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Investigation of reacted copper(II) species in micronized copper treated wood Xue, Wei 2015

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Investigation of Reacted Copper(II) Species in Micronized Copper Treated Wood  by Wei Xue  MSc., Imperial College London, 2008  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) June 2015  © Wei Xue, 2015 ii  Abstract Wood preservatives using micronized particulate copper as the active ingredient recently introduced in the USA has generated controversies due to their limited intrinsic solubility compared to the conventional soluble copper treatments. Because the availability of soluble copper ions is essential for these preservatives to provide an effective treatment, concerns are centered on whether they are able to produce soluble copper, and the copper fixation mechanism of the treatment is little understood.  In this thesis, micronized copper treated wood were studied using a combination of Electron Paramagnetic Resonance (EPR) spectroscopy and X-ray Fluorescence (XRF) spectroscopy. The identification and characterization of soluble and chemically fixed copper species were discussed. A calibration standard was developed to quantify the solubilized and fixed copper species in the micronized copper treated wood, which also contains unreacted particulate copper.  On the basis of the experimental results, the fixation mechanism is thought to be triggered by the reaction between the carboxylic acid protons in hemicellulose and pectin of wood with the particulate copper, and the quantities of the solubilized and fixed copper species are determined by the availability of the acidic protons. Results from the studies on micronized copper treated earlywood and latewood, as well as the effect of monoethanolamine additive provided further support on the theory of the fixation mechanism.  Soil exposure experiment suggested that the Cu fixation may be affected by the moisture level, organic content and metal content in the soil. Study on micronized copper treated heartwood showed that the particulate Cu may react with the resin acids in addition to the major iii  wood components. The effects of fungal colonization and bio-incision on the pre-treatment material were also briefly discussed.  iv  Preface The work in Chapter 2 is based on a publication in the journal Holzforschung: [Xue W], Kennepohl P, Ruddick JNR (2012) Investigation of copper solubilization and reaction in micronized copper treated wood by electron paramagnetic resonance (EPR) spectroscopy. Holzforschung 66:889–895. The results are reproduced by permission of De Gruyter. The preparation of the sawdust from the untreated and commercially treated lumbers, and collection of the XRF data were carried out by Prof. John Ruddick and his students. I carried out the in-lab micronized copper treatments, collection and analysis of all the EPR data. Manuscript for publication was written in collaboration with Prof. Pierre Kennepohl and Prof. John Ruddick.  The work in Chapter 3 is based on a publication in the journal Holzforschung: [Xue W], Kennepohl P, Ruddick JNR (2013) Quantification of mobilized copper(II) levels in micronized copper-treated wood by electron paramagnetic resonance (EPR) spectroscopy. Holzforschung 67:815–823. The results are reproduced by permission of De Gruyter. The preparation of the sawdust from the untreated and commercially treated lumbers, and collection of the XRF data were carried out by Prof. John Ruddick. The DDACarbonate analysis was carried out by FPInnovations. I carried out the in-lab micronized copper treatments, collection and analysis of all the EPR data. Manuscript for publication was written in collaboration with Prof. Pierre Kennepohl and Prof. John Ruddick.  The work in Chapter 4 is based on a publication in the journal Holzforschung: [Xue W], Kennepohl P, Ruddick JNR (2015) Reacted copper(II) concentrations in earlywood and latewood of micronized copper-treated Canadian softwood species. Holzforschung 69: 509-512. The v  results are reproduced by permission of De Gruyter. The preparation of the sawdust from the commercially treated lumbers and collection of the XRF data were carried out by Ravi Parhar and Prof. John Ruddick. I carried out the collection and analysis of all the EPR data. Manuscript for publication was written in collaboration with Prof. Pierre Kennepohl and Prof. John Ruddick.  In Chapter 5, the preparation of the sawdust from commercially treated lumbers, and collection of the XRF data were carried out by Prof. John Ruddick. I carried out all the EPR data collection and SOLVER calculations.  A conference paper based on part of the work in Chapter 6 was accepted by the 44th Annual Meeting of International Research Group on Wood Protection: [Xue W], Kennepohl P, Jin X, Ruddick JNR (2013) Effect of soil contact on reacted copper(II) levels in micronized copper treated wood. Internat. Res. Group on Wood Pres. Doc. No. IRG/WP 13-30616. The soil exposure and the sonication vs. stirred leaching experiments were carried out by Xingguo Jin. The static leaching experiment was carried out by Prof. John Ruddick. The collection of the XRF data was carried out by Xingguo Jin and Prof. John Ruddick. The soil analysis was carried out by Pacific Soil Analysis Inc. I carried out all the pH and EPR data collections and analysis. Manuscript for the conference paper was written in collaboration with Prof. Pierre Kennepohl, Xingguo Jin and Prof. John Ruddick.  A conference paper based on part of the work in Chapter 7 was accepted by the 32th Annual Meeting of Canadian Wood Protection Association: [Xue W], Kennepohl P, Ruddick JNR (2012) Mobilized copper(II) concentration in sapwood and heartwood of MCQ treated sawdust. Proc. Canadian Wood Preservation Association. The preparation of the sawdust from the untreated and commercially treated lumbers, and collection of the XRF data were carried out vi  by Ravi Parhar, Xingguo Jin and Prof. John Ruddick. I carried out all the in-lab micronized copper treatments, extraction of resin acids, synthesis of the Cu-resin complex, collection and analysis of the EPR and FTIR data. Manuscript for the conference paper was written in collaboration with Prof. Pierre Kennepohl and Prof. John Ruddick.  vii  Table of Contents  Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iv Table of Contents ........................................................................................................................ vii List of Tables ............................................................................................................................... xii List of Figures ...............................................................................................................................xv List of Equations ........................................................................................................................ xxi List of Schemes .......................................................................................................................... xxii List of Abbreviations ............................................................................................................... xxiii List of Symbols ...........................................................................................................................xxv Acknowledgements .................................................................................................................. xxvi Dedication ................................................................................................................................ xxvii Chapter 1: Introduction ................................................................................................................1 1.1 Fundamentals of wood and copper based wood preservatives ....................................... 1 1.1.1 Basic anatomy of wood ............................................................................................... 2 1.1.2 Chemical composition of wood .................................................................................. 4 1.1.2.1 Major chemical components ............................................................................... 4 1.1.2.2 Extractives........................................................................................................... 8 1.1.2.3 Minor polymeric substances ............................................................................. 15 1.2 Copper based wood preservatives ................................................................................. 15 1.3 Electron Paramagnetic Resonance (EPR) Spectroscopy .............................................. 20 1.3.1 The Zeeman Effect .................................................................................................... 22 viii  1.3.2 g-factor ...................................................................................................................... 25 1.3.3 Hyperfine coupling ................................................................................................... 27 1.3.4 EPR of copper(II) complexes.................................................................................... 29 1.4 Thesis overview ............................................................................................................ 31 Chapter 2: Investigation of copper solubilization and reaction in micronized copper treated wood ..............................................................................................................................................33 2.1 Introduction ................................................................................................................... 33 2.2 Material and methods .................................................................................................... 33 2.2.1 In-lab sawdust treatment method .............................................................................. 33 2.2.2 Sawdust from industrial treated wood ...................................................................... 34 2.2.3 EPR data acquisition and process ............................................................................. 34 2.3 Results and discussion .................................................................................................. 35 2.3.1 In-lab CuSO4 solution treated sawdust ..................................................................... 35 2.3.2 In-lab BCC treated sawdust ...................................................................................... 40 2.3.3 Industrial ACQ, MCQ and MCA treated samples .................................................... 44 2.4 Conclusions ................................................................................................................... 47 Chapter 3: Quantification of reacted Cu(II) in micronized copper treated wood .................48 3.1 Introduction ................................................................................................................... 48 3.2 Material and methods .................................................................................................... 49 3.2.1 Sawdust treatment with CuSO4 solutions ................................................................. 49 3.2.2 Sawdust treatment with micronized copper suspensions .......................................... 49 3.2.3 Examination of commercial material ........................................................................ 50 3.2.4 XRF and EPR data acquisition and process .............................................................. 51 ix  3.3 Results and discussion .................................................................................................. 51 3.3.1 CuSO4 treated sawdust .............................................................................................. 51 3.3.2 Sawdust treatment with micronized copper suspensions .......................................... 53 3.3.2.1 MC treatment .................................................................................................... 53 3.3.2.2 MCA treatment with fixed copper to azole ratio .............................................. 57 3.3.2.3 MCQ treatment with fixed Cu-to-quat ratio ..................................................... 59 3.3.2.4 MCQ treatment with varying Cu-to-quat ratio ................................................. 62 3.3.3 Quantification of reacted Cu levels in commercial micronized Cu treated wood .... 64 3.4 Conclusions ................................................................................................................... 72 Chapter 4: Reacted Cu(II) concentrations in earlywood and latewood of micronized copper treated Canadian softwood species.............................................................................................73 4.1 Introduction ................................................................................................................... 73 4.2 Material and methods .................................................................................................... 74 4.3 Results and discussion .................................................................................................. 74 4.4 Conclusions ................................................................................................................... 79 Chapter 5: Reacted Cu(II) concentrations in amine amended micronized copper treated red pine and lodgepole pine ........................................................................................................80 5.1 Introduction ................................................................................................................... 80 5.2 Material and methods .................................................................................................... 82 5.2.1 Sampling of MCEA treated wood............................................................................. 82 5.2.2 Leaching of MCEA treated wood ............................................................................. 82 5.2.3 Mixtures of ACQ and CuSO4 treated sawdusts ........................................................ 82 5.2.4 Data acquisition and process ..................................................................................... 83 x  5.2.5 Simulation of Cu-O and Cu-N mixed spectra using Microsoft Excel SOLVER ...... 83 5.3 Results and discussion .................................................................................................. 84 5.3.1 Simulation of EPR spectra of ACQ and CuSO4 treated sawdust mixtures............... 84 5.3.2 Quantification of reacted Cu(II) in MCEA treated red pine and lodgepole pine ...... 86 5.3.3 Leaching of MCEA treated red pine ......................................................................... 91 5.4 Conclusions ................................................................................................................... 93 Chapter 6: Effect of soil contact on reacted copper(II) levels in micronized copper treated wood ..............................................................................................................................................94 6.1 Introduction ................................................................................................................... 94 6.2 Material and methods .................................................................................................... 98 6.2.1 Materials ................................................................................................................... 98 6.2.2 Soil ............................................................................................................................ 98 6.2.3 Installation and recovery of the samples ................................................................. 100 6.2.4 pH measurement and measurement of possible leaching during pH determination101 6.2.5 Sonication and stirred leaching comparison study .................................................. 102 6.2.6 Static leaching study ............................................................................................... 102 6.3 Results and discussion ................................................................................................ 103 6.3.1 Soil exposure studies............................................................................................... 103 6.3.1.1 Soil A .............................................................................................................. 103 6.3.1.2 Soil B .............................................................................................................. 107 6.3.2 Leaching methods: stirring vs. sonication .............................................................. 111 6.3.3 Static leaching ......................................................................................................... 113 6.4 Conclusions ................................................................................................................. 116 xi  Chapter 7: Chemistry of micronized copper treatment of sapwood and heartwood ..........119 7.1 Introduction ................................................................................................................. 119 7.2 Material and methods .................................................................................................. 120 7.2.1 Micronized copper treatment of sawdust ................................................................ 120 7.2.2 Extraction of resin from red pine heartwood .......................................................... 121 7.2.3 Synthesis of Cu-abietate and Cu-resin .................................................................... 121 7.2.4 Simulations of Cu-wood and Cu-resin mixed spectra ............................................ 122 7.2.5 Commercial micronized copper treated lodgepole pine ......................................... 123 7.2.6 Micronized copper treatment of bio-incised spruce sawdust .................................. 123 7.3 Results and discussion ................................................................................................ 123 7.3.1 Effect of resin acids on micronized copper treated red pine heartwood ................. 123 7.3.2 In-lab micronized copper treatments in sapwood and heartwood .......................... 128 7.3.2.1 Southern pine .................................................................................................. 129 7.3.2.2 Red pine .......................................................................................................... 131 7.3.2.3 Lodgepole pine................................................................................................ 136 7.3.3 Micronized copper treatment responses in sapwood and heartwood of commercial treated lodgepole pine ......................................................................................................... 138 7.3.4 Micronized copper treatment of biologically-incised spruce sawdust .................... 143 7.4 Conclusions ................................................................................................................. 145 Chapter 8: General conclusions and future directions ...........................................................148 Bibliography ...............................................................................................................................153  xii  List of Tables Table 1.1 Subclasses of terpenes (terpenoids) ................................................................................ 9 Table 1.2 Field of resonance at g = 2. Spectrometers are classified based on microwave frequency ranges which are labeled with specific letters .............................................................. 26 Table 2.1 Treatment, drying method and EPR schedule for southern pine sawdust .................... 34 Table 2.2 Simulated EPR parameters for CuSO4 treated sawdust (set 1) at various Cu concentrations, recorded 2 months after the treatment ................................................................. 36 Table 2.3 Simulated EPR parameters for CuSO4 (0.051% m/m on Cu basis) treated wood (set 1), recorded before and after leaching over a period of 2 months ..................................................... 38 Table 2.4 Simulated EPR parameters for sawdust treated with BCC suspension (0.53% m/m on Cu basis), recorded before and after leaching over a period of 2 months .................................... 42 Table 2.5 Simulated EPR parameters for commercial ACQ, MCQ and MCA treated red pine samples before and after leaching ................................................................................................. 45 Table 3.1 Total Cu content of southern pine sawdust treated by MC and MCA suspensions with increasing Cu concentration (% m/m on Cu basis). aStandard error estimated at ±0.02% ........... 56 Table 3.2 Total Cu (% m/m on Cu basis) content of southern pine sawdust treated by MCQ with increasing Cu concentration and MC with increasing quat concentration. aStandard error estimated at ±0.01% ...................................................................................................................... 61 Table 4.1 Simulated EPR parameters of RPSW29B, RPSW36A, and WHHW50A .......................... 75 Table 5.1 Theoretical and SOLVER simulated Cu-N and Cu-O contents of mixture C, D and E made up from reference samples A and B (c.f Chapter 5.2.3)...................................................... 85 xiii  Table 5.2 Total Cu retention (% m/m Cu) determined by XRF in MCEA treated red pine and lodgepole pine. a ±0.03% .............................................................................................................. 88 Table 5.3 Total Cu and simulated reacted Cu(II) contents in RP2-1 before and after leaching. a ±0.02% .......................................................................................................................................... 92 Table 6.1 Soil characteristics ........................................................................................................ 99 Table 6.2 Designations of the 8 end-matched pairs sawn from each red pine slice ................... 101 Table 7.1 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of MCQ treated red pine HW sawdust and synthesized Cu-resin complex. a stdev = ±0.01; b stdev =±0.01 .................................................................................................................. 126 Table 7.2 Simulated EPR parameters of micronized copper treated southern pine SW and HW..................................................................................................................................................... 130 Table 7.3 Simulated EPR parameters of micronized copper treated red pine RP-1 and RP-2 ... 133 Table 7.4 Simulated EPR parameters of micronized copper treated lodgepole pine SW and HW..................................................................................................................................................... 137 Table 7.5 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine SW. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02..................................................................................................................................................... 139 Table 7.6 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02..................................................................................................................................................... 140 xiv  Table 7.7 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW knots. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 ......................................................................................................................................... 140 Table 7.8 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW with signs of white-rot decay. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 ........................................................................................ 142  xv  List of Figures Figure 1.1 Earlywood (light colored bands) and latewood (dark colored bands) ........................... 3 Figure 1.2 Treated sapwood (green region) and heartwood (brown region) .................................. 4 Figure 1.3 Principle structures of: a) cellulose; b) arabinoglucuronoxylan, a type of hemicellulose......................................................................................................................................................... 5 Figure 1.4 A segment of softwood lignin proposed by Adler (1977) ............................................. 6 Figure 1.5 Basic monolignol units of lignin: p-coumaryl alcohol (1), coniferyl alcohol (2) and sinapyl alcohol (3)........................................................................................................................... 7 Figure 1.6 An adaptation of Fengel's (1970) model of the associations between cellulose, hemicellulose and lignin ................................................................................................................. 8 Figure 1.7 a) Isoprene; b) examples of monoterpene; c) examples of diterpenoids ..................... 10 Figure 1.8 Structures of eight common resin acids: pimaric acid (1), sandaracopimaric acid (2), isopimaric acid (3), abietic acid (4), levopimaric acid (5), palustric acid (6), neoabietic acid (7) and dehydroabietic acid (8) ........................................................................................................... 11 Figure 1.9 Examples of simple phenols (1), stilbenes (2), flavonoids (3) and lignans (4) ........... 13 Figure 1.10 Examples of fats (1), generic structure of waxes (2), fatty acids (3) and fatty alcohols (4) .................................................................................................................................................. 14 Figure 1.11 Poly-α-1,4-D-galacturonic acid ................................................................................. 15 Figure 1.12 Co-biocides: a) didecyldimethylammonium bicarbonate/carbonate (DDA bicarbonate/ carbonate) used in ACQ-B and ACQ-D; b) tebuconazole used in CA-B ................ 17 Figure 1.13 The energy of an unpaired electron diverges into two spin states in the presence of an external magnetic field .................................................................................................................. 23 xvi  Figure 1.14 Comparison of an absorption spectrum and its dispersion spectrum ........................ 