Assessment and Evaluation of Contamination in Single Stream Recycling Systems Due to Broken Glass and Other Non-Recyclables

Transcription

1 Assessment and Evaluation of Contamination in Single Stream Recycling Systems Due to Broken Glass and Other Non-Recyclables by Haluk Damgacioglu, Lea Perez, and Nurcin Celik (PI) University of Miami, Coral Gables, FL, USA Department of Industrial Engineering Submitted to Hinkley Center for Solid and Hazardous Waste Management University of Florida P. O. Box Gainesville, FL Report # I

2 TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLES LIST OF ACRONYMS EXECUTIVE SUMMARY DISSEMINATION ACTIVITIES III IV V XI XV 1 INTRODUCTION 1 2 BACKGROUND AND LITERATURE REVIEW 2 3 MATERIAL RECOVERY FACILITIES Material Definitions Single Stream MRF Process Flow 10 4 DATA COLLECTION AND ANALYSIS Inbound Contamination Analysis Outbound Contamination Analysis Material Recovery Facility (MRF) Audit Analysis 20 5 CONCLUSION 26 6 REFERENCES 28 7 APPENDICES 31 APPENDIX A: ANALYSIS OF VARIANCE 31 II

3 LIST OF FIGURES Figure 1. Distribution of paper/paperboard collection techniques in the United States (AF&PA, 2015) 1 Figure 2: End-market for collected glass (Kinsella & Gertman, 2007) 2 Figure 3. Residual characterization for each MRF type in California (Beck, 2006) 3 Figure 4. Effects of single stream on NORPAC Paper Mill (Morawski, 2010) 3 Figure 5. Chittenden County residue rates before and after their switch to single stream (Moreau, 2015) 4 Figure 6. End markets for glass collected from different systems (DSM Environmental Services, 2011) 5 Figure 7. Glass losses across the recovery process (Sustainability Victoria, 2014) 6 Figure 8. Glass losses in Ohio by collection system (CRI, 2009) 6 Figure 9. Number of cullet processors in 35 states (GPI, 2018) 6 Figure 10. Average recycling rates (AR) and glass recycling rates (AGR) of counties that switched to SSR in Florida (FDEP, 2017) 7 Figure 11. Single stream MRF process flow with equipment configuration to recover fiber, glass, plastic and metal materials 11 Figure 12. Boxplot of SSR and DSR contamination data 12 Figure 13. Histograms of SSR and DSR contamination rates 13 Figure 14. Results of AD normality test for SSR contamination data 14 Figure 15. Results of AD normality test for DSR contamination data 14 Figure 16. Histograms of contamination rates of each county 15 Figure 17. Contamination rates in SSR counties 16 Figure 18. Contamination rates in SSR counties 17 Figure 19. County correlation matrix 18 Figure 20. OCC prohibitive materials analysis 19 Figure 21. ONP prohibitive materials analysis 19 Figure 22. Types of contamination in corrugated cardboard (a) and newspapers (b) 20 III

4 LIST OF TABLES Table 1. Construction application of glass cullet (GPI, N.D.) 5 Table 2. Plastic material definitions 8 Table 3. Paper recyclables recovered in MRFs 9 Table 4. Glass recyclables recovered in MRFs 9 Table 5. Metal recyclables recovered in MRFs 9 Table 6. Residues found in MRFs during single stream recycling 10 Table 7. ANOVA results of SSR-DSR comparison 14 Table 8. Descriptive analysis of contamination rates for each county 15 Table 9. ANOVA results of contamination on the mean contamination rates of six selected SSR counties 16 Table 10. SSR separation of efficiencies in percentage (Presley et al., 2015) 21 Table 11. MRF efficiency table based on the results of mass balance analysis 23 Table 12. Single stream MRF sort results 24 Table 13. Summary of ANOVA formulas 32 IV

5 LIST OF ACRONYMS AD AF&PA ANOVA CRI DSR EPA FDEP GPI HDPE ISRI MRF OCC ONP PET SSR TAG : Anderson-Darling normality test : American Forest and Paper Association : Analysis of variance : Container Recycling Institute : Dual stream recycling : Environmental Protection Agency : Florida Department of Environmental Protection : Glass Packaging Institute : High density polyethylene : Institute of Scrap Recycling Industries : Material recovery facility : Old corrugated containers : Old newspapers : Polyethylene terephthalate : Single stream recycling : Technical awareness group V

6 FINAL REPORT (April March 2018) PROJECT TITLE: PRINCIPAL INVESTIGATOR: AFFILIATION: Assessment and Evaluation of Contamination in Single Stream Recycling Systems Due to Broken Glass and Other Non-recyclables Nurcin Celik, Ph.D. Department of Industrial Engineering, University of Miami celik@miami.edu PHONE NUMBER: PROJECT WEBSITE: COMPLETION DATE: March 31 st, 2018 TAG MEMBERS: David Gregory, Jeremy O Brien, Karen Moore, Paul Valenti, Eddie McManus, Sean Williams, Michael Heimbach, Michael J. Fernandez, Brenda S. Clark, Katie Brown, Samuel B. Levin, Patrick Sullivan, Florin Gradinar, Himanshu Mehta, Stephanie Watson, Sally Palmi, Ron Hixson, Scott Harper, Teddy Lhoutellier, Greg Schaffer, Johnny Gold, Leonard Marion. KEY WORDS: Single stream recycling, assessment of inbound contamination rates, evaluation of outbound contamination rates, material recovery facilities, prohibitive materials VI

7 ABSTRACT In single stream recycling (SSR), all recyclables are separated from municipal solid waste into a sole compartment in a collection truck. Amongst the curbside recycling programs, SSR has grown rapidly in the past decade. This growth is likely due to SSR s ability to better attract the participation of communities, reduce the cost of collection of curbside recyclables, and avoid a cumbersome sorting process at the individual level. In Florida, 24 counties have recently switched their recycling programs from dual stream recycling (DSR) to SSR. These changes include the counties covering major cities such as Brevard, Broward, Hillsborough, and Miami- Dade. In a DSR system, two collection bins are provided to consumers. The consumer then separates paper products from the other glass, metal, and plastic recyclables. This separation results in lower participation rates and smaller amounts of collected recyclables compared to SSR. Despite an SSR system s inherent advantages on reducing collection costs and increasing community recycling participation, it may not necessarily lead to a higher recycling rate. The use of the mixed-material bin brings up issues of contamination, as materials sometimes cannot be sorted properly with other recyclables and non-recyclables. This further leads to higher costs during processes in material recovery facilities (MRFs) and recycled material discard. In order to better understand the impact of SSR on the Florida solid waste management system, in this study, we conducted an assessment of contamination in MRFs in Florida, aiming to determine to which extent broken glass and other non-recyclables are responsible for the contamination of recovered material. Researchers collected various data regarding the inbound contamination rates from waste composition studies provided by 15 counties around Florida, the outbound contamination rates from four currently operating facilities in Florida, and the assessment of existing processing technologies from one MRF audit. After assessing the waste composition studies, researchers obtained 170 samples from SSR and 45 samples from DSR for inbound contamination rates. Based on the results of the descriptive statistical analysis and one-way analysis of variance (ANOVA) technique on the inbound contamination data, researchers concluded that there is a statistical significance of the difference between the mean contamination rates of SSR and DSR systems. Researchers further tested the statistical significance of the difference between the mean contamination rates of the counties which currently implement SSR. A correlation analysis was also carried out between the contamination rates and demographics of the considered counties. Based on the results, contrary to popular belief, no statistical correlation between inbound contamination and ethnicity was found in county level analysis. However, a positive correlation between median age and contamination, as well as a negative correlation between income level and contamination were identified in our analysis. In the assessment of outbound contamination, researchers obtained 266 old newsprint (ONP) samples and 35 old corrugated cardboard (OCC) samples from four currently operating facilities in Florida. In this assessment, researchers focused on prohibitive materials in the sorted and separated recyclable due to the scope of the project. Average rates (weight of the contamination/weight of total sample) of prohibitive materials in the ONP stream and the OCC stream were 7.13 percent and 5.12 percent, respectively. Considering the paper mill standards are only 2 percent for ONP and 3 percent for OCC, 34 percent of OCC samples and only 0.3 percent of ONP samples could meet the paper mill standards. The most common types of prohibitive VII

