i 

## ONLINE SORTING OF RECOVERED WOOD WASTE

USING AUTOMATED X-RAY TECHNOLOGY

FINAL REPORT Submitted on November 30, 2009

Prepared for Town of Medley for Submission to the FDEP Innovative Recycling Grants Program

Submitted by:

Hasan Abdel Fattah, M.S. Helena Solo-Gabriele, Ph.D., P.E. Dept. of Civil, Arch., and Environ. Engineeri ng, University of Miami, Coral Gables, FL

Timothy Townsend, Ph.D., P.E. Jianye Zhang, M.S. Dept. of Environmental Engineering Sciences, University of Florida, Gainesville, FLii 

### TABLE OF CONTENTS
Page

LIST OF FIGURES

LIST OF TABLES

LIST OF ABBREVIAT IONS AND ACRONYMS

ABSTRACT

ACKNOWLEDGEMENTS iii

iv

v vi

vi

MAIN REPORT

I . Motivation II. Objectives III. Background

IV. Online Sorting Equipment used for Current Study

V. Theory of Treated Wood Sorting by XRF and Associated Definitions

VI. Infeed Wood Characteristics

VII. Experimental Design

VIII. Experimental Results

IX. Summary and Recommendations 2

2

2

6

12

14

16

17

23

REFERENCES 26

APPENDIX A, Project Admini stration and Draft Manuscript APPENDIX A.1, Project Administration APPENDIX A.2, Draft Manuscript

APPENDIX B, Operating Manuals APPENDIX B.1, Radiation Safety Requireme nts for Analytical X-Ray Equipment –

Florida Administrative Code APPENDIX B.2, Use of XRF Analyzer APPENDIX B.3, XRF Safety Manual APPENDIX B.4, Field Safety Manual APPENDIX B.5 Stationary (QXR-W) XRF Safety Manual APPENDIX B.6, QXR-W XRF User Manual APPENDIX B.7, Field Safety Practices

APPENDIX C, Raw Data A-2

A-5

B-2

B-6

B-8

B-10

B-11

B-25

B-54

C-2iii 

### LIST OF FIGURES

Figure 1 Treated Wood “Identifiers” in C&D wood wa ste. End tags show the type of chemical contained in treated wood (left). Wood that contains incisions (righ t) is also treated.

Figure 2 Untreated and Treated Wood with Va rious Wood Chemical Formulations. Wood

Preservatives that Contain Copper Impart a Green Color to the Wood. Wood treated with less chemical (e.g. 0.25 pcf, pounds per cu bic foot) has a lighter olive green color in comparison to wood treated with a grea ter amount of chemical (e.g. 2.5 pcf). The copper based alternatives to CCA, ACQ and CB A, also impart an olive green color to

the wood. Borate treated wood does not cont ain copper and so this chemical does not impart a green color.

Figure 3 Wood Color after 3 Y ears of Weathering. Once CCA-t reated wood at the 0.25 pcf level is weathered, the green co lor tends to turn towards a s ilver grey tone typical of weathered untreated wood. At this point it is difficult to identify CCA-treated wood based upon color alone. Weathered CCA -treated wood treated with high concentrations of CCA, 2.5 pcf, retains its gr een color. Historically most CCA-treated wood used for residential applications has been treated at the lower retention levels of 0.25 and 0.4 pcf.

Figure 4 Illustrations of Augmentation Technologi es Used in this Study. PAN Indicator Stain (left) and hand-held XRF units (right).

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15 Large conveyor during the installation

Inclined conveyor

XRF-unit enclosure in the top of the large conveyor

XRF-unit components

XRF-unit enclosure in the top of the large conveyor

Screen photo of AAI-UofM software

Slide-way diverter (operated pneumatically)

one and three phases’ generators

Variable frequency drives assembly

setup of the sorting system

As spectrum with a peak of in terest highlighted in yellowiv Figure 16

Figure 17

Figure 18

Figure 19

Figure 20

Figure 21

Figure 22

Figure 23 

### LIST OF FIGURES (con’d)

Cu spectrum with a peak of in terest highlighted in yellow

Schematic diagram for treated wood detection by online XRF system

Distribution of wood length for the 50:50 infeed set

Wood distribution in two piles after an experiment of 50:50, based on number of pieces and weight

Wood distribution in two piles after an experiment of 95:05, based on number of pieces and weight

Treated wood sorting efficiencies based on number of CCA pieces and their metallic content, a) As and b) Cr

Treated wood sorting efficiencies based on number of ACQ pieces and their metallic

content of Cu

Treated and untreated wood so rting efficiencies based on their total number of pieces



### LIST OF TABLES

Table 1 Treated wood characteristicsv 

### LIST OF ABBREVIATIONS AND ACRONYMS

ACQ

As

BS Alkaline Copper Quat

Arsenic

Belt Speed

CBA Copper Boron Azole

CCA Chromated Copper Arsenate

C&D

Cr

Cu

DPP Construction and Demolition

Chromium

Copper

Digital Pulse Processor

FDEP

FR Florida Department of Environmental Protection

Feeding Rate

MSDS Material Data Safety Sheet

PAN 1-(2-pyridylazo)-2-naphthol , an orange-red solid

with a molecular formula C 15 H 11 N 3 O

pc

Pcf

VFD Piece

Pounds per Cubic Foot

Variable Frequency Drive

XRF X-Ray Fluorescencevi 

### ABSTRACT

Dimensional waste wood is frequently cont aminated with wood treatment preservatives including chromated copper arsenate (CCA). Because of difficulties in visually identifying treated wood especially afte r the wood has been weathered, wood treatment preservatives frequently contaminate dimensional waste wood, thereby limiting recycling options for Construction and Demolition (C&D) wood waste. The purpose of the proposed project is to

evaluate the use of automate d X-ray fluorescence (XRF) system s for identifying and removing CCA- and ACQ- treated wood within recovere d C&D wood waste. The study was conducted within a vicinity of a mid-sized wood waste recy cling facility (Florida Wood Recycling) located within the Town of Medley, Florida. The sortin g system consisted of two full-scale motorized belt conveyors, an XRF-detection chamber mounted in the top of one of the conveyors, and a pneumatic slide-way diverter mounted at the end of the conveyor that holds the XRF unit. The system was designed to divert treated wood w ith untreated wood falling onto a second conveyor