24 Figure 1.15 Simulated spectrum of a rhombic molecule with anisotropic g values ..................... 27 Figure 1.16 Influence of the magnetic field of a nucleus on the field experienced by an electron spin ................................................................................................................................................ 28 Figure 1.17 Simulated spectrum of methoxymethyl radical ......................................................... 29 Figure 1.18 The relationship between the EPR spectral parameters gz (■) and Az (○) for a series of Cu(II) compounds (based on data reported in Peisach and Blumberg 1974; Ruddick 1992; Ruddick et al. 2001) ...................................................................................................................... 31 Figure 2.1 EPR spectra of CuSO4·5H2O solid in boron nitride (BN), and sawdust treated with CuSO4 solutions at various concentrations (set 1). The sawdust samples were unleached (UL) and spectra recorded 2 months after the initial treatment ............................................................. 37 Figure 2.2 EPR spectra sawdust treated with 0.051% CuSO4 (set 1), unleached (UL) and leached (L). Samples measured over a period of 24 h (day 1) to 2 months ............................................... 38 Figure 2.3 EPR signal intensity of sawdust treated with CuSO4 versus treatment concentration (sample set 2) ................................................................................................................................ 40 Figure 2.4 EPR spectra of solid BCC in BN, micronized copper suspension containing 1% Cu, de-ionized water treated southern pine sawdust and 0.58% BCC suspension treated sawdust. Spectra were recorded 2 h after the initial sawdust treatment ...................................................... 42 Figure 2.5 Changes in EPR signal intensities of BCC suspension treated sawdust (set 2) with time. Spectra at day 0 were recorded within 2 h after initial treatment ........................................ 44 Figure 2.6 EPR spectra of commercial ACQ, MCQ and MCA treated red pine samples, as well as southern pine sawdust treated with BCC and CuSO4 in-lab. All samples were unleached ..... 46 xvii  Figure 3.1 Cu contents of CuSO4 treated sawdust determined by XRF against the corresponding EPR signal intensities ................................................................................................................... 52 Figure 3.2 Changes in reacted Cu levels of MC treated southern pine as a function of time after treatment: a) wet samples; b) dry samples .................................................................................... 55 Figure 3.3 Changes in reacted Cu levels of MCA treated southern pine as a function of time after treatment: a) wet samples; b) dry samples .................................................................................... 58 Figure 3.4 Changes in reacted Cu levels of MCQ treated southern pine as a function of time after treatment: a) wet samples; b) dry samples .................................................................................... 60 Figure 3.5 Changes in reacted Cu levels of MC with varying concentrations of quat treated southern pine as a function of time after treatment: a) wet samples; b) dry samples ................... 63 Figure 3.6 Reacted Cu, total Cu  and quat content  at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP25B). Relative orientations of faces sampled: a) S1; b) S3 (parallel to S1)........................................................................................................... 65 Figure 3.7 Reacted Cu, total Cu and quat content at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP29B). Relative orientations of faces sampled: a) S1; b) S2.................................................................................................................................... 66 Figure 3.8 Reacted Cu, total Cu and quat content at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP41B). Relative orientations of faces sampled: a) S1; b) S2.................................................................................................................................... 67 Figure 3.9 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP34A). Opposite faces sampled: a) S1; b) S3 ................ 69 Figure 3.10 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP36A). Adjacent faces sampled: a) S1; b) S2 ................ 70 xviii  Figure 3.11 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP46A). Adjacent faces sampled: a) S1; b) S2 ................ 71 Figure 4.1 Earlywood (EW) and latewood (LW) retentions of reacted Cu(II) and total Cu, measured in three consecutive rings of: a) MCQ treated RPSW29B; b) MCA treated RPSW36A . 76 Figure 4.2 Earlywood (EW) and latewood (LW) retentions of reacted Cu(II) and total Cu, measured in five consecutive rings of MCA treated WHHW50A .................................................. 77 Figure 5.1 Experimental (RAWD) and SOLVER simulated (SIMD) EPR spectra of mixture D compared against the Cu-N and Cu-O references ......................................................................... 86 Figure 5.2 Cu-N and Cu-O retentions of reacted Cu determined by simulations of MCEA treated red pine 4×4, measured in 1mm increments (up to 10mm): a) RP1-1; b) RP4-1 ......................... 89 Figure 5.3 Cu-N and Cu-O retentions of reacted Cu determined by simulations of an MCEA treated lodgepole pine 2×6 (LPP5-2), measured in 1mm increments (up to 10mm) .................... 90 Figure 5.4 Cu-N and Cu-O retentions of reacted Cu determined by simulations of an MCEA treated lodgepole pine 2×6 (LPP7-2), measured in 1mm increments (up to 10mm) .................... 91 Figure 6.1 A model structure of humic acid proposed by Stevenson (1994), comprising catechol, quinone and phenol as building blocks ......................................................................................... 95 Figure 6.2 A generalized model for a Cu2+ complexes to humic acid proposed by Senesi (1990)....................................................................................................................................................... 96 Figure 6.3 a) Samples being placed in the soil bed; b) final row being buried in soil.................. 99 Figure 6.4 Total Cu retentions, reacted Cu concentrations and pH of a) MCQ and b) MCA treated red pine exposed to soil A. The sonicated data is based on the effects of ultrasonication leaching during the measurement of the sample pH ................................................................... 106 xix  Figure 6.5 Total Cu retentions, reacted Cu concentrations and pH of a) MCQ and b) MCA treated red pine exposed to soil B. The sonicated data is based on the effects of ultrasonication leaching during the measurement of the sample pH ................................................................... 110 Figure 6.6 Total Cu retentions and reacted Cu concentrations of MCQ treated red pine before and after leaching by stirring and sonication ..................................................................................... 112 Figure 6.7 Total Cu retentions and reacted Cu concentrations of MCA treated red pine before and after leaching by stirring and sonication ..................................................................................... 113 Figure 6.8 Total Cu retentions and reacted Cu concentrations of MCQ treated red pine before and after static leaching ..................................................................................................................... 114 Figure 6.9 Total Cu retentions and reacted Cu concentrations of MCA treated red pine before and after static leaching ..................................................................................................................... 115 Figure 7.1 FTIR spectra of abietic acid, red pine HW extractives and Cu-resin ........................ 124 Figure 7.2 a) EPR spectra of MCQ treated red pine HW and SOLVER simulated spectrum of the treated HW using the treated HW-E and Cu-resin spectra as refrences; b) enlarged portion of a) in the region 2500-3000 G ......................................................................................................... 127 Figure 7.3 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MCA treated southern pine sapwood (SW) and heartwood (HW) ................................................................... 130 Figure 7.4 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated red pine SW, HW-M (30-33 years) and HW-J (0-10 years): a) RP-1; b) RP-2 ........................................ 132 Figure 7.5 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated red pine SW and SW-B: a) RP-1; b) RP-2 ................................................................................................ 135 Figure 7.6 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated lodgepole pine SW and HW ....................................................................................................... 137 xx  Figure 7.7 EPR spectra of 109B-8 from the knotty region of lodgepole pine HW and synthesized Cu-resin ....................................................................................................................................... 141 Figure 7.8 Lodgepole pine showing signs of white-rot decay .................................................... 143 Figure 7.9 Total copper loadings determined by XRF in bio-incised spruce and uncolonized controls after being treated with MCQ and MCA ...................................................................... 144  xxi  List of Equations Equation 1.1  E = msgeμBB0 ................................................................................................. 22 Equation 1.2  ∆E = ∆msgeμBB0 = geμBB0 .......................................................................... 22 Equation 1.3  hv =  geμBB0 ................................................................................................... 22 Equation 1.4  Beff = B0(1 − σ) ............................................................................................ 25 Equation 1.5  hv =  geμBB0(1 − σ) ...................................................................................... 25 Equation 1.6  g = hv/μBB0 .................................................................................................... 25 Equation 3.1  %Cu = 9.7 × 10−8(AUCmass) − 0.014 ................................................................. 52 Equation 5.1  %CuCu−N = 1.80 × 10−7(AUCmass) − 0.0097 ..................................................... 83 Equation 5.2  SIMc = z(Ax + By) ≈ RAWc........................................................................... 83 Equation 5.3  %CuCu−N = 1.80 × 10−7(xzAUCAmassc) − 0.0097 ............................................... 84 Equation 5.4  %CuCu−O = 9.7 × 10−8(yzAUCBmassc) − 0.013 .................................................... 84  xxii  List of Schemes Scheme 1.1 MeaH is monoethanolamine...................................................................................... 18  xxiii  List of Abbreviations  ACQ  Amine copper quat AUC  Area under the curve BCC  Basic copper carbonate CA  Copper azole CCA  Chromated copper arsenate CEC  Cation exchange capacity Cu-HDO Bis-(N-cyclohexyldiazeniumdioxy) copper DDA  Didecyldimethylammonium DPPH  2,2-diphenyl-1-picrylhydrazyl EDX  Energy Dispersive X-ray spectroscopy EPR  Electron Paramagnetic Resonance spectroscopy EW  Earlywood HW  Heartwood HW-J  Juvenile heartwood HW-M  Mature heartwood ICP-MS Inductively Coupled Plasma Mass Spectrometry ICP-OES Inductively Coupled Plasma Optical Emission Spectroscopy LW  Latewood LPP  Lodgepole pine MC  Micronized copper without co-biocide MCA  Micronized copper azole xxiv  MCQ  Micronized copper quat MeaH  Monoethanolamine RP  Red pine SP  Southern pine STEM  Scanning Transmission Electron Microscopy STXM  Scanning Transmission X-ray Microscopy SW  Sapwood SW-B  Blue stained sapwood WH  Western hemlock XAS  X-ray Absorption Spectroscopy XRF  X-ray Fluorescence spectroscopy   xxv  List of Symbols A  Hyperfine coupling constant B  Magnetic field strength E  Energy ge  g-factor of a free electron 𝑔𝑒 = 2.0023 h  Planck constant  ℎ = 6.6260 × 10−34𝑚2𝑘𝑔𝑠−1 I  Nuclear spin ms  Magnetic spin s  Electron spin B  Bohr magneton  𝜇𝐵 = 9.2740 × 10−24𝐽𝑇−1 υ  Frequency xxvi  Acknowledgements First and foremost I would like to thank my supervisors Prof. Pierre Kennepohl and Prof. John Ruddick, who are resourceful, patient and tremendously supportive throughout my time as a graduate student. Secondly, I would like to thank all the past and present members of the Kennepohl group, especially Dr. Vlad Martin-Diaconescu for the training in EPR experiments, Dr. Tulin Okbinoglu, Dr. Thamayanthy Sriskandakumar and Dr. Insun Yu for their support and encouragement. I am also very grateful to Prof. Chris Orvig for taking the time to read my thesis and giving valuable advice.  I would like to acknowledge Osmose Inc. and Timber Specialties Co. for their financial and material support on the project. I would like to thank the co-op students Xingguo Jin and Ravi Parhar from the UBC Forestry department who worked with me on the project.   I would like to thank the UBC Chemistry department support staff, in particular Ken Love and Alan Klady for their help over the years with equipment trouble shooting.  I wish to thank my parents for their constant support and encouragement. I am also eternally grateful to the Chen Family for their help in difficult times. Finally I would like to thank my friends Jie Fang, Luping Yan, Ningjian Liang, Jay Chi, Emiliya Mamleeva and Dr. Dinesh Aluthge who make the pleasant days fantastic and the occasional gloomy days slightly less unbearable. xxvii  Dedication This thesis is dedicated to Yongguang Xue and Qiaoling Wei.1  Chapter 1: Introduction 1.1 Fundamentals of wood and copper based wood preservatives As one of the most important products of nature, wood has long been used as a source of fuel, a chemical raw material and a construction material. Data released by Food and Agriculture Organization Statistics Division (FAOSTAT) of the United Nation shows that global roundwood removals in 2013 were over 3.6×109 m3, of which about half were wood fuel and half industrial roundwood. The decrease of total forest area in the period 2000-2010 is estimated at 5.2 million hectares per year, which equals a loss of 0.13% of the remaining forest area each year (FAO 2010). The net loss in this period is 37% lower than that in the 1990s as a result of both an increase in the reforestation and a decrease in the deforestation rate, which is indirectly facilitated by the advancement and greater application of wood protection methods that extend the service life of timbers and upgrade the values of less durable species. Wood used in construction and for utility distribution is prone to deterioration by various biological organisms including insects, bacteria and fungi due to sustained exposure to moisture. Wood in direct contact with soil, or fresh water or sea water, will suffer enhanced biodegradation unless protected, while sunlight leads to a loss of surface quality. Wood preservation measures make great environmental sense by protecting timber against the deterioration. This thesis studies the fixation chemistry and distribution of copper in micronized copper treated wood. Therefore, understanding the basic structure and composition of wood is essential to the experimental design and data interpretation of the research. 2  1.1.1 Basic anatomy of wood Wood from angiosperm trees (broad-leaved, dicotyledonous species) is classified as hardwood, and wood from gymnosperm trees (needle or cone shaped leaves, conifer species) is classified as softwood (Sjöström 1993). Hardwoods and softwoods are distinct at both macroscopic and microscopic levels. Because the studies presented in this thesis do not involve hardwood species, the discussion in this chapter will be limited to softwood.  In the temperate regions such as those found in North America, tree growth is restricted to the spring and summer months of a year, whereas in some tropical areas the growth periods are in response to wet and dry seasons. In softwood, cells formed early in the growth periods have larger cavities and thinner walls which are desirable features in an effective liquid transportation system (Sjöström 1993). These cells are lighter in color and are known as earlywood. The rate of growth reduces later in the growth period as rainfall or temperature decrease, and the cells formed are known as latewood, which consist of cells with a smaller diameter and thicker walls. These cells are densely packed and appear to have a darker color. The mechanical strength of wood is mainly provided by the thick-walled fibers of latewood. The distinct color differences between earlywood and latewood give rise to growth rings, which can be used to calculate the age of a tree (Figure 1.1). However, in regions where seasonal changes in temperature and rainfall are less pronounced, such as humid tropical regions, the growth period is continuous, therefore making the growth rings in softwoods less discernible (Fengel and Wegener 2011). 3   Figure 1.1 Earlywood (light colored bands) and latewood (dark colored bands)  All wood in a tree is first formed as sapwood, in which the cells are alive and filled with protoplasts. As the stem of a tree increases in girth the cells in the inner portion die after gradually losing water and stored nutrients, leaving only the younger and outer most part of the stem as sapwood (Figure 1.2). The dead heartwood is impregnated with organic deposits, known as extractives, such as oils, resin, phenolic substances and tannins, etc. The pits (perforations on cell walls for water and nutrient exchange) in softwood become aspirated as a result of the chemical transformation (Sjöström 1993). Oxidation of phenolic compounds often causes a darkening of color in the heartwood. While sapwood and heartwood are similar in strength, heartwood in some wood species (e.g. western red cedar and some pines) is more resistant to fungal decay due to the toxic chemical deposits. On the other hand, the high soluble carbohydrate and moisture contents in sapwood make it more susceptible to attack by insects, bacteria and fungi. Therefore, treating it with a suitable preservative chemical is vital to prolonging the service life of the timber. In lower biological hazard environments, such as above ground end-uses, other strategies such as wood modification or treatment with polymers to lower moisture uptake have also been used to extend the service life of building components (Fengel and Wegener 2011). 4   Figure 1.2 Treated sapwood (green region) and heartwood (brown region) 1.1.2 Chemical composition of wood 1.1.2.1 Major chemical components Wood is a highly structured composite with three major chemical components: cellulose, hemicellulose and lignin. Cellulose constitutes approximately 40-55% of the total cell wall mass and is the most abundant constituent of wood. The other 25-40% of the dry wood mass is made up of hemicellulose, and the rest of the 18-33% is lignin (Eaton and Hale 1993). Cellulose is a linear homopolysaccharide derived from β-D-glucopyranose units linked by β(1→4) glycosidic bonds (Figure 1.3a). It is colorless and hydrophilic. Naturally occurring cellulose microfibers are cellulose molecular chains arranged in a highly ordered fashion, and the crystalline structure is the main factor to the high tensile strength of wood. On the other hand, hemicellulose has an amorphous structure which is made up of extensively branched heteropolysaccharides. The building blocks of different hemicellulose consist of a variety of hexose and pentose sugars, some of which often contain uronic acid derivatives such as glucuronic acid (Figure 1.3b) or galacuronic acid. Hemicelluloses with extensive branching are soluble in water and susceptible to hydrolysis by acid. Unlike cellulose and hemicellulose, lignin is an amorphous macromolecule 5  with no defined primary structure (Figure 1.4). It is consist of cross-linked aromatic alcohols known as monolignols. Coniferyl alcohol, p-coumaryl alcohol and sinapyl alcohol (Figure 1.5) are the three basic types of monolignols from which all lignins are constructed. Lignin is hydrophobic, a property which is vital in conducting water in the plant stem, due to the aromatic nature of the molecule. a)  b)  Figure 1.3 Principle structures of: a) cellulose; b) arabinoglucuronoxylan, a type of hemicellulose 6   Figure 1.4 A segment of softwood lignin proposed by Adler (1977) 7   Figure 1.5 Basic monolignol units of lignin: p-coumaryl alcohol (1), coniferyl alcohol (2) and sinapyl alcohol (3)  Several theoretical models (Preston 1962; Fengel 1970; Fengel and Wegener 2011) have been developed to describe the associations between the three major chemical components in wood cell walls. It is commonly accepted that the strong crystalline cellulose microfibers make up the backbone structure of cell wall, while the amorphous hemicellulose and lignin act as matrix and encrustation materials bracing the microfibers (Figure 1.6). The hydrophobic lignin outer layer insulates the hydrophilic cellulose and hemicellulose from water, and the cross linkage of the material also increases the overall rigidity of cell wall (Eaton and Hale 1993). 8   Figure 1.6 An adaptation of Fengel's (1970) model of the associations between cellulose, hemicellulose and lignin 1.1.2.2 Extractives In addition to the main structural components, a large variety of low molecular weight compounds that comprise both lipophilic and hydrophilic types exist in wood. These non-structural constituents are called extractives and mainly consist of terpenoids, fats, waxes and phenolic derivatives. The extractives are located in the resin canals and the ray parenchyma cells. A large portion of the extractives are not soluble in water but can be extracted using organic solvents such as acetone, dichloromethane, diethyl ether or hexane. The extractives in each part of the same tree differ both in terms of the total amount and the composition. The heartwood  normally contains much more extractives than sapwood  in the case of pines (Fengel and Wegener 2011). Many extractable substances, such as certain terpenoids and phenolic compounds, are thought to be important contributing factors in the natural durability of wood by 9  having toxicity against microorganisms and insects (Rudman and Gay 1963; Weissmann and Dietrichs 1975; Bauch et al. 1977).  Terpenes are derived from isoprene units of pure hydrocarbons (Figure 1.7a) whereas terpenoids bear functional groups such as hydroxyl, carbonyl or carboxylic acid groups etc. Terpenes and terpenoids are divided into sub-classes based on the number of isoprene units linked in the molecule (Table 1.1), among which the mono- and di- terpene/terpenoids are dominant in softwood oleoresin. The monoterpenoids can either be acyclic, monocyclic or bicyclic compounds, and a few examples are illustrated in Figure 1.7b. Similarly, the diterpenes and diterpenoids are divided into acyclic, bicyclic, tricyclic, tetracyclic and macrocyclic according to their structural characteristics (Figure 1.7c). The resin acids are mostly tricyclic terpenoids (Figure 1.8) and they consist of 0.2-0.8% of the dry wood mass in pine and spruce (Fengel and Wegener 2011). Table 1.1 Subclasses of terpenes (terpenoids) Prefix Number of carbon atoms Number of isoprene (C5H8) units Hemi 5 1 Mono 10 2 Sesqui 15 3 Di 20 4 Sester 25 5 Tri 30 6 Tetra 40 8 Poly >40 >8   10   Figure 1.7 a) Isoprene; b) examples of monoterpene; c) examples of diterpenoids 11   Figure 1.8 Structures of eight common resin acids: pimaric acid (1), sandaracopimaric acid (2), isopimaric acid (3), abietic acid (4), levopimaric acid (5), palustric acid (6), neoabietic acid (7) and dehydroabietic acid (8) 12   A large number of phenolic compounds can be isolated from softwood extractives and many of them are evidently residuals of lignin biosynthesis. The phenolic compounds ranges from the simple phenols to the increasingly complicated stilbenes, flavonoids and lignans (Figure 1.9). Extractives also contain fats and waxes. Fats are esters of fatty acids with glycerol and waxes are esters of fatty acids with fatty alcohols (Figure 1.10). Their common fatty acid and alcohol components can also be found in the free forms in extractives found in the heartwood.  13   Figure 1.9 Examples of simple phenols (1), stilbenes (2), flavonoids (3) and lignans (4) 14   Figure 1.10 Examples of fats (1), generic structure of waxes (2), fatty acids (3) and fatty alcohols (4) 15  1.1.2.3 Minor polymeric substances Small amounts of proteins, starch and pectin can be found in the wood cell wall. Pectin is a polysaccharide found in the middle lamella and the membrane of the boarded pits between wood cells. It is made up of α-(1-4)-linked D-galacturonic acid (Figure 1.11), therefore rich in carboxylic acid functionality.   Figure 1.11 Poly-α-1,4-D-galacturonic acid 1.2 Copper based wood preservatives Timber treatment often involves applications of different biocides in combination with various physical processes to increase the wood durability. Chemical wood preservatives are either oilborne or waterborne. Selection of the preservative treatment often depends on the cost, as well as application of the timber and the environment it is installed in. Waterborne preservatives are exclusively used in residential consumer products and marine applications in North America due to their excellent effectiveness, low cost, lack of odor and relatively low toxicity to larger organisms. A key ingredient of many waterborne preservative formulae is copper – generally used as basic copper carbonate, which is often combined with other organic biocides to protect against copper tolerant organisms. Copper, an essential micronutrient in most living organisms, 16  has long been recognized for its biocidal activities in large doses. However, early applications in Europe and North America tended to use simple salts and leaching was a major problem. The development of fixed preservative formulations, particularly those containing chromium, allowed their widespread acceptance throughout the world. Even though development of new preservatives in recent years has focused increasingly on organic biocides, copper remains the most extensively used component due to its excellent performance against a wide range of organisms including algae, insects, bacteria, and fungi.   