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APPENDIX A

Publications

A.1, Project Administration A.2, Draft of Manuscript to be Submitted to Waste

Management

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APPENDIX A 1: PROJECT ADMINISTRATION

A considerable amount of effort during this project focused on project

administration. The Town of Medley project manager was Roy Danziger, Town Finance Director, in consultation with Melvin Wolfe, Town Attorney. The host facility for this project was Florida Wood Recycling. Harvey Schneider, President of Florida Wood Recycling, was the primary contact at the host facility. The principal investigators for the University team included Helena Solo-Gabriele of the University of Miami College of Engineering, and Timothy Townsend of the University of Florida, Department of Environmental Engineering Science. Helena Solo-Gabriele served as the lead administrator of the project for the University Team.

INFORMATION DISSEMINATION  Information was disseminated on this project through presentations at academic meetings, professional conference, a web site, and through technical advisory group (TAG) meeting. It is important to keep in mind that information dissemination is an on-going process and will continue beyond the end-date of the project as the University researchers continue to publish and present the final results of this project. The information activities presented herein correspond to those activities through October 31, 2008. Presentations

Presentations of the study were provided at two different types of meetings. The first consisted of a TAG (Technical Awareness Group) meetings organized by the project team established for this study. TAG meetings were designed to obtain feedback from representative individuals from industry, regulatory agencies, and academia. These TAG meetings were open to the public. The TAG meeting was held on October 16, 2008 in Medley, Florida and was attended by about 28 individuals. PowerPoint presentations and minutes of the TAG meeting are posted at www.eng.miami.edu/~hmsolo/medley2.

The second type of presentations were before conferences organized by other

organizations. Presentations which discussed the interim results of this study are listed below. Of note is that funding for international travel came from other sources

• “Rapid Identification of Wood Treated with Waterborne Preservatives.” March

2006. Wood Protection 2006, Sponsored by the Forest Product Society, Madison Wisconsin. Conference held in New Orleans, LA.

• “Recycling Potential of Wood Waste.” October 2005. National Conference of

the Mulch and Soil Council, Washington D.C.

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• “Wood Waste Management Practices in the US.” September 2005. Second

European Cost E31 Conference, Management of Recovered Wood Strategies Towards a Higher Technical Economical and Environmental Standard in Europe. Bordeaux, France. Keynote presentation.

• “Management of Wood Treated with Metals-Based Preservatives.” September

2005. Second European Cost E31 Conference, Management of Recovered Wood Strategies Towards a Higher Technical Economical and Environmental Standard in Europe. Bordeaux, France. Of note, during this meeting, Helena Solo-Gabriele took an XRF unit with her to Bordeaux, France where she held demonstrations of the unit at the CTBA [Centre Technique du Bois et de l’Ameublement, Technical Center for Wood and Furniture] and a local C&D recycling center in France. Claire Cornellier of the CTBA facilitated the contacts in France.

• “Disposal and Management Options for Wood Waste Containing Metals-Based

Preservatives”. The International Symposium on the Environmental Impacts of Preservative Treated Wood for Achieving Healthy Environments, Kyoto, Japan. March 2005. Of note that during this meeting, arrangements were made for Innov-X representatives to provide a demonstration of the XRF unit. Innov-X participated by setting up a table with the unit and literature. Helena Solo-Gabriele provided the wood samples.

• “Technologies for the Management of Wood Waste Containing Metals-Based

Preservatives.” February 2005. Environment and Wood Preservation 6th International Symposium sponsored by the Centre Technique du Bois et de l’Ameublement (Technical Center for Wood and Furniture) and the International Research Group on Wood Preservation. Cannes-Mandelieu, France.

• “CCA Management Issues.” December 2004. 19th Annual Hazardous Materials

Management Conference on Household and Small Business Waste, sponsored by the North American Hazardous Materials Management Association (NAHMMA). Miami, FL. (Dual presentation with Drs. Townsend and Solo-Gabriele).  

• “Leachability of Arsenic, Chromium and Copper from Weathered Treated Wood.” May 2008. 39th Annual Conference of the International Research Group for Wood Preservation Conference. Instanbul, Turkey. (Poster presentation by John Schert)

• Leachability of Arsenic, Chromium and Copper from Weathered Treated Wood, IRG/WP 08-50255. International Research Group on Wood Preservation, Stockholm, Sweden.  

