain contaminants.
which are not removed during reprocessing and cause degradation reactions. At the
processing temperature (280 0C), PCR-PET flakes undergo thermal and hydrolytic
degradations. Hydrolysis reactions occur between water and PET resulting in shorter
chains with acid and hydroxyl-ester end groups (Figure 2-14 (a)). The thermal cleavage
of the PET ester bond also results in Shorter PET chains with acid and vinyl ester end
groups (Figure 2-14(b)) [14, 25]. Therefore, the main disadvantage of mechanical

recycling is the reduction of molecular weight and intrinsic viscosity during processing.

37

On the other hand, the main advantages of mechanical recycling are simple process,
environmentally friendly and low investment.

PET

High temperature H20

c\ c\\

O O
Carboxyl acid end group Hydroxyl-ester end group
(a)
PET
High temperature
OH CH QC 112

/
C \ + \\
\O O
Carboxyl acid end group Vinyl ester end group

(b)

Figure 2-14. Degradation of PET: (a) hydrolysis (b) thermal degradation [14, 25]

2. 6. 4 Effects of contaminants on recycling of PE T
Quality of recycled PET mostly depends on its intrinsic viscosity, aluminum

content, and color. These properties are affected by contamination of PCR-PET flakes.

38

Minimizing the presence of these contaminants leads to better recycled PET quality [7].
Recycled PET can be contaminated with various substances, such as PVC, adhesives.

labels, fragments of colored bottles, water and acetaldehyde.

2. 6. 4.] Acid producing contaminants

The most troublesome contaminant in recycled PET is the adhesive [20].
Typically, adhesives produce acids, such as rosin producing abietic acid. Another acid
producing contaminant is PVC which generates hydrochloric acid. Acetic acid is
produced by poly (vinyl acetate) closure degradation [6, 17, 49]. These acids promote the
chain scission reactions during melt processing of PCR-PET . Especially, the presence of
small amounts of PVC increases PCR-PET flakes chain scission clue to the catalytic
effect of hydrogen chloride during degradation of PVC [16]. The presence of PVC also

causes discoloration of PCR-PET during processing.

2. 6.4.2 Water

As shown in Figure 2-14 (a), the presence of water causes a hydrolysis reaction to
reduce molecular weight and intrinsic viscosity. In order to prevent hydrolysis reactions,
moisture content must be below 0.02% [49]. Most of the water can be removed by proper

drying during reprocessing of PCR—PET.

2. 6. 4. 3 Coloring contaminants
Discoloration of PCR-PET can occur not only due to the presence of PVC, but

also fragments of colored bottles and printed ink labels. By proper sorting and washing

39

processes, discoloration due to fragments of colored bottles and printed ink labels can be

reduced.

2. 6. 4.4 Acetaldehyde

Acetaldehyde is also a degradation product in recycled or virgin PET, and is a by-
product of hydrolysis degradation reactions of PET. Due to the migration of acetaldehyde
into food products, the presence of acetaldehyde can be a serious problem when recycled
PET containers are made for food contact applications. However, acetaldehyde can be

easily removed by processing under vacuum or by drying, due to its high volatility [49].

2. 6. 4. 5 Other contaminants
Since PET containers are containing not only food and beverage but also other
substances such as detergents, fuel and pesticides, the remains of these substances can

cause health hazards if these substances remain after PCR-PET recycling.

2. 6.5 End use applications ofrecycled PET

In 2007, a total 862 mm lbs were used for the primary conversion categories of
recycled PET [I]. In addition, U.S. reclaimers sold 38 mm lbs to secondary markets.
including exporters, for a total of 900 mm] bs of recycled PET end use consumption
(Table 2-15) [1]. Among 900 mm lbs, US. and Canadian reclaimers supplied about 744
mm lbs which was mainly produced from post consumer bottles [1]. The remaining 156
mm lbs was imported from reclaimers all over the world, including France, Italy. India,

China, Mexico, Brazil, Peru and other Central and South American countries [1]. Figure

40

2-15 indicates that the sheet converters increased their purchasing of PET by 73% over

2006. The use of recycled PET in industrial strapping continued to grow by 9% compared

to 2006 while recycled PET use in bottles also increased but at a much lower rate [1].

Table 2-15. U.S. consumption of recycled PET as different product categories [I]

 

 

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Fiber 415 417 452 435 344 296 479 463 422 383
Sheet & Film 89 68 65 37 18 32 58 71 74 128
Strapping 67 80 101 82 83 77 116 131 132 144
Engineered Resin 30 26 27 24 10 10 12 8 9 l l
F°°d & Beverage 52 68 54 77 86 106 126 1 15 139 136
Bottles

Non-Food Bottles 47 50 40 44 43 24 63 63 49 60
Other 7 9 5 2 4 7 24 13 30 38
Total US.

CONVERTER 707 718 744 701 588 552 878 864 855 900
CONSUMPTION

 

4l

500

 

 

 

’5?

:9 400 ~

E

E

'5

3 300 -

::

E—< V /
Lu / /
O-t A/ /
“U

.2

g 100 -

O

Q)

a:

0

 

 

Figure 2-15. U.S. converter consumption of recycled PET as different product categories
[I ]; Fiber (0), Sheet & Film (0), Strapping (V), Engineering resin (A), Food & Beverage
bottles (I), Non-food Bottles (13), Other (0)

42

3. METHODOLOGY

3.1 Materials

Feedstocks of 100% virgin PET (V) and 100% post-consumer recycled PET (R)
(RPET were blended to create ratios Of 0, 20, 40, 60, 80 and 100% RPET in a plant trial
conducted at Peninsula Packaging Company (Exeter, CA, USA), Virgin PET resin was
supplied by Eastman (Columbia, CA, USA) with an intrinsic viscosity of 0.80 :1: 0.02 dl
g". Recycled PET, which is mostly collected by bottle deposit system, was provided by
ECO2 (Modesto, CA, USA),PET Sheets were tested after processing. A detailed

description of manufacturing steps is Shown in APPENDIX A.

3.2 Optical properties

UV-Visible spectroscopy was used to determine the light transmission of PET
sheets with varying percent of virgin and recycled PET. UV analysis was perfomied
using a Perkin-Elmer Lambda 25 (Waltham, MA, USA) with measurements carried out at
480 nm/min and a wavelength range of 190 to 800 nm in transmittance (%) mode. All
results are presented as transmittance values. Five to ten samples were scanned for each
PET sheet with varying percent of virgin and recycled PET contents.

Tristimulus color values of PET samples with varying percent of virgin and
recycled PET contents were obtained using LabScan XE from HunterLab (Reston, VA,
USA) and were converted by the instrument to Hunter L*, a*, b* values. ‘L*’ value
indicates the level of light and dark, the ‘a*’ value redness or greenness, and the ‘b*‘

value yellowness or blueness. The maximum ‘L*’ is 100, which would be a perfect

43

reflecting diffuser. The minimum ‘L*’ would be zero, which would be black. A positive
‘a*’ is red, and negative ‘a*’ is green. Positive ‘b*’ is yellow, and negative ‘b*’ is blue.
AE indicates the total color difference which takes into account the differences between
the ‘L*’, ‘a*’ and ‘b*‘ of the sample and standard. 100% virgin PET (V) was assumed to
be the standard, and was compared with varying percent of virgin and recycled PET
Sheets for AE. AE was calculated with Equation (3.1) [50]. Five replicates were measured

and averaged.

 

A13=xlAL2+Aaz+Ab2 (3“

Where AL : L Sample " L Standard» A3 I a Sample " a Standard and Ab 2 b Sample " b Standard

3.3 Mechanical properties

Dynamic mechanical analysis (DMA) was utilized to analyze the thermo-
mechanical properties Of PET sheets with varying percent of virgin and recycled PET
contents. A DMA 0800 from TA Instruments (New Castle, DE. USA) was used.
Samples with a width of 4.8 -— 6.0 mm and a length Of 17-20 mm were cut and tested with
a tension mode clamp and 0.010 N preload force applied. The frequency was 1 Hz. These
measurements were carried out at a heating rate of 5 °C /min and a temperature range of -
80 to 150°C under the DMA-multi-frequency strain. The glass transition temperature was
determined from the storage modulus, loss modulus and loss tan delta. Each treatment
was replicated three times per Sheet.

A Universal Material Testing Machine was used to analyze the tensile and break
strength, break elongation, modulus of elasticity and energy to break by using a Universal

Material Testing Machine 5560 series (Dual Column Models) from Instron (Norwood,

44

MA, USA) in accordance with ASTM D 882 [51]. Samples with a width of 25.4 mm
were cut and tested at 508 mm/sec with 50.8 mm of gauge length. Five samples were

measured and averaged.

3.4 Thermal properties

A differential scanning calorimeter (DSC Q100, TA Instruments, (New Castle,
DE, USA)) was used to determine the thermal properties of PET Sheets with varying
percent of virgin and recycled PET contents. Every sample was tested under a
heat/cool/heat cycle between 40 to 300°C at a rate of 10 °C /min with a nitrogen
atmosphere. The weight of the samples ranged between 12 - 17 mg. The glass transition
temperature (Tg), onset of cold crystallization temperature (ch onset), cold crystallization
temperature (ch), onset of melting temperature (Tm onset) and melting temperature (Tm) of

the samples were recorded. ch onset and ch were taken from the first heating run, and TE.
TIm On,“ and Tm were Obtained from the second heating run. The percent of crystallinity, XL.
for samples was calculated from the Equation (3.2).