Other than production costs and product performance, increasing public awareness on health and environmental safety over the past few decades has become an important factor influencing the development of new preservatives. The negative public perception regarding chromium and arsenic led to the voluntary withdrawal of chromated copper arsenate (CCA) in the North American residential treated wood market in 2003. Several alkaline copper based preservatives have been successfully commercialized as replacements. Freeman and McIntyre (2008) published a detailed review of current copper based wood preservatives. Conventional copper based wood preservatives, such as alkaline copper quaternary (ACQ), copper azole (CA), copper citrate, copper chromate and bis-(N-cyclohexyldiazeniumdioxy)copper (Cu-HDO), contain copper solubilized in aqueous ethanolamine solutions. Earlier formulations solubilized copper using ammonium hydroxide, and ammoniacal copper zinc arsenate is still used for some industrial products. ACQ and CA are the most commonly used copper preservatives in Canada for protecting residential products such as decking and fencing. Both formulations contain solubilized copper in an aqueous organic amine (such as monoethanolamine) solution as the primary biocide. The major difference being that ACQ formulations use quaternary ammonium 17  compounds (quats) as the co-biocide (Figure 1.12a), whereas CA is augmented by an azole co-biocide (Figure 1.12b). a)  b)  Figure 1.12 Co-biocides: a) didecyldimethylammonium bicarbonate/carbonate (DDA bicarbonate/ carbonate) used in ACQ-B and ACQ-D; b) tebuconazole used in CA-B  Copper-amine complexes formed in the impregnating solution can be physically trapped in the polymeric matrices of wood cell walls by weak Van der Waals forces, and they are easily removed during leaching. However, most woods in temperate zones are weak or moderately acidic with pH ranges from 6.4 to 3.3 (Fengel and Wegener 2011). During treatment the alkaline copper complex in the solution also interacts with the acidic wood components, such as carboxylic acid, aromatic esters and phenolic hydroxyl groups, causing the copper to be bound (fixed) to the wood. These forms of chemically fixed copper complexes are stronger and less prone to leaching, which in turn reduces preservative depletion and environmental impact.  The balance of the copper and the alkaline solvent is important to ensure efficient fixation of the copper (Zhang and Kamdem 1999; Lucas and Ruddick 2002; Lee and Cooper 2010b), and 18  the fixation mechanism of alkaline copper preservatives relies on reaction between the alkaline copper and the acidic protons in wood (Lee and Cooper 2010a). The highly pH dependent mechanism is triggered by the interaction of the basic preservative solution with the most acidic protons of the carboxylic acids in a rapid acid base reaction (Scheme 1.1). This leads to protonation of the copper bound amine cation and a lowering of the pH to around 7 to 9, followed by cation exchange between the metal complexes and the acidic protons in wood (Staccioli et al. 2000). Studies on ammonia copper and amine copper treated wood and vanillin (as a lignin model) suggest the copper complexes formed are either axial elongated octahedral or square based pyramidal, in which wood functional groups are complexed with the copper center axially (Xie et al. 1995; Ruddick et al. 2001).  Scheme 1.1 MeaH is monoethanolamine  Even though the retentions of alkaline copper based preservatives remained similar to those used for CCA, the higher copper content in the formulations (often more than 60% compared to the 18 % on an oxide basis for CCA), caused an increase in the soluble copper component in the wood. This is particularly evident at the higher retentions required for industrial products in high decay hazard end uses. Studies conducted by Lee and Cooper (2010a) show that the cation exchange capacity (CEC) of wood is 0.6% w/w Cu per gram of wood at pH 7, and the value doubles to 1.3% at pH 11. However the actual preservative retentions in treated wood are much higher. The question whether the CEC of wood can stabilize all of the copper 19  without posing a higher biological hazard has been a matter of debate (Staccioli et al. 2000). Research conducted has shown elevated levels of mobile metal in alkaline copper treated wood as opposed to CCA (Lucas and Ruddick 2002; Jiang and Ruddick 2004; Ung and Cooper 2005). This finding also coincides with the enhanced potential for corrosion observed in alkaline copper treated wood (Choi and Ruddick 2007).  Recently, new formulations using micronized particulate copper as the active ingredient have been introduced in the USA (Leach and Zhang 2006; Zhang and Zhang 2009). ‘Micronized’ basic copper carbonate [CuCO3·Cu(OH)2] (BCC) particles are produced by mechanical grinding with the aid of dispersing/wetting agents resulting in 90% or more of the particles being less than 1000 nm size. In contrast to the soluble copper used in alkaline copper preservatives, BCC has extremely low solubility (Ksp=10-33.78 for malachite) at neutral pH (Astilleros et al. 1998). Copper particles are being dispersed in an aqueous solution in combination with the same co-biocides used in ACQ and CA. These new preservatives, which are known as micronized copper quat (MCQ) and micronized copper azole (MCA), provide an alternative to the alkaline copper preservatives that had been the principal preservative used for residential products in the USA and remain the case currently in Canada. Reported advantages of the micronized formulations include lower leachability and less corrosion to metal fasteners compared to wood treatment with alkaline copper (Freeman and Mcintyre 2008). However some studies have also suggested a weakness of micronized preservative against soft rot fungi (Larkin et al. 2008; Zhang and Ziobro 2009).   It has been long recognized that copper preservatives assert their fungicidal action through free cupric ions in a biological system (McCallan 1949; Montag et al. 2006). Therefore, 20  the availability of soluble copper ions is essential for these preservatives to provide an effective treatment. Such a requirement has not been a central concern for conventional water-based preservative formulations because the copper complexes employed are all in a soluble form. Moreover, soluble cupric ions are able to migrate and re-deposit onto untreated surfaces from a thin shell of treated wood (Choi et al. 2004; Morris et al. 2004), overcoming the potential threat of internal decay due to fungal spore germination in the untreated check surfaces. However, the limited intrinsic solubility of the newly developed micronized copper formulations has sparked greater interest regarding whether they are able to produce soluble copper, and what the effective level of fixed copper is required for fungi resistance. Cupric ions have been detected in laboratory leaching of MCQ treated wood (Zhang and Ziobro 2009). A field exposure test conducted by Stirling and Morris (2010) has also shown small but significant amounts of copper leached from MCQ treated wood. The level of leached metal ions was low but steady rather than the flush-and-decline pattern observed in ACQ treated wood. Nevertheless, maximising the potential efficacy of micronized copper preservatives will not be achieved until the mechanism responsible for the delivery of particulate copper into wood cell walls is fully elucidated. 1.3 Electron Paramagnetic Resonance (EPR) Spectroscopy Copper complexes found in treated wood are susceptible to chemical manipulation, and at the same time surrounded by matrices that are active to common spectroscopic methods such as nuclear magnetic resonance (NMR) and infrared (IR). Any attempt to extract and separate the different Cu species in treated wood for quantitative or structural characterization is likely to alter the complexes from their original states. Therefore, non-destructive techniques that are highly selective toward the target analytes are preferred in probing different copper species in 21  preservative treated wood. Energy dispersive X-ray (EDX) spectroscopy, scanning electron microscopy (SEM) and X-ray fluorescence (XRF) have been frequently applied in the surface characterization of copper distribution and quantification of total copper loadings (Matsunaga et al. 2004; Zahora 2010; Ahn et al. 2010; Zahora 2011; Pankras et al. 2012). Unfortunately such analysis can neither distinguish the different copper species deposited in preservative treated wood, nor can they characterize the bonding or geometry of the newly formed copper complexes on a molecular level. However the ability to probe these properties are essential in understanding the efficacy and the underlying mode of action of micronized copper preservatives, as well as the treatment response to environmental effects such as soil contact and fungal colonization. The research undertaken for this thesis relies extensively on the application of electron paramagnetic resonance (EPR) spectroscopy on copper treated wood and model complexes to characterize, quantify and differentiate the concentration and speciation of various copper complexes in micronized copper preservative treated wood. EPR spectroscopy is a spectroscopic technique that detects species that have unpaired electrons. Many of the basic principles of EPR are analogous to those of NMR, but it is transitions between electron spins states that are induced instead of the nuclear spin states. Most stable molecules do not have unpaired electrons, which limit the application of EPR but also offer a great advantage in specificity, since ordinary solvents and matrices are invisible by EPR spectroscopy. Similar to NMR, EPR has the ability to identify the molecular structure near the paramagnetic center, and can provide much more information based on the interpretation of spectral parameters. 22  1.3.1 The Zeeman Effect An isolated unpaired electron has a magnetic moment () and behaves like a bar magnet in the presence of an external magnetic field (B0). The interaction allows the magnetic moment only two possible orientations, either parallel to the magnetic field in a lower energy state, or antiparallel to the field in a higher energy state. This is called the Zeeman effect (Figure 1.13). An electron has a spin 𝑠 =12, therefore the magnetic spin quantum number of the parallel state is designated 𝑚𝑠 = −12 and the antiparallel state is 𝑚𝑠 = +12. Each state has a specific energy (Equation 1.1):      𝑬 = 𝒎𝒔𝒈𝒆𝝁𝑩𝑩𝟎      Equation 1.1 where ge is the proportionality factor of the free electron and B is the Bohr magneton. Therefore, the energy difference between the two spin states is given by Equation 1.2:    ∆𝑬 = ∆𝒎𝒔𝒈𝒆𝝁𝑩𝑩𝟎 = 𝒈𝒆𝝁𝑩𝑩𝟎    Equation 1.2 where the change in spin state is ∆𝑚𝑠 = ±1. There is no energy difference without the presence of the external magnetic field, and the magnitude of the energy difference between the spin states has a linear dependence on the strength of the magnetic field. Transition between the states can only happen by absorbing or emitting a photon of appropriate frequency, and the energy associated with the radiation is therefore:    𝒉𝒗 =  𝒈𝒆𝝁𝑩𝑩𝟎      Equation 1.3  23   Figure 1.13 The energy of an unpaired electron diverges into two spin states in the presence of an external magnetic field Because the mass of an electron is much lighter than a nucleus, the magnetic moment of the electron is also significantly greater than that of a nucleus. Therefore, the incident photon required to bring about an electron spin state transition in EPR is in the microwave frequency range rather than the radio frequency range as in NMR spectroscopy. The transition can be achieved by either varying the electromagnetic frequency or the magnetic field strength based on Equation 1.3. However most EPR spectrometers operate at a fixed frequency while the magnetic field is scanned because of technical difficulties in scanning microwave frequencies. Under these conditions, a paramagnetic sample is exposed to microwaves of a fixed frequency, and the external magnetic field is increased until the widening energy gap between the transition states 24  matches the energy of the incident radiation. The magnetic field at which the transition occurs is called the field of resonance, where the unpaired electron can move between the two spin states. Spin state transitions can happen by either absorbing or emitting a photon of appropriate frequency. However the population in the lower energy spin state is normally higher according to the Maxwell-Boltzmann distribution, therefore a net input of energy is required and the absorption is translated into a spectrum as shown on the top of Figure 1.14. In practice, phase sensitive detection which converts an absorption signal to its first derivative (dispersion spectrum) is applied in EPR spectrometers in order to increase the resolution.  Figure 1.14 Comparison of an absorption spectrum and its dispersion spectrum 25  1.3.2 g-factor An isolated electron in vacuum has 𝑔𝑒 = 2.0023 (Odom et al. 2006). In theory there can be countless pairs of υ and B0 that satisfy this correlation expressed in Equation 1.4.  A list of microwave frequencies and their matching fields of resonance for 𝑔𝑒 = 2.0023 commonly available in commercial EPR spectrometers is shown in Table 1.2. Neither the frequency nor the field of resonance can be seen as a unique fingerprint feature for the identification of a compound. However an unpaired electron is susceptible to the influence of the local magnetic environment as well as the applied magnetic field B0. The angular momentum of the unpaired electron is changed as a result, which in turn alters the field of resonance. The effective field of resonance Beff is expressed as:    𝑩𝐞𝐟𝐟 = 𝑩𝟎(𝟏 − 𝝈)      Equation 1.4 where σ can be positive or negative. Therefore, Equation 1.4 can be rewritten to include the influence of the local field as:    𝒉𝒗 =  𝒈𝒆𝝁𝑩𝑩𝟎(𝟏 − 𝝈)     Equation 1.5 The g-factor of the electron,  𝑔𝑒(1 − 𝜎),  is different from ge as a result and simply denoted g. Equation 1.5 is rearranged to:    𝒈 = 𝒉𝒗/𝝁𝑩𝑩𝟎      Equation 1.6 The g-factor is a constant of proportionality that is independent of the microwave frequency. The magnitudes of deviation from ge are indications of certain interactions of the 26  unpaired electron with certain electronic environment of the molecule. Therefore, the g-factor is used as the unique fingerprint feature for characterizing and identifying types of samples. Table 1.2 Field of resonance at 𝒈 = 𝟐. Spectrometers are classified based on microwave frequency ranges which are labeled with specific letters Microwave band Microwave frequency (GHz) B0 (gauss) L 1 390 S 3 1070 X 9 3380 K 24 8560 Q 35 12480 W 94 33600   An unpaired electron is not only influenced by the nucleus of the atom that it is located within, but also the electrostatic field of other atoms in the molecule.  Therefore, the orientation of the molecule with respect to the applied magnetic field is another influence on the electron-Zeeman interaction. In fact the g-factor is not a number but a tensor represented by a 3 × 3 matrix and is thus anisotropic. For a large ensemble of randomly oriented spins, such as in powder samples, a three dimension Cartesian coordinate system in the local field would reduce the number of components from nine to three, which will be represented by three peaks in an EPR spectrum (Figure 1.15). 27   Figure 1.15 Simulated spectrum of a rhombic molecule with anisotropic g values 1.3.3 Hyperfine coupling Hyperfine coupling is the interaction of an unpaired electron with neighboring nuclei. It is an essential factor in the application of EPR. A nucleus with non-zero magnetic moment can produce a local magnetic field that influences the magnetic moment of a nearby unpaired electron (Figure 1.16). The result is a micro-scale Zeeman effect on the local environment which creates sub energy levels in each electronic spin state where additional transitions can happen. Consequently a single spectral line is split into multiple lines called hyperfine splitting, and the spacing between spectral lines is the hyperfine coupling constant (A). The number of hyperfine splitting lines and the magnitude of the hyperfine coupling constant give abundant information such as the number and the identity of the nuclei in a molecule, as well as spin density at the 28  paramagnetic center. Same as the g-factor, the hyperfine coupling constant is a tensor and therefore may be anisotropic.  Figure 1.16 Influence of the magnetic field of a nucleus on the field experienced by an electron spin Predicting the splitting patterns due to hyperfine coupling is similar to that of NMR. For an unpaired electron interacting with M symmetry-equivalent nuclei that each has a nuclear spin of I (𝐼 ≠ 0), the number of spectral lines expected is 2𝑀𝐼 + 1. For an unpaired electron interacting with n sets of equivalent nuclei that each have their own nuclear spin, the number of spectral lines expected is (2𝑀1𝐼1 + 1)(2𝑀2𝐼2 + 1)… (2𝑀𝑛𝐼𝑛 + 1). For example, the spectrum shown in Figure 1.17 is the methoxymethyl radical, H2C(OCH3), which has (2 × 2 ×12+1) (2 × 3 ×12+ 1) = 12 spectral lines. Each set of equivalent nuclei also has a different hyperfine coupling constant associated. 29   Figure 1.17 Simulated spectrum of methoxymethyl radical 1.3.4 EPR of copper(II) complexes Copper(II) is a common d9 system which has been widely studied using EPR (Peisach and Blumberg 1974; Nagy et al. 1989; Ruddick et al. 2001; Humar et al. 2002; Hoffmann et al. 2008). Interaction of the unpaired electron with the Cu(II) nuclei (𝐼 = 3/2) gives rise to four splitting patterns in the gz  region of the spectrum, each is equally separated by the hyperfine coupling constant Az. As a non-destructive spectroscopic technique, EPR has been frequently applied to in-situ monitoring of copper-based wood preservative reactions present in wood (Yamamoto and Ruddick 1992; Hughes et al. 1994; Zhang and Kamdem 2000; Humar et al. 2002; Hoffmann et al. 2008; Ratajczak et al. 2008). 30   Peisach and Blumberg (1974) analyzed a series of natural and artificial Cu proteins for the relation of their chemical structures to the EPR parameters. It was concluded that the general trend for the changes of gz and Az indicates that the gz value becomes smaller and the Az increases as the number of nitrogen atoms bonded to the Cu increase. The relationship of gz and Az in different Cu compounds bound to oxygen and/or nitrogen is summarized in Figure 1.18 (Peisach and Blumberg 1974; Ruddick 1992). EPR analysis on the reaction product between vanillin, a lignin model compound with monoethanolamine (MeaH) containing CuSO4 solution (Ruddick et al. 2001) shows a spectrum of 𝑔𝑧 = 2.33 and 𝐴𝑧 = 148 𝐺, which suggests that the Cu is complexed to one nitrogen atom according to Peisach and Blumberg's (1974) finding. The structure of the complex was verified by single crystal X-ray crystallography (Ruddick et al. 2001). Studies conducted by Zhang and Kamdem (2000), Hughes et al. (1994), as well as Humar et al. (2002) on wood impregnated by MeaH containing Cu treatment solutions were found to have gz values of 2.258-2.271, and Az values of 159-170 G. These results agreed with a Cu-wood complex of the type CuN2O2. In nitrogen free formulations, such as CuSO4 and Cu(NO3)2 solutions, the Cu-wood complexes formed appeared to be in a distorted octahedral environment with the Cu metal centre bonding to four oxygen atoms (Hughes et al. 1994; Humar et al. 2002; Hoffmann et al. 2008; Ratajczak et al. 2008). These complexes were found to have gz values of 2.365-2.413, and Az values of 125-133 G, which again agreed well with the relation suggested in Figure 1.18. 31   Figure 1.18 The relationship between the EPR spectral parameters gz (■) and Az (○) for a series of Cu(II) compounds (based on data reported in Peisach and Blumberg 1974; Ruddick 1992; Ruddick et al. 2001) 1.4 Thesis overview The limited intrinsic solubility of the newly developed micronized copper formulations compared to the conventional soluble copper treatments has sparked great interest regarding whether they are able to produce soluble copper, and the underlying mechanisms for their apparent preservative performance. The thesis aims to improve understanding in these matters by looking into the speciation of copper in the micronized treated wood using EPR in combination 32  with XRF. Chapters 2 and 3 discuss the identification, characterization and quantification of the solubilized and chemically fixed copper species in the micronized copper treated wood, as well as the potential mechanisms involved in the treatment reaction. The distributions of the different Cu species in the treated earlywood and latewood are described in Chapter 4. The study focuses on understanding the effect of monoethanolamine additive and soil exposure on the Cu species formed in the treated wood in Chapters 5 and 6 respectively. In Chapter 7, efforts are made to identify the formation of copper complex with resin acids in the heartwood, and the effects of the resin acids and fungal colonization on the copper species in the treated wood are discussed. 33  Chapter 2: Investigation of copper solubilization and reaction in micronized copper treated wood 2.1 Introduction The study compares the chemistry of BCC formulations with that of soluble Cu salts such as CuSO4, as well as an alkaline copper quaternary ammonium preservative formulation (ACQ-D). EPR was employed to examine the copper reactions in wood. The spectroscopic technique probes the paramagnetic Cu(II) species generated in the treatment reactions and provides detail on the molecular structure of the complexes formed. The aim of this study was: a) to confirm whether the BCC is solubilized and able to react with the wood components; b) to determine how fast (rapid or slow) the reaction occurred under laboratory conditions using sawdust with an indication of its time scale; and c) to compare the Cu species formed by reaction of soluble hydrated Cu (II) with wood.  2.2 Material and methods 2.2.1 In-lab sawdust treatment method Southern pine (Pinus sp.) sapwood (2 g) sawdust, approximately 30-40 mesh was added to treatment solutions (50 mL) and stirred for 10 min at room temperature. The resultant slurry was suction filtered without washing. To determine the effect of leaching, selected samples (1.5g) were stirred in deionized water (100 mL, pH 6.7) for 48 h to remove any soluble Cu complexes before being filtered. The conditions of sawdust treatment and the type of drying (if any) are shown in Table 2.1, together with the EPR schedule.  34  Table 2.1 Treatment, drying method and EPR schedule for southern pine sawdust Treatment Treatment conc. (% w/v Cu) Drying EPR schedule CuSO4 Set 1 0.03-0.51 Vacuum desiccator 2 h, 24h and 2 months leaching 24 h and 2 months Set 2 0.003-0.102 Kept wet in sealed containers 2 weeks      BCC Set 1 0.58 30 °C oven dry 2 h, 24 h and 2 months leaching 50 °C oven dry 24 h and 2 months Set 2 0.025-0.127 Kept wet in sealed containers Daily for 6 days     De-ionized water - 30 °C oven dry 2 h  2.2.2 Sawdust from industrial treated wood ACQ, MCQ or MCA treated lumber and fence posts, produced either commercially or in a full size pilot plant, were also studied. The samples were prepared from preservative treated red pine (Pinus resinosa) with dimensions of 89×89 mm (nominal “4×4”). The surface layers were removed in 1 mm increments by means of computer controlled router and the sawdust was collected. It was carefully reduced to 40 mesh. 2.2.3 EPR data acquisition and process Data were collected on an Elexsys E500 series continuous wave EPR spectrometer (Bruker, Billerica, MA, USA). The spectrometer was operated at a frequency of 9.40 GHZ (X-band) at 77K, 50 KHz field modulation, 3 G modulation amplitude, and 0.64 mW microwave power. Frequency calibration (Krzystek et al. 1997) was independently verified using 2,2-diphenyl-1-picrylhydrazyl (DPPH, 𝑔 = 2.0036) (Sigma Aldrich, St Louis, MO, USA) as an external 35  standard. Each spectrum recorded was the average result over 5 scans. Spectra recorded were simulated using SimFonia (Bruker, Billerica, MA, USA). OriginPro 8.5 (OriginLab, Northampton, MA, USA) was used to calculate spectral intensities. Three replicate EPR samples for each wet specimen (set 2, Table 2.1) were packed over 100 mm (sample height) in the EPR tubes (5 mm OD, Wilmad Labglass, Vineland, NJ, USA) so that it exceeded the vertical length of the cavity in order to maximize the EPR spectra and minimize variation caused by the amount of sample.  2.3 Results and discussion 2.3.1 In-lab CuSO4 solution treated sawdust The g-factor and hyperfine coupling constant (A) are key parameters in EPR studies for characterizing the structure of the complex in question. The anisotropy of the electronic structure surrounding the paramagnetic center gives rise to different g-factors and hyperfine coupling constants depending on the orientations of the unpaired electron in the external magnetic field. Studies on various copper complexes (Peisach and Blumberg 1974; Xie et al. 1995; Hoffmann et al. 2008; Ratajczak et al. 2008) have shown that gz and Az where the unpaired electron spin is parallel to the external magnetic field, are most sensitive to structural changes. Simulated EPR parameters had been previously reported for CuSO4 treated wood recorded at room temperature with 𝑔𝑧 = 2.365 and 𝐴𝑧 = 133 𝐺 (147 × 10−4𝑐𝑚−1, Hoffmann et al. 2008). Our simulated spectral parameters are  𝑔𝑧 = 2.383 and 𝐴𝑧 = 130 𝐺 for southern pine sawdust treated with 0.025% (m/v on Cu basis) CuSO4 solution (Table 2.2 and Figure 2.1). In terms of the potential for sequential reactions, it is important to note that the EPR spectra of the samples taken 24 h after the initial treatment (day 1) were very similar to those ones taken after 2 months of storage 36  (Table 2.3 and Figure 2.2).  