• “Environmental Impacts of Preservative Treated Wood: On-going Research in Florida.” May 2008. 39th Annual Conference of the International Research

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Group for Wood Preservation Conference. Instanbul, Turkey. (Speaker presentation by John Schert).  

Web Site

A web site has been developed for this project and has been posted on the internet at http://www.eng.miami.edu/~hmsolo/medley2. This web site includes a brief description of the project, contact information for the core project participants, a copy of the proposal, minutes and PowerPoint presentations of all meetings, project progress reports, and the final project report. A link to this web page has been established through www.ccarsearch.org, which is the web page that the research team has established to post information addressing other related research projects. Also of interest is that Innov-X initiated a Press Release describing the project and now also markets the XRF units specifically for wood preservative identification (http://innov-xsys.com/applications/environmental.html). Written Documents

The report included herein will serve as an important means by which the results of the project will be disseminated to those interested. In order to facilitate distribution of this report, it will be posted on the web at http://www.eng.miami.edu/~hmsolo/medley2. The interim results of this study will also be submitted for potential publication within Construction and Demolition Recycling, a lay industry-focused journal (See Appendix A.1). The final technical results of this study will be submitted for potential publication within Waste Management which will serve as an alternate means for distributing the bulk of the technical results (See Appendix A.2). Furthermore the interim results from this study were also included as portions of conference proceedings.

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APPENDIX A2: Draft of Manuscript to be submitted to Waste Management

Online Sorting of Recovered Wood Waste

by Automated XRF Technology

Submitted by

A.R. Hasan1, Helena Solo-Gabriele1,*,

Timothy Townsend2

December 1, 2008

For consideration for possible publication in

Waste Management

1University of Miami, Department of Civil, Architectural, and Environmental

Engineering. Coral Gables, Florida 33146-0630

2University of Florida, Department of Environmental Engineering Sciences. Gainesville,

FL 32611-6450

*Corresponding Author. Tel.305-284-3489; fax: 305-284-3492, Email address:

hmsolo@miami.edu

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ABSTRACT

Waste wood is frequently contaminated with wood treatment preservatives including

chromated copper arsenate (CCA) and alkaline copper quat (ACQ), both of which

contain metals which contaminate recycled wood waste products. The objective of this

research was to evaluate the use of automated X-ray fluorescence (XRF) systems for

identifying and removing CCA and ACQ treated wood within recovered wood waste

stream. A full-scale unit was used for experimentation. This unit consisted of two large

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. A

randomized block design was used to evaluate the operational parameters of the system,

including wood feeding rate and conveyor belt speed. Results indicated that online

sorting efficiencies of waste wood by XRF technology were high based on their number

of pieces (70-99%), weight (74-92%) or metal contents (81-99% for As, 74-92% for Cu

and 83-97% of Cr).

Keywords: ACQ, arsenic, CCA, copper, chromium, treated wood, waste wood and XRF.

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1. INTRODUCTION

Waste wood is either considered as raw material for many industries such as mulch

production (Blassino et al. 2002, Jacobi et al. 2007, Solo-Gabriele and Townsend 1999)

Waste to Energy plants (Jambeck et al 2007, Solo-Gabriele et al, 2002), panel boards, or

ends up in landfills. Waste wood commonly contains two basic types of wood:

vegetative debris and construction/demolition (C&D) wood (Jacobi et al. 2007). C&D

wood waste includes sawn wood products (lumber, timber, plywood, posts, etc...) which

can be either untreated or treated. As-based treated wood such as CCA-wood (that

contains chromium and copper also) is the most common portion among the treated

fraction of the wood waste stream in the U.S.. Cu-based treated wood such as ACQ-wood

is another common material that is expected to increase in the wood waste stream due to

the shift from the production of As-based treated wood to a copper-based treatment, due

to the phase out by regulatory agencies in the US and other countries.

The metals found in the more common treated wood products, arsenic, chromium and

copper, are all of environmental concerns. The first two are considered human

carcinogens and copper is toxic for aquatic organisms (Flemming and Treavors, 1989;

Stook et al., 2004; Dubey et al., 2007). The primary benefit of sorting As- and Cu-based

treated wood from wood waste is the production of a recycled product that is free from

wood preservative contaminants. The untreated wood fraction can then be used for

beneficial uses, such as for the production of a much cleaner mulch or wood fuel.