which then moved the untreated wood to a se parate area. Experiments were conducted according to a randomized factorial design with 1000 pieces of wood sorted per experiment. The composition of the infeed was 50:50 or 95 (untreat ed):05 (treated). Results show that online sorting efficiencies (amount in sorted pile/a mount in infeed) by XRF technology are high based on number of pieces (>70%) and more important based upon metals contents, where results

showed that 90 to 99% of arsenic was diverted for experiments utilizing a 50:50 infeed and 80 to 96% was diverted for experiments utilizing a 95:05 infeed. Results also show that efficiency of copper diversion ranged from 63 to 92% and chromium diversion wa s 80 to 98%. Observations during the sorts indicates that the vast majority of the wood that was incorrectly sorted was due

to either mechanical issues associated wi th the movement of the wood or background

concentrations of metals in th e conveyor belt (e.g. c opper in the seam and rivets, interferences from zinc in the rubber belt). Future wo rk should focus on the materials of conveyor construction to minimize background interferen ces and to improve the wood conveyance system so that near perfect sorting efficiencies can be obtained.



### ACKNOWLEDGEMENTS

Funding for this project was received from the Town of Medley through the Florida Department of Environmental Protection Innova tive Recycling Grants Pr ogram. This project

was a collaborative effort betwee n several different organizations including the Town of Medley, Florida Wood Recycling, Austin AI Inc., the University of Miami, and the University of Florida. We thank the many individuals who assisted with the administration of this project, and the

attendees of the technical a dvisory group (TAG) meeting held on October 16, 2008 in the TownHall of the Town of Medley.1 

## MAIN REPORT2 

### I. MOTIVATION

Numerous studies have shown that recovered wood waste, in particular C&D wood waste (a.k.a. sawn wood), in many instances is cont aminated with wood treatment preservatives (Tolaymat et al. 2000; Solo-Gabri ele et al. 2004), the most predom inant of which is chromated copper arsenate (CCA). The amount of arsenic, chromium, and copper contained in the wood is high varying from 1,000 to 10,000 mg/kg for each me tal. Given the high concentrations in the wood product, even small quanti ties of CCA-treated wood with in recycled wood waste would cause significantly elevated metals concentrations . For example, if the goal is to meet Florida SCTL residential guidelines for land application of recycled materials, the amount of CCAtreated wood that can be commingled with untreat ed wood must be less than 0.05% or in other words there must be less than 1 pound of arse nic-treated wood per U.S. ton of wood processed (Townsend et al. 2003). If the goa l is to produce a wood fuel, with a resultant ash that does not fail US regulatory requirements for hazardous wa ste (e.g. Toxicity Characteristic) then the tolerance is 5% (5% CCA-treated wood and 95% unt reated wood) (Solo-Gabr iele et al. 2002).

Because of the strict regulatory levels fo r arsenic, compliance with the regulatory guidelines is difficult, especia lly given that CCA-treated w ood is very common within C&D wood waste representing up to 30% of the C&D w ood waste stream (Blassino et al. 2002). As a result, sorting of CCA-treated wood will be re quired if C&D waste wood is to be recycled. Identification of CCA-treated wood is not always easy, in particular for wood that has been weathered (Solo-Gabriele et al. 2006). Thus in order to maintain the viability of the C&D wood recycling market, technologies should be impl emented to effectively sort and remove CCAtreated wood from recycled C&D wood waste.

Earlier research showed that visual sortin g was effective for removing the small amounts of treated wood present in relatively uncontaminat ed piles of source separated C&D wood (<1% treated wood), but cost associated with visual so rting is considered rela tively high, laborious and time consuming (Jacobi et al. 2007a). This proj ect focused on developing on-line sorting systems for commingled C&D wood. The on-line systems should be able to increase the throughput of a particular XRF unit due to more rapid analysis tim es and will also greatly decrease the amount of labor required thereby reducing costs.



### II. OBJECTIVES

The primary objective of the current study wa s to document the performance of a fullscale online sorting system for recovered w ood waste utilizing the XRF technology. The study focused on evaluating operational parameters such as wood loading rate and conveyor belt speed. Recommendations are provided for the improve d design of on-line sorting systems.



### III. BACKGROUND

The simplest form of sorting C&D wood is based upon “visual” methods. Visual identification is based upon severa l factors including a judgment concerning the possible original use, noting “identifiers” for treated wood, and no ting the color of the w ood. Original intended use of the wood is important si nce wood is almost exclusively treated when used for outdoor settings, industrial applications, and some indoor se ttings (e.g. in contact with the foundation of a3 home or exterior concrete walls). Thus if a waste load contains the remnants of an exterior structure, such as portions of a fence or a dock, then that load likely co ntains treated wood, and should be sorted accordingly. Other criteria fo r evaluating the original use include noting the dimensions of the wood. In ge neral, wood characterized by ve ry large dimensions had likely been used for industrial applications and are almost exclusively treated. Examples include railroad ties which are 8 inches x 8 inches x 3 feet or more and utility poles which are typically 1

foot in diameter or more. In some cases, landscape timbers whic h are also typical ly treated can be identified by their shapes which in many cases are characterized by rounded edges for decorative purposes. Also, wood characterized by dimensions of 4 inches by 4 inches or more are commonly used as structural component s and in many cases are treated. Notable

“identifiers” in wood waste include end-tags and incisions (Figure 1). End tags t ypically list the type of chemical contained in th e wood. If the wood is incised, it is also tr eated. Incising is a process by which uniform cuts are made in the wood to improve the penetration of the preservative chemical during treatm ent. Incising is typically us ed for denser wood species, such as Douglas Fir, which is primar ily used in the Wester n U.S (Figure 1). In some cases treated wood can be identified by its color, which if no t treated, typically has a light yellow hue. If treated with CCA or other non-arsenic copper-co ntaining preservative (e.g. ACQ and CBA) the wood would be characterized by an olive color whic h is faint for lower retention levels and very distinct for wood treated at high retention levels (Figure 2). However, once CCA-treated wood

has been weathered in many cases the color of the wood is almost indistinguishable from

weathered untreated wood. This is particularly the case for wood tr eated at low retention levels (0.25 and 0.40 pounds of chemical per cubic foot of wood, pcf) which was the most common

retention level used for resi dential uses of treated w ood in the U.S. (Figure 3).