8 materials in the OCC streams apart from residues were film plastic, and high density polyethylene (HDPE). On the other hand, residue, polyethylene terephthalate (PET), and film plastic were the most common types of prohibitive materials found in the ONP streams. Lastly, researchers investigated which of the current methods being applied to MRFs (i.e., for sorting, etc.) lead to increased contamination rates in the outbound stream. Here, researchers assessed MRF audit data using mass balance analysis and achieved two main tables: an efficiency table and a sorting results table. According to the efficiency table, the efficiency rate of Disc Screen 1, which separates OCC from other types of fiber, was found as approximately 45 percent. Despite the low efficiency rate, the contamination was approximately 5 percent according to the sorting table. This means that even slight improvement on the efficiency of Disc Screen 1 can provide much lower contamination since the screen eliminates OCC from other recyclables and non-recyclables in the incoming stream. Based on the sorting results, the acceptable rate of the mixed paper was 92 percent, which is considered a very low rate according to mill standards. The efficiency rate of Optical Sorters that separate PET and HDPE plastics was approximately 85 percent. This rate is very close to industry standards. In plastic recycling, colored HDPE was the most contaminated recyclable with 65 percent of material weight being acceptable. In glass recycling, the efficiency of the Glass Breaker Screen was found to be 95 percent; however, the sort results indicated that the screen failed to separate grit, fines and sweepings from glass cullet. The acceptable rate of mixed glass was only 70 percent despite the high level of efficiency or the processing techniques. Here, efforts could be shaped to decrease the amount of grit, fines and sweepings in the inbound stream. VIII

9 METRICS: 1. List graduate student or postdoctoral researchers funded by THIS Hinkley Center project. Last name, first Rank Department Professor Institution name Damgacioglu, Haluk Ph.D. Candidate Department of Industrial Engineering Prof. Nurcin Celik University of Miami 2. List undergraduate researchers working on THIS Hinkley Center project. Last name, first Rank Department Professor Institution name Perez, Lea Undergraduate Department of Prof. Nurcin University Student Industrial Engineering Celik of Miami 3. List research publications resulting from THIS Hinkley Center project (use format for publications as outlined in Section 1.13 of this Report Guide). Damgacioglu, H., Perez, L., Celik, N. Assessment and Evaluation of Inbound Contamination in Single Stream Recycling Systems A Case Study of Florida working journal paper. Damgacioglu, H., Hornilla, M., Celik, N. Assessment and Evaluation of Outbound Contamination in Single Stream Material Recovery Facilities A Case Study of Florida working journal paper. 4. List research presentations (as outlined in of this Report Guide) resulting from THIS Hinkley Center project. Technical Awareness Group (TAG) I Meeting took place on July 14 th, 2017 at the McArthur Engineering Building of the University of Miami with 13 attendees (both onsite and via conference call). Technical Awareness Group (TAG) II Meeting took place on March 9 th, 2018 at the McArthur Engineering Building of the University of Miami with 14 attendees (both onsite and via conference call). 5. List of individuals who have referenced or cited publications from this project. No publications to date. 6. How have the research results from THIS Hinkley Center project been leveraged to secure additional research funding? PI Celik has secured an additional funding through the DOE-funded REMADE Institute. The project will start in the second half of 2018 once the Institute administration is fully launched. University of Miami is also becoming a Tier 1 member of this Institute where PI Celik is serving as the Technical Lead. The initial foundational funding will be at 110K from the Institute with a 1:1 cost share from University of Miami. 7. What new collaborations were initiated based on THIS Hinkley Center project? IX

10 Eddie McManus, the director of material recovery facilities owned by Waste Management in Florida has been very helpful for providing necessary information. He is our direct point of contact if we need any further information from Waste Management. Jonathan Gold, a renowned expert in the paper recovery industry has been very helpful for explaining how the single stream collection affected paper recycling industry. He has a wealth of experience in paper recycling industry, public and private. He has been interested in the finding of both the last year s project, Assessment of the Impact of Single Stream Recycling on Paper Contamination in Recovery Facilities and Paper Mills, and the current project. He also serves in the TAG committee of the current project. 8. How have the results from THIS Hinkley Center funded project been used (not will be used) by FDEP or other stakeholders? (1 paragraph maximum). The results of this study have not yet been presented. X

11 EXECUTIVE SUMMARY PROJECT TITLE: PRINCIPAL INVESTIGATOR: AFFILIATION: PROJECT WEBSITE: TAG MEMBERS: Assessment and Evaluation of Contamination in Single Stream Recycling Systems Due to Broken Glass and Other Non-recyclables Nurcin Celik, Ph.D. Department of Industrial Engineering, University of Miami David Gregory, Jeremy O Brien, Karen Moore, Paul Valenti, Eddie McManus, Sean Williams, Michael Heimbach, Michael J. Fernandez, Brenda S. Clark, Katie Brown, Samuel B. Levin, Patrick Sullivan, Florin Gradinar, Himanshu Mehta, Stephanie Watson, Sally Palmi, Ron Hixson, Scott Harper, Teddy Lhoutellier, Greg Schaffer, Johnny Gold, Leonard Marion. COMPLETION DATE: March 31, 2018 OBJECTIVES: In single stream recycling (SSR), all recyclables are separated from municipal solid waste into a sole compartment in a collection truck. Amongst the curbside recycling programs, SSR has grown rapidly in the past decade. This growth is likely due to SSR s ability to better attract the participation of communities, reduce the cost of collection of curbside recyclables, and avoid a cumbersome sorting process at the individual level. According to an American Forest and Paper Association report, in 2005, 22 percent of the United States population had access to SSR, but by 2014, that had grown to 73 percent (AF&PA, 2015). This surge in popularity is also evident in Florida where, based on our investigations, at least 24 of the 67 counties have currently operating SSR programs in place. The list of counties include Brevard, Dade, Escambia, Marion, and Orange counties. While SSR increases the number of recyclables collected and eases the collection process, SSR systems may operate at the expense of higher volumes of materials requiring pre-sorting at regional material recovery facilities (MRFs), and higher contamination rates in the materials directed to the mills. In SSR, increasing amounts of non-recyclable materials (e.g., plastic bags, food waste) in single collection bins and incoming comingled recyclables (e.g., small glass pieces and shards may get stuck in fiber items, making them unable to be recycled) fosters issues of contamination. This further leads to higher costs during processes in MRFs and recycled material discard. To better understand the impact of SSR on the Florida solid waste management system, in this study, we assessed the contamination issues found in MRFs operating around the state of Florida. Our aim is to determine the extent which broken glass and other non-recyclables are responsible for the contamination of recovered material. XI