AHm —|AHC|

gc(wt.%) =100x
A173,

 

where AH m is the heat of melting, and AH c is the heat Of crystallization, and AH 31 is

the heat offusion of100% crystalline PET ( AHg, = 140 J /g ) [15].

45

3.5 Barrier properties
The water vapor transmission rate (WVTR) was measured with a PermatranTM

C3/31 (Modern Controls Inc., Minneapolis, MN,) according to ASTM F1249 [52]. The

testing temperature was 37.8 °C with 100% RH. All measurements were performed in

triplicate for all samples. The WVTR values were used to calculate the water vapor

permeability fi'om Equation (3.3).

Water vapor transmission rate (q) x thickness‘(_l)_

partial pressure (Ap)xtime (sec)xarea(m2 )

 

Water vapor permeability = ( 3 , 3)
The oxygen transmission rate (OTR) was measured using an Illinois 8001 system
(Illinois Instruments Inc., Johnsburg, IL, USA). The test was performed in accordance
with ASTM D 3985 [53]. The temperature and relative humidity were 23 °C and 50% RH.
All PET sheet measurements were performed in triplicate. OTR values were used to

calculate the oxygen permeability value from the Equation (3.4).

Oxygen transmission rate (q) x thickness (1)

 

Oxygen permeability = (3,4)

partial pressure (Ap)xtime (sec)xarea(m2 )

3. 6 Nuclear Magnetic Resonance (NMR) Spectroscopy

NMR spectra were Obtained on a Varian VXR-500 FT Spectrometer (Chemistry
Department, Michigan State University). IH Spectra were at 500MHz. PET sheets with
varying percent Of virgin and recycled PET contents were dissolved in a ratio of 2 to 1
mixture of trifluoroacetic acid/chloroform solution by volume. These mixtures dissolve

the high molecular weight polyesters to analyze the end group signal at ambient

46

temperature [54]. Chemical Shifts are reported in parts per million from tetramethylsilane.

Samples were tested in triplicate.

3. 7 Viscosimetry

Solution viscosity measurement were carried out using 1C Ubbelhode capillaries
provided by Cannon instrument company (State College, PA,) (Appx.constant: 0.03
mmz/sz, Kinematic viscosity range: 6 to 30 mmz/s) in a mixture of phenol and l, 1, 2. 2-
tetrachloroethane (60:40 by volume) provided by Sigma-Aldrich (St. Louis, M0) at 24 3:
05°C. This test was performed in accordance with ASTM D 445 and D 446 [55-56]. The

intrinsic viscosity, [n] was determined by the Huggins equation (3.5). The viscosity

molecular weight, M—V , was determined by the Mark-Houwink Equation (3.6)

(K = 7.44x10_4dl/ g and a = 0.648 at 25°C) [7].
n
C

[11] =KMS (3.6)

3. 8 Statistic Analysis

One way ANOVA and Tukey's HSD (Honestly Significant Differences) test were
performed to analyze the statistical Significant differences Of the data set from each
experiment (01:0.05). This test was conducted using the SPSS software program, SPSS
Inc. (Chicago, IL, USA).

A stepwise regression analysis was used to develop a model to predict the amount
Of RPET in the samples. The stepwise regression used a mixture Of categorical and

continuous variables to handle partially observed responses [57]. This regression can be

47

carried out in three different ways: forward, backward and stepwise selection. Due to a
relatively small data set, the power was too low to identify important predictors as
statistically significant at the standard significant level (OF-0.05). Therefore, backward
selection was applied in this study with a high significant level (0t=0.15) [58]. Backward
elimination was performed to remove the weakest predictor variable, and to establish the
optimal regression model. The SAS software program, SAS Inc. (Cary, NC, USA) was
used. APPENDIX B explains the stepwise regression analysis and backward regression

analysis with SAS code used for this study.

48

4. RESULTS AND DISCUSSION

4. I Optical analysis
4.1.1 UV - Visible Spectroscopy

Figure 4-1 Shows the constitutional unit of PET. The chromophorie groups in PET
are the benzene ring and the ester group. The ester group (-COOR) absorbs at the 205 nm
wave length through it _. 11‘ transition and q—t n‘ transition, and benzene ring absorbs the
UV-light source at 198 and 255 nm maximum wave length [59]. Therefore, the

absorbance of PET mainly occurred in the ultraviolet region (200~400nm).

\ //O
c 0 CH2
O/ O—CHZ/

Figure 4-1. Constitutional unit of PET

Figure 4-2 indicates that most of the absorbance of PET occurred between 330
and 390 nm. Figure 4-3 shows that there is another peak arising between 675 and 678 nm
where the red light region is located. This might be because of residual contaminants.

especially fragments of green or blue colored bottles and printed ink labels.

49

Transmittance (%)

 

80-

40—

20%

 

 

 

 

IOOV
— — — - 80V20R
60V40R
40V60R
— — — - 20V80R
100R

 

 

 

l l l I I

 

 

3 80 400
Wavelength (nm)

Figure 4-2. Light transmission of PET sheets with varying percent of virgin and recycled
PET contents between 323 and 450nm

Transmittance (%)

 

 

 

 

i

 

94
92- /*’”":.’_~;:*-
wA\ v/fldvi—av "' v“
’v, -~ ’1 ........
...-..-,:?'_::'.:.='.'~'-e""-"‘"" 7'
2"“.T ..— ~ ~' " T" ‘
90 - .- . ,I- I’m! a-
V.o__,’_<_9, '1' ./
Jun-s. 7‘ 7* 7‘ T—u—‘AN
I “mo/If l 100v
88 - \.P_ — — — 80V20R
............. 40V60R
, . _ _ — - 20V80R
20 f 1 ._ ...... 100R
0 L ' ' l L
640 660 680 700 720 740

Wavenumber (nm)

760

Figure 4-3. Light transmission of PET sheets with varying percent of virgin and recycled
PET contents between 650 and 750nm

50

According to Tsai et al. [60], the number, the volume fraction and the Size of the
crystallites contribute to the scattering of the light. Namely, recycled PET contains lead
to lower transmittance because of impurities acting as nucleating agents. However, in this
study, % crystallinity values from DSC Show no statistically significantly differences at 01
= 0.05. Table 4-1 provides the light transmission values for PET and RPET at different
wavelengths. At 350, 380, 676, 677 and 678 nm, there are statistically Significant
differences amongst the light absorption of PET sheets with varying percent of virgin and

recycled PET content.

51

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4.1.2 Calorimeter

Results of color measurement for varying percents of virgin and recycled PE'l‘
content as Hunter L, a, b scale are Shown in Table 4-2. The data show that more recycled
PET contents lead to grayer (‘L*’ decreases), greener (‘a*’ becomes more negative). and
more yellow (‘b*’ increase) of PET Sheets. The data also indicate that ‘L*’, ‘a*’ and ‘b*’
value Of PET Sheets with varying percent of recycled PET contents Show statistically
significantly differences (11:0.05), except ‘L*’ value between 40V60R and 20V80R. b
value between 80V20R and 60V40R, and AE between 40V60R and 20V80R. Since
recycled PET flake may contain fragments Of green or blue colored bottles, this causes
the ‘a*’ value to be more negative. Generally, PET yellowing is associated with thermal
degradation [6]]. During PET processing above its melting temperature, the thermal
cleavage Of the PET ester bond result in Shorter chain with acid and vinyl ester end
groups [6]. The carboxyl end group content generated by PET processing promotes the
oxidation of PET [18]. Namely, repeated recycling processes generate more carboxyl end
groups in PET, and cause more oxidation of PET. Therefore, more recycled PET contents

in PET sheets leads to an increased ‘b*’ value.

53

Table 4-2. Results of color measurement for varying percent of virgin and recycled PET

 

 

sheets

L* a* b* AE
100V 89941002221 -l.l4:1:0.015a 1.10e0.022a 03
80V20R 89.18 a: 0.110 b -129 :t 0.013 b 1.62 :1: 0.047 b 0.93 e 0.08 b
60V40R 88.76 at 0.283 c -1.36 a: 0.019 c 1.55 i 0.015 b 1.28 i 0.26 C
40V60R 87.69 i 0.103 d -1.58 i 0.017 d 2.31 i 0.034 c 2.59 :1: 0.09 d
20V80R 87.60 a 0.168 d -1.65 d: 0.012 e 2.39 :1: 0.061 d 2.72 e 0.16d
100R 86.90 i 0.075 e -1.68 a: 0.005 f 3.10 a: 0.022 e 3.68 a: 0.06 e

 

*Values in the same column with different superscripts are significantly different at

(1:005.

4.2 Mechanical analysis

4. 2.] Dynamic Mechanical Analysis (DMA)

The transition of polymeric materials from the glassy to the rubbery state has long

been recognized as an important material and polymer property [62]. During this

transition, Tg can be Observed from storage, loss modulus and tan delta peak of the

dynamic mechanical test. The storage modulus represents the stiffness Of a viscoelastic

material, and loss modulus is defined as being proportional to the energy dissipated

during the loading cycle. Tan delta is composed of the storage and loss modulus and

determines how well the material can disperse energy. As Shown in table 4-3, it was

found that PET Sheets with varying percent of virgin and recycled PET content show no

statistically significant differences at 95% confidence level.