Sorting based upon visual methods is helpful but not adequate for situations where the

wood is weathered and the use of the wood is unknown. Given the low tolerances for CCAtreated wood within recycled wood, augmentati on technologies were in troduced earlier as a requirement for the production of recycled C&D wood that meet regulator y guidelines (Jacobi et al. 2007a; Solo-Gabriele et al. 2004). “Augmentat ion” refers to the visual sorting method as described above supplemented by another technology to assist in the iden tification of treated wood. Several augmentation technologies have been evaluated throu gh earlier studies (SoloGabriele et al. 2006; Omae et al . 2007). The most promising te chnologies evaluated in earlier

studies were identified as PAN Indicator Stain and handheld XRF. These technologies have

been evaluated most extensivel y through two prior Innovative Recy cling Grants, one awarded to Sarasota County during 2000 a nd 2001 (http://www.eng.miam i.edu/~hmsolo/sarasota/ index_sara.htm) and another awarded to the Town of Medley (http://www.eng.miami.edu/ ~hmsolo/medley/) during 2006.

During the Sarasota study bot h x-ray and laser technologie s were evaluated in their efficiency to identify treated wood. The x -ray technology was found ha ve certain advantages over the laser system (Solo-Gabriele et al. 2004), in particular with resp ect to its capability to detect CCA in wet and painted wood. The x-ray instrument used in the Sarasota County study (ASOMA Model 400) was large and bulky wei ghing about 25 pounds. Since the work in Sarasota County, smaller more portable hand-held units (3.5 pounds) have since become available. These newer units (Figure 4) are ca pable of identifying up to 15 metals including arsenic, chromium, copper, lead, and mercury within seconds.4 During the 2006 Innovative Recycli ng Grant awarded earlier to the Town of Medley the chemical stain (PAN Indicator) was found as a us eful tool for identifying CCA-treated wood within C&D wood waste (Jacobi et al. 2007). When PAN stain is applied to the wood, the wood stains a magenta color if treated with copper and orange if untreat ed (See Figure 4). The stain is not capable of distinguishing be tween CCA and other copper-contai ning preservatives. Results from Medley-2006 project showed that visual sorting was effective for removing the small amounts of treated wood present in relatively uncontaminated p iles of source separated C&D wood (<1% treated wood). For pi les of source separated wood that were contaminated with 50% treated wood, visual sorts were not accurate an d benefited from augmented sorting using PAN indicator stain. For commingled loads of C&D wood, visual sort s and visual sorts augmented

with PAN indicator were not eff ective due to the exces sive amount of dust and dirt on the wood

which inhibited the visual identification of the wood color and also inhibited the performance of

the stain. For the case of comm ingled C&D wood, the handheld XRF units were found to be the augmentation technology of choice due to their ab ility to detect preserva tive treatment, even when the wood was dirty and wet. For relativ ely uncontaminated loads, visual sorting was estimated to cost $22 per U.S. ton without au gmentation and $44 per U.S. ton with PAN stain augmentation. For more contaminated loads, visual sorting augmented with PAN stain was estimated to cost $84 per U.S. ton, and for commingled wood, visual sorting augmented with hand-held XRF units was estimated at $103 per U.S ton. The bulk of these costs were associated

with labor.

Figure 1: Treated Wood “Identifiers” in C&D wood waste. End tags show the type of chemical contained in treated wood (left). Wood that contains incisions (right) is also treated.

Figure 2: Untreated and Treated Wood with Various Wood Chemical Formulations. Wood preservatives that contain copper impart a green color to the wood. Wood treated with less chemical (e.g. 0.25 pcf, pounds per cubic foot) has a lighter olive green color in comparison to wood treated with a greater amount of chemical (e.g. 2.5 pcf). The copper-based alternatives, ACQ and CBA, also impart an olive green color to the wood. Borate treated wood does not contain copper and so this chemical does not impart a green color. Incisions

Untreated Borate CCA

2.5 p cf CCA

0.25 p c f ACQ CBA5 Figure 3: Wood Color after 3 Years of Weathering. Once CCA -treated wood at the 0.25 pcf level is weathered, the green color tends to turn towards a silver grey to ne typical of weathered

untreated wood.

Figure 4: Illustrations of Augmentation T echnologies Used in the Medley-2006 Study. PAN Indicator Stain (left) and handheld XRF units (right). Positive for Copper Negative for Copper PAN Stain CCA

2.5 p c f CCA

0.25 p c f Untreated6 

### IV. ON-LINE SORTING EQUIPMEN T USED FOR CURRENT STUDY

The sorting system was installed in a temporary area away from commercial sorting activities at Florida Wood Recycling facility. The system consisted of an infeed motorized beltconveyor of 20’ length, 42.5” widt h and 117” height (Figure 5). Because of the need for guard rails (6” high) to maintain the wood on the be lt, the effective width of the belt was 32”. In addition, an inclined conveyor, 45 o incline of 10’ length and 42.5” width and 65” highest end (Figure 6) was installed perpendicular to the di scharge end of the infeed conveyor. The infeed conveyor was designed to convey wood to the XRF detection unit, and the inclined conveyor to convey the untreated to a separate pile for further processing as mulch. The XRF detection unit was installed on the top end of the infeed conve yor (Figure 7) and enclosed in a compartment that was connected on the top ch annels of the conveyor using vi bration absorbers to minimize interference from the moving part s of the system. The XRF detec tion unit consisted of an X-ray tube that emitted X-rays downward when ener gized. The diffracted ray was monitored by a detector that was connected to a digital pulse processing (DPP) unit (Fig ure 8); the DPP by itself is connected to a control panel (Figure 9). Th e control panel has a ce ntral computer and the system is operated and controlled by special software (AAI-UofM; Fi gure 10). After inspection of wood pieces conveyed by the belt of the in feed conveyor and passing through the inspection chamber, treated wood was sorted once discharged from the end side of the conveyor by a slideway diverter (Figure 11) which consiste d of a steel sheet of 32x32x1/4” which was pneumatically driven by a piston connected to an air compressor a nd controlled by the software. Sorted treated wood would be moved by the divert er to bypass the inclined conveyor and would thus fall in the front of the system. Belt moto rs were wired to a 3-phase 480 volt generator (Figure 12) through a variable fr equency drive (VFD) that contro led the belt speed (Figure 13). The whole sorting system was set up under a canopy as shown in Figure 14.