12 In this study, researchers first assessed and evaluated the impact of inbound contamination resulting from SSR systems and compared the results with inbound contamination resulting from the dual stream recycling (DSR) system. The use of DSR system necessitates the residents to separate fiber (newspaper, magazines and catalogs, mixed paper, cardboard, etc.) and other recyclables for collection. The inbound contamination rates in both SSR and DSR were obtained by analyzing the collected waste composition studies from 15 Florida counties Alachua, Brevard, Broward, Citrus, Escambia, Hillsborough, Indian River, Lee, Leon, Marion, Okaloosa, Pasco, Santa Rosa, Sarasota, and Seminole. The inbound contamination data was analyzed using the analysis of variance (ANOVA) techniques, which measures the statistical significance, if any, of the difference between the mean contamination rates of the two systems. Based on ANOVA statistics and descriptive statistical analysis, the difference was found to be significant and variance in contamination rates in SSR samples were much higher than the variance in DSR samples. Further analysis was conducted to better understand the high variance in SSR samples. Here, researchers compared the mean contamination rates of the counties which currently implement SSR. This analysis showed that the inbound contamination rates were higher in counties with higher median age and lower income level. In addition to inbound contamination, outbound contamination rates of single stream MRFs in Florida were assessed to represent the impact of SSR on the recovered material quality. Finally, one MRF audit was analyzed to investigate which of the current methods being applied to MRFs (i.e., for sorting, etc.) lead to increased contamination rates in the outbound stream. METHODOLOGY: The study consisted of the following phases: 1. Collection and Analysis of Inbound Contamination Rates in SSR and DSR: Researchers identified and assessed the impact SSR has on inbound contamination rates by analyzing collected waste composition studies from 15 Florida counties. Researchers obtained 170 samples from SSR and 45 samples from DSR to find contamination rates in the inbound stream. Based on descriptive statistical analysis, the mean contamination rates were found to be percent for samples from SSR and 3.89 percent for samples from DSR. It was also shown that SSR contamination rates were more spread out over a wide range of values than were DSR contamination rates. The data was further analyzed using ANOVA to test if there is statistically significant evidence that shows contamination rates in SSR systems are higher than the rates in DSR systems. The analysis rejected the null hypothesis that the contamination rates in SSR and DSR systems are the same and supported the alternative hypothesis that the contamination rates in single stream recycling are higher than those in dual-stream recycling at significance level. 2. Assessment of Inbound Contamination Rates at County Level: The standard deviation (8.97) of the SSR contamination samples was found to be higher than that of the DSR contamination samples (3.08). To better understand this significant variance in inbound contamination rates among SSR samples, researchers investigated the difference in contamination rates of the SSR and DSR systems at a county level. Here, three counties operationing with DSR demonstrate the lowest contamination rates at less than 5 percent, while three other counties, after switching to SSR from DSR demonstrated the highest contamination rates at more than 20 percent. It was also found that a wider variation of contamination rates exists between counties operating with SSR. An ANOVA test was XII

13 designed to determine the statistical significance of the difference between the mean contamination rates of the six selected counties. The results indicated that two counties, with respective contamination rates of 28.2 and 22.3 percent on average, have means significantly higher than the other counties based on a 95 percent confidence level. Researchers then conducted a correlation analysis to further investigate the differences between counties and find if any relationship exists between contamination rates and the demographics of these six counties. The results found no correlation between inbound contamination rates and ethnicity; however, the test showed a positive correlation between median age and contamination, as well as a negative correlation between income level and contamination. 3. Assessment of Outbound Contamination Rates: Researchers assessed the contamination levels in the recovered fiber samples baled by MRFs. We obtained 35 old corrugated cardboard (OCC) and 266 old newspaper (ONP) samples from audit reports conducted in 2016 for four currently operating facilities in Florida. In our assessment, we focused on prohibitive materials in the outbound stream, due to the scope of the study. Average rates (weight of the contamination/weight of total sample) of prohibitive materials in the OCC stream and the ONP stream were 5.12 and 7.13 percent, respectively. The assessment of the contamination rates of outbound materials produced alarming results. Considering the paper mill standards are only 3 percent for OCC and 2 percent for ONP, these results are disconcerting. With these standards in place, only 34 percent of OCC samples and 0.3 percent of ONP samples meet paper mill standards. Our analysis also found that both OCC and ONP samples were most frequently contaminated with residue and plastics. In the OCC stream, these contaminants mostly included film plastics and high density polyethylene (HDPE). Comparatively, ONP samples were mostly contaminated by polyethylene terephthalate (PET) and MRF film plastics. 4. Assessment of Material Recovery Processes: Researchers obtained MRF audit data conducted by one of the largest counties in Florida, in terms of population and waste generation. Based on the process flow of the single stream MRF, efficiency of each process and sort results of each recyclable stream were analyzed using mass balance analysis. Based on the results, researchers found the most common types of contaminants in each recyclable stream and the most inefficient processes in the separation and sorting of recyclables. Here, the efficiency rates of Disc Screen 1 and Eddy Current Separator were remarkably low. Disc Screen 1, which separates OCC from other types of fiber, had an efficiency rate of 45 percent, and Eddy Current Separator, used to separate aluminum cans from the stream, had an efficiency rate of 75 percent. With respect to the sorting results, the lowest recovery rates among colored HDPE materials and mixed glass were found to be 65 and 70 percent, respectively. XIII

14 RESEARCH TEAM Nurcin Celik (P.I.) is an Associate Professor in the Department of Industrial Engineering at the University of Miami. She received her M.S. and Ph.D. degrees in Systems and Industrial Engineering from the University of Arizona. Her research interests lie in the areas of integrated modeling and decision making for large-scale, complex, and dynamic systems such as solid waste management systems and electric power networks. She received the Presidential Early Career Award for Scientists and Engineers in 2017 from the White House. This is the highest honor bestowed by the U.S. government on outstanding scientists and engineers beginning their independent careers. She has also received many other awards including the IAMOT Young Investigator Award (2016), Eliahu I. Jury Career Research Award (2014), AFOSR Young Investigator Research Award (2013), University of Miami Provost Award (2011, 2016), IAMOT Outstanding Research Project Award (2011), IERC Best Ph.D. Scientific Poster Award (2009), and Diversity in Science and Engineering Award from Women in Science and Engineering Program (2007). She can be reached at Haluk Damgacioglu is a Ph.D. candidate in the Department of Industrial Engineering at the University of Miami. He received a B.S. and an M.S. in Industrial Engineering from the Middle East Technical University in Turkey. He has received several awards including the 2017 IISE Gilbreth Memorial Fellowship Award, 2016 University of Miami GSA Academic Excellence, Leadership and Service Award and 2015 ICCS Best Workshop Paper Award. His research interests lie broadly in application of dynamic data driven adaptive simulations and simulation optimization under uncertainty. His address is haluk.damgacioglu@miami.edu. Lea Perez is an undergraduate student studying Industrial Engineering and minoring in Architecture at the University of Miami. She graduated from Design & Architecture Senior High in the Design District of Miami, where she studied fashion design. She is presently Internal Affairs Chair and member of Tufaan, UM's premier South Asian acappella group. Her interests include designing systems in areas like fashion and architecture that give priority to sustainability and the environment. She can be reached at lmp72@miami.edu. XIV