54

Table 4-3. Maximum loss, tan delta curve and onset of rubbery plateau as temperature

 

 

values
Maximum loss Maximum Tan delta Onset of rubbery
moglulus (o C) plateau
( C) ( C)

100V 849240.96 a 92.524078 a 89.154061 a
80V20R 841241.10 a 92.2041 .40 a 884541.18 a
60V40R 853540.01 a 928340.75 a 895740.16 a
40V60R 840841.05 a 91.594106 3 883541.15 a
20V80R 85.194072 3 92.314091 a 895040.43 a
100R 844840.99 a 922740.93 a 889140.93 a

 

*Values in the same column with different superscripts are significantly different at
a=0.05.
4. 2.2 Universal Material Testing

The percent crystallinity, the size of Spherulites and the molecular weight Of semi-
crystalline polymers, such as PET, affect the mechanical properties of the materials [7].
Usually, crystallization produces a drastic mobility restriction that renders the material
brittle [7]. Table 4-4 indicates that the mechanical properties of varying percent of virgin
and recycled PET sheets show no linear trend; mechanical properties were not a function

of recycled PET content.

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4.3 Thermal analysis

During the first DSC heating run, the onset of cold crystallization temperature and
the cold crystallization temperature were Obtained. The cold crystallization temperature,
ch, is the point where the amorphous area of polymer starts to reorganize itself and turn
into crystalline area. PET Sheets with 100% virgin Show the highest onset 0chC and T“.
Generally, PET Sheets containing more recycled PET contents show lower onset Of ch
and RC. This indicates that more recycled PET content leads to crystallization process at
a lower temperature. During the second heating run, Tg, onset of Tm, Tm and xc were
obtained. According to Torres et al. [7], impurities in recycled PET may play the role of
nucleating agents, facilitating crystallization. However, it was found that the %
crystallinity showed no statistically significantly differences among PET sheets with

varying virgin and recycled PET content (0t=O.05) (Table 4-5).

57

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In order to analyze the intrinsic viscosity of PET Sheets with varying percent of
recycled PET, solution viscosity measurement was carried out. Basically. the
concentration and molecular weight of the dissolved polymer determine the viscosity 0 f a
polymer solution. In order to determine the intrinsic viscosity of a polymer solution. the
Huggins equation was used. In addition, the viscosity molecular weight was calculated
using the Mark-Houwink equation.

Table 4-6 indicates the intrinsic viscosity [1]] and viscosity average molecular

weight My of PET sheets with varying recycled PET content at 24 :t 05°C. All intrinsic
viscosity values were between 0.53 and 0.72 dl/mol. Viscosity molecular weight ranged
from 25,000 to 41,000 g/mol. There were significantly statistically differences in both
intrinsic viscosity and viscosity molecular weight for 100V and 100R PET. It was also
found that the higher the percent Of recycled PET in PET sheets the lower the intrinsic
viscosity and viscosity molecular weight. This reduction of the intrinsic viscosity may be
due to the contaminants of recycled PET, such as retained moisture, adhesive and so on
[63], which generate acid compounds during processing and catalyze the hydrolytic
cleavage of the ester bond to yield carboxylic acid end group and hydroxyl-ester end
group [7]. The impurities in recycled PET contents may induce chain scission processes
that lead to lower intrinsic viscosity and viscosity molecular weight. In addition,

additional heat history also played a role to change the [n] Of PET.

59

Table 4—6. Intrinsic viscosity and viscosity molecular weight

 

Intrinsic viscosity (dl/ g) Viscosity molecular weight (g/mol)
100V 0.72240029 3 40742 4 2052 a
80V20R 069640.022a 38449 4183921
6OV4OR 063040.006 b 32989 4 449 b
40V60R 063140.006 b 33038 4 478 b
20V80R 060740.009 b 31 141 4 695 b
100R 053340.017 c 25479 4 1275 c

 

*Values in the same column with different superscripts are significantly different at
01=0.05

4.5 Barrier properties

Generally, permeability of water vapor and oxygen play a major role in deciding
the protective properties of plastic films and containers. The water vapor transmission
rate and oxygen transmission rate were analyzed for PET sheets with varying percent of
recycled PET. Four replicates were measured and averaged. The last ten points of the
water vapor transmission rate were collected from the machine and averaged for
calculating water vapor permeability values. Table 4-7 Show that water vapor
permeability Of 100V, 80V20R, 60V40R and 40V60R are statistically significantly
different, and 80V20R and 60V40R, and 40V60R, 20V80R are statistically significantly
different (01:0.05) with respect to 100R. In the case Of oxygen permeability results, it was
found that 100V and 60V40R are statistically significantly different, and 60V40R,
40V60R, 20V80R and 100R are not statistically significantly different (u=0.05) (Table 4-

7).

60

Table 4-7. Water vapor permeability for PET sheets with varying percent of recycled

 

 

PET as SI units
Water vapor permeability Oxygen permeability
(ngm/mZXPaXsec) (X1045) (ngm/mZXPaXsec) (x 10-19)

100v 2.734831810’2 a’d 58640.13 3
80V20R 2.52 4 2.88><10'2 b 5.62 4 0.06 a’ b
60v40R 2.58 4 9.85><10'2 b 5.26 4 0.08 c
40V60R 2.65 4 5.54><10'2 c 5.34 4 0.24 b’ C
20V80R 2.72 4 1.97810’2 3’ c 5.32 4 0.06 b’ c

100R 2.7642.21><10'2 d 55440.15 b’c

 

*Values in the same column with different superscripts are significantly different at
a=0.05

4. 6 Nuclear Magnetic Resonance analysis (NMR)

Through the recycling processes, chemical or mechanical, PET can be degraded.
Chemical recycling of PET utilizes depolymerization of PET, and may create bis-
(hydroxyethyl) terephthalate, dimethylterephthalate and terephthalic acid. In mechanical
recycling of PET, degradation reactions of PET occur including hydrolysis and thermal
degradation. PET hydrolysis generally introduces carboxylic acid and hydroxyl-ester end.
groups, and thermal degradation generally produces carboxylic acid end group and vinyl
ester end groups. The 1H NMR spectrum of the 100V PET samples is illustrated in
Figure 4-4. There are four peaks in the spectrum attributed to four kinds Of IH protons.
The most obvious peaks are a singlet at 5 8.2 arising from aromatic protons (a) of the
PET repeat units. Since mixtures of TFA/CDCl3 (2:1) were used as solvents for the PET
samples, trifluoroacetic acid anhydride leads to a rapid esterification of the OH end-
groups. As a consequence, the two CH2 Signals of the ethylene glycol (b) end-groups Shift

down field and coalesce with the main signal at 8 4.8 [64]. The diethylene glycol (c). (d)

6]

signals were remained without change. The small peaks between 5 1 and 2 ppm were

analyzed as impurities Of CDCl3 and residual of moisture, respectively.

 

 

 

 

 

O a a O
b b ~ II II c d
""" OCHchz—O—C C—OCHZ-RHZ
a a O
0 Id
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a m
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{—4 E 3
_.:, c d ;
u e e I
Q R 3
1, U - if V ---___,. ”—__
12 10 8 6 4 2 0 -2 ppm

Figure 4-4. 500 MHz lH-NMR Spectrum of 100V PET samples measured in TFA/CDCI;

Table 4-8 indicates the composition ratio of aromatic protons (a). ethylene glycol
protons (b) and diethylene glycol protons (c), (d) for PET sheets with varying recycled
and virgin PET content. Due to the recycling process, protons of ethylene glycol (b) and
diethylene glycol (c), (d) were considered as indicators for the difference among PET

sheets with varying percent of virgin and recycled PET contents. It was found that

62

protons of end groups in 60V40R, 40V60R and 20V80R PET were statistically

significantly higher than 100V PET.

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4. 7 Stepwise regression analysis

Different kinds of PET sheets with varying percent of virgin and recycled PET
were chosen as the criterion variables. DSC values (Tg, ch, Tm, xc), UV-Visible
spectroscopy (UV350, 380, 678), WVTR, OTR, NMR, Intrinsic viscosity and colorimeter
(L, a and b) results were included as predictor variables. DMA (Tg from storage, loss
modulus, and tan delta peak) and universal material testing results were excluded since
they were no statistically significant differences amongst PET sheets with varying
percent of virgin and recycled PET contents at u=0.05. In order to obtain a good
prediction, the predictor variables should be correlated with the criterion variables.
However, the predictor variables must not be correlated among themselves. Therefore. a
Pearson correlation and a simple linear regression were used to exclude predictor
variables, which were highly correlated with other ones. The upper top part of Table 4-9
indicates the Pearson correlation of predictor variables for PET sheets with varying
percent of virgin and recycled PET. Predictor variables that were not highly correlated
with another predictor variable (r<0.5), are highlighted. Initially, Tm, WVTR were chosen

by Pearson correlation as valid predictor variables.

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In order to make sure that the highly correlated variables were not just excluded
since they may be important predictor variables, and easy to determine experimentally, a
simple linear regression analysis was performed with Tg, Tm, xc, UV380, IV, OTR,
WVTR, intensity ratio of 6 4.2 combined with 4.0 peak (NMR424) and ‘L’, ‘a’ and “b“
values as a function of RPET contents. Good correlation between the predictor variables
with the criterion variable must have p-value <0.05, moderate skewness, and the median
value must be similar to the mean value to comply with the condition of residual
normality.
Table 4-10. p-value, skewness, mean, median for the simple regression analysis for the
predictor variables for PET sheets with varying percent of virgin and recycled PET

content. (a and [3 values for the equation y=a*X+[3 and the normal distribution of the
standard errors are shown in appendix C.)