Furthermore, sorting will facilitate the diversion of treated wood from open dumpsites

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and unlined landfills and so provides protection of the surface and ground waters that

receive leachate from unlined landfill facilities and decrease the requirement of leachate-

treatment at these facilities. In many cases in the U.S., wood waste is disposed in lined

landfills (Jambeck et al 2007). Efficient sorting of the treated wood component will

allow for a smaller waste volume (as it would be free from untreated wood which can be

recycled) thereby decreasing the demand of lined landfills that receive waste wood

products.

Visual sorting of treated wood sorting augmented by chemical stains or handheld XRF

units is considered laborious, time consuming and expensive (Jacobi et al 2007, Solo-

Gabriele et al 2004), LIBS technology is suitable for online sorting but requires a longer

time of inspection compared to XRF technology and is also impacted by the presence of

surface coatings. XRF technology is a non-destructive technique of metals’ inspection,

requiring no prior sample preparation. The technology is very fast, requiring only

milliseconds for sample inspection, which makes it suitable for online applications.

Online sorting by XRF has been well established for sorting metal scraps but never been

applied at the full scale for the sorting of waste wood.

Theory behind XRF inspection is summarized here. High energy X-ray aimed to treated

wood pieces from X-ray tube will knock electrons out of the innermost orbital of atoms

in the treated wood changing the atoms into unstable ions. A more energetic electron

from outer orbital will move into the newly vacant space in the inner orbital in order to

reach the lowest stable energy state and so releasing the extra energy possessed before.

The emitted energy is equal to the difference in energies between the innermost orbital

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and the outer one, thus it is a characteristic of the element fluorescing. Emitted energy as

photons can be detected by an 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 versus energy (KeV). The ratio of area under

the measured counts-curve to a reference area of pure metal spectrum is called the

threshold. Minimizing the threshold is important for detection and diversion of weathered

wood pieces, but may increase the interference from other metals that has a spectrum

overlapping or very close to the one of concern as the case of Pb with As and Zn with Cu.

After inspection of high energy dispersion from metals, the time to count the emitted

energies is called the measurement time.

2. METHODS

2.1 Sorting Equipment

The sorting equipment consisted of an infeed motorized belt-conveyor of 6 m length, 108

cm width and 297.2 cm height topped with 15.3 cm side guard-channels, the actual width

of the belt is 81.3 cm. In addition, an inclined conveyor, 45o incline of 3 m length and

108 cm width and 165 cm highest end, was installed perpendicular to the discharge end

of the infeed conveyor. The infeed conveyor was designed to convey wood to the XRF

detection unit, and the inclined conveyor to move the untreated wood to a separate pile

for further processing as mulch. The belt motors were wired to a 3-phase 480 volts

generator through a variable frequency (0-60 Hz) drive (VFD) that controls the belt

speed.

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The XRF detection unit was installed on the top of the infeed conveyor. The XRF

inspection system consisted of an X-ray tube (Varian Medical Systems, model VF-50J

RH/S-1.0/S, Salt Lake City, UT) operated at 44 kV and 1 mA, mounted at 40 cm distance

from the belt, emitting an X-ray beam downward when energized with 70o cone angle.

The diffracted ray from the wood was detected by a detector (Amptek, model XR-

100CR, Bedford, MA). This X-ray detection system overcame some of the proximity

problems of earlier systems and was mounted with 45o angle from the horizontal at a

distance of approximately 30 cm above the wood pieces thereby significantly increasing

the proximity requirement from 2.5 cm in earlier models and thus allowing for inspection

of the wood from the top down, instead of from the bottom up. The detector was

connected to a digital pulse processing (DPP) unit (Amptek, DP4, Bedford, MA) which

was connected to a control panel. The control panel had a central computer and was

controlled by customized software (AAI-UofM, Austin AI, Austin, TX). After inspection,

wood pieces passed through the rest of the inspection chamber mounted on the infeed

conveyor. Treated wood was then discharged from the end side of the conveyor by a

slide-way diverter (a steel sheet of 81.3x81.3x0.6 cm operated pneumatically by a driving

piston connected to an air compressor) thereby bypassing the inclined conveyor.