15 DISSEMINATION ACTIVITIES JOURNAL PAPERS AND BOOK CHAPTERS: 1. Damgacioglu, H., Perez, L., Celik, N. Assessment and Evaluation of Inbound Contamination in Single Stream Recycling Systems A Case Study of Florida working journal paper. 2. Damgacioglu, H., Hornilla, M., Celik, N. Assessment and Evaluation of Outbound Contamination in Single Stream Material Recovery Facilities A Case Study of Florida working journal paper. PRESENTATIONS AND SITE VISITS: 1. TAG I Meeting: The first TAG meeting took place on July 14, 2017 at the McArthur Engineering Building of the University of Miami with 13 attendees. A conference call for those who wanted to attend the meeting remotely was established. Several comments made during the first TAG meeting were recorded. 2. TAG II Meeting: The second TAG meeting took place on March 9, 2018 at the McArthur Engineering Building at the University of Miami with 14 attendees. A conference call for those who wanted to attend the meeting remotely was established. Multiple comments were offered during the second TAG meeting. TAG MEETINGS: The project team hosted two TAG meetings on July 14, 2017 and on March 9, WEBSITE: The team created and posted an enhanced website describing the project, accessible at XV

16 Percent of Population with Recycling 1 INTRODUCTION Over the past two decades, the quantity of municipal solid waste produced in the United States and particularly in Florida has increased significantly (by over 73 percent), outpacing all other nations (Environmental Protection Agency, 2017). In order to deal with this burgeoning waste stream, as well as a multitude of other environmental, economic, and social factors, different curbside recycling programs, including single stream recycling (SSR), have been introduced to practice over time. SSR has become increasingly popular due to its capabilities to better attract the participation of communities in recycling while reducing the cost of collection of curbside recyclables compared to multi or dual stream recycling. In SSR, all recyclables are separated from municipal solid waste into a sole compartment in a collection truck, where payloads and costs are significantly reduced. According to an American Forest and Paper Association report, in 2005, 22 percent of the United States population had access to SSR, but by 2014, that had grown to 73 percent (AF&PA, 2015) as shown in Figure 1. Similarly, 77 percent of material recovery facilities (MRFs) built in the United States after 2007 are equipped to process single stream (Berenyi, 2015). This surge in popularity is also evident in Florida where, based on our investigations, at least 24 out of a total of 67 counties have currently operating SSR programs in place including Brevard, Dade, Escambia, Marion, and Orange counties Two or More Streams Single Stream Including Galsss Single Stream Excluding Glass Combination Figure 1. Distribution of paper/paperboard collection techniques in the United States (AF&PA, 2015) The advantages of SSR systems are comprised of lower worker injuries on collection routes, reduced collection costs due to single-driver trucks, increased participation rates by residents, and higher volumes of collected recyclables. However, SSR systems may operate at the expense of higher volumes of materials requiring pre-sorting at regional MRFs, as well as higher contamination rates in the materials directed to the mills (Lakhan, 2015). To this end, glass, plastic bags, and the increasing amount of food-waste in the incoming comingled stream pose significant challenges for MRFs (Cascadia Consulting Group, Inc., 2006). Small glass pieces and shards may get stuck in paper, cardboard, and plastic items, making them unrecyclable. Glass also reduces the life of the equipment at the MRFs intermediary processors and increases the operational costs for increased facility downtime. The impact of the damage leads to a loss in labor for repairs, new parts and equipment, and broken pieces of glass shards, which present safety hazards for MRF employees. For instance, Shoreline Recycling & Transfer Station in DC estimated that the damage caused by glass shards costs their facility about $500,000 per year, solely for replacement of their screen basket valves (Cascadia Consulting Group, Inc., 2006). 1

17 On average, 40 percent of glass from single stream collection winds up in landfills and another 20 percent constitutes small broken glass ( glass fines ), used for low-end applications. Only 40 percent remains to be recycled into containers and fiberglass (Kinsella & Gertman, 2007). In contrast, 90 percent of the mixed glass from dual stream recycling (DSR) systems is recycled into containers and fiberglass, and the remaining 10 percent comprises glass fines used for lowend applications, with nearly nothing being sent to landfills (see Figure 2). The broken glass adversely affects MRF operations as it leads to higher rates of residuals and degraded product quality. In the recycling supply chain, receiving poorly sorted materials from a processor discourages manufacturers from expanding upon or investing in new recycled product manufacturing capacity. Additionally, the manufacturer may return to using raw virgin resources (Kinsella & Gertman, 2007). The low quality of recovered materials may further lead to imperfections in the finished products and low customer satisfaction, resulting in lower demand. Percentage Single Stream Dual Stream Landfill Glass Fines Recycled(containers and fiberglass) Figure 2: End-market for collected glass (Kinsella & Gertman, 2007) To this end, we investigate the extent to which recovered materials are contaminated and evaluate if SSR programs have a significant role on the contamination of recycled materials. We also explore new and emerging advanced material recovery processes that may help with the issue of contamination in recovered materials. The remainder of this report is organized as follows: Section 2 provides background information, along with a review of works in the literature. Section 3 details the considered material recovery facilities. Section 4 explains the specifics of the collected data, details of the statistical analysis methods conducted, and the results obtained in this study. Finally, Section 5 discusses the conclusions drawn in this work. 2 BACKGROUND AND LITERATURE REVIEW In SSR systems, all recyclables are separated from municipal solid waste into a sole compartment in a collection truck. Amongst the curbside recycling programs, SSR has been a growing trend in the last decade due to its ability to reduce collection costs, increase the amount of collected material and increase participation. SSR accomplishes this by avoiding a cumbersome sorting process at the individual level (i.e., customers use a single all-purpose bin 2

18 Residual rate (%) for recycling) (Wang, 2006), making the process more consolidated and user-friendly. However, this system does not necessarily lead to a higher recycling rate since improperly-sorted materials may be mixed with other recyclables and go on to contaminate the recycling stream. Contamination in SSR systems has been found to result in down-cycling of the products (Chameidas, 2013). Contaminated recyclables pose serious problems for processors and endusers such as paper mills and glass manufacturers. These problems include but are not limited to equipment damage, lower quality in recyclables, and frequent downtime due to equipment cleaning and repair. Composition and quantity of contaminants vary among communities and waste collection types. Beck (2006) analyzed this in different types of MRFs in California, including single stream, multi stream, and mixed waste facilities. Results obtained from 83 MRF lines have shown that multi stream processing facilities have the least inbound contamination rate (6 percent) with less moisture and food contamination within the fiber material than expected. Comparatively, the average contamination rate in the incoming material for single stream was found to be 14 percent, with a range of 2 to 50 percent. Beck (2006) also provided a contaminant characterization of different MRF types in California in terms of the average proportion of each material type by weight in the total contaminant weight, as shown in Figure 3. 35% 30% 25% 20% 15% 10% 5% 0% C&D Paper Glass Metal Electronics Plastic Organic Single Stream Multi Stream Mixed Waste Figure 3. Residual characterization for each MRF type in California (Beck, 2006) While overall profiling of these recycling systems provides valuable insights for the improvements and investments on MRF, the Beck (2006) study is limited to the 68% Commingled 0.33% 3.40% 15% incoming stream of MRFs. In a related Stream and complementary study, Department of Ecology of State of Washington 42% Commingled 0.10% 1.30% Stream (2010) studied the effectiveness of 5.70% sorting each material in the commingled 100% Curbside collection systems. As a result of this Sort 0.25% study, on average, approximately 93 to 96 percent of recyclable paper and 84 Glass Rate Prohibitives Outthrows percent of plastic containers were found Figure 4. Effects of single stream on NORPAC Paper to be properly sorted and sent to correct Mill (Morawski, 2010) 3