Leached samples did not show any significant changes in the spectral parameters either. The consistency of EPR parameters with time and leaching indicates that the rapid ion exchange reaction between soluble Cu and wood produces stable complexes. Table 2.2 Simulated EPR parameters for CuSO4 treated sawdust (set 1) at various Cu concentrations, recorded 2 months after the treatment Treatment concentration (% m/v Cu) g-factors Hyperfine coupling constant (G) gz gy gx Az Ay Ax 0.51 2.395 2.095 2.084 130 36 4 0.25 2.395 2.098 2.079 130 30 4 0.13 2.389 2.094 2.078 130 30 4 0.05 2.382 2.092 2.076 130 30 4 0.03 2.383 2.088 2.076 130 30 4  37   Figure 2.1 EPR spectra of CuSO4·5H2O solid in boron nitride (BN), and sawdust treated with CuSO4 solutions at various concentrations (set 1). The sawdust samples were unleached (UL) and spectra recorded 2 months after the initial treatment 38   Figure 2.2 EPR spectra sawdust treated with 0.051% CuSO4 (set 1), unleached (UL) and leached (L). Samples measured over a period of 24 h (day 1) to 2 months Table 2.3 Simulated EPR parameters for CuSO4 (0.051% m/m on Cu basis) treated wood (set 1), recorded before and after leaching over a period of 2 months Sample g-factors Hyperfine coupling constant (G) gz gy gx Az Ay Ax Unleached day 1 2.405 2.089 2.081 130 24 4 Unleached, 2 months 2.382 2.092 2.076 130 30 4 Leached, day 1 2.405 2.084 2.080 130 24 4 Leached, 2 months 2.382 2.082 2.078 130 30 4  39   The study conducted by Hoffmann et al. (2008) also noted that at concentrations higher than 0.1% (m/v on Cu basis), the EPR spectrum is dominated by the signal from precipitated CuSO4·5H2O salt. Our results agree with this finding that at treatment concentrations of 0.13% and above some CuSO4 is precipitated and this can be observed in the spectra for these two treatments in Figure 2.1.  The feature from the precipitated CuSO4 salt limits the accuracy of the simulated spectral parameters for these three treatments. The carboxylic acid functional group in hemicellulose and pectin, and the phenolic moiety in the guaiacyl units of the softwood lignin are the major sources of exchangeable protons in sapwood. The acidity of these functionalities is crucial to the extent of the cation exchange reaction. The hemicellulosic carboxylic acid protons are more acidic with a pKa value of around 4 to 5 while the lignin phenolic protons have pKa values of around 7 to 10. A titration curve established by Lee and Cooper (2010a) on the CEC of wood shows that at a pH of 7, the maximum CEC of red pine sapwood sawdust is 0.09 mmol·g-1 for Na+, which corresponds to the carboxylic acid content of 0.09 mmol·g-1 for wood reported by (Kamdem and Zhang 2000). The same study also showed that the chemisorption of Cu2+ from CuSO4 solutions followed the same trend as that of Na+ up to pH 5, which corresponds to the binding of Cu2+ with carboxylic groups in hemicellulose and pectin, as confirmed by the FTIR study. In our study, only a limited amount of Cu-wood complex is formed due to the limited availability of carboxylic functional groups, and thus leaving the rest of Cu as precipitated CuSO4 salt.   In order to observe the influence of CuSO4 treatment concentration on the extent of cation exchange in wood, another batch of samples (set 2) treated by a series of CuSO4 solutions with concentrations lower than 0.1% was studied (Figure 2.3). The EPR samples were loaded 40  without drying immediately after the initial treatment. Despite variations due to the packing densities of the samples, the signal intensities of the spectra increase logarithmically with increasing treatment solution concentration. Eventually the increase in signal intensity is reduced as the amount of absorbed Cu begins to approach the optimum CEC, because the maximum amount of chemically fixed Cu is limited by the total number of exchangeable protons in wood.  Figure 2.3 EPR signal intensity of sawdust treated with CuSO4 versus treatment concentration (sample set 2) 2.3.2 In-lab BCC treated sawdust  The reaction between wood and a BCC suspension in water was examined in this study. The EPR spectra of solid BCC, micronized copper suspension in water and deionized water treated 41  southern pine sawdust are depicted in Figure 2.4. None have any features of significance. The pattern shown for the water treated sawdust control is due to intrinsically contained Mn(II) in the sawdust, whereas BCC is antiferromagnetic in its solid state (Janod et al. 2000) and hence EPR silent (the small multiplet signal at 3350 G is due to an impurity in BN). From the spectrum recorded within 2 h after the initial treatment, it is clear that the suspension of BCC reacts quickly with wood. The simulated spectral parameters (Table 2.4) indicate the complexes formed are similar to those of CuSO4 solution treated samples (Table 2.2), since they have similar gz and identical Az values. Furthermore, the 48h static leaching test confirms that the rapid reaction between wood and BCC suspension produces stable Cu complexes that are bound to the wood components. 42   Figure 2.4 EPR spectra of solid BCC in BN, micronized copper suspension containing 1% Cu, de-ionized water treated southern pine sawdust and 0.58% BCC suspension treated sawdust. Spectra were recorded 2 h after the initial sawdust treatment Table 2.4 Simulated EPR parameters for sawdust treated with BCC suspension (0.53% m/m on Cu basis), recorded before and after leaching over a period of 2 months Sample g-factors Hyperfine coupling constant (G) gz gy gx Az Ay Ax Unleached day 1 2.399 2.081 2.081 130 30 5 Unleached, 2 months 2.375 2.078 2.074 130 30 5 Leached, day 1 2.375 2.076 2.076 130 30 5 Leached, 2 months 2.379 2.078 2.076 130 33 5  43   To study a possible time dependence on the Cu complexes formed in the BCC treated sawdust, additional EPR samples (set 2) treated with BCC suspensions at different concentrations were loaded without drying immediately after the initial treatment, and monitored repeatedly over 6 days. The signal intensities for all three samples increased continuously for the first 3 days, after which the signal intensity did not change (Figure 2.5). The samples treated with a higher concentration of BCC produced a much larger initial signal intensity due to increased reaction rate. However, as time passed, the difference in the optimum signals after 6 days was much less. This is likely because the amount of soluble Cu produced and complexed with the wood is dependent on the protons available to solubilize the Cu, rather than the amount of BCC. In other words, the extent of cation exchange is determined by the total amount of exchangeable protons available in wood. Therefore, the advantage of having higher BCC concentration is diminished with time as more and more carboxylic acid sites are complexed to reacted Cu. 44   Figure 2.5 Changes in EPR signal intensities of BCC suspension treated sawdust (set 2) with time. Spectra at day 0 were recorded within 2 h after initial treatment 2.3.3 Industrial ACQ, MCQ and MCA treated samples In the third part of the study, the simulated EPR spectral parameters of commercial ACQ, MCQ and MCA treated red pine were compared with those samples treated with BCC suspensions (Table 2.5 and Figure 2.6). The simulations carried out by SimFonia are not fitted curves to the experimental data; therefore the exact statistical inference cannot be determined. The estimated confidence interval for the g-value is ±0.01 and A is ±4 gauss, based on data collected in the thesis. Cu-wood complexes formed in commercial micronized copper treated red pine are very similar to those of southern pine sawdust treated by CuSO4 and BCC in-lab. The simulated data based on the experimental spectrum of commercial ACQ treated red pine are in very good 45  agreement with results generated previously for ammoniacal copper carbonate treated wood, to which with gz values of 2.26 to 2.28 and Az values of 160 to 169 G (169 to 179 × 10−4𝑐𝑚−1, Ruddick 1992; Zhang and Kamdem 2000; Humar et al. 2002). The general trend for the spectral changes indicates that the gz value becomes smaller and the Az becomes bigger as the number of nitrogen atoms bonded to the Cu increases (Peisach and Blumberg 1974; Ruddick 1992). The most stable amine-copper-wood complex is believed to contain only one Cu-N bond (Ruddick et al. 2001; Lucas and Ruddick 2002; Lee and Cooper 2010a) so an Az value of 140 to 150 G would be expected. The higher Az value of 169 G with the gz value of 2.27 found in this study is more consistent with a Cu complex with two Cu-N bonds. Under a more rigorous hydrolysis one of the amine molecules bound to the Cu may be replaced resulting in a lowering of the Az value. It may be concluded that different complexes are formed in ACQ treated wood and would produce very different EPR spectra from those micronized copper treated samples where the bonding is solely Cu to oxygen. Table 2.5 Simulated EPR parameters for commercial ACQ, MCQ and MCA treated red pine samples before and after leaching Treatment g-factors Hyperfine coupling constant (G) gz gy gx Az Ay Ax ACQ, unleached 2.270 2.095 2.064 169 42 6 ACQ, leached 2.268 2.094 2.064 169 42 6 MCQ, unleached 2.363 2.069 2.067 130 30 5 MCQ, leached 2.367 2.071 2.071 130 30 5 MCA, unleached 2.363 2.069 2.067 130 30 5 MCA, leached 2.367 2.072 2.372 132 30 5  46   Figure 2.6 EPR spectra of commercial ACQ, MCQ and MCA treated red pine samples, as well as southern pine sawdust treated with BCC and CuSO4 in-lab. All samples were unleached  Our results for MCQ and MCA treated red pine confirmed that BCC contained in the formulations reacts with wood to produce soluble Cu, which in turn fixed with wood components by forming octahedral complexes. The complexes formed are stable to 48 h static leaching. Their EPR spectra are identical to those resulted from CuSO4 solution and BCC suspension treated sawdust samples. The spectra for MCQ, MCA, BCC and CuSO4 treated sawdust all had larger gz values and smaller Az values than the spectrum for the ACQ treated sample, consistent with complexes containing only Cu-oxygen bonding. 47  2.4 Conclusions This study shows that CuSO4 solution reacts with wood components to produce axially elongated octahedral complexes that have only oxygen atoms bonded to the Cu centre. Sawdust treatment with aqueous suspension of BCC yields similar Cu species. It is suggested that the Cu solubilized by the reaction of the carboxylic acid groups in the sapwood with BCC to form stable Cu-wood complexes which resist leaching. The fixed complexes formed as a result have a similar geometry to the Cu-wood complexes found in the CuSO4 treated samples. The study also indicates that soluble copper species, which can be identified by EPR, is produced rapidly within 2 h of the initial treatment. The EPR spectra confirmed that these complexes are very different from those formed in the alkaline copper preservative treated samples, which contain Cu centres that have both Cu-N and Cu-O bonds.  48  Chapter 3: Quantification of reacted Cu(II) in micronized copper treated wood 3.1 Introduction The experiments described in Chapter 2 have shown that when wood is treated with an aqueous suspension of BCC, soluble hydrated copper species are produced, which rapidly react with wood components resulting in Cu-wood complexes. The results are consistent with the findings that cupric ions had been detected during laboratory leaching of MCQ treated wood (Zhang and Ziobro 2009; Stirling and Morris 2010). However, the amount of the solubilized and chemically fixed Cu(II) in micronized copper treated wood has not previously been established because of the difficulty in differentiating the reacted Cu(II) from the total Cu present after treatment.  BCC deposited in the treated wood contains both unreacted solid particles, and Cu(II) species that has been solubilized and/or subsequently bound to the wood substrate (here defined as reacted Cu). Routine elemental analysis techniques, such as X-ray fluorescence analysis (XRF), cannot distinguish between the two types of Cu. However, while BCC is an antiferromagnetic material (Janod et al. 2000), the Cu-wood complexes formed in the wood after treatment contain paramagnetic cupric ions (Hughes et al. 1994; Xie et al. 1995). The differing magnetic behavior of the two Cu species enables the determination of the reacted cupric ions by means of EPR. The spectroscopic characteristics of the cupric species in sapwood treated with micronized copper and CuSO4 are identical. This allows the EPR data to be calibrated by XRF data of the CuSO4 treated sapwood. 49   In this chapter, a novel method will be presented for quantifying the reacted Cu levels in the micronized copper treated wood. The hypothetical direct correlation between EPR and XRF signal intensities, as indicated above, will first be confirmed. Then the calibration curve will be used for the analysis of Cu species in the wood treated with micronized BCC. The results presented focus on the inter-relations of the reacted Cu concentrations with time after treatment, preservative formulation, and solution concentration. The results of these laboratory experiments will be compared with those of commercially produced fence posts and dimensional lumber. 3.2 Material and methods 3.2.1 Sawdust treatment with CuSO4 solutions CuSO4 solutions containing between 0.0005 and 0.10% Cu (m/m) were made up in 100 mL aliquots. Oven dried southern pine (Pinus sp.) sapwood sawdust (4.00 g), ground to approximately 30-40 mesh was stirred in the treating solution for 10 min at room temperature. The product was filtered under suction and immediately stored in a sealed Petri dish to prevent drying. After 1 week, the sawdust was oven dried at 50 °C to constant weight. 3.2.2 Sawdust treatment with micronized copper suspensions Oven dried southern pine sapwood sawdust (8.00 g, 30-40 mesh) was treated with aqueous suspensions (200 mL) of micronized copper either without co-biocide (MC), or with one of two co-biocides MCA and MCQ, for 10 min at room temperature. The treatment solutions were prepared by diluting the respective commercially provided suspensions of MC, MCA (Cu/azole=1:0.04) and MCQ (Cu/quat=1:0.625) with deionized and distilled water (pH 6.7). The product was filtered under suction. Three replicate EPR samples for each wet specimen were immediately packed into EPR tubes (5 mm OD, Wilmad Labglass, Vineland, NJ, USA), sealed 50  and continuously monitored daily for a week. The sample heights in all of these tubes were packed over 100 mm so that they exceeded the vertical length of the EPR cavity to minimize the intensity variation. The rest of the product was placed in a sealed Petri dish.   A small portion of each sample was taken out from the sealed Petri dish each day and dried at 90oC for at least 4 h before its EPR spectrum was recorded on the same day. Three replicate EPR samples were prepared for each dried specimen, and sample heights in the EPR tubes were controlled within 40 mm so that they did not exceed the vertical length of the EPR cavity. Sawdust was recovered from each tube following the EPR measurement and the mass was recorded. The remaining sawdust was dried after 7 days and examined by XRF analysis.  Because of the unusual behavior observed between the MCQ treatment concentration and the reacted Cu levels, an additional series of treatments was done using solutions containing a constant 0.05% (m/m on Cu basis) MC suspension with increasing quat concentrations. The quat content in the treated sawdust was analyzed by ultrasonic extraction of the sawdust with acetonitrile followed by HPLC analysis (the instrument was equipped with an evaporative light scattering detector) (Daniels 1992). 3.2.3 Examination of commercial material Sections of commercially treated red pine (Pinus resinosa) “4×4” fence posts (85×85 mm) and lodgepole pine (Pinus contorta) dimensional “2×6” lumber (38×136 mm) were provided by the Osmose (Griffin, GA, USA). The sawdust samples were removed from the surface of the treated wood in 1 mm increments by means of an automated computer controlled router. The sawdust was oven dried and reground to 30 mesh, and then analyzed by XRF and EPR. Three replicate EPR samples were made for each commercial treated specimen. 51  3.2.4 XRF and EPR data acquisition and process Total copper retentions were determined by XRF (ASOMA, Ametek, Austin, TX, USA) (AWPA 2012a). EPR data were collected on an Elexsys E500 series continuous wave EPR spectrometer (Bruker, Billerica, MA, USA). The spectrometer was operated at a frequency of 9.40 GHZ (X-band) at 77K, 100 KHz field modulation, 1 G modulation amplitude, and 0.64 mW microwave power. Each spectrum recorded was the averaged result over 5 scans. All samples were analyzed under the same instrument settings. Frequency calibration (Krzystek et al. 1997) was independently verified using 2,2-diphenyl-1-picrylhydrazyl (DPPH, g = 2.0036) (Sigma Aldrich, St Louis, MO, USA) as an external standard. Spectra recorded were simulated using SimFonia (Bruker, Billerica, MA, USA). OriginPro 8.5 (OriginLab, Northampton, MA, USA) was used to perform baseline correction and calculate spectral intensities (AUC). The AUC values obtained for dried samples were normalized over the EPR sample mass. The normalized values are mass independent and less affected by the sample packing density. 3.3 Results and discussion 3.3.1 CuSO4 treated sawdust An excellent correlation between the copper contents determined by EPR and XRF was established (Figure 3.1) using sawdust treated with CuSO4 solutions with concentrations range of 0.0005-0.105% (m/m on Cu basis). There was no significant effect of treatment concentration on the type of copper complexes formed within the range of treatment concentrations observed, with all EPR spectra being very similar to each other. The spectra of the Cu(II) complexes exhibited gz values of 2.358-2.380 and Az tensors of ~132 G, which are typical of the Cu-wood complexes formed with only Cu-O bonding (Hoffmann et al. 2008). They are also similar to those of 52  commercial MCQ treated samples. The Cu contents of the samples determined by XRF were plotted against the corresponding EPR intensities and a linear correlation with a correlation coefficient (R2) of 0.98 was found (Equation 3.1). Because the Cu-wood complexes formed during the CuSO4 treatment contain similar Cu-ligand bonding to those of micronized copper treated wood, the linear correlation is applicable as a calibration standard to convert the EPR signal intensity of the reacted Cu levels in micronized copper treated wood into the mass of reacted Cu (Cu%).  %𝑪𝒖 = 𝟗. 𝟕 × 𝟏𝟎−𝟖 (𝑨𝑼𝑪𝒎𝒂𝒔𝒔) − 𝟎. 𝟎𝟏𝟒  𝑹𝟐 = 𝟎. 𝟗𝟖  Equation 3.1  Figure 3.1 Cu contents of CuSO4 treated sawdust determined by XRF against the corresponding EPR signal intensities 53  3.3.2 Sawdust treatment with micronized copper suspensions The treated sawdust with various micronized BCC suspensions was studied as a function of time after treatment. Although the initial experimental design in which the same sample was measured continuously over the experiment duration permitted the collection of data under optimal conditions, the difficulty of normalizing the EPR data with respect to sample mass for the wet sawdust (having varying moisture contents) prevented the quantification of the data. An additional problem was the possible sample drying during measurements. To improve the results, a small portion of each sample was oven dried at 50 °C for 5 h (to constant mass) and then examined again by EPR. The low drying temperature was used so as to prevent possible de-acetylation of the galactoglucomannan in hemicellulose, which occurs at >160 °C and releases acetic acid (Esteves et al. 2008; Esteves and Pereira 2009), and therefore may affect the formation of reacted Cu. However, considering most of the cation exchange reaction should happen between Cu and the carboxylic acid groups in hemicellulose and pectin, decomposition of the acetyl functional groups due to thermal treatment should have little impact on the reacted Cu concentration in wood. The spectral parameters showed very little change during the 7-day monitoring period. All samples, despite being treated by different preservative formulations, had similar gz values ranging between 2.368 and 2.355 and AZ tensors of ∼133 G. These values are close to those of CuSO4 treated samples. 3.3.2.1 MC treatment The average spectral intensities for the wet sawdust show that reacted Cu levels increased continuously up to 2-3 days after initial treatment (Figure 3.2a). The spectra for the dried samples show a similar trend. In some cases the amount of reacted Cu reduced slightly at the end 54  of the monitoring period (Figure 3.2b). The reacted Cu contents in the treated samples were quantified by comparing the EPR signal intensities against the calibration standard created by the CuSO4 treated wood. The signal intensities (AUC/mass) for reacted Cu were converted to mass of Cu in terms of Cu% by applying Equation 3.1. The reacted Cu concentrations for all samples at time ‘zero’, which was no later than 6 h after the initial treatment, are more than 50% of those at the end of the 7-day monitoring period. It is clear that the suspension of insoluble micronized basic copper carbonate is able to react rapidly with exchangeable protons near the sawdust particle surface to release solubilized monomeric cupric ions, which in turn complex with the wood components forming Cu-O-wood complexes.    From a comparison of the total Cu determined by XRF with the reacted Cu determined by the EPR (Table 3.1) it is clear that unreacted BCC remained in the samples, particularly at suspension concentrations above 0.05% Cu. Both EPR and XRF data confirmed that reacted Cu and total Cu increased consistently with increasing treatment concentrations. The EPR data shows that for treatment with MC at 0.05% or above, the maximum values of between 0.19 and 0.22% reacted Cu were observed at the end of the 7-day reaction period. The samples treated with a suspension of 0.20% MC have the highest Cure content of 0.22%, or 1.10 kg.m-3 or approximately 2300 ppm (Figure 3.2b) which is considerably more than predicted in the literature based on a bulk value for wood pH (Scaife 1957; Jin et al. 2010). 55  a)  b)  Figure 3.2 Changes in reacted Cu levels of MC treated southern pine as a function of time after treatment: a) wet samples; b) dry samples 56  Table 3.1 Total Cu content of southern pine sawdust treated by MC and MCA suspensions with increasing Cu concentration (% m/m on Cu basis). aStandard error estimated at ±0.02% Treatment conc. (% Cu) aTotal Cu (%) MC MCA 0.02 0.19 0.15 0.05 0.24 0.20 0.10 0.35 0.29 0.20 0.52 0.43   Lee and Cooper (2010a) studied the CEC of red pine with alkaline copper quat solutions and observed a pH dependent interaction of the amine copper species. The CEC increased with increasing pH. Two inflection points were identified at pH 3-5 and 7-11, which were ascribed to interactions of carboxylic acid groups in hemicellulose and pectin, and phenolic protons in lignin, respectively. Thus it is possible to estimate the likely maximum reacted Cu concentration to be produced in MC treated sapwood, because only the acidity of carboxylic acid groups allows Cu to solubilize from BCC under the experimental condition in this study. From the CEC data published by Lee and Cooper (2010a),  ~0.05 mmol Cu g-1 of sapwood will be produced at pH 4, which corresponds to approximately 0.32% Cu. The amount of reacted Cu determined is within this limit, and it is possible that a longer storage period under high humidity condition may further increase the reacted Cu level to the maximum CEC for the reaction pH, provided there is enough unreacted BCC available. 57  3.3.2.2 MCA treatment with fixed copper to azole ratio The EPR analysis on both wet and dried samples shows that the reacted Cu levels increased with increasing MCA treatment concentration (Figure 3.3) up to 3 to 4 days following treatment. The maximum reacted Cu of 0.23 % was achieved using a 0.20 % Cu suspension strength, which is similar to the level found in the MC treatment. The XRF analysis on the Cu content in the MCA treated sawdust shows that the total amount of Cu taken up by the sawdust increased with increasing treatment concentration (Table 3.1). The total Cu retained following treatment is slightly lower than the corresponding values for sawdust treated with simple MC treatment without any co-biocide. At the lowest MCA concentration of 0.02 % Cu, all of the Cu appeared to be reacted and this would limit the amount of reacted Cu produced in the wood. However, the total Cu content in wood determined by XRF at 0.05% suspension strength is 0.20 % Cu, which slightly exceeded the reacted Cu concentration (0.18 % Cu).    58  a)  b)  Figure 3.3 Changes in reacted Cu levels of MCA treated southern pine as a function of time after treatment: a) wet samples; b) dry samples 59  3.3.2.3 MCQ treatment with fixed Cu-to-quat ratio Sawdust was treated with 0.02 - 0.20% (on Cu basis) MCQ dispersions with fixed Cu-to-quat ratio (1:0.625 b.wt.). The average spectral intensities recorded for the wet samples show that the amount of reacted Cu increased for 72 h after the treatment but then reached a plateau (Figure 3.4a). However, the impact of increasing the treatment solution concentration for MCQ was quite different from that of MC or MCA. The sample that has the highest level of reacted Cu present was treated by 0.05% MCQ suspension despite it being the second lowest treatment strength. Further increase in treatment concentration led to lower reacted Cu levels. In fact, the lowest reacted Cu content detected was in the sample treated with the highest suspension concentration (0.20% Cu).  Similar to the wet samples, EPR signal intensities for dried samples increased continuously for the first 72 h before reaching a plateau or, in a few cases decreased slightly (Figure 3.4b). Another pattern similar to that of the wet samples is the decrease in reacted Cu concentration detected when the treatment strength exceeded 0.05 % Cu. A comparison with the XRF analysis (Table 3.2) shows that only a limited amount of BCC was able to produce monomeric Cu species and complex with wood. The maximum reacted Cu content of 0.17 % Cu is ~70% of the maximum 0.22 % Cu obtained with the MC treatment.  60  a)  b)  Figure 3.4 Changes in reacted Cu levels of MCQ treated southern pine as a function of time after treatment: a) wet samples; b) dry samples 61  Table 3.2 Total Cu (% m/m on Cu basis) content of southern pine sawdust treated by MCQ with increasing Cu concentration and MC with increasing quat concentration. aStandard error estimated at ±0.01% MCQ MC with varying quat Treatment conc. (% m/m) aTotal Cu (% ) Treatment conc. (% m/m) aTotal Cu (%) Cu quat Cu Quat 0.02 0.01 0.15 0.05 0.01 0.23 0.05 0.03 0.36 0.05 0.03 0.45 0.10 0.06 0.56 0.05 0.06 0.61 0.20 0.13 0.46 0.05 0.13 0.31 - - - 0.05 0 0.20   It is known that the quaternary amine co-biocide reacts with wood via cation exchange during its fixation. These observations may be interpreted as indicating the impact of competition between the BCC and the quat for the carboxylic acid protons. Such competition has been suggested previously (Tascioglu et al. 2005). If the quat is able to exchange with these protons, they may not be available to solubilize Cu from BCC.  