Untreated wood would fall on the incline conveyor which would move this wood type to

a separate location.

2.2 Wood sorting by XRF

This project focuses on wood inspection and sorting based on the presence of As and/or

Cu, the main elements of CCA wood preservative and the later for ACQ preservative.

Once As or Cu are inspected in the wood, the time required to move the slide-way

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diverter which is equal to the travel time of the wood piece on the moving belt from the

inspection point to the discharge end of the conveyor is called the delay time. The delay

time is a function of the belt speed. The diverter was designed to stay in the sorting open

position (45o to the horizontal level) for a time equal to the sum of measurement times

providing consecutive detection of each treated wood piece, this total time can be

increased or decreased by a small value called pulse adjust to allow time for wood to

transition from the belt to the diverter. The total time the diverter to remain in the sorting

position is called the dwell time.

Lower threshold limits will allow higher efficiencies of treated wood sorting, but to an

extent where the interference from the background levels of targeted elements or

elements of overlapping spectra starts to give false indication of As and/or Cu detection

such as Pb with As and Zn with Cu, the four of these elements can be found at very low

concentrations in the untreated wood (need a reference). Both As and Cu was found to

have a finite background levels in the rubber belt, As was in the order of 100 ppm, and

Cu is in 250 ppm, also, Cu was found as a component of the belt seam and its rivets. Zinc

was found as a major component of the rubber belt material. The lowest achieved

threshold for As in this research was 0.02 and 0.05 for Cu. At the 0.05 limit of Cu, the

sorting system was detecting Cu in the revolving seam in a rate of one over three

consecutive times.

Reducing the measurement time will increase the capacity of the system to sort wood

pieces in time units to an extent where the system will not be able to detect the targeted

metals due to the weathering effects of wood or it small sizes. In the contrary it was

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found that increasing the measurement time will increase the sorting efficiency to an

extent where the background levels of elements will start to play a major rule in the

collected number of counts during the time interval of measurement and so less accurate

sorting of wood. In this research, measurement time of 250 ms was chosen for most of

the experiments and found to reflect in the higher efficiencies of wood sorting.

2.3 Experimental design

Wood pieces used in this study were chosen based on their length to range from 5 cm to

150 cm, and grouped in two sets with 50:50 of untreated wood vs. treated wood for the

first set and 95:05 for the second set. In order to eliminate the effect of spatial distribution

of wood pieces, each wood group used in this research (500 pc of treated wood and 500

pc of untreated wood for the first set and 50 pc of treated wood and 950 pc of untreated

wood for the second set) has the same probability distribution regarding their length,

since the length was found as the most important dimension to affect wood inspection

and sorting. Figure 5 show the distribution based on the length of the 50:50% set.

Each wood piece used in this research was characterized and labeled for its dimensions,

treated wood in addition, was characterized and labeled for its type of treatment (CCA,

ACQ or as others, when identified as treated but with no match and usually these pieces

are very weathered) and the concentration of arsenic, chromium and copper in ppm using

a handheld XRF (Innov-X type alpha, Woburn, MA, USA), the resulted distribution of

each metal among the 500 pieces of the 50:50 experiments and the 50 pieces of the 95:05

experiments is shown in figure 2.2. The quantity in grams for each metal was calculated

from the volume of each piece and its metals’ content assuming all pieces are Southern

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Yellow Pines of density 511 kg/m3. Since the handheld XRF readings are relevant 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

concentration was corrected using Block’s formula (Block et al., 2007), chromium and

copper were modified using unpublished formulas of the author. Table 1 summarizes the

characteristics of the treated wood pieces.

Two main sets of experiments were conducted to evaluate the efficiency of wood sorting

under different operational conditions of wood 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), both sets were

designed as randomized factorial block design with replication (Hicks and Turner, 1999).

The first set included nine experiments each with a different combination of FR and BS

and the second 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.

After each experimental run, wood-pieces in the two piles (treated and untreated) were

sorted counted and weighed manually according to their label as treated or untreated, and

further to their type of treatment for treated pieces ending up with four groups in each

pile (CCA, ACQ, Others and Untreated).