19 Inbound Tons Residue Rates (%) markets, while 14 percent of plastic containers were found to cause contamination in the paper that was being sent to paper mills, and the remaining 2 percent were disposed of immediately. On average, one-third of aluminum cans and two-thirds of aluminum foil were found to be improperly sorted and mixed with other materials. Despite these occurrences, the processing facilities were shown to sort the materials quite effectively (i.e., on average, percent of the materials were transferred to the proper markets). However, significant loss may occur at enduser facilities such as paper mills and recycled glass processors as well as glass bottle manufacturers even if the level of contamination is small. For instance, only 0.46 percent of glass contaminants in the total material stream caused NORPAC Paper Mill an additional $360,000 per year (Morawski, 2010). Figure 4 further shows that this facility experienced drastic increases in the rates of out-throws, prohibitive materials, and glass contamination once its suppliers switched to single stream collection. Some studies in the literature focus on the economic impacts of high rates of contamination on the sorting facilities. For example, even though commodity prices were declining (Robinson, 2014), Waste Management Inc. s processing costs increased by 20 percent between 2012 and 2014, due to contamination in single stream collection and low-quality recyclables. A similar study conducted by McCormick (2015) concluded that in Florida, the cost of inbound contamination to the MRFs was estimated to be around $125 per ton between 2013 and In another study, Moreau (2015) investigated the Chittenden County MRF in Vermont. The facility was built as a dual stream facility in 1993 and converted into single stream in 2003, and its glass processing system was also updated in Residue rates (including the non-recyclable materials in the incoming stream and the recyclables lost during the sorting process) were measured before and after the conversion to single stream (see Figure 5). Following the conversion to single stream, the amount of materials collected as well as the residue rates increased simultaneously. However, the residue rates diminished immediately after an equipment upgrade in 2014, suggesting that the way sorting is handled in MRFs also has an impact in these rates. 50,000 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000 0 Dual Stream Single Stream Upgrade 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% Fiscal Year Figure 5. Chittenden County residue rates before and after their switch to single stream (Moreau, 2015) 4

20 Several studies (AF&PA, 2013; Conservatree, 2016; Yasar et. al., 2017) have concluded that the SSR-driven paper recycling industry faces contamination issues from prohibited materials like glass, plastics and other polymer materials. The glass recycling industry suffers from similar problems. Even though glass is 100 percent recyclable and does not lose its quality in the recycling process (GPI, N.D.), much of the glass recycling process is hindered by contaminants in the commingled stream. Cullet and glass fines are the two main types of recovered glass. Cullet is a higher-grade product (worth $100-$149 per ton) that is produces new glass when it is mixed with virgin material in glass manufacturing furnaces (Sustainability Victoria, 2014). Glass cullet is defined as contaminant-free container glass, which is sorted by color (clear amber, and green) and is expected to meet particle size specifications before it is used in glass manufacturing (Cattaneo, 2010). The other main type of recovered glass is glass fines, which are very small pieces of glass that are used for non-container glass products. The collection and processing of glass using SSR poses the following challenges to the recycling industry: SSR causes glass to break into very small pieces that cannot be sorted with currently available technologies in MRFs. To be reused, glass cullet needs to be sorted by color, and the optical color sorting technologies require high capital investment. Contaminants such as non-recyclable material, metal, paper, plastic, etc. in glass cullet decrease the quality of recovered glass, cause equipment damage, and increase the cost for glass manufacturers and MRFs. Table 1: Construction application of glass cullet (GPI, N.D.) Application Cullet Debris Content Level 100% Recycled Glass Fines Retaining Wall (structural 20%-30% 5% backfill) 50% Retaining Wall 100% 10% (Non-structural backfill) 0% Utility Bedding 100% 5% Single Dual Deposit Embankments 20%-30% 5% Stream Stream Return Foundation Drainage 100% 5% Figure 6. End markets for glass collected from Pavement Base 20% 5% different systems (DSM Environmental Services, Trench and Foundation 2011) Backfill 100% 5%-10% Contaminated glass cullet obtained from SSR is down-cycled and cannot be used for new glass production. Luckily, the glass container industry has seen an increase in average glass cullet use from 25 percent to approximately 34 percent since December 2008 (Bragg, 2015). Table 1 represents the glass cullet purity and usage in construction. Some studies in the literature analyze the impacts of different collection systems on glass recycling. For example, DSM Environmental Services (2011) observed that glass from source separated drop-offs are often found to be less contaminated than the glass collected from dual or 5

21 single stream. At Strategic Materials, Inc., which is the largest glass processor in North America, 98 percent of color sorted glass from deposit return collection and 90 percent of mixed glass from dual stream collection are used for containers and fiberglass, while only 40 percent of commingled glass from single stream collection can be recycled into containers and fiberglass (see Figure 6) (Cattaneo, 2010). In a related study conducted for the State of Victoria in Australia, researchers analyzed glass loss across the recovery process (Sustainability Victoria, 2014). They found the highest loss occurred due to splintering during collection and compaction of recyclables (see Figures 7 and 8). According to a Container Recycling Institute (CRI) report, breakage during collection and processing resulted in lower-grade glass fines (CRI, 2009). Then, DSM Environmental Services (2011) analyzed the glass losses for different types of glass collection methods in Ohio. Eighteen percent of glass collected is lost during the Optical Sorting process after commingled collection. Source separation by color resulted in the lowest glass loss rate with 1 percent (Figure 8). 26 % 3% 3% Loss to Landfill 24 % Breakage During Collection Figure 7. Glass losses across the recovery process (Sustainability Victoria, 2014) 18 % 1 % 3 % Source Separated Three Mix Commingled Figure 8. Glass losses in Ohio by collection system (CRI, 2009) Figure 9. Number of cullet processors in 35 states (GPI, 2018) 17 The most important users of recycled glass are glass container manufacturers. In one study, Goodman (2006) interviewed recycled glass end users in Minnesota about contaminant types in their feedstock, operational problems caused by contamination, and the change in the quantity of recycled cullet that they receive. Ceramics, pottery, Pyrex, and mixed glass are listed as the most problematic contaminants for their operation. According to a GPI report (GPI, 2018), Florida is amongst the top 10 states in U.S. with respect to number of glass processing facilities (see Figure 9). However, Florida s average glass recycling rates have decreased since the number of SSR systems in Florida has increased over the past decade (FDEP, 2017). Collier (2005), Miami Dade (2008), Broward (2009), Brevard (2009), and Charlotte (2010) are examples of counties in Florida that have made the switch to SSR. The average recycling (AR) rates and the average glass recycling (AGR) rates of these counties before and after switching to SSR are shown in Figure 10, respectively. Here, all five counties have experienced an increase in AR with a decrease in their AGR after switching to SSR. Investigating this issue, in this work, we evaluate if the SSR programs have a significant role on the contamination of material from broken glass and other non-recyclables. 6