Figure 5: Large conveyor during the installation7 Figure 6: Inclined conveyor

Figure 7: XRF-unit enclosure in the top of the large conveyor8 X-ray Tube

Detector XRF Box Window

Figure 8: XRF-unit components.9 Figure 9: XRF-unit enclosure in the top of the large conveyor

Figure 10: Screen photo of AAI-UofM software10 Figure 11: Slide-way diverter (operated pneumatically)

Figure 12: one and three phase generators11 Figure 13: Variable frequency drives assembly

Figure 14: Final setup of the sorting system12 

### V. THEORY OF TREATED WOOD SORTING BY XRF AND

ASSOCIATED DEFINITIONS

The theory of XRF detection is presented he re as this information should be known in order to understand the logic be hind the experimental design. The discussion below focuses on arsenic and copper as both are found in CCA-tr eated wood and copper is found in ACQ-treated

wood.

XRF technology works at the atomic level by knocking out electrons from the innermost orbital of atoms in the treated wood changing th e atoms into unstable ions. A more energetic

electron from outer orbital will move into the ne wly vacant space in the inne r orbital in order to reach the lowest stable energy state and so re leasing the extra energy possessed before. The emitted energy is equal to the difference in energi es between the innermost orbital and the outer one, thus it is a characteristic of the element fluorescing. Emitted energy as photons can be detected by X-ray detector and so the count of emitted energies is proportional to the concentration of the metal in wood pieces and is simulated by a spectrum representing the number of counts according to the dispersed en ergy in KeV. The time during which the emitted energy is counted, the measurement time , is held constant from sample to sample in order to compare the emitted energies from one sample to another.

The software has a previously stored spect rum of As and Cu (F igure 15 and 16). The

ratio of area under the measured counts-curv e to the reference area is called the threshold

. Minimizing the threshold is important for detecti on and diversion of weathered wood pieces, but may increase the interference from other metals that has a spectrum overlap ping or very close to the one of concern. The overlap fr om other elements is of particul ar concern in the case of lead (Pb) which overlaps the arsenic reference spec trum, and zinc (Zn) which overlaps the copper reference spectrum.

Figure 15: As spectrum with a peak of interest highlighted in yellow (source: http://ie.lbl.gov/ xray/as.htm).13 Figure 16: Cu spectrum with a peak of interest highlighted in yellow (source: http://ie.lbl.gov/xray/cu.htm ).

Incorporating the detection of the signal into diversion of the wood on a conveyor system requires an understanding of the timing between de tection and diversion of the wood piece. Once As or Cu are detected in the wood, the wood mu st travel from the detector to the slide-way

diverter. This time is called the delay time . The delay time is a function of the belt speed. Thus

the diverter was de signed to open (45 o to the horizontal level) after the delay time. It would then remain open for a time equal to the sum of measurement times providing consecutive detection of each treated wood piece, plus the pulse adjust time. The pulse adjust time is the time needed for the wood to transition from the belt to the diverter. The total time the diverter remained open in the sorting position is called the dwell time (Figure 17).

Figure 17: Schematic diagram for treated wood detection by online XRF system.14 

### VI. INFEED WOOD CHARACTERISTICS

Each treated wood piece used in this research was given a un ique identifying code. This

code was linked to the characteristics of that piece of wood. These characteristics included the wood piece dimensions, type of treatment (CCA , ACQ or Other) and the concentration of arsenic, chromium and copper in ppm using a handheld XRF (I nnov-X type alpha, Woburn, MA, USA). Thus, the quantity in grams for each metal was calculated for each piece of wood from the volume of each piece and its metals’ content assuming all pieces are Southern Yellow Pines of density 511 kg/m 3 . Since the handheld XRF readings are rele vant to the surface concentration of metals and this is usually higher than the entire concentration in the wood piece due to natural tendency of metals to migrate to the surface, arsenic concentra tion was corrected using Block’s formula (Block et al. , 2007). Chromium and copper were modified using unpublished formulas

of the author.

Two sets of wood were used as infeed. Both sets consisted of a 1000 pieces of wood. One set was characterized by 50% untreated wood and 50% treated wood (50:50) and another set was characterized by 95% untreated wood and 5% treated wood (95:05). Treated wood included CCA-treated wood, ACQ-treated wood, and “Special”- treated wood (also referred to as “other” treated wood) which were extremely weathered w ood samples that contained elevated levels of

chromium and low levels of arsenic. Most of these special-treated wood pieces appeared very

weathered and could have been CCA-treated w ood where the arsenic wa s depleted. Table 1

summarizes the chemical characteri stics of the treated wood pieces.

Table 1: Treated wood characteristics

No. of Pieces Arsenic content (g) Copper content (g) Chromium content (g) Experiment 50:50 95:05 50: 50 95:05 50:50 95:05 50:50 95:05

CCA- treated 417 44 1252 137 682 50 736 71 ACQ- treated 66 5 2.9 0.1 403.1 7.1 11.6 0.3

Others 17 1 0.74 0.01 3.74 0.00 4.72 0.13
Total 500 50 1,256 137 1,089 57.1 752 71

Wood pieces were chosen based on their length to range from 5 cm to 150 cm, in order to

minimize the effects from the different sizes of wood pieces. Each wood infeed used (50:50 and 95:05) had the same probability distribution with respect to th eir length, since the length was found as the most important characteristic to affect proper sorting. Figure 18 shows the length distribution of the 50:50 infeed set. The length di stribution for the 95:05 infeed was very similar

to that of the 50:50.15 0% 20% 40% 60% 80% 100% 120%

0 10 20 30 40 50 60 70 80 90 100Frequency

Length (cm) 

## Treated Wood Histogram (500 pc)

Frequency

Cumulative %

0% 20% 40% 60% 80% 100% 120%

0 10 20 30 40 50 60 70 80 90 100Frequency

Length (cm) 

## Untreated Wood Histogram (500 pc)

Frequency

Cumulative %

Fig. 18. Distribution of wood length for the 50:50 infeed set16 

### VII. EXPERIMENTAL DESIGN

Two sets of experiments were conducted: pre liminary and main experiments. The primary goals of the preliminary experiments were to tr ouble-shoot the system so that it was operational and to determine the following.