As would then be expected, the highest treatment concentration produced the greatest interference and hence the lowest amount of reacted Cu. However, in all but the lowest MCQ suspension concentration, the amount of BCC was adequate to produce 0.20% reacted Cu. A second effect noted was the ability of the quat to enhance interaction of treatment solutions due to its surfactant nature. The total Cu uptake observed for MCQ by XRF was greater than that of either the MC or MCA suspensions at equivalent treatment strengths for suspension concentrations of 0.05-0.10 % Cu (Table 3.1). 62  3.3.2.4 MCQ treatment with varying Cu-to-quat ratio The decrease of reacted Cu content on increasing the MCQ treatment concentration above 0.05% is unexpected. Thus an additional study was carried out, in which the quat content was varied while maintaining the Cu concentration constant (0.05% Cu). The four quat concentration levels matched those of the previous MCQ treatments. Spectra for both the wet and dried sawdust show that reacted Cu levels reached a plateau after ~3 days (Figure 3.5). Both EPR and XRF data (Table 3.2) show that adding quat to the treatment solution initially facilitated physical adsorption of MCQ and solubilization of Cu until the quat concentration reached 0.06 % after which the values decreased. An examination of the reacted Cu content indicated that a small quat addition (0.01 % quat) enhanced the formation of reacted Cu from ~0.18 % in absence of quat to a value of ~0.20% Cu. Further increase in the quat concentration initially had little effect until it reached 0.125%, at this level the reacted Cu content reduced markedly from a maximum of 0.21% (at 0.03 and 0.06 % quat) to the lowest value of 0.16 % Cu. It seems that the Cu-to-quat ratio is an important factor in physical adsorption and solubilization of Cu during and after the treatment. This phenomenon is worthy of further investigation. 63  a)  b)  Figure 3.5 Changes in reacted Cu levels of MC with varying concentrations of quat treated southern pine as a function of time after treatment: a) wet samples; b) dry samples 64  3.3.3 Quantification of reacted Cu levels in commercial micronized Cu treated wood Sawdust samples were removed at 1 mm increments from the surfaces of red pine fence posts and a lodgepole pine. The resulting sawdust was analyzed for total Cu by XRF and reacted Cu by EPR. The quat content of the samples was also measured because of the competition between the quat co-biocide and the formation of reacted Cu as shown in the laboratory experiments. The total Cu retention at the surface is higher than that further from the surface typically. The average retention corresponds to > 9 kg m-3 Cu (or > 11.3 kg m-3 CuO) in red pine. This value is slightly higher than that usually observed in commercial materials, but the assay zone in this study was not the complete sapwood depth. The quat profiles are also similar to those found in the commercially treated wood, with a high surface loading and gradually diminishing values as a function of the distance from the wood surface. However, the reacted Cu profile is generally quite different and reflects the chemistry of the interaction between the wood and the BCC. The mechanism of Cu solubilization depends only on the availability of acid groups (carboxylic acid functionality). As the latter is independent of the distance from the wood surface, the amount of reacted Cu will also be independent of the depth of the measurements from the wood surface, provided that sufficient BCC has penetrated into the sample. It is clear from Figure 3.6-3.8 that the total Cu content always exceeded that of reacted Cu.  65  a)  b)  Figure 3.6 Reacted Cu, total Cu  and quat content  at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP25B). Relative orientations of faces sampled: a) S1; b) S3 (parallel to S1) 66  a)  b)  Figure 3.7 Reacted Cu, total Cu and quat content at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP29B). Relative orientations of faces sampled: a) S1; b) S2 67  a)  b)  Figure 3.8 Reacted Cu, total Cu and quat content at sampling locations 0-10 mm from the wood surface in commercially MCQ treated red pine (RP41B). Relative orientations of faces sampled: a) S1; b) S2   68   The corresponding data for MCA treated wood is shown in Figure 3.9-3.11 and reveal similar trends to those found in the MCQ treated wood. The total Cu content gradually diminishes with increasing distance from the wood surface whereas the reacted Cu seems to remain constant. The reacted Cu found in MCQ treated wood (average 0.12%) versus that found in MCA treated wood (average 0.14%) can be interpreted that a slightly greater degree of Cu solubilization occurred in the latter. This finding would support a small interference by the quat on the formation of reacted Cu. This relatively small effect is also consistent with the data from the laboratory study.    The occasional high amount of reacted Cu at the wood surface (e.g., RP25B face S1, RP41B face S1 and RP46A faces S1 and S2) compared with the values in deeper layers, as recorded in Figure 3.6a, 3.8a and 3.11, could be the result of surface oxidative effects. This and its possible relation with surface browning due to weathering are of interest for additional investigations. The magnitude of reacted Cu was greater in the laboratory studies than in the commercial materials and may be ascribed to the use of sawdust compared with full sized material. The possible ongoing reactions due to migration of the unreacted micronized Cu in treated wood will be further studied. 69  a)  b)  Figure 3.9 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP34A). Opposite faces sampled: a) S1; b) S3 70  a)  b)  Figure 3.10 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP36A). Adjacent faces sampled: a) S1; b) S2 71  a)  b)  Figure 3.11 Reacted Cu and total Cu at sampling locations 0-10 mm from the wood surface in commercially MCA treated red pine (RP46A). Adjacent faces sampled: a) S1; b) S2 72  3.4 Conclusions Within the range of concentrations studied, all cupric ions in CuSO4 solution treated wood are fully detectable by both EPR and XRF spectroscopy, and there is a linear relation between the Cu signal intensities detected by both methods. This calibration curve is suitable for quantifying reacted Cu in various micronized Cu treated sawdust. The rapid reaction between the sawdust and micronized copper was demonstrated by the fact that the reacted Cu concentrations for all samples at time ‘zero’ are more than 50% of the final levels. The levels of reacted Cu were found to increase for 2–3 days before reaching a maximum value of between 0.21% and 0.23% Cu. An impact of the quat co-biocide on Cu fixation with wood was observed in MCQ treatments, with increasing MCQ suspension concentration causing a reduction in the reacted Cu content. This effect arose probably from the competition for the reactive carboxylic acid protons in the wood between the BCC and the quat. Reacted Cu contents (0.10% and 0.16%) in several commercially treated samples support the results of the laboratory experiments. It can be anticipated that the amount of reacted Cu is independent of the distance from the wood surface provided that sufficient micronized copper is present to allow the full reaction. This was confirmed in the commercial materials. 73  Chapter 4: Reacted Cu(II) concentrations in earlywood and latewood of micronized copper treated Canadian softwood species 4.1 Introduction The solubility of BCC is increased upon reaction of the treatment solutions with wood as a result of the acidic nature of wood. However, because the fixation mechanism is controlled by the low solubility of BCC and the availability of carboxylic acid protons in wood, the interaction of the particulate copper with the cell wall materials is a crucial element in the effectiveness of the treatment. As a result, physical differences between earlywood and latewood may have a significant influence on the total and reacted micronized copper species in them, as well as the penetration pathways of the treatment solutions. Earlywood has a much higher ratio of lumen volume to cell wall materials compared to latewood, and thus lower density for more micronized copper treatment solution to penetrate. However, the flow of the treatment solution in the longitudinal and tangential directions through bordered pits in the sapwood of softwoods may be restricted by drying of the lumber (Ericson and Crawford 1959; Usta 2005), since it causes a much higher degree of pit aspiration in earlywood than in latewood. Therefore, a greater solution penetration and wider particulate distribution may be expected in the latewood of the micronized copper treated softwood. BCC deposited in wood contains unreacted, chemically fixed and soluble copper species. Various studies have been conducted to probe the micro-distribution of metals in the particulate system treated wood (Evans et al, 2012; Matsunaga et al, 2012; Zahora 2010 and 2011; Schultz and Nicholas, 2011 and 2012). Earlier studies (Xue et al., 2010; Xue et al, 2012) confirmed that hydrated copper species were produced and fixed rapidly with wood upon treatment with an 74  aqueous suspension of BCC. A quantification method using EPR in combination with X-ray fluorescence (XRF) spectroscopy was developed for determining the reacted copper concentrations in the treated wood (Chapter 3). In the study reported here, we continue to apply the quantification method to examine the reacted and total copper levels in earlywood and the latewood, of full size sawn wood of two Canadian softwoods, pressure treated with micronized copper. 4.2 Material and methods Red pine (Pinus resinosa) and incised, western hemlock [Tsuga heterophylla (Raf.) Sarg], nominal 4×4s (89×89 mm) were pressure treated with fresh solutions in a pilot plant based on a commercial schedule. Earlywood and latewood sawdust samples were recovered from cross-cut sections of the dried MCQ- and MCA-treated red pine sapwood (RPsw) and MCA-treated WH heartwood (WHHW), by a combination of drilling with a fine drill bit and sectioning with a razor blade. All recovered material was ground to 40 mesh sawdust and dried prior to analysis. The presence of heartwood in the western hemlock was confirmed visually as well as colorimetrically (Barton 1973). Total copper in the ground samples was determined by XRF (AWPA 2012a). Reacted copper in the samples was determined by EPR using methods described in Chapter 3.2.4 and Equation 3.1. 4.3 Results and discussion Simulated EPR parameters of all the micronized Cu treated RPSW and WHHW samples show that there was no obvious difference in the type of reacted Cu species in earlywood or latewood (Table 4.1), with 𝑔𝑧  =  2.36 and 𝐴𝑧  =  133 𝐺. The values are consistent with copper reaction 75  products containing only Cu-O bonding being formed in the micronized copper treated wood. The amount of total Cu retentions in earlywood and latewood of red pine sapwood and western hemlock heartwood treated by micronized copper was quantified in the study, as well as the reacted Cu(II) concentrations (Figure 4.1 and 4.2). The total Cu loadings determined by XRF for red pine sapwood show higher quantities in earlywood than latewood for both MCQ and MCA treated red pine as confirmed by the paired t-tests (Skoog et al. 2007) at 0.05 significance (P=0.015 and 0.003 respectively) due to a lower permeability in the latewood. The MCA treated red pine had lower retention than that treated with MCQ, with approximately 1.7% total Cu in earlywood, and 1.1% in latewood. For the RPSW, the total Cu content tended to be lower furthest from the wood surface, reflecting the resistance to the penetration of the dispersed Cu particles (Figures 4.1).  Table 4.1 Simulated EPR parameters of RPSW29B, RPSW36A, and WHHW50A Sample g-factors Hyperfine coupling constant (G) gz gy gx Az Ay Ax RPSW29B 2.358 2.070 2.070 133 30 5 RPSW36A 2.363 2.070 2.070 133 30 5 WHHW50A 2.357 2.071 2.071 133 33 5  76  a)  b)  Figure 4.1 Earlywood (EW) and latewood (LW) retentions of reacted Cu(II) and total Cu, measured in three consecutive rings of: a) MCQ treated RPSW29B; b) MCA treated RPSW36A 77   Figure 4.2 Earlywood (EW) and latewood (LW) retentions of reacted Cu(II) and total Cu, measured in five consecutive rings of MCA treated WHHW50A  Western hemlock heartwood is known to be among the more treatable of the western wood species (Kumar and Morrell 1989). The paired t-test shows that the total Cu loading in the latewood is statistically higher than in the earlywood in this wood sample (at a significance of 0.05, P=0.006), with values ranging from 4.1% to 2.5% in the latewood and 2.6% to 1.3% in the earlywood (Figure 4.2). The consecutive rings did not illustrate a clear trend of decrease in total Cu from the surface towards the inner part of the sample, reflecting a variable permeability. The results obtained from both wood samples are in agreement with previous studies on southern pine sapwood (Zahora 2010; Zahora 2011) in that the earlywood and latewood bands have distinctly different total Cu distributions in micronized Cu treated wood. However, while the RPSW, like the southern pine sapwood, had higher Cu loadings in earlywood than latewood, the western hemlock heartwood had a higher total Cu retention in the latewood.  78   In softwood sapwood, latewood typically has a higher density than earlywood does. Therefore, a higher number of carboxylic acid reaction sites will be present in the former per wood volume. The reacted Cu concentrations in this study are calculated from mass normalized EPR spectral intensities, which eliminates the influence of different densities between earlywood and latewood (Equation 3.1). The paired t-tests shows that the reacted Cu levels detected by EPR in earlywood did not significantly differ from those in the latewood for both softwood species treated with MCA (at p = 0.05, P = 0.093 for RPSW and 0.578 for WHHW). Only for MCQ treated red pine sapwood were the reacted Cu contents in the earlywood significantly higher than the latewood, (At p=0.05, P = 0.0005). The maximum values of reacted Cu(II) concentrations are expected to be 0.25% for MCQ and 0.33% for MCA treatments based on previous studies (Chapter 3.3.2). These values are limited by the available carboxylic acid functionality at the reaction pH of 4-6 (Lee and Cooper 2010a), as well as the cation competitions between the quat co-biocide and soluble Cu in the case of MCQ treatment. The highest reacted Cu(II) concentration detected from all the samples in this study is 0.19% (RP36A EW3, Figure 4.1b), much lower than the 0.33% maximum level achievable without quat competition.   For both softwood species, there was no significant decrease in reacted Cu(II) levels from the surface towards the interior. Despite the large excess of unreacted BCC available and the distinct differences in total Cu loadings between earlywood and latewood, the data reflects a comparable capacity of each to solubilize and complex the reacted Cu(II). The comparison of the XRF and EPR results demonstrated the fundamental differences between the reactions of soluble Cu (as found in alkaline copper preservatives) and that in the micronized copper treatment systems, the fixation of Cu in the former is largely influenced by solution uptake and penetration 79  pathways, whereas the latter mostly relies on the reaction with wood to initiate the solubilization and the subsequent complexation of free cupric ions with wood, as well as being limited by the availability of the carboxylic acid groups in wood. 4.4 Conclusions EPR was used in combination with XRF to quantify the total Cu and the reacted Cu(II) in the earlywood and latewood of micronized Cu treated RPSW and WHHW. The total Cu loadings were found to be distinctly different between the earlywood and the latewood for both wood species, whereas the concentrations of reacted Cu(II) were very similar in earlywood and latewood. This confirms that the primary solubilization and fixation reaction of micronized copper treatment is controlled by the reaction with the wood acidic protons, rather than being influenced by solution uptake. 80  Chapter 5: Reacted Cu(II) concentrations in amine amended micronized copper treated red pine and lodgepole pine 5.1 Introduction Reaction of the soluble alkaline copper is driven by the large pH gradient between the treatment solution and wood. Fixed Cu-amine-wood complexes, precipitated Cu compounds and soluble unreacted Cu-amine complexes are left in the treated lumber as a result. Unlike soluble alkaline copper preservatives, micronized copper solutions are only slightly alkaline due to the low solubility of BCC (Ksp=10-33.78 for malachite. Astilleros et al. 1998). However the solubility of BCC is promoted by the acidic nature of wood through reaction with the protons in carboxylic groups of hemicellulose and pectin, releasing solubilized Cu ions as a result. The reaction also creates reactive sites for the solubilized Cu ions to be fixed rapidly. The treated wood contains fixed Cu-wood complexes, unreacted BCC (insoluble) and a small amount of un-complexed soluble metal ions. Because the fixation mechanism is controlled by the low solubility of BCC and the availability of acidic protons in wood, the concentration of reacted Cu species in micronized treated wood is lower than compared to that in wood treated by alkaline copper preservatives, in which all the Cu species are soluble and hence considered to be reacted.  Recently a Canadian patent application (Patel 2009) described the modification of micronized copper preservative with some alkaline copper in an attempt to enhance the surface appearance of the treated wood. The patent aimed at addressing an issue described as surface “chalking” whereby surface residue was formed on wood treated with micronized copper. The inventor had envisaged the amine copper and micronized copper working together. 81  Unfortunately, the most probable reaction of the amine copper would be with the most reactive protons in wood, those of the carboxylic acid functionality, although the high pH of the amine could also activate phenolic protons where the carboxylic acid protons are limited in availability.  Therefore, based on the studies presented in the previous chapters, the reaction of the BCC with the carboxylic acid protons in hemicellulose and pectin would be sensitive to the acid base reaction of the amine, and one would expect the amine reaction of the amended micronized copper formulation (MCEA) to inhibit the reaction of the micronized copper until the amine has been completely utilized. Furthermore, if the amine reacts with all the available carboxylic acid in wood, then the metal-wood species formed in the treated wood will contain only Cu-amine-wood complexes (designated as the Cu-N component) found in alkaline copper treated wood, but no Cu-oxygen-wood complexes (designated as the Cu-O component) found in micronized copper treated wood.  However, if the chemistry proposed in the patent was valid one might expect the treated wood to contain both the Cu-N and Cu-O components. The objective of this study is to confirm that the presence of the amine will prevent the micronized copper from reacting until all of the amine is used.   In this chapter, we continue to apply the calibration standard created by the CuSO4 treated sawdust as a reference to quantify the Cu-O component in MCEA treated wood, as well as create a separate calibration standard using ACQ treated sawdust to quantify the Cu-N components. A simulation procedure using Microsoft Excel analysis tool SOLVER was devised to separate the Cu-O and Cu-N components in EPR spectra of MCEA treated wood, before each component was quantified based on the respective standards. Total Cu uptake of the samples were analyzed by XRF. 82  5.2 Material and methods 5.2.1 Sampling of MCEA treated wood Red pine 89 x 89 mm (nominal 4×4s), and lodgepole pine, 38×140 mm (nominal 2×6) were pressure treated with a 1.92 % MCQ solution modified by the addition of 0.269% MeaH to create a small amount of amine solvated Cu. Sawdust samples were recovered from sections of this MCEA pressure treated red pine 4×4s and lodgepole pine 2×6 boards. All samples were sapwood. Samples were removed in 1 mm increments using a computer aided router. 5.2.2 Leaching of MCEA treated wood Sawdust was prepared from the outer 0 to 1mm and 1 to 2 mm assay zones in the 4 x 4 sample RP2-1. After grinding to 40 mesh 2g samples were leached by stirring in distilled water (50 mL) for 24 h or 7 days at room temperature. The resultant products were filtered under suction and dried in the oven at 100 °C for 24 hours. An unleached reference sample was also oven dried and retained. 5.2.3 Mixtures of ACQ and CuSO4 treated sawdust In order to test the effectiveness of the proposed simulation procedure, three mixtures were prepared from sawdust treated with ACQ and CuSO4. The original ACQ and CuSO4 treated samples, which contain 0.19 and 0.20% total (reacted) Cu as determined by XRF, were chosen from the same sample pool of sawdust that were used to make up the ACQ and MC calibration standards. The mixed samples were made up by physically combining the ACQ and CuSO4 treated southern pine sapwood sawdust at 3:1, 1:1 and 1:3 mass to mass ratios.  83  5.2.4 Data acquisition and process Total Cu and Cu-O component of the reacted Cu(II) in the samples were determined by XRF and EPR as described in Chapter 3.2 and Equation 3.1. Another calibration standard for quantifying the Cu-N component was created by the same method using sawdust samples treated by ACQ at concentration range between 0.01-0.1% (on Cu basis). The samples were analyzed by both EPR and XRF. The mass independent Cu(II) EPR signal intensities were correlated with the corresponding total Cu detected by XRF. A linear relationship was established from the correlation and linked the Cu(II) EPR signal intensity (AUC) with mass indirectly through Equation 5.1:  %𝑪𝒖𝑪𝒖−𝑵 = 𝟏. 𝟖𝟎 × 𝟏𝟎−𝟕 (𝑨𝑼𝑪𝒎𝒂𝒔𝒔) − 𝟎. 𝟎𝟎𝟗𝟕 𝑹𝟐 = 𝟎. 𝟗𝟗  Equation 5.1 5.2.5 Simulation of Cu-O and Cu-N mixed spectra using Microsoft Excel SOLVER Simulation was carried out using the SOLVER analysis tool in Excel. EPR spectra of an ACQ and a CuSO4 treated samples were used as reference spectra to simulate the spectra of MCEA treated samples based on the relation:    𝑺𝑰𝑴𝒄 = 𝒛(𝑨𝒙 + 𝑩𝒚) ≈ 𝑹𝑨𝑾𝒄    Equation 5.2  Where RAWc is the experimental spectrum of a MCEA treated sample C and SIM is the simulated spectrum. The references used for the simulation consist of the spectra of an ACQ treated sample (A) that represents the Cu-N component, and a CuSO4 treated sample (B) that represents the Cu-O component. The x and y are the corresponding fractions of spectra A and B. z is a scaling factor to match the intensities of the simulated spectrum with that of the experimental. 84   The coefficient of determination (RSQ) of a good simulated spectrum should be close to 1. Using the SOLVER analysis tool in Excel, the RSQ (RAW, SIM) was defined as the target and was set to maximize the fitting of data points between 2550-3000 G, because this is the region where the spectrum is most sensitive to changes in Cu-wood complexes. The magnetic field range had been chosen to give the best simulation results amongst several field ranges tested. The values of x and y are defined as two variables that affects RSQ which will be determined by SOLVER. The output results of x and y are used to quantify the amount of Cu-N and Cu-O components based on Equation 3.1 (Chapter 3.3.1) and 5.1:   %𝑪𝒖𝑪𝒖−𝑵 = 𝟏. 𝟖𝟎 × 𝟏𝟎−𝟕 (𝒙𝒛𝑨𝑼𝑪𝑨𝒎𝒂𝒔𝒔𝑪) − 𝟎. 𝟎𝟎𝟗𝟕   Equation 5.3   %𝑪𝒖𝑪𝒖−𝑶 = 𝟗. 𝟕 × 𝟏𝟎−𝟖 (𝒚𝒛𝑨𝑼𝑪𝑩𝒎𝒂𝒔𝒔𝑪) − 𝟎. 𝟎𝟏𝟑   Equation 5.4 where AUCA and AUCB are the spectral intensities of reference A and B. In practice the CuSO4 treated reference B can be replaced by a spectrum of micronized copper treated sample. 5.3 Results and discussion 5.3.1 Simulation of EPR spectra of ACQ and CuSO4 treated sawdust mixtures MCEA treated wood was assumed to contain both Cu-N and Cu-O components, where the micronized copper complexed to wood with all Cu-O bonding and ACQ formed CuN2O4 bonding. To determine how much of each component was present in the treated sample, a simulation method using Excel SOLVER was used to separate the mixed components from a single EPR spectrum. To test the effectiveness of the proposed simulation procedure, three mixtures of ACQ and CuSO4 treated sawdust at 3:1, 1:1 and 1:3 mass to mass ratios (Table 5.1) 85  were prepared. Figure 5.1 shows a comparison of the experimental spectrum of sample D with the simulation and the two reference spectra. Although the reference spectra each looked different from the raw spectrum of D, the simulation based on the combination matched the raw spectrum very well. The Cu-N and Cu-O components were then calculated along with the total reacted Cu(II) based on the simulations, and the results are comparable to the theoretical values calculated from the XRF results (Table 5.1). The same simulation procedures were used to study reacted Cu(II) levels in MCEA treated the red pine and lodgepole pine samples. Table 5.1 Theoretical and SOLVER simulated Cu-N and Cu-O contents of mixture C, D and E made up from reference samples A and B (c.f Chapter 5.2.3) Sample Mixture ratio (m/m) Cu content (% m/m Cu) Theoretical Simulated Cu-N Cu-O Total Cu-N Cu-O Total C A:B = 3:1 0.14 0.05 0.19 0.15 0.05 0.20 D A:B = 1:1 0.10 0.10 0.20 0.09 0.10 0.19 E A:B = 1:3 0.05 0.15 0.20 0.05 0.16 0.21  86   Figure 5.1 Experimental (RAWD) and SOLVER simulated (SIMD) EPR spectra of mixture D compared against the Cu-N and Cu-O references 5.3.2 Quantification of reacted Cu(II) in MCEA treated red pine and lodgepole pine BCC is extremely insoluble in water and its reaction with wood is predicated on availability of the acidic protons of carboxylic groups in wood. It is known that solvated Cu2+ ions in the MCEA solution is in the form of [Cu(Mea)2]0 or [Cu(Mea)(MeaH)]+ (Scheme 1.1, Chapter 1.1.3), whereas the ion being adsorbed is [Cu(Mea)]+ (Lee and Cooper 2010b). The [Cu(Mea)2]0 species may remove one labile proton from wood to form [Cu(Mea)(MeaH)]+, and  another one upon being complexed to wood as [Cu(Mea)]+. Any free MeaH additive will rapidly undergo acid-base reactions with the most labile protons in wood and thus compete with the BCC (Lucas and Ruddick 2002; Lucas 2003). Therefore, Cu-N-wood complexes should dominate the treated 87  lumber until all the MeaH has been used up. However, in bulk analysis of a treated lumber, there may be a possibility that the MeaH is used up in certain regions but still present in the others. This study tries to verify whether there is a gradual increase in the level of Cu-O-wood complexes as the treatment solution penetrates deeper into the wood surface.   