22 Figure 10. Average recycling rates (AR) and glass recycling rates (AGR) of counties that switched to SSR in Florida (FDEP, 2017) 3 MATERIAL RECOVERY FACILITIES Material recovery facilities (MRFs) are one of the critical components in the integrated solid waste management system. Understanding the way MRFs operate and handle challenges given their recent technological and organizational developments is critical for establishing an effective solid waste management system. MRFs are the processing facilities where received materials are separated, sorted, and prepared for marketing either to end users (manufacturers) or to other facilities for additional processing. The design of the MRF processing depends heavily upon the type of the waste collection system they use. Below are the main types of waste collection systems and their descriptions. Source separated: Residents sort the recyclables by type for collection. The primary purpose of the facility is to remove contaminants often by baling, flattening, or crushing prior to sending them to their respective markets. Dual stream: Residents sort the materials in two separate streams, generally fiber (newspaper, magazines and catalogs, mixed paper, cardboard, etc.) and commingled containers (plastic, glass, metal, and sometimes aseptic containers). Dual stream systems utilize a combination of automated equipment and manual sorting to separate and sort the received materials. Single stream: Residents put fiber and commingled containers in the same bin for collection. The separation of materials into two separate streams (fiber and containers) occurs during the first stages of processing. The rest of the processes are similar to those of dual stream. Mixed waste: Unsegregated mixed waste is separated using various technologies. Collected waste is first dumped on a tipping floor where recyclable materials are then processed using equipment similar to that of single stream MRFs. 7

23 While each type of MRF employs common design principles and sequencing in the configuration of equipment and labor, each one has different additional steps and processes for sorting and recovering waste streams. Seventy-seven percent of all MRFs built after 2007 in the US are single stream MRFs due to increasing popularity of the single stream collection system (Berenyi, 2015). These new single stream plants process, on average, 225 tons of recycled materials per day with multiple mechanical and optical technologies to achieve high levels of sorting efficiency (Berenyi, 2015). 3.1 Material Definitions The understanding and categorization of the materials (both recovered and discarded) is essential to the proper comprehension of the functioning of any MRF. In this report, we adopt the same material definitions used in waste composition studies provided by Kessler Consulting Inc (Kessler Consulting Inc, 2009, 2010, 2013, 2014a, 2014b, 2016). The entirety of the materials processed in a recycling facility are organized into five categories. These categories are paper, plastic, glass, metal, and residue. The recoveries of plastics occur throughout the entire MRF processing and can be seen in Table 2. Table 2. Plastic material definitions Plastic Sub-Category PET Bottles (SPI #1) Polyethylene terephthalate Natural HDPE Bottles (SPI #2) High density polyethylene Colored HDPE Bottles (SPI #2) High density polyethylene Non-Bottle PET Non-Bottle HDPE Expanded Polystyrene (Styrofoam) Mixed Plastic Containers Bulky Rigid Plastics Plastic Film (Residue) Non-Container Expanded Polystyrene (Styrofoam) (Residue) Description/Examples Clear and colored plastic bottles coded PET #1 such as soda bottles, water bottles label with SPI #1. Does not include loose caps. Clear/natural plastic bottles coded HDPE #2 such as milk jugs, vinegar bottles and gallon water bottles. Does not include loose caps and lids. Pigmented plastic bottles coded HDPE #2 such as detergent, shampoo, and orange juice bottles. Does not include loose caps and lids. Clear and colored plastic items labeled PET #1 such as clamshell containers, frozen food trays, disposable cups and other items labeled PET #1. Wide mouthed tubs and containers labeled HDPE #2 including lids. Examples include yogurt cups, margarine tubs, Cool Whip tubs and other non bottle HDPE items. Styrofoam containers such as egg cartons and clamshell food containers. All plastic containers coded #3 #7, such as containers, pill bottles, Arizona Iced Tea gallon jugs, etc. Consists of non container rigid plastic items such as plastic drums, crates, buckets, baskets, toys, refuse totes, and lawn furniture, flower pots, laundry baskets, and other large plastic items. Does not include electronic toys. Loose and bagged plastic bags, garbage bags, shrink wrap, resealable bags, etc. Non container Styrofoam such as packaging peanuts and other packaging. 8

24 The next tables are organized in the order in which each material is recovered in a typical MRF. The first type of material to be recovered is paper (see Table 3), which is immediately followed by glass (see Table 4). Because glass is crushed in the early stages of the process, and then optically sorted by color during the SSR process.it does not necessarily have multiple subcategories. Still, we defined a table for it in order to provide details of the collected materials. Lastly, there are metals, or ferrous materials (see Table 5). Table 3. Paper recyclables recovered in MRFs Paper Sub-Category Newspaper Corrugated Cardboard (OCC) Waxy Cardboard Mixed Paper Loose Shredded Paper Aseptic Containers Description/Examples Newspaper (loose or tied) including other paper normally distributed inside newspaper such as ads, flyers, etc. Newspaper found inside plastic sleeve will be removed from plastic and sorted accordingly. Brown cardboard boxes with a wavy core (no plastic liners or packaging Styrofoam ). Does not include small pieces of OCC within shrink-wrap plastic such as those from a case of bottled water. All wax coated OCC will be sorted and weighed separately from non wax OCC. Printed or unprinted paper including white, colored, coated and uncoated papers, manila and pastel colored file folders magazines, telephone books, catalogs, paperboard, chipboard, brown paper bags, mail, bagged shredded paper and other printed material on glossy and non glossy paper. Loose shredded residential mixed paper or newspaper. Gable top milk cartons, juice boxes, and other similar containers. Table 4. Glass recyclables recovered in MRFs Glass Sub-Category Mixed Glass Containers and Jars (Glass Containers) Description/Examples Clear, green, and amber glass bottles and jars as well as broken glass pieces larger than half a square inch. Table 5. Metal recyclables recovered in MRFs Metal Sub-Category Aluminum Cans Aluminum Foil and Pie Plates Tin/Steel Cans Scrap Metals Rejects Description/Examples Aluminum soft drink, beer, and some food cans. Aluminum foil, pie plates, and clean catering trays. Tin plated steel cans, usually food containers, and aerosol cans, including labels and steel caps. Non container ferrous scrap metals such as pipes, coat hangers, and miscellaneous scrap metal. The previous tables contain the materials recovered during the SSR process. The residues that are discarded during the recycling process are described in Table 6. These are non-recyclables that are sorted out by any of the different recycling processes. 9