 

p-value Skewness Mean Median
Tg 0.0504 -0.3450 0.0000 0.1212
Tm” ' ' "“<0.0001"” ' 0.7269 ‘ ' “0.30000 " ”9.0.0374
XC 0.1062 .0.7702 0.0000 0.1556
UV380 <0.0001 p 0.3335 0.0000 0.0141
1ng ‘ <0.0001 _ -O.268_2 0.0000 -0.0148
WVTR 0.2543 0.6301 0.0000 -0.0633
OTR ' 0.0255 ' 0.6791 0.0000 0.1476
NMR424 0.8292 0.0034 0.0000 0.0606
L 0.9774 -0075 0.0000 00915
a 0.7154 0.1656 0.0000 0.0649
"b   0.0004 4.5935 ~ 0.0000 ' V 0.0308 .

._.L;_ .

 

To sum up, Tm, OTR, UV380, W, ‘b’ values were included since the residual are
normally distributed (data not shown). APPENDIX C shows detailed descriptions for
each linear regression. So, those predictor variables were used in the backward stepwise
regression analysis (final predictor variables are highlighted in gray in Table 4-10). Table

68

4-11 shows the backward elimination steps with R-square and adjusted R—square as
goodness of fit indicators. It was found that every model from step 0 to 1 accounts for at
least over 95% of variance in each predictor. By using MANOVA, it was also confirmed
that every model was statistically significant at p< 0.0001.

Table 4-11. Backward elimination sequence for PET sheets with varying percent of
virgin and recycled PET as function of results from each different technique

 

 

Step 0 Step 1
R2 0.9812 0.9809
Adjusted R2 0.9718 0.9740
P value 104.23 (p<0.0001) 141.38 (p<0.0001)
IV (p=0.2180) IV (p=0.1047)
OTR (p=0.0843) OTR (p=0.0162)
Tm (p=0.1479) Tm (p=0.0563)
b (p=0.0382) b (p=0.0031)

UV3 80 (p=0.7215)

 

Table 4-12 indicates the final simple proposed model for determining recycled
PET contents from PET sheets. Figure 4-5 shows the experimental values of PET sheets
with varying percent of virgin and recycled PET contents and the predicted ones, and the
standard residual between these values. APPENDIX C shows the estimated parameters

for each step.

69

Table 4-12. Promsed linear model (PET= a+[3*IV+x*OTR+5*Tm+n *b+e)

 

 

Predictor . 95% confidence interval
. bl Parameter est1mate P value
var1a e Lower bound Upper bound
a 20.317 i 9.885 0.145 41.568 0.064
[3 1.101 :t 0.623 0.196 2.558 0.105
x 0.222 :t 0.078 0.040 0.349 0.016
5 -0.086 9: 0.040 -0.173 -0.004 0.056
I] -0.267 t 0.071 -0.387 -0.102 0.003

 

*Values are expressed as 3(— i std

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4.8 Preliminary verification of the model

For the preliminary verification of the model, one unknown PET container from
Pactiv (Lake Forest, IL) and 3 different kinds of unknown PET sheets from Clearlam
(Elk Grove Village, IL) were requested and tested. Techniques selected in the backward
stepwise regression analysis, intrinsic viscosity, UV-Visible spectroscopy, melting
temperature, oxygen permeability, and ‘b’ value, were used to verify the model. In the
case of intrinsic viscosity, there was no statistically significantly difference amongst the
Pactiv container and the 3 different kinds of Clearlam PET sheets at a=0.05. For the
results of UV-Visible spectroscopy at 380 nm, it was found that only sample A of
Clearlam PET sheets shows statistically significantly difference, compared to Pactiv
container, sample B and sample C of Clearlam PET sheets (01:0.05). The results of the
‘b’ value shows that the Pactiv container is statistically significantly different from
samples A,B and C of Clearlam PET sheets (01:0.05). The results of melting temperature
indicate that sample A and B of Clearlam PET sheets have higher melting temperatures
than the Pactiv container and sample C of the Clearlam PET sheets (a=0.05). Sample A
of the Clearlam PET sheets had lower water vapor permeability value than Sample B of
Clearlam PET sheets. The results of oxygen permeability values indicated that sample B
of Clearlam PET sheets is statistically significantly different with respect to Pactiv and
samples A and C of Clearlam PET sheets (01:0.05). The results of each predictor
parameter for 4 different kinds of unknown PET samples are shown in Table 4-13. Based
on these results, the percentage of PET was predicted using the stepwise regression
model (Table 4-12). Table 4-14 indicates that actual PET contents of sample A of

Clearlam PET sheets was difference with averaged predicted PET percentage of sample

A of Clearlam PET sheets, whereas the actual PET percentage of Pactiv was close to their
averaged predicted PET percentage, and were located within the 95% confidence interval.
The difference between the actual PET percentage of sample A of Clearlam PET sheets
and averaged predicted PET percentage is due to the origin of its RPET flakes as reported
by the company after the test was conducted. Namely, the current generated model was
based on post-consumer recycled PET mostly collected by the bottle deposit system and
recycled mechanically. However, as reported by Clearlam samples A, B and C of
Clearlam PET sheets contained industrial recycled PET from bottle production (This
information was reported after the test was conducted). Pre-consumer recycled PET is not
expected to be contaminated by consumers so it has generally higher quality than post-
consumer recycled PET. In consequence, sample A, B and C of Clearlam PET sheets”

can not be used to verify the model. Further, new samples and analysis will be needed to
verify and validate the model. At this stage, only one sample provide by Pactiv can be
considered as tested to validate the model and the value was predicted betweent the 95%
confidence interval. Further exhaustive testing are needed to determine if the model may
possible predict the recycled PET content in PET sheets. At this time, the model was
developed for a specific mechanical RPET stream provided by the EC 02 company
(Modesto, CA, USA). Therefore. it may not be applicable for other recycled PET streams

and products without new studies.

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75

4. 9 Limitation of the study and the model

As previously explained, the aim of this study was to explore the use of stepwise
regression analysis to determine the amount of recycled PET content, which was
previously recycled by mechanical recycling, in PET/RPET sheets. Therefore, few
limitations should be stated about this study.

a- The model was developed only considering a single recycled PET stream
obtained from the bottle deposited program and provided by the EC ()2
company (Modesto, CA, USA) and one virgin PET stream supplied by
Eastman (Columbia, CA, USA) with an intrinsic viscosity of 0.80 i:
0.02 dl g".

b- The model was not properly validated between for different batch from the
same company. This should be conducted to understate if the model can
predict the amount of RPET for the same providers but a different
industrial batch.

c- The model was not properly validated with unknown sarnples from the
industry since only one unknown RPET samples could be tested with 20
to 30 % RPET. Therefore, further validation is needed.

d- The model does not consider postindustrial PET content as feedstock;
therefore, it should not be tested outside the design domain of the model.
At this stage, this model is not applicable for other recycled PET

streams and products without new studies.

76

5. CONCLUSION

This study explored the use of stepwise regression analysis as a tentative tool to
create a model to predict RPET content in PET sheets. A backward stepwise regression
analysis was performed with a high significance level (0:0.15). By using backward
elimination, a significant model emerged (F4~ 15 = 141.38, p< 0.0001) with adjusted R
square = 0.9740. Good prediction of the recycled content in PET samples between the
designed domain of the model was obtained by measuring the melting temperature,
intrinsic viscosity, oxygen permeability and ‘b*’ value. Since this model was developed
for a specific mechanical RPET stream provided by the EC02 company (Modesto, CA,
USA), one virgin PET stream supplied by Eastman (Columbia, CA, USA), this model is
not applicable for other recycled PET streams and products without further studies.
Furthermore, verification of the model is needed inside and outside of the design domain
of the model. At this time, only one sample with PCR-PET was obtained; therefore, the
model needs further verification. Additiinal studies are needed for comparing post-
industrial and post-consumer recycled PET.

Specifically, for the results of UV-Visible spectroscopy for PET sheets with
varying percent of virgin and recycled PET contents, it was found that most of the
absorption occurred from 200 to 400 nm due to their ester groups and benzene rings. The
peak arising around 678 nm may be due to fragments of green or blue colored bottles and
printed ink labels. These green or blue colored fragments also affect the color results.
especially ‘a*’ value. The results of ‘b*’ value were affected by oxidation of PET
(yellowing). It was found that more RPET content leads to greyer (‘L*‘ decreases),

greener (‘a*’ decrease) and more yellow color (‘b*‘ increase). Dynamic mechanical

77

analysis and universal material testing did not show differences between PET sheets with
varying percent of virgin and recycled PET. The percent crystallinity measured by DSC
showed no statistically significant differences except between 100V and 40V60R PET
(a=0.05). Oxygen permeability results show that 100V and 60V40R PET show
statistically significantly differences (a=0.05). It was also found that there was no a linear
trend of oxygen permeability values as function of recycled PET contents. Water vapor
permeability values indicate that there was no statistically significantly different between
100V and 100R PET. The NMR results do not show a trend as function of recycled PET
contents. The results of intrinsic viscosity and viscosity molecular weight indicate that
the reduction of molecular weight was occurred with chain scission through repeated

recycling.

Future Work
After developing this exploratory stepwise regression model to tentatively
determine RPET in PET samples, few points arise for further consideration and study.
- The criterion parameters used for this model should be further evaluated
and verified. Also, it should be evaluated if better criterion parameters
could be obtained to get better predictions. Models with different
criterion parameters should be studied (e.g., including all the criterion
parameters of this study and also a lower number than the current

model.)

78

This type of model should be verified with samples provided by the same
manufacturer for different PET sample lots to understand if the model
can predict inside its domain.