Samples were recovered in 1 mm increments from the red pine sapwood. Simulations of the EPR spectra of MCEA treated red pine samples show that the Cu-N-wood complexes are the dominant form of reacted Cu in the wood. The Cu-N component retention decreased rapidly with increasing sample depth, from 0.23% to 0.05% in the S1 face of RP1-1 and from 0.24% to 0.06% in the face S2 of RP1-1 (Figure 5.2a). A similar trend was observed in RP4-1 S1 and S2 (Figure 5.2b). XRF analysis on the total Cu retention in the treated red pine (Table 5.2) shows that most of the Cu absorbed during the treatment remained as unreacted BCC and was not detected by EPR. The Cu-N concentrations were well below the expected CEC found by Lee and Cooper (2010a), and the levels of the Cu-O component were extremely low throughout the sample zones examined, with most of the values being essentially zero.   The finding agrees with our understanding of the chemistry that while the MeaH-Cu complexes in the residual solution after treatment are almost completely depleted, the remaining free MeaH was also able to react with the limited available carboxylic acid protons, thereby preventing their use in solvating the BCC. Unless there is a much greater number of carboxylic acid functionalities available in the wood, no gradual change in composition of Cu-wood complexes from the Cu-N form to the Cu-O form will be observed within the depth examined. The simulations did show a very small increase in the amount of the Cu-O component as the 88  sampling zone moved from the surface towards the inner part of the “4×4” (Figure 5.2). However values never exceeded 0.01% Cu. Table 5.2 Total Cu retention (% m/m Cu) determined by XRF in MCEA treated red pine and lodgepole pine. a ±0.03% Depth/mm Total Cu (% m/m Cu) by XRFa RP1-1 S-1 RP1-1 S2 RP4-1 S1 RP4-1 S2 LPP 5-2 LPP 7-2 1 3.29 4.58 3.73 3.87 3.011 1.821 2 1.83 1.91 2.81 1.55 0.887 0.711 3 1.64 1.63 2.34 1.38 0.607 0.615 4 1.26 1.26 2.00 1.19 0.479 0.447 5 1.07 1.11 2.02 1.10 0.423 0.383 6 1.02 1.06 1.50 1.13 0.423 0.447 7 0.75 1.06 1.80 0.96 0.343 0.399 8 0.69 0.96 1.57 0.99 0.327 0.304 9 0.76 1.03 1.68 0.92 0.423 0.319 10 0.66 0.97 1.46 0.87 0.423 0.343  89  a)  b)  Figure 5.2 Cu-N and Cu-O retentions of reacted Cu determined by simulations of MCEA treated red pine 4×4, measured in 1mm increments (up to 10mm): a) RP1-1; b) RP4-1  90   Sapwood in samples of MCEA treated lodgepole pine show similar trends as the red pine sapwood. The levels of the Cu-N component decreased rapidly with increasing sampling depth for both LPP5-2 and LPP7-2 (Figure 5.3 and 5.4), reducing to 0% m/m Cu for the Cu-N component at 6 mm. The levels of the Cu-O component were negligible throughout all the assay zones.   Figure 5.3 Cu-N and Cu-O retentions of reacted Cu determined by simulations of an MCEA treated lodgepole pine 2×6 (LPP5-2), measured in 1mm increments (up to 10mm) 91   Figure 5.4 Cu-N and Cu-O retentions of reacted Cu determined by simulations of an MCEA treated lodgepole pine 2×6 (LPP7-2), measured in 1mm increments (up to 10mm) 5.3.3 Leaching of MCEA treated red pine Based on the above hypothesis that residual amine hinders the reaction of BCC with the wood, even when the amine-Cu complexes are depleted, it was decided to study the effect of leaching on the reacted Cu content. If the amine could be removed leaving some free carboxylic acid reaction sites then there should be a small increase in the Cu-O component.   Surface samples (1mm and 2mm) of MCEA treated red pine RP2-1 were leached for 24 h and 7 days. Simulations of the EPR spectra for the unleached samples contained only the Cu-N component in the reacted Cu and no detectable Cu-O level. Leaching of the samples shows a slight increase in Cu-O levels from 0% to 0.02% and a small decrease in the amount of the Cu-N species (Table 5.3). The small increase in the Cu-O component supports the hypothesis that 92  removing traces of free amine allowed some BCC to react with free carboxylic acid groups in hemicellulose and pectin that had not undergone an acid base reaction with amine. The static leaching study in Chapter 6 shows that the reacted Cu level can increase up to the optimum CEC allowed under high moisture level. The fact that the combined reacted Cu concentration for the 2mm samples were much lower than the expected 0.33% even after 7-day leaching means that the a significant number of labile protons were sequestered by the MeaH, and less than half of the carboxyl functionality was complexed to Cu.   Significant decrease in total Cu retention was observed in the 1mm samples, while those of 2mm samples remained constant. Because the loss of reacted Cu was significantly less in comparison, this suggested that the BCC was leached from the surface. It is unclear whether it was simply lost as a surface precipitate due to extremely high surface retention, or the MeaH assisted the leaching of the BCC. Table 5.3 Total Cu and simulated reacted Cu(II) contents in RP2-1 before and after leaching. a ±0.02% Sample Cu content (% m/m Cu) Simulated aTotal Cu by XRF Cu-N Cu-O RP2-1, 1mm, unleached 0.26 0.00 10.48 RP2-1, 2mm, unleached 0.17 0.00 4.21 RP2-1, 1mm, 24 h leaching 0.21 0.02 8.21 RP2-1, 2mm, 24 h leaching 0.14 0.02 4.52 RP2-1, 1mm, 7-day leaching 0.24 0.02 5.06 RP2-1, 2mm, 7-day leaching 0.13 0.02 4.29  93  5.4 Conclusions EPR was used in combination with XRF to quantify the reacted Cu and the total Cu in MeaH amended micronized copper treated red pine 4×4s and lodgepole pine 2×6s. A simulation procedure using Microsoft Excel SOLVER was used to isolate and quantify the concentrations of Cu-N-wood and Cu-O-wood species in the treated wood.  Based on the simulations, the MCEA treated wood was found to have only Cu-N species at the wood surface, the concentration of which diminished quickly as the sample depth increased. The Cu-O component concentrations were close to the detection limit throughout the treated zone. This was consistent with the hypothesis proposed that the addition of the MeaH formed some amine-Cu complex similar to ACQ. The Cu-MeaH complex and any free MeaH remaining, reacted with the wood acid protons that could have been utilized to solubilize the BCC. The total Cu content determined by XRF reduced as the sampling location moved further from the wood surface. Comparison of the combined reacted Cu levels and the total Cu retention shows most of the absorbed Cu in the treated wood remained unreacted. Leaching of the outer wood samples for 24 h and 7 days resulted in an overall decrease of the Cu-N component and a slight increase on the Cu-O component which would be consistent with the removal of some free amine and the lowering of the wood pH to allow any available carboxylic acid sites to react with BCC. 94  Chapter 6: Effect of soil contact on reacted copper(II) levels in micronized copper treated wood 6.1 Introduction Results from the previous chapters showed that while the maximum CEC of wood at the reaction pH with micronized copper is about 0.33%, the reacted Cu concentrations in the commercial treated wood immediately following treatment is often only 0.10% for MCQ and 0.15% for MCA. Solubility of BCC is very sensitive to changes in pH, and the free Cu(II) ions are subjected to complexation with both wood constituents and various chelators in the service environment (Jin et al. 2010; Kartal et al. 2013). An acidic environment within the wood will be need to be created, if the vast excess pool of unreacted BCC deposited in the treated wood is to be solubilized and fixed. One potential source of acidic compounds is soil, which is known to contain humic acids and/or fulvic acids. Humic acid is formed by the decomposition of dead plant matter. It is a complex mixture of many different acids rich in carboxyl and phenolate groups (Figure 6.1). Fulvic acids are humic acids of lower molecular weight. Compositions of humic acids and fulvic acids varies with the origin and nature of the soil. The typical carboxyl content tends to be 3-5 mol.kg-1 for humic acids and 4-8 mol.kg-1 for fulvic acids. The phenolic -OH content is about 1-4 mol.kg-1 for both humic and fulvic acids (Sposito 2008a). 95   Figure 6.1 A model structure of humic acid proposed by Stevenson (1994), comprising catechol, quinone and phenol as building blocks 96   Humic acids can easily complex with ions found in the soil and form humic colloids. Humic acids’ cation exchange capacity and metal ion complexing property has been studied extensively (Tipping et al. 2002; Sposito 2008b; Klucakova 2014; Shoba and Chudnenko 2014; Chotpantarat et al. 2015). Many naturally occurring and artificially-prepared metal-humic substance complexes have been studied by EPR, including iron, manganese, copper, vanadium and molybdenum (Senesi et al. 1977; Templeton III and Chasteen 1980; Goodman and Cheshire 1982; Senesi and Sposito 1989; Jerzykiewicz et al. 2002). Senesi and Calderoni (1988) reported the indigenous Cu-humic acid complex extracted from paleosols with EPR parameters 𝑔𝑧 =2.282 and 𝐴𝑧 = 165 𝐺 (176 × 10−4𝑐𝑚−1). Such values are consistent with Cu(II) in a 𝑑𝑥2−𝑦2 ground state complexes with one Cu-N bond and three Cu-O bonds arranged in a tetragonal environment (Figure 6.2). EPR studies on fulvic acid extracted from sewage sludge and soil organic matter indicated the main residual Cu(II) complexes contain only oxygen ligands, with EPR parameters of 𝑔𝑧 = 2.346 and 𝐴𝑧 = 136 𝐺 (149 × 10−4𝑐𝑚−1), whereas the N-ligand containing Cu complex is in minority (Senesi and Sposito 1984). The nitrogen contents are 2.04% for the humic acid and 0.86% for the fulvic acid respectively.  Figure 6.2 A generalized model for a Cu2+ complexes to humic acid proposed by Senesi (1990) 97   Organic acids from compost are known to be effective at extracting Cu from CCA treated wood (Cooper and Ung 1992). Studies conducted by Cooper et al. (2001) shows that humic acid solutions collected from boggy areas can increase leaching of Cu from CCA treated wood, especially in the presence of free water below the groundline. However, the humic acid and fulvic acid contents in virgin soil are typically much lower than those used in these studies, and they are often in colloidal form, being complexed to other ions. Therefore, it is uncertain whether the unreacted BCC can be solubilized and fixed when in contact with soil.  A study conducted using untreated southern pine exposed to chemically amended soils at different pH concluded that the pH of the treated wood trends towards the soil pH (Vidrine et al. 2010). Jin et al. (2011) reported that the pH of particulate Cu oxide treated southern pine increased during a 12-month soil exposure from about 5 to 5.5, while the pH of the chemically amended acidic soil increased from 4.8 to 5.7. Similarly, in a twelve-week study conducted using natural soils with different pH (Wang and Kamdem 2011), the pH of micronized copper treated wood also increased from pH 5.7 to 6.0 exposed to an acidic soil at pH 5, the pH of which changed very little during the testing period and was significantly lower than the final wood pH. Copper leaching as high as 10% from micronized copper treated wood exposed to the acidic soil were detected in the study. The carboxylic protons in humic acids and fulvic acids were readily dissociated at the soil pH in both studies. Chelating effect of the organic acids in soil may be the cause of high leaching of Cu in the treated wood.   The current study was initiated in order to further understand the role of unreacted BCC in wood and its possible interaction with the acidic soil components. Small slices of micronized copper treated wood were exposed to two naturally acidic soils for 8 weeks to determine whether 98  the acidic components in soil can solubilize some of the residual micronized BCC and increase reacted Cu concentration in the treated wood.  6.2 Material and methods 6.2.1 Materials Two red pine (Pinus resinosa) ‘4×4’ fenceposts were selected from several treated in a pilot plant to commercial standards with MCQ and MCA. The ratios of Cu to quat were the same as that in ACQ (AWPA 2012b) while the Cu to azole ratio was the same as that in alkaline copper azole (CA-B) (AWPA 2012c). A thin slice approximately 3 mm in thickness was sawn from two faces of each ‘4×4’. The slices were comprised of treated sapwood. Each slice was then sawn into 8 end-matched pairs (16 pieces) of small sized samples taking care to exclude any wood associated with knots or other defects. The location of each sample in the parent slice was noted and the sample numbered. This allowed end matched samples to be removed at different time periods. The samples varied in size but were typically 80 to 100 mm long and 30 to 40 mm wide. 6.2.2 Soil To create a soil exposure which was uniform, each soil was placed in a basin and small treated wood stakes inserted fully into the soil. Two different soils from the UBC Research Forest at Haney, B.C. were used. A representative sample from each soil was analyzed for selected physical and chemical properties by Pacific Soil Analysis Inc. The soil characteristics are shown in Table 6.1. The soils were used as soon as received. The soil A was collected from a cleared forest area that has been used as a test site and was grassed over. Soil B was recovered from a nearby area that was still undisturbed forest, with the usual leaf litter. The soils were placed in 99  basins to a height that would allow all stakes to be buried completely when inserted vertically (Figure 6.3a). Table 6.1 Soil characteristics Soil A B pH 5.0 5.1 Total organic matter (%) 15.3 25 Total N (%) 0.33 0.74 C/N 26.9 19.6 Avail. Ca (ppm) 400 2032 Avail. Mg (ppm) 45 271 Avail. Cu (ppm) 1.5 0.8 Avail. Fe (ppm) 38 13 Avail. P (ppm) 8 34 Avail. K (ppm) 60 130 Sand (%) 68.2 68.0 Silt (%) 20.9 17.0 Clay (%) 10.9 14.1  a)   b)   Figure 6.3 a) Samples being placed in the soil bed; b) final row being buried in soil 100  6.2.3 Installation and recovery of the samples Prior to installation, the moisture content of the stakes was measured and averaged 7.95 % for the MCA samples and 7.85 % for the MCQ samples. To ensure a rapid response to the soil exposure the samples were vacuum impregnated with distilled water to raise the moisture content to above 100%. The moisture content of the soil was raised to about 80% and allowed to equilibrate for three days before the samples were added. The samples were installed randomly in the soil using a pre-determined grid, so that after being buried they could be easily located (Figure 6.3b). The soil basin was stored in the laboratory at room temperature (approximately 22 °C). Periodically the total mass of the basin and soil was measured and when the mass decreased by approximately 10% additional water was carefully added to the soil surface.  The designations of the 8 pairs of end-matched pieces from each wood slice are listed in Table 6.2.  Four samples were selected from each slice to act as pre-exposure reference samples. They were oven dried and ground to 30 mesh sawdust, for determination of the total Cu by x-ray fluorescence spectroscopy (XRF) (AWPA 2012d). The quantification of the reacted Cu(II) was determined as described previously in Chapter 3.2. The remaining twelve pieces were placed into the soil so that each sample designated for the same collection period was placed at a different row in the grid. This ensured that samples were available over the whole soil bed for all three times. All samples were buried full length into the soil. A total of 24 samples were installed in each soil bed. At 2, 4 and 8 weeks four MCQ and four MCA treated samples were removed. At each time of removal, the samples were shaken for 1 minute in distilled water and then carefully very lightly wiped free of soil deposits. They were oven dried at 100 °C for 5 hours and left for 48 hours before being ground into 30 mesh sawdust. The sawdust was then analyzed for total Cu 101  and reacted Cu using XRF and EPR, respectively, as described earlier. Comparison of the total and reacted copper measurements at each time of soil exposure, with those of the unexposed samples provided a measure of copper depletion, as well as changes in the reacted copper with increasing exposure. Table 6.2 Designations of the 8 end-matched pairs sawn from each red pine slice Pair Piece #1 #2 1 Pre-exposure reference Week 2 2 Week 4 Week 8 3-8 Replicates of pairs 1 and 2  6.2.4 pH measurement and measurement of possible leaching during pH determination The pH of the matching unexposed wood samples and samples removed after being exposed to soil were determined based on the method described by Vidrine et al., 2010. A 3 g aliquot of sawdust was mixed with 60 g of distilled water and sonicated for 90 min. The product was filtered under suction and oven dried at 100 °C for 5 h. The pHs of these solutions (referred to as leachate solutions) were measured using a Beckman 350 pH meter (Beckman Coulter, Pasadena, CA, USA) equipped with an ACCuTupH double junction electrode (Thermo Fisher Scientific, Waltham, MA, USA). The sawdust after measurement of the pH and dried is referred to as being “leached”. However, the procedure was not designed specifically to evaluate the depletion of copper in the study, but rather to measure changes in pH of the wood. After drying, the “leached” sawdust was analyzed by XRF and EPR for total Cu retention and reacted Cu(II) concentrations. Comparison with the values for obtained immediately after soil exposure, 102  provided a measure of the copper depletion and changes in the reacted copper content, due to the pH assessment.   Because an increase in the reacted Cu(II) concentration was found in most samples with almost no change in the total Cu retention, additional studies were conducted to better understand the role of sonication, compared to simple stirring in water, on the reaction of micronized copper in wood.  6.2.5 Sonication and stirred leaching comparison study Materials remaining from the main soil study were used. Three pieces from MCQ and three pieces from MCA treated red pine were cut in half. One half was ground to sawdust (40 mesh) while the second half remained intact. Each sample was placed in 50 g of distilled water. The solid sample was ultrasonicated while the matching sawdust sample was stirred for 90 min at room temperature. After leaching the samples were oven dried at 100 °C for 12 h. the solid sample was then ground to sawdust (40 mesh). The samples were analyzed for total Cu by XRF and reacted Cu using EPR. 6.2.6 Static leaching study Three unexposed MCQ and MCA treated red pine stakes from the soil study were each cut into three pieces. In each set of subsamples, one was left as the reference, the other two were vacuum impregnated with distilled water for 35 min after they were completely submerged in distilled water. The ratio of sample to water was 1:20 and usually 50 g of water was required. The first samples were removed after 2 weeks and the second removed after 12 weeks. All of the samples were oven dried at 100 °C for 24 h and ground into 40 mesh. Total Cu contents and reacted Cu(II) concentrations of the samples were analyzed by XRF and EPR. 103  6.3 Results and discussion 6.3.1 Soil exposure studies Simulated EPR parameters of all the samples recovered from soil exposure are consistent with Cu reaction products previously recorded in micronized copper treated wood (Xue et al., 2012), with 𝑔𝑧 = 2.37 and 𝐴𝑧 = 131 𝐺. The species are different from those of Cu-humic acid complex containing one nitrogen ligand, with 𝑔𝑧 = 2.282 and 𝐴𝑧 = 165 𝐺 (176 × 10−4𝑐𝑚−1) reported by Senesi and Calderoni (1988).  EPR parameters due to Cu-fulvic acid complex with only oxygen ligands described by Senesi and Sposito (1984), with 𝑔𝑧 = 2.346 and 𝐴𝑧 = 136 𝐺 (149 × 10−4𝑐𝑚−1) were not observed. The humic acid and the fulvic acid used in those studies were highly purified from composted soils, which were different from the normal soils used in this study. It may be concluded that the reactions with soil did not lead to any apparent change in the types of reacted Cu complex in the micronized copper treated wood. 6.3.1.1 Soil A XRF studies of the MCQ treated samples exposed to soil A show no statistically significant changes at 0.05 level [𝐹(1,6) = 2.95, 𝑝 = 0.14] at the end of the 8-week exposure period (Figure 6.4a). However, the trend of total Cu loadings appeared to show a gradual decrease from 3 to 2.5% over time. Similar to the MCQ treated samples, total Cu changes in the MCA treated samples were statistically insignificant [𝐹(1,6) = 4.78; 𝑝 = 0.07]. The average total Cu content in the MCA treated samples exposed to soil A reduced from 3.2 to 2.4% in the first two weeks, but remained unchanged for the rest of the exposure period (Figure 6.4b). The loss of total Cu retentions could be masked by the relatively large variations between the small number of replicates, hence rendering the changes statistically insignificant. The apparent decrease of total 104  Cu could be due to loss of particulate BCC through the washing and wiping of sample after removal. Alternatively, available BCC on the wood surface could have leached by reacting with the acidic component in soil within 2 weeks, after which no further reduction was observed for the rest of the exposure period.   Un-exposed controls and those removed from soil A were subjected to ultrasonication for the purpose of pH measurement. The changes in pH were not statistically significant for both MCQ and MCA treated samples (Figures 6.4) remaining at 5.6 ± 0.3. This observation was different from those tests conducted in both natural and chemically amended acidic soil at pH 5 (Jin et al. 2011; Wang and Kamdem 2011), in which the pH of micronized copper treated wood increased at the end of both the 12-week and 12-month exposure periods respectively. The 8-week exposure period was probably not long enough to cause significant change in the pH of the wood.  One concern about the ultrasonication process is the possible loss of particulate materials which would then be observed as a loss in total Cu. Examination of the total Cu contents before and after sonication showed no significant difference (Figure 6.4). Therefore, less vigorous processes like washing and wiping of the samples would not have caused the loss of particulate BCC and decrease in total Cu retentions. It is more likely that the acidic component in the soil reacted with the BCC on the wood surface, and the newly formed Cu complexes leached into the soil rather than remained in the wood. The loss of 10% total Cu loadings observed by Wang and Kamdem (2011) are consistent with the results in this study. The gradual decline of total Cu observed in the MCQ treated samples could be the result of the quat competing with the BCC on the wood surface for the available binding sites in soil, similar to the effect studied in Chapter 3. 105  Whereas the reaction with the soil acidic component and leaching of the BCC was unhindered and rapid in the MCA samples exposed to soil A.  EPR analysis on reacted Cu concentrations shows a different trend from that observed in the XRF studies. The amount of Cu-wood complex in both MCQ and MCA treated samples exposed to soil A, increased significantly over the 8 week exposure period (Figure 6.4). The average reacted Cu(II) levels in the MCQ treated samples increased from 0.10 to 0.23%, whereas those in the MCA treated samples increased from 0.15 to 0.28%. The gradual increase in the reacted Cu concentration could be the result of both high moisture levels and interaction of the acidic soil components with the BCC. EPR analysis on the sonicated samples also shows that all the samples have higher reacted Cu(II) concentrations than was present before the sonication process. The highest reacted Cu levels reached after sonication were 0.28% for MCQ and 0.33% for MCA treated samples.  106  a)  b)  Figure 6.4 Total Cu retentions, reacted Cu concentrations and pH of a) MCQ and b) MCA treated red pine exposed to soil A. The sonicated data is based on the effects of ultrasonication leaching during the measurement of the sample pH 107  6.3.1.2 Soil B  The MCQ treated samples had an average total Cu content of 3% before exposure to soil B, and the value did not change significantly [𝐹(1,7) = 0.006, 𝑝 = 0.94] throughout the 8 week exposure period (Figure 6.5a). Though statistically insignificant [𝐹(1,7) = 2.24, 𝑝 = 0.19] due to the large variation in the sample total retentions, the average total Cu content in the MCA treated samples exposed to soil B noticeably reduced from 3.2 to 2.6% in the first two week exposure , but remained relatively constant for the rest of the exposure period (Figure 6.5b). The lack of changes in the total Cu retentions of the MCQ samples exposed to soil B compared with the un-exposed control further confirms that the reductions observed in the MCA treated samples, as well as those exposed to soil A, are more likely to be resulted from the BCC reacting with the soil acidic components and leaching to the environment.  Reacted Cu concentrations in both MCQ and MCA treated samples exposed to soil B increased in the first 2 weeks and remained constant for the rest of the exposure period (Figure 6.5). The average reacted Cu levels in the MCQ treated samples increased from 0.10 to 0.16%, and those in the MCA treated samples increased from 0.15 to 0.19%. Similar to those observed in soil A, the pH measurements show no significant changes throughout the 8-week exposure period for both MCQ and MCA treated red pine. Examination of the total Cu contents before and after sonication had no significant difference. The EPR analysis shows that all of the sonicated samples have higher reacted Cu(II) concentrations than their original before the sonication process. The highest reacted Cu levels reached after sonication were 0.22% for MCQ and 0.25% for MCA treated samples. It was noted that after the sonication leaching, reacted Cu concentrations in all the soil exposed samples (both soil A and B) were higher than those of pre-108  exposure controls. This seems to suggest that the acidic components may have moved into the wood and were utilized in solubilizing Cu during the sonication process. However, one could also argue that the 90 min sonication process was a relatively short time to allow a more complete reaction between the BCC and the acidic wood protons in the pre-exposure controls, considering the soil-exposed samples had been keep under a high moisture level environment for much longer periods.  