25 Table 6. Residues found in MRFs during single stream recycling Residue Sub-Category Rejects Grit Liquids 10 Description/Examples Materials not included in the other categories, such as bagged garbage, fast food lids and straws, CDs and VHS tapes, composite materials, Christmas lights, hoses, electronics, recyclable items full of food (non liquid), loose plastic caps and lids, or plastic cutlery and plates. All items that fall through a half inch mesh. All liquids found within recyclable containers. 3.2 Single Stream MRF Process Flow Single stream MRFs are capable of recovering fiber, glass, metal and plastic from a commingled recyclables stream with the appropriate equipment and design. Based on our literature review (Kessler Consulting Inc., 2009; Combs, 2011; Pressley et al., 2015), synthesis of our discussions with the counties in Florida and our experience from previous studies, we demonstrated a typical single stream MRF design that is capable of paper, glass, plastic, and metal recycling, as shown in Figure 11. Paper recycling process: The collection truck unloads the collected recyclables on the tipping floor and a claw pushes the material into the Drum Feeder. The Drum Feeder distributes the collected material to the Conveyor, where large items and prohibitive materials that can damage downstream equipment are removed by manual sorting. During manual sorting, plastic films (e.g., plastic bags) are also removed. Then, the remaining recyclables continue to Disc Screen 1, which separates the OCC. Remaining mass travels to Disc Screen 2, which removes ONP. Residual material from Screen 2 continue to the Scalping Screen, which then separates fiber from containers and other materials. The fiber streams from Disc Screen 2 and the Scalping Screen proceed to a manual sort to remove contaminants before the baling process. After the baling process, the paper bales are sent to paper mills and processors. Glass recycling process: After glass and other containers are separated from fiber materials by Disc Screens, all containers continue to the Glass Breaker Screen. The Glass Breaker Screen is designed to separate glass from other materials like plastic bottles, milk cartons, and metal cans. It allows crushed glass to fall between discs, while fiber and remaining containers (i.e., plastic, aluminum, and metal) pass over the top. It also provides more the uniform sizing of glass cullet required for optical separation and subsequent remanufacturing. Then Air Knife eliminates light contaminants (i.e., fiber, light debris, etc.) to maximize the end product quality. In the last step, Optical Sorter identifies pre-determined material(s) using optical technology (e.g., cameras, lasers, sensors) and sorts glass cullet by color. Plastic and metal recycling process: The materials passing over the Glass Breaker Screen are conveyed to an Optical Sorter that recovers PET. The remaining stream is conveyed to a second Optical Sorter that removes all colors of HDPE. The remaining stream proceeds to a magnet for ferrous recovery. The material remaining after the magnet proceeds to an Eddy Current Separator for aluminum recovery. The remaining residual stream goes to a manual sort, where any recyclable materials missed by the separation equipment are recovered by pickers and sent to the 2-way Baler. The aluminum, ferrous, HDPE, and PET streams are separated and stored in cages prior to baling. Each stream is inspected for contaminants prior to baling.

26 Figure 11. Single stream MRF process flow with equipment configuration to recover fiber, glass, plastic and metal materials 4 DATA COLLECTION AND ANALYSIS Researchers collected various data regarding the inbound contamination rates from waste composition studies provided by 15 counties around Florida, the outbound contamination rates from four currently operating facilities in Florida, and the assessment of existing processing technologies from one MRF audit. 4.1 Inbound Contamination Analysis One of the major tasks in this work is to investigate if the contamination rates of the inbound stream have been impacted by switching to SSR programs. In order to identify and evaluate this impact, the contamination rates in different recycling programs should be compared. Researchers first collected the data regarding the inbound contamination rates by bringing together the recyclable composition studies conducted for the inbound waste stream in the following counties and major cities in Florida: Alachua, Brevard, Broward, Citrus, Escambia, Hillsborough, Indian River, Lee, Leon, Marion, Okaloosa, Pasco, Santa Rosa, Sarasota, Seminole, Fort Lauderdale, Margate, and Lauderdale by the Sea. The waste composition studies provided individual sample results showing the breakdown of recyclable materials, as well as the contamination rates. DSR data consisted of the contamination in the paper stream. For confidentiality purposes, county names are removed in the rest of the report. After assessing the weights of non-recyclables in the collected waste composition studies, we obtained 170 samples from SSR and 45 samples from DSR for inbound contamination rates. We 11

27 conducted descriptive statistical analysis and analysis of variance (ANOVA) to investigate if there is a statistical significance of the difference between the mean contamination rates of the inbound SSR and DSR systems. In order to visualize the descriptive statistics of the data collected for SSR and DSR systems, we built a boxplot combining the samples of both systems along with their outliers (see Figure 12). Here, the standard deviation (8.97) and mean (18.54) of the SSR contamination dataset were found to be higher than that of the DSR contamination data set (3.08 and 3.89, respectively). Comparison of the two boxplots reveals the difference in rates between the two systems in terms of mean, median, and overall distribution of outliers. It is also shown that SSR contamination rates were more spread out over a wide range of values than were DSR contamination rates. A higher standard deviation in the SSR data denotes the differences in implementation and success rates of variations of SSR programs and people s contributions towards it. For example, some may assume that even non-recyclable materials can be thrown in SSR bins (i.e., researchers found diapers, food waste in the SSR bins). Histograms for the SSR and DSR contamination rates were plotted to better represent the wide range of SSR contamination rates (see Figure 13). The contamination rate of one SSR sample was 48.2 percent which means that almost half of the collected materials were actually non-recyclables. However, approximately 3 percent of samples promised that even in SSR systems, low levels of contamination rates could be achieved. Based on the significant difference observed through these boxplots and histograms, we have conducted further detailed analysis on the data obtained as the following. Figure 12. Boxplot of SSR and DSR contamination data 12

28 Figure 13. Histograms of SSR and DSR contamination rates We use ANOVA to test if there is statistically significant evidence that shows contamination rates in SSR systems are higher than the rates in DSR systems. ANOVA primarily assumes that the data of each group are normally distributed. Since the histogram plot of DSR samples did not follow a bell-shaped curve, we first conduct a normality test on the collected data for each group. Here, we conducted the Anderson-Darling (AD) normality test, a non-parametric test that comes in handy when there are a limited number of samples available. AD takes both the means of samples and differences in shape and variability of the distributions into account. Normality test plots and statistics for SSR and DSR samples are shown in Figures 14 and 15, respectively. In these figures, blue points represent each sample and red lines shows the normality test statistic curves. It is expected that all the samples lie on the red line. Based on AD normality test statistics, p-values of both groups were smaller than which means that both SSR and DSR samples comply with the normality assumption of ANOVA. Once the available data passes the normality test as described, an ANOVA test is conducted to differentiate between the sources of variances amongst these available data. ANOVA is a widely-used technique to compare the ratio of between-group variance to within-group variance using the F-critical ratio test statistic. The detailed information about ANOVA is provided in Appendix A. Here, our null hypothesis was SSR and DSR systems have equal contamination rates while the alternative hypothesis was the contamination rates in these systems are different. Our ANOVA resulted in very high F-ratio ( ) which corresponds to very low p-values (almost equals to 0) as shown in Table 7. The ANOVA results rejected the null hypothesis at more than (α = 1 p value) significance level. In other words, the ANOVA analysis below reveals significant statistical evidence in rejection of the hypothesis that the contamination rates in SSR and DSR systems are the same and supports the alternative hypothesis that the contamination rates in single stream recycling are higher than those in dualstream recycling. 13