Verification of the model should also be conducted with a number of
unknown samples for a number of PET sheet producers that add post-
consumer RPET in their samples.

Studies should include a number of different PET samples suppliers with
different type of PET and RPET streams.

Limitations of the RPET predictions of this model should be better
evaluated, and the effect of different RPET streams should be further

understood.

79

6. APPENDICES

6.] Appendix A- Description of sample production and processing conditions

In order to make PET sheets with varying percent of virgin and recycled PET
contents, the resins of virgin PET and the flakes of recycled PET were delivered by train
to Peninsula Packaging Company (Exeter, CA, USA). PET resins were stored at PET
resin silos. RPET flakes were stored at RPET regrind storages. Amounts of RPET resins
needed for making the expected concentration with PET were shifted to blender, AEC
Whitlock blending system OS series blender (Wooddale, IL, USA). After passing through
the blender, RPET was crystallizaed by crystallizers, Conair model CGT 700 (Franklin.
PA, USA) during 45 min to 1 hour to increase crystalline areas of RPET. The
temperature of air flowed in the crystallizer at 310 OF. The temperature of air flowed out
from crystallizer was usually 100~150 0F. RPET was delivered to another blender, AEC
Whitlock blending system OS series blender (Wooddale, IL, USA) to mix up with virgin
PET. These subsequent blends experienced drying process using a Conair model CAG
2400 carousel drier (Franklin, PA, USA). After the drying process, the mixed resins were
feed to two extruders and extruded on one die and turned to sheets. In order to analyze
the difference between silicon coated PET sheet and uncoated PET sheet. two kinds of
sheets were made as cutting half and half of origin sheets for making coated containers
and uncoated containers. The silicon, Ivanhoe Industries Inc 35% silicone antifoam
emulsion l-SIL 335 EFG (Zion, IL, USA), was used for coating materials. Cutting and

coating process was carried out using a Montalvo system 3000 S-3100-CE (Gorham. MN.

80

USA). Figure 6-1 shows the flow chart of PET sheets processing. This study was only

worked with the uncoated samples.

Table 6-1. Description of extruder zone

 

 

 

 

 

 

 

 

 

 

ZONE Description ZONE Description Zone Description
0.1 Feed zone 2.1 Transition zone 3.4~3.8 Feed block
. . . . Eastside
1.1 Transmon zone 2.2 Pineapple mix 4.] deckless
1.2 Pressure ring 2.3 Bullet zone 4.2~4.8 Die
. West side screen Westside
1.3 Pressure mg 2.4 changer 4.9 deckless
1.4 Pressure ring 2.5 East Slde screen 4.10 Die lip
changer
1 .5 Trans't'igl‘l’; ”lung 3.1 Flow choke 4.1 1 Die lip
T.1 Vacuum port 3.2 Gear pump
T.2 Vacuum chamber 3.3 Crossover zone

 

 

 

 

 

 

81

 

VACUUM. LINE

 

 

.. _M. L- .__; §-__-____-~... ___-__.__ .7
\\ RPET regrindW // \\ PET resin silo //
\ storage 1/ \ /
\ ____-__ _g, __J F,_:_:T _____ ’
:.---—— _.__ ~ , J VACUUM PUMPS
\ / 1. ________ _,
\ BlenderA ‘ VACUUM LINE
'1 / J
J ‘
\ It”
‘1, Crystallizers If VACUUM LINE
J /
\ A W W WWW—“f
\ BlenderB f," VACUUM LINE
\ /
l
_Jl, _z .,
i J/
l‘ Primary dryers ,1"! VACUUM LINE
'\ _ , , I,” ‘
l
x’/ \\‘-,
L Extruder barrers J VACUUM LINE
\ ___1,________ _/
l
V

,7 Final Product J
1 ’ '
_-.S_11se.t e _ ‘J

Figure 6-1. The flow chart of PET sheet processing

82

6.1.1 Processing condition of 80R20VPET sheet

Table 6-2, 6-3 and 6—4 describe the conditions of two extruders, roller and dryer

used for making the sheets of 80R20V PET sheet

Table 6-2. The condition of two extruders for 80R20V PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure TM- Screen Melting Melt pressure
(1 /min) (%) (psi) imp (psi) pressure behmd dosmg
( F) control pump
Extruder A 86 64 916 564 930 450 60
D°Sl"§p“mp 36 41 732 i 44
Extruder B 85 66 1025 549 950 600 1020
D°5m§pump 36 42 593 ‘ 1523
Die 161 l 326
Actual temperature (0F

ZONE I Extruder A I Extruder B ZONE 1 Die

0.1 522 520 3.4 495

1 .1 513 5 I 3 3.5 495

1.2 506 505 3.6 495

1.3 505 499 3.7 495

1.4 504 501 3.8 495

1 .5 507 499 4.1 495

2.1 51 l 505 4.2 495

2.3 503 515 4.3 495

2.4 528 540 4.4 495

2.5 536 534 4.5 495

3.1 502 497 4.6 495

3.2 533 537 4.7 495

3.3 505 500 4.8 498

T l 135 104 4.9 498

T 2 999 999 4.10 554

2.2 505 504 4.11 534

 

Table 6-3. The temperature of dryer and plant for 80R20V PET sheet

 

 

 

Dyer Setting point (°F) Actual temperature (”F)
Delivery Air 285 0F 285 0F
Dew point -40 0F -43 0F

 

Plant temperature at roller

83

108°F

 

Table 6-4. The condition of roller for 80R20V PET sheet

 

 

 

 

 

Speed Current Temperature (Sig)
(rm/mi“) (%) (OF) left right
Roll 1 23.63 38 63 0.06 0.05
Roll 2 23.63 38 70
Roll 3 23.63 7 68 0.19 0.17
Haul-off 23.39 18

 

84

 

6.1.2 Processing condition of100R PET sheet

Table 6-5, 6-6 and 6-7 describes the conditions of two extruders, roller and dryer

used for making the sheets of 100R PET sheet.

Table 6-5. The condition of two extruders for 100R PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure M- Screen Melting Melt pressure
(1 /min) (%) (psi) Temp ( si) pressure behind
(°F) p control dosmg pump
Extruder A 82 66 1249 558 1270 450 50
DOSinipump 36 39 742 i 70
Extruder B 88 65 1003 547 1030 600 940
DOSmgpump 36 38 610 l 1410
Die 1476 295
Actual temperature (°F

ZONE 1 Extruder A 1 Extruder B ZONE 1 Die

0.1 520 520 3.4 495

I .I 516 515 3.5 495

1.2 505 505 3.6 495

1.3 505 500 3.7 495

1 .4 505 501 3.8 495

1.5 505 499 4.1 498

2.1 509 508 4.2 495

2.3 501 515 4.3 495

2.4 530 528 4.4 495

2.5 530 530 4.5 495

3.1 505 503 4.6 495

3.2 529 533 4.7 495

3.3 505 500 4.8 498

T l 135 112 4.9 498

T 2 999 999 4.10 548

2.2 505 504 4.11 530

 

 

Table 6—6. The temperature of dryer and plant for 100R PET sheet

 

 

 

Dryer Setting point (°F) Actual temperature (0F)
Delivery Air 285 °F 285 0F
Dew point -40 °F -40 °F

 

Plant temperature at roller

81°F

 

85

 

Table 6-7. The condition of roller for 100R PET sheet

 

 

 

 

 

 

Speed Current Temperature (SSE)
(In/min) (%) (0F) left 1 right
R011 1 23.62 38 63 0.06 0.05
Roll 2 23.62 38 7O .
Roll 3 23.64 6 68 0.19 0.17
Haul-off 23.39 18

 

86

6.1.3 Processing condition of 60R40VPET sheet

Table 6-8, 6-9 and 6-10 describe the conditions of two extruders, roller and dryer

used for making the sheets of 60R40V PET sheet.

Table 6-8. The condition of two extruders for 60R40V PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure TM- Screen Melting Me: pressure
(1 /min) (%) (p81) emp (p81) pressure . e in
(°F) control dosmg pump
Extruder A 80 62 1036 565 1030 460 150
Dogmfipump 36 45 734 i 150
Extruder B 80 62 1047 554 980 590 1 140
D°Smgpump 36 43 625 i 1710
Die 1842 367
Actual temperature (0F
ZONE | Extruder A 1 Extruder B ZONE 1 Die
0.1 507 518 3.4 494
1.1 536 537 3.5 495
1.2 527 523 3.6 493
1.3 522 520 3.7 485
1.4 51 l 513 3.8 490
1.5 524 516 4.1 495
2.1 515 516 4.2 495
2.3 500 517 4.3 495
2.4 533 533 4.4 495
2.5 529 529 4.5 493
3.1 513 510 4.6 490
3.2 534 542 4.7 487
3.3 51 1 510 4.8 494
T 1 135 109 4.9 485
T 2 999 999 4.10 552
2.2 503 502 4.11 529

 

 

Table 6-9. The temperature of dryer and plant for 60R40V PET sheet

 

 

 

Dryer Setting point (0F) Actual temperature (T)
Delivery Air 285 °F 285 0F
Dew point 40 "F -43 °F

 

Plant temperature at roller

78 0F

 

87

 

Table 6-10. The condition of roller for 60R40V PET sheet

 

 

 

 

 

Speed Current Temperature (312:3)
("n/mi“) (%) (OF) left right
Roll 1 23.62 41 63 0.06 0.05
Roll 2 23.62 41 69
Roll 3 23.59 6 68 0.19 0.17
Haul-off 23.37 18

 

88

6.1.4 Processing condition of 40R60VPE T sheet

Table 6-11, 6-12 and 6-13 describe the conditions of two extruders, roller and

dryer used for making the sheets of 40R60V PET sheet.