2.4 Data analysis

Sorting efficiencies were calculated for each experimental run based on the number of

pieces, weight and metal contents of As, Cu and Cr. Treated wood pieces efficiencies

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were calculated based on the fraction of treated pieces ended up in the treated pile to the

total number of pieces (500 in the 50:50 exp or 50 in the 95:05 exp.). Untreated wood

pieces efficiencies were calculated based on the fraction of untreated pieces ended up in

the untreated pile to the total number of pieces (500 or 950, accordingly). Untreated

pieces ended up in the treated pile due to two mechanisms, either overlapping over the

belt with treated pieces and so diverted together or bounced from the inclined conveyor

and so not ending up in the untreated pile. Bounced wood pieces were found always to be

from pieces taller than 80 cm, Also when tall untreated pieces overlap with shorter

treated ones, it was found unlikely to be sorted together especially if the treated pieces

were proceeding on the belt. Based on this, Overlapping rate was calculated as

percentage fraction of untreated pieces of length less than 80 cm ended up in the treated

pile, and the bouncing rate was calculated the same but for pieces of length greater than

80 cm.

3. RESULTS AND DISCUSSION

3.1 Wood distribution

Wood characteristics were collected in advance to experimentation and retrieved during

different experiments, figure 3.1a show wood distribution in two piles for the 50:50

experiment based on number of pieces and weight for one of the experimental runs in this

research (BS = 0.25 m/s, FR = 20 pc/min), and figure 3.1b same but for 95:05

experiment. For the 50:50 experiment, the treated pile is mostly consists of treated wood

96% by number of pieces and 95% by weight, same the untreated pile (86% of untreated

wood by number of pieces and 84% by weight). The 95:05 experiments have similar

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trends in the untreated pile (99% untreated wood by number of, 98% by weight), but a

different behavior was found in the treated pile were less than half of the pile are treated

wood. In the 95:05 experiments, untreated wood pieces ended up in the treated pile were

mostly due to overlapping with treated pieces. Detection and sorting of small portion of

treated wood in a wood waste stream will cause a diversion of almost similar number of

untreated wood, and in this case, will not be a major loss of clean wood, since the number

of treated wood originally is small. ACQ and others’ wood pieces are mostly shown to be

located in the untreated pile.

3.2 Wood dimensions

Wood dimensions as one of the characteristics were found to affect the sorting of treated

and untreated wood. Dimension of treated wood play a major role in the number of times

a piece will be detected and so based on its physical appearance and metallic contents as

new or weathered, the number of counts registered will decide the diversion of the piece

or not. Also it was found that some small treated pieces will be sorted by the diverter but

will bounce from the diverter and fly to rest on the inclined conveyor and so sorted to the

untreated pile, such pieces will not have a major effect on the sorting efficiency based

weight or metallic content, but has n equal effect to any wood pieces based on the

efficiency of the number of pieces, and hence this research is taking into consideration all

types of sorting efficiencies.

Untreated wood sorting efficiency that represent the fraction the untreated wood in the

untreated pile was less than 100% as it should be since untreated wood should fall on the

inclined conveyor and move to the untreated pile, the main reason behind that was due to

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the overlapping between the treated and the untreated wood, where overlapped pieces

were sorted by the diverter, also some tall untreated wood pieces were bouncing off the

inclined conveyor and fell down nearby the treated pile. Overlapped pieces in all

experiments ranged from 0.6-29% and bounced pieces ranged from 2.2-5.8%. Generally,

both overlapping and bouncing rates increase with increasing the belt speed and the

feeding rates, hereby, reducing the sorting efficiency of the untreated wood.

3.3 Sorting efficiencies

Based on the randomized block design with replication, and according to the combination of

threshold limits and measurement times, sorting efficiencies were very high based on the

fraction of CCA wood-pieces (figure 3.2 a and b) and were higher for the 50:50

experiments (92-96%) in comparison to 95:05 (77-86%), a much lower sorting

efficiencies based on the fraction of ACQ (figure 3.3) and others of wood pieces (20-61%

of the 50:50 exp.), but still very high regarding the Cu content in wood. Efficiencies of sorting

both treated and untreated wood based on number of pieces was generally above 76% (fig 3.4).