- The minimum thresholds for sorting trea ted wood based on the presence of As

and/or Cu.

- The effect of changing the measurement time of the digital pulse processing (DPP) unit on the sorting efficiency.

The main experiments were designed to eval uate the efficiency of wood sorting using a combination of different feeding rates (FR, 20, 40 and 60 pc./min) and belt speed of the infeed conveyor (BS, 0.25, 0.375 and 0.5 m/s). These experiments were designed as randomized factorial block design with repl ication. The first set included nine experiments each with a

different combination of FR and BS and the sec ond set include four experiments of the array FR (20 and 60 pc./min) and BS (0.375 and 0.5 m/s) . Each experimental run was conducted by sorting 1000 pieces of wood with 50:50 of treated wood vs. untreated wood for the first set and

95:05 for the second set.

After each experimental run through the XR F system, wood-pieces in the two piles (presumed treated and presumed untreated) were manually sorted to confirm actual treatment, counted, and weighed. Within each “presumed” pile from the XRF system, wood was identified as either correctly sorted or incorrectly sorted. For example, within the presumed untreated pile, the wood would be identified as truly untreated. Treated wood in the presumed untreated pile were further separated into va rious categories includi ng truly CCA-, ACQ-, and Other- treated wood. Manual sorting of the presumed treated and presumed untreat ed wood was based upon the unique identifier established for each wood pi ece and the piece numbers were thus recorded allowing the researchers to track each individual piece of wood w ithin the set of 1000. Although the actual experiments were relatively quick (on the order of an hour or two) documentation after each experiment was very time consuming because of the need to manually sort and record the location of each wood piece.

Sorting efficiencies were calculated for each e xperimental run based on the number of pieces, weight, and metal contents of As, Cu and Cr . Treated wood efficien cies by number were calculated based on the fraction of true treated pi eces that ended up in the presumed treated pile to the total number of pieces ( 500 in the 50:50 exp or 50 in the 95:05 exp.). Untreated wood efficiencies by number were calcul ated based on the fraction of tr ue untreated piec es that ended up in the presumed untreated pile to the tota l number of pieces (500 or 950, accordingly). Untreated pieces usually ended up in the treated pile due to two mechan isms, either overlapping over the belt with treated pieces and so these pieces were divert ed together or the untreated pieces bounced from the inclined conveyor because of their forward momentum. Because of the forward momentum the wood pieces would bounce si deways over the inclined conveyor into the treated pile. Bounced wood pieces were usually longer than 80 cm. Based on these observations, an estimated overlapping rate was cal culated as percentage fraction of untreated17 pieces of length less than 80 cm which ended up in the presumed treated pile, and the estimated bouncing rate was calculated the same but for pieces of length greater than 80 cm.



### VIII. EXPERIMENTAL RESULTS

VIII.a Preliminary Results

Qualitative Results Associated with System Operation and Trouble-Shooting

After the installation of the sorting system, th e system was operated using software provided through Austin AI. The system was shown to det ect arsenic at lower th reshold limits and low

concentrations in the treated wood and above the natural-background levels in wood. Several problems were encountered and re solved, below is a summary:

• The system was not capable of achieving lower threshold limits of copper due to the background levels of copper in th e belt material, in pa rticular due to high levels of copper in the seam, rivets and lacing of the belt. Th is issue decreased the sorting efficiency of copper-based treated wood. Future refi nements should correct these issues.

• The system was operated by the available so ftware. This software however required several steps to initiate, and included upload of the software, initiation of the sorting software, hooking the XRF-components with electricity, and star ting communications with the system. Troubleshooting was nece ssary during system initiation which frequently required resetting the system by a previously installed reset-button. The system operation required trained personnel who are familiar with software operations. Future refinements should simplify the syst em initiation process.

• The XRF unit was installed in the middle right half above the large conveyor which made the farthest side of the conveyor to be limite d in its sensitivity to metal detection. An infeed slide-way was manufactured and installed by University of Miami research staff to help guide the wood to the right half of th e conveyor. Future refinements should include an improved material feed delivery system to as sure that the wood in fact falls within the

field of view of the XRF unit.

• Untreated wood was found to bounce from th e inclined conveyor and end up in the treated wood pile, and so guard slides were manufactured in the University of Miami workshop and installed on the three sides of th e lower part of the inclined conveyor, in addition a discharge slide-wa y was manufactured and installed and found to help in decreasing the bouncing rate of untreated wood. However, even with the slide-way, large pieces of untreated wood, in particular duri ng higher conveyor belt speeds, were observed to bounce from the inclined conveyor (which was intended to carry the untreated wood) into the treated wood pile. Fu ture refinements of the syst em will require improved design of the conveyance system on the out put side of the XRF unit.

• During the operation of the system, the divert er would occasionally start to observe As alone or both As and Cu, even with a bare be lt. This problem caused several delays of18 the research activities and required trouble-shooting investig ations and literature reviews.

Continuous detection of both As and Cu is believed to be as sociated with overheating due to high ambient temperature, heat production by the X-ray, and the poor cooling system of the XRF-chamber. This problem was resolv ed by increasing the air flow rate into the chamber and aiming the air injection into the body of the X-ra y tube. Continuous detection of As only is believed to be due to the corrosion of the lead sheets installed inside the XRF-chamber and pr oduction of lead dust that fe ll in the field view of the detector. Lead corrosion was believed to occur due to the low quality of the purge air and catalysis of the lead sheeting by the X-ray. Ai r can be contaminated with low levels of landfill gases due to the location of Florida Wood Recycling near the Medley landfill. The lead corrosion issue was minimized by fr equent cleaning the XRF chamber with a vacuum and through wiping the XRF components with alcohol wipes. The production of lead dust was minimized by replacing the lead parts with polyvinyl-coated lead sheets and by painting the small lead pieces with polyurethane spray paint.