Table 6—11. The condition of two extruders for 40R60V PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure M- Screen Melting Melt pressure
(1 /min) (%) (psi) Temp (psi) pressure behmd
(0 F) control dosmg pump
Extruder A 76 70 996 565 1040 460 90
Dosmfipmnp 36 48 722 i 77
Extruder B 78 72 985 555 940 600 1 180
D°S‘“§p“m" 36 47 610 I 1780
Die 1945 384
Actual temperature (°F

ZONE | Extruder A j Extruder B. ZONE 1 Die

0.1 522 518 3.4 495

1.1 521 525 3.5 495

I .2 514 513 3 .6 495

1 .3 513 512 3.7 495

1 .4 51 1 514 3.8 495

1.5 510 510 4.1 495

2.1 512 512 4.2 495

2.3 504 520 4.3 495

2.4 535 535 4.4 495

2.5 535 535 4.5 495

3.1 509 503 4.6 495

3.2 532 540 4.7 495

3 .3 510 510 4.8 498

T l 135 104 4.9 498

T 2 999 999 4.10 554

2.2 505 506 4.11 533

 

 

Table 6—12. The temperature of dryer and plant for 40R60V PET sheet

 

 

 

Dryer Setting point (0F) Actual temperature (“17)
Delivery Air 295 °F 293 0F
Dew point -40 0F -47 °F

 

Plant temperature at roller

77 °F

 

89

 

Table 6-13. The condition of roller for 40R60V PET sheet

 

 

 

 

 

 

Speed Current Temperature ($221))
("mm“) (%) (0F) left right
Roll 1 23.66 41 63 0.06 0.05
Roll 2 23.66 41 70
Roll 3 23.64 6 68 0.19 0.17
Haul-off 23.40 17

 

90

6.1.5 Processing condition of 20R80V PET sheet

Table 6-14, 6—1 5 and 6—1 6 describe the conditions of two extruders, roller and

dryer used for making the sheets of 20R80V PET sheet.

Table 6-14. The condition of two extruders for 20R80V PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure M- Screen Meltmg Melt pressure
(1 /min) (%) (psi) Temp (psi) pressure behind
(°F) control dosmg pump
Extruder A 76 73 1267 572 1250 450 190
0°“me 36 53 732 I 179
Extruder B 74 70 1223 561 1230 600 1340
Downgwmp 36 51 612 I 2007
Die 2205 442
Actual temperature (°F
ZONE [ Extruder A | Extruder B ZONE 1 Die

0.1 531 531 3.4 500
1.1 515 520 3.5 500
1.2 511 510 3.6 500
1.3 510 510 3.7 500
1.4 51 1 51 1 3.8 500
1.5 511 51 1 4.1 500
2.1 512 514 4.2 500
2.3 506 520 4.3 500
2.4 535 S35 4.4 500
2.5 535 535 4.5 500
3.1 511 507 4.6 500
3.2 539 548 4.7 500
3.3 510 510 4.8 500
T 1 135 112 4.9 500
T 2 999 999 4.10 561
2.2 505 505 4.11 539

 

 

Table 6-15. The temperature of dryer and plant for 20R80V PET sheet

 

 

 

Dryer Setting point (°F) Actual temperature (T)
Delivery Air 295 0F 290 0F
Dew point -40 0F -47 °F

 

Plant temperature at roller

79 0F

 

91

 

Table 6-16. The condition of roller for 20R80V PET sheet

 

 

 

 

 

 

Speed Current Temperature (Earp)
(In/min) (%) (0F) left right
Roll 1 23.65 34 63 0.06 0.05
Roll 2 23.65 34 72
Roll 3 23.65 7 68 0.19 0.17
Haul-off 23.41 15

 

92

6.1.6 Processing condition of 1 00V PET sheet

Table 6-17, 6-18 and 6-19 describe the conditions of two extruders, roller and

dryer used for making the sheets of 100V PET sheet.

Table 6-17. The condition of two extruders for 100V PET sheet

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

SPEED Current Pressure Tit-1p Screen [33:31:38 Megeplriejssure
(1/rmn) (%) (p51) (°F) (p31) control dosing pump
Extruder A 74 69 1 157 576 1 170 450 530
DOS‘"§p‘"“p 36 56 766 l 513
Extruder B 73 71 1205 564 1210 600 1400
DOS‘"§pump 36 55 600 i 2091
Die 2329 469
Actual temperature (°F
ZONE 1 Extruder A | Extruder B ZONE 1 Die
0.1 564 548 3.4 500
1.1 515 519 3.5 500
1.2 509 510 3.6 500
1.3 510 510 3.7 500
1.4 51 l 51 1 3.8 500
1.5 510 509 4.1 500
2.1 513 519 4.2 500
2.3 509 520 4.3 500
2.4 535 535 4.4 500
2.5 535 535 4.5 500
3.1 510 507 4.6 500
3.2 548 552 4.7 501
3.3 510 510 4.8 500
T 1 135 1 10 4.9 501
T 2 999 999 4.10 564
2.2 505 505 4.11 544

 

 

Table 6-18. The temperature of dryer andilant for 100V PET sheet

 

 

 

Dryer Setting point (°F) Actual temperature (°F)
Delivery Air 295 °F 290 °F
Dew point -40 °F -50 °F

 

Plant temperature at roller

81°F

 

93

 

Table 6—19. The condition of roller for 100V PET sheet

 

 

 

 

 

Speed Current Temperature (gang)
(In/min) (%) (01:) left right
Roll 1 23.63 35 63 0.06 0.05
Roll 2 23.63 35 72
Roll 3 23.64 6 68 0.19 0.17
Haul-off 23.43 15

 

94

6. 2 Appendix B — Description of stepwise regression analysis and SA S code

6.2.1 Multiple linear regression analysis

Basically, regression analysis is a statistical method for analyzing a relationship
between two or more variables in such a manner that one variable can be predicted or
explained by using information on the others [65]. In simple linear regression, the
relationship is focused on only one factor variable and the relationship can be described
by a straight line. Namely, simple linear regression relates observed values of the

dependent or response variable y to values of a single independent variable x (Equation

(6.1)).

yzflO +fl1x+8 (6.1)

Multiple linear regression is the extension Of simple linear regression to allow a number

of independent variables and it can be written as Equation (6.2)

y=fl0 + flm + flzxz +°°°+ flmxm + 5 “"2”

In the Equation (6.2), y is the dependent variable, and the xi, i = 1, 2, ..., m, are the m
independent variables. The Bi are the (m) parameters or regression coefficients and 130 is

the intercept.

6. 2.2 Pearson correlation coefficient
In statistics, correlation coefficient provides a convenient index of the strength of
the linear relationship between two variables. There are several different coefficients used

for different situations. Pearson correlation coefficient is one Of the correlation coefficient.

95

which is obtained by dividing the covariance of the two variables by their standard
deviation (Equation (6.3)) [65].

n _ _
Z (X,- -X)(Y,- - Y)
i=1

n n (6.3)
\/thi—?)2\/Z(n—Y)2

i=1 i=1

Pearson correlation coefficient (r) =

In the Equation (6.3), Xi and Yi is sample of paired data. 815 sample mean of independent
variables and 7 is sample mean of dependent variables. Pearson correlation coefficient is

reported from -1 tO +1, with a value Of 0 indicating no relationship and values of -1 and

+1 indicating a perfect linear relationship.

6. 2.3 R, R Square and adjusted R Square

Correlation and regression analysis can be related in number of ways. R is a
measure of the correlation between the observed value and the predicted value of the
dependent variables. R Square (R2) is the square of this measure of correlation and

indicates the proportion of the variance in the dependent variable (Equation (6.4)) [66].

R2 = Var(Y') (_ 6. 4)
var(Y)

In the Equation (6.4), Y’ is predicted value by only using independent variables (X). Y is
dependent variables. Therefore, by knowing R Square (R2), it can be measured how good
a prediction of the dependent variables when only X are observed. However, R Square

tends to somewhat over-estimate the success Of the model when applied to the actual case.

Adjusted R Square is the solution of this problem, and it is calculated which takes into

96

account the number of variables in the model and the number of observations [66]. For
example, Adjusted R Square is 0.90, indicating this model has accounted for 90% of the

variance in the dependent variables.

6. 2. 4 Stepwise regression

Stepwise model-building technique is one of the techniques for designing
regression model. The basic procedures consists of (1) identifying an initial model, (2)
repeatedly altering the model at the previous step by adding or removing a predictor
variable in accordance with critical value, and (3) terminating the search when adding or
removing predictor variable is no longer possible given the critical value, or When a

specified maximum number of steps has been reached [67].

6. 2. 4. 1 Forward selection

In forward selection, predictor variables are into the model one at a time in an
order determined by the strength of their correlation with the dependent variable. The
effect of adding each is assessed as it is entered, and variables that do not significantly

add to the success of the model are excluded [66].

6. 2. 4. 2 Backward selection

In backward selection, all the predictor variables are into the model. The weakest
predictor variable is than removed and the regression recalculated. This procedure is then
repeated until only useful predictor variables remain in the model. It is generally agreed
upon that backward selection is preferable to forward selection [68]. The stopping rule

for adding or removing predictor variables usually applies the standard significance level

97

(01=O.05). However, this significance level is too small to identify important predictor
variables. Therefore, if stepwise regression analysis is used, backward manner with a

high significance (a=0.15 or 0.20) level must be used.