29 Figure 14. Results of AD normality test for SSR contamination data Figure 15. Results of AD normality test for DSR contamination data Table 7. ANOVA results of SSR-DSR comparison Source of variation Sum of Degrees of Mean F (test P-value squares freedom square statistic) Between Groups Within Groups Total Once we analyzed the data in its totality as mentioned above, we further investigated the difference in contamination rates of the SSR and DSR systems at a county level. Here, we first plotted a combined histogram of contamination rates of each county as shown in Figure 16, followed by some descriptive parameters as in Table 8. The names of the counties here are noted as County 1 through 16 for confidentiality purposes. With respect to descriptive analysis, the samples of Counties are removed from some of our analysis due to their sample size (<5). The combined histogram in Figure 16 visibly shows that DSR systems in general have lower contamination rates than those of SSR systems. Of these, Counties 5, 8, and 9 (DSR) demonstrate the lowest contamination rates at less than 5 percent, while Counties 3, 4, and 14 (SSR) demonstrate the highest contamination rates at more than 20 percent. From this histogram, we can conclude a wider variation of contamination rates between counties operating with SSR, with the largest variation occurring between Counties 1-4. On the contrary, County 10 demonstrates the lowest and most promising contamination rate of all counties operating with SSR at just 5.98 percent. 14

30 Figure 16. Histograms of contamination rates of each county Table 8. Descriptive analysis of contamination rates for each county County Recycling Number of Standard Mean Index System Samples Deviation Maximum Minimum County 1 SSR County 2 SSR County 3 SSR County 4 SSR County 5 DSR County 6 SSR County 7 SSR County 8 DSR County 9 DSR County 10 SSR County 11 SSR County 12 DSR SSR DSR County 13 SSR County 14 SSR NA County 15 SSR NA County 16 SSR NA Supplementary analysis on inbound contamination data was conducted to better understand the variance in contamination rates among counties. Here, six SSR counties (Counties 1-4 and Counties 6-7), which had more than 10 samples, were selected. A boxplot of the contamination rates in the six SSR counties is shown below in Figure 17. Then, another ANOVA test was designed to determine the statistical significance of the difference between the mean 15

31 contamination rates of these counties (see Table 9). Here, the difference in the counties inbound contamination rates was found to be statistically significant at a 99 percent significance level. A more detailed comparison was conducted using a multi-comparison test on these six SSR counties. Our results (see Figure 18) indicated that Counties 3 and 4, with respective contamination rates of 28.2 and 22.3 percent on average, have means significantly higher than the other counties based on a 95 percent confidence level. Figure 17. Contamination rates in SSR counties Table 9. ANOVA results of contamination on the mean contamination rates of six selected SSR counties Source of variation Sum of squares Degrees of freedom Mean square F (test statistic) P-value Between Groups Within Groups Total

32 Figure 18. Contamination rates in SSR counties To further understand the differences between counties, our data was analyzed to find if any correlation exists between contamination rates and the demographics of these six counties (see Figure 19). These factors included population, population density, median age, average income level, poverty level, White population percentage, Hispanic population percentage, and Black population percentage. Contrary to popular belief (Kessler Consulting Inc. 2013; 2014a; 2014b; EPA, 2015), our research showed no correlation between inbound contamination rates and ethnicity, but a positive correlation between median age and contamination, and a negative correlation between income level and contamination. Here, the counties with lower income levels and higher ages can develop specific education programs and/or incentives to reduce the contamination levels in the collected recyclables. 17

33 Figure 19. County correlation matrix 4.2 Outbound Contamination Analysis SSR affects not only the collection systems, but also the MRFs, as adaptation is needed to process the commingled recyclables. As shown in the previous section, SSR systems had significantly higher contamination rates compared to DSR. In this section, we assessed the contamination levels in end products baled by MRFs. To conduct this assessment, we obtained 35 old corrugated cardboard (OCC) samples and 266 old newspaper (ONP) samples from audit reports for four currently operating facilities in Florida. In our assessment, we only focused on prohibitive materials in the outbound stream due to the scope of the study. Based on the collected audit reports, glass, plastic, metals and residue were considered prohibitive materials for both ONP and OCC streams. In our assessment, we compared mill standards of accepted contamination rates and the number of samples in SSR that meet these standards. The assessment of the contamination rates of outbound materials produced distressing results. Average rates (weight of the contamination/weight of total sample) of prohibitive materials in the OCC stream and the ONP stream were 5.12 and 7.13 percent, respectively. Figures 20 and 21 show how these samples compared to allowable paper mill limits for each of the OCC and ONP samples. Considering the paper mill standards are only 3 percent for OCC and 2 percent for ONP, these results are disconcerting. With these standards in place, only 34 percent of OCC samples and 0.3 percent of ONP samples meet paper mill standards. 18

34 Figure 20. OCC prohibitive materials analysis Figure 21. ONP prohibitive materials analysis Figure 22(a) shows that OCC samples were most frequently contaminated with residue and plastics, which includes film plastics and high density polyethylene (HDPE). Similarly, Figure 22(b) shows ONP samples were mostly contaminated by residue and plastics, specifically polyethylene terephthalate (PET) and MRF film plastics. The prohibitive material categories with respect to SSR are defined as the following. Residues: Residues make up the largest portion of prohibitive materials in the outbound stream. Residues in the end products of MRFs arise from the following: 1) collected nonrecyclables in the inbound stream (inbound contamination) and 2) collected recyclables that are not separated out in the MRFs. As shown in Section 4.1, inbound contamination rates were much higher in SSR systems compared to DSR. Also, since recyclables are commingled in the SSR bins, residue rates in single stream MRFs are expected to be higher than residue rates in dual stream MRFs. Plastics: Plastics are collected in separate bins in DSR, which naturally decreases the amount of plastics in the outbound stream, compared to SSR. In single stream MRFs, 19

35 sticky plastics such as film plastic and plastic bags were problematic in the fiber stream separation process. Metals: Tin is the most problematic contaminant metal in fiber recycling. It makes up an average of 80 percent of metal contaminants in fiber stream. Glass: The average rates of glass (weight of the glass/weight of total sample) in the OCC and ONP streams were 0.04 percent and 0.2 percent, respectively. While these numbers are perceivably very low, even a small amount of glass can cause significant equipment damage in MRFs. For example, in the NORPAC Paper Mill case, 0.33 percent of glass in the fiber stream resulted in $400,000 equipment damage (Morawski, 2010). Moving forward, MRFs should improve process efficiency where the HDPE and PET are separated out from the OCC and ONP streams. Since film plastics are generally considered nonrecyclable, the amount of collected film plastics can be reduced in the inbound stream by educating the residents and through advertisement. a) b) 72% 25% 0% 3% 57% 35% 4% 4% Plastics Glass Metal Residue Figure 22. Types of contamination in corrugated cardboard (a) and newspapers (b) 4.3 Material Recovery Facility (MRF) Audit Analysis In this study, MRF audit data (obtained from one of the largest counties in Florida in terms of population and waste generation) was analyzed using a mass balance analysis. Mass balance analysis represents the mass of each proportion of recycled materials (i.e., paper, glass, metal, etc.) that passes through a process or equipment in the MRF, recorded in terms of mass per hour. To the best of our knowledge, this study is the first to analyze the separation of efficiencies for each part of the MRF process. The information that exists is based on shared information from experienced MRF operators and examination of operating MRF equipment (Pressley et al., 2015). More specifically, the mass of the waste proportion, i, recovered by each process or equipment; j, is calculated as follows. m removed j,i = f separation TP j,i m j,i (1) In Equation (1), m removed j,i shows the mass of waste proportion i removed by equipment j, f separation TP j,i represents the separation efficiency of equipment j for waste proportion i, and m j,i demonstrates the incoming mass to equipment j for waste proportion i. The units used for all analysis of mass throughput are megagrams (Mg). The mass of waste proportion i remaining 20