Qualitative Evaluation of Threshold and Measurement Time

XRF parameters such as threshold and meas urement time have significant effects on the sorting efficiencies. Lower threshold limits will al low higher efficiencies of treated wood sorting, allowing for the separation of treated wood that c ontains lower levels of metals. However, too low of a threshold causes false positives due to the interference from the background levels of targeted elements (arsenic or copper) or from elements of overlapping spectra (such as the

detection of false As due to interference from th e lead spectra and the detection of false copper

due to interference from the zinc spectra). Both As and Cu were found to have finite background levels in the rubber belt; As was on the order of 100 ppm, and Cu was on the order of 250 ppm. Also, Cu was found at high levels in the belt s eam and its rivets. Zinc was found as a major component of the rubber belt mate rial. The lowest achieved threshol d for As in this research was 0.02 and 0.05 for Cu. At the 0.05 limit for Cu, the sorting system was detecting Cu in the revolving seam at a rate of one over three consecutive times.

Reducing the measurement time was observed to increase the capacity or speed of the system. However a reduction in the measurement time resulted in a decrease of the sensitivity, so that very weathered pieces of treated wood would go undetect ed. A benefit of the reduced sensitivity was that background in terferences were reduced (e.g. pr esence of zinc in the belt, copper in the belt seam, etc ..). Qualitative experimentati on was thus conducted to find a measurement time that would provide a balanc e between speed and sensitivity. From the preliminary experimentation a measurement time of 250 ms was found to be an optimum value and this value was used for most of the subsequent experiments.

VIII.b Main Results

Wood Distribution in Presumed Treated and Presumed Untreated Piles

Figure 19 shows the wood dist ribution in the presumed trea ted and presumed untreated piles for one of the experimental runs in this res earch t(50:50 infeed, BS = 0.25 m/s, FR = 20 pc/min). Figure 20 shows results for the same e xperiment except that th e 95:05 infeed was used.19 For the 50:50 infeed, the presumed treated pi le mostly consisted of treated wood, 96% by number of pieces (89%+5%+2%) an d 95% by weight. Similarly the presumed untreated pile was characterized by 86% untreated wood by nu mber of pieces and 84% by weight. For the 95:05 infeed, the presumed untreated pile show ed 99% untreated wood by number of pieces and 98% by weight. The presumed treated pile had significantly different re sults showing less than half of the pile was in fact treated wood. Since treated wood represents such a small fraction of the untreated wood portion for th e 95:05 the incorrect diversion of a small fraction of the untreated wood can result in a significant contribu tion to the treated wood p ile. In practice, the main priority is to keep the treated wood out of th e untreated wood pile. The loss of some untreated wood within the treated wood pile is accep table, especially if it assures a conservative sort resulting in a majority of the true treated within the treated wood pile. Within the results of both experiments (Figures 19 and 20), ACQ- and Other- treated wood pieces were mostly shown

to be located in the untreated pile. This was likely because of the high threshold set for copper (because of interferences from the belt) and because of the very low levels of arsenic characteristic of the “other” treated wood pi eces which was not detected by the XRF system.

CCA

89% ACQ

5% O

2%

UT

4% Treated Pile 50:50 exp %by No.

Belt speed = 0.25 m/s Feeding rate= 20 pc/min

CCA

4% ACQ

8% O

2%

UT

86% Untreated Pile 50:50 exp %by No.

Belt speed = 0.25 m/s Feeding rate= 20 pc/min

CCA

89% ACQ

6% O

0%

UT

5% Treated Pile 50:50 exp %by wt.

Belt speed = 0.25 m/s Feeding rate= 20 pc/min

CCA

2%

ACQ

13% O

1%

UT

84% Untreated Pile 50:50 exp %by wt.

Belt speed = 0.25 m/s Feeding rate= 20 pc/min

Fig. 19. Wood distribution in presum ed treated and presumed untreat ed piles after an experiment

conducted using a 50:50 wood infeed. Experime ntal parameters included a belt speed of 0.25 m/s and a feeding rate of 20 pieces per minute. Wood distribution is based on number of pieces (above) and weight (below). PRESUMED TREATED PILE PRESUMED UNTREATED PILE

% number pieces

% by weight PRESUMED UNTREATED PILE20 CCA

45%

UT

55% Treated Pile 95:05 exp %by No.

Belt speed = 0.375 m/s Feeding rate= 20 pc/min

CCA

1%

UT

99% Untreated Pile 95:05 exp %by No.

Belt speed = 0.375 m/s Feeding rate= 20 pc/min

CCA

35%

UT

65%

Treated Pile 95:05 exp %by wt.

Belt speed = 0.375 m/s Feeding rate= 20 pc/min

CCA

1% ACQ

1%

UT

98% Untreated Pile 95:05 exp %by wt.

Belt speed = 0.375 m/s Feeding rate= 20 pc/min

Fig. 20. Wood distribution in presum ed treated and presumed untreat ed piles after an experiment

conducted using a 95:05 wood infeed. Experime ntal parameters included a belt speed of 0.25 m/s and a feeding rate of 20 pieces per minute. Wood distribution is based on number of pieces (above) and weight (below).

Affects of Wood Dimensions

Wood dimensions were found to affect the co rrect sorting of treated and untreated wood.