Wang and Kamdem (2011) reported a 10.4% and 9.1% loss of total Cu retentions in MCQ and MCA treated samples exposed to a soil at pH 5 from Georgia, compared to ~16%  in MCQ and ~19% in MCA treated samples exposed to soil A in this study. The organic content (3.2%) in the Georgia soil was much lower than those of both soils used (15% for soil A and 25% for soil B) in this study. The higher organic content could suggest a higher level of acidic components such as humic acids and fulvic acids, which in theory may increase Cu leaching through reaction with the BCC. However, the reacted Cu concentrations for samples exposed to Soil B before and after the sonication leaching process were both lower than those of corresponding samples exposed to Soil A, despite having a higher organic content. Even though the effect of the wood-soil interaction will likely be mainly at the surface because of the small exposure period, it is clear that variations between the two soils other than the organic content are contributing to the differences in reacted Cu levels. Soil analysis results show that the calcium content in soil B is five times higher than that of soil A (Table 6.1). A study conducted by Shoba and Chudnenko (2014) on ion exchange equilibriums of humic acids with metal cations concluded that calcium, magnesium, and iron were the major components in the exchange complex of humic acids with copper of subordinate importance. It is possible that the 109  Ca2+ ions may compete with Cu2+ for the available cation exchange sites in both the soil and wood. Therefore, the leaching of total Cu was slightly less pronounced in MCA treated samples exposed to soil B (~13%) than that of soil A (~19%), and the overall reacted Cu concentrations were lower. The limited available carboxylic groups complexed to the Ca2+ were stable and the glucuronic acid was not available to solubilize Cu2+ during the sonication process, therefore the increases in reacted Cu concentrations after sonication were less significant than those of samples exposed to soil A. If the hypothesis is correct, the Ca2+ ions not only compete with Cu2+ but also the quat and further retard the BCC reaction with the soil acidic components. This may explain why no Cu leaching was observed in MCQ treated samples exposed to soil B.  The hypothesis should be further verified by analysis on the calcium and other metal contents in the exposed samples.     110  a)  b)  Figure 6.5 Total Cu retentions, reacted Cu concentrations and pH of a) MCQ and b) MCA treated red pine exposed to soil B. The sonicated data is based on the effects of ultrasonication leaching during the measurement of the sample pH 111  6.3.2 Leaching methods: stirring vs. sonication Even though the sonication process for the purpose of pH measurement did not result in any significant loss in total Cu retentions, the EPR analysis did show that all of the sonicated samples have higher reacted Cu(II) concentrations than before the sonication. It was suspected that the cavitation process arising from sonication was able to move BCC particles in wood thereby increasing the reaction with the carboxylic acid groups and increasing the solubilized Cu(II). In order to better evaluate the role of ultra-sonication on these differences in reacted copper, alternative leaching procedures were compared. MCQ and MCA treated samples were subjected to 90 minute leaching by either stirring or sonication. Simulated EPR parameters of samples in the leaching tests are consistent with Cu reaction products previously recorded in micronized copper treated wood, with 𝑔𝑧 = 2.36 and 𝐴𝑧 = 131 𝐺. Paired t-tests of the XRF results show that there were no differences in terms of total Cu loadings between the original sample and the leached samples by either methods for both MCQ and MCA treated samples at the 0.05 significance level (Figure 6.6 and 6.7). The reacted Cu(II) concentrations for the stirred and sonicated samples were higher than their unleached originals, which was similar with what was observed in soil exposure study. The sonicated solid samples had slightly lower reacted Cu(II) levels than the corresponding sawdust samples leached by simple stirring, but the differences were not statistically significant at 𝑝 = 0.05 (𝑝 = 0.10 and 𝑝 = 0.076 for MCQ and MCA treated samples respectively). The amount of reacted Cu increased when the sample became wet suggesting that water can move the particles around until all the effective reaction sites are reacted. The smaller the size of the wood sample (sawdust), the more effective is the interaction between BCC and the wood regardless of the leaching method. Therefore, a third study by static leaching of samples for 12 weeks was conducted to examine the effect of increasing the moisture 112  content of wood on reacted Cu(II) concentrations. Comparisons between the soil exposed samples and the statically leached samples should reveal the effects of soil exposure without the influence of increased moisture levels.  Figure 6.6 Total Cu retentions and reacted Cu concentrations of MCQ treated red pine before and after leaching by stirring and sonication 113   Figure 6.7 Total Cu retentions and reacted Cu concentrations of MCA treated red pine before and after leaching by stirring and sonication  6.3.3 Static leaching MCQ and MCA treated samples prepared from the same source red pine slices as the other materials discussed in these soil experiments, were subjected to vacuum impregnation with distilled water and submerged in distilled water for 2 weeks and 12 weeks. The XRF results show that there was no significant loss of Cu during the static leaching periods for both MCQ and MCA treated samples (Figure 6.8 and 6.9). The EPR result shows that the reacted Cu(II) concentration levels increased with longer static leaching periods for both MCQ and MCA treated samples. The average reacted Cu(II) concentration in the MCQ treated samples increased 114  from 0.12 to 0.21% after 12 weeks of leaching, whereas for the MCA treated samples the average concentration increased from 0.15 to 0.31%. These values are similar to those of un-sonicated samples exposed to soil A after 8 weeks (Figure 6.4). Simulated EPR parameters of samples in the leaching tests are consistent with those recorded for soil exposed samples, with 𝑔𝑧 = 2.36 and 𝐴𝑧 = 131 𝐺.  Figure 6.8 Total Cu retentions and reacted Cu concentrations of MCQ treated red pine before and after static leaching 115   Figure 6.9 Total Cu retentions and reacted Cu concentrations of MCA treated red pine before and after static leaching   Comparisons of the EPR spectra and reacted Cu concentrations between soil exposed and statically leached samples shows no formation of new Cu species and minimal effect on reacted Cu concentrations from the soil A exposure. The bigger impact of soil exposure was on total Cu retentions, in which significant losses were observed in both soils but absent in subsequent leaching experiments. One explanation for this phenomenon may be that the BCC on the wood surface can interact with acidic components in the soil and form reacted Cu. However, because of the lack of change in the reacted Cu parameters, and the assumption that due to the limited 116  exposure time the interaction occurs primarily at the sample surface, it suggests that any copper complexes likely to leach into the soil rather than remain in the wood.   EPR studies conducted previously have noted that the amount of reacted Cu in some commercial treatment samples is often lower than that achieved under laboratory condition. This may be expected because in large sized timbers the maximum reaction between BCC and the wood may not always be attained before the timber dries, therefore limiting the solubilization of BCC and terminating the Cu-wood complexation reaction. The reacted Cu(II) levels approaching the expected maximum at the end of the 8 week exposure period suggests that higher moisture level in soil enhanced the solubility and fixation of BCC with most of the carboxylic acid sites in the wood. The acidic components in soil seemed to cause leaching of the BCC from the wood surface rather than enhancing the reacted Cu concentration in the wood within this period. Furthermore, a comparison of the total Cu and the reacted Cu(II) levels shows that a significant amount of residual micronized BCC still remains even after the soil exposure (Figure 6.4 and 6.5). The implication of these observations for commercial treated timbers is that once they become wet in service, the BCC under humid environment can continue to be solubilized and allow the reaction to proceed until all available sites in wood are occupied. 6.4 Conclusions Exposure of small samples prepared from treated red pine 4 x 4’s in two soil beds of pH 5 for 8 weeks generally resulted a slight decrease of total Cu contents but an increase in the reacted Cu(II) levels. The combination of soil acidity and moisture increased the solubilization and fixation of BCC, which allowed a more complete reaction with the acidic carboxylic functionalities in the wood. At the end of the exposure period, the reacted Cu(II) appeared to 117  plateau at about 0.23% Cu for MCQ treated samples and 0.28% Cu for MCA treated samples exposed to soil A. These values are similar to the range of retentions of reacted Cu(II) observed in the samples treated by micronized copper under laboratory conditions. Comparison of the Cu leaching results with those of Wang and Kamdem's (2011) shows no conclusive evidence that the soil organic content is one of the factors that influences Cu solubilization and fixation. The overall Cu leaching values and reacted Cu concentrations for samples exposed to soil B were less than those of soil A despite having higher organic content. The high calcium content in soil B suggests that a possible competition between the Ca2+ and Cu2+ for the limited available binding sites in both the soil and the wood may be the underlying reason for the observed phenomenon.   Sawdust samples sonicated in water for the pH measurements, were found to have elevated reacted Cu(II) concentrations than before sonication. A comparison study between the sonication and stirred leaching methods shows no significant difference between the two methods, but both resulted in increased reacted Cu(II) concentrations when compared to the unleached references. A third study treating samples with static leaching shows that simply increasing the moisture content of micronized copper treated wood can further solubilize BCC and provide opportunities for more efficient reaction of BCC with available carboxylic acid groups up to the threshold CEC in wood.   Only reacted Cu with EPR parameters similar to those found in treated wood were observed after soil exposure. This suggests that Cu products in wood after the 8-week soil exposure were primarily Cu-wood complexes, with no evidence of Cu-humic acid products. The loss of total Cu from soil exposure which was not observed from leaching of matching samples with distilled water in the laboratory, suggests that acid components in soil may remove BCC 118  from the surface of wood during exposure. However, any Cu products formed were not detected in the wood, and presumably remained in the soil.  Based on the results of this study, it appears unlikely that the acidic components from soil will enhance the reacted Cu content in treated wood above the maximum cation exchange capacity for sapwood where only the carboxylic acid protons can solubilize the BCC. The solubilization and fixation of Cu in the micronized copper treated wood exposed to soil is influence not only by the pH but also other characteristics of soil, such as organic contents, types of metal cation and concentrations, etc. 119  Chapter 7: Chemistry of micronized copper treatment of sapwood and heartwood 7.1 Introduction Studies conducted using sapwood (SW) in the previous chapters have established that the BCC mainly reacts with hemicellulose and pectin to form reacted Cu, and the extent of the reaction is limited by the availability of exchangeable carboxyl protons in the glucuronic acid units. However, hemicellulose and pectin are not the only chemical components of wood that can assist in the solubilization and fixation of BCC. In contrast to SW, heartwood (HW) is rich in both fatty acid and resin acid extractives (Chapter 1.1.2.2), which contain exchangeable carboxyl protons. In principle, these extractive contents in the HW could increase the solubility of BCC and also provide extra reaction sites for the fixation of solubilized cupric ions. If present this effect may result in an increase in reacted Cu(II) concentration. Furthermore, any complexes formed by solubilized Cu(II) with the resin acids (Cu-resin) may give rise to new features in the EPR spectrum compared to that of treated SW, which should contain predominantly Cu(II) complexes with hemicellulose and pectin (Cu-wood). Probing the extent of micronized copper reaction in SW and HW will provide a further understanding of the fixation mechanism and chemical behavior of micronized copper in the treated wood.  While the resin acids may be an internal factor that alters the quantity and composition of the Cu complexes formed in the treated wood, fungal colonization of the wood prior to treatment as an external influence, is known to affect both the chemical and physical properties of wood. Non-decay fungi such as a blue stain fungus are known to produce xylanase and pectinase during 120  colonization (Schirp et al. 2003; Schmidt 2006). Many wood-decay fungi are known to synthesize melanin and low molecular weight metal chelating agents, such as organic acids and catecholates during colonization (Takao 1965; Caesar-Tonthat et al. 1995; Hastrup et al. 2013). Wood strength properties are affected as a result of decaying due to degradation of the key chemical components. However, the decay properties of certain fungi may be used to facilitate preservative treatment. The white-rot fungi Dichomitus squalens and Physisporinus vitreus have been studied for biological incising of refractory wood species due to  their ability to open up the bordered pits in HW without substantial wood strength losses (Rosner et al. 1998; Schwarze et al. 2008; Morris et al. 2011; Schwarze and Schubert 2011). The changes in chemical and physical properties of wood due to fungal colonization could potentially affect the formation of Cu complexes in the micronized copper treated wood.  In this study, we continue to exploit the quantification methodology developed in Chapter 3 to determine both total Cu loadings and reacted Cu(II) concentrations in SW and HW of several micronized copper treated Canadian wood species. Further study has also been carried out to investigate the effects on the Cu species of blue stain affected red pine SW, white-rot colonized lodgepole pine HW, and bioincised spruce. 7.2 Material and methods 7.2.1 Micronized copper treatment of sawdust SW and HW sawdust of southern pine (Pinus sp.), red pine (Pinus resinosa) and lodgepole pine (Pinus contorta) were oven dried at 100 °C for 5 h. The red pine sawdust in particular was sampled in the regions of SW visible free of blue-staining, SW affected by blue stain (SW-B), mature HW (HW-M, 30-33 years) and juvenile HW (HW-J, 0-10 years) from two untreated red 121  pine utility pole tops. Sawdust (4 g) was added to 0.05% (w/w on Cu basis) MCQ, MCA or MC solutions (100 mL) and stirred for 10 min at room temperature. The resultant slurry was filtered without washing to remove any remaining solution. Products were stored in sealed containers for 7 days before being dried in the oven at 100 °C for 3 h. Total Cu loadings of the treated sawdust was determined by XRF (AWPA 2012d) and the reacted Cu(II) concentrations were determined using the same method and calibration standard (Equation 3.1) described previously in Chapter 3.2. 7.2.2 Extraction of resin from red pine heartwood The extraction method followed procedures published by Peng and Roberts (2000). Red pine HW sawdust (50 g) recovered from the untreated red pine utility pole top (sectioned at 12-25 years) was retained in a Soxhlet extractor with a mixture (340 mL) of dichloromethane, acetone and methanol in equal proportions refluxing for 10 h. The solvent was removed under vacuum and yielded the crude resin as a brown oily mixture (12.41 g). The resin was used without further purification. The extracted red pine HW (HW-E) sawdust was dried in the oven and used in further treatment with MCQ. 7.2.3 Synthesis of Cu-abietate and Cu-resin The synthesis of Cu-abietate followed procedures published by (Roussel et al. 2000) with some modifications identified below. Abietic acid (2.35 g, Sigma Aldrich, St. Louis, MO, USA) was dissolved in 10 mL of ethanol. 6.6 mL of NaOH (1M) was added to the solution to saponify the resin acids, which was then stirred with 6.6 mL of CuSO4 solution (1 M). The green sludge formed was filtered and washed with a large amount of distilled water. The green solid was freeze dried and analyzed by EPR. 122   Cu-resin was synthesized by the same method using the crude resin product extracted from red pine HW as the starting material.  Crude resin (4.15g) was dissolved in 10 mL of ethanol. 15 mL of NaOH (1M) was added to the solution to saponify the resin acids, which was then stirred with 15 mL of CuSO4 solution (1 M). The green sludge formed was filtered and washed with a large amount of distilled water. The green solid was freeze dried and analyzed by EPR.  7.2.4 Simulations of Cu-wood and Cu-resin mixed spectra The simulation method is similar to the one used for characterizing the MCEA treated wood (Chapter 5.2.5). Simulations were carried out using the Solver analysis tool in Microsoft Excel 2013 (Redmond, WA, USA). EPR spectra of MCQ treated red pine HW-E and synthesized Cu-resin complex were used as references to simulate the spectra of the un-extracted red pine HW and several lodgepole pine samples by applying Equation 5.2:    𝑆𝐼𝑀𝐶 = 𝑧 ∙ (𝐴 ∙ 𝑥 + 𝐵 ∙ 𝑦) ≈ 𝑅𝐴𝑊𝐶    Equation 5.2 where in this case RAWC is the experimental spectrum of treated HW and SIMC is its simulation. In this case A is the spectrum of MCQ treated red pine HW-E, which is used as a treated SW-like reference that contains mainly Cu-wood complex, and B is the spectrum of synthesized Cu-resin complex. Fractions of A and B are represented by x and y respectively. z is a scaling factor to match the intensity of the simulated spectrum to that of the experimental. By applying the similar parameter setting in Solver as described in Chapter 5.2.5, the RSQ of the RAWc and SIMc were set to be maximized to 1 between 2550-3000 G in the calculation. 123  7.2.5 Commercial micronized copper treated lodgepole pine MCQ or MCA treated lodgepole pine “2×6”, produced either commercially or in a full size pilot plant, were also studied. The surface layers were removed in 1 mm increments by means of computer controlled router and the sawdust was collected. It was carefully reduced to 40 mesh. 7.2.6 Micronized copper treatment of bio-incised spruce sawdust Sawdust from spruce HW boards (5𝑚𝑚 × 100𝑚𝑚 × 400𝑚𝑚, avoiding bark, wane and obvious defects) biologically incised with Dichomitus squalens together with sawdust that had not been exposed to the fungus, was provided by FPInnovations from the work described by Morris et al. (2011). 5 paired samples of bio-incised and uncolonized spruce sawdust were treated with aqueous dispersions of MCQ and MCA respectively, produced by diluting commercially provided solutions. They were prepared by diluting the respective suspensions of MCQ (Cu:quat 1.0:0.625) and MCA (Cu:azole 1:0.04) with de-ionized distilled water. Sawdust (4 g) was added to treatment solution (100 mL, 0.5% m/m Cu) and stirred for 10 min at room temperature. The product was filtered under suction and stored in a sealed container for 4 days before being oven dried at 90 °C for 5 h. 7.3 Results and discussion 7.3.1 Effect of resin acids on micronized copper treated red pine heartwood Extractives were removed from the red pine HW sawdust (12-25 years) in order to study the possible effect of resin acids, on the preservative retentions and Cu species formed in micronized copper treated wood. The extraction method was optimized for recovering resin acids according to Peng and Roberts (2000). The IR spectrum of the extractives was similar to that of the abietic 124  acid (Figure 7.1), which is one of the major components of resin acids (Chapter 1.1.2.2). The spectrum shows strong absorptions at 2931 cm-1 (O-H stretch), 1692 cm-1 (C=O stretch) and 1226 cm-1 (C-O stretch) due to the carboxylic acid functional group, which indicated that the recovered extractives was rich in resin acids. The lack of strong absorption at 3200-3600 cm-1 means that phenolic alcohol containing compounds were not major constituents in the extractives removed.   Figure 7.1 FTIR spectra of abietic acid, red pine HW extractives and Cu-resin  The extracted HW (HW-E) and the original HW sawdust were treated with MCQ. Simulated EPR parameters show that 𝑔𝑧 = 2.363 and 𝐴𝑧 = 132 𝐺 for the MCQ treated HW-E (Table 7.1), which are similar to those of the treated southern pine SW. However, the z-125  component of the HW spectrum is shifted slightly up-field that resulted a lower gz and a higher Az value compared with those of the HW-E (Figure 7.2). It is hypothesized that while the HW-E contained mainly the Cu-wood complexes formed by reaction of the BCC with hemicellulose and pectin similar to that of the southern pine SW, the treated HW had a mixture of Cu-wood and Cu-resin acid complex, and the differences in the EPR parameters were brought about by the latter species. Note that thermal modification of wood is known to cause decarboxylation of extractives (Chow 1972; Kacik et al. 2015). The EPR spectra of HW and HW-E suggest that the Cu-resin reaction is not lost in the 90 °C drying process.  Total Cu loading in the HW-E was lower than that of the HW (Table 7.1), and both were well below the maximum CEC threshold of wood at pH 7 (Lee and Cooper 2010a). Because there were only minor differences between the SW and HW spectra, the reacted Cu concentrations were quantified using the same calibration standard. Reacted Cu(II) concentrations determined by EPR show no difference between the HW-E and HW samples, and the quantities were limited by the low total Cu retentions. The lower permeability of the extracted sawdust was surprising, and may be due to the relocation of the waxy substances in wood to the pit structures, where they blocked the cell wall, rendering the HW-E less permeable to preservative uptake.    126  Table 7.1 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of MCQ treated red pine HW sawdust and synthesized Cu-resin complex. a stdev = ±0.01; b stdev =±0.01 Sample %Cu by EPRa %Cu by XRFb g-factor Hyperfine coupling (G) gx gy gz Ax Ay Az HW 0.11 0.20 2.071 2.071 2.351 5 34 139 HW-E 0.10 0.13 2.073 2.073 2.363 5 34 132 Cu-resin - - 2.067 2.067 2.330 5 35 148 Cu-abietate - - 2.067 2.067 2.327 5 35 148    127  a)  b)  Figure 7.2 a) EPR spectra of MCQ treated red pine HW and SOLVER simulated spectrum of the treated HW using the treated HW-E and Cu-resin spectra as refrences; b) enlarged portion of a) in the region 2500-3000 G 128   In order to verify whether the changes in the EPR spectra observed were indeed due to the formation of Cu-resin species, a Cu-resin complex was synthesized via saponifying the extractive contents collected from the red pine HW. FTIR spectrum of the synthesized Cu-resin shows C=O stretching frequency at 1601 cm-1 (Figure 7.1), which was similar to the value reported by Gunn et al. (2002) for Cu-abietate. The EPR spectrum of the synthesized Cu-resin has spectral parameters comparable to those of Cu-abietate with 𝑔𝑧 = 2.330 and 𝐴𝑧 = 148 𝐺 (Table 7.1). Assuming that the treated HW-E contains predominantly Cu-wood complexes and very little Cu-resin, by applying the treated HW-E and the synthesized Cu-resin spectra as references, simulated spectra of the treated HW were produced based on the method established in Chapter 6. In theory the convolution of the two reference spectra should resemble that of the treated HW. Figure 7.2b shows that the changes are subtle yet distinguishable between the references and the HW in the 2500-3000 G region. The z-component of the HW-E spectrum shifted to a slightly higher magnetic field upon mixing with the Cu-resin spectrum, as a result the simulation is much more similar to the HW spectrum than the two references. The results clearly establish that the BCC can react with resin acids in wood, and the Cu complexes in the treated HW is a mixture of Cu-wood and Cu resin. The SimFonia simulated EPR parameters are no longer accurate representations of the magnetic properties of the analyte due to the presence of the mixture. However, they will continued to be used as qualitative indicators of the presence of a Cu-wood and Cu-resin mixture throughout the chapter.  7.3.2 In-lab micronized copper treatments in sapwood and heartwood Treatment responses in SW and HW in terms of total Cu loadings, reacted Cu(II) concentrations and the types of Cu species formed were investigated by treating southern pine, red pine and 129  lodgepole pine with either MCQ, MCA or MC. Red pine SW affected by the blue stain mold (SW-B) and the un-stained control were sampled separately to probe the potential effect of the colonization. Additionally, the red pine HW materials were separately sampled from juvenile (HW-J, 0-10 years) and mature (HW-M, 30-33 years) regions to see if potential differences in extractive content in mature vs. juvenile HW has an impact on the results. 