6. 2. 4. 3 Stepwise selection

Stepwise selection is the most sophisticated methods among stepwise regression
analysis. Each predictor variables-is entered in sequence and its value assessed. If adding
the variable contributes to the model then it is remained, but all other variables in the
model are then re-tested to assure that they are still contributing to the success of the
model. If they have no effect they are removed. Therefore, this method produces smallest

possible set of predictor variables included in model.

6.2.5 SAS code for this study
For raw data input,

data PET;

input PET TG TCC TC TM DH LM MT ORP UV350 UV380 UV678 IV VM
WVTR OTR NMR424 L a b E;

cards;

observation data input here

run;
proc print data=PET;
run;

98

For Pearson correlation test

proc corr data=PET;

var PET TG TCC TM Xc UV350 UV380 UV678 IV VM WVTR OTR
NMR424 L a b;

run;

For simple linear regression analysis with residual plot and normality test

*TG;

proc reg data=PET ;

model PET=TG/Cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

*TM;

proc reg data=PET ;

model PET=TM/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;

var resid;
run;

99

*UVBBO;

proc reg data=PET ;

model PET=UV380/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;

plot resid*pred;

run;

proc univariate data=myout plot normal;
var resid;

run;

+I\’7;

proc reg data=PET ;

model PET=IV/cli Clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

*WVTR;

proc reg data=PET ;

model PET=WVTR/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

100

*OTR;

proc reg data=PET ;

model PET=OTR/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

*NMR424;

proc reg data=PET ;

model PET=NMR424/Cli clm ;
output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

T a
.14]

proc reg data=PET ;

model PET=L/Cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

101

*a;

proc reg data=PET ;

model PET=a/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

+10].

proc reg data=PET ;

model PET=b/cli clm ;

output out=myout r=resid p=pred;
run;

proc plot data=myout;
plot resid*pred;
run;

proc univariate data=myout plot normal;
var resid;
run;

For stepwise regression analysis (Backward manner)

proc reg data=PET;

model PET=TM UV380 IV OTR b/adjrsq selectionzbackward
sl820.15;

run;

6. 3 Appendix C — Description far each linear regression and estimated parameter/Or

each step

6. 3. 1 Description for simple linear regression between TG and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr>F
Model 1 0.46559 0.46559 4.52 0.0504
Error 15 1.54382 0.10292

Corrected Total 16 2.00941

Root MSE 0.32081 R-Square 0.2317
Dependent Mean 0.49412 Adj R-Sq 0.1805
Coeff Var 64.92654

Parameter Estimates

Parameter Standard
Variable DF Estimate Error t Value Pr > |t|

Intercept 1 -16.57983 8.02794 -2.07 0.0566
TG 1 0.21940 0.10315 2.13 0.0504

Basic Statistical Measures

Location Variability

Mean 0.000000 Std Deviation 0.31063
Median 0.121152 Variance 0.09649
Mode . Range 1.03256

Interquartile Range 0.54365

103

Tests for Normality

Test --Statistic--- ----- p Value ------

Shapiro-Wilk W 0.918466 Pr < W 0.1391

Kolmogorov-Smirnov D 0.207068 Pr > D 0.0504

Cramer-von Mises W-Sq 0.126398 Pr > W-Sq 0.0453

Anderson-Darling A-Sq 0.676624 Pr > A-Sq 0.0666
The UNIVARIATE Procedure

Variable: resid (Residual)

Normal Probability Plot

+*+*++*
:1: ***+*+**
+*++++
++++*+*
-05+- +*++++* *

0.5+ +++++*+
I
|
l
1

6.3.2 Descriptionfiir simple linear regression between TM and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr> F
Model 1 1.71533 1.71533 87.49 <.0001
Error 15 0.29408 0.01961

Corrected Total 16 2.00941

Root MSE 0.14002 R-Square 0.8536
Dependent Mean 0.49412 Adj R-Sq 0.8439
Coeff Var 28.33735

104

Parameter Estimates

Parameter Standard
Variable DF Estimate Error tValue Pr> |t|

Intercept 1 88.52697 9.41160 9.41 <.0001
TM 1 -0.35745 0.03821 -9.35 <.0001

Basic Statistical Measures

Location Variability

Mean 0.00000 Std Deviation 0.13557
Median -0.03739 Variance 0.01838
Mode . Range 0.53992

Interquartile Range 0.21004

Tests for Normality

Test --Statistic--- ----- p Value ------
Shapiro-Wilk W 0.933711 Pr < W 0.2509
Kolmogorov-Smirnov D 0.165698 Pr > D >0.1500

Cramer-von Mises W-Sq 0.093171 Pr > W-Sq 0.131 1
Anderson-Darling A-Sq 0.531804 Pr> A-Sq 0.1518

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

035+ * +++
| ++++++++
I * *+*++*+

(105+ +++*+*++
I +**+*+***
| +*++*+*

-O,25+ ++++*+++

105

6. 3.3 Description for simple linear regression between xc and dependant variables

Source

hdodel
Enor

Corrected Total

Root MSE

Analysis of Variance

Sum of Mean
DF Squares Square F Value Pr > F

1 0.35077 0.35077 2.98 0.1062
14 1.64673 0.11762

15 1.99750

0.34296 R-Square 0.1756

Dependent Mean 0.48750 Adj R-Sq 0.1167

Coeff Var

Variable

Intercept

Xc

Test

DF

1
1

70.3 5 1 36
Parameter Estimates

Parameter Standard
Estimate Error t Value Pr > |t|

1.42648 0.55046 2.59 0.0213
-0.10986 0.06361 -1.73 0.1062

Basic Statistical Measures

Location Variability

Mean 0.000000 Std Deviation 0.33133
Median 0.155594 Variance 0.10978
Mode . Range 1 .041 86

Interquartile Range 0.50959
Tests for Normality

--Statistic--- ----- p Value ------

Shapiro-Wilk W 0.870606 Pr < W 0.0278

Kolmogorov-Smimov D 0.258146 Pr > D <0.0100
Cramer-von Mises W-Sq 0.184956 Pr > W-Sq 0.0072
Anderson-Darling A-Sq 0.965296 Pr > A-Sq 0.0115

106

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot
05+ +++++*
I +*+*++*
I **+**+*+*
-0J+- ++*+++
| ++++*+*

I +++++* *
-0,7+ ++++++*
+----+----+----+----+----+----+----+----+----+----+
-2 -1 0 +1 +2

 

6. 3. 4 Descriptionfor simple linear regression between U V380 and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 2.54680 2.54680 336.48 <.0001
Error 20 0.15138 0.00757

Corrected Total 21 2.69818

Root MSE 0.08700 R-Square 0.9439
Dependent Mean 0.49091 Adj R-Sq 0.941 1
Coeff Var 17.72224

Parameter Estimates

Parameter Standard

Variable DF Estimate Error t Value Pr > It]
Intercept 1 -5.51895 0.32816 -16.82 <.0001
UV380 1 0.07847 0.00428 18.34 <.0001

Basic Statistical Measures

107

Location Variability

Mean 0.000000 Std Deviation 0.08490
Median 0.0141 13 Variance 0.00721
Mode . Range 0.39426

Interquartile Range 0.07267

Tests for Normality

Test --Statistic--- ----- p Value ------
Shapiro-Wilk W 0.931772 Pr < W 0.1336
Kolmogorov-Smimov D 0.151982 Pr > D >0.1500

Cramer-von Mises W-Sq 0.103095 Pr > W-Sq 0.0967
Anderson-Darling A-Sq 0.628273 Pr > A-Sq 0.0911

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

(l225+ * ++

I ++++++

I ++++++

I ++++*+* *
0025+ *+***** **

I *4: ****+

I ++++++

I ++*++**
-0J75+ ++++*+

108

6. 3.5 Description for simple linear regression between [V and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 1.76878 1.76878 108.27 <.0001
Error 14 0.22872 0.01634

Corrected Total 15 1.99750

 

Root MSE 0.12782 R-Square 0.8855
Dependent Mean 0.48750 Adj R-Sq 0.8773
Coeff Var 26.21902

Parameter Estimates

Parameter Standard

Variable DF Estimate Error t Value Pr > lt|
Intercept 1 -2.80581 0.31812 -8.82 <.0001
IV 1 5.20692 0.50042 10.41 <.0001

Basic Statistical Measures

Location Variability

Mean 0.00000 Std Deviation 0.12348
Median -0.01478 Variance 0.01525
Mode . Range 0.38397

Interquartile Range 0.21655
Tests for Normality

Test --Statistic--- ----- p Value ------
Shapiro-Wilk W 0.9318 Pr < W 0.2603
Kolmogorov-Smimov D 0.182203 Pr > D >0.1500
Cramer-von Mises W-Sq 0.080368 Pr > W-Sq 0.1978
Anderson-Darling A-Sq 0.459591 Pr> A-Sq 0.2333

109

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

(1225+ +*++
I *+++
I * *+*++
I *++++
(1025+ +**++
I ++++
I ++*+* *1!
I ++*+*

-0.175+ * +++*
+----+----+----+----+----+----+----+----+----+----+

-2 —l 0 +1 +2

 

6. 3. 6 Description for simple linear regression between ()TR and dependant variables

Analysis Of Variance

Sum of Mean
Source DF Squares Square F Value Pr> F
Model 1 0.60903 0.60903 5.83 0.0255
Error 20 2.08915 0.10446