The dimension of treated wood affects the number of times a piece will be detected. The longer the wood piece the greater the number of times that the wood piece would be evaluated by the

XRF unit and thus the more accurate the detecti on. Furthermore, the length also impacted the ability of the conve yor system to divert the wood. It wa s found that even w ith a correct XRF identification, pieces of wood that were very small or very large were not sorted properly because of the mechanical aspect s of the diverter. For example, small treated pieces would cause the diverter to open; however in the process these small pieces would bounce on th e divertor and instead of moving forward (as intended) they would bounce sideways and ultimately fall on the inclined conveyor causing them to be sorted into the untreated pile. In such cases, the XRF unit identified the piece correctly, the diverter opene d as intended, but because of the momentum and PRESUMED UNTREATED PILE PRESUMED TREATED PILE

% number pieces

% by weight21 small size of the piece it would bounce and end up in the incorrect location. When considering

the overall amount of metals in each pile due to incorrectly sorted treated wood, the actual amount of metals contributed by the small pieces was relatively low because the pieces were so

small.

The “bouncing” problem was also very a pparent for long pieces of untreated wood (>80cm). Such long pieces carried a considerab le momentum from the primary conveyor and as a result had a tendency to continue moving in the longitudinal direction. In order to be sorted properly these long pieces of unt reated wood would be need to fall and remain on the incline conveyor and be carried in a dire ction perpendicular to the dire ction of the primary conveyor. These long pieces had a tendency to fall on th eir end on the incline conveyor and bounce sideways out of the incline conveyor into the trea ted wood pile. The defici encies associated with “bouncing” does not represent a defici ency in the actual XR F detection. It is a reflection of the need to improve the mechanical aspects of th e conveyor and diverter system. In general, bouncing was estimated to be the 2.2 to 5.8% of th e incorrect identification within the presumed treated/untreated piles.

Another issue to consider is the potentia l for wood pieces to ove rlap, where a treated wood piece overlaps an untreated wood piece. In general, overlapping was estimated to be the

cause of 0.6-29% of the incorrect identification w ithin the presumed treated/untreated piles. Generally, both overlapping and bouncing rates incr ease with increasing th e belt speed and the feeding rates, hereby, reducing th e sorting efficiency.

Sorting Efficiencies

Based on the randomized block design with repl ication, and according to the combination of threshold limits and measurement times, sort ing efficiencies were very high based on the fraction of CCA wood-pieces (figure 21 a and b) and were higher for the 50:50 infeed experiments (92-96%) in comparison to 95:05 in feed experiments (77-86%). A much lower sorting efficiency was observed based on the nu mber of ACQ-treated pieces correctly sorted (figure 22) and Other-treated wood correctly sorted (20-61% for the 50:50 infeed). When observing the amount of copper, the efficiency increases (generally above 75%) as the ACQtreated wood that contained very high levels of copper was sorted out co rrectly in comparison to ACQ-treated wood that contained low levels of c opper. Efficiencies of sorting both treated and untreated wood based on number of pieces was generally above 76% (figure 23). Sorting

efficiencies in terms of the meta llic contents of three elements of concern were very high and higher for the experiments conducted with the 50:50 infeed in comparison to experiments conducted with the 95:05 infeed. In summary for all experiments, sorting efficiencies based on As content ranged from 82-99%, and when base d on Cu content ranged from 63-92%. The higher efficiencies based upon meta l content are due to the fact that wood samples with higher levels of metals were correctly sorted more often in comparison to wood samples with low levels of metals. With respect to chromium, 80-98% was diverted, since chromium is a major component of the CCA-treated wood.

In general, sorting efficiency based on number of pieces wa s found to increase for treated

wood and to decrease for untreat ed wood with increasing feed rate from 20 to 60 pc/min. The primary reason for the decrease in untreated wood so rting efficiencies is believed to be a greater22 amount of wood overlapping (more pieces of unt reated wood overlapped with treated wood pieces on the belt and so both were diverted into the treated wood pile). Overlapping rate also helps in the diversion of very weathered treate d wood pieces (under detection limit) and is the primary reason for increasing treated wood efficiency at higher feeding rates. In contrary to what was expected, belt speed did not have a measured effect on the different efficiencies with the studied ranges.

a)

84 86 88 90 92 94 96 98 100

78 80 82 84 86 88 90 92 94 96 98 20 40 60 20 40 60 20 40 60 Belt speed (m/s)AsSortingeff.(%wt.)CCAsortingeff.(%wt.) Feeding rate

(pc./min) CCA (pc./pc.)

As (g/g)

b)

84 86 88 90 92 94 96 98 100

78 80 82 84 86 88 90 92 94 96 98 20 40 60 20 40 60 20 40 60 Belt speed (m/s)CrSortingeff.(%wt.)CCAsortingeff.(%wt.) Feeding rate

(pc./min) CCA (pc./pc.)

Cr (g/g)

Fig. 21. Treated wood sorting efficiencies base d on number of CCA pieces and their metallic content, a) As and b) Cr23 0 10 20 30 40 50 60 70 80 90 100

0 10 20 30 40 50 60 70 20 40 60 20 40 60 20 40 60 Belt speed (m/s)CuSortingeff.(%wt.)ACQsortingeff.(%wt.) Feeding rate

(pc./min) ACQ (pc./pc.)

Cu (g/g)

Fig 22. Treated wood sorting effi ciencies based on number of ACQ pieces and their metallic

content of Cu

0 20 40 60 80 100 120

74 76 78 80 82 84 86 88 90 92 94 20 40 60 20 40 60 20 40 60 Belt speed (m/s)UTWSortingeff.(%bypc.No.)TWsortingeff.(%bypc.No.) Feeding rate

(pc./min) TW (pc./pc.)

UTW (pc./pc.)

Fig. 23. Treated and untreated wood sorting effici encies based on their total number of pieces



### IX. SUMMARY AND RECOMMENDATIONS

The overall results of this study show that the online sorting of recovered wood waste by XRF technology is a promising process and achieve s high efficiencies based on number of pieces sorted (>70%) and more important, based on the metal contents, where results showed that 90-

99% of arsenic was diverted for the experiments utilizing 50:50 infeed and 80-96% was diverted for experiments utilizing a 95:05 infeed. Simila r results achieved for the copper and chromium.

Operational parameters, in particular feeding rate had an effect on the recovery rate of untreated wood from the waste stream, which in turns affects the economics of the facility. Medium feeding rates (such as 0.375 m/s) and lo wer feeding rates will allow a more accurate sorting and less bouncing and overlapping rates of untreated wood but less material processed per given period of time.24 The following recommendations are provided gi ven the observations obtained during both the preliminary and main experimental phases of this study.