7.3.2.1 Southern pine The total Cu loading of MCQ treated southern pine SW was 0.65%, over twice of the amount found in the HW (Figure 7.3). The total Cu loadings of MCA treated SW and HW are similar. The reacted Cu concentrations were not statistically different between the SW and the HW for both treatments. A significant portion of the deposited Cu has been converted to reacted Cu(II). EPR simulations using SimFonia show that the z-component of the SW spectra were shifted to a higher magnetic field (Table 7.2) compared to those of the southern pine SW samples examined in previous studies, which normally have a slightly higher 𝑔𝑧 ≈ 2.36 and lower 𝐴𝑧 ≈ 130 𝐺. The gz values for the HW samples were even lower than those of SW. The observations are consistent with the presence of both Cu-resin and Cu-wood, similar to those of MCQ treated red pine HW in the previous section. The southern pine HW possibly contained more resin acid than in the SW, and therefore the simulated EPR parameters deviated further from those of the SW.  130   Figure 7.3 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MCA treated southern pine sapwood (SW) and heartwood (HW) Table 7.2 Simulated EPR parameters of micronized copper treated southern pine SW and HW Treatment Sample g-factor Hyperfine coupling (G) gx gy gz Ax Ay Az MCQ SW 2.074 2.074 2.353 5 40 136 HW 2.071 2.071 2.346 5 40 136 MCA SW 2.074 2.074 2.350 5 40 136 HW 2.073 2.073 2.345 5 40 136  131  7.3.2.2 Red pine The total Cu loadings in SW ranged from 0.32-0.43%, and the reacted Cu concentrations were 0.24-29% in RP-1 and RP-2 (Figure 7.4). The reacted Cu levels were close to the upper limit of the CEC in all cases. Total Cu loadings in HW-J (0-10 years) were similar to or slightly lower than the corresponding SW. Despite having plenty of unreacted BCC in excess, the reacted Cu concentrations in HW-J were significantly lower than those of SW, except in the MCQ treated RP-2 in which they were similar. It is apparent that preservative penetration is not the cause for the low reacted Cu levels in HW-J. The SimFonia simulated EPR spectral parameters show that the gz values of the HW-J were slightly lower than those of SW (Table 7.3), which indicated the presence of Cu-resin in the former. The extractives are commonly located in cell lumen. It is possible that the occupation of extractives in HW cells may leave less space for BCC uptake, and the water insoluble nature of the substance may block the BCC from gaining access to the exchangeable protons in hemicellulose and pectin, rather than increasing the reacted Cu concentration overall. However, HW-J in theory should contain much smaller amounts of extractives and may behave similar to SW, in which the cell lumens are empty. In contrast, the results show that the reacted Cu concentrations in HW-J were substantially reduced (except in MCQ treated RP-2) while the impact on the total Cu retentions was less significant compared to the SW. It is speculated that the pectin may be degraded in the HW as more cells undergo cell death, but very little information was reported on this matter and further research is need to substantiate the hypothesis.  132  a)  b)  Figure 7.4 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated red pine SW, HW-M (30-33 years) and HW-J (0-10 years): a) RP-1; b) RP-2 133  Table 7.3 Simulated EPR parameters of micronized copper treated red pine RP-1 and RP-2 Treatment Sample g-factor Hyperfine coupling (G) gx gy gz Ax Ay Az MCQ RP-1 SW 2.072 2.072 2.360 5 35 134 HW-M 2.067 2.067 2.336 5 30 145 HW-J 2.070 2.070 2.356 5 35 134 SW-B 2.068 2.068 2.357 5 35 134 RP-2 SW 2.071 2.071 2.357 5 40 134 HW-M 2.067 2.067 2.347 5 35 134 HW-J 2.071 2.071 2.356 5 38 134 SW-B 2.070 2.070 2.357 5 38 134 MC RP-1 SW 2.074 2.074 2.361 5 35 134 HW-M 2.067 2.067 2.346 5 33 143 HW-J 2.070 2.070 2.349 5 33 143 SW-B 2.073 2.073 2.360 5 33 134 RP-2 SW 2.072 2.072 2.358 5 40 132 HW-M 2.072 2.072 2.351 5 40 135 HW-J 2.072 2.072 2.354 5 40 135 SW-B 2.071 2.071 2.357 5 40 132   The above observed effects were demonstrated further by the treatment responses in red pine HW-M (30-33 years). HW-M normally has higher density and more extractive contents than HW-J (Gryc et al. 2011). Total Cu loadings of HW-M were significantly lower than those of SW and HW-J, except in MC treated RP-2 (Figure 7.4b). However less than half of the total Cu was in the form of reacted Cu, which is well below the CEC threshold and also much less than the corresponding SW and HW-J. Simulated EPR spectral parameters deviated further from those of SW and HW-J to resemble the Cu-resin spectrum with decreased gz and increased Az values (Table 7.3). This suggests the BCC reaction with hemicellulose and pectin were hindered by the 134  increase presence of resin acids. The reacted Cu concentration could also be impacted by the degradation of pectin if the aforementioned speculations were true.  Total Cu loadings in SW-B were significantly lower than those in the SW except in MCQ treated RP-2. Reacted Cu concentrations were also much lower than those of SW in all cases despite having unreacted BCC in excess (Figure 7.5). The SimFonia simulated EPR spectral parameters of the SW-B are similar to those of SW with 𝑔𝑧 ≈ 2.36 and 𝐴𝑧 ≈ 134 𝐺 (Table 7.3). Blue stain fungi are known to produce xylanase and pectinase during colonization (Schirp et al. 2003; Schmidt 2006). Glucuronic acid units in hemicellulose and pectin may be degraded as a result of the blue staining, and therefore reducing the amount of available carboxyl protons to react with BCC. However, one may expect that the degradation of pectin, which are commonly found in the boarded pits between cells, could increase permeability of the cell wall and thus preservative retentions as a consequence. Even though such improvement may not be observed because the experimental material is in the form of sawdust, the significantly lower total Cu loadings of SW-B in this study were unexpected and further research is needed to identify the cause. 135  a)  b)  Figure 7.5 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated red pine SW and SW-B: a) RP-1; b) RP-2 136  7.3.2.3 Lodgepole pine Lodgepole pine has very thin layer of SW and high extractive contents in the HW. Lodgepole pine HW frequently contains white-rot decay in the tree, which is known to degrade lignin (Fackler et al. 2006) and release organic acids during colonization (Takao 1965; Mäkelä et al. 2009). If this is the case it may have an additional effect on the treatment results. Total Cu loadings in MCQ treated lodgepole pine SW and HW sawdust are not significantly different (Figure 7.6). Total Cu loadings in MC treated SW is lower than that of HW. EPR analysis shows that the reacted Cu(II) concentration in the HW were about 0.28% in both treatments, which are significantly higher than those of corresponding SW, as well as having very little unreacted Cu left in the samples. Simulated EPR parameters again show that the Cu complexes formed in the treatments have much lower gz and higher Az values than those of SW (Table 7.4) suggesting the presence of Cu-resin type complexes in the treated HW. The results of the reacted Cu concentrations are different from those of southern pine and red pine, in which the resin acids did not seem to increase the reacted Cu levels in the HW. The degradation of lignin may be the reason for the increased created Cu levels because the hemicellulose is more accessible. Alternatively, there is a possibility that the largely water insoluble, carbon rich resin acids were degraded by the fungi, and rendering them more soluble and reactive with the BCC. 137   Figure 7.6 Total Cu loadings and reacted Cu(II) concentrations of MCQ and MC treated lodgepole pine SW and HW Table 7.4 Simulated EPR parameters of micronized copper treated lodgepole pine SW and HW Treatment Sample g-factor Hyperfine coupling (G) gx gy gz Ax Ay Az MCQ SW 2.070 2.070 2.346 6 36 135 HW 2.070 2.070 2.326 5 25 147 MC SW 2.073 2.073 2.346 5 36 135 HW 2.070 2.070 2.326 5 25 147  138  7.3.3 Micronized copper treatment responses in sapwood and heartwood of commercial treated lodgepole pine SW and HW sawdust sampled from several commercial MCQ and MCA treated lodgepole pine boards were analyzed by XRF and EPR for their total Cu loadings and reacted Cu(II) concentration. The reacted Cu concentrations of SW were between 0.14-0.23%, all with unreacted BCC in excess (Table 7.5). EPR spectra of the SW samples have gz values of 2.354-2.370 and Az value of 130-137 G. It appeared that some of the SW samples also contained Cu-resin complexes based on the spectral parameters. Spectra of the HW samples have average 𝑔𝑧 =2.354 and Az value of 133-139 G (Table 7.6). As observed in the previous experiments, total Cu loadings in the HW are generally lower than those of SW. Several HW samples contained reacted Cu concentrations close to the threshold CEC of 0.33% Cu. Samples collected from the knots of HW were found to have EPR parameters similar to those of synthesized Cu-resin (Table 7.7 and Figure 7.7). This was expected because the knots are rich in resin acids and hard to penetrate due to the high density of the material.   139  Table 7.5 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine SW. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 Sample Description %Cu by EPRa %Cu by XRFb g-factor Hyperfine coupling (G) Surface Depth/mm gx gy gz Ax Ay Az 4B-2 X 1-2 0.19 1.97 2.070 2.070 2.353 5 33 134 26B-2 S - 0.17 0.83 2.071 2.071 2.353 5 33 138 58A-5 S - 0.23 1.75 2.074 2.074 2.370 5 35 132 62A-1 S - 0.20 1.94 2.072 2.072 2.355 5 33 134 62A-6 S - 0.18 1.41 2.072 2.072 2.356 5 33 137 64A-4 S - 0.18 1.29 2.072 2.072 2.355 5 33 137 80A-3 X - 0.15 0.79 2.071 2.071 2.362 5 33 130 85B-7 S 0-2 0.14 0.47 2.071 2.071 2.354 5 35 136    140  Table 7.6 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 Sample Description %Cu by EPRa %Cu by XRFb g-factor Hyperfine coupling (G) Surface Depth/mm gx gy gz Ax Ay Az 2B-1 S 1-2 0.31 0.67 2.070 2.070 2.352 5 35 134 58A-1 X 1-2 0.24 0.64 2.072 2.072 2.354 5 35 134 62A-4 S 1-2 0.30 0.93 2.071 2.071 2.352 5 40 133 80A-2 X 1-2 0.25 0.47 2.071 2.071 2.354 5 35 134 85B-1 S1 0-1 0.31 0.63 2.073 2.073 2.354 5 40 139 85B-2 S1 1-2 0.08 0.10 2.071 2.071 2.353 5 40 138 85B-3 S2 0-1 0.27 0.65 2.072 2.072 2.354 5 40 139 85B-4 S-2 1-2 0.07 0.15 2.072 2.072 2.354 5 40 139  Table 7.7 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW knots. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 Sample Description %Cu by EPRa %Cu by XRFb g-factor Hyperfine coupling (G) Surface Depth/mm gx gy gz Ax Ay Az 76A-3 S - 0.20 0.42 2.070 2.070 2.334 5 35 148 109B-6 S - 0.12 0.16 2.070 2.070 2.332 5 30 150 109B-8 X - 0.17 0.30 2.069 2.069 2.332 5 30 148  141   Figure 7.7 EPR spectra of 109B-8 from the knotty region of lodgepole pine HW and synthesized Cu-resin  Various degree of fungal colonization from the tree were found in many HW samples (Table 7.8), several of which had reacted Cu concentrations exceeding the threshold CEC of 0.33% Cu (based on the hemicellulose and pectin reaction considered to be the main reaction in sapwood under the conditions of MC treatment). It is known that the fungal colonization in lodgepole pine heartwood leads to enhanced preservative penetration in the HW. The fungal colonization often penetrated from the surface of the board in a radial direction towards the pith (Figure 7.8). Results from the previous studies did not appear to support the hypothesis that the BCC reaction with resin acids increased the overall reacted Cu concentration in wood. Therefore, further study is needed to investigate the cause of these higher than usual reacted Cu levels, which are found when fungal colonization arises in the tree. They could result from fungal acids 142  or a degradation of the resin acids rendering them more reactive during treatment with aqueous treating solutions. Table 7.8 Total Cu loadings, reacted Cu(II) concentrations (% m/m Cu) and simulated EPR parameters of commercial treated lodgepole pine HW with signs of white-rot decay. Samples denoted with an ‘A’ were treated with MCA and those denoted with a ‘B’ were treated with MCQ. a stdev = ±0.01; b stdev =±0.02 Sample Description %Cu by EPRa %Cu by XRFb g-factor Hyperfine coupling (G) Surface Depth/mm gx gy gz Ax Ay Az 2B-2 S 1-2 0.31 0.58 2.072 2.072 2.354 5 35 134 4B-1 S 1-2 0.27 0.89 2.071 2.071 2.354 5 35 134 26B-3 S - 0.26 0.65 2.070 2.070 2.336 5 30 149 58A-2 X 1-2 0.28 0.49 2.072 2.072 2.354 5 35 134 64A-1 S 0-1 0.35 1.08 2.072 2.072 2.356 5 40 137 64A-2 S 1-2 0.22 0.59 2.072 2.072 2.356 5 40 137 64A-3 S 3-4 0.46 1.00 2.072 2.072 2.350 5 35 136 76A-1 S - 0.41 1.29 2.072 2.072 2.358 5 35 134 80A-1 S 1-2 0.17 1.08 2.073 2.073 2.356 5 40 137 109B-1 S 0-1 0.38 0.92 2.072 2.072 2.354 5 40 139 109B-2 S 1-2 0.22 0.31 2.072 2.072 2.354 5 40 139 109B-3 X 0-1 0.50 1.00 2.072 2.072 2.354 5 40 139 109B-4 X 1-2 0.39 0.64 2.073 2.073 2.354 5 40 140 117B-1 S 0-2 0.36 0.39 2.073 2.073 2.354 5 40 140 117B-2 X 0-2 0.37 0.88 2.073 2.073 2.354 5 40 140  143   Figure 7.8 Lodgepole pine showing signs of white-rot decay 7.3.4 Micronized copper treatment of biologically-incised spruce sawdust The total Cu loadings determined by XRF (Figure 7.9) for the MCQ treatment yielded 0.37% Cu on average for both colonized and uncolonized controls. The average total Cu contents in the MCA treated spruce were lower compared to those in the MCQ treatment, with 0.21 and 0.25% Cu contained in the colonized and uncolonized controls respectively. The results demonstrated that biological incising had little effect on total Cu loadings as confirmed by the paired t-tests at 0.05 significance, 𝑝 = 0.85 and 0.19 for MCQ and MCA treatments respectively.  This was not unexpected, since the samples were sawdust with small particle size, so that the wood cell structure and their chemical components were all readily accessible without the need for improvement in penetration pathways. 144   Figure 7.9 Total copper loadings determined by XRF in bio-incised spruce and uncolonized controls after being treated with MCQ and MCA  The EPR studies show the biologically-incised spruce had significantly higher reacted Cu(II) concentrations than the uncolonized controls on average in both treatments, with 0.20% compared to 0.11% in the MCQ treatment, and 0.25% compared to 0.18% in the MCA treatment (Figure 7.9). The paired t-tests confirmed the significance of the differences at 0.05 significance, 𝑝 = 0.015 and 0.031 for MCQ and MCA treatments correspondingly. The reacted Cu(II) concentrations recorded for the biologically-incised spruce sawdust are consistent with maximum values achieved in previous studies of laboratory treated southern pine sawdust (Chapter 3), considering the CEC of wood at the reaction pH of 4-6 (Lee and Cooper 2010a). 145  The results suggested that the controlled biological incising process with D. squalens was able to increase the accessibility of carboxyl groups in the pits and cell walls through selective delignification of lignocellulosic materials, enabling the particulate BCC to be solubilized by the dissociated carboxylic acid protons and to react with the wood. Simulated EPR parameters of all the MCQ and MCA treated samples show that there was no difference in the type of reacted copper species in bioincised spruce or uncolonized controls, with 𝑔𝑧 = 2.360 and 𝐴𝑧 = 131 𝐺. The values are consistent with Cu reaction products containing only Cu-O bonding being formed with hemicellulose and pectin.  The MCQ treated spruce yielded higher total Cu retentions but lower reacted Cu(II) concentrations than those treated by MCA. Similar observations have been noted in previous studies, which suggested that while the surfactant like quaternary ammonium co-biocide can facilitate the mass uptake, it can also react with wood in a way similar to soluble Cu(II) ions and hence compete with micronized copper for the limited cation exchange sites available. As a result of the competition, the MCQ treated samples often have a higher total Cu retention but slightly lower reacted copper level than those treated by MCA of the same formulation strength. 7.4 Conclusions Removal of extractive contents in red pine HW and the subsequent treatment of the sawdust recreated a SW-like EPR spectrum with 𝑔𝑧 = 2.36 and 𝐴𝑧 = 132 𝐺 while the reacted Cu(II) concentration remain similar to the un-extracted control. Cu-resin complex synthesized from the red pine extractives produced an EPR spectrum with 𝑔𝑧 = 2.33 and 𝐴𝑧 = 148 𝐺, which are similar to those of Cu-abietate. Convolution of the two EPR spectra recreated a spectrum similar 146  to that of the un-extracted HW, confirming the formation of Cu-resin and the existence of a Cu-wood and Cu-resin mixture in the treated HW.   Total Cu loadings of micronized copper treated southern pine, red pine HW were generally lower than those of SW possibly due to increased occupation of resin acids in the cell lumen. The reacted Cu concentrations of southern pine and red pine HW were lower than those of the corresponding SW, despite having vast excess of unreacted BCC in the samples. EPR spectra of the HW samples were consistent with a mixture of Cu-wood and Cu-resin complex. The results suggested the presence of resin acids may obstruct the accessibility of exchangeable protons in hemicellulose and pectin, and therefore reduce the Cu-wood formation. Additionally, lower reacted Cu concentrations were observed in blue stain colonized red pine SW compared to those of the un-colonized controls, possibly because the carboxylic acid rich pectin were degraded as a result of colonization.   Unlike southern pine and red pine, lodgepole pine has higher reacted Cu(II) concentrations in the HW than in the SW even though there was no significant difference in total Cu loadings. EPR spectra consistently show an up-field shift of the z-component in the treated HW like those of the southern pine and red pine HW, which agreed with the presence of a Cu-wood and Cu-resin mixture. However, examination of the penetration pattern by the micronized copper in the HW clearly shows a greatly enhanced permeability, which is usually associated with colonization of the HW while in the tree by a white rot fungus. The increased reacted Cu concentration in the HW could be the result of lignin degradation and consequently an increase in the accessibility of hemicellulose. Examination of the commercial treated lodgepole pine also 147  shows reacted Cu concentrations close to or well above the threshold CEC (0.33%) in the HW, in which several of them had signs of fungal colonization underneath the wood surfaces.    In-lab treatments of D. squalens bio-incised spruce show no obvious improvement in preservative penetration, but the reacted concentrations were significantly higher than those of the un-colonized controls. EPR spectra of all the samples were similar to those of typical Cu-wood complexes containing only Cu-O bondings in the SW. Further investigation is needed to verify whether the potential release of organic acids during fungal colonization may have increased the overall reacted Cu levels. 148  Chapter 8: General conclusions and future directions In this thesis, the characters and quantities of Cu species in the micronized copper treated wood were studied using XRF and EPR. It was shown that the micronized copper treatment rapidly yields stable Cu-wood species, which are axially elongated complexes that have only oxygen atoms bonded to the metal center, similar to those produced by CuSO4 solution treatments. The species formed are very different from those of the ACQ treated samples, which contain Cu centers that include both Cu-N and Cu-O bonds. A linear relation between the Cu signal intensities of CuSO4 solution treated sapwood detected by XRF and EPR up to 0.30% was used as a calibration curve for quantifying reacted Cu species in micronized copper treated wood, which also contains residual BCC that is undetectable by EPR. The total Cu loadings in the micronized copper treated wood were found to be distinctly different between the earlywood and the latewood, whereas the concentrations of reacted Cu(II) were very similar. The MCEA treated wood contained predominantly Cu complexes similar to those of ACQ treated wood due to the reaction of Cu-MeaH complex and free MeaH with the wood acid protons. These results demonstrated that the BCC is solubilized by the reaction of the carboxylic acid groups in the sapwood hemicellulose and pectin, thus the reacted Cu levels formed in the micronized copper treated sapwood is limited by the CEC of wood at the reaction pH.  In Chapter 2, the Cu-wood complexes formed by micronized copper treatments were characterized by EPR. Additional FTIR or NIR studies comparing green wood, dried wood and treated wood will provide further details on the impact of drying and the coordination environment of the reacted Cu. 149   In Chapter 3, the increasing addition of the quat co-biocide demonstrated a positive impact on the total Cu retentions only up to a certain concentration, and a negative effect on the reacted Cu concentrations. It is thought that the large surfactant-like quat molecules facilitate particle uptake but possibly also compete with the BCC for the limited available acidic protons in wood. Proper assessment of the effect of Cu-to-quat ratio on physical adsorption and solubilization of Cu during and after the treatment will help further our understanding of the phenomenon.  The work in Chapter 6 reported small leaching of total Cu retentions, and significant increase of reacted Cu concentrations were observed in micronized copper treated wood exposed to soils at pH 5 under high moisture level. The combination of soil acidity and moisture increased the solubilization and fixation of BCC, which allowed a more complete reaction with the acidic carboxylic functionalities in the wood. Comparison of the results from different soils showed no conclusive evidence that the soil organic content is one of the factors that influences Cu solubilization. Additionally, the results suggest a possible competition between the Ca2+ from soil and Cu2+ for the limited available binding sites in both the soil and the wood. A HNO3 digest of the soil exposed sawdust samples and an assessment using techniques such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS) or Optical Emission Spectroscopy (ICP-OES) should be able to confirm and quantify Ca2+ uptake in wood from the soil. A more comprehensive analysis on the formation of reacted Cu with wood using a calcium amended micronized copper treatment solution may provide further supporting evidence to the hypothesis. It will also be useful to look for possible influences from other common metal ions found in soil, such as iron, magnesium and potassium. 150   Chapter 6 concluded that the BCC reaction with the acidic components in soil was likely to be on the wood surface only, and the soluble Cu2+ ions formed in the reaction are unlikely to remain in the wood. However, considering that the exposure period was only 8-weeks and a large portion of the Cu-wood complexes was formed gradually due to the high moisture level during this time, further effort to identify the impact of the soil organic acid components on the solubility of BCC in micronized copper treated wood is needed. The experiments should be conducted using treated materials that have already reached the maximum possible reacted Cu levels before soil exposures, and there should be excess unreacted BCC in the samples. Analysis on the quantities and characters of the Cu species in the wood and the soil wiped off from it may be able to provide answers to whether any organic acids in soil can move into the wood and the Cu complexes formed will remain other than being leached out.  In Chapter 7, a mixture of Cu-wood and Cu-resin complexes were found in micronized copper treated heartwood, and the total Cu loadings in the heartwood were consistently lower than those of sapwood. It was hypothesized that the extractives filled heartwood cell lumen had less space to accommodate the BCC, and the water insoluble extractives also obstructed the access of the BCC to the acidic protons in hemicellulose and pectin.  Imaging techniques such as High Resolution Scanning Transmission Electron Microscopy (HR-STEM) in combination with Energy Dispersive X-ray (EDX) spectrometry analysis on the Cu particle distribution on the cellular level (Matsunaga et al. 2010; Ahn et al. 2010; Matsunaga et al. 2011) may provide clarification to the proposed theory.  The work in Chapter 7 also reported that colonization by the blue stain mold resulted in lowered reacted Cu concentrations in the sapwood, whereas the presence of white-rot decay was 151  correlated to elevated reacted Cu levels that occasionally exceeded the threshold CEC of wood. The observations were proposed to be the results of degradation in different chemical components of wood caused by the different fungal decay mechanisms. Synthesis of melanin and low molecular weight metal chelating agents, such as organic acids and catecholates were known in many fungal species (Takao 1965; Caesar-Tonthat et al. 1995; Hastrup et al. 2013). The secretion of extracellular acids was implicated in the metal-detoxification process in certain metal tolerant fungi by forming insoluble complexes with the metal (Gadd and Griffiths 1978; Gadd and Rome 1988; Gadd 1990a; Gadd 1990b; Mehra and Winge 1991; Gadd 1992a; Gadd 1992b; Gadd 1992c). For example, copper tolerance of some brown-rot fungi has been linked to extracellular accumulation of copious amounts of oxalic acid during the primary metabolic phase (Murphy and Levy 1983; Shimada et al. 1997). It is suggested that oxalic acid precipitates insoluble copper oxalate, rendering the copper metabolically inert (Shimazono and Takubo 1952). Oxalic acid is also a by-product of lignin degradation by white-rot fungi, but the accumulation is to a lesser extent because it is also metabolized further by the fungi (Mäkelä et al. 2009). For a preservative system that fundamentally relies on the availability of acidic chemical components in wood, it is important to continue research on how the fungal colonization affects the solubilization and fixation of micronized copper. Colonization studies on the micronized copper treated wood using fungi with different decay mechanisms and levels of Cu tolerance should be carried out. The quantities and characteristics of various Cu species in the wood need to be monitored at different stages of fungal colonization. In view of the potentially more complicated Cu species involved in the colonization studies, the use of X-ray Absorption Spectroscopy (XAS) and the imaging technique Scanning Transmission X-ray Microscopy (STXM) may provide more comprehensive information in addition to the usual techniques used 152  in the thesis. These spectroscopic methods have a proven record in high resolution 3D elemental mapping and characterizing metal speciation (Dupont et al. 2002; Kuch 2004; Lau et al. 2008; Zhang et al. 2009; Coker et al. 2012; Lawrence et al. 2012; Laan 2013; Rouchon and Bernard 2015). Moreover, the spectroscopic technique operates in applied magnetic field, and therefore enables the study of systems of mixed magnetic properties (Kuch 2004; Coker et al. 2012; Laan 2013). This function is particularly useful considering the fact that the Cu complexes in the micronized copper treated wood is a mixture of paramagnetic and antiferromagnetic Cu species.  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