Corrected Total 21 2.69818

Root MSE 0.32320 R-Square 0.2257
Dependent Mean 0.49091 Adj R-Sq 0.1870
Coeff Var 65.83683

Parameter Estimates

Parameter Standard
Variable DF Estimate Error t Value Pr > ItI

Intercept 1 -3.43158 1.62593 -2.1 1 0.0476
OTR 1 0.71277 0.29519 2.41 0.0255

110

Basic Statistical Measures

Location Variability

Mean 0.000000 Std Deviation 0.31541
Median 0.147601 Variance 0.09948
Mode . Range 1.00191

Interquartile Range 0.44258

Tests for Normality

Test --Statistic--- ----- p Value ------
Shapiro-Wilk W 0.876023 Pr < W 0.0102
Kolmogorov-Smimov D 0.214006 Pr > D <0.0100
Cramer-von Mises W-Sq 0.189236 Pr > W-Sq 0.0066
Anderson-Darling A-Sq 1.090584 Pr> A-Sq 0.0061

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

*+*+++++
*+****+
++++*+
++++*++**
417+++++++*

+----+----+----+--—-+----+----+----+----+----+----+
-2 -1 0 +1 +2

(13+ ******+*+* * *
|
1
l
1

1H

6. 3. 7 Description for simple linear regression between W VTR and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 0.19151 0.19151 1.39 0.2543
Error 18 2.48649 0.13814

Corrected Total 19 2.67800

 

Root MSE 0.37167 R-Square 0.0715
Dependent Mean 0.49000 Adj R-Sq 0.0199
Coeff Var 75.85089

Parameter Estimates

Parameter Standard
Variable DF Estimate Error tValue Pr> |t|

Intercept 1 2.85714 2.01211 1.42 0.1727
WVTR 1 -0.88319 0.75008 -1.18 0.2543

Basic Statistical Measures

Location Variability

Mean 0.00000 Std Deviation 0.36176
Median -0.06326 Variance 0.13087
Mode . Range 1 .0961 3

Interquartile Range 0.47153

Tests for Normality

Test --Statistic--- ----- p Value ------
Shapiro-Wilk W 0.903731 Pr < W 0.0485
Kolmogorov—Smimov D 0.145487 Pr > D >0.1500
Cramer-von Mises W-Sq 0.085857 Pr > W-Sq 0.1676
Anderson-Darling A-Sq 0.628571 Pr> A-Sq 0.0898

112

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot
0.7+ * ++*+++
I * *+++++
I ++++—++
0.1+ ++***+**
I +++***
I *+*+** **

-0.5+ * ++*++

6. 3.8 Descriptionfor simple linear regression between NMR424 and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 0.00707 0.00707 0.05 0.8292
Error 17 2.50241 0.14720 -

Corrected Total 18 2.50947

Root MSE 0.38367 R-Square 0.0028
Dependent Mean 0.49474 Adj R-Sq —0.0558
Coeff Var 77.54970

Parameter Estimates

v Parameter Standard
Variable DF Estimate Error tValue Pr> ItI

Intercept 1 0.48635 0.09598 5.07 <.0001
NMR424 1 0.00059792 0.00273 0.22 0.8292

113

Basic Statistical Measures

Location Variability

Mean 0.000000 Std Deviation 0.37286
Median 0.060554 Variance 0.13902
Mode . Range 1.05187

Interquartile Range 0.60001

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

 

*+*+++
**+**+
++*+*
+++*+**
-O,5+ * ++*++* *

0.5+ * *++*++ *
l
1
|
l

6. 3. 9 Descriptionfiir simple linear regression between ‘L * ' and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 0.00011269 0.00011269 0.00 0.9774
Error 24 3.29835 0.13743

Corrected Total 25 3.29846

Root MSE 0.37072 R-Square 0.0000
Dependent Mean 0.50769 Adj R-Sq -0.0416
Coeff Var 73.02004

114

Parameter Estimates

Parameter Standard
Variable DF Estimate Error tValue Pr> ItI

Intercept 1 0.50203 0.21062 2.38 0.0254
L 1 0.00007255 0.00253 0.03 0.9774

Basic Statistical Measures

Location Variability
Mean 0.000000 Std Deviation 0.36323
Median 0.091514 Variance 0.13193
Mode 0.491441 Range 1.00639

Interquartile Range 0.59990

Tests for Normality

Test -—Statistic-~- ----- p Value ------
Shapiro-Wilk W 0.897894 Pr < W 0.0141
Kolmogorov-Smirnov D 0.148208 Pr > D 0.1455
Cramer-von Mises W-Sq 0.109424 Pr > W-Sq 0.0829
Anderson-Darling A-Sq 0.804914 Pr> A-Sq 0.0337

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

055+ +++
3|! *+* 1! *

+++
****

|

I

I

I +++

I ****

I ++

I ++***

I +++

l +++*** :1:
I ++

_O.55+ I1: +*+* * *

115

6. 3. 10 Description for simple linear regression between ‘a* ’ and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square F Value Pr > F
Model 1 0.01860 0.01860 0.14 0.7154
Error 24 3.27986 0.13666

Corrected Total 25 3.29846

Root MSE 0.36968 R-Square 0.0056
Dependent Mean 0.50769 Adj R-Sq -0.0358
CoeffVar 72.81512

Parameter Estimates

Parameter Standard
Variable DF Estimate Error tValue Pr > M

Intercept 1 0.53266 0.09918 5.37 <.0001
a 1 0.02358 0.06392 0.37 0.7154

Basic Statistical Measures

Location Variability
Mean 0.00000 Std Deviation 0.36221
Median 0.06486 Variance 0.131 19
Mode -0.49305 Range 1 .10140

Interquartile Range 0.59175

Tests for Normality

Test --Statistic--- --‘---p Value ------
Shapiro-Wilk W 0.920065 Pr < W 0.0451
Kolmogorov-Smimov D 0.140449 Pr > D >0.1500
Cramer-von Mises W—Sq 0.088835 Pr > W-Sq 0.1527
Anderson-Darling A-Sq 0.644568 Pr > A-Sq 0.0858

116

The UNIVARIATE Procedure
Variable: resid (Residual)

Normal Probability Plot

0.45+ II: *+* =1! *

I +++

I * *+*

I *++

I **+

I ***

I +++

I **+ II:

| +++

I * *+*

I +++
-0.65+ *+++

6. 3. l l Descriptionfor simple linear regression between ‘b* ’ and dependant variables

Analysis of Variance

Sum of Mean
Source DF Squares Square FValue Pr>F
Model 1 1.32665 1.32665 16.75 0.0004
Error 25 1.98002 0.07920

Corrected Total 26 3.30667

Root MSE 0.28143 R-Square 0.4012
Dependent Mean 0.51111 Adj R-Sq 0.3773
Coeff Var 55.06167

Parameter Estimates

Parameter Standard
Variable DF Estimate Error t Value Pr > Itl

Intercept 1 0.98081 0.12690 7.73 <.0001
b 1 -0.26592 0.06497 -4.09 0.0004

117

Location

Mean 0.00000
Median 0.03081
Mode -0. 1 591 1

Test

Shapiro-Wilk

Basic Statistical Measures

Variability
Std Deviation 0.27596
Variance 0.07615
Range 1.30049
Interquartile Range 0.39846
Tests for Normality
--Statistic--- ----- p Value ------

W 0.827949 Pr<W 0.0004

Kolmogorov-Smimov D 0.165207 Pr>D 0.0574

Cramer-von Mises

W-Sq 0.153676 Pr> W-Sq 0.0207

Anderson-Darling A-Sq 1.14039 Pr > A-Sq <0.0050
The UNIVARIATE Procedure
Variable: resid (Residual)
Normal Probability Plot
0.3+ ****+**+++ * =1:
I **+*+**+++
I ** ***+*++
-0.3+ * +*+++++
I +++++++
I++++
—0.9+ *

118

6.3.12 Description of the estimated parameter for each step

Table 6-20 indicate the description of the estimated parameter, P value and 95%
confidence interval for step 0. At the step 0, F value is 104.23 (<0.0001) with adjusted R-
square of0.9718.

Table 6-20. Estimated parameter, P value and 95% confidence interval for step 0

 

Predictor Parameter 95% confidence interval P value
variable est1mate Lower bound Upper bound
Intercept 17.551 2: 12.767 -6.580 46.567 0.1992
IV 0.971 + 0.739 -0.011 2.702 0.2180
OTR 0.198 3: 0.103 -0.024 0.397 0.0843
TM -0.077 + 0.049 -0.188 0.017 0.1479
b -0.241 3: 0.101 -0.449 -0.023 0.0382
UV380 0.009 1 0.023 -0.044 0.050 0.7215

 

Table 6-21 indicate the description of estimated parameter, P value and 95%
confidence interval for step 1. At the step 1, F value is increased to 141.38 (<0.0001) with
adjusted R-square of 0.9740 by excluding UV380 variable.

Table 6-21. Estimated parameter, P value and 95% confidence interval for step 1

 

Predictor Parameter 95% confidence interval P value
var rable est1mate Lower bound Upper bound
Intercept 20.317 i 9.885 0.145 41.568 0.064
1V 1.10] d: 0.623 0.196 2.558 0.105
OTR 0.222 3: 0.078 0.040 0.349 0.084
TM -0.086 + 0.040 -0.173 -0.004 0.056
b -0.267 :t 0.071 -0.387 -0.102 0.003

 

119

10.

11.

12.

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