Sorting efficiencies in terms of the metallic contents of three elements in concern were very

high and higher for the 50:50 than the 95:05 exp’s, in summary for all experiments,

sorting efficiencies based on As content ranged from 82-99%, based on Cu content: 63-

92% were sorted in a contrary to the number of pieces, which shows that the small

portion of sorted ACQ wood was richer in their Cu-contents. 80-98% of chromium was

diverted, since Cr is a major component of the CCA-treated wood.

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

wood and to decrease for untreated wood with increasing the feeding rate from 20 to 60

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pc/min. Overlapping rate of weathered treated (under detection limit) stands behind the

increasing of this treated wood efficiency. Same reason for untreated wood, and so the

number of diverted pieces will increase due to the overlapping rate and thus decreasing

this untreated wood efficiency. In contrary to what was expected, belt speed didn’t have a

measured effect on the different efficiencies with the studied ranges.

4. CONCLUSIONS

Online wood waste sorting by XRF for the diversion of CCA and ACQ treated wood

preservatives is a promising process, where efficiencies as high as 90% can be achieved

based on the number of sorted pieces and efficiency as high as 99% can be achieved

based on the metallic contents. It is important to reduce the background levels of targeted

metals and noises from other metals of interfering spectra from the adjacent ancillaries of

the sorting system and so a much lower threshold limits, in addition to proper mechanical

design and inclusions of containment shields to reduce the bouncing rates of untreated

wood. Overlapping rate is a problem will domain in such speeds of operations.

In a summary, bouncing and overlapping rates were found to increase with increasing the

conveyor belt speed and the feeding rate. Also, increasing the feeding rate from 20 to 60

pc/min led to an increase in the sorting efficiency of based on the number of pieces for

the treated wood and to a decrease for the untreated wood. Metallic contents’ sorting

efficiencies were found to be independent from the system operational parameters in the

studied ranges and to depend mainly on the threshold limits and measurement time of

detection.

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Online sorting system by XRF will has a cost burden for a facility that depends on hand

sorting, regarding the capital cost of the XRF detection and sorting system, since the

operation cost is shared in both hand and online sorting, and so it is believed that the

environmental cost of diverted toxic metals pays back the equipment of the sorting

system.

ACKNOWLEDGEMENTS

This project was funded by the Town of Medley through Florida Department of

Environmental Protection, Innovative Recycling Grants Program. The authors of the

manuscript thank the wood recycling facility that hosted this project and the many

individuals who helped with the experimentation.

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REFERENCES

Blassino, M.; Solo-Gabriele, H. M.; Townsend, T. G., 2002. Pilot scale evaluation of sorting technologies for CCA treated wood waste. Waste Management and Research, 20(3): 290-301.

Block, C. N.; Shibata, T.; Solo-Gabriele, H. M.; Timothy G. Townsend, 2007. Use of handheld X-ray fluorescence spectrometry units for identification of arsenic in treated wood. Environmental Pollution, 148:627-633. Dubey, B.; Townsend, T.; Solo-Gabriele, H.; Bitton, G., 2007. Impact of Surface Water Conditions on Preservative Leaching and Aquatic Toxicity from Treated Wood Products. Environ. Sci. Technol., 41(10): 3781 -3786. Flemming, C.; Trevors, J., 1989. Copper toxicity and chemistry in the environment: a review. Water, Air, Soil Pollut. 44, 143- 158. Hicks, R. C.; Turner, K. V., (1999) Fundamental Concepts in the Design of Experiments, 5th edition. Oxford University Press, New York. Jacobi, G., Solo-Gabriele, H., Townsend, T., Dubey, B., 2007. Evaluation of Methods for Sorting CCA-treated Wood. Waste Management, 27: 1617-1625. Jambeck, J.; Weitz, K., Solo-Gabriele, H.; Townsend, T.; Thorneloe, S., 2007. CCA-Treated Wood Disposed in Landfills and Life-cycle Trade-Offs With Waste-to-Energy and MSW Landfill Disposal. Waste Management, 27(8): S21-S28. Solo-Gabriele, H. M; Townsend, T. G., 1999. Disposal Practices and Management Alternatives for CCA-treated Wood Waste. Waste Manage. Res., 17: 378-389. Solo-Gabriele, H.M., Townsend, T.G., Hahn, D.W., Moskal, T.M., Hosein, N., Jambeck, J., and Jacobi, G., 2004. Evaluation of XRF and LIBS Technologies for On-Line Sorting of CCA-Treated 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 Hazardous Materials, 89 (2-3): 213-232. Stook, K.; Dubey, B.; Ward, M.; Townsend, T.; Bitton, G.; Solo-Gabriele, H., 2004. Heavy Metal Toxicity of Pressure Treated Wood Leachates with MetPLATETM. Bull. Environ. Contam. Toxicol. 73:987–994. Townsend, T.G., Solo-Gabriele, H.M., Tolaymat, T., and Stook, K., 2003. Impact of Chromated Copper Arsenate (CCA) in Wood Mulch. The Science of the Total Environment, 309: 173-185.