- Minimize Background Signal from Conveyor : 1. Replace the belt of the infeed conveyor with one containing less background concentrations of As, Pb, Cu and Zn. 2. Replace the seam, lacing and rivets with anot her material (maybe st ainless steel) with one containing less background concentr ations of As, Pb, Cu and Zn. 3. Equip the infeed conveyor with a roller br ush (best location at the bottom middle side of conveyor's belt). Cleaning the belt with a water hose and sprinkler system at the end of working day would help in mi nimizing dust buildup which may contain interfering metals.

- Wood bouncing : 1. Replace the discharge belt with another one of a rougher surface. This should

minimize the roll-back of the wood going up the incline conveyor. 2. Decrease the height of the discharge conve yor while maintaining the location of the diverter and the slide-way. 3. Increase the height of the guard slides. 4. Improve wood materials movement thr ough an entirely new conveyor design. Consider a conveyor manufacturer that sp ecializes in construction and demolition materials handling.

- Lead corrosion : 1. Replace the lead inside the XRF-chamber w ith another material like thick stainless steel or vinyl coated lead sheets (must be coated on all surfaces to avoid lead corrosion). 2. Or/Separate the XRF-tube and the detector into different chambers with thick steel

barriers. 3. Take the digital pulse processor outside the XRF chamber to avoid damage from the ionized aggressive air. 4. Consider the use of a high purity aluminum filter to help protect the system from

interferences.

- Wiring and safety : 1. Enclose all wires and air hoses by conduits and use labels to distinguish between

them. 2. Install additional emergency stops near the diverter and ou tlet conveyor. Also, consider wiring which will prevent accidents associated with the need to remove residual pressure from air tank. The syst em should automatically turn-off the unit including the X-rays when it gets blocked or jammed. 3. Although no issues associat ed with X-ray exposures were encountered, the system should be designed with more X-ray monitoring in mind, in addition to body badges for individuals. This monitoring system should provide some type of automated warning in the event of X-ray releases. 4. Require XRF and conveyor manufacturer to install more safety warning signs which are more permanent. In th is study the warning signs we re prepared through U.Miami25 and were taped to the system at various points; however the manufacturer should provide these signs in the future to assure that the can be affixed in a more permanent manner to the equipment.

- Sorting capacity : 1. Replacing the conveyors with wider ones, as wide as the picking lin e’s chutes or a little

bit wider. 2. Use slides along with infeed conveyor to avoid wood bouncing once thrown from the

chutes. 3. Increase the length of th e infeed-conveyor chute to avoi d wood blockage due to long wood pieces. 4. Double the XRF-components (tube, detector , digital pulse processing unit, wires and control panel) so that scanning can oc cur across a wider wi dth of the conveyor.

- Software Upgrades : 1. Simplify start up procedures by replacing th e several operational steps mentioned above by one power button (ON/OFF) and a nearby reset button.

2. Upgrade software to provide improved sort ing efficiency for the detection of Cu treated wood (in addition to the option to sort based upon As or As plus Cu).

- System Robustness : 1. Problems were encountered during days of extreme heat. Add a c ooling system to the XRF unit to minimize problems associated with extreme heat.

2. Problems were encountered with dust. A ddressing the lead corrosion issue listed above may alleviate this issue. However, th e system needs to be made less sensitive to

dust or dust is to be further minimized from the XRF chamber. Consideration must be given to further minimizing dust, even beyond resolving the issue as sociated with lead

corrosion. 3. The system should be designed with extr eme weather conditions in mind including

extreme rainfall events and hurricanes. The system should be weather proof, withstanding direct rainfall. The system should also be designed to minimize wind resistance and should be stable enough to withstand hurricane wind conditions.26 

### REFERENCES

Blassino, M., Solo-Gabriele, H., and Townsend, T., 2002. Pilot Scale Evaluation of Sorting Technologies for CCA-Treated Wood Waste. Waste Management and Research, 20: 290-301.

Jacobi, G., Solo-Gabriele, H., Townsend, T ., Dubey, B., 2007a. Evaluation of Methods for Sorting CCA-treated Wood. Wa ste Management, 27: 1617-1625.

Jacobi, G., Solo-Gabriele, H., Dubey, B., Town send, T., and Shibata, T., 2007b. Evaluation of Commercial Landscaping Mulch for Possible C ontamination from CCA. Waste Management,

27: 1765–1773.

Omae, A., Solo-Gabriele, H., and Townsend, T., 2007. A Chemical Stain for Identifying

Arsenic-Treated Wood Products. Journal of Wood Chemistry and Technology, 27(3-4): 201-

217.

Tolaymat, T.M., Townsend, T.G., and Solo-Gabriele, H., 2000. Chromated Copper Arsenate

Treated Wood in Recovered Wood at Constructi on and Demolition Waste Recycling Facilities. Environmental Engineeri ng Science, 17(1): 19-28.

Townsend, T.G., Solo-Gabriele, H.M., Tolaymat, T., and Stook, K., 2003. Impact of Chromated Copper Arsenate (CCA) in Wood Mulch. The Sc ience of the Total E nvironment, 309: 173-185.

Solo-Gabriele, H.M., Townsend, T.G., Hahn, D.W ., Moskal, T.M., Hosein, N., Jambeck, J., andJacobi, G., 2004. Evaluation of XRF and LIBS Technologies for On-Line Sorting of CCATreated Wood Waste. Waste Management, 24: 413-424.

Solo-Gabriele, H.M., Townsend, T, Messick, B. , Calitu, V., 2001. Characteristics of Chromated Copper Treated – Wood Ash. Journal of Hazar dous Materials, 89 (2-3): 213-232.

Solo-Gabriele, H., Omae, A., Townsend, T., an d Hahn, D., 2006. Identifica tion of Wood Treated

with Waterborne Metal-Based Preservatives. In Environmental Impacts of Preservative Treated Wood (T. Townsend and H. Solo-Gabriele, eds.). CRC Press, Boca Raton, FL.