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Table 2.1: 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

Fig. 2.1. Histograms of wood distribution based on number of pieces according to their

length for each group of treated and untreated wood samples of the 50:50%

experiment.

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Fig 2.2. As, Cu and Cr distribution in ppm and based on number

of pieces in the 50:50 (500 pc.) and 95:05 (50 pc.)

experiments.

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90%

100%

0

1

2

3

4

5

6

7

8

Frequency

Cr (ppm)

95:05 exp.

A-22

CCA89%

ACQ5%

O2%

UT4%

Treated Pile       50:50 exp      %by No.Belt speed = 0.25 m/s     Feeding rate= 20 pc/min

CCA4%

ACQ8% O

2%

UT86%

Untreated Pile       50:50 exp      %by No.Belt speed = 0.25 m/s     Feeding rate= 20 pc/min

CCA89%

ACQ6%

O0%

UT5%

Treated Pile       50:50 exp      %by wt.Belt speed = 0.25 m/s     Feeding rate= 20 pc/min

CCA2%

ACQ13%

O1%

UT84%

Untreated Pile       50:50 exp      %by wt.Belt speed = 0.25 m/s     Feeding rate= 20 pc/min

CCA45%

UT55%

Treated Pile       95:05 exp      %by No.Belt speed = 0.375 m/s     Feeding rate= 20 pc/min

CCA1%

UT99%

Untreated Pile       95:05 exp      %by No.Belt speed = 0.375 m/s     Feeding rate= 20 pc/min

CCA35%

UT65%

Treated Pile       95:05 exp      %by wt.Belt speed = 0.375 m/s     Feeding rate= 20 pc/min

CCA1%

ACQ1%

UT98%

Untreated Pile        95:05 exp      %by wt.Belt speed = 0.375 m/s     Feeding rate= 20 pc/min

a) a)

a) a)

b) b)

b) b)

A-23

Fig. 3.1. Wood distribution in two piles after an experiment of a) 50:50 and b) 95:05, based on number of pieces (above) and weight (below).

a)

b)

Fig. 3.2. Treated wood sorting efficiencies based on number of CCA pieces and their

metallic content, a) As and b) Cr

8486889092949698100

7880828486889092949698

20 40 60 20 40 60 20 40 60

Belt speed (m/s)

As So

rting eff. (%

wt.)

CCA sorting eff. (%

wt.)

Feeding rate(pc./min)

CCA (pc./pc.)

As (g/g)

8486889092949698100

7880828486889092949698

20 40 60 20 40 60 20 40 60

Belt speed (m/s)

Cr Sorting eff. (%

wt.)

CCA sorting eff. (%

wt.)

Feeding rate(pc./min)

CCA (pc./pc.)

Cr (g/g)

A-24

Fig 3.3. Treated wood sorting efficiencies based on number of ACQ pieces and their

metallic content of Cu

Fig. 3.4. Treated and untreated wood sorting efficiencies based on their total number of

pieces

0102030405060708090100

0

10

20

30

40

50

60

70

20 40 60 20 40 60 20 40 60

Belt speed (m/s)

Cu Sorting eff. (%

wt.)

ACQ sorting eff. (%

wt.)

Feeding rate(pc./min)

ACQ (pc./pc.)

Cu (g/g)

0

20

40

60

80

100

120

7476788082848688909294

20 40 60 20 40 60 20 40 60

Belt speed (m/s)

UTW

 Sorting eff. (%

by pc. No.)

TW sorting eff. (%

by pc. No.)

Feeding rate(pc./min)

TW (pc./pc.)UTW (pc./pc.)